Hamman’s syndrome is a rare condition that mostly affects young males, often with a predisposition of asthma. It includes the presence of free air in the mediastinum and subcutaneous emfysema with no other underlying cause such as trauma or infection. It occurs spontanously and often in association with prolonged valsalva manouvre. This might explain why there are some cases of Hamman syndrome among young females giving birth. Here we present a case report of a 24-year- old primigravida with Hamman’s syndrome. She presented with symptoms a few hours after an uncomplicated vaginal delivery at 40+1 pregnancy week. The symptoms resolved spontanously after a few days of observation. We also give a systemic review of reported cases since 2000 to provide overview on pathomechanism, symptoms, diagnostics, treatment and management of this condition. Hamman’s syndrome is a rare, usually benign, but potentially serious complication that can occur during the second stage of labour. Diagnostics include inquiring about typical symptoms, clinical examination and chest x-ray or CT scan. Treatment is usually conservative with oxygen, bronchodilators and pain relief. The reccurence rate is low and there is no contraindication to vaginal delivery in future pregnancies. However, it is suggested that physicians and midwives be cautious and consider low threshold for instrumental delivery or caesarean section to avoid excessive valsalva manoeuvre.

The Shule River Basin (SRB) is a typical arid area in northwest China with a fragile ecology. Un-derstanding vegetation dynamics and its response to climate change and human activities provides essential information for ecological and environmental resource management. This study extracted fractional vegetation coverage (FVC) data from 2000 to 2019 using the Google Earth Engine plat-form and Landsat satellite images, employing trend analysis and other methods to examine spati-otemporal changes in vegetation in the SRB. Additionally, partial correlation and residual analysis were utilized to explore the response of FVC to climate change and human activities. The main results were as follows: (1) The regional average FVC in the SRB showed a significant upward trend from 2000 to 2019, increasing by 1.3 × 10−3 y–1. The area within 1 km of roads experienced a higher increase of 3 × 10−3 y–1, while the roadless areas experienced a lower increase of 1.1 × 10−3 y–1. Road construction from 2004 to 2006 significantly reduced the FVC within 200 meters of the roads. FVC spatial heterogeneity in the SRB is significant. (2) Partial correlation analysis shows that FVC has a strong positive correlation with precipitation and surface water area, with correlation coefficients of 0.575 and 0.744, respectively. There is a weak negative correlation between FVC and land surface temperature (LST). FVC changes are more influenced by precipitation than by LST. (3) Compared to climate factors, human activities have a greater impact on vegetation dynamics in the SRB. The contributions of climate change to vegetation recovery are increasing. (4) The area changes of dif-ferent land types are closely related to climate factors and human activities, reflecting their impact on vegetation. These results provide valuable information for ecosystem restoration and environ-mental protection in the SRB.

Teledermatology, the dermatological consultation and diagnosis via digital communication technologies, has become increasingly important in modern healthcare. The integration of teledermatology into clinical practice has gained significant interest, especially during the COVID-19 pandemic. Numerous studies have shown the effectiveness and reliability of teledermatology, with high levels of patient satisfaction and diagnostic accuracy. Pathpoint® eDerma is a cloud-based dermatology platform that aims to streamline the documentation and management of dermatological conditions. It offers several clinical benefits, including faster diagnosis, reduced unnecessary procedures, improved access to care, and cost savings. The platform follows a comprehensive risk management plan and complies with safety regulations. It undergoes regular recertification and reviews to ensure its safety and effectiveness. The clinical evaluation of eDerma confirms its ability to deliver significant clinical benefits while effectively mitigating risks. The benefit-risk ratio of eDerma is highly acceptable, supporting its use in clinical settings to enhance dermatological care.

The Interdisciplinary Canadian Collaborative ME Research Network (ICanCME), established in 2019, aims to foster research in Canada and contribute to finding the causes and possible treatments for myalgic encephalomyelitis /chronic fatigue syndrome (ME/CFS), thereby reducing the impact of ME/CFS on the health of Canadians. The main objectives of this paper are to suggest standards for ME/CFS research for the collection of data from participants (Recommended Data Elements) and to consider other factors, such as design, language, cultural issues, equity, and diversity. Consensus of the relevant contents of this research guideline was reached during the ICanCME working group meetings and were based on existing guidelines. Members of the working group contributed to guideline development based on their respective expertise. The proposed research guidelines could improve research quality and advance knowledge in the field of ME/CFS, and ultimately benefit ME/CFS patients.

Almost contact complex Riemannian manifolds, known also as almost contact B-metric manifolds, are equipped with a pair of pseudo-Riemannian metrics that are mutually associated with each other using the tensor structure. Here we consider a special class of these manifolds, those of the Sasaki-like type. They have an interesting geometric interpretation: the complex cone of such a manifold is a holomorphic complex Riemannian manifold (also called a Kähler–Norden manifold). The basic metric on the considered manifold is specialized here as a soliton, i.e. has an additional curvature property such that the metric is a self-similar solution of an intrinsic geometric flow. Almost solitons are more general objects than solitons because they use functions rather than constants as coefficients in the defining condition. A β -Ricci-Bourguignon-like almost soliton ( β is a real constant) is defined using the pair of metrics. The introduced soliton is a generalization of some well-known (almost) solitons (such as those of Ricci, Schouten, Einstein), which in principle arise from a single metric rather than a pair of metrics. The soliton potential is chosen to be pointwise collinear to the Reeb vector field, or the Lie derivative of any B-metric along the potential to be the same metric multiplied by a function. The resulting manifolds equipped with the introduced almost solitons are characterized geometrically. Appropriate examples for two types of almost solitons are constructed and the properties obtained in the theoretical part are confirmed.

It is challenging to precisely measure the slow interseismic crustal deformation rate from SAR data. The long-wavelength orbital errors, owing to the uncertainties in satellite orbit vectors, commonly exist in SAR interferograms, which degrade the precision of the InSAR products and become the main barrier of extracting interseismic tectonic deformation. In this study, we propose a novel temporal network orbital correction method that is able to isolate the far-fault tectonic deformation from the mixed long-wavelength signals based on its spatio-temporal characteristic. The proposed approach is straightforward in methodology but could effectively separate the subtle tectonic deformation from glaring orbital errors without ancillary data. Both synthetic data and real Sentinel-1 SAR images are used to validate the reliability and effectiveness of this method. The derived InSAR velocity fields clearly present the predominant left-lateral strike-slip motions of the Tuosuo Lake segment of the Kunlun fault in western China. The fault-parallel velocity differences of 5-6 mm/yr across the fault between areas ~50 km away from the fault trace are addressed. The proposed method presents significantly different performance from traditional quadratic approximate method in the far-field. Through the implementation of the proposed method, the RMSE between the LOSGPS and our derived descending InSAR LOS is reduced to less than one-third of the previous study, suggesting its potential to enhance the availability of InSAR technology for interseismic crustal deformation measurement.

New advances in creating effective and affordable copper-based catalysts for water splitting represent a promising strategy for driving sustainable energy technologies. However, ma- terials containing copper are susceptible to corrosion and agglomeration. In this study, we describe a synthesis route to produce olamine-functionalized CuO nanoparticles using the Hot Injection method. Nanoparticles were obtained and subsequently deposited on FTO substrates, undergoing thermal treatment at 500°C and 600°C in atmospheres containing O2 and N2, aiming to enhance the adhesion of the active material to the substrate and modify its oxidation state. Microstructural properties were analyzed using XRD, SEM, and TEM, while electrochemical properties were studied using CV, LSV, and EIS. Electrodes treated thermally in an N2 atmosphere at 600°C exhibited higher ESCA, indicating a greater area of active sites exposed to surface reactions and, therefore, superior catalytic activity in Hy- drogen Evolution Reaction (HER). These findings show an interesting strategy for avoiding rapid electron-hole recombination and, consequently, CuO corrosion. For Oxygen Evolution Reaction (OER), samples treated thermally in O2 atmosphere at 500°C and 600°C appear to be more effective.

Background Neisseria gonorrhoeae can acquire antimicrobial resistance (AMR) through horizontal gene transfer (HGT) from other Neisseria spp. such as commensals like Neisseria subflava. The prevalence of Neisseria subflava in the oropharynx is close to 100%. Low doses of antimicrobials in food could select for AMR in N. subflava, which could then be transferred to N. gonorrhoeae. In this study, we aimed to determine the lowest concentration of ciprofloxacin that can induce ciprofloxacin resistance (minimum selection concentration – MSC) in N. subflava. Methods Neisseria subflava Co000790/2 was serially passaged on GC agar plates containing ciprofloxacin concentrations ranging from 1:100- to 1:10,000-below its ciprofloxacin MIC (0.006 µg/ml) for six days. Results After 6 days of serial passaging at ciprofloxacin concentrations 1/100th of the MIC, 24 colonies emerged on the 0.06 µg/ml ciprofloxacin plate. Their ciprofloxacin MICs were between 0.19 to 0.25 µg/ml, and whole genome sequencing revealed a missense mutation T91I in the gyrA gene, which has previously been found to cause reduced susceptibility to fluoroquinolones. Conclusion The N. subflava MSCde novo was determined to be 0.06 ng/mL or 1:100 below the MIC. The implications of this finding are that the low concentrations of antibiotics found in certain environmental samples and even the food we eat may be able to select for ciprofloxacin resistance in N. subflava.

Vinyltriethoxysilane (VTES) was covalently bonded onto graphene oxide. Several methods, including X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and X-ray diffraction, were used to demonstrate the presence of VTES on the surface of graphene oxide and the creation of this covalent link. Following that, different quantities of the resultant vinyltriethoxysilane functionalized graphene oxide (VTESFGO) were mixed with polyvinyl alcohol (PVA) to form VTESFGO/PVA nanocomposite films (NCFs) with a 3-dimensional network structure. The creation of these NCFs and the presence of a three-dimensional network were confirmed by Fourier transform infrared spectroscopy. The three-dimensional network structure provided these NCFs extraordinary characteristics. The mechanical and thermal stability, oxygen transfer rate (OTR), and water resistance pressure (WRP) of the NCFs were investigated. The nanocomposite film (NCF) with the highest weight percentage of VTESFGO (3.0 wt.%) was 47.5% more thermally stable than pure PVA, with an oxygen transmission rate of 0.3 cm3/m2 per day and a water resistance pressure of 780 mm/cm2. However, as the weight percentage of VTESFGO increased, the mechanical strength of the NCFs decreased as a result of silanol self-condensation, resulting in particulate formation, as confirmed by scanning electron microscopy.

Infill well location optimization poses significant challenges due to its complexity and time-consuming nature. Currently, determining the scope of infill wells relies heavily on field engineers' experience, often using single indices such as remaining oil saturation or abundance of remaining oil reserves to evaluate the potential of remaining oil. However, this approach lacks effectiveness in guiding the precise tapping of remaining oil in ultra-high water cut reservoirs. To address this, our study comprehensively considers factors influencing the recoverable potential of remaining oil in such reservoirs. We characterize differences in reservoir heterogeneity, the scale of recoverable remaining oil reserves, water flooding conditions, and oil-water flow capacity to construct a quantitative evaluation index system for the recoverable potential of remaining oil. Recognizing the varying degrees of influence of different indices on the recoverable potential of remaining oil, we determine the objective weight of each evaluation index by combining an accelerated genetic algorithm with the projection pursuit model. This approach enables the construction of a recoverable potential index for remaining oil and forms a quantitative evaluation method for the recoverable potential of remaining oil in ultra-high water cut reservoirs. Subsequently, we establish a mathematical model for infill well location optimization, integrating and optimizing infill well location coordinates, well length, well inclination angle, and azimuth angle. Using the main layer sand body of an oilfield in Bohai as a case study, we conducted evaluations of remaining oil potential and infill well location optimization. Results demonstrate that the assessment of remaining oil potential comprehensively characterizes the influence of reservoir physical properties and oil-water diversion capacity on remaining oil potential across different regional positions. This evaluation can effectively guide the determination of infill well location ranges based on the evaluation results. Furthermore, further optimization of infill well locations can effectively enhance reservoir development outcomes.

Aiming at the problem of small size of some spots on apple leaves and the difficulty of accurate detection of spot targets brought by the complex background of the orchard, this paper takes the alternaria leaf spot, rust, brown spot, grey spot and frog eye leaf spot on apple leaves as the research object, and proposes a high-accuracy detection model YOLOv5-Res and lightweight detection model YOLOv5-Res4 are proposed. Firstly, a multiscale feature extraction module ResBlock is designed by combining the Inception multi-branch structure and ResNet residual idea. Secondly, a lightweight feature fusion module C4 is designed to reduce the number of model parameters while improving the detection ability of small targets. Finally, a parameter streamlining strategy based on optimized model architecture is proposed. The experimental results show that the performance of YOLOv5-Res model and YOLOv5-Res4 model is significantly improved, the [email protected] value is improved by 2.8% and 2.2% compared with YOLOv5s model and YOLOv5n model, respectively, and the size of YOLOv5-Res model and YOLOv5-Res4 model is only 10.8MB and 2.4MB, and the number of model parameters is reduced compared with YOLOv5s model and YOLOv5n model. counts are reduced by 22% and 38.3% compared to the YOLOv5s model and YOLOv5n model.

