bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study on Characteristics of Semi-Natural Hatchery Habitat for Olive Ridley Sea Turtle Lepidochelys olivacea (Eschscholtz, 1829) Conservation: A Case Study of Batu Hiu Beach, Pangandaran, West Java, Indonesia
Authors: Faddilah Thallita Nasywa , Hasan Zahidah , Arief Mochamad Candra Wirawan , Herawati Titin
Published: January 2025

Sea turtle populations have declined due to habitat destruction and the widespread collection of eggs for commercial purposes. This study assessed the characteristics and suitability of semi-natural hatchery habitats for Olive Ridley Sea Turtles (Lepidochelys olivacea) at Batu Hiu Beach, Pangandaran, West Java, Indonesia, from June 1-July 31, 2023. The survey method and purposive sampling were employed to determine nesting sites based on turtle landing points.Biophysical habitat measurements were analyzed descriptively and statistically using one-way ANOVA and Tukey's post hoc test to compare sand temperature, sand humidity, and air humidity. An L. olivacea landed at site 4, laying 73 eggs in a natural nest with 34 cm nest depth and 24 cm nest diameter. Semi-natural nests measured 37 cm nest depth and 26 cm in nest diameter. The sand type at Batu Hiu Beach was characterized by black sand grains and fine sand substrate with a percentage of 51.02%. The temperature within the hatchery ranged from 25.3°C to 42.1°C.  with average of 29.7 ± 1.88 °C.The sand humidity in the hatchery ranged from 2% to 14%, with an average daily humidity of 10 ± 0.22 %. The air humidity within the hatchery ranged from 56% to 94%, with a daily average of 85 ± 0.05 %. Based on all the analyzed parameters, the hatchery at Batu Hiu Sea Turtle Preservation were suitable with the nest criteria by Technical Guidelines for Sea Turtle Conservation Management by DKP for the hatching of L. olivacea eggs, with a hatching success rate of 85%.Keywords: Lepidochelys olivacea, temperature, humidity, sand type, hatching success
Effectiveness Probiotic of Nitrosomonas sp. and Bacillus sp. in Improving the Water Quality and Growth of Tilapia Larasati (Oreochromis niloticus)
Authors: Sya’bana Izzatin Nashiroh , Amalia Rosa , Harwanto Dicky
Published: January 2025

Water quality is the main factor that has a major influence on the growth and survival of Tilapia Larasati (Oreochromis niloticus). Nitrosomonas sp. and Bacillus sp. can optimize water quality through nitrification and denitrification processes and optimize feed utilization. This study aims to determine the effectiveness of using probiotic Nitrosomonas sp. and Bacillus sp. in O. niloticus maintenance media in improving water quality and growth. The method used was CRD with 4 treatments and 3 replications, namely treatment A (without probiotic), B (probiotic 1.0 µL/L), C (probiotic 1.5 µL/L), and D (probiotic 2.0 µL/L). This study used an aquarium measuring 40 x 30 x 40 cm filled with 20 liters of fresh water, and filled with 10 fish weighing 6.97 ± 0.20 g each (density of 1 fish/2 liters). Molasses as feed bacteria and probiotics were given according to the treatment dose. Siphon was accomplished twice a week according to the level of turbidity. Water changes once a week as much as 50 - 60%. The results from the study showed that the use of probiotics had a significant effect (P<0,05) in improving water quality and fish growth. The best result observed from treatment C, with the reduce ammonia and nitrite (0.002 and 1.291 mg/L), highest fish growth, specific growth rate, and survival rates (14.63±0.24 g; 2.48±0.01%/day; and 97±0,06%, respectively), and also lowest feed conversion ratio (1.07±0.02). Based on these results, the best dose for improving water quality and growth of O. niloticus is 1.5 µL/L.Key words: aquaculture, bioflock, organic matter, sludge, waste
Analyzing the Use of E-Voting Indonesian Election In 2024
Authors: Indrawan Jerry , Suprayitno Dede
Published: January 2025

The implementation of general elections in Indonesia poses various challenges, due to the form of an archipelagic country. The aspect of the region with its isolated, lagging, and remote character makes the election process require large resources, ranging from manpower, time and costs. To overcome this, the e-voting option emerged as an alternative to answer these challenges. The development of increasingly better technology makes the implementation of e-voting not impossible. The background of this study is based on the proposal to make elections in Indonesia less expensive. The purpose of the study is to determine whether the use of e-voting is suitable for implementation in Indonesia. The research method uses qualitative with research sources derived from primary and secondary data. The main result of this study is that e-voting can be considered for use in future elections. The author's conclusion is that e-voting is very possible to be implemented in Indonesia. However, the government needs to answer a number of needs. Among others, such as network infrastructure, data security, and readiness of human resources to remote areas.
De-growth: A Practical Path to Just Sustainability
Authors: Nuryananda Praja Firdaus , Rudiany Novita Putri , Hamdan Arva Rizqullah , Zein Isynariyah , Bilqis Thufailah Nafiisah
Published: January 2025

