We have shown that our varying physical constant model is consistent with the recently published variational approach wherein Einstein equations are modified to include the variation of the speed of light c, gravitational constant G and cosmological constant Λ using the Einstein-Hilbert action. The general constraint resulting from satisfying the local conservation laws and contracted Bianchi identities provides the freedom to choose the form of the variation of the constants as well as how their variations are related. When we choose dG/Gdt=3dc/cdt, ̇the same as in our quasi-phenomenological model, c=c₀ exp⁡(a^α-1), G=G₀ exp⁡[3(a^α-1)] and Λ=Λ₀ exp⁡[(a^-α-1)], where a is the scale factor and α=1.8, we are able to confirm the success of our the model in explaining three astrometric anomalies and the null results on the variation of G and the fine structure constant. We show that the model: (a) fits the supernovae 1a observational data better than the ΛCDM model; (b) determines the first peak in the power spectrum of the cosmic microwave background temperature anisotropies at multipole value of l=217.3; (c) calculates the age of the universe as 14.1 Gyr; and (d) finds the BAO acoustic scale to be 145.2 Mpc. These numbers are within less than 3% percent of the observed values and the values obtained by the ΛCDM model. Surprisingly we find that the dark-energy density is negative in a universe that has significant negative curvature and whose expansion is accelerating at a faster rate than predicted by the ΛCDM model.

Electricity demand forecasting plays a significant role in energy markets. Accurate prediction of electricity demand is the key factor to optimize power generation, consumption, saving energy resources, and determining the energy prices. However, integrating energy mix scenarios, including solar and wind power which are highly non-linear and seasonal, into an existing grid increases uncertainty in generation, adds the challenges for precise forecast. To tackle these challenges, state-of-the-art methods and algorithms have been implemented in literature. We have developed Artificial Intelligence (AI) based deep learning models that can effectively handle the information of long time-series data. Based on the pattern of dataset, four different scenarios were developed and two best scenarios were selected for prediction. Dozens of models were developed and tested in deep AI networks. In the first scenario (Scenario1), data for weekdays excluding holidays was taken and in the second scenario (Scenario2) all the data in the basket was taken. Remaining two scenarios, weekends and holidays were tested and neglected because of their high prediction error. To find the optimal configuration, models were trained and tested within a large space of alternatives called hyper-parameters. In this study, an Aritificial Neural Network (ANN) based Feed-forward Neural Network (FNN) showed the minimum prediction error for Scenario1 while a Recurrent Neural Network (RNN) based Gated Recurrent Network (GRU) showed the minimum prediction error for Scenario2. While comparing the accuracy, the lowest MAPE of 2.47% was obtained from FNN for Scenario1. When evaluating the same testing dataset (non-holidays) of Scenario2, the RNN-GRU model achieved the lowest MAPE of 2.71%. Therefore, we can conclude that grouping of weekdays as Senario1 prepared by excluding the holidays provides better forecasting accuracy compared to the single group approach used in Scenario2, where all the dataset is considered together. However, Scenario2 is equally important to predict the demand for weekends and holidays.

This study assessed the relationship between head posture displacements and biomechanical parameters in three different tasks. One hundred male and female students (20 ± 3yrs) were assessed via the PostureScreen Mobile app to quantify postural displacements of head rotations and translations including: 1) the cranio-vertebral angle (CVA) (°), 2) anterior head translation (AHT) (cm), 3) lateral head translation in the coronal plane (cm), and 4) lateral head side bending (°). Biomechanical parameters during gait and jumping were measured using the G-Walk sensor. The assessed gait spatiotemporal parameters were cadence (steps / min), speed (m / s), symmetry index, % left and right stride length (% height), and right and left propulsion index. The pelvic movement parameters were: 1) tilt symmetry index, 2) tilt left and right range, 3) obliquity symmetry index, 4) obliquity left and right range, 5) rotation symmetry index, and 6) rotation left and right range. The jump parameters measured were: 1) flight height (cm), 2) take off force (kN), 3) impact Force (kN), 4) take off speed (m / s), 5) peak speed (m / s), 6) average speed concentric phase (m / s), 7) maximum concentric power (kW), 8) average concentric power (kW) during the counter movement jump (CMJ), and 9) CMJ with arms thrust (CMJAT). At a significance-level of p ≤ 0.001, moderate to high correlations (0.4 < r < 0.8) were found between CVA, AHT, lateral translation head and all the gait and jump parameters. Weak correlations (0.2 < r <  0.4) were ascertained for lateral head bending and all the gait and jump parameters except for gait symmetry index and pelvic symmetry index, where moderate correlations were identified (0.4 < r < 0.6). The findings indicate moderate to high correlations between specific head posture displacements, such as CVA, lateral head translation and AHT with the various gait and jump parameters. These findings highlight the importance of considering head posture in the assessment and optimization of movement patterns during gait and jumping. Our findings contribute to the existing body of knowledge and may have implications for clinical practice and sports performance training. Further research is warranted to elucidate the underlying mechanisms and establish causality in these relationships, which could potentially lead to the development of targeted interventions for improving movement patterns and preventing injuries.

In the FCC conversion of heavy petroleum fractions as atmospheric residues, the main challenge for refiners to achieve the quantity and quality of various commercial products depends essentially on the catalyst used in the process. A deep characterization of the catalyst at different steps of the process (fresh, regenerated, and spent catalyst) was investigated to study the catalyst's behavior including the physicochemical evolution, the deactivation factor, and kinetic-thermodynamic parameters. All samples have been characterized by various spectroscopy methods such as N2 adsorption-desorption, UV-visible spectroscopy, Raman spectroscopy, LECO carbon analysis, Scanning electron microscopy (SEM), X-ray diffraction (XRD), X‐ray fluorescence (XRF), nuclear magnetic resonance spectroscopy (NMR13C) analysis, and Thermogravimetric analysis. The results of N2 adsorption-desorption, UV-vis, Raman, LECO carbon, and SEM images showed that the main causes of catalyst deactivation and coking were the deposition of carbon species that covered the active sites and clogged the pores, and the attrition factor due to thermal conditions and poisonous metals. The XRD and XRF results showed the catalyst’s physicochemical evolution during the process and the different interlinks between catalyst and feedstock (Nickel, Vanadium, Sulfur, and Iron) elements which should be responsible for the coking and catalyst attrition factor. It has been found that, in addition to the temperature, the residence time of the catalyst in the process also has an influence on catalyst structure transformation. NMR13C analysis revealed that polyaromatic hydrocarbon is the main component in the deposited coke of the spent catalyst. Thermogravimetric analysis showed that the order of catalyst mass loss was fresh > regenerated > spent catalyst due to the progressive losses of the hydroxyl bonds (OH) and the structure change along the catalyst thermal treatment. Moreover, the kinetic and thermodynamic parameters showed that all zones are non-spontaneous endothermic reactions.

Estimating the parameters of statistical distributions generally involves solving a system of nonlinear equations or a nonlinear equation, being a technical difficulty in their usual application in hydrology. This article presents improved approximations and, in some cases, new approximations for the estimation with the method of ordinary moments and the method of linear moments, which are useful for the direct calculation of the parameters, because the errors in the approximate estimation are similar to the use of iterative numerical methods. Thirteen statistical distributions of two and three parameters frequently used in hydrology are presented, for which parameter estimation was laborious. Thus, the approximate estimation of the parameters by the two methods is simple but also precise and easily applicable by hydrology researchers. The approximate forms characterized by very small errors are the result of the research conducted within the Faculty of Hydrotechnics to update the romanian normative standards in the hydrotechnical field.

Recent advances in embedded antenna and sensor technologies for 5G communications have galvanized a response toward the investigation of their electromagnetic (EM) performance for urban context and civil engineering applications. This article quantitatively investigates the effects of material loading on an evolved antecedent-based design of a hexagonal-stubbed Complementary Split-Ring Resonator (CSRR)-loaded antenna through simulation and experimentation. The optimized antenna design is first conceptualized within a simulation environment to achieve EM resonance at 3.50 GHz before delving into the analysis of operational performance characteristics. As a proof-of-concept, a physical antenna prototype is fabricated on a printed circuit board for the in-situ evaluation of S11 parameter plot. Subsequently, a simulation-based parametric study is conducted on antenna prototypes embedded into Ordinary Portland Cement pastes with varying weight percentages of iron(III) oxide. Simulation-derived and experimental results are mutually verified, achieving a systemic downward shift in resonant frequency and corresponding variations in impedance matching induced by changes in the loading reactance. Finally, an inversion modeling procedure is employed using perturbation theory to extrapolate the relative permittivity of the dielectric embedding materials. Our proposed analysis contributes to optimizing concrete-embedded 5G antenna sensor designs and establishes a foundational framework for estimating unknown EM parameters of cement-based composites.

The objective of this research was to evaluate the physicochemical and sanitary parameters of raw cow's milk intended for consumption in the Amazonas region, Peru. We sampled 31 collection centers and dairy processors. We evaluated physicochemical parameters (fat, protein, solids not fat, lactose, ash, pH, and density), somatic cell count, and microbiology (mesophilic aerobic bacteria and total coliforms) of raw milk. We applied an analysis of variance (α=0.05) and the comparison of means between the collection centers and livestock basins (p<0.05). In addition, we performed a cluster analysis, principal components and correlation. Depending on the collection center, we found differences in all the physicochemical parameters, somatic cell count and milk microbiology. In the livestock basin analysis, we found differences for somatic cells, fat, protein, solids, pH, coliforms and bacteria. The Jumbilla basin presented less somatic cells, less fat was found in the Levanto basin and higher protein in the Yambrasbamba basin. Lactose, ash, density, total coliforms and mesophilic aerobic bacteria did not vary according to basin. The cluster analysis yielded four groups, Group 1 is higher in ash and density, Group 2 and 3 are higher in fat, Group 3 with higher protein, but higher in total coliforms and mesophilic aerobic bacteria. Group 4 registered the highest pH and the lowest protein concentration. There was a positive correlation of fat with protein and solids not fat, lactose with solids not fat, ash with density. Negative correlations of somatic cells with fat and, protein and solids not fat with pH.

Farmers are continually looking for new reliable, objective and non-invasive methods for evaluation of ewe condition. Live weight (LW) and body condition score (BCS) are used by farmers as a basis to determine the condition of the animal. Body composition is an important aspect of monitoring animal condition. The body composition is the amount of fat, lean and bone; knowing the amount of each is important because the information can be used for better strategic management interventions. Experiments were conducted to establish the relationship between body composition and body parameters, at key life’s stages (weaning and pre-mating), using measurements automatically determined by an image processing ap-plication at Lincoln University sheep farm for 88 Coopworth ewes. Computerized Tomography technology was used to develop relationship with body parameters and a subset was used to validate the predicted model. Multivariate linear regression (MLR), artificial neural network (ANNs) and regression tree (RT) statistical analysis methods were evaluated to determine their efficacy to predict body fat, lean and bone. The results showed a correlation between fat, lean and bone determined by CT and the fat, lean, bone weight estimated by live weight and body parameters calculated using the image processing application with R2 values of 0.90 for fat, 0.72 for lean and 0.50 for bone using ANNs statistical model. From these results, farmers can utilize accurate measures of fat which will enhance nutritional and management practices.

Extraction techniques of important bioactive molecules from the major concern of Seafood byproducts are getting emphasis for better valorization. Employing green extraction technologies for efficient and quality production of these bioactive molecules is also strictly required. Hence, understanding the extraction process parameters to effectively design an applicable optimization strategy could make this real. In this review, statistical optimization strategies applied for the extraction process parameters of bioactive molecules from Seafood byproducts are focused. The type of experimental designs, and techniques applied to criticize and validate the effects of independent variables on the extraction output was addressed. Dominant parameters studied were enzyme/substrate ratio, pH, time, temperature and power of extraction instruments. The yield of bioactive compounds, chitin and chitosan, proteins and peptides, enzymes and carotenoids (Astaxanthins) were the most studied responses. Efficiency and/or economic and quality considerations and their selected optimization strategies that favour the production of potential bioactive molecules were also reviewed.

We measure the accelerated cosmic expansion rate of the late-time Universe and derive constraints on cosmological parameters from the final baryon acoustic oscillation (BAO) uncorrelated measurements of different surveys after two decades of dedicated spectroscopic observation combined with the Pantheon sample of Type Ia supernovae, the Hubble diagram of gamma-ray bursts & quasars data, the Cosmic Chronometers data, and the recent Hubble constant value measurement from the Hubble Space Telescope and the SH0ES Team as an additional prior. In Λ cold dark matter (ΛCDM) scenario, the model fit yields Ωm=0.313±0.034 and ΩΛ=0.672±0.025. Combining BAO with CC+Pantheon+QSR+GRB data sets we get H0=69.21±1.22 km s−1 Mpc−1, rd=133.46±2.49 Mpc. For the a flat wCDM model, we get w=−1.111±0.030. For a dynamical evolution of dark energy in a flat w0waCDM cosmology, we get wa=−0.292±0.167. We apply the Akaike information criteria probe to compare the three models, and see that all models are favored and cannot be discarded from the current data.

This study investigates the use of programming language Python to analyse and model chemical engineering processes. Using municipal sewage sludge (MSS) drying as an example, the study demonstrates how Python can support analyses and model drying data. The drying process was performed on a flat plate while maintaining a uniform, parallel drying air speed of 1.15 m s-1. The Python program helped to analyse the digitalised weight measurements from each sample. The program enables sorting input data, determining the drying critical point and evaluating the first and second drying periods.

This study evaluated eight herbal and fruit teas to produce kombucha beverages. Besides, the effect of initial sucrose concentration (10, 40, and 70% w/v) on kombucha fermentation from tea extracts was investigated. Kinetic characterization and modeling of kombucha fermentation were also performed. Results showed that kombucha beverages' characteristics and chemical content changed according to tea type and initial sucrose concentration. It was determined that as initial sucrose concentration increased, the consumed substrate concentration increased. The highest total biomass values were determined when green tea and pomegranate tea were supplemented with 70 g/L sucrose. The highest total phenolic content and antioxidant activity were achieved with green tea samples. The total acidity and phenolic substance concentration increased as fermentation progressed in general. The kinetic parameters including maximum consumption rate, sugar utilization, yield, biomass yield, maximum biomass, total acidity, phenolic production rate, and the phenolic result were computed depending on changing substrate concentration. Concerning kinetic modeling, proposed models (Logistic and Luedeking-Piret models) estimated satisfactorily experimental substrate consumption and total acidity values. Besides, total acidity was associated with the substrate consumption.

The solid-state welding method known as friction stir welding (FSW) bonds two metallic work parts, whether the same or different, by plastically deforming the base metal. The frictional resistance between both metallic work pieces causes them to produce heat, which produces plastic deformation and welds them. However, the weldability and strength of FSW joints mainly depend on the FSW parameters. This review work highlights the previous research work on the FSW parameters and their effects on the weldability and quality of the aluminum alloys joined with similar and dissimilar metals through the FSW method. About 150 research studies were systematically reviewed, and the articles included data from peer-reviewed journals. It has been concluded that the key parameters, including welding speed, “rotational speed”, “plunge depth”, “spindle torque”, “shoulder design”, “base material”, “pin profile” and “tool type", significantly affect the weldability of the aluminum joint through the FSW method. Also, the selection of these parameters is important and fundamental as they directly affect the joint. It is recommended that future work focus on FSW for aluminum. Among these, the most essential is the application of artificial intelligence (AI) techniques to select the optimum FSW parameters for aluminum welding.