This paper addresses the cosmological constant problem, a significant discrepancy highlighted by \cite{Weinberg:1988cp} that underlines a fundamental inconsistency between quantum field theory (QFT) and general relativity (GR). QFT examines matter dynamics within Lorentzian spacetime under standard model symmetry, while GR uses Riemannian geometry but adapts it to ensure local Lorentzian behavior in small regions. Despite the experimental successes of both theories, a major challenge exists in theoretical understanding. This letter seeks to clarify this critical misunderstanding. As the universe cools from its hot beginning, the \(SU(3) \times SU(2) \times U(1)\) standard model gauge symmetry evolves. This symmetry breaks to \(SU(3) \times U(1)\) upon cooling at the electroweak scale and ultimately to \(SU(3)\) alone as temperatures approach near-absolute zero kelvin, facilitated by the experimental Meissner effect. This suggests that \(SU(3)\) symmetry forms the foundational "atoms" of vacuum energy. Calculating the number of \(SU(3)\) vacuum atoms across the universe results in a value that perfectly aligns the theoretical predictions with the observed vacuum energy densities, thereby resolving the cosmological constant problem. Since \(SU(3)\) atoms account for the cosmological constant, they must be unbreakable. The third law of thermodynamics, which states that it is impossible to reach absolute zero Kelvin, provides the protection that prevents SU(3) atoms from breaking at zero Kelvin. This reveals the connection between the third law of thermodynamics and the quark confinement. This leads to the \(SU(3)\) atom creating a mass gap within the universe. This solution serves as a symmetric evidence of gauge-gravity duality as well as gravity-superconductor duality.

The current 2019-2021 marine pharmacology literature review provides a continuation of previous reviews covering the period 1998 to 2018. Preclinical marine pharmacology research during 2019-2021 was published by researchers in 42 countries and contributed novel mechanism of action pharmacology for 171 structurally characterized marine compounds. The peer-reviewed marine natural products pharmacology literature reported antibacterial, antifungal, antiprotozoal, antituberculosis,and antiviral mechanism of action studies for 49 compounds, 87 compounds with antidiabetic and anti-inflammatory activities as well as affecting the immune and nervous system, while another group of 51 compounds demonstrated novel miscellaneous mechanisms of action, which upon further investigation, may contribute to several pharmacological classes. Thus, in 2019-2021, a very active preclinical marine natural product pharmacology pipeline provided novel mechanism of actions as well as new lead chemistry for the clinical marine pharmaceutical pipeline targeting the therapy of several disease categories.

As cardiovascular diseases continue to be a leading cause of mortality, recent-ly, wearable devices for monitoring cardiac activity have gained much interest among medical community. This paper introduces an innovative ECG monitoring system based on a single – lead ECG machine enhanced with machine learning methods. The system only processes and analyses the ECG data, but also predict potential heart disease at an early stage. The wearable device was built on the ADS1298 and a microcontroller STM32L151xD. A server module based on REST API architecture style was designed to fa-cilitate interaction with web-based segment of the system. The module is responsible for receiving data in real time from microcontroller and their deliver to web – based segment. Algorithms for analyzing ECG signals have been developed, including band filter artifact removal, K-means clustering for signal segmentation, and PQRST analysis. Machine leaning methods as Isolation Forest have been employed for ECG anomaly detection. Moreover, a comparative analysis with various machine learning methods, including lo-gistic regression, random forest, SVM, XGBoost, decision forest and, CNNs was conducted to predict cardiovascular diseases. Convoluted Neural Networks (CNN) showed an accu-racy of 0.926, proving high effectiveness in ECG data process.

Tryptophan, an essential amino acid in mammals obtained from the diet, is influenced by maternal diet, which impacts early life and development of offspring. This is studied under the Developmental Origins of Diseases and Health (DOHaD) concept, so factors from conception to early childhood affect health and disease susceptibility. Tryptophan is metabolized mainly through two pathways: serotonin (5-HT) and kynurenine. The kynurenine pathway, active in the brain, gut, liver, and placenta, breaks down over 95% of tryptophan and plays roles in inflammation, neurotransmission, immune responses, and immune modulation during pregnancy. The serotonin pathway uses up to 5% of Tryptophan, mainly in the gut, adipose tissues, pancreatic cells, and central nervous system, and regulates responses to environmental changes, including sleep, cognition, and feeding behavior. Key enzymes in these pathways include Trp-2,3-dioxygenase (TDO), indoleamine-2,3-dioxygenase (IDO) type1 (IDO1), and type 2 (IDO2) (kynurenine pathway), and tryptophan hydroxylase type 1 (TPH1) and type 2 (TPH2), serotonin pathway. The fetus-placental unit manages tryptophan metabolism. Serotonin and kynurenine are crucial for placental health and fetal development. Serotonin adjusts placental blood volume and aids neurodevelopment. Kynurenine metabolites protect the fetus from maternal immunity and offer initial neuroprotection. At birth, infants switch from placental nutrients to breast milk, rich in tryptophan and protective bioactive molecules. Tryptophan, solely from breast milk, is crucial for infants. Its levels are high in newborns (first three weeks, 2-4 times higher than in adults), gradually declining to adult levels by the fourth week. The highlights the importance of tryptophan for the serotonin and kynurenine pathways in fetuses, newborns and babies applied to the DOHaD concept.

Grey mullets comprise different species which represent the most ubiquitous teleost families in the planet coastal waters. They represent an important proportion of the Mediterranean lagoons production and have been recently considered a cultivated marine fish. This study aimed to explore the intestinal bacterial communities of 34 wild-caught grey mullets in order to study their composition and the variation during different seasons. Thirty four healthy wild-caught fish were sampled and the V3-V4 hypervariable regions of 16S rRNA were sequenced. Sixty prokaryotic phyla were identified and the most abundant ones were: Proteobacteria (mean relative abundance 35.4%±17.9), Actinobacteriota (mean relative abundance 16.4%±9.9) and Firmicutes (mean relative abundance 10.1%±10.9). Bacteria belonging to the phylum Chloroflexi were rele-vant in autumn, Spirochaetota, Verrucomicrobiota, Fusobacteriota and Cyanobacteria were particularly abundant in winter while Bacteroidota characterized summer fish. A total of three hundred thirty-two prokaryotic families were identified and the twenty-six most abundant ones were: Rhodociclaceae (Proteobacteria), Brevinemataceae (Spirocheaetota) and Fusobacteriaceae (Fusobacteriota) and the Staphylococcaceae (Firmicutes). This study sheds light on the ecology and high variation in the complex gut microbial community structure of Mediterranean grey mullets, the potential biotechnological role for fish nutrition and health and for preserving the aquatic habitat, a prerequisite for a sustainable aquaculture.

Fluidized beds are pivotal in the process industry and chemical engineering, with Computational Fluid Dynamics (CFD) playing a crucial role in their design and optimization. Challenges in CFD modeling stem from the scarcity or inconsistency of experimental data for validation, along with the uncertainties introduced by numerous parameters and assumptions across different CFD codes. This study navigates these complexities by comparing simulation results from the open-source MFIX and OpenFOAM, and the commercial ANSYS FLUENT, against experimental data. Utilizing a Eulerian-Eulerian framework and the kinetic theory of granular flow (KTGF), the investigation focuses on solid-phase properties through the classical drag laws of Gidaspow and Syamlal-O’Brien across varied parameters. Findings indicate that ANSYS Fluent, MFiX, and OpenFOAM can achieve reasonable agreement with experimental benchmarks, each showcasing distinct strengths and weaknesses. The study also emphasizes that both the Syamlal-O’Brien and Gidaspow drag models exhibit reasonable agreement with experimental benchmarks across the examined CFD codes, suggesting a moderated sensitivity to the choice of drag model. Moreover, the analysis were also carried out for 2D and 3D simulations, revealing that the dimensional approach impacts the predictive accuracy to a certain extent, with both models adapting well to the complexities of each simulation environment. The study highlights the significant influence of restitution coefficients on bed expansion due to their effect on particle-particle collisions, with a value of 0.9 deemed optimal for balancing simulation accuracy and computational efficiency. Conversely, the specularity coefficient, impacting particle-wall interactions, exhibits a more subtle effect on bed dynamics. This finding emphasizes the critical role of carefully choosing these coefficients to effectively simulate the nuanced behaviors of fluidized beds.

Objective: Daratumumab (Dara) is the first-in-class human-specific anti-CD38 mAb approved for treating multiple myeloma (MM). However, DARA-induced depletion of CD38high natural killer (NK) cells results in crippled antibody-dependent cellular cytotoxicity (ADCC), which limits its clinical detection and prediction for Dara efficacy. Therefore, we aimed to explore new NK subsets that could predict Dara efficacy and the underlying mechanism in Dara development. Methods: Multicolour spectral flow cytometry monitored changes in the immune cells of 13 paired RRMM patients. We used machine learning-driven clustering, FlowSOM (Flow Self-Organizing Maps), and dimensional reduction with tSNE (t-distributed Stochastic Neighbour Embedding) to identify unique cell populations pre- and posttreatment. Then, in vitro, fratricide and proliferation assays were performed to explore the function of new NK subsets against MM under Dara treatment. Results: The NK cells were divided into 25 subsets, among which we found that the percentages of KIR-NKP46+ NK cells decreased in paired RRMM patients compared to healthy controls but increased significantly post-Dara treatment. The fold change in KIR-NKP46+ after one dose of Dara treatment can predict whether the best response could be achieved within one month (ROC=0.86, p=0.011). Further in vitro experiments showed that KIR-NKP46+ NK cells are superior to KIR+ NK cells, cooperatively acting with daratumumab to sustainably eradicate MM cells. Meanwhile, apoptosis was significantly decreased, and the proliferation ability was relatively increased post-Dara treatment. Conclusion: In conclusion, the fold change in KIR-NKP46+ NK cell subsets after one dose of Dara treatment can predict the outcome of the curative effect, indicating a putative role of KIR-NKP46+ subsets against MM cells. The mechanism attributed to a relative expansion of the subset due to decreased apoptosis and increased proliferation ability.

Coronavirus disease 2019 (COVID-19) continues to cause morbidity and mortality worldwide; therefore, effective treatments remain crucial to controlling it. As interferon-alpha (IFN-α) and -beta (β) have been proposed as COVID-19 treatments, we sought to assess their effectiveness on respiratory, cardiovascular, neurological, and psychiatric signs and symptoms, as well as PASC and death, in hospitalized COVID-19 patients without multiple sclerosis (MS). Using a federated data research network (TriNetX), we performed a retrospective cohort study of hospitalized COVID-19 patients without MS who received IFN-α or -β treatment, comparing them to a similar cohort who did not receive treatment. Following propensity score-matched analyses, we demonstrate that hospitalized COVID-19 patients who were treated with IFN-α or -β had significantly higher odds of death. In contrast, there was no significant difference in any other outcomes between 1-30 days or 1 day to anytime afterward. Overall, hospitalized COVID-19 patients without MS who were treated with IFN-α or -β had similar short- and long-term sequelae (except for mortality) as those who did not receive treatment. The potential benefits of utilizing IFN-α or -β treatment as therapeutics remain to be realized, and our research highlights the need to explore repurposing drugs for COVID-19 using real-world evidence.

This study investigates the transformative impact of ChatGPT, a cutting-edge AI language model developed by OpenAI, on the financial sector. We explore ChatGPT's applications in financial analysis, focusing on its ability to perform tasks traditionally handled by human analysts. By creating a set of multi-step and advanced reasoning financial tasks, and establishing several task-specific evaluation metrics, our experimental results demonstrate that ChatGPT-4o can effectively perform both basic and some complex financial analysis tasks comparable to those executed by humans. However, our empirical evaluation reveals limitations in its performance on complex tasks that require comprehensive understanding and critical thinking. The study highlights the necessity for meticulous task formulation and robust evaluation to achieve consistent functionality. While ChatGPT enhances efficiency in financial analysis, its integration with human expertise remains crucial for effective decision-making. This study contributes to the understanding of AI's role in finance and provides insights into its potential and constraints, guiding future integration of AI technologies in financial practices.

We have investigated the influence of the relative proportions of glass formers in a series of lithium alumino-borosilicate glasses with respect to electrical conductivity () and glass transition temperature (Tg) as functions of glass structure, as determined by Raman spectroscopy. The ternary lithium alumino-borate glass exhibits the highest  and lowest Tg among all the compositions of the glass series, 30Li2O•3Al2O3• (67-x) B2O3•xSiO2. However, as B2O3 is replaced by SiO2, a shallow minimum in  as well as a shallow maximum in Tg are observed near x = 27, where the Raman spectra indicate isolated diborate/tetraborate/orthoborate groups are being progressively replaced by danburite/reedmergnerite-like borosilicate network units. Overall, as the glasses become silica-rich,  is minimized, while Tg is maximized. In general, these findings show correlations among Tg, (sensitive to network polymerization),  (proportional to ionic mobility), and the different borate and silicate glass structural units as determined by Raman spectroscopy. X-ray diffraction analyses demonstrate the absence of appreciable crystallinity in the glasses investigated. However, scanning electron microscopy (SEM) images of HF-etched samples showed that glasses, and especially the borate-rich compositions comprise two distinct glassy phases. The isolated phase is 25-100 nm in diameter, dispersed evenly in a glassy matrix.

The electronic properties of calcium intercalated graphite (CaC6) as a function of pressure are revisited using density functional theory (DFT). The electronic band structures of CaC6, like many other layered superconducting materials, display cosine-shaped bands at or near the Fermi level (FL). Such bands encompass bonding/antibonding information with a strong connection to superconducting properties. Using an hexagonal cell representation for CaC6, construction of a double supercell in the c-direction effects six-folding in reciprocal space of the full cosine function, explicitly revealing the bonding/antibonding relationship divide at the cosine midpoint. Similarly, folding of the Fermi surface (FS) reveals physical phenomena relevant to electronic topological transitions (ETT) with application of pressure. For CaC6, the peak value for the superconducting transition temperature, Tc, occurs at about 7.5 GPa, near to the observed pressure of the calculated ETT. At this pressure, the radius of the nearly spherical Ca 4s-orbital FS coincides with three times the distance from the G centre point to the Brillouin zone (BZ) boundary of the 2c supercell (which is equal to half the identically defined distance for the primitive rhombohedral BZ). In addition, the ETT coincides with alignment of the non-bonding (inflection) point of the cosine band (the point at which the sign of the cosine amplitude modulation is reversed) with the FL. At other calculated pressure conditions, the Ca 4s-orbital FS undergoes topological changes that correspond and can be correlated to experimentally determined changes in Tc. The ETT is a key mechanism that circumscribes the known significant drop in Tc for CaC6 as a function of increasing pressure.

