bluuebunny/crossref_metadata_2025 huggingface dataset:
HLA-B*58 and HLA-C*2 Alleles Are Associated with the Occurrence of Rheumatoid Arthritis Among Omanis
Authors: Al-Balushi Mohammed S. , Antony Irin , Al-Shirawi Ali H. , Al-Riyami Hamad , Al-Busaidi Jumaa Z. , Koh Crystal Y. , Al-Naamani Khalid M. , Hasson Sidgi S. , Al-Jabri Ali A. , Said Elias A.
Published: February 2025

Background/Objectives: Rheumatoid arthritis (RA) is an autoimmune disease that is influenced by polymorphisms in the HLA molecules. Only a few studies assessed the presence of an association between HLA class I genes and RA. Moreover, ethnic background influences the association of HLA molecules and RA. HLA-I molecules are essential for the activation of CD8 T cells and natural killer (NK) cells. The implication of these cells in RA pathogenesis is controversial. Therefore, we investigated the presence of associations between HLA-I alleles and RA in Omani patients. Methods: HLA class I alleles were genotyped in a total of 206 volunteers (102 RA patients and 104 controls). The control group included volunteers who were not affected by any known disease. The Chi square test was used to investigate the significance of the associations between the HLA alleles and the occurrence of RA. A corrected p value (pc) was calculated using the Bonferroni correction. Results: The frequency of HLA-B*58 was ≈2.7-fold lower in RA patients (10.8%) compared to the control group (28.8%; pc = 0.0324). Moreover, the frequency of HLA-C*02 in RA patient was ≈8-fold higher compared to the control group (pc = 0.0104). Conclusions: This study is the first to demonstrate the presence of association between HLA-B*58 and HLA-C*02 and the occurrence of RA, which could guide future research on targeted therapies. It also suggests that these HLA alleles might influence CD8 T cells and NK cells implication in RA pathogenesis.
Statin-Intolerant Patients Exhibit Diminished Muscle Strength Regardless of Lipid-Lowering Therapy
Authors: Vinci Pierandrea , Di Girolamo Filippo Giorgio , Pellicori Federica , Panizon Emiliano , Pirulli Alessia , Tosoni Letizia Maria , Altamura Nicola , Rizzo Stefania , Perin Andrea , Fiotti Nicola , Biolo Gianni
Published: February 2025

Background and Aims: Statin-associated muscle symptoms (SAMS) is a frequent side effect of statin therapy, limiting its clinical use and increasing cardiovascular risk. Its relationship with muscle performance and quality is not completely understood. The aim of our study was to retrospectively assess the differences between body composition and muscle strength in patients with SAMS, compared with matched controls. Material and Methods: cardiovascular risk factors, lipid profile, and body mass index (BMI), were analyzed in 148 statin-intolerant (SI) and in 145 sex- and age-matched statin-tolerant (ST) patients attending a secondary-level outpatient lipid clinic. At the end of follow-up (mean 45 months), the evaluations were reassessed and bioelectrical impedance analysis (BIA)-assessed body composition, and muscle quality (handgrip/skeletal muscle mass) were further determined. Results: At baseline, BMI, cholesterol, and triglycerides in SI were higher than in ST patients. During follow-up, SI patients underwent a further increase in BMI and low-density lipoproteins (LDL)-cholesterol remained significantly higher than in ST patients. At the end of the follow-up, BIA-assessed fat mass percentage was higher in SI than in ST. Handgrip absolute values or standardized for skeletal muscle mass (muscle quality) were significantly lower in SI patients (p < 0.001), but this was confirmed only in their non-dominant arm (p < 0.01 for all arms). Circulating creatine kinase levels, which was higher in SI patients at baseline (p < 0.001), remained higher in those who never restarted statins after re-challenge (p = 0.029). Conclusions: Statin intolerance is clinically associated with lower muscle quality, particularly in less exercised arms.
Beyond the Lungs: Extrapulmonary Effects of Non-Invasive and Invasive Ventilation Strategies
Authors: Silva Pedro Leme , Chiumello Davide , Pozzi Tommaso , Rocco Patricia Rieken Macedo
Published: February 2025

Background/Objectives: Non-invasive respiratory support and invasive mechanical ventilation are critical interventions that can induce significant changes not only in the lungs but also in extra-pulmonary organs, which are often overlooked. Understanding the extra-pulmonary effects of non-invasive respiratory support and invasive mechanical ventilation is crucial since it can help prevent or mitigate complications and improve outcomes. This narrative review explores these consequences in detail and highlights areas that require further research. Main Text: Non-invasive respiratory support and invasive mechanical ventilation can significantly impact various extrapulmonary organs. For instance, some ventilation strategies can affect venous return from the brain, which may lead to neurological sequelae. In the heart, regardless of the chosen ventilation method, increased intrathoracic pressure (ITP) can also reduce venous return to the heart. This reduction in turn can decrease cardiac output, resulting in hypotension and diminished perfusion of vital organs. Conversely, in certain situations, both ventilation strategies may enhance cardiac function by decreasing the work of breathing and lowering oxygen consumption. In the kidneys, these ventilation methods can impair renal perfusion and function through various mechanisms, including hemodynamic changes and the release of stress hormones. Such alterations can lead to acute kidney injury or exacerbate pre-existing renal conditions. Conclusions: This review emphasizes the critical importance of understanding the extensive mechanisms by which non-invasive respiratory support and invasive mechanical ventilation affect extrapulmonary organs, including neurological, cardiovascular, and renal systems. Such knowledge is essential for optimizing patient care and improving outcomes in critical care settings.
Coronary Artery Calcium Is Independently Associated with Arterial Stiffness and LDL Cholesterol Burden in Patients with Familial Hypercholesterolemia
Authors: Mattina Alessandro , Giammanco Antonina , Noto Davide , Geraci Giulio , Nardi Emilio , Barbagallo Carlo Maria , Gagliardo Carola Maria , Giusti Maria Ausilia , D’Ignoto Francesco , Giallauria Francesco , Di Benedetto Carla , Cardella Antonella Maria , Toia Patrizia , La Grutta Ludovico , Cefalù Angelo Baldassare , Averna Maurizio
Published: February 2025

