bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Numerical Integration in Analysing the Volume of Reinforcement Particles in Algorithms for Generating Representative Volume Elements (RVEs)
Authors: Mieczkowski Grzegorz , Szpica Dariusz , Borawski Andrzej 
Published: October 2024

Abstract
The paper focuses on spatial modelling of composites with discontinuous reinforcement. The algorithm for creating a representative volume element (RVE) must consider random distribution and size of reinforcing particles (RP), prevention of RP interpenetration, and maintaining the desired volume fraction of the reinforcing phase (Vp) in the composite microstructure. Assuming fixed RVE dimensions and randomly determined RP size, the actual Vp value needs to be continuously determined. If the assumed (desired) Vp is lower than the current value, additional reinforcement is added to the RVE. As the RP location is random, some particles may extend beyond the RVE limits, affecting Vp calculation. The research aims to determine the RP volume within the RVE boundaries when RP extends outside. The RVE was discretized with N points, and the number of Ni points within the area occupied by RP was determined. The sought value was calculated using the ratio Ni /N = Vp /VRVE, where VRVE, is the volume of the RVE. Two discretisation methods, systematised (RI) and random (Monte Carlo (MC)), were employed. The study investigated the effects of discretisation type and number N points on calculation accuracy and microstructure generation time for particle-reinforced composites in sphere, cylinder, and ellipsoid shapes. Systematised discretisation yielded higher accuracy/stability, with number N dependent on RP dimensions. The MC method reduced generation time but introduced instability and significant errors.
Automation of the Oil Extraction Process Performed by Means of A Screw Press
Authors: Lobur Mykhailo , Korendiy Vitaliy , Kachur Oleksandr , Havran Volodymyr 
Published: October 2024

Abstract
The continuous development of the oil-manufacturing industries causes the necessity of improving extraction technologies. In this case, the specific interest is focused on the control systems of screw presses. Among a great variety of such machines, the small household presses are in significant demand among consumers. Various seeds and kernels require different technological conditions to be provided in order to maximize the qualitative and quantitative characteristics of the extracted oil. Therefore, the main objective of this research is developing and testing the control system allowing for automation of the oil extraction process. Particularly, the temperature parameters of the pressing chamber, extracted oil, and electric motor are to be monitored and limited. In addition, the consumer should be able to predefine the mass of the oil to be extracted. Considering the small household screw press LiangTai LTP200, the general algorithm (block diagram) of the control system operation is proposed and the corresponding experimental prototype is developed. The latter is based on the Arduino Mega microcontroller and is equipped with three temperature sensors, two coolers (fans), one heater, and one mass sensor. The proposed control system allows for continuous monitoring and limiting of the pressing chamber, oil, and electric motor temperatures, as well as the mass of the extracted oil. The experimental data show that the pressing chamber preheating process lasts for about 3 min (170…190 s) and its maximal temperature does not exceed 44°C. The temperature of the extracted oil does not rise over 61°C. The motor temperature changes within the range of 69...71°C. The oil extraction productivity is as follows: 1.2 kg/h (sunflower seeds), 1.06 kg/h (walnut kernels), 0.9 kg/h (almond kernels), and 0.78 kg/h (peanut kernels). The obtained results can used in further investigations focused on analyzing the influence of these parameters on the quantitative and qualitative characteristics of the extracted oil.
The Effect of the Molecular Weight of Hyaluronic Acid on the Rheological and Tribological Properties of the Base for Artificial Synovial Fluid Preparations
Authors: Karpowicz Monika Izabela , Klekotka Marcin , Dąbrowski Jan Ryszard 
Published: October 2024

Abstract
The synovial fluid is responsible for adequately lubricating, moisturizing, and nutritional human joints. This liquid should have appropriate viscoelastic properties and ensure a low coefficient of friction in biotribological systems. Many artificial synovial fluid preparations used in viscosupplementation treatments are based on hyaluronic acid. This work aimed to evaluate the influence of molecular weight on the functional properties of solutions based on hyaluronic acid. 1% solutions based on hyaluronic acid with five different molecular weights from 50,000 Da to 2 MDa were made. Rheological (viscosity, viscoelasticity), tribological (coefficient of friction, wear assessment), and wettability tests were carried out. Significant differences were observed in the rheological tests, where the viscosity strictly depends on the molecular weight of the hyaluronic acid. It has been shown that the molecular weight of HA has little effect on the coefficient of friction. On the other hand, the differences in the tribological wear are much more significant. The molecular weight of biopolymers is one of the essential parameters in developing new artificial synovial fluids. Using a higher molecular weight of hyaluronic acid increases viscosity and wettability, resulting in less tribological wear.
Automatic Method of Macular Diseases Detection Using Deep CNN-GRU Network in OCT Images
Authors: Powroznik Pawel , Skublewska-Paszkowska Maria , Rejdak Robert , Nowomiejska Katarzyna 
Published: October 2024