Accurate forecasting of crop yields holds paramount importance in guiding decision-making processes related to breeding efforts. This study focused on the application of multi-sensor data fusion and machine learning algorithms based on unmanned aerial vehicles (UAVs) in wheat yield prediction. Five machine learning (ML) algorithms namely random forest (RF), partial least squares (PLS), ridge regression (RR), K-Nearest Neighbor (KNN) and eXtreme Gradient Boosting Decision Tree (XGboost) were utilized for multi-sensor data fusion, and three ensemble methods including the second-level ensemble methods (stacking and feature-weighted) and the third-level ensemble method (simple average) for wheat yield prediction. The 270 wheat hybrids were used as planting materials under full and limited irrigation treatments. A cost-effective multi-sensor UAV platform, equipped with red–green–blue (RGB), multispectral (MS), and thermal infrared (TIR) sensors, was utilized to gather remote sensing data. The results revealed that the XGboost algorithm exhibited outstanding performance in multi-sensor data fusion, with the RGB+MS+Texture+TIR combination demonstrating the highest fusion performance (R2=0.660, RMSE= 0.754). Compared with the single ML model, the employment of three ensemble methods significantly enhanced the prediction accuracy of wheat yield. Notably, the third-layer simple average ensemble method demonstrated superior performance (R2 = 0.733, RMSE= 0.668 t ha-1). It significantly outperformed both the second-layer ensemble methods of Stacking (R2= 0.668, RMSE= 0.673 t ha-1) and feature-weighted (R2= 0.667, RMSE= 0.674 t ha-1), thereby exhibiting superior predictive capabilities. This finding demonstrated that the third-layer ensemble method not only augments the predictive ability of the model but also fine-tuned the accuracy of wheat yield prediction through the employment of simple average ensemble learning. Consequently, it offers a novel perspective for crop yield prediction and breeding selection.

The present article describes the synthesis of an isonicotinate-derived meso-arylporphyrin, that has been fully characterized by spectroscopic methods (including fluorescence spectroscopy), as well as by elemental analysis and by HR-MS. The structure of a n-hexane monosolvate has been determined by single crystal X-ray diffraction analysis. The radical scavenging activity of this new porphyrin against the 2,2-diphenyl-1-picrylhydrazyl (DDPH) radical has been measured. Its antifungal activity against three yeast strains (C. albicans ATCC 90028, C. glabrata ATCC 64677 and C. tropicalis ATCC 64677) has been tested, using the disk diffusion and the microdilution methods. Whereas the measured antioxidant activity was low, the porphyrin showed moderate but encouraging antifungal activity. Finally, a study of its effect on the germination of lentil seeds revealed interesting allelopathic properties.

Entanglement is one of the most striking features in quantum systems. Today, quantum entanglement plays a vital role in quantum technology, the non-classical correlation of quantum entanglement is an important resource for quantum communication and quantum computing. Entanglement can be divided into two categories: between multi-particle systems and between various degrees of freedom in a single-particle system (intraparticle entangled states). This work first analogized the distinctions and connections between two kinds of entangled states. Then it designed three types of entanglement-swapping methods based on Bell state joint measurement, cross-Kerr medium, and linear optical elements for intraparticle entangled states by analogizing the entanglement swapping between multiple particles. Intraparticle entanglement swapping can be applied in super quantum dense encoding, quantum information transmission, and quantum teleportation. This work is beneficial for promoting the development of quantum information technologies.

Citrus fruits are extensively cultivated worldwide, with Italy and Spain being major producers. Southern Italy, particularly in Reggio Calabria, a typical citrus fruit is produced, namely, bergamot (Citrus bergamia Risso et Poiteau), known for its mysterious origins and exceptional quality essential oil protected by the EU's PDO designation. Despite historical challenges, bergamot has regained prominence for its nutraceutical potential, especially its flavonoid-rich juice, offering significant health benefits. However, little attention has been paid to understanding the qualitative and quantitative differences of bergamot juice in Calabrian production areas. For this reason, this work aims to investigate the quality characteristics of bergamot juice produced in different areas of Ca-labria sites. The results showed the best quality attributes of bergamot fruits harvested in the DPO area. In particular, higher levels of total soluble solids, stable acidity and higher juice were found. In addition, higher contents of ascorbic and citric acids, which are nutritionally valuable and tasteful, were found. The phenolic profile, characterized by the key compounds of bergamot, highlighted the better nutraceutical potential of the fruit grown in the DPO area.

Aluminum (Al), making up a third of the Earth's crust, is a widespread toxic contaminant, particularly in acidic soils. It impacts crops at multiple levels, from the cellular to the whole plant. This review delves into aluminum's reactivity, including its cellular transport, involvement in oxidative redox reactions, development of specific metabolites, and the influence of genes on the production of membrane channels and transporters, as well as its role in triggering apoptosis leading to senescence. It discusses the involvement of channel proteins in calcium influx, vacuolar proton pumping, the suppression of mitochondrial respiration, and the initiation of programmed cell death. At the cellular nucleus level, the effects of Al on gene regulation through alterations in nucleic acid modifications, such as methylation and histone acetylation, are examined. The review in addition outlines the pathways of Al induced metabolic disruption specifically citric acid metabolism, regulation of proton excretion, induction of specific transcription factors, modulation of Al-responsive proteins, changes of citrate and nucleotide glucose transporters and overall metal detoxification pathways in tolerant genotypes. It also considers the expression of phenolic oxidases in response to oxidative stress, their regulatory feedback on mitochondrial cytochrome proteins, and their consequences on root development. Ultimately, the review focuses on the selective metabolic pathways that facilitate Al exclusion and tolerance, emphasizing compartmentalization, antioxidative defense mechanisms, and the control of programmed cell death to manage metal toxicity.

Many studies on flexible strain and pressure sensors have been reported due to growing interest in wearable devices for healthcare. However, most are fabricated with multiple ingredients and complicated methods even though commercial textiles, such as cotton, nylon, polyester, and silk were used. Here we present flexible pressure and strain (motion) sensors prepared with only graphene oxide (GO) and commercial silk fabrics and yarns. The pressure sensors were fabricated by simply dipping the silk fabric into GO solution followed by thermal treatment at 400 °C for reduction of GO (rGO). The pressure sensors were made from rGO-coated fabrics, which were stacked in 3-, 5-, and 7-layers. The super-sensitivity of 2.58 ×103 kPa-1 at low pressure was observed in the 7-layer pressure sensor. The strain sensors were obtained from rGO-coated twisted silk yarns whose gauge factor was 0.307. Although this value is small or comparable to other sensors, it is appropriate for motion sensing. The results of this study show a cost-effective and simple method for the fabrication of pressure and motion sensors with commercial silk and GO.

In the intricate landscape of software development, the distinction between average and exceptional outcomes often hinges on the approach taken by the engineers involved. This paper explores the core aspects that characterize responsible and professional software engineering, emphasizing the importance of stakeholder engagement, innovative problem-solving, and adherence to standards and best practices. Through detailed real-life examples, we illustrate how professional engineers ensure the creation of robust, efficient, and adaptable software solutions. Additionally, the paper delves into advanced strategies for enhancing database security, including the implementation of Sealed Secrets in Kubernetes environments, continuous improvement, and future enhancements. The goal is to provide a comprehensive understanding of professional software engineering practices and their impact on delivering superior value to projects and organizations.

This study is the first to investigate the asymmetric effects of oil price volatility on stock returns for the Ho Chi Minh Stock Exchange (HOSE). We utilized weekly series of VN30-Index, WTI crude oil prices, geopolitical risks (GPR) index and gold prices spanning from 6 February 2012 to 31 December 2023 as data sources. Using a nonlinear Autoregressive Distributed Lag (NARDL) bounds testing approach, we found that in the short-term, oil price volatility has negative asymmetric effects on the market returns. Specifically, in the short-term, a one percent increase in oil price volatility immediately leads to a 2,6868 percent decrease in the market returns while a similar magnitude decrease in oil price volatility is associated with 6.3180 percent increase in the market returns. In addition, the results obtained from the NARDL model indicated that, in the long-term, the negative and positive changes of oil price volatility have significantly negative effects on the market returns. Finally, the findings derived from the error correction model (ECM) show that 98.21 percent of the disequilibria from the previous week are converged and corrected back to the long-term equilibrium in the current week.

Studies and opinion articles present unequal conclusions concerning empathy and morality, mainly because a somewhat heterogeneous and foggy conceptual approach prevails. This scoping review aims to analyse the relationship between empathy and morality and to present a novel conceptual model of empathy applied to moral decisions.A search in PsycINFO, Scopus and PubMed identified articles addressing the relationship between empathy and morality.Thirty-two articles were included. We find an absence of a consensual definition of empathy. It is commonly defined as a predominant emotional process and a factor of bias and prejudice in moral decisions.According to our conceptual model, empathy is a distinct, complex human neuropsychological capacity that mobilises and is dependent on the proper functioning of several brain areas and balances the scales on which are Emotion and Reason, enabling the most thoughtful moral decisions possible in diverse circumstances and contexts.

The collection of photo shoots during the systematic monitoring activities is useful to witness the ecological role of marine phanerogams as hosts for a rich variety of organisms in coastal and transitional waters. Cymodocea nodosa is present in the Taranto seas. In the Mar Piccolo, it reached high covers in short times, up to 100%, due to the bettering of the environmental conditions. The most recent observations showed that it offers welcoming towards several vertebrates and invertebrates, native and non-indigenous, as well as to micro and macroalgae. The NPPR funded activities will make these observations more robust and structural.

Candida auris is considered an emerging Candida species that has rapidly spread all over the world. The evidence of its origin and emerging resistance is still unclear. The severe infection by this species causes significant mortality and morbidity among the elderly and immune compressed individuals. Development of drug resistance is the major factor associated with therapeutic failure of existing antifungal agents. Previous studies addressed the antifungal resistance profile and drug discovery for C. auris. However, comprehensive coverage of these information in a single investigation yet to be available. In this review, we have mainly focused on recent development in therapeutic strategy against C. auris. Based on the available information, several differential approaches were discussed, including existing antifungal drugs, chemical compounds, essential oils, natural products, antifungal peptides, immunotherapy, antimicrobial photodynamic therapy, drug repurposing, and drug delivery systems. Among them, chemical medications, natural products, and antifungal peptides are the prime contributors. However, a limited number of resources are available to prove the efficiency of these potential therapies in clinical usage. Hence, we hope that the data gathered in this review can encourage in vivo studies and clinical trials.

In this research work the study of Buongiorno Model Darcy Forchheimer flow of Hybrid nanofluid flow on isothermal permeable stretch/shrink sheet with homogeneous and heterogeneous reaction is investigated. The effects of MHD, thermal radiation, viscous dissipation, Joule heating, and heat generation/absorption are taken into account. Hybrid nanofluids can act as a medium for heterogeneous-homogeneous reactions. The nanoparticles dispersed in the fluid can influence reaction kinetics and species transport, potentially, altering reaction rates and pathways. The applications of HNF in reactions, both homogeneous and heterogeneous, lie in leveraging their enhanced thermal properties, catalytic potential, and improved mixing capabilities to optimize reaction efficiency and control reaction conditions. Similarity transformation is used to convert a set of PDEs into a set of ODEs. HAM is used for the solution of the obtained ODEs system. In a heterogeneous reaction, the concentration gradient is amplified; in a homogeneous reaction, the impact is opposite. Moreover, at higher compositions of HNPs, the concentration and velocity rise while the temperature falls. Furthermore, as the values of homogeneous and heterogeneous reactions increase, the concentration falls. It is reliable with the idea that a greater reaction rate lowers the diffusion rate. Nevertheless, these parameters do not affect temperature or velocity.

Molecular transport and quantum tunneling of H2 and H2O molecules through nanoporous gra-phene is studied using computational modeling and first principles density functional theory. It is demonstrated that molecules with sufficiently high kinetic energies can tunnel through the na-nopores. It is also demonstrated that molecules can be trapped in front of the nanopore or behind it. These investigations help us learn the behavior of molecules in and around nanopores of gra-phene. They also help us learn fundamentals of molecular tunneling. We believe, nanoporous gra-phene can play important roles for gas separation and nanofiltration.

Low-frequency electromagnetic induction (EMI) is a non-invasive geophysical method that is based on the induction of electromagnetic (EM) waves into the subsurface to quantify changes in electrical conductivity. In this study we present an open (design details and software are accessible) and modular system for the collection of EMI data. The instrument proposed allows to adjust the separations between the transmitter and up to four receiving antennas as well as the acquisition frequency (in the range between 3 and 50 kHz) to permit measurements with variable depth of investigation. The sensor provides access to raw data and the software described in this study allows control of the signal processing chain. The design specifications permit apparent conductivity measurements in the range of between 1 mS/m and 1000 mS/m, with a resolution of 1.0 mS/m and with a sampling rate of up to 10 samples per second. The sensor allows for a synchronous acquisition of a time stamp and a location stamp for each data sample. The sensor has a mass of less than 5 kg, is portable and suitable for 1-person operation, provides 4 hours of operation time on one battery charge, and provides sufficient rigidity for practical field operations.

