bluuebunny/crossref_metadata_2025 huggingface dataset:
Online High Frequency Impedance Identification Method of Inverter-Fed Electrical Machines for Stator Health Monitoring
Authors: Creux Jérémy , Haje Obeid Najla , Boileau Thierry , Meibody-Tabar Farid
Published: November 2024

In electric powertrain traction applications, the adopted trend to improve the performance and efficiency of electromechanical power conversion systems is to increase supply voltages and inverter switching frequencies. As a result, electrical machine conductors are subjected to ever-increasing electrical stresses, leading to premature insulation degradation and eventual short-circuits. Winding condition monitoring is crucial to prevent such critical failures. Based on the scientific literature, several methods can be used for early identification of aging. A first solution is to monitor partial discharges. This method requires the use of a specific measurement device and an undisturbed test environment. A second solution is to monitor the inter-turn winding capacitance, which is directly related to the condition of the insulation and can cause a change in the stator impedance behavior. Several approaches can be used to estimate or characterize this impedance behavior. They must be performed on a machine at standstill, which limits their application. In this paper, a new characterization method is proposed to monitor the high-frequency stator impedance evolution of voltage source inverter-fed machines. This method can be applied at any time without removing the machine from its operating environment. The range and accuracy of the proposed frequency characterization depend in particular on the supply voltage level and the bandwidth of the measurement probes. The effects of parameters such as temperature, switching frequency, and DC voltage amplitude on the impedance characteristic were also studied and will be presented. Tests carried out on an automotive traction machine have shown that the first two series and parallel resonances of the high-frequency impedance can be accurately identified using the proposed technique. Therefore, by monitoring these resonances, it is possible to predict the aging rate of the conductor.
Modeling Shearing and Bending Behavior of Kiwifruit Branches Using the Discrete Element Method
Authors: Zhao Hongbo , Zheng Zhiqi , Tan Ruihong , Liu Wenzheng , Zhang Zhiqiang
Published: November 2024

Returning pruned branches into the field is a key procedure in kiwifruit cultivation. It utilizes discarded branches and aids in orchard management. Shearing and bending behaviors dominate the mechanized process of branch return; however, current research lacks appropriate modeling methods for these processes. In this study, we developed a discrete element method (DEM) model to simulate the shearing and bending behaviors of kiwifruit branches. Initially, laboratory experiments determined the shear strength and elastic modulus of branch samples to be 31.38 MPa and 1.21 GPa, respectively. An annular kiwifruit branch DEM model was constructed. A Plackett–Burman design test identified significant influencing factors: effective modulus of bond, bond cohesion, effective modulus between ball and wall, and the normal-to-shear stiffness ratio. Utilizing the response surface method, we derived relationships between DEM parameters and mechanical responses. Optimal parameter combinations were found: an effective modulus of bond at 2.2 × 109 Pa, bond cohesion at 2.56 × 108 Pa, effective modulus between ball and wall at 1.27 × 108 Pa, and a normal-to-shear stiffness ratio of 1.16. Finally, simulations of the shearing and bending processes were conducted. The optimal parameter combination was verified with a relative error of 4.5%. Displacement–force curves showed general consistency, indicating reliability in the modeling approach.
In Vitro and In Vivo Digestibility of Putative Nutraceutical Common-Bean-Derived Alpha-Amylase Inhibitors
Authors: Takács Krisztina , Nagy András , Jánosi Anna , Dalmadi István , Maczó Anita
Published: November 2024

The inhibition of the alpha-amylase digestive enzyme impedes starch digestion by blocking access to the active site of the enzyme, thereby playing a role in the prevention of obesity and type 2 diabetes. Plant-derived alpha-amylase inhibitors (αAIs) are promising nonpharmacological alternatives for the prevention of these diseases. Alpha-amylase inhibitor-1 (αAI-1) present in common bean (Phaseolus vulgaris) is derived from a precursor protein. In this study, the effect of digestion on the digestibility, immune reactivity, and bioactivity of αAI-1 was assessed from four varieties of Hungarian common bean (Phaseolus vulgaris), with special regard to the precursor protein. For this purpose, αAI-1 was tested in both matrix (native flour and cooked flour) and purified forms under in vitro and acute rat in vivo digestion experiments. The effect of digestion on αAI-1s was monitored by lab-on-a-chip (LOC) electrophoresis, SDS-PAGE/immunoblot, and inhibitory activity analyses by native PAGE. After both in vitro and in vivo digestion, we established that αAI-1 was not degraded even after 60 min gastric digestion and showed immune-reactive properties as well. Although the activity of the purified αAI-1 was lost, that of αAI-1 in the flour matrix (noncooked and cooked) was retained in the stomach. Presumably, in the beans, αAI-1 polypeptides became active due to the pepsin digestion of the precursor protein. The latter samples were also tested in vivo in the small intestine and their resistance and immune reactivity were observed, but αAI-1 did not show activity, as αAI-1 polypeptides were probably complexed by pancreatic amylases. From these results, we can assume that the αAI-1-rich bean protein preparation can affect the carbohydrate metabolism; thus, it could be a promising ingredient for weight loss purposes.
Advanced Scanning Technology for Volume Change Measurement of Residual Soil
Authors: Orazayeva Saltanat , Satyanaga Alfrendo , Kim Yongmin , Rahardjo Harianto , Qian Zhai , Moon Sung-Woo , Kim Jong
Published: November 2024

