Hasil untuk "Military Science"

Євген Камалов

Законом України “Про основи національного спротиву” визначено завдання з підготовки громадян України до національного спротиву. Метою цього закону є підвищення обороноздатності держави, надання обороні України всеосяжного характеру, забезпечення готовності громадян України до національного спротиву. Підготовка громадян України здійснюється за допомогою загальновійськової підготовки, яка передбачає початкову та базову. Аналізуючи роки війни з російською федерацією, можна констатувати, що проблемним питанням всеосяжної оборони держави є низький рівень підготовки населення (мобілізаційного ресурсу) до виконання конституційного обов’язку із захисту суверенітету та територіальної цілісності. Мета статті полягає в комплексному аналізі та визначенні змістовних аспектів підготовки громадян України до національного спротиву, що є ключовим елементом національної безпеки та обороноздатності держави. Методологічну основу дослідження становлять загальнонаукові методи пізнання, що дозволили провести комплексний аналіз проблеми. Зокрема, системний аналіз використано для вивчення підготовки громадян до національного спротиву як цілісної, багатоетапної системи, що охоплює формальну та неформальну освіту. Порівняльно-правовий аналіз нормативно-правової бази дав можливість виявити наявні протиріччя між законодавчими вимогами та реальним станом справ, особливо щодо впровадження базової підготовки в закладах вищої освіти. Методи аналізу та синтезу були ключовими для декомпозиції змісту підготовки за чотирма основними етапами життя громадянина, виявлення сильних і слабких сторін кожного етапу, а також для формулювання обґрунтованих завдань щодо підвищення рівня підготовленості населення. Ретроспективний аналіз досвіду мобілізації 2022 року та історичних аспектів військової справи підкреслив гостру актуальність проблеми навченості та став основою для практичних висновків. У статті досліджено стан та особливості функціонування підготовки громадян України до національного спротиву протягом життя. Проаналізовано загальновійськову підготовку громадян України до національного спротиву, Типові освітні програми в закладах середньої освіти та навчальні програми закладів вищої освіти, вищих військових навчальних закладів. Визначено періоди здобування формальної чи неформальної освіти, категорії громадян України за етапами підготовки, досліджено порядок підготовки громадян України до національного спротиву на кожному періоді життя, виявлено недоліки на кожному етапі підготовки та визначено завдання, які необхідно виконати для підвищення рівня підготовки громадян України до національного спротиву. Практичне значення роботи полягає у розробленні систематизованих та конкретних рекомендацій, які мають безпосереднє застосування для вдосконалення державної політики у сфері безпеки та освіти. Результати дослідження надають Міністерству освіти і науки та Міністерству оборони України чіткі завдання для коригування нормативно-правової бази (зокрема Концепції військово-патріотичного виховання та навчальних програм), а також для вирішення кадрових, фінансових і матеріально-технічних проблем у закладах освіти, що проводять початкову та базову підготовку. Визначення вразливих аспектів (некомпетентний викладацький склад, застаріла матеріальна база) та розроблення чотириетапної структури підготовки дозволяють створити диференційовані та адаптовані навчальні програми для різних категорій громадян (школярів, студентів, осіб, які самостійно готуються), що зрештою має забезпечити підвищення ефективності національного спротиву та зміцнення обороноздатності держави.

Wei Meng

This study proposes a systematic non-kinetic deterrence path modeling framework based on strategic rare earth supply cut-off, aiming to assess the strategic effects of China's export control policy against the United States at the military system level. The model adopts a four-layer structure of "policy input -- resource node -- equipment system -- capability output" and integrates path dependency modeling, degradation function design, and capability lag prediction mechanisms to form a strategic simulation system. The study incorporates graph neural networks and LSTM-based time series methods to dynamically evaluate the impact of rare earth supply disruption on key U.S. military platforms such as the F-35 fighter, nuclear submarines, and AI combat systems, identifying critical path nodes and strategic timing windows. Results indicate that a ten-year zero-tolerance policy on rare earth exports would lead to a significant technological disconnect between years 3 to 5 and a systemic capability lag between years 8 to 12, with an estimated average annual economic impact of 35 to 40 billion USD. These findings demonstrate that rare earth export cut-offs can serve as a structural strategic deterrent capable of disrupting deployment tempos without direct confrontation. The proposed model provides quantifiable and visualized tools for strategic decision-making and supports national-level security simulations and policy optimization research.

