bluuebunny/crossref_metadata_2025 huggingface dataset:
Physical modeling as a verification tool for geomechanical tasks solving
Authors: Sokornov Anton , Kon'kov Aleksandr
Published: December 2024

to verify the mathematical model of the interstation and station subway tunnels junctionsection by creating a physical model using the method of equivalent materials. To analyze the formation of vertical loads from ground pressure on the tunnel linings, taking into account the selected sequence of work. To establish the station tunnel and its face wall influence on the interstation tunnel lining stressstrain state, and determine the size of this area of influence based on the simulation results. Methods: the finite element method in combination with the analytical method (mathematical modeling), the method of equivalent materials (physical modeling). Results: patterns of load distribution from vertical ground pressure on the interstation tunnel lining at the interface with the deep shallow pylon station have been revealed. It was found that on the approach to the face wall of the station, the interstation tunnel lining perceives the vertical load from the ground pressure, exceeding the load on the lining outside the area of the station influence by about 2–4 times. In addition, it was found that the initial deformations of the station workings lead to an increase in the load on the interstation tunnel. Thus, it is rational to forecast the load from the ground pressure on the interstation tunnel lining, taking into account the initial deformations of the station workings. It is established that the boundary of the station tunnel influence area on the stress-strain state of the interstation tunnel lining practically does not depend on the depth of laying and can be assumed to be 7 m. Practical significance: the results of the study can be used at the design stage of the interstation and station tunnel junction to determine the length of the interstation tunnel section with reinforced lining.
Sanctuary
Authors: Grobbel Abby
Published: December 2024

Sanctuary delves into the realms of memory, forgiveness, and present contemplation through a four-phase journey into the past. Each segment intimately explores significant periods and memories, providing an external lens for reassessment. Employing collage illustrations for world-building and drawing inspiration from common gaming elements, such as an inventory system and interactive dialogue options, the artist reflects on themes of causality and the profound impact decisions make on our lives. This contemplation extends to the construction and dissolution of the foundations of our realities, mirroring the ebb and flow of our homes throughout different life phases. The reiteration of memories and contemplation of choices are seamlessly woven into the narrative through the lens of game mechanics, offering users the agency to shape their own version of the past. The immersive journey culminates in an envisioned 'sanctuary,' a symbolic space that mirrors the user’s unique disposition, encapsulating the essence of their inner world.
Oneiromancy – Divination through Dreams
Authors: Buena Onda Collective  , Ksel Dominika , Morales Camila
Published: December 2024

Oneiromancy – Divination through Dreams by Buena Onda Collective (Dominika Ksel and Camila Morales) is an immersive, interactive animated project designed to empower the Far Rockaway, Queens community in the face of climate crisis and environmental injustice. Collaborating with local organizations like RISE and Shore Corps, as well as residents and CUNY students, the project engaged over 100 participants (ages 5-65+) in workshops to create drawings, 3D models, audio recordings, and animations that reflect personal histories, dreams, and ecological connections. Guided by questions about capitalism and rising tides, the collective envisioned alternative futures, blending fantasy, dystopia, and resilience. Using open-source software, AI, and stop-motion animation, these visions were transformed into immersive 360-degree experiences, accessible via mobile devices and QR codes across the Rockaway Peninsula. The 360 animations culminated in an interactive exploratorium built with Unity and Community Toolkit, showcasing the power of artistic collaboration and digital media in addressing socio-environmental challenges, and moving from scarcity to empowerment and abundance.
RISK FACTORS FOR LEPROSY: A SYSTEMATIC REVIEW
Authors: Pertiwi Aisyah Noer Auliyah Madani , Syahrul Fariani
Published: December 2024

Introduction: In 2021, the global prevalence rate of registered leprosy cases stands was 16.9 cases per one million people, with a case detection rate of 17.83 new cases per one million people. This indicates a 10.2% rise in new cases compared to the previous year. Aims: This study aims to examine the risk factors associated with leprosy. Methods: The inclusion criteria for this study were articles published in the last five years, available in full-text, and written either in Indonesian or English. Articles that were literature reviews, systematic reviews, meta-analyses, or classified as grey literature were excluded. The exclusion criteria were established to determine which studies to include in this study. Results: This study found that leprosy is associated with household density, personal hygiene, history of contacts, ventilation, humidity levels, BCG vaccination history, flooring type, house lighting, temperature, and wall type. Personal hygiene was identified as the primary risk factor for leprosy based on individual characteristics and behaviors, while household density was identified as the most significant risk factor based on the physical environment of the occupants. Therefore, poor personal hygiene and high residential density increase the risk of leprosy. Conclusion: The key risk factors for leprosy include household density and personal hygiene, while a history of BCG vaccination serves as a protective factor. This study provides valuable information for governments and stakeholders to assess healthy household indicators and promote clean and healthy living practices in communities
Systemic leadership in sustainable collaborative governance: A case study of urban green space management in Surabaya
Authors: Haryono Nanang , Rahayu Amy Yayuk Sri , Soeling Pantius Drahen
Published: December 2024

