bluuebunny/crossref_metadata_2025 huggingface dataset:
Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach
Authors: Ni Haowei , Meng Shuchen , Chen Xupeng , Zhao Ziqing , Chen Andi , Li Panfeng , Zhang Shiyao , Yin Qifu , Wang Yuanqing , Chan Yuxi
Published: August 2024

Accurate stock market predictions following earnings reports are crucial for investors. Traditional methods, particularly classical machine learning models, struggle with these predictions because they cannot effectively process and interpret extensive textual data contained in earnings reports and often overlook nuances that influence market movements. This paper introduces an advanced approach by employing Large Language Models (LLMs) instruction fine-tuned with a novel combination of instruction-based techniques and quantized low-rank adaptation (QLoRA) compression. Our methodology integrates ‘base factors’, such as financial metric growth and earnings transcripts, with ‘external factors’, including recent market indices performances and analyst grades, to create a rich, supervised dataset. This comprehensive dataset enables our models to achieve superior predictive performance in terms of accuracy, weighted F1, and Matthews correlation coefficient (MCC), especially evident in the comparison with benchmarks such as GPT-4. We specifically highlight the efficacy of the llama-3-8b-Instruct-4bit model, which showcases significant improvements over baseline models. The paper also discusses the potential of expanding the output capabilities to include a ‘Hold’ option and extending the prediction horizon, aiming to accommodate various investment styles and time frames. This study not only demonstrates the power of integrating cutting-edge AI with fine-tuned financial data but also paves the way for future research in enhancing AI-driven financial analysis tools.
Exploration of Genes Related to Intramuscular Fat Deposition in Xinjiang Brown Bulls
Authors: Wanping Ren , Yu Gao , Liang Yang , Kangyu Yao , Yiran Wang , Wei Shao , Min Yang , Xinyu Zhang , Yong Wei
Published: August 2024

The aim of this study was to investigate the differentially expressed genes associated with intramuscular fat deposition in the longissimus dorsi muscle of Xinjiang Brown Bulls. The longissimus dorsi muscles of 42 Xinjiang Brown Bulls were selected under the same feeding conditions. The intramuscular fat content of muscle samples were determined by Soxhlet extraction method, from which 5 samples with high intramuscular fat content (HIMF group) and 5 samples with low intramuscular fat content (LIMF group) were selected. It was found that the intramuscular fat content of HIMF group was 46.054% higher than that of LIMF group. Muscle samples produced by paraffin section for morphological observation. It was found that the fat richness of the HIMF group was better than that of the LIMF group. Transcriptome sequencing technology was used to analyze the gene expression differences of longissimus dorsi muscle. Through in-depth analysis of the longissimus dorsi muscle by transcriptome sequencing technology, we screened a total of 165 differentially expressed genes. The results of Gene Ontology (GO) enrichment analysis showed that the differentially expressed genes in the two groups were mainly clustered in biological pathways related to carbohydrate metabolic processes, redox processes and oxidoreductase activities. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the differentially expressed genes were significantly clustered in 15 metabolic pathways, which mainly covered fatty acid metabolism (related to lipid metabolism and glucose metabolism), pentose phosphate pathway, Peroxisome Proliferator-Activated Receptors (PPAR) signalling pathway and other important metabolic processes. The three genes that were predominantly enriched in the glycolipid metabolic pathway by analysis were SCD5, CPT1C, and FBP2, all of which directly or indirectly affect intramuscular fat deposition. In summary, the present study investigated the differences in gene expression between high and low intramuscular fat content in the longissimus dorsi muscle of Xinjiang Brown Bulls by transcriptome sequencing technology, and revealed the related signalling pathways. Therefore, we hypothesized that SCD5, CPT1C, and FBP2 were the key genes responsible for the significant differences in intramuscular fat content of the longissimus dorsi muscles in a population of Xinjiang Brown Bulls. We expect that these findings will provide fundamental support for subsequent studies exploring key genes affecting fat deposition characteristics in Xinjiang Brown Bulls.
Equine Gait Analysis: New Techniques, Trials and Thinking
Authors: Harrison Adrian , Isbell Diane , Bowker Robert
Published: August 2024

Veterinary science has benefitted from technological advancements in the past and will hopefully continue to do so, especially in the field of equine gait analysis. There is a need for rapid and easy to use technology that is accurate and portable, but at the same time is also readily interpretable. This manuscript presents two new approaches to equine gait analysis, both of which are commer-cial devices. The use of Acoustic MyoGraphy (AMG) has been proven in the field of muscle func-tion and performance as well as ligament health, but it can also provide details concerning gait when placed on the wall of the hoof of a horse. The TendibootTM system is a limb focused unit that can be easily attached, activated and used in a Veterinary clinic setting, rapidly providing gait details for equine diagnostic purposes. In conclusion this manuscript provides an insight into gait parameters from recent research trials that are novel and challenge current thinking.
Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients
Authors: Lu Xiaolei , Qiao Chenye , Wang Hujun , Li Yingqi , Wang Congxiao , Wang Yingpeng , Qie Shuyan
Published: August 2024

