bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficacy of Fascial Manipulation on Pain, Function, and Neck Disability in Chronic Non-Specific Neck Pain: A Randomized Controlled Trial
Authors: Zhang Peng , Zhao Xiaoxiao , Guo Jianye , Ma Ming , Fan Youqiang , Stecco Carla
Published: February 2025

Background: Chronic Non-Specific Neck Pain (CNSNP) is a common musculoskeletal issue that impairs daily activities. This study investigates the effects of Fascial Manipulation (FM), a technique targeting fasciae, on pain and neck function in individuals with CNSNP. Methods: Fifty-two participants diagnosed with CNSNP were randomly assigned to two groups: Group A (n=26) received FM in addition to routine physical therapy, while Group B (n=26) received only routine therapy. Pain (VAS), range of motion (ROM), and maximal voluntary isometric contraction (MVIC) for cervical flexion and extension were assessed at baseline (T0), post-treatment (T1), and after four weeks (T2). The Neck Disability Index (NDI) was measured at T0 and T2. Three months post-treatment, VAS and NDI were reassessed through follow-ups. Results: Both groups showed significant improvements in VAS and ROM at T1 and T2 (P < 0.01), with Group A demonstrating superior outcomes (P < 0.01). For MVIC, Group A showed significant changes at T1 and T2, while Group B had notable changes only at T2. NDI scores improved significantly for both groups at T2 (P < 0.01), with Group A outperforming Group B. At three-month follow-up, Group A maintained significant improvements (P < 0.01), while Group B did not (P > 0.05). Conclusion: FM significantly improves pain and neck function in CNSNP patients, with sustained benefits three months post-treatment.
Investigation of Biodegradation and Biocompatibility of Chitosan-Bacterial Cellulose Composite Scaffold for Bone Tissue Engineering Applications
Authors: Yodsanga Somchai , Poeaim Supattra , Chantarangsu Soranun , Swasdison Somporn
Published: February 2025

Developing scaffolds with a three-dimensional porous structure and adequate mechanical properties remains a key challenge in tissue engineering of bone. These scaffolds must be biocompatible and biodegradable to effectively support osteoblastic cell attachment, proliferation, and differentiation. This study successfully fabricated a chitosan-bacterial cellulose (CS-BC) composite scaffold using the solvent casting/particle leaching (SCPL) technique, with NaOH/urea solution as the solvent and sodium chloride crystals as the porogen. The scaffold exhibited a well-distributed porous network with pore sizes ranging from 300 to 500 µm. Biodegradation tests in PBS containing lysozyme revealed a continuous degradation process, while in vitro studies with pre-osteoblastic MC3T3-E1 cells demonstrated excellent cell attachment, as observed through SEM imaging. The scaffold also promoted cell proliferation, as indicated by increased OD values in the MTT assay, and enhanced ALP activity and upregulated expression of osteogenic-related genes. These findings suggest that the CS-BC composite scaffold, fabricated using the SCPL method, holds great potential as a candidate for bone tissue engineering applications.
Revolutionizing Energy: A Brief Overview of Varied Fuel Cell Technologies and Their Transformative Potential
Authors: Ahmmad Shoaib , Hossain Md. Imam
Published: February 2025

Energy storage and conversion is a critical connection between the stages of energy generation and use. Conventional fossil fuels are a natural and unsustainable energy storage medium with finite reserves and infamous environmental concerns, necessitating a better alternative for storing and using green and renewable energies in the future. Fuel cells produce heat and electricity as a result of the electrochemical process that occurs when oxygen and hydrogen combine to make water. A possible method of supplying energy to rural regions without connection to the public grid or where the expense of wiring and transmitting power is prohibitive is through the use of fuel cells. Furthermore, it has grown in popularity because of the desire for clean energy, the scarcity of fossil fuel supplies, and the ability to generate electricity without the usage of any moving mechanical components. Furthermore, fuel cells can be used as an energy source in applications that require consistent electrical power, such as distributed systems, power generation facilities, and uninterruptible power supplies (UPS). The current study analyses the fundamental structure, function, and applications of the numerous fuel cell technologies that are now available. In this study, we focus on current breakthroughs in fuel cell technology.
Carbon Tax Implementation in Transportation Sector to Encourage Low Carbon Emission
Authors: Pranita Diaz , Sarjana Sri
Published: February 2025

The implementation of carbon tax in the transportation sector aims to reduce carbon emissions and encourage the transition to sustainable mobility amidst increasing urbanization. In determining an effective carbon tax rate, economic, environmental, and social factors need to be considered, including the social cost of carbon, emission reduction target, economic impact, revenue for environmental programs, and social justice and equity. The social cost of carbon provides an estimate of the economic and social damage impacts of carbon emissions, so that the tax rate reflects comparable costs. The emission reduction target is consistent with national commitments and focuses on mitigating climate change in urban areas. The economic impact considers the effect of the carbon tax on energy prices, the competitiveness of the transportation sector, and the cost of living in Jakarta. Carbon tax revenues can be allocated to city environmental programs, such as the development of green transportation infrastructure and the integration of renewable energy. The social equity aspect ensures that this policy does not burden vulnerable groups and supports inclusiveness in access to transportation. In Jakarta, a carbon tax policy can facilitate the use of low-emission vehicles, accelerate the transition to public transportation and electric vehicles, and reduce dependence on fossil fuels. This approach is expected to create a more environmentally friendly urban transportation system, support the achievement of climate targets, and improve the overall quality of life in Jakarta.
The Sensory Adaptations and Behavior of Quetzalcoatlus: Exploring the Ecology and Survival Strategies of the Giant Pterosaur
Authors: Hu Tyler
Published: February 2025