Collaborative governance has been widely recognized as an effective strategy to address complex public challenges, particularly in managing urban green spaces. This research examines systemic leadership in promoting cross sectoral collaboration for sustainable urban green space management. Specifically, it explores the role of systemic leadership in fostering cross-sectoral collaboration for sustainable urban green space management in Surabaya during Mayor Tri Rismaharini’s administration (2010-2020). A qualitative case study approach was employed, involving in-depth interviews with 15 informants from various sectors, document analysis, and observations. The findings reveal that systemic leadership ensures alignment between private sector contributions and public goals. Additionally, the integration of multifunctional green infrastructure, such as pedestrian pathways and stormwater management systems, contributes to environmental sustainability and urban resilience. This study reinforces existing collaborative governance theory and highlights the importance of long-term leadership in nurturing sustainable urban green space partnerships. It concludes that systemic leadership acts as a balancing force among stakeholder interests, facilitating compromise and institutional interactions crucial to achieving collaborative goals. This research contributes to the literature by emphasizing the significance of systemic leadership in promoting sustainable urban governance and offers practical insights for policymakers and urban planners to enhance collaborative processes in similar contexts.
ANADOLU'DA ROMA EGEMENLİĞİNE KARŞI İLK BÜYÜK TEPKİ: ARİSTONİKOS İSYANI
Authors: Türk Mustafa
Published: December 2024

Aristonikos, Pergamon Kralı III. Attalos’un MÖ 133 yılındaki vasiyetinin ardından krallık topraklarının Roma tarafından ilhak edilmesine karşı çıkmıştır. Aristonikos’un bu çıkışı, Eskiçağ tarihi literatüründe uzun süredir tartışılmaktadır. Tartışmalar daha çok III. Attalos’un neden böyle bir yola başvurduğu, Aristonikos’un kraliyet ailesiyle ilişkisi, vasiyetin kapsamı ve özellikle de Aristonikos’un girişiminin niteliği üzerinde yoğunlaşmış durumdadır. Vasiyetin sahte olabileceği yönündeki görüşler, Pergamon’da ele geçen ve isyana verilen desteğinin önlenmesi amacıyla çıkarıldığı anlaşılan yasaları içeren bir yazıtla sonlanmış gözükmektedir. Buna karşın III. Attalos’un tercihinin nedenleri, vasiyetin kapsamı ve isyanın niteliği konusundaki tartışmalar hala devam etmektedir. Üç bölümden oluşan bu çalışma; Antik yazarların eserleri, sikkeler, yazıtlar ve bu kaynaklara dayanarak yazılmış olan modern literatür ışığında, Anadolu’daki Roma hâkimiyetinin hemen başında gerçekleşen Aristonikos isyanını irdelemeyi amaçlamaktadır. Konu; Roma’nın Anadolu ile ilişkilerinin dönüm noktaları, III. Attalos’un vasiyeti ve Aristonikos isyanı başlıkları altında değerlendirilecektir.
Electrical properties of nanostructured silicon layers, obtained by a chemical method
Authors: Bilyk T.YU.
Published: December 2024

In the paper further investigation of correlation between properties and formation conditions of nanostructured layers is performed. In this work dependence of nanoporous silicon layer properties from formation time is studied and charge transfers regimes are investigated by differentiate analysis. Etching time increment results on decrement of layer conductivity and formation of unidirectional potential hill
Laser processing in the production of conductive tracks by printing silver nanoparticles for the needs of electronics
Authors: Lesyuk R.I. , Bobitskiy Ye.V. , Kotlyarchuk B.K. , Yillek V.
Published: December 2024

Formation of conductive tracks on the ceramics substrates based on combining the inkjet printing method of stabilized silver nanoparticles and its laser sintering using light induced substrate heating mechanism is described in th work. Optimal laser radiation parameters which provide the conductivity of fabricated structures at the rate of 10% of bulk silver conductivity were found. Also the laser annealing of silver nanoparticles on the polyimide substrate was implemented
Component analysis of liquid-phase objects by the method gas discharge visualization
Authors: Zavhorodniy A.B.
Published: December 2024

The analysis of some GDV-gram’s parameters (like lightning square, lightning square dispersion) for component analysis of physical (in particular – liquid-state) objects was done. The correlation between specific conductance and GDV-gram lightning square in aqueous solutions of strong and weak electrolyteswas shown
Application of neural networks in the formation system magnetic field pulses
Authors: Shlykov V.V. , Delavar-Kasmai M.
Published: December 2024

The control system for the magnetic field pulse shaping device responding on the shaper input pulse shape change and performing the shape selection on the basis of a neural network which is integrated in a microprocessor system is offered
Mathematical model for optimising the contemporary process of training specialists in the field of cybersecurity and information protection
Authors: Horlichenko Serhii , Horlichenko Anastasiia
Published: December 2024