Background: Three-dimensional gait analysis plays a crucial role in the rehabilitation assessment of post-stroke hemiplegic patients. However, the data generated from such analysis is often complex and difficult to interpret in clinical practice, requiring extensive time and complicated procedures. The Gait Deviation Index (GDI) serves as a simplified metric for quantifying the severity of pathological gait. Although isokinetic dynamometry is widely employed in muscle function assessment and rehabilitation, its application in gait analysis remains underexplored. Objective: This study aims to investigate the use of isokinetic muscle strength data obtained from the Biodex system, combined with machine learning techniques, to predict the GDI in hemiplegic patients. Methods: A cohort of 150 post-stroke hemiplegic patients was evaluated. The peak torque, peak torque/body weight, maximum work of repeated actions, coefficient of variation, average power, total work, acceleration time, deceleration time, range of motion, and average peak torque for both flexor and extensor muscles on the affected side were measured at three angular velocities (60°/s, 90°/s, and 120°/s) using the Biodex System 4 Pro. GDI was calculated using data from a Vicon three-dimensional motion capture system. The study employed four machine learning models—Lasso regression, random forest (RF), support vector regression (SVR), and BP neural networks—to model and validate the data. Model performance was evaluated using mean squared error (MSE), the coefficient of determination (R²), and mean absolute error (MAE). SHapley Additive exPlanations (SHAP) analysis was used to enhance model interpretability. Results: The RF model outperformed others in predicting GDI, with an MSE of 16.18, an R² of 0.89, and an MAE of 2.99. In contrast, the Lasso regression model yielded an MSE of 22.29, an R² of 0.85, and an MAE of 3.71. The SVR model had an MSE of 31.58, an R² of 0.82, and an MAE of 7.68, while the BP neural network exhibited the poorest performance with an MSE of 50.38, an R² of 0.79, and an MAE of 9.59. SHAP analysis identified the maximum work of repeated actions of the extensor muscles at 60°/s and 120°/s as the most critical features for predicting GDI, underscoring the importance of muscle strength metrics at varying speeds in rehabilitation assessments. Conclusion: This study highlights the potential of machine learning techniques in analyzing complex clinical data. The developed GDI prediction model, based on isokinetic dynamometry data, offers a novel, streamlined, and effective tool for assessing rehabilitation progress in post-stroke hemiplegic patients, with promising implications for broader clinical application.
Improved Small Object Detection Algorithm CRL-YOLOv5
Authors: Wang Zhiyuan , Men Shujun , Bai Yuntian , Yuan Yutong , Wang Jiamin , Wang Kanglei , Zhang Lei
Published: August 2024

Detecting small objects in images poses significant challenges due to their limited pixel representation and the difficulty in extracting sufficient features, often leading to missed or false detections. To address these challenges and enhance detection accuracy, this paper presents an improved small object detection algorithm, CRL-YOLOv5. The proposed approach integrates the CBAM attention mechanism into the C3 module of the backbone network, which enhances the localization accuracy of small objects. Additionally, the Receptive Field Block (RFB) module is introduced to expand the model's receptive field, thereby fully leveraging contextual information. Furthermore, the network architecture is restructured to include an additional detection layer specifically for small objects, allowing for deeper feature extraction from shallow layers. When tested on the VisDrone2019 small object dataset, CRL-YOLOv5 achieved an mAP50 of 39.2%, representing a 5.4% improvement over the original YOLOv5, effectively boosting the detection precision for small objects in images.
Real-Time Document Collaboration System Using Orchestrated Containers
Authors: Iovescu Daniel , Tudose Cătălin
Published: August 2024

In modern times, technology has become more than just a tool; it is a vital component of our lives, driving society and humanity towards new horizons, better living standards, and solu-tions for complex, global challenges. This article explores the world of dependable systems, specifically focusing on system design, software solutions, and architectural decisions that fa-cilitate collaborative work. It aims to dive into the intricacies of designing robust and effective document collaboration software. Throughout this paper, readers will gain insights into the proposed design process, enabling them to understand, learn from, and critically evaluate the examined methodologies and outcomes. Like everything else in the software technology field, there are multiple solutions to any given problem, and this work is no exception to this rule.
The objective of this study is to provide a detailed architectural overview of the microservices pattern in an orchestrated cloud environment based on independent containers. To examine the pros and cons of such a system, the paper will detail how a real-time document collaboration system can benefit from such an architecture regarding availability, elasticity, scaling, and disaster recovery.
Moreover, the paper will analyze how cloud-native technologies can be used to create a scalable platform solution, capable of handling traffic, dynamic resource storage, asynchronous com-munication, and application scaling. The intricate nature of this system renders this paper a valuable resource for prospective investigations within the domain of dependable systems, cloud computing, and distributed systems.
This paper not only showcases the design and implementation process but also sets a founda-tion for future research and innovation in dependable systems, collaborative technologies, sustainable solutions, and distributed system architecture.
Psychological Cognitive Mechanism of Residents Under the Background of the Renewal of Suburban Historical and Cultural Villages
Authors: Li Meng , Wu Tiehong , Zhong Linsheng , Tang Chengcai , Wang Jingwen , Yi Ruhan
Published: August 2024

