bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictors of pulmonary hypertension in the subacute period of myocardial infarction in young and middle-aged males
Authors: Menshikova A. N. , Gordienko A. V. , Sotnikov A. V. , Nosovich D. V.
Published: January 2025

Aim. To identify predictors of the development of pulmonary hypertension (PH) in the subacute period of myocardial infarction (MI) in young and middle-aged males to improve preventive measures.

Materials and methods. We studied the results of treatment of male patients aged 32–60 years with a verified diagnosis of MI. Based on echocardiography findings and detection of PH at the end of the third week of MI, the patients were divided into the study group (patients with PH) and the comparison group (patients with a normal pressure in the pulmonary artery). In the studied groups, a comparative assessment of various parameters was performed, and an analysis of the risks of developing PH using the Pearson’s chi-squared test was conducted.

Results. We found that the risk of developing PH in the subacute period of MI was significantly affected by certain parameters of peripheral hemodynamics, the presence of bradycardia, and the calculated value of total pulmonary resistance. The main parameters of the lipid profile were found to be significant predictors of PH in the subacute period of MI, along with some parameters of electrolyte metabolism (sodium and magnesium in the first 48 hours of MI, potassium and calcium at the end of the third week of the disease). We established the presence of a reliable relationship between several parameters of the structural and functional state of the myocardium both in the first 48 hours of MI and the end of the third week of the disease with the risk of developing PH in the subacute period of MI.

Conclusion. The identified predictors make it possible to determine patients with MI who are at an increased risk of PH to timely diagnose and treat the disease and improve the prognosis.
Regenerative viticulture and climate change resilience
Authors: O'Brien Flora , Nesbit Alistair , Sykes Rebecca , Kemp Belinda
Published: January 2025

Regenerative viticulture (RV) draws on disciplines and concepts such as ecology, agroecology, functional biodiversity, ecosystem services and permaculture, integrated into vineyard management to enhance both production and environmental outcomes. Its core aims are to regenerate vineyard soils and biodiversity, support vine health, enhance vineyard ecological conditions and resilience, and mitigate climate change. The purpose of this review was to evaluate the literature concerning individual, yet often interconnected components of, and approaches to RV, including soil management, cover crops, weeds, pests and diseases, and livestock integration, to establish current knowledge and inform future research opportunities. Where sufficient evidence was available, we also address the impact of RV related practices on vineyard performance, and grape and wine quality characteristics. The review found literature and science supporting viticulture’s potential for: soil and biodiversity regeneration, carbon sequestration, land cooling, ecological enhancements, and soil water holding capacity improvements. There is less consensus regarding the impact of RV approaches on grape yield, wine quality and greenhouse gas (GHG) emissions, as well as a lack of vineyard-based evidence demonstrating the efficacy of biostimulants and Biological Control Agents (BCAs). Research covering a range of regional or context specific environments regarding regenerative approaches or practices are limited, particularly when seeking to address opportunities for, and impacts of whole vineyard systems change–this is a complex area that has not yet been fully addressed. Findings illustrate the emerging status of RV as a researched and/or applied concept, and this review supports those establishing RV systems and contributes to evidence-based RV approaches. It also supports policymakers by highlighting aspects of RV that contribute to the provision and protection of ecosystem services, climate change mitigation and vineyard resilience, fostering opportunities in viticulture.
Application of Islamic business ethics in online marketplace: A study among Bukalapak users in Yogyakarta, Indonesia
Authors: Ilham S. Walhaarik , Andriansyah Yuli , Sobirov Bobur
Published: January 2025

Introduction The rapid growth of e-commerce has revolutionized trade and consumer behavior. Bukalapak, as one of Indonesia’s leading platforms, plays a crucial role in supporting digital transformation for micro, small, and medium enterprises (MSMEs). However, the implementation of Islamic business ethics in e-commerce remains underexplored. This study investigates how Bukalapak applies Islamic business ethics principles and the relationship between security, privacy, non-deception, and reliability. Objectives The research aims to evaluate Bukalapak’s adherence to Islamic business ethics and analyze the influence of ethical dimensions (security, privacy, and non-deception) on user-perceived reliability. Method This quantitative study employed a descriptive research design using Structural Equation Modeling (SEM). Data were collected through online questionnaires distributed to 665 Bukalapak users in Yogyakarta, with variables assessed against the principles of fairness, free will, responsibility, and truth. Results The findings reveal that Bukalapak incorporates Islamic business ethics in its operations. The principles of truth and responsibility are reflected in security, privacy, and non-deception, while free will is evident in non-deceptive practices. However, security, privacy, and non-deception were not significantly correlated with reliability. Implications The study emphasizes the importance of reinforcing ethical practices to enhance user trust in e-commerce platforms. It provides actionable insights for Bukalapak and similar platforms to strengthen the alignment between ethical principles and operational reliability. Originality/Novelty This research offers a pioneering framework for assessing the application of Islamic business ethics in digital commerce. It bridges the gap between theoretical principles and practical implementation, contributing to the discourse on ethical e-commerce practices in Muslim-majority contexts.
Next-Generation Liposomal Drug Delivery Systems: Core Principles, Innovations, and Targeting Strategies
Authors: Sengar Ashutosh
Published: January 2025

