bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Hyaluronic Acid-Sorbitol formulation in Patients Undergoing Knee Arthroscopy: Effects on Pain and Articular Recovery
Authors: Giusti Simone , Di Paola Berardino , De Fenu Edoardo , Caria Clemente , Adriani Ezio
Published: January 2025

Background: Following non-bleeding arthroscopy, patients that are injected with 6 ml of hyaluronic acid (2%) and sorbitol (4%) formulation (Synolis VA) show better results in terms of pain reduction and improved mobility recovery compared to patients that did not receive the treatment. Introduction: Although there is no best irrigation solution for the knee arthroscopy, many studies showed that the common irrigation fluids, especially cold ones, are toxic for the articular chondrocytes, suppressing their metabolism and function. The purpose of this study is to evaluate the clinical outcome of patients injected with Synolis V-A after knee arthroscopy. Materials and Methods: 60 patients were randomly divided into 2 groups. At the end of the procedure 30 patients received an intra-articular injection of hyaluronic acid (2%) and Sorbitol (4%) solution for a total of 6 ml (2 ml per syringe), the remaining 30 patients did not receive any treatment. Inclusion criteria: age (ranging from 18 to 60 years), meniscectomy or cartilage treatment (non-bleeding knee arthroscopy), body mass index (<30). Patients with joint-line misalignment, ligamentous lesions, bone pathology, synovial membrane pathology, rheumatoid arthritis or inflammatory disease, or pregnancy were excluded from the study. Patients were reviewed at several follow-up points and monitored using outcomes such as the IKDC subjective knee evaluation score, pain variaton (using VAS and WOMAC pain sub-score) and variation of stiffness (using WOMAC Stiffnes sub-score). Patients were also asked to fill in a self-assessment questionnaire on a weekly basis as well as at each visit in order to follow the clinical evolution of the symptoms. The statistical analysis was performed with IBM SPSS Statistics for Windows, Version 28.0. Results: Patients injected with Synolis V-A at the short and intermediate check-points showing better clinical results than the patients that were not injected with the product; these patients had higher IKDC Subjective Knee Evaluation scores, as well as lower point of pain and reduced stiffness. Conclusions: Based on our results, the injection with hyaluronic acid (2%)/sorbitol (4%) formulation (Synolis V-A) in patients undergoing non-bleeding arthroscopy for degenerative and traumatic changes to the knee joint effectively reduces pain and improves mobility in the short-term post-operative phase.
Unveiling Long COVID: General Perceptions and Challenges for Diagnosis and Management
Authors: Ozanic Katia , Watanabe Aripuana Sakurada Aranha , Machado Alessandra Barbosa Ferreira , da Silva Vania Lucia , Dias Vanessa Cordeiro , Diniz Claudio Galuppo
Published: January 2025

On March 11, 2020, the World Health Organization (WHO) declared a pandemic caused by SARS-CoV-2, raising global health concerns. Reports of persistent and new symptoms following the acute phase of infection highlighted the complexities of recovery and prompted the investigation of what is now termed long COVID. Officially recognized by the WHO in October 2021, long COVID presents various health implications, though terminology—such as post-COVID syndrome and post-acute sequelae of COVID-19 (PASC)—remains inconsistent, complicating diagnostic standardization. Long COVID affects an estimated 10% to 30% of SARS-CoV-2 infected individuals, with common symptoms including fatigue, dyspnea, cognitive dysfunction, and joint pain, all of which significantly impair quality of life. Public perception is influenced by factors like education and health history, while misinformation and stigma hinder accurate diagnosis and treatment. The absence of biomarkers and overlap with other post-viral syndromes further complicate clinical recognition. Experts emphasize the need for refined diagnostic criteria and integrated strategies combining biomedical research, public policy, and educational initiatives to improve clinical management, address healthcare inequalities, and mitigate the impacts of long COVID. This review unveils state of art and knowledge gaps to raise discussion leading to better clinical decision-making and public awareness related to long COVID.
Assessment of the Inter and Intra-Individual Variability in the Jump of Agility Dogs
Authors: López Patricia , Gutiérrez-Cepeda Luna , Miró Francisco
Published: January 2025

Although significant progress has been made in recent years regarding jumping biomechanics of agility dogs, there is still a lack of data on the specific biomechanical pattern of the jump. The main objective of the present study was to describe the biomechanic variables involved in the jumping pattern of agility dogs, analyzing both intra- and inter-individual variability. Eleven agility dogs were analyzed while jumping over a 60-cm hurdle. Results of low or acceptable and similar intra and inter-individual coefficients of variation obtained in variables such as percentage of take-off and landing distances, percentages of take-off and landing durations, maximum jump height, jump height at the hurdle and percentage duration to maximum jump height, may indicate these variables as components of a general biomechanical pattern of jumping in agility dogs. Low or acceptable and consistent intra- and inter-individual variation observed in variables such as percentage of take-off and landing distances, percentages of take-off and landing durations, maximum jump height, jump height at the hurdle, and percentage duration to maximum jump height suggests that these variables could represent key elements of a general biomechanical jumping pattern in agility dogs. This stability, maintained across multiple jumps by the same dog and across different dogs, highlights their potential as reliable indicators of a shared biomechanical framework for jumping. Lower intra-individual than interindividual coefficients of variation obtained in most of the angular variables, jump distance, jump duration and speed, take-off, and landing distances, and jump heights at take-off and at landing indicate these variables as related with the individual technique of each animal. All of this data can be used in the design of training plans as well as when monitoring the progress of canine athletes.
Carbamoylated Erythropoietin Rescues Social Deficits in a Mouse Model of Autism
Authors: Street Amaya L. , Thakkar Vedant P. , Lemke Sean W. , Schoenbeck Liza M. , Schumacher Kevin M. , Sathyanesan Monica , Newton Samuel S. , Kloth Alexander D.
Published: January 2025

