bluuebunny/crossref_metadata_2025 huggingface dataset:
Domain-Specific Fine-Tuning in a Retrieval-Augmented Generation Framework for Precision Geriatric Medical QA
Authors: Lin Shaofu , Wang Baoxin , Huang Zhisheng , Li Chunlin
Published: January 2025

Large language models (LLMs) have demonstrated remarkable general-purpose capabilities, yet they often struggle to accurately answer complex questions in specialized domains such as geriatric medicine. Although existing Retrieval-Augmented Generation (RAG) methods can mitigate hallucinations by leveraging external knowledge sources, these methods lack robust domain adaptation, resulting in persistent issues of inaccurate or irrelevant answers. To address this limitation, we present a novel domain-specific fine-tuning approach within the RAG framework, complemented by a specially constructed geriatric medical dataset designed for RAG tasks. Through full-parameter fine-tuning of a large language model, our method achieves a 6–10 percentage-point increase in GPT-4-based answer accuracy over general-purpose RAG baselines on a geriatric medicine test set. Human evaluations further confirm the enhanced professionalism and clinical relevance of the model’s outputs. Notably, the model maintains strong performance on Longbench’s general capability benchmarks, underscoring both the specificity and generalizability of our strategy. This study provides a new pathway toward building more reliable and domain-focused medical QA systems, offering insights for future RAG applications in specialized fields.
Gender Bias Analysis for Different Large Language Models
Authors: Mirza Imran , Jafari Akbar Anbar , Ozcinar Cagri , Anbarjafari Gholamreza
Published: January 2025

Large language models (LLMs) have transformed NLP applications across various domains, while raising crucial fairness and ethical concerns, especially regarding gender bias. This study examines gender bias in four leading LLMs, GPT-4o, Gemini 1.5 Pro, Sonnet 3.5, and LLaMA 3.1:8b—by evaluating the gender distributions these models generate for "perfect personas" across diverse occupational roles, including healthcare, engineering, and professional services. Using standardized prompts, controlled experimental settings, and repeated trials, we systematically quantify gender representation against a uniform baseline. The results reveal stark contrasts between models: GPT-4o exhibited pronounced occupational gender segregation, overwhelmingly assigning healthcare roles to females while reserving engineering and physically demanding roles for males. In contrast, Gemini 1.5 Pro, Sonnet 3.5, and LLaMA 3.1:8b showed predominantly high female assignments across a broad spectrum of occupations, with no comparable specificity in job-level representation. These findings underscore how architectural choices, training data composition, and token embedding strategies can amplify or mitigate biases, often at the expense of inclusivity. This research highlights the pressing need for designing inclusive datasets, implementing advanced bias-mitigation techniques, and conducting rigorous audits to ensure LLMs not only avoid perpetuating stereotypes but actively contribute to equitable and representative AI systems.
Physical and Competitive Environments Experienced by Basketball Athletes During the Years of Sports Development
Authors: Maciel Larissa Fernanda Porto , Folle Alexandra , Beirith Mariana Klauck , Ibáñez Sergio José
Published: January 2025

The characteristics of the physical environment where the main sports experiences are experienced are decisive for achieving positive results in sports. The objective of this article was to verify the quality of the facilities and materials for practicing basketball during the formative years. A mixed-method study with a sequential explanatory design was conducted. Quantitative data were collected from Brazilian athletes aged 18 and 19 (n = 141), and then interviews were conducted with 24 athletes. To discover the differences between age groups, the Kruskal-Wallis test was used, and the association between qualitative variables was analyzed using the Chi2 test. The analysis of qualitative data was guided by Thematic Analysis. The results showed that public and private gyms were the most frequented places for practicing basketball, with private gyms being considered better in terms of structure and materials. The athletes' perception of the broader structure of the sports system in the different Brazilian states demonstrated the influence that certain contexts and cultures, more specifically structural and social characteristics, have on sports development. This study demonstrates that options for accessing and remaining in sport are directly influenced by factors such as the geographic location of athletes and their families.
The Offshore Oil & Gas Industry and Additive Manufacturing: A Competitiveness Analysis
Authors: Gonçalves Tiago , Martins Rúben , Vale Vera , Oliveira Manuel
Published: January 2025

This study examines the impact of Additive Manufacturing (AM) on the Off-shore Oil and Gas Industry, focusing on its role in enhancing competitiveness, operational efficiency, and sustainability. Using strategic frameworks such as PESTEL, Porter’s Five Forces, and SWOT, the research highlights AM’s potential to optimize supply chains, reduce downtime, and support on-demand production. Key findings suggest that AM offers significant benefits, including cost re-duction, supply chain flexibility, and environmental advantages through waste minimization. However, challenges remain, such as high initial investment costs, technical limitations, and the need for workforce upskilling. Additionally, regulatory and standardization issues hinder broader AM adoption. The study emphasizes that overcoming these challenges requires strategic investments, workforce development, and collaboration across sectors. Future research should focus on assessing the long-term economic benefits of AM through lifecycle cost analyses, as well as exploring its integration with emerging technologies like artificial intelligence and digital twins. Additionally, harmonizing international standards for AM and investigating its environmental impacts will be crucial for enabling widespread adoption in the offshore sector. This paper provides valuable insights for industry stakeholders, demonstrating that AM has the potential to drive innovation and sustainability in the Offshore Oil and Gas Industry, positioning companies for long-term competitive advantage.
Carbon Monoxide Concentration in the Garage of a Single-Family House–Experiment and a OneDimensional Model of Carbon Monoxide Concentration
Authors: Teleszewski Tomasz Janusz , Gładyszewska-Fiedoruk Katarzyna
Published: January 2025

