bluuebunny/crossref_metadata_2025 huggingface dataset:
Dual Roles of Plasma miRNAs in Myocardial Injuries After Polytrauma: miR-122-5p and miR-885-5p Reflect Inflammatory Response, While miR-499a-5p and miR-194-5p Contribute to Cardiomyocyte Damage
Authors: Han Jiaoyan , Leppik Liudmila , Sztulman Larissa , De Rosa Roberta , Pfeiffer Victoria , Busse Lewin-Caspar , Kontaxi Elena , Adam Elisabeth , Henrich Dirk , Marzi Ingo , Weber Birte
Published: February 2025

Cardiac injury after severe trauma is associated with higher mortality in polytrauma patients. Recent evidence suggests that miRNAs play a key role in cardiac pathophysiology and could serve as potential markers of cardiac damage after polytrauma. To explore this hypothesis, plasma miRNA profiles from polytrauma patients (ISS ≥ 16) with and without cardiac injury, stratified by troponin T levels (TnT, > 50 pg/mL vs. < 12 pg/mL), were analysed using NGS and validated via RT-qPCR. Five miRNAs (miR-122-5p, miR-424-5p, miR-885-5p, miR-194-5p, and miR-499a-5p) were found to be significantly upregulated in polytrauma patients with elevated TnT levels. miR-122-5p was associated with markers of right ventricular dysfunction (TAPSE) and left ventricular hypertrophy (IVS/LVPW), while miR-885-5p correlated with left ventricular hypertrophy (IVS/LVPW) and diastolic dysfunction (E/E’ ratio). In vitro, miR-194-5p mimic and miR-499a-5p mimic exhibited more active roles in cardiomyocyte injury by increasing caspase-3/7 activity and/or enhancing caspase-1 activity. Notably, the miR-194-5p mimic significantly enhanced the cytotoxic effects of the polytrauma cocktail, while miR-499a-5p boosted effects of LPS/nigericin stimulation in cardiomyocytes. Our findings identify miR-122-5p and miR-885-5p as potential biomarkers reflecting the cardiomyocyte response to polytrauma-induced inflammation, while miR-499a-5p and miR-194-5p appear to play a direct role in myocardial injury after polytrauma.
Humanized FcεRI Expressed on Mouse Eosinophils Mediates IgE-Facilitated Eosinophil Antigen Presentation
Authors: Wang Haibin , Kinet Jean-Pierre , Weller Peter F.
Published: February 2025

High-affinity IgE receptors (FcεRI) are expressed on human blood eosinophils and may be upregulated on eosinophils at sites of allergic inflammation including atopic dermatitis and allergic asthma. FcεRI engagement, however, fails to elicit “effector” responses from eosinophils. Thus, a functional role for FcεRI on eosinophils has been uncertain. We evaluated the role of FcεRI in enhancing eosinophil antigen presentation in vivo by using humanized FcεRI α chain (hFcεRIα) transgenic mice. Eosinophils from hFcεRIα transgenic mice expressed humanized FcεRIα, with higher levels of eosinophils from the bronchoalveolar lavage of experimental asthma than those from polymyxin-elicited peritoneal lavage. The hFcεRIα-bearing eosinophils instilled intratracheally (i.t.) into recipient wild-type mice migrated from airways into paratracheal lymph nodes (pLNs) and spleens. Eosinophils, pretreated in vitro with nitrophenyl-ovalbumin ((NP)-OVA) and anti-NP human IgE complexes and instilled i.t., presented NP antigen via hFcεRIα to T cells more effectively than those pretreated with NP-OVA only, as assessed by pLN cell proliferation. IgE/FcεRIα-facilitated eosinophil antigen presentation resulted in increased IL-4 but not INF-γ production by pLN cells, with a bias towards Th2 cytokine production. Furthermore, cross-linking hFcεRIα on eosinophils increased eosinophil expressions of T cell costimulatory proteins CD40, CD80, and CD86. Humanized FcεRIα on murine eosinophils functions to enhance eosinophil antigen presentation capacities by mediating IgE-facilitated antigen presentation and upregulating expression of requisite T cell costimulatory proteins. Thus, a functional, non-“effector” role for FcεRI on eosinophils is revealed through identifying a means by which IgE may act on eosinophils to mediate their immunomodulatory, enhanced antigen presentation capabilities.
Simulating Analyte Extraction via Sorption in Powdered and Lyophilized Pharmaceutical Products Using Butyl Rubbers
Authors: Kritikos Nikolaos , Bletsou Anna , Kousoulos Constantinos , Dotsikas Yannis
Published: February 2025

A novel extraction method based on solid-to-solid interactions has been developed to investigate the acquisition of contaminants from butyl rubber materials, with potential applications in the pharmaceutical industry. The extraction medium used is silica gel—a cost-effective, non-toxic, heat-resistant, and chemically inert material that is easy to handle in laboratory settings. Silica gel also enables straightforward recovery of adsorbed species using standard laboratory solvents. This method effectively exhausts contaminants from typical rubber articles within a reasonable timeframe, even under ambient conditions, while preserving the integrity of the material. Unlike traditional destructive liquid-based extractions, this approach produces significantly cleaner chromatographic profiles. This study focuses on the primary analytes extracted from chlorobutyl rubber, including halogenated rubber volatile impurities (VOIs), and tracks their acquisition over the course of the experiment. The findings provide valuable insights into the diffusion-based process by which pharmaceutical powders acquire contaminants, spanning a wide range of volatility and lipophilicity.
Child-to-Parent Violence Among Adolescents: A Preliminary Analysis of Its Association with Sociodemographic Variables, Dating Violence, and Antisocial Traits
Authors: Espuig Alba , Lacomba-Trejo Laura , González-Sala Francisco
Published: February 2025