Quetzalcoatlus, a giant pterosaur from the Late Cretaceous period, stands as one of the largest flying animals ever known, with a wingspan exceeding 10 meters. Its sensory adaptations, such as acute vision and olfactory capabilities, played crucial roles in its behavior and ecological success. This literature review explores how these sensory adaptations helped Quetzalcoatlus thrive in a competitive environment. Paleontological evidence indicates that Quetzalcoatlus possessed advanced visual acuity, allowing it to spot prey from great heights, while its olfactory structures likely aided in detecting food sources and environmental changes. Beyond its sensory capabilities, this review investigates the behavior of Quetzalcoatlus by examining its foraging strategies and flight patterns. The combination of its massive wingspan and efficient flight mechanics enabled it to soar for long distances, likely exploiting both terrestrial and aquatic prey. Comparisons with modern birds and biomechanical analyses suggest that Quetzalcoatlus relied on both soaring flight and opportunistic hunting, making it a versatile predator in the Late Cretaceous ecosystem.
Association Between Academic, Initial Licensure, Employment Factors, and NCLEX-RN Performance of Philippine-Educated Nurses
Authors: Montegrico James , Chen Zhuo Job
Published: February 2025

The United States’ nursing shortage attracted internationally educated nurses (IENs) to take the National Council Licensure Examination–Registered Nurses (NCLEX-RN), which is required to practice nursing in the U.S. Philippine-educated nurses (PENs) comprised more than half of IENs in the U.S. nursing workforce. From 2002 to 2021, only 45.8% of 177,730 PENs passed the exam. Published studies investigating IEN NCLEX-RN performance are limited. This study addresses this gap in the literature. This study determined the association between academic, initial nursing licensure, and employment factors on PEN NCLEX-RN passing. A retrospective correlation research design was used to determine the association among the research variables. Participants were recruited through online nursing groups. Descriptive statistics compared characteristics of PEN who passed and failed the NCLEX on the first attempt. Chi-square and Fisher’s exact test were used to determine the association between the research variables. Initial nursing licensure and nursing workplace were significantly associated with PEN NCLEX-RN passing. Identifying unique PEN contextual characteristics is critical in helping them pass the NCLEX-RN. Findings provide input to educational and regulatory bodies to improve the NCLEX-RN individual outcomes and Philippine NCLEX-RN pass rates.
The Management of Tinnitus in Non-Surgical Cases of Otosclerosis by Oral Supplementation of Calcium and Fluoride – Our Experience in a Tertiary Care Unit in Romania
Authors: Osman Andrei , Ghenea Alice Elena , Zlatian Ovidiu Mircea , Boldeanu Lidia , Enache Irina , Georgescu Madalina Gabriela , Mogoanta Carmen Aurelia
Published: February 2025

Background and Objectives: Tinnitus management in otosclerosis is a significant clinical challenge, especially in patients who are ineligible or unwilling to undergo surgical treatment. While otosclerosis surgery may alleviate tinnitus, alternative non-surgical treatments are still being explored. This study evaluates the effects of oral calcium and fluoride supplementation on tinnitus severity in otosclerosis patients who opted for non-surgical management. Materials and Methods: A total of 128 otosclerosis patients with tinnitus were included in this study, which was conducted over a five-year period. Patients received Florical (Mericon Industries, Inc., USA), a calcium and fluoride supplement, and were monitored for three months. Tinnitus severity was assessed using the Tinnitus Handicap Inventory (THI) before and after supplementation. Results: Assessing patients by degree of tinnitus, we achieved a clinically significant reduction in THI scores (≥10 points) in patients with mild tinnitus, the moderate and severe degrees of tinnitus having a lower degree in tinnitus reduction. Conclusions: Oral calcium and fluoride supplementation appears to be a promising and safe non-surgical approach for tinnitus management in mild otosclerosis-related tinnitus. However, its efficacy diminishes as tinnitus severity increases.
Terrestrial Carbon Storage Estimation in Guangdong Province (2000–2021)
Authors: Wang Wei , Hu Yueming , Mao Xiaoyun , Zhang Ying , Tang Liangbo , Cai Junxing
Published: February 2025