Modern therapeutics have come to focus attention on liposomal drug delivery systems as innovative and effective vehicles for targeted drug delivery. Lipid-based vesicles may encapsulate drugs that are either hydrophilic or hydrophobic, bringing about unique advantages such as improved bioavailability, protection of the encapsulated drug from degradation, and the potential to provide controlled and sustained release. Liposomal systems have also been formulated to produce different kinds of formulations including surface-modified liposomes, stealth liposomes, and cationic liposomes; each has a different therapeutic application. The introduction of liposomal systems into some newly emerging technologies like nanotechnology helps target drugs better and personalize treatment protocols. This review on the basics in drug delivery as liposomes that covers structural and compositional aspects, mechanisms associated with the encapsulation, and release, also incorporates new developments in the formulations of liposomal, comparisons between liposomes, and other types of delivery systems, and possibilities in the integration of herbal medicines, such as the Tribulus terrestris to enhance therapeutic performance. Further discussed issues are scaling up, stability, and regulatory challenges of liposomal formulation, besides the opportunities for further advancements of liposomal technology in future pharmaceutical applications. Thus, it is expected that the role of liposomes in personalized medicine will continue to increase significantly with a good prospect for the creation of safer, more efficient, and targeted therapies for most diseases.
Achieving Transparency and Minimizing Loss of Rough Additively Manufactured Optical Components by a Dip-Coating Surface Finish
Authors: Shrotri Abhijeet , Preu Sascha , Stübbe Oliver
Published: January 2025

Additive manufacturing of optical, electrical and mechanical components is a beneficial approach for rapid prototyping of components and error elimination with short turn around times. However, additively manufactured components usually have rough surfaces which need post-processing, in particular for optical components where the surface roughness must be a small fraction of the wavelength. We demonstrate an innovative and economical approach by dip-coating with the same resin as used for printing, providing high transparency of the 3D-printed optical components and reduced surface roughness with perfect index matching of the coating layer in a simple post processing step. The surface roughness of the 3D-printed optical components drops to 5 nm (arithmetic average) after the dip-coating process. We observed significant performance enhancement after comparing the unprocessed optical components and dip-coated optical components, including achieving optical transparency and shiny surface finish of previously rough surfaces.
Navigating Equitable Access to Cancer and Mental Health Services During Pandemics: Stakeholder Perspectives on COVID-19 Challenges and Community-Based Solutions for Immigrants and Refugees – Proceedings from Think Tank Sessions
Authors: Vahabi Mandana , Devotta Kimberly , Ledwos Cliff , Wong Josephine , Narushima Miya , Rayner Jennifer , Hawa Roula , Fung Kenneth , Datta Geetanjali D. , Janczur Axelle , Damba Cynthia , Lofters Aisha
Published: January 2025

Background: Increasing evidence shows that the COVID-19 pandemic has disproportionately impacted certain populations, particularly those facing structural marginalization, such as immigrants and refugees. Additionally, research highlights that structurally marginalized populations living with chronic conditions, such as cancer and/or mental health and addiction (MH&A) disorders, are more vulnerable to the adverse effects of COVID-19. These individuals face higher susceptibility to infection and worse health outcomes, including increased rates of hospitalization, severe illness, and death. To better understand the challenges faced by people living at the intersection of social and clinical disadvantages, we organized a series of Think Tank sessions to engage stakeholders in exploring barriers and identifying community-based solutions for immigrants and refugees living with cancer and/or MH&A disorders during the current and future pandemics.
Methods: Two virtual Think Tank sessions were held in September 2023 as integrative knowledge exchange forums. The Cancer Think Tank was attended by 40 participants, while the MH&A disorders Think Tank included 41 participants. Each group comprised immigrants and refugees living with or affected by cancer (in the Cancer Think Tank) or MH&A disorders (in the MH&A disorders Think Tank), alongside service providers, policymakers, and researchers from Ontario. This paper presents the key discussions and outcomes of these sessions.
Results: Participants identified and prioritized actionable strategies during the Think Tank sessions. In the Cancer Think Tank, participants emphasized the importance of leveraging foreign-trained healthcare providers to address workforce shortages, creating clinical health ambassadors to bridge gaps in care, and connecting immigrants with healthcare providers immediately upon their arrival in Canada. In the MH&A disorders Think Tank, participants highlighted the need to remove silos by fostering intersectoral collaboration, empowering communities and building capacity to support mental health, and moving away from one-size-fits-all approaches to develop tailored interventions that better address diverse needs.
Conclusions: The Think Tank sessions enhanced our understanding of how the COVID-19 pandemic has impacted immigrants and refugees living with cancer and/or MH&A disorders. The insights gained informed a series of actionable recommendations to address the unique needs of these populations during the current pandemic and in future public health crises.
Oxidation of Organic Matter in Wastewater Applying Selective Ionic Flow Cells (SIFC) to Produce Gaseous Hydrogen
Authors: Lozada-Castro Juan Jose , Guerrero-Fajardo Carlos Alberto , Coltan-Solarte Jhon David
Published: January 2025

