The safety of vegetable food is compromised by various factors, including the inefficient or excessive use of sanitizers. Instances of individuals falling ill after consuming raw vegetables have been reported, with outbreaks of diseases caused by pathogens on fresh vegetables becoming increasingly prevalent globally, attracting significant media coverage and impacting the economic viability of vegetable cultivation. Measures to enhance food safety in postharvest horticultural produce involve controlling microbial proliferation and minimizing cross-contamination. Sanitizers were utilized in the food safety arsenal for a variety of purposes, including pathogen elimination and microbe reduction, hand, tools, and vegetable contact surface cleaning, and produce shelf life extension. Choosing an appropriate sanitizer for all vegetables is difficult due to a lack of knowledge on which sanitizers are ideal for the many types of vegetables grown on farms under different environmental circumstances. Although chlorine-based sanitizers, such as sodium or calcium hypochlorite, have been widely used for the past 50 years, recent research has revealed that chlorine reacts with an organic compound in fresh vegetables to produce trihalomethane, a carcinogen precursor, and as a result, many countries have prohibited the use of chlorine in all foods. As a result, horticulture research groups worldwide are exploring for non-chlorine, ecologically friendly sanitizers for the vegetable industry. They also want to understand more about present procedures in the vegetable business for employing alternative sanitizers, as well as the efficacy and potential dangers to the food safety of fresh salad vegetables. This review-cum-research paper presented detailed information on non-chlorine sanitizers, such as their efficacy, benefits, drawbacks, regulatory requirements, and the need for additional research to lower the risk of marketed salad vegetable food safety.

Unmanned aerial vehicle (UAV), or drone is recognized for its potential to improve efficiency and address last-mile delivery issues. As a result, there has been a lot of activity in recent years in the field of drone scheduling and routing. Unlike the vehicle routing problem, drone route design is difficult due to several operational characteristics, such as speed optimization, multitrip operation, and energy consumption estimation. On the one hand, drone energy consumption is a complex nonlinear function of both speed and payload in practice. On the other hand, the high operating speed of drones can significantly curtail the drone range, thereby limiting the efficiency of drone delivery systems. Most of the existing drone delivery models either assume constant drone speed or do not consider the effect of drone speed and parcel weight on energy consumption, leading to costly or energy-infeasible routes. This paper addresses the trade-off between speed and flight range in a multi-trip drone routing problem with variable flight speeds (DRP-VFS), in which a team of homogeneous drones is employed for delivery services. We propose a new model to particularly consider energy constraints using a nonlinear energy consumption model and treat drone speeds as decision variables so that various drone speeds can be adopted in applications. The DRP-VFS is initially formulated as mixed-integer linear programming (MILP) to minimize total energy consumption. To solve large-scale instances, we propose a three-phase adaptive large neighborhood search (ALNS) algorithm. The experimental results demonstrate that suboptimal solutions can be found effectively in practical scenarios using the proposed method. Furthermore, results indicate that operating drones at variable speeds leads to about 21% of energy savings compared to fixed speeds, boasting advantages in cost-savings and range extensions.

Non-isocyanate polyurethane synthesis by non-Sn catalysis is an essential challenge toward green polyurethane synthesis. Bismuth compounds are attractive candidates due to their low cost, low toxicity, and availability to urethane chemistry. We applied various Bi catalysts to the self-polycondensation of a bishydroxyurethane monomer and found BiCl3 to be an excellent catalyst through optimization. The catalytic activity and price of BiCl3 are comparable to those of Bu2SnO, while its toxicity is significantly low. BiCl3 is, therefore, a promising alternative to Sn-based catalysts in non-isocyanate polyurethane synthesis.

The splitting method developed in a previous study for linear, multi – component, convection-diffusion mass transfer equations is extended to non-linear, multi-component, convection-diffusion mass transfer equations. The diffusion term is non-linear (the diffusion coefficients depend on chemical species concentrations). Theoretical results about the splitting error are presented, as well as numerical simulations for mixtures with n ≤ 5. The numerical experiments show second-order accuracy and stability for the present splitting algorithm.

In natural, laboratory and industrial conditions, the density of a fluid or gas, depending on temperature, pressure, concentration of dissolved substances or suspended particles, changes under the influence of a large number of physical factors. We assume that undisturbed liquid is stratified. The analysis is based on a system of fundamental equations for the transfer of energy, momentum and matter in periodic flows of a viscous compressible fluid. The propagation of periodic flows in viscous uniformly stratified fluids is considered. Taking into account the compatibility condition, dispersion relations are constructed for two-dimensional internal, acoustic and surface linear disturbances with a positive definite frequency and complex wave number in a compressible viscous fluid exponentially stratified by density. The temperature conductivity and diffusion effects are neglected. The obtained regularly perturbed solutions to the equations describe weakly damped waves. Singular solutions characterize the thin ligaments that accompany each type of wave. In limiting cases, the constructed solutions transform into known expressions for a viscous homogeneous and ideal fluid or degenerate.

In this paper, we are interested in a model of exact asymptotically flat charged hairy black holes in the background of dilaton potential. We study the weak gravitational lensing in the spacetime of hairy black hole in Einstein-Maxwell theory with a non-minimally coupled dilaton and its non-trivial potential. In doing so, we use the optical geometry of the flat charged hairy black hole for some range of parameter $\gamma$. For this purpose, by using Gauss-Bonnet theorem, we obtain the deflection angle of photon in a spherically symmetric and asymptotically flat spacetime. Moreover, we also investigate the impact of plasma medium on weak gravitational lensing by asymptotically flat charged hairy black hole with a dilaton potential. Our analytically analyses show the effect of the hair on the deflection angle in weak field limits.

Malnutrition problems are related to diets that lack one or more essential elements, which it is extremely important to food enrichment to improve the content of compounds effective for health. The objective of this study is to evaluate the effect of the addition of Ca2+, K+ and Mg2+ on the induction of nutraceutical quality in grafted tomatoes grown in the NFT (Nutrient Film Technique) system. In the experiment, two factors were evaluated: plants with and without grafting and the foliar application of 10 ml L−1 Ca2+, 4 ml L−1 K+ and 10 ml L−1 Mg2+ cations separately for each case, in addition to the control. The treatments were evaluated using a completely randomized design, with 5 repetitions per treatment. The interactive effects between grafting and foliar application of Ca2+ induced a greater content lycopene, β-carotene and total flavonoids in fruits of tomato. The interactive effects between the graft and the Mg2+ foliar applications obtained the best results in the phenol content. As regards, capacity DPPH and ABTS, the graft decreased concentration, increasing the content of these through foliar applications of calcium. Regarding the enzymatic variables, graft factor increased activity catalase, glutathione peroxidase and phenylalanine ammonium lyase, obtained the best results graft interaction and foliar application of calcium and magnesium. The results obtained demonstrate the influence of the use of grafts and foliar applications of cal-cium and magnesium as tools that could improve the nutraceutical quality content of tomato crop

The massive amount of human biological, imaging and clinical data produced by multiple and diverse sources, necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels as well as their orchestration and links are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof of concept study cases. Personalized simulations over the actual anatomy of a patient have been carried out. The hypermodel has also applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin based clinical decision support system and the core of future in silico trial platforms, although additional retrospective adaptation and validation is necessary.

Background: Recent research suggests a concerning trend of non-suicidal self-injury (NSSI) and suicidal behaviors emerging at younger ages (as early as age 12). Early onset of NSSI is linked to more severe outcomes. While universal school-based prevention programs have shown promise in addressing suicidal behaviors, there's limited research on their effectiveness in preventing NSSI onset among adolescents. This study aims to evaluate the efficacy of a universal prevention program in schools for NSSI and mental complaints while enhancing resilience and mental health in 11-14-year-old adolescents. Methods: In total, 329 Flemish secondary school students (55.6% female), aged 11 to 14 years, participated in a 4-hour classroom universal prevention, with a focus on emotion regulation, mental health, and specific strategies to prevent NSSI and reduce stigma. For both the intervention and control group (N = 124), a pre-, post- and one-month follow-up questionnaire was administered, containing reliable and valid measures for NSSI and suicidality, emotion regulation, help-seeking behaviors, well-being, and psychological distress. Results: The prevention program effectively reduced NSSI and psychological distress, particularly for adolescents with a history of NSSI. Conclusions: These findings support previous research on the effectiveness of school-based programs in reducing mental complaints and suggest promising outcomes for NSSI prevention.

The article focuses on mining of non-energy mineral resources with minimum environmental impacts. It issues from research results of a project Competence Centre for Effective and Ecological Mining of Mineral Resources implemented at the Faculty of Mining and Geology at VŠB-Technical University of Ostrava, Czech Geological Survey, a company Watrad ltd., a state enterprise Diamo, a company RPS Ostrava plc and a company Sedlecký kaolin plc. The paper starts with a partial analysis of the existing legal norms related to mining and processing of mineral resources. Next, it analyses mineral resource mining options free of negative environmental impacts. The fundamental tool to assess potential environmental impacts of mining is the implementation of Environmental Impact Assessment (EIA) process for a given mineral resource. In the Czech Republic environmental impact assessment is carried out by course of Act 100/2001 Coll. Its important amendment is Act 39/2015 Coll. claiming, inter alia, that the environmental impact assessment is rigidly connected with other permits and procedures, such as the zoning process and building construction permits. The article describes the environmental impacts of mining of non-energy mineral resources, including the following factors: appropriation of land, impacts on surface water, ground water and soil, noise, influence on the landscape character, and air pollution. The paper also includes a case study summarizing information on the environmental factors that may play a role in potential underground mining of graphite in the deposit Český Krumlov - Městský Vrch and the deposit Lazec - Křenov.

This paper focuses on evaluating airline service quality from the perspective of passengers view. Until now a lot of researches has performed in airline service quality evaluation in the world but a little research has been conducted in Iran, yet. In this research a framework for measuring airline service quality in Iran is proposed. After reviewing airline service quality criteria, SSQAI model was selected because of its comprehensiveness in covering airline service quality dimensions. SSQAI questionnaire items were redesigned to adopt with Iranian airlines requirements and environmental circumstances in the Iran's economic and cultural context. This study includes fuzzy decision-making theory, considering the possible fuzzy subjective judgment of the evaluators during airline service quality evaluation. Fuzzy TOPSIS have been applied for ranking airlines service quality performances. Three major Iranian airlines which have the most passenger transfer volumes in domestic and foreign flights, were chosen for evaluation in this research. Results demonstrated Mahan airline has got the best service quality performance rank in gaining passengers' satisfaction with delivery of high quality services to its passengers, among the three major Iranian airlines. IranAir and Aseman airlines placed in the second and third rank, respectively, according to passenger's evaluation.Statistical analysis have been used in analyzing passenger responses. Due to abnormality of data, Non-parametric tests were applied. To demonstrate airline ranks in every criterion separately, Friedman test was performed. Variance analysis and Tukey test were applied to study the influence of increasing in age and educational level of passengers' on degree of their satisfaction from airline's service quality. Results showed that age has not significant relation with passenger satisfaction of airlines, however increasing in educational level demonstrated a negative impact on passengers' satisfaction from airline's service quality.

Byers Peninsula is considered one of the largest ice-free areas in Maritime Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving effects of climate changes in lives cycles, limnology and microbiology. Soils from maritime Antarctica are generally weakly developed and have chemical, physical and morphological characteristics strongly influenced by the parent material. However, biological activity during the short Antarctic summer promotes intense transference of nutrients and organic matter in areas occupied by different species of birds and marine mammals. To mapping and monitoring those areas with high biological occupation, could be very useful to have models of edaphic properties prepared from satellite images. In this approach, Deep Learning and Linear Regression models of soil properties and spectral indexes as explicative variables were performed. We training models of soil properties closely related to biological activity such as Dissolved Organic Carbon (DOC) and the iron fraction associated with organic matter (Fe). We tested the best approach to model the spatial distribution of DOC, Fe and pH by training models of Linear Regression and Deep Learning over Sentinel2 and WorldView2 images. The most robust models were used to track possible areas with ornithogenic soils as well as areas of the Byers Peninsula that could support the highest biological development.