(1) Terrestrial ecosystems are critical carbon sinks, and accurate assessment of their carbon storage is vital for understanding global carbon cycles and formulating climate change mitigation strategies.; (2)This study integrated vegetation indices, meteorological factors, land use data, soil/vegetation types, field sampling, and a convolutional neural network (CNN) model to estimate the carbon storage of terrestrial ecosystems in Guangdong Province; (3) Total carbon storage increased by 0.11 Pg from 2000 to 2021, with vegetation carbon gains (+0.19 Pg) offsetting soil carbon losses (-0.08 Pg), the latter primarily driven by reduced soil carbon in forest ecosystems; (4) Northern and eastern Guangdong exhibit high potential for enhancing carbon storage capacity, which is crucial for achieving regional carbon peaking and neutrality targets. Dataset: DOI number or link to the deposited dataset in cases where the dataset is published or set to be published separately. If the dataset is submitted and will be published as a supplement to this paper in the journal Data, this field will be filled by the editors of the journal. In this case, please make sure to submit the dataset as a supplement when entering your manuscript into our manuscript editorial system. Dataset License: license under which the dataset is made available (CC0, CC-BY, CC-BY-SA, CC-BY-NC, etc.)
An Encoder-Only Transformer Model for Depression Detection from Social Network Data: The DEENT Approach
Authors: Burbano Robinson Narvaez , Caicedo Oscar Mauricio , Astudillo Carlos Alberto
Published: February 2025

Depression is a common mental illness magnified by the COVID-19 pandemic. In this path, its early detection is pivotal for the public health systems. Various works have addressed depression detection in social network data. Nevertheless, they used data before the pandemic and did not exploit transformers’ architecture capabilities for realizing binary classification on extensive dimensional data. This paper introduces DEENT, an approach with a depression-oriented dataset built with BERT and K-means from a previous Twitter dataset labeled for sentiment analysis, and two models called DEENT-Generic and DEENT-Bert for classifying depressive and non-depressive tweets effectively. DEENT was evaluated extensively and compared to Random Forest, Support Vector Machine, XGBoost, and Recurrent and Convolutional Neural Networks. Results revealed that DEENT outperforms baseline models regarding accuracy, balanced accuracy, precision, recall, and F1-Score. We argue that these results are due to the DEENT leveraging the encoder-only transformer architecture and fine-tuning to detect depression in large Twitter data effectively. Therefore, we concluded that DEENT is a promising solution for detecting depressive and non-depressive tweets.
Evidence-Based Selection of Antiepileptic Drugs During Pregnancy: A Narrative Review of Safety and Efficacy
Authors: Shahi Uday Bir , Panthi Sandesh
Published: February 2025

Pregnancy is the period of time when a fetus develops inside a woman's uterus. When counting from the last menstrual cycle through delivery, a pregnancy typically lasts around 40 weeks, or slightly over 9 months. Pregnancy is divided into three trimesters, as described by healthcare professionals. First trimester: from conception to 12 weeks; second trimester: from 13 to 28 weeks; third trimester: from 29 to 40 weeks. Seizures are a defining feature of the illness, however not all seizures are caused by epilepsy, such as febrile seizures or seizures brought on by drugs. The multilevel categorization of epilepsies was developed to facilitate categorizing epilepsy in varied clinical contexts. There are three types of seizures: those with undetermined onset, generalized onset, and focal onset. The second level is epilepsy type, which introduces the new categories of generalized epilepsy, focal epilepsies, and unknown. A variety of seizure forms, including absence, myoclonic, atonic, tonic, and tonic-clonic seizures, can occur in generalized epilepsies. An epilepsy syndrome diagnosis comes in third place. An epilepsy syndrome is a collection of symptoms that includes seizure types, EEG patterns, and imaging characteristics that frequently co-occur. This review underwent a narrative evaluation, for which papers from the Cochrane library, PubMed, Google Scholar, and Web of Science were gathered. Epilepsy is treated with antiepileptic medications (AEDs). There is evidence that suggests some antiepileptic drugs (AEDs) increase the chance of congenital malformation and induce teratology. The risk of malformation is increased by medications including carbamazepine, phenobarbital, phenytoin, topiramate, and valproate, but not by lamotrigine, gabapentin, levetiracetam, oxcarbazepine, primidone, or zonisamide. Lacosamide, Eslicarbazepine, Clonazepam, Clobazam, and Rivaracetam did not either.
Void Reactivity Coefficient for Hybrid Reactor Cooled by Liquid Metal
Authors: Wojciechowski Andrzej
Published: February 2025

The negative value of void reactivity coefficient (V) is one of the most important passive safety properties for the operation of nuclear reactor. Herein, are presented calculated values of void reactivity coefficient for different geometries of reactors cooled by liquid lead (LFR) and sodium (SFR) with fuel U-238-Pu-239 and Th-232-U-233. The calculations were carried out for the reactors filled with either one or two types of fuel assemblies. The most interesting results are obtained for reactor filled with two different types of fuel assemblies (Hybrid reactor). The Hybrid reactor consists of central and peripheral types of fuel assemblies, using low enrichment fuel and high enrichment fuel, respectively. Both Hybrid reactors based on Uranium cycle (U-cycle) and Thorium cycle (Th-cycle) can maintain a negative value of void reactivity coefficient for wide range of reactor parameters. The calculation results of Hybrid reactor agree with experimental data from FBR-IME reactor.
From Foundations to Diagnosis: A Comprehensive Guide to Building Energy Analysis
Authors: Akbari Sevda
Published: February 2025

