bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Tuning of ENZ Wavelength in Conductive Polymer Films via Polaron Excitation
Authors: Ye Hui 
Published: January 2025

Abstract

Traditional metal and n–type doped semiconductor materials serve as emerging epsilon–near zero (ENZ) materials, showcasing great potential for nonlinear photonic applications. However, a significant limitation for such materials is the lack of versatile ENZ wavelength tuning, and thus dynamic tuning of the ENZ wavelength remains a technical challenge, thereby restricting their potential applications, such as multi–band communications. Here, dynamic tuning of the ENZ wavelength in p–type organic PEDOT: PSS films is achieved through a reversible change in hole concentrations originated from the polaron formation/decoupling following optical excitation, and a tunable ENZ wavelength shift up to 150 nm is observed. Experimental investigations about ultrafast dynamics of polaron excitation reveal a ∼80 fs time constant for polaron buildup and a ∼280 fs time constant for polaron decoupling, indicating the potential of reversal ultrafast switching for the ENZ wavelength within subpicosecond time scale. These findings suggest that p–type organic semiconductors can serve as a novel platform for dynamically tuning the ENZ wavelength through polaron excitation, opening new possibilities for ENZ–based nonlinear optical applications in flexible optoelectronics.
Cognitive Alignment Between Humans and LLMs Across Multimodal Domains
Authors: Wang Yuwei , Liang Dongqi , Zeng Yi 
Published: January 2025

Abstract

Large Language Models (LLMs) show remarkable text abilities, prompting investigations into their alignment with human cognition.
Using the Brain-Based Componential Semantic Representation (BBSR), a neurobiologically grounded semantic framework, we evaluate nine LLMs, including Qwen2, Llama-3, Llama-3.1, and GPT series.
We examine their multimodal cognitive boundaries, representational similarity, cross-modality consistency, abstract/concrete divergences, psycholinguistic factors, and stability across repeated responses.
Larger models align more closely with human cognition, particularly for concrete concepts and early-acquired words.
Still, discrepancies persist, especially for abstract concepts, spatial cognition, embodied experiences (e.g., olfaction, gustation), and causal reasoning.
These findings reveal limitations in LLM cognitive architectures, emphasizing models embodying human cognition.
Workplace Flourishing as a Mediator in the Relationship between Relationship-Oriented Leadership and Organizational Citizenship Behavior in the Context of Nursing Staff in Hospitals
Authors: Türe Aysun , Akkoç İrfan , Arun Korhan , KARA Arzu UĞURLU 
Published: January 2025

Abstract

Background: This study investigates the impact of relationship-oriented leadership on organizational citizenship behavior among hospital nurses, focusing on the mediating role of workplace flourishing. The research aims to fill gaps in understanding the indirect effects of leadership on organizational citizenship behavior through workplace well-being in the context of healthcare professionals.
Methods: A cross-sectional design was employed, surveying 448 nurses from a university hospital using structured Likert-type scales. Data were analyzed through structural equation modeling and the bootstrap method to test the hypothesized relationships among the variables.
Results: The findings indicate that relationship-oriented leadership significantly affects organizational citizenship behavior dimensions such as altruism, conscientiousness, courtesy, and sportsmanship. Additionally, workplace flourishing was found to mediate the relationship between leadership style and organizational citizenship behavior, with flourishing showing a strong positive influence on organizational citizenship behavior dimensions.
Conclusion: The study highlights that relationship-oriented leadership fosters workplace flourishing, which in turn enhances organizational citizenship behaviors. These results suggest that healthcare leaders can promote better workplace outcomes by fostering a flourishing environment, ultimately improving nurse engagement and citizenship behaviors.
Impact of Topological Defects on Strain-Induced Crystallization in Elastocaloric Polymers
Authors: Lin Shaoting , Yu Zhaohan , Xu Duo , Usmanova Zumrat , Swarnkar Aditya , Ye Chuwei , Scott Emma , Huang Sizhe , Rao Siyuan , Boriskina Svetlana , Bai Ruobing 
Published: January 2025