Advances in next-generation sequencing have facilitated the discovery of a multitude of long non-coding RNAs (lncRNAs) with pleiotropic functions in cellular processes, disease and viral pathogenesis. It came as no surprise when viruses were also revealed to transcribe their own lncRNAs. Among them, gammaherpesviruses, one of the three subfamilies of the Herpesviridae, code their largest number. These structurally and functionally intricate non-coding (nc) transcripts modulate cellular and viral gene expression to maintain viral latency or prompt lytic reactivation. The lncRNAs allow the virus to escape cytosolic surveillance, sequester and re-localize essential cellular factors and modulate the cell cycle and proliferation. Some viral lncRNAs act as “messenger molecules”, transferring information about viral infection to neighboring cells. This broad range of lncRNA functions is achieved through lncRNA structure-mediated interactions with effector molecules of viral and host origin, including other RNAs, proteins and DNAs. In this review, we discuss examples of gammaherpesvirus-encoded lncRNAs, emphasize their unique structural attributes, and link them to viral life cycle, pathogenesis and disease progression. We will address their potential as novel targets for drug discovery and propose future directions to explore lncRNA structure and function relationship.

The Microwave Humidity and Temperature sounder (MWHTS) on board the Fengyun (FY)-3C satellite measure the outgoing radiance form the Earth surface and atmospheric constituents. MWHTS makes measurements in the isolated oxygen absorption line near 118 GHz and the vicinity of strong water vapor line around 183 GHz, can provide fine vertical distribution structure of both atmospheric humidity and temperature. However, in order to obtain the accurate soundings of humidity and temperature by the physical retrieval method, bias between the observed radiance and those simulated by radiative transfer model from the background or first guess profiles must be correct. In this study, two bias correction methods are developed through the correlation analysis between MWHTS measurements and air mass identified by the first guess profiles of the physical inversion, one is the linear regression correction (LRC) and the other is neural networks correction (NNC), representing the linear and nonlinear nature between MWHTS measurements and air mass, respectively. Both correction methods have been applied to MWHTS observed brightness temperatures over the geographic area (180° W-180° E, 60° S-60° N). The corrected results are evaluated by the probability density function of the difference between corrected observations and simulated values and the root mean square error (RMSE) with respect to simulated observations. The numerical results show that the NNC method perform better, especially in MWHTS channels 1 and 7-9 whose peak weight function heights are close to the surface. In order to assess the effects of bias correction methods proposed in this study on the retrieval accuracy, a one-dimensional variational system was built and applied to the MWHTS uncorrected and corrected brightness temperatures to estimated atmospheric temperature and humidity profiles, The retrieval results show that the NNC has better performance which is to be expected. An indication of the stability and robustness of NNC method is given which suggests that the NNC method has promising application perspectives in the physical retrieval.

Pronounced differences exist in the biodiversity and structure of coral reef assemblages with increasing distance from shore, which may be expected given marked cross-shelf gradients in environmental conditions. Cross-shelf variation in the abundance of coral reef organisms is likely to be caused, at least in part, by differences in demography (e.g., growth and survival), though this has rarely been tested. This study quantified growth of three distinct coral taxa (Acropora nasuta, Pocillopora spp., and Stylophora pistillata) at 6 sites on Australia’s Great Barrier Reef (GBR), encompassing inshore, mid-shelf and outer-shelf reefs. Replicate colonies (up to 15 colonies per species, per reef) were stained using Alizarin red in December 2015 and retrieved 1-year later to quantify linear extension on replicate branches for each colony. Annual linear extension varied within and among coral taxa, with pronounced differences among reefs. For A. nausta. and S. pistillata, growth rates were highest at Orpheus Island, which is an inner shelf reef. However, inter-reef differences in coral growth were not explained by shelf position. Based on differences in skeletal density, which did vary according to shelf position, branching corals at the inshore sites may actually have higher rates of calcification compared to conspecifics on mid- and outer-shelf reefs. This study shows that growth of branching corals is not lower at inshore sites (and perhaps even higher) compared to sites at mid-shelf and outer reefs, despite generally higher levels of sedimentation and turbidity.

Indirect imaging methods involve at least two steps, namely optical recording, and computational reconstruction. The optical recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object’s image corresponding to different spatial and spectral dimensions. There have been numerous optical modulation functions and reconstruction methods developed in the past years for different applications. In most cases, a compatible pair of optical modulation function and reconstruction method gives optimal performance. A new reconstruction method termed non-linear reconstruction (NLR) was developed in 2017 to reconstruct the object image in the case of optical scattering modulators. During the years, it was revealed that the NLR could reconstruct an object’s image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR has been investigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.

Objective: To evaluate the variables influencing the length of stay (LoS) for COVID-19 ICU patients at Tygerberg Hospital (Cape Town) and to identify the covariates that significantly influenced it and any potential risk factors associated with LoS. Methods and Results: Poisson, negative binomial (NB), Hurdle–Poisson, and Hurdle–NB regression models were used to model the LoS in this prospective cohort study. The fitted models were compared using the Akaike information criterion (AIC), Vuong’s test criteria, and Rootograms. Based on the chosen performance criteria, the NB model provided the best fit outperforming other candidate models. The baseline LoS count was 8 days. On average, antibiotics reduced LoS by 0.74-fold (95% CI 0.62-0.89) compared to not taking antibiotics. The second wave had a significant effect on the average LoS, which decreased by 0.36-fold (95% CI 0.14-0.93) compared to the first wave. Average LoS increased by 1.01-fold (95% CI 1.01-1.02) for every one-year increase in the age of the patient and by 1.02-fold (95% CI 1.01-1.03) for every 1 unit increase in neutrophils. A 1 ng/L increase in log (TropT) levels decreased the average LoS by 0.87-fold (95% CI 0.81-0.93) similarly, a unit increase in the PF ratio decreased the average LoS by 0.998-fold (95% CI 0.997-0.999) respectively. Conclusion: The study identified common clinical characteristics associated with length of stay in ICU for COVID-19 patients, including age at admission, PF ratio, neutrophils, TropT, Wave, and antibiotic use. These results can aid in identifying risk factors for increased length of stay, assist in healthcare systems planning, and aid in evaluating different models for analysing this type of data.

To assess the community health workers’ (CHWs) knowledge, attitude, and practices (KAP) in type-2 diabetes (T2D) and hypertension (HTN) management. We thus also sought to assess the potential health system barriers for incorporating CHWs in T2D and HTN management. Mixed-method study comprised (1) a survey among 153 active CHWs to assess their KAP of T2D and HTN, and (2) semi-structured interviews with key informants to understand challenges of the health system and proposed solutions in incorporating CHWs in T2D and HTN management. The majority of CHWs correctly answered general knowledge questions on NCDs, risk factors, and prevention; however, only one-quarter correctly answered questions on smoking, family history, or tobacco use as risk factors. Most respondents appeared to have positive attitudes and have been practicing some activities related to T2D and HTN. Both financial and non-financial resource constraints were cited as challenges of the health system; therefore, re-structuring the role definition of CHWs and task of responsibilities, and assessment the need and workload have been proposed as ways forwards to effectively incorporate CHWs in T2D and HTN care. CHWs in Cambodia have shown their potential in T2D and HTN management; however, a well-designed strategy including technical training, clearly defined roles and responsibilities, and strong supporting structure are important to maximize their potential in the health system.

Numerical models widely used for hydrocarbon phase behavior and compositional flow simulations are based on assumption of thermodynamic equilibrium. However, it is not uncommon for oil and gas-condensate reservoirs to exhibit essentially non-equilibrium phase behavior, e.g., in the processes of secondary recovery after pressure depletion below saturation pressure, or during gas injection, or for condensate evaporation at low pressures. In many cases the ability to match field data with equilibrium model depends on simulation scale. The only method to account for non-equilibrium phase behavior adopted by the majority of flow simulators is the option of limited rate of gas dissolution (condensate evaporation) in black oil models. For compositional simulations no practical yet thermodynamically consistent method has been presented so far except for some upscaling techniques in gas injection problems. Previously reported academic non-equilibrium formulations have a common drawback of doubling the number of flow equations and unknowns compared to the equilibrium formulation. In the paper a unified thermodynamically-consistent formulation for compositional flow simulations with non-equilibrium phase behavior model is presented. Same formulation and a special scale-up technique can be used for upscaling of an equilibrium or non-equilibrium model to a coarse-scale non-equilibrium model. A number of test cases for real oil and gas-condensate mixtures are given. Model implementation specifics in a flow simulator are discussed and illustrated with test simulations. A non-equilibrium constant volume depletion algorithm is presented to simulate condensate recovery at low pressures in gas-condensate reservoirs. Results of satisfactory model matching to field data are reported and discussed.

From grape cultivation to ripening and harvest timing to processing, each step can be a critical point when it comes to wine quality and phenolic composition. In this study, the influence of winemaking technology on resveratrol and quercetin content, as well as other polyphenolic compounds, was investigated. Resveratrol is a non-flavonoid polyphenolic stilbene synthesized by grape skin when damaged by infectious diseases or ionizing radiation. Quercetin is a phenol found in grape skins and stems and is produced to protect grapes from UV light damage. Trans-resveratrol and quercetin are known to act as antioxidants, reduce the risk of atherosclerosis and type 2 diabetes, inhibit the growth of cancer cells, and prevent the release of allergic and inflammatory molecules. However, the question was whether red wine could be enriched with these phenols using an innovative winemaking technology. The innovative idea was to completely replace the cold maceration process with maceration with the addition of wild yeast (Torulaspora delbrueckii, Td). Maceration with the addition of wild yeast (Td) offers the following advantages over traditional cold maceration: (1) higher concentrations of trans-resveratrol (>35-40%) and quercetin (>35-40%) in the final wine, (2) the new wine has a higher potential for human health, (3) the wine has a better aroma and stability due to the higher mannoprotein content, and (4) the better energy efficiency in the production process. The study of stability during storage and aging also included derivatives of benzoic acid and hydroxycinnamic acid, piceid, catechin, naringenin, rutin, kaempherol, hesperetin, and anthocyanins. The study found that younger wines had higher phenolic content, while storage of the wine resulted in a decrease in total phenolic content, especially monomeric stilbenes and quercetin.

The method for quantitative analysis is based on the direct measurement of the analyte using differential pulse voltammetry (DPV), exploiting its oxidation peak. Calibration curves are set up to evaluate the figures of merit of the analytical method (LOD, LOQ, linear range). The application of the sensor for the dosing of GA in real matrices is carried out by analyzing non-alcoholic and alcoholic beverages and comparing the results with those reported in the literature and with the content of total polyphenols determined by the Folin-Ciocalteu method. In all cases, concentrations of GA align with those previously found in the literature for the beverages examined. Moreover, the values are always lower than the total polyphenols content; this demonstrates the good selectivity of the sensor that can discriminate the target molecule from other polyphenols present.