This paper presents a comprehensive review of methodologies for building energy analysis, simulation, and optimization, with a focus on improving energy efficiency and sustainability. It synthesizes research across various domains, including data-driven models, building performance simulations (BPS), infrared thermography (IRT), and innovative design approaches. The study underscores the significance of accurate energy prediction models and the impact of early-stage design interventions on long-term energy performance. Advanced technologies such as machine learning, artificial intelligence, and statistical analysis are examined for their role in enhancing energy assessments. A key highlight of this review is the critical role of IRT as a non-invasive diagnostic tool for detecting thermal anomalies, insulation defects, and energy inefficiencies. The integration of AI with IRT is discussed as a promising advancement for automating defect detection and improving building diagnostics. Additionally, the study explores emerging materials, including high-performance insulation and phase-change materials, which contribute to sustainable construction practices. Furthermore, the paper evaluates the role of smart building technologies, parametric design, and occupancy-driven energy management in optimizing energy use. The effectiveness of various energy forecasting models, including white-box, black-box, and grey-box approaches, is analyzed, demonstrating the strengths and limitations of each methodology. Despite significant progress in the field, research gaps remain in model calibration, data integration, and real-time energy monitoring. The study proposes future directions, such as enhancing hybrid modeling techniques, standardizing assessment methods, and leveraging big data analytics to refine energy performance predictions. This review serves as a valuable resource for researchers, policymakers, and industry professionals, bridging the gap between theoretical research and practical applications in sustainable building design and energy management.
Transforming Customer Experience Management with Real-Time Data Analytics
Authors: Barnabas Barnty , Johnson Joshua
Published: February 2025

This study explores the transformative role of real-time data analytics in customer experience management (CXM). As businesses strive to meet the growing demands of consumers for personalized, fast, and seamless services, real-time data analytics has emerged as a critical tool to enhance customer engagement, satisfaction, and retention. The purpose of this study is to examine how real-time data analytics impacts key aspects of CXM, including customer interactions, response times, and loyalty.The research adopts a mixed-methods approach, combining quantitative surveys and interviews with industry professionals across sectors such as retail, banking, telecommunications, and hospitality. The data collected from these sources were analyzed to assess the impact of real-time analytics on customer satisfaction, engagement, and operational efficiency.Key findings indicate that real-time data analytics leads to an 18% improvement in customer satisfaction, a 28% increase in engagement, and a 17% rise in retention rates. Additionally, customer response times were reduced by 75%, indicating a significant enhancement in service efficiency. Regression analysis revealed that real-time analytics accounted for 54% of the variance in customer satisfaction, further confirming its positive influence on CXM outcomes.In conclusion, the study underscores the importance of integrating real-time data analytics into customer experience management strategies. The findings suggest that businesses that adopt real-time analytics platforms can significantly improve customer interactions, responsiveness, and loyalty, positioning themselves for long-term success in a highly competitive market. The study recommends that organizations invest in real-time data analytics tools, focus on training employees, and ensure ethical data practices to maximize the benefits of this technology in transforming customer experiences.
Epidemiology and Genetic Characterization of Distinct Ebola Sudan outbreaks in Uganda
Authors: Branda Francesco , Ciccozzi Massimo , Scarpa Fabio
Published: February 2025

Sudan ebolavirus (SUDV) has caused multiple outbreaks in Uganda over the past two decades, leading to significant morbidity and mortality. The recent outbreaks in 2022 and 2025 highlight the ongoing threat posed by SUDV and the challenges in its containment. This study aims to characterize the epidemiological patterns and phylogenomic evolution of SUDV outbreaks in Uganda, identifying key factors influencing transmission and disease severity. We conducted a retrospective observational study analyzing epidemiological and genomic data from SUDV outbreaks in Uganda between 2000 and 2025. Epidemiological data were collected from official sources, including the Ugandan Ministry of Health and the World Health Organization, supplemented with reports from public health organizations. Genomic sequencing was performed on SUDV-positive samples to investigate viral evolution and identify genetic variations associated with pathogenicity and transmissibility. The 2022 outbreak involved 164 confirmed cases and a case fatality rate (CFR) of 33.5%, with significant geographic variation in case distribution. The 2025 outbreak, still ongoing, was first detected in Kampala, with evidence of nosocomial and community transmission. Phylogenomic analysis revealed the presence of two main genetic groups, representing Sudan and Uganda, respectively. The genetic variability of the Ugandan cluster is higher than that observed in Sudan, suggesting a greater expansion potential, which aligns with the current outbreak. Epidemiological findings indicate that human mobility, weaknesses in the health system, and delays in detection contribute to the amplification of the outbreak. Our findings underscore the importance of integrated genomic and epidemiological surveillance in understanding SUDV transmission dynamics. The recurrent emergence of SUDV highlights the need for improved outbreak preparedness, rapid response mechanisms, and international collaboration. Strengthening real-time surveillance and enhancing healthcare system resilience are critical to mitigating the impact of future outbreaks.
Modulating the Progression: Combined Effects of Magnesium Supplementation and Intermittent Fasting on Tau Hyperphosphorylation in Alzheimer’s Disease
Authors: Balaji Adithi , Swaminathan Sumuga
Published: February 2025