Introduction: Child-to-parent violence (CPV) is influenced by factors such as sex, age, dating violence, psychopathy traits, and antisocial and law-violating behaviors. This study explores how these variables relate to aggression towards parents, identifying key explanatory factors. Methods: This research engaged 136 Spanish adolescents aged 15–18 (mean age = 16.47; 51% female). Assessments included the Conflict in Adolescent Dating Relationships Inventory (CADRI) for dating violence, the Psychopathy Content Scale (P-16) for psychopathy, the Antisocial and Criminal Behavior Scale in Adolescents (ECADA) for antisocial and law-violating behaviors, and the Conflict Tactics Scales (CTS2) for CPV. Analyses of associations included linear regression and qualitative comparative analysis (QCA). Results: Females exhibited higher levels of verbal violence, less delinquency, and more frequent CPV towards mothers. Psychopathy, antisocial and law-violating behaviors, and exposure to verbal violence were correlated with filial aggression. Violence towards mothers was associated with older age, female sex, verbal violence exposure, and psychopathy (47% variance explained), while violence towards fathers was linked to younger age and psychopathy (28% variance explained). QCA results indicated that specific combinations of having experienced violence and psychopathic traits contribute to CPV towards both parents. Conclusions: These findings highlight the importance of addressing psychological and sociodemographic risk factors for CPV. Prevention efforts should focus on reducing exposure to violence, identifying at-risk adolescents, and implementing targeted interventions to promote family well-being.
Salvage Ultrasound-Guided Robot-Assisted Video-Endoscopic Inguinal Lymphadenectomy (RAVEIL) as a Metastasis-Directed Therapy (MDT) in Oligoprogressive Metastatic Castration-Resistant Prostate Cancer (mCRPC): A Case Report and Review of the Literature
Authors: Drobot Rafał B. , Lipa Marcin , Antoniewicz Artur A.
Published: February 2025

Background: Metastatic castration-resistant prostate cancer (mCRPC) remains challenging due to progression despite androgen deprivation therapy (ADT). Current treatments, including androgen receptor-targeted agents, chemotherapy, bone-targeted agents, and PARP inhibitors, extend survival but face challenges, such as resistance, adverse effects, and limited durability. Metastasis-directed therapies (MDTs), such as stereotactic ablative radiotherapy (SABR), show promise in oligometastatic disease, but their role in oligoprogressive mCRPC is unclear. Salvage lymphadenectomy is rarely pursued due to invasiveness and limited data. This is the first report of robotic surgery as an MDT in this setting, demonstrating the potential of salvage robot-assisted video-endoscopic inguinal lymphadenectomy (RAVEIL) to manage oligoprogressive mCRPC and delay systemic progression. Methods: A 47-year-old male with metastatic hormone-sensitive prostate cancer (Gleason 10) underwent ADT, docetaxel chemotherapy, and radical retropubic prostatectomy with super-extended pelvic and retroperitoneal lymphadenectomy. Upon progression to oligoprogressive mCRPC, 68Ga-PSMA PET/CT detected a single metastatic inguinal lymph node. Salvage RAVEIL was performed using the da Vinci X™ Surgical System, guided by preoperative ultrasound mapping. Results: Histopathology confirmed metastasis in one of the eight excised lymph nodes. The patient achieved undetectable PSA levels and prolonged biochemical progression-free survival. Minor complications (lymphorrhea, cellulitis) resolved without sequelae. No further progression was observed for over 14 months. Conclusions: This case highlights RAVEIL as a viable MDT option for oligoprogressive mCRPC, potentially extending progression-free intervals while minimizing systemic treatment.
Gamma-Glutamyl Transferase Plus Carcinoembryonic Antigen Ratio Index: A Promising Biomarker Associated with Treatment Response to Neoadjuvant Chemotherapy for Patients with Colorectal Cancer Liver Metastases
Authors: Yin Yanjiang , Xu Bowen , Chang Jianping , Li Zhiyu , Bi Xinyu , Wei Zhicheng , Che Xu , Cai Jianqiang
Published: February 2025

