Hasil untuk "Military Science"

Mengli Yin, Haoyang Guo, Erhai An et al.

RDX/Al mixtures are widely utilized in energetic materials, yet their hybrid dust generated during production and application poses potential explosion hazards. Moreover, the synergistic explosion mechanisms remain poorly understood, particularly at varying dust concentrations. This study systematically investigates the effects of different aluminum powder mass percentages and dust concentrations (300 g/m3, 600 g/m3, 900 g/m3) on RDX dust explosion severity, flame propagation behavior, and gaseous products. The results indicate that the maximum explosion pressure peaks at 35% RDX, 65% RDX, and 80% RDX at 300 g/m3, 600 g/m3, and 900 g/m3, respectively. Concurrently, the time for the flame to propagate to the wall (t1) reaches minimum values of 34.8 ms, 25.66 ms, and 23.93 ms. The maximum rate of pressure rise is observed for pure RDX at 900 g/m3. Aluminum powder enhances flame propagation velocity and combustion duration, as validated by the flame propagation system. Overall, the concentrations of carbon oxides (CO+CO2) decrease significantly with increasing aluminum mass percentage. At 20% RDX, the concentrations decreased by 51.64%, 72.31%, and 79.55% compared to pure RDX at 300 g/m3, 600 g/m3, and 900 g/m3, respectively. Notably, N2O concentration only at 300 g/m3 showed such a trend. It rises first and then falls at 35% RDX at 600 g/m3 and 900 g/m3. These findings elucidate the synergistic explosion mechanisms and provide critical guidelines for safe production and handling.

Zachary T. Rewolinski, Bin Yu

Data science is a pillar of artificial intelligence (AI), which is transforming nearly every domain of human activity, from the social and physical sciences to engineering and medicine. While data-driven findings in AI offer unprecedented power to extract insights and guide decision-making, many are difficult or impossible to replicate. A key reason for this challenge is the uncertainty introduced by the many choices made throughout the data science life cycle (DSLC). Traditional statistical frameworks often fail to account for this uncertainty. The Predictability-Computability-Stability (PCS) framework for veridical (truthful) data science offers a principled approach to addressing this challenge throughout the DSLC. This paper presents an updated and streamlined PCS workflow, tailored for practitioners and enhanced with guided use of generative AI. We include a running example to display the PCS framework in action, and conduct a related case study which showcases the uncertainty in downstream predictions caused by judgment calls in the data cleaning stage.

Ryan Harries, Cornelia Lawson, Philip Shapira

This paper examines the impact of Generative Artificial Intelligence (GenAI) on scientific practices, conducting a qualitative review of selected literature to explore its applications, benefits, and challenges. The review draws on the OpenAlex publication database, using a Boolean search approach to identify scientific literature related to GenAI (including large language models and ChatGPT). Thirty-nine highly cited papers and commentaries are reviewed and qualitatively coded. Results are categorized by GenAI applications in science, scientific writing, medical practice, and education and training. The analysis finds that while there is a rapid adoption of GenAI in science and science practice, its long-term implications remain unclear, with ongoing uncertainties about its use and governance. The study provides early insights into GenAI's growing role in science and identifies questions for future research in this evolving field.

Athanase Papadopoulos

Vincenzo Galilei and Constantijn Huygens were both humanists and eminent musicians, the former from the late Renaissance and the latter from the early Modern era. Their respective sons, Galileo and Christiaan, were scientists whose importance cannot be overestimated. My aim in this chapter is to set the scene for a parallel presentation of the legacy of the Galilei on the one hand, and the Huygens on the other. This will give us an opportunity to talk about mathematics, music and acoustics, but also about science in general, at this time of birth of the Modern era.