Alzheimer's disease (AD) is a neurodegenerative condition, often associated with aging and genetic hereditary, where profound modifiable risk factors are still being studied. AD is a progressive neurodegenerative disorder, with tau protein hyperphosphorylation playing a central role in its pathogenesis. Phosphatases (enzymes that remove phosphate groups from proteins) can counteract tau hyperphosphorylation, potentially slowing disease progression. Magnesium has been shown to activate phosphatases and reduce oxidative stress, suggesting it may help regulate tau phosphorylation. Similarly, intermittent fasting (IF) has been found to significantly increase Brain-Derived Neurotrophic Factor (BDNF) in animals, which may further enhance phosphatase activity, particularly protein phosphatase 2A (PP2A), involved in tau dephosphorylation. A randomized controlled trial will assign participants to one of four groups: a control group, an IF-only group, a magnesium-only group, and a combined magnesium + IF group. Primary outcomes might include changes in hyperphosphorylated tau levels, measured by ELISA in cerebrospinal fluid (CSF), and glucose variability, assessed via continuous glucose monitors (CGMs). This study aims to explore the combined effects of magnesium supplementation and IF on tau phosphorylation in individuals with early-stage AD. We hypothesize that it is likely both magnesium and IF, particularly in combination, will result in reduced tau phosphorylation and improved metabolic health. Previous studies of magnesium and IF corresponding to AD have been conducted on mice, but the exact correlation of these interventions in humans, their relation to phosphatase activity in TP, and how they complement each other are still yet to be investigated. This research could provide insights into dietary interventions as potential strategies for slowing AD progression.
Lidocaine Enhances Anti-Tumor Immune Responses by Reprogramming Tumor-Infiltrating Immune Cells in Gastric Cancer
Authors: Wu Yi-Ying , Chen Ming-Shan , Chen I-Chun , Wu Feng-Hsu , Liao Tsai-Ling , Wen Hsiao-Wei , Nielsen Brent L. , Liu Hung-Jen
Published: February 2025

Lidocaine, a local anesthetic, has been shown to modulate immune responses. This study examines its effects on cytokine production in peripheral blood mononuclear cells (PBMCs) from healthy donors and tumor-infiltrating immune cells (TIICs) from gastric cancer patients. PBMCs from healthy donors and TIICs from gastric cancer patients were treated with lidocaine. Cytokine production was assessed using flow cytometry and cytokine assays, with a focus on IFN-γ, IL-12, IL-10, TGF-β, and IL-35 levels. Cytotoxicity against primary gastric cancer cells (PGCCs) was also evaluated. Lidocaine inhibited IFN-γ production in CD8+ PBMCs and IL-12 in CD14+ PBMCs while increasing anti-inflammatory cytokines (IL-10, TGF-β, IL-35) in CD4+CD25+ and CD14+ cells. In TIICs, lidocaine enhanced IFN-γ and IL-12 production in CD8+ and CD14+ cells, while reducing IL-10, TGF-β, and IL-35 levels, promoting an M1-like phenotype in macrophages. Lidocaine also increased IFN-γ production and cytotoxicity in CD8+ TIICs via NF-κB activation. Importantly, lidocaine did not affect the viability of PBMCs, TIICs, or PGCCs at concentrations up to 1.5 mM. Lidocaine reprograms the tumor immune microenvironment, enhancing anti-tumor immune responses, suggesting its potential to modulate immune functions in gastric cancer.
The Intersection of Autonomic Dysfunction and Parkinson’s Disease: Insights into Neurogenic and Classical Orthostatic Hypotension
Authors: Pitton Rissardo Jamir , Khalil Ibrahim , Iyad Khalil , Dway Ali , Sayed Ahmed Serour Aya , Fornari Caprara Ana Leticia
Published: February 2025

Neurogenic Orthostatic hypotension (nOH) and classical orthostatic hypotension (OH) are prevalent non-motor manifestations of Parkinson’s disease (PD), affecting 5.7–64.9% of patients. They can significantly impact quality of life, increasing the risk of falls, cognitive decline, and functional impairment. The current manuscript aims to review the epidemiology, pathophysiology, diagnostic strategies, and management of nOH and OH in PD. External factors cause classical OH, whereas nOH is caused by impaired autonomic control. nOH in PD results from complex interactions between central and peripheral autonomic dysfunction, alpha-synuclein accumulation, baroreflex failure, and medication effects. Its prevalence increases with disease progression and age. Clinical evaluation remains the cornerstone of diagnosis, supported by specialized testing such as the active standing test, ambulatory blood pressure monitoring, and autonomic function assessments. Management requires a tailored approach, combining non-pharmacologic strategies—like fluid and salt intake optimization, compression garments, and physical counter-maneuvers—with pharmacologic treatments, including midodrine, droxidopa, and fludrocortisone. Emerging therapies and ongoing clinical trials offer promising avenues for future interventions. Early recognition and individualized management of OH are critical in PD care.
Is Artificial Intelligence a New Stakeholding Agent?
Authors: Moro Visconti Roberto
Published: February 2025

