Multi-criteria decision analysis (MCDA), one of the prevalent branches of operations research, aims to design mathematical and computational tools for selecting the best alternative among several choices with respect to specific criteria. In the cloud, MCDA based online brokers uses customer specified criteria to rank different service providers. However, subjected to limited domain knowledge, the customer may exclude relevant or include irrelevant criterion, which could result in suboptimal ranking of service providers. To deal with such misspecification, this research proposes a model, which uses notion of factor analysis from the domain of unsupervised machine learning. The model is evaluated using two quality-of-service (QoS) based datasets. The first dataset i.e., feedback from customers, was compiled using leading review websites such as Cloud Hosting Reviews, Best Cloud Computing Providers, and Cloud Storage Reviews and Ratings. The second dataset i.e., feedback from servers, was generated from cloud brokerage architecture that was emulated using high performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu). The simulation runs in a stable cloud environment i.e. when uncertainty is low, shows that online broker (equipped with the proposed model) produces optimized ranking of service providers as compared to other brokers. This is due the fact that proposed model assigns priorities to criteria objectively (using machine learning) rather than using priorities based on subjective judgments of the customer. This research will benefit potential cloud customers that view insufficient domain knowledge as a limiting factor for acquisition of web services in the cloud.

We present a general theory of estimation of analysis error covariances based on cross-validation as well as a geometric interpretation of the method. In particular we use the variance of passive observation–minus-analysis residuals and show that the true analysis error variance can be estimated, without relying on the optimality assumption. This approach is used to obtain near optimal analyses that are then used to evaluate the air quality analysis error using several different methods at active and passive observation sites. We compare the estimates according to the method of Hollingsworth-Lönnberg, Desroziers et al., a new diagnostic we developed, and the perceived analysis error computed from the analysis scheme, to conclude that, as long as the analysis is near optimal, all estimates agree within a certain error margin.

The overall comfort experienced by an individual in an n-dimensional space can be theoretically constructed using a mathematical equation, that relates the comfort experienced by an individual in a particular point in space with spatial points associated with higher comfort attributes and the desirable factors affecting the current environmental space.

This review provides an overview of eXplainable AI (XAI) methods for oncological ultrasound image analysis and compares their performance evaluations. A systematic search of Medline Embase and Scopus between March 25 and April 14 2024 identified 17 studies describing 14 XAI methods, including visualization, semantics, example-based, and hybrid functions. These methods primarily provided specific, local, and post-hoc explanations. Performance evaluations focused on AI model performance, with limited assessment of explainability impact. Standardized evaluations incorporating clinical end-users are generally lacking. Enhanced XAI transparency may facilitate AI integration into clinical workflows. Future research should develop real-time methodologies and standardized quantitative evaluative metrics.

The primary objective of this study was to demonstrate the potential of digital image analysis as a tool to identify microplastic (MP) particles in surface waters and to facilitate their characterisation in terms of 2D and 3D morphology. Digital image analysis preceded by microscopic analysis was used for an exhaustive quantitative and qualitative evaluation of MPs isolated from the Vistula river. Using image processing procedures, 2D and 3D shape descriptors were determined. The Principal Components Analysis (PCA) was used to interpret the relationships between the parameters studied, characterising MP particle geometry, type and colour. This multivariate analysis of the data allowed 3 or 4 main factors to be extracted, explaining approximately 90% of the variation in the data characterising MP morphology. It was found that the first principal component for granules, flakes and films was largely represented by strongly correlated with 2D shape descriptors (area, perimeter, equivalent area diameter) and 3D shape descriptors (CSF, Compactness, Dimensionality). Considering the scraps, PC1 was represented by only five of the above descriptors, and the Compactness variable had the largest contribution to PC2. In addition, for granules, flakes and films, a relationship between 2D shape and the colour of their particles could be observed. For the most numerous MP group identified of multicoloured scraps, no such association was found. The results of our study can be used for further multivariate analysis regarding the presence of microplastic floating on the river surface, with a particular focus on particles of secondary origin. This is of key importance for optimising future efforts in conducting small-scale and multidimensional monitoring of and reducing plastics in the aquatic environment.

Background: Though ancient Greece preserves many pictures of combat sports, there is research in terms of biomechanics on the principles of human motion. This research aimed to investigate Pankration postures of ancient Greek athletics, expecting to bridge the gap between historical sports practices and contemporary biomechanical applications. Methods: This study employed computational tools to analyze two images from ancient Greek Pankration, constructing a static multi-segmental model. Anthropometric models simulated postures analogous to those in historical depictions. Analysis estimated joint forces and moments, along with weight distribution and ground reaction forces for these postures. Implications for training and strength development were deduced through integration with modern scientific insights. Moreover, strategic elements of these postures were assessed using game theory to explore their correspondence with contemporary theoretical constructs. Results: The findings indicated that static postures facilitate the development of tendon stiffness, joint stability, and neuromuscular control. In the "readiness" posture, 68% of the athlete's centre of gravity (CoG) was distributed to the hind leg, enhancing stability and power generation, while the front leg promoted agility. Analysis of the kick posture revealed delivery with a dorsiflexed ankle and pronounced heel protrusion.Conclusion: The application of the proposed model suggests that ancient athletes optimized their performance using biomechanical principles, thereby gaining a competitive advantage. This study highlights the value of integrating ancient biomechanical strategies with contemporary athletic training and injury prevention, advocating for a synthesis of historical practices and modern biomechanical analysis in combat sports.

We propose a novel approach for time series forecasting with many predictors, referred to as the GO-sdPCA, in this paper. The approach employs a variable selection method known as the group orthogonal greedy algorithm and the high-dimensional Akaike information criterion to mitigate the impact of irrelevant predictors. Moreover, a novel technique, called peeling, is used to boost the variable selection procedure so that many factor-relevant predictors can be included in prediction. Finally, the supervised dynamic principal component analysis (sdPCA) method is adopted to account for the dynamic information in factor recovery. In simulation studies, we found that the proposed method adapts well to unknown degrees of sparsity and factor strength, which results in good performance even when the number of relevant predictors is large compared to the sample size. Applying to economic and environmental studies, the proposed method consistently performs well compared to some commonly used benchmarks in one-step-ahead out-sample forecasts.

An undesirable sensory attribute (“floral taint”) has been recently detected in red wines in some winegrowing jurisdictions in North America (e.g. Ontario, British Columbia, Washington), caused by introduction of frost-killed leaves and petioles [materials-other-than-grapes (MOG)] during mechanical harvest and winemaking. It was hypothesized that terpenes, norisoprenoids, and higher alcohols would be the main responsible compounds. Objectives were to investigate causative volatile compounds for floral taint, and explore threshold concentrations for this problem. Commercial wines displaying varying intensities of floral taints were subjected to GC-MS and sensory analysis. Several odor-active compounds were higher in floral-tainted wines, including terpenes (geraniol, citronellol, cis- and trans-rose oxide), norisoprenoids (β-damascenone, β-ionone), five ethyl esters, and three alcohols. Thereafter, fermentations of Cabernet franc (CF) and Cabernet Sauvignon (CS) (2016, 2017) were conducted. MOG treatments were (wt/wt): 0, 0.5%, 1%, 2% and 5% petioles, and 0, 0.25%, 0.5%, 1%, and 2% leaf blades. Terpenes (linalool, geraniol, nerol, nerolidol, citronellol, citral, cis- and trans-rose oxides, eugenol, myrcene), norisoprenoids (α- and β-ionone), and others (e.g. hexanol, octanol, methyl and ethyl salicylate) increased linearly/quadratically with increasing MOG levels in both cultivars. Principal components analysis separated MOG treatments from the controls with 5% petioles and 2% leaves as extremes. Increasing MOG levels in CF wines increased floral aroma intensity, and were primarily associated with terpenes, higher alcohols, and salicylates. Increased leaf levels in CF were associated with higher vegetal and earthy attributes. Increased petioles in CS were not correlated with floral aromas, but increased leaves increased floral, vegetal and herbaceous attributes. Overall, petioles contributed more to floral taint than leaves through increased terpenes and salicylates (floral notes), while leaves contributed norisoprenoids and C6 alcohols (green notes).

Boeing and Airbus developed a special testing procedure to investigate the compressive response of laminates that have been impacted (following standards ASTM D 7137 and DIN 65561). This study focuses on both experimental and numerical analysis of Kevlar plates subjected to compression after impact. To ensure high quality and appropriate mechanical properties, the composite plates were manufactured using autoclaving. The DIN 65561 protocol was followed for all three test systems. Initially, ultrasonic C-scanning was performed on all plates before testing to confirm they were free of any significant defects arising from the manufacturing process. Subsequently, low-energy impact testing was conducted at levels ranging from 0 to 8 Joules. Three specimens were tested at each energy level. After the impact, all specimens underwent ultrasonic C-scanning again to assess the internal delamination damage caused by the impactor. Finally, both pristine and impacted specimens were subjected to compressive testing using the special jig specified in DIN 65561. The compressive impact strength results obtained from these tests were plotted against the delamination area measured by C-scanning. This data was then compared to results obtained from specimens with artificial damage. Semi-empirical equations were used to fit both sets of curves. The same procedure (impact testing, C-scanning, and data analysis) was repeated to investigate the relationship between impact energy and total delamination area. Lastly, finite element modeling was employed to predict the buckling stresses that develop under compression in the impacted systems studied. These modelling approaches have demonstrated good accuracy in reproducing experimental results for CAI tests.

Background: Gait analysis systems offer invaluable insights for rehabilitation, yet their expense limits clinician access. We developed GAITWell®, a low-cost modular system for capturing spatiotemporal gait variables, and evaluated its measurement properties. Methods: The GAITWell® uses discreet binary sensors on interconnected boards to collect gait data, which is then analyzed using the DBSCAN algorithm on the Cartesian points from sensor outputs. Reliability was assessed using ICC2,1, standard error of the mean (SEM) and Bland-Altman plots. Validity was determined by comparing GAITWell® with the Qualisys Pro-Reflex system. Results: Participated 38 healthy adults, with an average age of 33.2 years (SD 13.0). Correlations between GAITWell® and the Qualisys system ranged from moderate to very high for most gait variables, with the exception of stride length, which demonstrated a low but significant correlation (r = .360, p < .05). The ICC2,1 indicated moderate to good agreement for most gait variables. Stance and double support times, cadence, and base of support exhibited poor reliability, characterized by larger SEM and limits of agreement. Conclusions: Our findings indicate that the GAITWell® system is a promising tool for gait analysis. Future research will enhance sensor accuracy and refine algorithms to improve reliability.

In the rapidly evolving landscape of AI-supported programming education, there's a growing interest in leveraging such tools to support students helping about what good code makes out. This study investigates the impact of ChatGPT on code quality among part-time undergraduate students enrolled in introductory Java programming courses. With no prior Java experience, students from two separate groups completed identical programming exercises emphasizing coding conventions and code quality. Utilizing static code analysis tools, we assessed adherence to a common coding convention ruleset and calculated cyclomatic and cognitive complexity metrics for submitted code. Our comparative analysis highlights significant improvements in code quality for the ChatGPT-assisted group (treatment group), with marked reductions in rule violations and both cyclomatic and cognitive complexities. Specifically, the treatment group demonstrated greater adherence to coding standards, with fewer violations across several rules, and produced code with lower complexity. These results suggest that ChatGPT can be a valuable tool in programming education, aiding students in writing cleaner, less complex code and better adhering to coding conventions. However, the study's limitations, including the small sample size and the novice status of the participants, necessitate further research with larger, more diverse populations and in different educational contexts.

Objective To investigate the functional and biological significance of telomere-related active genes in cholangiocarcinoma (CCA) using single-cell sequencing and cell communication analysis. Methods First, we identified and annotated different cell types in CCA samples using single-cell sequencing data. Pseudotime analysis revealed the transcriptional status and differentiation process of CCA cells. We then explored interactions between CCA cells and their regulatory pathways through cell communication analysis. 47 key genes related to telomere activity were identified, and GO and KEGG pathway enrichment analysis was performed. Additionally, we constructed a prognostic model and verified the model's predictive efficacy. Finally, we identified genes associated with drug sensitivity in CCA patients and identified pathways associated with CCA prognosis through tumor TMB analysis. Results We identified 452 active telomere-associated cells. Then, we assessed telomere associated gene activity, obtaining 47 differentially expressed telomere genes by intersecting with CCA differentially expressed genes. Major up-regulated signaling pathways, including MIF-(CD74+CXCR4) and HLA-A-CD8A, were identified through pseudotime analysis. Three telomere-associated prognostic genes were identified using LASSO analysis, and prognostic-related models were built. In addition, PBRM1 mutation load was found to be highest in the high-risk group, making it a potential diagnostic target. Finally, drug sensitivity analysis revealed higher sensitivity to certain therapeutic drugs in the high-risk group, providing guidance for tailored CCA treatment. Conclusion The MIF-(CD74+CXCR4) and HLA-A-CD8A signaling pathways appear to be major pathways for CCA cell proliferation. Prognostic models based on telomere-associated genes show promise for application, indicating the biological and clinical significance of telomere activity genes in CCA.