Metal additive manufacturing technologies have large potential for future use in load bearing aerospace applications, requiring a deeper understanding of mechanical performance and influencing factors. The objective of this study is to manufacture fatigue specimens by laser powder bed fusion with comparable bulk and different as-built surface quality (without post-processing). This goal was pursued by using identical bulk/hatch scan parameters while varying contour scan parameters. The bulk quality was evaluated by density measurements according to Archimedes’ principle and tensile testing. The surfaces were investigated using the optical fringe projection method and surface quality was assessed by the areal surface texture parameters Sa (arithmetic mean height) and Sk (core height, derived from material ratio curve). The resulting mean values of max (ultimate tensile strength) were between 375 and 405 MPa, which is a variation of roughly 8%, for seven different surface conditions. It could be confirmed that the influence of contour scan variation on bulk quality is insignificant for the assessed samples.

In recent years, the discharge of various emerging pollutants, chemicals and dyes in water and wastewater has represented one of the prominent human problems. Since water pollution is directly related to human health, highly resistant and emerging compounds in aquatic environments will pose many potential risks to the health of all living. Therefore, water pollution is a very acute problem that has constantly increased in recent years with the expansion of various industries. Consequently, choosing efficient and innovative wastewater treatment methods to remove contaminants is crucial. Among advanced oxidation processes, electrochemical oxidation (EO) is the most common and effective method for removing persistent pollutants from municipal and industrial wastewater. However, there are still many gaps despite the great progress in using EO to treat real wastewater. This is due to the lack of comprehensive information on the operating parameters which affect the process and its operating costs. In this paper, among various scientific articles, the impact of operational parameters on the EO performances, a comparison between different electrochemical reactor configurations, and a report on general mechanisms of electrochemical oxidation of organic pollutants have been reported. Moreover, an evaluation of cost analysis and energy consumption requirements have also been discussed. Finally, the combination process between EO and another important advanced oxidation technology, PEC, called photoelectrocatalysis (PEC), has shortly been discussed and reviewed. This article showed that there is a direct relationship between important operating parameters with the amount of costs and the final removal efficiency of emerging pollutants. Optimal operating conditions can be achieved by paying special attention to reactor design, which can lead to higher efficiency and more efficient treatment. The rapid development of EO for removing emerging pollutants from impacted water and its combination with other green methods can result in more efficient approaches to face the pressing water pollution challenge.

The impact of nutrients on the environment, particularly on water bodies, has led to extensive studies for nutrient control. Within this context, studies have been focused on source separation of human urine from domestic wastewater to recover nutrients. Potassium is one of the most important components of human urine. However, data on potassium removal or recovery are quite limited except for some indirect information through use of zeolites for mostly ammonia removal. Potassium struvite or K-struvite (MgKPO₄·6H₂O) is a sparingly soluble salt belonging to struvite and has the potential of being used as a means of potassium and phosphate recovery from segregated human urine. This study aimed to assess the potential of K-struvite precipitation for control and recovery of nutrients. Within this context, K-struvite precipitation experiments were performed on both synthetically prepared samples and synthetic human urine solution to determine effect of operation parameters i.e. pH, stoichiometry, and temperature on potassium recovery performance. Results indicated that process performance as well as type of solid phases co-precipitated with K-struvite were closely related to initial potassium concentration, pH and reaction stoichiometry. At pH 10, the potassium recovery efficiency was maximized up to 87% by application of 100% excess dose of Mg and P for both synthetic samples and synthetic human urine solution. On the other hand, application of excess dose of K did not provide any improvement in K recovery efficiency. The effect of temperature on solubility of K-struvite was insignificant at the temperature of 24-90°C. Solid phase analyses confirmed that K-struvite was co-precipitated with either Mg₃(PO₄)₂, MgNaPO₄·7H₂O, or MgHPO₄·7H₂O depending on pH and stoichiometry instead of a pure compound.

This study was to determine the effects of different irrigation, fertigation and mulching applications on the yield and quality parameters of strawberries. The study was conducted at the Bursa Uludağ University Yenişehir Ibrahim Orhan Vocational School Agricultural Research Field in 2019-2020. In the research, four different irrigation topics, three different fertigation and three different mulching topics were selected The maximum and minimum yield values of the study years were calculated as 5.05-18.70 t ha-1 and 1.20-8.7 t ha-1, respectively, from I100F100M1 and I25F50M0 treatments. As a result, a three-factor study determined that irrigation, fertigation, and mulching had a significant effect on the yield and quality characteristics of strawberries. However, when the reductions in yield and quality losses are evaluated together, despite the reductions in irrigation water and fertigation levels, I75 and F75 topics can be recommended. Also, in mulching treatments, black mulch material (M1) should be chosen over clear mulch material (M1) and no mulch (M0).

Electroencephalography (EEG) signals provide valuable insights into various activities of the human brain, including the detection of mental stress, which is a complex physiological and psychological response. However, the challenge lies in identifying mental stress accurately while mitigating the limitations associated with a large number of EEG channels. This includes issues such as computational complexity, the risk of overfitting, and the increased setup time for electrode placement, which can be cumbersome for real-life applications. Therefore, it is crucial to develop EEG channel selection algorithms that enable the creation of a wearable device capable of assessing mental stress in real-life scenarios. This study introduces a novel channel selection method aimed at identifying highly accurate channels for detecting mental stress. Our approach, known as the Correlation Coefficient of Hjorth Parameters (CCHP), assesses the correlation between activity, mobility, and complexity in the time domain to nominate the most relevant channels. By selecting channels that exhibit high correlation with the stress task while being uncorrelated with each other, CCHP significantly reduces the number of EEG channels required, without compromising accuracy or performance. To evaluate the effectiveness of CCHP, we conducted experiments using the DEAP public dataset. Comparing our results with other recent algorithms that utilize the full set of EEG channels, CCHP achieved a superior classification accuracy of 81.56% using only eight EEG channels. Furthermore, CCHP outperformed existing channel selection methods by an impressive 8%. These findings strongly indicate that the CCHP algorithm shows great promise in the design of a wearable application for mental stress detection, utilizing a minimal number of EEG channels.

The objective of this study was to evaluate the effect of the addition of atomized black Maca in the cryopreservation medium of epididymal spermatozoa of alpaca species. Fifteen pares of testes and epididymis from alpacas of reproductive age were collected from a local (Huancavelica) slaughterhouse and transported in NaCl 0,9% at 10°C to the laboratory. Each sample of epididymal sperm was divided into six groups: 1) Fresh, 2) Yolk medium (YM), 3) YM+10mg/ml Maca, 4) YM+20mg/ml Maca, 5) YM+30mg/ml Maca, and 6) YM+ Resveratrol (antioxidant positive control). Sperm cryopreservation was performed through the slow-freezing method. Markers associated with functionality such as motility, vitality and plasma membrane integrity. Cellular markers associated with oxidative damage, such as DNA fragmentation, total ROS production and lipid peroxidation, were analyzed before and after freezing. The results showed that the supplementation with black Maca at 20mg/ml improved the sperm motility, viability and integrity of the membrane. Similarly, total ROS production decreased with Maca at 10 mg/ml (25 ± 2.23%) and 20mg/ml (20 ± 2.52%) (P<0.05). However, DNA fragmentation and lipid peroxidation were similar in all groups. These results suggest that Maca at 20mg/ml has a protective effect during the freezing/thawing process of epididymal sperm of alpaca species.

Background: Acute heart failure (AHF) is a serious medical problem that necessitates hospitalisation and often results in death. Patients hospitalised to the emergency department (ED) should therefore receive an immediate diagnosis and treatment. Unfortunately, there is not yet a fast and accurate laboratory test for identifying AHF. The purpose of this research is to apply the principles of explainable artificial intelligence (XAI) to the analysis of hematological predictors for AHF. Methods: In this retrospective analysis, 425 patients with AHF and 430 healthy individuals served as assessments. Patients' demographic and hematological information was analyzed to determine AHF. Important risk variables for AHF diagnosis were identified using LASSO feature selection. To test the efficacy of the suggested prediction model (XGBoost), a 10-fold cross-validation procedure was implemented. The area under the receiver operating characteristic curve (AUC), F1 score, Brier score, and Positive Predictive Value (PPV) and Negative Predictive Value (NPV) were all computed to evaluate the model's efficacy. Permutation-based analysis and SHAP, were used to assess the importance and influence of the model's incorporated risk factors. Results: White blood cell (WBC), monocytes, neutrophils, neutrophil-lymphocyte ratio (NLR), red cell distribution width-standard deviation (RDW-SD), RDW-coefficient of variation (RDW-CV), and platelet distribution width (PDW) values were significantly higher than the healthy group (p&lt;0.05). On the other hand, erythrocyte, hemoglobin, basophil, lymphocyte, mean platelet volume (MPV), platelet, hematocrit, mean erythrocyte hemoglobin (MCH) and procalcitonin (PCT) values were found to be significantly lower in AHF patients compared to healthy controls (p &lt;0.05). When XGBoost was used in conjunction with LASSO to estimate AHF, the resulting model had an AUC of 87.9%, an F1 score of 87.4%, a Brier score of 0.036, and an F1 score of 87.4%. PDW, age, RDW-SD, and PLT were identified as the most crucial risk factors in differentiating AHF. Conclusions: The XGBoost model demonstrated exceptional performance in accurately estimating Acute Heart Failure, and the application of Explainable Artificial Intelligence effectively provided intuitive explanations for the model's estimations. The suggested interpretable model holds potential for the identification of patients at high risk, thereby facilitating the optimization of treatment and planning for follow-up in cases of AHF.

The Yamuna River in Delhi is a prevalent epitome of the depleted ecosystem that has transformed into a sewage drain due to intense pollution and blooming anthropogenic pressure. As a leading polluter, Delhi contributes to more than 70% of Yamuna's pollution load. Its drains discharge a massive B.O.D. load daily into the river, making it severely polluted, as reflected by the water quality index. The paper uses secondary data to analyze the parameters to determine the water quality of Yamuna at different monitoring sites. It performs correlation analysis to determine the relationship among factors contributing to river water pollution. The results of correlation analysis suggest a highly significant association between parameters COD-BOD, but the association is mild to a minimum among other parameters such as BOD-DO, BOD-pH, COD-DO, COD-pH and DO-pH. Most parameters were observed to be above the hazardous level acceptable for using river water. The analysis of S.T.P.s indicates the need to increase the capacity in terms of treatment, storage, reopening of closed plants and efficient operation to meet the increasing demand for fresh Water. Also, there is a need to create demand for wastewater in different sectors of urban areas like construction, horticulture, industrial coolants, etc.

Today, there is a time series analysis that has gained significant popularity across various industries to provide effective solutions for any specific challenges. Artificial intelligence logic is generally used to solve time-series problems with the help of various frameworks that are available for the development of AI-based applications. Currently, there is a significant framework in Python that is driven by its comprehensive libraries and their practical implementations. Time series analysis can be built with the help of some specific models that give results to differentiate the efficiency and domains of great work. This paper focuses on three diverse libraries of Python to predict the Gulf stock exchange market. These libraries are prediction models that are helpful in predicting future values. These models utilized include SARIMA (Seasonal Auto-Regressive Integrated Moving Average), Neural Prophet Model, and Fb Prophet model. Each model is trained using the provided datasets, which are followed by evaluation parameters such as MSE, RMSE, recall, MDAPE, accuracy, precision, etc. The main purpose of using these three models for stock market prediction is to find the better-suited models. In the past few decades, the stock market industry has seemed to have promising growth after 2022 onwards. This paper will help us make a significant decision about model usage for addressing such complex challenges. Especially, the research findings indicate that all three models demonstrate in different domains. SARIMA can perform well in overall prediction tasks, while the Prophet model works great with smaller datasets that contain seasonality trends.

Electrospinning is a simple versatile method to generate nanofibres. Remarkable progress has been made in the development of electrospinning process. The production of nanofibers is affected by many parameters, which influence the final material properties. Electrospun fibers have a wide range of applications such as energy storage and biomedical scaffolds. Polyacrylonitrile (PAN) has been widely used in the production of carbon nanofibers. PAN has received increasing interest in recent years, due to its excellent characteristics, such as spinnability, biocompatibility, and commercial viability, opening new applications in the biotechnological field. This paper provides an overview of the electrospinning process, its main parameters, and operation modes that affect nanofibers fabrication. A review of their biological applications is proposed. A focus is made on PAN fibers formation, functionalization, and application as scaffolds to allow cell growth. Overall, nanofibre scaffolds, made of stabilized PAN, appear as a powerful tool in medical applications needing controlled cell culture.

We conducted an experiment on lambs to determine the effect of infection with the gastrointestinal nematode (GIN) Haemonchus contortus on growth performance, nutrient composition, microbiota, and ruminal fermentation in vivo and in vitro. Twelve female lambs were equally divided into two groups: uninfected animals (CON) and animals infected with approximately 5000 third-stage ISE larvae derived from the MHCo1 strain of H. contortus (INF). Two lambs per group were killed on days 48, 49, and 50 after infection and ruminal content was collected separately from each lamb. Batch cultures of ruminal fluid from CON and INF were incubated in vitro with 0.25 g meadow hay, a plant mixture and chicory used as substrates. The ruminal populations of protozoa, bacteria, total Archaea, and the archaean orders Methanobacteriales and Methanomicrobiales were significantly higher in INF than CON. In vivo concentrations of n-butyrate, iso-butyrate, and iso-valerate were significantly lower in INF than CON. In vitro values after 24 h of ruminal fermentation varied within the substrate. GIN infection by H. contortus was associated with increased methanogenesis. In conclusion, chicory was a promising substrate for mitigating methane production and may modulate the ruminal microbiome of GIN-infected lambs due to its chemical and phytochemical composition.

The increased demand for resources and energy that is developing with rising global consumption represents a key challenge for our generation. Biogas production can contribute to sustainable energy production and closing nutrient cycles using organic residues or as part of a utilization cascade in the case of energy crops. Compared to hydrogen (H2), biogas with a high methane (CH4) content can be fed into the gas grid without restrictions. For this purpose, the CH4 content of the biogas must be increased from 52 to 60 % after anaerobic digestion to more than 96 %. In this study, biological hydrogen methanation (BHM) in trickling-bed reactors (TBR) is used to upgrade biogas. Design of experiments (DoE) is used to determine the optimal process parameters. The performance of the reactors is stable under all given conditions, reaching a “low” gas grid quality of over 90 %. The highest CH4 content of 95.626 ± 0.563 % is achieved at 55 °C and 4 bar, with a methane formation rate (MFR) of 5.111 ± 0.167 m³/(m³·d). The process performance is highly dependent on the H2:CO2 ratio in the educts, which should be as close as possible to the stochiometric ratio of 4. In conclusion, BHM is a viable approach to upgrade biogas to biomethane quality and can contribute to a sustainable energy grid.