The limited understanding of how digital platforms, especially the Metaverse, influence public perception and attitude towards sustainable fashion in large scaled markets such as China highlights a critical gap. This study aims to examine the perspectives and perception of the Chinese public regarding sustainable fashion in the Metaverse. Through content analysis, this study evaluated 3,889 Weibo posts from Shanghai Fashion Week 2024 to identify key sentiments and discussions on sustainable and digital fashion. Results indicate that 76.08% of the conversations centered on sustainable fashion, reflecting strong public commitment to environmental issues. The findings highlight characteristics of public perception towards the utilization of immersive technologies and underscore the Metaverse's potential as a platform for fostering environmental consciousness in the fashion industry. This research provides crucial insights for fashion brands looking to integrate sustainability into their digital strategies, addressing a significant gap in current literature and offering practical guidance for leveraging digital platforms to promote sustainable consumption.

Alkaloid-based urea derivatives were produced with high yield through the reaction of anabasine and cytisine with isoxazolylphenylcarbamates in boiling benzene. Their antitumor ac-tivity in combination with the commonly used six anticancer drugs namely cyclophosphane, fluorouracil, etoposide, cysplatine, ribomustine with different mechanisms of action was investi-gated. Based on the quantum chemical calculations data and molecular docking, hypotheses have been put forward to explain their mutual influence when affecting on the С6 rat glioma model cells.

Urinary tract infections in kidney transplant patients are a real challenge. We conducted a retrospective observational study, enrolling all kidney transplant patients hospitalized for urinary tract infection (UTI), with the objective to evaluate the epidemiology, clinical sta-tus, therapeutic management, and clinical outcome of kidney transplant patients hospi-talized for urinary tract infection in a university hospital. From our real-life experience, infection with multidrug-resistant germs was confirmed as a risk factor for the severe evolution of the infection and at the same time the re-evaluation of immunosuppressive therapy could be an important therapeutic strategy in the course of infection. Prompt ini-tiation of empiric antibiotic therapy upon initiation of microbiological investigations could potentially reduce the risk of severe infection progression.

In modern warfare, the diversified tasks can sometimes be challenging to fulfill with a single projectile, necessitating the incorporation of cooperation constraints in trajectory planning. Limited by the stringent requirements of the launch platform and lower costs, the maneuverability and ability to adjust the flight time range of projectiles are weak. Therefore, the rationality of performance indicators and flight time coordination strategies is especially critical. To fully exploit the control capabilities of projectiles, a battlefield area segmentation method is proposed, differentiated performance indicators and a cooperative trajectory planning model that considers the entire range of projectiles are established. Considering the limitations of existing flight time coordination strategies in applications, targeted improvements have been made in different cooperation scenarios, and a bi-level adaptive cooperation strategy(BACS) with both optimality and flexibility is proposed. To rapidly determine feasible conditions, a simple and universal method for obtaining the capability ranges of cooperation is introduced. The multi-phase optimal control problems are transformed into nonlinear programming problems using the Radau pseudo-spectral method, and simulation results show that the proposed methods are capable of handling trajectory planning tasks in different cooperation scenarios. The improved strategies effectively enhance the planning success rate under relatively harsh conditions and BACS demonstrates good compatibility with the problems studied.

Purpose: This study aims to investigate the role of blockchain technology in enhancing supply chain transparency in Italy.Design/Methodology/Approach: A quantitative research approach was employed, with data collected through a structured questionnaire distributed to 240 companies across various industries in Italy. The questionnaire focused on assessing blockchain adoption rates, interoperability standards, stakeholder collaboration, regulatory support, cost considerations, and perceived impacts on supply chain transparency.Findings: The findings reveal high levels of blockchain adoption among surveyed companies, with strong positive correlations observed between blockchain adoption and interoperability standards, stakeholder collaboration, and regulatory support. However, challenges such as cost considerations and potential trade-offs between interoperability and transparency were also identified. Overall, blockchain technology shows promise in improving supply chain transparency in Italy.Research Limitations/Implications: This study is limited by its focus on a specific geographical context (Italy) and the use of self-reported data. Future research could explore the dynamics of blockchain adoption in other regions and employ objective measures to assess supply chain transparency.Practical Implications: The findings offer practical insights for businesses and policymakers aiming to leverage blockchain technology to enhance supply chain transparency and efficiency.Social Implications: Blockchain adoption has the potential to foster greater trust and accountability within supply chains, benefiting various stakeholders including consumers, producers, and regulators.Originality/Value: This study contributes to the growing body of literature on blockchain technology in supply chain management, particularly within the Italian context, by providing empirical evidence on its adoption and impact on transparency.Limitations: Despite the robust methodology employed, limitations include the reliance on self-reported data and the exclusion of qualitative insights.

Abstract Background: Atrazine, a widely used herbicide, is recognized for its potential endocrine-disrupting effects, though its direct link to diabetes has not been extensively studied. Objectives: This study investigates the relationship between atrazine exposure and diabetes incidence, especially in agricultural settings, and examines how socioeconomic factors like income and education levels influence diabetes risk. Methods: A retrospective cohort study was conducted using data from 67 counties in Pennsylvania from 2011 to 2019. Atrazine exposure was measured in local water sources and correlated with diabetes data from the Pennsylvania Behavioral Risk Factor Surveillance System (BRFSS). Socioeconomic data were sourced from U.S. Census Bureau records, with logistic regression used to adjust for confounders such as age, race, and lifestyle. Results: Findings showed a significant association between high atrazine exposure and increased diabetes incidence, even after adjusting for confounders. Discussion and Conclusion: The study highlights a significant health risk posed by atrazine, particularly for socioeconomically disadvantaged groups. It underscores the need for stricter atrazine regulation and public health interventions to mitigate its impact. Further research is crucial to understand how atrazine affects glucose metabolism and diabetes development. Implementing stricter environmental controls and educational initiatives could reduce the diabetes burden in impacted communities.

Recently, microfluidics deformability cytometry has emerged as a powerful tool for high throughput mechanical phenotyping of large populations of cells. These methods characterize cells by their mechanical fingerprints through exerting hydrodynamic forces and monitoring the resulting deformation. These devices have shown great promise for label free cytometry, yet there is a critical need to improve their accuracy and reconcile any discrepancies with other methods, such as atomic force microscopy. In this study, we employ computational fluid dynamics simulations and uncover how the elasticity of frequently used carrier fluids such as methyl-cellulose dissolved in phosphate-buffered saline is significantly influential to the resulting cellular deformation. We conducted CFD simulations that are conventionally used within the deformability cytometry field, which neglect fluid elasticity. Subsequently, we incorporated a more comprehensive model that simulates the viscoelastic nature of the carrier fluid. A comparison of the predicted stresses between these two approaches underscores the significance of the emerging elastic stresses in addition to the well-recognized viscous stresses along the channel. Furthermore, we utilize a two-phase flow model to predict the deformation of a promyelocyte (i.e. HL-60 cell type) within a hydrodynamic constriction channel. The obtained results highlight a substantial impact of the elasticity of carrier fluid on cellular deformation and raise questions about the accuracy of mechanical property estimates derived by neglecting elastic stresses.

The awareness of ciliate importance in freshwater has changed dramatically in the last decades, reflecting methodological attempts. We analysed two decades (1994-2018) of data on the surface (0-3 m) ciliate assemblage in the Slapy reservoir (Vltava River, Czech Republic) during two different nutrient-load defined periods. We identified, quantified, and evaluated the biomass of ciliates in the quantitative protargol-stained preparations. We used water age, nutrients, bacteria, heterotrophic nanoflagellates and rhodomonads as the main explanatory background variables. The sampling median and interquartile range data analysis and a non-metric multidimensional scaling were applied. Ciliates were grouped according to their feeding behaviour. The picoplankton filtering species dominated the assemblages in an annual mean (halteriids and minute strobilidiids followed by peritrichs). Algae hunters Balanion planctonicum, urotrichs and nanoplankton filtering tintinnids were important before the spring phytoplankton peak when a maximum of ciliate biomass reflected mixotrophic nanoplankton filtering pelagostrombidiids. Only there, ciliate biomass tightly followed their quantified prey. Heterotrophic and mixotrophic Askenasia and Lagynophrya were typical raptorial/flagellate hunters; only Mesodinium spp. peaked during autumn. The oligotrophication increased the ciliate assemblage biomass in the surface layer during the stratification in concordance with the PEG model.

Introduction: Transforming growth factor beta receptor 2 (Tgfbr2) signaling regulates odontoblast differentiation, dentin mineralization, and the paracrine signaling that guides sensory innervation in developing mouse molars. We hypothesized that Tgfbr2 also regulates the neuro-pulpal responses to injury to activate axon sprouting and tertiary dentin secretion. Methods: We per-formed a timed deletion of Tgfbr2 using tetracycline-responsive Osterix-Cre;Tgfbr2f/f (Tgfbr2^cko) mice, which allowed them to develop normally. At 3 months, we drilled a shallow hole on the mesial side of the first mandibular molar (M1) in both control and Tgfbr2^cko mice. Hemi-mandibles were collected 4, 8, 21, and 56 days post-injury (dpi). In situ hybridization (ISH) for Sp7 was performed to confirm Osterix-Cre transcription. Microcomputed tomography (micro-CT) imaging and histology were used to examine the tertiary dentin, and immunofluorescence was used to visualize CGRP+ axons following the injury. Results: Tgfbr2 deletion was inferred by Sp7 ISH. Micro-CT and histology indicated a lower dentin volume in 21 dpi Tgfbr2^cko M1s compared to WT M1s, but the volume was comparable by 56 dpi. The duration of axon sprouting was longer in injured Tgfbr2^cko M1s compared to WT M1s. Conclusions: These results suggest that sensory afferents may support dentin repair in Tgfbr2-deficient odontoblasts.

Infrastructure such as transport, electricity, telecommunications, and sanitation are indispensable drivers for improving the country’s social and economic development. The industrial, agricultural, fisheries and service sectors are also key tools for the country's economic growth. This study aims to analyze the influence of infrastructure development on Djibouti’s economic growth and determine the other economic sectors. This study employs multiple regression analyses from Eviews Software to establish a correlation between these variables and Djibouti’s economic growth, utilizing data spanning from the period 2013 to 2022. The results reveals that mobile cell phone subscriptions, and the people using the health service management, industry, and service have a positive and highly significant influence on Djibouti's economic growth. The study found that access to electricity has a positive influence on economic growth in Djibouti, but is not statistically significant. In addition, the study shows that agriculture, forestry, and fisheries have a negative influence on economic growth in Djibouti, but are statistically significant. Therefore, we recommend that the Government of Djibouti strengthen and ensure the benefit of developing electricity infrastructure in Djibouti and the agriculture, forestry, and fisheries sectors to achieve sustainable economic growth in the coming years.

Autonomous search is an ongoing cycle of sensing, statistical estimation and motion control with objective to find and localise targets in a designated search area. Traditionally, the theoretical framework for autonomous search combines the sequential Bayesian estimation with the information theoretic motion control. This paper formulates autonomous search in the framework of possibility theory. Although the possibilistic formulation is slightly more involved than the traditional, it provides means for quantitative modelling and reasoning in the presence of epistemic uncertainty. This feature is demonstrated in the paper in the context of partially known probability of detection, expressed as an interval value. The paper presents an elegant Bayes-like solution to sequential estimation, with the reward function for motion control defined to take into account the epistemic uncertainty. The advantages of the proposed search algorithm are demonstrated by numerical simulations.

This contribution attempts to provide a state-of-the-art account on the physicochemical and biomedical properties of plasma-sprayed hydroxylapatite (HAp) coatings that are routinely applied to the surfaces of metallic endoprosthetic and dental root implants, designed to replace or restore lost functions of diseased or damaged tissues of the human body. Even though the residence time of powder particles of HAp in the plasma jet is extremely short, the high temperature applied introduces compositional and structural changes of the precursor hydroxylapatite that severely affect its chemical and physical properties and in turn, its biomedical performance. These changes are based on the incongruent melting behaviour of HAp and can be traced, among many other analytical techniques, by high-resolution synchrotron X-ray diffraction, vibrational (Raman), and nuclear magnetic resonance (NMR) spectroscopies. In vivo reactions of the plasma-sprayed coatings with extracellular fluid (ECF) can be assessed and predicted by in vitro testing using simulated body fluids as proxy agents. Ways are being discussed to safeguard appropriate biological performance of hydroxylapatite coatings in long-term service by controlling their phase content, porosity, surface roughness, residual stress distribution, and adhesion to the implant surface.

We present a formalism to assess the safety of the COVID19 vaccines and infer a causal relation between vaccine administration and adverse effects, in particular death. We use data on adverse effects from VAERS covering the time interval [01-10-2020, 31-12-2021] (downloaded on 1 Feb 2022). We measure a vaccine fatality rate of order 0.01 for all vaccine manufacturers and identify a strong heterogeneity in the vaccine toxicity across vaccine lots, spanning up to four orders of magnitude. We compute the correlation between vaccination dates and death dates, and produce an estimate of the time lag that maximises the correlation, finding that the onset of adverse effects happened statistically (i.e. 32-41 percentiles) within one day after the vaccine administration and that death happened statistically (i.e. 22-50 percentiles) within about two weeks after the vaccine administration. These results provide data-based insights that can guide public health measures and health insurance policies.