Background: Familial hypercholesterolemia (FH) is a genetic disorder characterized by high plasma levels of low-density lipoprotein cholesterol (LDL-C) and exposing patients to higher risk of early cardiovascular (CV) atherosclerotic diseases. Though the estimated prevalence of heterozygous FH (HeFH) is about 1 in 200, FH is still underdiagnosed and undertreated. Coronary artery calcification (CAC) assessment and arterial stiffness measured as pulse wave velocity (PWV) have demonstrated their accuracy in CV risk assessment, but data on HeFH are lacking. This study aims to evaluate CAC and PWV in a population of HeFH patients to improve risk stratification and therapy timing and setting. Methods: One hundred genetically characterized HeFH patients, regularly followed up since diagnosis, were recruited at our outpatient clinic. In all patients, CAC, PWV measurement, and LDL-C burden calculation were assessed. Results: The mean age was 45 ± 16 years. A total of 25% of patients had hypertension, and 15% were in secondary prevention. Through univariate analysis, we found strong positive correlations between CAC and both PWV (r = 0.52 p > 0.0001) and total LDL-C burden (r = 0.52 p < 0.0001). No other associations with lipid parameters were found. Multivariate analysis showed that CAC was independently associated with PWV adjusted for sex, total LDL-C burden, systolic blood pressure, smoking, LDL-C, HDL-C, and statin treatment. Conclusions: Arterial stiffness is strongly associated with CAC in HeFH patients with similar total LDL-C burden and CV risk profiles. Personalized risk assessment based on arterial stiffness and CAC evaluation enhances the stratification and management of cardiovascular risk in FH patients, supporting individualized therapeutic approaches.
Evaluation of Echocardiographic, Conventional Electrocardiographic, and Holter Variables in Jaguars (Panthera Onca) Anesthetized with Medetomidine and Ketamine: Implications for Management and Conservation
Authors: Kirnew Murillo Daparé , Silveira Matheus Folgearini , Ampuero Roberto Andres Navarrete , Simões Ana Paula Rodrigues , Azzolini Felippe , de Araújo Gediendson Ribeiro , Jorge-Neto Pedro Nacib , Polizelle Sofia Regina , Sipp Juliane Patrícia , Pizzutto Cristiane Schilbach , Deco-Souza Thyara , Camacho Aparecido Antonio
Published: February 2025

Jaguars play a crucial role in population control across multiple biomes. They are endangered and protected by in situ and ex situ conservation mechanisms to ensure their conservation. Cardiovascular diseases in wild mammals, including jaguars, often have unclear etiopathogenies, underscoring the need for research into novel hemodynamic parameters. This study evaluates the cardiovascular health of fifteen clinically healthy jaguars using conventional and Holter electrocardiography, non-invasive systemic blood pressure measurement, and echocardiography. Chemical restraint was achieved with medetomidine (0.08–0.1 mg/kg) and ketamine (5 mg/kg), with anesthesia reversed using atipamezole (0.25 mg/kg). The average heart rate was 72 ± 18 bpm, with sinus rhythm in ten animals and sinus arrhythmia in five. Six animals exhibited first and second-degree atrioventricular blocks, one had supraventricular complexes, and another had premature ventricular complexes. Non-invasive systolic blood pressure remained stable at 163 ± 29 mmHg during anesthesia. Echocardiographic examination revealed mitral, tricuspid, pulmonary, and aortic valve insufficiencies via color Doppler. The transmitral flow showed a normal E/A ratio and E` < A`, suggesting a pseudonormal ventricular filling pattern. No significant anesthetic complications were observed, affirming the protocol’s safety. This study provides valuable data, validating the anesthetic protocol and establishing reference cardiovascular values for jaguars, thus paving the way for future research in other veterinary species.
Impact of Aging on Farmland Abandonment: Evidence from Rural China
Authors: Zhang Ziqi , Ding Jingyi , Zhang Kuan , Deng Xin
Published: February 2025