The paper presents tests of carbon monoxide concentration in a single-car garage equipped with exhaust ventilation, while the combustion engine of a parked passenger car is operating. The main source of carbon monoxide in the garage is the internal combustion engine of a passenger car. Single-car garages are characterized by a relatively small volume, which causes the rapid accumulation of carbon monoxide inside the garage. Currently, the walls of residential buildings and garage doors are characterized by high tightness, which, when the garage door is closed and a combustion car running, may result in too little air exchange in the garage and a significant concentration of pollutants emitted by the combustion engine in the garage. The test results showed significant exceedances of the permissible values (WHO, NAAQS) of carbon monoxide concentrations both with exhaust ventilation on and off. The highest carbon monoxide concentration values (2253 ppm) in the garage were observed when the exhaust ventilation was turned off. The study also developed two one-dimensional models of carbon monoxide concentrations in a garage with the combustion engine of a passenger car turned on for the case of exhaust ventilation turned on and off. The models developed in this work can be used when designing ventilation to estimate carbon monoxide concentrations in garages based on the type of car and the number of air changes.
Perceptions of Supplier Relationships and Service Quality in Italian Dining
Authors: Warwick Isabelle
Published: January 2025

This study explores the perceptions of supplier relationships and their impact on service quality in Italian dining establishments. With a focus on understanding how suppliers contribute to operational efficiency, product quality, and customer satisfaction, the research aims to identify key factors that influence the success of these partnerships. The study uses a qualitative research design, employing semi-structured interviews with restaurant owners and managers to gain in-depth insights into their experiences and perceptions of supplier relationships. Key themes identified in the analysis include trust, reliability, communication, collaboration, cost management, supplier innovation, and sustainability. The findings reveal that strong, reliable supplier relationships are critical to maintaining consistent quality and ensuring a smooth operational flow. Communication and collaboration between restaurants and suppliers play an essential role in addressing challenges, innovating menu offerings, and adapting to evolving consumer preferences. Moreover, cost management remains a significant concern, with restaurants balancing the need for high-quality ingredients with financial constraints. The study also highlights the growing importance of sustainability and ethical sourcing practices, with both consumers and restaurants increasingly prioritizing responsible sourcing. The research concludes that effective supplier relationships are fundamental to the success of Italian dining establishments, impacting both the quality of service provided and the financial sustainability of the business. The findings offer valuable insights for restaurant managers, suppliers, and stakeholders in the foodservice industry, providing a framework for building and maintaining successful supplier partnerships.
Open, Randomised, Controlled Study to Evaluate a Dietary Supplement with Pelargonium sidoides Extract, Honey, Propolis, and Zinc in Children with Acute Tonsillopharyngitis
Authors: Cardinale Fabio , Barattini Dionisio Franco , Centi Alessandro , Giuntini Greta , Bordea Maria Morariu , Herteg Dorina , Barattini Luca , Monaco Martina , Matei Cristian Radu
Published: January 2025

Background/Objectives: Acute tonsillopharyngitis (ATR), typically caused by viruses, is a common reason for consultation with pediatricians. A dietary supplement with Pelargonium sidoides extract, propolis, honey, and zinc has been proposed as an effective adjuvant for the treatment of respiratory tract infections. This study aimed to verify, in a setting of standard clinical practice, the efficacy of this dietary supplement plus standard of care (SoC) versus SoC alone in a pediatric population affected by ATR. Methods: This open randomized study (registered on ClinicalTrials.gov: NCT 04899401) involved three Romanian sites specialized in pediatric care. The primary endpoints were changes in Tonsillitis Severity Score and the number of treatment failures (evaluating the use of ibuprofen or high-dose paracetamol as rescue medicine). One hundred and thirty children, divided into two groups, were enrolled and treated for six days. Results: The results showed an overall better performance in terms of efficacy of dietary supplement + SoC, compared to SoC alone, with lower total Tonsillitis Severity Score ratings and lower sub-scores (swallowing on day 4 and throat pain and erythema on day 6). No adverse events were reported. Investigators found compliance to be optimal. Conclusions: The administration of the dietary supplement + SoC in pediatric patients with ATR was found to be safe and superior to the administration of SoC alone in terms of efficacy. The results confirmed the tested dietary supplement as an optimal effective adjuvant in the treatment of respiratory tract infections and useful in the daily clinical practice of the paediatricians.
Exploring the Role of Positive Body Image, Psychological Factors, Disability and Age in Acceptance of Illness in Multiple Sclerosis
Authors: Matusik Edyta , Lewicka Barbara , Czepczor-Bernat Kamila , Maciejowska Katarzyna , Kowalcze Paulina
Published: January 2025