Weathering processes of rocks lead to the formation of residual soil layers, which are typically characterized by a deep groundwater table and a thick unsaturated zone. Hence, the calculation of a slope’s safety factor under the influences of climatic circumstances is a function of unsaturated characteristics, such as the soil–water characteristic curve (SWCC). To determine the SWCC, the volume of the soil specimen must be determined in order to compute the void ratio and degree of saturation. The drying processes of the soil specimen led to uneven soil volume change during laboratory SWCC testing, demanding the development of a soil shrinkage curve. Several methods for measuring soil volume change have been developed over the years. However, there are significant limitations, and it is rarely used due to the difficulty linked to accurately measuring the soil volume during drying processes. In this study, a revised scanning approach is developed to evaluate residual soil volume change utilizing 3D scanning technology. The proposed method is applied in a case study on residual soil from the Old Alluvium in Singapore. The laboratory data and analysis results suggested that 3D scanning technology should be required to provide a correct estimation of the air-entry value of soil.
Quality Evaluation of Effective Abrasive Grains Micro-Edge Honing Based on Trapezoidal Fuzzy Analytic Hierarchy Process and Set Pair Analysis
Authors: Su Jie , Liang Yuan , Yu Yue , Wang Fuwei , Zhou Jiancong , Liu Lin , Gao Yang
Published: November 2024

Studying the factors affecting machining accuracy, surface quality, and machining efficiency in the powerful honing machining process system, analyzing the basic law between various errors and machining quality, exploring the method of evaluating the quality of honing, and improving the machining quality and transmission performance of hardened gears has important engineering application value. Firstly, this paper establishes an effective abrasive grains micro-edge honing quality evaluation model, proposes a method based on the Trapezoidal Fuzzy Analytic Hierarchy Process (Tra-FAHP) and Set Pair Analysis (SPA) to comprehensively evaluate the quality of the honing process, and obtains the influence weights of each factor on the quality of honing. Secondly, the paper analyzes the influence rules of three types of abrasive grain sizes on helix error, tooth pitch error, tooth profile error, surface roughness, and honing efficiency. Finally, the correctness of the established comprehensive evaluation model of honing quality was verified with the threshold method and weights. The research results show that the model can correctly evaluate the quality of hardened gear honing and can be applied to studying the influence of abrasive grain micro-edge honing on machining characteristics.
Artificial Intelligence and Statistical Models for the Prediction of Radiotherapy Toxicity in Prostate Cancer: A Systematic Review
Authors: Piras Antonio , Corso Rosario , Benfante Viviana , Ali Muhammad , Laudicella Riccardo , Alongi Pierpaolo , D'Aviero Andrea , Cusumano Davide , Boldrini Luca , Salvaggio Giuseppe , Di Raimondo Domenico , Tuttolomondo Antonino , Comelli Albert
Published: November 2024

Background: Prostate cancer (PCa) is the second most common cancer in men, and radiotherapy (RT) is one of the main treatment options. Although effective, RT can cause toxic side effects. The accurate prediction of dosimetric parameters, enhanced by advanced technologies and AI-based predictive models, is crucial to optimize treatments and reduce toxicity risks. This study aims to explore current methodologies for predictive dosimetric parameters associated with RT toxicity in PCa patients, analyzing both traditional techniques and recent innovations. Methods: A systematic review was conducted using the PubMed, Scopus, and Medline databases to identify dosimetric predictive parameters for RT in prostate cancer. Studies published from 1987 to April 2024 were included, focusing on predictive models, dosimetric data, and AI techniques. Data extraction covered study details, methodology, predictive models, and results, with an emphasis on identifying trends and gaps in the research. Results: After removing duplicate manuscripts, 354 articles were identified from three databases, with 49 shortlisted for in-depth analysis. Of these, 27 met the inclusion criteria. Most studies utilized logistic regression models to analyze correlations between dosimetric parameters and toxicity, with the accuracy assessed by the area under the curve (AUC). The dosimetric parameter studies included Vdose, Dmax, and Dmean for the rectum, anal canal, bowel, and bladder. The evaluated toxicities were genitourinary, hematological, and gastrointestinal. Conclusions: Understanding dosimetric parameters, such as DVH, Dmax, and Dmean, is crucial for optimizing RT and predicting toxicity. Enhanced predictive accuracy improves treatment effectiveness and reduces side effects, ultimately improving patients’ quality of life. Emerging artificial intelligence and machine learning technologies offer the potential to further refine RT in PCa by analyzing complex data, and enabling more personalized treatment approaches.
In Silico Benchmarking of Fatigue Life Estimation Models for Passive SMD Solder Joints Under Thermal Cycling
Authors: Bakonyi Antal , Fekete Gusztáv , Zelei Ambrus
Published: November 2024