Song Zeng, Xin-Lu Wang, Hua Yang

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors continues to pose significant challenges due to variability in image performance, resulting in a lack of objectivity that relies heavily on the expertise of medical professionals. This challenge can be addressed through the emergence and advancement of radiomics, which enables high-throughput extraction of valuable information from conventional medical images. Furthermore, radiomics can integrate with genomics, a novel approach termed radiogenomics, which allows for a more comprehensive, precise, and personalized assessment of tumor biological features. In this review, we present an extensive overview of the application of radiomics and radiogenomics in diagnosing and predicting ovarian tumors. The findings indicate that artificial intelligence methods based on imaging can accurately differentiate between benign and malignant ovarian tumors, as well as classify their subtypes. Moreover, these methods are effective in forecasting survival rates, treatment outcomes, metastasis risk, and recurrence for patients with OC. It is anticipated that these advancements will function as decision-support tools for managing OC while contributing to the advancement of precision medicine.

Krisztina Kállai

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Serhiy OREL, Vadim DURACH

In 2021, Ukraine produced such an amount of food that it would have been possible to feed about 400 million people, not counting the population of Ukraine. The strategy for the development of the agricultural sector of Ukraine envisages providing food for 1 billion of the world’s population by 2030. However, the aggression of Russia on February 24, 2022, and the subsequent hostilities led to the contamination of agricultural lands with a significant amount of Explosive Remnants of War (ERW), which requires humanitarian demining. This article is devoted to the review of the humanitarian demining process from the point of view of its impact on the environment and the determination of the main components affecting the production of agricultural products. In the first period of the demining process, there will be a significant decline in the production of agricultural products. This decline will be determined by the reduction in the area of cultivated agricultural land due to the danger of explosion. In the course of the demining and liquidation of ERW, the area of land will increase, as will the volume of production, but the quality of products will decrease due to the presence of heavy metal compounds and explosive residues in it and the deterioration of the quality of the soil itself. Therefore, after the liberation of Ukraine’s territory, contaminated by mines and ERW, taking into account its importance as the world’s granary, the demining time is of great importance and Ukraine will be very grateful for any help that will reduce it.

Alan Gatherer, Chaitali Sengupta, Sudipta Sen et al.

Despite the success of the O-RAN Alliance in developing a set of interoperable interfaces, development of unique Radio Access Network (RAN) deployments remains challenging. This is especially true for military communications, where deployments are highly specialized with limited volume. The construction and maintenance of the RAN, which is a real time embedded system, is an ill-defined NP problem requiring teams of specialized system engineers, with specialized knowledge of the hardware platform. In this paper, we introduce a RAN Domain Specific Language (RDSL(TM)) to formally describe use cases, constraints, and multi-vendor hardware/software abstraction to allow automation of RAN construction. In this DSL, system requirements are declarative, and performance constraints are guaranteed by construction using an automated system solver. Using our RAN system solver platform, Gabriel(TM) we show how a system engineer can confidently modify RAN functionality without knowledge of the underlying hardware. We show benefits for specific system requirements when compared to the manually optimized, default configuration of the Intel FlexRAN(TM), and conclude that DSL/automation driven construction of the RAN can lead to significant power and latency benefits when the deployment constraints are tuned for a specific case. We give examples of how constraints and requirements can be formatted in a "Kubernetes style" YAML format which allows the use of other tools, such as Ansible, to integrate the generation of these requirements into higher level automation flows such as Service Management and Orchestration (SMO).