The most modern technique utilized to create intricate and complexly manufactured parts for a variety of applications is called additive manufacturing (AM). Fused deposition modeling (FDM) has received the greatest attention in the development and manufacturing sectors. The main objective of this study was to investigate how printing factors affected the mechanical characteristics of printed samples. Samples were produced using an FDM 3D printer in compliance with ASTM D638 using a variety of input settings, including orientation, layer thickness, speed, and infill pattern. On the printed samples, tensile tests and morphological analysis using a scanning electron microscope (SEM) were done. The findings of this study demonstrate that factors including layer thickness, printing speed, and orientation significantly affect the tensile strength of ABS printed samples. Discovering the process settings that could lead to superior mechanical and physical characteristics would undoubtedly assist designers and manufacturers worldwide as the FDM 3D printer becomes more and more crucial in manufacturing engineering parts.

Condition monitoring of rotating shafts is essential for ensuring the reliability and optimal performance of machinery in diverse industries. In this context, as industrial systems become increasingly complex, the need for efficient data processing techniques is paramount. Deep learning has emerged as a dominant approach due to its capacity to capture intricate data patterns and relationships. However, a prevalent challenge lies in the black-box nature of many deep learning algorithms, which often operate without adhering to the underlying physical characteristics intrinsic to the studied phenomena. To address this limitation and enhance the fusion of data-driven methodologies with the fundamental physics of the system under study, this paper leverages physics-informed neural networks (PINNs). Specifically, a simple but realistic numerical case study of an extended Jeffcott rotor model, encompassing damping effects and anisotropic supports for a more comprehensive modelling, is considered. PINNs are used for the estimation of five parameters that characterize the health state of the system. These parameters encompass the radial and angular position of the static unbalance due to the disk installed on the shaft, the stiffness along the principal axes of elasticity, and the non-rotating damping coefficient. The estimation is conducted solely by exploiting the displacement signals from the centre of the disk and, to showcase the efficacy and precision provided by this novel methodology, various scenarios involving different constant rotational speeds are examined. Additionally, the impact of noisy input data is also taken into account within the analysis.

The challenge of achieving ultrafast switching of electric polarization in ferroelectric materials remains unsolved, as there is no experimental evidence of such switching to date. In this study, we have developed an enhanced model that describes switching within a two-dimensional space of generalized coordinates. Our findings indicate that stable switching in barium titanate cannot be achieved through a single linearly polarized pulse. When the intensity of the linearly polarized pulse reaches a certain threshold, the sample experiences depolarization, but not stable switching. Our study also reveals that phonon friction plays a minor role in the switching dynamics and provides an estimate of the optimal parameters of the perturbing pulse with the lowest intensity that results in depolarization of an initially depolarized sample.

While some research supports utilizing plain radiography for measuring biomechanical alignment of the spine for prognosis and treatment, there are contrasting viewpoints regarding both the value and utilization of these procedures in conservative care. Evaluation of both conservative and non-conservative approaches to spinal care revealed vast differences in radiographic utilization and interpretation between orthopedic surgeons, primary care physicians, chiropractic physicians, and physical therapists, which may account for the different viewpoints and rationale in the literature. A research summary is provided regarding the various methods of spinal analysis utilized by these professions to help determine if there is any unique diagnostic or prognostic value associated with radiographic utilization that could assist in advancing conservative spinal assessment and treatment. Understanding any unique value provided through biomechanical assessment utilizing plain radiography of the spine established in the literature may help chiropractic physicians determine the appropriate use of radiographic procedures in clinical practice and how to coordinate efforts with other conservative and non-conservative professions to improve spinal healthcare.

Bare slope instability is a prevalent concern. The root system of, herbaceous vegetation enhances the shear strength of shallow–slope soil. Indoor experiments were conducted on rootless undisturbed soil (RUS) and undisturbed soil with a root system (USRS) using a triaxial compression apparatus to analyze the slope stability of composite soil with a Tagetes erecta root system. Significance tests and correlation analysis of the factors affecting shear performance were conducted using R software. The slope reinforcement, effect by the plant root system was simulated under 24 working conditions using the MIDAS finite element method. The results revealed the influence of the–root content (RC), moisture content (MC), and stress on the shear strength of USRS, the contribution degree, and the variables’ influences on slope stability. Both RUS and USRS exhibited strain hardening during shearing. The internal friction angle (φ) and cohesion (c) of USRS were negatively and positively correlated with the RC and MC (root burial depth), respectively, and a good fit was obtained for the relationship. The maximum deviatoric stress during shear failure was 1.29 times higher for USRS than for RUS. The RC (root depth) was positively correlated with the slope safety coefficient and the slope of the line under different working conditions, whereas the slope gradient was negatively correlated with the slope safety coefficient. The reinforcement effect by the root system resulted in a 13.2% increase in the safety coefficient and improved stability of slopes with a gradient larger than 1.5%. This article investigated the mechanism of the root–soil system and, the effects of different influencing factors on the shear strength of the soil, and slope stability. The findings provide new insights into shallow slope stability in practical slope protection projects.

Abstract: Background: The diagnosis of nasal airway disorders relies on questionnaires, subjective data, and objective data. Interpretation of objective data obtained from measurement technology is not well understood by providers and researchers who use the equipment to test nasal airway function, justifying the need to cre-ate a new clinical tool. The Davidson Airway Function & Nasal Evaluation (DAFNE) Scoring System is a web-based scoring system that allows healthcare providers (MDs, PAs, PTs, APRNs, DMDs, DDSs, SLPs, and DCs) and researchers who treat nasal obstruction and breathing disorders to make more accurate diagnostic decisions, select the appropriate treatment for individualized patient care, monitor treatment progression and outcomes, and show how to approach a collaborative care model with other healthcare professionals. The current technologies, such as 4-phase rhinomanometry, use a simple approach that relies on a measurement tracing intersecting a color-coded y-axis on a four-quadrant graph with diagnostic numeric data output de-scribing nasal airflow and resistance. This is a good source of biofeedback demonstrating abnormal nasal breathing patterns but lacks interpretation guidelines to describe the severity of disease. The more sophisti-cated proprietary DAFNE approach uses multiple parameters which include airflow restriction, speed, vol-ume, and patient characteristics to identify patients’ disease progression much more accurately. Additionally, it explains how to segregate patients into appropriate treatment options which minimizes risks and compli-cations associated with sleep and breathing disorders while improving patient outcomes. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were necessary to identify studies which determined the ranges of nasal function measurement parameters among three airway measurement technologies used in writing the DAFNE Score algorithm. The performance of DAFNE was evaluated compared to the research data and patient demographics used in previous studies. Results: By using primary outcome measurements from the literature, we were able to create a reliable, re-peatable, and validated tool to facilitate patient identification, treatment stratification, and collaboration for sleep and nasal breathing dysfunction. Subsequently, we found DAFNE could be used to identify the appro-priateness of a sleep study. Conclusions: DAFNE Scoring System has demonstrated the ability to detect high risk patients in the pediatric and adult populations susceptible of sleep apnea and breathing dysfunction needing a sleep study and treatment to improve nasal airway function and sleep. DAFNE Scoring System should be used as an adjunct tool in routine clinical practice and research to further understand the technol-ogy data output, identify patients at risk, stratify treatment options, progress, and stabilization after treatment, and how to collaborate with other healthcare providers to improve patient outcomes.

Background: The Davidson Airway Function &amp; Nasal Evaluation (DAFNE) Scoring System was developed as an intuitive and research-based scoring system that could be validated through beta testing and easily introduced to healthcare providers of several subspecialties who treat nasal obstruction and breathing disorders (MDs, PAs, PTs, APRNs, DDSs, and DCs). This scoring system was shown to increase the knowledge of airway function, nasal measurement parameters, and identification of proper treatment options for sleep and breathing disorders. The basis for the DAFNE score was developed from a systematic review of nasal measurement data. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were used to identify studies validating nasal function measurement parameters to create the algorithm for the DAFNE Score™. The systematic review was accomplished using the 2020 ‘Preferred Reporting Items for Systematic Reviews’ (PRISMA) guidelines. Results: Twenty studies met the inclusion criteria for systematic review. Primary outcomes measurements demonstrated reliability, repeatability and validity of the DAFNE measurement technologies, data and output. Conclusions: The data analysis and systematic review uncovered a need and framework to develop and validate a web-based software algorithm for global access to improve the understanding of data interpretation of nasal measurements from three nasal measurement technologies. DAFNE Scoring should be used as an adjunct tool in routine clinical practice and research to further understand the technology data output and how to collaborate with other healthcare providers to improve patient outcomes.

It is common knowledge that estimating the height component of GNSS stations in general is much more problematic than estimating the horizontal position. Many different effects, such as tectonic signals, non-tectonic signals, atmospheric delay, noise, etc., are known to affect the height component of GNSS stations more than the horizontal component. However, the height component of GNSS stations is still poorly estimated. In this study, the height time series of 37 continuous GNSS stations covering the 2014–2019 date range is used from the Turkish National Permanent GNSS Network-Active (TUSAGA-Active). Since it is easier to interpret the effects of the height component due to its topographic features and seasonal changes being more effective than in the rest of the country, stations were chosen in the Eastern Anatolia region of Turkey. The daily coordinates of the GNSS stations were obtained as a result of the GAMIT/GLOBK software solution. By applying time series analysis to the daily coordinate values of the stations, statistically significant trends, periodic and stochastic components of the stations were determined. As a result of the analysis, the vertical velocities of the GNSS stations and the standard deviations of the vertical velocities were determined. Furthermore, when the height components of continuous GNSS stations were examined, it was seen that there were seasonal effects, and it was investigated whether the height components were related to meteorological parameters. For that, simple linear regression analysis was performed to determine how dependent the height components of the continuous GNSS stations were on meteorological parameters. As a result of the analysis, the height components of the continuous GNSS stations are dependent on meteorological parameters such as temperature, pressure, relative humidity, wind speed, and precipitation. In addition, height component time series analysis of continuous GNSS stations was performed by using Autoregressive Moving Average (ARMA) models from linear time series methods. As a result of the study, the performance of the ARMA modeling results again indicated the dependence of the height component of the continuous GNSS stations on the meteorological parameters.

Background and objectives: The impact of prenatal exposure to polycyclicaromatic 17 hydrocarbons (PAHs) on birth outcomes as weight, length, head circumference, placenta 18 weight, and Apgar. Materials and Methods: Two cohorts of children born in the years 2013 and 19 2014 in Karvina (Northern Moravia, N=144) and Ceske Budejovice (Southern Bohemia, 20 N=198), were studied for the relationship between the prenatal exposure to PAHs and growth 21 parameters up to two years of age. PAHs exposure was evaluated according to the concentration 22 of benzo[a]pyrene (B[a]P) in polluted air and monohydroxylated PAH metabolites (OH-PAHs) 23 in urine of newborns as well as their mothers. Data of growth parameters were obtained from 24 pediatric questionnaires up to 24 months. 25 Results: Concentrations of B[a]P were significantly higher in Karvina (p<0.001). OH-26 PAH metabolites were significantly higher in the mothers´ as well as in the newborns´ urine in 27 Karvina. The length was shorter in newborns in Karvina at birth (p<0.001), but this difference 28 was straightened out during next 3 to 24 months. Birth weight at the delivery did not differ 29 between newborns in Karvina and Ceske Budejovice. Newborns in both locations significantly 30 decreased their weight gain between birth and 3 months after delivery. OH-PAHs metabolites 31 in mother’s or newborn’s urine did not affect birth weight. Top 25% values of concentrations 32 of 2-OH-FLUO, 1-OH-NAP, 2-OH-NAP, 1-OH-PHEN, 2-OH-PHEN, 3-OH-PHEN, 4-OH-33 PHEN, and the sum of all-OH-PAHs higher than median in the newborns´ urine decreased their 34 length. 2-OH-PHEN top 25% of concentrations in the newborns´ urine decreased their head 35 circumference, 2-OH-FLUO, 1-OH-NAP, 2-OH-NAP, 1-OH-PHEN, 2-OH-PHEN, 3-OH-36 PHEN, 4-OH-PHEN, 9-OH-PHEN, 1-OH-PYR, and all-OH-PAHs decreased placenta weight; 37 2-OH-FLUO, 1-OH-NAP, 2-OH-NAP, 1-OH-PHEN, 2-OH-PHEN, 3-OH-PHEN, 4-OH-38 PHEN, and all-OH-PAHs decreased Apgar 5´. Conclusions: We observed that higher 39 concentration of PAHs determined as OH-PAHs metabolites in newborns´ urine decreased their 40 length, head circumference, placenta weight, and Apgar 5´, but did not affect birth weight.

Thrombosis is characterized by the pathological formation of fibrin clots within a blood vessel, leading to the obstruction of blood flow. Fibrinolytic enzymes from microorganisms have exhibited promising effects to dissolve clots in a more efficient and safe way. Then, the aim of this study was to evaluate the biomass and fibrinolytic enzyme production of Tetradesmus obliquus under autotrophic and mixotrophic conditions using different concentration of corn steep liquor (CSL). Different extraction and precipitating methods were tested, and the enzyme was purified by ion exchange chromatography. More advantageous culture condition was mixotrophic using 0.25% CSL, showing the highest values of biomass productivity (Px = 169.3 ± 44.36 mg∙L-1day-1) and specific growth rate (µmax = 0.17 ± 0.00 day-1), and significant fibrinolytic production (391.34 ± 40.03 U∙mg-1). Moreover, fibrinolytic activity was higher when extracted by homogenization and precipitated using acetone, which exhibited clear zone of fibrin degradation in the fibrinolytic plate assay. Additionally, the purified enzyme showed specific activity of 1176.90 ± 140.37 U∙mg-1 and molecular weight around 97 kDa. Finally, the enzyme has higher enzymatic activity than various fibrinolytic enzymes, and the obtained enzyme has potential to be developed as a therapeutic agent in thrombosis treatment. Additional studies are need to investigate the biochemical properties and biological profile of this enzyme.

Urban vitality, understood as a key factor for the achievement of cities’ sustainability, shows a strong relationship with urban morphology. The city theorist Jane Jacobs suggested morphologi-cal aspects to promote vital cities already in the 1960s, which remain valid in the present. How-ever, few studies in the Andean region quantitatively exemplify this. This paper aims to test the measurement of urban vitality in a neighborhood of Quito, Ecuador, called La Mariscal, inte-grating Jacobs’ approach. In particular, three urban vitality indexes are evaluated with the appli-cation of GIS software using cadastral data obtained from the municipality and field data col-lection. Results show that the context-based previous knowledge and the scale of analysis are es-sential factors in the configuration of dimensions, indicators, and spatial representation of any urban vitality index. In the study area land use mixture, contact opportunity, and accessibility dimensions are fundamental. Regarding indicators, the incorporation of the informal small-scale commerce, the quality of sidewalks, the street slope, and the good-conditioned street furniture is recommended. Finally, a hybrid representation (raster and vectorial) is suggested to precisely measure urban vitality at a block scale. Altogether, by providing a comparative approach, we in-tend to bring a useful framework for researchers and planners to study urban vitality in Andean cities.