There are challenges and contradictions presented by the green economy, and its derivative, namely green growth, including the phenomenon of greenwashing and the sustainability paradox. The green economy has the potential to cause technological determinism in sustainable development. This article attempts to reintroduce and amplify the idea of ​​de-growth, which was once a manifestation of post-pandemic recovery in 2020 as a form of economic re-orientation towards sustainable development. This article, written with a qualitative approach and literature study instruments, also portrays de-growth globally and in Indonesia, especially for the tourism sector with examples in Raja Ampat and Nusa Penida. We can examine the application of de-growth as an economic principle in Raja Ampat and Nusa Penida through restrictions on the number of tourists, zoning areas, and the involvement of existing local communities.
Drainless Technology for Processing Highly Moist Iron-Containing Sludge and Dust
Authors: Ibraev I.K. , Bludova D.I. , Ibraeva O.T. , Aitkenov N.B.
Published: January 2025

A drainless energy-saving technology for processing highly moist iron-containing sludge from metallurgical production has been developed. The patterns of the combined process of chemical dewatering of highly moist iron-containing sludge with pulverized lime and dolomite wastes, hardening and caking by pressing in a single technological cycle at the developed experimental facility are investigated. In the course of laboratory studies, the temperature of the mass, rate of dehydration, chemical composition of the mixtures, appearance of the resulting briquettes, weight loss during caking, moisture content of the mixtures, and mechanical strength of the briquettes were monitored. New patterns have been established that have made it possible to develop an annealing-free method for producing iron-containing materials and self-healing briquettes. The essence of this method, which is one of the main provisions of scientific novelty, combines the processes of dehydration self-curing of the mixture with the process of forming by applying external pressure to the hardening mixture in molds to obtain a lumped material in the form of briquettes in a single technological cycle. The proposed technology does not require drying and firing, and a set of strength properties occurs as the material cools in the air during the day. A new energy-efficient and waste-free method for the production of iron-containing briquettes has been developed, combining the processes of chemical dehydration and condensation in one technological cycle. The proposed project and technology will make it possible to organize production for the processing of highly moist iron-containing sludge and the production of complex iron-containing material as a secondary metal-containing raw material for metallurgical plants for the production of steel and rolled metal. This technology will make it possible to fully utilize not only iron-containing sludge but also finely ground limestone and dolomite roasting waste (limestone and dolomite dust of dry gas purification) as dehydrating and binders, as well as screening coke and coal as reducing agents. The proposed technology also solves the problems of environmental pollution and the allocation of land for the storage of industrial waste.
Autophagy and Respiratory Viruses: Mechanisms of Viral Manipulation and Cellular Defense
Authors: Aligolighasemabadi Farnaz , Kiełbowski Kajetan , Bakinowska Estera , Sadeghdoust Mohammadamin , Coombs Kevin M. , Mehrbod Parvaneh , Ghavami Saeid
Published: January 2025

Respiratory viruses, such as influenza virus, rhinoviruses, coronaviruses, and respiratory syncytial virus (RSV), continue to impose a heavy global health burden. Despite existing vaccination programs, these infections remain leading causes of morbidity and mortality, especially among vulnerable populations like children, the elderly, and immunocompromised individuals. However, the current therapeutic options for respiratory viral infections are often limited to supportive care, underscoring the need for novel treatment strategies. Autophagy, particularly macroautophagy, has emerged as a fundamental cellular process in the host response to respiratory viral infections. This process not only supports cellular homeostasis by degrading damaged organelles and pathogens but also enables xenophagy, which selectively targets viral particles for degradation and enhances cellular defense. However, viruses have evolved mechanisms to manipulate the autophagy pathways, using them to evade immune detection and promote viral replication. This review examines the dual role of autophagy in viral manipulation and host defense, focusing on the complex interplay between respiratory viruses and autophagy-related pathways. By elucidating these mechanisms, we aim to highlight the therapeutic potential of targeting autophagy to enhance antiviral responses, offering promising directions for the development of effective treatments against respiratory viral infections.
Impact of Internet of Things (IOT) and Artificial Intelligence (AI) on National Development Through Science and Technology; A Systematic Review
Authors: Augustine Elozana Ezekwueme , Gloria, Adaku Dike
Published: January 2025

The rapid advancements in Internet of Things (IoT) and Artificial Intelligence (AI) over the past decade have significantly influenced national development through science and technology. This study synthesizes 40 literature from 2017 to 2024 to assess the impacts of IoT and AI on various national development aspects. This study critically evaluates the role of IoT and AI in driving national development, focusing on key developments and trends within this period. It also investigated how IoT and AI contribute to industrial innovation, economic growth, and sustainability from the synthesized literature, while also identifying key challenges and opportunities associated with their integration into national development strategies. Employing a systematic review of 40 recent literature from 2017 to 2024, the study focuses on peer-reviewed articles, conference papers, and industry reports. A comprehensive analysis is conducted to extract relevant data and insights using both qualitative and quantitative methods. Findings reveal that about 85% of articles reviewed show significant advancements in IoT and AI technologies, leading to improved industrial processes, enhanced economic growth, and increased sustainability. However, challenges such as data security, infrastructure limitations, and policy implications are also identified. In conclusion, this study highlights the transformative impact of IoT and AI on national development, providing strategic recommendations for policymakers and stakeholders, and underscores the need for robust frameworks to address challenges and leverage opportunities, aligning with sustainable development goals.
The Exhaustion Triangle: How Psychosocial Risks, Engagement, and Burnout Impact Workplace Well-Being
Authors: Lara-Moreno Raquel , Guzmán Nancy , Vázquez Pérez Mª Luisa , Ogallar-Blanco Adelaida Irene
Published: January 2025