Background: Colorectal cancer liver metastasis (CRLM) is a significant contributor to cancer-related illness and death. Neoadjuvant chemotherapy (NAC) is an essential treatment approach; however, optimal patient selection remains a challenge. This study aimed to develop a machine learning-based predictive model using hematological biomarkers to assess the efficacy of NAC in patients with CRLM. Methods: We retrospectively analyzed the clinical data of 214 CRLM patients treated with the XELOX regimen. Blood characteristics before and after NAC, as well as the ratios of these biomarkers, were integrated into the machine learning models. Logistic regression, decision trees (DTs), random forest (RF), support vector machine (SVM), and AdaBoost were used for predictive modeling. The performance of the models was evaluated using the AUROC, F1-score, and external validation. Results: The DT (AUROC: 0.915, F1-score: 0.621) and RF (AUROC: 0.999, F1-score: 0.857) models demonstrated the best predictive performance in the training cohort. The model incorporating the ratio of post-treatment to pre-treatment gamma-glutamyl transferase (rGGT) and carcinoembryonic antigen (rCEA) formed the GCR index, which achieved an AUROC of 0.853 in the external validation. The GCR index showed strong clinical relevance, predicting better chemotherapy responses in patients with lower rCEA and higher rGGT levels. Conclusions: The GCR index serves as a predictive biomarker for the efficacy of NAC in CRLM, providing a valuable clinical reference for the prognostic assessment of these patients.
Model-in-the-Loop Simulation for Model Predictive Controlled High-Pressure Direct Injection Dual-Fuel Engine Combustion Control
Authors: Shuai Xiuyun , Liu Hongyu , Li He , Cui Wei , Wang Qingxin , Yu Wenbin , Zhao Feiyang
Published: February 2025

Given the intricate combustion process and the multitude of control parameters inherent to the high-pressure direct injection (HPDI) diesel/natural gas dual-fuel engine, achieving precise combustion control represents a significant challenge. It is imperative to develop a high-precision engine model and integrate it with advanced control algorithms to achieve an optimal combustion strategy. In this study, a system-level engine plant model with high accuracy and real-time performance was developed using a modular modeling method through the calibration of experimental data and the simplification of model calculations. In this model, the relative error of the model simulation is controlled to be less than 5%, and the real-time factor (RTF) is less than 1. The multi-stage combustion process was parameterized by performing piecewise linear fitting of the heat release rate curve, and the relationship between injection parameters and combustion parameters was established using multiple regression analysis. On this basis, a model predictive control (MPC) algorithm was designed and verified in the constructed model-in-the-loop (MiL) platform. The results demonstrate that the designed MPC algorithm can accurately track the combustion phasing CA50 and the indicated mean effective pressure (IMEP) targets with a maximum error of 0.0624° and 0.046% within 6 and 8 cycles while ensuring the stability of the control process. The MiL platform not only meets the current combustion control requirements but also provides a general basis for the development of subsequent engine multi-control strategies and cooperative control optimization.
Primary Sinonasal Mucosal Melanoma: A Narrative Review
Authors: Todorovic Nikola , Djurkovic Petar , Krstic Aleksandar , Tomanovic Nada , Milanovic Pavle , Kablar Djurdjina , Rajkovic Pavlovic Zlata , Stevanovic Momir , Milanovic Jovana , Arnaut Aleksandra , Ljubisavljevic Ivan , Selakovic Dragica , Rosic Gvozden , Vasiljevic Milica
Published: February 2025

Mucosal melanomas (MMs) are under-researched tumors with a poor prognosis that arise from melanocytes found in the mucous membranes at different anatomical locations throughout the body. MMs are an uncommon yet highly aggressive tumor that typically develops on mucosal surfaces, predominantly in the head and neck region. MM of the head and neck occurs in 8–10% of all head and neck melanomas. It most commonly affects the mucosa of the nasal cavity and paranasal sinuses (75%), followed by the oral cavity mucosa (25%). A family history and the presence of mucosal nevi are associated with the occurrence of MM. Inhaled and dietary carcinogens are also linked to the development of sinonasal melanoma, much like other malignancies of the nasal cavity. Overexpression of the C-KIT gene is found in more than 80% of all primary mucosal melanomas, with somatic mutations in 10–30% of cases. The presence of these genetic alterations is also reflected in recent clinical studies of specific gene inhibitors that have proven efficiency in the systemic therapy of melanoma. There are various treatment modalities for MM. Surgical therapy involves en bloc surgical resection with a macroscopically visible and palpable mucosal margin of 1.5–2 cm. Partial resection of the maxilla may be considered if it ensures adequate tumor-free margine. Because of its rarity, outcome data for locally advanced head and neck MM is limited and primarily derived from retrospective studies with small case numbers. This review aims to update and summarize findings from clinical trials, prospective observational studies, and retrospective studies, while also exploring future directions for multimodal treatment approaches in this area.
Stiffness Perception Analysis in Haptic Teleoperation with Imperfect Communication Network
Authors: Park Yonghyun , Ju Chanyoung , Son Hyoung Il
Published: February 2025

Incomplete communication networks (e.g., time delay and packet loss/switching) in haptic interaction and remote teleoperation systems can degrade both user performance and system stability. In this study, we hypothesized that human operator performance would decrease monotonically as network imperfections worsened. To test this hypothesis, we conducted two psychophysical experiments measuring the just-noticeable difference (JND), point of subjective equality (PSE), and perception time under varying conditions of packet separation time and packet loss. Our findings show that increasing packet separation time significantly elevated both JND and PSE, indicating a poorer discrimination ability and a systematic bias toward perceiving the environment as stiffer. By contrast, packet loss rates of up to 75% had no significant impact on perceptual performance, suggesting that, at sufficiently high sampling rates, human operators can compensate for substantial data loss. Overall, the results underscore that packet separation time, rather than packet loss, is the dominant factor affecting perceptual performance in haptic teleoperation.
Resume2Vec: Transforming Applicant Tracking Systems with Intelligent Resume Embeddings for Precise Candidate Matching
Authors: Bevara Ravi Varma Kumar , Mannuru Nishith Reddy , Karedla Sai Pranathi , Lund Brady , Xiao Ting , Pasem Harshitha , Dronavalli Sri Chandra , Rupeshkumar Siddhanth
Published: February 2025

