bluuebunny/crossref_metadata_2025 huggingface dataset:
The Historic Pathophysiologic Journey of Heart Failure Management: Targeting Oxidative Stress with the Antioxidant Glutathione. Are Antioxidants Another “Arrow” in the Quiver of Heart Failure Therapy?
Authors: Yutani Ray
Published: January 2025

Early treatments of heart failure (HF) were directed toward management of fluid overload and providing inotropic support. Now, management of HF is multifaceted. Many of these treatments were established from outcomes of clinical trials. Each study has broadened our understanding of HF pathophysiology. The current regimens now include medications directed against the renin-aldosterone, angiotensin system (RAAS), the sympathetic system, and the natriuretic system. Recently, the sodium-glucose transport-2 inhibitors (SGLT2i) that were initially given to treat Type 2 diabetes are now recognized as being effective to treat HF. Since this effect was also beneficial in non-diabetic individuals, it prompted investigations to determine another mechanism of action (MOA) apart from its primary one that inhibits renal glucose reuptake. It led to the discovery of its anti-inflammatory property. This is notable since HF is associated with oxidative stress (OS) that is the result of excessive inflammation. It has highlighted the goal of reducing OS with an antioxidant as another target in HF treatment. Glutathione (GSH) is a well-known anti-inflammatory agent. Studies with its use in HF patients could determine the role of antioxidants in HF by reducing OS. A novel nano-product, the glutathione-cyclodextrin (G-C) complex will be presented that therapeutically delivers GSH. Studies using the G-C complex should determine the efficacy of GSH to suppress OS. If those studies are confirmatory, antioxidants could be another “arrow” in the quiver of HF management.
The Geometry of the Functional Space Type of Lebesgue-Morrey with Many Groups of Variables
Authors: Kerbalayeva Rena
Published: January 2025

In mathematics as in everyday life we encounter the concept of the mathematics. We can speak of the space of function with many groups of variables on the plane of Analysis, Function Analysis and so on. The concept of a space is not so general that it would be difficult to give it a definition which would not reduce to simply replacing the word “norm” by one of the equivalent expressions: Lebesgue-Morrey, Bessov-Morrey, etc. The concept of normed function spaces plays an extraordinarily important role in modern mathematics not only because the theory of space itself has become at the present time a very extensive and comprehensive discipline but mainly because of the influence which the theory of spaces, arising at the end of the last century, exerted and still exerts on mathematics as a whole. Here we shall briefly discuss only those very basic normed spaces concepts which will be used in the following areas. The geometry of functional Analysis and functional spaces aims at presenting the theorems and methods of modern mathematics and giving several applications in Geometry and Function Analysis. It is in fact an important theory for mathematics, since introducing some new relationship between Function analysis and Geometry. In this article I discuss some new results which stand between geometry, analysis and functional analysis.
Optimal Positioning of UAV Base Stations using Mixed-Integer Linear Programming
Authors: Veeraswamy Premkumar Gowtham Raj , Van Scoy Bryan
Published: January 2025

In wireless communications, traditional base-stations act as the backbone for providing network connectivity to users. These base-stations, however, require significant resources to construct and are therefore not suitable for remote areas and disaster scenarios. This challenge makes them unfit for deployment in remote areas or in disaster scenarios where fast network establishment is necessary. To address these challenges, cellular base stations installed on Unmanned Aerial vehicles (UAVs) can be an alternative solution. UAVs provide quick deployment capability and can adapt to changing environmental situations, making them ideal for dynamic network scenarios. In this paper we address the critical issue of UAV positioning to maximize the total user coverage, which can be formulated as an mixed-integer linear program. Given the complexity of larger-scale scenarios related to number of users, we suggest a two-step method. First, we group users into clusters and then we optimize the UAV positions with respect to these clusters. This approach introduces a trade-off among computational time efficiency and optimality, which can be tuned by adjusting the number of clusters. By varying the number of clusters, we balance computation time with the optimality of the UAV locations, allowing flexible deployment in diverse scenarios.
Evaluating Multidisciplinary Team Effectiveness and Parental Satisfaction in Special Education Settings in Jordan: Insights and Areas for Improvement
Authors: Swafta Batul , Qat Bayan , Abu-Dahab Sana , Aldughmi Mais , Hadoush HIkmat , Almasri Nihad
Published: January 2025

Background/Objectives: Children with developmental delays encounter many medical and functional obstacles, requiring all-encompassing care from multidisciplinary teams (MDT). In Jordan, these teams are common in special education environments, offering both rehabilitation and education services. It is important to comprehend the factors that impact team effectiveness and parental satisfaction in these settings to improve rehabilitation services in special schools. The study aims to (1) describe health professionals' perceptions of the effectiveness of MDTs in delivering services to children with developmental delays, (2) describe parents of children with DD satisfaction with the performance of the MDTs, (3) compare the effectiveness of MDTs based on professional and setting variables, and (4) compare the parental satisfaction based on parent and setting variables. Methods: Ethical approval was obtained. Data were collected through interviews with therapists and special education specialists from seven public and private special education schools in Jordan. Health professionals completed the Team Effectiveness Questionnaire (TEQ), while parents completed the Satisfaction Survey. Results: The Team Effectiveness Questionnaire (TEQ) scored an average of 3.85 out of 5, with the "Purpose and Goals" dimension receiving the highest ratings, while "Problem Solving" scored the lowest. Parents expressed the highest satisfaction with the team's respect for their priorities, rating it at 4.66, while communication with physicians received the lowest parental rating at 4.10. Significant associations were found between professionals' income levels and the effectiveness of team relationships and problem-solving capabilities (p<0.05). Additionally, satisfaction ratings varied by school type, with parents from private schools reporting higher satisfaction than those from public schools (p<0.05). Conclusions: Overall, MDTs are effective in establishing clear goals and respecting parents’ roles in the process. However, addressing communication and problem-solving weaknesses within the teams could further enhance their effectiveness. The influence of income on team performance and the differences in satisfaction across school types highlight areas for future research and the need for contextual adjustments in team practices.
Number-Operator-Based Inverse Engineering Technique for the Shortcut to Adiabaticity in Two Level Quantum Mechanical System
Authors: Kiran T. , Ponmurugan M.
Published: January 2025