Water is an essential commodity to sustain life. The condition of water in Tiruchirappalli was measured using different Physicochemical parameters like Temperature, pH, TDS, Total Solids, Salinity, Total Hardness, and Electrical Conductivity. Water samples were collected from different places in Tiruchirappalli city, Tamil Nadu. Water samples were examined by different chemical methods. According to the results, Thiruvarambur-1 showed comparatively higher results in the case of every parameter compared to other sampling stations. Obtained results were further interpreted using statistical tools. Considering ECs as a principal component for the regression and correlation analysis with other parameters significant correlation was found. A strong correlation was observed between ECs and TDS, Total Hardness, Turbidity, and Salinity.

Background: Pre-pregnancy overweight and obesity of women of childbearing ages, has alarmingly a growing trend in developed countries. This study aimed to evaluate potential associations between maternal pre-pregnancy excess body weight and childhood demographic and anthropometric characteristics, as well as perinatal and postnatal outcomes. Methods: This is a cross-sectional study conducted on 5198 pre-school children aged 2-5 years old and their matched mothers that were enrolled from nine different Greek regions. Maternal and childhood anthropometric and demographic data, perinatal and postnatal outcomes were collected from medical history records or validated questionnaires. Results: A prevalence of 24.4% and 30.6% of overweight/obesity was recorded for the enrolled children and their mothers 2-5 years postpartum. In multivariate analysis, childhood overweight and obesity was significantly more frequently observed when maternal pre-pregnancy BMI status was overweight or obese [OR: 2.11 (1.80-2.42) p=0.0001]. A high prevalence of caesarean section delivery and childhood diabetes type I was also significantly associated with maternal pre-pregnancy overweight/obesity [OR:1.71 (1.33-2.19) p=0.0175) and OR: 1.27 (1.04-1.53) p=0.0014, respectively]. Conclusions: Maternal pre-pregnancy overweight and obesity rates were related with increased childhood weight status at birth and 2-5 years postpartum, highlighting the necessity of encouraging healthy lifestyle promotion, including healthier nutritional habits, and focusing on obesity population policies and nutritional interventions among women of reproducible age.

The quality of yarn is essential in the control of the fabrics processes. There is some commercial equipment that measures the quality of yarn based on sensors, of different types, used for collecting data about some yarn characteristic parameters. The existing equipment, for the above-mentioned purpose, is characterized by its high size and cost, and for allowing the analysis of only few yarn quality parameters. Thus, this paper presents the development and results obtained with the design of a mechatronic prototype integrating a computer vision system that allows, among other parameters, the analysis and classification, in real time, of the hairs of the yarn using artificial intelligence techniques. The system also determines other characteristics inherent to the yarn quality analysis, such as: linear mass, diameter, volume, twist orientation, twist step, average mass deviation, coefficient of variation, hairiness coefficient, average hairiness deviation and standard hairiness deviation, as well as performs spectral analysis. A comparison of the obtained results with the designed system and a commercial equipment was performed validating the undertaken methodology.

Abstract: In recent years, low frequency (LF) electroencephalogram (EEG) signals have been decoded to obtain kinematic trajectories with the aim of achieving closed loop natural control. However, decoded trajectories suffer variability and low correlation against the measured movement. This paper suggests that if EEG features of motor intents are directly associated with fixed points along a given range of motion, then the natural kinematic parameters can be quantified. A novel classification method is proposed to evaluate this hypothesis along with equations for obtaining the movement parameters (velocity, acceleration). Furthermore, this implies that the force of an end-effector and work done in moving the end-effector may be computed, leading to natural control of EEG-based robotic arms and neuroprostheses. Finally, expectations are that combining the proposed method with existing classification methods will increase the accuracy and scalability of brain-computer interface (BCI) applications.

Natural systems of units $\{U_i\}$ need to be overhauled to include the dimensionless coupling constants $\{\upalpha_{U_i}\}$ of the natural forces. Otherwise, they cannot quantify all forces of nature in a unified manner. Thus, each force must furnish a system of units with at least one dimensional and one dimensionless constant. We revisit three natural systems of units (atomic, cosmological, and Planck). The Planck system is easier to rectify, and we do so in this work. The atomic system discounts $\{ G, \upalpha_G \}$, thus it cannot account for gravitation. The cosmological system discounts $\{ \slashed{h}, \upalpha_\slashed{h} \}$, thus it cannot account for quantum physics. Here, the symbols have their usual meanings; in particular, $\upalpha_G$ is the gravitational coupling constant and $\upalpha_\slashed{h}$ is Dirac's fine-structure constant. The speed of light $c$ and the impedance of free space $Z_0$ are resistive properties imposed by the vacuum itself, thus they must be present in all systems of units. The upgraded Planck system with fundamental units $${\rm UPS} \,:=\,\{ c, Z_0, G, \upalpha_G, \slashed{h}, \upalpha_\slashed{h}, \,\dots\,\!\},$$ describes all physical scales in the universe---it is nature's system of units. As such, it reveals a number of properties, most of which have been encountered previously in seemingly disjoint parts of physics, and some of which have been designated as mere coincidences. Based on the UPS results, that relate (sub)atomic scales to the Planck scale and the fine-structure constant to the Higgs field, we can state with confidence that no observed/measured physical properties are coincidental in this universe. Furthermore, we derive from first principles Koide's $K=2/3$ enigmatic constant and additional analogous quark and vector boson constants. These are formal mathematical proofs that justify a posteriori the use of geometric means in deriving the quark/boson mass ladder. This ladder allows us to also calculate the Higgs couplings to the vector bosons and the Weinberg angle in terms of only $K$.

The pore-throat radius of shale oil reservoir is extremely small, and it is difficult to accurately obtain the absolute permeability and oil-water two-phase relative permeability of actual oil reservoir through conventional core experiments. However, these parameters are very important for reservoir numerical simulation. In this paper, a method for characterizing flow parameters based on pore network model that considers differential pressure flow and diffusion flow is proposed. Firstly, a digital core was reconstructed using focused ion beam scanning electron microscopy (FIB-SEM) from the Gulong shale reservoir in the Songliao Basin, China, and a pore network model was extracted. Secondly, quasi-static single-phase flow and two-phase flow equations considering diffusion were established in the pore network model. Finally, pore throat parameters, absolute permeability, and oil-water two-phase permeability curves were calculated, respectively. The results show that the pore throat distribution of Gulong shale reservoir is mainly concentrated in the nanometer scale, the mean pore radius is 87 nm, the mean throat radius is 41 nm, and the mean coordination number is 3.97; The calculated permeability considering diffusion is 0.000124mD, which is approximately twice the permeability calculated without considering diffusion; The irreducible water saturation of the Gulong shale reservoir is approximately 0.26, and the residual oil saturation is approximately 0.73. The method proposed in this paper can provide an important approach for characterizing the flow parameters of similar shale oil reservoirs.

Background. Pose estimation based on deep learning has been expected to be a breakthrough method to increase the accuracy of clinical photographic evaluation and to decrease interobserver errors. The purpose is to quantify pose estimation from photography of patients with adolescent idiopathic scoliosis (AIS) using open-source software packages and determine correlations between parameters obtained by radiography and photography. Methods. We included 12 consecutive patients with AIS treated with spinal correction surgery. Photographs were taken preoperatively using a tripod-mounted camera (iPhone 13Pro) on an X-ray tube head. To assess photographic parameters obtained by photography, we defined 17 points to analyze posture and define parameters. Results. In the sagittal plane, there was a significant correlation between the radiographic trunk tilt angle and the photographic sagittal trunk tilt angle of the shoulder–hip and ear–hip. In the coronal plane, there was a significant correlation between the radiographic clavicle angle and the photographic shoulder height angle, and the radiographic C7–CSVL and the photographic coronal trunk tilt angle. Conclusions. Posture analysis by photography using popular mobile devices has clinical utility for improving and promoting the screening and early detection of AIS because it is simple, without patient exposure to X-ray radiation.

This research paper examines a cosmological model in flat space-time via $f(R,G)$ gravity where $R$ and $G$ are respectively the Ricci scalar and Gauss-Bonnet invariant. Our model assumes that $f(R,G)$ is an exponential function of $G$ combined with a linear combination of $R$. We scrutinize the observational limitations under a power law cosmology that relies on two parameters - $H_0$, the Hubble constant, and $q$, the deceleration parameter, utilizing the 57-point $H(z)$ data, 8-point BAO data, 1048-point Pantheon data, joint data of $H(z)$ + Pantheon, and joint data of $H(z)$ + BAO + Pantheon. The outcomes for $H_0$ and $q$ are realistic within observational ranges. We have also addressed Energy Conditions, $Om(z)$ analysis and cosmographical parameters like Jerk, Lerk and Snap. Our estimate of $H_0$ is remarkably consistent with various recent Planck Collaboration studies that utilize the $\Lambda$CDM model. According to our study, the power law cosmology within the context of $f(R,G)$ gravity provides the most comprehensive explanation for the important aspects of cosmic evolution.

Foxtail millet (Setaria italica (L.) P. Beauv) is an important food and forage crop that is well adapted to nutrient-poor soils. However, little is known about how foxtail millet adapts to low nitrogen (LN) at the physiological and molecular levels. In the present study, two foxtail millet varieties with contrasting low nitrogen (LN) tolerance properties were investigated through integrative analyses of physiological featureparameters and transcriptomics. The physiological results showed that JG20 (high tolerance to LN) had higher biomass accumulation, nitrogen content and nitrogen use efficiency compared with JG22 (low tolerancesensitive to LN) under LN. JG20 had higher soluble sugar and soluble protein concentration in shoots compared with JG22 under LN, while contcentrations of soluble sugar and soluble protein contents were higher in the roots of JG22. Higher levels of CTK contentzeatin concentration were found in the shoots of JG20 com-pared with JG22, and a higher ABA contcentration was found in both the shoots and roots of JG22 compared with JG20 under LN. In the transcriptomics results, JG20 had more differentially ex-pressed genes (DEGs) than JG22 both in shoots and roots in response to LN. These LN-responsive genes were enriched in glycolysis, starch and sucrose metabolism, photosynthesis, biosynthesis of amino acids, hormone metabolism and nitrogen metabolism. Furthermore, the high-affinity nitrate transporter gene, SiNRT2.1, and glutamine synthetase gene, SiGS5, chlorophyll apoprotein of photosystem II gene, SiPsbQ, ATP synthase subunit gene, b, auxin-responsive protein gene, SiIAA25, and aldose 1-epimerase gene, SiAEP, in shoots, and high-affinity nitrate transporter gene, SiNRT2.3, SiNRT2.4, and glutamate synthase gene, SiGOGAT2, auxin-responsive protein gene, SiIAA4, fructose-bisphosphate aldolase gene, SiAEP5, in root, were important genes in-volved in the LN tolerance of foxtail millet. These results provide a detailed description of the physiological and transcriptome response of foxtail millet under LN condition.

This article analyzes 6 probability distributions from the Generalized Pareto family, with 3, 4 and 5 parameters, with main purpose to identify other distributions from this family with applicability in flood frequency analysis compared to the distribution already used in the literature from this family such as Generalized Pareto Type II and Wakeby. This analysis is part of a larger and more complex research carried out in the Faculty of Hydrotechnics regarding the elaboration of a norm for flood frequency analysis using the linear moments method. In Romania, the standard method of parameter estimation is the method of ordinary moments, thus the transition from this method to the method of linear moments is desired. All the necessary elements for the distributions use are presented like, the probability density functions, the complementary cumulative distribution functions, the quantile functions, the exact and approximate relations for estimating parameters, for both methods of parameters estimation. All these elements are necessary for a proper transition between the two methods, especially since the use of the method of ordinary moments is done by choosing the skewness of the observed data depending on the origin of the maximum flows. A flood frequency analysis case study, using annual maximum and annual exceedance series, was carried out for the Prigor river, to numerically present the analyzed distributions. The performance of this distributions is evaluated using relative mean error, relative absolute error and linear moments diagram.

This article presents six probability distributions from the Gamma family with three parameters, for the flood frequency analysis in hydrology. The choice of the Gamma family of statistical dis-tributions was driven by its frequent use in hydrology. In the Faculty of Hydrotechnics, the im-provement of the estimation of maximum flows and including the methodological bases for the realization of a regionalization study with the linear moments method with the corrected pa-rameters was researched, being an element of novelty. The linear moments method is better than MOM because it avoids the choice of skewness depending on the origin of the flows, practiced in Romania. The L-moments method conforms to the current trend for estimating the parameters of statistical distributions. Observed data from hydrometric stations are of relatively short length, so the statistical parameters that characterize them are of a sample that requires correction. The correction of the statistical parameters is proposed, using the method of least squares based on the inverse functions of the statistical distributions expressed with the frequency factor for L-moments. All the necessary elements for their use are presented like, quantile functions, the exact and ap-proximate relations for estimating parameters and frequency factors. A flood frequency analysis case study was carried out for the Ialomita river, to verify the proposed methodology. The per-formance of this distributions is evaluated using Kiling-Gupta and Nash-Sutcliff coefficients.

Colic, a primary cause of illness and death in horses, necessitates improved prognostic tools. We assessed the predictive value of physiological parameters in colic prognosis. A comprehensive clinical evaluation encompassed heart rate, mucous membranes, capillary refill time, rectal temperature, respiratory rate, gut motility, reflux, and limb pulse strength. Results reveal key predictors of fatal outcomes in colic-affected horses. Stomach reflux, absence of gut noises, and increased heart rate (mean increase of 12 bpm) strongly correlate with a poor prognosis. Prolonged capillary refill (mean increase of 3 seconds), elevated packed cell volume (mean increase of 4%), and blood lactate levels (mean increase of 5 mmol/L) underscore the significance of these markers. Notably, blood lactate (p < 0.001), gut noises (p < 0.05), and heart rate (p < 0.001) exhibit the highest predictive significance based on statistical analysis. Future research should explore the prognostic potential of additional parameters and assess the impact of recommended treatments on colic prognosis. This data-driven study emphasizes the critical role of early recognition and thorough assessment in colic cases, offering vital insights into improving equine healthcare and mitigating mortality rates.