Background
Multiple sclerosis (MS) is a chronic, neurodegenerative disease leading to a progressive disability that can affect not only the physical but also the mental state of patients. The psychological adaptation to the illness plays an important role in the general effectiveness of treatment. The study aimed to determine modifiable and nonmodifiable correlates of acceptance of illness.
Methods
A total of 139 Caucasian patients with MS (pwMS) (106 females) was included. The Acceptance of Illness Scale (AIS), the Body Appreciation Scale (BAS-2), and the Depression, Anxiety and Stress Scale – 21 items (DASS-21) together with socio-demographic and clinical data, including the Expanded Disability Status Scale (EDSS), were used.
Results
Pearson correlation analysis showed that all variables (Disability status pwMS, Intensity of depression symptoms, positive body image) are significantly related to acceptance of illness. After including all the predictors in the regression analysis, all the correlations turned out to be significant (except the one with multiple sclerosis disability rating). Both age and severity of depressive symptoms decrease the level of acceptance of the disease. An increase in the level of positive body image positively affects the level of acceptance of the disease.
Conclusion
The acceptance of the disease is correlated with both modifiable and nonmodifiable factors. The work on the modifiable factors should be taken into account in creating a complex program of rehabilitation and treatment of MS patients.
Electroanalytical Approaches to Combat Food Adulteration: Advances in Non-Enzymatic Techniques for Ensuring Quality and Authenticity
Authors: Tsopelas Fotios
Published: January 2025

Food adulteration remains a pressing issue with serious implications for public health and economic fairness. Among the diverse methods available for detecting adulteration, non-enzymatic electroanalytical techniques have emerged as promising tools due to their high sensitivity, cost-effectiveness, and adaptability to field conditions. This review delves into the application of these techniques across various food matrices, including olive oil, honey, milk, and alcoholic beverages. By leveraging methodologies such as voltammetry and chemometric data processing, significant advancements have been achieved in identifying both specific and non-specific adulterants. The review highlights novel electrode materials, such as carbon-based nanostructures and ionic liquids, which enhance sensitivity and selectivity. Additionally, electronic tongues employing multivariate analysis have shown promise in distinguishing authentic products from adulterated ones. The integration of machine learning and miniaturization offers potential for on-site testing, making these techniques accessible to non-experts. Despite challenges, such as matrix complexity and the need for robust validation, electroanalytical methods represent a transformative approach to food authentication. The findings underscore the importance of continuous innovation to address emerging adulteration threats and ensure compliance with quality standards.
Biomechanical Effects on Periodontal Ligaments During Expansion of the Maxillary Arch Using Thermoformed Aligners Modeled by Computational Methods
Authors: Rojas Gustavo A. , Garcia Melo Jose Isidro , Arstizabal Juan S.
Published: January 2025

Purpose: this paper investigates the biomechanical the effect of thermo-formed aligners equipped with complementary biomechanical attachments (CBAs) on periodontal ligaments (PDL) during the expansion process of the maxillary arch. The analysis was conducted using advanced simulations based on the finite element method (FEM). Methods: High-resolution 3D CAD models were created for four tooth types: canine (3), first premolar (4), second premolar (5), and first molar (6). Additional 3D models were developed for aligners, CBAs, and PDLs. These were integrated into a comprehensive FEM model to simulate clinical rehabilitation scenarios. Validation was achieved through comparative analysis with empirical medical data. Results: The FEM simulations revealed the following: for canine 3, the displacement was 0.134 mm with a maximum stress of 4.822 x10-3MPa in the amelocemental junction. For premolar 4, the displacement was 0.132 mm at a maximum stress of 3.273x10-3MPa in the amelocemental junction. Premolar 5 had a displacement of 0.129 mm and a stress of 1.358 x10-3MPa at 1 mm from the amelocemental junction. Molar 6 had a displacement of 0.124 mm and a maximum stress of 2.440 x10-3MPa. Conclusions: The inclusion of CBAs significantly reduced tooth tipping during maxillary arch expansion. Among the models tested, the Vestibular CBA demonstrated superior performance, delivering optimal tooth movement when combined with thermoformed aligners. Significance: FEM techniques provide a robust and cost-effective alternative to in-vivo experimentation, offering precise and reliable insights into the biomechanical efficacy of CBAs in thermoformed aligners. This approach minimizes experimental variability and accelerates the evaluation of innovative orthodontic configurations.
Heritage and Hollywood: Shaping Human Identity and Gender from the Renaissance to the Age of AI
Authors: Giannini Tula , Bowen Jonathan P.
Published: January 2025