A. Qureshi, M. Patel, S. Neumark et al.

Introduction Chronic non-cancer pain is common among military veterans; however, the prevalence is uncertain. This information gap complicates policy decisions and resource planning to ensure veterans have access to healthcare services that align with their needs. Methods Following Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols, we searched MEDLINE, EMBASE, PsycINFO, CINAHL and Web of Science from inception to 9 February 2023 for observational studies reporting the prevalence of chronic non-cancer pain among military veterans. We performed random-effects meta-analysis to pool pain prevalence data across studies and used the Grading of Recommendations, Assessment, Development and Evaluation approach to evaluate the certainty of evidence. Results Forty-two studies that included 14 305 129 veterans were eligible for review, of which 28 studies (n=5 011 634) contributed to our meta-analysis. Most studies (90%; 38 of 42) enrolled US veterans, the median of the mean age among study participants was 55 years (IQR 45–62) and 85% were male. The pooled prevalence of chronic non-cancer pain was 45%; however, we found evidence of a credible subgroup effect based on representativeness of the study population. Moderate certainty evidence found the prevalence of chronic pain among studies enrolling military veterans from the general population was 30% (95% CI 23% to 37%) compared with 51% (95% CI 38% to 64%) among military veterans sampled from populations with high rates of conditions associated with chronic pain (p=0.005). Conclusion We found moderate certainty evidence that 3 in every 10 military veterans from the general population live with chronic non-cancer pain. These findings underscore the importance of ensuring access to evidence-based care for chronic pain for veterans, and the need for prevention and early management to reduce transition from acute to chronic pain. Further research, employing a standardised assessment of chronic pain, is needed to disaggregate meaningful subgroups; for example, the proportion of veterans living with moderate to severe pain compared with mild pain.

Clara Maathuis

Through recent advancements, AI stands as a transformative force by reshaping societal domains and strategies. In the military cyber domain, this transformation pivots on data and contribution to increasing systems’ efficiency and human decision-making activities. However, building and conducting military Cyber Operations are processes that require dealing with context complexity and uncertainty while directly involving multiple stakeholders that need to understand and interpret the results provided by the AI systems. This represents a notable knowledge gap in current scientific and practitioner efforts that this research tackles by proposing a Human Centered Explainable AI (HCXAI) framework for military Cyber Operations. To achieve this goal, the Design Science Research methodology is used in respect to the Value Sensitive Design approach. Moreover, the framework proposed is successfully evaluated on a use case on conducting the proportionality assessment in military Cyber Operations. Conclusively, this research contributes to building responsible and trustworthy AI systems in the military domain opening a new avenue for the research and practitioner communities.

A. Phelps, A. Adler, S. Bélanger et al.

Moral injury is a relatively new, but increasingly studied, construct in the field of mental health, particularly in relation to current and ex-serving military personnel. Moral injury refers to the enduring psychosocial, spiritual or ethical harms that can result from exposure to high-stakes events that strongly clash with one’s moral beliefs. There is a pressing need for further research to advance understanding of the nature of moral injury; its relationship to mental disorders such as posttraumatic stress disorder and depression; triggering events and underpinning mechanisms; and prevalence, prevention and treatment. In the meantime, military leaders have an immediate need for guidance on how moral injury should be addressed and, where possible, prevented. Such guidance should be theoretically sound, evidence-informed and ethically responsible. Further, the implementation of any practice change based on the guidance should contribute to the advancement of science through robust evaluation. This paper draws together current research on moral injury, best-practice approaches in the adjacent field of psychological resilience, and principles of effective implementation and evaluation. This research is combined with the military and veteran mental health expertise of the authors to provide guidance on the design, implementation and evaluation of moral injury interventions in the military. The paper discusses relevant training in military ethical practice, as well as the key roles leaders have in creating cohesive teams and having frank discussions about the moral and ethical challenges that military personnel face.

Jeff Carter

How are patterns of military spending shaped by political leaders who have substantive policy preferences and need the support of their constituents to remain in power? A formal model developed to address this question indicates leaders’ preferences, political vulnerability, and motivation and their domestic audiences’ preferences jointly influence equilibrium military spending. I find variation in patterns of military spending consistent with the model's implications between 1946 and 2010. My analyses demonstrate that leaders’ desire to remain in power and individual-level characteristics and domestic audiences’ preferences jointly shape policy outcomes and, accordingly, suggest studying the interactions among them can provide insights into a range of topics central to peace science.