In this study is considered the design and implementation of pilots in desalination plants, in a systematic way, to evaluate energy improvements in water desalination processes. Pilot tests with the latest generation of reverse osmosis membranes in large desalination plants are becoming increasingly common, as small-scale experiments are carried out on the operation of new generation membranes with better salt rejection and lower energy consumption, to achieve the best water quality required for each case at the lowest possible cost. In this way, pilot tests are being carried out before the decision is made whether or not to change the reverse osmosis membranes, as this represents a significant investment and we minimize the risk of making a mistake in order to ensure the best results in terms of energy consumption, operating costs and reducing the environmental impact while complying with the required water quality. In this case, the Pareto analysis is used to highlight the 2 or 3 most significant causes whose treatment affects more than 80% of the possible energy improvement to be implemented. In this sense, figure 3 below shows the Pareto diagram for the energy improvement of N plants in a given territory. A series of factors that can affect this energy improvement have been numbered from 1 to 7, such as the seawater intake, the decision on the membranes, the energy recuperators, the high-pressure pump, the decisions on the pre-treatment, the feed pump or the post-treatment. The Pareto diagram has been studied at territorial level with a total of 180 seawater desalination plants. The novelty of this article is to apply Pareto diagram to a study of a total of 180 seawater desali-nation plants at territorial level in Canary Islands.

Objectives: This study aims to explore the use of murine models in peripheral nerve transection research, evaluating and synthesizing key methods for analyzing nerve regeneration to guide future research and clinical interventions. Methodology: A systematic review was conducted in February 2024, adhering to Cochrane and PRISMA 2020 guidelines, using Medline, Scielo, and Lilacs databases. The focus was on experimental studies of nerve regeneration in animal models post-transection. Only experimental clinical trials reporting nerve regeneration outcomes were included; studies lacking a comparator group or functional evaluation methods were excluded. Results: Out of 273 studies initially identified from MEDLINE, 19 were selected for detailed analysis. The average study included 32.5 subjects, with about 10.16 subjects per intervention subgroup. The predominant model was the sciatic nerve injury with a 10mm gap. The most common intervention involved unprocessed adipose-derived stem cells, utilized in 14 articles. Conclusions: The review underscores the significant potential of current methodologies in peripheral nerve regeneration, particularly highlighting the use of murine models and thorough evaluation techniques. These studies significantly contribute to our understanding of nerve regeneration processes and inform directions for future research.

There is a recent growth and development with regard to the female athlete. This trend has been reflected in a greater concern for aspects such as nutrition, body composition and the health of female athletes, given the repercussion of these factors on their sporting performance. The aim was to carry out an anthropometric and nutritional assessment of elite Spanish female football athletes based on different biochemical parameters. Ethical consent was obtained from a total of 21 players from a Spanish elite women's football team(20-33years). Anthropometric analysis was carried out using the International Society for the Advancement of Kineanthropometry(ISAK). Clinical analyses were performed by the club's medical staff at the beginning of the season through serum and fasting urine samples taken by the players. The athletes presented fat% of 19.1(SD±2.89). 100% of the players had Mg values within the reference values. Values below reference values were observed for Hb (85.7%), vit.D (33.3%), ferritin (23.8%), serum iron (28.6%), transferrin (4.8%) and TSI (42.9%); and above for CK (42.9%), basal cortisol (38.1%), testosterone (19%) and creatinine, total cholesterol, iron, transferrin, TSI and serotonin (4.8%). Differences in Mg levels were only observed between playing positions (p<0.05). There were associations between age and vit.D levels (r=0.607), and weight with vit.D levels (-0.464) and blood cholesterol (-0.487) among others. Given the nutritional knowledge of Spanish elite female football players, as well as the prevalence of deficiencies in iron metabolism parameters and vit.D levels in athletes, the need to implement a correct nutritional assessment and education in this type of athletes is highlighted

Sentiment analysis has become an important tool for understanding public opinion across languages and domains. Recently, there has been an increase in the number of studies on sentiment analysis in low-resource languages such as Kazakh. This is important to ensure that modern text analysis technologies are accessible to all users, regardless of their language background. The aim of the study is to create a sentiment analysis model for analyzing texts in Kazakh. As part of this work, we aim to use fine-tuning techniques on our own dataset for already existing models, thus improving their accuracy and efficiency for analyzing Kazakh language texts. This paper presents a manually collected dataset "KazIntTelCom" from the city information service 2GIS, consisting of user reviews, manually annotated by the authors taking into account the polarity of sentiment (i.e. negative positive or neutral). This dataset was used to fine-tune two pre-trained multi-lingual Transformer-based sentiment analysis models taken from the HuggingFace platform. The distillBERT and XLM-RoBERTa models were used for tuning. Also, the models were tested on the dataset "KazSAnDRA". The results show that accurate tuning even on a relatively small dataset gives a significant increase in performance, which is confirmed by an increase in the accuracy index by 20%-30%. In addition, false misses and false detections are analyzed, which allows us to identify directions for further improvement of the models. The contribution of this work, in addition to the dataset, is the analysis of model errors, which will help future developers to make more accurate settings of hyperparameters of training for sentiment analysis in Kazakh. These results are important for natural language processing and their adaptation to low-resource languages, promoting more inclusive and equitable access to modern analytical tools. Thus, this study demonstrates the effectiveness of the Transformers architecture for sentiment analysis in Kazakh and opens new opportunities for further model improvement.

This study provides a comprehensive analysis of global patent trends in battery recycling, focusing on secondary batteries and related technologies across Korea, China, and the United States. The data, collected from various patent databases, was quantitatively analyzed to identify technology trends and direct future development. The analysis reveals distinct emphases on technologies such as lithium-ion and waste battery recycling, highlighting notable differences in patent activities among key companies and countries. China's large number of patents in battery manufacturing processes contrasts with the USA's focus on electrochemical cell construction and storage systems, while Korea shows significant activity in waste battery technology. The study underscores the competitive landscape and innovation efforts in the battery recycling sector, providing insights into the technological focuses and priorities of each country. It also identifies key challenges, such as the need for consistent innovation and broader geographic coverage in Korea, enhancing patent influence and international presence in China, and ensuring high patent quality and fostering innovation in lagging sectors in the United States. Addressing these challenges through enhanced collaboration, increased R&D investments, and supportive policies is crucial for strengthening the global position and driving further innovation in the battery recycling sector.

Exoskeleton technology has been shown to be useful for individuals with spinal cord injury (SCI), potentially facilitating their recovery of motor function and social reintegration. However, studies on the safety and usability of exoskeletons are limited. This study aimed to design a powered exoskeleton for SCI and evaluate its safety and usability. Ten healthy adults participated in this study. The prototype exoskeleton featured an adjustable frame, computer-controlled hip and knee joint actuators, and a gait-trigger sensor. The experimental actions included walking, standing, and sitting, with and without the prototype. Safety outcomes included adverse events, vital signs, numerical rating scale (NRS) scores for pain, discomfort, and fatigue, and prototype-human body clearance. Usability outcomes included donning and doffing times, subjective ratings, gait speed, stride length, and kinematic parameters of hip and knee joint angles. Safety outcomes showed no serious adverse events, stable vital signs, minimal NRS scores, and acceptable clearance. Usability outcomes showed high efficiency and received positive ratings. Kinematic parameters showed significant positive correlations between normal walking and walking with the prototype for both hip and knee joint angles, confirming its effectiveness in assisting walking. However, further device improvements and gait parameter tuning are necessary for future clinical application.

In this paper, single and repetitive frequency UIS characteristics of 1200 V asymmetric (AT)and double trench silicon carbide (DT-SiC) metal–oxide-semiconductor field-effect transistors (MOSFETs) under different working conditions are investigated by experiment and simulation. For asymmetric trench SiC MOSFETs, the failure mode is all thermal runaway under working conditions. However, the failure mode of double trench SiC MOSFETs mostly is gate oxide rupture, which indicates an instable avalanche robustness under UIS stress. The variations of measured parameters are recorded to evaluate typical electrical features of device failure. Furthermore, TCAD simulation is used to reveal the electro-thermal stress inside the device during avalanche. Additionally, failed devices are decapsulated to verify the location of failure point from the perspective of the semiconductor die. Finally, a new type of stepped-oxide vertical power DT MOSFET with P-type shielding and current spread layers is proposed for improvement of gate dielectric reliability.

Congenital heart disease (CHD) is the most commonly detected congenital anomaly and affects up to 1 % of all live-born neonates. Current guidelines support the use of Chromosomal Microarray Analysis (CMA) and Next Generation Sequencing (NGS) as diagnostic approaches to identify genetic causes. The aim of our study was to evaluate the diagnostic yield of CMA and NGS in a cohort of neonates with both isolated and syndromic CHD. The present study included 188 infants under 28 days of age with abnormal echocardiography findings hospitalized at the Department of Neonatology, UMC Ljubljana, between January 2014 and December 2023. Phenotypic data were obtained for each infant by retrospective medical chart review. We established the genetic diagnosis of 22 distinct syndromes in 17% of neonates. The most common genetic diagnoses were 22q11.2 microdeletion (22.7%) and CHARGE syndromes (22.7%), Noonan syndrome (9.1%), and Williams syndrome (9.1%). In addition, we detected variants of uncertain significance in 4.8% of neonates. Timely genetic diagnosis is important for the detection of syndrome-related comorbidities, prognosis, reproductive genetic risks and, when appropriate, genetic testing of other family members.

This study addresses the importance of conducting mass movement susceptibility mapping and hazard assessment using quantitative techniques, including machine learning, in the Northern Lima Commonwealth (NLC). Previous exploration of the topographic variables revealed high correlation and multicollinearity among some of them, which led to dimensionality reduction through principal component analysis (PCA). Six susceptibility models were generated using weights of evidence, logistic regression, multilayer perceptron, support vector machine, random forest, and naive Bayes methods to produce quantitative susceptibility maps and assess the hazard associated with two scenarios: the first being an El Niño phenomenon and the second being an earthquake exceeding 8.8Mw. The main findings indicate that machine learning models exhibit excellent predictive performance for the presence and absence of mass movement events, as all models surpassed an AUC value of >0.9, with the random forest model standing out. In terms of hazard levels, in the event of an El Niño phenomenon or an earthquake exceeding 8.8Mw, approximately 40% of the NLC area would be exposed to the highest hazard levels. It also highlights the importance of integrating methodologies to reduce model uncertainty, such as comprehensive analysis of variables supported by high quality data and organized workflows. The findings of this research are expected to serve as a supportive tool for land managers in formulating effective disaster prevention and risk reduction strategies.

Research has shown that unsociability, reflecting as a personal choice, is not necessarily associated with socio-emotional problems in Western countries, and the associations between unsociability and peer problems are consistently evident in Chinese culture. Yet the strength and direction of the associations were mixed. The present study aimed to examine whether unsociability is associated with peer problems and explored the potential moderators among the associations. A meta-analysis was conducted using publications that measured unsociability and peer problems. A total of 21 articles involving 43 effect sizes from 12,696 Chinese children and adolescents were included. The results revealed that (1) unsociability was positively associated with peer problems (r = .32, p < .001) among children and adolescents. (2) informants (i.e., self-reports, peer nominations, teacher ratings, parent ratings) and living areas (i.e., urban, suburban, and rural areas) significantly moderated the associations between unsociability and peer problems. Specifically, the associations were stronger for peer-nominated unsociability, self-reported peer problems, and samples in suburban areas. These findings shed light on unsociability linked to higher levels of peer problems among Chinese children and adolescents. Still, the influences are unique to peer problems and moderated by both data sources and environmental factors.

This paper utilizes the 2020 financial data of A-share listed companies, both ST and non-ST, as the data sample. The model is constructed employing the Factor-Logistic fusion algorithm. Eight key indicator factors were selected from the frameworks of profitability, solvency, operating capacity, development potential, shareholder retained earnings, cash flow and asset growth. An independent indicator system was subsequently established to address the issue of collinearity among risk indicators. The results of model are presented in the form of probabilities, enhancing the interpretability of model. The weights of the features indicate the influence of different features on the final outcome. The model achieves a prediction accuracy of over 89%, with an AUC score exceeding 95%. Finally, by applying the principles of interval estimation theory in statistical hypothesis testing, the risk levels are categorized as A-level representing significant risk, B-level representing moderate risk, C-level representing minor risk and D-level representing no risk. This paper aims to provide a comprehensive definition of a universal financial risk management warning model for enterprises, applicable to all enterprises in China.