Corporate governance has been primarily concerned with  agency problems among human stakeholders. However, the rise of artificial intelligence (AI) is changing the dynamics of governance across the corporate ecosystem. AI has evolved from a passive tool to an autonomous entity, driving strategic decisions, streamlining enterprise processes, and upending traditional governance mechanisms. Though AI does not have intent like a human, its algorithms and decision-making processes are still susceptible to bias and opacity, which raises issues of ethics and accountability. The paper examines AI's changing role as a governance agent in the interaction with traditional corporate stakeholders and calls for adaptive governance frameworks. It illustrates the need for AI ethics committees, public disclosure requirements for algorithmic transparency, and mixed human-AI governance structures to support responsible corporate AI.
Duality of Navier-Stokes to a One-Dimensional System
Authors: Migdal Alexander
Published: February 2025

The Navier-Stokes (NS) equations describe fluid motion via a high-dimensional, nonlinear system of partial differential equations (PDEs). Despite their fundamental role, their behavior in turbulent regimes remains poorly understood, and their global regularity is an open Millennium Problem. Here, we show that the NS system can be transformed to a nonlinear equation for the momentum loop P→(θ,t), reducing the original problem in R3 to a one-dimensional problem. A key consequence is the No Explosion Theorem, which rules out finite-time singularities for stochastic initial conditions, suggesting a pathway to proving NS regularity for deterministic data. Additionally, we derive an exact solution of the momentum loop equation, the Euler ensemble, which describes the asymptotic state of decaying turbulence. This solution, validated by numerical and experimental data, replaces heuristic turbulence models with an analytically derived structure. While the Euler ensemble solves a specific boundary problem, its universality as an attractor remains an open question. By reducing NS to a nonlinear equation on S1, this work opens new pathways toward resolving turbulence and fluid mechanics’ fundamental challenges.
Enhancing E-Commerce and Logistics Management for Şölen: A Digital Transformation Approach
Authors: Ahmed Algaafari Hatem , Ruxshan Juhardeen Hammad , Muzaffar Arat Ahmed , Sadeq Al Kharraz Khaled , Mushtaq Mohsin , Weitao Feng , Ul Amin Noor
Published: February 2025

The modern business world demands responsiveness and adaptability, particularly in logistics and e-commerce. Şölen, as a leading Turkish candy company, is faced with order fulfillment, tracking, customer feedback, and inventory management issues that impede its efficiency and future growth opportunities. This paper outlines a digitalization strategy for Şölen's Malaysian business unit focusing on the incorporation of e-commerce, real-time delivery tracking, automated inventory management, and customer support enhancement. Through utilizing cloud-based technology, artificial intelligence, and GPS tracking systems, the study offers solutions for optimizing logistics, improving customer satisfaction, and raising the overall efficiency in operations. Utilizing these technologies will be expected to transform Şölen as a competitive player in the evolving global market.
Impact of Ultrasound Pretreatment and Temperature on Drying Kinetics and Quality Characteristics of Blood Orange: Comparison with Different Drying Methods
Authors: Yılmaz Damla , TEKIN-CAKMAK Zeynep Hazal , Karasu Salih
Published: February 2025

This study aimed to investigate the impact of ultrasonic pretreatment vacuum drying (UAVD) and temperature on drying kinetics and qualitative attributes of blood oranges, in comparison to several drying methods: hot air drying (HAD), vacuum drying (VD), and freeze drying (FD). The drying kinetics and modeling, total phenolic content (TPC), anti-oxidant capability (assessed using DPPH and ABTS tests), individual phenolic profiles, vitamin C concentration, and color factors were meticulously examined. The HAD, VD, and UAVD procedures were conducted at 50, 60, and 70°C, resulting in reduced drying periods with increasing temperature. The integration of ultrasound markedly lowered drying durations. Eleven thin-layer drying models were utilized to recreate the drying process precisely. Among the desiccated blood orange slices, the greatest total phenolic content (TPC) was observed in freeze-dried samples (131.27 mg GAE/100g), followed by those dried using ultrasonic-assisted vacuum drying (UAVD) at 50°C (128.77 mg GAE/g DM). Dried blood orange slices have a vitamin C content of 29.79 to 49.01 mg/100. The drying process substantially impacted the color parameters L*, a*, and b*. These findings highlight the efficacy of ultrasound-assisted drying in decreasing drying duration while improving the retention of bioactive components in blood orange slices.
Targeting Hepatic Stellate Cells for the Prevention and Treatment of Liver Cirrhosis and Hepatocellular Carcinoma: Strategies and Clinical Translation
Authors: Xiong Hao , Guo Jinsheng
Published: February 2025

Hepatic stellate cells (HSC) are the major source of myofibroblasts (MFB) in fibrosis and cancer associated fibroblasts (CAF) in both primary and metastatic liver cancer. Over the past few decades, there has been significant progress in understanding the cellular and molecular mechanisms by which liver fibrosis and HCC occur and the key roles of HSC in the pathogenesis. HSC targeted approaches via specific surface markers and receptors may enable selective delivery of drugs, oligonucleotides, and therapeutic peptides that exert optimized anti-fibrotic and anti-HCC effects. Recent advances in omics, particularly single-cell sequencing and spatial transcriptomics, hold promise for identifying new HSC targets for diagnosing and treating liver fibrosis/cirrhosis and liver cancer.
The Law of Strata Behavior and Risk Assessment of Rock Burst During the Square Period in Deep Inclined Working Faces
Authors: Sun Qipeng , Kong Linghai
Published: February 2025