Юрій ЮРЧАК

Проаналізовано унікальні методики протистояння військовополонених негативному інформаційно-психологічному впливу під час конфліктів, зокрема воєнних ситуацій. Визначено важливість та роль керування інформаційними аспектами у контексті ведення війни та перебування у полоні, забезпечення безпеки державного кордону та підвищення обороноздатності країни. Вивчено взаємозв’язок між інформаційним впливом і перебігом воєнних операцій. Окреслено стратегію підготовки майбутніх офіцерів прикордонної служби до протидії негативному інформаційно-психологічному впливу у полоні. Закцентовано на важливості психологічної стійкості та готовності до відсічі ворожій пропаганді під час воєнних конфліктів. У статті викладено історію інформаційної війни, психологічні та фізіологічні аспекти полону, а також фази, які проходить військовослужбовець у полоні. Установлено, що іноді цю інформацію подають із вираженням співчуття, що призводить до значного зниження оборонної готовності військовополонених. У додаток до цього погіршення мотивації та втрата смислового сприйняття серед військовополонених мають дуже негативні наслідки, включно із втратою інтересу до професійної діяльності, розчаруванням у вибраній сфері занять і іншими подібними аспектами. Надано практичні рекомендації для збереження морального духу та психологічного здоров’я у полоні.

Donghyun Kim, Jongwook Jeong, Soo-Hyun Lee et al.

Existing archive formats provide encryption to protect data, but vulnerabilities in these formats can lead to data leakage. This study proposes a novel attack to leak original data from encrypted archive files by exploiting the integrity check value and unencrypted metadata. The proposed attack obtains the size of the original data and the integrity check value by parsing the encrypted file, and identifies the original data by leveraging password-cracking techniques. Experiments with seven archive formats and seven utilities demonstrate the effectiveness of our proposed attack, successfully leaking data from 11 out of 20 encrypted files. This research uncovers vulnerabilities in existing archive formats and contributes to the design of more secure archiving systems.

М.Р. Арасланов, О.А. Малишев, В.Й. Климченко et al.

Пропонується в оглядових радіолокаційних станціях “старого парку” метрового діапазону хвиль замінити застарілу аналогову апаратуру черезперіодного віднімання на цифрову, що реалізується на готових процесорних модулях. Це дає можливість за незначних затрат і в мінімальні строки значно покращити технічні та експлуатаційні параметри системи селекції рухомих цілей РЛС, що забезпечить надійне виявлення та супроводження повітряних об’єктів на фоні земної поверхні. Наводиться алгоритм функціонування розробленої цифрової системи селекції рухомих цілей, де додатково здійснюється некогерентне накопичення обробленого сигналу для покращення виявлення малорозмірних цілей. Приводиться приклад реалізації такої системи і фотографії результатів її роботи в реальних військових умовах.

Yelu Hao, Yujie Niu, Fei Shi et al.

Early life stress (ELS) has been thought to increase vulnerability to developing psychiatric disorders later in life, while some researchers have found that adversity early in life may promote stress resilience. Studies investigating the resilient effect of maternal separation (MS) are still relatively few, and the underlying mechanisms remain unknown. In the current study, the effect of a single 24 h MS paradigm at postnatal day 9 (PND 9) in female C57BL/6J mice was investigated by assessing behavioral performance in middle adolescence. We demonstrated that, mice in MS group displayed decreased anxiety-like behavior and increased exploratory behavior than controls in the open field test and elevated plus maze test. Furthermore, MS mice exhibited improved hippocampal-dependent spatial learning in the Morris water maze test. This performance indicated behavioral resilience to early life stress. The protein expression levels of Homer1 isoforms, which are implicated in a variety of neuropsychiatric disorders, were evaluated using Western blot analysis. A significant increase in hippocampal Homer1a protein expression was observed immediately after MS, which subsequently decreased until adolescence (PND 27–42), when a significant increase was observed again. This distinctive change of hippocampal Homer1a protein expression pattern indicated that hippocampal Homer1a might play a role in behavioral resilience to MS in female C57BL/6J mice. In conclusion, this study demonstrated that exposure to a single 24 h MS at PND 9 promoted behavioral resilience of female C57BL/6J mice in middle adolescence. This behavioral resilience might be related to increased expression of hippocampal Homer1a.