This study introduces a novel algorithm tailored for the precise detection of lower outliers in univariate datasets, particularly suited for scenarios with a single cluster. The approach leverages a combination of transformative techniques and advanced filtration methods to efficiently segregate anomalies from normal values. Notably, the algorithm emphasizes high precision, ensuring minimal false positives, and requires only a few parameters for configuration. Its unsupervised nature enables robust anomaly filtering without the need for extensive manual intervention. To validate its efficacy, the algorithm is rigorously tested using real-world data obtained from photovoltaic (PV) module strings with similar DC capacities, containing various anomalies. Results demonstrate the algorithm's capability to accurately identify lower outliers while maintaining computational efficiency and reliability in practical applications.

This study investigates the impact of thin flame combustor design on hydrogen flame characteristics and combustion performance through numerical simulations. Variations in flame shape and combustibility between 100% methane and 100% hydrogen combustion are analyzed. Three combustor header shapes (flat, concave, and convex) are modeled to assess their influence on flame behavior. Results show distinct flow patterns, with concave headers promoting strong central flows and convex headers dispersing the flow outward. Temperature field analysis indicates that hydrogen flames have higher temperatures and shorter quenching distances compared to methane flames. A comparative analysis of combustion products is conducted to evaluate combustion performance and NOx emissions. Consequently, the concave header has high combustibility and increases temperatures and NOx fraction in hydrogen combustion.

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics, and thermodynamic parameters of peanut shell using TGA under atmospheric air. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (Eα) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R2) close to 1. Pre-exponential factors using FWO range from 2.19×106 to 8.06×107 s–1, and for KAS range from9.72×105 to 2.25×107 s–1. Thermodynamic analysis indicates a low-energy barrier (≤ ±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass.

This article aimed to evaluate, using statistical tools, the generation and composition of urban solid waste (MSW) in the city of Belém, Pará, from nine urban collection sectors in the municipality, and the average nominal income of the population. Approximately 900kg of urban solid waste were col-lected from the municipality in the period from 2021 to 2022. Statistical tests were carried out on hypotheses with 5% significance in comparative evaluations, and their respective average nominal incomes. The results indicated that the organic fraction corresponds to 55.57% of the waste generated in the municipality, 14.26% is inert waste (potentially contaminating) and 0.67% is miscellaneous waste. It was observed that the waste generated by families with high purchasing power tends to contain higher percentages of recyclables, while in families with lower purchasing power the highest percentages tend to be organic. Knowledge of the generation of MSW is fundamental for the choice and dimensioning of operations and processes involved in the management chain at the municipal level. The decentralization of services offered based on solid waste management would enable greater success in serving the population.

Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for Breast Cancer Liver Metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, it aimed to shed light on the diversities of this process. This research investigates Breast cancer liver metastasis relapse by employing a comprehensive approach that integrates data filtering, Gene Ontology and KEGG Pathway Analysis, Overall Survival analysis, identification of the Alteration in the DEGs, Visualization of Protein-Protein Interaction Network, Signor 2.0, identification of positively correlated genes, screening results of the function of hub genes, immune cell infiltration analysis, genetic alternation analysis, Copy number variant analysis, Gene to mRNA interaction, transcription factor analysis , autodocking and identification of Potential Treatment Target. This study’s integrative approach unveils metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.

In order to study the key factors that induce green travel among urban residents under the carbon inclusive mechanism, analyze the formation mechanism of green travel intention and reduce urban transportation carbon emissions. First, an SEM model of urban residents’ green travel under the carbon inclusive mechanism was constructed (the 8 latent variables including Subjective Norms (SN), Attitude (ATT), Perceived Behavioral Control (PBC), Habits (HAB), Perceived Usefulness (PU), Perceived Ease of Use (PEU), Continuous Intention of Carbon Inclusive Platform application (CI), Behavioral Intention (BI)). Then, based on the data analysis and path analysis results of 354 valid sample data obtained through online surveys, the interrelationships and corresponding parameters between latent variables and manifest variables were obtained. The results show that SN, ATT, PBC, HAB, PU, PEU and CI all have varying degrees of effects on BI. Among them, in the direct influence relationship, the influence path coefficients of CI, PBC and ATT on BI are 0.529, 0.299 and 0.146 respectively; The influence coefficient of HAB on BI is 0.152, but P>0.05, it fails the test, so the influence of HAB on BI is Not significant; in the indirect impact relationship, the coefficient of HAB indirectly affecting BI through ATT is 0.102, and the coefficient of PU indirectly affecting BI through CI and SN is 0.450. It can be seen that under the carbon inclusive mechanism, useful methods such as increasing the value of carbon points and the breadth of application, improving perceived behavioral control, increasing publicity and social awareness, and cultivating green travel attitudes can promote the willingness of urban residents’ green travel behavioral intention.

Hypoxia is one of the common abiotic stresses that negatively affects the development and productivity of agricultural crops. Quercetin is used to protect plants from oxidative stress when exposed to environmental stressors. O2 deficiency leads to impaired development and morphometric parameters in wheat varieties Orenburgskaya 22 (Triticum aestivum) and varieties Zolotaya (Triticum durum). Cytological analysis revealed various types of changes in the cytoplasm under conditions of hypoxia and treatment with quercetin. The most critical changes in the cytoplasm occur in the Zolotaya variety during pretreatment with quercetin followed by hypoxia, and in the Orenburgskaya 22 variety during hypoxia. Quercetin has a protective effect only on the Orenburgskaya 22 variety, and also promotes more effective recovery after exposure to low O2 content. Hypoxia causes an increase in ROS and activates the antioxidant system. It has been shown that the most active components of the antioxidant system in the Orenburgskaya 22 variety are MnSOD and Cu/ZnSOD, and in the Zolotaya variety GSH. We have shown that quercetin provides resistance only to the wheat genotype Orenburgskaya 22, as a protective agent against abiotic stress, which indicates the need for a comprehensive study of the effects of exogenous protectors before use in agriculture.

The classical limit definition of a derivative is expressed in a more general form. The general form includes two arbitrary functions of the parameter for which the limit is calculated. A special case of the general form, which includes scaling and translational symmetry transformations of the limiting parameter, is also discussed. The errors in using the classical definition and the generalized form are calculated for small values of the limiting parameter. The derivatives of some known functions are proven using the new definition. For some well-known functions, a suitable selection of the generalized form may introduce simplicity in calculating the derivatives.

Multi-cropping is becoming an increasingly popular approach in agriculture to tackle major and complex agroecosystem problems such as biodiversity and soil fertility losses, erosion and degradation, increased greenhouse gas emissions, etc. Comprehensive assessment of the impact of multi-cropping intensity on the agroecosystem is a new and still under-researched approach that provides a better understanding of the impact of the individual indicators studied on the overall functioning of the biodiversed agroecosystems. Data from a stationary field experiment with multi-cropping at the Vytautas Magnus University, Experimental Station between 2020 and 2022 were used to achieve this objective. The study included maize, hemp and faba bean as single, binary, and ternary crops. A complex assessment approach (CEI value) was used to determine the impact of these diversified crops on the agroecosystem, the interrelationships between the main indicators and the strength of their effects. It was found that the most positive effect on agroecosystem had ternary maize-hemp-faba bean crop. The effectiveness of other crops was from 2 to 35% less. The lowest one was calculated for the maize-faba bean crop.

The aim of this research work is to study the influence of temperature, solar irradiation and wind dust on the production of solar energy. In addition, it aims to study the assessment of water quality, in particular groundwater used for cooling and cleaning photovoltaic panels (quality analysis). it's an important source, stable and sustainable can be used entirely for cooling and cleaning PV modules from the sales dust, in order to improve their performance. To date, all research studies carried out in this context of cooling and cleaning using water have not taken account of the nature of this water. We have taken a sample of water from a well in a rural area in the Darra Tafilalet region of Morocco. This region has an arid and semi-arid climate, with very high temperatures and dust-laden winds, particularly in summer. These meteorological characteristics influence the efficiency of cells, particularly photovoltaic (PV) panels, reducing their performance. Next, the water sample was analysed in the laboratory. The results obtained show that the groundwater in this area is very sensitive to cooling and cleaning photovoltaic panels. Moreover, these results indicate that the temperature, solar irradiation and wind-blown dust have a significant influence on energy production.

Ozonated oil has several benefits for humans, as it contributes to numerous interventions, maintaining the quality of life and the well-being of individuals. Being a natural product, it has few or almost no side effects. Thus, the study aimed to verify the sensitivity and/or resistance of fixed o “Ozonated” and “Non-Ozonated” oils from Mauritia flexuosa (Buriti), Carapa guaianensis (Andiroba) and essential “Ozonated” oils from Menta piperita (Mint), Eugenia caryophyllus (Clove) in different concentrations, against internationally known bacteria from the American Type Culture Collection – ATCC, comparing with the “Non-Ozonated” versions of the respective oils, using the Agar diffusion technique. Thus, it is evident that the ozonation of the fixed oils of Buriti and Andiroba, as well as the essential oils of Mint and Clove, provided significant results, although they were statistically different. The Buriti and Andiroba oil were ineffective in inhibiting microorganisms. On the other hand, the essential oil of Mint and Clove obtained similar activity of inhibition of microorganisms. With regard to Ozonation, the Essential Oil of “Ozonated” Clove provided greater activity than the “Non-Ozonated” one, which inhibited only one tested microorganism, in addition to producing changes in its chemical composition, requiring individualized studies for the ozonation of each essential oil.

Colorectal cancer (CRC) with KRAS mutation is prone to develop metachronous metastasis. However, effective measures for prediction and prevention of such clinical issue are currently unavailable. In this study, we confirmed that KRAS mutation is a risk factor for CRC metachronous metastasis through meta-analysis and public database analysis. Based on the ICGC-AGRO database, we have constructed a risk scoring model for predicting metachronous metastasis in KRAS-mutant CRC using machine learning, which was validated in public datasets. Furthermore, we discovered that KRAS inhibitors can effectively suppress the migration and invasion capabilities of high risk CRC cells by wound healing assay and transwell experiment, which was validated ex vivo and in vivo using organoids and splenic liver metastatic mouse model. Finally, RNA sequencing, RT-qPCR, and western blots have proven that KRAS inhibitors can suppress the epithelial-mesenchymal transition (EMT) and transforming growth factor beta (TGF-beta) signaling pathway in CRC. Collectively, our study suggests that KRAS inhibitors may inhibit the metastatic ability of CRC by suppressing EMT and the TGF-beta pathway, suggesting their potential for the prevention of metachronous metastasis in CRC with KRAS mutation.

Our research proposes two different training and modelling approaches of Generative Pre-trained Transformers (GPT) with specialized news feeds specific to the Spanish market: in-context example prompts and fine-tuned GPT models. Our findings indicate that integrating GPT insights into electricity price trend forecasting can result in more precise predictions and a deeper understanding of market dynamics. Through our research, we aim to provide insights to understand the capabilities of GPT solutions, and how those can be used to enhance prediction accuracy, ultimately supporting informed decision-making for stakeholders across the Spanish electricity market and companies whose margins heavily depend on electricity costs and price volatility.

Workplace bullying is common among nurses affecting negatively several work-related variables, such as job burnout and job satisfaction. However, no study until now has examined the impact of workplace bullying on quiet quitting among nurses. Thus, our aim was to examine the direct effect of workplace bullying on quiet quitting and to investigate the mediating effect of coping strategies on the relationship between workplace bullying and quiet quitting in nurses. We conducted a cross-sectional study with a convenience sample of 650 nurses in Greece. We collected our data during February 2024. We used the Negative Acts Questionnaire-Revised, the Quiet Quitting Scale and the Brief COPE to measure workplace bullying, quiet quitting and coping strategies, respectively. We found that workplace bullying and negative coping strategies were positive predictors of quiet quitting, while positive coping strategies was a negative predictor of quiet quitting. Our mediation analysis showed that positive and negative coping strategies partially mediated the relationship between workplace bullying and quiet quitting. In particular, positive coping strategies caused competitive mediation, while negative coping strategies caused complimentary mediation. Nurses’ managers and policy makers should improve working conditions by reducing workplace bullying and strengthening positive coping strategies among nurses.

RNA extraction from human cumulus cells (CCs) is considered challenging due to low cell’s pop-ulation and small cell. The successful gene expression analysis from cumulus cells ultimately de-pends on an excellent concentration of Ribonucleic acid (RNA) yield by an appropriate technique. Our study aims to consolidate appropriate cumulus cell collection method, preparation and ex-traction techniques to ensure a good yield of RNA for better gene expression analysis. From the results obtained, the optimal strategy found involved mechanical denudation without an enzy-matic process, followed by the use of RNA stabilizer prior to RNA extraction. Subsequently, uti-lizing a smaller homogenizer, preferably manual pressure control with filter (Bio-Masher III®) is paramount for a pure and homogenize sample. Subsequently, during RNA extraction, the use of RNeasy micro kit and RNA carriers is recommended. These sample collection, preparation, and extraction techniques yielded an excellent-quality RNA concentration and successful gene expres-sion analysis. We also conducted a systematic review to consolidate our findings with current evidence of RNA extraction technique. Our results added a value as a current strategy for opti-mizing RNA extraction in CCs for experimental studies. Thus, our findings can contribute to for-mulating a better strategy for optimizing the RNA extraction in CCs for transcriptomic studies.