Applying selective iconic flow cells, it was studied the degradation of organic matter, using urea as reference pattern to a concentration of 10% and domestic residual waters. The experiments were done in two hours, doing analysis in different stages. The chemical demand of oxygen (COD) and to measure the quantity of produced hydrogen by the SIFC, the monitoring system, Mhydros was used. Furthermore, a photovoltaic cell was used of 100 watts as the energy resource for the organic matter oxidation. The results point out that the SIFC do degrade the organic matter and produce energetically viable hydrogen.
Eosinophilic Esophagitis: Etiology, Pathogenesis, Diagnosis and Treatment. Hypothesis.
Authors: Levin Michael
Published: January 2025

Gastroenterologists' recommendations are the results of consensuses adopted by voting at various meetings. In no known science there are new achievements registered by voting. What is happening in gastroenterology is regrettable. At all conferences, most votes recommend not perform histological examination in case of suspected gastroesophageal reflux disease (GERD), since supposedly only pH monitoring provides an objective diagnosis of GERD. The exception is dysphagia with suspected eosinophilic esophagitis (EoE), which cannot be differentiated from GERD and esophageal achalasia without histological examination. Based on the literature review, we have come to the following understanding of the pathophysiology of EoE. Eosinophilic esophagitis is reflux-esophagitis in individuals with an allergic reaction to various food allergens. The trigger is hypersecretion of hydrochloric acid, which disrupts the integrity of the esophageal mucosa and causes an inflammatory reaction, in which, both EoE and GERD, in addition to eosinophils, basal cell hyperplasia, intercellular edema, and elongation of epithelial papillae are observed. There is no absolute histological criterion that allows us to distinguish between EoE and GERD. Different food products can cause an allergic reaction with eosinophilic infiltration in the esophageal wall. Elimination of products that cause allergies from diets leads to a decrease in eosinophilia and clinical improvement in more than 75% of patients. Clinical and histological improvement after refusing to drink milk is explained by the cessation of lactose intake, which in people with lactose intolerance causes hypersecretion of hydrochloric acid. Understanding that EoE is GERD against the background of an allergic reaction allows us to use pathogenetic treatment.
Augmenting Forensic Science Through AI: The Next Leap in Multidisciplinary Approaches
Authors: Montgomery Richard Murdoch
Published: January 2025

Abstract: The field of forensic science has witnessed a remarkable evolution, transitioning from purely analog methods of evidence collection and analysis to highly sophisticated digital systems. Today, this transformation is gaining renewed momentum through the integration of artificial intelligence (AI). By leveraging the power of machine learning, pattern recognition, and data analytics, forensic science stands on the threshold of a revolution that will refine investigative processes and bolster the accuracy of results. This article examines the multidisciplinary nature of forensics, outlines contemporary scientific methods, and explores how AI-driven advancements promise to reshape the field. The synergy between specialists in chemistry, biology, digital forensics, criminology, and computer science is highlighted to demonstrate the inherent collaborative nature of modern investigations. Limitations such as data bias and ethical concerns are addressed, and prospects for near-future developments are discussed. The results indicate that, despite a few constraints, AI represents a tremendous opportunity for forensic science to become faster, more precise, and more efficient.
AI Is Not Intelligent
Authors: Opara Emmanuel
Published: January 2025

The global advancement of Artificial Intelligence (AI) in problem-solving, pattern recognition and natural language processing is notable but it continues to fall short in exhibiting the essential qualities that constitute real intelligence. This paper analyses AI's limitations with philosophical and psychological viewpoints combining them with ethical and technological constraints to show how these systems excel at large data processing and complex tasks but yet remain deficient in the key elements of human intelligence. The operational boundaries of AI systems require them to use statistical analytical models with pattern recognition capabilities rather than actual comprehension or independent decision processing. Without self-awareness artificial intelligence systems create uncertainties regarding who is responsible and how moral judgments should be established. The findings from this paper will advance our current understanding of the distinction between human intelligence and artificial intelligence and the need to understand how AI mechanisms affecting human choices and independence.
Gravitational Wave Distance Estimation Using Intrinsic Signal Properties: Dark Sirens as Distance Indicators
Authors: V Trisha , V Rakesh , Kenath Arun
Published: January 2025

Gravitational Waves (GWs) offer a unique avenue for cosmological distance measurement, bypassing the systematic uncertainties associated with traditional electromagnetic (EM) distance indicators. This paper presents a novel model for estimating the distance to binary black hole (BBH) merger events using only GW data, independent of EM counterparts. By leveraging the intrinsic properties of the GW signal, specifically the strain amplitude and merger frequency, this model provides an efficient preliminary distance estimation approach that can enhance our understanding of the host binary system. Applied to 87 sources from the LIGO and Virgo Gravitational Wave Transient Catalogs (GWTC), the model demonstrates consistent agreement with distances reported by LIGO, validating its reliability as a GW only estimator. This model offers a promising solution for BBH systems, which typically lack detectable EM signatures, thereby expanding the scope of GW-based cosmology. Additionally, this approach provides critical preliminary distance estimates that can inform parameter constraints for BBH systems during subsequent analyses, enhancing our capacity to probe the universe using dark sirens.
Treatment with Kampo Medicine and Minocycline for Influenza
Authors: Ohe Masashi , Tsuchida Naoshi
Published: January 2025