Conventional Applicant Tracking Systems (ATSs) encounter considerable constraints in accurately aligning resumes with job descriptions (JD), especially in handling unstructured data and intricate qualifications. We provide Resume2Vec, an innovative method that utilizes transformer-based deep learning models, including encoders (BERT, RoBERTa, and DistilBERT) and decoders (GPT, Gemini, and Llama), to create embeddings for resumes and job descriptions, employing cosine similarity for evaluation. Our methodology integrates quantitative analysis via embedding-based evaluation with qualitative human assessment across several professional fields. Experimental findings indicate that Resume2Vec outperformed conventional ATS systems, achieving enhancements of up to 15.85% in Normalized Discounted Cumulative Gain (nDCG) and 15.94% in Ranked Biased Overlap (RBO) scores, especially within the mechanical engineering and health and fitness domains. Although conventional the ATS exhibited slightly superior nDCG scores in operations management and software testing, Resume2Vec consistently displayed a more robust alignment with human preferences across the majority of domains, as indicated by the RBO metrics. This research demonstrates that Resume2Vec is a powerful and scalable method for matching resumes to job descriptions, effectively overcoming the shortcomings of traditional systems, while preserving a high alignment with human evaluation criteria. The results indicate considerable promise for transformer-based methodologies in enhancing recruiting technology, facilitating more efficient and precise candidate selection procedures.
Estimation of Uncertain Parameters in Single and Double Diode Models of Photovoltaic Panels Using Frilled Lizard Optimization
Authors: Dal Süleyman , Sezgin Necmettin
Published: February 2025

Renewable energy sources are increasingly crucial for sustainable development. Photovoltaic (PV) systems, which convert solar energy into electricity, offer an environmentally friendly solution. Enhancing energy efficiency and minimizing environmental impacts in these systems heavily rely on parameter optimization. In this study, the Frilled Lizard Optimization (FLO) algorithm is proposed as a novel approach, integrating the newton-raphson method into the root mean square error (RMSE) objective function process to address nonlinear equations. Extensive analyses conducted on RTC France, STM6-40/36, and Photowatt PWP201 modules demonstrate the superior performance of the FLO algorithm using MATLAB R2022a software with Intel(R) Core(TM) i7-7500U CPU@ 2.70GHz 2.90 GHz 8 GB RAM. The RMSE values were calculated as 0.0030375 and 0.011538 for SDM and DDM in the RTC France dataset, 0.012036 for the STM6-40/36 dataset and 0.0097545 for the Photowatt-PWP201 dataset, respectively, indicating significantly lower error margins compared to other optimisation methods. Additionally, comprehensive evaluations were carried out using error metrics such as individual absolute error (IAE), relative error (RE) and mean absolute error (MAE), supported by detailed graphical representations of measured and predicted parameters. Current-voltage (I-V) and power-voltage (P-V) characteristic curves, as well as convergence behaviors, were systematically analyzed. This study introduces an innovative and robust solution for parameter optimization in PV systems, contributing to both theoretical and industrial applications.
Micro-Electro-Mechanical Systems-Based Devices for Determining Natural Gas Calorific Value and Measuring H2 Content in Hydrogenated Gaseous Fuels
Authors: Knapkiewicz Pawel
Published: February 2025

This article presents advancements in using Micro-Electro-Mechanical Systemsbased (MEMS-based) devices for measuring the calorific value and hydrogen content in hydrogenated gaseous fuels, such as natural gas. As hydrogen emerges as a pivotal clean energy source, blending it with natural gas becomes essential for a sustainable energy transition. However, precise monitoring of hydrogen concentrations in gas distribution networks is crucial to ensure safety and reliability. Traditional methods like gas chromatography and mass spectrometry, while accurate, are often too complex and costly for real-time applications. In contrast, MEMS technology offers innovative, cost-effective alternatives that exhibit miniaturization, ease of installation, and rapid measurement capabilities. The article discusses the development of a novel MEMS thermal conductivity detector (TCD) and a new ionization spectrometer with an optical readout, both of which enable accurate assessment of hydrogen content and calorific values in natural gas. The TCD has demonstrated a 3% uncertainty in calorific value measurement and an impressive accuracy in determining hydrogen concentrations ranging from 2% to 25%. The research detailed in this article highlights the feasibility of integrating these MEMS devices into existing infrastructure, paving the way for efficient hydrogen monitoring in real-world applications. Moreover, preliminary findings reveal the potential for robust online process control, positioning MEMS technology as a transformative solution in the future of energy measurement. The ongoing innovations could significantly impact residential heating, industrial processes, and broader energy management strategies, facilitating a sustainable transition to hydrogen-enriched energy systems.
A Universal Highly Concentrated Electrolyte for Improved Cycling Stability in Li(Ni1-x-yMnxCoy)O2-NMC-Based Batteries
Authors: Lim Jun Ji Nicholas , Cai Yi , Srinivasan Madhavi
Published: February 2025