The article examines current issues of training cybersecurity specialists, which are of particular importance in the context of rapid development of information technology and the growing number of cyber threats. It is noted that in Ukraine, as in many other countries, there are problems related to the organisation and management of the process of training such specialists. Traditional teaching methods do not always correspond to the specifics of the rapidly changing cyber environment, which makes it difficult for graduates to adapt to real working conditions. There is also a lack of uniform methodological approaches to regulating the educational processes in the field of cybersecurity, which leads to different quality of training in different educational institutions. Emphasises the need to develop a mathematical model for optimising the modern educational process of cybersecurity specialists, which would provide an integrated approach to planning and managing the training of cybersecurity specialists. Analyses the latest scientific researches and publications on the education of cybersecurity specialists, which investigated the problems and ways of improving cyber-education both in Ukraine and abroad. The purpose of the article is to develop a mathematical model for optimising the modern educational process of training cybersecurity specialists. This model takes into account the interaction between students, teachers and employers, as well as the dynamic development of students' competences. The authors propose to define the main roles of the participants in the educational process and their strategies. The model allows to take into account the transition probabilities of the development of students' competences and possible risks associated with the choice of certain educational pathways. The proposed mathematical model makes it possible to optimise the process of training specialists, which will help to improve their professional competence and ability to respond to current challenges in the field of cybersecurity. Such an integrated approach makes it possible to ensure effective decision-making at each stage of the educational process, which is extremely important for training qualified personnel in the field of cybersecurity, capable of countering modern cyber threats and ensuring high levels of information security.
Application directions of artificial intelligence in software development technologies
Authors: Sokolov Volodymyr , Riabtsev Viacheslav , Uspenskyi Oleksandr , Kopych Danylo
Published: December 2024

The article presents the results of a systematic analysis of the current state of application of artificial intelligence (AI) in software engineering (SW) based on the analysis of publications, assessment of AI capabilities, experience in its application, and conducted experiments. The conceptual foundations of the research were formed, which determine: perception of AI as a tool, not an individual of work; the main directions of its application are engineering and management; the subject of AI application is the processing of artifacts (synthesis and analysis) and obtaining consultations; the need to assess the quality of AI-derived products and analyze the risks of its use is emphasized. Directions of application of AI in management: agreement processes (development of product concept and contract), organizational processes (project group formation and selection of technologies) and project management (planning, risk management, control and analysis of project implementation) Directions of application of AI in engineering: requirements management, design, construction, testing and documenting. To systematize the analysis of AI application directions, a conceptual model was developed, which includes: the direction, subject, and mode of application of AI. The mode of application of AI: the format of the prompt (problem statement and set of input data), the required product and its type (finished product, prototype, template, solution options, information support), the role of AI (executor, co-author, consultant), form of AI interaction (external service, integration via API, integrated system or local autonomous system). A structure of derivative models was formed for the analysis of the application of AI in specific directions with an overview of the capabilities of the most effective AI tools. As conclusions, it was determined that in management, the most rational model of using AI is to receive consultations and prototypes of documentation when contacting external AI services, in engineering – creating prototypes of project solutions and documentation based on external services, using integrated AI systems for design and testing in co-authorship mode. The risks of using AI include the possibility of obtaining insufficiently detailed documentation, complex and confusing software artifacts, and errors in the software code. To reduce risks and increase the effectiveness of AI application, it is determined that constant quality control of its products and training based on corporate requirements and standards is required.
Use of large language models to identify fake information
Authors: Lande Dmytro , Hyrda Vira
Published: December 2024

In recent years, the field of artificial intelligence has undergone a true revolution with the emergence of large language models (LLMs) such as GPT-4, Llama-3, Gemini, and others, which have been successfully applied across a wide range of tasks – from text generation to data analysis. This article examines how these models can be effectively used for detecting fake information. This study explores the use of the ChatGPT chatbot for identifying fake information in the context of cybersecurity. Using a large language model, a swarm of virtual experts was created, which generated informational messages on the topic of cybersecurity (both fake and truthful) and assessed them as either “fake” or “true.” For analysis, a semantic network was constructed and subsequently visualized using Gephi. The research analyzed two datasets of messages: one created by human experts and the other by artificial experts. Each message was rated and converted into a numerical format for further analysis. Using the Hamming distance, the results were validated, and the accuracy of matches between assessments was determined. As a result of building the semantic network, key concepts in the field of cybersecurity were identified, along with the relationships between them. A swarm of artificial experts generated a dataset of messages with fake and truthful content, which was assessed both by the artificial experts themselves and by a human expert. Analysis of the Hamming distance between these assessments demonstrated that artificial intelligence has potential in detecting fake information; however, at this stage, its performance requires human oversight and adjustments.
Experimental and Numerical Study of the Flow Field Generated by a Flapping Plate Using the POD Method
Authors: Hernández-Montañez Carlos E. , González-Rangel J. Michel , Moreno-Hernández David , Martínez-González Adrián
Published: December 2024