The main classes of antiviral drugs used to treat influenza are M2 inhibitors (e.g., amantadine), neuraminidase inhibitors (e.g., oseltamivir, zanamivir, and peramivir), and cap-dependent endonuclease inhibitors (e.g., baloxavir marboxil). Amantadine, a pioneering antiviral drug, was globally used for treating influenza. However, influenza A viruses have developed resistance to amantadine. Neuraminidase inhibitors are also at a risk of developing resistance. Combination treatments including these drugs have been successfully administered as new therapeutic approaches for addressing the issue of resistance. Kampo medicine, which is based on traditional Chinese medicine, is traditional Japanese medicine with unique theories and therapeutic methods. Kampo medicines including Mao-to, Kakkon-to, Sho-seiryu-to, Sho-saiko-to, and Saiko-keishi-to have been empirically used for treating influenza. Kampo medicines are mainly composed of organic plant-based ingredients. The ingredients used to make Kampo medicine include Ephedra herb, Ziziphus jujuba, Glycyrrhiza, Bupleurum root, and others, the extracts of which have demonstrated anti-influenza and/or anti-inflammatory activities. Recently, minocycline, a tetracycline, was also observed to exert anti-influenza virus activities. Multidrug treatment is more effective compared with single-drug treatment because of the synergistic effects of the different mechanisms of actions of the drugs involved. Therefore, we propose the combination of Kampo medicine and minocycline for treating influenza as an alternative to the above-mentioned conventional drugs and hope that this might resolve the issue of conventional drug-resistant influenza.
Leveraging Blockchain for Ethical AI: Mitigating Digital Threats and Strengthening Societal Resilience
Authors: Norta Alex , Udokwu Chibuzor , Voicu-Dorobanțu Roxana , Ogunyemi Abiodun Afolayan , Sturua Nata , Crass Stefan
Published: January 2025

The rise of online activities and the increasing prevalence of artificial intelligence (AI) in socio-technical systems have brought about both significant opportunities and ethical challenges. Among these challenges, one of the most relevant is addressing digital threats such as sextortion (a form of coercion and sexual exploitation) that disproportionately affect vulnerable groups, such as minors. This position paper advocates the integration of blockchain technology into AI systems to enhance trust, transparency, and ethical governance in combating such threats. The paper argues that, by adhering to ethical guidelines, the specific integration of blockchain operations that bring about strong decentralization, immutability, and auditability into AI may be better managed. Through a literature review and using the specific case study of sextortion, we propose a set of guidelines that ensure secure data management, empower victims, and support law enforcement efforts. This set of guidelines aims to strengthen societal resilience by ensuring privacy, security, and transparency in AI-driven systems and using technology ’for good.’ The paper explores the potential of blockchain-integrated AI in various stages of sextortion mitigation, from prevention through education and early detection to providing immediate support and facilitating secure reporting. Consequently, we put forward the position that blockchain-decentralized AI models integrated with user-controlled data wallets considerably enhance the trust in and transparency of AI models. In this way, the paper proposes that a balance should exist between the innovation potential of blockchain-decentralized AI models versus the ethical implications. The paper highlights the critical intersection of ethical AI development, social resilience, and digital ethics and addresses the complexities of integrating technologies while emphasizing the need for interdisciplinary collaboration and adaptive policy frameworks.
Generative AI in Learning: Empowering the Next Generation of Education
Authors: Bura Chiranjeevi
Published: January 2025

The emergence of Generative Artificial Intelligence (GenAI) marks a transformative moment in educational technology, fundamentally reshaping teaching and learning methodologies. This comprehensive study examines the multifaceted impact of GenAI in education, analyzing its current applications, challenges, and future implications through a systematic review of recent literature and emerging practices. We explore how GenAI technologies enhance personalized learning, automate administrative tasks, foster creative problem-solving skills, and support inclusive education. The research particularly focuses on the intersection of learning analytics and AI, the evolution from algorithmic approaches to human-centered learning, and the development of sustainable AI integration in education. This paper also addresses critical concerns regarding ethical implementation, equity in access, and the evolving role of educators in an AI-enhanced educational landscape, while proposing frameworks for effective integration and future development.
A Unified Model of Energy-Space Dynamics: The Dynamic Equilibrium Approach
Authors: Zhao Roy
Published: January 2025