This study aims to investigate the psychological cognitive mechanisms of rural residents amidst the renewal of suburban historical and cultural villages by examining the interplay between nostalgia, collective memory, subjective well-being and place identity in rural tourism destinations. Using Naobao Village as a case study—a suburban historical and cultural village in Hohhot, Inner Mongolia, this research employs a comprehensive approach integrating experimental methods and questionnaire surveys. The findings demonstrate that analyzing the interaction among the four emotions can elucidate the psychological cognitive mechanism of residents. Moreover, it uncovers that tourism effects significantly influence residents' perception of their living environment with positive effects on collective memory, subjective well-being and place identity. In the theoretical model for generating psychological cognition among residents in suburban historical and cultural villages, subjective well-being and collective memory play crucial mediating roles. This study provides a theoretical foundation and practical guidance for spatial reconstruction and cultural evolution of tourist landscapes in suburban rural tourist destinations.
Therapeutic Effect of Shikimic Acid on Heat Stress-Induced Myocardial Damage: Assessment via Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation, and In Vitro Experiments
Authors: Gu Yan , Zhang Jingyi , Zheng Min , Qin Yuyang , Zheng Haohong , Hu Yanchun , Xin Jialiang
Published: August 2024

The elderly population is particularly susceptible to myocardial damage caused by heat stress (HS). With the continuous increase in global temperatures, this poses an undeniable challenge to human health. This study aimed to investigate the therapeutic effect of Shikimic Acid (SA) in treating HS-induced myocardial damage through network pharmacology, molecular docking, molecular dynamics (MD) simulations, and in vitro experiments. Network pharmacology analysis revealed that SA alleviates the inflammatory response in the heart muscle associated with HS by targeting 60 disease-related targets, such as TP53, TNF, and IL-6. The tumor proteoglycan, the PI3K-Akt signaling pathway, and hepatitis B were identified as the primary therapeutic pathways. Molecular docking and MD simulation results confirmed that SA can stably bind to both TNF (-6.642 kcal/mol) and IL-6 (-7.261 kcal/mol), and the complexes of Shikimic Acid-IL-6 and Shikimic Acid-TNF did not undergo significant changes within 100 ns. In addition, the in vitro experiment showed that 250 μM SA significantly increased the survival rate of HL-1 cells exposed to 43°C for 2 h by 71.1% and promoted the proliferation of HL-1 cells by 30.7%. Overall, these findings provide substantial evidence for the therapeutic potential of SA in HS-induced myocardial damage.
Effects of Three Yeast Strains on In Vitro Rumen Fermentation of Corn Stover and a Total Mixed Ration
Authors: Gonzalez-Mora Bexy , Castillo-Rangel Francisco , Dominguez-Viveros Joel , Ordoñez-Baquera Perla Lucia , Hume Michael E. , Anderson Robin C. , Félix-Portillo Monserrath , Corral-Luna Agustin , Salinas-Chavira Jaime , Castillo-Castillo Yamicela , Ruiz-Barrera Oscar
Published: August 2024

This study aimed to evaluate the effect of three yeast strains, Pichia guilliermondii (Levica 27), Candida norvegensis (Levazoot 15), and a commercial product (Levucell® SC 10) containing Saccharomyces cerevisiae, on in vitro rumen fermentation of two substrates: corn stover and a total mixed ration (TMR). Samples were taken 24 hours post-fermentation to measure pH, ammonia nitrogen (NH3-N), gas production, and volatile fatty acid (VFA) concentrations. The addition of yeasts did not affect gas production at 24 hours for either diet. For pH, differences between yeast strains were noted when TMR was used. The lowest NH3-N concentration (6.1 mM) was recorded with corn stover, showing similar results across strains. Conversely, NH3-N levels with TMR ranged from 47 mM to 66 mM. The inclusion of all three yeast strains increased the molar concentrations of total VFA, as well as acetic (C2), propionic (C3), and butyric (C4) acids in the rumen fluid. The C2:C3 ratio remained unchanged with corn stover but decreased with the inclusion of Levica 27 and Levazoot 15 in the TMR. With the commercial product Levucell® SC 10, this ratio was comparable to the control treatment. In conclusion, Levica 27 and Levazoot 15 demonstrated a stimulatory effect on in vitro rumen fermentation for the evaluated diets, evidenced by increased VFA concentrations.
Massive Black Holes
Authors: Lavi Eran Magshim
Published: August 2024

The study of supermassive black holes has significantly advanced our understanding of galaxy structures, yet fundamental questions remain, particularly concerning the structure and dynamics of massive black holes. This article addresses the core structure of massive black holes, defined as those originating from supernova events. Integrating the concept of "Dachus density," a state of maximum matter density, I propose that the core of all massive black holes exists at this density. The research investigates the size of these cores and their event horizons, using Cygnus X-1 and Sagittarius A* as examples. Calculations reveal that the core size is exceedingly small compared to the overall black hole, with the core's volume being up to ~155 orders of magnitude smaller than the event horizon volume in the case of Sagittarius A*. The article briefly explores the implications of a rotating Dachus core on the black hole's structure, including the "mantle" region between the core and the event horizon. The discussion extends to absolute zero temperature, asserting that for a non-spinning, static Massive black hole, the temperature of its core reaches 0[K] as in this state, particles do not move in relation to each other and do not have any kinetic and in particular rotational Energy.
Conversion of Atmospheric Gases into Glucose Using Solar Energy
Authors: Qadri Syed Munim , Ahmad Shah Khalid
Published: August 2024