Plate flapping motion is a common phenomenon in different engineering applications. Therefore, this study is realized in the context of different flapping frequencies and uses experimental and numerically simulated results for the analysis. The flapping frequencies studied are 10 Hz, 30 Hz, and 40 Hz, and the plate has length and width dimensions of 0.022 m and 0.0195 m. The experimental results are obtained using the time-resolved Schlieren technique, and the numerical one is obtained using ANSYS Fluent software. The numerical and experimental results show good agreement between them. The POD method applied to the simulated velocity field allows us to decompose the data set into the main properties of the unsteady flow. For the three cases analyzed, energy greater than 80% is accumulated in the first four POD modes.
Comparative Study of Chinese Herbal Medicines on Dermatitis Focus on Quercetin and Its Derivatives
Authors: Cheng Ching-Yi , Young Guang-Huar , Wang Hsiang-Ting , Kuo Ting-Chun , Yang Ching-Chieh , Lin Horng-Chyuan
Published: December 2024

Dermatitis is commonly treated using Western medicine, systemic medication, or phototherapy. However, long-term monitoring and side effects remain a concern. Chinese herbal medicine has gained attention as an alternative. Although studies have explored the antioxidant and anti-inflammatory effects of quercetin (Q) and its derivative rutin (RT) on the skin, quercitrin (QI) and hyperoside (HP) have not yet been thoroughly investigated. This research aims to compare these four Chinese herbal medicines for their potential to improve dermatitis and explore their mechanisms. CM-H2DCFDA staining, Western blotting and ELISA analysis showed that Q exhibited the best antioxidant and anti-inflammatory effects, mainly inhibiting free radical production and affecting downstream pathways, including MEK1/2-Erk1/2-c-Fos, JNK1/2-c-Jun, and traditional IκB-NF-κB pathway. We also confirmed the anti-inflammatory effect of Q in a mouse model of atopic dermatitis (AD). In conclusion, though less potent than Q, its derivatives still possess anti-inflammatory and antioxidant abilities.
Stem Cell-Derived Extracellular Vesicle-Mediated Therapeutic Signaling in Spinal Cord Injury
Authors: Poongodi Raju , Hsu Yung-Wei , Yang Tao-Hsiang , Huang Ya-Hsien , Yang Kuender D. , Lin Hsin-Chieh , Cheng Jen-Kun
Published: December 2024

Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have emerged as a promising therapeutic strategy for spinal cord injury (SCI). These nanosized vesicles possess unique properties such as low immunogenicity and the ability to cross biological barriers, making them ideal carriers for delivering bioactive molecules to injured tissues. MSC-EVs have been demonstrated to exert multiple beneficial effects in SCI, including reducing inflammation, promoting neuroprotection, and enhancing axonal regeneration. Recent studies have delved into the molecular mechanisms underlying MSC-EV-mediated therapeutic effects. Exosomal microRNAs (miRNAs) have been identified as key regulators of various cellular processes involved in SCI pathogenesis and repair. These miRNAs can influence inflammation, oxidative stress, and apoptosis by modulating gene expression. This review summarizes the current state of MSC-EV-based therapies for SCI, highlighting the underlying mechanisms and potential clinical applications. We discuss the challenges and limitations of translating these therapies into clinical practice, such as inconsistent EV production, complex cargo composition, and the need for targeted delivery strategies. Future research should focus on optimizing EV production and characterization, identifying key therapeutic miRNAs, and developing innovative delivery systems to maximize the therapeutic potential of MSC-EVs in SCI.
A Short Survey on the Riemann Hypothesis and Some Attempts to Prove It
Authors: Spigler Renato
Published: December 2024

A short survey on the Riemann Hypothesis is presented, and various even recent attempts aimed at proving it are described.
Polynomial Identities for Binomial Sums of Harmonic Numbers of Higher Order
Authors: Komatsu Takao , Sury B.
Published: December 2024

We study the formulas for binomial sums of harmonic numbers of higher order n ∑ k=0 H (r) k n k (1 − q) k q n−k = H (r) n − n ∑ j=1 Dr(n, j) q j j . Recently, Mneimneh proved that D1(n, j) = 1. In this paper, we find several different expressions of Dr(n, j) for r ≥ 1.
Description and Analysis of the Influence of Social Support on the Postoperative Evolution of Adult Patients Undergoing Retinal Detachment Surgery
Authors: Castellano-Santana Pedro Raúl , Cabrera-López Francisco , Martín-Alonso María DeLasNieves , Flores-Jardo Yésica , González-Martín Jesús María , Díaz-Ginory Ariday Miguel , Torres-Duchement Abián-David , Santana-Socorro Yurena , Hernández-Rodríguez José Enrique
Published: December 2024