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

Gradual disability worsening in Multiple Sclerosis (MS) is indicative of confirmed progression that mostly involves progression independent of relapse activity (PIRA) and is associated with neurodegeneration. Insights from pathology reveal grey matter involvement (neocortex, hippocampus, spinal cord, and deep grey matter structures) and microglia activation in early stages of MS. Cortical lesions result in thinning and atrophy and are considered accurate predictors of disability progression and cognitive decline.Neuroimaging biomarkers, such as high-resolution 7T MR images and TSPO-PET, have been examined for the detection of cortical pathology linked to cognitive deficits and thus progression, but are limited in clinical practice due to availability, time constraints, and cost.Electroencephalography (EEG) emerges as a non-invasive, cost-effective tool that reflects cortical activity in MS. Its potential in monitoring cognitive impairment is explored by focusing on nonlinear EEG analysis. The MuST PREDICT^TM project aims to extract linear and nonlinear EEG features, investigating their role in predicting disease progression and optimizing treatment. The study employs retrospective, cross-sectional, and prospective designs, utilizing EEGs from various MS forms, cognitive assessments, serum/cerebrospinal fluid biomarkers and neuroimaging. The methodology involves time-based and spectral feature extraction, employing artificial intelligence classifiers and brain criticality-based approaches.The conceptual framework of an innovative modality is herein presented, that would EEG for early MS progression detection. Standardization of the methodology could lead to the creation of a digital tool for better prognostication and treatment strategy optimization.

Commuting is a vital travel channel for college students throughout their higher education career; nevertheless, excessive commute time negatively impacts students’ school satisfaction, academic achievement, health, and quality of life. Meanwhile, few studies have explored students’ commute time, covering a large population and scope. Therefore, this study analyzes the dwelling type that influences college and graduate students’ school commute times in the Seoul Metropolitan Area, using data from the 2016 Household Travel Diary Survey. This study uses spatial data on housing development to classify five dwelling types (i.e., new town, housing site development, Seoul, Incheon, and Gyeonggi-do). A multiple linear regression model empirically analyses students’ household and personal characteristics. The results reveal that dwelling type significantly affects students’ commute time. Specifically, Students living in Seoul have a shorter commute to school than those living in new towns. Socioeconomic characteristics have less effect on college and graduate students' school commute time. This study discusses the problem of excessive commuting of college and graduate students in new towns.

Prompt removal of misfolded membrane proteins and misassembled membrane protein complexes is essential for membrane homeostasis. However, the elimination of these toxic proteins from the hydrophobic membrane environment has high energetic barriers. Transmembrane FtsH is the only known ATP-dependent protease responsible for this task, unlike other well-studied soluble ATP-dependent proteases. The mechanisms by which FtsH recognizes, unfolds, translocates, and proteolyzes its substrates remain unclear. Here, we report the crystal structures of the Thermotoga maritima FtsH periplasmic domain (PD) in an associative trimeric state at a 1.5-1.95 Å resolution. We also describe the pH-dependent oligomerization states of the isolated PD using dynamic light scattering. These observations help us understand how FtsH recognizes membrane-anchored misfolded proteins.

Sugar-sweetened beverages are associated with metabolic dysfunction, particularly in those with increased risk factors. Artificial sweeteners (AS) are often promoted as a healthier alternative, yet findings remain conflicting as to their effects on metabolic function. Further, there is a lack of data exploring the interaction between AS and high-fat diets (HFD). We therefore examined the effects of HFD and the AS Acesulfame-potassium (Ace-K) on glucose intolerance and adipose tissue physiology in male and female C57BL/6 mice. 40 mice were randomised to receive either a) a control diet (CDCon; standard control diet/water), b) control diet and Ace-k (CDAS; CD/7.5mM AS in drinking water), c) HFD (HFCon; HFD (45%kcal from fat)/water), or d) HF and AS (HFAS; HFD/7.5mM AS in drinking water) for 6 weeks. A HFD increased body weight in male and female mice independently of AS supplementation. AS induced sex-specific effects protecting against HFD-induced hyperglycaemia and adipocyte hypertrophy in male mice and reducing inflammatory gene expression in the adipose tissue. Conversely in females, AS induced hyperinsulinemia in HFD mice and increased expression of immune-related genes. These findings suggest that supplementation of HFD with AS exacerbates metabolic dysfunction in female mice. This work supports the importance of studying sexually dimorphic responses to an altered nutritional environment and highlights the need for further investigation into the intake of AS, particularly in those already at risk of metabolic disease such as the obese or overweight.

Non-impregnated small pore graphite (NSPG) with the compact microstructure for using in molten salt reactors (MSR) was prepared by the novel process, and the pore diameter of the obtained graphite was reduced to ~800 nm. The irradiation evaluation of the prepared graphite was carried out by 7 MeV Xe26+ ion irradiation and the microstructural changes of the graphite were investigated with IG-110 as a comparison. The graphitization degree of NSPG was higher than that of IG-110, though it was not subjected to an impregnation process. Under low-dose ion irradiation (

An approximation-free and fully quantum optic formalism for parametric processes is presented. Phase-dependent gain coefficients and related phase-pulling effects are identified for quantum Rayleigh emission and the electro-optic conversion of photons providing parametric amplification in small scale integration of photonic devices. These mechanisms can be manipulated to deliver, simultaneously, sub-Poissonian distributions of photons as well as phase-dependent amplification in the same optical quadrature of a signal field.

Cancer is a disease caused by the abnormal growth of cells in different parts of body is one of the top causes of death globally. Microarray gene expression data plays a critical role in the identification and classification of cancer tissues. Due to recent advancements in Machine Learning (ML) techniques, researchers are analyzing gene expression data using a variety of such techniques to model the progression rate & treatment of cancer patients with great effect. But high dimensionality alongside the presence of highly correlated columns in gene expression datasets leads to computational difficulties. This paper aims to propose the use of ML classification techniques- Linear Discriminant Analysis (LDA) & Random Forest (RF) for classifying five types of cancer (breast cancer, kidney cancer, colon cancer, lung cancer and prostate cancer) based on high dimensional microarray gene expression data. Principal component analysis (PCA) was used for dimensionality reduction, and principal component scores of the raw data for classification. Six distinct categorization performance measures were used to evaluate these approaches; RF method provided us with higher accuracy than LDA method. The method and results of this article should be helpful to researchers who are dealing with many genes in microarray data.

This paper provides a proof of concept for a linear electric generator that can be used to harvest energy from various sources of linear motion, such as vibrations, free-piston engines and wave energy. The generator can be used to power small electronic devices, such as sensors, or charge household batteries. Literature was reviewed to develop an understanding about the applications, control methods, excitation methods and mechanics of rotating and linear electric machines. A bidirectional, two-sided linear machine was designed with two stator cores and a single mover core. The stator windings and mover winding can be independently excited, allowing for three modes: no mover excitation, DC excited mover, and AC excited mover. Simulations results showed that the magnetic flux generated by DC excited stator cores were concentrated in the centre of the mover core. The use of two stator cores eliminates lateral flux in the mover core when it is not excited, minimising attraction and repulsion forces. Parametric analysis showed that flux cutting occurred in all operation modes, verifying that the generator will produce power when operating. Hardware tests produced an output current when the machine is electrically and mechanically excited, verifying the proposed design.

Polymer electrolyte was used as a medium for testing the performance of microband electrodes under conditions of linear diffusion. Cyclic voltammetry and chronoamperometry experiments were performed in such viscous medium, where diffusion rates are much slower than in fluid solutions. Confirmation of the existence of such conditions from the log i vs. log v or log i vs. log t relationships in the current equation always yielded values lower than the expected value of 0.5. This could indicate impure linear diffusion profile, i. e. some contribution from radial diffusion (edge effect). However, performing these tests in monomeric solvents of similar viscosities, such as glycerol or propylene glycol, gave the desired value of 0.5. These results lead to the conclusion that current equations which are based on Fick’s laws may not be applicable for polymer electrolytes, where various obstruction to diffusion make it a more complicated process than in monomeric solvents.

In this work, we investigate the weak deflection angle of light from exact black hole within the non-linear electrodynamics. First we calculate the Gaussian optical curvature using the optical spacetime geometry. With the help of modern geometrical way popularized by Gibbons and Werner, we examine the deflection angle of light from exact black hole. For this desire, we determine the optical Gaussian curvature and execute the Gauss-Bonnet theorem on optical metric and calculate the leading terms of deflection angle in the weak limit approximation. Furthermore, we likewise study the plasma medium's effect on weak gravitational lensing by exact black hole. Hence we expose the effect of the non-linear electrodynamics on the deflection angle in the weak gravitational field.

Food-borne transmission is a recognized route for many viruses associated with gastrointestinal, hepatic or neurological diseases. Therefore, it is essential to identify new bioactive compounds with broad-spectrum antiviral activity is needed to exploit innovative solutions against these hazards. Lately, antimicrobial peptides (AMPs) have been recognized as promising antiviral agents. Indeed, while the antibacterial and antifungal effects of these molecules have been widely reported, their use as potential antiviral agents has not yet been fully investigated. Herein, the antiviral activity of previously identified or newly designed AMPs, was evaluated against the non-enveloped RNA viruses, Hepatitis A virus (HAV), and Murine Norovirus (MNV), a surrogate for human Norovirus. Moreover, specific assays were performed to recognize at which stage of the viral infection cycle the peptides could function. Results showed that almost all peptides displayed virucidal effects with about 90% of infectivity reduction on HAV or MNV. However, the decapeptide RiLK1 demonstrated, together with its antibacterial and antifungal properties, a notable reduction in viral infection for both HAV and MNV, possibly through direct interaction with viral particles or inhibition of the viral bonding to the cell receptors. Hence, RiLK1 could represent a versatile ‘antimicrobial agent effective against various foodborne pathogens including viruses, bacteria, and fungi.

Quantifying an imaging modality’s ability to reproduce results is important for establishing its utility. In Magnetic Resonance Spectroscopic Imaging (MRSI), new acquisition protocols are regularly introduced, which improve upon their precursors with respect to signal-to-noise ratio (SNR), total acquisition duration, and nominal voxel resolution. This study has quantified the within-subject and between-subject reproducibility of one such new protocol (reduced-Field-of-View-Density-Weighted-Concentric-Ring-Trajectory (rFOV-DW-CRT) MRSI) by calculating the Coefficient of Variance of data acquired from a test-retest experiment. The Posterior Cingulate Cortex (PCC) and the Right Superior Corona Radiata (SCR) were selected as the Regions of Interest (ROIs) for Grey Matter (GM) and White Matter (WM), respectively. CVs for between-subject and within-subject are consistently around or below 15% for Glx, tCho, and Myo-Ins and below 5% for tNAA and tCr.

The motion of a circular elastic plate floating on the surface is investigated in the time–domain. The solution is found from the single frequency solutions and the method to solve for the circular plate is given using the eigenfunction matching method. Simple plane incident waves with a Gaussian profile in wavenumber space are considered and a more complex focused wave group is considered. Results are given for a range of plate and incident wave parameters are investigated. Code is provided to show how to simulate the complex motion.

(1) Background: The aim of the research was to present and emphasize the importance of magnetic resonance imaging (MRI) in diagnosing Achilles tendon (AT) ruptures by presenting case reports. (2) Materials and Methods: The sample of respondents included 7 patients (4 males and 3 females, 2 athletes and 5 non-athletes), aged 25 to 58 years, with AT injuries, who were examined and treated at the Institute for Treatment and Rehabilitation "Niška Banja", Niš, Serbia. Ankle examinations with MRI were conducted using the Esaote O-scan 0.3 T machine. The examinations were performed without the application of a paramagnetic contrast agent and without the use of anesthesia. Results: The MRI method's sensitivity and overall diagnostic accuracy were excellent, with 100% true positives. In our study, the method accurately detected the presence, location, and severity of AT injuries in all cases. MRI is an important and reliable method for detecting AT injuries, classifying them, monitoring the course of recovery, and assessing the effects of therapy. Conclusions: An unrecognized or delayed diagnosis of an AT injury can lead to chronic changes. Timely diagnosis (clinical examination, ultrasonography, magnetic resonance imaging) and appropriate treatment (conservative or operative) enable patients to return to normal activities, including sports. Unfortunately, the use of MRI is limited by restricted access and the cost of the examination.