Employee burnout levels have risen due to teleworking, increased job demands, and the lack of clear boundaries between personal and professional life. (1) Background: This study evaluated burnout levels, occupational health (through the presence or absence of psychosocial risk factors), engagement, and well-being/job satisfaction in a sample of employees aged over 18 from varying sociodemographic backgrounds. Additionally, we sought to explore the relationships among these variables and their influence on workplace well-being. (2) Methods: The sample comprised 112 employees aged 18 to 65 (of both genders). The instruments used included the Burnout Syndrome Scale, the DECORE multidimensional questionnaire, the UWES questionnaire, and the General Work Well-Being Questionnaire (qBLG). (3) Results: The results indicated that overall workplace well-being levels are high, while the presence of psychosocial risk factors and burnout levels are moderate to low. Most variables correlated with each other in the expected directions. Furthermore, job well-being was inversely predicted by cynicism and burnout and positively predicted by support, engagement, and control. (4) Conclusions: This study highlights the importance of workplace well-being and occupational health. Our findings suggest the need for intervention programs that include strategies to motivate employees, improve the work environment, and enhance stress coping mechanisms, among other areas.
Next-Gen Dental Therapies: Bridging Bioengineering with Pharmacological Science "Stem to Structure: Orchestrating Oral Renewal"
Authors: Alsuraifi Ali , A. Haji Sarah , Husam Yousef , R. Mohammed Noor Alhuda , Kareem Sarah , Mohammed Zainab , Ezzat Dina , Ayad Abdullah
Published: January 2025

Dental regeneration is undergoing a transformative shift through the fusion of bioengineering innovations and pharmacological science. Traditional therapies often fall short in fully restoring complex dental tissues, prompting exploration of novel regenerative strategies that address age-related changes and enhance clinical outcomes.Purpose: This review synthesizes current advancements in regenerative dentistry, focusing on how stem cells, biomaterials, growth factors, nanotechnology, and 3D bioprinting are revolutionizing dental tissue regeneration. It highlights the potential of these innovative approaches in overcoming the limitations of conventional therapies.Methods: An extensive analysis of recent studies and clinical trials was conducted, examining the roles of growth factors, platelet-rich plasma (PRP), platelet-rich fibrin (PRF), and stem cell-based therapies. The review emphasizes their biological properties, preparation methods, and applications in periodontal regeneration, bone grafting, and wound healing.Results: Integration of dental pulp stem cells with biomaterials and growth factors shows significant promise in restoring damaged tissues. Bioinspired materials and nanotechnology enhance the efficacy of regenerative therapies. Technologies like 3D bioprinting enable precise fabrication of complex tissue structures. Combining pharmacological agents with regenerative techniques offers tailored solutions for tissue regeneration.Conclusion: The convergence of bioengineering and pharmacological strategies marks a new era in dental regeneration, offering transformative approaches that address the limitations of traditional therapies and pave the way for personalized care. These advancements have the potential to revolutionize dental practice, leading to improved oral health outcomes and setting new standards in patient care.
Minimum Displacement in Existing Moment (MDEM)- A New Supervised Learning Algorithm by Incrementally Constructing the Moments of the Underlying Classes
Authors: Nizam Ahmed Mehedi
Published: January 2025

We propose a new supervised learning algorithm, where each data point in test set is included into the class into which such inclusion causes minimum displacement in the existing n-th central moment of the respective class under construction. After each such inclusion, the n-th central moment of the corresponding class is updated by some incremental calculations in constant time, i.e., each class evolves gradually and changes its definition incrementally after the inclusion of every new data point. We then use k-fold and stratified k-fold cross validation techniques to compare the performance of our proposed model with various state of the art supervised learning algorithms including Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbor (KNN) and Logistic Regression (LR) using Pima Indian Diabetes (PID) dataset, which is a popular dataset in machine learning research. Our analyses suggest that the performances of our proposed algorithms involving lower order moments are comparable to that of K-Nearest Neighbor (KNN) with a far better testing time complexity, while it is a bit under-performed as compared to Logistic Regression (LR), Support Vector Machine (SVM) and Random Forest (RF) in terms of accuracy. Our analyses also suggest that our proposed algorithms also outperform the Neural Network (NN) models with relatively lower number of nodes and layers. However, if we continue to increase nodes and layers in the Neural Network, it tends to outperform the proposed algorithm. In a nutshell, the performances of different MDEM algorithms as proposed here involving different order of moments vary within the range of [83.19%-95.82%] of the best algorithm under consideration in k-fold and stratified k-fold cross validation techniques.
Research on the Spatial Environment Design of Traditional Settlements of Ethnic Minorities in Tropical Rainforest
Authors: Liu Yaping , Huang Xuanrui , Feng ZiWei , Zhou Dequan
Published: January 2025