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects over 2% of the population worldwide and is characterized by repetitive behaviors, restricted areas of interest, deficits in social communication, and high levels of anxiety. Currently, there are no known effective treatments for the core features of ASD. Previous literature has established erythropoietin (EPO) as a promising antidepressant, working as a potent neurogenic and neurotrophic agent with hematopoietic side effects. Carbamoylated erythropoietin (CEPO), a chemically engineered non-hematopoietic derivative of EPO, appears to retain the neuroprotective factors of EPO without the hematologic properties. Recent evidence shows that CEPO corrects stress-related depressive behaviors in BALB/cJ (BALB) mice, which also have face validity as an ASD mouse model. We investigated whether CEPO can recover deficient social and anxiety-related behavioral deficits, as compared to C57BL/6J controls. After administering CEPO (40 μg/kg in phosphate-buffered saline) or vehicle over 21 days, we analyzed performance in the three-chamber social approach, the open field, the elevated plus maze, and the Porsolt’s forced swim tasks. CEPO appears to correct sociability in the three-chamber social approach task to C57 levels, increasing the amount of time mice interacted with novel, social mice overall rather than altering the overall amount of exploratory activity in the maze. Consistent with this finding, there was no concomitant increase in distance traveled in the open field, nor was there an alteration of anxiety-related measures in the task. On the other hand, CEPO administration improved exploratory behavior in the elevated-plus maze. This study marks the first demonstration of the benefits of a non-erythropoietic EPO derivative for social behavior in a mouse model of autism and merits further investigation of the mechanisms by which this action occurs.
Pain Management in Burned Patients Treated with Bromelain-Based Enzymatic Debridement
Authors: Laurens Acevedo Michelle , Usua Gemma , Barret Juan P.
Published: January 2025

Background: Bromelain-based enzymatic debridement is a treatment for deep partial and full thickness burns. It is a painful procedure that requires anaesthesia techniques. However, there is limited information on the best strategy to guarantee adequate pain control. Objective: To describe the anaesthetic strategy in patients treated with bromelain-based enzymatic debridement after burn injury. Methods: We performed an observational retrospective study by recording data from the clinical records of burned patients treated with bromelain-based enzymatic debridement. Patients admitted to the Burn Unit of Vall d´Hebron University Hospital between January 2015 and December 2019 were included. Results: We enrolled 112 patients that met the inclusion criteria. The mean burned total body surface area (TBSA) was 10.7% ± 11.34 and the median Abbreviated Burn Severity Index (ABSI) was 5 (2–12). The most frequently burned and treated areas were the upper limbs (73%), followed by the lower limbs (30%) and abdomen (8%). Regional anaesthesia was the most used technique, accounting for 96% of the cases. Axillary blockage was performed in 47% of the patients, with a continuous catheter being placed in 31% of them. In the next 48 hours after bromelain-based enzymatic debridement, 61% of the patients had controlled pain. In 12.5% of the cases, opioids were used for pain relief after the procedure, and in 2.7% of the cases, the anaesthesia technique was repeated. There were no differences in pain control when single nerve block was compared with catheter placement (p = 0.809). Complications appeared in nine patients and included hypotension, nausea and urinary retention. Conclusions: Bromelain-based enzymatic debridement is a painful procedure that requires advanced and specialized anaesthesia management. Regional anaesthesia techniques are a feasible and safe strategy for pain control. Optimal analgesia in the first 48 hours is still a challenge in these patients.
Urban Green Space Measurements: A Narrative Review of Practical Applications
Authors: Lee Doo-Hong , Chamberlain Brent , Park Hye-Yeon
Published: January 2025

Interdisciplinary research has significantly advanced Urban Green Space (UGS) measurement by employing objective methods tailored to diverse research objectives. Despite this progress, the varied development of UGS measurement techniques calls for a comprehensive review to integrate and evaluate these approaches. This narrative review examines constructs underlying UGS measurements, emphasizing objective and GIS-enabled datasets, and highlights recent advancements in measuring greenness visibility. Specifically, it focuses on two methods: the viewshed-based and the image segmentation-based methods, proposing their classification under "Perspective View." Our findings reveal a shift in UGS measurement focus, moving beyond simple quantification to incorporate visibility, accessibility, and availability dimensions. Moreover, this review demonstrates the growing relevance of hybrid techniques integrating quantitative and qualitative approaches, such as combining GPS data with visibility analyses. These techniques bridge the gap between physical and perceptual aspects of greenspaces, enhancing their applicability in urban planning and public health. Furthermore, advancements in computational tools, including AI-driven methods, now enable high-resolution visibility measurements on a city-wide scale, supporting epidemiological research and urban development. These insights aim to guide researchers and practitioners in selecting suitable methodologies and datasets, fostering the collection of diverse UGS data for practical management and policymaking. By providing a structured framework for UGS measurement, this review contributes to the development of more equitable and effective urban greenspace strategies.
A Quantitative Evaluation of the Impact of Digital Transformation on Operational Efficiency in Service-Oriented Organizations
Authors: Nath Avishek , Onib Sayed Abdullah Al Sanazid , Barsa Nusrat Jahan , Anika Afrin
Published: January 2025

