bluuebunny/crossref_metadata_2025 huggingface dataset:
The Link between Loneliness, Social Isolation, and Cardiovascular Disease
Authors: Khairina  , Yusuf Ibrahim
Published: December 2024

Introduction: Cardiovascular disease (CVD) is a major cause of morbidity and mortality worldwide. Loneliness, a subjective feeling of social isolation, and social isolation, an objective lack of social connections, contribute to social vulnerability and physical frailty. Psychological factors and social support play important roles in CVD, affecting health behaviors and physiological mechanisms. This review aims to provide an understanding of how loneliness and social isolation impact CVD. Methods: A literature review was conducted to identify relevant studies investigating the association between loneliness, social isolation, and cardiovascular disease. Results: The findings indicate that social isolation and loneliness are significant risk factors for CVD, independent of other risk factors. The prevalence of loneliness has increased in modern society, affecting individuals of all ages. Loneliness and social isolation influence physiological processes such as activating the HPA axis, causing inflammation and alterations in immune function, and activating the sympathetic nervous system. These effects contribute to an increased risk of CVD, including elevated blood pressure, hypertension, atherosclerosis, and potential cardiac autonomic dysregulation. Conclusion: Loneliness and social isolation pose significant risks for cardiovascular disease (CVD), influencing physiological processes such as inflammation, immune function, and sympathetic nervous system activation. Understanding these relationships is crucial for developing effective strategies to prevent and manage CVD, emphasizing the importance of interventions targeting both psychological and physiological aspects of social well-being.
Keywords: Loneliness, Social Isolation, Cardiovascular Disease
Pseudarthrosis following adult spinal deformity surgery may be predicted with preoperative MRI adipose tissue features: an artificial intelligence study on raw 3D imaging
Authors: Johnson Graham W. , Chanbour Hani , Doss Derek J. , Makhoul Ghassan S. , Abtahi Amir M. , Stephens Byron F. , Zuckerman Scott L.
Published: December 2024

Aim: The purpose of this study is to investigate the utility of incorporating magnetic resonance imaging (MRI) into an artificial intelligence (AI) model to preoperatively predict pseudarthrosis for patients undergoing adult spinal deformity (ASD) surgery.

Methods: A retrospective cohort study was conducted on patients undergoing ASD surgery at Vanderbilt University Medical Center with at least 2 years of follow-up. We first collected demographic variables and measured traditional radiographic variables with Surgimap software. The primary outcome of interest was pseudarthrosis, defined as mechanical pain without evidence of bony union with or without a rod fracture. Next, cohort differences between patients diagnosed with and without pseudarthrosis were evaluated with t -tests for continuous variables and chi-squared tests for categorical variables using Bonferroni-Holm multiple comparison correction. Using a subpopulation of patients with preoperative thoracic MRI available, a three-dimensional convolutional neural network (3D-CNN) with five-fold nested cross-validation was developed to predict pseudarthrosis - accuracy was evaluated with the Youden index. Finally, class activation mapping (CAM) was conducted to visualize the MRI features utilized by the model for accurate classifications.

Results: Of 191 patients undergoing ASD surgery, the demographic and traditional radiographic variables were collected, and only age was observed to be significantly different between the patients diagnosed with pseudarthrosis (69.9 ± 10.1 years old) and those without (60.9 ± 19.9), with a t -test P -value of 0.003. The 3D-CNN demonstrated an average Youden index of 0.49 ± 0.25 on the withheld data, with a P -value of 5.50e-3 compared to an equivocal null model. Finally, CAM consistently revealed posterior adipose tissue to be most important in preoperatively predicting pseudarthrosis.

Conclusion: Adipose tissue features in MRI, independent of body mass index (BMI), may be useful for preoperatively predicting pseudarthrosis. Overall, this work demonstrates the capabilities of raw imaging AI in spine surgery and can serve as the basis for a deeper biological inquiry into the pathogenesis of pseudarthrosis.
Boas práticas de transcrição de documentos histórico-bibliográficos em formato digital
Authors: Silva Diana Rocha da , Castro Cesar Augusto , Mendes Anna Júlia Aires
Published: December 2024

A transcrição de documentos disponibilizados em ambiente digitais tem se mostrado útil para discentes e profissionais da informação, como bibliotecários, arquivistas e historiadores, impactando na preservação de informações históricas. Este trabalho propõe apresentar e explicar as boas práticas de transcrição documental para o campo histórico-bibliográfico, a partir das revistas pedagógicas publicadas no século XIX. Caracteriza-se como uma pesquisa descritiva e explicativa, com enfoque qualitativo feito por meio de levantamento bibliográfico sobre a temática; levantamento de transcrições das revistas pedagógicas Pará e Maranhão entre 1900 e 1930; descrição dos desafios que durante a transcrição demandaram esforços adicionais. Mapeou-se normas da NTTDEM para auxiliar no processo de transcrição, orientações positivas na preservação e disseminação de informações.
Phase Error Correction in Magnetic Resonance: A Review of Models, Optimization Functions, and Optimizers in Traditional Statistics and Neural Networks
Authors: Jiang Aixiang
Published: December 2024