Traditional settlements in tropical rainforest regions exemplify harmonious coexistence between humans and nature through their ecological and cultural characteristics. The Li ethnic group settlements in Hainan, China, serve as a prominent example, where their architecture and lifestyle demonstrate a profound adaptation to the tropical rainforest ecosystem. Despite this, global research on traditional ethnic minority settlements in tropical rainforest regions has largely concentrated on natural conditions and distribution patterns, with insufficient attention paid to the design elements of spatial morphology. This study focuses on the Li settlements within Hainan Tropical Rainforest National Park, utilizing field surveys, literature analysis, and questionnaire studies to identify the key design elements of environmental spaces in these settlements. It further explores how the interaction between cultural and ecological factors influences the construction of settlement spaces. By doing so, the research aims to provide a valuable reference for the protection of traditional settlements in tropical rainforest regions globally and underscore the significant role of ethnic minority settlements in preserving cultural heritage and promoting ecological conservation.
The Great Tao Model: The Theory of Elementary Particles and Their Interactions
Authors: Zeng Jiqing , Zeng Tianhe
Published: January 2025

The origin of the universe has always been a philosophical question that humans have been curious about and tirelessly exploring since ancient times, and has now become a significant issue in modern scientific research. At present, the Standard Model and the Big Bang theory are the two mainstream theories related to this question. However, these two theories still have many serious defects and deficiencies, failing to thoroughly resolve this major scientific issue. Here, we propose the Yin-Yang Model of elementary particles and the Theory of Existence Fields for their interactions (collectively referred to as the "Great Tao Model"). The Yin-Yang Model categorizes elementary particles into charged and uncharged types, with charged elementary particles further divided into positively charged and negatively charged types, thereby determining that there are only three types of elementary particles: electrons, positrons, and subston (物子) particles. The Existence Field Theory holds that charge and mass are the fundamental physical quantities of elementary particles, and they have the inherent property of continuously and uniformly diffusing their physical information into the surrounding space. Elementary particles propagate their physical information through the existence field of fundamental physical quantities, and interact with each other by receiving physical information emitted by other elementary particles. Based on the Great Tao Model, we propose a series of new perspectives on the binding of elementary particles and the formation and evolution of the universe, uncovering many mysteries that have long plagued the physics community. The Great Tao Model may be the true "theory of everything" with significant scientific and philosophical implications.
Computational Identification of Specific Genes and Those Functions on the Gut Microbiota
Authors: Arita Kazuki , Nakano Yoshio , Kasai Satoka , Yoshizawa Kazumi , Miyazaki Satoru
Published: January 2025

The gut microbiota interacts with the brain via the intestines and is related to diseases such as depression. Metagenome analysis, which measures bacterial genes, is commonly used in the analysis of bacterial flora. However, only a small portion of bacterial genes have known functions, and most have unknown functions, so the information is insufficient with existing analysis methods. Therefore, we developed an analysis method that combines “16S rRNA amplicon analysis data” and “prediction information obtained by database search” to enable the analysis of genes with unknown functions. Using this method, we were able to add information to the gene of bacteria with unknown functions and show part of the mechanism by which intestinal bacteria affect mouse diseases. We applied this method to the intestinal flora of mice that show hyperalgesia due to ultrasound irradiation. M. scheadleri was found to be increased in the ultrasound-irradiation group (USV). Adapting the analysis method to the M. scheadleri genome, we were able to predict the function of proteins specifically produced by M. scheadleri. The specifically produced protein may have the function of Peptidase M23 in addition to the function related to the membrane obtained by the usual search.
The Culture War and Secularized Theological Concepts: A Voegelinian perspective
Authors: Batista Francisco
Published: January 2025

This article explores the dynamic interplay between theological and secular paradigms in shaping contemporary political movements and social justice discourse, with a particular focus on the Culture War surrounding reproductive rights and gender identity. It examines the historical transition from the Judeo-Christian tradition to modern secular frameworks, highlighting how core theological concepts—such as imago Dei, the sanctity of life, and divine sovereignty—have been reinterpreted and secularized. In the context of an increasingly secular world and the resurgence of religion in a post-secular society, the article leverages Eric Voegelin’s philosophical framework to deepen the dialogue on the Culture War and secularization. The analysis argues that modern social justice ideology can be seen as the "immanentization of the eschaton”, where transcendent values are reconfigured as temporal, political constructs for ultimate justice and redemption. By tracing modern concepts of social justice back to their theological roots, this article aims to enrich debates on secularization and the ideological divisions fueling the Culture War, fostering pathways toward a more cohesive and less polarized political landscape.
A Study of Machine Learning Model’s Performance for Load Forecasting Based on XAI Techniques
Authors: Dean Christopher M. , Ma Xuzhe , Ding Tong , Xu Ke , Chen Yujia , mo huadong
Published: January 2025