This comprehensive review explores the multifaceted landscape of supercapacitors, highlighting their pivotal role in meeting the global demand for efficient energy storage solutions. Supercapacitors, with their high power density, rapid charge-discharge cycles, and extended cycle life, offer a compelling alternative to conventional batteries and capacitors. The review delves into the fundamental mechanisms of energy storage in supercapacitors, categorizing them into Electrochemical Double-Layer Capacitors (EDLCs), pseudocapacitors, and hybrid capacitors. It discusses significant advancements in supercapacitor technology, including nanostructured materials, flexible and wearable supercapacitors, solid-state supercapacitors, and hybrid supercapacitors, highlighting their potential applications across industries such as transportation, renewable energy, consumer electronics, and industrial power management. Through continued research and development, supercapacitors are poised to play a pivotal role in driving the transition towards a greener and more efficient future.

In Korea, laver (Gim) is the leading traded marine product and an important food source, accounting for 82.0% of the world’s exports. Laver exports reached $100 million in 2010 and steadily increased to $600 million in 2020. An increase in laver exports improves the income of laver farmers and promotes the growth of fisheries. However, marine algae are vulnerable to climate change. In this study, we aimed to predict changes in laver production due to climate change using environmental variables, including water temperature, rainfall, and sunlight duration. The results showed that water temperature considerably affected laver production; when water temperature increased by 1 °C, production decreased by 13.78% (t) in the same month. By contrast, when sunlight duration and rainfall increased by 1 h and 1 mm, respectively, 1 month before harvesting laver, production increased by 0.32% (t-1) and 0.13% (t-1), respectively. Using four scenarios based on climate change published by the Intergovernmental Panel on Climate Change in a modeling exercise, we found that laver production in 2100 in Wando in Korea may decline by 73.3% owing to water temperature changes (based on 2020 production), threatening food security. Accordingly, short-, mid-, and long-term countermeasures are needed for sustainable laver aquaculture. Appropriate water temperature (21–22 °C) during seeding is necessary to control environmental variables, based on scientific data and activation of land-based seeding methods. Moreover, mid- and long-term countermeasures should include development of high-temperature resistant laver seeds, identification of suitable new laver aquaculture grounds, and research on seeds that can adapt to climate change.

Multi-stage hydraulic fracturing with horizontal well technology has been widely used in shale oil reservoir. After hydraulic fracturing, hydraulic fractures and opened beddings are intertwined, which result in a complex fracture network. As well as the migration of multi-phase fluids during fracturing and soaking processes, which lead to complex flowback performance, and brings dif-ficulty to productivity evaluation and flowback strategies optimization. In this paper, taking the Daqing Gulong shale reservoir as an example, a numerical model for flowback period, which considered oil-water-gas three-phase flow and orthogonal fracture network has been established. The characteristics and influencing factors of flowback performance have been deeply studied, and the flowback modes of shale oil are reasonably optimized. Factors such as PTPG (pseu-do-threshold pressure gradient), opened bedding stress sensitivity, opened bedding permeability and matrix permeability have obvious effects on the flowback performance, resulting in signifi-cant variations in production peaks, high yield periods, and decline rates. In addition, three flowback modes are distinguished based on the rate at which the BHP (bottom hole pressure) drops. These correspond to three types of choke modes. Based on the result of numerical model, three flowback modes are optimized and the impacts of different flowback modes on shale oil flowback are clarified. This study is particularly important for understanding the performance of shale oil flowback and guiding the efficient exploitation of shale oil.

The rise in IoT (Internet of Things) devices poses a significant security challenge. Maintaining privacy and ensuring anonymity within the system is a sought-after feature with inevitable trade-offs, such as scalability and increased complexity, making it incredibly challenging to handle. To tackle this, we introduce our proposed work for managing IoT devices using Hyperledger fabric. We integrated our system on the blockchain with a closed-circuit television (CCTV) security camera fixed at a rental property. The CCTV security camera redirects its feed whenever a new renter walks in. We have introduced the web token for authentication from the renter to the owner. Our contributions include the proposition of efficient framework architecture, a novel chain code algorithm, and stealth addresses with modified ring signatures. We performed different analyses to show the system's throughput and latency through stress testing. We have shown the advantages of the proposed architectures by comparing similar existing schemes. Our proposed scheme enhances the security of blockchain-enabled IoT devices and mitigates the single point of failure issue. Our future work includes scaling it up to cater to the needs of the healthcare system.

There is growing interest in the discovery of novel xanthine oxidase inhibitors for gout prevention and treatment with fewer side effects. This study aimed to identify the xanthine oxidase (XO) inhibitory potential and drug-likeness of the metabolites present in the methanolic leaves extract of Anastatica (A.) hierochuntica L. using in vitro and in silico models. The extract-derived metabolites were identified by liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Molecular docking predicted the XO inhibitory activity of the identified metabolites and validated the best scored in vitro XO inhibitory activities for experimental verification as well as predictions of their anticancer, pharmacokinetic and toxic properties, oral bioavailability, and endocrine disruption using SwissADMET, PASS, ProTox-II and Endocrine Disruptome web servers. A total of 12 metabolites with a majority of flavonoids were identified. Rutin, quercetin and luteolin flavonoids demonstrated the highest ranked docking score of -12.39, -11.15 and -10.43, respectively, while the half-maximal inhibitory concentration (IC50) values of these metabolites against XO activity were 11.35 µM, 11.1 µM and 21.58 µM, respectively. In addition, SwissADMET generated data related to physicochemical properties and drug-likeness of the metabolites. Similarly, PASS, ProTox-II and Endocrine Disruptome prediction models stated the safe and potential use of these natural compounds. However, in vivo studies are necessary to support the development of prominent and promising therapeutic use of A. hierochuntica methanolic leaves extract-derived metabolites as XO inhibitors for the prevention and treatment of hyperuricemic and gout patients. Furthermore, the predicted findings of the present study open a new paradigm for these extract-derived metabolites by revealing novel oncogenic targets for the potential treatment of human malignancies.

Cirina forda caterpillars are a significant protein source in Central Africa, yet their preservation and consumption pose challenges. This study investigates the drying of Cirina forda caterpillars to enhance preservation methods and product quality. Caterpillars were subjected to drying experiments at temperatures ranging from 40°C to 70°C, using tunnel and oven dryers. The drying kinetics was analyzed using mathematical models, revealing a water diffusion-limited mechanism in all the tested conditions. The Newton model provided adequate estimations of the drying behavior, facilitating further practical dryer design. Shrinkage analysis indicated a two-step process independent of the drying conditions. Achieving a moisture content suitable for prolonged storage resulted in substantial volume loss, highlighting the challenges of preserving dried caterpillars. These findings shed light on how to optimize drying processes for Cirina forda caterpillars, crucial for sustaining protein sources in Central Africa.

This study aimed to examine the chemical makeup and antioxidant properties of hydroalcoholic extracts obtained from Lonicera japonica Thunb. Thunb. (honeysuckle) flowers collected from two geographically distinct regions of Romania: a mountainous region (Făgăraș Mountainous, Brașov) and a coastal region (Black Sea, Constanța). Our research revealed that the extracts from these two regions differed significantly in terms of their total polyphenol, flavone, and phenolic carboxylic acid content, as well as their antioxidant activity. These results suggest that climatic factors play a crucial role in shaping the phytochemical profile and antioxidant activity of Lonicera japonica Thunb. Thunb. extracts. Therefore, these findings could potentially contribute to the development of standardized herbal preparations and nutraceutical products.

This research paper presents a new test based on a novel approach for identifying clustered graphical passwords within the Passpoints scenario. Graphical authentication methods serve as a viable alternative to the conventional alphanumeric password-based authentication method, which is susceptible to known weaknesses arising from user-generated passwords of this nature. The test proposed in this study is based on estimating the distributions of the perimeter of the convex hull. This perimeter is calculated based on the points users select as passwords within an image measuring 1920 × 1080 pixels. The test is formulated once the optimal theoretical distributions that fit the data are identified. Evaluating the proposed test’s effectiveness involves estimating type I and II errors. In this study, we compare the effectiveness and efficiency of the proposed test with existing tests from the literature that can detect this type of pattern in Passpoints graphic passwords. Our findings indicate that the new test demonstrates a significant improvement in effectiveness compared to previously published tests. Furthermore, the joint application of the two tests also shows improvement. Depending on the significance level determined by the user or system, the enhancement results in a higher detection rate of clustered passwords, ranging from 0.1% to 8% compared to the most effective previous methods. This improvement leads to a decrease in the estimated probability of committing a type II error. In terms of efficiency, the proposed test outperforms several previous tests; however, it falls short of being the most efficient. It can be concluded that the newly developed test demonstrates the highest effectiveness and the second-highest efficiency level compared to other tests available in the existing literature for the same purpose.

This paper presents a compact wideband circularly polarized cross dipole antenna with low-pass filter response. It consists of two pairs of folded crossed dipole arms printed separately on both sides of the top substrate, and the two dipole arms on the same surface are connected by an annular phase-shifting delay line to generate circular polarization. A bent metal square ring and four small metal square rings around the cross dipoles are employed to introduce new resonant frequencies, effectively extending the impedance and axial ratio bandwidth. Four square patches printed on the middle substrate are connected to the ground plane by the vertical metal plates, in order to reduce the antenna height. Thus, a compact wideband circularly polarized antenna is realized. In addition, a transmission zero can be introduced at the upper frequency stopband by the bent metal square rings, without using extra filter circuits. For verification, the proposed model is implemented and tested. The overall size of the model is 90mm×90mm×33mm(0.37λ0×0.37λ0×0.14λ0, λ0 denotes the center operating frequency). The measured impedance bandwidth and 3 dB axial ratio bandwidth are 53.3% and 41%, respectively. More than 15 dB upper-band radiation suppression level is realized, indicating a good low-pass filter response.

This study investigates the factors influencing consumers' intentions to purchase overseas travel packages via social media in Thailand, with a focus on consumer trust and perceived risks. A mixed-methods approach was employed, combining qualitative and quantitative research techniques. In the qualitative phase, the Fuzzy Set Delphi Method was applied to gather expert consensus from 19 participants. For the quantitative phase, a survey was conducted among 600 individuals who had experience purchasing overseas travel packages on social media in Thailand. First-order and second-order confirmatory factor analyses were used to examine the relationships between eight identified factors: social media influencer, e-WOM, trust, perceived risk, brand image, rating review, personal attitude, and destination image. The results indicate that trust and perceived risk are the most significant factors affecting purchase intention. Trust plays a crucial role in customers' decision-making processes, while perceived risk influences their tendency to avoid purchasing packages if the risk is perceived as high. The insights gained from this study contribute to the understanding of factors influencing purchase intentions for overseas travel packages through social media in Thailand, providing valuable information for travel agencies to develop effective marketing strategies.

Iron tailings are solid waste generated after the mining of iron mines, which have caused serious damage to the surrounding ecology and environment and have attracted widespread attention. By analyzing the formation causes, main components, and environmental effect mechanisms of iron tailings, the article systematically elaborates on the degree and mechanism of the harm of iron tailings to water bodies, atmosphere, soil, and ecosystems, and evaluates its impact on human health and sustainable development of society. On this basis, specific prevention and control measures have been proposed to reduce iron tailings emissions, realize resource recycling, and restore ecosystems. Research shows that iron tailings containing heavy metals can widely pollute the environment through dissolution and migration, and have significant biological toxicity effects. The research results can provide a theoretical reference for decision-making departments to formulate scientific and reasonable iron tailings disposal and ecological protection policies. It is recommended to strengthen specific research on the infiltration of toxic and harmful components in tailings in the future, and develop efficient and stable solidification technology, and vegetation-microbial joint restoration models to further reduce the ecological and environmental risks of iron tailings.

This study investigated a novel radioimmunotherapy strategy for targeting tumor angiogenesis. We developed a radiopharmaceutical complex by labeling an anti-adenosine triphosphate syn-thase (ATPS) monoclonal antibody (mAb) with the radioisotope 177Lu using DOTA as a chelating agent. 177Lu-DOTA-ATPS mAb demonstrated high labeling efficiency (99.0%) and stability in se-rum. MKN-45 cancer cells exhibited the highest cellular uptake, which could be specifically blocked by unlabeled ATPS mAb. In mice, 177Lu-DOTA-ATPS mAb accumulated significantly in tumors, with a tumor uptake of 16.0 ± 1.5%ID/g on day 7. 177Lu-DOTA-ATPS mAb treatment sig-nificantly reduced the viability of MKN-45 cells in a dose-dependent manner. In a xenograft tumor model, this radioimmunotherapy strategy led to substantial tumor growth inhibition (82.8%). Furthermore, combining 177Lu-DOTA-ATPS mAb with sunitinib, an anti-angiogenic drug, en-hanced the therapeutic efficacy of sunitinib in the mouse model. Our study successfully developed 177Lu-DOTA-ATPS mAb, a radioimmunotherapy agent targeting tumor blood vessels. This ap-proach demonstrates significant promise for inhibiting tumor growth, both as a single therapy and in combination with other anti-cancer drugs.

We describe a family of paraxial and quasi-monochromatic optical wave packets with finite energy and smoothly shaped amplitude in space and time that develops a singularity in the intensity when spatiotemporally focused by imparting a converging spherical wave front and a negative temporal chirp. This singular behavior upon ideal focusing is manifested in actual focusing with finite apertures and in media with high-order dispersion in an "exploding" behavior featuring indefinitely increasing concentration of the energy when opening the aperture radius, thus exercising a continuous control on the focal intensity and spatial and temporal resolution. These wave packets offer a new way of focusing that outperforms what can be achieved with standard Gaussian wave packets in terms of focal intensity and resolution, and new possibilities in applications where energy concentration and its control are crucial.