Related to microelectronics’ reliability, lifetime estimation methods have gained importance, especially for surface-mounted devices. The virtual testing of electronic assemblies necessitates the geometry modeling and finite element analysis of the solder joint. The effect of the simplification of the solder geometry on the predicted lifetime is an open question. Furthermore, there is still not yet straightforward guidance for the choice of the material model and fatigue lifetime model. In this study, the impact of the geometry input method, the material model and the lifetime model choice is investigated on two different surface-mounted capacitors in a simulation-based benchmark analysis under thermal cyclic loading. Four different types of solder geometry modeling approaches are compared, among which one is a physics-based approach. Ten different fatigue models founded on plastic and viscoplastic material models are benchmarked. The results show that the component standoff height and the solder volume have a positive effect on the lifetime, while the capacitor size has a slightly negative effect on the lifetime. The results also suggest that approximate geometries can be used to replace the physics-based model with a restriction for the minimum standoff height.
Triple Collocation-Based Uncertainty Analysis and Data Fusion of Multi-Source Evapotranspiration Data Across China
Authors: Wang Dayang , Liu Shaobo , Wang Dagang
Published: November 2024

Accurate estimation of evapotranspiration (ET) is critical for understanding land-atmospheric interactions. Despite the advancement in ET measurement, a single ET estimate still suffers from inherent uncertainties. Data fusion provides a viable option for improving ET estimation by leveraging the strengths of individual ET products, especially the triple collocation (TC) method, which has a prominent advantage in not relying on the availability of “ground truth” data. In this work, we proposed a framework for uncertainty analysis and data fusion based on the extended TC (ETC) and multiple TC (MTC) variants. Three different sources of ET products, i.e., the Global Land Evaporation and Amsterdam Model (GLEAM), the fifth generation of European Reanalysis-Land (ERA5-Land), and the complementary relationship model (CR), were selected as the TC triplet. The analyses were conducted based on different climate zones and land cover types across China. Results show that ETC presents outstanding performance as most areas conform to the zero-error correlations assumption, while nearly half of the areas violate this assumption when using MTC. In addition, the ETC method derives a lower root mean square error (RMSE) and higher correlation coefficient (Corr) than the MTC one over most climate zones and land cover types. Among the ET products, GLEAM performs the best, while CR performs the worst. The merged ET estimates from both ETC and MTC methods are generally superior to the original triplets at the site scale. The findings indicate that the TC-based method could be a reliable tool for uncertainty analysis and data fusion.
Dust Content Modulation and Spring Heat Waves in Senegal (2003–2022)
Authors: Diouf Semou , Sambou Marie-Jeanne G. , Deme Abdoulaye , Fall Papa , Gueye Dame , Mignot Juliette , Janicot Serge
Published: November 2024

The population of Senegal faces health challenges related to desert dust and heat waves (HWs). This study aims to (a) update the documentation of HWs in Senegal, expanding on the work of Sambou et al. (2019); (b) investigate the modulation of dust indicators during HWs; and (c) assess the distinct impacts of dust content on night-time and daytime HWs. We use [i] the daily maximum air temperature (Tx), minimum air temperature (Tn), and apparent temperature (Ta) from 12 stations in the Global Surface Summary of the Day (GSOD) database and [ii] the Dust Aerosol Optical Depth (Dust AOD), particulate matter (PM) concentrations, 925 hPa wind, and Mean Sea Level Pressure (MSLP) from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. HWs are defined for each station in spring as periods when Tx, Tn, or Ta exceeds the 95th percentile for at least three consecutive days. Three homogeneous zones from the Atlantic coast to inland Senegal are identified using hierarchical cluster analysis: Zone 1 (Saint-Louis, Dakar-Yoff, Ziguinchor, and Cap Skirring), Zone 2 (Podor, Linguère, Diourbel, and Kaolack), and Zone 3 (Matam, Tambacounda, Kédougou, and Kolda). Our results show that Zone 1 records the highest number of HWs for Tx, Tn, and Ta, while Zone 3 experiences more HWs in terms of Tn and Ta than Zone 2. The influence of dust is notably stronger for HWs linked to Tn and Ta than for those related to Tx. Analysis of the mechanisms shows that the presence of dust in Senegal and its surrounding regions is detected up to four days before the onset of HWs. These findings suggest that dust conditions associated with spring HWs in Senegal may be better distinguished and predicted.
Sensitivity of Streamflow to Changing Rainfall and Evapotranspiration in Catchments Across the Nile Basin
Authors: Onyutha Charles , Ayugi Brian Odhiambo , Lim Kam Sian Kenny Thiam Choy , Babaousmail Hassen , Arineitwe Wenseslas , Akobo Josephine Taata , Chelangat Cyrus , Mubialiwo Ambrose
Published: November 2024