Accurate load forecasting is crucial for efficient management, planning, and operation of modern power systems, especially in an era of increasing electrical demand driven by technological advancements and environmental changes. This paper explores the development of hybrid Transformer-based models to improve load forecasting accuracy by capturing short-term fluctuations and long-term dependencies in energy demand. Three hybrid models were developed, the RNR-Transformer, the GRU-Transformer, and the LSTM-Transformer, and compared with traditional hybrid models such as LSTM-GRU and GRU-RNN. Transformer models outperformed standard RNN-based architectures, with an MSE of 0.0066 and a Symmetric Mean Absolute Percentage Error (sMAPE) of 15.09\%, highlighting its ability to predict energy demand with higher accuracy. Feature importance analysis, using Random Forest, Permutation Importance, and SHAP, highlighted temperature as the most influential variable affecting demand, followed by solar radiation and humidity. The implications of these findings are significant in this field, as hybrid models can enhance the adaptability of load forecasting. These can be implemented in different geographical regions and market conditions, improving energy management, reducing operational costs, and facilitating the integration of renewable energy sources into power grids.
A Design of Experiments Approach for Enhancing Room Temperature Stability of a Lyophilised and Paper-Based Bacterial Cell-Free System
Authors: Shivakumar Tejasvi , Clark Joshua , Goode Alice , Anyanwu Valentine E. , Williams Philip M.
Published: January 2025

Centralised cell-based biomanufacturing severely limits applicability in low-resource and extreme environments, where a largely untreated human population are present. Cell-free protein synthesis (CFPS) can surpass many of these limitations, due to its flexibility and low maintenance. After initial optimisation for high-level expression, we conceptualised CFPS platforms composed of lyophilised pellets and cellulose stacks for ease-of-storage and distribution. The latter platform consisted of lyophilised components on cellulose discs, which were layered and rehydrated to kickstart protein synthesis. Such paper-encompassed reactions were capable of robust expression, where the system can be modulated by simply changing the DNA layer. Using an initial screening design followed by a minimalistic design of experiments approach, we were able to improve the shelf-life of lyophilised CFPS at room temperature from < 1 week to 100% preservation at month 1. We anticipate that our strategy will enable quicker and more efficient stability optimisation for sustainable applications in all environments.
Exosomes in Precision Oncology: From Bench to Bedside in Diagnostics and Therapeutics
Authors: Youssef Emile , Palmer Dannelle , Fletcher Brandon , Vaughn Renee
Published: January 2025

Exosomes have emerged as pivotal players in precision oncology, offering innovative solutions to longstanding challenges such as metastasis, therapeutic resistance, and immune evasion. These nanoscale extracellular vesicles facilitate intercellular communication by transferring bioactive molecules that mirror the biological state of their parent cells, positioning them as transformative tools for cancer diagnostics and therapeutics. Recent advancements in exosome engineering, artificial intelligence (AI)-driven analytics, and isolation technologies are breaking barriers in scalability, reproducibility, and clinical application. Bioengineered exosomes are being leveraged for CRISPR-Cas9 delivery, while AI models are enhancing biomarker discovery and liquid biopsy accuracy. Despite these advancements, key obstacles such as heterogeneity in exosome populations and the lack of standardized isolation protocols persist. This review synthesizes pioneering research on exosome biology, molecular engineering, and clinical translation, emphasizing their dual roles as both mediators of tumor progression and tools for intervention. It also explores emerging areas, including microbiome-exosome interactions and the integration of machine learning in exosome-based precision medicine. By bridging innovation with translational strategies, this work charts a forward-looking path for integrating exosomes into next-generation cancer care, setting it apart as a comprehensive guide to overcoming clinical and technological hurdles in this rapidly evolving field.
Hemispheric Disconnection and Neurodegeneration: Cross-Disciplinary Approaches to Apraxias and Alzheimer’s
Authors: Sanna Marco
Published: January 2025

AbstractIntroduction: Alzheimer's is a neurodegenerative disease characterized by a progressive decline in cognitive and motor functions. This research proposes an innovative multimodal hypothesis. According to the hypothesis, the loss of emotionally engaging interests and goals in at-risk individuals leads to a reduction in conscious goal-oriented activities. Not only are enacted movements affected, but also those imagined during mental travels. Investigating these mechanisms can significantly accelerate research on apraxias and Alzheimer's. Method: A review of multidisciplinary literature on hemispheric connection and disconnection, proprioception, embodied cognition, motor language, and the syntax and semantics of gestural actions, among other topics, is employed to support the proposed hypothesis. From theoretical speculation, entirely new interpretations of motor-cognitive degenerations emerge. Discussion: Healthy connectivity between the dominant and contralateral hemispheres consists of a functional tension where data integration is complementary. The left hemisphere articulates already learned gestures into chains experienced as advantageous for achieving a goal, working towards maximum efficiency in goal-oriented action. In contrast, the right hemisphere provides a repertoire of gestural units with intrinsic meaning, independent of chains, to be used when execution on the left is interrupted or when more creative solutions are required. Conclusion: The lack of interhemispheric dialogue results in the atrophy of neural contacts capturing contralateral inputs, with progressive necrosis leading to the formation of amyloid plaques and advanced cerebral atrophy. The root cause of this lack of dialogue lies in the loss of value-driven motivations, particularly existential ones.
Machine Learning-Enhanced Mobility System Selection for Unmanned Ground Vehicles
Authors: Demir Cüneyd , Danışmaz Merdin
Published: January 2025