Wang Shuangyu, Shen Qingmao, Sun Mingyang, Tang Shuang, Zhen Ziyang

The weapon-target assignment problem is the key to the combat mission of the UAV against the enemy in the battlefield environment. The purpose is to find a reasonable weapon target assignment scheme based on the threat, value and damage probability of the target, so as to improve the combat efficiency. Aiming at the problem that the current multi-objective optimization algorithm has slow convergence speed and poor convergence stability when solving the static weapon-target assignment problem, and it is difficult to adapt to the high real-time performance of the current battlefield, an improved non-dominated sorting genetic algorithm based on reference points is proposed. The initial population is optimized by binary coding attack scheme, and adaptive mutation and crossover strategy as well as population optimization update strategy is introduced. Based on the threat matrix and advantage matrix obtained by evaluating the battlefield situation, the target attack scheme is generated after multiple iterations of the population. Finally, the Pareto solution set satisfying the constraint condition is calculated, and the relative optimal solution in the Pareto frontier is taken as the attack scheme of multi-UAV. Multiple experiments show that under good conditions, the improved algorithm reduces convergence time by 46.74%, reduces target threat value by 50.5%, reduces total flight range by 26.46%, and increases the number of killing targets by 11.76% compared with the original algorithm. It is proved that the algorithm is reasonable and efficient in solving the problem of target assignment of multi-UAV air-to-ground strike mission.

Ziwei Dong, Ameya Patil, Yuichi Shoda et al.

Data science pipelines inform and influence many daily decisions, from what we buy to who we work for and even where we live. When designed incorrectly, these pipelines can easily propagate social inequity and harm. Traditional solutions are technical in nature; e.g., mitigating biased algorithms. In this vision paper, we introduce a novel lens for promoting responsible data science using theories of behavior change that emphasize not only technical solutions but also the behavioral responsibility of practitioners. By integrating behavior change theories from cognitive psychology with data science workflow knowledge and ethics guidelines, we present a new perspective on responsible data science. We present example data science interventions in machine learning and visual data analysis, contextualized in behavior change theories that could be implemented to interrupt and redirect potentially suboptimal or negligent practices while reinforcing ethically conscious behaviors. We conclude with a call to action to our community to explore this new research area of behavior change interventions for responsible data science.

Elenna Capote, Louis Dartez, Derek Davis

The next generation of ground-based gravitational-wave interferometers is expected to generate a bounty of new astrophysical discoveries, with sensitivities and bandwidths greatly improved compared to current-generation detectors. These detectors will allow us to make exceptional advancements in our understanding of fundamental physics, the dynamics of dense matter, and the cosmic history of compact objects. The fundamental design aspects of these planned interferometers will enable these new discoveries; however, challenges in technical noise, data quality, and calibration have the potential to limit the scientific reach of these instruments. In this work, we evaluate the requirements of these elements for next-generation gravitational-wave science, focusing on how these areas may impact the proposed Cosmic Explorer observatory. We highlight multiple aspects of these fields where additional research and development is required to ensure Cosmic Explorer reaches its full potential.

Peter Fettke, Wolfgang Reisig

Process science is a highly interdisciplinary field of research. Despite numerous proposals, process science lacks an adequate understanding of the core concepts of the field, including notions such as process, event, and system. A more systematic framework to cope with process science is mandatory. We suggest such a framework using an example. The framework itself addresses three aspects: architecture, statics, and dynamics. Corresponding formal concepts, based on established scientific theories, together provide an integrated framework for understanding processes in the world. We argue that our foundations have positive implications not only for theoretical research, but also for empirical research, e.g., because hypothesized relationships can be explicitly tested. It is now time to start a discussion about the foundations of our field.