Background and Objectives: retinal detachment is an ophthalmological emergency requiring immediate surgical intervention and comprehensive management. This study evaluated the in-fluence of Perceived Social Support (PSS) on postoperative outcomes, including reintervention rates, adherence to recommendations, pain management, and local complications. It was hy-pothesized that higher levels of PSS would be associated with improved postoperative outcomes.
Materials and Methods: A prospective study was conducted involving 166 patients who under-went retinal detachment surgery at a tertiary hospital (2022–2024). Sociodemographic and clinical data were collected, and PSS was assessed using the Medical Outcomes Study (MOS) question-naire, which demonstrated a Cronbach’s alpha reliability coefficient of 0.96. Dependent variables included reintervention rates, adherence, analgesic consumption, and local complications. De-scriptive and inferential statistical analyses were performed, with significance set at p < 0.05.
Results: PSS scores were high (median: 5; SD: 0.55). Adherence rates were excellent (100% at 7 and 15 days; 99.04% at 30 days). Reintervention rates were low (0.5%, 1.0%, and 1.5% at 7, 15, and 30 days, respectively). The need for additional analgesia significantly decreased (46.43% at 7 days versus 13.33% at 30 days; SD: 6.0 to 3.2). No significant associations were found between PSS and major clinical variables, although higher levels of preoperative anxiety were associated with greater analgesic use (p = 0.041).
Conclusions: PSS positively influences adherence and emotional well-being, highlighting its relevance in comprehensive postoperative management. These findings support the integration of tailored psychosocial and educational strategies alongside surgical treatment.
Networked Predictive Trajectory Tracking Control for the Underactuated USV with Time-Varying Delays
Authors: Lei Tao , Wen Yuanqiao , Yu Yi , Zhang Minglong , Xiong Xin , Tian Kang
Published: December 2024

This paper investigates the trajectory tracking control problem of unmanned surface vessel (USV) with time-varying communication delays by taking advantage of the discrete-time sliding mode control approach and networked predictive control strategy. To address the aforementioned problem, a novel networked predictive control scheme based on a discrete-time sliding mode is proposed. Forward Euler discretization technology is applied to construct the discrete-time model of the USV. Then, a virtual velocity controller is developed to convert the trajectory tracking into virtual velocity tracking which can be achieved by utilizing a sliding mode control. Subsequently, a networked predictive control technique is performed to make the compensation for time-varying delays. Finally, theoretical analysis and extensive comparative simulation tests demonstrate that the proposed control scheme guarantees complete compensation for time-varying delays while ensuring the stability of the closed-loop system.
Mechanical Properties of 7075-T6 Aluminum Alloy in Electrically-Assisted Forming
Authors: Dou Shasha , Liu Zhuang , Li Zhijun , Zhu Chunyu , Shi Haojie , Zhou Kang , Xia Jiansheng
Published: December 2024

The coupling effects of electrical pulse, temperature, strain rate, and strain on the flow behavior and plasticity of 7075-T6 aluminum alloy were investigated and character-ized. The isothermal tensile test and electrically-assisted isothermal tensile test were performed at the same temperature, and the typical models were further embedded in ABAQUS for numerical simulation to illustrate the electroplastic effect. The results showed that electrical pulses reduced deformation resistance but greatly increased elongation. Compared with the traditional Johnson-Cook model, the proposed modi-fied Electrothermal coupling constitutive equations has a certain improvement in cal-ibration accuracy for highly nonlinear and thermoelectric coupling dynamic behavior. Moreover, Combined with the electrically assisted three-point bending experiment, it was found that the rebound angle decreases with the increase of current density. This is very close to the experimental result, further verifying the effectiveness of the ther-moelectric coupling constitutive equation.
Age-specific Mortality Forecasting In Kazakhstan. Modeling Applying Experience
Authors: Koichubekov Berik , Omarkulov Bauyrzhan , Mukhanova Meruert , Zakirova Rimma
Published: December 2024

This study aimed to summarize the results of using the Lee-Carter model and its extensions to predict mortality in Kazakhstan for ten years up to 2033. We analyzed Kazakhstan's age-specific mortality rates, observed annually from 1991 to 2023. Different mortality models were used to predict mortality. Among them Lee-Carter model, Hyndman-Ullah method with regression of scores on exogenous factors, time series analysis methods. The Lee-Carter model and its extensions did not give satisfactory results for predicting mortality in the testing timeframe. Including external socio-economic factors in the model did not improve forecasting accuracy. The accuracy of the forecast increased with a separate analysis of the subpopulations of children and adults. This was because since 1991 in the children subpopulation there has been a pronounced linear downward trend, while in the adult subpopulation, the global trend in mortality dynamics is nonlinear. As a result, it is possible to make forecasts for 7 years with a high degree of accuracy (error <10%) and forecast for the 8th, 9th, and 10th years with a "good" degree of accuracy (error 10-20%). In 2024-2033, a further mortality decline is expected in most age groups. Only in groups over 80 years old is a slight increase in mortality predicted in the coming year, but then a downward trend will be observed again
Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions
Authors: Korolis John S. , Bourdalos Dimitrios M. , Sakellariou John S.
Published: December 2024