This study emphasizes the importance of accurately determining the mobility systems for unmanned ground vehicles (UGVs) to ensure optimal performance. The mobility system is crucial for reliable operation across various terrains and significantly affects energy efficiency, maneuverability, and load-carrying capacity. Choosing an unsuitable mobility system can hinder mission success and lead to costly design modifications. Therefore, selecting a system that meets mission requirements and user needs is vital for operational effectiveness. The research explores the complex interactions among UGV parameters and the challenges of designing a versatile mobility system. Unlike conventional design processes that prioritize mobility system selection early on, this study employs a novel machine learning approach. By analyzing feedback from five key questions, the most appropriate mobility system option was quickly identified. The performance of several classification algorithms was assessed, including Random Forest (98.7%), Naive Bayes (81.3%), Support Vector Machines (94.4%), and k-Nearest Neighbors (98%). Evaluation metrics such as precision, recall, and F1 scores revealed that the Random Forest model yielded the highest accuracy, achieving a success rate of 98.7%.
Computer Vision-Based Road Accident Classification from Traffic Surveillance
Authors: Chowdhury Shourav , Barua Subrata , Banik Shudipta , Naimuddin K.M. , Sajib Imam Hassan
Published: January 2025

Traffic accidents stand as a leading cause of fatalities worldwide, significantly impacting global mortality rates. Accurate classification of road accidents through advanced technological solutions presents a crucial opportunity to revolutionize accident prevention and emergency response strategies. This paper presents an advanced deep-learning methodology customized for the classification of road accidents using CCTV surveillance footage. This real-time dataset, comprising approximately 18,000 frames, has been amassed, which is pivotal for enabling comprehensive research in this field. This substantial dataset is the foundation for these investigative efforts, providing a rich and diverse source for conducting an in-depth analysis of the features. We have achieved a remarkable accuracy of 97\% on this dataset through the strategic utilization of transfer learning in conjunction with LSTM (Long Short-Term Memory) techniques. This accomplishment underscores the efficacy of our approach, combining the strengths of transfer learning and LSTM models, resulting in a highly accurate classification system for road accident events.
Assessment of Financing for Biodiversity Conservation in Mexico. Links between Biodiversity and Climate Change Adaptation Funds
Authors: Sosa Miriam , Ivanova Antonina
Published: January 2025

At COP16 in Cali, Colombia, significant progress was made in biodiversity conservation efforts, in this regard, financing has been considered a key issue for the achievement of the objectives. The over-view of Mexico’s experience with biodiversity finance in this study pre-sents the experience of an emerging economy, which must finance pressing development priorities and biodiversity and climate action at the same time. Therefore it is very important to find synergies in the available finance and look for new innovative options The large overlap between the climate and biodiversity agendas and the international commitments derived from these also presents an op-portunity to accelerate biodiversity funding. The methodology applied is the Systematic Literature Review (SLR) The study presents the na-tional strategy on biodiversity in Mexico (ENBioMex), the financial needs of the country, and the existing biodiversity financing, stressing of GEF, BIOFIN, and the Adaptation Fund in Mexico. The discussion section centers on analyzing the existing results and outlining some proposals to enhance the existing instruments, looking for innovation and synergies. In authors´ opinion, the financing of Ecosystem based Adaptation (EbA) is the main instrument that can link biodiversity con-servation and the adaptation to climate change impacts, at the same time providing a sustainable way of life and guaranteeing the well-be-ing of the communities but is not adequately used. Finally we present some concluding remarks and some future topics of research.
Smart Smiles in “Go Go Brush” App.: Technical and Clinical Insights into an Arabic Preschooler-Friendly Oral Hygiene Mobile App.
Authors: Barakat Farah , Elkalla Ibrahim , Salama Rabab , M. Elhady Abdelghafar , M. Elhady Mona , Shohieb Samaa M.
Published: January 2025

Background/Objectives: Oral hygiene is crucial to preventing dental caries. However, many preschool children fail to maintain proper oral hygiene practices due to a lack of assistance from parents and dentists because tooth brushing seems too lengthy and tedious. The goal of this article is to design a gamified mobile application called "GoGo Brush" that will appeal to Arab preschoolers and verify its effectiveness in enhancing their oral condition and their parents' knowledge. Methods: There were two groups: a study group of 122 children and parents, and a control group of 50 children. Parents in the study group filled in questionnaires, and all children received toothbrushes and education on oral hygiene. Plaque and gingival indices were measured. The study group was introduced to the GoGo Brush app and a video on plaque removal. The app's effectiveness was assessed over one week and one month. Changes in plaque and gingival status were noted. Researchers also conducted a usability evaluation of the app. Results: The app led to significant improvements in plaque and gingival indices after one month compared to the baseline and control groups. Plaque scores decreased from 2.41±0.28 to 0.695±0.25 (p
Placing Objects on Table Is Preferred over Direct Handovers When Users Are Occupied
Authors: Phan Thieu Long , Cosgun Akansel
Published: January 2025