This research seeks to evaluate the impact of digital transformation on improving operational efficiency in service-oriented firms in Bangladesh. In a time when digital technologies are swiftly transforming company processes, comprehending the unique aspects that propel operational enhancements is crucial for firms to maintain competitiveness. The study identified five main elements that affect operational efficiency: Digital Technology Adoption, Employee Digital Proficiency, Leadership Support for Digital Transformation, Customer-Centric Digital Strategies, and Availability of Digital Infrastructure. The research used a survey methodology, gathering data from 218 participants employed in service-oriented firms. The investigation indicated that the availability of digital infrastructure is essential for enhancing operational efficiency, demonstrating a substantial positive association between the two variables. Moreover, while Digital Technology Adoption and Employee Digital Skills had a modest correlation with operational efficiency, their effects were less significant than those of infrastructure. This research revealed that although leadership support and customer-centric initiatives are essential for overall organizational success, their impact on operational efficiency is more indirect. The results underscore the need of investing in resilient digital infrastructure and recommend that businesses prioritize ongoing skill development and effective leadership to achieve successful digital transformation. The study gives significant insights for managers and policymakers seeking to enhance digital transformation initiatives inside service-oriented firms in Bangladesh and suggests avenues for further research in this domain.
The Utilization of The Large Unstained Cell (LUC) Parameter in Lymphoid, Haematopoietic and Related Tissue’s Malignant Neoplasms
Authors: Gök Gamze , Erdoǧan Serpil , Asutay Erbay , Yılmaz Gülsen , Erel Özcan , Yılmaz Fatma Meriç
Published: January 2025

Large unstained cells (LUC) is a differential count parameter reported by routine hematology analysis, and LUC percentages (LUC %) reflect active lymphocytes and peroxidase-negative cells. We aimed the evaluate the LUC % parameter in routine practice towards malignant neoplasms, stated or presumed to be primary, of lymphoid, haematopoietic, and related tissue. LUC analysis was performed with Siemens ADVIA® 2120 Hematology System. Data were obtained from Ankara Bilkent City Hospital’s laboratory information system. A statistical difference in the LUC % data in the case of LUC % <4.5 and LUC % ≥4.5 among preliminary diagnoses was observed (p<0.001). According to the Kruskal-Wallis test, a statistical difference was observed between preliminary diagnosis and LUC % values (p<0.001). The One-way ANOVA test with Bonferroni correction was performed for post hoc multiple comparisons of the preliminary diagnosis among LUC%. LUC % was higher in Hodgkin Lymphoma patients than Myeloid leukaemia patients (p=0.002). LUC % was higher in the Lymphoid leukaemia patients than in the patients with Hodgkin lymphoma (p<0.001), Other and unspecified types of non-Hodgkin lymphoma (p<0.001), Multiple myeloma and malignant plasma cell neoplasms (p<0.001). LUC % was higher in patients with leukemia unspecified cell type than Hodgkin lymphoma (p<0.001), Follicular lymphoma (p<0.001), Non-follicular lymphoma (p<0.001), Mature T/NK-cell lymphomas (p<0.001), Other and unspecified types of non-Hodgkin lymphoma (p<0.001), Malignant immunoproliferative diseases (p<0.001), Multiple myeloma and malignant plasma cell neoplasms (p<0.001), Lymphoid leukaemia (p<0.001), Myeloid leukaemia (p<0.001), Other leukaemias of specified cell type patients (p<0.001). Prospective studies may be useful in assessing LUC%.
A Timescale in AltPNT: New Dynamic Radio Resource Assignments and Clock Steering Strategies
Authors: Pham Khanh
Published: January 2025