Phase errors in magnetic resonance (MR) techniques, including Nuclear Magnetic Resonance (NMR) spectroscopy and Magnetic Resonance Imaging (MRI), pose significant challenges to data accuracy and interpretation. As MR technologies advance, the demand for more sophisticated phase correction methods continues to grow, enhancing diagnostic precision and analytical outcomes. This review explores the evolution of phase correction models, beginning with simple global phase shifts, progressing through traditional linear statistical models, and culminating in modern machine learning techniques—specifically, neural networks. It also examines a range of optimization functions and optimizers, including both MR data-specific and common statistical approaches, applied in phase error correction. While significant progress has been made, current methods often struggle to achieve full automation due to inherent challenges such as the absence of ground truth in real-world MR data. By analyzing key methods and their limitations, this review identifies opportunities for innovation, proposing ensemble learning and other advanced strategies as potential pathways for overcoming existing barriers and advancing the field.
Recent Advances on SAW Sensors for Detection Cancer Biomarkers
Authors: Aleixandre Manuel , Horrillo Mari Carmen
Published: December 2024

Surface Acoustic Wave (SAW) sensors are a promising approach for the detection of cancer biomarkers due to their high sensitivity and potential label-free operation. This review focuses on their application examining the diverse range of biomarkers detectable with SAW sensors, including volatile organic compounds (VOCs) from exhaled breath and larger biomolecules such as proteins, DNA, and microRNAs in body fluids. SAW sensor configurations are discussed with attention to their specific properties, wave propagation modes, and suitability for different environments. Detailed case studies are reviewed, highlighting applications in lung, colorectal, prostate, breast, and ovarian cancer diagnostics, as well as the detection of circulating tumor cells and cancerous cell growth. The review identifies current challenges, including optimizing sensitivity, addressing environmental interferences, and the need for clinical validation. Finally, future research directions are proposed, emphasizing the use of VOC biomarkers and the integration of SAW technology into hybrid systems and microfluidic platforms to enable scalable, non-invasive diagnostic tools.
Empathy for the Partner Eliminates the Endowment Effect
Authors: Dyke Ellis , Noble Russell , Hsu Robert , Preston Stephanie
Published: December 2024

The endowment effect is a long-standing and powerful phenomenon in behavioral economics whereby people consistently overvalue objects they possess compared to the prices buyers will offer to acquire them. The endowment effect is usually considered irrational and causes disadvantageous choices in realms from online auctions to home sales to domestic clutter. Finding ways to reduce the impact of endowment processes could benefit people and society in myriad ways. Drawing from social psychology, we predicted that people would be more generous toward partners in a common experimental endowment mug task when their partner was portrayed as in pain or need. Combining existing study methods, two pilot studies successfully replicated the endowment effect in control conditions but eliminated or reversed it toward partners in physical (N = 156) or emotional (N = 278) pain (respectively). A pre-registered, in-person study (N = 106) directly contrasted physical pain, emotional pain, and control conditions. We again replicated the endowment effect toward control partners and eliminated it toward partners in physical or emotional pain (buyer prices increased and seller prices decreased; ηp2 = .13). People’s generosity toward those in need can be harnessed to release them from an often troubling and disadvantageous need to hold onto unneeded items that could benefit others.
How Do Segment Disclosure and Cost of Capital Impact the Investment Efficiency of Listed Firms in Nigeria?
Authors: Sule Dolapo Faith
Published: December 2024

Investment inefficiencies in listed firms around the world have led to investors demanding more transparency in segment disclosure. Transparency in corporate activities is essential for investors to determine the parameters of their stock return and investment efficiency across various segments of firms. Previous studies have primarily focused on a broader investment landscape in Nigeria, without adequate attention to the impacts of segment disclosure and cost of capital on investment efficiency of listed firms. Against this backdrop, this study investigates the impacts of segment disclosure and cost of capital on investment efficiency of firms in Nigeria, using longitudinal research design. Secondary data from 2015 to 2022 were extracted from the annual reports of 85 listed firms on the Nigerian Exchange Group (NGX), which were analysed through descriptive and inferential statistical methods. Firms that reported their business or geographic segments were purposively selected for this study. Study findings showed that the cost of capital of the examined firms has a negative and significant impact on their investment efficiency (Coefficient = -0.0268, p-value = 0.03079). On the other hand, the segment disclosure of the firms has a positive impact on their investment efficiency (Coefficient = 0.0119, p-value = 0.0303). These findings imply that improved segment disclosure and a lower cost of capital tend to improve the investment efficiency of listed firms in Nigeria. This study, thus, recommends that the management of firms in Nigeria should disclose more segment information in their annual reports. This could consequently boost investors’ confidence in the reporting practices of firms, reduce the cost of capital of firms, and improve firms’ investment efficiency.
Performance Analysis of Buffer-Aided FSO Relaying with an Energy Harvesting Relay
Authors: Abou-Rjeily Chadi
Published: December 2024