This paper introduces the "Dynamic Equilibrium Model of Energy and Space," proposing that the universe operates as a dynamically balanced system where energy and space are two inseparable aspects of the same phenomenon. By redefining gravity as "compressive pressure," the model provides novel explanations for macroscopic phenomena like the Big Bang, black hole formation, and cosmic expansion, as well as microscopic effects such as quantum entanglement and tunneling. The theory intro-duces a nonlinear correction to classical gravitational laws, enabling better descriptions of extreme gravitational environments. Testable predictions, such as directional variations in cosmic expansion and microscopic gravitational effects, are proposed, offering new experimental pathways to validate the theory. This model presents a unified framework bridging general relativity and quantum mechanics, aiming to resolve foundational inconsistencies and inspire fresh perspectives in cosmology and fundamental physics.
A Machine Learning Framework for Predicting Structural Failures in Ship Recycling: Overcoming Data Gaps Across Recycling Methods
Authors: Akpadiaha Ini
Published: January 2025

This paper introduces a machine learning framework to predict structural failures during ship dismantling, focusing on four common recycling methods: Dry Docking, Pier Breaking/Alongside, Landing/Slipway, and Beaching. The framework leverages advanced techniques, including generative data imputation (WFGAIN-GP), GAN-based augmentation, and a multi-model approach combining Random Forests and Graph Neural Networks, to address challenges like incomplete data and method-specific risks. Results indicate that beaching poses the highest failure risks due to uncontrolled stresses, while Landing/Slipway methods demonstrated the lowest failure probabilities in this study, attributed to ship-specific factors such as age and corrosion rates. The model also highlights the influence of recycling methods on structural risks and showcases the potential for integrating real-time monitoring to enhance safety and operational efficiency. Future work will focus on validating the model with real-world data and incorporating advanced degradation models to improve predictive accuracy. This framework provides a robust foundation for improving safety and risk management in the ship recycling industry.
Cross-Reactions at the Table: Pollen Food Allergy Syndrome in Southern Europe’s Adults
Authors: Rousou Christina , Kostin Egor , Christodoulou Eleni , Theodorou Theodoros , Pavlou Zenon , Pitsios Constantinos
Published: January 2025

Oral Allergy Syndrome (OAS) and Pollen Food Allergy Syndrome (PFAS) represent significant challenges in allergy research. This review examines the epidemiology, pathogenesis, and diagnostic approaches of OAS and PFAS, with a focus on their prevalence and impact in the adult population in Southern Europe. Key panallergens such as profilins, PR-10 proteins, and lipid transfer proteins (LTPs) are highlighted for their role in mediating PFAS, and their regional variation. The review explores the differential prevalence of PFAS across Southen Europe countries, where multi-sensitization to pollen like Olive, Cypress, Parietaria, Mugwort, and Grass is common, and underscores unique en-vironmental and ecological factors contributing to this phenomenon. Cross-reactivity, a hallmark of PFAS, is explored with emphasis on the interactions between common Southern European pollens and foods, such as fruits, nuts, and vegetables. Diagnostic challenges, including symptom variability, underreporting, and the need for region-specific diagnostic algorithms, are discussed. This comprehensive review aims to deepen understanding of OAS and PFAS among adults in the Mediterranean region of Southern Europe, offering insights that can improve the diagnosis, management, and overall care for this population.
Is Deuterium Sequestering by Reactive Carbon Atoms an Important Biological Mechanism to Reduce Deuterium Content in Biological Water?
Authors: Seneff Stephanie , Nigh Greg , Kyriakopoulos Anthony
Published: January 2025

Deuterium is a natural heavy isotope of hydrogen, having a neutron as well as a proton. Theoretically, deuterium disrupts ATP synthesis in mitochondria, causing increased production of reactive oxygen species and reduced synthesis of ATP. Gut microbes likely play a significant role in providing deuterium depleted short chain fatty acids (SCFAs) to human colonocytes, through hydrogen gas recycling. The production of deuterium depleted (deupleted) nutrients necessarily leaves behind deuterium enriched water, unless there is a process that can sequester deuterium in small molecules that are excreted through the faeces. Here, we provide evidence that a small number of classes of uniquely structured carbon-nitrogen rings and bis-allylic carbon atoms in certain biologically active small molecules may play a crucial role in sequestering deuterium for export into faeces or urine. Specifically, we have identified the amino acid proline, the imidazole ring present in histidine, histamine, and microbial derivatives of histidine, the tetraterpenoid lutein and likely related molecules derived from plants, bilirubin and the derivatives urobilinogen and stercobilinogen produced by gut microbes, the bis-allylic carbons in polyunsaturated fatty acids, and 8-dehydrocholesterol, an intermediate in the cholesterol synthesis pathway, as likely candidates for sequestering deuterium and thereby reducing the deuterium levels in the water-based medium. Normally, carbon atoms never exchange their bound protons with deuterons from the medium, but all the above classes of molecules are important exceptions to this rule, as has been shown experimentally. This is likely not an exhaustive list.
Immobilization of Enzyme on Electrode and Electrode Design in Biofuel Cell
Authors: Chen Chang-Yen , Bojang Adama A. , Damayanti Damayanti , Wu Ho Shing
Published: January 2025