The sandwich format immunoassay is generally more sensitive and specific than more common assay formats, including direct, indirect, or competitive. A sandwich assay, however, requires two receptors to bind non-competitively to the target analyte. Typically, pairs of antibodies (Abs) or antibody fragments (Fabs) capable of forming a sandwiching with the target are identified through a slow, guess-and-check method with panels of candidate binding partners. Additionally, sandwich assays reliant on commercial antibodies can suffer from changes to reagent quality outside the researchers’ control. This report presents a reimagined and simplified phage display selection protocol that directly identifies sandwich binding peptides and Fabs. The approach yielded two sandwich pairs, one peptide-peptide and one Fab-peptide sandwich for the cancer and Parkinson’s disease biomarker DJ-1. Requiring just a few weeks to identify, the sandwich pairs delivered apparent affinity comparable to other commercial peptide and antibody sandwiches. The results reported here could expand the availability of sandwich binding partners for a wide range of clinical biomarker assays.

Amorphous germanium films on non-refractory glass substrates were annealed by ultrashort near-infrared (1030 nm, 1.4 ps) and mid-infrared (1500 nm, 70 fs) laser pulses. Crystallization of germanium irradiated at a laser energy density (fluence) range from 25 to 400 mJ/cm2 under single-shot and multi-shot conditions was investigated using Raman spectroscopy. The dependence of the fraction of the crystalline phase on the fluence was obtained for picosecond and femtosecond laser annealings. The regimes of almost complete crystallization of germanium films over the entire thickness are obtained (from the analysis of Raman spectra with excitation of 785 nm laser). The possibility of scanning laser processing is shown, which can be used to create films of micro and nanocrystalline germanium on flexible substrates.

We study a conformation of an albumin protein in the temperature range of 300K-315K, i.e. in the physiological range of temperature. Using simulations we calculate values of two backbone angles, that carry most of information about positioning of the protein chain in a conformational space. Given these, we calculate energy components of such protein. Further, using the Flory theory we determine the temperature in which investigated albumin chain model is closest to the free joined chain model. Near the Flory temperature, we study energy components and the conformational entropy, both derived from two angles that reflect most of the chain dynamics in a conformational space. We show that the conformational entropy is an oscillating function of time in considered range of temperature. Our finding is that, the only regular oscillation pattern appears near the Flory temperature.

QSO B0218+357 is a blazar located at a cosmological redshift of 0.944. The source is gravitationally lensed by a spiral galaxy located at the redshift of 0.68. Strong gravitational lensing splits the signals emitted by the source into two components separated by 10-12 days, as observed in radio and gamma-ray bands. In July 2014 a GeV flare was observed by Fermi-LAT, triggering follow-up observations with the MAGIC telescopes at energies above 100 GeV. The expected time delay between the components allowed us to plan broad band MWL observations before, during and after the trailing component of the emission. The MAGIC observations at the expected time of arrival of the trailing component resulted in the first detection of QSO B0218+357 in Very-High-Energy (VHE, >100 GeV) gamma rays. It is both the farthest known VHE object and one of only a few Flat Spectrum Radio Quasars detected in this energy range. We report here the observed multiwavelength spectral and temporal properties of the emission during the 2014 flare.

Neural tissue engineering, nanotechnology and neuroregeneration are diverse biomedical disciplines that have been working together in recent decades to solve the complex problems linked to central nervous system (CNS) repair. It is known that the CNS demonstrates a very limited regenerative capacity because of a microenvironment that impedes effective regenerative processes, making development of CNS therapeutics challenging. Given the high prevalence of CNS conditions such as stroke that damage the brain and place a severe burden on afflicted individuals and on society, it is of utmost significance to explore the optimum methodologies for finding treatments that could be applied to humans for restoration of function to pre-injury levels. Extracellular vesicles (EVs), also known as exosomes, when derived from mesenchymal stem cells, are one of the most promising approaches that have been attempted thus far, as EVs deliver factors that stimulate recovery by acting at the nanoscale level on intercellular communication while avoiding the risks linked to stem cell transplantation. At the same time, advances in tissue engineering and regenerative medicine have offered the potential of using hydrogels as bio-scaffolds in order to provide the stroma required for neural repair to occur, as well as the release of biomolecules facilitating or inducing the reparative processes. This review introduces a novel experimental hypothesis regarding the benefits that could be offered if EVs were to be combined with biocompatible injectable hydrogels. The rationale behind this hypothesis is presented, analyzing how a hydrogel might prolong the retention of EVs and maximize the localized benefit to the brain. This sustained delivery of EVs would be coupled with essential guidance cues and structural support from the hydrogel until neural tissue remodeling and regeneration occur. Finally, the importance of including non-human primate (NHP) models in the clinical translation pipeline, as well as the added benefit of multi-modal neuroimage analysis to establish non-invasive, in vivo, quantifiable imaging-based biomarkers for CNS repair are discussed, aiming for more effective and safe clinical translation of such regenerative therapies to humans.

The Circular Economy of plastics is a promising concept that has the potential to reduce pollution and close the loop on plastic waste. However, further research is needed to develop more efficient and environmentally friendly methods of recycling plastic. This review article discusses the Circular Economy of plastics, its potential benefits and drawbacks, and the challenges that need to be addressed to make it a reality. Some case studies are also examined to explore how the Circular Economy of plastics has been implemented across the globe.

We evaluate the complexity of Colombian climate from extreme behavior of gauge temperature and precipitation, using the the novel Tsallis' non-extensive entropy principle based on physical information through the q-index. We find the spatial structure of non additive universal categories (q-index) and compare with some complex systems with the potential to have some degree of dynamical affinity. Our results evidence the great dynamical variability of regional climate expressed in the large range of values of $q$-index, and the high degree of non-extensitivity for both temperature and precipitation.

Applications of gradient method for nonlinear optimization in development of Gradient Neural Network (GNN) and Zhang Neural Network (ZNN) are investigated. Particularly, the solution of the matrix equation AXB=D which changes over time is studied using the novel GNN model, termed as GGNN(A,B,D). The GGNN model is developed applying GNN dynamics on the gradient of the error matrix used in the development of the GNN model. The convergence analysis shows that the neural state matrix of the GGNN(A,B,D) design converges asymptotically to the solution of the matrix equation AXB=D, for any initial state matrix. It is also shown that the convergence result is the least square solution which is defined depending on the selected initial matrix. A hybridization of GGNN with analogous modification GZNN of the ZNN dynamics is considered. The Simulink implementation of presented GGNN models is carried out on the set of real matrices.

Climate change, recognized as a global crisis, is not only altering our environment but also significantly impacting human health. Particularly, its influence on non-communicable diseases (NCDs), a leading cause of global mortality, is becoming increasingly evident yet underexplored. This review aims to synthesize current research on the impact of climate change on NCDs, addressing a critical gap in our understanding of how environmental changes affect human health. We examine the complex interplay between climate change and NCDs, drawing insights from recent studies that highlight the adverse effects of climate variables on chronic diseases, such as cardiovascular and kidney diseases, and the role of food and nutrition security in this nexus. Furthermore, the review explores the disproportionate impact on vulnerable regions and populations, particularly in Pacific Island countries and territories, underscoring the urgent need for context-specific solutions and a cross-sectoral approach. By integrating findings from various disciplines, this review aims to inform policy and public health interventions, highlighting the necessity of collaborative efforts to mitigate the burgeoning burden of NCDs in a rapidly changing climate.

Mathematical models of non-small cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with “omics” approaches will improve our understanding of the nature of NSCLC. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.

Understanding the optimal strategy for a real estate investment and how performance changes based on characteristics is crucial for optimising the achievable return. This is prominent in tourist areas such as Paphos where there is no clear distinction as to whether short or long-term approaches are optimal. The study aimed to develop a model for predicting the optimal rental strategy whilst assessing which model performed best and which property attributes impacted its return the greatest. Short-term data was collected from AirDNA and long-term data was manually collected from real estate agents websites. Furthermore, Random Forest, K-Nearest Neighbour and Multiple Linear Regression models were created to predict the highest and best use for each property. Model accuracy varied between data sets with the best performing model for short-term properties being Random Forest (R-Squared: 0.843), and Distance-Based Multiple Linear Regression for long-term approach (R-Squared: 0.843). The study demonstrated that accurate models could be created to predict the optimal rental strategy with the number of bedrooms being the main driver for rental income, followed by luxury finishes and the presence of a pool. It found that locational characteristics didn’t impact the returns significantly assuming that the property was located within a tourist area.

This paper presents a mathematical modeling approach utilizing a fuzzy modeling framework for fixed wing aircraft systems with the goal of creating a highly desirable mathematical representation for model-based control design applications. The starting point is a mathematical model comprised of fifteen non-linear ordinary differential equations representing the dynamic and kinematic behavior applicable to a wide range of fixed wing aircraft systems. Here the proposed mathematical modeling framework is applied to the AIRBUS A310 model developed by ONERA. The proposed fuzzy modeling framework takes advantage of sector non-linearity techniquesto recast all the non-linear terms from the original model to a set of combined fuzzy rules. The result of this fuzzification is a more suitable mathematical description from the control system design point of view. Therefore, the combination of this fuzzy model and the wide range of control techniques available in the literature for such kind of models will enable us to avoid common control design methods, such as gain scheduling, where stability issues can be extremely challenging.

Tuberculosis (TB) is the primary cause of death by a single infectious agent; responsible for around two million deaths in 2016. A major virulence factor of TB is the ability to enter a latent or Non-Replicating Persistent (NRP) state which is presumed untreatable. Approximately, 1.7 billion people are latently infected with TB and on reactivation many of these infections are drug resistant. As the current treatment is ineffective and diagnosis remains poor, millions of people have the potential to reactivate into active TB disease. The immune system seeks to control the TB infection by containing the bacteria in a granuloma, where it is exposed to stressful anaerobic and nutrient deprived conditions. It is thought to be these environmental conditions that trigger the NRP state. A number of in vitro models have been developed that mimic conditions within the granuloma to a lesser or greater extent. These different models have all been utilised for the research of different characteristics of NRP Mycobacterium tuberculosis, however their disparity in approach and physiological relevance often results in inconsistencies and a lack of consensus between studies. This review provides a summation of the different NRP models and a critical analysis of their respective advantages and disadvantages relating to their physiological relevance.

Globally, noncommunicable diseases (NCDs) were responsible for 41 million deaths in 2016, with the majority of these occurring in low and middle-income countries. These diseases were on the rise as a result of unhealthy, low-quality, and unbalanced diets, which resulted in overweight and obesity. The National School Nutrition Programme (NSNP) was created to regulate the foods sold to schoolchildren. To ascertain school management teams' perspectives on the relationship between the NSNP and the development of lifestyle diseases. A phenomenological qualitative study using Focus Group Discussions among 16 purposively selected members of the School Management Teams were conducted in Mt Frere, Eastern Cape in 2016. The narrative data was analyzed using Tesch's eight-phase thematic analysis approach. The data analysis revealed two themes (NSNP and the vendor system) and six sub-themes. The NSNP was viewed as making a significant contribution to children's food security, thereby improving academic output. However, reengineering of the NSNP was need through improved budgeting and inclusion of breakfast in the menu to control NCDs risk factors. The current implementation of the vendor system did not support reduction of NCDs risk factors. Improved implementation of the guide to vendor system is needed.