The age of artificial intelligence (AI) is taking hold like an expanding universe and setting into motion the spawning of a new global culture. In parallel with these changes. humans interact with media messages steeped in visual and conversational language streamed across neural global platforms, with billions of humans participating. How is this tech-saturated environment impacting human and gender identity and aesthetics? This paper considers these issues, looking through the lens of the arts, past to present and back again. A central theme is the personification of male and female symbolic characteristics. We see that arts and culture are an enduring and powerful influence across time and space, from Ancient Greece to the 21st century, juxtaposing rapid change in AI technology with time-tested symbols and personas of gender identity. This paper offers a visual journey of cultural transmission that exemplifies this fascinating dichotomy to both reveal and question, especially given recent years that have witnessed a significant surge of gender and cultural wars, and a defining moment for cultural heritage.
The Jacod-Yor Theorem for Sigma Martingales and the Second Fundamental Theorem of Asset Pricing
Authors: Sohns Moritz
Published: January 2025

In this paper, we prove the Jacod-Yor Theorem for sigma martingales, a class of processes that generalize local martingales and play a pivotal role in financial mathematics. While the Jacod-Yor Theorem has been extensively studied for \( L^2 \)-martingales, martingales, and local martingales, no prior version exists for sigma martingales. Our result establishes the connection between sigma martingales and their martingale representation properties, addressing a critical gap in the literature. As an application, we prove the Second Fundamental Theorem of Asset Pricing for markets where price processes are modeled as sigma martingales.
Race, Genes, Evolution, and IQ: The Key Datasets and Arguments
Authors: Johnson Brian
Published: January 2025

There is considerable variation in the mean IQ scores of human racial groups. Such group differences may be caused by genetic or environmental effects. Here we review and refute the claims of those who argue that mean IQ differences are the result of genetic effects, a claim which has seen a resurgence in recent years. We begin with data that question the notion that races vary in IQ and real-world achievement in a manner supporting a racial hierarchy. First, minorities of different genetic ancestry have comparable IQ and achievement levels in the US. Second, worldwide, we often see gaps as large as between White and Black Americans within single racial groups. Third, the Black-White achievement gap is entirely due to sex specific differences in achievement. There are, however, no sex specific mean differences in IQ. With respect to the magnitude of racial achievement gaps, they are well within the range of effects caused by socioeconomic factors, particularly those related to education. Further, when IQ tests do not reference past knowledge (particularly vocabulary), the IQ gap disappears. We then review work showing that mixed race persons do not typically show intermediate IQ, a key prediction of the genetic hypothesis. Finally, we review the three extant transracial adoption studies, which do not provide any support for a genetic explanation for group level differences in IQ. In sum, there is nothing about the nature of racial IQ gaps that suggests a genetic explanation, and the experimental work does not support a genetic explanation.
Cybernetics 3.0: Addressing Grand Challenges in Human-Machine Interaction and Decision-Making
Authors: Hallo Leonie , Hanzis Anastasia , Rowe Caroline
Published: January 2025

This paper examines the framework of Cybernetics 3.0 as a way of addressing grand challenges related to human-machine interaction in complex systems. The paper explores the evolution of Cybernetics and highlights the limitations of the earlier versions. The current approach to Cybernetics, Cybernetics 3.0, focuses upon human agency and the co-evolution of humans and machines in the decision-making space. The paper argues that this approach when combined with Web 3.0 technologies gives new ways to optimise decision-making by integrating human capabilities and ethical considerations with machine capabilities. The paper uses causal loop diagrams to demonstrate the factors leading to interconnectedness between human and machine decision-making. A practical example from the field of healthcare illustrates the interconnections and demonstrates the utility of this framework for more sustainable and wise decisions. A holistic systems thinking approach in addressing grand challenges such as these could promote human flourishing, and the discipline of Cybernetics is a promising way to better understand the interaction and its potential, through its focus on systems of control, human AI learning and communication, feedback loops, self-regulating systems, and knowledge enhancement in humans and machines.
The Influence of Domestic Socioeconomic Development on Migration Decisions in Low- and Middle-Income Countries: Insights from the Migration Transitions and Capabilities Perspective
Authors: Paudel Shesh Narayan
Published: January 2025

People, their families, and communities weigh the costs and benefits of migration to decide whether to move or stay; however, these decisions are complex and influenced by multiple factors. This study uses the Migration Transition and Aspirations-Capabilities framework to examine how domestic socioeconomic development shapes migration decisions. Applying the Generalized Method of Moments (GMM) and Quantitative Descriptive Analyses (QDA) to panel data from 109 low- and middle-income countries, it compares the impact of GDP per capita and the Human Development Index (HDI) on net migration and emigration trends. The dynamic panel regression results show that the HDI exerts a more substantial effect on positive net migration, with its impact being approximately 10.69 times greater than GDP per capita. Coefficients for HDI range from 9.144 to 13.79, while those for GDP per capita range from 0.994 to 1.785. The QDA results also suggest that migration equilibrium is reached at approximately $4,000 GDP per capita, based on emigration rates, and around $7,000 when measured by net migration rates. Additionally, countries with GDPpc between $2,000 and $4,000 experience sharp negative net migration, indicating a highly mobile population in this income range. Finally, the regression results question the theoretical assumption of non-linearity, revealing almost a linear relationship between development and migration. We project that the high emigration flows from low- and lower-middle-income countries will likely continue for the foreseeable future. In light of this, governments in countries of migrant origin must transition from restrictive migration policies and border controls to strategies that promote sustainable socioeconomic development. By improving the Human Development Index (HDI), migration can shift from necessity to a matter of choice. This approach can unlock the full developmental benefits of migration while contributing to the global objectives of the 2030 Agenda for Sustainable Development and the Global Compact for Safe, Orderly, and Regular Migration (GCM).
The Weapon – the Use of Kolmogorov Complexity to Combat Plagiarism in the Classroom
Authors: Sturm George
Published: January 2025