This ambitious research project seeks to revolutionize sustainable glucose production by harnessing solar energy for the conversion of atmospheric gases. The process involves water collection, electrolysis for hydrogen and oxygen production, PDMS membrane-based CO2 collection, CO2 splitting, formaldehyde generation, and the synthesis of glucose/sucrose. Key innovations include the strategic application of PDMS membranes with varying pore sizes and non-reactive chemical layers to facilitate selective permeability for specific gases. Our goal is to create a cost-effective, eco-friendly glucose production method, paving the way for renewable and sustainable energy solutions.
Deep Convolutional Neural Networks: A Comprehensive Review
Authors: Mienye Ibomoiye Domor , Swart Theo G. , Obaido George , Jordan Matt , Ilono Philip
Published: August 2024

Deep convolutional neural networks (CNNs) have revolutionised computer vision technology by automatically learning hierarchical representations of image data, leading to state-of-the-art performance in visual recognition tasks. This article presents a comprehensive review of deep CNNs, from their evolution and architectures to the current state-of-the-art research. The review also provides the core concepts and building blocks of CNNs and their concise mathematical representations. Furthermore, it explores applications of deep CNNs in three popular domains, including medical diagnosis, remote sensing, and facial recognition. This review will benefit researchers and practitioners in computer vision and artificial intelligence, as well as industry professionals seeking to leverage the latest advancements in deep learning technologies.
Immobilizing Effects on Exchangeable CD Merged Soil by Various Amendments – Focused on Plant Uptake and Soil Microbial Community
Authors: Nguyen Quoc Tuan , Jung Myung Chae
Published: August 2024

Cadmium (Cd) contaminated soil is a serious environmental problem due to its effect on crop production, soil microbial community, and risk to human health. The commercial amendments are widely used in the immobilization of heavy metal-contaminated soil because of their cost-effectiveness, eco-friendliness, and community acceptance. This study is conducted to assess the effect of sole commercial amendments including bentonite (B), talc (T), activated carbon (AC), cornstarch (CS), and their combination on exchangeable Cd content in soil, Cd uptake by the plant, and soil microbial community. The results indicated that CS and its composites (T+CS and B+CS) showed the highest effect on reducing Cd mobility in soil (up to 10% in CS), decreasing the Cd uptake by lettuce (up to 78% in T+CS), and increasing the microbial community in soil compared to the control. Furthermore, results from Biolog Ecoplate and realtime-Polymerase chain reaction indicated that the mixture amendments (B+CS and T+CS) showed the highest effect on the microbial community by increasing soil microbial population maximum of 3.81-fold difference (in B+CS) compared to the control. The results indicated that applying composite amendments provided an efficient option for immobilizing Cd in soil, reducing the Cd uptake by plants, and increasing microbial community.
Comprehensive Risk and Efficacy Analysis of Emergency Medical Response Systems in Serbian Healthcare: Assessing Systemic Vulnerabilities in Disaster Preparedness and Response
Authors: Cvetković Vladimir M. , Tanasić Jasmina , Renner Renate , Raupenstrauch Harald , Rokvić Vanja , Beriša Hatidža
Published: August 2024

Emergency Medical Response Systems (EMRS) play a vital role in delivering medical aid during disasters. In Serbia, these systems encounter several obstacles due to economic limitations, scarce resources, and ongoing healthcare reforms, all of which affect their performance. This study focuses on examining the risk factors and effectiveness of Serbia's EMRS, identifying systemic issues, and proposing enhancements to improve emergency preparedness for disasters. A survey was conducted across healthcare institutions in Serbia to gather comprehensive insights. The survey explored various aspects, including organizational structures, resource distribution, communication systems, and the speed of emergency responses. Statistical methods such as Pearson's correlation, multivariate regression analysis and chi-square tests were utilized to interpret data collected from 172 healthcare institutions. The multivariate regression analysis of EMS organization identified that factors such as the structuring of working hours and shift patterns are significant predictors, contributing to small but meaningful variations in various EMS outcomes. In contrast, other factors, such as financial resources and the availability of ambulance vehicles, showed more targeted significance depending on the specific EMS aspect being analyzed. Institutions with written mass casualty plans and procedures demonstrate superior effectiveness in EMS activities, excelling in resource allocation, operational continuity, and emergency preparedness, particularly through enhanced coordination and specialized systems for managing large-scale emergencies. The findings highlighted notable disparities in how EMRS are organized, with only 46% of institutions having specific emergency departments. Resource limitations were evident, as many facilities operated with minimal staff and outdated equipment. The communication systems revealed weaknesses, with just 54% having established protocols for handling emergency calls. Response times frequently surpassed international standards, which negatively affected patient outcomes. Additionally, the study found training deficiencies, with 68% of participants expressing a need for further education. Serbia’s EMRS are significantly impacted by systemic issues such as insufficient funding, disjointed service delivery, and inadequate training. Overcoming these challenges necessitates a comprehensive approach that includes boosting financial support, implementing standardized protocols, and fostering enhanced collaboration across different sectors.
Increasing the Wear and Corrosion Resistance of a CP-Ti Surface by Plasma Electrolytic Borocarburizing and Polishing
Authors: Volosova Marina A. , Kusmanov Sergei A. , Tambovskiy Ivan V. , Mukhacheva Tatiana L. , Mitrofanov Artem P. , Suminov Igor V. , Grigoriev Sergey N.
Published: August 2024