The study focused on the technical and scale efficiency of smallholder pineapple farmers in the Central Region of Ghana. The input-oriented Data Envelopment Analysis (DEA) was used to estimate technical, pure and scale efficiencies of the smallholder pineapple farmers, of which a random sampling procedure was used to select 320 respondents. The study revealed that the farmers were technically inefficient with mean technical efficiency under Constant Returns to Scale (CRS), pure efficiency under Variable Returns to Scale (VRS) and the Scale Efficiency levels of 0.505, 0.641 and 0.772, respectively, due to farmers’ inability to exploit fully the available technology while experiencing evident post-harvest losses resulting from low adoption of post-harvest technologies. Such findings are meaningful and could help the farming communities and relevant policymakers to understand the issues in farming production and hence undertake necessary actions to potentially improve farmers’ technical and scale efficiencies in the study area.

Our study reviews the significance of archaeological parks in the tourism sector, with a specific focus on how digital presence and visitor feedback impact their cultural and touristic appeal. Utilizing statistical analyses such as regression and cluster analysis on data sourced from both Hungarian and Western European parks, the research scrutinizes TripAdvisor and Google ratings, alongside the volume of photographs and reviews. The findings highlight a modest correlation between digital visibility and overall visitor ratings, underscoring the complex relationship between online engagement and the quality of visitor experience. Notably, the cluster analysis identified two distinct groups, signifying diverse levels of visitor engagement and digital visibility across the parks. The conclusions drawn advocate for a comprehensive strategy to enhance visitor experiences, emphasizing the integration of digital engagement with the promotion of the parks cultural and historical values. By exploring the influence of digital presence on the appeal of archaeological parks, our study sheds light on the evolving interface between urban studies and digital heritage, highlighting how digital tools and online platforms are becoming increasingly integral in shaping the perceptions and experiences of urban cultural sites.

Alhagi pseudalhagi in the arid zone of the Atyrau region and an analysis of their current state with an assessment of raw material reserves were studied. Botanical characteristics, ontogenetic spectrum, morphological indicators, productivity, areas of thickets and reserves of raw materials of above-ground organs were assessed. The structural parameters of these coenopopulations in the Zhangyr and Coneu Rivers valleys, the vicinity of Imankara Mountain, and the Taisoigan sands were studied. It was established that the species composition of the populations includes 63 species from 54 genera and 30 families. The most common species include 49 taxa, category II – 17 taxa, category III – 7 species, category IV–V – 2 species. The maximum similarity in species composition was noted between populations in the Zhangyr and Coneu Rivers valleys. The maximum morphometric indicators were observed among the population of the river valley. Coneu and the minima are located on the Taisoigan sands. Analysis of the age spectrum made it possible to determine that the populations in the Zhangyr and Coneu Rivers valleys are characterized as young, in the area of Imankara Mountain and on the Taisoigan sands - as stable and middle-aged.

This investigation mainly focused on the microstructural analysis of Al based hybrid metal matrix composites. Aluminium as base metal and reinforced with 2% B4 C, ZrO2 (2%,4%,6%), SiC (4%,8%,12%). Specimens were manufactured by using conventional stir casting technique. Hybrid metal matrix composites were examined by using Scanning electron microscope. This research explained XRD, EDS and Fractography analysis. This investigation shows the reinforced material has given better results in all aspects than pure Al6061 alloy and homogeneous dispersion of particles inside the matrix. Porosity, delamination, cracks, particle distributions were observed through microstructural analysis. Additionally determined the crystal size of pure Aluminium 6061 alloy and hybrid composites.

Quantum logic is a well-structured theory, which has recently received some attention because of its fundamental relation to quantum computing. However, the complex foundation of quantum logic borrowing concepts from different branches of mathematics as well as its peculiar settings have made it a non-trivial task to device suitable applications. This article aims to propose for the first time an approach to use quantum logic in image processing at hand of a process for shape classification. We show how to make use of the principal component analysis to realize quantum logical propositions. In this way we are able to assign a concrete meaning to the rather abstract quantum logical concepts, and we are able to compute a probability measure from the principal components. For shape classification we consider encrypting given point clouds of different objects by making use of specific distance histograms. This enables to initiate the principal component analysis. At hand of experiments, we explore the possibility to distinguish between different geometrical objects and discuss the results in terms of quantum logical interpretation.

The spread of high-performance personal computers, frequently equipped with powerful Graphic Processing Units (GPU), raised the interest on a set of techniques able to extract models of electromagnetic phenomena (and devices) directly from available examples of the desired behavior. Such approaches are collectively referred to as Machine Learning (ML). A typical representative ML approach is the so called “Neural Network” (NN). Using such data-driven models allows evaluating the output in a much shorter time when a theoretical model is available, or allows predicting the behavior of the systems and devices when no theoretical model is available. With reference to a simple yet representative benchmark electromagnetic problem, some of the possibilities and the pitfalls of the use of NN for the interpretation of measurements (inverse problem) or to obtain the required measurements (optimal design problem) are discussed. The investigated aspects include the choice of the NN model; the generation of the dataset(s); the selection of hyperparameters (hidden layers, training paradigm). Finally, the capabilities in the handling of ill-posed problems are critically revised.

The global food system has three recognized challenges: (a)increasing the availability of food consumption, (b) reducing food loss, and (c) reducing food waste. The increasing demand for food consumption, increasing quantity of food loss, and corresponding increase in food waste are resulting in serious health, aesthetic, social, economic, and environmental problems due to a lack of appropriate planning and management. Despite its importance, there is no clear, concise, and comprehensive definition of food consumption, loss, and waste. Generally, food consumption, food loss, and food waste are dealt with separately. This article presents a logically constructed ontological framework of food consumption, loss, and waste. It gives equal importance to all three aspects of global food management. The systematic ontological framework is general, and the analysis can be applied to any country. The framework deconstructs the combinatorial complexity of the problem and explicates the pathways to manage the consumption, loss, and waste. The ontological framework encapsulates 19*8*7*4*5*6 = 25,536 possible components of the challenge. A critical analysis based on available data using the framework will help to develop strategies to deal with the problem. It can help to discover the gaps and to find ways to bridge the gaps. It is novel to conceptualize food consumption, loss, and waste together.

Imaging flow cytometry (ImFC) represents a significant technological advancement in the field of cytometry, effectively merging the high-throughput capabilities of flow analysis with the image-based features of microscopy. In this comprehensive review article, we take a historical perspective and delve into the evolution of this methodology, presenting its past, exploring current state-of-the-art and forecasting potential future advancements. The inception of ImFC arose from the innovative combination of a flow cytometer's hydraulics with the technology of an advanced camera. This synergistic coupling facilitated the morphological analysis of cell populations at a high-throughput scale, effectively evolving the landscape of cytometry. However, the application of ImFC faced several challenges. Among the most prominent ones, is the development and implementation of software systems that can reliably and efficiently handle the robust data acquisition and analysis inherent in ImFC. The scale and complexity of the data generated by ImFC necessitates the creation of novel analytical tools that can effectively manage and interpret this data, thus allowing us to unlock the full potential of ImFC. Interestingly, artificial intelligence (AI) algorithms have begun to be implemented on ImFC, offering a promise for enhancing analytical capabilities. The adaptability and learning capacity of AI may prove to be essential in knowledge mining from high-dimensional data produced by ImFC, potentially enabling more accurate analyses. Looking forward, we project that ImFC may become an indispensable tool, not only in research laboratories but also in clinical settings. Given the unique combination of high-throughput cytometry and detailed imaging offered by ImFC, we foresee a critical role for this technology in the next generation of scientific research and diagnostics. As such, we encourage both current and future scientists to consider the integration of ImFC as an addition to their research toolkit and clinical diagnostic routine.

In the era of large data, the cloud is increasingly used as a computing environment, necessitating the development of cloud-compatible pipelines that can provide uniform analysis across disparate biological datasets. The WDL Analysis Research Pipelines (WARP) repository is a GitHub repository of open-source, cloud-optimized WDL workflows for biological data processing that are semantically versioned, tested, and documented. A companion repository, WARP-Tools, hosts Docker containers and custom tools used in WARP workflows.

We propose a method that enables precise determination of the number of atoms in a Dick-noise-free optical lattice clock, by effectively addressing quantum projection noise. Our approach relies on conducting stability measurements at three distinct parameter sets, allowing us to differentiate between quantum projection noise, photon shot noise, and technical noise. Importantly, our method enables accurate extraction of the atom number, even in the presence of photon shot noise and technical noise. To validate the effectiveness of our approach, we employ numerical simulations and optimize the modulation parameters to achieve the smallest uncertainty possible. The numerical simulations show the validity of our method and demonstrate a measurement uncertainty in the atom number that is below 4% across a wide range of atom numbers, provided that the standard deviation of atom number fluctuation is kept below 0.23 times the average atom number.

Air pollution poses a significant risk to public health and ecosystems. The use of sophisticated models to simulate the transformation and dispersion of pollutants in the atmosphere is a recognized method to assess air pollution levels and its sources and inform policy decisions for effective mitigation strategies in urban and industrial environments. The reliability of models depends, in part, on the sensitivity to the variance of input parameters, which can introduce uncertainty into the model's predictions. This uncertainty is especially challenging when the input parameters exhibit inherent variability. In this study, we analyse the uncertainty of an integrated emission/dispersion model by evaluating the relationship between input parameters and model outcomes. We uncover new aspects of this relationship while clarifying some previously known dependencies. Wind speed was found to have the most significant effect on calculated concentrations, with small differences leading to substantial concentration variations. The time of day, which reflects prevailing vertical turbulence conditions, was also found to have a notable impact on concentrations, whereas ambient temperature can also significantly influence model’s results. Based on these findings, we offer specific recommendations for regulators and scientists involved in environmental impact assessment to improve the accuracy and reliability of air pollution modelling.

Neuropathic pain is caused by a lesion or disease of the somatosensory system and is one of the most incapacitating pain types, representing a significant non met medical need. Due to the increase in research in the field and since innovative therapeutic strategies are required, namely in intractable neuropathic pain, neurostimulation has been used. Within this approaches, transcranial magnetic stimulation (TMS) that uses a transient magnetic field to produce electrical currents over the cortex emerges in the literature. Since this is an area in expansion and due to the putative role of TMS, we performed a bibliometric analysis in Scopus with the primary objective of identify the scientific production related to the use of TMS to manage neuropathic pain. The research had no restrictions and the analysis focused on the characteristics of the literature retrieved, scientific collaboration and main research topics from inception to July 6, 2023. A total of 474 articles were collected. A biggest co-occurrence between the terms “neuropathic pain” and “transcranial magnetic stimulation” was obtained. The journal “Clinical Neurophysiology” leads the Top 5 most productive sources. The United States is the most productive country with 50% of the documents being “review articles” followed by France with 56% of the documents being “original articles”. Lefaucheur, JP and Saitoh, Y are the two most influents authors. The most frequent type of documents was “original article”. This study allows to perform a general overview in the field of TMS application for neuropathic pain and is useful to establish future directions of research in this field.

Fingerhuthia africana Lehm belongs to family Poaceae, is an erect perennial grass used traditionally to cure different diseases. The current study was carried out to find the bioactive compounds by GC-MS, elemental analysis through atomic absorption spectrophotometry, proximate analysis by AOAC, genotoxic activity through comet assay, antioxidant activity through DPPH and antidiarrheal activity through castor oil induce diarrhea followed by charcoal meal on mice model. GC-MS chromatogram represents different compounds detected in the crude extract. Major pharmacological bioactive compounds are 4H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl-; 4-Methyl itaconate; .alpha.-Terpineol; 1,2,3-Propanetriol, 1-acetate; Benzofuran, 2,3-dihydro-; Caryophyllene oxide; Hinesol; n-Hexadecanoic acid; 9,12-Octadecadienoic acid (Z,Z)-, methyl ester; Hexadecanoic acid and methyl ester. Elemental analysis of stem, leaves and roots of the plant show the presence of (macro and micro) nutrients such as Ca, Mg, K, Na, Cu, Pb, Zn, Mn, Fe, Cd and Co were absent in all parts. Proximate analysis of different parts revealed the presence of moisture contents (8.57%), ash (9.77%), fats contents (5.96%), fibers contents (45.03%), protein (3.62%), carbohydrates (39.71%) and Gross energy (Kcal/100g) (220.10). The ethanolic extract show dose-dependent genoprotective potential (127.38 ± 1.16), (83.28 ± 0.65), and (44.08 ± 1.40) at 50, 75, and 100 mg/100 ml, respectively, as compared to the methanolic extract which show genotoxic activity (85.13 ± 1.23) at high dose. After 90 minutes at a concentration of 300 (g/ml), methanolic extract demonstrated the greatest antioxidant potential (79.5%), followed by aqueous extract (76.5%). The methanolic extract of F. africana demonstrated antidiarrheal efficacy, with the maximum inhibition of charcoal movement (83.78%) occurring at a dosage of 300 mg/kg, followed by doses of 200 and 100 mg/kg, 73.26% and 59.56%, respectively. The current research highlights that the plant contains a substantial quantity of micro and macro nutrients, possesses high nutritional value, and exhibits pharmacological activities. These properties render the plant suitable for developing remedies to treat various therapeutic diseases.