Service robots commonly deliver objects through direct handovers, assuming users are fully attentive. However, in real-world scenarios, users are often occupied with other tasks. This paper investigates how user attentiveness affects preferences between direct handovers and placing objects on a table. A user study was conducted (n=15) to evaluate these strategies in scenarios where participants were either occupied (simulated via a typing task) or unoccupied. Results show that placing objects on the table significantly enhances user experience when users were occupied, with higher ratings for satisfaction, perceived safety, confidence in robot's ability and intuitiveness of interaction. While direct handovers performed better with unoccupied users compared to occupied users, table placement maintained consistently high performance regardless of user state. All participants preferred table placement when occupied, and the majority preferred it even when unoccupied. These findings suggest table placement should be the default object delivery strategy for service robots, particularly in environments where user attention may vary. We also discuss implications for robot design and propose future directions for adaptive delivery behaviors.
Analytical Representations of Heaviside and Ramp Function
Authors: Venetis John Constantine
Published: January 2025

In this paper, explicit exact forms of Heaviside Step Function and Ramp Function are presented. These significant functions constitute fundamental concepts of operational calculus and digital signal processing theory and are also involved in many other areas of applied sciences and engineering.
In particular, Heaviside and Ramp Function are performed as bi-parametric single - valued functions with only one restriction imposed on each parameter. The novelty of this work when compared to other investigations concerning exact forms of Unit Step Function and/or Ramp Function, is that the proposed analytical formulae are not exhibited in terms of miscellaneous special functions, e.g. Gamma Function, Biexponential Function or any other special functions such as Error Function, Complementary Error Function, Hyperbolic Function, Orthogonal polynomials etc.
Hence, these formulae may be much more practical, flexible and useful in the computational procedures which are inserted into operational calculus and digital signal processing techniques as well as other engineering practices.
Involvement of Oxidative Stress and Oxidants in Modification of Cardiac Dysfunction Due to Ischemia-Reperfusion Injury
Authors: Dhalla Naranjan S. , Ostadal Petr , Tappia Paramjit S.
Published: January 2025

Delayed reperfusion of the ischemic heart (I/R) is known to impair recovery of cardiac function and produce a wide variety of myocardial defects including ultrastructural damage, metabolic alterations, subcellular Ca2+-handling abnormalities, activation of proteases and changes in cardiac gene expression. Although I/R-injury has been reported to induce the formation of reactive oxygen species (ROS), inflammation and intracellular Ca2+-overload, generation of oxidative stress is considered to play a critical role in the development of cardiac dysfunction. There occurs an increase in the production of superoxide and hydroxyl radicals as well as oxidants such as hydrogen peroxide and hypochlorous acid in hearts subjected to I/R-injury. In fact, mitochondria are a major source of excessive production of ROS in I/R hearts due to impairment in the electron transport system as well as activation of xanthine oxidase, monoamine oxidase and NADPH oxidase. Nitric oxide synthase, mainly present in the endothelium, is also activated due to I/R injury to produce nitric oxide, which upon combination with superoxide radicals, generates nitrosative stress. Alterations in cardiac function, sarcolemma and sarcoplasmic reticulum Ca2+-handling activities, and mitochondrial oxidative phosphorylation as well as protease activation due to I/R-injury are simulated upon exposing the heart to oxyradical generating system (xanthine plus xanthine oxidase) or H2O2. On the other hand, the activation of endogenous antioxidants such as superoxide dismutase, catalase and glutathione peroxidase as well as the concentration of a transcription factor (Nrf2), which modulates the expression of various endogenous antioxidants, are depressed due to I/R injury in hearts. Furthermore, pretreatment of hearts with antioxidants such as catalase plus superoxide dismutase, N-acetylcysteine and mercaptopropionylglycerine was observed to attenuate the I/R-induced subcellular Ca2+-handling and changes in Ca2+-regulatory activities as well as depress protease activation and improve the recovery of cardiac function. These observations indicate that oxidative stress is intimately involved in the pathological effects of I/R-injury and different antioxidants attenuate I/R-induced subcellular alterations and improve the recovery of cardiac function. Thus, there is a challenge to develop safe and effective antioxidants as well as agents for upregulating the expression of endogenous antioxidants for the therapy of I/R-injury.
Designing a 3D and Virtual Reality Course: Integrating Technology and Creativity for Immersive Learning
Authors: Isaev Ruslan , Migranov Ruslan
Published: January 2025

The rapid advancement of 3D modeling and virtual reality (VR) technologies has created a demand for innovative educational approaches to equip students with the skills necessary for careers in these fields. This paper outlines the development of a comprehensive course in 3D design and VR, emphasizing the integration of foundational knowledge, practical skills, and immersive learning experiences. The course framework incorporates Bloom’s Taxonomy to structure learning outcomes, promoting critical thinking, creativity, and real-world application. Key methodologies such as experiential learning, project-based assessments, and regular feedback mechanisms are employed to ensure an engaging and effective learning environment. By using industry-standard software and providing access to VR technology, the course prepares students for the evolving demands of the 3D and VR industries.
South China Sea Sst Fronts, 2015–2022
Authors: Belkin Igor M , Zang Yi-Tao
Published: January 2025