Reducing farmland abandonment is important to address food security issues. China is accelerating its transition into an aging society, and this change in the labor force structure may have an impact on farmland abandonment. This study is based on the China Labor Force Survey conducted in 2012, 2014, 2016, and 2018 and collects data from 29,704 valid farmer samples in 29 provinces and cities across the nation. We investigate how farmer aging affects farmland abandonment from the viewpoints of information, mutual aid, and factor substitution using the Tobit and mediation effect models. The core conclusions are as follows: (1) There is a significant positive correlation between aging and abandoned farmland, that is, the higher the degree of aging in rural households, the more likely it is that farmland will be abandoned and the larger the area of abandoned farmland. (2) Aging has a multi-level impact on abandoned farmland, that is, aging will aggravate the abandonment of farmland from the perspectives of household head characteristics, family characteristics, and village characteristics. (3) Using the mediation effect model, aging will increase the abandonment of farmland due to less use of the Internet, agricultural cooperatives, and mechanization. This conclusion provides a basis for policy intervention, indicating that improving agricultural digitalization and modernization and increasing policy subsidies may be an effective way to slow down land abandonment.
Exploring Attitudes on the Sustainable Balance Between Nature Conservation and Economic Development Through Ecotourism—Lessons from EU and Non-EU Countries
Authors: Gajić Tamara , Vukolić Dragan , Spasojević Ana , Blešić Ivana , Petrović Marko D. , Bugarčić Jovan , Bugarčić Marina , Drašković Bojana D. , Milivojević Milovan
Published: February 2025

This study examines attitudes toward achieving a sustainable balance in ecotourism using the Stimulus-Organism-Response (SOR) model, focusing on economic and environmental factors shaping sustainable practices. Data were collected from tourists, local residents, and managers in Serbia and Croatia, encompassing diverse perspectives on natural resource conservation, economic benefits, and community engagement. The results indicate that natural resource conservation significantly contributes to local participation, tourist awareness, and community engagement, with notable differences observed among respondent groups. Economic benefits also positively influence these mediating factors, emphasizing their role in achieving sustainability goals. The MGA revealed significant differences between respondent groups, highlighting that managers and local communities in Croatia demonstrated higher levels of awareness and participation compared to Serbia, while differences among tourists were less pronounced. This research contributes to the sustainable tourism literature by integrating perspectives from various stakeholder groups and emphasizing the importance of community involvement and environmental preservation. Practical implications include recommendations for policymakers and managers to develop strategies that encourage stakeholder participation and promote sustainable tourism development.
Enhancing Logistical Performance in a Colombian Citrus Supply Chain Through Joint Decision Making: A Simulation Study
Authors: Vargas-Muñoz Juan Camilo , Sanchez-Nitola Flor Angela , Adarme Jaimes Wilson , Rios Richard
Published: February 2025

Background: Agriculture plays a key role in Colombia’s economy. However, the sector faces persistent logistics, infrastructure, and supply chain integration challenges that hinder its development. While background studies have primarily addressed socio-economic needs and strategies to overcome these long-standing challenges, supply chain coordination remains critical for enhancing efficiency and sustainability. This study examined the impact of joint decision-making mechanisms on the logistical performance of a citrus food supply chain in Colombia. Methods: We employed agent-based modeling and simulation to evaluate three scenarios: single distribution (the current system referred to as Single-distribution), joint consolidation (Joint-consolidation), and joint consolidation–distribution (Joint-consolidation-distribution). Key performance indicators, including total logistics costs, Staytime, and load capacity utilization, were analyzed to evaluate the scenarios. Results: The joint-consolidation–distribution model emerged as the most effective, reducing logistical costs, improving load utilization, and increasing farmers’ revenues by 55.9% compared to individual sales. Consolidating harvest and distribution through a food hub improved efficiency by centralizing logistics and reducing the reliance on middlemen. Conclusions: Our findings provide actionable insights into how joint coordination enhances smallholder farmers’ economic outcomes, strengthens supply chain sustainability, and fosters community development. These results support policies promoting productive associations and local food hubs as key facilitators of market access and logistical efficiency in rural agricultural sectors.
Synthesis of Magnetic Nanoparticles Coated with Human Serum Albumin and Loaded by Doxorubicin
Authors: Petrov Kirill , Ryabova Elena , Dmitrienko Elena , Chubarov Alexey
Published: February 2025

Magnetic iron oxide (II,III) nanoparticles (MNPs) are highly interested in biomedicine. However, their application is limited by oxidation, aggregation, rapid clearance from the body, and poor biodistribution. Coating by human serum albumin (HSA), the predominant blood plasma protein, can significantly influence properties, prolong circulation half-life, and enhance tumor capture efficiency. Here, we report the synthesis of oleic acid and Tween20-coated MNPs and their interaction with HSA. The influence of albumin coating on MNP size, zeta potential, aggregation ability, and toxicity was studied. The particles were characterized by dynamic light scattering, transmission electron microscopy, and Fourier transform infrared spectroscopy methods. The nanoparticles’ relaxivities (r1 and r2) were assessed under a magnetic field of 1.88 T to evaluate their performance in MRI applications. The anticancer drug doxorubicin (DOX) loading capacity of up to 725 µg/mg for albumin-coated MNPs was determined. DOX-loaded MNPs displayed pH-sensitive drug release during acidic conditions. The series of DOX-loaded nanocomposites indicated inhibition of A549 cell lines, and the IC50 values were evaluated. This research underscores the utility of HSA-coated MNPs in enhancing the efficacy and stability of drug delivery systems in biomedicine.
On the Three-Dimensional Shape of a Crystal
Authors: Indrei Emanuel , Karakhanyan Aram
Published: February 2025