Lightweight component design is effectively achievable through the sandwich structures, many past research studies in the aerospace and racing sectors (since 1920s) has proven it. To extend their application into automotive and other transport industries, the manufacturing cycle times must be reduced. This can be achieved by thermoplastic sandwich materials of continuous fibre-reinforced thermoplastic (CFRTP) cover layers and thermoplastic honeycomb cores. To widespread the application of flat thermoplastic-based sandwich panels into complex parts, a novel forming technology was developed by the Fraunhofer Institute of Microstructure of Materials and Systems (IMWS). For an increase in reproducibility of the sandwich component production and a decrease in manufacturing defects, numerical modelling methods and experimental validation are needed. The finite element (FE) modelling of this thermoforming process is a thermo-mechanical assignment with all three: material, geometry, and boundary non-linearities. In the scope of this work, the material behavior of different sandwich components (cover layers, honeycomb core, interface) under thermo-mechanical loads is characterized in detail, and a complex numerical model is developed to describe the thermoforming process of thermoplastic-based sandwich laminate. The critical forming condition like wrinkling that occurs due to friction in a sandwich or poor intra-ply shear in cross-ply studied, validated, and optimized. A thermoplastic sandwich made of polypropylene (PP) honeycomb core and polypropylene glass fibre (PP/GF) cross-ply as cover layers was used for this study, and numerical modelling was executed in LS-DYNA software.

Gastric mixing relies both on enzymatic reactions and mechanical solicitations through antral contraction waves (ACWs). This work aims at discussing the influence of ACWs frequency and digesta viscosity on human gastric mixing efficiency by comparison with that of a soft elastic reactor (SER), that induces mixing by vibration of its wall in a similar way as ACWs promote stomach motility. The SER mixing curve was considered in order to determine the flow regime reached during gastric mixing. The number of contractions required to achieve homogenization was found to depend on the viscosity of the stomach content and the ACWs amplitude. Moreover, it was deduced from the same range of SER and ACWs operating points that the mechanical solicitation provided by human peristalsis was low and that gastric mixing was confined in laminar regime. Further efforts are needed to investigate the role of other physiological processes such as gastric secretions and emptying in overall gastric mixing performance.

Due to their contribution to human health, the production of healthy snacks has garnered the attention of both the scientific community and the food industry. This study was conducted to determine the suitability of frying and baking processing methods for producing green banana chips using two varieties: Barraganete and Dominico. The aim was to identify a treatment geared towards producing healthy snacks. Initially, the physicochemical properties of the raw materials were analyzed, revealing significant differences in starch, fat, fiber, and protein content. Subsequently, the bananas were processed into baked and fried chips. Multivariate statistical techniques such as ANCOVA, MANOVA, and post-hoc tests were applied to examine the influence of initial characteristics and detect variations attributable to the cooking method. The main findings showed that the initial protein level had a significant covariate effect on the final content in the chips. The Dominico variety generally proved more suitable for making baked chips, retaining higher percentages of protein, starch, fiber, and lower fat content than Barraganete. Baked chips showed significantly lower sodium and fat values than fried ones when differentiated by processing method. The "Dominico + Baked" treatment emerged as the superior alternative, with favourable levels of protein, starch, and low sodium and fat, positioning it as the most suitable for producing a healthy snack.

Purpose: Understanding how older adults perceive and interpret emotional cues in speech prosody contributes to our knowledge of cognitive aging. This study provides a systematic review with meta-analysis to investigate the extent of the decline in affective prosody recognition (APR) among older adults in terms of overall and emotion-specific performance and explore potential moderators that may cause between-study heterogeneity. Method: Incorporated into the literature search were six electronic databases, with a specific emphasis on studies comparing the APR performance of older adults with that of younger adults. This comparison was focused on basic emotions. Meta-regression analyses were executed to pinpoint potential moderators related to demographic and methodological characteristics. Results: A total of 19 studies were included in the meta-analysis, involving 560 older adults with a mean age of 69.15 years. The findings indicated a substantial negative effect size (g = －1.21). Furthermore, the magnitude of aggregated effect sizes showed a distinct valence-related recognition pattern with positive prosody exhibiting smaller effect sizes. Years of education were found to moderate the overall performance effect estimate while age and gender significantly influenced the effect estimate of happiness. Conclusions: The results confirmed a significant decline in APR ability among older adults, but this decline was unbalanced across basic emotions. Educational level emerged as a significant factor influencing APR ability. Moreover, participants with a higher mean age exhibited notably poorer performance in recognizing happy prosody. These findings underscore the need to further investigate the neurobiological mechanisms for APR decline associated with aging.

Universal Stress Protein (USP) plays an important regulatory role in the response to abiotic stress. Most of the research related to USP so far has been conducted on plant models such as Arabidopsis, rice, and cotton. The potato is one of the four major food crops in the world. Therefore, it is of great significance to study the expression pattern of the potato StUSP gene family under abiotic stress conditions. In this study, a total of 108 USP genes were identified from the genome of the Atlantic potato, divided into four subgroups. And based on the genetic structure, the physical and chemical properties of proteins and other aspects of their biological characteristics are comprehensively analyzed. Collinear analysis showed that the homologous genes of StUSPs and four other representative species (Arabidopsis, rice, coyote tobacco, and tomato) were highly conserved. The cis-regulatory elements of the StUSPs promoter are involved in plant hormones, environmental stress, mechanical damage, and light response. RNA-seq analysis showed that under different abiotic stresses, there are differences in the expression patterns of members of each subgroup. WGCNA co-expression analysis of the central gene showed that the differential co-expression gene is mainly involved in the plant-pathogen response process, plant hormone signal transduction, and the biosynthesis process of secondary metabolites. Through qRT-PCR analysis, it was confirmed that StUSP13, StUSP14, StUSP15, and StUSP41 may be important candidate genes involved in the response to adversity stress in potatoes. The results of this study provide the basis for further research on the functional analysis of StUSPs in the potato response to adversity stress.

In preserving genetic diversity among domestic animal breeds, the strategies emphasizing be-tween-breed diversity may be not optimal by neglecting within-breed variation. The present study aimed to assess the extent of the population subdivision of Mangalica pigs and the contri-bution of migration intensity to their substructure. Genealogy analysis was performed for breeding animals born between 1981 and 2023 examining three colour variations (Blonde, Swal-low-Belly, and Red). The fixation index (FST) was calculated and evaluated by Multidimensional Scaling and Clustering to expose the population substructure. The average FST is 0.04 for the Blonde and 0.05 for the Swallow-Belly and the Red while in the active herds, these parameters are smaller being 0.03 and 0.04, respectively. The migration of individuals affected 61.63% of the Blonde, 75.53% of the Swallow-Belly, and 63.64% of the Red breed herds. No population sub-structure was found in any Mangalica breed which can be explained by the extensive within breed migration among the herds.

In this paper, we present a general version of polygonal fitting problem called Unconstrained Polygonal Fitting (UPF). Our goal is to represent a given 2D shape S with an N-vertex polygonal curve P with a known number of vertices, so that the Intersection over Union (IoU) metric between S and P is maximized without any assumption or prior knowledge of the object structure and the location of the N-vertices of P that can be placed anywhere in the 2D space. The search space of the UPF problem is a superset of the classical polygonal approximation (PA) problem, where the vertices are constrained to belong in the boundary of the given 2D shape. Therefore, the resulting solutions of the UPF may better approximate the given curve than the solutions of the PA problem. For a given number of vertices N, a Particle Swarm Optimization (PSO) method is used to maximize the IoU metric, which yields almost optimal solutions. Furthermore, the proposed method has also been implemented under the equal area principle so that the total area covered by P is equal to the area of the original 2D shape to measure how this constraint affects IoU metric. The quantitative results obtained on more than 2,800 2D shapes included in two standard datasets quantify the performance of the proposed methods and illustrate that their solutions outperform baselines from the literature.

This study delves into the therapeutic potential of two natural compounds, Amentoflavone and Bilobetin, by investigating their interactions with the BPIFB4 protein. BPIFB4, a member of the BPI fold-containing superfamily, has been associated with various biological processes, particularly in longevity and cardioprotection( LAV-BPIFB4). Molecular docking analyses revealed promising binding energies for Amentoflavone and Bilobetin with BPIFB4, suggesting favorable interactions.Additionally by pKCSM database are showed the predicted toxicity properties of Amentoflavone and Bilobetin respectively.This research contributes to the growing body of knowledge on natural compounds and their therapeutic implications in the context of vital biological processes. However, these findings underscore the need for further investigations, including in vivo studies and clinical trials, to validate the observed effects and explore the translational potential of Amentoflavone and Bilobetin in promoting cardiovascular health and longevity.

With the deterioration of the bridge performance and ever-increasing amount of traffic, the bridge safety is becoming a concern for engineering community. A method that can assess the bridge's condition in real-time is urgently needed. The main factors that hinder the bridge condition assessment are the uncertain operational environments. A new moving principal component analysis (MPCA) based method is developed for structural damage detection of bridges in operational environments in this paper. Two main operational environmental factors: the environmental temperature and traffic loads, are studied in the assessment process to verify the robustness and practicality of the proposed method. The numerical and experimental results show that the proposed method is effective and accurate to assess the bridge condition in operational environments.

Within the past few decades, thousands of experiments have been performed to characterize waste and biomass to estimate the bioenergy potential and product identification. There is a need to develop an integrated process model based on experimental literature, and simulation to obtain suitable products. In this study municipal solid waste (MSW) characterization and integrated process model have been developed to optimize final products in a reactor system. The process model has two modes R&D and reactor control (RC) to obtain suitable products including bio-oil, char, and gases. A database was integrated based on thermokinetics, machine learning and simulation models to optimize product efficiency. The experimental data includes thermogravimetric analysis, Fourier transform Infrared Spectroscopy, Gas chromatography, and Mass spectrometry, which are linked with pyrolysis experimental setup. Feedstock-product mapping models were incorporated into the database along with the temperature, heating rates, elemental analysis, and final product concentration, which are utilized for pyrolysis reactor setup. Product feasibility is conducted based on lifecycle cost, affordability, and product efficiency. The present work will bridge the gap between experimental study and decision making based on obtained products at several experimental conditions around the world.

The aim of this research was to undertake laboratory testing to investigate the beneficial effects of epoxy resin grouts on the physical and mechanical properties of sands with a wide range of granulometric characteristics. Six sands, of different particle size and uniformity coefficients, were grouted using epoxy resin solutions with three ratios of epoxy resin to water (3.0, 2.0 and 1.5). A set of unconfined compressive strength tests were conducted on grouted samples at different curing periods and a set of long-term unconfined compressive creep tests in dry and wet conditions after 180 days of curing were also carried out, in order to evaluate the development of the mechanical properties of the sands, as well as, the impact of water on them. The findings of the investigation showed that epoxy resin resulted in appreciable strength values in the specimens, especially those of fine sands, grouted with the different epoxy resin grouts. In general, the compressive strength varied between 0.68 - 5.60 MPa and the modulus of elasticity between 75 - 480 MPa, after a curing period of 180 days. In terms of physical properties, the permeability and porosity (before and after the grouting process) were estimated. Grouts with an epoxy resin to water ratio of 3 decreased permeability by up to four orders of magnitude. Using laboratory results and regression analysis, three mathematical equations were developed that relate each of the dependent variables; compressive strength, elastic modulus, and coefficient of permeability, with particular explanatory variables.

Diabetes mellitus is acknowledged as a significant contributor to severe complications. The present work has explorated the potential role amentoflavone as an aldose reductase inhibitor through Docking Simulations. From these results this compound has shown excellent results with this enzyme with a high binding energy of -11 kcal/mol. If amentoflavone,a natural biflavonoid, proves effective in inhibiting aldose reductase, it could hold therapeutic promise for managing diabetic complications. However, it's crucial to emphasize that while computational studies offer valuable insights, experimental validation is essential to confirm the actual inhibitory effects and to establish the safety and efficacy of amentoflavone for this purpose. Further research and clinical studies are warranted to fully understand and harness the potential therapeutic benefits of amentoflavone in the context of diabetes.