Diabetes mellitus – type 2 (DM2) is a hypercoaguable state with enhanced platelets (PLTs) activation and increased clotting factor production. Simultaneously, the fibrinolytic cell system is inhibited due to formation of clots with high resistance to fibrinolysis. The stages of PLTs "activation" have been well-characterized microscopically, morphometrically and nanomechanically (by light microscope, transmisiion electron microscope - TEM, scanning electron microscope - SEM and atomic force microscope - AFM). Thrombocytes in "acivated" (pro-coagulant) state play central role in two main biological processes: hemostasis and repair of vascular vessels. Pro-coagulant PLTs participate in generation of thrombin and in development of fibrin fibers in the clot matrix. Enhanced PLTs reactivity in dibetic- (diabetes mellitus - DM2) patients is considered as a "pro-thrombotic" state. In the retrospective- and prospective- studies on the topic, the higher are the PLTs' hematometrical indices: PLTs (count), MPV (mean platelet volume), PDW (platelet distribution width), PCR (plateletcrit), as well as PLTs/Ly ratio. The PLТs parameters/indices are usefull biomarkers in early diagnosis and prognosis of DM2. The precise studies of PLTs' state of activation during DM2 might be useful for creation of new diabetes (DM2) treatment strategies and effective medicines. Using the amount of blood glucose, attached to hemoglobin (HbA1c values) as markers of glycemic control in diabetic patients, researchers have observed association between MPV and medications as Insulin, Metformin, sulphonyl ureas. Computational modellng of PLTs' activation in DM2 is also a controlling factor for thrombocyte distribution and margination in bood vessels, associated with micro- and macrovascular disease in DM2. PLTs-derived miRNAs are novel molecular biomarkers for diagnosis and prognosis of DM2, insulin resistance and diabetes complications. We have proposed (2010) oleic acid (OA) as a substance suppressing "PLT hyperactivation" and inhibiting “thrombocyte aggregation”. Antiplatelet agents, natural plant products including, could be effective in the prevention and the secondary treatment of micro- and macrovascular complications in the type 2 Diabetes mellitus. Our proposal on following up of a combination of hematological-, hemorheological- and hemostatic parameters (indices) as a new way in diagnosis, treatment, predicting and management of DM2 and its related vascular complications, probably could be more explored in future studies.

Buckwheat is returning to the countries of Central Europe. There are several reasons for this: firstly, because of its interesting chemical composition, which is reflected in its nutritional value and potential health benefits. And secondly because buckwheat, and especially buckwheat flour, are suitable raw materials for the production of gluten-free foods. Buckwheat flours are classified similarly to wheat flours, but the different anatomy of wheat grains and buckwheat seeds makes this classification partly misleading. While wheat flours are largely produced by one standard process, the production process for buckwheat flours is more varied. For wheat and wheat flours, the basic quality parameters and their required ranges for different types of primary and secondary processing are clearly defined. This is not the case for buckwheat and buckwheat flours, and the definition of the parameters and their ranges that characterize its technological quality remain unclear. The standardization of quality parameters and production processes is likely to be necessary for the potential expansion of the use of buckwheat for food production and in particular for bakery products.

This study aimed to analyse the variation of recreational water quality in Plettenberg Bay in an attempt to comprehend the effects of pollution on the environment, and more specifically the potential impacts on the quality of surface water used for recreational activities. Plettenberg Bay is a major destination for tourists in South Africa, with recreational water activities representing an important attraction. For this study, data were obtained from Bitou Municipality, the local au-thority in charge of the water monitoring program in Plettenberg Bay. The selected datasets contained water quality data collected by the Bitou Municipality waterworks department in three sampling sites in Plettenberg Bay. The samples were tested for six water quality parameters namely, Ammonia, Suspended Solids, Conductivity, Nitrates/Nitrites, pH, and E coli. Water quality trends appeared stabile over the five years, with only a few parameters showing variation in their concentration levels. It is recommended that the Bitou Municipality increase the sampling frequency to allow a clearer understanding of water quality variation and to minimise potential uncertainties.

The rationalization and modeling of an electric discharge in a fluid require the knowledge of electron swarm parameters. In this work, transport coefficients of alcohols, including methanol, ethanol, propanol, and butanol are reported. The electron energy distribution function, mean energy, reduced mobility, and diffusion coefficient, are calculated using the two-term expansion of the electron Boltzmann equation in the frame of BOLSIG+ and the Monte Carlo collision code METHES. For such, experimental and theoretical values of the electron-alcohol collision cross-section, covering a range of electron impact energy from 1 eV to 1000 eV, are employed. A temperature of 300K, reduced fields E/N between $1-10^4$ Td (1Td = $10^{-21}~\rm Vm^2$), and Plasma density of $10^{19}~\rm m^{-3}$ were used in simulations. The calculated coefficients are compared with data available from previous studies.

Electrode degradation in continuous resistance spot welding process of BH 220 steel was evaluated by electrode life test, and weldability tests were conducted by geometry features measurement, mechanical property analysis, and electrode diameter measurement with 88 or 176 weld intervals. The analysis of weld geometry shows that the HAZ width, nugget diameter, and nugget area tend to decrease rapidly, while the nugget height tends to firstly increase with the weld repetitions till the welding heat input becomes too small to form the valid nugget. The peak load shows a rapid downward trend, while failure energy and maximum displacement slightly increase till the 176th weld and then decrease. The cavities and pores in the nugget mainly appear after the 176th spot weld. The electrode diameter increases during welding. The reason for the increase in electrode diameter may be that the contact area between the electrode and BH 220 steel sheets becomes smaller in the welding process, which causes the continuous sticking phenomenon between the electrode and the BH 220 steel sheets. In the absence of alloying, the edge of the electrode is geometrically deformed, while Cu-Zn-Fe alloying occurs in the area in contact with the BH 220 steel sheet.

Determining genetic and non-genetic sources of variation in a breed is vital for the formulation of strategies for its conservation and improvement. The present study was aimed at estimating the (co)variance components and genetic parameters of Mecheri sheep by fitting six different animal models in the restricted maximum likelihood method, with a preliminary investigation on the performance of animals for non-genetic sources of variation. A total of 2616 lambs were studied, and varying levels of significance were found for the effect of period, season, parity of dam and birth type on different body weight traits. Direct heritability estimates derived from the best animal model for body weight at birth, 3 months, 6 months, 9 months and 12 months were 0.21, 0.24, 0.10, 0.15 and 0.09, respectively, and maternal heritabilities of the corresponding traits were 0.12, 0.05, 0.04, 0.04 and 0.04, respectively. The genetic correlations between body weight traits were all positive and moderate to strong except for birth weight with the other body weight traits. The significance of non-genetic factors studied in this work demanded a correction to improve the accuracy of the direct selection of lambs for body weight traits. The estimated genetic parameters identified the weaning weight as a selection criterion for the improvement in body weight of Mecheri lambs at different ages. Inbred individuals accounted for approximately 13% of the total population in the Mecheri sheep population studied. There were 877 founders in the population, and the actual effective size of the population was 128.48. The population's mean generation interval was 3.26. The mean inbreeding values ranged from 0.005 to 0.010 across generations. The population's average relatedness ranged from 0.001 to 0.014 across generations. Individual inbreeding was found to be 0.45 per cent for the entire population and 3.4 per cent for the inbred population.

Induction heating (IH) technology is widely recognized and utilized in residential applications due to its high efficiency and safe operating characteristics. Resonant inverter circuits are widely used in IH systems because of their high efficiency and ability to perform soft-switching. Among the various resonant inverters used in IH systems, the single-switch quasi-resonant (SSQR) inverter topology is typically preferred for low-cost and low-output-power applications. Despite its cost advantage, the SSQR topology has a relatively narrow soft-switching range, which can be unstable depending on the electrical parameters of the load and the resonant converter circuit. Accurately determining the capacitance value of the resonant capacitor and the inductance value of the induction coil, which are the key circuit elements of the SSQR induction cooker, is crucial for designing a reliable, efficient, and durable cooking system. In other words, there exists a critical relationship between the resonant converter circuit parameters, load characteristics, and safe operating conditions. Additionally, when considering closed-loop control methods used for power control and safety, selecting appropriate resonant circuit elements becomes vital in ensuring both reliable and efficient operation. This paper focuses on a novel and simplified design method for the SSQR inverter utilized in household appliances. The proposed method and its advantages in terms of the safe operating area of the switch are theoretically investigated and verified through simulations and prototype circuits.

This study presents the manufacturing process driven development of an interlocking metasurface mechanism (ILM) for Fused Filament Fabrication (FFF) with a focus on open-source accessibility. The presented ILM is designed to enable strong contact between to planar surfaces. The mechanism consists of spring elements and locking pins which snap together when forced into contact. The mechanism is designed to optimize mechanical properties, functionality and printability with common FFF printers. The mechanisms is printed from thermoplastic polyurethane (TPU) filament which was selected for its flexibility, crucial for spring element performance and tolerances of the fabrication method. To characterize the designed mechanism a tensile test is carried out to assess the holding force of the ILM. The force-displacement profiles are analyzed and categorized into distinct phases, highlighting the interplay between spring deformation, sliding, and disengagement. The results show variations in holding forces attributed to geometric and material-related factors. The testing results are compared and discussed to a numerical simulation carried out with a frictionless approach with a nonlinear Neo–Hookean material law. The study underscores the importance of meticulous parameter control in 3D printing for consistent and reliable performance of interlocking metasurface mechanisms. The investigation leads to a scalable model of a ILM element pair with a distinct three-phase snapping characteristics ensuring reliable holding capabilities.

Abstract: Field studies with large-stemmed plants Artemisia dubia (wormwood) have been carried out at Vėžaičiai Branch LAMMC since 2018. According to three years of experimental results, annual dry matter (DM) yield varied from 7.94 to 10.14 t ha-1. Growing conditions, nitrogen ap-plication level and harvesting time had significant impacts on Artemisia dubia productivity. This article presents the results of research on preparation and use of Artemisia dubia biomass for en-ergy conversion and evaluation of technological-technical and environmental parameters of these plants utilization for solid biofuel. For experiments were used 6 variants of Artemisia dubia samples, which were grown in 2021: plants were cut three times and two fertilization options were used: (1) no fertilization and (2) fertilization with 180 kg ha-1 of nitrogen fertilizer. These harvested plants were chopped, milled and were pressed into the pellets. The physi-cal-mechanical characteristics (mоisture content, density and strength) of Artemisia dubia pellets were investigated. During this study, it was found that the density in dry mass (DM) of pellets ranged from 1119.86 to 1192.44 kg m-3. The pellet moisture content ranged from 8.80 to 10.49%. After testing of pellet strength, it was found that the pellets which were made from plant bio-mass PK-1-1, were the most resistant to compression, they withstood 560.36 N of pressure. Dry fuel lower heating value (LHV) of pellets was sufficiently high and was very close to pine saw-dust pellets, it varied from 17.46±0.25 MJ kg-1 to 18.14±0.28 MJ kg-1. The ash content of burned pellets ranged from 3.62±0.02% to 6.47±0.09%. Emissions of harmful pollutants – CO2, CO, NOx and unburnt hydrocarbons (CxHy) did not exceed the maximum permissible levels. Summariz-ing the results of investigated properties, cоmbustion and emissiоns of Artemisia dubia pellets, it can be concluded that this biofuel can be used for production of pressed biofuel and it is charac-terized by sufficient high quality, efficient combustion and permissible emissions to the envi-ronment.

Accurate evaluation of health status of lithium-ion batteries must be deemed as of great significance, insofar as utility and safety of batteries are of concern. Lithium plating, in particular, is notoriously known to be a chemical reaction that can cause deterioration in, or even fatal hazards to, the health of lithium-ion batteries. Electrochemical impedance spectroscopy (EIS), which has distinct advantages such as fast or non-destructive over its competitors, suffices in detecting lithium plating and thus has been attracting increasing attention in the field of battery management, but its ability of assessing quantitatively the degree of lithium plating remains largely unexplored hitherto. On this point, this work seeks to narrow that gap, by proposing an EIS-based method that can quantify the degree of lithium plating. The core conception is to eventually circumvent the reliance on state-of-health measurement, and use instead the impedance spectrum, to acquire an estimate on battery capacity loss. To do so, the effects of solid electrolyte interphase formation and lithium plating on battery capacity must be first decoupled, so that the mass of lithium plating can be quantified. Then, based on an impedance spectrum measurement, the parameters of the fractional equivalent circuit model (ECM) of the battery can be identified. These fractional ECM parameters are received as inputs by an artificial neural network, which is tasked to establish a correspondence between the model parameters and the mass of lithium plating. The empirical part of the work revolves around the data collected from an aging experiment, and the validity of the proposed method is truthfully attested by dismantling the batteries, which is otherwise not needed during the actual uptake of the method.

Different toll collection types of vehicles and different distribution of tollbooths lead to the toll plaza diverging area becoming a typical vehicle weaving area with frequent crossing behaviors and conflicts on highways. This study aims to identify contributing factors to conflict risks of four vehicle-following patterns in a toll plaza diverging area by developing random parameters ordered logit models with heterogeneity in means and variances. The model can flexibly capture the unobserved heterogeneity of the contributing factors in different vehicle-following patterns. Real-world vehicle trajectory data obtained from the toll plaza diverging area in Nanjing, China, are used for model estimation. The results show that vehicle-following patterns with the same toll collection types have higher percentage of severe conflict risks. The average acceleration of the following vehicles, lane marking indicator, the initial lanes and lane-changes of vehicles are significantly associated with the collision risk levels. The standard deviation of surrogate safety measures of all vehicles in sub-segments are found differ significantly between vehicle-following patterns. Furthermore, a series of likelihood ratio tests are adopted to test the spatial dependence in sub-segments of the diverging area. The findings of this study could provide valuable information for safety improvement in toll plazas.

This work is the first scientific study on the development of the composition and technology of a new antioxidant agent based on a combination of extracts of tree medicinal plants and the study of the technological parameters of a dry extract. Further draw up technological regulations for their production and their introduction into production. This study aims to the antioxidant activity of dry extract "Antioxim" was determined. In order to create this herbal collection of plant, first of all, to study the technological parameters of raw materials, such as mass size, porosity, dispersibility, free volume of layers of raw materials, water absorption coefficient of extractives, and technological process efficiency to study the effect of parameters, developed at the Department of "Industrial Technology of Medicines" of the Tashkent Pharmaceutical Institute:

In recent years, there has been growing interest in thermal spray techniques using suspension or solution-based coatings. These techniques offer precise control over particle size and microstructure, improving feedstock flowability and allowing for high-quality coatings customization. Spray parameters, such as stand-off distance (SOD) and feedstock flow rate, can alter the performance and characteristics of these coatings. Geothermal power plant heat exchangers often face issues like corrosion, scaling, and fouling. These issues could be mitigated, at least in part, by the use of spray coatings. In this study, TiO2 coatings were applied to a carbon steel substrate using suspension plasma spray (SPS) to enhance the performance of geothermal heat exchanger materials. The impact of SOD (50, 75, and 100mm) and feedstock flow rate (10, 20, and 30 ml/min) on these coatings was examined through various techniques, including SEM, profilometry, XRD, and adhesion testing. The results demonstrated that coatings deposited using 10ml/min feedstock flow rate were well-adhered to the substrate due to efficient melting of coating material but as the SOD and feedstock flow rate increase due to poor thermal and kinetic energy exchange between the torch and feedstock particles, adhesion between coating and substrate decreases. smaller SODs led to more compact coatings, while higher feedstock flow rates increased coating porosity. Smaller SODs and lower flow rates resulted in well-adhered coatings, offering valuable insights for advancing geothermal heat exchanger coatings.