In an enzyme-based fuel cell system, glucose oxidase and laccase were immobilized on carbon papers as the anode and cathode electrodes. A conductive polymer (polypyrrole) was added to improve conductivity. The mediator and enzyme were mixed in a phosphate buffer solution for entrapment. A Nafion 212 membrane separated the two half-cells. Power density measurements were taken at a glucose concentration of 10 mM across different operating voltages. Potassium hexacyanoferrate III was used as a redox mediator in the anode, and 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) in the cathode to boost power output. The biofuel cell, constructed from acrylic (40 mm × 50 mm × 50 mm) with a working volume of 20 mm × 30 mm × 40 mm, was assembled using a rubber gasket to secure the Nafion membrane. Micropore tape covering the electrodes extended the system's operational lifespan. Without micropore tape, the maximum power density was 57.6 μW/cm² at 0.24 V. With micropore tape, the cell achieved a maximum power density of 324.9 μW/cm² at 0.57 V, sustaining performance for 20 day. Thus, micropore tape effectively enhances enzyme retention and biofuel cell performance.
Trustworthy AI for Whom? GenAI Detection Techniques of Trust Through Decentralized Web3 Ecosystems
Authors: Calzada Igor , Németh Géza , Al-Radhi Mohammed Salah
Published: January 2025

As generative AI (GenAI) technologies proliferate, the need for trust and transparency in digital ecosystems intensifies, especially within democratic frameworks. This article investigates decentralized Web3 mechanisms, specifically those based on blockchain, decentralized autonomous organizations (DAOs), and data cooperatives, to establish robust detection techniques fostering trust in GenAI. These mechanisms are explored against the backdrop of the EU-funded Horizon Europe lighthouse project on Trustworthy AI entitled ENFIELD as foundational elements that support content authenticity, community-driven verification, and data sovereignty, aligning with the EU’s AI Act and Draghi Report policy framework. After a state-of-the-art deep analysis, this article presents a multi-layered framework to address the risks associated with AI-generated misinformation encompassing seven detection techniques of trust, including (i) federated learning for decentralized AI detection, (ii) blockchain-based provenance tracking, (iii) Zero-Knowledge Proofs for content authentication, (iv) DAOs for crowdsourced verification, (v) AI-powered digital watermarking, (vi) explainable AI (XAI) for content detection, and (vii) Privacy-Preserving Machine Learning (PPML). This approach not only strengthens AI governance through P2P frameworks but also mitigates the socio-political impacts of AI on public trust, offering a pathway through these seven techniques to allow resilient democratic systems in an era of increasing technopolitical polarization.
Essential Oils as an Antifungal Alternative to Control Several Species of Fungi Isolated of Musa paradisiaca: Part III
Authors: RuizMedina MaritzaD. , Ruales Jenny
Published: January 2025

Essential oils are widely recognized for their antifungal properties, their effectiveness against fungi fungal remains an area of active research. This study evaluates the antifungal potential of essential oils from oregano (Origanum vulgare), rosemary (Salvia rosmarinus), clove (Syzygium aromaticum), thyme (Thymus), cinnamon (Cinnamomum verum), and basil (Ocimum basilicum) in inhibiting the growth of fungi associated with banana rot, Fusarium spp., Colletotrichum spp., and Verticillium spp. Dilutions containing all the relevant fungal species were prepared and inoculated onto PDA medium supplemented with chloramphenicol for fungal growth assessment. Subcultures were performed weekly to obtain isolated and purified fungal strains, followed by macroscopic and microscopic analysis to identify the genera. Growth inhibition was quantified through in vitro inhibition and ex vivo. Results revealed that thyme exhibited the highest antifungal activity, with complete inhibition at 1000 ppm, while the cinnamon and oregano essential oils showed effective inhibition at 600 ppm. In contrast, rosemary, basil, and clove did not demonstrate significant inhibitory effects at the tested concentrations. These findings suggest that specific essential oils offer a natural alternative for controlling banana rot fungi, supporting their potential use in integrated disease management strategies.
Moving Forward in Effective Deployment of the Smart Readiness Indicator and the ISO 52120 Standard to Improve Energy Performance with Building Automation and Control Systems
Authors: Walczyk Gabriela , Ożadowicz Andrzej
Published: January 2025

The transition towards energy-efficient and sustainable buildings is a cornerstone of global efforts to combat climate change. Building Automation and Control Systems (BACS), standardized under EN ISO 52120, and the Smart Readiness Indicator (SRI) have emerged as pivotal tools for optimizing energy performance, integrating smart technologies, and enhancing building adaptability. This review provides a comprehensive analysis of the current research landscape and practical applications of these frameworks, focusing on their role in advancing energy efficiency, occupant comfort, and environmental sustainability. Key contributions include an exploration of challenges in SRI evaluation, considering the limitations of simplified methods, the need for long-term validation, and gaps in integrating advanced control functions. The study emphasizes innovative solutions for adapting SRI assessments to diverse building types, climate conditions, and regulatory frameworks. Furthermore, it presents original insights into leveraging advanced technologies, including Building Information Modeling (BIM) and Digital Twins (DT), to refine SRI evaluation methods and optimize BACS system designs. These findings contribute to the development of sustainable, intelligent buildings that align with EU climate goals. The authors conclude by highlighting promising directions for future research to further enhance smart energy and strategic facility management practices.
A Zero-Shot Comparison of Large Language Models for Efficient Screening in Periodontal Regeneration Research
Authors: Galli Carlo , Colangelo Maria Teresa , Guizzardi Stefano , Meleti Marco , Calciolari Elena
Published: January 2025