Terrestrial and satellite communications, tactical data links, positioning, navigation, and timing (PNT), and distributed sensing will continue requiring precision timing and the ability to synchronize and disseminate time. However, as the supply of space-qualified clocks with Global Navigation Satellite Systems (GNSS)-level performance is limited and the understanding of disruptions to GNSS due to potential adversarial actions increases, the current practice of reliance on the GNSS-level timing becomes costly and outdated when compared with an on-orbit assembly of robust and stable timescale references, especially being considered as the development of diverse alternatives to GNSS. Onboard realization of clock ensembles is particularly attractive for applications such as on-demand dissemination of GPS Time (GPST) like navigation services via a proliferated Low-Earth-Orbit (pLEO) constellation. This article investigates the overarching goal of agility and reprogrammability, where rate-based linear quadratic regulators for both communication and clock data transfer services are proposed to flexibly allocate radio resources away from primary communication services to clock data transfer services for on-demand pLEOT formations within pLEO constellations. Next, the work here is proposing the model-based control of wireless networked timing systems. It embraces the vision of optimally placing critical information of the implicit ensemble mean (IEM) estimation about the multi-platform clock ensemble that has better stability than any individual member of the ensemble on the network to flexibly reduce the data traffic. By making the remote sensor of IEM estimates running onboard the anchor platform and actuators for optimal steering of remote frequency standards located at participating platforms more "intelligent" that supports onboard IEM timescale realizations across a pLEO constellation, the networked control system can predict future behaviors of local reference clocks accompanied with low-noise oscillators and then send precise information on the IEM estimation at critical times to ensure the realization of a common pLEO timescale onboard all participating platforms. Clock steering is especially essential for the realization of timescales. Performance realizations are generally dependent on the control intervals and steering techniques chosen. Towards performance robustness beyond what the existing steering technique of Linear Quadratic Gaussian control can offer, the minimal-cost-variance (MCV) steering paradigm is proposed from the perspective of minimizing the variance of the integral-quadratic-form performance measure of the Linear Quadratic Gaussian control subject to a constraint on its mean.
Whole Cottonseed as an Effective Strategy to Mitigate Enteric Methane Emissions in Cattle Fed Low-Quality Forages
Authors: Hernández Olegario , López Agustin , Ceron Cucchi María Esperanza , AdégbéÏga Alabi Cham Donald , Loza Cecilia , Juárez Sequeira Ana Veronica , Fissolo Héctor Miguel , García Elisa Mariana , Gere José Ignacio
Published: January 2025

This study evaluated enteric methane (CH₄) emissions, dry matter intake (DMI), and performance in rearing beef heifers fed either a guinea grass-only diet (0WCS) or guinea grass supplemented with whole cottonseed (WCS) at 0.5% of body weight (BW). Twenty-four Braford heifers were randomly allocated into four pens (three animals per pen) per treatment over two experimental periods. Methane emissions were measured using the SF₆ tracer technique. Heifers receiving WCS supplementation produced 29% less CH₄ (120.64 vs. 169.54 g/day for 0.5WCS and 0WCS, respectively; p = 0.02) and showed a 22% reduction in CH₄ yield (7.30% vs. 9.41% of gross energy intake; p = 0.02). Methane intensity was 33% lower in supplemented heifers (0.37 vs. 0.55 g CH₄/kg BW; p = 0.01). However, WCS supplementation significantly reduced total DMI and forage DMI (p = 0.01 and p < 0.01, respectively). In terms of performance, heifers in the 0.5WCS group gained 0.24 kg/day, while those in the 0WCS group lost 0.10 kg/day. These results indicate that WCS supplementation mitigates CH₄ emissions while improving weight gain in beef heifers fed low-quality forage diets, making it a promising strategy for enhancing the sustainability of beef cattle production systems.
Integrating Synthetic Data and Deep Learning for Enhanced Defect Detection and Quality Assurance in Manufacturing Processes
Authors: Moghadam Armin , Bhatia Sahib , Davoudi Kakhki Fatemeh , Ichikawa Hiroyuki
Published: January 2025

In this research, we investigate an advanced methodology for process monitoring in manufacturing that employs synthetic data with deep learning to enhance production and process quality monitoring. Traditionally, process supervision in the manufacturing industry has depended on manual checks and physical sensors, which are costly, time-consuming, and prone to errors. The study introduces a new approach that utilizes synthetic data to train deep learning models for precise defect detection in 3D-printed objects. We further recommend diverse data augmentation and fine-tuning techniques to improve model efficacy. Our evaluation demonstrates an impressive 90% overall accuracy in real-object defect detection, with a 93% precision rate in identifying defects. These results suggest that models trained on synthetic data are effectively equivalent to those trained on real-world data, indicating that the technique used to generate synthetic data is pivotal to model performance. This innovative strategy mitigates the challenges associated with conventional process monitoring methods, and addresses the practical challenges of applying such technological advancements in actual manufacturing environments. By enabling the creation of extensive training datasets and applying deep learning algorithms for object and pattern recognition, this approach boosts the precision and efficiency of operational supervision within the manufacturing process. The approach and findings of this study significantly enhances efficiency, accuracy, and the overall effectiveness of quality assurance in manufacturing.
Experimental Assessment on Multiple Properties of Mycelium-Based Composites with Sewage Sludge and Bagasse
Authors: Hu Min , Cao Xuejuan
Published: January 2025

Because of their superior environmental performance, mycelium-based composites (MBCs) offer a promising sustainable lightweight alternative material. MBCs are frequently prepared using agricultural by-products as substrates. However, because agricultural by-products are seasonal, their output is limited by a constant need for substrates. In order to examine the feasibility of creating MBCs using sewage sludge (SS) in place of bagasse, this study used SS and bagasse as nutrient substrates and cultivated MBCs on ready-made mycelium (Pleurotus ostreatus). The physico-mechanical properties, morphological properties, and thermal stability analysis were tested and analyzed. The results showed that the bagasse MBCs’ colonization appearance took precedernce over that of the SS MBCs at early stagy. However, both the bagasse and SS promoted fungal growth to create a dense mycelial network on day 10. The bagasse-based MBCs were the lightest and adding SS increased the density and compressive strength of the MBCs. The volume shrinkage first decreased and then increased. The optimal ratio of mycelium to sewage sludge was 2:1, which produced an outstanding compressive strength of 690.20 KPa. The thermal conductivity of bagasse-based and SS-based MBCs were 0.12 Wm-1K-1 and 0.13 Wm-1K-1. The physico-mechanical characteristics satisfiy the requirements of lightweight backfill materials in highway. Additionally, SS improved the hyphae of MBCs, giving them a denser and stronger structure. In comparison to bagasse, it also showed better thermal stability and a higher residual mass. It is feasible to produce MBCs with SS in place of bagasse, and the biocomposite proposed in this study could be used as lightweight backfill materials that are widely needed in highway.
Proposal of a Modified Bayesian Model to Improve the Clinical Utility of Treadmill Stress Testing
Authors: Peters Robert M.
Published: January 2025