Corrugated board, widely used in the packing industry, is a recyclable and durable material. Its strength and cushioning, influenced by geometry, environmental conditions like humidity and temperature, and paper quality, make it versatile. Double-walled (or five-ply) corrugated board, comprising two flutes and three liners, enhances these properties. This study introduces a novel approach to analyze 5-layered corrugated board, extending a previously published algorithm for single-walled boards. Our method focuses on measuring layer and overall board thickness, flute height, and center lines of each layer. Integrating image processing and genetic algorithms, the research successfully developed an algorithm for precise geometric feature identification of double-walled boards. Images were recorded using a special device with a sophisticated camera and image sensor for detailed corrugated board cross-sections. Demonstrating high accuracy, the method faced limitations only with very deformed or damaged samples. This research contributes significantly to quality control in the packaging industry and paves the way for further automated material analysis using advanced machine learning and image sensors. It emphasizes the importance of sample quality and suggests areas for algorithm refinement to enhance robustness and accuracy.

This work presents the electrochemical degradation of the herbicide Diuron by anodic oxidation on a Ti/Ru0.3Ti0.7O2 dimensionally stable anode (DSA) using sulfate as electrolyte. The study includes the influence of the Diuron concentration and the current density on the anodic oxidation. The results evidence a first-order degradation, with the highest degradation capacity achieved at 40 mA cm2 and an initial Diuron concentration of 38 mg L1. Nevertheless, in terms of efficiency and energy demand, the operation at 10 mA cm2 is favored due to the more efficient and less energy-consuming condition. To discern the optimum design and operation conditions, this work presents the results of a preliminary technical-economical analysis, demonstrating that, to minimize the total costs of the system, it is recommended to seek the most efficient conditions, i.e., the conditions demanding the lowest applied charges with the highest Diuron degradation. At the same time, attention must be given to the required cell voltage to not increase excessively the operating costs.

Background: A careful work-up before Transcatheter aortic valve replacement (TAVR) consists not only of measuring anatomical conditions but also assessment of frailty. Previous studies have evaluated body composition parameters, primarily fat and muscle mass. Few data are available on other frailty parameters, which, however, can be easily determined by pre-TAVR computed tomography (CT). Objectives: The primary objective was to investigate the impact of total muscle area (TMA) and visceral adipose tissue (VAT), as frailty parameters, on 5-year all-cause mortality in patients undergoing TAVR. Methods: Between 01/2017 and 12/2018, consecutive TAVR patients undergoing CT-angiography scan enabling TMA and VAT measurement were included. A single axial image was acquired at the level of the middle third lumbar vertebra to perform TMA and VAT measurements using dedicated slicing software (Sliceomatic, TomoVision). Results: A total of 500 patients qualified for TMA analysis. Age was not associated with a higher risk of 5-year mortality HR 1.02 (95% CI: 0.998 - 1.049; p=0.069). Body surface area normalized TMA (nTMA) was significantly associated with 5-year all-cause mortality (HR 0.927, 95% CI: 0.927-0.997; p= 0.033), while VAT had no effect (HR 1.002, 95% CI: 0.99-1.015; p= 0.7). The effect of nTMA on 5- year all-cause mortality was gender-dependent: the protective effect of higher nTMA was found in male patients (pinteraction: sex * nTMA = 0.007). The combination of normalized TMA and VAT was not associated with higher mortality rates. Conclusion: Normalized TMA derived from routine CT before TAVR complements frailty assessment in patients undergoing TAVR.

In recent decades, as eutrophication in inland and coastal waters (ICWs) has increased due to anthropogenic activities and global warming, so has the need for timely monitoring. Compared with traditional sampling and laboratory analysis methods, satellite remote sensing technology can provide macro-scale, low-cost, and near real-time water quality monitoring services. The Geostationary Ocean Color Imager (GOCI), integrated onboard the Communication Ocean and Meteorological Satellite (COMS) from the Republic of Korea, was the first geostationary ocean color observation satellite and was operational from April 1, 2011 to March 31, 2021. Over ten years, GOCI has observed oceans, coastal waters, and inland waters within its 2,500 km×2,500 km target area centered on the Korean Peninsula. The most attractive feature of GOCI, compared with other commonly used watercolor sensors, was its high temporal resolution (1h, eight times daily from 0 UTC to 7 UTC), providing the opportunity to monitor the quality of ICWs, where optical properties can change rapidly throughout the day. This systematic review aims to comprehensively review GOCI features and applications in ICWs, analyzing progress in atmospheric correction algorithms and water quality monitoring. Analyzing 123 articles from the Web of Science and China National Knowledge Infrastructure (CNKI) through a bibliometric quantitative approach, we examined GOCI’s strength and performance with different processing methods. These articles reveal that GOCI played an essential role in monitoring the ecological health of ICWs in its observation area in East Asia. GOCI has led the way to a new era of geostationary ocean satellites, providing new technical means for monitoring water quality in oceans, coastal zones, and inland lakes. We also discuss the challenges encountered by geostationary satellites in monitoring water quality and provide suggestions for improvements.

Four-polarisation camera was used to map absorbance of olivine micro-grains before and after high temperature annealing (HTA). It is shown that HTA of olivine xenolith at above 1200∘C in O2 flow makes it magnetised. Different mode of operation of polariscope with polarisation control before and after the sample in transmission and reflection modes was used. The reflection type was assembled for non-transparent samples of olivine after HTA. Sample for optical observation in transmission was placed on an achromatic plastic quarter-wavelength waveplate as a sample holder. Inspection for sample’s birefringence (retardance) as well as absorbance can be made. A best fit of transmitted intensity or transmittance T (hence absorbance A=−log10T) becomes accessible by simple best-fit using only three orientations (from measured four orientations by the camera). When intensity of transmitted light at one of the orientations was very low due to cross-polarised condition (polariser-analyser arrangement), the three-points fit can be used. Three-point fit in transmission and reflection modes was validated for T(θ)=Amp×cos(2θ−2θshift)+offset, where amplitude Amp, offset offset and orientation azimuth θshift are extracted for each pixel via the best fit.

Accurate and robust methods are needed to monitor crop growth and predict grain yield and quality in breeding programs under variable agrometeorological conditions. Field experiments were conducted during two successive cropping seasons (2021, 2022) at four trial locations (Estonia, Latvia, Lithuania, Norway). The focus was on assessment of grain yield (GY), grain protein content (GPC), and UAV-derived NDVI measured at different plant growth stages. Performance and stability of 16 selected spring wheat genotypes were assessed under two N application rates (75, 150 kg N ha−1) and over contrasted agrometeorological conditions were assessed, and the quantitative relationships between agronomic traits and UAV-derived variables were figured out. None of the traits were subject to a significant (p&lt;0.05) genotype by nitrogen interaction. High-yielding and high-protein genotypes were detected with high WAASB stability, specifically under high and low N rates. This study highlights the significant effect of NDVI analysis on growth stages GS55 and GS75 as key linear predictors, especially in the context of spring wheat GY. However, the effect of these indices depends on the specific growing conditions in the respective locations, thus limiting their universal utility.

Sanctuaries devoted to Asclepius were established and operated for almost a thousand years in various Greek and Roman cities throughout the Mediterranean region. The Asclepieion sanctuary in Lenta (formerly known as Ancient Lebena) in Crete was famous for receiving water from a sacred spring. In the Ancient Lebena, Levinaion was a famous centre for hydrotherapy, physiotherapy and a psychiatric hospital. In the present paper, we aim to assess the hydrochemical status of this sacred spring that holds a prominent position in archaeological and historical studies. The main objectives of this study are: Initially, to present supervisory evidence (archaeological, geological, hydrochemical) of an area that was a water resource management model for many centuries, carrying out therapeutic work. The second objective is to present and compare hydrochemical data in the last century, i.e. from 1915 to 2021. The third objective is to highlight and warn of an incipient saltwater intrusion in the area along the Lentas coast. The fourth objective is to propose an alternative and sustainable form of water resources management in the region that requires the study and rational utilization of the sporadic small water springs in the region. Our study focuses on a basic hydrochemical analysis of spring and borehole water in the remains of Levinaion in the Lentas region and their comparison with spare historical data of the sacred spring water, aiming to interpret the impact of the changes in the spring water resources that occurred in the last decades due to urban modernization. Our results highlight (i) visible fluctuations in chemical composition of borehole water samples, (ii) a neutral to alkaline pH in borehole waters, and an alkaline pH in spring waters, (iii) un-detectable arsenic of Lentas borehole water, unlike historical data of Lentas spring water, (iv) low values of dissolved radon of Lentas borehole water and spring water of Kefalovrysa, and (v) a timeless constant and hypothermic nature of the water of both sacred spring and borehole of Lenta, but also of Kefalovrysa spring. The recorded historical data, i.e. from 1915 to 1957, due to the absence of substantial anthropogenic activity in the area, can be used as reference values (natural background levels, NBLs) for the Lentas area. Our findings emerge with the need to bring again the flowing spring water of the sacred spring of Lentas in its original form through sustainable management and re-discover its beneficial therapeutical effects.

In this study, we investigate the existence of positive solutions within a system of Riemann-Liouville fractional differential equations that incorporate the (r1,r2,r3)-Laplacian operator while being subject to three-point boundary conditions. These equations incorporate various fractional derivatives and are influenced by parameters represented as (ψ1,ψ2,ψ3). Our approach involves employing techniques such as cone expansion and compression of the functional type, in conjunction with the Leggett-Williams fixed point theorem, to establish the existence of positive solutions. To emphasize the practical significance of our findings in the realm of fractional differential equations, we provide two illustrative examples.

The vehicles number continuously growing lead to increasingly intense and congested traffic and it will additionally demand the braking system, and drivers behave more aggressively and as result is required that the braking system to be durable and efficient. For this is necessary the study the braking system behavior in conditions of intense and moderate traffic to increase the safety of traffic participants, respectively to demonstrate the need for more frequent replacement of some braking system elements. Thus, on a vehicle were performed a series of successive tests, through which the degree of wear of the brake pads and discs was monitored periodically and as a result the efficiency evolution of the braking system. The tests were carried out both in laboratory (on dynamometer) and in traffic to establish the efficiency of the braking system according to some parameters considered essential. The experimental tests showed that the recommendations regarding the frequency of replacement of brake pads and disks are inconsistent with their actual wear. Therefore, the aim of this paper is the establishment of the braking system efficiency of an auto-vehicle, subject to testing depending on the auto-vehicle mass, travel speed, distance driven, and braking time, based on experimental on stand and in-traffic tests, according the road safety regulations.

In a saline semi-isolated Lagoon on the Cape Zeleny (White Sea), the annual dynamics of the vertical hydrological structure, and the seasonal dynamics of phytoplankton were traced, including species composition, and vertical distribution, abundance, nutrition type,and biomass.293 species and supraspecific taxa of algae and cyanobacteria were found. Most of the identified species are marine, and 38 species are freshwater. Taxonomic composition changed in the Lagoon during the year. Dinoflagellates dominated in winter and early June; unidentified cocci and flagellates in July; diatoms, dinoflagellates and unidentified cells in August; dinoflagellates in September; and unidentified cocci and flagellates in October–November. The abundance of algae also changed in the Lagoon during the year. The integrated biomass in the water column varied from 0.01 g C/m2 in January to 0.78 g C/m2 in early September. According to the abiotic parameters, the water column of the Lagoon is subdivided into several zones with different conditions and corresponding phytoplankton communities. Similarity between the communities of different horizons was 32-46% in summer and 7% in winter. The chemocline layer was the most populous. Almost the entire year it contained a maximum of phytoplankton biomass, 1-2 orders of magnitude higher than that in the overlying horizons. Comparison phytoplankton in the lagoon and in the nearby sea area was carried out. Despite the connection between the Lagoon and the sea phytoplankton structure in the surface water layer in the Lagoon and in the sea differs significantly in composition, quantitative parameters, and seasonal dynamics. The similarity of the communities in the sea and the Lagoon never exceeded 50%. In terms of biomass, the Lagoon lags behind the sea until mid-summer, but, starting from August, it outnumbers it, and the phytoplankton development in the Lagoon lasts longer, until late autumn. The phytoplankton structure and dynamics in the Lagoon and the sea by 24.5% was related to the daylight, water salinity, oxygen content and pH, but did not depend on water T, underwater illuminance, and depth. Oxygen content and pH are defined by PhP activity. Salinity serves as a vector of the vertical sequence of ecological niches. The daylight length seems to be the crucial factor of the seasonal PhP dynamics in the semi-isolated coastal stratified lakes and lagoons.

The aim of the study was to assess the adaptability of Polish Red cows to extensive housing and feeding conditions. The study was carried out using 22 cows together with their offspring, kept on a certified organic family farm, from 15 October 2017 – the start of the winter feeding season – to 30 October 2018 – the end of the pasture season. The animals were kept as beef suckler cows, which stayed in the pasture during the summer and were kept in buildings with permanent access to a large cattle run in winter. The following were determined in the study: changes in the cows’ weight and body condition, daily gains in calves, 210-day standardized body weight, and estimated milk yield of suckler cows. To evaluate the cows’ health, blood was collected from them twice and analysed for haematological and biochemical parameters. The results indicated that during the study period the Polish Red cows had adequate body condition, normal vital parameters, and a normal course and development of pregnancy despite the sparse winter diet. This definitively confirms the breed’s high capacity to adapt to an extensive system.

Transforaminal lumbar interbody fusion (TLIF) is a commonly used technique for treating lumbar degenerative diseases. Here, we developed a fully computer-supported pipeline to predict the cage height and the degree of lumbar lordosis subtraction from the pelvic incidence (PI-LL) after TLIF surgery through preoperative X-ray images. The automated pipeline included two primary stages. First, a deep learning model was used to extract essential features from X-ray images. Second, five machine learning algorithms were trained to identify the optimal models to predict the interbody cage height and postoperative PI-LL. Lasso regression and support vector regression exhibited superior performance for predicting the interbody cage height and postoperative PI-LL, respectively. For cage height prediction, the root mean square error (RMSE) was calculated as 1.01, and the model achieved the highest accuracy at a height of 12 mm, with exact prediction achieved in 54.43% (43/79) of cases. In most of the remaining cases, the prediction error of the model was within 1 mm. In addition, the model demonstrated adequate performance for predicting PI-LL, with an RMSE of 5.19 and an accuracy of 0.81 for PI-LL stratification. In conclusion, the interbody cage height and postoperative PI-LL can be reliably predicted using artificial intelligence and ML models.