In general, the conventional Lewis-Riesenfeld invariant-based inverse engineering is a nonadiabatic process that results in the adiabatic final states to achieve the shortcut to adiabaticity, which does not provide complete suppression of non-adiabaticity throughout the evolution. We propose a new method to accomplish the shortcut to adiabaticity through an entirely adiabatic path. This new method is developed using the number operator as an invariant of the Hamiltonian. This paper discusses the mathematical framework of the new method in two-level quantum system and analyzes its performance compared to the conventional Lewis-Riesenfeld invariant-based inverse engineering method.
A Non-Trans-Epithelial “Channel Absorption” in the Villi of the Small Intestine: An Intestinal Absorption Basis for Overnutrition
Authors: Sun Xiao-Wei , Hao Yu-Meng , Niu Ting-Ting , Lin Wen-Jiao , Xie Lan , Zhang Jian-Gang , Hua Ai
Published: January 2025

Absorption plays a pivotal role in the development of nutritional obesity. However, little is known about nutritional-obesity–related absorption augmentation. The aim of this study was to observe the morphological features of villous absorption in fasting–refeeding (FaF) and nutritional obesity. After 48 h of fasting, adult male Sprague Dawley (SD) rats were refed, and their intestines were sampled 2–6 h after feeding. After 20 weeks of modeling, we collected the intestines of obese rats. Samples were processed and observed under a light microscope and an electron microscope. Villous-tip openings and the subepithelial space formed an unrestricted-absorption channel connecting the enteric lumen with the submucosal lymphatic sinus and porous capillaries. FaF and high ingestion of a high-fat diet (HFD) were effective inducing factors. Channel absorption of villi was related to apoptosis and the loss of tight junctions in the epithelium. In cases of FaF or obesity, villous-tip openings and the subepithelial space of the villi formed a continuous channel, providing transient and functional unrestricted channel absorption.
Research on Lightweight Kiwifruit Detection Algorithm Based on YOLOv8-BFW
Authors: Shan Wei , Zhao Dan , Yue Yurong
Published: January 2025

Aiming at the problems of low recognition efficiency and accuracy and high computing resources of YOLOv8 model in kiwifruit detection, this paper proposes a lightweight kiwifruit detection algorithm YOLOv8-BFW based on YOLOv8. Firstly, the weighted bidirectional feature pyramid network BiFPN module is introduced into the Neck part of YOLOv8 to realize multi-scale feature fusion, so as to improve the efficiency and accuracy of its detection; Secondly, all C2f modules are integrated into the FasterNet network to form a C2f-Faster module to reduce computing resources; Finally, the WIOU boundary loss function is used to replace the original CIOU to improve the regression performance of the network bounding box and accelerate the convergence speed of the model, which can more accurately measure the overlapping area of the box and further improve the efficiency and accuracy of its detection. The experimental results show that the average detection accuracy mAP of the YOLOv8-BFW algorithm on the self-made kiwifruit dataset collected and labeled in this paper reaches 96.9%. Compared with the original YOLOv8 algorithm, the model size is reduced by 32%, the calculation amount is reduced by 22.2%, the parameter quantity is reduced by 29.6%, and the detection speed is increased by 26.7%.
Numerical Analysis on Impact of Membrane Thickness and Temperature on Characteristics of Biogas Dry Reforming Membrane Reactor Using Pd/Cu Membrane and Ni/Cr Catalyst
Authors: Nishimura Akira , Ichii Ryoma , Yamada Souta , Ichikawa Mizuki , Hayakawa Taisei , Hu Eric
Published: January 2025

The aim of this study is to clarify the characteristics of BDR in the membrane reactor using Pd/Cu membrane and Ni/Cr catalyst by the numerical simulation. This study has conducted the numerical simulation using the CFD software COMSOL Multiphysics ver. 6.2. The impact of the initial reaction temperature and the thickness of Pd/Cu membrane on the characteristics of BDR in the membrane reactor using Pd/Cu membrane and Ni/Cr catalyst is also investigated. The initial reaction temperature is changed by 400 ℃, 500 ℃ and 600 ℃ and the thickness of Pd/Cu membrane is changed by 20 m, 40 m and 60 m. The molar concentrations of CH4 and CO2 decrease with the increase in the initial reaction temperature, while the molar concentrations of H2, CO, H2O and C increase with the increase in the initial reaction temperature. In addition, the molar concentrations of H2 in reaction chamber, Pd/Cu membrane and sweep chamber increase with the increase in the initial reaction temperature. Moreover, the molar concentrations of H2 in Pd/Cu membrane and sweep chamber increase with the decrease in the thickness of Pd/Cu membrane. It is revealed that CH4 conversion, CO2 conversion and H2 yield increase with the increase in the initial reaction temperature as well as the decrease in the thickness of Pd/Cu membrane.
Scoping Review of Dysregulation of Mood, Energy, and Social Rhythms Syndrome (DYMERS) Regarding Burnout in Healthcare Professionals During COVID-19
Authors: Nash Carol
Published: January 2025