The paper examines the possibility of increasing the wear and corrosion resistance of a CP-Ti surface by duplex plasma electrolytic treatment (borocarburizing and polishing). The structure and composition of diffusion layers, their microhardness, surface morphology and roughness, wear resistance during dry friction and corrosion resistance in Ringer's solution were studied. The formation of a surface hardened layer up to 200 m thick with a microhardness of up to 950 HV, including carbides and a solid solution of boron and carbon, is shown. Subsequent polishing makes it possible to reduce surface roughness and remove weak areas of the porous oxide layer, which is formed during high-temperature oxidation in aqueous electrolyte vapor during borocarburizing. Changing the morphology and structural-phase composition of the CP-Ti surface helps reduce weight wear by 3 times (the mode of frictional interaction changes from microcutting to oxidative wear) and corrosion current density by 4 times after borocarburizing in a solution of boric acid, glycerin and ammonium chloride at 950 °C for 5 minutes and subsequent polishing in an ammonium fluoride solution at a voltage of 250 V for 3 minutes.
A Distributed Algorithm for Reaching Average Consensus in Unbalanced Tree Networks
Authors: Parlangeli Gianfranco
Published: August 2024

In this paper, a distributed algorithm for reaching average consensus is proposed for multi-agent systems with tree communication graph, when the edge weight distribution is unbalanced. First, the problem is introduced as a key topic of core algorithms for several modern scenarios. Then, the relative solution is proposed as a finite-time algorithm, which can be included in any application as a preliminary setup routine, and it is well-suited to be integrated with other adaptive setup routines, thus making the proposed solution useful in several practical applications. A special focus is devoted to the integration of the proposed method with a recent Laplacian eigenvalue allocation algorithm, and the implementation of the overall approach in a wireless sensor network framework. Finally, a worked example is provided, showing the significance of this approach for reaching a more precise average consensus in uncertain scenarios.
Exploring a Dynamic Homotopy Technique to Enhance the Convergence of Classical Power Flow Iterative Solvers in Ill-conditioned Power System Models
Authors: Lima-Silva Alisson , Freitas Francisco Damasceno
Published: August 2024

This paper presents a dynamic homotopy technique that can be used to calculate a preliminary result for a power flow problem (PFP). This result can then be used as an initial estimate to efficiently solve the PFP using either the classical Newton-Raphson (NR) method or its fast decoupled version (FDXB) while still maintaining high accuracy. The preliminary stage for the dynamic homotopy problem is formulated and solved by employing integration techniques, where implicit and explicit schemes are studied. The dynamic problem assumes an initial condition that coincides with the initial estimate for a traditional iterative method such as NR. In this sense, the initial guess for the FPF is adequately set as a flat start, which is a starting for the case when this initialization is of difficult assignment for convergence. The static homotopy method requires a complete solution of a PFP per homotopy pathway point, while the dynamic homotopy is based on numerical integration methods. This approach can require only one LU factorization at each point of the pathway. Allocating these points properly helps avoid several PFP resolutions to build the pathway. The hybrid technique was evaluated for large-scale systems with poor conditioning, such as a 109272-bus model and other test systems under stressed conditions. A scheme based on the implicit backward Euler scheme demonstrated the best performance among other numerical solvers studied. It provided reliable partial results for the dynamic homotopy problem, which proved to be suitable for achieving fast and highly accurate solutions using both the NR and FDXB solvers.
Adverse Outcomes Following Exposure to Perfluorooctanesulfonamide (PFOSA) in Larval Zebrafish (Danio rerio): A Neurotoxic and Behavioral Perspective
Authors: David Nikita , Ivantsova Emma , Konig Isaac , English Cole , Avidan Lev , Kreychman Mark , Rivera Mario L. , Escobar Camilo , Valle Eliana Maira Agostini , Sultan Amany , Martyniuk Christopher J.
Published: August 2024