In this paper, we consider a three-node free space optical (FSO) decode-and-forward (DF) cooperative network. The relay is not connected to a permanent power supply and relies solely on the optical energy harvested (EH) from the source node. This energy is accumulated in an energy buffer in order to enable the relay-destination communications. Moreover, buffer-aided (BA) relaying is considered where the relay is equipped with a data buffer for storing the incoming packets. For such networks, we propose a relaying protocol that delineates the roles of the source and the EH BA relay in each time slot. We develop a Markov chain framework for evaluating the analytical performance of the considered system. Numerical results validate the accuracy of the theoretical analysis and demonstrate significant reductions in the network outage, especially when the relay’s transmit level is appropriately selected.
Modelling the Performance of a Continuous Durum Wheat Cropping System in a Mediterranean Environment: Carbon and Water Footprint at Different Sowing Dates, Under Rainfed and Irrigated Water Regimes
Authors: Garofalo Pasquale , Cammerino Anna Rita Bernadette
Published: December 2024

This study evaluates the environmental impacts and productivity of a continuous durum wheat cropping system under three sowing dates, and two water regmes; rainfed and irrigation at flowering in Mediterranean context, specifically in the Capitanata plain of Apulia, Italy. AquaCrop-GIS was employed to model the yield response of durum wheat under the different sowing dates (15 October, 1 November and 15 November) and water management practices. In addition, the Carbon and Water Footprint (CWFP) tool was used to quantify the environmental impacts in terms of greenhouse gas emissions and water use, including green, blue and total water components. Results indicated that the total greenhouse gas emissions (CO2_eq) from wheat production averaged 1201.3 kg CO2_eq ha-1, with fertilization, in particular the application of ammonium nitrate and urea, being the main contributor. Soil management practices contributed 362.9 kg CO2_eq ha-1. Early November sowing achieved the highest productivity, 5573 kg/ha under the rainfed option and 5722 kg/ha under irrigated management, while mid-November sowing resulted in lower yields and 21% higher CO2_eq emissions per kilogram of grain compared to early November. Water Footprint analysis revealed that early November sowing had the highest green water demand, with negligible differences in blue water use between sowing dates. Overall, the integration of these data showed that optimizing sowing dates and irrigation practices can significantly improve yields and reduce environmental impacts.
Algorithmic Advances for 1.5D Two-Stage Cutting Stock Problem
Authors: Grieco Antonio , Caricato Pierpaolo , Margiotta Paolo
Published: December 2024

The 1.5D Two-Stage Cutting Stock Problem is tackled by building upon two established methodologies from the literature: a straightforward Generate & Solve approach and a combined Row & Column Generation approach, both originally developed for the one-dimensional model. To account for the unique challenges posed by the 1.5D nature of the problem, these canonical methods are extended to handle intermediate orders introduced by the two-stage cutting process. The proposed algorithm undergoes rigorous validation through an extensive experimental campaign, which includes benchmarking the performance of the two approaches.
From Data to Power: AI-Enhanced Renewable Energy Systems for the Smart Grid Era
Authors: Islam Md Suzon
Published: December 2024

This work aims at analyzing the part of AI given its capability to improve reliability, efficiency, and flexibility of renewable energy integration. The growing world demand for energy requires the incorporation of renewable energy into smart grids to create effective and efficient power systems. Through the utilization of sophisticated machine learning, predictive analytical tools, and real-time calculated data, we implemented forecasts, schedules, and management of renewable power within the grid. Our methods included establishing models that predict renewable power generation, demand, and real-time operations of the grid. According to the findings, the power oscillation range has been decreased by 30%, the use of renewable energy generation has been increased by 25%, and the dependence of fossil fuel backup generation has been decreased by 40% based on the usage of AI-enabled systems. Moreover, several of the AI-fortified systems were much more capable of maintaining the stability of the grid, cutting energy costs and CO2 emissions by 20 on average. These insights demonstrate AI’s capability to facilitate smarter and more antifragile energy grids by navigating renewable energy and supply-demand Plexus effectively. Overall, our findings support the statement that AI-based renewable energy systems can help integrate the transition to more sustainable energy resources by enhancing grid performance, reducing carbon footprints, and improving energy access. This study also reveals the significant reality of AI to enhance global sustainable goals for energy systems.
Biological Decontamination by Microplasma
Authors: Blajan Marius Gabriel , Ciorita Alexandra , Surducan Emanoil , Surducan Vasile , Shimizu Kazuo
Published: December 2024

Dielectric barrier discharge microplasma has various applications such as flow control, surface treatment, air treatment or biomedical applications. Microplasma was used for the inactivation of Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa. Bacterial strains spread on Petri dishes containing Nutrient Agar were treated with microplasma and after incubation, inhibition zones were observed. By comparison, the experiments carried out with the already-grown bacteria on the Petri dish did not show any inhibitory response. Environmental air was used as discharge gas. The reactive oxygen and nitrogen species mainly carry out the inactivation process. A negative pulse voltage energized the microplasma electrodes. The microplasma treatment was the most potent against S. aureus, followed by E. coli, and P. aeruginosa, which was the least susceptible bacteria from the tested strains. An increase in the inhibitory efficiency was observed with the increase of discharge voltage from -1.5 kV to -1.7 kV. This research proved the efficiency of microplasma in biological decontamination and provides valuable insights of the inactivation of bacteria carried out with a technology that is suitable for easy integration and portability.
Design and Performance Study of a Solar UAV for Martian Exploration
Authors: Jha Nandan Kumar , Gautam Aditya , Malve Bhakti Sachin , Nadig Nachiketh , Mehta Gourav , N Jitesh , Malhi Dr. Gurmail Singh , Chand Dr. Dharmahinder Singh
Published: December 2024