Background/Objectives: Dysregulation of Mood, Energy, and Social Rhythms Syndrome (DYMERS) characterizes the poor regulation of biological (sleep/waking), social, and behavioral rhythms that affected the level of burnout in healthcare professionals during the pandemic in particular. The aim is to scope the range of publications on this topic. Methods: The keywords “Stress Rhythms Dysregulation Bipolar Disorder Burnout DYMERS Healthcare professionals COVID-19” were searched on 9 December 2024 following PRISMA 2020 guidelines, using five primary databases (OVID, ProQuest, PubMed, Scopus, Web of Science), one register (Cochrane COVID-19 register), and one supplementary database (Google Scholar). Included were peer-reviewed publications. Excluded were duplicates, reports lacking either a research study or any keywords, or including irrelevant information regarding them. Results: The returns for all databases were (n = 0) except for ProQuest (n = 4) and Google Scholar (n = 14). Of these, three ProQuest returns were duplicates of the Google Scholar search. The remaining report contained irrelevant information on healthcare professionals. The Google Scholar search results produced two relevant reports—neither duplicated with ProQuest. The excluded contained a duplicate in the search itself, three that did not mention healthcare professionals, two that contained irrelevant information concerning them, four returns that were not a research study, and three that were not peer-reviewed. Conclusions: The two studies published on this topic are by various members of the same investigating institution. DYMERS has provided valuable insights regarding burnout in healthcare professionals. The suggestion is for further DYMERS research by this team and others, anticipating future pandemics.
Advanced Phosphorus-Protein Hybrid Coatings for Fire Safety of Cotton Fabrics, Developed Through the Layer-by-Layer As-sembly Technique
Authors: Yang Xuqi , Li Xiaolu , Guo Wenwen , Mohammadi Abbas , Entezar Shabestari Marjan , Naderi Kalali Ehsan , Li Rui , Zhang Shuyi
Published: January 2025

An advanced, eco-friendly, and fully bio-based flame retardant (FR) system has been created and applied to the cellulose structure of the cotton fabric through a layer-by-layer coating method. This study examines the flame-retardant mechanism of protein based and phosphorus containing coatings to improve fire resistance. During combustion, the phosphate groups (-PO₄²⁻) in phosphorus containing flame retardant layer interact with the amino groups (-NH₂) of protein, forming ester bonds which results in generation of crosslinked network between the amino groups and the phosphate groups. This structure greatly enhances the thermal stability of the residual char, hence, improving fire resistance. Tests such as the cone calorimeter and flammability tests show significant improvements in fire safety, including lower peak heat release rates, reduced smoke production, and higher char residue, all contributing to better flame-retardant performance. pHRR, THR and TSP of the flame-retarded cotton fabric demonstrated 25, 54 and 72% reduction, respectively. These findings suggest that LbL-assembled protein-phosphorus based coatings provide a promising, sustainable solution for creating efficient flame-retardant materials.
Commutative Quaternion Algebra with Quaternion Fourier Transform-Based Alpha-Rooting Color Image Enhancement
Authors: Gomez Alexis , Grigoryan Artyom
Published: January 2025

The alpha-rooting method in the quaternion space is one of the most effective methods of color image enhancement. Quaternions allow all colors in each pixel to be processed as a whole, rather than individually as is done in traditional processing methods. In this paper, we describe the color image enhancement alpha-rooting which is based on the 2D quaternion discrete Fourier transform (QDFT) in the associative and commutative algebra, or the (2,2)-model. It is the model, where the aperiodic convolution of quaternion signals can be calculated by the product of their Fourier transforms. The concept of linear convolution is simple, that is, it is unique, and the reduction of this operation to the multiplication in the frequency domain makes this model very attractive for processing color images. In the traditional quaternion algebra, which is not commutative, the convolution can be chosen in many different ways, and the number of possible QDFTs is infinite. And most importantly, the main property of the traditional Fourier transform that states that the aperiodic convolution is the product of transform in the frequency domain is not valid. We describe the main property of the (2,2)-model of quaternions, the quaternion exponential functions and convolution. Three methods of the alpha-rooting based on the 2D QDFT are presented and illustrative examples on color image enhancement are given.
LLM-Powered GUI Agents in Phone Automation: Surveying Progress and Prospects
Authors: Liu William , Liu Liang , Guo Yaxuan , Xiao Han , Lin Weifeng , Chai Yuxiang , Ren Shuai , Liang Xiaoyu , Li Linghao , Wang Wenhao , Wu Tianze , Liu Yong , Wang Hao , Li Hongsheng , Xiong Guanjing
Published: January 2025