This research focuses on the complex dynamics governing the sensitivity of streamflow to variations in rainfall and potential evapotranspiration (PET) within the Nile basin. By employing a hydrological model, our study examines the interrelationships between meteorological variables and hydrological responses across six catchments (Blue Nile, El Diem, Kabalega, Malaba, Mpanga, and Ribb) and explores the intricate balance between rainfall, PET, and streamflow. Nash Sutcliffe Efficiency (NSE) for calibration of the hydrological model ranged from 0.636 (Ribb) to 0.831 (El Diem). For validation, NSE ranged from 0.608 (Ribb) to 0.811 (Blue Nile). With rainfall kept constant while PET was increased by 5%, the streamflows of the Blue Nile, El Diem, Kabalega, Malaba, Mpanga, and Ribb decreased by 7.00, 5.08, 2.49, 4.10, 1.84, and 7.67%, respectively. With the original PET data unchanged, increasing rainfall of the Blue Nile, El Diem, Kabalega, Malaba, Mpanga, and Ribb by 5% led to an increase in streamflow by 9.02, 9.87, 5.38, 4.34, 6.58, and 8.32%, respectively. The research reveals that the rate at which a catchment losing water to the atmosphere (determined by PET) substantially influences its drying rate. Utilizing linear models, we demonstrate that the surplus rainfall available for increasing streamflow (represented by model intercepts) amplifies with higher rainfall intensities. This highlights the pivotal role of rainfall in shaping catchment water balance dynamics. Moreover, our study stresses the varied sensitivities of catchments within the basin to changes in PET and rainfall. Catchments with lower PET exhibit heightened responsiveness to increasing rainfall, accentuating the influence of evaporative demand on streamflow patterns. Conversely, regions with higher PET rates necessitate refined management strategies due to their increased sensitivity to changes in evaporative demand. Understanding the intricate interplay between rainfall, PET, and streamflow is paramount for developing adaptive strategies amidst climate variability. By examining these relationships, our research contributes essential knowledge for sustainable water resource management practices at both the catchment and regional scales, especially in regions susceptible to varying sensitivities of catchments to climatic conditions.
A Theoretical Review of Area Production Rates as Test Statistics for Detecting Nonequilibrium Dynamics in Ornstein–Uhlenbeck Processes
Authors: Strang Alexander
Published: November 2024

A stochastic process is at thermodynamic equilibrium if it obeys time-reversal symmetry; forward and reverse time are statistically indistinguishable at a steady state. Nonequilibrium processes break time-reversal symmetry by maintaining circulating probability currents. In physical processes, these currents require a continual use and exchange of energy. Accordingly, signatures of nonequilibrium behavior are important markers of energy use in biophysical systems. In this article, we consider a particular signature of nonequilibrium behavior: area production rates. These are the average rate at which a stochastic process traces out signed area in its projections onto coordinate planes. Area production is an example of a linear observable: a path integral over an observed trajectory against a linear vector field. We provide a summary review of area production rates in Ornstein–Uhlenbeck (OU) processes. Then, we show that, given an OU process, a weighted Frobenius norm of the area production rate matrix is the optimal test statistic for detecting nonequilibrium behavior in the sense that its coefficient of variation decays faster in the length of time observed than the coefficient of variation of any other linear observable. We conclude by showing that this test statistic estimates the entropy production rate of the process.
Investigating Offensive Language Detection in a Low-Resource Setting with a Robustness Perspective
Authors: Abdellaoui Israe , Ibrahimi Anass , El Bouni Mohamed Amine , Mourhir Asmaa , Driouech Saad , Aghzal Mohamed
Published: November 2024

Moroccan Darija, a dialect of Arabic, presents unique challenges for natural language processing due to its lack of standardized orthographies, frequent code switching, and status as a low-resource language. In this work, we focus on detecting offensive language in Darija, addressing these complexities. We present three key contributions that advance the field. First, we introduce a human-labeled dataset of Darija text collected from social media platforms. Second, we explore and fine-tune various language models on the created dataset. This investigation identifies a Darija RoBERTa-based model as the most effective approach, with an accuracy of 90% and F1 score of 85%. Third, we evaluate the best model beyond accuracy by assessing properties such as correctness, robustness and fairness using metamorphic testing and adversarial attacks. The results highlight potential vulnerabilities in the model’s robustness, with the model being susceptible to attacks such as inserting dots (29.4% success rate), inserting spaces (24.5%), and modifying characters in words (18.3%). Fairness assessments show that while the model is generally fair, it still exhibits bias in specific cases, with a 7% success rate for attacks targeting entities typically subject to discrimination. The key finding is that relying solely on offline metrics such as the F1 score and accuracy in evaluating machine learning systems is insufficient. For low-resource languages, the recommendation is to focus on identifying and addressing domain-specific biases and enhancing pre-trained monolingual language models with diverse and noisier data to improve their robustness and generalization capabilities in diverse linguistic scenarios.
On Non-Random Mating, Adaptive Evolution, and Information Theory
Authors: Carvajal-Rodríguez Antonio
Published: November 2024