Abstract

Elastocaloric polymers, whose performance typically relies on phase transformation between amorphous chains and crystalline domains, offer a promising alternative to traditional refrigeration technologies due to their solid-state characteristics and environmental benefits. While engineering polymer-network architecture has shown the potential to boost elastocaloric performance, the role of topological defects remains unexplored despite their prevalence in real polymers. This study investigates strain- and temperature-induced crystallization in a series of model end-linked star polymers (ELSPs) with controlled dangling-chain defects, focusing on their effects on mechanical properties and elastocaloric performance. Our findings reveal two competing effects: suppression of strain-induced crystallization (SIC), which hinders amorphous chain alignment and crystalline domain orientation, and promotion of temperature-induced crystallization (TIC), which enhances polymer network flexibility. Increasing dangling-chain defects monotonically lowers ELSPs’ mechanical performance at high temperatures due to suppressed SIC, but nonmonotonically impacts the mechanical performance at low temperatures due to the competition between suppressed SIC and enhanced TIC. Additionally, elastocaloric experiments show an intriguing defect-dependent adiabatic temperature change, highlighting the critical role of topological defects in maximizing the cooling performance of elastocaloric polymers.
The silver bullet - new evidence for a hypervelocity impact origin for the Silverpit Crater
Authors: Nicholson Uisdean Alasdair , de Jonge-Anderson Iain , Gillespie Alex , Kenkmann Thomas , Jones Tom Dunkley , Collins Gareth S. , Frankel James , Bray Veronica , Gulick Sean P.S. , Parr Ronnie 
Published: January 2025

Abstract

An impact origin for the Silverpit Crater, on the UK continental shelf, has been contested over the last two decades, with a lack of a ‘silver bullet’ – traditionally petrographic evidence of shock metamorphism – to resolve the debate. Here we present new 3D seismic, petrographic and biostratigraphic data, and numerical impact simulations to test the impact hypothesis. The seismic data provide exceptional imaging of the entire structure for the first time, confirming the presence of a central uplift, annular moat, damage zone and numerous secondary craters on the contemporaneous seabed. The distribution of normal and reverse faults in the brim, and curved radial faults around the central uplift suggest a low-angle impact from the west. The pitted, flat-topped central uplift at the top chalk horizon may indicate significant devolatilization of chalk immediately following impact. Biostratigraphic data confirm that this event occurred during the middle Eocene, between 43-46 million years ago. Petrographic analysis from the reworked ejecta sequence in the nearby 43/25-1 well reveals two grains with shock lamellae, indicating shock pressures of ~10-13 GPa, consistent with results from our numerical models. This combination of evidence proves that the Silverpit structure is an exceptionally preserved hypervelocity impact structure.
A Child Presenting with Arthralgia Confirmed to Be Wilson's Disease
Authors: Li Yiyuan , Wen Yang 
Published: January 2025

Abstract

Backgrounds
:Wilson's disease (WD) is a rare inherited disorder characterized by impaired hepatic copper metabolism, resulting in copper accumulation and multi-systemic manifestations, but arthritis as an initial manifestation is rare .We report a pediatric case of WD visiting the hospital for arthralgia.
Case presentation
A ten-year-old patient experienced recurrent arthralgia in the lower limbs, predominantly involved ankles and knees, and physical examination revealed tenderness in the right ankle joint and hepatomegaly. Laboratory investigations demonstrated liver disfunction, including elevated alanine aminotransferase, aspartate aminotransferase, and total bilirubin levels. The patient was subsequently diagnosed with WD based on the presence of Kayser-Fleischer rings on ophthalmic examination, low ceruloplasmin levels, and increased urinary copper excretion. With penicillamine and Zinc preparations therapy, the patient reported gradual improvement in arthralgia and liver function.
Conclusion
Wilson's disease should be considered in the differential diagnosis of patients presenting with arthralgia, especially in the presence of abnormal liver function tests.
Investigation of longitudinal modes for different microchip Nd:YVO4/KTP green lasers
Authors: Elsafty Ahmed Saudi. 
Published: January 2025

Abstract

Nowadays, single-frequency diode-pumped solid-state lasers play an important role in laser frequency standard and length metrology. In this paper, the longitudinal modes oscillation of three different low-cost microchips Nd:YVO4/KTP green lasers have been investigated. A short-cavity Nd:YVO4 laser is used to explore Single Longitudinal Mode (SLM) without inserting any optical elements inside the cavity. The experiment confirms that SLM can occur by controlling the diode pumping current and laser crystal temperature at a wide range from (300 mA to 388 mA) and (18.5°C to 30°C), respectively.
Re-evaluating the associations of abdominal and ectopic fat accumulation with impaired glucose metabolism based on Q-CT measurements in overweight/obese Chinese subjects by gender
Authors: Ma Xiaoli , Liu Yang , Li Bohan , Zhao Huichen , Sun Yanpei , Han Heli , Yu Wanjiang , Mu Weina , Liu Yuantao 
Published: January 2025