Toxicity mechanisms of per- and polyfluoroalkyl substances (PFAS), a chemical class present in diverse ecosystems, are not well characterized in aquatic species. Perfluorooctanesulfonamide (PFOSA, C8H2F17NO2S) is a common precursor of perfluorooctane sulfonic acid (PFOS), a long-chain PFAS. Here, we assessed sub-lethal endpoints related to development, oxidative stress, locomotor activity, and gene expression in zebrafish embryos and larvae following continuous exposure to PFOSA beginning at 6 hours post fertilization (hpf). PFOSA decreased survival in fish treated with 1 µg/L PFOSA, however the effect was modest relative to the controls (difference of 10%). Exposure up to 10 µg/L PFOSA did not affect hatch rate, nor did it induce reactive oxygen species in 7-day-old larvae fish. However, locomotor activity of larval fish treated with 100 µg/L PFOSA was reduced relative to the solvent control. Transcripts related to oxidative stress response and apoptosis were measured and BCL2 associated X, apoptosis regulator (bax), cytochrome c, somatic (cycs), catalase (cat), superoxide dismutase 2 (sod2) were induced with high concentrations of PFOSA. Genes related to neurotoxicity were also measured and transcript levels of acetylcholinesterase (ache), elav-like RNA binding protein 3 (elavl3), growth associated protein 43 (gap43), synapsin II (syn2a), and tubulin 3 (tubb3) levels were all increased in larval fish with higher PFOSA exposure. This study contributes to our knowledge regarding the relative toxicity of PFOSA to fish and contributes data to future risk assessment strategies of these concerning, persistent environmental pollutants.
From Play to Understanding: LLMs in Logic and Spatial Reasoning Coloring Activities for Children
Authors: Tapia Sebastián , Araya Roberto
Published: August 2024

Visual thinking leverages spatial mechanisms in animals for navigation and reasoning. Therefore, given the challenge of abstract mathematics and logic, spatial reasoning-based teaching strategies can be highly effective. Our previous research verified that innovative box and ball coloring activities help teach elementary school students complex notions like quantifiers, logical connectors, and dynamic systems. However, given the richness of the activities, correction is slow, error-prone, and demands high attention and cognitive load from the teacher. Moreover, feedback to the teacher should be immediate. Thus, we propose to provide the teacher with real-time help with LLMs. We explored various prompting techniques with and without context Zero shot, Few shot, Chain of Thought, Visualization of Thought, Self Consistency, logicLM and Emotional to test GPT-4o’s visual, logical, and correction capabilities. We obtained that Visualization of Thought and Self Consistency techniques enabled GPT-4o to correctly evaluate 90% of logical-spatial problems that we tested. Additionally, we propose a novel prompt combining some of these techniques that achieved 100% accuracy on a testing sample, excelling in spatial problems and enhancing logical reasoning.
A Mixed Review of Research on Competencies of Built Environment Professionals in Infrastructure Delivery within Emerging Economies
Authors: Molusiwa Ramabodu Stephan
Published: August 2024

This study presents a mixed review of research on the competencies of built environment professionals in infrastructure delivery within emerging economies. By integrating bibliometric analysis with a systematic review, the research offers a comprehensive understanding of key themes, trends, and debates in the field. The review process culminated in the selection of 59 publications, which were analyzed to identify critical topics including embedding emerging skills in built environment competencies, competency-based curriculum, technology infrastructure and assessment, municipal competency training, and the role of the Fourth Industrial Revolution (4IR). The findings underscore the importance of evolving educational frameworks to meet the demands of globalization, integrating advanced technologies, and fostering industry-academic collaborations to enhance the skills of professionals in the built environment sector. This approach ensures a robust examination of the competencies necessary for effective infrastructure delivery in emerging economies.
Microplastics and Climate Change: Unveiling Ecological Impacts and Addressing Research Gaps
Authors: Navarro Andrea
Published: August 2024

Microplastics, pervasive in both terrestrial and aquatic ecosystems, have emerged as significant contributors to greenhouse gas (GHG) emissions, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). This review synthesizes recent studies from 2022 to 2024, revealing the complex mechanisms through which microplastics influence GHG production. These mechanisms include the adsorption of nutrients and pollutants onto microplastic surfaces and their role as substrates for microbial colonization. The impacts of microplastics vary significantly across different environments, such as agricultural soils and marine sediments. The review underscores the urgent need for standardized methodologies and long-term field studies to accurately assess the ecological consequences of microplastics. Notably, the role of nitrous oxide (N2O), a potent GHG with a global warming potential nearly 300 times that of CO2, remains underexplored in the context of microplastic interactions, highlighting a critical research gap. Additionally, the synergistic effects of microplastics with other pollutants require further investigation to understand their cumulative impact on GHG emissions fully. This review calls for a coordinated effort among researchers and policymakers to advance our understanding of microplastics' role in global GHG budgets and to develop effective strategies for mitigating their environmental and climatic impacts.
Study on Minimum Inhibitory Concentration of Selected Antibacterials against Bacterial Isolates from Canine Pyometra
Authors: Chhetri Avinash , Paudel Madhav , Gompo Tulsi Ram , Thapaliya Sharada
Published: August 2024

Minimum Inhibitory Concentration (MIC) measures the lowest concentration of antibiotic that inhibits in-vitro growth of microorganisms. Canine pyometra is a frequently occurring reproductive disorder where reliable antibiotics along with surgical excision of uterus predicts better prognosis. Scarce literature is available to facilitate proper antibiotic selection to avoid septicemia in clinical cases. The present study was conducted to determine sensitivity and potency of selected antibacterials based on MIC values against bacterial isolates obtained from Canine Pyometra in Kathmandu district, Nepal by Agar Dilution method. Isolates obtained from 63 intra-uterine samples after ovariohysterectomy were Enterococcus spp (n=41), Klebsiella spp. (n=7), Staphylococcus spp. (n=11) and Streptococcus spp. (n=4). Enrofloxacin and Amikacin were found highly sensitive (0% resistance) with a null hypothesis of resistance to all bacterial isolates and were significantly more potent than other antibacterials tested (p
Effect of Oriented External Electric Fields on the Electronic Properties of Linear Acenes: A TAO-DFT Study
Authors: Chen Chi-Yu , Chai Jeng-Da
Published: August 2024