Population genetics describes evolutionary processes, focusing on the variation within and between species and the forces shaping this diversity. Evolution reflects information accumulated in genomes, enhancing organisms’ adaptation to their environment. In this paper, I propose a model that begins with the distribution of mating based on mutual fitness and progresses to viable adult genotype distribution. At each stage, the changes result in different measures of information. The evolutionary dynamics at each stage of the model correspond to certain aspects of interest, such as the type of mating, the distribution of genotypes in regard to mating, and the distribution of genotypes and haplotypes in the next generation. Changes to these distributions are caused by variations in fitness and result in Jeffrey’s divergence values other than zero. As an example, a model of hybrid sterility is developed of a biallelic locus, comparing the information indices associated with each stage of the evolutionary process. In conclusion, the informational perspective seems to facilitate the connection between cause and effect and allows the development of statistical tests to perform hypothesis testing against zero-information null models (random mating, no selection, etc.). The informational perspective could contribute to clarify, deepen, and expand the mathematical foundations of evolutionary theory.
Diabetic Glycation of Human Serum Albumin Affects Its Immunogenicity
Authors: Croes Cresci-Anne C. C. , Chrysanthou Marialena , Hoppenbrouwers Tamara , Wichers Harry , Keijer Jaap , Savelkoul Huub F. J. , Teodorowicz Malgorzata
Published: November 2024

Advanced glycation end-products (AGEs) are products of a non-enzymatic reaction between amino acids and reducing sugars. Glycated human serum albumin (HSA) increases in diabetics as a consequence of elevated blood glucose levels and glycating metabolites like methylglyoxal (MGO). The impact of different types of glycation on the immunomodulatory properties of HSA is poorly understood and is studied here. HSA was glycated with D-glucose, MGO, or glyoxylic acid (CML). Glycation-related biochemical changes were characterized using various biochemical methods. The binding of differentially glycated HSA to AGE receptors was determined with inhibition ELISAs, and the impact on inflammatory markers in macrophage cell line THP-1 and adherent monocytes isolated from human peripheral blood mononuclear cells (PBMCs) was studied. All glycation methods led to unique AGE profiles and had a distinct impact on protein structure. Glycation resulted in increased binding of HSA to the AGE receptors, with MGO modification showing the highest binding, followed by glucose and, lastly, CML. Additionally, modification of HSA with MGO led to the increased expression of pro-inflammatory markers in THP-1 macrophages and enhanced phosphorylation of NF-κB p65. The same pattern, although less prominent, was observed for HSA glycated with glucose and CML, respectively. An increase in pro-inflammatory markers was also observed in PBMC-derived monocytes exposed to all glycated forms of HSA, although HSA–CML led to a significantly higher inflammatory response. In conclusion, the type of HSA glycation impacts immune functional readouts with potential relevance for diabetes.
A Versatile Skin-Derived Extracellular Matrix Hydrogel-Based Platform to Investigate the Function of a Mechanically Isolated Adipose Tissue Stromal Vascular Fraction
Authors: Zhang Xue , Schipper Jan Aart M. , Schepers Rutger H. , Jansma Johan , Spijkervet Fred K. L. , Harmsen Martin C.
Published: November 2024

Introduction: To accelerate cutaneous wound healing and prevent scarring, regenerative approaches such as injecting a mechanically derived tissue stromal vascular fraction (tSVF) are currently under clinical and laboratory investigations. The aim of our study was to investigate a platform to assess the interaction between skin-derived extracellular matrix (ECM) hydrogels and tSVF and their effects on their microenvironment in the first ten days of culture. Material and Methods: A tSVF mixed with ECM hydrogel was cultured for ten days. After 0, 3, 5, and 10 days of culture viability, histology, immunohistochemistry, gene expression, and collagen alignment and organization were assessed. Results: The viability analysis showed that tSVF remained viable during 10 days of culture and seemed to remain within their constitutive ECM. The fiber analysis demonstrated that collagen alignment and organization were not altered. No outgrowth of capillaries was observed in (immuno)histochemical staining. The gene expression analysis revealed that paracrine factors TGFB1 and VEGFA did not change and yet were constitutively expressed. Pro-inflammatory factors IL1B and IL6 were downregulated. Matrix remodeling gene MMP1 was upregulated from day three on, while MMP14 was upregulated at day three and ten. Interestingly, MMP14 was downregulated at day five compared to day three while MMP2 was downregulated after day zero. Conclusions: Skin-derived ECM hydrogels appear to be a versatile platform for investigating the function of a mechanically isolated adipose tissue stromal vascular fraction. In vitro tSVF remained viable for 10 days and sustained the expression of pro-regenerative factors, but is in need of additional triggers to induce vascularization or show signs of remodeling of the surrounding ECM. In the future, ECM-encapsulated tSVF may show promise for clinical administration to improve wound healing.
Effect of Photolithographic Biomimetic Surface Microstructure on Wettability and Droplet Evaporation Process
Authors: Zhang Zhihao , Yan Yuying
Published: November 2024