The purpose of this paper is to investigate the Almgren problem in R3 under generic conditions on the potential and tension functions which define the free energy. This problem appears in classical thermodynamics when one seeks to understand whether minimizing the free energy with convex potential in the class of sets of finite perimeter under a mass constraint generates a convex minimizer representing a crystal. Our new idea in proving a three-dimensional convexity theorem is to utilize convexity and a stability theorem when the mass is small, as well as a first-variation partial differential equation along with a new maximum principle approach.
Energy Efficacy Enhancement in a Reactive Couple-Stress Fluid Induced by Electrokinetics and Pressure Gradient with Variable Fluid Properties
Authors: Banjo Peace O. , Lebelo Ramoshweu S. , Adesanya Samuel O. , Unuabonah Emmanuel I.
Published: February 2025

This study presents a mathematical analysis of the collective effect of chemical reactions, variable fluid properties, and thermal stability of a hydromagnetic couple-stress fluid flowing through a microchannel driven by electro-osmosis and a pressure gradient. The viscosity of the biofluid is assumed to depend on the temperature, while the electrical conductivity is assumed to be a linear function of the drift velocity. The governing equations are derived non-dimensionalized, and numerical solutions are obtained using the spectral Chebyshev collocation method. The numerical solution is validated using the shooting Runge–Kutta method. The effects of varying the parameters on the thermal stability, temperature, velocity, and entropy profiles are discussed with adequate interpretations using tables and graphs. The results reveal that the chemical reactions and viscosity parameter increase the fluid temperature, while the Hartmann number decreases the temperature and increases the flow velocity and entropy generation. It was also observed that the chemical reactions and viscosity parameter increased the entropy at the channel walls, while the Hartmann number decreased the entropy at the core center of the channel. This study has tremendous empirical significance, including but not limited to biophysical applications of devices, engineering applications such as control systems, and thermo-fluidic transport.
A Two-Stage Estimation Approach to Cox Regression Under the Five-Parameter Spline Model
Authors: Teranishi Ren , Furukawa Kyoji , Emura Takeshi
Published: February 2025

The Cox proportional hazards model is one of the most popular regression models for censored survival data. In the Cox model, the baseline hazard function is often modeled by cubic spline functions. However, the penalized likelihood estimation for fitting cubic spline models is computationally challenging. In this paper, we propose a computationally simple approach to implement the cubic spline model without penalizing the likelihood. The proposed method consists of two stages under the five-parameter spline model. The first stage estimates a scale parameter for a given shape model. The second stage adopts a model selection from 13 candidate shape models. We implement the proposed methods in our new R package “splineCox” (version 0.0.3) and it has been made available in CRAN. We conduct simulation studies to assess the performance of the proposed method. To illustrate the advantage of the proposed model, we analyze a life test dataset on electrical insulations and a gene expression dataset on lung cancer patients.
Reconstruction of Highway Vehicle Paths Using a Two-Stage Model
Authors: Yin Weifeng , Zhai Junyong , Yu Yongbo
Published: February 2025

The accurate reconstruction of vehicle paths is essential for effective highway toll management. To address the challenge of multiple possible paths due to missing trajectory data, this study proposes a novel two-stage model for vehicle path reconstruction. In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. In the second stage, based on the estimated time parameters, path choice prior probabilities and observed data are combined using maximum likelihood estimation to infer the most probable paths among candidate routes. The results indicate that the improved EM algorithm achieved convergence in 17 iterations compared to 41 iterations for the traditional EM algorithm. The two-stage model outperforms the Shortest Path and Bidirectional Long Short-Term Memory models in path reconstruction, particularly with a high number of missing trajectory points. Additionally, when the number of candidate paths K=4, the path reconstruction performance is optimal. These results demonstrate the effectiveness of the proposed method in handling sparse and incomplete trajectory data, offering robust and accurate vehicle path estimations that enhance traffic management and toll calculation precision.
Sensory Evaluation of Effervescent Nutritional Supplements: Identification and Characterisation of Off-Tastes
Authors: Delompré Thomas , Martin Christophe , Briand Loïc , Salles Christian
Published: February 2025

Nutritional supplements are often characterised by unpleasant tastes or aftertastes, primarily due to the presence of vitamins, minerals, and amino acids as active compounds. These taste defects can be masked by sweeteners or specific flavourings. However, the development of such strategies requires a thorough understanding of the sensory characteristics of nutritional supplements. In the present study, the sensory properties of four effervescent nutritional supplements, differing in composition, were evaluated using Quantitative Descriptive Analysis (QDA) across three modalities: orthonasal and retronasal odour perception, as well as aftertaste and aroma persistence. Bitterness, astringency, and metallic sensations were found to be responsible for the negative sensory attributes of the products in solution. The addition of flavouring agents was found to have either a positive or negative effect on the taste characteristics of the supplements. Indeed, certain fruity notes enhanced sweet and sour sensations and were found to mask negative sensory perceptions, although this effect varied depending both on the nature of the nutritional supplement and on the QDA modalities, mainly due to the oral process progressing. A better understanding of these perceptual interactions could provide a solution for masking strategies, potentially reducing the use of additives that can be expensive and detrimental to health.
Indium Imidazo[4,5,-b]porphyrins as Photocatalysts for Oxidation of Sulfides
Authors: Abdulaeva Inna A. , Filatov Mikhail A. , Kechiche Azhar , Bessmertnykh-Lemeune Alla
Published: February 2025