Abstract
The increasing development of Deep Learning mechanism allowed ones to create semi-fully or fully automated diagnosis software solutions for medical imaging diagnosis. The convolutional neural networks are widely applied for central retinal diseases classification based on OCT images. The main aim of this study is to propose a new network, Deep CNN-GRU for classification of early-stage and end-stages macular diseases as age-related macular degeneration and diabetic macular edema (DME). Three types of disorders have been taken into consideration: drusen, choroidal neovascularization (CNV), DME, alongside with normal cases. The created automatic tool was verified on the well-known Labelled Optical Coherence Tomography (OCT) dataset. For the classifier evaluation the following measures were calculated: accuracy, precision, recall, and F1 score. Based on these values, it can be stated that the use of a GRU layer directly connected to a convolutional network plays a pivotal role in improving previously achieved results. Additionally, the proposed tool was compared with the state-of-the-art of deep learning studies performed on the Labelled OCT dataset. The Deep CNN-GRU network achieved high performance, reaching up to 98.90% accuracy. The obtained results of classification performance place the tool as one of the top solutions for diagnosing retinal diseases, both early and late stage.
Research on the traceability of attack teams based on offensive and defensive confrontation
Authors: Guo Libo , Yang Lin , Wang Ye , Chen Xiang , Bai Yunhe , Hou Shuangshuang 
Published: October 2024

Abstract
This paper explores how attack teams effectively counter trace-back efforts to safeguard their anonymity and security in network attack and defense confrontations. As network attacks become more prevalent and complex, attackers constantly use more covert and sophisticated methods to conduct attacks, making tracking and tracing a critical challenge in cybersecurity. The paper begins by evaluating joint attack trace-back techniques and methods, which include those based on network traffic analysis, malicious code analysis, and log auditing. Simulated experiments in natural network environments validate the effectiveness and feasibility of the proposed strategies. The research findings demonstrate that anti-tracing strategies based on offensive confrontation can effectively enhance the anonymity of attack teams and their ability to withstand trace-back attacks, offering new insights and methods for cybersecurity defense.
Construction of a multi-technology fusion e-commerce data transaction optimization model based on federated learning
Authors: Xu Chang , Wu Peng , He Jingyu , Chen Zhijie , Liu Yang 
Published: October 2024

Abstract
The constraints of data protection make the data confined to different enterprises and organizations, forming many “data islands” and making it difficult to bring out the important value it contains. In this paper, we use federated learning technology as the service foundation and introduce differential privacy, federation chain, interstellar file system, and trusted execution environment to construct a multi-technology fusion e-commerce data transaction method. The three concepts of budget feasibility, individual rationality, and incentive mechanisms are applied to the data transaction scenario to design smart contracts. At the same time, the incentive mechanism is created by combining the trusted execution environment and Shapley value, and the transaction process model is optimized. Simulation comparison is carried out based on the public dataset of the Taobao e-commerce platform, and the experimental results show that MTFDT can realize the accurate evaluation of the model training effect, and the incremental profit stabilization point of the data buyer and seller is around 0.4, which improves the fairness of benefit distribution.
Jewish Art Studies in the Lithuanian Yiddish Press of the Interwar Period (1918–1940)
Authors: Gradinskaitė Vilma 
Published: October 2024

Summary
Lithuanian art studies as an independent branch of science began to take shape in the First Republic of Lithuania between year 1918 and 1940. During 22 years in a multinational free state, it followed a winding path of mastery, professionalism, and the formation of a critic’s thought. However, if the origins, development, and forms of interwar Lithuanian art studies already are being explored, the Jewish art studies are still waiting for its first investigations. The purpose of this article is to broaden the scope of Lithuanian art research by incorporating the layers of interwar Jewish art studies conducted in the Yiddish language. Using the combined methodology of research as method of source studies, the aspects of social history of art and the comparative method, the Jewish art studies were analysed as a specific phenomenon which functioned alongside Lithuanian art studies. Throughout this research, over 1,000 Yiddish publications were reviewed to find the answers to the never previously discussed questions – how many Jewish art historians and critics contributed articles to the Yiddish press, what kind and quality of publications about Jewish art were featured, what aspects of Jewish art, artists, and society did Jewish art critics emphasise, and what kind of relationship existed among art critics, artists and public. The article also encompasses the short biographies of the most prominent Jewish authors in the field of art criticism.
Enhancing Wireless Communication Efficiency Using Dynamic Nonlinear Distortion Adaptive Optimization Analysis
Authors: Jayarani R , Narmadhai N 
Published: October 2024