Bayes' theorem has been an integral part of traditional treadmill stress testing for many years. However,
several issues have been raised regarding this approach: imperfect identification of important coronary obstruction, limited usefulness in certain patients, inconsistent results and interpretation, and confusion
regarding the outcomes of various studies. This has led to disenchantment with basic stress testing in
favor of more expensive methods, and difficulties for the clinicians managing patients. The proposal presented in this paper modifies the traditional Bayes approach so as to provide greater clinical utility for
physicians perfoming treadmill stress tests.
A Novel Beneficiary‐Centric Analysis of Public Distribution System Constraints: Evidence from Multi‐Regional Assessment in an Emerging Economy
Authors: Smith Mary
Published: January 2025

This study examines the operational constraints affecting India's Public Distribution System (PDS), with particular focus on beneficiary experiences across northern, central, southern, and eastern states. Employing a multi-stage random sampling methodology, the research analysed data from 1,120 beneficiaries (560 rural, 560 urban) using Garrett's ranking technique to quantify the relative significance of identified constraints. Seven critical implementation challenges were evaluated: quality of foodgrains, geographical accessibility, temporal consistency of distribution, procedural efficiency, waiting times, staff behaviour, and inventory management. The findings reveal that the provision of inferior quality foodgrains consistently emerges as the primary constraint across regions, achieving the highest Garrett scores (ranging from 60.85 to 73.16). The non-availability of scheme-specified items ranks second in severity, particularly pronounced in central states (GS: 68.48 in rural areas). Operational inefficiencies, manifested through multiple visits to Fair Price Shops, constitute the third most significant barrier, with notable urban-rural variations in impact. The research indicates that while physical access and staff behaviour pose minimal impediments, systemic issues in quality control and supply chain management require immediate policy intervention to enhance PDS effectiveness in ensuring food security for vulnerable populations.
Fusion of Improved A* Algorithm and Optimal Dynamic Window Approach for Mobile Robot Path Planning
Authors: Zong Ruilong , Lin Jianhui
Published: January 2025

Aiming at global path planning of mobile robot in unknown environment and how to avoid random dynamic and static obstacles in unknown environment, A path planning algorithm combining improved A* algorithm and optimized dynamic window method is proposed. The A* algorithm has a more comprehensive global path planning ability, and has a good computational speed, but also is currently the most widely used algorithm for global path planning. But the traditional A* algorithm also has many drawbacks, low search efficiency in complex environments, the existence of a large number of redundant nodes, the path is not smooth and other problems. Therefore, this paper proposes an improved A* algorithm first, which reduces the search direction, removes redundant turning points and covariance nodes, and obtains a smooth optimal planning path after Bessel curve optimization; secondly, it is optimized for the single motion state of the dynamic window method, and the safety distance is set to cope with obstacles that have a similar motion state to the robot, and the improved A* algorithm is integrated with the optimized dynamic window method, so as to meet the global planning The improved A* algorithm is integrated with the optimized dynamic window method, so as to realize obstacle avoidance in the face of random obstacles at the local position while satisfying the optimal curve in the global planning path. After simulation experiments with the traditional A* algorithm in several groups of different environments, the experimental results are obtained, the improved A* algorithm has obvious advantages in global path planning, the computation time is reduced by 40%, the search nodes are reduced by 50%, and the cost of global path search is reduced by 75%, and the fusion with the optimized dynamic window method can solve the local obstacle avoidance problem very well.
Text-Guided Synthesis in Medical Multimedia Retrieval: A Framework for Enhanced Colonoscopy Image Classification and Segmentation
Authors: Peter Ojonugwa Oluwafemi Ejiga , Taiwo Adeniran Opeyemi Taiwo , John-Otumu Adetokunbo Macgregor , Khalifa Fahmi , Rahman Md Mahmudur
Published: January 2025

The lack of extensive, varied, and thoroughly annotated datasets impedes the advancement
of Artificial Intelligence (AI) for medical applications, specially colorectal cancer detection. Models
trained with limited diversity often display biases, especially when utilized on disadvantaged
groups. Generative models (e.g., DALL-E 2, VQ-GAN) ‘have been used to generate images, but
not colonoscopy data for intelligent data augmentation. This study developed an effective method
for producing synthetic colonoscopy image data, which can be used to train advanced medical
diagnostic models for robust colorectal cancer detection and treatment. Text-to-image synthesis was
performed using fine-tuned Visual LLMs. Stable Diffusion and DreamBooth Low Rank Adaptation
produce images that look authentic, with an average Inception score of 2.36 across three datasets.
The validation accuracy of various classification models– BiT, FixResNeXt, and EfficientNet– were
92%, 91%, and 86%, respectively. ViT and DeiT had an accuracy rate of 93%. Secondly, for the
segmentation of polyps, the ground truth masks are generated using SAM. Then, five segmentation
models (U-Net, PSNet, FPN, LinkNet, and MANet) were adopted. FPN produced excellent results,
with an IoU of 0.64, an F1-score of 0.72, a recall of 0.87, and a Dice Coefficient of 0.72. This highlights
how AI-generated medical images can improve colonoscopy analysis, which is critical for early
colorectal cancer detection.
Lithum Battery Enhacement Throught Electrical Characterization and Optimization Using Deep Learning
Authors: de Anda-Suárez Juan , Pérez-Zúñiga Germán , López-Ramírez José Luis , Herrera-Pérez Gabriel , Zeferino González Isaías , Verde-Gómez José Ysmael
Published: January 2025