This work investigates the use of Non-destructive tests as a tool for monitoring the structural performance of concrete structures. The investigation encompassed four phases; the first of which involved the use of destructive and non-destructive mechanisms to assess concrete strength on cube specimens. The second phase research focused on site assessment for a twin engineering theatre located at the Faculty of Engineering, University of Lagos using rebound hammer and ultrasonic pulse velocity tester. The third phase was the use of linear regression analysis model with MATLAB to establish a relationship between calibrated strength as well as ultrasonic pulse velocities with their corresponding compressive strength values on cubes and values obtained from existing structures. Results show that the root-mean squared-R² values for rebound hammer ranged between 0.275 and 0.742 while ultrasonic pulse velocity R² values were in the range of 0.649 and 0.952 for air curing and water curing systems respectively. It initially appeared that the Ultrasonic pulse velocity was more suitable for predicting concrete strength than rebound hammer but further investigations showed that the latter was adequate for early age concrete while the former was more suited for aging concrete. Hence, a combined use is recommended in this work.

Background: A growing number of clinical practice guidelines (CPGs) with regards to non-pharmacological interventions for breast cancer survivors are available. However, given the limitations in guideline development methodologies and inconsistency of recommendations, it remains uncertain how best to design and implement such non-pharmacological strategies to tailor interventions for breast cancer survivors with varied health conditions, healthcare needs, and preferences. Aim: To critically appraise and summarise available non-pharmacological interventions for symptom management and health promotion that can be self-managed by breast cancer survivors based on the recommendations of the CPGs. Methods: Clinical practice guidelines which were published between January 2016 and September 2021 and described non-pharmacological interventions for breast cancer survivors were systematically searched in six electronic databases, nine relevant guideline databases, and five cancer care society websites. The quality of the included CPGs was assessed by four evaluators using the Appraisal of Guidelines for REsearch and Evaluation, second edition tool. Content analysis was conducted to synthesise the characteristics of the non-pharmacological interventions that were recommended by the included CPGs, such as the intervention’s form, duration and frequency, level of evidence, grade of recommendation, and source of evidence. Results: Fourteen CPGs were identified and analysed. Of the 14 CPGs appraised, only five were rated as high quality. The domain with the highest standardised percentage was “scope and purpose” (84.61%), while the “applicability” domain had the lowest standardised percentage (51.04%). Five guidelines were assessed as “recommended”, seven were rated as “recommended with modifications”, and the remaining two were considered “not recommended”. Regarding the content analysis, physical activity/exercise, meditation, hypnosis, yoga, music therapy, stress management, relaxation, massage, and acupressure were the common self-managed non-pharmacological interventions recommended by the 14 CPGs. Physical activity/exercise was the only self-managed non-pharmacological intervention that was mostly recommended for psychological and physical symptom management by the included CPGs. However, there were significant disparities in terms of level of evidence and grade of recommendation in the included CPGs. Conclusion: The recommendations for the self-managed non-pharmacological interventions were varied and limited among the 14 CPGs, and some were based on medium- and low-quality evidence. More rigorous methods are required to develop high-quality CPGs in order to guide clinicians in offering high-quality and tailored breast cancer survivorship care.

This paper examines the correlation between numbers of computer cores in parallel genetic algorithms. The objective to determine the linear polynomial complementary equation in order represent the relation between number of parallel processing and optimum solutions. Model this relation as optimization function (f(x)) which able to produce many simulation results. F(x) performance is outperform genetic algorithms. Compression results between genetic algorithm and optimization function is done. Also the optimization function give model to speed up genetic algorithm. Optimization function is a complementary transformation which maps a TSP given to linear without changing the roots of the polynomials.

The current work reports the upper bound of the state variable of the of the Pointwise Steady Fluid Flow Approximation (PSFFA) model of non-stationary M/Ek/1 queueing system.

With the use of linear regression modeling, this study sought to forecast and analyze rainfall patterns in Ethiopia. The dataset included historical rainfall data as well as pertinent independent variables. The R-squared score and mean squared error (MSE) were used to assess the effectiveness of the linear regression model. The results showed that the model's ability to forecast and analyze rainfall patterns was not very good. Only around 5.3% of the variance in rainfall could be explained by the chosen independent variables, according to the R-squared score of 0.053. This low number indicated that there was little correlation between the selected variables and rainfall, and that a sizable percentage of the variation in the dependent variable was not captured by the model. The model's accuracy in forecasting rainfall was shown to be quite low by the MSE error, with significant squared discrepancies between the expected and actual amounts. These results support the notion that the linear regression model as it is now designed is not appropriate for studying or forecasting Ethiopia's rainfall patterns. Alternative modeling approaches, the inclusion of other pertinent factors, and the assurance of the availability of high-quality data that faithfully captures the intricate dynamics of rainfall in the area all require more investigation.

Abstract: Global ecological concern regarding the transfer of fouling organisms to ship hulls is increasing. This study investigated the species composition, dominant species, distribution patterns, community structure, and life-cycle differences of hull-fouling macroinvertebrates on five research vessels (R/Vs: Isabu, Onnuri, Eardo, Jangmok 1, and Jangmok 2) operated by the Korea Institute of Ocean Science and Technology (KIOST). Hull-fouling macroinvertebrates were collected three to five times on quadrats from the upper and middle sectors of the hull sides, bottom, and niche areas (the propellers and shafts and the thrusters). A total of 47 macroinvertebrate species were identified, represented by 8,519 individuals(ind.)/m2 and a biomass of 1,967 gWWt/m2 on the five vessels. The number of species, density, and biomass were greater on the coastal vessels the Eardo, Jangmok 1, and Jangmok 2 than on the ocean-going vessels the Isabu and Onnuri. Among the coastal vessels, barnacles were the most abundant and had the greatest density, while mollusks had the highest biomass. Differences between hull sectors showed that the highest species abundance and density appeared on all hulls in ports and bays where the Jangmok 1 operated, while the highest species abundance, density, and biomass were identified in the niche areas of the Eardo, which operated farther from the coast. The hull-fouling macroinvertebrates that exceeded 1% of all organisms were the barnacles Amphibalanus amphitrite, Balanus trigonus, and Amphibalanus improvisus; the polychaete Hydroides ezoensis; the bivalves Magallana gigas and Mytilus galloprovincialis; and the amphipod Jassa slatteryi. The dominant species were cosmopolitan and globally distributed, and many of them were cryptogenic. Six native species were identified: M. gigas, H. ezoensis, the amphipod Melita koreana, the isopod Cirolana ko-reana, and the barnacle B. trigonus and F. kondakovi. Eight non-indigenous species (NIS) were de-tected: barnacles A. amphitrite and A. improvisus, the bivalve M. galloprovincialis, the polychaete Perinereis nuntia, amphipods J. slatteryi and Caprella californica, and bryozoans Bugulina californica and Bugula neritina. Of the fouling macroinvertebrates found on the vessel hulls, 13% were native and 17% were NIS. The nMDS ordination analysis of the five vessels showed four clusters of fouling macroinvertebrate communities: two ocean clusters (the Isabu and Onnuri), one coastal cluster (the Eardo and Jangmok 2), and one local cluster (the Jangmok 1). More diverse communities developed on the hulls of vessels that operated locally rather than globally or in deep oceans. Spearman rank correlation showed that biological indices such as number of species, density, and biomass correlated highly and positively with the numbers of days on coastal operations and negatively with the number days on ocean operations. The species diversity index correlated positively with the total number of anchoring days and coastal operation days and negatively with the total number of operation days and ocean operation days. The macroinvertebrates differed by the area of operation, the port of anchorage, the number of days in operation and at anchor, and the hull sectors. There is no previous research data on hull-fouling macroinvertebrates in the Republic of Korea, and this study provides a basis for future studies to identify introduced species and their differences based on operation area.

In this paper, modelling design and analysis of a triple inverted pendulum have been done using Matlab/Script toolbox. Since a triple inverted pendulum is highly nonlinear, strongly unstable without using feedback control system. In this paper an optimal control method means a linear quadratic regulator and pole placement controllers are used to stabilize the triple inverted pendulum upside. The impulse response simulation of the open loop system shows us that the pendulum is unstable. The comparison of the closed loop impulse response simulation of the pendulum with LQR and pole placement controllers results that both controllers have stabilized the system but the pendulum with LQR controllers have a high overshoot with long settling time than the pendulum with pole placement controller. Finally the comparison results prove that the pendulum with pole placement controller improve the stability of the system.

Non-coding RNAs have been described as crucial regulators of gene expression and guards for cellular homeostasis. Some recent papers are focused on vault RNAs, one of the classes of non-coding RNA, and their role in cell proliferation, tumorigenesis, apoptosis, cancer response to therapy, and autophagy, which made them potential therapy targets in oncology. In the human genome, four vault RNA paralogues can be distinguished. They are associated with vault complexes, considered the largest ribonucleoprotein complex. The protein part of these complexes consists of a major vault protein (MVP) and two minor vault proteins (vPARP and TEP1). The name of the complex, as well as vault RNA, comes from the hollow barrel-shaped structure that reminds a vault. Their sequence and structure are highly evolutionary conserved and show many similarities in comparison with different species, but vault RNAs show various roles. Vaults were discovered in 1986, and their functions remained unclear for many years. Although not much is known about their contribution to cell metabolism, it has become clear that vault RNAs are involved in various processes and pathways associated with cancer progression and modulating cell functioning in normal and pathological stages. In this review, we discuss known functions of the human vault RNAs in the context of cellular metabolism, emphasizing processes related to cancer and cancer therapy efficacy.

High pressure crystallization technique has been successfully used to prepare an elusive form II of a non-steroidal anti-inflammatory drug, Mefenamic acid. Single crystal of form II was grown at 0.3 GPa from an 4:1 methanol/ ethanol mixture as a solvent using Diamond Anvil Cell. Comparison of crystal structures show that the efficient packing of MA molecules in Form II results from the structural flexibility of MA acid molecules. Compression studies performed on the single crystal of form I resulted in 14 % decrease of unit cell volume up to 2.5 GPa. No phase transition was observed up to this pressure. A reconstructive phase transition is required to induce conformational changes in the structure, which is confirmed by crystallization at high pressure results.

This paper presents the application of optimal control problem in modeling of stirred tank heater temperature control. The analysis of the open loop system shows that the system is not efficient without a controller. Linear Quadratic Gaussian (LQG) and Linear Quadratic Integral (LQI) controllers are used to increase the performance of the system. Comparison of the closed loop system with the proposed controllers have been done with Matlab/Simulink Toolbox and a promising results have been analyzed.

Non-exhaust road transport emissions in cities contribute to poor air quality and create health impacts. This paper presents a new study of the emitted particles due to the tyres-road wear ‘TRWP’ in real driving and gives their emission factors EF. The most frequently observed particles were <1 µm; followed by particles size between [1µm, 4µm] for urban, suburban and highway areas. These particle sizes are well-known to have a higher degree of toxicity. An overall analysis of all the measured pollutants gave EF equal to 30 10+12 #/km and 35 10+12 #/km, respectively for urban and sub-urban areas; and 5 10+12 #/km on highway. The analysis of the 19 most emitted pollutants, taken individually, showed that their EFs ranged from 0.003 to 18.142 10+12#/km. The obtained EF are above the value of the Euro standard for vehicles, but are below the values for vehicles unequipped with a particle filter. Significant test analysis confirmed that inertia of chemical pollutants is homogeneous. EF assessment of the PM10 and PM2.5 emitted is equal to 1.45 mg/km and 0.35 mg/km respectively. These results should contribute to the emergence of future regulations of non-exhaust emissions and should help to analyse the exposure-impact relationship to TRWP.