In recent years, rock burst accidents have frequently occurred in deep mining operations in China's coal mines. With the gradual increase in mining depth of inclined coal seams in many mining areas, the threat of rock burst disasters in working faces has intensified. This paper employs a comprehensive approach, including theoretical analysis, numerical simulation, and field measurements, to analyze the movement of overlying strata and the distribution laws of abutment pressure in inclined coal seam working faces. A computational model for stress superposition on the working face and the solid coal side of the gate road is established. Based on stress control theory, a method for assessing rock burst risk in inclined coal seam working faces is proposed. By analyzing the calculated results of abutment pressure and numerical simulation results, the rock burst risk level of the working face is comprehensively determined. Building on theoretical analysis and field measurements, the relationship between deep mining pressure and rock burst in inclined coal seam working faces is further investigated. The results indicate that the theoretical model calculates a medium rock burst risk level during the square period of the working face, with abutment pressure reaching its maximum value. The microseismic events and energy release also peak, validating the rationality of the theoretical model. The numerical simulation results and field monitoring data collectively demonstrate that mining pressure manifestations are most pronounced during the square period of the working face. By combining the established model to assess the rock burst risk level, the research confirms the mining pressure manifestation laws during the square period. The calculated rock burst risk level aligns with field conditions, providing guidance for subsequent mining operations and rock burst prevention during the square period of the working face.
Estimating Biomass and Above-Ground Carbon in Wetlands: Influence of Plot Size and Sample Data Treatment in a Model Based on Remote Sensing and Random Forest
Authors: Belloli Tássia Fraga , de Arruda Diniz Carvalho , Guasselli Laurindo Antonio , Cunha Christhian Santana , Korb Carina Cristiane
Published: February 2025

Wetlands are essential carbon sinks in the global ecosystem, absorbing CO2 in their biomass and soils and mitigating global warming. Accurate above-ground biomass (AGB) and organic carbon (Corg) estimation is crucial for wetland carbon sink research. Remote sensing (RS) data effectively estimates and maps AGB and Corg in wetlands using various techniques, but there is still room to improve the efficiency of Machine Learning (ML) based approaches. This study examined how different sample data treatments and plot sizes impact a Random Forest model’s performance based on RS for AGB and Corg prediction. The model was trained with samples of emergent vegetation collected in a palustrine wetland in southern Brazil and spectral variables (single bands and Vegetation Indices — VI) from medium and high-resolution optical images, Sentinel 2 and PlanetScope, respectively. The treatments involve the AGB and Corg values dimensioned for three different plot sizes (Group 1) and the same subjected to the Natural Logarithmic normalization — NL (Group 2). Therefore, six AGB and Corg models were created for each sensor. Models and sensor performances and spectral variable importance were compared. In our results, NL-normalized sample data RF models proved more accurate. Larger plots produced smaller prediction errors with S2 models, indicating the influence of plot size on the reliability of the estimate. S2 surpassed PS in AGB/Corg prediction, but PS was superior in mapping spatial variability. The VI CO2Flux and S2’s SWIR, Blue, Green, and RE bands 6 and 7, were more importance for AGB/Corg prediction. The innovation of this study is that, in addition to optimizing RF model parameters, optimizing the AGB and Corg dataset collected in the field, i.e., evaluating normalization and plot sizes, is crucial to obtain more accurate estimates with RS and ML-based models. This approach, integrated with Sentinel 2’s medium-resolution data and the combination of VIs and bands, enhances AGB/Corg stock estimation and monitoring in wetlands, and the highlighted predictors can act as spectral indicators of these ecological functions.
Predictive Modelling of Healthcare Insurance Costs Using Machine Learning
Authors: Bin Mahathir Addy Arif , Ee Shan Lu , Bin Khairudin Adruce , Ting Xi Ng , Ul Amin Noor
Published: February 2025

With more healthcare spending comes the added demand for predictive models, which would deliver forecasts of medical insurance spending as well as propose significant determining factors. Machine learning is used here to analyze the bills in healthcare insurance based on demographic and lifestyle factors such as age, BMI, smoking status, and geography. Based on the Medical Insurance Cost Prediction dataset, three regression models—Linear Regression, Random Forest Regression, and Gradient Boosting Regression—were employed to forecast insurance charges. Based on the outcome, the most significant variable influencing medical spending is revealed to be smoking status, followed by BMI and age. Among the models employed, Gradient Boosting Regression had the maximum predictive capability, outperforming Linear Regression, which struggled with complex relationships, and Random Forest Regression, which experienced some overfitting. The study highlights the ability of machine learning to enhance insurance pricing for optimization, enabling enhanced risk assessment by providers and decision-making by individuals. The research promotes the optimization of cost estimation methods in the healthcare sector based on data insights.
Improving State of Health Estimation for Lithium-ion Batteries based on GAN and Partial Discharge Profiles
Authors: Zhang Hangyu , Lai Yi-Horng
Published: February 2025