In nature, engineering technology and daily life, wetting phenomena are widespread and have essential roles and significance. Bionics is becoming increasingly important nowadays and exploring the mechanism that influences biomimetic surface microstructure on droplet wetting process and heat and mass transfer characteristics is becoming more meaningful. In this paper, based on photolithography technology, SU-8 photoresist was used as raw material to prepare biomimetic surfaces with microstructures in various arrangements. The research results show that the wettability of biomimetic functional surfaces can be regulated by regulating the shape and arrangement of photoresist micro-pillars. At the same time, the effects of surface microstructure configuration and roughness on the heat and mass transfer processes within the droplets were also comprehensively studied. The results show that a biomimetic surface with cylindrical micro-pillars can effectively inhibit the evaporative cooling effect of the liquid–vapour interface. This effect becomes more evident with the increase in roughness, and the interface temperature difference can be reduced by up to 18%. Similarly, the biomimetic surface with cylindrical micro-pillars can also effectively promote the evaporation rate of sessile droplets, which can be increased by about 13%. In addition, the research also shows that regardless of the structure, substrate temperature changes will significantly impact the wetting phenomenon of the biomimetic surface. This study aims to guide the optimal design of biomimetic surfaces prepared based on photoresistance.
Valorization of Selected Biomass-Derived Molecules on Olea europaea Leaves-Biotemplated TiO2-g-C3N4 Photocatalysts
Authors: Herrera-Beurnio M. Carmen , López-Tenllado Francisco J. , Ariza-Pérez Alejandro , Hidalgo-Carrillo Jesús , Estevez Rafael , Martín-Gómez Juan , Urbano Francisco J. , Marinas Alberto
Published: November 2024

Biotemplating technique allows the synthesis of catalysts, recreating the sophisticated structure of nature templates. In this work, some biotemplated TiO2 semiconductors were synthesized using Olea europaea leaves as templates. Then, g-C3N4 was coupled to materials to later incorporate Pt on the surface or as dopant in the structure to evaluate the efficiency of the solids in two photocatalytic applications to valorize biomass: hydrogen production through glycerol photoreforming, and photoacetalization of cinnamaldehyde with 1,2-propanediol. In glycerol photoreforming, the presence of Pt (superficial or dopant) enhanced hydrogen production, being Pt@AOLCN (a heterojunction containing biotemplated TiO2, g-C3N4, and Pt) the system that exhibited the highest efficiency (3053.4 µmol·gcat−1·h−1). For photoacetalization, while Pt reduced cinnamaldehyde conversion, it improved selectivity when incorporated on TiO2. Notably, carbon nitride (CN) exhibited the highest yield after 16 h of testing. The study emphasizes the importance of tailoring catalyst selection to specific reactions, as efficiency is closely tied to the structural and chemical properties of the materials. These findings contribute to the development of efficient photocatalysts for sustainable biomass valorization processes.
Relations Between Executive Functions and Reading Comprehension: A Study of Fourth-Grade Students with and Without Reading Comprehension Difficulties
Authors: Escobar José-Pablo , Espinoza Victoria , Balboa Sofia
Published: November 2024

Background: The role of non-linguistic factors, such as executive functions, in the reading comprehension process has been analyzed. The present research sought to investigate the relationship between executive functions and reading comprehension. Methods: In an exploratory cross-sectional study, a group of 89 fourth-grade students were evaluated, considering a balanced number of children with and without reading comprehension difficulties. Results: The results indicate that students with reading comprehension difficulties present a lowered profile with respect to both executive functions and reading variables. The path analysis indicates the presence of differences in the variables that explain reading comprehension for both groups. While in the case of students without reading comprehension difficulties, working memory has both a direct and an indirect effect, i.e., through vocabulary, on reading comprehension; in the case of children with reading comprehension difficulties, only cognitive flexibility has a direct impact. In both cases, inhibition has an indirect impact through vocabulary. Conclusions: We reflect on the differentiated role of executive functions according to the level of development of reading skills, highlighting the possibility that some skills may act in a compensatory manner in the presence of general difficulties. The role of vocabulary in the relationship between executive skills and reading is highlighted.
How Do Algorithmic Management Practices Affect Workforce Well-Being? A Parallel Moderated Mediation Model
Authors: Zayid Husam , Alzubi Ahmad , Berberoğlu Ayşen , Khadem Amir
Published: November 2024

Modern workplaces increasingly use algorithmic management practices (AMPs), which shape task assignment, monitoring, and evaluation. Despite the potential benefits these practices offer, like increased efficiency and objectivity, their impact on workforce well-being (WFW) has raised concerns. Drawing on self-determination theory (SDT) and conservation of resources theory (COR), this study examines the relationship between algorithmic management practices and workforce well-being, incorporating job burnout (JBO) and perceived threat (PT) as parallel mediators and person–job fit (PJF) as a moderator. The research employed a cross-sectional survey design targeting 2450 KOSGEB-registered manufacturing SMEs in Istanbul, Turkey. A sample of 666 respondents participated, and the data were analyzed using Smart PLS 4, employing structural equation modeling to test the proposed model. The results indicated that algorithmic management practices significantly increased job burnout and perceived threat, both of which negatively impacted workforce well-being. However, the direct effect of algorithmic management practices on workforce well-being was non-significant. Person–job fit moderated the relationships between algorithmic management practices and both job burnout and perceived threat, further influencing workforce well-being. The findings underscore the critical need for organizations to balance algorithmic efficiency with human-centric practices. Prioritizing person–job fit and fostering transparency in algorithmic processes can mitigate negative impacts, enhance employee well-being, and drive sustainable organizational success in the digital age.
Servant Leadership and Teachers’ Emotional Exhaustion—The Mediation Role of Hindrance Stress and Depersonalization
Authors: Wu Hongchao , Zhao Jun , Qiu Shaoping , Li Xiuhong
Published: November 2024