Laser marking on polymer composite surfaces can be difficult to contrast and cause readability problems for electronic decoding equipment on production lines due to poor interaction between the laser and the fibres used to reinforce these materials. This problem can be solved with the right choice of marking parameters, resulting in savings for companies by avoiding production problems such as rejection, scrap and customer complaints. The present work uses the PBT/glass fibre composite used in the manufacture of instrument panels for motorcycles. The tests were carried out with different laser marking parameters using a Nd: YAG laser. Subsequently, the laser-marked DMC codes were analysed using a Verifier to evaluate the quality according to the ISO/IEC 29158:2020 standard. A detailed analysis of these surfaces was also carried out to observe some physical and chemical changes using SEM microscopy and EDS spectroscopy. The optical analysis showed that the lower the radiation power and pulse frequency and the higher the marking speed, the weaker the laser marking and therefore the poorer the DMC code quality, which was confirmed by the SEM. EDS spectroscopy showed that the laser marking process did not affect the chemical changes on the sample surface.

Aim: This study aimed to investigate whether baseline 18F-FDG PET-derived semiquantitative parameters could predict disease-free survival in patients with grade III breast cancer of different molecular subtypes undergoing neoadjuvant chemotherapy (NAC). Materials and Methods: Patients were retrospectively retrieved from the databases of two Italian hospitals (University of Padua and University Hospital of Ferrara). Inclusion criteria were: 1) histologically proven diagnosis of grade III breast cancer; 2) history of NAC; 3) execution of a baseline 18F-FDG PET/CT scan before the start of NAC; 4) adequate follow-up time to compute the 3Y-DFS. For each 18F-FDG-PET/CT scan, the following parameters were calculated in the primary tumor (SUVmax, SUVmean, MTV, TLG) and whole-body (WB_SUVmax, WB_MTV, and WB_TLG). Receiver operating characteristic (ROC) analysis was used for each parameter to assess the prediction capability for 3Y-DFS. DFS differences between groups were assessed using Kaplan-Meier curves and compared by log-rank test. Results: Ninety-five grade III breast cancer patients with different molecular types were retrieved (luminal A: 5; luminal B: 34; luminal B-HER2: 22; HER2-enriched: 7; triple-negative: 27). In the whole group of patients, WB_SUVmax was the best predictor of recurrence (AUC: 0.66; best cut-off: WB_SUVmax>9.43; SS: 96%; SP: 38.1%; p<0.008). Patients with luminal A and Her-2-enriched breast cancer types were excluded from the molecular subgroup analysis due to the small study samples (5 and 7, respectively). In luminal B patients (n=34), WB_MTV (AUC: 0.75; best cut-off: WB_MTV>195.33; SS: 55.56%, SP: 100%; p=0.002) and WB_TLG (AUC: 0.73; best cut-off: WB_TLG>1066.21; SS: 55.56%, SP: 100%; p=0.05) were the best predictors of 3Y-DFS. Patients had a higher probability of DFS in case of a WB_MTV≤195.33 (3429±210 vs. 446±144 days; p<0.001) or WB_TLG≤ 1066.33 (937.35±19 vs. 496±131 days; p<0.001). In luminal B-HER2 patients (n=22), WB_SUVmax was the only predictor of 3Y-DFS (AUC: 0.857; best cut-off: WB_SUVmax>13.12; SS: 100%; SP: 71.43%; p<0.001); patients with WB_SUVmax≤13.12 had a significantly longer DFS (3857 days) than patients with a WB_SUVmax >13.12 (1693±430 days; p<0.004). No parameter resulted significant in the prediction of 3Y-DFS in patients with grade III triple-negative cancer. Conclusion: Volume-based parameters, extracted from baseline 18F-FDG PET, seem to be promising tools in the prediction of recurrence within 3 years in patients with grade III luminal B and luminal B- HER2 breast cancer undergoing NAC. Larger study samples are needed to confirm these preliminary findings.

Per- and polyfluoroalkyl substances (PFASs) are a group of fluorinated, organic, man-made chemicals; they do not occur naturally in the environment. This study aimed to determine the profile and content of PFASs in volunteers’ blood plasma and urine after fermented red beetroot juice consumption and correlated it with the blood parameters. During 42 days, 24 healthy volunteers intake 200 mL/60 kg of body weight fermented red beetroot juice. PFASs were analyzed using micro-HPLC-MS/MS method. Five perfluoroalkyl substances were found in human body fluids. After juice consumption, PFASs, due to the consumption of food contaminated with them, was discovered that for perfluorocarboxylic acids, a downward trend was observed, while for perfluoroalkane sulfonates, their plasma content showed a statistically significant upward trend. Analysis of the hematology parameters indicated that the intake the fermented red beetroot juice showed a significant decrease in mean corpuscular volume (MCV), platelets concentration, mean platelet volume (MPV), platelet large cell ratio (P-LCR) at the significance level p < 0.01, and he-matocrit (p < 0.05). On the other hand, the dietary intervention also indicated a significant (p < 0.01) increase corpuscular/ cellular hemoglobin concentration (MCHC). In the case of blood biochemi-stry, no significant change in blood samples after intake the fermented beetroot juice was observed. However, a decreasing tendency of total cholesterol and low-density lipoprotein concentration (LDL-C) were observed. Based on the presented results, there is a need to analyze and monitor health-promoting food regarding undesirable substances and their impact on consumer health.

Keywords: Deep mining; Drill bit structural parameters; Fidelity coring; Abaqus simulation and analysis.

The process of Thermal spray is effective for creating a metal matrix composite (MMC) by embedding zirconium diboride reinforcement into a molybdenum matrix. This allows for the combination of beneficial properties in a new composite, as both materials have a high The materials Mo and ZrB2 possess different characteristics. For example, Mo has a melting point of 2622 ◦C while ZrB2 has a higher melting point of 3246 ◦C. Additionally, Mo has a high thermal conductivity of 139 W/m◦C compared to ZrB2's thermal conductivity of 24 W/m◦C. However, both materials have good thermal shock resistance, and Mo has a low coefficient of thermal expansion of 5.35 µm/m◦C while ZrB2 has a coefficient of thermal expansion of 5.8 × 10−6 K−1., as well as the ability to maintain strength at elevated temperatures and stability in extreme environments. The study focused on creating Mo/Zrb2 composites using a thermal spray coating technique, varying the parameters of spraying distance, number of passes, and gas pressure, and testing the resulting castings to evaluate their hardness and Young's Modulus. The primary objective of the research was to use the Taguchi technique for identifying the optimal parameters for generating the highest Young's Modulus and hardness for the castings. The Taguchi method integrates experimental and analytical principles to identify the most significant parameter affecting the response, which can significantly enhance overall performance. The study found that the optimal parameters were a spraying distance of 20 cm, gas pressure of 6 bar, and the number of passes of 18. The Taguchi method accurately predicted the parameters that produced the highest properties for the composite coatings, which demonstrated good surface formation without hot cracks and fewer pores, with well-formed metallurgical bonding between the coating and the substrate.

This paper addresses the problem of non-cooperative spectrum sensing in very low signal noise ratio (SNR) conditions. In our approach, detecting an unoccupied bandwidth consists to detect the presence or absence of a communication signal on this bandwidth. Major well known communication signals may contain hidden periodicities, we use the Recurrence Quantification Analysis (RQA) to reveal the hidden periodicities. RQA is very sensitive to a reliable estimation of the phase space dimension m or the time delay τ. In view of the limitations of algorithms proposed in the literature, we have proposed a new algorithm to estimate simultaneously the optimal values of m and τ. The new proposed optimal values allow the states reconstruction of the observed signal and then the estimation of the distance matrix. This distance matrix has particular properties which we have exploited to propose the Recurrence Analysis based Detector (RAD). RAD can detect a communication signal in a very low SNR condition. Using Receiver Operating Characteristic curves, our experimental results corroborate the robustness of our proposed algorithm comparing to classical widely used algorithms.

Film cooling technology is of great significance to enhance the performance of aero-engines and extend service life. With the increasing requirements for film cooling efficiency, researchers and engineers have carried out a lot of work on the precision and digital measurement of cooling holes. Based on the above, this paper outlines the importance and principles of film cooling technology, reviews the evolution of cooling holes. Also, this paper details the traditional measurement methods of the cooling hole used in current engineering scenarios with their limitations and categorizes digital measurement methods into five main types, including probing measurement technology, optical measurement technology, infrared imaging technology, computer tomography(CT) scanning technology, and composite measurement technology. The five types of methods and integrated automated measurement platforms are also analyzed. Finally, through a generalize and analysis of cooling hole measurement methods, this paper points out technical challenges and future trends, providing a reference and guidance for forward researches.

Diets that restrict the amount of carbohydrates positively affect markers related to metabolic syndrome (MS). However, completely carbohydrate-free diets have been studied in lesser extent, being their effect on biochemical and morphometric parameters in a rat model of MS the main objective of this study. MS was induced by a high-glucose diet for 20 weeks in male Wistar rats with a subsequent exposition to an essentially carbohydrate-free diet (CFD) for 20 weeks. Daily measurements of food consumption and monthly measurements of body weight were made. At week 40, glucose, insulin, lipid profile, ketone bodies, C-reactive protein (CRP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), urea, creatinine, liver and muscle glycogen, and serum, hepatic, renal and pancreatic malondialdehyde (MDA) were assessed. Exposition to CFD showed decrease in caloric intake and body weight. Likewise, the group showed normalization in liver and serum MDA parameters, insulin, lipid profile, ALT, liver glycogen, and creatinine. The CFD decreased glucose concentration and the inflammatory state, also, increased the concentration of ketone bodies and urea. The change towards CFD reverses the metabolic alterations generated with MS except for glycemia and uremia, probably due to the high rate of gluconeogenesis generated by the high protein content in the diet.

Dirac's Large Number Hypothesis (LNH), proposed in 1937, has captivated the scientific community with its exploration of profound correlations between cosmic and atomic scales. This hypothesis delves into the intricate interplay between the infinitesimally small and the vastly large, offering potential insights into the fundamental nature of the universe. As we continue to uncover the mysteries of the cosmos, the LNH oscillates on the precipice of scientific acceptance—neither fully validated nor entirely dismissed. In this review paper, we embark on a comprehensive journey through Dirac's LNH, shedding light on its theoretical underpinnings, its implications for universe models, and its resonance with the Anthropic Principle. We delve into the possibilities of variable gravitational constants and continuous mass creation, inviting further exploration into the intricacies of our cosmic symphony. By embracing the ongoing quest for understanding, we endeavor to unravel the profound harmonies that connect the infinitesimal with the infinite, contributing to the symphony of knowledge in theoretical physics and cosmology.

The welding and construction processes of H-type thick-plate-bridge steel involve complex multi-pass welding processes, which is difficulty to ensure its welding performance. Accordingly, it is crucial to explore the inherent correlation among the welding processes parameters and welding quality, and applied it into the welding robots, eliminating the instability from manual welding. In order to improve the welding quality, the GMAW (Gas Metal Arc Welding) welding process parameters are simulated using the Q345qD bridge steel flat joint model. Four welds with X-shaped grooves are designed to optimize the parameters of welding current, welding voltage, and welding speed. The optimal welding process parameters are investigated through thermal-elastic-plastic simulation analysis and experimental verification. The results indicate that when the welding current is set to 230A, the welding voltage to 32V, and the welding speed to 0.003m/s, the maximum deformation of the welded plate is 0.52mm, with a maximum welding residual stress of 345MPa. Both the simulation results of multi-pass welding and experimental tests meet the welding requirements, as they show no excessive stress or strain. These parameters can be applied into building large steel frame bridges with welding robots, improving the quality of welded joints.

Because of the large number of parameters that interact in their function, determining dynamic regime parameters as well as the mode of function of amplifying stages is an extremely complex problem. This paper describes a LabVIEW application for studying the functioning of an ampli-fier in various connections. The user selects the generator's parameters, the type of connection and its parameters, as well as the electric charge characteristics. The application can determine both the stage characteristics and the Bode characteristics. The amplifier's stability zone, as well as its gain and phase, are determined based on these characteristics. An important advantage of this application is that the design of the amplifier stage can be made starting from some param-eters that the amplifier can establish, from which the values of components can be determined. In order to validate the simulation results using the LabVIEW application, a specialized program Multisim was used, as well as experimental measurements using the Electronics Explorer Board. Both Multisim and Electronics Explorer Board can determine Bode characteristics. In both simu-lations and experimental amplifiers, the same schemes with the same transistor was used. The application can be used for educational purposes as well as to design the amplifier's stage to achieve specific parameters.

: The article examines the regularities of structure formation of ultrafine fibers based on poly-3-hydroxybutyrat under the influence of technological (electrical conductivity, viscosity), molecular (molecular weight), and external factors (low-molecular and nanodispersed substances of different chemical nature). Systems with polar substances are characterized by the presence of intermolecular interactions and the formation of a more perfect crystalline fiber structure. Changes in technological and molecular characteristics affect the fiber formation process, resulting in alterations in the morphology of the non-woven fabric, fiber geometry, and supramolecular fiber structure. Polymer molecular weight, electrical conductivity, and solution viscosity influence fiber formation and fiber diameter. The fiber structure is heterogeneous, consisting of both crystalline and non-equilibrium amorphous phases. This is significant in the development of matrix-fibrillar systems for drug delivery, bioactive substances, antiseptics, tissue engineering constructs, tissue engineering scaffolds, artificial biodegradable implants, sorbents, and other applications.

Limited scientific evidence shows that alpha lipoic acid (ALA) can induce regression rates of low-grade squamous intraepithelial lesions (LSIL) but the mechanisms of these effects have not been elucidated. To gain a broader insight into its therapeutic potential and mechanisms of action, the effects of 3-month supplementation with 600 mg of ALA on antioxidant- and lipid status param-eters in 100 patients with LSIL were investigated in randomized placebo-controlled study. Obtained results were discussed in terms of patients’ initial metabolic status and diet quality (particularly nutritional intake of antioxidants). Obtained results showed that oxidative status biomarkers were not significantly affected by ALA supplementation. However, serum superoxide dismutase (SOD) activity was positively affected in the subgroup of patients with higher dietary antioxidant intake. Surprisingly, ALA supplementation resulted with small but statistically significant increase of serum low density lipoprotein (LDL) and observed effect was significantly affected by the initial lipid status of participants. Larger studies are necessary to gain additional insights on the clinical significance of ALA as an antioxidant and hypolipemic agent and to optimize its potential application in LSIL treatment.

A reduced order model is developed to monitor aeroengines condition (defining their degradation from a baseline state) in real-time, by using data collected in specific sensors. This reduced model is constructed by applying higher order singular value decomposition plus interpolation to appropriate data, organized in tensor form. Such data are obtained using a detailed engine model that takes the engine physics into account. Thus, the method synergically combines the advantages of data-driven (fast online operation) and model-based (the engine physics is accounted for) condition monitoring methods. Using this reduced order model as surrogate of the engine model, two gradient-like condition monitoring tools are constructed. The first tool is extremely fast and able to precisely compute `on the fly’ the turbine inlet temperature, which is a paramount parameter for the engine performance, operation, and maintenance, and can only be roughly estimated by the engine instrumentation in civil aviation. The second tool is not so fast (but still reasonably inexpensive) and precisely computes both, the engine degradation and the turbine inlet temperature at which sensors data have been acquired. These tools are robust in connection with random noise added to the sensors data and can be straight forwardly applied to other mechanical systems.