Over the past two decades, the application of photocatalytic reactions in organic synthesis has increased remarkably. Porphyrins, renowned for their exceptional photophysical properties, photostability, and prevalence in natural catalytic processes, are attracting significant attention as promising photocatalysts for reactions proceeding through energy transfer and one-electron transfer. In this work, we synthesized the indium(III) complex of 2-[4-(diethoxyphosphoryl)phenyl]-1H-imidazo[4,5-b]-5,10,15,20-tetramesitylporphyrin (InTMPIP) and explored its application as a photocatalyst for the oxidation of sulfides by dioxygen or air. Complex InTMPIP was found to generate singlet oxygen with quantum yield of 0.92 (toluene) and enables efficient photooxidation of sulfides to sulfoxides by dioxygen in “green” acetonitrile/water (4:1 v/v) or methanol/chloroform (2:1 v/v) solvent mixtures with almost quantitative yield. Furthermore, InTMPIP was grafted onto hydrated mesoporous titania and materials InTMPIP/TiO2-1 and InTMPIP/TiO2-2 with different In/Ti ratios were obtained and investigated. The composition and structure of the materials were studied using a combination of elemental analysis, various spectroscopic methods, gas adsorption measurements, and SEM imaging. Finally, the photocatalytic efficiency of InTMPIP/TiO2-2 was explored in aerobic photooxidation of sulfides. The heterogenized complex enables selective synthesis of sulfoxides under “green” conditions; however, it is prone to leaching into the solution when irradiated with both blue and red LEDs.
Dietary Patterns and Migraine: Insights and Impact
Authors: Tu Yi-Hsien , Chang Ching-Mao , Yang Cheng-Chia , Tsai I-Ju , Chou Ying-Chen , Yang Chun-Pai
Published: February 2025

Migraine is a prevalent neurological disorder characterized by significant disability and triggered by various factors, including dietary habits. This review explores the complex relationship between diet and migraine, highlighting both triggering and protective roles of dietary patterns and specific nutrients. Evidence suggests that certain foods, such as alcohol, caffeine, chocolate, MSG, nitrates, and tyramine, can trigger migraines in susceptible individuals. Conversely, dietary interventions, including carbohydrate-restricted diets, ketogenic diets, vitamin D3 supplementation, omega-3 fatty acids, Mediterranean dietary patterns, and increased water intake, have shown potential in reducing migraine frequency and severity. Observational studies also indicate that maintaining a healthy diet, rich in fruits and vegetables and low in processed foods, is associated with better migraine outcomes. The effectiveness of these interventions varies among individuals, underscoring the importance of personalized approaches. Future studies should further explore the role of diet in migraine management, focusing on randomized trials to establish causality and refine dietary recommendations for patients.
Generation of Liquid Crystal Elastomer Fibers via a Wet Spinning Technology with Two-Stage Crosslinking
Authors: Benecke Lukas , Schwingshackl Sina Anna , Schyra Peter , Cherif Chokri , Aibibu Dilbar
Published: February 2025

Liquid crystal elastomers (LCE) are a promising material to achieve reversible actuation while being able to perform work, showing great potential as artificial muscles in soft robotics and medical technology. Here, a wet spinning process to prepare liquid crystal elastomer fibers (LCEF) with reversible actuation capability is presented. Furthermore, we demonstrate the ability to process side-chain liquid crystal (LC) 4-Methoxyphenyl 4-(3-butenyloxy)benzoate (MBB) into a fiber, enlarging the material variance available in this field. The wet spinning process is presented and discussed in terms of spinning parameters and their influence on fiber properties, especially LC orientation. Moderate draw ratios of up to 2.3 enable highly oriented mesogens (f = 0.64), enabling the contractile behavior. The generated MBB-based LCEF show low activation temperature (54.52 °C), temperature-dependent mechanical properties, reversible contraction behavior while lifting up to 140 times their own weight and are able to perform work of up to 3.857 J kg−1. Actuation properties are compared with human skeletal muscle, and possible strategies of further enhancing the LCEF performance are discussed. The generated data show promising features of the LCEF for use as artificial muscle fibers in medical applications, e.g., prosthetics and artificial cardiac tissue.
Study on Energy Efficiency Characteristics of Ground Source Heat Pump with Coupled Evaporative Condensers in Different Regions
Authors: Pei Yingju , Zeng Lei , Xue Zhezhong , Qin Songhai , Luo Xu
Published: February 2025

Geothermal resources are a type of green energy, primarily utilized in buildings for cooling and heating through heat pump systems. However, heat pump systems all face the challenges of high operating energy consumption and cost. In this study, in order to solve the problem of the high total energy consumption of compressors and pumps in traditional ground source heat pump systems, a new ground source heat pump system with coupled evaporative condensers (EC-GSHP) is proposed, and a calculation model was built to compare and analyze its comprehensive performance compared with a traditional ground source heat pump in different climate environments. It was concluded that in a region with balanced cooling and heating loads, the energy consumption was reduced by 48.48 kW, the cooling energy saving coefficient (CESC) was 21.09%, and the comprehensive coefficient of performance (COP) increased by 1.31. In a region where the total cooling load was greater than the total heating load, the energy consumption was reduced by 105.19 kW, the CESC was 22.98%, and the comprehensive COP increased by 1.49. In a region where the total heating load was greater than the total cooling load, the energy consumption was reduced by 47.77 kW, the CESC was 21.41%, and the comprehensive COP increased by 1.30. It can be seen that the cooling and energy saving performance of the EC-GSHP system is significantly better than that of a traditional GSHP.
Fault Classification and Precise Fault Location Detection in 400 kV High-Voltage Power Transmission Lines Using Machine Learning Algorithms
Authors: Özdemir Ömer , Köker Raşit , Pamuk Nihat
Published: February 2025