Floating wind turbines (FWTs) operate in offshore environments under harsh and varying operating conditions, making frequent in situ monitoring dangerous for the maintenance teams and costly for operators. The remote and automated diagnosis including the stages of detection, identification and severity characterization of early-stage damages in FWTs through advanced vibration-based SHM methods of Machine Learning (ML) type is evidently critical for timely repairs extending their operational lifecycle, reducing maintenance costs, and enhancing safety. This study investigates for the first time the complete (all stages) diagnosis problem by employing well-established ML SHM methods and conducting hundreds of experiments on a lab-scale FWT model operating under different wind speeds and directions, both in healthy and damaged states. The latter include two distinct blade cracks of limited-length, two added masses on the blade edge simulating potential ice accumulation and connection degradation at the mounting of the main tower with the floater. The results indicate that the proper training of advanced ML methods using damage-sensitive feature vectors that represent the structural dynamics within the entire frequency bandwidth of measurements may achieve flawless damage diagnosis, reaching 100% success at all diagnosis stages, even when only minimal number of vibration signals from a limited number of sensors (a single sensor in this study) are used.
Integrated Strategy for Urban Traffic Optimization: Prediction, Adaptive Signal Control, and Distributed Communication via Messaging
Authors: Zrigui Ismail , Khoulji Samira , Kerkeb Mohamed Larbi
Published: December 2024

This work introduces an integrated approach to optimizing urban traffic by combining predictive modeling of vehicle flow, adaptive traffic signal control, and a modular integration architecture through distributed messaging. Using real-time data from various sensors, the system anticipates traffic fluctuations and dynamically adjusts signal phase durations to minimize delays and improve traffic flow. This proactive adjustment, supported by algorithms inspired by simulated annealing and reinforcement learning, also enhances energy efficiency, reduces pollutant emissions, and responds effectively to unexpected events (adverse weather, accidents, or temporary gatherings). Preliminary simulations conducted in a realistic urban environment demonstrate a significant reduction in average waiting times. Future developments include incorporating data from connected vehicles, integrating new modes of transport, and continuously refining predictive models to address the growing challenges of urban mobility.
Effectiveness of Self-Learning Module Developed on the Enhancement of Student’ Academic Performance in Basic Calculus Amidst COVID-19
Authors: Malgapo Cherry Rose
Published: December 2024

Self-learning Modules plays a vital role in the development of student progress wherein the necessary knowledge, theory, concept and formulas where written and explained. The researcher aimed to the determine the effectiveness of personally developed self-learning module on the enhancement of students’ academic performance in accordance to the compliance standards by the Department of Education on guidelines in the evaluation of layout and design of DepEd-developed ADM modules. The researcher used the descriptive and experimental type of research to collect and analyze data using one-shot pre-test and post-test in two groups of student-participants - control and experimental. The participants were purposively selected and group using matching technique based on their previous grade in Pre-Calculus. With regards to the findings of the study, the pretest scores of the two groups of student-participants in Basic Calculus were evidently shows almost the same. Whereas, the posttest scores revealed that the average posttest weighted mean scores of three sets of posttests on the same competencies, experimental group have an outstanding performance while controlled group have performed very satisfactory. The findings imply that those in experimental group were improved their posttest scores compare to those in controlled group. The findings concluded that the used of developed self-learning module in Basic Calculus helped student-participants in experimental group to have a better improved academic performance.
AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision
Authors: Albayati Nubul , Talluri Sesha Rajeswari , Dholaria Nirali , Michniak-Kohn Bozena
Published: December 2024

Transdermal drug delivery systems (TDDS) offer an alternative to conventional oral and injectable drug administration by bypassing the gastrointestinal tract and liver metabolism, improving bioavailability, and minimizing systemic side effects. However, widespread adoption of TDDS is limited by challenges such as the skin's permeability barrier, particularly the stratum corneum, and the need for optimized formulations. Factors like skin type, hydration levels, and age further complicate the development of universally effective solutions.
Advances in artificial intelligence (AI) address these challenges through predictive modeling and personalized medicine approaches. Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. Personalized TDDS design tailors drug delivery to individual patient profiles, enhancing therapeutic precision.
Innovative systems, such as sensor-integrated patches, dynamically adjust drug release based on real-time feedback, ensuring optimal outcomes. AI also streamlines the pharmaceutical process, from disease diagnosis to the prediction of drug distribution in skin layers, enabling efficient formulation development. This review highlights AI's transformative role in TDDS, including applications of models such as Deep Neural Networks (DNN), Artificial Neural Networks (ANN), BioSIM, COMSOL, K-Nearest Neighbors (KNN), and Set Covering Machine (SVM). These technologies revolutionize TDDS for both skin and non-skin diseases, demonstrating AI's potential to overcome existing barriers and improve patient care through innovative drug delivery solutions.
Machine Learning Discoveries of WLS-X Synergy in ETC-1922159 Treated Colorectal Cancer Cells
Authors: Sinha Shriprakash
Published: December 2024