In this article, we analyze the weak gravitational lensing in the context of Einstein-non-linear Maxwell-Yukawa black hole. To this desire, we derive the deflection angle of light by Einstein-non-linear Maxwell-Yukawa black hole using the Gibbons and Werner method. For this purpose, we obtain the Gaussian optical curvature and implement the Gauss-Bonnet theorem to investigate the deflection angle of Einstein-non-linear Maxwell-Yukawa black hole. Moreover, we derive the deflection angle of light in the presence of plasma medium. We also analyze the graphical behavior of deflection angle by Einstein-non-linear Maxwell-Yukawa black hole in the presence of plasma as well as non-plasma medium.

The vast majority of antibodies generated against a virus will be non-neutralising1. However, this does not denote an absence of protective capacity. Yet, within the field there is typically a large focus on antibodies capable of directly blocking infection (neutralising antibodies, nAbs) of either specific viral strains or multiple viral strains (broadly-neutralising antibodies, bnAbs). More recently, a focus on non-neutralising antibodies (nnAbs), or neutralisation-independent effects of nAbs, has emerged. These can have additive effects on protection or in some cases, be a major correlate of protection. As their name suggests, nnAbs do not directly neutralise infection but instead, through their Fc domains, may mediate interaction with other immune effectors to induce clearance of viral particles or virally infected cells. nnAbs may also interrupt viral replication within infected cells. Developing technologies of antibody modification and functionalisation may lead to innovative biologics that harness the activities of nnAbs for antiviral prophylaxis and therapeutics. In this review, we discuss specific examples of nnAb actions in viral infections where they have known importance. We also discuss the potential detrimental effects of such responses. Finally, we explore new technologies for nnAb functionalisation to increase efficacy or introduce favourable characteristics for their therapeutic applications.

The present article addresses the long-standing problem of the polymer brush bilayers under stationary shear flow at non-linear response regime where the system gets a non-Newtonian fluid. The main idea behind this research would be the fact that the immense lubricity of the polymer brush bilayers originates from a global restructuring that takes place at large shear rates. It is shown here that physical quantities like, stress tensor, viscosity tensor, the friction coefficient and the chain extensions could become dependent on the shear rate at non-Newtonian regime. Apparently, the sub-linear scaling of the physical quantities at large shear rates is solely due to the fact that the chains stretch in the shear direction.

Over the last decades, an important number of regional and global Digital Elevation Models (DEMs) have been released publicly. As a consequence, researchers need to choose between several of these models to perform their studies and to use these DEMs as third-party data to compute derived products (e.g., for orthorectification). However, the comparison of DEMs is not trivial. For most quantitative comparisons, DEMs require to be expressed in the same Coordinate Reference System (CRS), sampled over the same grid (i.e., be at the same ground sampling distance with the same pixel-is-area or pixel-is-point convention), and with heights relative to the same Vertical Reference System (VRS). Thankfully, many open tools allow us to perform these transformations precisely and easily. Despite these rigorous transformations, local or global planimetric displacements may still be observed from one DEM to another. These displacements, or disparities, may lead to significant biases in comparisons of DEM elevations or derived products such as slope, aspect or curvature. Therefore, the control of DEM planimetric accuracy is certainly the most important task to perform at first before any comparison. This paper presents the disparity analysis method enhanced to achieve a sub-pixel accuracy, by interpolating the linear regression coefficients computed within an exploration window. This new method is significantly faster than oversampling the input data because it uses the correlation coefficients that have been already computed in the disparity analysis. To demonstrate the robustness of this algorithm, artificial displacements have been performed in a 11x11 grid with a 0.1-pixel step in both directions. The Copernicus DEM GLO-30 has been interpolated by a “classical” bicubic to achieve these 11x11 displacements. This validation method has been applied in four 10 km x 10 km DEMIX tiles showing different height distributions. Globally, this new sub-pixel accuracy method is robust. Artificial displacements have been retrieved with with typical errors (e_b) ranging from 12 to 20 % of the pixel size (worst case in Croatia).These errors in displacement retrievals are not constant in the 11x11 grid and the overall error E_b depends on the roughness (altimetry variations) encountered in the different tiles. The second idea of this paper is to assess the impact of the bicubic parameter (slope of the weight function at a distance d=1 of the interpolated point) on the accuracy of the displacement retrieval. By considering E_b as a quality indicator, tests have been performed in the four DEMIX tiles making the bicubic parameter vary between -1.5 and 0.0 by step of 0.1. For each DEMIX tile, the best bicubic (BBC) parameter b* is interpolated from the four E_b minimal values. This BBC parameter b* is low for flat areas (around -0.95) and higher in mountainous areas (around -0.75). The roughness indicator is the standard deviation of the slope norms computed from all the pixels of a tile. A logarithmic regression analysis performed between the roughness indicator and the BBC parameter b* computed in 67 DEMIX tiles shows a high correlation (r=0.717). The logarithmic regression formula estimating the BBC parameter from the roughness indicator is generic and may be applied to estimate the displacements between two different DEMs. This formula may also be used to set up a future Adaptative Best BiCubic (ABBC) that will estimate the local roughness in a sliding window to compute a local BBC.

Background: In the functional data analysis (FDA), the hybrid or mixed data are scalar and functional datasets. The semi-functional partial linear regression model (SFPLR) is one of the first semiparametric models for the scalar response with hybrid covariates. Various extensions of this model are explored and summarized. Methods: Two first research articles, including “semi-functional partial linear regression model”, and “Partial functional linear regression” have more than 300 citations in Google Scholar. Finally, only 106 articles remained according to the inclusion and exclusion criteria such as 1) including the published articles in the ISI journals and excluding 2) non-English and 3) preprints, slides, and conference papers. We use the PRISMA standard for systematic review. Results: The articles are categorized into the following main topics: estimation procedures, confidence regions, time series, and panel data, Bayesian, spatial, robust, testing, quantile regression, varying Coefficient Models, Variable Selection, Single-index model, Measurement error, Multiple Functions, Missing values, Rank Method and Others. There are different applications and datasets such as the Tecator dataset, air quality, electricity consumption, and Neuroimaging, among others. Conclusions: SFPLR is one of the most famous regression modeling methods for hybrid data that has a lot of extensions among other models.

Porous β-tricalcium phosphate (Ca3(PO4)2; β-TCP) was prepared by freeze-drying and the effects of this process on pore shapes and sizes were investigated. Various samples were prepared by freezing β-TCP slurries above a liquid nitrogen surface at −180 °C with subsequent immersion in liquid nitrogen at −196 °C. These materials were then dried under reduced pressure in a freeze-dryer after which they were sintered by heating. Compared with conventional heat-based drying, the resulting pores were more spherical, which increased both the mechanical strength and porosity of the β-TCP. These materials had a wide range of pore sizes from 50 to 200 µm, with the mean and median values both approximately 100 µm regardless of the freeze-drying conditions. Mercury porosimetry data showed that the samples contained small, interconnected pores with sizes of up to 1.24 µm and macroscopic, interconnected pores up to 25.8 µm in size. The effects of non-ionic surfactants having different hydrophilic/lipophilic balance (HLB) values on foaming and pore size were also investigated. Materials made with surfactants having lower HLB values exhibited smaller pores and lower porosity whereas higher HLB surfactants gave higher porosity and slightly larger macropores. Even so, the pore diameter could not be readily controlled solely by adjusting the HLB value. The findings of this work indicated that high porosity (75%) and good compressive strength (>2 MPa) can both be obtained in the same porous material and that foaming agents with HLB values between 12.0 and 13.5 were optimal.

This paper focuses on the problem of finite-time stabilization of homogeneous, non-Lipschitz systems with dilations. A key contribution of this paper is the design of a virtual recursive Hölder, non-Lipschitz state feedback which renders the non-Lipschitz systems in the special case dominated by a lower-triangular nonlinear system, finite-time stable. The proof is based on a recursive design algorithm developed recently, to construct the virtual Hölder continuous, finite-time stabilizer as well as a C¹ positive definite and proper Lyapunov function that guarantees finite-time stability of the non-Lipschitz non-linear systems.

Single-phase-to-ground fault in non-effectively grounded systems poses serious public safety concern. Along with increasing deployment of low-voltage (LV) sensors, new opportunities and ways are created for solving this traditional problem in distribution systems. A new approach, identifying primary single-phase-to-ground line fault and locating it through measurement data from smart sensors deployed in the secondary side of distribution transformers, is proposed in this paper. When a fault occurs in primary distribution feeder, the transient aerial mode voltage (AMV) of each LV smart sensor is calculated. The fault line can be identified by an abrupt change value of AMV at LV side. Next, by finding the position of the maximum value of this AMV from LV sensors on the fault line, the fault location can be pinpointed to two neighboring distribution transformers. The proposed method has been proven to be efficient and reliable by simulation studies.

The Zika virus (ZIKV) is a mosquito-borne Flavivirus and can be transmitted through an infected mosquito bite or through human-to-human interaction by sexual activity, blood transfusion, breastfeeding or perinatal exposure. After the 2015-2016 outbreak in Brazil, a strong link between ZIKV infection and microcephaly emerged. ZIKV specifically targets human neural progenitor cells, suggesting that proteins encoded by ZIKV bind and inactivate host cell proteins leading to microcephaly. Here, we present a systematic annotation of interactions between human proteins and the seven non-structural ZIKV proteins corresponding to a Brazilian isolate. The interaction network was generated by combining tandem-affinity purification followed by mass spectrometry with yeast two-hybrid screens. We identified 150 human proteins, involved in distinct biological processes, as interactors to ZIKV non-structural proteins. Our interacting network is composed of proteins that have been previously associated with microcephaly in human genetic disorders and/or animal models. This study builds on previously published interacting networks of ZIKV and genes related to autosomal recessive primary microcephaly to generate a catalog of human cellular targets of ZIKV proteins implicated in processes related to microcephaly in humans. Collectively, this data can be used as a resource for future characterization of ZIKV infection biology and help create a basis for the discovery of drugs which may disrupt the interaction and reduce the health damage to the fetus.

Due to the extraordinary mechanical properties of ultra-high-performance concrete (UHPC), the shear stirrups in UHPC beams could potentially be removed. The aim of this study is to determine the effect of beam height and steel fiber volume content on the shear behavior of non-stirrup UHPC beams under a larger shear span-depth ratio (up to 2.8). Eight beams were designed and fabricated, including six non-stirrup UHPC beams and two comparing stirrup-reinforced normal concrete (NC) beams. The experimental results demonstrated that the volume content of steel fiber could be a crucial factor affecting the ductility, cracking strength, and shear strength of non-stirrup UHPC beams and altering their failure modes. Additionally, the height of the beam had a considerable effect on its shear resistance. This study revealed that the French standard formulae were more accurate for the UHPC beams with larger shear span-depth ratios and PCI-2021 formulae greatly overestimate the shear capacity of UHPC beams with larger shear span-depth ratios. Xu’s formulae were more accurate for the steel fiber-reinforced UHPC beams with larger shear span-depth ratios.

Objective: To investigate fundamental movement skills (FMS) and physical activity differences among Hispanic and non-Hispanic White elementary school children. Materials and Methods: This study included 194 children aged between 4 and 11 in kindergarten, 2nd, and 5th grades. For evaluable participants, t-tests were used to test potential differences in fitness or movement skills. The characteristics of Hispanic and non-Hispanic White were compared using the p-value to detect statistical differences in anthropometric, FMS, and fitness characteristics. To identify any noticeable differences, the means and standard deviations of each group were compared. Results: There were significant group differences across the participants in age, height, Body Mass Index (BMI), BMI percentile, arm circumference, and waist circumference. In addition, there were significant differences between Hispanic and Non-Hispanic White in catch, run, dodge, punt, and two-hand strike (all p’s <0.05). Lastly, there were significant differences between Hispanic and Non-Hispanic White in pull-up, push-up, and sit-up (all p’s <0.05). Conclusion: Future studies should focus on decreasing obesity, increasing fitness, and FMS in elementary school children. Particularly, with Hispanic children whose FMS is negatively affected at such a young age, leading to eventual implications for their physical fitness and health in the future.