This paper discusses a unique usage of Kolmogorov Complexity that combats the bane of all teachers – plagiarism. The theoretical foundation of this tool is presented and illustrated using real-life data from the area of software programming.
Liposomal Drug Delivery Systems: An Intro as a Primer for Advanced Therapeutics
Authors: Sengar Ashutosh
Published: January 2025

Application of liposomal drug delivery systems-a revolutionary approach applied in the modern therapeutic era-has shown great efficiency in elevating the level of efficacy and safety delivery drugs. Lipid-based vesicles enclose therapeutic agents with enhanced solubility, stability, and controlled release. Since their composition comprises both hydrophilic and hydrophobic drug components, it is possible for liposomes to encapsulate the latter as a way of overcoming some of the main challenges that come with the use of classical delivery systems. Some of the most significant clinical applications of liposomal formulations have been Doxil® for anticancer treatment and AmBisome® in fungal infections that significantly improved their pharmacokinetics and reduced toxicity. Liposomes have also served as very efficient carriers in delivering vaccines, where they were extremely useful in an mRNA vaccine formulation to elicit intense immune responses. The scope of liposomal systems for personalized medicine and targeted therapies is vast and keeps opening up the avenues of novel treatments to treat complex medical challenges. This paper is a review of the mechanism, advantages, clinical applications, and future prospects of liposomal drug delivery systems in modern therapeutics. Further highlighted with the development of new liposomal formulations and its inclusion with new technologies, it underlines the importance of liposomes in future drug delivery.
Multimodal Information Integration and Retrieval Framework Based on Graph Neural Networks
Authors: Yuan Yuping , Xue Haozhong
Published: January 2025

In the context of the rapid proliferation of multimodal data (e.g. text, image, audio), the effective integration and retrieval of information across different modalities has emerged as a pivotal research area. The present paper proposes a multimodal information integration and retrieval framework based on a Graph Neural Network (GNN). The objective of this framework is to enhance the fusion effect and cross-modal retrieval performance of heterogeneous data. The proposed model innovatively adopts a graph structure to model the complex relationship between modalities, building upon existing multimodal fusion methods. Specifically, a hierarchical graph structure is introduced, wherein each modality functions as a node, with edges denoting dependencies between modalities and within modalities. The graph is processed by a Graph Convolutional Network (GCN) to aggregate the features of adjacent nodes to optimize the joint representation of multimodal information. Furthermore, a cross-modal attention mechanism is integrated to dynamically learn the relevance of different modalities under a specific query, with the aim of further improving retrieval accuracy. The proposed framework facilitates end-to-end training, enabling efficient learning of multimodal representations and enhancement of retrieval robustness. The experimental results demonstrate that the proposed model significantly enhances the retrieval accuracy and recall rate in comparison with existing multimodal retrieval models on the benchmark dataset.
Efficacy of Prostate Biopsies via Transperineal and Transrectal Routes for Significant Prostate Cancer Detection: A Multicenter Paired-Matched Study
Authors: Paesano Nahuel , Picola Natàlia , Muñoz-Rodriguez Jesús , Ruiz-Plazas Xavier , Muñoz-Rivero Marta V. , Celma Ana , García-de Manuel Gemma , Miró Berta , Servian Pol , Abascal José M. , Trilla Enrique , Morote Juan
Published: January 2025

Objective: To compare the efficacy of transrectal and transperineal prostate-guided biopsies to magnetic resonance imaging (MRI) index lesions in detecting clinically significant prostate cancer (csPCa), and to evaluate the role of systematic biopsies. Methods: This prospective and multicenter trial, conducted in the early detection program of csPCa of Catalonia (Spain) between 2021 and 2023, involved 4,029 men suspected of ha-ving PCa who underwent multiparametric MRI followed by guided and systematic biopsies. From this cohort, 1,376 men with reported size and localization of index lesions were selected. A matched group of 325 pairs of men subjected to transrectal and transperineal biopsy was chosen to account for confounding variables. We compared csPCa detection rates at index lesions and systematic biopsies, as well as by lesion localization. Results: Transperineal and transrectal biopsies detected csPCa in 49.5% vs. 40.6% overall (p = 0.027), 44.6% vs. 30.8% at index lesions (p = 0.001), and 24.3% vs. 35.1% at systematic biopsies (p = 0.003). CsPCa detection rates were higher in transperineal biopsies across all index lesion localizations, with significant increases in anterior zone (47.8% vs. 20.8% at mid-base, p = 0.039; 52.9% vs. 24.2% at apex, p = 0.024) and central zone (33.3% vs. 5.9%, p = 0.003). CsPCa detected only in systematic biopsies was 10.5% in transrectal biopsies and 4.9% in transperineal biopsies (p = 0.012). Conclusions: Targeted biopsies via the transperineal route showed higher csPCa detection rates than transrectal biopsies, parti-cularly for anterior and apical lesions, with systematic biopsies showing reduced utility.
Research on a Cow Rumination Behavior Recognition Method by Integrating Biformer and GSConv
Authors: Zhao Yingjie , Mu Xuanyu , Wang Zhen , Liu Dongjie , Yao Jiangtan , Yu Ruirui , Jia Zongwei
Published: January 2025