Recently, oriented external electric fields (OEEFs) have earned much attention due to the possibility of tuning the properties of electronic systems. From a theoretical perspective, one can resort to electronic structure calculations to understand how the direction and strength of OEEFs affect the properties of electronic systems. However, for multi-reference (MR) systems, calculations employing the popular Kohn-Sham density functional theory with the traditional semilocal and hybrid exchange-correlation energy functionals can yield erroneous results. Owing to its decent compromise between accuracy and efficiency for MR systems at the nanoscale (i.e., MR nanosystems), in this study, thermally-assisted-occupation density functional theory (TAO-DFT) is adopted to explore the electronic properties of n-acenes (n = 2--10), containing n linearly fused benzene rings, in OEEFs, where the OEEFs of various electric field strengths are applied along the long axes of n-acenes. According to our TAO-DFT calculations, the ground states of n-acenes in OEEFs are singlets for all the cases examined. The effect of OEEFs is shown to be significant on the vertical ionization potentials and vertical electron affinities of ground-state n-acenes with odd-number fused benzene rings. Moreover, the MR character of ground-state n-acenes in OEEFs increases with the increase of the acene length and/or the electric field strength.
Modeling Thermal Effects of Pulsating Currents in Human Tissues: How to Prevent Necrosis
Authors: Farina Angiolo , Fasano Antonio , Rosso Fabio
Published: August 2024

In some clinical applications pulsating currents are delivered into a body region for therapeutic purposes.
In this paper we analyze the generated thermal field with the aim of determining the amplitude, period and duration of those stimuli, guaranteeing that the temperature of the interested tissue stays below the necrosis threshold.
Mortality Risk and Urinary Proteome Changes of Acute COVID-19 Survivors in the Multinational Study CRIT-COV-U Study
Authors: Siwy Justyna , Keller Felix , Banasik Mirosław , Peters Björn , Dudoignon Emmanuel , Mebazaa Alexandre , Gülmez Dilara , Spasovski Goce , Lazo Mercedes Salgueira , Rajzer Marek , Fuławka Łukasz , Dzitkowska-Zabielska Magdalena , Mischak Harald , Hecking Manfred , Beige Joachim , Wendt Ralph
Published: August 2024

Background/Objectives: Survival prospects following SARS-CoV-2 infection may extend beyond the acute phase, influenced by various factors including age, health conditions, and infection se-verity. However, this topic has not been studied in detail. We therefore investigated mortality risk post-acute COVID-19 in the CRIT-COV-U cohort. Methods: We could retrieve survival data from 651 patients and also assess the association between urinary peptides and future death. Data spanning until December 2023 were collected from six countries, comparing mortality trends with age- and sex-matched non-infected controls. A death prediction classifier was developed and validated using pre-existing urinary peptidomics datasets. Results: Notably, 13.98% of post-COVID-19 patients succumbed during the follow-up, with mortality rates significantly higher than non-infected controls, particularly evident in younger individuals (<65 years). These data for the first time demonstrate that SARS-CoV-2 infection highly significantly increases the risk of mortality not only during the acute phase of the disease, but also beyond, for a period of about one year. In our study we were further able to identify 201 Urinary peptides linked to mortality, and integrated these into a predictive classifier (DP201). Higher DP201 scores, alongside age and BMI, significantly predicted death. Conclusions: Our findings underscore the utility of urinary peptides in prognosticating post-acute COVID-19 mortality, offering insights for targeted interventions. Our data also suggest that mortality should be considered as one possible symptom or conse-quence of post-acute sequelae of SARS-CoV-2 infection, a fact that is currently overlooked.
A Simple Procedure to Obtain the Grounding Resistance Measure of Very Large and Urban Electrodes by a Modified Fall-of-Potential Method
Authors: Moreno Jorge , Simon Pascual , Faleiro Eduardo , Garcia Daniel , Denche Gregorio , Asensio Gabriel
Published: August 2024

The measurement of the grounding resistance of protection grids in large installations as well as grounding electrodes in urban areas is addressed in this article. The resistance value is obtained using a three-pin array by measuring the fall-of-potential on the ground surface. The resistance measured by this method is corrected using the so-called correction factor that adjusts the measured resistance value to its real value. The proposed measurement method obtains correct values of the grounding resistance even when the auxiliary and potential electrodes of the tree-pin array are close to the electrode to be measured. Thus, it can be applied to large electrodes as well as electrodes in urban areas. Several simulated examples are used to illustrate the method, and some real cases with field measurements are presented for a final validation of the method.
Glycogen Synthase Kinase 3 (GSK-3) and Suicide: A Systematic Review
Authors: RUBATINO RODRIGUES JULIANO FLAVIO , Serna Rodrigues María Fernanda , Peregrino Rodrigues Lívia , Marques Payão Spencer Luiz , Martins Rubatino Fernando Victor , Perez Maya Antonio Ali , de Araújo Filho Gerardo Maria
Published: August 2024