Andrés Hernando Matiz-Rojas, Jaime Alexander Fernández-Camargo

Este artículo busca determinar los usos de la inteligencia artificial en la conducción de conflictos armados como medio, a través de armamento autónomo o semiautónomo, y como método, en la toma de decisiones en operaciones militares psicológicas. También se tiene en cuenta las operaciones militares psicológicas, los conflictos híbridos y el potencial aporte de esta tecnología en el escenario militar actual y futuro. Para esto, se consultó información en fuentes primarias y se adaptó el método Delphi para responder a seis hipótesis planteadas y establecer su influencia y su dependencia. Entre las conclusiones, se establecen el aporte de la inteligencia artificial como herramienta eficiente en la conducción de conflictos armados, como factor disuasivo o como factor de confrontación directa, y la importancia de fortalecer el derecho internacional frente a esta tecnología.

A. Y. Timofeev

The article analyzes the attitude of Yugoslav military analysts to the deployment of the Soviet troops in Afghanistan in 1979–1981. Afghanistan was not among diplomatic, or military priorities for Yugoslavia. After the coup in Afghanistan on April 27, 1978, relations between the two countries, previously rather formal, deteriorated, as Kabul started to move away from the non-alignment movement taking a pro-Soviet orientation. Yugoslavia saw Afghanistan as a non-aligned country and was extremely concerned about the Soviet interference in the internal affairs of a sovereign state. This political assessment heavily influenced the views of Yugoslav military expert, resulting into some distorted conclusions and numerous overlooked lessons. This testifies to the primacy of everyday political (and even propaganda) needs over military science in Yugoslavia. They believed that Afghanistan would turn into a permanent problem for the USSR. Despite the rich empirical material, Yugoslav analysts did not see any novelty in tactics and the use of new weapons in mountainous areas. They neglected to analyze the tactics of anti-partisan actions in the highlands; their predictions were not original; they ignored the presence of militant fundamentalism as a factor in the conduct of hostilities.

Tai Le Quy, Gunnar Friege, Eirini Ntoutsi

Ensuring fairness is essential for every education system. Machine learning is increasingly supporting the education system and educational data science (EDS) domain, from decision support to educational activities and learning analytics. However, the machine learning-based decisions can be biased because the algorithms may generate the results based on students' protected attributes such as race or gender. Clustering is an important machine learning technique to explore student data in order to support the decision-maker, as well as support educational activities, such as group assignments. Therefore, ensuring high-quality clustering models along with satisfying fairness constraints are important requirements. This chapter comprehensively surveys clustering models and their fairness in EDS. We especially focus on investigating the fair clustering models applied in educational activities. These models are believed to be practical tools for analyzing students' data and ensuring fairness in EDS.

Balaram Panda

Data Science is a modern Data Intelligence practice, which is the core of many businesses and helps businesses build smart strategies around to deal with businesses challenges more efficiently. Data Science practice also helps in automating business processes using the algorithm, and it has several other benefits, which also deliver in a non-profitable framework. In regards to data science, three key components primarily influence the effective outcome of a data science project. Those are 1.Availability of Data 2.Algorithm 3.Processing power or infrastructure

Сергій Павленко, Олександр Путро, Ярослав Павлов et al.