Cow rumination behavior monitoring is crucial in the precision management of dairy farming as this behavior serves as a key indicator for assessing cow health and productivity. However, noncontact, video-based cow rumination behavior monitoring encounters challenges, such as varying shooting angles, random distributions of individual cows, and complex outdoor environments; hence, accurately identifying changes in the mouth region during cow rumination is particularly challenging. In this study, based on real farming environment data, we constructed a multienvironment cow rumination dataset and proposed a Biformer–YOLOv7 model, which combines double-routing attention (Biformer) and lightweight convolution (GSConv) techniques to effectively recognize a small target region around a cow’s mouth. We compared the performance of YOLOv3, YOLOv4, YOLOv5, YOLOv7, and the proposed Biformer–YOLOv7 model for cow mouth region detection. Results demonstrate that the proposed model outperforms others in terms of mean average precision, recall rate, detection accuracy, and detection speed. Specifically, the average precision of cow mouth region detection reaches 95.90%, the recall rate is 91.16%, accuracy achieves 93.73%, and the detection speed reaches 35.6 FPS, meeting real-time requirements. Moreover, the proposed model demonstrates high accuracy in recognizing and locating cows even under partial occlusion, overcast, and nighttime conditions, exhibiting robustness and applicability. Furthermore, compared with the manual recognition of the rumination behavior, average error in the rumination frames and chewing counts are 4.2% and 3.09%, respectively, indicating the wide application prospects of the Biformer–YOLOv7 model for cow farming video monitoring and management.
Evaluation of Sirs, Mews, and qSOFA Scores to Predict ICU Admission and 14- and 30-Day Mortality in Patients with Hematological Malignancies and Sepsis or Septic Shock
Authors: Luz e Silva Luciane , Boldim Ferreira Diogo , Medeiros Eduardo Alexandrino
Published: January 2025

Introduction: In hospitalized patients, the risk of mortality in patients with hematological malignancies, related to sepsis and septic shock are high, can be assessed using the Modified Early Warning Scoring score (MEWS). Currently, different tools that predict deterioration have been introduced into clinical practice in hospitals around the world. It remains unclear which screening tool for mortality in patients with hematological malignancies is best. The aim of this study was to evaluate the mortality predictive performance of four sepsis-based scores (i.e. Systemic Inflammatory Response Syndrome (SIRS) criteria, and quick Sepsis-related Organ Failure Assessment (qSOFA) in comparison with the more general MEWS score in hospitalized sepsis patients. Methods: We conducted a retropective study. Patients with hematological malignancies and sepsis or septic shock, between January 2017 and August 2020, were included. Suspected sepsis was defined as blood culture collection and initiation of intravenous antibiotics. Outcome was defined as in-hospital mortality within 14 days and 30 days after the sepsis episode or until death. Predictive performance was expressed as discrimination (AUROC) and calibration using the highest You-den index fit test. In addition, the sensitivity, specificity, negative predictive value, and positive predictive value of four scoring systems were calculated. The scoring systems were compared with McNemar's test and AUROC by DeLong's method. Results: A total of 775 with sepsis were included in the institution. Of these, 329 (42.5%) patients had diagnosis of hematological malignancies and were included in the study, of which mortality was 89 (27%) at 14 days and 126 (38.3%) at 30 days. Regarding AUROC, qSOFA and MEWS showed higher accuracy than SIRS. However, qSOFA showed low sensitivities for score ≥2, while MEWS low specificities with score ≥4. Conclusions: MEWS seems to be a better choice of score in this study population, shows higher sensitivity than qSOFA and higher AUROC than SIRS for prediction of ICU inter-nation and 14- and 30-day mortality in patients with hematological malignancies and sepsis.
Alzheimer’s Dementia. The Influence of Oxidative Stress in Its Pathophysiology. Can the Antioxidant Glutathione Delay or Prevent Cognitive Impairment of Alzheimer’s Disease?
Authors: Yutani Ray
Published: January 2025

Dementia from Alzheimer’s disease (ADz) is an enormous and growing healthcare problem. The economic and societal burden of caring for those who develop Alzheimer’s dementia (ADm) is rising as the population of those over 65 years of age increases. Current treatments are given to manage symptoms or to reverse established pathological insults of ADm. Evidence is presented that oxidative stress (OS) may initiate and promote the development of ADm when ADz is asymptomatic and that the antioxidant, glutathione (GSH), can counter OS. A novel nano-product, the glutathione-cyclodextrin (G-C) complex can effectively deliver GSH. It is proposed that if GSH is administered early in ADz to asymptomatic individuals with ADz it should delay or prevent the development of Adm. The complex is a topically applied non-prescription product that has no significant adverse side effects. As of 2023 GSH has not been studied in any current clinical trials.[1] Rigorous studies will be needed confirm its efficacy. If proven, its use should reduce the burden of ADm.
Adaptive Machine Learning Models for Dynamic Environments: A Mathematical Framework for Real-Time Decision Making
Authors: Raja Varoon , Kung James
Published: January 2025