The green synthesis of metallic nanoparticles is an emerging and promising field owing to its environmentally friendly nature and diverse applications. In this article, a new technology for the green synthesis of functional ultrastable biopolymer gold nanoparticles is introduced. This approach employs thiolated single-stranded DNA (ssDNA-SH) aptamers instead of conventional self-assembled monolayers, resulting in the production of highly stable aptamer-tagged gold-core-shell nanoparticles. A comprehensive discussion on the use of glucose as a simple reducing agent for the green synthesis of Au nanoparticles and the utilization of ssDNA-SH aptamers as smart and biologically functional capping agents is provided. The potential of this innovative approach for the green synthesis of nanoparticles is demonstrated through a case study involving the use of the naked eye for qualitative detection of human fungal infections caused by Candida albicans for women's health.

Taking into consideration the arising resistance towards the currently available antimycobacterial, there is still an unmet need for the development of new chemotherapeutic agents to combat the infectious agent. This study presents the X-ray single-crystal analysis to verify the structure of leading sulfonyl hydrazone 3b, which have proven their potent antimycobacterial activity against Mycobacterium tuberculosis H37Rv with MIC value of 0.0716 μM, respectively, low cytotoxicity and very high selectivity indexes (SI=2216) and fully characterized by NMR and HRMS methods. Furthermore, this study assessed the ex vivo antioxidant activity, acute and subacute toxicity, and in vitro inhibition capacity against enoyl-ACP reductase of hydrazones 3a and 3b, as 3a was identified as the second leading compound in our previous research. Compared to isoniazid, compounds 3a and 3b demonstrated lower acute toxicity for intraperitoneal administration, with LD50 values of 866 and 1224.7 mg/kg, respectively. Subacute toxicity tests, involving the repeated administration of a single dose of the test samples per day, revealed no significant deviations in hematological and biochemical parameters or pathomorphological tissues. The compounds exhibited potent antioxidant capabilities, reducing malondialdehyde (MDA) levels and increasing reduced glutathione (GSH). Enzyme inhibition assays of the sulfonyl hydrazones 3a and 3b with IC50 values of 18.2 µM and 10.7 µM, respectively and molecular docking studies revealed enoyl acyl carrier protein reductase (InhA) as the possible target enzyme of the compounds to show their antitubercular activities. In conclusion, the investigated sulfonyl hydrazones display promising antitubercular drug-like properties and warrant further investigation.

A partial mitochondrial DNA Cytochrome Oxidase subunit I (mtCOI) gene haplotype variant of the coconut rhinoceros beetle (CRB) Oryctes rhinoceros classed as ‘CRB-G (clade I)’ has been the focus of much research since 2007 with reports of invasions into new Pacific Island locations (e.g., Guam, Hawaii, Solomons Islands). For numerous invasive species, inference of invasion biology via whole genome is superior to assessments via the partial mtCOI gene. Here, we explore CRB draft mitochondrial genomes (mitogenomes) from historical and recent collections, with assessment focused on individuals associated within the CRB-G (clade I) classification. We found that all Guam CRB individuals possessed the same mitogenome across all 13 protein coding genes and differed from individuals collected elsewhere, including ‘non-Guam’ individuals designated as CRB-G (clade I) by partial mtCOI assessment. Two alternative ATP6 and COIII partial gene primer sets were developed to enable distinction between CRB (clade I) that invaded Guam and CRB-G (Clade I) individuals collected elsewhere. Phylogenetic analyses based on concatenated ATP6-COIII genes showed that only Guam CRB-G (clade I) individuals clustered together, and therefore Guam was not the source of the CRB that invaded the other locations in the Pacific assessed in this study. The use of the mtCOI and/or mtCOIII genes for initial molecular diagnosis of CRB remained crucial, and assessment of more native CRB populations will further advance our ability to identify the provenance of CRB invasions being reported within the Pacific and elsewhere

Consumption of ultra-processed foods is associated with abdominal obesity, but this association has not yet been investigated in individuals on hemodialysis. This cross-sectional study, developed with 1014 individuals, aimed to analyze the prevalence of abdominal obesity and its association with the consumption of ultra-processed foods in individuals on hemodialysis. Consumption of ultra-processed foods was measured using a questionnaire, whose list of foods was based on the Surveillance System of Risk and Protective Factors for Chronic Non-Communicable Diseases through Telephone Enquiry. Waist circumference was used to determine the presence of abdominal obesity. The difference in proportions between the independent variables and the outcome was verified using Pearson's chi-square test. Hierarchical logistic regression was used to determine the association between the outcome and the independent variables. The prevalence of abdominal obesity was 77.22%. In the final model, higher consumption of ultra-processed foods, be male and an adult, have between 8 and 11 years of schooling and practice physical activity below the recommended level increased the chances of having abdominal obesity. The research provides a basis for the creation and improvement of public policies that promote improvements in these health determinants.

Abstract: Nordic exercises aim to improve physical abilities and prevent injuries; However, it is not clear in what type of sports modalities to use it, so this study arises from the interest of ana-lyzing its effect in different sports modalities. Objective: To analyze Nordic exercises effects on the lower limbs, and their relationship with the explosive and absolute strength inherent to demands of different sports modalities (football, athletics, basketball, sport climbing, cycling and taekwondo). Method: quasi-experimental research, identifying 122 athletes (18±3 years old) from: football (n=24), athletics/speed (n=20), sport climbing (n=20), basketball (n=24), taekwondo (n=14) and cycling (n=20); classified into a control group CG (n=57) and an experimental group EG (n=65). Results: dominant absolute strength of the initial (12.4±0.51) and final (14.5±0.98) EG, in greater proportion in basketball (P= < 0.05); explosive strength of the initial (42.4±1.2) and final (45.8±1.5) EG, with a significant difference in all modalities between before and after (p≤0.05), except in cy-cling and taekwondo; no major changes were found in the GC. Conclusion: Nordic exercises are recommended as part of training to improve levels of explosive strength with emphasis on the modalities of football, basketball, athletics/speed and sport climbing, being applicable to increase absolute strength in basketball.

RM (red mud) was acidified with sulphuric acid and the acidified ARM (acidified red mud) was utilized as an innovative adsorption material for treating antibiotic-contained wastewater. The adsorption conditions, kinetics, isotherms, thermodynamics, and mechanism of ARM for CIP (ciprofloxacin) were investigated. Characterization of the ARM involved techniques such as scanning electron microscopy(SEM), transmission electron microscope(TEM), brunauer- emmett-teller (BET), X-ray diffraction (XRD), X-ray fluorescence (XRF), thermogravimetric analysis (TGA) and NH3-TPD analysis. Adsorption studies were conducted employing response surface methodology (RSM) for experimental design. The results showed that ARM can absorb CIP effectively. The RSM optimal experiment indicated that the most significant model terms influencing adsorption capacity were solution pH, CIP initial concentration and ARM dosage, under which the predicted maximum adsorption capacity achieved 7.30 mg/g. The adsorption kinetics adhered to a pseudo-second-order model, while equilibrium data fitted the Langmuir-Freundlich isotherm, yielding maximum capacity values of 7.35 mg/g. The adsorption process occurred non-spontaneously and absorbed heat, evidenced by ΔG0 values between 2.06 and 0.87 kJ/mol, ΔS0 at 39.41 J/mol/K, and ΔH0 at 13.8 kJ/mol. Analysis using attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) indicated there existed complex reaction between Al-O in ARM and the ester group –COO in CIP. The C=O bond in CIP was likely to undergo a slight electrostatic interaction or be bound to the internal spherical surface of ARM. The findings indicate that ARM is a promising and efficient adsorbent for CIP removal from wastewater.

In light of growing concerns over water contamination, particularly in regions like Sindh, Pakistan, this research aimed to evaluate and map the groundwater quality in Taluka Larkana for both drinking and irrigation applications, addressing the expressed worries of the local community. A total of forty groundwater samples were collected from various sources such as hand pumps, taps, and tube wells. These samples underwent comprehensive analysis encompassing parameters including color, odor, taste, turbidity, pH, total hardness (TH), electrical conductivity (EC), and total dissolved solids (TDS), with comparisons drawn against WHO guidelines.Results indicated that taste, color, odor, and turbidity of the groundwater samples generally fell within acceptable ranges. However, EC levels varied from moderately elevated to excessively high. Notably, a significant proportion of samples (84% EC, 21% Cl, 30% Ca, 37% Mg, 22% TH, and 84% TDS) exceeded WHO-recommended thresholds.Assessment via the SPI model classified approximately 16% of samples as moderately contaminated, while 65% were deemed highly contaminated, and 19% were found unsuitable for drinking purposes. These findings underscore the pressing need for concerted efforts to address water quality issues in the region.

Motivation is essential in education, with highly motivated learners engaging more deeply with content and more ably transferring knowledge to new contexts. However, the validity of scales to measure motivation has been underexplored in pre-clerkship medical education. This study evaluates the validity of the Situational Motivation Scale (SIMS) for measuring motivation among pre-clerkship medical students in post-situational and short-term contexts. Using a sample of n = 156 students from the Frank H. Netter MD School of Medicine at Quinnipiac University, SIMS was tested for construct validity with attention paid to content, response process, internal structure, relationships to other variables, and consequences of use evidence. Small modifications from present to past tense in English were made for clarity following focus group feedback, and content validity was ensured via expert consultation. SIMS demonstrated strong internal consistency with a satisfactory Cronbach’s alpha for all subscales and anticipated patterns of correlations. Factor analysis confirmed appropriate factor loadings, with a stronger model fit for the short-term context, and no observed adverse effects on student engagement. These findings support the robustness of SIMS in capturing intrinsic, extrinsic, and amotivation in pre-clerkship medical students, highlighting its applicability for short-term and situational motivational assessment.

Exogenous auxins such as indole-3-acetic acid (IAA) can modulate the effect of a plant's endogenous auxins. The objectives of this work were to quantify the concentration of IAA in sand-based substrates with vermicompost (S-VC), to establish the relationship between the concentration of exogenous IAA and the amount of vermicompost (VC), as well as determine its influence on the development of tomato plants. S-VC substrates with different percentages based on volume (0, 20, 40 and 50% VC) placed in pots, with five replicates and randomly distributed, were used to transplant tomato seedlings. In each substrate, the concentration of IAA was determined at the beginning and at the end of a culture cycle, as well as the microbial load; In addition, some performance components were measured in the plants. The results showed that gram-positive bacteria were found in the substrates with VC, whose colony-forming units were related to the concentration of IAA and the amount of VC in the substrates. Therefore, the IAA concentration presented a linear and positive relationship with the amount of VC in the substrates (R2 = 0.9171, at the beginning and R2 = 0.9712, at the end of the experiment).

Background: The aim of this study was to investigate a series of complete blood cell count – based biomarkers of systemic inflammation as predictors of clinical outcomes in patients who underwent first-line chemoimmunotherapy for advanced NSCLC. Methods: Consecutive patients with pathologically diagnosed stage III/IV NSCLC who underwent first-line chemoimmunotherapy were retrospectively enrolled. The clinical outcomes used for biomarker evaluation were Objective Response Rate (ORR) and Overall Survival (OS). Results: Non-responders had significantly higher values of neutrophil to lymphocyte ratio (NLR, median: 5.36; IQR: 2.78–10.82 vs. 3.31; IQR: 2.15–4.12, p = 0.019), neutrophil to monocyte ratio (NMR, median: 14.00; IQR: 8.82–21.20 vs. 9.20; IQR: 7.45–11.20, p = 0.013), and systemic inflammation index (SII, median: 1,395; IQR: 929–3,334 vs. 945; IQR: 552–1,373, p = 0.025), but only NLR and NMR remained independently related with clinical response in multivariate logistic regression. In univariate analysis white blood cells (OR:1.2202; 95% CI: 1.0339 - 1.4400, p=0.019), neutrophils (OR:1.2916; 95% CI: 1.0692 - 1.5604, p=0.008), NLR (OR:1.3601: 95% CI: 1.0949 - 1.6896, p=0.005) and NMR (OR:1.2159; 95% CI: 1.00396 - 1.4221, p=0.015) were significantly associated with survival; Cox regression models confirmed that neutrophils, NLR and MLR were independently associated with survival; NLR at a cut-off value of 4.0 showed the better AUC (0.749) in predicting survival. Conclusions: Baseline complete blood cell count biomarkers, especially the NLR, can predict clinical outcomes in patients with advanced NSCLC treated with first-line chemoimmunotherapy.

The Galápagos Islands are one of the most emblematic protected areas on the planet, and also one of the most studied. Their main economic activity is tourism, which has grown rapidly in recent years. The increase in tourists is associated with the increase in population and the introduction of invasive species, which puts conservation at risk. This makes adequate management even more necessary and relevant on an international scale, since the economy of Galápagos depends on the good state of conservation of its ecosystems and species. Numerous studies have shown that social factors, rather than physical-natural ones, determine the success or failure of a marine protected area (MPA), so they must be urgently incorporated into all phases of MPA management. In this study we have analyzed the management of the protected areas of Galápagos: the National Park and the Marine Reserve. The methodology used presents five prescribed scenarios in which priority is given to one or other factors, each of which has an impact on biophysical and socio-economic systems that are influenced by the MPA. These scenarios have been called: proactive, interactive, centralized, learning, and formal management. The results show that the archipelago's protected areas follow a proactive management model, with a continuous feedback loop. This feedback is a key element in any adaptive management process, which also allows practitioners to anticipate future problems. Both public participation and strategic planning are essential.