The aging effect will weaken the capacity of lithium batteries and seriously affect the performance of electric vehicles. Developing State of Health estimation technology for lithium batteries can help optimize the charging and discharging strategies of electric vehicles. This study investigates the use of partial discharge data for SOH estimation. To overcome the limitation of unstable output of traditional estimation models caused by partial discharge data in low voltage scenarios. This study first used the DoppelGANger network to generate artificially synthesized data. After the data augmentation process, train the Temporal Convolutional Network to construct a data-driven SOH model. Finally, the performance of the SOH model output is evaluated using three indicators: RMSE, MAPE, and delta. The proposed method improved 5 kinds of low-voltage operating conditions in 7 testing scenarios compared with traditional SOH estimation models. The experimental results provide a practical solution for data-driven SOH estimation.
Geomorphological, Biophysical, and Photogrammetric Analysis of Agroforestry Systems Associated with Cocoa (Theobroma cacao L.) Cultivation in the Dominican Republic
Authors: Iñiguez Ender Antonio , Echevarría Ezequiel , Ramírez Agripina
Published: February 2025

Cocoa (Theobroma cacao L.) cultivation in the Dominican Republic is a vital economic activity, yet it faces significant challenges related to land use, environmental variability, and resource management. This study analyzes the geomorphological, biophysical, and photogrammetric characteristics of agroforestry systems associated with cocoa cultivation to optimize productivity and sustainability. High-resolution satellite imagery (Sentinel-2, Landsat 9) and drone-based photogrammetry were used to assess terrain features, soil properties, and vegetation health. A georeferenced cadastral database was developed to consolidate critical information for land management. Results indicate that terrain slope, soil organic matter, and water availability significantly influence cocoa yield. NDVI analysis revealed spatial variability in plant health, highlighting areas requiring intervention. The findings underscore the importance of soil conservation practices, targeted irrigation strategies, and precision monitoring to enhance sustainability. The integration of remote sensing, GIS, and field validation provides a robust framework for decision-making in cocoa agroforestry systems. This study contributes valuable insights for policymakers, researchers, and farmers, offering practical recommendations to improve land productivity while ensuring long-term environmental sustainability.
Big Data and National Security Threats in Nigeria: Challenges, Opportunities, and Strategies
Authors: Onazi Sunday Omanchi , Olanrewaju Rashidah Funke , Aimufua Gilbert
Published: February 2025

Nigeria faces persistent national security threats, including terrorism, insurgency, cybercrime, and communal violence, which have significant socio-economic and governance implications. This study investigates the role of big data analytics in mitigating these security threats by analyzing structured and unstructured data from multiple sources. Using a mixed-methods approach, the study integrates literature review, case studies, and government policy analysis to assess the effectiveness of big data analytics in intelligence gathering, surveillance, cybersecurity, and early threat detection. The findings reveal that while big data enhances predictive capabilities and situational awareness, challenges such as data privacy concerns, infrastructure deficits, and ethical dilemmas must be addressed. The study recommends strengthening legal frameworks, improving technical capacity, and fostering public-private partnerships to maximize the potential of big data in national security strategies. The implications suggest that a data-driven approach can significantly improve Nigeria's ability to respond proactively to emerging security threats while balancing privacy and civil liberties.
Paired-Like Homeodomain Transcription Factor 2 (PITX2): Time Behavioural Study of 3rd Order Combinations in WNT3A Stimulated HEK 293 Cells
Authors: Sinha Shriprakash
Published: February 2025

PITX2 (also known as pituitary homeobox 2), encodes a member of the RIEG/PITX homeobox family (a bicoid class of homeodomain proteins), that acts as a transcription factor and regulates procollagen lysyl hydroxylase gene expression. It is known to play an important role in pituitary, heart, brain, lungs, spleen, twisting of the gut and stomach, as well as the development of the eyes. Gujral and MacBeath [1] provides a quantitative, and dynamic study of WNT3A-mediated stimulation of HEK 293 cells, where they record time based expression profiles of several response genes which correlated significantly with proliferation and migration. By monitoring the dynamics of gene expression using self-organizing maps, they identified clusters of genes that exhibit similar expression dynamics and uncovered previously unrecognized positive and negative feedback loops. However, their study depicts/uses singular measurements of individual gene expression at different time snapshots/points to infer the system wide analysis of the pathway. At any particular time point, it is often the case that genes are working synergistically in combinations, even though their expression measurements are singular in nature. Here, I • enumerate and rank all 2415 PITX2 related 3rd order combinations in a forest of 71C3 combinations using four different sensitivity methods; • show the conserved rankings for PITX2-X-X combinations, which point to existence of biological synergy of some of these combinations across the different sensitivity methods; and • study the behaviour of some of these combinations related to WNT3A response genes that are ranked by the machine learning search engine (Sinha [2]) in time. Patterns of combinations emerge, some of which have been tested in wet lab, while others require further wet lab analysis.