Monthly climatology of thermal fronts in the South China Sea was derived from high-resolution (2 km) high-frequency (hourly) SST data of the Advanced Himawari Imager (AHI) onboard the Japanese Himawari-8 geostationary satellite. The Belkin and O’Reilly algorithm (BOA) was applied to SST data from 2015-2022 to generate maps of SST gradient magnitude GM, which were log-transformed to enhance contrasts in digital maps and reveal additional features (fronts). The combination of high-resolution cloud-free four-day-composite SST imagery from AHI, advanced front-preserving gradient algorithm BOA, and digital contrast enhancement with log-transformation of SST gradients allowed us to identify numerous mesoscale/submesoscale fronts (including a few fronts that have never been reported) and document their month-to-month variability and spatial variability on the submesoscale. Spatio-temporal variability of SST fronts was analyzed in detail in five regions: (1) In Taiwan Strait, six fronts were identified: China Coastal Front, Taiwan Bank Front, Northern/Eastern Changyun Ridge fronts, and Eastern/Western Penghu Islands fronts; (2) The Guangdong Shelf is dominated by the China Coastal Front in winter, with the eastern and western Guangdong fronts separated by the Pearl River outflow; (3) Hainan Island is surrounded with fronts formed by wind-induced coastal upwelling in the southeast; tides and topographic upwelling in the northeast; and tidal mixing and upwelling in the west, where fronts are steered by giant sand ridges; in the western Beibu Gulf, the Red River Outflow Front extends southward as the Vietnam Coastal Front, while the northern Beibu Gulf features a tidal mixing front off the Guangxi coast; (4) Off SE Vietnam, the 11°N coastal upwelling gives rise to a summertime front, while the Mekong Outflow and associated front extend seasonally toward Cape Camau, close to the Gulf of Thailand Entrance front; (5) In Luzon Strait, the Kuroshio front manifests as a chain of three submesoscale fronts across the Babuyan Islands, while west of Luzon Island a broad offshore frontal zone persists in winter. The summertime eastward jet (SEJ) off SE Vietnam is documented from five-day mean SST data. The SEJ emerges in June-September off the 11°N coastal upwelling center and extends up to 114°E. The zonally oriented SEJ was observed located between two large gyres, each about 300 km in diameter.
Beyond Data: How Simulation Can Empower LLMs to Revolutionize Science
Authors: Garbey Marc
Published: January 2025

We hypothesize that large language models (LLMs) can effectively generate 'thought experiments' that can be evaluated using virtual simulators. This approach has the potential to automate knowledge generation, accelerate scientific discovery, and provide a systematic method for training subsequent LLMs with verifiable and reproducible datasets. To illustrate this concept, we will use the clinical workflow optimization challenge as a case study.
Analysis of Methods for Intensifying Heat and Mass Transfer in Liquid Media
Authors: Pavlenko Anatoliy
Published: January 2025

In many technological processes, liquids or mixtures of mutually insoluble liquids, suspensions, emulsions, etc. are used as working media. The transformation of the energy supplied to such me-dia and the related effects can be usefully realised not only for the implementation of technological processes but also for their intensification. In this connection, an important task in increasing the efficiency of the use of the supplied energy is the analysis of the processes that take place in liquids or their mixtures at the level of thermodynamic saturation. In this work, it is shown that the crea-tion of thermodynamic conditions for local energy transformation in a disperse system signifi-cantly increases the intensity of heat and mass transfer processes, and in some technologies, e.g. homogenisation, dispersion can be increased by 2-3 times in comparison with traditional methods at the same energy consumption.
EXPLORING THE LANGUAGE AND REPRESENTATION OF ISLAMIC ETHICS IN THE SONGS OF SAMI YUSUF’S ALBUM SALAAM
Authors: Assyifa Putri Azzahra  , R. Myrna Nur Sakinah
Published: January 2025

This research explores the use of language and the representation of Islamic ethics in Sami Yusuf's songs contained in the album Salaam. Through a qualitative analytical approach, to provide an in-depth understanding of the use of language used in the lyrics of these songs, as well as the representation of Islamic ethics contained therein, such as love, patience, peace, contentment, and others, delivered through simple and powerful language. An analysis of the lyrics of songs such as “Happiness”, “Salaam”, “Forgotten Promises”, “Hear You Call”, “Smile”, “To Guide You Home”, “Dryer Land”, “All I Need”, “I'm Your Hope”, and “It's A Game” shows that Sami Yusuf uses simple, powerful yet universal language to convey moral and spiritual messages that can be accepted by a global audience. This research shows that the music in the album Salaam serves as a modern medium of da'wah, combining elements of popular culture with Islamic ethical values, thus allowing these messages to reach listeners from different cultural and religious backgrounds.