Abstract

Objective: Re-evaluate the associations of abdominal adiposity and ectopic fat accumulation with impaired glucose metabolism (IGM) in overweight/obese Chinese subjects by gender, based on quantitative computed tomography (Q-CT) measurements.
Materials and Methods: This study included 205 participants (100 males, 105 females ) with BMI ≥24, aged between 18 and 50 years. All participants underwent a standard 75g oral glucose tolerance test (OGTT). The subjects were divided into three categories according to their glucose status: normal glucose tolerance (NGT), impaired glucose tolerance (IGT) and diabetes (DM) for both genders. Abdominal computed tomography (CT) was conducted to ascertain the quantities of abdominal fat and fat within the liver, pancreas, and skeletal muscle. IGM was defined as the presence of IGT or DM. The data was analyzed separately by gender.
Results: The hepatic fat fraction (HFF) was found to be significantly higher in IGMpatients than in NGT subjects, across both genders. After adjusting for age and dyslipidemia, the odds ratio for the prevalence of IGM in the highest tertile of HFF was 5.24 (95% CI 1.64-16.73) in males and 6.45 (95% CI 2.12-19.63) in females, respectively. Further analysis demonstrated that other fat fractions, specifically visceral adipose tissue (VAT), exhibited significantly higher levels in IGM patients compared to NGT subjects, across both genders. With regard to VAT, the odds ratio for IGM was 6.56 (95% CI 1.55-27.86) in males and 3.29 (95% CI 1.17-9.29) in females, respectively. The results for subcutaneous fat tissue (SAT) demonstrated significantly lower levels in diabetic patients than in non-diabetic and IGT patients. In males, the odds ratio for IGM of SAT was 0.13 (95% CI 0.03-0.60).
Conclusions: The results demonstrated that both HFF and VAT were independent risk factors for IGM in Chinese overweight/obese subjects of both genders. In male subjects, SAT was found to be a beneficial factor in reducing the risk of IGM. The findings revealed useful biomarkers and therapeutic targets for the early detection and prevention of diabetes in Chinese subjects with overweight/obesity.
MSE-NERSPPNet: A Multi-Channel Framework for Bearing Fault Diagnosis in the Presence of Imbalanced Samples
Authors: Lin Daxuan , Dong Zhilin , Sun Jianfeng , Xu Wanxiu , Chen Xiaohao , Liu Siyu , Jiang Yonghua , Jiao Weidong 
Published: January 2025

Abstract

Bearing monitoring data in industrial applications exhibits pronounced class imbalance, where the disproportionate ratio of healthy to faulty samples imposes significant constraints on the feature extraction and generalization capabilities of intelligent diagnostic models. Multi-channel sensing systems are extensively deployed in engineering practices to facilitate precise fault diagnosis and obtain multidimensional complementary information. However, the intrinsic heterogeneity of such data (e.g., spatiotemporal dependencies across channels) and unavoidable redundancy (e.g., overlapping or correlated information among channels) substantially escalate the complexity of implementing robust feature engineering techniques. To overcome these challenges, a Multi-scale Sample Entropy-driven Nonlinear Residual Spatial Pyramid Pooling Network (MSE-NERSPPNet) is proposed in this study. Initially, multi-scale sample entropy is employed to analyze signals from each channel, extracting complexity-domain entropy features. Subsequently, multi-channel features are pooled and fused across three distinct spatial scales (global, intermediate, and local) via a spatial pyramid pooling layer, enhancing the capability of model to extract features from heterogeneous multi-channel data. Finally, a residual module, augmented with the Kolmogorov–Arnold Network, is introduced to refine feature fusion further. The fused features are then subjected to residual learning and nonlinear mapping mechanisms to optimize the overall feature representation. MSE-NERSPPNet is extensively evaluated using two sets of multi-channels bearing data featuring varying imbalance ratios. Experimental results indicate that MSE-NERSPPNet outperforms several benchmark algorithms, achieving superior recognition rates across various tasks.
Designing Serious Games for Cognitive and Motor Rehabilitation in Post-Stroke Patients
Authors: Alves Thiago , Gonçalves Rogério Sales , Kishi Marcos Seizo 
Published: January 2025