Dynamic environments challenge traditional machine learning (ML) models due to their inability to adapt to non-stationary data distributions. This paper introduces a mathematically rigorous framework for adaptive ML models tailored for real-time decision-making in dynamic settings. Our framework integrates anomaly detection, transfer learning, and reinforcement learning (RL), leveraging statistical learning theory and optimization techniques to ensure robustness. Experimental validation demonstrates the framework’s superiority in accuracy, adaptability, and computational efficiency.
A Systematic Literature Review on Supplier Relationship Management in the Context of Global Supply Chains
Authors: Jones Jennifer
Published: January 2025

This study explores the evolving dynamics of Supplier Relationship Management (SRM) within the context of global supply chains, emphasizing its strategic importance in achieving resilience, efficiency, and sustainability. As supply chains become increasingly interconnected and complex, SRM has transitioned from transactional processes to a strategic function critical for long-term organizational success. The review highlights the role of trust, collaboration, and mutual benefit as foundational elements in fostering robust supplier relationships. It also examines the transformative impact of emerging technologies, such as blockchain, artificial intelligence, and the Internet of Things, in enhancing transparency, real-time monitoring, and predictive analytics for supplier performance. Additionally, the study emphasizes the importance of resilience and adaptability in supplier partnerships, especially in mitigating risks associated with global disruptions. Cultural variations and power dynamics further influence SRM practices, necessitating tailored strategies for diverse geographic and economic contexts. The increasing integration of sustainability into supplier selection and evaluation processes underscores the growing importance of environmental and social governance in global supply chains. The findings also reveal that performance measurement, innovation, and joint problem-solving are essential for continuous improvement and alignment with strategic goals. By synthesizing recent research, this study provides a comprehensive understanding of SRM's role in driving competitive advantage, fostering innovation, and ensuring long-term sustainability in global supply chains. The insights presented serve as a valuable resource for academics and practitioners seeking to navigate the complexities of supplier management in a rapidly changing global landscape.
Decreased Serum Sphingolipids in Diabetic Ketoacidosis: Possible Role of β-Hydroxybutyrate and Lactate
Authors: Aslan Ibrahim , Çeker Tuğçe , Ustabaş Tayfun , Zorlu Vuslat , Aslan and Mutay
Published: January 2025

Background/Objectives: This study aimed to determine the serum sphingolipid profile in diabetic ketoacidosis (DKA) and investigate its relationship with neutral sphingomyelinase (N-SMase), pro-inflammatory cytokines, β-hydroxybutyrate (β-OHB), and lactate levels. Methods: Thirty-three participants were divided into three groups: control (BMI ≤30, no health issues), obese (BMI >30), and DKA (BMI ≤30). Sphingomyelins (16:0-24:0 SMs) and ceramides (C16-C24 CERs) were measured using ultra-fast liquid chromatography combined with tandem mass spectrometry (LC-MS/MS). N-SMase, interleukin 1 beta (IL-1β), and tumor necrosis factor alpha (TNF-α) levels were assessed by enzyme-linked immunosorbent assay. Evaluations were done in the DKA group before and after treatment (post-DKA group). Results: β-OHB levels were significantly higher in the DKA group than in the control, obese, and post-DKA groups. Although β-OHB levels decreased in the post-DKA group, they remained elevated compared to the control and obese groups. Lactate levels were also higher in the DKA group, with a significant decrease in the post-DKA group. TNF-α and IL-1β were higher in the obese group compared to control and DKA groups, and TNF-α decreased significantly in the post-DKA group compared to DKA. N-SMase, 16:0-18:0 SMs, and C18-C24 CER levels were lower in the DKA and post-DKA groups compared to obese and control groups. Serum β-OHB and lactate levels were significantly correlated with S1P, total CER, total SM, and N-SMase values. Conclusions: The study reveals significant metabolic and inflammatory changes in DKA and post-DKA states, suggesting a relationship between sphingolipids, N-SMase, and these alterations, which could offer insights into DKA pathophysiology and therapeutic targets.
The Influence of Information Systems on Supply Chain Resilience During Disruptive Events
Authors: Holloway Samuel
Published: January 2025