Edafetanure-Ibeh Faith, Evah Patrick Tamarauefiye, Mark Uwuoruya Uyi

The aim of attending an educational institution is learning, which in turn is sought after for the reason of independence of thoughts, ideologies as well as physical and material independence. This physical and material independence is gotten from working in the industry, that is, being a part of the independent working population of the country. There needs to be a way by which students upon graduation can easily adapt to the real world with necessary skills and knowledge required. This problem has been a challenge in some computer science departments, which after effects known after the student begins to work in an industry. The objectives of this project include: Designing a web based chat application for the industry and computer science department, Develop a web based chat application for the industry and computer science and Evaluate the web based chat application for the industry and computer science department. Waterfall system development lifecycle is used in establishing a system project plan, because it gives an overall list of processes and sub-processes required in developing a system. The descriptive research method applied in this project is documentary analysis of previous articles. The result of the project is the design, software a web-based chat application that aids communication between the industry and the computer science department and the evaluation of the system. The application is able to store this information which can be decided to be used later. Awareness of the software to companies and universities, implementation of the suggestions made by the industry in the computer science curriculum, use of this software in universities across Nigeria and use of this not just in the computer science field but in other field of study

Henry Torres-Vásquez, Misael Tirado-Acero

El tratamiento penal de los menores que trasgreden la ley penal es un tema de recurrente preocupación, ante el aumento de la criminalidad. Se exige justicia sin importar si se vulneran derechos fundamentales de los menores de edad. Este artículo estudia el Sistema de Responsabilidad Penal Adolescente de Colombia, las sanciones que contempla, su enfoque de justicia restaurativa, aunque enmarcado dentro del derecho penal. Este sistema considera la sanción privativa de la libertad como último recurso de uso excepcional, pero este principio no se aplica plenamente. A la vez, hay presión por aumentar penas que puede vulnerar el interés superior del menor. Se concluye que es fundamental reforzar la aplicación de la justicia restaurativa para cumplir con los propósitos de prevención, reparación y reintegración social del menor.

Tianqi Yang, Yang He, Lin Wu et al.

Background: Suicide is a worldwide public health problem. Evidence from previous studies has confirmed the relationship among anxiety, depression and suicidal ideation. However, the complex psychopathological pathways between anxiety and suicidal ideation and between depression and suicidal ideation require further study. Methods: A total of 505 college students from China during COVID-19 pandemic were investigated in an online study. Anxiety, depression and suicidal ideation of the participants were investigated. R software was used to construct the anxiety-suicidal ideation and depression-suicidal ideation networks and to evaluate the bridge expected influences. Results: The anxiety-suicidal ideation network had 28 cross-community edges, the strongest one was A7 “Afraid something will happen”–S7 “Unable to solve personal problem”; A5 “Restlessness” and S3 “Hopelessness and suicide thoughts” had the highest bridge expected influences. The depression-suicidal ideation network had 36 cross-community edges, and the strongest one was D9 “Thoughts of death”–S5 “Unable to accomplish something important”; D9 “Thoughts of death” and S3 “Hopelessness and suicide thoughts” had the highest bridge expected influences. Conclusion: Intricate psychopathological pathways exist between anxiety and suicidal ideation and between depression and suicidal ideation. “Restlessness”, “Thoughts of death” and “Hopelessness and suicide thoughts” are considered targets for suicidal ideation interventions. The present study enriches the theory of symptoms and mental disorders and provides a reliable reference for the intervention practice of suicidal ideation.

Yu-Xu Guo, Feng Xi, Ying-Hua Tan et al.

Based on the background of structural protection and Disaster Reduction Engineering, the dynamic behaviour and failure mechanism of restrained beams in portal steel frames in localised fire are investigated via experimental measurement and numerical simulation techniques. Comprehensive parametric studies are carried out to discuss the influence of end connection types, temperature, impact velocity, impact mass and span-to-depth ratio (SDR) on the dynamic response of the beams. The characteristics of deformation, internal force and energy distribution about the restrained beams and its joints are investigated. A temperature dependent criterion for evaluating the frame joint performance is proposed to measure the degree of performance degradation and impact resistance of the joint. The dynamic displacement amplification factor in different temperature environments are proposed for the different beam end constraint types and SDRs. Results of the experimental and numerical analysis show that the welded connection (WC) of three typical joint types is the strongest, and the extended endplate connection (EEC) is the weakest in terms of the impact resistance performance. With regard to the failure mode of the joint, the failure positions of the WC and the welded-bolted connection are located in the inner web of the column. Meanwhile, the EEC is located in the connection position between the beam and the endplate. Three different internal force stages and two obvious critical temperature boundaries of the restrained beams emerge with the increase in temperature, and they have significant characteristics in terms of deformation trend, internal force transfer and energy distribution. During the impact, a phenomenon known as “compression arch action” develops into “catenary action” with the increase in deflection in the frame beam mechanism.