Fault detection, classification, and precise location identification in power transmission lines are critical issues for energy transmission and power systems. Accurate fault diagnosis is essential for system stability and safety as it enables rapid problem resolution and minimizes interruptions in electrical energy supply. The characteristic parameters of mixed-conductor power transmission lines connected to the grid were calculated using the relevant line data. Based on these parameters, a dataset was created with computer-derived values. This dataset included variations in arc resistance and the short circuit power of the corresponding bus, facilitating the performance testing of various machine learning algorithms. It was observed that the correct determination of the faulty phase was of high importance in the correct determination of the fault position. For this reason, a gradual structure was preferred. It was achieved with a 100 percent success rate in fault detection with the ensemble bagged algorithm. It was obtained with the neural network algorithm with a 99.97 percent success rate in faulty phase detection. The most successful location results were obtained with the interaction linear algorithm with 0.0066 MAE for phase-to-phase faults and the stepwise linear algorithm with 0.0308 MAE for phase ground faults. Using the proposed algorithm, fault locations were identified with a maximum error of 26 m for phase-to-ground faults and 110 m for phase-to-phase faults on a transmission line with a mixed conductor of approximately 178 km. Additionally, we compared the training and testing results of several machine learning algorithms metrics including the accuracy, total error, mean absolute error, root mean square, and root mean square error to provide informed recommendations based on their performance. The findings aim to guide users in selecting the most effective machine learning models for predicting failures in transmission lines.
Spirituality in Action: Catholic Pastoral Care of Men in Poland as a Response to Secularisation
Authors: Rybicki Adam
Published: February 2025

This article contains some proposals for the development of pastoral care and spiritual formation of men, which might be a response of the Church in Poland to widespread secularisation. I justify this need and some theoretical aspects of men’s spiritual formation. I show the practical aspects and the initiatives that I believe are worth promoting and developing: the coordination of spiritual formation activities among men in Poland, the support of academia and science, and the spiritual formation of candidates for priesthood. Finally, I propose to internationalise men’s spiritual formation. The arguments presented here indicate that proper coordination, promotion, and involvement in the spiritual formation of men could bear good fruit in families and the entire Church in Poland.
A Comparative Analysis of Different Algorithms for Estimating Evapotranspiration with Limited Observation Variables: A Case Study in Beijing, China
Authors: Sun Di , Zhang Hang , Qi Yanbing , Ren Yanmin , Zhang Zhengxian , Li Xuemin , Lv Yuping , Cheng Minghan
Published: February 2025

Evapotranspiration (ET) plays a crucial role in the surface water cycle and energy balance, and accurate ET estimation is essential for study in various domains, including agricultural irrigation, drought monitoring, and water resource management. Remote sensing (RS) technology presents an efficient approach for estimating ET at regional scales; however, existing RS retrieval algorithms for ET are intricate and necessitate a multitude of parameters. The land surface temperature–vegetation index (LST-VI) space method and statistical regression by machine learning (ML) offer the benefits of simplicity and straightforward implementation. This study endeavors to identify the optimal long-term sequence LST-VI space method and ML for ET estimation under conditions of limited observed variables, (LST, VI, and near-surface air temperature). A comparative analysis of their performance is undertaken using ground-based flux observations and MOD16 ET data. The findings can be summarized as follows: (1) Long-term remote sensing data can furnish a more comprehensive background field for the LST-VI space, achieving superior fitting accuracy for wet and dry edges, thereby enabling precise ET estimation with the following metrics: correlation coefficient (r) = 0.68, root mean square error (RMSE) = 0.76 mm/d, mean absolute error (MAE) = 0.49 mm/d, and mean bias error (MBE) = −0.14 mm. (2) ML generally produces more accurate ET estimates, with the Random Forest Regressor (RFR) demonstrating the highest accuracy: r = 0.79, RMSE = 0.61 mm/d, MAE = 0.42 mm/d, and MBE = −0.02 mm. (3) Both ET estimates derived from the LST-VI space and ML exhibit spatial distribution characteristics comparable to those of MOD16 ET data, further attesting to the efficacy of these two algorithms. Nevertheless, when compared to MOD16 data, both approaches exhibit varying degrees of underestimation. The results of this study can contribute to water resource management and offer a fresh perspective on remote sensing estimation methods for ET.
A Projective-Geometry-Aware Network for 3D Vertebra Localization in Calibrated Biplanar X-Ray Images
Authors: Ye Kangqing , Sun Wenyuan , Tao Rong , Zheng Guoyan
Published: February 2025