Federated learning (FL) has emerged as a crucial technology in today’s data-centric technological environment, enabling decentralized machine learning and safeguarding user privacy. This study introduces “Federated Operations (FedOps) Mobile,” a novel FL framework optimized for the dynamic and heterogeneous ecosystem of mobile devices. FedOps Mobile enhances traditional FL approaches for mobile devices by integrating real-time operational control and advanced on-device training capabilities using TensorFlow Lite and CoreML, addressing critical challenges in scalability, efficiency, and system heterogeneity. Our approach utilizes a wide range of devices, facilitated by intelligent client-selection mechanisms. This mechanism evaluates the capabilities and readiness of multiple devices per client to ensure fair and efficient network participation. The framework also utilizes remote device control for seamless task management and sustained engagement, enabling continuous learning without compromising the user experience. We conducted extensive experiments to validate the framework’s performance, focusing on three core aspects: operational efficiency, model personalization, and resource optimization in multi-device environments. The results demonstrate that the proposed method is effective for efficient client selection, energy consumption, and model optimization.

We propose an $E_8 \otimes E_8$ unification of the standard model with pre-gravitation, on an exceptional Lie algebra-valued space . Each of the $E_8$ has in its branching an $SU(3)$ for space-time and an $SU(3)$ for three fermion generations. The first $E_8$ further branches to the standard model $SU(3)_c \otimes SU(2)_L \otimes U(1)_Y$ and describes the gauge bosons, Higgs and the left chiral fermions of the standard model. The second $E_8$ further branches into a right-handed counterpart (pre-gravitation) $SU(3)_{grav}\otimes SU(2)_R \otimes U(1)_g$ of the standard model, and describes right chiral fermions, a Higgs, and twelve gauge bosons associated with pre-gravitation, from which general relativity is emergent. We account for 208 out of the 496 degrees of freedom of $E_8 \otimes E_8$ and propose an interpretation for the remaining 288, motivated by the trace dynamics Lagrangian of our theory. We explain how the two copies of $SU(3)_{spacetime}$ together give rise to a 6D spacetime with signature $(3,3)$ which upon symmetry breaking gives rise to our 4D spacetime and to a second 4D anti-spacetime with flipped signature.

This study aims to provide empirical evidence on whether using renewable and non-renewable energy, CO₂ emissions and the resulting changes in temperature and precipitation can alter cereal yields in European Union countries. To this end, a panel data set covering 1992-2021 has been used to analyse the impact of climate change and economic factors on cereal production in European Union countries. The study employed various analytical techniques to understand better the relationship between climate change, energy consumption, and economic growth. These included using annual average temperature and rainfall to measure climate change and energy consumption and economic growth to analyse the economic aspects. To achieve the objective, feasible generalised least squares (FGLS) models with robust standard errors and bootstrap and a quantile regression (QR) model with marginal analysis were employed. The Westerlund cointegration test confirmed the presence of cointegration between cereal production and climate variables, economic growth, and energy consumption. The results indicate that increases in temperature and precipitation may contribute to increased cereal production in European Union countries. In contrast, energy consumption, including renewable energy and CO₂ emissions, may have a nonlinear effect on cereal production. Quantile regression analysis suggests climate change may impact crop yields most in countries with low and moderate cereal production per hectare. Increased CO₂ emissions may increase yields in the initial period, but excessive CO₂ may negatively impact cereal production in the long term. It would be advisable for countries with low and moderate crop productivity to consider implementing technological advances and combating global warming by modernising cultivation methods and making greater use of renewable energy sources.

(1) Background: Double-strand breaks (DSBs) in a single nucleus are usually measured using the sperm chromatin structure assay (SCSA), sperm chromatin dispersion (SCD) test, and comet assay (CA). We developed mono-dimensional single-cell pulsed-field gel electrophoresis (1D-SCPFGE) and angle-modulated two-dimensional single-cell pulsed-field gel electrophoresis (2D-SCPFGE) to observe DNA fragmentation in separated motile sperm. (2) Methods: We set up comparative standards, calibration curves, the required sensitivity, and eligibility criteria for test sperm to validate their measurement principles. (3) Results: We revealed that the conventional methods overlooked the interference of nucleoproteins in their measurements. In-gel proteolysis improves the measurement accuracies of 1D- and 2D-SCPFGE. We recommend using naked DNA for comparative standards and test specimens. Moreover, we have observed several dysfunctions that may induce DNA damage in the separated motile sperm. Overall, our discussion highlights the need to revisit the conventional univariable analyses based on the SCSA, SCD test, and CA. (4) Conclusions: Human infertility is a complex syndrome, and the aim of quality control in intracytoplasmic sperm injection is to identify the underlying dysfunctions remaining in the separated motile sperm that render them ineligible for injection. Well-designed, multivariable analyses with special consideration to confounding factors are necessary in future cohort studies.

Patients with Multiple Myeloma have an increased susceptibility to severe infections due to several various factors, especially the high tumor burden. The use of the anti-CD38 monoclonal antibodies-based therapies has changed the frequency and epidemiology of infections. We report herein the safety profile of the pivotal clinical trials conducted with anti-CD38 mAbs (daratumumab and isatuximab) and anti-SLAMF7 mAbs (elotuzumab) that led to the approval of regimens employed today in NDMM and RRMM patients.

Students studying dentistry and nursing experience anxiety daily, which affects both their general well-being and academic achievement. Anxiety is exacerbated by several circumstances, such as stressors in one's personal life, clinical environment exposure, and academic expectations. To effectively regulate anxiety and support students' achievement, treatments that take these elements into account must be designed. In this study, 271 students from the National and Kapodistrian University of Athens, Greece's departments of dentistry and nursing were polled. Being the following resources, participants filled out an electronic questionnaire that was uploaded to Google Forms and assessed their levels of stress, anxiety, depression, resilience, hope, and spiritual well-being: a) the Depression, Anxiety, Stress Scale (DASS-21), b) the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-12), c) the Adult Hope Scale (AHS), d) the Resilience Assessment Questionnaire (RAQ8), and e) the Brief Resilience Scale (BRS). Additionally, demographic data was gathered, such as gender, educational attainment, family income, and country of origin. Statistical analyses were performed to investigate the relationships between the variables, including hierarchical multiple linear regression and t-tests. The sample consisted of 271 students from the Department of Nursing (n=126, 46.5%) and Dentistry (n=145, 53.5%), with 68.60% of them being female, 80.10% being undergraduate students, and 48.30% being from Athens, the country's capital. Comparatively speaking, 74.50 percent of nursing students were female, while 62.80% of dental students were. Compared to dental students (2.10%), nurses (40.50%) participated in postgraduate studies at a higher rate. Compared to dental students (44.80%), nursing students reported a household income of just 13.90%, which is much less than €35,000. Anxiety was reported by 51.30% of participants overall, with dental students reporting higher anxiety than nursing students. Higher family wealth was associated with reduced stress levels, while female undergraduate students reported higher levels of anxiety than their male counterparts. Hope was a strong predictor of resilience, but stress and worry had a negative correlation. Promoting students' well-being and academic success requires effective stress-reduction and resilience-building techniques aimed to not only improve student performance but also support future healthcare professionals' personal sustainability and holistic growth.

(Background) Canine mammary tumors (CMT) have emerged as an important model for understanding pathophysiological aspects of human disease. Liquid biopsy (LB), which relies on blood-borne biomarkers and offers minimal invasiveness, holds promise for reflecting the disease status of patients. Small extracellular vesicles (SEVs) and their protein cargo have recently gained attention as potential tools for disease screening and monitoring. (Objectives) This study aimed to isolate SEVs from canine patients and analyze their proteomic profile to assess their diagnostic and prognostic potential. (Methods) Plasma samples were collected from female dogs grouped into CMT (malignant and benign), healthy controls, relapse, and remission groups. SEVs were isolated and characterized using ultracentrifugation (UC), nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Proteomic analysis of circulating SEVs was conducted using Liquid Chromatography–Mass Spectrometry (LC–MS). (Results) While no significant differences were observed in the concentration and size of exosomes among the studied groups, proteomic profiling revealed important variations. Mass spectrometry identified exclusive proteins that could serve as potential biomarkers for mammary cancer. These included Inter-alpha-trypsin inhibitor heavy chain (ITIH2 and ITI4), phosphopyruvate hydratase or alpha enolase (ENO1), eukaryotic translation elongation factor 2 (eEF2), actin (ACTB), transthyretin (TTR), beta-2-glycoprotein 1 (APOH) and gelsolin (GSN) found in female dogs with malignant tumors. Additionally, Vitamin D-binding protein (VDBP), also known as group-specific component (GC), was identified as a protein present during remission. (Conclusion) The results underscore the potential of proteins found in SEVs as valuable biomarkers in CMT. Despite the lack of differences in vesicle concentration and size between the groups, the analysis of protein content revealed promising markers with potential applications in CMT diagnosis and monitoring. These findings suggest a novel approach in the development of more precise and effective diagnostic tools for this challenging clinical condition.

Despite their Nobel prize-winning empirical confirmation, the interpretation of the Bell inequality remains controversial. By carefully analyzing Bell's work on nonlocality, we show how the correct appreciation of Bell's rationale calls for reformulating a widespread argument on quantum nonlocality, yielding a more consistent formulation of the problem. We delve into a formal proof of quantum mechanics' violation of local causality strikingly overlooked in favor of less appropriate arguments. For completeness, we also mention a few alternatives that may rationally justify considering quantum mechanics as a local theory.

Medical image segmentation is a critical step in various healthcare applications, aiding in diagnosis, treatment planning, and disease monitoring. In this study, we investigate the efficacy of a segmentation approach based on the 2D wavelet transform. Leveraging a dataset comprising 10 diverse medical images, we evaluate the performance of our segmentation method using three key metrics: accuracy, precision, and recall. Our findings demonstrate that the proposed approach enhances segmentation accuracy, offering promising results compared to existing methods. By harnessing the multi-resolution feature extraction capabilities of the 2D wavelet transform, our method achieves improved delineation of medical image structures, paving the way for more accurate and efficient healthcare interventions.

This study investigates the microbial composition of a commercially available Swiss fermented milk and colostrum product with a history of use in chronic condition management since 2014. The analysis, performed using the Axiom Microbiome Array, identified a high number of targets corresponding to microbial species classified as probiotics belonging to the Bifidobacteriaceae family. The array provided 28 unique targets, each corresponding to a specific microbe. Next, the amino acid sequences of beta-galactosidase and sialidase from Bifidobacteria and humans were studied because these enzymes are responsible for the production of GcMAF (Gc protein-derived Macrophage Activating Factor) from the Gc protein that is abundant in colostrum. The Bifidobacterial enzymes showed striking functional similarities with their human counterparts. In addition, the study explores the potential health benefits of this product with a focus on GcMAF and chondroitin sulfate, a glycosaminoglycan highly represented in milk and colostrum. The high concentration of specific Bifidobacteria strains contributes to these benefits through two mechanisms: enhanced GcMAF production and activation of chondroitin sulfate, which in turn exhibits GcMAF-like activity. These findings suggest that the Bifidobacteria-rich Swiss product could offer health benefits through these combined mechanisms.

Infrared thermography is a contactless imaging technique, useful to measure surface temperature at distance which has been widely applied in animal production. The possible applications within the pig husbandry include sow heat detection, reduction of the incidence of neonatal mortality, recognition of febrile state caused by pathogens, study of metabolic efficiency, evaluation of stress caused by heat, by constraints, or by aggressive interaction and meat quality prediction. Even if this technique could be easily influenced by environmental factors, the continuous improvement in the procedures and the decrease in the cost of the equipment will allow in the next future new and more applications in swine farming.

Due to the increasing use of computer equipment, institutions and companies face challenges, such as sensitive data leaks and the spread of hate speech, which have severe consequences for organizations and their employees. Addressing these challenges is essential to avoid financial losses, reputational damage, and impacts on the psychological health of those involved. This paper presents a solution based on microservices for monitoring computers used by employees in organizations, including capturing information from the equipment using spyware techniques and a web application for managing alerts. The solution seeks to detect data leaks, suspicious behaviour, and hate speech. The results of the evaluation indicate that the proposed solution has an efficient data capture time and can identify unwanted behaviour in a short period. The solution also includes applying prediction models to detect hate speech, achieving an average accuracy of approximately 87%. The performance, scalability, and security evaluation demonstrate that the solution is suitable for dealing with data leakage and hate speech challenges in the corporate environment.

The COVID-19 virus was first detected in Wuhan, China and its genesis was traced to infected bats, passed through an intermediate host to humans. COVID-19 or “Coronavirus” reached approximately 4 million confirmed cases in the United States by July 2020. The spread of this virus has affected both social and economic affairs on a global scale with more than 15 million confirmed cases worldwide in July 2020. The pandemic has proven a global public health and socio-economic crisis. In addition, the shelter-in-place orders provide an unprecedented opportunity for examining the resulting reduction in greenhouse gases and aerosols on the atmosphere. The Sentinel-5P satellite has shown distinct changes in atmospheric compounds over the COVID-19 epicenter in Wuhan. After Texas, U.S.A. established similar shelter-in-place orders to prevent the spread of the virus, the state’s industrial activity experienced an economic slowdown. This paper quantifies the changes in the atmosphere during the time of the COVID-19 slowdown over major cities in Texas and compares it to similar changes in Wuhan, China using satellite imagery.

In this paper, we introduce a new causal formula to distinguish Gliosarcoma (GSM) from Glioblastoma (GBM). Our formula combines Probabilistic Easy Variational Causal Effect (PEACE) with XGBoost, or eXtreme Gradient Boosting algorithm. Unlike prior research, which often relied on statistical models to reduce dataset dimensions before causal analysis, our approach uses the complete dataset with PEACE and XGBoost algorithm. PEACE provides a comprehensive measurement of direct causal effects, applicable to both continuous and discrete variables. It offers a spectrum of both positive and negative causal effects of the events causal effect values based on the degree ?, reflecting the rarity and frequency of the events. By using PEACE with XGBoost, we achieve a detailed and nuanced understanding of the causal relationships within the dataset features, facilitating accurate differentiation between GSM and GBM.