Mahender Kumar, Ruby Rani, Mirko Botarelli et al.

Ontologies play a critical role in Semantic Web technologies by providing a structured and standardized way to represent knowledge and enabling machines to understand the meaning of data. Several taxonomies and ontologies have been generated, but individuals target one domain, and only some of those have been found expensive in time and manual effort. Also, they need more coverage of unconventional topics representing a more holistic and comprehensive view of the knowledge landscape and interdisciplinary collaborations. Thus, there needs to be an ontology covering Science and Technology and facilitate multidisciplinary research by connecting topics from different fields and domains that may be related or have commonalities. To address these issues, we present an automatic Science and Technology Ontology (S&TO) that covers unconventional topics in different science and technology domains. The proposed S&TO can promote the discovery of new research areas and collaborations across disciplines. The ontology is constructed by applying BERTopic to a dataset of 393,991 scientific articles collected from Semantic Scholar from October 2021 to August 2022, covering four fields of science. Currently, S&TO includes 5,153 topics and 13,155 semantic relations. S&TO model can be updated by running BERTopic on more recent datasets

George Boateng, Samuel John, Samuel Boateng et al.

Africa has a high student-to-teacher ratio which limits students' access to teachers for learning support such as educational question answering. In this work, we extended Kwame, a bilingual AI teaching assistant for coding education, adapted it for science education, and deployed it as a web app. Kwame for Science provides passages from well-curated knowledge sources and related past national exam questions as answers to questions from students based on the Integrated Science subject of the West African Senior Secondary Certificate Examination (WASSCE). Furthermore, students can view past national exam questions along with their answers and filter by year, question type, and topics that were automatically categorized by a topic detection model which we developed (91% unweighted average recall). We deployed Kwame for Science in the real world over 8 months and had 750 users across 32 countries (15 in Africa) and 1.5K questions asked. Our evaluation showed an 87.2% top 3 accuracy (n=109 questions) implying that Kwame for Science has a high chance of giving at least one useful answer among the 3 displayed. We categorized the reasons the model incorrectly answered questions to provide insights for future improvements. We also share challenges and lessons with the development, deployment, and human-computer interaction component of such a tool to enable other researchers to deploy similar tools. With a first-of-its-kind tool within the African context, Kwame for Science has the potential to enable the delivery of scalable, cost-effective, and quality remote education to millions of people across Africa.

Wenceslao Arroyo-Machado, Enrique Herrera-Viedma, Daniel Torres-Salinas

Twitter bots are a controversial element of the platform, and their negative impact is well known. In the field of scientific communication, they have been perceived in a more positive light, and the accounts that serve as feeds alerting about scientific publications are quite common. However, despite being aware of the presence of bots in the dissemination of science, no large-scale estimations have been made nor has it been evaluated if they can truly interfere with altmetrics. Analyzing a dataset of 3,744,231 papers published between 2017 and 2021 and their associated 51,230,936 Twitter mentions, our goal was to determine the volume of publications mentioned by bots and whether they skew altmetrics indicators. Using the BotometerLite API, we categorized Twitter accounts based on their likelihood of being bots. The results showed that 11,073 accounts (0.23% of total users) exhibited automated behavior, contributing to 4.72% of all mentions. A significant bias was observed in the activity of bots. Their presence was particularly pronounced in disciplines such as Mathematics, Physics, and Space Sciences, with some specialties even exceeding 70% of the tweets. However, these are extreme cases, and the impact of this activity on altmetrics varies by speciality, with minimal influence in Arts & Humanities and Social Sciences. This research emphasizes the importance of distinguishing between specialties and disciplines when using Twitter as an altmetric.