Wntless (WLS) is a receptor required for WNT secretion. WLS is a cargo for the retromer complex. In the absence of retromer, WLS is degraded in lysosomes and the WNT secretion is impaired. In colorectal cancer (CRC) cells treated with ETC-1922159, WLS was found to be up regulated along with other genes. A recently de- veloped search engine ranked combinations of WLS-X (X, a particular gene/protein) at 2nd order level after drug administration. Some combinations have been experimen- tally validated, while many remain untested/unexplored. These rankings reveal which WLS-X combinations might be working synergistically in CRC. In this research work, I cover combinations of WLS with WNT, prolactin regulatory element-binding protein (SEC12), member RAS oncogene family (RAB), vacuolar protein sorting protein, a component of the retromer complex (VPS), sorting nexin (SNX), ADP ribosylation factors (ARF), ubiquitin conjugating enzyme E2 (UBE2), ATPases and transmembrane protein (TMEM) family.
Emotional Intelligence and Work Life Balance: A Case Study of Higher Education Department of Jammu and Kashmir
Authors: Yousuf Aabid , Mir Aasim
Published: December 2024

This study explores the relationship between emotional intelligence (EI) and work-life balance (WLB) among the teaching faculty of the Higher Education Department in Jammu and Kashmir (J&K). The higher education sector in J&K is crucial for the region’s development, and the study aims to assess the impact of emotional intelligence on faculty members' ability to manage their professional and personal lives. A quantitative approach was used, with data collected through structured questionnaires distributed to faculty members in government degree colleges across the region. The results indicate that higher emotional intelligence positively correlates with better work-life balance. Key components of EI such as self-awareness and social-awareness are particularly influential, while work-life balance is significantly impacted by factors such as working conditions, job enrichment, and grievance handling. The study concludes that emotional intelligence plays a vital role in enhancing work-life balance for faculty members in J&K, highlighting the need for targeted interventions to improve emotional management and institutional policies supporting work-life balance.
Exploring Proso Millet Resilience to Abiotic Stresses: High-Yield Potential in Desert Environments of the Middle East
Authors: Samineni Srinivasan , Gummadi Sridhar , Thushar Sumitha , Khan Dil Nawaz , Gkanogiannis Anestis , Becerra Luis Augusto , Singh Rakesh Kumar
Published: December 2024

Scarce water resources, high temperatures, limited rainfall, elevated soil salinity, and poor soil quality (98% sand) challenge crop production in the desert regions of the Middle East. Proso millet’s resilience under these stresses presents a potential solution for enhancing food security in arid environments. This study evaluated 24 proso millet genotypes across three stress conditions (100% freshwater, 50% freshwater, and 10 dS/m salinity) in the UAE during normal and summer seasons, aiming to identify genotypes resilient to water, heat, and salinity stresses and to assess genotype-by-environment (G×E) interactions and key traits associated with grain yield. ANOVA indicated significant G×E interactions. Genotypes G9 and G24 displayed high yield and stability across environments during the normal season. In summer, genotypes G7 and G10 exhibited resilience with high yields under high-temperature stress alone, while combined stresses led to yield reductions across all genotypes, with greater susceptibility under cumulative stress. GGE biplot analysis identified G9 as ideal in the normal season, while G15 and G23 demonstrated stability under combined stresses in the summer season. High chaffy grain yield (CGY) observed under summer stress conditions suggests a shift in resource allocation away from productive grain formation. The reproductive phase was highly vulnerable to heat stress, with 88% of this period experiencing daytime temperatures exceeding 40°C, with a peak reaching up to 49°C. These extreme conditions, coinciding with the crop's critical growth stages, triggered a significant increase in chaffy grain production, substantially reducing overall grain yield. Despite these challenges, genotypes G7, G10, and G12 exhibited notable resilience, maintaining yields above 0.75 t ha⁻¹. Correlation analysis suggested that selecting for increased plant height, forage yield, and 1000-grain weight (TGW) could enhance grain yield under normal and summer conditions. This study highlights the potential of proso millet genotypes as climate-resilient options for arid regions, providing a basis for developing stress-tolerant varieties and promoting sustainable agriculture in desert climates.
ECG-Based Fatigue Detection in Elderly Individuals Using Machine Learning Models
Authors: Baccouch Chokri , Bahar Chaima
Published: December 2024