Наведено модель, за допомогою якої є можливість оцінити і спрогнозувати ефективність заходів маскування підрозділів тилового забезпечення під час здійснення переміщення (маршу) при підготовці і в ході виконання бойового завдання. Отримані результати моделювання можливо використовувати для розроблення рекомендацій командирам підрозділів Національної гвардії України та інших військових формувань для прогнозування ефективності заходів маскування під час здійснення переміщення. В моделі є вісім етапів. На першому етапі відбувається збирання, оброблення, введення вхідних даних для отримання шуканої оцінки ефективності заходів маскування або імовірність досягнення мети маскування підрозділів тилового забезпечення під час здійснення переміщення (маршу) при підготовці і в ході виконання бойового завдання. На другому етапі обчислюється імовірність своєчасного проведення заходів маскування підрозділів тилового забезпечення. На третьому етапі проводиться перевірка отриманих значень імовірностей щодо відповідності визначених вимог критерію ефективності. Четвертий етап присвячений обчисленню імовірності неухилення противника від органів спостереження. Під час п’ятого етапу проводиться перевірка отриманих значень імовірностей щодо відповідності визначених вимог критерію ефективності. На шостому етапі обчислюється імовірність знищення засідки противника силами похідної охорони всіма наявними вогневими засобами. Під час сьомого етапу проводиться перевірка отриманих значень імовірностей щодо відповідності визначених вимог критерію ефективності. На завершальному, восьмому етапі, отримавши результати в блоках (1)–(7), які задовольняють умови критерію, проводимо розрахунки оцінювання ефективності заходів маскування підрозділів тилового забезпечення під час здійснення переміщення (маршу) при підготовці і в ході виконання бойового завдання. Для оцінки шуканих значень ймовірностей можливо отримати за допомогою застосування відомих та апробованих підходів математичного моделювання військових дій.

Yanjie Yang, Wei Han, Yiyong Huang et al.

Propellant Gauging is of vital importance to a spacecraft at the end of its life. Based on the Monte Carlo Method, uncertainty analysis and the improvement of propellant gauging using gas injection have been studied. As a result of the analysis, the gauging uncertainty has weak relation to the uncertainties of the volumes of the injection room and tank, the uncertainties of the pressure, and the temperature in the injection room. Relatively, the uncertainties of the temperature and pressure in the tank have a great effect on the gauging uncertainty. By improving the uncertainties of the tank pressure and temperature within 0.04% and 0.4%, the final gauging uncertainty can be obtained within 0.4%. Ground tests have been conducted and the results came out with approximately 0.4% error, well within the theoretical analysis.

Chong Wang, Jian-Hao Lu, An-Bang Wang et al.

The shuttling effect of soluble lithium polysulfides (LiPSs) and the sluggish conversion kinetics of polysulfides into insoluble Li₂S₂/Li₂S severely hinders the practical application of Li-S batteries. Advanced catalysts can capture and accelerate the liquid–solid conversion of polysulfides. Herein, we try to make use of bismuth tantalum oxide with oxygen vacancies as an electrocatalyst to catalyze the conversion of LiPSs by reducing the sulfur reduction reaction (SRR) nucleation energy barrier. Oxygen vacancies in Bi₄TaO₇ nanoparticles alter the electron band structure to improve instinct electronic conductivity and catalytic activity. In addition, the defective surface could provide unsaturated bonds around the vacancies to enhance the chemisorption capability with LiPSs. Hence, a multidimensional carbon (super P/CNT/Graphene) standing sulfur cathode is prepared by coating oxygen vacancies Bi₄TaO_7−x nanoparticles, in which the multidimensional carbon (MC) with micropores structure can host sulfur and provide a fast electron/ion pathway, while the outer-coated oxygen vacancies with Bi₄TaO_7−x with improved electronic conductivity and strong affinities for polysulfides can work as an adsorptive and conductive protective layer to achieve the physical restriction and chemical immobilization of lithium polysulfides as well as speed up their catalytic conversion. Benefiting from the synergistic effects of different components, the S/C@Bi₃TaO_7−x coin cell cathode shows superior cycling and rate performance. Even under a high level of sulfur loading of 9.6 mg cm⁻², a relatively high initial areal capacity of 10.20 mAh cm⁻² and a specific energy density of 300 Wh kg⁻¹ are achieved with a low electrolyte/sulfur ratio of 3.3 µL mg⁻¹. Combined with experimental results and theoretical calculations, the mechanism by which the Bi₄TaO₇ with oxygen vacancies promotes the kinetics of polysulfide conversion reactions has been revealed. The design of the multiple confined cathode structure provides physical and chemical adsorption, fast charge transfer, and catalytic conversion for polysulfides.