Abstract
Modern communication networks require improved signal quality and spectrum efficiency. Modern wireless communication relies heavily on the multiple input multiple output (MIMO) technology to improve spectrum efficiency and achieve faster data rates. However, the performance of MIMO systems is significantly hampered by non-linear distortions in power amplifiers (PA), especially under dynamic operating conditions. Traditional methods to reduce these distortions often lack the adaptability required for effective optimization. The proposed dynamic nonlinear distortion adaptive optimization analysis (DNDAOA) therefore introduces an adaptive approach that dynamically adjusts the pre-distortion signals using real-time feedback mechanisms. DNDAOA effectively reduces non-linear distortions and thus improves the performance of MIMO systems. Simulation results show that DNDAOA significantly increases spectrum efficiency, reduces error rates, and improves signal quality. This method is widely used in areas such as wireless telecommunications, internet of things (IoT), autonomous vehicles, and smart infrastructure, driving advances in connectivity, reliability, and data integrity.
Advanced Computer Vision Techniques for Accurate Measurement in Unmanned Mobile Robots
Authors: Bharathi V , Natraj N A , Gopinath S , Kiruthikaa R 
Published: October 2024

Abstract
For years, researchers have been studying computer vision, i.e. the ability of artificial intelligence (AI) systems to perceive and interpret visual data like humans. This study is gaining increasing attention as researchers aim to develop tools that automate visual tasks and replicate human visual awareness. However, the interpretation of images is very complex due to the vast amount of multi-resolution information they contain, making the development of AI technologies for visual recognition particularly challenging. This article provides an overview of digital image processing, highlighting the main concepts and introducing key algorithms. These methods are designed to capture, process, and interpret digital images and enable the extraction of important data from real-world environments. We conduct rigorous image processing tests and compare AI-driven recognition systems with human analysis. The results show that computer vision technology significantly outperforms human observation in terms of accuracy and consistency. These results highlight the potential of computer vision to revolutionize various industries by automating complex visual tasks and offer promising future applications in areas such as healthcare, security, and manufacturing. The paper provides valuable insights into current advances in digital image processing and the role of AI in improving visual recognition capabilities, paving the way for further innovation in this area.
Metric Stability of One Month Handgrip Maximal and Explosive Isometric Strength Measured by Classic and Impulse Contractions
Authors: Vukadinović Nevena , Šmrkić Marko , Stefanović Života , Ilić Vladimir , Nikolić David , Zlatović Igor , Dopsaj Milivoj 
Published: October 2024

Abstract
The aim of this study is to determine the metric stability of the one-month handgrip test (HGT) in order to define the contractile characteristics of the biological variation of maximal isometric strength (F
max) and maximal isometric rate of force development (RFD
max) of the handgrip in two different testing regimes (classic and impulse). The study was conducted with a total of 16 participants (11 men and 5 women). Testing was performed using an isometric handgrip probe with a standardized test protocol and equipment sports medical solutions (SMS). The results of F
max showed a low relative standard error of the mean (RS = 1.33 %), a high value of inter-class correlation (ICC = 0.996), and no statistically significant change in trend (p > 0.05) during the testing period. Therefore, can conclude that the HGT procedure in classic mode can be used as a stable parameter in a human subject sample. However, the RFD
max results showed a low RS (2.13 %) and a high ICC value (0.996), but a statistically significant change of trend (p < 0.05) during the measurement period. The regression constant (RCO) trend was 42.629 N/s, which can be attributed to learning or to the adaptive effects of the test procedure, which triggered similar adaptation processes as the training. In general, it can be concluded that the handgrip can be used to sensitively measure the effects of different long-term health improvements, or the effects of different medical/health exercises, rehabilitation programs, effects of medication applications, or dietary supplements for F
max. However, further research should be conducted for the RFD
max considering the metric stability parameters.
Criteria and Sustainability Practices in Public Procurement: An Analysis From the Perspective of UNB'S Procurement Agentes
Authors: Ulhoa Tatiana , Costa Abimael De Jesus Barros , Faria Emília de Oliveira , Mendes Nara Cristina Ferreira 
Published: October 2024

Objective: The objective of this study is to analyze the adoption of sustainability criteria and practices in public contracting processes at University of Brasília (UnB) based on the perception of purchasing agents.