This study examines the influence of information systems on supply chain resilience during disruptive events. As global supply chains become increasingly complex and vulnerable to unforeseen disruptions, organizations are turning to information systems to enhance their resilience and ability to adapt in crisis situations. The research investigates the role of various information technologies, such as real-time tracking, predictive analytics, cloud-based collaboration tools, and emerging technologies like blockchain, IoT, and AI, in building resilient supply chains. By utilizing a qualitative approach, this study gathers insights from a sample of 38 professionals across diverse industries who shared their experiences in managing supply chains during disruptions. The findings reveal that information systems significantly improve supply chain visibility, enabling organizations to anticipate disruptions, respond more efficiently, and maintain operational continuity. Additionally, the integration of information systems enhances collaboration and communication among supply chain partners, fostering trust and facilitating joint problem-solving. Furthermore, the study highlights the importance of agility, flexibility, and data-driven decision-making in navigating disruptions. Despite these advantages, the research also identifies challenges related to system integration, cybersecurity risks, and resistance to change, which can hinder the effective implementation of information systems. The study concludes that while information systems are critical to enhancing resilience, their success depends on strategic planning, a culture of innovation, and context-specific solutions. The findings contribute to the growing body of knowledge on supply chain resilience and offer practical insights for organizations looking to strengthen their supply chain operations in the face of increasing uncertainty.
Towards a Secure Cloud Ecosystem: Innovations in Cybersecurity
Authors: Bin Samshul Kamar Anamallah , Hong Eddy Au Cheng , Chun Bing Brendan Wong , Wen Jun Chow , Whei Teik Dillon Teh , Kah Fatt Lee , Wei Hao Loh , Haider Rajpar Mohamed Jawad , Jun Zi Sean Ng , Hao Zen Yeo , Sindiramutty Siva Raja
Published: January 2025

Cloud computing has become a fundamental part of many households and organizations today offering many advantages such as cost savings, scalability, remote accessibility and more making it a foundational component of modern digital infrastructure. Along with the benefits of cloud computing, it also introduces significant security challenges that are the primary concern of many people and organisations as it contains the private data of many stakeholders. To address the vulnerabilities, security-related technologies such as encryption, firewalls, Intrusion Detection Systems (IDS), Identity and Access Management (IAM) and Service Level Agreements (SLA) should be considered. This paper aims to investigate the details of security-related technologies such as their components and processes to justify how the security-related technologies can help cloud-based systems combat their vulnerabilities ensuring the best interests of those involved. The paper consists of a background, detailed discussion on how security-related technology works, the impact and limitations of cloud computing, cloud computing’s potential, security countermeasures and proposed countermeasures. Through the analysis of all the discussed topics, the paper aims to provide a comprehensive understanding of the importance of adopting security-related technologies in maintaining a secure and optimised cloud-based system.
Comprehensive Investigation of Crystallographic Architectures, Electronic Bandgap Characteristics, and Anisotropic Mechanical Properties in Ternary Tellurides KAlTe2 and KInTe2 Employing WIEN2k and CASTEP Computational Paradigms
Authors: Ullah Zahid , Khan Muhammad Amir , Gul Sabahat
Published: January 2025

A first-principles study was performed on the anisotropic ternary compounds KAlTe2 and KInTe2 using the WIEN2k and CASTEP codes to optimize their energy to the ground state. The optimized results were then compared with existing theoretical and experimental data for validation. The findings reveal that both KAlTe2 and KInTe2 exhibit both direct and indirect band gaps, depending on the chosen symmetry points during the calculations. The calculated band gaps for KAlTe2 and KInTe2 are found to be 1.68 eV and 0.931 eV, respectively. This dual band-gap behavior indicates that these materials have significant potential for applications in both thermoelectric and optical devices, where direct band gap semiconductors are particularly desirable for efficient energy conversion and light emission. Additionally, the study highlights that the bonding in these materials is characterized by a mixture of covalent and ionic interactions, contributing to their unique electronic properties. The combination of these features makes KAlTe2 and KInTe2 promising candidates for advanced material applications, particularly in fields where the manipulation of band structure and bonding characteristics is crucial for optimizing device performance. This work provides valuable insights into the fundamental properties of these materials and paves the way for further exploration in practical applications.
Software Development and Performance Evaluation of DreamMachine Mobile EEG
Authors: Samimisabet Paria , KRIEGER LAURA , VIDAL DE PALOL Marc , GÜN DENIZ , PIPA GORDON
Published: January 2025

Electroencephalography (EEG) is an essential method used across diverse fields, including neurological diagnosis, cognitive neuroscience, sleep research, and mental health studies. It enables the investigation of neurophysiological functions by recording the brain's electrical activity. A wide variety of EEG and mobile-EEG systems are available on the market. However, adherence to the standards set by the International Federation of Clinical Neurophysiology (IFCN) is essential for ensuring high-quality data collection in clinical environments. The DreamMachine, a mobile EEG device that fully meets these standards, offers 24-channel recordings at a 250 Hz sampling rate, Bluetooth Low Energy (BLE), and additional capabilities to capture electrooculography (EOG) and electrocardiography (ECG) signals. With its low cost, it presents an affordable solution for EEG recording. The software architecture of the open-source DreamMachine is detailed in this study. Focus is placed on data compression and communication between the device and its companion Android application. The details of the Android application's features, including gain settings, bits per channel, filters, bit-shifting, and safety factors are investigated. Subsequently, the system's performance is evaluated through a standard eyes open/closed experiment, comparing its results with a laboratory EEG system across a significant number of participants to assess the performance of the DreamMachine system.