Currently, research on lithium-ion batteries has been driven by increased demand for electric vehicles to mitigate greenhouse gas emissions. Despite advances, batteries still face significant challenges in efficiency, lifetime, safety, and material optimization for their production. In this context, we present a Transformer-based deep learning model to predict lithium-ion batteries' charging and discharging behavior from their electrochemical parameters. A database of experiments characterized by their electrochemistry and their charge-discharge response was performed to achieve this goal. The database was generated by experimentation on a set of commercial batteries and new approaches in materials science. Subsequently, a model based on the Deep-Learning Transformers methodology was designed and trained from the database measurements. The results show that the deep-learning model can accurately predict lithium-ion batteries' charging and discharging behavior, even in complex scenarios such as abrupt changes in charging capacity. In conclusion, developing a Transformer deep-learning-based model to predict lithium-ion batteries' charging and discharging behavior is effective. These results significantly affect the battery industry and their optimization in electric vehicles.
Polypyrrole Hybrid Nanocomposite Electrode Materials with Outstanding Specific Capacitance
Authors: Andezai Andekuba , Iroh Jude
Published: January 2025

This study investigates the processing condition of modified carbon nanotube sheets doped with polypyrrole (CNTs-PPy) for high-performance energy storage applications, focusing on the impact of processing temperatures. The hybrid nanocomposites were prepared by coating CNTs with PI. The composites were then processed at three different temperatures 90°C, 180°C, and 250°C to study the effects of thermal treatment on their electrochemical properties. After processing, the composites underwent electrodeposition with polypyrrole (PPy) to enhance their electrochemical performance. A comprehensive set of electrochemical tests, including cyclic voltammetry (CV) and galvanostatic charge-discharge (GCD), was employed to assess the nanocomposites' specific capacitance, charge-discharge efficiency, and cycling stability. The results revealed that the composite processed at 90°C exhibited the highest specific capacitance, reaching up to 655.34 F/g at a scan rate of 5 mV/s. This composite also demonstrated excellent cycling stability, with only minimal capacitance loss over 10 cycles. The superior performance at 90°C is attributed to the optimal microstructural properties achieved at this temperature, including enhanced porosity, and effective PPy deposition, all of which contribute to improved ion transport and reduced internal resistance. In contrast, composites processed at higher temperatures (180°C and 250°C) exhibited significantly lower specific capacitance and reduced cycling stability. These findings suggest that higher temperatures may induce adverse structural changes, such as increased bulk resistance and reduced porosity, which negatively impact the electrochemical performance of the composites. The study underscores the importance of carefully controlling processing temperatures to improve the structural integrity and electrochemical functionality of PI/CNTs-PPy hybrid nanocomposites for advanced energy storage systems.
Unmasking the Silent Threat: Prevalence of Cardiovascular Risk Factors in MS Patients
Authors: Pleșa Florentina Cristina , Arsene Elena Andreea , Pleșa Andreea , Bucurică Săndica , Anghel Daniela , Sîrbu Carmen Adella , Țânțu Monica Marilena , Badea Alexandru Andrei , Vasiliu Octavian , Munteanu Alice Elena
Published: January 2025

This study aims to identify cardiovascular risk factors among 91 patients with multiple sclerosis in Bucharest, Romania, using data from medical records and a self-administered questionnaire. The research focuses on smoking status, body mass index, blood sugar, cholesterol, triglycerides, blood pressure and renal function. The average age of the patients was 42.90 ± 10.60 years and 74.73% were female. The average BMI was 23.89 kg/m2 ± 4.74 kg/m2 (lower than in general population), with 41.76% of patients having a BMI outside normal limits. The majority were former smokers (35.87%), followed by non-smokers (28.26%) and the fewest were smokers with more than 20 cigarettes/day (7.61%). The average total cholesterol was 198.48 ± 38.56 mg/dl, triglycerides were 114.22 mg/dL ± 76.2281 mg/ dl, and blood glucose was 97.54 ± 36.58 mg/dl. 25.27% of the patients had fasting blood glucose > 126 mg/dl, but only 5 patients were diagnosed with DM. The average blood pressure was 137,5165 ± 19,5047 mmHg, with only 11 patients diagnosed with HTA. The study found an average cardiovascular risk of 6,6133% ± 7,1412%, with higher values among males, rural patients, those with secondary-progressive MS, and those with a disease progression >10 years (after age adjustment). The study underscores the importance of identifying and combating cardiovascular risk factors in patients with multiple sclerosis.
Hybrid Convolutional Neural Network with Intuitionistic Fuzzy Estimates for Detection of Children Pneumonia
Authors: Sotirov Sotir , Orozova Daniela , Angelov Boris , Sotirova Evdokia , Vylcheva Magdalena
Published: January 2025