This Paper outlines a rigorous methodology for the preliminary design and its performance analysis of Unmanned Aerial Vehicles (UAVs) intended for Martian atmospheric exploration, focusing on the study of the Martian boundary layer up to an altitude of 100 meters. The UAVs are designed to operate continuously during a Martian solar day, which lasts 12 hours and 40 minutes, emphasizing extended hovering capabilities. Three UAV configurations—Tiltable Quadcopter, Coaxial Rotorcraft, and Coaxial Trirotor—are systematically analysed across six key stages: mission profiling, vehicle sizing, aerodynamic parameter determination, propulsion system design, mass breakdown, and stowage strategies. The aerodynamic analysis and design of UAVs for Martian exploration, focusing on rotor performance under the planet's unique atmospheric conditions. Detailed CFD simulations assess airfoils NACA 0012 and CLF5605, chosen for their suitability in low Reynolds number and high Mach number environments, optimizing rotor efficiency. A Propulsion system is developed to account for solar variability, informing optimal flight profiles and energy management for solar-powered UAV operations. Energy balance calculations validate the UAV designs, ensuring efficient power consumption and reliable performance for sustained Martian exploration. Stowage mechanisms are developed to fit within a 2.5-meter aeroshell, ensuring compact deployment without compromising structural integrity. Optimized UAVs ensure reliable performance for extended Martian missions.
Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques
Authors: Kazi Mohamed Ali
Published: December 2024

Banking malware poses a significant threat to users by infecting their computers and then attempting to perform malicious activities such as surreptitiously stealing confidential information from them. Banking malware variants also continue to evolve and have been increasing in numbers for many years. Amongst these, the banking malware Zeus and its variants are the most prevalent banking malware variants discovered. This prevalence was expedited by the fact that the Zeus source code was inadvertently released to the public in 2004, allowing malware developers to reproduce the Zeus banking malware and develop variants of this malware and examples of these include Ramnit, Citadel and Zeus Panda. Tools such as anti-malware programs do exist and are able to detect banking malware variants, however, they do have limitations. The reliance on regular updates to incorporate new malware signatures or patterns means that they can only identify known banking malware variants. This constraint inherently restricts their capability to detect novel, previously unseen malware variants. Adding to this challenge is the growing ingenuity of malicious actors who craft malware specifically developed to bypass signature-based anti-malware systems. This paper presents an overview of the Zeus, Zeus Panda and Ramnit banking malware variants, and discusses their communication architecture. Subsequently, a methodology is proposed for detecting the banking malware C&C communication traffic and this methodology is tested using several feature selection algorithms to determine which feature selection algorithm performs the best. The feature selection algorithms are also compared with a manual feature selection approach to determine whether a manual, automated or hybrid feature selection approach would be more suitable for this type of problem.
Сравнение двух подходов к построению комбинированных схем для многомерных уравнений Эйлера
Authors: Bragin Mikhail Dmitrievich
Published: December 2024

Существенным недостатком стандартных численных схем с нелинейной коррекцией потоков является резкое ухудшение точности в областях влияния ударных волн: падение порядка сходимости до первого и значительное увеличение погрешностей решения. Комбинированные численные схемы позволяют решить данную проблему и при этом сохраняют монотонность рассчитываемого решения. Главным элементом всякой комбинированной схемы служит немонотонная схема, обладающая высокой точностью в областях влияния ударных волн. Сравниваются два подхода к построению таких схем. Первый - локальное повышение порядка аппроксимации по времени методами Рунге-Кутты или Адамса. Второй - глобальное, апостериорное повышение порядка точности по времени методами Ричардсона. Сравнение проводится для схем с бикомпактной пространственной аппроксимацией четвертого порядка на примере одной тестовой задачи для двумерных уравнений Эйлера. Ее решением является периодическая гладкая изоэнтропическая волна, которая с течением времени претерпевает градиентную катастрофу и обращается в периодическую ударную волну. Показывается, что первый подход предпочтительнее в том случае, если задача допускает полный расчет по немонотонной схеме и при этом используются не слишком подробные сетки.
Гибридная модель расчeта эффективной площади рассеяния летательного аппарата
Authors: Sysenko Aleksandr Valer'evich , Tarakanov Il'ya Alekseevich , Chukharev Fedor Sergeevcih
Published: December 2024