While 1 M LiPF6 has been widely adopted as the standard electrolyte in current LIBs, its chemical instability has reduced the battery’s cycling stability by, for instance, accelerating the dissolution of transition metals from electrode materials, particularly in high-voltage cathodes. Lithium bis(fluorosulfonyl)imide (LiFSI) has emerged as a promising alternative salt for next-generation high-voltage energy-dense LIB electrolytes. However, despite extensive research, the optimal concentration and formulation of LiFSI remain unresolved, with variations typically tested across different Li(Ni1-x-yMnxCoy)O2 (NMC) series cathodes. Herein, 6:4.5:8.3 LiFSI/EC/DMC (in molar ratio) is proposed as a universal electrolyte for high-voltage NMC series cathodes. The 6:4.5:8.3 LiFSI/EC/DMC electrolyte decomposes to form a uniform cathode–electrolyte interface with abundant inorganic species, resulting in a lower interface resistance. By adopting the 6:4.5:8.3 LiFSI/EC/DMC electrolyte, NMC series Li-ion half-cells are all able to stably cycle up to 200 cycles at a cut-off voltage of 4.4 V. Especially for high Ni content (NMC 811) cathode, the capacity retention was improved from 43.6% to 87.5% when charged to 4.4 V at 1C rate. This work provides a feasible universal electrolyte formulation for developing next-generation high-voltage LIBs.
Gas Production and Storage Using Hydrates Through the Replacement of Multicomponent Gases: A Critical Review
Authors: Zhu Zhiyuan , Zhao Xiaoya , Wang Sijia , Jiang Lanlan , Dong Hongsheng , Lv Pengfei
Published: February 2025

With the continuous growth of global energy demand and the gradual depletion of traditional fossil energy reserves, natural gas hydrates have attracted widespread attention as a potential clean energy source due to their vast reserves and wide distribution. Although various extraction methods, including depressurization, thermal stimulation, chemical inhibitors, and displacement methods, have been proposed, there are still challenges, such as low extraction efficiency, poor sustainability, and high costs, making it difficult to achieve large-scale engineering applications. Among these, the use of gases such as CO2 for displacement extraction of natural gas hydrates can both develop hydrate resources and sequester CO2, achieving a win–win situation for resource development and greenhouse gas reduction. This paper provides a detailed review of the multi-gas displacement extraction technology for natural gas hydrates, systematically summarizes the latest progress in thermodynamic and kinetic studies, analyzes the technical advantages and feasibility of combining displacement methods with traditional techniques, and explores the effects of multi-gas mixtures, such as N2, CO2, and H2, and their ratios on hydrate extraction efficiency. Finally, this paper summarizes the technical challenges faced by displacement extraction methods for hydrates and offers future research directions to promote the development of multi-gas displacement technology for natural gas hydrates.
Experimental Study and Reaction Pathway Analysis of Solvothermal Directional Conversion of Pyrolysis Crude Oil to Liquid Fuel
Authors: Wei Qi , Luo Zhongyang , Qian Qian , Shi Jingkang , Miao Feiting
Published: February 2025

The high viscosity and oxygen content of pyrolysis crude oil hinder the advancement of pyrolysis technology. To address the issue, this study conducted hydrodeoxygenation upgrading experiments on pyrolysis crude oil using hydrothermal directional conversion. A variable analysis was performed to assess the differences in upgrading effects based on the active metal (Ru, Pt) and the supports (activated carbon, Nb2O5, MgO) of the supported catalyst, and further investigations were conducted on the catalyst with bimetallic doping modification. Optimal reaction conditions were determined by adjusting the reaction temperature. Additionally, directional conversion studies of model compounds were carried out to elucidate the reaction pathway. The results indicated that the Pt/MgO catalyst achieved the highest yield of stable and combustible compounds (hydrocarbons, alcohols, ethers, esters, and ketones), with a yield of 17.8 wt%. Upon modification with Ni doping, the yield increased by 49.5%. The upgrading effect improved with an increase in reaction temperature, and the yield of target compounds was 26.7 wt% at 290 °C, with an energy conversion rate of 72.6% and a selectivity of 75.8%. Moreover, the physicochemical properties of the upgraded oil were similar to those of ethanol. All three model compounds underwent 100% conversion. This study provides both experimental support and a theoretical foundation for the further development of biomass conversion technology.
Reliability Evaluation of Improved Sampling Method for Mechanical Test of Cable Insulation
Authors: Lee Seung-Won , Choe Jin-Wook , Kwon Ik-Su , Lim Jin-Seok , Park Byung-Bae , Kim Hae-Jong
Published: February 2025

Underground and submarine power cables are subjected to mechanical stress during installation and operation, which degrades the cable insulation and reduces the reliability of power transmission. Therefore, tests that can evaluate the mechanical properties of power cable insulation are very important. The purpose of this paper is to introduce an improved sampling method for the test sample, the peeling, for mechanical testing of power cable insulation and to evaluate the reliability of the method. The influence of the sampling method of the test sample on the mechanical property values was analyzed. The tensile strength and elongation of XLPE (cross-linked polyethylene) and PP (polypropylene) insulation prepared by the slice method and the peeling method were measured, and the surface of the test samples according to the sampling methods was photographed by SEM. The results show that the mechanical property of the cable insulation increased by more than 10% when the improved peeling method was used, and the precision of the peeling method was relatively better. The SEM analysis showed that the surface of the sliced test sample was rougher than the peeled test sample and was physically damaged. Therefore, the high reliability of the peeling method for mechanical testing of cable insulators was demonstrated.
A Comparative Study Between Synchrophasor-Measurement-Based Linear and Nonlinear State Estimation in Power Systems
Authors: Aljazaeri Ali , Toman Petr , Muhayimana Obed
Published: February 2025