With the rapid rise of large language models (LLMs), phone automation has undergone transformative changes. This paper systematically reviews LLM-driven phone GUI agents, highlighting their evolution from script-based automation to intelligent, adaptive systems. We first contextualize key challenges, (i) limited generality, (ii) high maintenance overhead, and (iii) weak intent comprehension, and show how LLMs address these issues through advanced language understanding, multimodal perception, and robust decision-making. We then propose a taxonomy covering fundamental agent frameworks (single-agent, multi-agent, plan-then-act), modeling approaches (prompt engineering, training-based), and essential datasets and benchmarks. Furthermore, we detail task-specific architectures, supervised fine-tuning, and reinforcement learning strategies that bridge user intent and GUI operations. Finally, we discuss open challenges such as dataset diversity, on-device deployment efficiency, user-centric adaptation, and security concerns, offering forward-looking insights into this rapidly evolving field. By providing a structured overview and identifying pressing research gaps, this paper serves as a definitive reference for researchers and practitioners seeking to harness LLMs in designing scalable, user-friendly phone GUI agents. Project Homepage: github.com/PhoneLLM/Awesome-LLM-Powered-Phone-GUI-Agents
Toward Convenient and Accurate IMU-based Gait Analysis
Authors: Boutaayamou Mohamed , Pelzer Doriane , Schwartz Cédric , Gillain Sophie , Garraux Gaëtan , Croisier Jean-Louis , Verly Jacques G. , Brüls Olivier
Published: January 2025

While inertial measurement unit (IMU)-based systems have shown their potential in quantifying medically-significant gait parameters, it remains to be demonstrated that they can provide accurate and reliable parameters both across various walking conditions and in healthcare settings. Using an IMU-based system we have previously developed, with one IMU module on each subject’s heel, we quantify gait parameters in 55 men and 46 women, all healthy and aged 40-65, in normal, dual-task, and fast-walking conditions. We evaluate their intra-session reliability, and we establish a new reference database of such parameters showing good to excellent reliability. ICC(2,1) assesses relative reliability, while SEM% and MDC% evaluate absolute reliability. The reliability is excellent for all spatiotemporal gait parameters and stride length (SL) symmetry ratio (ICC≥0.90, SEM%≤4.5%, MDC%≤12.4%) across all conditions. It is good to excellent for fast-walking performance (FWP) indices of stride (Sr), stance (Sa), double-support (DS), and step (St) times; gait speed (GS), and GS normalized to leg length (GSn1) and body height (GSn2) (ICC≥0.91, |SEM%|≤10.0%, |MDC%|≤27.6%). Men have higher swing time (Sw) and SL across all conditions. The following parameters are gender-independent: (1) Sa, DS, GSn1, GSn2; (2) symmetry ratios of Sa, Sa ratio (Sa%), Sw, Sw ratio (Sw%), SL, GS; and (3) FWPs of Sr, Sa, Sw, DS, St, cadence, Sa%, Sw%. Our results provide reference values with new insights into gender FWP comparisons rarely reported in the literature. The advantages and reliability of our IMU-based system make it suitable in medical applications such as prosthetic evaluation, fall-risk assessment, and rehabilitation.
Advanced Displacement Magnitude Prediction in Multi-Material Architected Lattice Structure Beams Using Physics Informed Neural Network Architecture
Authors: Mishra Akshansh
Published: January 2025

This paper proposes an innovative method for predicting deformation in architected lattice structures that combines Physics-Informed Neural Networks (PINNs) with finite element analysis. A thorough study was carried out on FCC-based lattice beams utilizing five different materials (Structural Steel, AA6061, AA7075, Ti6Al4V, and Inconel 718) under varied edge loads (1000-10000 N). The PINN model blends data-driven learning with physics-based limitations via a proprietary loss function, resulting in much higher prediction accuracy than linear regression. PINN outperforms linear regression, achieving greater R² (0.7923 vs 0.5686) and lower error metrics (MSE: 0.00017417 vs 0.00036187). Among the materials examined, AA6061 had the highest displacement sensitivity (0.1014 mm at maximum load), while Inconel718 had better structural stability.
Microbial Approach to Sustainable Cotton Agriculture: The Role of PaleoPower® in Soil Health and Glyphosate Mitigation
Authors: Cano Raul de Jesus , Daniels Judith M. , Carlin Martha , Huber Donald M.
Published: January 2025

The extensive use of glyphosate-based herbicides has raised concerns about its impact on soil health and microbial communities, particularly due to the persistence of AMPA. This study evaluates the effects of PaleoPower, a co-fermented microbial inoculant, on soil microbial composition, diversity, and glyphosate degradation in a cotton field. PaleoPower, applied at 1.6 × 10⁸ CFU per square meter, introduced eight bacterial strains, bioactive postbiotics, and prebiotics into the soil. Post-harvest analyses revealed reductions in glyphosate and AMPA levels in the soil of 72% and 50%, respectively from baseline levels treated and untreated respectively in untreated soil. LEfSe analysis identified 206 taxonomic biomarkers, including increases in beneficial taxa like Actinobacteria and Clostridia, alongside declines in oligotrophic groups. Random Forest and correlation analyses highlighted key taxa like Sphingomonas and Mesorhizobium in glyphosate metabolism, while increased microbial diversity metrics indicated ecosystem recovery. Metabolic pathway analysis demonstrated upregulation of nutrient cycling, phosphate metabolism, stress resilience processes, increases in methane metabolism and oxidative stress response pathways. These results suggest PaleoPower enhanced glyphosate degradation, enriched microbial diversity, and improved soil health to offer a promising approach for sustainable agriculture. The small sample size and single-field study design highlights the need for further validation.
Institutions as a Fundamental Cause for Long-Run Sustainibility
Authors: El Maachi Soukaina , Saadane Rachid , Chehri Abdellah Abdellah
Published: January 2025