Представлена математическая модель расчeта эффективной площади рассеяния летательного аппарата. Модель базируется на использовании двухэтапного подхода. 1 этап - получение параметров отражeнной электромагнитной волны в окрестности летательного аппарата (используется классический конечно-разностный метод интегрирования уравнений Максвелла в ограниченной области пространства, включающей летательный аппарат). 2 этап - расчeт ослабления отражeнной электромагнитной волны при еe распространении от летательного аппарата до приeмной антенны радиолокатора (используется метод функций Грина, источниками в которых являются параметры электромагнитных полей на границе расчeтной области первого этапа расчeта). Данный подход позволяет осуществить расчeт эффективной площади рассеяния летательных аппаратов, окружeнных формирующимися за счeт различных физических эффектов ионизованными образованиями. Расчeтная модель протестирована на известных аналитических решениях расчeта эффективной площади рассеяния для простых геометрических тел.
О решении дифференциальных уравнений с помощью нейронных сетей: целевые функционалы и верификация результатов
Authors: Muzalevskii Aleksey Vitalyevich , Repin Sergey Igorevich
Published: December 2024

Новым направлением в математическом моделировании является использование нейросетей для решения задач, связанных с дифференциальными уравнениями. В статье обсуждаются два вопроса, которые имеют важное значение для развития этого подхода: выбор целевого функционала для машинного обучения и верификация результатов. Соответствующая адаптация теории апостериорных оценок функционального типа позволяет осуществлять надежный контроль качества нейросетевых решений и выявлять ситуации, когда последние являются слишком грубыми или просто неверными. Анализ нескольких примеров такого рода приводит к выводу о том, что выбор целевого функционала может существенно влиять на результат. В частности, процедуры машинного обучения с целевыми функционала ми, использующими невязку уравнения в виде коллокации по случайному набору точек, могут приводить к эффектам типа блокировки. Предлагаются новые функционалы, не подверженные недостаткам подобного рода. Эффективность методов машинного обучения с различными целевыми функционалами сравнивалась в многочисленных примерах, которые обсуждаются в заключительной части статьи.
DEVELOPMENT OF TRANSFER PRICING REGULATIONS IN INDONESIA
Authors: Saragi Daniel Edgar Hirasma
Published: December 2024

This research driven by the urgency to understanding the massive improvement of transfer pricing regulations in Indonesia. Directorate General of Taxes (DGT) have adjusted along with the advancement of macroeconomic, business field, cross border trade, and domestic needs. This study aims to describe the development of transfer pricing regulations in Indonesia, since it was first enacted in 1983. The analysis covers three main topics, which are the implementation and examination of arm's length principle, transfer pricing documentation, and advance pricing agreement. This research used qualitative methodology, particularly analytical descriptive approach. Analytical descriptive performed by analyze, capture, and summary a set of regulations, then provide them in the text containing important provision from each regulation. The result shows that there has been a significant development in transfer pricing regulation in Indonesia. Since the first time enacted, there are eight regulations concerning arm’s length principle, three regulations concerning TP Doc, and five regulations concerning advance pricing agreement which enacted sequentially. Those have provided more detailed rules and fulfilled stakeholders' needs. Novelty of this research can be seen through the comprehensive inventory of transfer pricing regulations in Indonesia, which can provide broad explanation for readers. This research may contribute to enrich the transfer pricing literature for academics. Besides, by describe the whole transfer pricing regulations in Indonesia, this research may also contribute to broaden taxpayer’s understanding and improve service quality of tax authority. From this research, it can be concluded that development of the transfer pricing regulations has provided legal certainty and efficiency for taxpayers and DGT in its implementation.
BIODIVERSITY DISCLOSURE AND ESG PERFORMANCE: DOES A CHIEF SUSTAINABILITY OFFICER IMPORTANT?
Authors: Rizki Tabah , Perdana Halim Dedy
Published: December 2024

This study analyzes the impact of corporate biodiversity disclosure (CBD) on ESG performance, with the chief sustainability officer (CSO) as the moderating variable. Examining 73 observations from Energy and Mining companies listed on the Indonesia Stock Exchange from 2018-2022, this research employs PLS regression analysis. The findings demonstrate that CBD has a positive and significant effect on ESG performance, with companies implementing comprehensive CBD practices showing 35.4% higher ESG performance scores and 12.3% higher return on assets, indicating the economic viability of biodiversity initiatives. However, the presence of CSOs does not significantly moderate this relationship, suggesting the need for strengthened sustainability governance frameworks. These findings provide implications for academics, practitioners, and regulators in enhancing both CBD implementation and CSO effectiveness to achieve sustainable development targets while maintaining economic performance.
FLOW ANALYSIS IN A ROLLER DRILL BIT DURING DRILLING USING WATER-BASED AND HYDROCARBON-BASED MUD
Authors: Shudryk Oleksandr , Shevchenko Nataliia , Rezvaya Kseniya , Petruniak Maryna , Bovkun Viktor
Published: December 2024