Aging is a major risk factor for the higher incidence and prevalence of chronic conditions, such as cancer, cardiovascular and metabolic diseases, and neurodegenerative diseases. Closely linked with the onset of all these age-related diseases is immunosenescence, a condition defined as progressive reconfiguration of the immune functions leading to an increased susceptibility to infectious diseases, poorer response to vaccination, increased prevalence of cancer, rheumatoid arthritis, and other chronic diseases characterized by a pro-inflammatory state named inflammaging. Given that immunosenescence frames age-related diseases, it is natural to ask how these illnesses are related under the context of innate and adaptative components of the immune system. Knowledge processing by Formal Concept Analysis (FCA) of age-related diseases framed in an immunosenescence multivalued context shows that a hierarchy among these diseases emerges with a subconcept-superconcept nested structure, with two clusters, first made of metabolic diseases, cancer, and cardiovascular diseases. Second metabolic and neurodegenerative diseases and rheumatoid arthritis. Metabolic diseases seem to be a pivot illness and they must be a primary target given their global incidence and prevalence and their cost-effective treatments like regular physical activity, weight loss, healthy diet, stopping smoking, and reducing or managing stress. Another implication of the ontological analysis of age-related diseases is about the nature of immunosenescence, suggesting that initial symptoms of age-related diseases are mainly related to innate immune mechanisms, and developing of severe symptoms of age-related diseases like cancer, cardiovascular or neurodegenerative diseases depends on the activation of acquired immunity processes.

The insufficient toughness of concrete can lead to the occurrence of crack expansion, ultimately resulting in a decline in the physical and mechanical properties such as bearing capacity and deformation characteristics of structural components. In severe cases, this may lead to brittle failure, where the entire structure and system fail suddenly without significant deformation after being stressed. Additionally, during the process of shear and bending failure of reinforced concrete beams, the cracks generated on the side of the beam are mostly I-II composite cracks. Considering the material nonlinearity and geometric irregularity of reinforced concrete, it is of great significance to study the dynamic evolution law of crack expansion in reinforced concrete members. Based on experimental data, this paper aims to utilize the nonlinear finite element simulation software Abaqus to conduct finite element simulations of crack expansion in simple supported reinforced concrete beams. By accurately controlling the constitutive curves of concrete and reinforcement materials, the design of seismic performance of structural members can be enhanced, thereby making essential contributions to the preliminary analysis of actual crack control engineering. The nonlinear finite element results indicate that the joint cracks of the frame with the floor slab primarily manifest as flexural cracks, with the concrete damage degree of the floor slab being higher than that of the beam. This finding underscores the importance of considering the behavior of concrete and reinforcement materials in designing for seismic performance and crack control in actual engineering applications.

Slags and ashes generated in thermal waste treatment facilities require proper management. In line with the principles of the circular economy, new, more economical and ecological possibilities for utilizing these substances are sought. These waste materials exhibit characteristics similar to rocks in many aspects. This study focuses on analyzing the similarities and differences between nine selected rocks and three samples of slags and ashes obtained from municipal waste incineration. The main research device used was a polarizing microscope, using reflected, transmitted and fluorescent light. Additionally, low-pressure gas adsorption equipment, as well as helium and quasi-liquid pycnometers, were used for complementary analysis. The parameters analyzed mainly covered broadly defined petrographic properties of rocks and slags, with a particular emphasis on porosity, porous structure and the spatial distribution of pores and fractures. The conducted analyses confirmed a significant similarity between slags and ashes and clastic sedimentary rocks such as sandstones and mudstones. The research results underscore the importance of petrographic microscopic studies for analyzing materials other than rocks. They also allow for exploring applications for slags and ashes in areas traditionally reserved for natural rock resources. The findings also indicate the necessity of using methods other than microscopic ones to describe the pore space of rocks. The lower measurement range of the optical microscope is limited to approximately 1 μm, covering only macropores. Other methods extend this characteristic to micro- and mesopores. Therefore, a combination of different methods is often employed to obtain a more comprehensive characterization of rock porosity.

Dental implant fracture is closely connected to the stress buildup surrounding the implant system during static loading. In areas where the cross section of the implant rapidly changes or where the geometry of the implant system has discontinuities, stress concentrations arise. Therefore, the implant's design is crucial in preventing early failure of the implant system, including fracture, screw loosening, and increased leakage, in addition to reducing stresses at the implant-abutment interface. In the current work, three-dimensional (3D) models of mechanically connected Ti6Al4V implant systems in various dimensions were constructed. Finite Element Analysis (FEA) was used to conduct a stress study of the created implants under actual acting forces static loading conditions in accordance with ISO 14801. In the created models, design elements including implant screw type, thickness, and taper angle of abutment were modified in order to increase the longevity of the implants. The results show that the equivalent stress level is dramatically reduced from 596.22 MPa to 212.72 MPa in the implant model, which exhibit more homogeneous stress pattern under static loading conditions. Furthermore, the relatively smoother stress transmission observed in this model holds promise for the development of new implants capable of withstanding the forces encountered in the oral environment.

Accidents between right-turning commercial vehicles and crossing vulnerable road users (VRU) in urban environments often lead to serious or fatal injuries and therefore play a significant role in forensic accident analysis. To reduce the risk of accidents, blind spot assistance systems have been installed in commercial vehicles for several years, among other things, to detect VRUs and warn the driver in time. However, since such systems cannot reliably prevent all turning accidents, an investigation by experts must clarify how the accident occurred and to what extent the blind spot assistance system influenced the course of the accident. The occurrence of the acoustic warning message can be defined as an objective reaction prompt for the driver, so that the blind spot assistance system can significantly influence the avoidability assessment. In order to be able to integrate the system into forensic accident analysis, a precise knowledge of how the system works and its limitations is required. For this purpose, tests with different systems and accident constellations were conducted and evaluated. It was found that the type of sensor used for the assistance systems has a great influence on the system’s performance. The lateral distance between the right side of the commercial vehicle and the VRU as well as obstacles between them and the speed difference can take great influence on the reliability of the assistance system. Depending on the concrete time of the system’s warning signal the accident can be avoided or not by the driver when reacting on this signal.

To ensure sustainability of the future power grid, the rate of expansion of distributed renewable energy resources (DRER) has introduced operational challenges. These includes managing transmission constraints with DRER power injection, dispatching DRER efficiently, managing system frequency and ensuring sufficient reactive power for voltage support. Coupled with the intensification of wildfires, power infrastructure across the United States faces challenges to minimize the impact to maintain system reliability and resiliency. This research embarks on a comprehensive evaluation, beginning with an in-depth historical analysis to delineate regions most susceptible to wildfires. Utilizing a multidimensional approach, the study assesses wildfire-induced risks to power grids, by integrating historical wildfire occurrences, real-time wildfire proximities, Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation metrics, and system parameters, by employing Principal Component Analysis (PCA) based optimal weights, leading to the formulation of a novel risk factor model. This risk factor has the potential to be the key to ensuring the resilience of a renewable-rich smart grid when faced with a severe weather event. Our model’s applicability was further verified through an empirical assessment, selecting representative networks from diverse regions, providing insights into the geographical variability of risk factors. Ultimately, this study offers stakeholders and policymakers a comprehensive tool-set, empowering decisions regarding infrastructure investments, grid reinforcements, and strategic power rerouting to ensure consistent energy delivery using risk assessment against wildfire.

This study compared cortical responses to speech in preschoolers with typical language development (TLD) and Developmental Language Disorder (DLD), and in adults. We investigated whether top-down language effects modulate speech perception in an adult-like manner. We compared cortical mismatch responses (MMR) during passive perception of speech differing in linguistic complexity in three groups of participants: preschoolers with TLD (n=11), preschoolers with DLD (n=16) and adults (n=20). We also measured children’s phonological skills and investigated if they are associated with the cortical responses. MMR results indicated top-down language effects in adults, with enhanced cortical discrimination of lexical stimuli but not of non-words. In preschoolers, the TLD and DLD groups did not differ on the MMR measures and no top-down effects were detected. Moreover, we found no association between MMRs and phonological awareness skills, even though the DLD group’s phonological skills were significantly lower. Our findings suggest that top-down language modulations on speech discrimination may not be present during early childhood, and that children with DLD may not exhibit cortical speech perception deficits. The lack of association between phonological and MMR measures indicates that further research is needed to understand the link between language skills and cortical activity in preschoolers.

The field of CSR has witnessed considerable growth and established itself as a significant subject in family business literature. However, despite previous reviews exploring this topic from various angles, there remains a crucial gap in understanding the influence of diverse regulatory frameworks and cultural values on the development of literature production and research streams across different regions. This gap holds particular significance for comprehending the latest advancements in this dynamic field, particularly in emerging economies, where cultural norms play a substantial role in shaping the relationship between family firms and CSR. To bridge this gap, this paper conducts a comprehensive review of empirical studies focusing on sustainability in family firms. These studies are organized based on the country of study, and our review encompasses 232 articles published between 1996 and 2023. Utilizing bibliometric software, we systematically group these articles into three distinct clusters: North American studies, European studies, and Asian studies, adhering strictly to our inclusion criteria.

Internal combustion engine (ICE) vehicles contribute significantly to the global warming through their immense quantity of CO2 emissions and are on the way to be replaced by zero emission alternative solutions. Several replacement techniques with scientifically sound performances are proposed for the propulsion equipment including the related supply chains from renewable sources, but they often cannot fulfill the huge demand quantitatively. The paper discusses the quantitative aspects of the real demand with the example of the actual automotive park in Switzerland and analyses different alternatives like conventional EV’s, fuel-cell vehicles or energetic chains based on sustainable fuels like e-methanol or synthetic solar fuels. The analysis comprises energy efficiency considerations.

High-temperature cooking process like frying, baking, smoking, or drying can induce chemical transformations in conventional food ingredients, causing deteriorative modifications. These reactions, including hydrolytic, oxidative, and thermal changes, are a common occurrence and can result in alterations to the food's chemical composition. In this study, a combination of sucrose and histidine (Su-Hi) was transformed through a process of charring or pyrolysis. The GC-MS profiling study showed that when sucrose and histidine (Su-Hi) are exposed to high temperatures (≈240°C), they produce carbonyl and aromatic compounds including beta-D-Glucopyranose, 1,6-anhydro (10.11 %), 2-Butanone, 4,4-dimethoxy- (12.89 %), 2(1H)-Quinolinone-hydrazine (5.73%), Benzenamine (6.35%), 2,5-Pyrrolidinedione, 1-[(3,4-dimethylbenzoyl)oxy]- (5.82%), Benzene-(1-ethyl-1-propenyl) (5.62%), and 4-Pyridinamine-2,6-dimethyl (5.52%). The compounds mentioned have the ability to permeate the cell membrane and contribute to the development of cell death by necrosis in human immune cells. The evidence available suggests that a specific set of pyrolytic compounds may pose a risk to immune cells. This investigation reveals the complex relationship between high-temperature cooking-induced transformations, compound permeation inside the cells, and downstream cellular responses, emphasizing the significance of considering the broader health implications of food chemical contaminants.

Parkinson's disease (PD) stands as the most prevalent degenerative movement disorder, characterized by the loss of dopaminergic neurons in the substantia nigra of the midbrain. In this study, we assessed the transcriptome by analyzing post-mortem mRNA extracted from the substantia nigra of individuals with PD and healthy controls. A total of 16,148 transcripts were identified, with 92 mRNAs displaying differential expression between PD and control groups. Specifically, 33 mRNAs were significantly upregulated, while 59 mRNAs were downregulated in PD compared to controls. The identification of statistically significant signaling pathways, with an adjusted p-value threshold of 0.05, unveiled noteworthy insights. Particularly, enriched categories included cardiac muscle contraction (involving genes such as ATPase Na+/K+ transporting subunit beta 2 (ATP1B2), solute carrier family 8 member A1 (SLC8A1), and cytochrome c oxidase subunit II (COX2)), GABAergic synapse (involving GABA type A receptor-associated protein like 1 (GABARAPL1), G protein subunit beta 5 (GNB5), and solute carrier family 38 member 2 (SLC38A2)), autophagy (involving GABARAPL1 and tumor protein p53-inducible nuclear protein 2 (TP53INP2)), and Fc gamma R-mediated phagocytosis (involving amphiphysin (AMPH)). These findings uncover new pathophysiological dimensions underlying PD, including the involvement of cardiac muscle contraction and specific mitochondrial activity. This knowledge not only contributes to better diagnostic precision but also paves the way for the development of new targeted therapies.Keywords: mRNAs; RNA sequencing; Parkinson’s disease; transcriptome analysis; substantia nigra

Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The second scenario examined driver responses to phantom braking caused by the AEBS. As a result, the first scenario shows that none of the subjects could control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 seconds. In the second scenario, we found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered.