The development of sustainable societies relies upon the institutional structures that govern the relationship between economic systems and environmental leadership. In this study, we engage with the juxtaposition between inclusive and extractive institutions, as potential molders of the trajectory of sustainability. Featuring governance indicators and economic metrics, we explore the impact of institutional inclusiveness and extractiveness on sustainability outcomes. Inclusiveness, which enables the proposperity of collective well-being through democratic governance, legal integrity, and innovation, is posited as an affirmative force for sustainability. In contrast, extractive institutions, which concentrate power and resources, hinder the realization of sustainable development by perpetuating inequality and exploitation. This paper suggests a statistic pipeline, comprised of econometric regression, machine learning models, and clustering analysis to assess the impact of governance, economic performance, on sustainability indices. We posit that inclusiveness serves as a potent driver for sustainability, particularly when coupled with economic resources, whereas extractiveness leads to the attenuation of sustainable progress. Through this work, we aim to gauge how institutions can either hinder or propel the material conditions necessary for the achievement of sustainability.
Generation of a Transgenic Mouse Model for Investigating Mitochondria in Sperm
Authors: Sarkar Hironmoy , Batta Suryaprakash R , Wadhwa Neerja , Majumdar Subeer S. , Pradhan Bhola
Published: January 2025

Mitochondria play an important role in the development of sperm, yet the mechanisms regulating their function in sperm remain poorly understood. The development of a method to regulate the expression of a target gene in the mitochondria of the sperm is an essential step in this line of research. In this study, we attempted to generate a system to express the transgene in the mitochondria of the sperm. As a proof of concept, we generated the transgenic mice expressing green fluorescent protein (GFP) fused with a mitochondrial localization signal (MLS) driven by PGK2 promoter which expresses the transgene in the sperm. Although the PGK2 promoter has been previously demonstrated to drive gene expression in spermatocytes and spermatids, the novelty of our method is the combination of the PGK2-driven MLS-GFP expression to study the mitochondria in vivo. We established two founder lines of transgenic mice by pronuclear microinjection, and MLS-GFP expression was confirmed in the mitochondria of the sperm cells by fluorescence microscopy and flow cytometry. Therefore, we provide a novel platform for studying mitochondrial function in sperm where the GFP can be replaced with other genes of interest to study their effect on mitochondria. These results may also help in understanding mitochondrial inheritance, and mitochondrial dysfunction in vivo.
AI-Generated Abstract Expressionism Inspiring Creativity Through Ismail A Mageed's Internal Monologues in Poetic Form
Authors: A Mageed Ismail , Nazir Abdul Raheem
Published: January 2025

Artificial Intelligence (AI) has revolutionized the creative process, allowing for novel ways of artistic expression. This paper focuses on the intersection of Abstract Expressionism and AI-generated imagery, exploring how poetic prompts inspire unique visual interpretations. By utilizing Leonardo AI with a medium contrast and leveraging the cinematic kino model/preset, the research demonstrates how simple poetic phrases can yield profound visual artworks. The study evaluates the quality, creativity, and emotional resonance of AI-generated art, offering insights into the synergy between human creativity and machine intelligence within an Abstract Expressionism framework. The Leonardo AI is applied to Ismail A Mageed’s internal monologues in poetic form. The paper ends with some potential open problems and concludes with remarks and future research pathways.
Comprehensive Evaluation of Soybean Germplasm Resources for Salt Tolerance During the Germination Period
Authors: Han Lei , Ge Lerong , Fei Lin , Huang Chengwei , Li Yilin , Fan Wentan , Zhu Dan , Zhao Longgang
Published: January 2025

Various biotic and abiotic stresses challenge plant growth and production, with salt stress notably impeding normal development, compromising quality, and reducing yield in plants. The objective is to identify salt-tolerant soybean germplasm resources and develop a comprehensive method for assessing salt tolerance during soybean germination. This study involved the utilization of 36 soybean germplasm to induce varying degrees of salt stress through the application of 0, 60, 120, and 180 mmol/L NaCl solutions, employing the Petri dish germination identification method to assess nine phenotypic indices, such as germination potential, rate, and radicle length. The salt tolerance of soybean germination was comprehensively assessed using one-way ANOVA, multi-factor ANOVA, principal component analysis, affiliation function, quadratic regression equation analysis, and cluster analysis. These methods were employed to investigate the impact of varied NaCl concentrations on different germination indices, determine the best screening parameters for identifying soybean germination salt tolerance, and identify soybean germplasm with varying salt tolerances. The results indicated that soybean seeds exhibited tolerance to low salt concentrations, while concentrations exceeding 120 mmol/L led to significant inhibition of germination indicators. Notably, the vitality index and radicle length were highly sensitive indicators reflecting the impact of salt stress on seed germination. By analyzing the quadratic regression equation correlating the germination index and the salt tolerance coefficient, an LC50 value of 155.4 mmol/L with a coefficient of variation of 20.00% was derived. This value serves as a viable screening concentration for identifying salt tolerance during the soybean germination stage. Additionally, clustering analysis categorized 36 soybean varieties into 4 salt tolerance levels, with QN-27, QN-35, and QN-36 demonstrating high salt tolerance, and QN-2, QN-17, and QN-19 were classified as salt-sensitive materials.
High Power Density IGBT Loss Calculation Model and Analysis
Authors: Wang Feng , Song Yifan , Dou Wang , Zheng Chao Lei , Li Zhuang Zhuang , Li Biao , Liu Jun
Published: January 2025