Drilling is the main type of increase in hydrocarbon production. Bits of various types are used as a rock-destroying tool during drilling. When drilling any wells for oil and gas, drilling fluids are used as a working fluid. The flow of these types of liquids differs from the flow of water, which is an incompressible medium. The purpose of this work is to study the flow of the Newtonian fluid of water and two types of water-based drilling fluids, which is described by the power-law model of a non-Newtonian fluid and the hydrocarbon-based fluid of the Herschel-Bulkley type. In the work, the construction of the geometric model of the square bit was carried out, and the estimated unstructured grid of the liquid volume filling the internal area of the bit and the space behind the bit was constructed. Calculations of the three-dimensional flow of water, drilling fluids on water and hydrocarbon bases were carried out using the open platform OpenFOAM. It was found that during the flow of liquids described by non-Newtonian models, the kinematic viscosity of the liquid changes depending on the velocities and shear stresses. Another important factor in the use of non-Newtonian fluids when drilling wells is the reduction of hydraulic losses during their flow. This is achieved due to the presence of a certain structure of the liquid, non- zero values of shear stresses, lubricating properties even with their viscosity, which is ten times higher than the viscosity of water. Visualization of the flow of three types of fluids: Newtonian, non-Newtonian power-law and non-Newtonian Herschel-Bulkley type is presented. The use of non- Newtonian fluids makes it possible to reduce the formation of vortices and, as a result, also affects the amount of hydraulic losses in the direction of their reduction.
ABOUT THE USE OF DIGITAL HYDRAULIC VALVES IN INDUSTRY
Authors: Ponomarov Vladyslav
Published: December 2024

The article discusses digital hydraulic valves, which are an innovative alternative to traditional proportional analog valves. Digital hydraulics utilize a combination of simple, reliable, and inexpensive ON/OFF type valves, offering high precision in flow and pressure control through programmable logic controllers. The main advantage of such systems is the reduction in energy consumption, as they eliminate the need for constant pump operation and have no internal leakage. The article highlights the economic benefits of digital valves, including lower initial investments due to their lower cost compared to proportional counterparts. Importantly, if one valve fails, the system remains operational, as the failure of individual components does not critically affect overall performance. Special attention is given to coding schemes and control methods, particularly binary coding and pulse number modulation. Binary coding allows for significantly improved regulation accuracy with a minimal number of valves and ensures system fault tolerance. The use of parallel-connected valves, which offer a wide range of states, allows precise control of flows and pressures without the need for switching after the desired positions are set. Additionally, digital hydraulic systems provide fast response times and precise control, making them effective for various industrial applications. Further research in this area could lead to the development of new technological solutions and broader implementation in the industry. The article also covers the technical aspects of such systems, particularly pulse-width modulation, the most common approach to controlling two-way valves. PWM achieves high regulation accuracy through frequency modulation, although low switching frequencies may cause pressure pulsations, which must be compensated through specialized system design or damping devices. In conclusion, digital hydraulic valves represent a promising solution for increasing the efficiency and reliability of hydraulic systems in modern industries, with the potential for significant reductions in energy consumption and operational costs.
Pemetaan Profil Anak Berkebutuhan Khusus di PAUD dan Implikasinya dalam Pendekatan Child-Centered Learning
Authors: Al Baqi Safiruddin
Published: December 2024

Children with special needs often require tailored learning methods to support their cognitive, physical, sensory, social-emotional, and behavioral development. Despite the importance of inclusivity in education, early childhood education (ECE) institutions face challenges in creating effective and inclusive learning environments due to limited resources, inadequate teacher training, and a lack of adaptive curriculum frameworks. Understanding the specific needs of these children through detailed profiles can help guide teaching practices and support their academic and social-emotional growth. This research aims to map the profiles of children with special needs in ECE based on a comprehensive literature review and analyze how these profiles can inform child-centered educational approaches. Using a library research methodology, the study synthesizes information from books, academic journals, and other relevant sources to build a comprehensive profile of common special needs categories in ECE. The findings reveal patterns in the prevalence of specific needs and highlight early indicators of developmental challenges. The study emphasizes the need for a responsive and inclusive educational environment, where teaching methods are adapted to meet the unique needs of each child. Recommendations include targeted training for educators on adaptive teaching strategies and inclusive classroom management, as well as advocating for resource allocation to improve supporting infrastructure. Additionally, the study suggests that policymakers consider using profiling tools as an essential component of early childhood education, enabling early identification and support for children with special needs. By integrating these practices, ECE institutions can enhance educational outcomes for all students, fostering a more inclusive learning culture that benefits children with diverse developmental needs.
Pengaruh Self-Acceptance Terhadap Academic Hardiness pada Mahasiswa Non-Muslim di Kampus Islam
Authors: Arief Yanwar , Hidayat Ahmad , Munthe Ricca Angreini , Yusdanisa Indah
Published: December 2024

Non-Muslim students studying at Islamic universities often face challenges, particularly with Islamic studies courses and Muslim dress code ethics. This situation creates a need for academic hardiness, allowing non-Muslim students to endure the academic pressures they encounter in such settings. One factor believed to contribute to the development of academic hardiness is self-acceptance. This research aims to examine the effect of self-acceptance on academic hardiness among non-Muslim students at an Islamic university. The subjects in this study are 104 active non-Muslim students at Universitas Islam Riau. The sampling technique used is nonprobability sampling, specifically snowball sampling. Data was collected using academic hardiness and self-acceptance scales. Data analysis was conducted using Partial Least Squares (PLS) with SmartPLS 3.0 software. The study results show a significant and positive effect of self-acceptance on academic hardiness among non-Muslim students at an Islamic university.
The Role of Self-Regulation on the Tendency of Nomophobia in College Students
Authors: Andrianie Prilya Shanty , Patimah Dwi Siti , Mukti Patria
Published: December 2024