Fatigue detection in elderly individuals is critical for preventing health complications and enhancing quality of life. This study presents a comprehensive approach to monitoring and classifying fatigue states using electrocardiogram (ECG) signals, leveraging advanced machine learning techniques. The proposed methodology involves five key stages: ECG signal acquisition, preprocessing, feature extraction, dimensionality reduction using Principal Component Analysis (PCA), and classification through recurrent neural network models. Among the evaluated models, the Gated Recurrent Unit (GRU), the Long Short-Term Memory (LSTM) model, and the standard Recurrent Neural Network (RNN) model exhibited the performance, of 98.86%, 97.73%, and 82.76%. respectivily. The results underscore the GRU model’s superior ability to classify fatigue states accurately, highlighting its potential for real-time applications in elderly care. This study emphasizes the importance of robust signal processing and advanced neural architectures in developing efficient fatigue detection systems, paving the way for improved health monitoring solutions for aging populations.
STATIC ANALYSIS OF SPINDLE SHAFTS ON NONLINEAR ELASTIC SUPPORTS OF INTERRELATED STIFFNESSES
Authors: Khavin Valerij , Khavin Evgen , Kyrkach Borys
Published: December 2024

The spindle assembly of a metal cutting machine determines the accuracy and productivity of metalworking. The stiffness of the spindle assembly is estimated by the elastic movements of the spindle shaft under the influence of the working load. Correct modeling of bearing stiffness is necessary for obtaining reliable results during spindle stiffness analysis. An approach is proposed for the static analysis of spindle shafts, in which the elastic behavior of the supports is determined by matrices of interconnected stiffnesses. A stiffness matrix was introduced, which links the radial deformations of the bearing in two mutually perpendicular directions as well as the longitudinal deformation with the corresponding forces. Iterative formation of the coefficients of this matrix is carried out by the Newton-Raphson method based on the values of forces and deformations in the supports. To solve the problem of analysis in matrix form, a system of equations was obtained, the non-linearity of which is formed by the dependence of the stiffness matrices of the bearings on the forces. A universal computer program for the static analysis of spindle shafts, in which the elastic behavior of the supports is specified by matrices of interconnected stiffnesses, has been created using the MatLAB software. The static analysis of a spindle shaft on radial/thrust bearings was considered. A comparison was made with the results for separate bending in two perpendicular planes when calculating the radial stiffness of the bearings according to the Jones-Harris model.
STUDY OF THE MECHANISM OF EDGE ROUNDING OF HARD-ALLOY MODULAR AND NON-MODULAR WORM CUTTERS DURING GEAR MACHINING
Authors: Hasanov Magomedemin Isamagomedovich , Ohrimenko Oleksandr , Klochko Oleksandr , Permyakov Egor , Hubskyi Serhii , Starchenko Vitaly , Tymoshenko Bohdan
Published: December 2024

The scientific foundations of research into the processes of rounding the edges of carbide tools during gear cutting are based on the key principles of wear theory, cutting mechanics and tribology. The formation of predicted roundings with a radius of 20–200 μm depends on cutting modes and processing conditions. The reduction of microchips on the edges and the optimization of the geometry of the cutting elements make it possible to increase the strength and wear resistance of the tools. In the initial stage of vibroabrasive processing, macrobrittle destruction of the edges with nonlinear kinetics prevails - the separation of rubble grains comparable to the rounding radius, in the final stage - microbrittle with linear - the separation of single grains comparable to the height of the irregularities. The moment of transition is determined by the amount of rounding, which is critical for macrostrength. The advantage of the exponential model obtained by solving the differential equation for describing the dependence of the rounding radius on the initial radius, the sharpening angle and the duration of processing is shown  for various combinations of fillers and machined hard alloys. The kinetics of other microgeometric parameters is described by the same model, but with a finite damping instead of a linear cross section.
THEORETICAL ANALYSIS OF THE REGULATIONS OF FORMATION OF THE ROUGHNESS OF THE TREATED SURFACE DURING GRINDING AND ABRASIVE POLISHING
Authors: Novikov Fedir Vasilivyth
Published: December 2024

Mathematical models for determining the roughness parameters of the treated surface during grinding with diamond wheels with cutting grains located at the same height and represented, respectively, in the form of cones (pointed grains), truncated cones (related to the wear of diamond grains) and spheres have been developed. It was established by calculations that in the first case the ratio of surface roughness parameters =4. In the second case, as the wear of diamond grains increases, the surface roughness parameter  decreases, and the  ratio can significantly exceed the value of =4. This corresponds to experimental data, according to which the ratio  during grinding can vary within 4 ... 11, and during abrasive polishing it can reach a value of 30 or more, which is associated with a significant number of grains that participate in the formation of surface roughness. Even larger values of  and, accordingly, smaller values of the parameter  were achieved in the third case. From a physical point of view, this is related to a decrease in the known ratio  (thickness of the cut to the radius of the grain) as a result of the transition from the cutting process to the process of elastic-plastic deformation of the processed material, since . Therefore, it is possible to significantly reduce the height parameters of the surface roughness during grinding and abrasive polishing by increasing the number of grains (in the form of a sphere), which participate in the formation of surface roughness, and their equal height location on the working surface of the abrasive tool.