The evolution of phasor measurement units (PMUs) marked a significant development in the field of electrical engineering. The integration of PMU-based linear state estimators or the augmentation of SCADA measurements with PMU measurements has emerged as a promising solution to address the limitations of conventional state estimation. The utilization of PMU measurements has been demonstrated to effectively address measurement errors, leading to the precise determination of the system’s state within a single iteration. This article provides a comprehensive discussion of both linear and nonlinear state estimation computational processes. A comparative analysis is conducted to assess their performance. PMU-based state estimator models are proposed based on different PMU locations and are further examined under abnormal conditions. The results are compared with the simulated results from a Simulink PSCAD model of the IEEE 14-bus system to ensure validation. The test results demonstrated that the proposed models outperformed the conventional model in terms of robustness and accuracy. The estimated and simulated states matched during both normal and abnormal conditions, demonstrating the model’s capability to track sudden changes in voltage profiles. This article promotes further investigations to develop new control and protection functions using this model.
Beyond Firewall: Leveraging Machine Learning for Real-Time Insider Threats Identification and User Profiling
Authors: Qawasmeh Saif Al-Dean , AlQahtani Ali Abdullah S.
Published: February 2025

Insider threats pose a significant challenge to organizational cybersecurity, often leading to catastrophic financial and reputational damages. Traditional tools such as firewalls and antivirus systems lack the sophistication needed to detect and mitigate these threats in real time. This paper introduces a machine learning-based system that integrates real-time anomaly detection with dynamic user profiling, enabling the classification of employees into categories of low, medium, and high risk. The system was validated using a synthetic dataset, achieving exceptional accuracy across machine learning models, with XGBoost emerging as the most effective.
CORES: Context-Aware Emotion-Driven Recommendation System-Based LLM to Improve Virtual Shopping Experiences
Authors: Lakehal Abderrahim , Alti Adel , Annane Boubakeur
Published: February 2025

In today’s business landscape, artificial intelligence (AI) plays a pivotal role in shopping processes and customization. As the demand for customization grows, virtual reality (VR) emerges as an innovative solution to improve users’ perception and decision making in virtual shopping experiences (VSEs). Despite its potential, limited research has explored the integration of contextual information and emotions in VR to deliver effective product recommendations. This paper presents CORES (context-aware emotion-driven recommendation system), a novel approach designed to enrich users’ experiences and to support decision making in VR. CORES combines advanced large language models (LLMs) and embedding-based context-aware recommendation strategies to provide customized products. Therefore, emotions are collected from social platforms, and relevant contextual information is matched to enable effective recommendation. Additionally, CORES leverages transformers and retrieval-augmented generation (RAG) capabilities to explain recommended items, facilitate VR visualization, and generate insights using various prompt templates. CORES is applied to a VR shop of different items. An empirical study validates the efficiency and accuracy of this approach, achieving a significant average accuracy of 97% and an acceptable response time of 0.3267s in dynamic shopping scenarios.
Effects of Different Pretreatments on Wheat Bran and Its Arabinoxylan Obtained by Sequential Extraction with Dilute Alkali and Alkali–Urea Mixture
Authors: Liu Axiang , Zhang Shengjie , Wang Wentao , Hou Hanxue , Dai Yangyong , Li Cheng , Zhang Hui
Published: February 2025

Arabinoxylan (AX), an abundant and highly valuable component in wheat bran, has its structure and function influenced by the extraction method. A two-step extraction method, involving sequential extraction with a dilute alkali followed by a concentrated alkali–urea mixture, was employed to extract AX from wheat bran. This approach aimed to obtain AX with a high phenolic acid content while achieving a relatively high extraction yield. The dilute alkali extraction could effectively retain the phenolic acid content in the AX extract (≤89 μg/g). However, its yield and sugar content were relatively low. In contrast, the alkali–urea extraction could achieve a relatively high yield (≤55%) and sugar content (≤75%). Different pretreatments (defatting, deproteinization, and delignification) were performed before extraction, causing significant changes to the chemical composition and cell wall structural characteristics of destarched wheat bran, which, in turn, affected the yield and composition of the AX extracts. Deproteinization effectively increased the sugar content, phenolic acid content, and overall yield of the extracts. Different pretreatment and extraction methods significantly affected the DPPH radical scavenging rate and Fe2+ chelating rate of the AX extracts but had little impact on the ABTS radical scavenging rate. The antioxidant activity of AX extracted using alkali–urea was unexpectedly higher than that extracted using a dilute alkali. This suggests that the antioxidant activity of AX does not entirely depend on its phenolic acid content but is influenced by various other factors.
Experimental Study on the Mechanical Properties and Fractal Characteristics of Gas-Containing Coal Under Cyclic Loading
Authors: Zou Peng , Wang Lei , Yuan Anying , Fan Hao , Liu Huaiqian
Published: February 2025