Current Deep Learning (DL)-based methods for vertebra localization in biplanar X-ray images mainly focus on two-dimensional (2D) information and neglect the projective geometry, limiting the accuracy of 3D navigation in X-ray-guided spine surgery. A 3D vertebra localization method from calibrated biplanar X-ray images is highly desired to address the problem. In this study, a projective-geometry-aware network for localizing 3D vertebrae in calibrated biplanar X-ray images, referred to as ProVLNet, is proposed. The network design of ProVLNet features three components: a Siamese 2D feature extractor to extract local appearance features from the biplanar X-ray images, a spatial alignment fusion module to incorporate the projective geometry in fusing the extracted 2D features in 3D space, and a 3D landmark regression module to regress the 3D coordinates of the vertebrae from the 3D fused features. Evaluated on two typical and challenging datasets acquired from the lumbar and the thoracic spine, ProVLNet achieved an identification rate of 99.53% and 98.98% and a point-to-point error of 0.64 mm and 1.38 mm, demonstrating superior performance of our proposed approach over the state-of-the-art (SOTA) methods.
Robotic Fast Patch Clamp in Brain Slices Based on Stepwise Micropipette Navigation and Gigaseal Formation Control
Authors: Qiu Jinyu , Zhao Qili , Li Ruimin , Liu Yuzhu , Ma Biting , Zhao Xin
Published: February 2025

The patch clamp technique has become the gold standard for neuron electrophysiology research in brain science. Brain slices have been widely utilized as the targets of the patch clamp technique due to their higher optical transparency compared to a live brain and their intercellular connectivity in comparison to cultured single neurons. However, the narrow working space, small scope, and depth of the field of view make the positioning of the operation’s micropipette to the target neuron a time-consuming task reliant on a high level of experience, significantly slowing down operation of the patch clamp technique in brain slices. Further, the current poor controllability in gigaseal formation, which is the key to electrophysiology signal recording, significantly lowers the patch clamp success rate. In this paper, a stepwise navigation of the micropipette is conducted to accelerate the positioning process of the micropipette tip to the target neuron in the brain slice. Then, a fuzzy proportional–integral–derivative controller is designed to control the gigaseal formation process along a designed resistance curve. The experimental results demonstrate an almost doubled patch clamp technique speed, with a 25% improvement in the success rate compared to the conventional manual method. The above advantages may promote the application of our method in brain science research based on brain slice platforms.
Servo Collision Detection Control System Based on Robot Dynamics
Authors: Xiang Qinjian , Chen Chao , Jiang Yadong
Published: February 2025

Collision detection and inspection of industrial robots have become essential functions in modern industrial automation. Sensor-based detection methods are commonly employed in research to achieve collision detection, including high-precision force sensors, ultrasonic ranging sensors, electronic skins, and others. While collision detection using force sensors or electronic skin sensors offers very high accuracy, the inclusion of these sensors increases the overall cost. This article proposes a solution using dynamic modeling for collision detection. First, the theoretical torque generated by each axis of the industrial robot under different pose conditions is analyzed in real time. Then, the actual torque is calculated by sampling the motor current of each axis. By setting error margins and collision detection thresholds, collision detection can be achieved in a cost-effective manner without the need for additional sensors. Experiments were conducted to evaluate this dynamic modeling approach to collision detection. The findings indicated that the approach is efficacious and capable of identifying the impacts of diverse collision objects. However, compared to sensor-based detection methods, collision detection using dynamic modeling has the disadvantage of lower accuracy. Future research will concentrate on enhancing the calculation accuracy of the theoretical torque to enhance the sensitivity of collision detection.
AI-Assisted Passive Magnetic Distance/Position Sensor
Authors: Qiu Chaoyi , Qian Zhenghong , Qi Qiao , Wang Ruigang , Li Xiumei , Bai Ru
Published: February 2025

Magnetic sensing technology is crucial for non-contact distance and position measurement. Due to the nonlinear characteristics of the magnetic fields from permanent magnets, conventional magnetic sensors struggle with accurate distance and position determination. To address this, we propose a distance/position sensor that employs a customized back propagation (BP) neural network. By detecting the magnetic field variations induced by a permanent magnet, the proposed sensor can effectively model the nonlinear mapping between magnetic field strength and distance, thereby enabling precise distance and position measurement. Experimental results demonstrate that the BP neural network approach, when employing a single magnetic sensor, exhibits a measurement error in the range of −0.0268 mm to 0.0362 mm over a distance of 0–70 mm, which is significantly lower than traditional methods based on the magnetic dipole model and the Levenberg–Marquardt (LM) algorithm. Increasing the number of sensors to three reduces the error further to −0.0107 mm to 0.0093 mm. Furthermore, when employing four magnetic sensors for position measurement within a 60 mm × 60 mm planar area, the positioning errors along the x-axis and y-axis are confined to the ranges of −0.6168 mm to 1.1312 mm and −0.6001 mm to 0.5133 mm, respectively.
MR-FuSN: A Multi-Resolution Selective Fusion Approach for Bearing Fault Diagnosis
Authors: Sha Lin , Tang Shikai , Wang Min , Qiao Sibo , Yu Shihang , Liu Weixia , Li Jiaqi
Published: February 2025