Abstract

Stroke remains the leading cause of disability, often resulting in severe motor and cognitive impairments, including functional deficits and memory loss. Rehabilitation leverages neuroplasticity, enabling undamaged brain regions to compensate for lost functions. Enhancing traditional therapy with robotic bilateral priming and non-invasive brain stimulation, such as serious games, addresses issues like learned non-use and interhemispheric inhibition. These approaches promote cortical excitability rebalancing, fostering a neuroplastic environment conducive to motor and cognitive recovery. Therapeutic tools, like pegboards, aid fine motor coordination recovery, supporting Activities of Daily Living (ADLs), while improving attention, concentration, and visuospatial cognition. Additionally, puzzle games further stimulate memory-related brain regions, stimulating cognitive improvements. This paper explores the potential of serious games and robotic devices in cognitive rehabilitation of stroke, detailing their ability to provide engaging and effective therapy. Several serious games combining memory tasks, reach, and pegboard fitting were developed, with careful consideration of design, therapeutic benefits, and clinical findings. Two stroke groups underwent an intervention with the serious games developed, demonstrating significant improvements (p < 0.05) in cognitive and motor performance across multiple parameters. Approved by the Research Ethics Committee of the Federal University of Uberlândia (ethics approval numbers 51133821.4.0000.5152 | 00914818.5.0000.5152).
Free-Living Muscle Activity in Type 2 Diabetes: Sitting, Standing and Walking
Authors: Lamberg Suvi , Brakenridge Christian , Gao Ying , Dunstan David W. , Finni Taija , Healy Genevieve N. , Owen Neville , Pesola Arto J. 
Published: January 2025

Abstract

AIMS: Using thigh-worn accelerometers and wearable electromyographic (EMG) shorts, we investigated muscle activity during sitting, standing and walking in adults with type 2 diabetes.
METHODS: Isometric maximal voluntary contraction measures for quadriceps, hamstring, and gluteal muscle groups normalized the EMG signal to individual maximum capacity. Participants concurrently wore accelerometers and EMG shorts for 3.2 days, and average EMG amplitude (aEMG) was assessed from quadriceps, hamstring, and gluteal muscle groups within accelerometer-derived sitting, standing, walking times.
RESULTS: Muscle groups examined used only 2.7–4.4% of their maximum voluntary capacity (%EMGMVC) and were inactive for 75-80% of the measurement time. Sitting time was significantly correlated with muscle inactivity across all three muscle groups, but inversely so for hamstring aEMG (r = -0.51). Standing (r = 0.51) and walking (r = 0.48) were correlated with daily aEMG only in hamstrings. Relative to sitting, standing aEMG was 1.3–5.6 times higher and walking aEMG was 3.1–15.2 times higher, indicating varied inter-individual responsiveness.
CONCLUSIONS: Reducing daily sitting, especially in favor of walking, may benefit hamstring and gluteal muscle engagement and help to prevent high levels of muscle inactivity in type 2 diabetes. Individual variability in EMG responses highlights the potential to personalize recommendations on sitting, standing and walking.
Leveraging level data for accurate downstream flow prediction in the Narmada River Basin with advanced machine learning models
Authors: Kumar Vijendra , Rathnayake Namal , Reddy S. Hariprasad , Kedam Naresh , Rathnayake Upaka , Hoshino Yukinobu 
Published: January 2025

ABSTRACT

Accurate river flow prediction is essential for effective water resource management and flood forecasting. This study investigates advanced machine learning (ML) models CatBoost, LGBM, Random Forest, and XGBoost for predicting downstream flow at ‘Mandleshwar' using level data from key stations in the Narmada River basin. The dataset, spanning 1978–2020 with over 15,000 daily observations, was obtained from India’s Water Resources Information System (WRIS). Rigorous preprocessing ensured high-quality input data for modeling. During training, XGBoost achieved an MAE of 0.0031, MSE of 0.00002, RMSE of 0.0048, and R2 of 0.99, effectively capturing flow dynamics. In validation, LGBM outperformed with an R2 of 0.95, MAE of 0.0646, and RMSE of 0.2262, while CatBoost, XGBoost, and Random Forest followed closely. In testing, XGBoost led with an R2 of 0.96, RMSE of 0.2326, and MAE of 0.0680, while Random Forest and other models also demonstrated strong predictive capability. The findings emphasize the utility of level data for downstream flow prediction and the effectiveness of ML models in hydrological applications. This study provides actionable insights for optimizing reservoir operations, flood mitigation, and sustainable water management, supporting policymakers in developing adaptive strategies for the Narmada River basin.
Assessment of natural fluoride contamination in water intended for human consumption from various regions in Tunisia
Authors: Selmi Rachid , Hadiji Rim , Mamlouk Aymen , Ben Said Mourad , Ben Youssef Samir , Gritli Abderraouf 
Published: January 2025