The Abdominal Aortic Aneurysm (AAA) is a local dilation of the abdominal aorta and it is a cause for serious concern because of the high mortality associated with its rupture. Consequently, the understanding of the phenomena related to the creation and the progression of an AAA is of crucial importance. In this work the complicated interaction between the blood flow and the AAA wall is numerically examined using a fully coupled Fluid-Structure Interaction (FSI) method. The study investigates the possible link between the dynamic behaviour of an AAA and the blood viscosity variations attributed to the haematocrit value, while it also incorporates the pulsatile blood flow, the non-Newtonian behaviour of blood and the hyperelasticity of the arterial wall. It was found that blood viscosity has no significant effect on von Mises stress magnitude and distribution, whereas there is a close relation between the haematocrit value and the Wall Shear Stress (WSS) magnitude in AAAs. This WSS variation can possibly alter the mechanical properties of the arterial wall and increase its growth rate or even its rupture possibility. The relationship between haematocrit and dynamic behaviour of an AAA can be helpful in designing a patient specific treatment.

Circulating cell-free DNA (cfDNA) refers to small fragments of DNA molecules released after programmed cell death and necrosis in several body fluids such as blood, saliva, urine, and cerebrospinal fluid. The discovery of cfDNA has revolutionized the field of non-invasive diagnostics in the oncologic field, in prenatal testing, and in organ transplantation. Despite the potential of cfDNA and the solid results published in recent literature, several challenges remain, represented by low abundance, need for highly sensitive assays and analytical issues. In this review, the main technical advances in cfDNA analysis are presented and discussed, with a comprehensive examination of the current available methodologies applied in each field. Considering the potential advantages of cfDNA, this biomarker is increasing its consensus among clinicians, as it consents to monitor patients’ conditions in an easy and non-invasive way, offering a more personalized care. Nevertheless, cfDNA analysis is still considered a research marker to be further validated, and very few centers are implementing its analysis in the real-life assistance. As technical improvements are enhancing the performances of cfDNA analysis, its application will transversally improve patients’ quality of life.

In this work, we offer a novel and accurate method in order to find the solution of the linear differential equations over the intervals [0, 1) based on the generalization of Legendre wavelets. The mechanism is still upon workable implementation of the operational matrix of integration and its derivatives. This method reduces the problems into algebraic equations via the properties of generalized Legendre wavelet (GLW) together with the operational matrix of integration. The function approximation has been picked out in such a way so as to enumerate the connection coefficients in an facile manner. The proposed numerical technique, based on the GLW, has been examined on three linear problems as a consequence of this investigation. The outcomes have shown that this method, as opposed to some other existing numerical and analytical methods, is a very useful and advantageous for tackling such problems.

German noise action plans aim to reduce negative health outcomes from noise exposure and identify quiet areas free of noise pollution. Quiet area identification in German noise action plans is based primarily on noise mapping and spatial analysis and not empirical or qualitative data about acoustic environments, thus leaving a gap in the understanding of the quality of formally recognized quiet areas in noise action plans. This work presents a comparative empirical case study in Dortmund, Germany, with the aim to describe the diurnal dB(A) and biophonic properties of quiet areas versus noise 'hot spots'. Sound observations were collected (n=282,764) in five different natural or recreational land use patch types larger than four acres within 33 proposed quiet areas in Dortmund (n=70) and 23 noise hot spots between April 27^th, 2022 and March 2^nd, 2023. We find that quiet areas are on average more than 20 dB(A) quieter than noise hot spots almost every hour of the day. Forests, managed tree stands, cemeteries, and agriculture diel patterns are dominated by dawn dusk chorus in spring and summer, whereas sport and recreation as well as noise hot spots are dominated by traffic and human noise. A novel composite biophony mapping procedure is presented that finds distinct temporal distribution of biophony in forested and agriculture peri-urban locations positively associated with patch size, distance away from LDEN > 55, proximity to water, and the number of vegetation layers in the plant community. Anthrophony distribution dominates urban land uses in all hours of the day, but expands during day and evening and contracts at night and in dusk hours. The procedures presented here illustrate how qualitative information regarding quiet areas can be integrated into German noise action planning.

The phenomenon of decreased serum uric acid (UA) levels in patients with Parkinson’s disease (PD) and its relationship with purine metabolic pathways remain unclear. We compared inosine, hy-poxanthine, xanthine, and UA levels in serum and cerebrospinal fluid (CSF) of PD patients with those of controls, and investigated the effect of changes in the purine metabolic system on UA levels in PD. Overall, 134 samples (serum, 45 PD patients and 30 controls; CSF, 39 PD patients and 20 controls), were analyzed using liquid chromatography-tandem mass spectrometry. A general linear model (GLM) was used to investigate relationships among purine metabolites. Compared to controls, PD patients had significantly lower UA levels in the serum and CSF, and serum and CSF UA levels were significantly correlated. Additionally, in PD, decreased serum hypoxanthine levels were observed with decreased CSF inosine and hypoxanthine levels, suggesting the involvement of the purine recycling system. GLM analysis indicated that the reduced UA levels in PD were mainly due to sources other than the purine metabolic system, such as exercise, nutritional indices, muscle volume, or adipose tissue. Our results highlight the impairment of purine recycling pathways in PD, as evidenced by the decreased serum hypoxanthine and CSF inosine.

In the current situation, the world is busy with technological advances, including Indonesia. Since its arrival, many business fields have competed with each other to take part as technology users. One business sector that cannot be separated from technological support is cooperatives. On the other hand, some cooperatives in the developing phase experience technological lag. At the same time, East Kutai Regency, which is the agricultural center in East Kalimantan Province, tends to rely on the cooperative sector to encourage small and medium-scale economies. This research aims to investigate the causality between access to computers (AC), internet networks (IN), digital administration skills (DAS), and financial literacy (FL) on profits (PFT). The objectivity of the study compares agricultural cooperatives that adopt technology with adopt non-technology. Using panel data regression from eighteen sub-districts in East Kutai, it is proven that technology adopting agricultural cooperatives were more prominent than non-technology adopting agricultural cooperatives during 2017–2022. However, there is a harmony in the statistical findings from both observations, where access to computers and financial literacy both have a significant effect on profits. Other analysis results show that internet networks and digital administration skills have an insignificant impact on profits. The study's implications provide valuable output for the future sustainability of agricultural cooperatives. The success of agricultural cooperatives depends greatly on the effectiveness of the application of technology.

The design of thin-walled structures is commonly based on the solutions of linear boundary-valued problems, formulated within well-developed theories for elastic plates and shells. However, in modern appliances, especially in MEMS design, it is necessary to take into account non-linear mechanical effects that become decisive for flexible elements. Among substantial non-linear effects, that significantly change the deformation properties of thin plates, are the effects of residual stresses caused by incompatibility of deformations, which inevitably arise during the manufacture of ultra-thin elements. The development of new methods of mathematical modeling of residual stresses and incompatible finite deformations in plates is the subject of the paper. To this end the local unloading hypothesis is used. It makes possible to define smooth fields of local deformations (inverse implant field) for the mathematical formalization of incompatibility. The main outcomes are field equations, natural boundary conditions and conservation laws, derived from least action principle and variational symmetries with account of implant field. The derivations were carried out in the framework of elasticity theory for simple materials and, over and above, within the Cosserat’s theory of a two-dimensional continuum. As illustrative examples the distributions of incompatible deformations in a circular plate are considered.

Non-normal mode stability analysis has long been employed to study linear transient characteristics of wall bounded shear flows. However, the application of this approach to investigate shear flows with stratified thermal conditions (STCF) has received limited attention. This paper examines thermal effects on Taylor-Couette flow. The results in this study indicate the possibility of a subcritical bifurcation in stratified Taylor-Couette flow.

Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 km² agricultural plain investigated through a dedicated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gamma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, the study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation R² = 0.879, compared to Landsat R² = 0.663. The application of supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations, manifested as a 70.3% increase in urban land, concurrently with a decrement in vegetative cover, especially 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09°C and 2.16°C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30°C and 2.24°C, with the bare land class showing the highest fluctuation 2.46°C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p &gt; 0.05 for both monthly and annual data sets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as warmest classes with 39.51°C, 38.20°C and water by 35.96°C and dense vegetation 35.52°C, sparse vegetation 37.71°C as coldest, a trend consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects.

In this study, we describe quark confinement in terms of linear interaction potentials and solve the problem of the net spin of a proton. The three quarks in a proton are assumed to revolve around a common center, and their masses are determined assuming they are Dirac particles. On the basis of these assumptions, the magnetic moment of a proton can be derived. Moreover, the rotation of the quarks is considered, in which an electrical current induces a magnetic field. Thus, the scalar product of the magnetic moment and field describes the linear interaction potential between the quarks, and the mass of the proton can be obtained. The proton mass predicted by this physical model is consistent with experimental values, and no numerical or fitting calculations are required. Furthermore, using the newly derived spins and angular momentum of the three quarks, we derived the net spin of a proton. Additionally, we predicted the mass of a pi-meson from the same model, which agrees with the experimental values.

The mixing of terrestrial groundwater and seawater creates dynamic reaction zones in intertidal areas, where land-derived Fe(II) is oxidized to Fe(III) and then precipitates as Fe hydroxides at groundwater-seawater interface. These hydrogeochemical processes contribute to the formation of iron curtains beneath soil surface, which in turn influences the evolution of coastal aquifers. This paper provides a comprehensive review of physical and geochemical processes at field scale in coastal areas, explores the impact of mineral precipitation on pore structure at pore scale, and synthesizes reactive transport modeling (RTM) approaches for illustrating continuum-scale soil physio-chemical parameters during the evolution of porous media. Upon this review, knowledge gaps and research needs are identified. Additionally, challenges and opportunities are presented. Therefore, the incorporation of observational data into a comprehensive physico-mathematical model becomes imperative for capturing the pore-scale processes in porous media and their influence on groundwater flow and solute transport at large scales. Furthermore, a synergistic approach integrating pore-scale modeling and non-invasive imaging can provide detailed insights into intricate fluid-pore-solid interactions for future studies, as well as facilitate the development of regional engineering-scale models and physio-chemical coupled models with diverse applications in submarine science and engineering.

The goal of this contribution is an application of the Linear General Model Predictive Control (LGMPC). In this paper, stability of the LGMPC is proven by means of a demonstration of a Theorem stating a sufficient and constructive condition. This condition can be applied for calculating the weight matrices of the cost function in the optimisation problem in LGMPC. Lower bounds conditions are found for one of these matrices and then a system with saturation is taken into consideration. The conditions could be interpreted and discussions through physical aspects. The obtained results were tested by means of computer simulations and an example with a recover water process is considered.

Overweight/obesity is a growing pandemic nowadays that affects many organs and tissues. We have investigated whether a high-lipid diet provokes an imbalance between type 1 and type 2 angiotensin II (Ang II) receptors signaling, leading to liver alterations associated with previously described cardiovascular and kidney disturbances. Chronic administration of a high-lipid diet can provoke an hepatocardiorenal syndrome as the result of activation of the Ang II→type 1 receptor axis, which is completely counteracted by Ang-(3–4) the allosteric enhancer of the Ang II→type 2 receptor pathway.