Abstract: This study aims to explore the impact of school servant leadership on teacher emotional exhaustion in the context of Chinese education, and analyze the mediating effects of teacher hindrance stress and depersonalization. Based on the Job Demand-Control-Support (JDCS) model and servant leadership theory, the research constructs a model for the influence mechanism of school servant leadership on teacher emotional exhaustion and validates it using Structural Equation Modeling (SEM). A total of 3751 primary and secondary school teachers from eight provinces in China participated in this study. The results indicate servant leadership demonstrates a strong negative relationship with emotional exhaustion, with hindrance stress and depersonalization serving as a sequential mediation between servant leadership and emotional exhaustion. This study offers a new perspective on how servant leadership can alleviate emotional exhaustion among teachers, and provides practical insights for optimizing educational management models and enhancing teacher mental well-being.
Experimental Study on Variable Amplitude Fatigue Performance of High-Strength Bolts in Steel Structure Flange Connections
Authors: Ni Huaguang , Zhang Shujia , Lei Honggang
Published: November 2024

Steel structure flange connections are extensively employed in structural nodes due to their superior mechanical properties. This study combines fatigue testing and theoretical methods to investigate the fatigue performance of high-strength bolts in flange connections under actual gradient descent loads and provide fatigue design methods. Initially, fatigue tests were conducted on two sets of high-strength bolts under a gradient descent loading mode, yielding a total of 11 sets of fatigue data. Subsequently, the stress–life (S-N) curve was plotted using a cumulative damage model combined with an equivalent constant amplitude stress method, and the results were compared with existing fatigue design specifications. Additionally, digital cameras and electron microscopes were utilized to capture fatigue fracture images of the high-strength bolts, allowing a detailed investigation into the mechanisms underlying bolt fatigue fractures. The results indicate that the allowable stress amplitudes for the two sets of high-strength bolts, corresponding to a fatigue life threshold of 2 million cycles, were 144.211 MPa and 130.316 MPa, respectively—both of which exceed the values specified in current fatigue design codes. Moreover, finite element simulations revealed that the most pronounced stress concentration occurs at the first thread where the bolt and nut interface, which is identified as the critical location for fatigue fracture in bolts. The allowable stress and fatigue calculation method of bolts obtained in this study will provide a reference for flange node design
Strengthening of Reinforced Concrete Hydraulic Structures with External Reinforcement System Made of Carbon Fiber-Based Composite Materials with Development of Calculation Recommendations
Authors: Rubin Oleg , Kozlov Dmitry , Antonov Anton , Zhang Junhao
Published: November 2024

During the long-term operation of hydraulic structures under the action of complex loads and impacts, non-design changes occur, which lead to a decrease in the bearing capacity and safety and, accordingly, to the need for structural reinforcements. Experiments were conducted to study the strengthening of reinforced concrete models of hydraulic structures with interblock construction joints (located in two directions) and with the low longitudinal reinforcement coefficients typical of hydraulic structures (μs = 0.0039 and μs = 0.0083), using the low concrete classes B15 and B25. These structures were strengthened using external reinforcement with carbon ribbons of the FibArm 530/300 type. The results revealed an increase in the bearing capacity (by 1.355- and 1.66-fold); accordingly, the high efficiency of this strengthening method for reinforced concrete hydraulic structures was proven. Using the results of these experiments, including the obtained special characteristic of the cracking of reinforced concrete structures and the results of studies by other authors, recommendations for calculations involving reinforced concrete hydraulic engineering structures strengthened with an external reinforcement system of carbon-fibre-based composite materials were developed and proposed. Carbon-fibre-based composite materials are used as elements of external reinforcement for building structures (unidirectional—tapes, bidirectional—meshes and fabrics). The calculation recommendations proposed by the authors can be taken into account for the creation of a regulatory framework for hydropower facilities, including hydroelectric power plants and pumped-storage power plants. They justify the use of an external reinforcement system made with carbon-fibre-based composite materials to strengthen hydraulic structures in operation and provide an increased level of safety for reinforced concrete structures and constructions.
Study on Error Influence Analysis of an Annular Cable Bearing-Grid Structure
Authors: Xu Jingshuo , Ding Mingmin , Lin Yu , Wei Yang , Hua Zhenliang
Published: November 2024

Manufacturing errors of cable length, external node coordinates and tension force by the passive tension method are inevitable, which will inevitably affect the prestressing of cable bearing-grid structures, while existing studies lack the error analysis of error influences in this area. This paper proposes a method for analyzing random errors in constructing annular cable bearing-grid structures. An error control index and a normal distribution-based random error model, considering the impact of cable and ring beam length errors on cable force, were established afterwards. Taking the roof of the Qatar Education City Stadium as an example, the influence of the length errors of the radial cable, ring cable, and outer pressure ring beam on the structural cable force and stress level was analyzed, and the coupling error effect analysis was carried out. The results show that ring cable force and radial cable force are less affected by the length error of each other’s cables, while they are more affected by the length error of the outer ring beam. Stress levels exhibit greater sensitivity to outer ring beam errors compared to cable length errors. As the error limits of outer ring beam increase, radial and ring cable error ratios and outer ring beam stress errors also rise.
Research on Natural Gas Leakage and Explosion Mechanisms in a Container House
Authors: Gao Yonghong , Duan Yapeng , Fu Runmei , Wu Hao , Wang Zicong , Li Dongyang , Zhou Liqiang
Published: November 2024