Using two infectious DNA clones originating from isolates obtained in Kenya, a genetic investigation of maize streak virus (MSV) pathogenicity was carried out. The susceptible Pioneer hybrid 3379 was used to investigate the virulence of kernels administered through vascular puncture inoculation. Mild [pMSV-KL (mild)] and severe [pMSV-Km(severe)] parental infectious MSV DNA clones were linked with considerable changes in the severity of chlorotic streaks and stunting of seedlings. Using restriction endonuclease fragments, chimeric clones were created from parental clones in order to investigate the genetic elements influencing these changes. Restrictions mapping was used to validate clone identities. For genomic portions encoding the replication initiator (Rep and RepA), movement (MP), and coat (CP) protein ORFs as well as for those containing non-coding long (LIR) and short intergenic regions (SIR), putative virulence determinants were discovered. Recombinant clones with intermediate symptoms included LIRs together with the first 189 nt of the Rep/RepA ORFs from the pMSV-Km (Severe) and pMSV-KL (Mild) ORFs. Symptoms identical to those of parental clones were produced by complementary substitution of the Rep/RepA ORF. When compared to pMSV-Km (Severe), the recombinant clone having MP, CP, and SIR genome sequences from pMSV-KL(Mild) and LIR, Rep, and RepA genome sequences from pMSV-Km (Severe) displayed much more severe symptoms and accumulated greater concentrations. The reciprocal clone, in contrast, displayed much milder signs and virus titers than pMSV-KL(Mild). The level of leaf chlorosis and plant stunting were linked with viral accumulation. These findings are consistent with the idea that MSV virulence is a polymorphic feature involving complementary sense genes (LIR and SIR) and the virion.

Trehalose is a non-reducing disaccharide and participates in physiological activities such as or-gan formation, energy metabolism, and stress resistance of insects. In the present study, phylo-genetic analysis divided 21 Bmtret1 orthologs into three clades. These genes are equally distrib-uted on the nine chromosomes. Cis-elements in the promoter regions of Bmtret1s indicated the possible function of Bmtret1s in response to hormones and environmental stimulus. The qPCR analysis showed the significantly different expression levels of Bmtret1s in different tissues and organs, indicating possible functional divergence. In addition, most Bmtret1s showed disturbed expression levels in response to BmNPV stresses. Our results provide a foundation for further functional dissection of Tret1s in Bombyx mori and implicate them as potential regulators for an-tiviral responses.

Thymus is an herbaceous perennials or subshrubs of the Lamiaceae family and is widely distributed worldwide. Essential oils extracted from thymus have attracted much attention owing to their potential biological functions. Here, we evaluated the chemical compositions of eight thyme essential oils (TEOs) using gas chromatography-mass spectrometry and assessed their antioxidant activity and in potential role in antibacterial and tumor therapy. The results showed that (1) the main components in eight TEOs were monoterpene hydrocarbons and oxygenated monoterpenes, and the chemical compositions of TEOs were affected by the specie factor; (2) eight TEOs could be divided into 3 groups (thymol-, geraniol-and nerol acetate-type), and thymol was main type; (3) eight TEOs had some common compounds, such as thymol and p-cymene, which were the main components in seven TEOs; (4) eight TEOs had antioxidant activit, and thymol-type EOs had strong antioxidant activity, while geraniol-type EOs had relatively weak antioxidant activity. In addition, it was found thymol had strong antibacterial activity against the growth of Escherichia coli and Staphylococcus aureus, and antimigratory activity of A549 cell. Overall, our results can provide theoretical basis for further exploring the function of natural products from thyme essential oils.

Microstructured optical fibres (MOFs) are a new type of optical fibres that possess a wide range of optical properties and many advantages over common optical fibres. Those are provided by unique structures defined by a pattern of periodic or quasi-periodic arrangement of air holes that run through the fibre length. In recent years, MOFs have opened up new possibilities in the field of optics and photonics, enabling the development of advanced devices and novel optical systems for different applications. The key application areas of PCFs vary from telecommunications and high-power energy transmission to quantum optics and sensing. The stack-and-draw method is a standard manufacturing technique for MOFs, where a preform is first manually created and then drawn in a high-tech furnace into a fibre with the required final dimensions and position of the air holes. Since in the manufacturing process experimenters can control only a few parameters, mathematical models and numerical simulations of the drawing process are highly requested. They not only allow to deepen the understanding of physical phenomena occurring during the drawing process, but they also accurately predict the final cross-section shape and size of the fibre. In this manuscript, we assume thermal equilibrium between the furnace and the fibre and propose a functional form of the fibre temperature distribution. We utilise it with asymptotic mass, momentum, and evolution equations for free surfaces already available in the literature to describe the process of fibre drawing. By doing so, the complex heat exchange problem between the fibre and the furnace need not be solved. The numerical results of the whole asymptotic model overall agree well with experimental data available in the literature, both for the case of annular capillaries and for the case of holey fibres.

Measurements of systems taken along a continuous functional dimension, such as time or space, are ubiquitous in many fields, from the physical and biological sciences to economics and engineering. Such measurements can be viewed as realisations of an underlying smooth process sampled over the continuum. However, traditional methods for independence testing and causal learning are not directly applicable to such data, as they do not take into account the dependence along the functional dimension. By using specifically designed kernels, we introduce statistical tests for bivariate, joint, and conditional independence for functional variables. Our method not only extends the applicability to functional data of the Hilbert-Schmidt independence criterion (HSIC) and its d-variate version (d-HSIC), but also allows us to introduce a test for conditional independence by defining a novel statistic for the conditional permutation test (CPT) based on the Hilbert-Schmidt conditional independence criterion (HSCIC), with optimised regularisation strength estimated through an evaluation rejection rate. Our empirical results of the size and power of these tests on synthetic functional data show good performance, and we then exemplify their application to several constraint- and regression-based causal structure learning problems, including both synthetic examples and real socio-economic data.

Cambodian spices Amomum kravanh, Citrus hystrix and Piper nigrum 'Kampot' have long history of seasoning of food products. In this study, essential oils (EOs) and supercritical CO2 extracts from all three species have been analyzed using GC-MS with two columns of different polarity, whereas EO and CO2 extract from P. nigrum fruits and CO2 extract from the peel of C. hystrix have been isolated and analyzed for the first time. The results showed that A. kravanh EO contained mostly eucalyptol (78.8/ 72.6 %), while CO2 extract was rich in oleic acid (29.26 %) and tricosane (14.74 %). C. hystrix EO was rich in β-pinene (29.95/29.45 %), followed by D-limonene (24.54/23.24 %) and sabinene (9.94/10.23 %). β-pinene (30.2/28.9 %), D-limonene (23.99/23.74 %) and sabinene (13.36/19.55 %) were also predominant in the CO2 extracts. β-Caryophyllene was the main constituent of both EO and CO2 extract from P. nigrum 'Kampot' with contents ranging from 37.84 to 55.84 %, followed by 3-carene (from 7.18 to 18.72 %). Such findings suggest that supercritical CO2 can potentially be used for extraction of all three Cambodian spices. Nevertheless, further research determining the most efficient extraction parameters will be needed before its application in the spice processing practice.

During the hand-eye calibration process of the manipulator, the Euclidean distance error of the calibration results cannot be calculated because the true values of the hand-eye conversion matrix cannot be obtained. In this paper, a new method of projection error analysis is presented. Error analysis is carried out by using a priori knowledge that the location of AR markers is fixed in the calibration process. The coordinates of the AR marker center point are reprojected to the pixel coordinate system, and then compared with the true pixel coordinates of the AR marker center point obtained by corner detection or manual labeling in order to obtain the Euclidean distance between the two coordinates as the basis for error analysis. Experimental results show that the proposed optimization method can greatly improve the accuracy of hand-eye calibration results.

This paper explores the application of wavelet analysis, a multiscale approach for enhancing visual clarity, in the context of image denoising, which reduces the impact of noisy pixels, caused by various factors such as electronic sensor limitations, low-light conditions, or transmission errors in digital imaging systems. This paper introduces some common noise types like Gaussian noise and processes of image denoising, eliciting the strength of wavelet analysis. As a powerful image denoising technology, wavelet analysis needs five steps to process the image, and the key step is thresholding. There are many kinds of wavelet, and each wavelet has different advantages and functions, which makes it suitable for different applications. Hence, wavelet analysis also makes a contribution in various fields beyond signal processing and data analysis, such as Biomedical Imaging and Geophysics and Seismology, where preserving image quality is essential for accurate analysis and interpretation. In short, this research highlights the promise of wavelet analysis, emphasizing the use of high- quality image data.

Background. In a changing European agricultural context, diversification of dairy farms is gaining attention. This study seeks to (1) assess musculoskeletal pain prevalence associated with tasks such as butter, yogurt, and cheese production; and (2) analyze associated risks. Methods. Observing 31 mostly female workers, it utilized the ERGOROM questionnaire, a methodology adapted from the Institut National de Recherche et de Sécurité, and Key Indicator Method forms. Results. Findings revealed that tasks like load carrying (42% of workers), manual work (17%), and awkward postures (14%) resulted in musculoskeletal pain, predominantly in the lower back (65%), neck (39%), and dominant upper limb areas (shoulder: 61%, elbow: 26%, and wrist: 65%). While psychosocial risks remained low, concerns arose from workload, hygiene standards, and resource unpredictability. Conclusions. As dairy farming evolves from artisanal to semi-industrial, the study emphasizes the importance of ergonomic adaptations to protect farmer health and prevent musculoskeletal disorders during diversification.

Alheira is a naturally fermented meat sausage traditionally made in the Portuguese region of Trás-os-Montes. Lactic Acid Bacteria (LAB) have been found to be the dominant microorganisms in alheira. This study aimed: 1) to characterize technological features and in vitro antimicrobial activity of LAB isolates; and 2) to reveal associations between such phenotypic characteristics and the isolates genotypically identified to species level through amplification and sequencing of the 16S ribosomal gene. Sixty-two LAB isolates were identified and Enterococcus faecium was the most prevalent (32.3%), followed by Leuconostoc mesenteroides (19.4%) and Latilactobacillus sakei (17.7%), aligning with previous research on traditional Portuguese fermented meat sausages. The phenotypic analysis of LAB isolates indicated diverse acidification capacities, proteolytic activities, and inhibitory effects against foodborne pathogens. Comprising the technological attributes, L. paracasei and L. mesenteroides had higher proteolytic activity (3.46 and 3.43 mm), whereas E. faecium and L. paracasei stood out for their acidifying capacity, with mean pH after 6 h of 5.78 and 6.03, respectively. Overall, lactobacilli presented higher inhibition diameter against the pathogens Staphylococcus aureus, Listeria monocytogenes and Salmonella Typhimurium. Although the mechanisms for inhibition of pathogen growth needs to be further elucidated, these findings enhance our understanding of LAB diversity and functionality in alheira sausages, contributing to product safety and quality assessment.

The practice of voluntary depigmentation is still prevalent in Africa, with a wide range of lightening cosmetics used. Our objective was to research and quantify three regulated and/or prohibited depigmenting ingredients present in lightening cosmetics sold in Ouagadougou. Twenty-nine lightening cosmetic samples were collected from vendors and HPLC analysis was subsequently conducted to identify and measure the concentrations of hydroquinone, clobetasol propionate, and kojic acid. The presence of hydroquinone was indicated on the label of 13.79% of the products, while 51.72% contained it after analysis. Furthermore, none of the products mentioned a concentration of hydroquinone exceeding 2.00%, even though 27.58% of them contained high concentrations. For clobetasol propionate, its presence was stated on the labels of 13.79% of the products, while 31.03% contained it. One sample had a clobetasol content exceeding 0.05%, although none mentioned a concentration higher than this value. Finally, while 24.13% of the samples claimed to contain kojic acid, only 17.24% did. We also observed that 41.38% of the samples contained combinations of two depigmenting ingredients investigated, with a predominance of the hydroquinone + clobetasol propionate (27.38%). These results demonstrate that manufacturers' declarations regarding the compositions of active ingredients in lightening cosmetics can sometimes be deceptive.

Wencheng waxy yam is famous for its glutinous and resilient taste, similar to waxy rice, but there is currently a lack of systematic research on the quality of this featured product, and little is known about its pesticide residues. We carried out a 2-year investigation of Wencheng waxy yam at seven sites from 2021 to 2022 to determine the oxidase content and phytochemical characteristics, namely amylose, amylopectin, protein, reducing sugar, and mineral contents such as K, Fe, and Zn, , including the status of pesticide residues. The results showed that oxidase content was affected by rainfall, and adequate water reduced the production of oxidase, including polyphenol oxidase (PPO), peroxidase (POD), and superoxide dismutase (SOD), during the late growth stage of waxy yam, which was beneficial for reducing browning in yam processing. Radar map analysis showed that, with comprehensive evaluation, standardized production sites 1 and 2 had a relatively higher quality than 3–7 with small farmers. The results of pesticide multi-residue testing showed that no pesticides were detected in 64.29% samples, and the detected residues samples were very low, making the consumption of yam safe for consumers. These findings could be beneficial for the exploitation of the health benefits of waxy yam tubers and the innovation of yam-based functional products.

In order to accurately identify the external economic situation in China and analyze the situation of economic development in Northeast China, based on the Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis framework, this article analyses the economy in Northeast China from the four factors of SWOT. To solve the lack of quantitative analysis in SWOT analysis, this article applies Analytic Hierarchy Process (AHP) to the analysis, and finally forms a complete system framework with the combination of qualitative and quantitative factors, through the analysis of the important degree of various factors and the consistency test, the key factors influencing the economic development in Northeast China are analyzed, and constructive countermeasures are proposed.