Pneumonia is one of the leading causes of morbidity and mortality in children, making its early detection critical for effective treatment. In this paper, we propose a novel approach for detecting childhood pneumonia using a hybrid convolutional neural network (CNN) enhanced with intuitionistic fuzzy estimations (IFE). The hybrid model integrates the powerful feature extraction capabilities of CNN with the uncertainty handling and decision-making strengths of intuitionistic fuzzy logic. By incorporating IFE, the model is better equipped to handle ambiguity and noise in medical imaging data, resulting in more accurate and robust pneumonia detection. Experimental results on pediatric chest X-ray datasets demonstrate the effectiveness of the proposed method, achieving higher sensitivity and specificity compared to traditional CNN approaches. This hybrid model offers a promising tool to assist healthcare professionals in early and accurate diagnosis of pneumonia in children.
Bloom Meets Gen AI: Reconceptualising Bloom's Taxonomy in the Era of Co-piloted Learning
Authors: Jain Jasmine , Samuel Moses
Published: January 2025

The rapid integration of generative Artificial Intelligence (AI) in educational contexts has fundamentally altered traditional pedagogical frameworks, particularly affecting the application and assessment of Bloom's Taxonomy. This shift presents significant challenges in maintaining student learning integrity and accurately measuring educational outcomes. This perspective paper critically examines these challenges, proposing a reconceptualization of Bloom's Cognitive Taxonomy to align with AI-enhanced learning environments. We argue for an updated framework that incorporates new cognitive levels, "Ventriloquising” and “Co-curating”, and the overlapping cognitive skills which we now labelled “Critical Understanding”. This reconceptualization advocates for viewing cognitive skills as interconnected nodes rather than hierarchical steps, reflecting the nuanced interactions between human learners and AI tools. The paper posits that assessment strategies must evolve to incorporate process measures, capturing the complexity of cognitive engagement facilitated by AI. We call for a dual approach, balancing AI's computational capabilities with human critical judgment (IA), to optimize educational outcomes. We invite readers to engage with this reconceptualisation, critically evaluate its implications, and contribute to the ongoing discourse on the future of learning and assessment in the age of Gen AI.
The Legal Environment of Digital Trade Inevitable for Sustainable Industrial Revolution
Authors: Aslam Muhammad Faisal , Wang Baomin , Zaidi Syed Yasir Abbas , Aslam Zubair
Published: January 2025

The article explores the history of industrial revolutions and their impact on various indus-tries and public life. Authors argue that industrial transformation and innovation are mani-festations of the Fourth Industrial Revolution (FIR), which introduced new technologies like virtual-real space, quality procedures, robotic systems, and smart factories. We examine how the widespread use of information and communication technology (ICT) has signifi-cantly altered economic behavior and highlighted the importance of new laws for sustaina-ble development. Additionally, we discuss that the fourth industrial revolution, character-ized by linked items, digitalization, artificial intelligence, and 3D printing, has led to in-creased automation and fragmentation of value chains worldwide. We also examine elec-tronic trade as a crucial component of industrialized nations' logistics value chain and eco-nomic strength. In this article, we highlighted the COVID-19 pandemic increasing the im-portance of digital trade for the resilience of the economy. We explore all the world gov-ernments now prepared to expand and supervise the digital economy by introducing new digital laws. However, least-developed countries struggle due to limited resources, infra-structure, and finance for substantial digital economy investments, emphasizing the need for increased digital economy skills and resources.
Week 48 Results from Dolutegravir/Lamivudine Versus Bictegravir/Emtricitabine/ Tenofovir Alafenamide Fumarate: Real-World Assessment of Weight Gain in Naïve People Living with HIV of Asian OrigiN (Dragon)
Authors: Yang Chia-Jui , Zhao Qingxia , Hsih Wen-Hsin , Ho Mao-Wang , Chen Tsung-Chia , Tsai Mao-Song , Lee Shu-Yuan , Lin Yi-Chun , Chen Cheng-Pin , Cheng Shu-Hsing , Zhang Xue , Zou Meiyin , Wu Yi-Wen , Huang Miao-Hui , Hung Tung-Che , Ma Ping , Cheng Chien-Yu
Published: January 2025