IntroductionGlycogen synthase kinase 3 (GSK-3) has been associated with a lot of diseases, such as Alzheimer’s Disease and diabetes. Its role in depression is connected to stress and neuroinflammation. Lithium is an essential inhibitor of GSK-3. Some studies have suggested that the use of this psychiatric medication may lower suicide rates. Here, we outline the current understanding and discoveries regarding the link between GSK-3 and suicide. MethodWe used the PRISMA statement and defined the PECOS strategy, such as Population (P) = individuals; exposure (E) = GSK-3 alteration function; comparison (C) = without GSK-3 alteration function; outcome (O) = suicide; and study design(S) = all kinds of studies with an association between GSK-3 and suicide.ResultsTwelve studies were included in this review. GSK-3 appears to be related to suicidal behavior by activating inflammatory pathways, activating genes, altering neurotransmission, and increasing impulsivity. Clinical studies do not present robust results that allow defining an epidemiological profile of greater risk for suicidal behavior in association with changes in the functioning of GSK-3.ConclusionThe interference of GSK-3 functioning in suicidal behavior seems inevitable, with solid evidence from laboratory animal studies. However, there is a need for further clinical studies on this crucial topic to answer better some questions about the association between GSK-3 and suicide.
Mapping the Knowledge Landscape of Money Laundering for Terrorism Financing: A Bibliometric Analysis
Authors: Thakkar Himanshu , Datta Saptarshi , Bhadra Priyam , Dabhade Siddharth Baburao , Barot Haresh , Junare Shankar O
Published: August 2024

This study employs a bibliometric analysis of the emerging trends in the area of Money Laundering for Ter-rorism Financing to provide direction for future research in the area. The authors used VOSviewer and an-alysed 2577 published documents generated from the SCOPUS search using the PRISMA methodology. The findings reveal a growing research interest in this area, with a focus on understanding the complex inter-play between money laundering and terrorism financing. Emerging trends such as the use of cryptocurren-cies, trade-based money laundering, and the role of non-profit organizations in facilitating these activities are highlighted. The research contributes to the broader understanding of money laundering for terrorist financing by providing insights into the evolving research landscape and identifying areas for future re-search.
Magnetic Resonance Imaging-Guided Single-Fraction Preoperative Radiotherapy for Early Stage Breast Cancer (The RICE Trial): Feasibility Study
Authors: Qadir Ayyaz , Singh Nabita , Dean Jenna , Brown Kerryn , Tacey Mark , Mann Bruce , Kron Tomas , Cahoon Glenn , Lau Eddie , Scot Andrew M , Yeo Belinda , Loh Su-Wen , Uribe Sergio , Moe Aung Aung Kywe , Ireland-Jenkins Kerryn , McAuley Rosly , McDermont Leah , Ooi Wei Ming , Ng Suat , Chao Michael , Foroudi Farshad
Published: August 2024

Background: Over the past decade, the adoption of screening programs, digital mammography, and Magnetic Resonance Imaging (MRI) has increased early-stage breast cancer diagnosis rates. Mortality rates have decreased due to early detection, improved treatments, including personalized therapies. Accelerated partial breast irradiation (APBI) is emerging as a convenient and effective treatment for some patients, with studies exploring its preoperative use. Preoperative APBI, especially with MRI guidance, offers improved tumor targeting and reduced side effects. The RICE trial aims to assess the feasibility and efficacy of MRI-guided single-dose radiotherapy for early-stage breast cancer.
Methods: The RICE study is a prospective, single-arm study evaluating single fraction pre-operative, accelerated partial breast irradiation treatment in patients with early-stage breast cancer using a Magnetic Resonance Imaging Linear Accelerator (MR Linac). Eligible patients enrolled in this study will have a core biopsy to confirm estrogen receptor positive, Her2 negative subtype. Radiotherapy planning will use a planning computed tomography co-registered with a magnetic resonance imaging (MRI) with the patient in either the supine or prone position. For the diagnostic workup, [18] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography ([18]FDG PET/CT) and [18] Fluoroestradiol Positron Emission Tomography/Computed Tomography ([18]FES PET/CT) will be performed prior to treatment. Thirty patients will receive a single ablative RT dose of 21 Gy to the tumor. Pre- and post-treatment MRI scans will be acquired at baseline and 5 weeks post radiotherapy respectively. Breast-conserving surgery will be scheduled for 6 weeks after APBI treatment using the MR- Linac.
The primary study endpoint is the successful administration of a single fraction of preoperative breast radiotherapy under the guidance of an MR-linac. Secondary endpoints include evaluating the utility of MRI, [18F] FDG PET/CT and [18F] FES PET/CT as a non-invasive method for assessing treatment response in patients undergoing single fraction preoperative accelerated partial breast irradiation.
Conclusion: The RICE trial represents a significant step in breast cancer treatment, offering insights that could lead to treatment protocols with minimized radiotherapy and enhanced patient outcomes.
Trial Registration: This trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR). Registered 31st of May 2021. Registration number: ACTRN12621000659808 https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12621000659808