Christopher S. Meyer, Isabel G. Catugas, John W. Gillespie, Jr. et al.

Spacesuits and spacecraft must endure high velocity impacts from micrometeoroids. This work considers the impact of 100 μm diameter projectiles into composite targets at velocities from 0.5 km/s to 2 km/s. This work begins by presenting an energy-based theoretical model relating depth of penetration (DoP) and impact force to impact velocity, characteristic time, and threshold velocity and force. Next, this work compares numerical simulations of normal impact on composites to the theoretical model. Numerical simulations are conducted with LS-DYNA and the well-known composite model, MAT-162. The numerical models consider unidirectional S2-glass fiber reinforced SC-15 epoxy composite laminates. The numerical model shows good correlation with the theoretical model. The numerical model also investigates lateral impact, parallel to the fiber direction, and oblique impact at angles from 30° to 82.5°. This work decomposes oblique impact into normal and lateral components, and compares them with normal and lateral impact results. The results show good correlation of the normal component of oblique results with the theoretical model. This numerical and theoretical study focuses on DoP, velocity, and penetration resistance force as functions of time. The theoretical model and numerical simulations are used to determine new DoP parameters: characteristic time of depth of penetration and threshold impact velocity. These models are a first step in developing the capability to predict DoP for oblique, microscale, high-speed impact on composite materials.

Sabri Touidjine, Moulai Karim Boulkadid, Djalal Trache et al.

To improve the performance of solid composite propellants (SCPs) supplemented with ammonium nitrate (AN) as an oxidizer, the incorporation of energetic ingredients such as explosives, energetic binders or catalysts is a common effective approach. For this purpose, polyurethane (PU), a typical inert binder, was mixed with nitrocellulose (NC) as an energetic polymer. Numerous composite solid propellant compositions based on AN and NC-modified polyurethane binder with different NC ratios were prepared. The prepared formulations were characterized using Fourier transform infrared spectroscopy (FTIR), RAMAN spectroscopy, X-ray diffraction (XRD), electron densimetry, thermogravimetric (TG) analysis, and differential scanning calorimetry (DSC). A kinetic study was then performed using the iterative Kissinger-Akahira-Sunose (It-KAS), Flynn-Wall-Ozawa (It-FWO), and non-linear Vyazovkin integral with compensation effect (VYA/CE) methods. The theoretical performances, such as theoretical specific impulse, adiabatic flame temperature, and ideal exhaust gaseous species, were also determined using the NASA Lewis Code, Chemical Equilibrium with Application (CEA). Spectroscopic examinations revealed the existence of NC and full polymerization of PU in the prepared propellants. According to density tests, the density of the propellant increases as the nitrocellulose component increases. According to the thermal analysis and kinetics study, the increase in NC content catalyzed the thermal decomposition of the AN-based composite solid propellants. Based on the theoretical study, increasing the amount of NC in the propellant increased the specific impulse and, as a result, the overall performance.

The Genomic Data Science Community Network, Rosa Alcazar, Maria Alvarez et al.

Over the last 20 years, there has been an explosion of genomic data collected for disease association, functional analyses, and other large-scale discoveries. At the same time, there have been revolutions in cloud computing that enable computational and data science research, while making data accessible to anyone with a web browser and an internet connection. However, students at institutions with limited resources have received relatively little exposure to curricula or professional development opportunities that lead to careers in genomic data science. To broaden participation in genomics research, the scientific community needs to support students, faculty, and administrators at Underserved Institutions (UIs) including Community Colleges, Historically Black Colleges and Universities, Hispanic-Serving Institutions, and Tribal Colleges and Universities in taking advantage of these tools in local educational and research programs. We have formed the Genomic Data Science Community Network (http://www.gdscn.org/) to identify opportunities and support broadening access to cloud-enabled genomic data science. Here, we provide a summary of the priorities for faculty members at UIs, as well as administrators, funders, and R1 researchers to consider as we create a more diverse genomic data science community.