Vibration signals serve as the primary data source for bearing fault diagnosis. However, when collected in complex industrial environments, these signals are often contaminated by noise interference, posing significant challenges to fault feature extraction and diagnostic accuracy. To address these issues, this paper proposes a novel bearing fault diagnosis network architecture: the Multi-Resolution Fusion Selection Network (MR-FuSN). The MR-FuSN effectively extracts domain-invariant features from input data through multi-resolution feature extraction and incorporates an adaptive kernel convolution strategy, thereby enhancing its robustness against environmental noise. Experimental results demonstrate that the MR-FuSN achieves outstanding performance in noisy environments with signal-to-noise ratios (SNRs) ranging from −5 dB to 10 dB, particularly attaining a diagnostic accuracy of 99.97% under 0 dB conditions. This study provides technical support for practical fault diagnosis applications.
Scene-Adaptive Loader Trajectory Planning and Tracking Control
Authors: Li Yingnan , Dong Wenwen , Zheng Tianhao , Wang Yakun , Li Xuefei
Published: February 2025

Wheel loaders play a crucial role in daily production and transportation. With the rapid development of intelligence in passenger vehicles, freeing loader operators from high-risk and repetitive tasks has become a pressing issue. This paper presents a novel and efficient path planning and tracking framework tailored to the unique body structure and specific operating environment of loaders. We improve the Hybrid A* search algorithm based on the operational characteristics of loaders and integrate it with dynamically updated grid maps to enable the autonomous planning of loader operating paths in unstructured environments, meeting the efficiency requirements of production. Additionally, to address the challenge of poor trajectory tracking control accuracy caused by hydraulic articulated steering, we propose a new loader trajectory tracking controller based on the idea of hierarchical control. We use an extended state observer to compensate for unknown disturbances in the steering execution layer and employ fuzzy fractional-order PID to handle the nonlinearity of loaders. Field experiments using the proposed approach demonstrate that loaders can autonomously and in real-time complete tasks in dynamically changing operating scenarios.
Validation of a Multi-Channel Ambient Sensor to Measure Vital Signs in Patients Within the Ward and at Home
Authors: Lim Seok Ming , Li Peixuan , Braat Sabine , Aung Ye Htet , Fu Susan , Johnson Douglas F. , Lim Wen Kwang
Published: February 2025

Hospitalised, unwell patients have vital signs such as heart rate (HR), oxygen saturation (SpO2) and temperature measured multiple times a day to detect clinical deterioration and monitor health trajectories. Advancements in contact-free (ambient) sensors (AS) to measure vital signs can help mitigate risks due to skin injury and infection transmission seen in conventional hospital equipment. This prospective, observational clinical study aims to validate vital sign measurements from a multi-channel AS compared to conventional equipment in three cohorts: patients in a hospital ward, patients at home within a Hospital-at-Home service, and healthy volunteers. Data analysis of 571 paired measurements from 29 participants indicates that heart rate measurements via AS were accurate, though they lacked precision, with the clinical agreement range between 6.38 and 6.49 beats per minute. Temperature and oxygen saturation measurements showed less agreement when compared with the reference standard. In conclusion, ambient sensors show promising utility in measuring vital signs, with this study amongst the first of its kind to utilise this in measuring vital signs in hospitalised patient cohorts in both ward and home environments.
Vehicle Vibration Reduction Using Hydraulic Dampers with Piezoelectric Valves
Authors: Knap Lech , Graczykowski Cezary , Holnicki-Szulc Jan
Published: February 2025

Ensuring adequate comfort and safety in vehicle motion is a subject of extensive research worldwide. Despite the implementation of new control algorithms, including those leveraging AI, the application of effective semi-active vibration dampers remains crucial for achieving optimal suspension performance. This article presents experimental studies conducted on a vehicle equipped with semi-active suspension featuring custom-designed hydraulic dampers controlled by piezoelectric valves. These innovative dampers are characterized by extremely short response times, enabling real-time adaptation to varying driving conditions. A simple control algorithm designed to operate based on real-time signals from suspension sensors is introduced and evaluated. The experimental setup, including the measurement system used during testing, is described in detail. The presented results highlight the significant potential of this approach for improving driver comfort under specific driving conditions, even without detecting road roughness ahead of the vehicle.
Optimized Production of High-Performance Activated Biochar from Sugarcane Bagasse via Systematic Pyrolysis and Chemical Activation
Authors: Nazbakhsh Mohammad , Nabavi Seyed Reza , Jafarian Sajedeh
Published: February 2025

The following work deals with the preparation of highly porous activated biochar from sugarcane bagasse (SB) via potassium hydroxide activation and optimization by a D-optimal design. Activation temperatures within the range of 600 to 800 °C, holding times between 60 and 180 min, and KOH impregnation ratios (WKOH/WRBC) ranging between 0.5, 1, and 2 were explored with a view to enhance properties like Brunauer–Emmett–Teller (BET) surface area and total pore volume of biochar while considering mean diameter as well. Optimized conditions in this study were an activation temperature of 800 °C, holding time of 120 min, and KOH impregnation ratio of 1:1. The activated biochar prepared under such conditions had a very high BET surface area, 1149 m2/g, and a total pore volume of 0.53 cm3/g. This was further characterized by thermal gravimetric analysis (TGA), and Fourier transform infrared (FTIR) spectroscopy, indicating improved microporosity with a view to application in adsorption studies. This is a sustainable work to obtain economical high-performance biochar from agricultural waste for application in adsorption and catalytic processes.