As mining progresses, complexities arise, leading to potential coal-rock gas dynamic disasters triggered by mining disturbances. These dynamic phenomena are influenced by factors such as loading mode, coal properties, and the presence of gas. To gain a comprehensive understanding of the mechanical properties, deformation, and failure characteristics of gas-containing coal under cyclic loading, we conducted uniaxial compression tests. These tests varied in loading frequencies, amplitudes, and durations. By analyzing the peak stress variation of gas-containing coal and utilizing digital image correlation (DIC) technology, we captured the deformation characteristics of the loaded coal surface. Following the tests, we examined the fragmentation degree of gas-containing coal under different cyclic loading using fractal theory. This involved screening and crushing samples to assess the impact of varying loading on coal fragmentation. The results showed that peak stress is positively correlated with loading frequency and negatively correlated with loading amplitude and the number of cycles. Cyclic loading significantly affects the surface deformation morphology of gas-containing coal, and there is a correlation between the stress level of the coal sample and its surface deformation, with the formation and development of cracks corresponding to the stress level. Fractal theory can analyze the crushing characteristics of materials and quantitatively characterize their degree of crushing, and the fractal dimension is closely related to the mode of cyclic loading and comprehensively reflects various experimental factors. The results of our study aim to provide insights that can guide the prevention and control of coal mine dynamic disasters.
Methane–Natural Clay Interfacial Interactions as Revealed by High-Pressure Magic Angle Spinning (MAS) Nuclear Magnetic Resonance (NMR) Spectroscopy
Authors: Ok Salim , Sheets Julia M. , Welch Susan A. , Cole David R.
Published: February 2025

The current investigation aims to offer fundamental, molecular- to microscopic-level descriptions of methane gas inside natural source clay minerals. Texas montmorillonite (STx-1), Georgia kaolinite (KGa-2), and Ca2+-saturated Texas montmorillonite (Ca-STx-1, Ca-bentonite) were utilized as subsurface model clay minerals for elucidating nano-confinement behaviors of 13C-labeled methane gas. High-pressure magic angle spinning (MAS) nuclear magnetic resonance (NMR) was used to describe the interactions between methane and the clays by varying temperature and pressure. Proton-decoupled 13C-NMR spectra were acquired at 28.2 bar at 307 K, 32.6 bar at 346 K, 56.4 bar at 307 K, 65.1 bar at 346 K, 112.7 bar at 307 K, and 130.3 bar at 346 K. In the pure state, no significant thermal effect on the behavior of methane was observed. However, there was a perceptible variation in the chemical shift position of confined methane in the mixtures with the clays up to 346 K. Conversely, the 13C-NMR chemical shift of methane altered by varying pressure in a pure state, and the mixtures with clays, attributed to the interaction of methane with the clay surfaces or the nanopore network of the clay–silica mixed phase. Pressure-induced shifts in methane peak positions were observed: 0.25 ppm (28.2–56.4 bar) and 0.47 ppm (56.4–112.3 bar) at 307 K. For methane in a montmorillonite mixture, shifts were 0.32 ppm for bulk-like methane and 0.20 ppm for confined methane under similar conditions. At 346 K, increasing pressure from 65.1 to 130.3 bar caused shifts exceeding 0.50 ppm, with bulk-like methane showing a 0.64 ppm shift and confined methane a 0.57 ppm shift. There was only one 13C-NMR methane peak in the mixture with either kaolinite (KGa-2) or Ca-bentonite with line broadening compared to that of pure methane. Still, two peaks were observed in the mixture with STx-1, explained by the imbibition and mobility of methane in the pore network.
Digital Health for Equitable Rheumatic Care: Integrating Real-World Experiences to Guide Policy Pathways
Authors: Santosa Anindita , Li James Weiquan , Tan Tze Chin
Published: February 2025

Background/Objectives: Digital health technologies show promise in improving rheumatic disease management and reducing healthcare access disparities globally. This paper examines how electronic health records, telemedicine, apps, and wearable devices are used in rheumatic care across different economic settings. Methods: The study evaluates digital health technology implementation and outcomes in high-income versus low- and middle-income countries (LMICs). Results: Digital health technologies demonstrate improvements in disease monitoring, treatment adherence, and doctor-patient communication, though impact varies by region. Key barriers include poor infrastructure, limited tech literacy, and the digital divide, particularly affecting LMICs. The proposed evidence-based framework recommends strategic investments in digital infrastructure, healthcare system integration, and professional training to address these challenges. Conclusions: Implementation of digital health technologies, guided by targeted interventions and regional adaptations, can effectively reduce global disparities in rheumatic care. Success requires sustained commitment to addressing infrastructure and literacy barriers while ensuring equitable access across all economic settings.
Leaf Water Storage Capacity Among Eight US Hardwood Tree Species: Differences in Seasonality and Methodology
Authors: Scavotto Natasha , Siegert Courtney M. , Alexander Heather D. , Varner J. Morgan
Published: February 2025