Integrated crop-livestock production (ILP) is an interesting alternative for more sustainable soil use. However, more studies are needed to analyze soil pore properties under ILP at the micrometer scale. Thus, this study proposes a detailed analysis of soil pore architecture at the micrometer scale in three dimensions. For this purpose, samples of an Oxisol under ILP subjected to minimum tillage (MT) and no-tillage (NT) with ryegrass as cover crop (C) and silage (S) were investigated. The soil micromorphological properties of the soil were analyzed using X-ray microtomography. The MT(C) system showed the highest values of porosity (c. 20.4%), connectivity (c. 32.8×103), volume (c. 26%), and number of pores (c. 32%) in a rod-like shape. On the other hand, the MT(S), NT(C), and NT(S) systems showed higher tortuosities (c. 2.2, c. 2.0, and c. 2.1) and lower pore connectivities (c. 8.3×103, c. 6.9×103, and c. 6.2×103), especially in S use. Ellipsoidal and rod-shaped pores predominated over spheroidal and disc-shaped pores in all treatments. The results of this study show that the use of ryegrass as a cover crop improves soil physical properties, especially in MT. For S use, the type of soil management (MT or NT) did not show any differences.

Purpose: Proximal Femur Fractures (PFFs) in elder patients lead to decreased productivity. Skilled nursing facilities (SNFs) and inpatient rehabilitation facilities (IRFs) are non-home destinations for post-discharge disposition. This study aims to evaluate the loss of independence (LOI) following PFFs and examine the economic impact it entails. Method: Literature from various databases was collected and analyzed retrospectively. The inclusion criteria included patients age >18 years and articles published after 1990. All studies were screened and a PRISMA chart was used to demonstrate the search process. 24 studies were finally used for review. Results: LOI following PFFs significantly increases with age. Fractures in geriatrics avail a significant amount of post-care resources and had longer lengths of stay. Furthermore, six pre-operative risk factors were identified for non-home disposition including age >75, female, non-Caucasian race, Medicare status, prior depression, Charlson Comorbidity Index. Patients discharged directly to home have lower total cost compared to those discharged to rehabilitation units. Loss of independence increases with advancing age. Discussion: PFFs can lead to serious loss of independence among elderly patients with direct impact on economic, social, psychological aspects and the healthcare system.

Antimicrobial peptides (AMPs) are promising tools for combating microbial resistance. However, their therapeutic potential is hindered by two intrinsic drawbacks – low target affinity and poor in vivo stability. Macrocyclization, a process that improves the pharmacological properties and bioactivity of peptides, can address these limitations. As a result, macrocyclic peptides represent attractive drug candidates. Moreover, many drugs are macrocycles that originated from natural product scaffolds, suggesting that nature offers solutions to the challenges faced by AMPs. In this review, we explore natural cyclic peptides from the DBAASP database. DBAASP is a comprehensive repository of data on antimicrobial/cytotoxic activities and structures of peptides. We analyze the data on small (≤25 AA) ribosomal and non-ribosomal cyclic peptides from DBAASP according to their amino acid composition, bonds used for cyclization, targets they act on, and mechanisms of action. This analysis will enhance our understanding of the small cyclic peptides that nature has provided to defend living organisms.

The detection accuracy of bridge superficial defect using the deep neural network approach decreases significantly under light variation and weak texture condition. To address these issues, an enhanced intelligent detection method based on the YOLOv8 deep neural network is proposed in this study. Firstly, multi-branch coordinate attention (MBCA) is proposed to improve the accuracy of coordinate positioning by introducing a global perception module in coordinate attention mechanism. Furthermore, a deformable convolution based on MBCA is developed to improve the adaptability for complex feature shapes. Lastly, the deformable convolutional network-attention-YOLO (DAC-YOLO) detection algorithm is formed by replacing the deep C2F structure in the YOLOv8 architecture with deformable convolution. A supervised dataset consisting of 4794 bridge surface damage images is employed to verify the proposed method, and results show that it achieves improvements of 2.0% and 3.4% in mAP and R. Meanwhile, the model complexity decreases by 1.2G, increasing the detection speed by 3.5/f·s-1.

Staphylococcus aureus bacteremia continues to be associated with significant morbidity and mortality, despite improvements in diagnostics and management. Persistent infections pose a major challenge to clinicians and have been consistently shown to increase the risk of mortality and other infectious complications. S. aureus, while typically not considered an intracellular pathogen, has been proven to utilize an intracellular niche, through several phenotypes including small colony variants, as a means for survival that has been linked to chronic, persistent, and recurrent infections. This intracellular persistence allows for protection from the host immune system and leads to reduced antibiotic efficacy through a variety of mechanisms. These include antimicrobial resistance, tolerance, and/or persistence in S. aureus that contribute to persistent bacteremia. This review will discuss the challenges associated with treating these complicated infections and the various methods that S. aureus uses to persist within the intracellular space.

Hydrotherapy, including the use of therapeutic showers and bathtubs, has been studied for its potential benefits in labor pain management. Previous research has indicated that hydrotherapy can alleviate pain, but comparative studies between therapeutic showers and bathtubs are scarce. Objective: This study aims to compare the effects of therapeutic showers and bathtubs on pain perception, labor duration, use of epi-dural analgesia, and maternal and neonatal outcomes during labor. Methods: A total of 124 pregnant women were included in this study. Participants were divided into two groups: those who used a thera-peutic shower and those who used a bathtub during labor. Pain levels were measured using a visual analog scale (VAS). Labor duration, use of epidural analgesia, types of delivery, maternal outcomes (postpartum hemorrhage, perineal status, maternal hypotension, fever, and breastfeeding), and neonatal outcomes (APGAR scores, fetal heart rate, complications, and neonatal unit admissions) were recorded and analyzed. Results: Both the therapeutic shower and the bathtub effectively reduced pain perception, with the bathtub showing a greater reduction in VAS scores. The therapeutic shower group experienced a signifi-cantly shorter labor duration compared to the bathtub group. The majority of participants in both groups did not require epidural analgesia, with no significant differences between the groups. There were no sig-nificant differences in the types of delivery. Maternal outcomes indicated a lower incidence of perineal tears and episiotomies in the therapeutic shower group. Neonatal outcomes, including APGAR scores and fetal heart rate, were similar between the groups, with no significant differences in complications or neo-natal unit admissions. Conclusions: Both therapeutic showers and bathtubs are effective for pain relief during labor, with the bathtub showing a higher reduction in pain intensity. The therapeutic shower is as-sociated with a shorter labor duration and a lower incidence of perineal tears and episiotomies. Both meth-ods are safe for neonatal well-being, making hydrotherapy a viable non-pharmacological option for pain management in labor. However, the therapeutic shower may offer additional benefits in terms of labor du-ration and maternal outcomes.

This study investigates the application of frequency augmentation techniques to improve condition-based maintenance (CBM+) systems for airborne weapon systems, focusing on the predictive accuracy of velocity and acceleration parameters. Utilizing MIL-STD-1553B MUX data from 138 sorties of fixed-wing aircraft, we explored six augmentation methods, including traditional interpolations (linear, quadratic, cubic spline) and advanced machine learning models (K-Nearest Neighbor, LSTM, and Bi-LSTM). Our findings indicate that while traditional methods like linear interpolation are more effective for velocity parameters, advanced ML techniques, particularly Bi-LSTM, provide better results for acceleration parameters, which exhibit more complex and rapid variability. The study underscores the necessity of tailoring augmentation approaches to specific parameter characteristics and highlights the potential of ML models in capturing intricate patterns within time-series data. These insights are critical for advancing CBM+ systems in military avionics, enhancing reliability and operational efficiency through improved data processing strategies. Future work should explore more performant augmentation techniques, such as by integrating multi-dimensional datasets, and explore ways to develop automated tools for a more powerful predictive maintenance framework.

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles has been discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we have compared the key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For the energy storage systems employing ultra capacitors, we have presented the characteristics such as cell voltage, cycle life, power density and energy density. Furthermore, we have discussed and evaluated the interconnection topologies for the existing energy storage systems. We have also discussed the hybrid battery-flywheel energy storage system as well as the mathematical modeling of the battery-ultracapacitor energy storage system. Toward the end, we have discussed energy efficient powertrain for hybrid electric vehicles.

One of the most prevalent and deadly types of cancer is breast cancer. The value and effectiveness of the current pharmacological therapy are, however, constrained. Using computational methods and publicly available data, the current study set out to identify the genes and molecular pathways linked to breast cancer. It also looked into potential treatments for the disease that would target these molecular processes. In this study, we mined genes that were strongly associated with breast cancer using text mining and GeneCodis. Using STRING and Cytoscape, protein-protein interaction (PPI) study was carried out. Candidate medications were then derived based on the drug-gene interaction study of the final genes. 2,658 genes linked to breast cancer were found by our investigation using text mining searches. Out of which 166 genes have been taken which are relevant to breast cancer. Ten genes representing ten pathways—which a total of ten proteins could target—were found by gene enrichment analysis. We have taken Holy Basil as our lead as it contains various bioactive compounds such as flavonoids, terpenoids, and phenolics, which have shown antioxidant, anti-inflammatory, and anticancer properties. For this analysis we choose the molecular docking technique to check the effects of different chemical constituents of Holy Tulsi on breast cancer targeted protein and compare their results. We’ve performed the molecular docking in between chemical constituents of Holy Basil and the targeted proteins and determined the binding affinity with the help of PyRx and BIOVIA Discovery studio software. Anti-mitotic activity of Pisum sativum using tulsi extract to check the cytotoxicity effect was done. To determine the toxicity level of the extract on rat liver was performed in the end. In conclusion, investigating candidate medications that target the genes/pathways relevant to breast cancer in order to uncover possible treatments may be accomplished through drug discovery employing in silico text mining and pathway analysis technologies along with the wet lab experimentation with plants and preclinicals.

Barley is rich in phenolic compounds, providing health benefits and making it a valuable addition to a balanced diet. However, most studies focus on these compounds at barley's final maturity, neglecting their synthesis during grain development and its impact on barley quality for food applications. This study investigates phenolic profiles during grain development in four hull-less barley genotypes with different grain colors, specifically bred for food applications. The objectives were to determine the phenolic profile and identify the optimal maturity stage for maximum phenolic content and antioxidant capacity. Using UPLC-MS/MS and in-vitro antioxidant capacity assays, results show that total phenolic compounds decrease as grain matures due to increased synthesis of reserve components. Flavan-3-ols, phenolic acids, and flavone glycosides peaked at immature stages, while anthocyanins peaked at physiological maturity. The harvest stage had the lowest phenolic content, with a gradient from black to yellow, purple, and blue genotypes. Antioxidant capacity fluctuated during maturation, correlating positively with phenolic compounds, especially bound phenolic acids and anthocyanins. These findings suggest that early harvesting of immature grain can help retain bioactive compounds, promoting the use of immature barley grains in foods. To support this market, incentives should offset costs associated with decreased grain weight.

The mechanical properties of the materials stored inside agricultural silos influence the loads generated inside them. The different silo calculation methodologies allow predicting these loads under static and dynamic conditions if the mechanical properties of the stored materials are known. It has been known for many years that these properties are highly dependent on the moisture content of the material. However, to date there are not many studies focused on its determination. The goal of this research is the determination of the angle of internal friction, apparent cohesion, dilatancy angle and apparent specific weight of maize subjected to different moisture contents. Direct shear and oedometer assay devices were used for this purpose. In addition, the maize samples used were moistened using a climatic chamber. Moisture contents applied to maize sample ranged from 9.3% to 17.4%. The results obtained for the angle of internal friction and apparent cohesion, as well as those obtained for the apparent specific weight, were similar to those reported in the literature. However, the values obtained for the dilatancy angle of maize as a function of moisture content could not be compared because nothing has been published so far. The values obtained for this parameter overlap with those published for this material under ambient conditions. In addition, no direct relationship between the values obtained for this parameter and the moisture content of the sample could be found. Finally, the apparent specific weight increased with increasing moisture content of the samples, which differed from that published in the literature. The values provided here can be used for the optimization of storage and handling structures for granular agricultural materials using numerical methods.

The prevalence of multidrug-resistant Gram-negative infections, particularly carbapenem-resistant strains, has become a significant global health concern. Ceftazidime-avibactam (CZA) has emerged as a promising treatment option. However, data on its efficacy and safety in children are scarce, necessitating further investigation. We conducted a retrospective study at a tertiary hospital in Spain from February 2019 to January 2022. Pediatric patients (<16 years) treated with CZA for confirmed or suspected multidrug-resistant Gram-negative infections were included. Clinical and microbiological characteristics, treatment approaches, and outcomes were examined. Eighteen children received CZA treatment. All had complex chronic conditions, with the most frequent underlying main diseases being liver transplantation (n=8) and biliary atresia (n=4). The predominant type of infection for which they received CZA was intra-abdominal infections caused or suspected to be caused by OXA-48-producing Klebsiella pneumoniae. CZA was generally well tolerated. Within the first month of starting CZA therapy, 2 patients died, with one case directly linked to the infection’s fatal outcome. Some patients needed repeated courses of therapy due to recurrent infections, yet no resistance development was noted. In summary, the use of CZA showed effectiveness and safety, while the lack of resistance development highlights CZA’s potential as a primary treatment option against OXA-48-producing infections.

This article examines varying viewpoints on the single-submission policy in scientific publishing, which has recently come under attack. The rule permits the sequential, rather than simultaneous, submission of a manuscript to more than one journal and dictates that an author(s) must wait for a response from one journal before resubmitting the same work to another for consideration. A corollary is that legitimising multiple-submissions would create more problems than it could solve.