This paper presents the establishment of an accurate loss model for high-power-density IGBT modules used in electric vehicles, leveraging the thermal simulation capabilities of the power electronics simulation software PLECS. The study aims to address the significant influence of IGBT losses on the energy efficiency and reliability of electric vehicles. A simulation model was built using the SVPWM modulation strategy to drive a three-phase inverter, and the average loss method was employed to determine both conduction and switching losses. The simulation results were compared with calculations based on the datasheet, showing a deviation of less than 4%, which confirms that the proposed model accurately predicts losses under specified conditions. Compared with traditional methods, the model presented in this paper offers higher precision and improved simulation speed, thus proving effective for accurate loss analysis of IGBT modules and supporting further energy efficiency improvement and system optimization in electric vehicles.
Skin Antiaging and Skin Health Benefits of Probiotics Intake Combined with Topical Ectoin and Sodium Hyaluronate: A Randomized, Double-Blind, Placebo-Controlled Trial
Authors: Nobile Vincenzo , Hajat Cother , Cestone Enza , Cascella Federica , Santus Giacomo
Published: January 2025

Well-aging strategies include the use of both oral and topic products to nourish the skin from the inside out. A clinical-instrumental study was conducted on 96 subjects with mild to moderate facial aging to demonstrate the efficacy of probiotics (Lactobacillus plantarum PBS067, Lactobacillus reuteri PBS072 and Lactobacillus rhamnosus LRH020) intake combined with topical ectoin and sodium hyaluronate. The skin sebum content, hydration and moisturization, profilometry (wrinkle depth and skin smoothness), TEWL, elasticity (R0 and R2 parameters), radiance, and pores (size and impurities) were measured after 4 and 8 weeks of products use. These parameters were also integrated by a self-assessment questionnaire to align the measured and the perceived efficacy. One hour after serum application, wrinkle depth was reduced by 9.2%, while skin hydration increased by 16.6% and skin radiance by 19.1% following cream application. After 4 and 8 weeks of use, both the oral and topical products were shown to respect the skin's hydrolipid film, effectively improve skin parameters associated with aging, and detoxify the skin from impurities. The mechanism behind these improvements was linked to an enhancement of the skin microbiome. Our findings clearly demonstrate the efficacy of probiotic intake combined with topical ectoin and sodium hyaluronate in enhancing skin health and mitigating signs of skin aging.
Assessment of Chemical Pollution Load in Surface Waters of the Turkestan Region and Its Indirect Impact on Landscapes: A Comprehensive Study
Authors: Akhmetova Dana , Ozgeldinova Zhanar , Ramazanova Nurgul , Sadvakassova Saltanat , Inkarova Zhansulu , Kenzhebay Rabiga
Published: January 2025

This study is aimed at a comprehensive assessment of the chemical composition of surface waters in the Turkestan region and their impact on regional landscapes. The primary objective of the research is to systematically evaluate the level of chemical pollution in the region's water resources and determine its indirect effects on landscape-ecological stability. In August 2024, water samples from eight sampling points (S1–S8) were analyzed for 24 physicochemical parameters, including total hardness (mg*eq/L), pH, dry residue (mg/L), electrical conductivity (µS/cm), total salinity (mg/L), Al, As, B, Ca, Cd, Co, Cr, Ti, Fe, Pb, Cu, Mg, K, Mn, Na, Ni, Zn, SO₄²⁻, and C₆H₅OH. To determine the degree of pollution, variational-statistical analysis, principal component analysis (PCA), as well as the calculation of the OIP, NPI, and HPI indices were performed. For land use and land cover change (LULC) analysis, LULC classification was carried out based on Landsat data from 2000 to 2020, forming the basis for land resource management and planning. The research results showed a deterioration in the ecological condition of water resources and an increasing anthropogenic impact. Specifically, at point S8, the concentration of Al was found to be 56 times higher than the maximum allowable limit, while the concentration of Fe was 42 times higher. High levels of pollution were also recorded at points S1, S4, S5, and S6, where the increase in Al and Na concentrations caused a sharp rise in the OIP value. The main factors influencing water pollution include industrial effluents, agricultural waste, and irrigation drainage waters. The pollution's negative impact on regional landscapes has led to issues related to the distribution of vegetation, soil fertility, and landscape stability. To improve the current ecological situation and restore natural balance, the phytoremediation method is proposed. The research results will serve as the foundation for developing water resource management strategies for the Turkestan region and making informed decisions aimed at ensuring ecological sustainability.
Effect of Sequential vs. Simultaneous Dual Growth Factor Release from Structured Heparin-Polyelectrolyte-Multilayer Coatings on Periimplant Bone Formation and Angiogenesis in Pig Mandibles
Authors: Kauffmann Philipp , Wolfer Susanne , Behrens Christina , Schlosser Pauline , Dullin Christian , Schirmer Uwe , Liefeith Klaus , Schliephake Henning
Published: January 2025