Theoretical Framework: The theoretical framework consists in relevant research on the topic and recent studies applied to Higher Education Institutions (HEIs), highlighting main findings, identified barriers and proposed solutions.

Method: Adopted documentary research and questionnaires. The data obtained through the application of the aforementioned instruments were transferred to an electronic spreadsheet and analyzed using descriptive methods.

Results and Discussion: Show a complex scenario, where the majority of UnB's purchasing agents have advanced training and seek information about sustainability, but there are still significant gaps in the knowledge and application of the institution's environmental policies. The perception about sustainability at UnB is divided, reflecting the need for greater communication, training and strategic alignment to promote more sustainable organizational culture.

Research Implications: This research deals with a relevant and current topic in the context of public administration, by demonstrating the practices adopted and potential for improvements.

Originality/Value: This study contributes to literature by delving deeper into a new topic, which consequently requires further studies and analyzes for advances in the technical and scientific field, since the results identified through evidence and findings can add gains for Public Administration.
Indaga-T Innovation Group: A Trajectory of Teaching Collaboration
Authors: Valero Joan-Anton Sánchez , Herraiz-García Fernando 
Published: October 2024

Objective/Theoretical Framework: This paper orders various experiences of teaching innovation in the context of the Indaga-t group of the University of Barcelona. In them, the collaboration between professors from different Degrees taught in the faculties of Education and Fine Arts is shown.

Method: The work carried out went beyond sharing teaching, displaying a series of methodologies that led teachers to work in joint actions intervening in the same space and time with students.

Results and Discussion: The text shows how various dilemmas were faced in a university context where, increasingly, the relationship between the credits of the courses and their teaching assignments do not invite teachers to interact by going to the classroom together.

Implications of the Research: The challenge involved reflecting and becoming aware of the motivations that combined efforts in the face of a stiff institution where time is a scarce resource.

Originality/Value: The experiences of communication are the result of learning relationships between teachers and students who worked together collaboratively from different areas of knowledge; These experiences speak of the commitments that were assumed as our beyond our own courses and their teaching plans.
Чувствительность метода цифровой обработки первичных сигналов лазерного гироскопа к возмущениям входной информации
Authors: Михаил Викторович Чиркин , Юлия Романовна Иваненко , Андрей Евгеньевич Серебряков , Валерий Юрьевич Мишин , Алексей Владимирович Молчанов 
Published: October 2024

Сформирована математическая модель для первичных сигналов лазерного гироскопа, которая учитывает связь встречных оптических волн, механическое вращение корпуса лазерного гироскопа и аддитивный шум. Исследована чувствительность к возмущениям входной информации метода вычисления мгновенной фазы Саньяка с компенсацией динамического захвата на базе лазерного гироскопа с гармонической частотной подставкой без ошумления. Для анализа корректности работы метода вычисления мгновенной фазы Саньяка с компенсацией динамического захвата полученные результаты сравниваются с угловой скоростью, найденной в результате аналитического решения дифференциального уравнения лазерного гироскопа с нулевой зоной захвата. Зафиксированы фазовые ошибки между исследуемым и эталонным сигналами угловой скорости вращения лазерного гироскопа. Определено влияние квазибелого шума, изменения значений амплитуд первичных сигналов и сдвига фаз между квадратурными сигналами и сигналом переменной составляющей суммы мощностных сигналов на зарегистрированные отсчеты угловой скорости вращения корпуса лазерного гироскопа.
The mathematical model for laser gyroscope primary signals that includes coupling between counter-propagating optical waves, mechanical rotation of laser gyroscope body and additive noise is formed. The sensitivity of the method to calculate the instantaneous Sagnac phase with compensation for dynamic lock-in to input perturbations is studied on the basis of laser gyroscope having the harmonic dither unnoised. To analyze the method to calculate the instantaneous Sagnac phase with compensation for dynamic lock-in, the results obtained are compared with the angular rate being the analytical solution of differential equation for laser gyroscope with zero lock-in zone. Phase errors between a test signal and a reference signal of angular rotation rate of laser gyroscope are recorded. The effect of quasi-white noise, changes in primary signal amplitudes and phase shift between quadrature signals and the signal being the alternating component of power signal sum is determined on the registered counts of angular rotation rate of laser gyroscope body.