As customer demand for green products increases in the digital economic era, this study analyses the green innovation of the e-tailer and supplier in drop shipping models. Moreover, drop shipping e-tailers and suppliers with a drop shipping option need to make choices regarding whether to provide green or normal products to the market. When a supplier with a drop shipping option produces green products, more fees may be invested on the production of green products than on normal products. The drop shipping e-tailers and suppliers with a drop shipping option can also choose to sell normal products at a low cost, as before. This study designs four models of drop shipping e-teilers and suppliers with a drop shipping option under different choices, analyzes their operational process in drop shipping models, and investigates five theorems. The optimal pricings decisions and green degree of drop shipping e-tailers and suppliers with a drop shipping option were evaluated in this study. The impacts of the green innovation factor, green elasticity coefficient, manufacturing and distribution costs on the drop shipping e-tailers and suppliers with a drop shipping option, and the effect of other environmental parameters on the green degree of green products are also analyzed through computer simulation. The findings of the simulation analysis provide valuable guidance for e-tailers and suppliers with green innovation in drop shipping models and offer important academic and practical implications for e-commerce and the digital economy.

In recent years, with the increase in maritime trade, the necessity of increasing the capacities of the ports has emerged. However, while it is planned to increase the capacities of the ports, it is important that the port continues to operate at the same time. In this respect, the old port structures should not be damaged during the capacity increase. In this study, the strengthening of a port in Guinea is discussed as a case study. In the study, the existing quay wall was evaluated, and geotechnical and structural alternatives of the new structure to be built for capacity increase were evaluated. A combined system was designed as a pile foundation and a reinforced foundation with plastic piles so as not to damage the existing quay wall. The pile capacities obtained as a result of the analyses were verified by loading tests.

The black-necked crane is the only species that lives in the plateau. At present, there is little re-search on viral diseases of the black-necked crane. In this study, a virus metagenomics approach was employed to investigate the viral composition of black-necked cranes in Saga County, Shi-gatse City, Tibet, China. The identified virus families carried by black-necked cranes mainly in-clude Genomoviridae, Parvoviridae, and Picornaviridae. Among them, one picornavirus genome is characterized as a novel species in the genus Grusopivirus of the family Picornaviridae, four new parvoviruses genome were obtained and classified into four different novel species within the genus Chaphamaparvovirus of the subfamily Hamaparvovirinae, and four novel genomoviruses ge-nome were also acquired and identified as members of three different species including Ge-mykroznavirus haeme1, Gemycircularvirus ptero6, and Gemycircularvirus ptero10. All of these viruses were firstly detected in fecal samples of black-necked cranes. This study provides valuable in-formation for understanding the viral community composition in the digestive tract of black-necked cranes in Tibet and for monitoring, preventing, and treating black-necked cranes viral diseases.

New detailed geological/structural mapping as well as field-based structural analysis were carried out to investigate the deformation pattern of well-preserved high-pressure rocks of the Blueschist Unit exposed on SE Syros (Cyclades, Greece). Our new geological mapping revealed the occurrence of a metasedimentary sequence underlain by a meta-igneous sequence. The contact between these two sequences displays typically interfingering patterns in map-scale due to folding. The earlier ductile deformation phase recognized in the mapped area, is associated with the development of a penetrative foliation, which was formed under eclogite/blueschist facies conditions at peak conditions. The subsequent main deformation phase occurred at blueschist facies conditions synchronous with the early stages of exhumation of the high-pressure rocks. This phase is mainly associated with the formation of map-scale WNW-trending folds and a pervasive axial planar foliation linked with ESE-directed shearing. The main deformation ceased within blueschist facies conditions and exhumation of the rocks to greenschist facies conditions took place under very weak deformation. Greenschist retrogression observed in the southwestern part of the mapped area seems to be controlled by fluids rather than by intense deformation. Our results indicate that the high-pressure rocks of the Blueschist Unit exposed on Syros Island represent a large-scale pod of low deformation under blueschist to greenschist facies conditions, likely occupying the core of an extrusion wedge.

Plant-derived diterpene synthases (PdiTPSs) play a critical role in the formation of structurally and functionally diverse diterpenoids. However, the specificity or promiscuity of PdiTPSs remains unclear. In order to gain more understanding of this, the sequences of 199 functionally characterized PdiTPSs and their corresponding 3D structures were collected and manually corrected. Then, the correlations among sequences, domains, structures and their corresponding products were comprehensively analyzed. However, those features alone was insufficient for ef-fective product-specific classification of PdiTPSs as these methods could not establish a clear mapping between the enzymes and products. Nevertheless, local structural analysis can identify residues that have been experimentally proven to influence product outcomes through mutagenesis, and these residues exhibit conservation in spatial positioning and physicochemical properties. And aromatic residues surrounding the substrate exhibited selectivity towards its chemical structure. Specifically, tryptophan (W) was preferentially located around the linear substrate geranylgeranyl pyrophosphate (GGPP), while phenylalanine (F) and tyrosine (Y) were preferentially located around the initial cyclized diterpene intermediate. This analysis revealed the functional space of residues surrounding the substrate of PdiTPSs, most of which have not been experimentally explored. These findings provide guidance for screening specific residues for mutation studies to change the catalytic products of PdiTPSs.

In the interaction of the rolling stock and the upper structure of the railway track, intense dynamic loads occur. They have a destructive effect both on the parts of the rolling stock and on the elements of the superstructure of the track. In order to develop a durable, rational and reliably functioning design of cars and locomotives with good dynamic properties and good indicators of the impact of rolling stock on the railway track, along with theoretical computational studies, experimental studies are also required, which are usually the final stage in the design and implementation of rolling stock or modernization of existing ones. Locomotives and wagons in order to improve their strength and dynamic performance. The article presents the results of field tests to determine the dynamic performance of the type CKD6e diesel locomotive. The description of the preparation of the CKD6e shunting locomotive for testing is given. An analysis of the dynamic performance of a diesel locomotive during the passage of turnouts, on a straight section of the track and in a curve with a radius of 400 m, was carried out. The studies performed showed that the minimum value of the stability factor against wheel derailment on a straight section of the track is significantly higher than the standard value. The experimentally obtained ratio of frame forces to the static load from the wheelset on the rails, the coefficients of vertical dynamics of the first and second stages of suspension and the coefficient of stability against derailment of the wheel from the rail, registered on the track section in a curve with a radius of 400 m) meet the current requirements. A calculation scheme and equations of vertical oscillations are proposed, an analysis is carried out according to the graphs of movements of bogies and a locomotive body when moving along irregularities of different lengths at different speeds.

According to ISO/TR 23383, smart textiles reversibly interact with their environment and respond or adapt to changes in the environment. The present review and bibliometric analysis was performed on 5,810 documents (1989–2022) from the Scopus database, using VOSviewer and Bibliometrix/Biblioshiny for science mapping. The results show that the field of smart textiles is highly interdisciplinary and dynamic, with an average growth rate of 22% and exponential growth in the last 10 years. Beeby, S.P., and Torah, R.N. have published the highest number of papers, while Wang, Z.L. has the highest number of citations. The leading journals are Sensors, ACS Applied Materials and Interfaces, and Textile Research Journal, while Advanced Materials has the highest number of citations. China is the country with the most publications and the most extensive cooperative relationships with other countries. Research on smart textiles is largely concerned with new materials and technologies, particularly in relation to electronic textiles. Recent research focuses on energy generation (triboelectric nanogenerators, thermoelectrics, Joule heating), conductive materials (MXenes, liquid metal, silver nanoparticles), sensors (strain sensors, self-powered sensors, gait analysis), specialty products (artificial muscles, soft robotics, EMI shielding), and advanced properties of smart textiles (self-powered, self-cleaning, washable, sustainable smart textiles).

Different methodologies are being used to study the effects of autonomous vehicle (AV) in the mixed traffic indicating the interaction among autonomous and human-driven vehicles. Micro-scopic simulation tools are popular in such assessment as it offers scope to experiment in eco-nomical, robust, and optimistic way. Lack of reliable real-world data to calibrate and evaluate the connected autonomous vehicles (CAV) simulation model is a major challenge. One interesting methodology could be dealing the CAVs as conventional human driven vehicles and predict its possible characteristics based on the simulation inputs. The conventional human driven vehicles from real world, in this methodology, come to aid as benchmark to offer the measure of effective-ness (MoE) for the calibration and validation. For the three most common driving modules, a sensitivity analysis of the driving behaviors of AVs and an effect assessment of CAVs in a mixed traffic environment were done to explore the human alike autonomous technology. The findings show that, up to a point, which is directly re-lated to the quantity of interacting vehicles, the impact of CAVs is typically favorable. This study validates the approach and supports past studies by showing that CAVs perform better in traffic than AVs for traffic performance and safety aspects. On top of that, the sensitivity analysis has shown that enhancements in technology are required for obtaining the maximum advantages.

Tyrosinases (TYR) play an important role in oxidizing phenols and catechols, leading to the formation of catechols and ortho-quinones, respectively. In mammals, TYR catalyzes the conversion of L-Tyrosine to quinone, a pivotal step in melanogenesis, which generates melanin pigments responsible for protecting against UV radiation and oxidative stress. Given TYR's importance in melanin-related disorders and cosmetic applications, the inhibition of TYR has garnered attention for controlling melanin production. However, current inhibitors like hydroquinone, arbutin, and kojic acid (KA) have limitations in terms of side effects and effectiveness. A novel class of TYR inhibitors featuring arylpiperidine and arylpiperazine components has demonstrated potent inhibitory activity. This study presents a computational analysis of these inhibitors using molecular docking, molecular dynamics (MD) simulations, and the Linear Interaction Energy (LIE) method was used to estimate binding free energies. The arylpiperidine and arylpiperazine inhibitors exhibit remarkable stability within the TYR active site during simulations. The van der Waals interactions are notably sustained, indicating effective inhibition mechanisms. The results from LIE calculations closely align with experimental binding affinities. In summary, these results contribute to the understanding of TYR inhibition and underscore the potential of arylpiperidine and arylpiperazine derivatives as effective agents for modulating melanin production in both cosmetic and pharmaceutical applications. Overall, this study sheds light on the intricate interactions between inhibitors and TYR, opening avenues for the development of novel therapies and interventions.

Dilated cardiomyopathy (DCM) is a common form of cardiomyopathy, characterized by ventricular chamber dilatation and systolic dysfunction, in the absence of coronary artery disease, arterial hypertension, valvular or congenital diseases. DCM is a heterogeneous group of disorders of the myocardium caused by genetic factors, environmental factors, or a combination of both. DCM affects mainly men aged between 20 and 50 years, being considered one of the main causes of heart failure (HF) and the main indication for heart transplantation. Guideline-based HF treatment is the mainstay of management for patients with DCM. In recent years, gene therapy and induced pluripotent stem cells have become promising strategies. In this review, we summarize the relevant clinical issues, and current treatment of DCM patients, including the role of genetic evaluation.

With the deepening of the diversification and openness of financial system, financial vulnerability, as an endogenous attribute of financial system, becomes an important measurement of financial security. Based on network analysis, we introduce network curvature indicator improved by Copula entropy as an innovative metric of financial vulnerability. Compared with previous network curvature analysis method, CE-based curvature proposed in this paper can measure market vulnerability and systematic risk with significant advantages.

The Earth’s synthetic gravitational and density models can be used to validate numerical procedures applied for a global (or large-scale regional) gravimetric forward and inverse modelling. Since the Earth’s lithospheric structure is better constrained by tomographic surveys than a deep mantle, most of existing 3-D density models describe only a lithospheric density structure, while 1-D density models are typically used to describe a deep mantle density structure below the lithosphere-asthenosphere boundary. The accuracy of currently available lithospheric density models is examined in this study. The error analysis is established to assess the accuracy of modelling the sub-lithospheric mantle geoid, while focusing on the largest errors (according to our estimates) that are attributed to lithospheric thickness and lithospheric mantle density uncertainties. Since a forward modelling of the sub-lithospheric mantle geoid comprises also numerical procedures of adding and subtracting gravitational contributions of similar density structures, the error propagation is derived for actual rather than random errors (that are described by the Gauss’ error propagation law). Possible systematic errors then either lessen or sum up after applying particular corrections to a geoidal geometry that are attributed to individual lithospheric density structures (such as sediments) or density interfaces (such as a Moho density contrast). The analysis indicates that errors in modelling of the sub-lithospheric mantle geoid attributed to lithospheric thickness and lithospheric mantle density uncertainties could reach several hundreds of meters, particularly at locations with the largest lithospheric thickness under cratonic formations. This numerical finding is important for a calibration and further development of synthetic density models of which mass equals the Earth’s total mass (excluding the atmosphere). Consequently, the (long-to-medium wavelength) gravitational field generated by a synthetic density model should closely agree with the Earth’s gravitational field.