Honey is a sweet substance extensively consumed in the world for its nutritional and healthy properties. However, residues of pesticides and environmental contaminants can compromise its quality. For this reason, the physicochemical parameters, and the organic contamination of monofloral and multifloral honeys from three regions of Algeria (Tiaret, Laghouat and Tindouf) were monitored to evaluate the quality of honey and the safety for consumers. In general, the results obtained from the physicochemical analyses were in line with the EU standards. In terms of contamination, pesticides authorised and used in Algerian agriculture (matalaxyl-M and cyromazine), as well as banned pesticide (carbaryl), were found in almost all the samples. However, only the concentration of cyromazine was higher than the relative EU maximum residue levels. PCB 180, PCB 189, anthracene, fluorene and phenanthrene were mainly detected. All the honeys show traces of DiBP, DBP, DEHP and DEHT, but no traces of bisphenols were found. Moreover, the dietary exposure assessment shows that a small amount of Algerian honey can be safely consumed. Overall, data from this study should motivate the Algerian government to enhance their monitoring activities in beekeeping and to find solutions for implementing more sustainable agricultural practices harmonizing with the international legislation.

The effect of varying concentrations of crude oil pollution on the germination and growth parameters of Mucuna pruriens (Var. cochinchinenesis) was investigated. The following treatments were used; 0ml, 100ml, 200ml, 400ml, 800ml 1600ml respectively. The germination of velvet bean was 100% but growth was found to be inhibited by a wide range of treatments (800ml and 1600ml). the lag phase of proceeding growth is also reduced at this treatment. Growth inhibition is attributed primarily to the characteristics of oil, which acts as a physical barrier to water and oxygen uptake. Reduction in the growth and development of plants was observed in the polluted treatments as against the control (non–polluted treatment) because of the deleterious effect of the petroleum products on the morphological parameters (plant height, number of leaves and leaf area) tested for. Velvet beans treated with lower treatment (100ml and 200ml) were observed to be more productive when compared to the control experiment. Consequently, as the crude oil exceeds the plant absorbing capacity at 800ml and 1600ml respectively, the growth retards, chlorosis, presence of tough apical meristem, and defoliation from the base of the plant.

This article introduces simulations of theoretical material with controlled properties for the evaluation of the effect of key parameters, as volumetric fractions, elastic properties of each phase and transition zone on the effective dynamic elastic modulus (Ed). The accuracy level of classical homogenization models was checked regarding the prediction of Ed. Numerical simulations were performed with finite element method (FEM) for evaluations of the natural frequencies and their correlation with Ed, through frequency equations. An acoustic test validated the numerical results and obtained the elastic modulus of concretes and mortars at 0.3, 0.5 and 0.7 water-cement ratios (w/c). Hirsch calibrated according to the numerical simulation (x = 0.27) exhibited a realistic behavior for concretes of w/c = 0.3 and 0.5, with 5% error. Nevertheless, for w/c = 0.7, Ed approached Reuss model, similarly to theoretical triphasic materials. Hashin-Shtrikman bounds is not perfectly applied to theoretical biphasic materials under dynamic situations.

Maize, a crop of international relevance, frequently undergoes xylem embolism due to water shortage, negatively impacting growth, yield, and quality. Consequently, a refined comprehension of xylem embolism is vital for enhancing maize cultivation. Notwithstanding extensive research and the generation of analytical models for embolism mechanisms, prevalent models often disregard crop-specific hydraulic processes and the formation of embolisms via air bubbles in the xylem conduit. In this research, we present an inventive model applying pipe cavitation parameters to discern water potential and bubble formation in maize leaf xylem. The model integrates pivotal physiological traits of maize—leaf count, leaf vein count, and average leaf radius—demonstrating robust correlations. Furthermore, we constructed a percentage conductivity loss (PLC) curve based on pre-dawn leaf water potential and compared it with our model, offering interval data to observe embolisation events triggered by air bubbles. Utilizing experimental data, our novel cavitation-parameters based model effectively corresponds with observed bubble phenomena and appropriately characterizes water transport in plant xylem conduits. This method enabled us to observe the transition from bubble occurrence to cavitation embolism microscopically, which aligned with the embolism intervals provided by the model. This procedure reveals potential trends in bubble-induced embolism and deepens our knowledge of microscopic plant hydraulics and crop embolism. This work establishes a basis for understanding the generation of bubble embolisms in maize, assists in evaluating maize plant water status for efficient water supply management throughout the growth cycle, and contributes towards potential water management strategies for maize.

Background: Hashimoto’s thyroiditis (HT) is an autoimmune disease that progressively leads to thyroid gland destruction and hypothyroidism. Patients produce antibodies against two thyroid-specific antigens: thyroglobulin and thyroid peroxidase. As a result of the abnormal amount of thyroid hormone produced and its autoimmune etiology, patients with HT display a higher frequency of either autoimmune or non-autoimmune dermatological disorders. On ultrasound examination, HT can be detected by observing an enlarged thyroid gland with hypoechoic parenchymal regions or by observing a small gland indicating atrophy and diffusely heterogeneous parenchyma. Changes in the parenchymal vascularity can be observed as decreased or increased levels of vascularization. Objective: This study aimed to analyze the role of clinical data and ultrasound evaluation of patients with HT in suggesting an association with dermatological disorders. Patients and methods: Complete dermatological and endocrinological assessments as well as ultrasonography of the thyroid and lymphnodes were performed in HT patients. Results: The data obtained showed that a family history of thyroid disease, increased diameter of the inferior thyroid artery, and the presence of cervical lymphadenopathy were more frequent in the group of patients with dermatological diseases. Taken together, our results suggest the usefulness of ultrasound in determining a possible association between HT and dermatological disorders.

Pool boiling is extensively utilized in various fields, such as electronics cooling, battery cooling, nuclear power plants, and chemical processing. In the process of temperature control through boiling, the generation and transportation of bubbles play a crucial role in calculating the heat transfer capacity of the system. Therefore, it holds immense significance to gain a profound understanding of the mechanisms underlying bubble formation, growth, and detachment. Currently, numerous mechanistic explanations and empirical correlations have been proposed to elucidate various parameters of bubbles during the boiling process. These findings were considered valuable references in selecting appropriate boiling media and designing efficient heating surfaces. To comprehensively present the progress of bubble formation and heat transfer during the boiling process, the forces exerted on the bubbles was highlighted in this article. And a meticulous review on bubble force analysis and correlation formulas pertaining to various relevant parameters (e.g. nucleation sites density, bubble growth rate, detachment diameter, detachment frequency) were conducted. This review article also were expected to provide a novel foundation for further exploration of enhanced boiling heat transfer.

The use of recombinant bovine somatotropin (rbST) leads to an increase, in variable amounts, of milk production in buffalo, but there is a lack of information on the influence of rbST on their metabolism. This study looked at the effects of a single 500 mg dose of rbST on lipid profile, liver and kidney function and physical, chemical and cellular constitution of milk in 14 buffalo over 14 days, from the 100th day of lactation, and compared them with 14 animals in a control group. From the 1st day after rbST, there was a rise in beta hydroxybutyrate (β-HBO), possibly due to the higher dry matter intake or by biotransformation of NEFA into β-HBO. Treatment did not influence blood glucose, non-esterified fatty acids (NEFA), triglycerides, cholesterol, total protein, albumin, AST, GGT, bilirubin, urea or creatinine. In 71.3% of the buffalo there was a gradual increase in milk production with maximal response in the first week that was then followed by a gradual decrease, whilst in 21.4%, the increase in production occurred between 7 and 10 days, and only 7.1% of animals did not respond. On the 3rd, 5th, 7th and 10th days after treatment, an increase was found in milk production between the two groups equal to 1.04, 1.52, 1.42 and 1.06 liters, respectively. In relative terms this means an increase in milk production, respectively, of 15.1%; 21.0%; 19.8 % and 15.1 %. The constitution of the milk showed no difference in the amounts of fat, lactose, total solids or somatic cell count; however, on the 3rd day after rbST, there was a decrease in protein; notably, from the 5th day, protein values show no statistical difference. It can be concluded that the application of rbST in buffalo from the 100th day of lactation is metabolically safe, since the treatment neither caused imbalances in fat metabolism nor overloaded the liver or renal function, and the changes in milk composition were transient and limited to a decrease in milk protein.

The Mexican Soil Mesh (MSMx) web service emerges as a pivotal tool for researchers, farmers, and policymakers in the efficient management of extensive soil databases. Built on a responsive and intelligent web design, MSMx synchronizes seamlessly with the SQL language, allowing users to selectively download variables tailored to their studies at the desired spatial scale. The programmatic structure enhances query speed, optimizes development times, and incorporates satellite programming modules for effective handling of the vast soil dataset. This paper high-lights the key features, benefits, and applications of MSMx, emphasizing its role in facilitating data-driven decision-making processes and promoting sustainable soil management practices on the continental shelf of Mexico.

The temperature effect plays an important role for an accurate determination of the polar free energy, polar thermodynamic parameters, and enthalpic and entropic Lewis’s acid base properties of oxides, polymers and composites polymers/oxides. The adsorption of polymers on other solid surfaces is crucial in many industrial applications, coatings, paints, catalysis, colloids and adhesion processes. (1) Background: Inverse gas chromatography at infinite was used for the physico-chemical characterization of solid substrates by determining the thermodynamic parameters of adsorption of model organic solvents on solid surfaces such as polymers, metallic oxides, carbon fibers, pharmaceutical or 3D/4D printing substrates. (2) Methods: A new method based on the London dispersion equation was applied with a new parameter associating the deformation po-larizability and the harmonic mean of the ionization energies of solvent. More accurate values of the dispersive and polar interaction energies of the various organic solvents adsorbed on PMMA in bulk phase and PMMA/silica at different recovery fractions were obtained as well as the Lewis acid-base parameters and the transition temperatures of the different composites. (3) Results: This new methodology gave very interesting results on the behavior of PMMA adsorbed on silica. An important effect of the temperature and the recovery fraction on the various physicochemical and thermodynamic properties was highlighted. The variations of all interaction parameters showed the presence of three transition temperatures for the different PMMA adsorbed on silica with the various coverage rates with a shift of these temperatures for a recovery fraction of 31% (4) Con-clusions: An important variation of the polar enthalpy and entropy of adsorption, the Lewis ac-id-base parameters and the intermolecular separation distance as a function of the temperature and the recovery fraction of PMMA on silica.

Tight gas, a category of Deep Green Energy Resources, rely on advanced intelligent monitoring methods for their extraction. Conventional logging for reservoir evaluation relies on logging data and the manual setting of evaluation criteria to classify reservoirs. However, the complexity and heterogeneity of tight reservoirs pose challenges in accurately identifying target layers by using traditional well-logging techniques. Machine learning may hold the key to solving this problem, as it enables computers to learn without being explicitly programmed and manually added rules. Therefore, it is possible to make reservoir evaluation via using machine learning methods. In this paper, the reservoir quality index (RQI) and porous geometric parameters obtained from the optimized inversion of the spherical-tubular model are adopted to evaluate the reservoir. Then, three different machine learning approaches, the random forest (RF) algorithm, support vector machine (SVM) algorithm, and extreme gradient boosting (XGB) algorithm, are utilized for reservoir classification. The selected dataset covers more than 7,000 samples from five wells. The data from four wells are arranged as the training dataset, and the data of the remaining one well is designed as the testing dataset to calculate the prediction accuracies of different machine learning algorithms. Among them, accuracies of RF, SVM, and XGB are all higher than 90%, and XGB owns the highest result by reaching 97%. Machine learning based approaches can greatly assist reservoir prediction by implementing the well-logging data. The research highlights the application of reservoir classification with a higher prediction accuracy by combining machine learning algorithms with NMR logging based pore structure characterization, which can provide a guideline for sweet spot identification within the tight formation. This not only optimizes resource extraction but also aligns with the global shift towards clean and renewable energy sources, promoting sustainability and reducing the carbon footprint associated with conventional energy production. In summary, the fusion of machine learning and NMR logging based reservoir evaluation plays a crucial role in advancing both energy efficiency and the transition to cleaner energy sources.

The quality of sedation and changes in cardiorespiratory variables after the intramuscular administration of alfaxalone and butorphanol in Galgo Español dogs were evaluated. Twenty-one adult dogs were included. The dogs received alfaxalone (2 mg/kg) and butorphanol (0,2 mg/kg) intramuscularly. Sedation scoring, cardiorespiratory parameters (including blood gas analysis), echocardiography, thoracic radiography and electrocardiography were performed before sedation and 30 minutes after drug administration. Moderate sedation was observed, and side effects, such as tremors, nystagmus and auditory hyperesthesia, were noticed. Statistically significant changes in heart rate, invasive blood pressure, pH, arterial saturation of O2 and partial pressure of O2 and CO2 were found. Echocardiographic variables, including end-diastolic volume, left ventricular diameter in diastole, aortic and pulmonic flow, diastolic transmitral flow and left atrial/aortic ratio, and electrocardiography parameters, including PQ interval and QT interval, showed statistically significant changes. In conclusion, the intramuscular administration of alfaxalone and butorphanol to healthy dogs produced moderate sedation with mild cardiorespiratory, echocardiographic and electrocardiographic changes, without alterations in cardiac size on X-ray images.

The saturation properties of symmetric and asymmetric nuclear matter have been computed using the finite range simple effective interaction having Yukawa form-factor. The results of higher order derivatives of the energy per particle and the symmetry energy computed at saturation, namely, Q0, Ksym, Kτ, Qsym, are compared with the corresponding range of values extracted from studies involving theory, experiment and astrophysical observations. The ability of the equations of state computed with this simple effective interaction in predicting the threshold mass for prompt collapse in binary neutron star merger and gravitational redshift have been examined in terms of the compactness of the neutron star and the incompressibility at the central density of the maximum mass star. The correlations existing between neutron star properties with the nuclear matter saturation properties have been analyzed and compared with the predictions of other model calculations.

Humming is probably more effective than speech improving mothers' cardiorespiratory function and infants' self-regulation. We intend to understand the effects of: 1) maternal humming vs. speech on preterm infants’ physiological parameters; 2) maternal humming vs. speech on mothers’ physiological parameters; 3) humming melodic contours and of the lengthening of the final note on preterm infants’ physiological parameters. This study was designed as a single group repeated measure, using microanalytical methodology (ELAN software), with a protocol (silent baseline / speech or humming / silence / humming or speech / silence) applied to preterm dyads (N = 36). Audio and video observations were recorded. Infants’ and mothers’ heart rate (HR) and O2 saturation were observed once a minute. Proportion of O2 saturation relative to HR (Prop. O2 saturation/HR) was estimated for both partners during protocol. We found an infants’ HR mean significantly lower during humming (p = .028), a significantly higher Prop. O2 saturation/HR during humming for infants (p = .027) and for mothers (p = .029). The duration of sinusoidal contours together with the lengthening of the final note predict infants’ Prop. O2 saturation/HR. Musical features of humming seem to improve the physiological stability of preterm infants during kangaroo care.