The aim of the present study was to test the sequential and simultaneous release of rhBMP2 and rhVEGF165 from poly-l-lysine-heparin (PLL-Hep) polyelectrolyte multilayer (PEM) coating on titanium surfaces for their ability to enhance periimplant bone formation and CD31 expression around disc shaped titanium implants (5 x 7 mm) in minipig mandibles. Bare titanium surfaces loaded with respective growth factor combinations served as controls. Ten different surface conditions were tested exhibiting early VEGF release, early BMP release, simultaneous VEGF and BMP release and sole VEGF / BMP release, respectively. The implants were inserted press-fit into 5 mm trephine cavities at the lower border of the mandibles of minipigs and left to heal for 4 and 13 weeks. After 4 weeks, there was no significant difference in periimplant bone formation, bone-implant-contact nor CD31 expression between the different surface conditions. After 13 weeks, bone formation was significantly higher in the zone of 100 µm next to implant surfaces releasing either BMP alone or with an early release of BMP2. Expression of CD31 has significantly decreased from 4 to 13 weeks with significantly higher values in the group of implants with early release of BMP2. The results indicate that the range of released growth factors is limited to a distance of appr. 100 µm and that the sequence of early release of BMP2 followed by VEGF165 promotes periimplant bone formation and periimplant angiogenesis, which is in contrast to the current understanding of the temporal patterns of growth factor release for enhancement of bone formation.
Monocyte Chemoattractant Protein-1 from a Conditioned Medium of Bone Marrow-Derived Mesenchymal Stem Cells Promotes Bone Regeneration by Enhancing Macrophage Phenotype Switching
Authors: Hashizume Kosuke , Katagiri Wataru , Takeuchi Ryoko , Suda Daisuke , Kobayashi Tadaharu
Published: January 2025

Objectives: Cytokines and chemokines contained in conditioned media from human bone marrow-derived mesenchymal stem cells (MSC-CM) promote bone regeneration. We recently reported macrophage phenotype switching towards the anti-inflammatory M2 phenotype induced by MSC-CM and its potential to promote bone regeneration. However, the specific factors in the MSC-CM responsible for this process remain unclear. Monocyte chemoattractant protein (MCP) -1, present in MSC-CM, promotes cell migration and activation of the monocyte-macrophage lineage; therefore, we hypothesized that MCP-1 is a key factor in MSC-CM-induced macrophage phenotype switching. In this study, we aimed to elucidate the effect of MCP-1 on MSC-CM-induced macrophage phenotype switching and subsequent bone regeneration. Methods: MCP-1 was depleted from MSC-CM (depMSC-CM) and used in subsequent experiments. Rat bone marrow macrophages were incubated in MSC-CM or depMSC-CM and expression of macrophage markers was examined in vitro. In addition, the effect of MSC-CM and depMSC-CM on bone regeneration and macrophage phenotype switching were evaluated using rat calvaria defect model in vivo. Results: MSC-CM enhanced M2 macrophage marker expression in rat bone marrow macrophages compared to those treated with depMSC-CM in vitro. In addition, MSC-CM increased the number of M2 macrophage marker-positive cells in bone defects and enhanced subsequent bone regeneration in a rat calvarial defect model. Conclusions: MCP-1 plays an essential role in MSC-CM-induced macrophage phenotypic switching and subsequent bone regeneration.
Factors Affecting Consumers’ Adoption of Solar Energy Products
Authors: Gupta Ankur , Saraswat Sanjeev
Published: January 2025

The objective of this study was to investigate the factors that influence consumer adoption of renewable energy in India. The study adopted an extended theory of planned behavior (TPB) by including three additional variables. A quantitative methodology was used, with primary data collected from surveys conducted in six major Indian cities. Data were analyzed using structural equation modeling (SEM). Results indicated that self-effectiveness, environmental concern, renewable energy awareness, and beliefs about renewable energy benefits significantly influenced consumer intention to adopt renewable energy. The cost of renewable energy showed a negative but non-significant influence, while risk/trust perception exhibited a positive but non-significant effect on consumer adoption. The study concluded that stakeholders should prioritize self-effectiveness, environmental concern, renewable energy awareness, and benefit-related beliefs in promoting solar energy adoption in India.
AI is Gullible and Other Problems
Authors: Yan Shih-Hsuan , de la Maza Michael , Rubin Rob
Published: January 2025

There is great interest in understanding the errors that generative AI makes. As this technology spreads across fields, from healthcare to marketing, its reliability is coming under increased scrutiny. Notable errors include hallucinations, reasoning errors, and factual errors. The potential impact of these errors is profound, particularly in fields such as medical diagnosis or military planning where lives are at stake. Some AI errors raise ethical questions particularly when they arise from biases in the training sets. Errors due to biases in the training set raise questions about the accountability of the developers of generative AI systems.As AI research and applications accelerate, understanding the nature and scope of these errors becomes ever more critical. By understanding the limitations of generative AI, both developers and end users can make appropriate adjustments and maximize the benefits while minimizing the risks.In this paper, we describe eight errors, five of which we have not seen mentioned in the literature previously, that generative AI is making as of December, 2024. Seven of these problems are very simple for humans, like finding the optimal move in a tic-tac-toe game. The seventh problem is more difficult but the error that the AI makes can be identified by a layperson. We have run these problems through many generative AI foundation models but in this paper we concentrate on ChatGPT 4o-latest and Claude-3.5.-Sonnet.
Calibration of the Intelligent Driver Model (IDM) at Microscopic Level
Authors: Vasconcelos Luís , Bandeira Jorge Marto
Published: January 2025