The advancing development of information and communication technology has resulted in the widespread integration of gadgets into nearly all aspects of daily life and the learning process. The use of gadgets not only facilitates daily activities but, when used excessively, can give rise to adverse consequences, one of which is Nomophobia. Individuals experiencing nomophobia develop a dependency on their smartphones, leading to excessive worry when they are separated from their smartphone or when its battery is depleted. There are several efforts aimed at preventing the emergence of Nomophobia, one of which involves self-regulation. The objective of this research is to examine the role of self-regulation in the predisposition towards Nomophobia among university students. The research design employed is quantitative correlational with a non-probability sampling technique, specifically purposive sampling. The research population comprises 1,411 university students at University X, with a sample size of 93 students determined using the Slovin formula. Data was collected using the Nomophobia questionnaire developed by Yildirim and the Self-Regulation scale by Bandura. Based on the results of hypothesis testing, an R value of 0.288 was obtained (F = 8.230; p 0.05).  Based on the results of data analysis and discussion that has been presented, the results show that self-regulation has a positive effect on nomophobia. The effective contribution of self-regulation to the propensity for nomophobia is 18.3%, while the remaining 81.7% is attributed to other variables or factors. The research findings indicate that 71% of the subjects exhibit high self-regulation, 18.3% possess very high self-regulation, and 10.2% demonstrate moderate self-regulation. As for the tendency towards Nomophobia among the research subjects, 34.4% display a low tendency, 25.8% fall into the moderate category, 20% exhibit a high tendency towards Nomophobia, and 19.8% are classified as having a very high tendency.
THE POTENTIAL OF SUBANG PINEAPPLE PEEL WASTE AS BIOVINEGAR
Authors: Triastuti Desy , Suciati Fitri , Putri Devry Pramesti
Published: December 2024

Limbah kulit nanas diperoleh dari sisa pengolahan nanas mengandung karbohidrat dan komponen bioaktif yang berpotensi dimanfaatkan menjadi biovinegar. Konsentrasi yeast dan lama fermentasi dapat mempengaruhi kualitas biovinegar. Penelitian ini bertujuan untuk mengetahui pengaruh konsentrasi ragi dan waktu fermentasi terhadap karakteristik biovinegar kulit nanas berasal dari daerah Jalancagak Subang. Penelitian ini menggunakan Rancangan Acak Lengkap dengan dua faktor yaitu konsentrasi ragi (1%, 2%, dan 3%) dan lama fermentasi (2, 4, 6, dan 8 minggu) melalui analisis karakteristik biovinegar (pH, total padatan terlarut, total asam tertitrasi, dan kandungan alkohol). Data dianalisis dengan analisis varian dan DMRT jika berbeda nyata pada taraf kesalahan 5%. Hasil penelitian menunjukkan bahwa konsentrasi ragi berpengaruh nyata terhadap pH, total padatan terlarut, total asam titrasi, dan alkohol. Waktu fermentasi berpengaruh nyata terhadap total asam titrasi dan kadar biovinegar alkohol. Perlakuan terbaik diperoleh pada perlakuan penambahan ragi sebanyak 3% dan lama fermentasi 8 minggu dengan nilai TAT 1,21, nilai pH 4,5, TPT 2,60, dan kadar alkohol 4,67%.
Kata kunci: biovinegar; fermentasi; kulit nanas; Subang, yeast.
Identification the m6A regulator mediated RNA methylation modification patterns and immune- related key genes involved in ischaemic stroke
Authors: Zheng Peng-Fei , Huang Cheng-Cheng , Zhou Ting , Pan Hong-Wei , Huang Li-Zhong , Wang Chang-Lu , Rong Jing-Jing
Published: December 2024