This paper conducts an extensive literature review focusing on the utilisation of crack tip plasticity as a crucial parameter in determining and enhancing crack growth models. The review encompasses a comprehensive analysis of various methodologies, predominantly emphasising numerical simulations of crack growth models while also considering analytical approaches. Although experimental investigations are not the focus of this review, their relevance and interplay with numerical and analytical methods are acknowledged. The paper critically examines these methodologies, providing insights into their advantages and limitations. Ultimately, this review aims to offer a holistic understanding of the role of crack tip plasticity in the development of effective crack growth models, highlighting the synergies and gaps between theoretical, experimental, and simulation-based approaches.

In this note, we provide some effective treatments of a general linear model with adding-up restrictions via algebraic operations of given vectors and matrices in the model, including analytic expressions of the well-known ordinary least-squares estimator (OLSE) and the best linear unbiased estimator (BLUE) of the unknown parameters in the model.

Tidal stream energy, due to its high level of consistency and predictability, is one of the feasible and promising type of renewable energy for future development and investment. Applicability of Blade Element Momentum (BEM) method for modeling the interaction of turbines in tidal arrays has been proven in many studies. Apart from its well-known capabilities, yet there is scarcity of research using BEM for the modeling of tidal stream energy farms considering full scale rotors. In this paper, a real geographical site for developing a tidal farm in the southern coasts of Iran is selected. Then, a numerical methodology is validated and calibrated for the selected farm by analyzing array of turbines. A linear equation is proposed to calculate tidal power of marine hydrokinetic turbines. This methodology narrows down the wide range of turbine array configurations, reduces the cost of optimization and focuses on estimating best turbine arrangements in a limited number of positions.

Predators are dependent on the capture of prey to meet their energetic and nutritive requirements, imposing a regime of predation risk. Consequently, prey experience both consumptive and non-consumptive effects. Non-consumptive effects may manifest through altered growth and ontogenetic trajectories of prey species, a dynamic modulated by olfactory or other sensory cues from predators. Bactrocera dorsalis Hendel represents a great invasive threat to global horticulture. While earlier research has primarily centered on the consumptive interactions between B. dorsalis and its natural enemies, the potential consequences of non-consumptive interactions on the development of B. dorsalis have been overlooked. In this study, we investigated the impact of predation risk effects, induced by both visual exposure to the predatory mantis Hierodula patellifera Serville and its associated odor, on the life history traits of B. dorsalis. Female B. dorsalis demonstrated reduced development time in the presence of isolated H. patellifera or H. patellifera odor, yet evidenced significantly increased fecundity. Conversely, males displayed no significant change in development time. Additionally, neither female nor male body weight at death was significantly influenced by predation risk from isolated predators or predator odor. These results indicated adaptive developmental strategies of B. dorsalis when faced with risks from predators and highlight the important role of predator odor, which has the potential to lay the groundwork for improving biological control efforts and innovative approaches within pest control.

Lots of efforts are made to optimize spectrum quality used for indoor farming to maximize artificial light utilization and reduce water loss. For such an improvement, green (G) light supplementation to a red-blue (RB) background was successfully employed in our previous studies to restrict both non-photochemical thermal dissipation (NPQ) and stomatal conductance (gs). At the same time, however, the downregulation of NPQ and gs influences the leaf temperature (Tleaf) in opposite ways. Thus, to elucidate which factor plays a more prominent role in Tleaf regulation and whether such response is temporal or permanent we investigated the correlation between NPQ or gs and the subsequent Tleaf. To this end, we analysed tomato plants (Solanum lycopersicum L. cv. Malinowy Ozarowski) grown solely under monochromatic LED lamps (435, 520, or 662 nm; 80 µmol m–2 s–1) or under mixed RGB spectrum (1:1:1; 180 µmol m–2 s–1), and simultaneously measured the gs and Tleaf with an infrared gas analyser and thermocouple or employed infrared thermal camera (FLIR) during thermal imaging analyses. Results documented that growth light quality significantly modified the Tleaf, and such response is not temporal. Furthermore, we found that plants' actual adaxial leaf surface temperature is more closely related to NPQ amplitude, while the temperature of the abaxial surface corresponds to gs.

We consider an autonomous heat engine in simultaneous contact with a hot and a cold reservoir, and described within a linear-irreversible framework. In the tight-coupling approximation, the rate of entropy generation is effectively written in terms of a single thermal flux which is a homogeneous function of the hot and cold fluxes. The specific algebraic forms of the effective flux are deduced in scenarios containing internal and external irreversibilities for the typical example of a thermoelectric generator.

The classical approach to non-linear regression in physics, is to take a mathematical model describing the functional dependence of the dependent variable from a set of independent variables, and then, using non-linear fitting algorithms, extract the parameters used in the modeling. Particularly challenging are real systems, characterised by several additional influencing factors related to specific components, like electronics or optical parts. In such cases, to make the model reproduce the data, empirically determined terms are built-in the models to compensate for the impossibility of modeling things that are, by construction, impossible to model. A new approach to solve this issue is to use neural networks, particularly feed-forward architectures with a sufficient number of hidden layers and an appropriate number of output neurons, each responsible for predicting the desired variables. Unfortunately, feed-forward neural networks (FFNNs) usually perform less efficiently when applied to multi-dimensional regression problems, that is when they are required to predict simultaneously multiple variables that depend from the input dataset in fundamentally different ways. To address this problem, we propose multi-task learning (MTL) architectures. These are characterized by multiple branches of task-specific layers, which have as input the output of a common set of layers. To demonstrate the power of this approach for multi-dimensional regression, the method is applied to luminescence sensing. Here the MTL architecture allows predicting multiple parameters, the oxygen concentration and the temperature, from a single set of measurements.

The novel coronavirus (COVID-19) was first reported in the U.S. on December 29, 2019 and has spread rapidly throughout the country, affecting individuals with varying severity due to their risk status. According to the Centers for Disease Control and Prevention, it is estimated that 45.4% of US adults are at higher risk for complications from coronavirus disease because of cardiovascular disease, diabetes, respiratory disease, hypertension, or cancer. In this study, we developed a mathematical model to assess the impact of a COVID-19 vaccine among low and high risk groups. Numerical simulations shows vaccinating both low and high risk groups simultaneously, rather than prioritizing the vaccine on high risk group only, further reduces the daily mortality. The result supports the need for an aggressive vaccination program, regardless of whether individuals are within the low or high risk population.

Stroke represents one of the neurological diseases most responsible for death and permanent disability in the world. Different factors, such as thrombus, emboli and atherosclerosis, take part in the intricate pathophysiology of stroke. Comprehending the molecular processes involved in this mechanism is crucial to developing new, specific and efficient treatments. Some common mechanisms are excitotoxicity and calcium overload, oxidative stress, and neuroinflammation. Furthermore, non-coding RNAs (ncRNAs) are critical in pathophysiology and recovery after cerebral ischaemia. ncRNAs, particularly microRNAs, and the long non-coding RNAs (lncRNAs) are essential for angiogenesis and neuroprotection, and they have been suggested to be therapeutic, diagnostic and prognostic tools in cerebrovascular diseases, including stroke. This review summarizes the intricate molecular mechanisms underlying ischemic and hemorrhagic stroke and delves into the function of miRNAs in the development of brain damage. Furthermore, we will analyze new perspectives on treatment based on molecular mechanisms in addition to traditional stroke therapies.

Let $n \geq 2$ be a fixed integer and $\mathcal{A}$ be a $C^*$-algebra. A permuting $ n $-linear map $ \mathcal{G} : \mathcal{A} ^{n} \rightarrow \mathcal{A} $ is known to be symmetric generalized $n$-derivation if there exists a symmetric $n$-derivation $ \mathfrak{D} : \mathcal{A} ^{n} \rightarrow \mathcal{A} $ such that $ \mathcal{G} \left(x_{1}, x_{2}, \ldots, x_{i} x_{i}^{\prime}, \ldots, x_{n}\right)= \mathcal{G} \left(x_{1}, x_{2}, \ldots, x_{i}, \ldots, x_{n}\right) x_{i}^{\prime}+x_{i} \mathfrak{D} (x_{1}, x_{2},\ldots, x_{i}^{\prime}, \ldots, x_{n})$ holds for all $x_{i}, x_{i}^{\prime} \in \mathcal{A} $. In this paper, we investigate the structure of $C^*$-algebras involving generalized linear $n$-derivations. Moreover, we describe the forms of traces of linear $n$-derivations satisfying certain functional identity.

The Energy Performance of Buildings Directive 2010 calls for the Nearly Zero Energy Standard for new buildings from 2021 onwards: Buildings using “almost no energy” are powered by renewable sources or energy produced by the building itself. For residential buildings, this ambitious new standard has already been reached. But for other building types this goal is still far away. The potential of these buildings to meet a Nearly Zero Energy Standard was investigated by analyzing ten case studies representing non-residential buildings with different uses. The analysis shows that the primary characteristics common to critical building types are a dense building context with a very high degree of technical installation (such as hospital, research and laboratory buildings). The large primary energy demand of these types of buildings cannot be compensated by building and property-related energy generation including off-site renewables. If the future Nearly Zero Energy Standard were to be defined with lower requirements because of this, the state related properties of Bavaria suggest that the real potential energy savings available in at least 85% of all new buildings would be insufficiently exploited. Therefore, it would be useful to instead individualize the legal energy verification process for new buildings to distinguish critical building types such as laboratories and hospitals.

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common break point even when the change happens immediately after the first time point or just before the last observation period. Another advantage of the elaborated change point estimator is that it results in the last observation in situations with no structural breaks. The consistency of the change point estimator in panel data is established. The results are illustrated through a simulation study. As a by-product of the developed estimation technique, a theoretical utilization for correlation structure estimation, hypothesis testing, and bootstrapping in panel data is demonstrated. A practical application to non-life insurance is presented as well.

In response to the growing inspection demand exerted by process automation in component manufacturing, Non-destructive testing (NDT) continues to explore automated approaches that utilize deep learning algorithms for defect identification, including within digital X-ray radiography images. This necessitates a thorough understanding of the implication of image quality parameters on the performance of these deep learning models. This study investigates the influence of two image quality parameters, namely Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), on the performance of U-net deep learning segmentation model. Input images were acquired with varying combinations of exposure factors such as kilovoltage, milli-ampere, and exposure time, which altered the resultant quality. The data was sorted into 5 different datasets according to their measured SNR and CNR values. The deep learning model was trained 5 distinct times, utilizing a unique dataset for each training session. Training the model with high CNR values yielded an intersection over Union (IoU) metric of 0.9594 on test data of the same category but drops to 0.5875 when tested on lower CNR test data. The result in this study emphasizes the importance of achieving a balance in training dataset according to the investigated quality parameters, to enhance the performance of deep learning segmentation models in NDT radiography applications.

In this paper, we present a framework to study the spatial structure of noctilucent clouds formed by ice particles in the upper atmosphere at mid and high latitude during summer. We study noctilucent cloud activity in optical images taken from three different locations and under different atmospheric conditions. In order to identify and distinguish noctilucent cloud activity from other objects in the scene, we employ linear discriminant analysis (LDA) with feature vectors ranging from simple metrics to higher-order local autocorrelation (HLAC), and histogram of oriented gradients (HOG). Finally, we propose a Convolutional Neural Networks (CNN) based method for the detection of noctilucent clouds. The results clearly indicate that the CNN based approach outperforms LDA based methods used in this article. Furthermore, we outline suggestions for future research directions to establish a framework that can be used for synchronizing the optical observations from ground based camera systems with echoes measured with radar systems like EISCAT in order to obtain independent additional information on the ice clouds.