The relentless growth of biomedical literature poses a significant challenge for systematic reviews, where manually screening thousands of studies can be very laborious. In this study, we explored the performance of large language models (LLMs) to assist in identifying randomized controlled trials (RCTs) pertaining to periodontal regeneration interventions. Starting from a recent review on Emdogain and bone grafts, we identified a target set of RCTs fulfilling its key inclusion criteria and then retrieved a larger pool of thematically related PubMed articles using the query “periodontal regeneration.” Each article was embedded using all-mpnet-base-v2, and the resulting vectors were compared against the mean embedding of the target set to group articles into quartiles of descending relevance. Various LLMs (Open Hermes, Flan T5, GPT-2, GPT-3.5 turbo and GPT-4o) were then tasked with classifying each article in the 4 datasets as “Accepted” or “Rejected.” By comparing their predictions, we calculated classification performance metrics. Overall, the results show that different LLM respond differently to prompt strategies and can effectively perform this task (or sub-tasks), confirming the potential role of these tools to expedite systematic reviews.
Surgical Site Infections: A Comprehensive Review
Authors: Rezaei Ahmad Reza , Zienkiewicz Damian , Rezaei Amir Reza
Published: January 2025

Surgical site infections are an important public health problem leading to increased morbidity and mortality and healthcare costs across the globe. The paper provides a systematic review of the epidemiology, classification, risk factors, microbiological aspects, treatment modalities, and prevention strategies of surgical site infections based on contemporary research and evidence-based practice protocols. Some of the more salient global concerns identified by surgical site infections have been antibiotic resistance and the contamination of surgical instruments, especially in resource-poor settings. These reports underscore the importance of preventive measures, such as appropriate preoperative interventions, strict use of aseptic technique, and appropriate antibiotic prophylaxis, in making the incidence of SSIs and patient outcomes improve better.
The Impact of Institutional Arbitration Rules on Corporate Dispute Resolution Efficiency
Authors: Broklyn Chris , Tioluwani Rhema
Published: January 2025

The growing complexity and globalization of business have heightened the importance of efficient and effective dispute resolution mechanisms. Institutional arbitration, as an alternative to traditional court litigation, plays a pivotal role in corporate dispute resolution. This study explores the impact of institutional arbitration rules on the efficiency of corporate dispute resolution, focusing on factors such as cost, speed, neutrality, enforceability, and flexibility. By analyzing the rules of major arbitration institutions, including the International Chamber of Commerce (ICC), the London Court of International Arbitration (LCIA), and the American Arbitration Association (AAA), the paper assesses how these rules streamline dispute resolution processes, mitigate risks of lengthy legal battles, and foster greater confidence among businesses. The findings indicate that well-designed institutional arbitration rules contribute to the acceleration of dispute resolution, reduction of costs, and ensure impartiality in the decision-making process. However, challenges remain, such as inconsistent application of rules and the potential for complexity in cross-border cases. The study concludes with recommendations for enhancing arbitration rules to further improve corporate dispute resolution efficiency, while emphasizing the need for continual adaptation to the evolving needs of global businesses.
Correlación entre riesgos psicosociales y estrés laboral en médicos de un instituto de medicina legal en el norte del Perú
Authors:   , Santa Cruz Garcia Veronica Medali , Alarcon Jimenez Jessica Jacqueline
Published: January 2025

Introducción. La medicina legal implica una exposición constante a riesgos psicosociales que pueden incrementar los niveles de estrés laboral, afectando la salud de los médicos. Objetivo. Determinar la correlación entre los riesgos psicosociales y el estrés laboral en médicos del Instituto de Medicina Legal en el norte del Perú. Métodos. Se llevó a cabo un estudio no experimental, transversal, con 26 médicos, utilizando cuestionarios validados para medir los riesgos psicosociales y el estrés. Resultados. Los resultados indicaron que todos los médicos con riesgo psicosocial presentaban también estrés laboral. El análisis multivariado mostró que la prevalencia de estrés en este grupo fue siete veces mayor que en aquellos sin riesgo psicosocial, y 6.95 veces mayor en el análisis ajustado, siendo un resultado estadísticamente significativo. Conclusión. Existe una asociación significativa entre riesgos psicosociales y estrés laboral, lo que hace crucial implementar intervenciones para mejorar su salud y la calidad del servicio.
New Crush Testing Method to Evaluate Proppant Performance Under Downhole Conditions
Authors: Nguyen T. C. , Dong T. N. , Yoo H. , Thieu T. K.
Published: January 2025

The main objective is to present a new crush testing method which, in contrast to the American Petroleum Institute (API) Crush Test, determines the proppant's ability to maintain its original size at specific applied pressures. This new crush test provides a better methodology for comparing and selecting a proppant type for hydraulic fracturing to maximize well performance and drastically improve cumulative well output and decline curve forecasting.