Background
The precise impact of RNA N6-methyladenosine (m6A) modification on the immune microenvironment in ischemic stroke (IS) remains unclear. This study aimed to investigate the influence of m6A modification on the immune microenvironment in IS and identify crucial immune-related genes associated with IS.
Methods
The RNA modification patterns among 108 IS samples were determined by examining the differential m6A regulators between samples from individuals with IS and normal samples. Single-sample gene-set enrichment analysis (ssGSEA) and gene set variation analysis (GSVA) were employed to estimate the abundance of specific infiltrating immune cells and assess 50 HALLMARK pathways between healthy subjects and IS patients, as well as among the distinct m6A modification patterns. The weighted gene co-expression network analysis (WGCNA) was utilized to identify meaningful modules associated with immune cells. Two machine learning methods were applied to identify the key immune-related genes associated with IS. Finally, meta-analysis based on six different datasets was employed to validate the expression levels of the identified key genes.
Results
A total of eight key differential m6A regulators were identified between healthy individuals and patients with IS using a random forest classifier. Based on the expression profiles of these eight m6A regulators, two distinct RNA modification patterns (m6A cluster-A and cluster-B) were observed among the IS samples. Differential abundance of infiltrating immune cells and activation of HALLMARK signalling pathways were identified between the normal and IS samples, as well as among the two distinct m6A modification patterns. Notably, the WGCNA method highlighted the significant association of the black module with m6A cluster-B and several infiltrating immune cells. Furthermore, two machine learning methods identified several key genes exhibiting differential expression between control subjects and IS patients, as well as among distinct m6A modification patterns, including ABCA1, CPD, PRRG4, WDR46, and C19orf24. Meta-analysis revealed an association between WDR46 and a decreased risk of IS, while CPD and ABCA1 were linked to an increased risk of IS.
Conclusions
The present study provides compelling evidence highlighting the pivotal role of m6A modification in shaping the intricate and diverse immune microenvironment of IS. Notably, the CPD, ABCA1 and WDR46 genes emerge as potential novel biomarkers with implications for accurate diagnosis and immunotherapy of IS. These discoveries deepen our understanding of the intricate interplay between m6A modification, immune responses, and the pathogenesis of IS, opening new avenues for personalized treatment approaches.
The effect of obstacle length and height in supercritical free-surface flow
Authors: Michalski Hugh , Mattner Trent , Balasuriya Sanjeeva , Binder Benjamin
Published: December 2024

Two-dimensional open channel flow past a rectangular disturbance in the channel bottom is considered in the case of supercritical flow, where the dimensionless flow rate is greater than unity. The response of the free surface to the height and length of a rectangular disturbance is investigated using the forced Korteweg-de Vries model of Michalski et al. (Theor Comput Fluid Dyn 38:511 - 530, 2024). A rich and complex structure of solutions is found as the length of the disturbance increases, especially in the case of a negative disturbance. As the length of the disturbance is decreased, some solutions approach those of the well-studied point forcing approximation, but there are other solutions, for a negative disturbance, that are not predicted by the point forcing model. The stability of steady solutions is then considered numerically with established pseudospectral methods.
Analysis of Solutions of Fuzzy Differential Equations under the Generalized Derivative
Authors: Longo Felipe , Laiate Beatriz , Gadotti Marta Cilene , Meyer João Frederico da Costa Azevedo
Published: December 2024

This work investigates the existence of non-gH\(\ast\)-solutions of fuzzy differential equations under g-derivative. We begin by establishing a theorem that extend the calculus fundamental theorem to the fuzzy context of g-differentiability. After some particular examples that help understand the possible cases for such differential equations, some results are settled giving the necessary conditions for each one of the observed behaviors and more.
Save the Farms: Nonlinear Impact of Climate Change on Banks' Agricultural Lending
Authors: Liu Teng
Published: December 2024

The agricultural sector is particularly susceptible to the impact of climate change. In this paper, I investigate how vulnerability to climate change affects U.S. farms' credit access, and demonstrates that such impact is unequally distributed across farms. I find that higher exposure to climate change, measured by temperature anomaly, reduces bank lending to farms. Such impact is persistent, nonlinear, and heterogeneous. Small and medium farms almost always experience loss of loan access. In comparison, large farms see less severe credit contraction, and in some cases may even see improvement in funding. While small banks carry the burden of continuing to lend to small farms, their limited market share cannot compensate for the reduction of lending from medium and large banks. These results suggest that factors such as farm size and bank type can amplify the financial impact of climate change.
Revealing the prognostic landscape of hemoglobin, albumin, lymphocyte and platelet score in patients with lung cancer: a meta-analysis
Authors: Wang Wenxia , Ren Bi , Gou Haocheng , Guo Wu
Published: December 2024

The hemoglobin, albumin, lymphocyte, and platelet (HALP) score has been reported to be associated with the progression of many types of tumors. Nevertheless, the connection between HALP score and individuals with lung cancer is still a subject of debate. We conducted a systematic evaluation to investigate the prognostic role of HALP score on survival outcomes in lung cancer patients. As of July 2024, we searched the PubMed, PubMed Central, Web of Science, and Embase databases to collect relevant articles evaluating the relationship between HALP and lung cancer prognosis. The pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) for overall survival (OS), progression-free survival (PFS), recurrence-free survival (RFS), and disease-free survival (DFS) were analyzed. A total of 12 studies involving 7775 lung cancer patients were included. The combined results revealed that a low HALP score was associated with poorer OS (HR = 1.71, 95% CI, 1.28–2.30, p < 0.001), PFS (HR = 1.44, 95% CI, 1.15–1.80, p < 0.001), and DFS/RFS (HR = 2.78, 95% CI, 1.14–6.78, p < 0.001). Subgroup analysis further confirmed that pretreatment HALP was an independent predictor of OS in lung cancer patients. The decreased pretreatment HALP score was strongly associated with inferior prognosis in lung cancer patients. Our findings highlight that HALP score is a reliable biomarker of lung cancer prognosis. However, multicenter and prospective studies are needed to further validate its clinical utility.