Several studies have demonstrated that significant weight gain occurs in some people living with HIV (PWH) after initiating integrase strand transfer inhibitors (INSTIs). Most studies on weight change have been clinical trials primarily focused on Africa, Europe, and North America, with limited representation from real-world studies in Asia. This retrospective observational study, conducted at nine designated HIV-care hospitals from March 2019 to January 2024, aimed to address this gap. Of the 533 patients screened, 314 met the criteria for the BIC/FTC/TAF group, while 181 qualified for the DTG/3TC group. At week 48, 86.3% of patients in the DTG/3TC group and 84.8% in the BIC/FTC/TAF group achieved HIV RNA <50 copies/mL (difference: 1.5%; 95% CI: -5.4% to 8.4%; p=0.67, evaluated in a snapshot, per-protocol-exposed population), meeting the criteria of non-inferiority. After calculating inverse probability of treatment weights, logistic regression analysis identified the following risk factors for weight gain of ≥10% at week 48: BIC/FTC/TAF (aOR 1.72; 95% CI: 1.16–2.54; p<0.01), CD4 counts <200 cells/uL (aOR 2.00; 95% CI: 1.32–3.03; p<0.01), HIV RNA ≥100,000 copies/mL (aOR 2.05; 95% CI: 1.37–3.07; p<0.01), and BMI <24 (aOR 3.51, 95% CI: 2.29–5.37, p<0.01). In conclusion, the study demonstrates that INSTIs, particularly BIC/FTC/TAF, may lead to significant weight gain in Asia. Furthermore, consistently high and comparable effectiveness was observed in both the BIC/FTC/TAF and DTG/3TC groups. Prospective studies involving a larger number of patients are warranted to further explore these findings.
The RSJ  and Winchester University Press 2024 Biennial Book Prize Report
Authors: Rohr Dr. Zita Eva
Published: January 2025

This report contains details of the RSJ and Winchester University Press Biennial Book Prize Campaign and the announcement of the winner.
Islamic Philanthropy and Social Services in Improving Community Welfare in Indonesia
Authors: Makhrus M , Hasan Ibnu , Budi Santoso Selamet Eko
Published: January 2025

Poverty in Indonesia has become a complex and multisectoral issue, necessitating comprehensive handling involving all stakeholders, including civil society and Islamic philanthropy managers. Islamic philanthropic activism in Indonesia continues to expand, as evidenced by a growing public understanding of the importance of channeling donations through institutions. Donations collected by Islamic philanthropic organizations are channeled into charity programs for non-urgent needs and productive programs with lasting effects on community empowerment. This form of research employs a qualitative-descriptive methodology. This study examines an Islamic philanthropic organization using documentation and observation techniques to collect data, and qualitative deductive and inductive methods to analyze the data qualitatively. The findings of this study indicate that Islamic philanthropy and social services in improving welfare carried out by Islamic philanthropy management organizations in Indonesia are manifested in various fields, including social, economic, educational, and health, and are channeled as assistance and empowerment programs to improve public welfare. The organization’s capacity to manage Islamic philanthropy is achieved by integrating its programs, policies, and services with government and private agencies with similar objectives. In measuring the impact of Islamic philanthropy and social services on enhancing community welfare, Islamic philanthropic organizations consider a change in thought patterns, attitudes, and actions in living life based on one’s abilities. Consequently, charitable social services have taken the form of empowerment programs in a society with lasting effects.
The Effect of Macroeconomic Variables on the Profitability of Islamic Commercial Banks in Indonesia
Authors: Huda Miftahul , Rofiqo Azidni , Abdul Razak Abdurrizqi Bin , Nabila Fikriyyatun
Published: January 2025

Islamic banks as a form of banking that operates based on sharia principles, are expected to show superior financial performance when compared to interest-based conventional banks. This study aims to determine the effect of inflation, JUB, and PUAS on the profitability of Indonesian Islamic Commercial Banks. The method used in this research is a deductive quantitative method, with the Vector Autoregressive (VAR) Vector Error Correction Model (VECM) approach and the E-Views 12 test tool. The data used in this study used secondary data with time series data from the period January 2013 to April 2023, where ROA was used as an independent variable and Inflation, Money Supply, and Islamic Interbank Money Market became the dependent variable. As for the results of this study, in the long term, the variables of Inflation and JUB have a significant and negative effect on the Return on Assets (ROA) of Indonesian Islamic Commercial Banks, while the Islamic Interbank Money Market (PUAS) variable does not have a significant and negative effect on the Return on Assets (ROA) of Indonesian Islamic Commercial Banks. In the short term, the variables of Inflation, Money Supply (JUB), and the Islamic Interbank Money Market (PUAS) do not have a significant and negative influence on the Return on Assets (ROA) of Indonesian Islamic Commercial Banks.
Literature Review: Factors Influencing Purchasing Decisions in the Service Industry
Authors: Umpusinga Hasrun Afandi , Warganegara Tri Lestira Putri , Alam Iskandar Ali , Habiburrahman Habiburrahman , Barusman Andala Rama Putra
Published: January 2025

This research focuses on the factors that interact with each other and influence consumers' purchasing decisions, as well as how implementing effective marketing strategies can influence these decisions across various industry sectors. The purpose of the study is to examine studies that are relevant to purchase decisions, this study uses a qualitative method with a systematic literature study approach, which is an assessment and analysis of previous research related to purchase decisions, using the keywords "Purchase Decision" and "Travel" in the period from 2004 to 2024 (20 years). The results of the study found that purchasing decisions are influenced by cognitive dissonance, social influence, corporate alliances, brand equity, brand preferences, gender roles: female dominance, online forum browsing, price, online reviews, promotions, demographics, travel preferences, domestic family decisions, brand decisions, price decisions, circle of acquaintance decisions, compromises, temporal constructions, perceived ease of use, electronic word of mouth, content marketing,  Brand image, lifestyle, trust in tour packages, trust in payment methods, intention to purchase tour services, promotion of online tour services, place of residence, previous purchase experience, information sources used and perception of reliability, professional status, age, education level, financial situation, and perception of value.