As unconventional building structures, container houses are now widely used in urban tourism to create characteristic buildings. Nowadays, natural gas accidents occur frequently in cities and towns; however, the development of laws and influencing factors of natural gas accidents in container buildings have rarely been studied. In this paper, a natural gas explosion test was carried out in an ordinary container house, and a numerical simulation was carried out according to the test results. The influence of methane proportion, ignition position, pressure-relief area, and pressure-relief intensity on the explosion load was analyzed. Research shows that natural gas will gather from top to bottom during the process of leakage and diffusion, and vertical stratification will occur. The most unfavorable working condition is 9.5% methane. Using the roof of the container house as a pressure-relief panel can effectively control the influence range of natural gas explosion accidents and help reduce accident losses. It is suggested that the stacking of container buildings should be reduced as much as possible, and the roof strength should be weakened to ensure structural safety. The research results have certain reference values for the disaster prevention and reduction design of urban characteristic buildings.
Analytical Validation and Performance Evaluation of Amplicon-Based Next-Generation Sequencing Assays for Detecting ERBB2 and Other Gene Amplifications in Solid Tumors
Authors: Olkhov-Mitsel Ekaterina , Chan Danny , Craddock Kenneth J. , Lin August , Luk Grace , Goswami Rashmi S. , Wang Hong , Plotkin Anna , Nofech-Mozes Sharon , Hwang David M. , Huang Weei-Yuarn
Published: November 2024

Background: Targeted next-generation sequencing (NGS) panels are increasingly being utilized to identify actionable gene amplifications (copy number > 4) among solid tumors. Methods: This study validated the analytical performance of two amplicon-based NGS assays, the Oncomine Comprehensive Panel (OCAv3) and the Oncomine Focus Assay (OFA), for detecting gene amplification in formalin-fixed paraffin-embedded (FFPE) tumors of varying cellularity. OCAv3 was assessed for amplification detection in 756 FFPE samples comprising various tumor types. Results: We demonstrated that with standardized quality control metrics, including median absolute pairwise difference score, these assays can achieve a near-perfect positive predictive value, although their sensitivity for detecting amplifications significantly decreased in tumors with cellularity below 30%. Stratifying tumor cellularity into 10–30%, 31–60%, and 61–95% groups revealed significantly higher gene amplification detection rates in the 31–60% and 61–95% groups versus the 10–30% group (20.6% and 26.7% vs. 9.2%, p < 0.0001). When considering all detected gene amplifications, the average amplification calling per sample was nearly five-fold lower in the 10–30% group versus the 61–95% group (0.11 vs. 0.52; p < 0.0001). To further investigate the analytic performance of OCAv3 in detecting ERBB2 amplification, we analyzed a cohort of 121 uterine carcinomas with confirmed ERBB2 status by HER2 IHC or FISH, in which a threshold incorporating amplifications and tumor cellularity achieved 79% sensitivity and 100% specificity, potentially eliminating the need for FISH analysis in 34% of equivocal cases. In a separate validation cohort, similar analytical performance was observed, with the threshold demonstrating consistent sensitivity and specificity. Conclusions: This study highlights the strengths and limitations of amplicon-based NGS assays in detecting amplifications using real-world data.
Evaluating the Safety of Immune Checkpoint Inhibitors and Combination Therapies in the Management of Brain Metastases: A Comprehensive Review
Authors: Podder Vivek , Ranjan Tulika , Margolin Kim , Maharaj Arun , Ahluwalia Manmeet Singh
Published: November 2024

Brain metastases (BM) are a frequent and severe complication in patients with lung cancer, breast cancer, and melanoma. Immune checkpoint inhibitors (ICIs) have become a crucial treatment option for BM, whether used alone or in combination with chemotherapy and stereotactic radiosurgery (SRS). However, ICIs are associated with immune-related adverse events (irAEs) that can affect multiple organ systems, complicating their use in BM patients. This review examines the mechanisms of irAEs and their effects on different organs and evaluates the safety of ICIs across various treatment strategies for BM. Our analysis indicates that ICIs significantly improve survival and disease control in BM patients, but their use increases the risk of irAEs, including dermatologic, gastrointestinal, endocrine, pulmonary, and neurologic toxicities. Neurotoxic events, particularly treatment-associated brain necrosis (TABN) and encephalitis, are more common in BM patients. While the overall incidence of irAEs is similar between patients with and without BM, the neurotoxicity risk is higher in the BM population. Combining ICIs with chemotherapy and SRS enhances efficacy but also heightens the risk of adverse events across organ systems. ICIs offer substantial benefits for BM patients but require careful management to mitigate the risks of irAEs. Close patient monitoring, individualized treatment protocols, and prompt intervention are essential for optimizing the outcomes. Future research should focus on refining combination strategies and improving the management of irAEs, particularly neurotoxicity, to maximize therapeutic benefits for BM patients.