Four samples of 40/140 mesh proppants were utilized. Initially, an API Crush Test was conducted to establish reference data. Subsequently, the new crushing testing method was performed, isolating each mesh size to determine the size's Retention of Original Size % under specific applied pressures. The Weight Score for each size was calculated by multiplying the Retained Original Size % by its distribution %. To assess total sample strength, an Effective Weight Score (EWS) was introduced by summing all weight scores together. Proppant permeability before and after crushing was measured to gain insights into performance under pressures ranging from 4,000 to 10,000 psi. Correlations between the EWS and permeability reduction were then established to enhance estimation of proppant performance under downhole conditions.

Results indicate that the samples #1, #2, #3, and #4 passed the API Crush Test under pressures of 7,000, 8,000, 10,000, and 11,000 psi respectively, assigning them K-Values (or K-Factors) of 7K, 8K, 10K, and 11K. However, it was observed that the K-Value is dictated by the smallest size in the sample, and therefore the manipulation of the distribution, especially the smallest sizes (i.e. 140-mesh) and larger sizes (i.e. 45 mesh), can dramatically alter the K- Value. Consequently, the API Crush Test was deemed unsuitable for assessing proppant strength or comparing samples.

The new crush testing method utilizes the EWS to indicate the percentage of a sample that maintains its original size under a specific pressure. Unlike the API Crush Test which grades the sample using the smallest size, the EWS simply provides the proportion of the entire sample that remains intact versus that which is crushed into smaller sizes. This makes the EWS a more reliable parameter for comparing sample strengths. Applying the new crush testing method to the four sand samples yielded vastly different results than the API Test: EWS values under 8,000 psi of 55.5%, 58.7%, 83.9%, and 85.7%, respectively. Strong correlations were observed between EWS values and permeability reduction, further supporting the efficacy of the new crush testing method for evaluating proppant performance.

The new crush testing method offers a superior methodology compared to the API Crush Test for selecting proppant types for hydraulic fracturing. Its implementation promises to maximize well performance, significantly improve cumulative well output, and enhance decline curve forecasting.
Utilizing Empirical Data and Theoretical Modeling to Build a Bigger Box and Increase Production
Authors: Hilton Tim , Bradham Connor , Aro Dustin , Gibbons Robert
Published: January 2025

Within the Permian Basin in Texas, the San Andres generally garners attention as a produced water disposal zone in the Midland and Delaware Basins or as a case study for enhanced oil recovery methods. The horizontal well development in the Northwest Shelf of the Permian Basin has steadily increased production to over 40,000 BOPD amongst several operators deploying replicable drilling programs followed by standard completion methodologies.

Initial technical focus was on how to reduce the water cut and optimize oil production by properly selecting well location. Additional work looked to improve results by analyzing theoretical well placement and model the fracture geometry and production against an existing well. As with any probabilistic workflow, the results were mixed with petrophysical heterogeneity being the primary determinant of the model accuracy (Yang et al. 2019).

This paper presents a comprehensive workflow based on a multi-well/multi-section development with over ten years of production history. All wells target the San Andres formation thus allowing for a consistent geologic reservoir model as field development expanded over time. The development timeline is organized into distinct time periods (2013-2016 (I), 2017-2020 (II) & 2021-2023 (III)) that are grouped according to well design and completion parameters. Phase III operations have increased Child well production +50-80% greater than the Parent wells and simultaneously decreased water production. The operator thus reduced the payback period for each new well drilled while increasing proved undeveloped (PUD) acreage.
Fracture Growth Through Microseismic Quiescent Zones: Indication of Stealth or Complex Fracturing?
Authors: Maxwell S. C. , Doss S. , Holman R. , Bryce B.
Published: January 2025

Often microseismicity levels tend to vary from one lithological unit to the next, with some layers being predominantly quiet and lack any microseismicity. Since shear activated deformation associated with microseismicity will depend on the geomechanical properties and natural fabric of the formation, the lack of microseisms in certain layers may or may not be indicative of a change in the hydraulic fracture geometry. In this work, microseismic observations are integrated with strain and other observations to investigate the microseismic response in relation to the underlying hydraulic fracture geometry for different rock types. The combined conclusions allow identification of two distinct types of response for aseismic layers. The first type are ‘stealth’ homogeneous layers that behave aseismically with the lack of natural fabric to host shear activated microseisms from consistent fracture growth. The second type are interbedded shaly layers where the lack of microseismicity is associated with fracture complexity that results in compartmentalized portions of the hydraulic fracture which may not effectively drain the reservoir. Examples are described of these types from integrated monitoring of hydraulic fracture growth in Uinta Basin, Utah and Midland Basin, Texas.