This paper presents a calibration technique for the Intelligent Driver Model (IDM) car-following model that considers the physical interpretation of each parameter. Using an instrumented vehicle, trajectory data was gathered for a group of Portuguese drivers. The data included various basic scenarios, such as unrestricted acceleration and deceleration maneuvers, as well as following other cars in steady-state conditions. The calibration process involved two steps. In the first step, specific parameters that have clear physical interpretations were manually adjusted to accurately reproduce the speed patterns of basic driving scenarios. In the second step, the obtained results were used to establish the limits of values for a simultaneous calibration procedure. The results demonstrate that the calibration procedure enables precise replication of the actual trajectories. Nevertheless, the model validation results indicate that calibrating without limitations on the parameter search space produces estimates with greater explanatory capability, contradicting previous research and supporting the need for additional analyses.
A New MARMA-GARCH Model with Applications to Cryptocurrency Volatility
Authors: Hecq Alain , Velasquez-Gaviria Daniel
Published: January 2025

This paper introduces a mixed causal-noncausal invertible-noninvertible autoregressive moving average generalized autoregressive conditional heteroskedasticity (MARMA-GARCH) model, which uniquely combines features to capture the nonlinear dynamics observed in financial markets. The MARMA component replicates explosive episodes observed during financial bubbles, while the GARCH model effectively captures time-varying conditional volatility. We propose two methods for parameter estimation: the Whittle function in the frequency domain and the maximum likelihood. Additionally, we suggest an identification scheme through high-order spectral densities and high-order dynamics of the residuals. Our findings demonstrate that an incorrect identification of the MARMA process leads to biased GARCH parameters, underestimating the effect of news and overestimating the volatility clustering. An empirical application to Bitcoin and Ethereum reveals the existence of noncausal dynamics in the mean, jointly with significant GARCH effects.
FeNO and Blood Eosinophil Counts in Idiopathic Pulmonary Fibrosis: Potential Biomarkers of Response to Nintedanib
Authors: Vietri Lucia , Reginato Mariano , D'Alessandro Miriana , Carnevale Aldo , Papi Alberto
Published: January 2025

In the bronchoalveolar lavage (BAL) of IPF patients, eosinophilia greater than 10% is observed. Additionally, nitric oxide (NO) plays a crucial role in the aberrant angiogenesis process in fibrotic lungs. Our aim is to evaluate the role of blood eosinophil counts (BECs) and FeNO as potential biomarkers for IPF. A total of 38 IPF patients (mean age 75.5 ± 6.7 years) followed at the University of Ferrara was enrolled. We monitored BECs and FeNO at baseline (T0, time of diagnosis and initiation of antifibrotic therapy) and after 12 months (T12) of treatment. We found higher BECs in patients on Nintedanib treatment (0.54 ± 0.13 x10³/mcrl) compared to those on Pirfenidone (0.13 ± 0.10 x10³/mcrl) or not on treatment (0.02 ± 0.01 x10³/mcrl). We also measured exhaled nitric oxide (FeNO) after 12 months of antifibrotic therapy and observed a higher FeNO concentration in patients treated with Nintedanib (29.42 ± 2.99 ppb) compared to the group on Pirfenidone therapy (20.8 ± 20.5 ppb). We propose for the first time in the literature the role of eosinophils and FeNO as potential biomarkers of response to antifibrotic therapy (Nintedanib). This needs to be further demonstrated in a larger population of patients.
Phytosucrophage: A Novel SGLT1 Inhibitor from Nigella sativa and Olea europaea Enhances Glycemic Control in Oral Drug-Resistant Type 2 Diabetes – Preliminary Observational Cohort Study Insights
Authors: Eto Bruno , Basilua Joe Miantezila , Akissi Zachée Louis Evariste , Outman Ahlam , Johnson Madeleine , Ndjib Rosette Christelle , Ngansop Tchatchouang Eric , Bourhim Mohamed , Adoum Djorou Abdoulaye , Ibet Brahim , Ramadam Issa , Torina Claire , Pagui Panatere , Tchalkoutou Kady , Mahamat Nour , Cordier Janine , Gressier Bernard , Desjeux Jehan-François
Published: January 2025

Background: Nigella sativa L. (seeds) and Olea europaea L. (leaves) are widely utilized as food supplements and traditional herbal remedies to reduce hyperglycemia. Purpose: This study evaluated the efficacy of a commercial combination of Nigella sativa and Olea europaea aqueous extracts, marketed as Phytosucrophage (PSP), in managing type 2 diabetes mellitus (T2DM) in patients resistant to oral antihyperglycemic drugs (OADs). Study Design: A multicenter, observational cohort study was conducted involving 38 treatment-naïve T2DM patients and 282 patients resistant to OADs. Participants received a fixed-dose capsule containing 550 mg of PSP, administered twice daily for 12 weeks. Clinical efficacy was assessed by monitoring fasting blood glucose, glycosylated hemoglobin (HbA1c), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine levels, and evaluating functional symptoms. Results: PSP treatment significantly reduced fasting blood glucose and HbA1c levels. Additionally, it alleviated functional symptoms of T2DM without inducing adverse effects. Conclusions: The findings suggest that PSP is an effective and safe adjunctive therapy for reducing blood glucose and HbA1c levels in T2DM patients resistant to OADs. PSP also improved clinical symptoms associated with T2DM without causing notable adverse effects.