ABSTRACT
Fluoride is a naturally occurring element present in the Earth's crust, which is released from rocks into the soil and water. Elevated levels of fluoride have been reported in phreatic groundwater worldwide, posing significant health risks to animals, plants, and humans. This study aims to assess the fluoride content in water intended for human consumption from both public networks and groundwater sources in various regions of Tunisia. A total of 46 water samples were collected between 2020 and 2021. The fluoride levels were determined using potentiometry with a combined Fluoride perfectION™ ISE selective electrode. The analysis revealed that fluoride content ranged from 0.351 to 6.016 mg/L. Samples exceeding the regulated limit of 1.5 mg/L were predominantly found in the southern areas of the country (64.3%, averaging 1.755 mg/L), regions known by hydrogeological fluoride deposits (54.8%, averaging 1.715 mg/L), and groundwater sources (75%, averaging 2.103 mg/L). Exposure of animals and humans to such high levels of fluoride poses a serious public health concern. Consequently, the implementation of a national strategy for the monitoring and control of public water resources intended for consumption is essential in mitigating the risks associated with fluoride contamination.
An investigation into the influence of climate extreme on groundwater regimes and human health in the Periyar Basin: A fast growing urban centre in India
Authors: Aditya Sanal Kumar , Krishnakumar Appukuttanpillai , Anoop Krishnan Krishnan 
Published: January 2025

ABSTRACT

A total of 212 groundwater samples were collected during North East Monsoon (NEM), South West Monsoon (SWM), Pre-Monsoon (PREM), and Post-Monsoon (POM) seasons of 2020–2021 from the Periyar River Basin, draining the south western flanks of Western Ghats. The analytical results revealed the order of abundance of cations as Ca2+ &gt; Na+ &gt; Mg2+ &gt; K+ and anions in the order of HCO3− &gt; Cl− &gt; SO42− &gt; NO3− for all seasons. The major hydrochemical facies identified were CaHCO3 and mixed Ca–Mg–Cl in all the seasons with rock–water interaction as the key process regulating water chemistry. Ionic ratios of Ca2+ + Mg2+/Na+ + K+ and Ca2+/Mg2+ suggested significant effect of silicate minerals and other sources. The Water Quality Index (WQI) shows that the majority of the samples, namely, 98% in NEM, 86% in POM, 82% in PREM, and 95% in MON, fall in the categories ranging from excellent to good for drinking purposes. Furthermore, the health risk assessment based on carcinogenic and non-carcinogenic risk of the United States Environmental Protection Agency (US EPA) during monsoon and non-monsoon seasons for adults and children revealed the potential risk posed by Pb via oral exposure in the study area suggesting children being more susceptible to the damaging effects than adults.
Navigating the complex landscape of waterborne disease research
Authors: Khant Naing Aung , Lumongsod Regina Martha , San Arkar , Moon Jinah , Namkoong Sim , Kim Heejung 
Published: January 2025

ABSTRACT

Waterborne pathogens and associated diseases continue to pose a significant global health challenge, requiring effective monitoring, detection, and treatment strategies. This review examines the current state of waterborne pathogen management, highlighting persistent issues and recent advancements. Here, we review cutting-edge detection methods and treatment technology, emphasizing their roles in water safety and outbreak prevention. The impact of climate change on waterborne pathogen dynamics is explored, alongside a discussion of interdisciplinary research approaches. We also aimed to investigate the crucial relationship between waterborne disease control and Sustainable Development Goals (SDGs), focusing on community engagement, well-being, water sanitation, public health policies, and international cooperation. The PRISMA protocol systematic process was used to filter papers for this study and carry out the review process. Machine learning and remote sensing techniques are promising features in the pathogen detection field. SDGs 3, 6, 11, 13, and 17 are the most closely interrelated with waterborne diseases. This review provides an in-depth overview of waterborne pathogen management, contributing to improved global water quality and public health strategies. This integrated approach aims to enhance health outcomes and promote resilience against waterborne diseases, particularly for vulnerable communities.