Canopy hydrology and forest water inputs are directly linked to the physical properties of tree crowns (e.g., foliar and woody surfaces), which determine a tree’s capacity to intercept and retain incident rainfall. The changing forest structure, notably the decline of oak’s (Quercus) dominance and encroachment of non-oak species in much of the upland hardwood forests of the eastern United States, challenges our understanding of how species-level traits scale up to control the forest hydrologic budget. The objective of this study was to determine how the leaf water storage capacity varies across species and canopy layers, and how these relationships change throughout the growing season. We measured the leaf water storage capacity of overstory and midstory trees of native deciduous oaks (Q. alba, Q. falcata, Q. stellata) and non-oak species (Carya tomentosa, Acer rubrum, Ulmus alata, Liquidambar styraciflua, Nyssa sylvatica) using two methods (water displacement and rainfall simulation). Overstory Q. alba leaves retained 0.5 times less water per unit leaf area than other overstory species (p < 0.001) in the early growing season, while in the late growing season, C. tomentosa leaves had the lowest storage capacity (p = 0.024). Quercus falcata leaves displayed a minimal change in storage between seasons, while Q. alba and Q. stellata leaves had higher water storage in the late growing season. Midstory U. alata leaves had 3.5 times higher water storage capacity in the early growing season compared to all the other species (p < 0.001), but this difference diminished in the late growing season. Furthermore, the water storage capacities from the simulated rainfall experiments were up to two times higher than those in the water displacement experiments, particularly during the early growing season. These results underscore the complexity of leaf water storage dynamics, the methodology, and the implications for forest hydrology and species interactions. Broader efforts to understand species-level controls on canopy water portioning through leaf and other crown characteristics are necessary.
Exploring Climate and Air Pollution Mitigating Benefits of Urban Parks in Sao Paulo Through a Pollution Sensor Network
Authors: Connerton Patrick , Nogueira Thiago , Kumar Prashant , de Fatima Andrade Maria , Ribeiro Helena
Published: February 2025

Ambient air pollution is the most important environmental factor impacting human health. Urban landscapes present unique air quality challenges, which are compounded by climate change adaptation challenges, as air pollutants can also be affected by the urban heat island effect, amplifying the deleterious effects on health. Nature-based solutions have shown potential for alleviating environmental stressors, including air pollution and heat wave abatement. However, such solutions must be designed in order to maximize mitigation and not inadvertently increase pollutant exposure. This study aims to demonstrate potential applications of nature-based solutions in urban environments for climate stressors and air pollution mitigation by analyzing two distinct scenarios with and without green infrastructure. Utilizing low-cost sensors, we examine the relationship between green infrastructure and a series of environmental parameters. While previous studies have investigated green infrastructure and air quality mitigation, our study employs low-cost sensors in tropical urban environments. Through this novel approach, we are able to obtain highly localized data that demonstrates this mitigating relationship. In this study, as a part of the NERC-FAPESP-funded GreenCities project, four low-cost sensors were validated through laboratory testing and then deployed in two locations in São Paulo, Brazil: one large, heavily forested park (CIENTEC) and one small park surrounded by densely built areas (FSP). At each site, one sensor was located in a vegetated area (Park sensor) and one near the roadside (Road sensor). The locations selected allow for a comparison of built versus green and blue areas. Lidar data were used to characterize the profile of each site based on surrounding vegetation and building area. Distance and class of the closest roadways were also measured for each sensor location. These profiles are analyzed against the data obtained through the low-cost sensors, considering both meteorological (temperature, humidity and pressure) and particulate matter (PM1, PM2.5 and PM10) parameters. Particulate matter concentrations were lower for the sensors located within the forest site. At both sites, the road sensors showed higher concentrations during the daytime period. These results further reinforce the capabilities of green–blue–gray infrastructure (GBGI) tools to reduce exposure to air pollution and climate stressors, while also showing the importance of their design to ensure maximum benefits. The findings can inform decision-makers in designing more resilient cities, especially in low-and middle-income settings.
An MGRN1-Based Biomarker Combination Accurately Predicts Melanoma Patient Survival
Authors: Sánchez-Beltrán José , Soler Díaz Javier , Herraiz Cecilia , Olivares Conchi , Cerdido Sonia , Cerezuela-Fuentes Pablo , García-Borrón José Carlos , Jiménez-Cervantes Celia
Published: February 2025

With ever-increasing incidence and high metastatic potential, cutaneous melanoma is the deadliest skin cancer. Risk prediction based on the Tumor-Node-Metastasis (TNM) staging system has medium accuracy with intermediate IIB-IIIB stages, as roughly 25% of patients with low-medium-grade TNM, and hence a favorable prognostic, undergo an aggressive disease with short survival and around 15% of deaths arise from metastases of thin, low-risk lesions. Therefore, reliable prognostic biomarkers are required. We used genomic and clinical information of melanoma patients from the TCGA-SKCM cohort and two GEO studies for discovery and validation of potential biomarkers, respectively. Neither mutation nor overexpression of major melanoma driver genes provided significant prognostic information. Conversely, expression of MGRN1 and the melanocyte-specific genes MLANA, PMEL, and TYRP1 provided a simple 4-gene signature identifying with high-sensitivity (>80%), low-medium TNM patients with adverse outcomes. Transcriptomic analysis of tumors with this signature, or from low-medium-grade TNM patients with poor outcomes, revealed comparable dysregulation of an inflammatory response, cell cycle progression, and DNA damage/repair programs. A functional analysis of MGRN1-knockout cells confirmed these molecular features. Therefore, the simple MGRN1-MLANA-PMEL-TYRP1 combination of biomarkers complemented TNM staging prognostic accuracy and pointed to the dysregulation of immunological responses and genomic stability as determinants of a melanoma outcome.