Objective: main concern is lack of codification of indigenous intelligent command and control model, main goal is to develop indigenous intelligent command and control model using military Internet of Things, other goals: to count dimensions and components, determine relationships between dimensions and components of model design, and to count achievements, consequences, functions and requirements of model design. Method: type of applied-developmental research, descriptive-case research method, mixed research approach and method of data collection, field and library, with library study tools are books, articles, documents, interviews, questionnaires, and time domain of years 1402-1403 for five years and spatial domain of country's armed forces. Statistical population of 70 experts and experts, structural equation modeling is used to analyze and investigate relationship and correlation between factors. Results:By testing PLS model in SRMR test, since it is smaller than 0.08, overall model of PLS has a good fit and is therefore consistent with desired model in society.Conclusion:dimensions of model design are intelligence, information management, sustainability, interoperability, integration, and network-oriented. achievements and consequences of designing model are improvement (intelligence of c4isr, and decision-making, comprehensive defense readiness, deterrence), increasing military authority and capability, and increasing indigenous cyber power. Functions of model design are intelligence-making (action-oriented and strategic command systems, control, monitoring and evaluation systems, communication systems, computer and cyberspace systems, information collection systems, surveillance and identification systems) and online situational awareness on battlefield.requirements of designing model are battlefield intelligence, localization of IoT standards, IoT software security, and funding and credit, training and skill development.
Jing-Lei Zhang, Shuo-Lan Tong, Qi-Qi Zhuang
et al.
Abstract Clonal hematopoiesis of indeterminate potential (CHIP), driven by leukemia-related somatic mutations in hematopoietic stem cells, previously recognized as a major risk factor for hematological malignancies, has now emerged as a potent risk factor for chronic inflammation and diverse non-hematologic diseases. CHIP-associated DNA methyltransferase 3 alpha (DNMT3A), tet methylcytosine dioxygenase 2 (TET2), and additional sex combs like 1 (ASXL1) mutations alter epigenetic programs, skew myelopoiesis, and increase proinflammatory cytokines, resulting in chronic inflammation and immune imbalance. This review integrates mechanistic insights with clinical evidence to delineate CHIP’s roles in solid tumors, cardiovascular disorders, and metabolic dysregulation, with an extended discussion of renal dysfunction and neurodegenerative conditions. Furthermore, we also discuss CHIP’s diagnostic and therapeutic impacts across multiple disease contexts, advocating for mutation-specific diagnostic paradigms to guide therapeutic interventions.
Застосування систем автоматичного наведення безпілотних літальних апаратів (БпЛА) на ціль на основі використання технологій штучного інтелекту, в тому числі машинного зору, є одним з перспективних напрямів підвищення ефективності бойового застосування ударних БпЛА. В статті запропоновано підхід до моделювання автоматичного наведення БпЛА перехоплювачів (винищувачів) на ціль на основі машинного зору, що враховує властивості відеокамери, льотно-технічні характеристики БпЛА і цілі, параметри руху цілі, турбулентність атмосфери. Показано, що в межах області можливого оптичного спостереження цілі її перехоплення може бути успішним лише в певному діапазоні початкових координат і напрямів польоту. Маневрування цілі суттєво обмежує діапазон початкових умов для успішного перехоплення. Турбулентність атмосфери і частота кадрів відеокамери БпЛА впливають на точність автоматичного наведення на ціль. Запропонований підхід до моделювання автоматичного наведення БпЛА на ціль на основі машинного зору можна використовувати для обґрунтування вимог до попереднього виведення БпЛА-перехоплювача в область можливих атак цілі, обґрунтування оперативно-тактичних вимог до безпілотних авіаційних комплексів з БпЛА-перехоплювачами і ударними БпЛА разового застосування, розробки найбільш ефективних методів наведення тощо.
Over the past decade, extensive research into single-atom catalysts (SACs) has revealed that the catalytic behavior of metal adatoms is highly dependent on how they interact with their support. A strong dependence on the local coordination environment has led to comparisons with metal-organic complexes, and there is growing excitement about the potential to fine-tune SACs by controlling the adsorption geometry. The rise of computational screening to identify the optimal support-metal combinations underscores the need for rigorous benchmarking of theoretical methods, to validate realistic geometries, mechanisms, and the impact of adsorption on stability and catalytic activity. The surface science approach is particularly well-suited for this task because it allows to precisely determine the geometry of the metal atom and interpret its catalytic behavior. Moreover, the effects of temperature and molecular adsorption on the model catalysts stability can be studied in isolation, and conclusions drawn from UHV studies tested in increasingly common near-ambient pressure and electrochemical setups. This perspective highlights recent breakthroughs and specific systems, including metal oxides, metal-organic frameworks, and carbon nitrides, where insights from surface science experiments can significantly advance understanding in this rapidly evolving field.
Keichi Takahashi, Tomonori Hayami, Yu Mukaizono
et al.
mdx II is an Infrastructure-as-a-Service (IaaS) cloud platform designed to accelerate data science research and foster cross-disciplinary collaborations among universities and research institutions in Japan. Unlike traditional high-performance computing systems, mdx II leverages OpenStack to provide customizable and isolated computing environments consisting of virtual machines, virtual networks, and advanced storage. This paper presents a comprehensive performance evaluation of mdx II, including a comparison to Amazon Web Services (AWS). We evaluated the performance of a 16-vCPU VM from multiple aspects including floating-point computing performance, memory throughput, network throughput, file system and object storage performance, and real-world application performance. Compared to an AWS 16-vCPU instance, the results indicated that mdx II outperforms AWS in many aspects and demonstrated that mdx II holds significant promise for high-performance data analytics (HPDA) workloads. We also evaluated the virtualization overhead using a 224-vCPU VM occupying an entire host. The results suggested that the virtualization overhead is minimal for compute-intensive benchmarks, while memory-intensive benchmarks experienced larger overheads. These findings are expected to help users of mdx II to obtain high performance for their data science workloads and offer insights to the designers of future data-centric cloud platforms.
<h4>Background/objectives</h4>Technological developments in point-of-care ultrasound (POCUS), particularly with portable devices, are transforming POCUS use in austere, resource-limited environments (RLS) distinct from typical hospital or medical settings. POCUS has potential to improve diagnostic accuracy in military combat zones, low-resource environments such as the desert or tropics, microgravity, and high altitudes. Our updated narrative scoping review describes POCUS use in these global settings.<h4>Methods</h4>Using the PRISMA-ScR guidelines, two ultrasound-trained emergency physicians searched PubMed, Embase, and Web of Science on August 6, 2024 for "point-of-care ultrasound in austere environments" and each individual category. Study titles and abstracts were independently screened, then full manuscripts, and data was abstracted with a data collection table. 324 articles met inclusion criteria: research studies describing POCUS in austere environments; involving healthcare professionals; and in English. We excluded abstracts, studies not involving POCUS in austere environments, and non-clinical studies. Reviewers critically appraised studies using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) Quality Assessment Tool.<h4>Results</h4>There were 39 military or conflict zone studies, 101 prehospital, 148 in RLS including low- and middle-income countries, 12 outer space, 15 high altitude, and 32 involving POCUS use in multiple austere environments. There were 6 randomized-control trials, 11 systematic/scoping reviews, 13 narrative reviews, 112 prospective observational/cohort, 34 prospective cross-sectional studies, 23 retrospective, 6 feasibility, 45 case reports, 13 case series, and 5 educational curriculum studies. GRADE study quality was variable, with 74 high quality, 129 moderate, 82 low, and 56 very low.<h4>Conclusion</h4>The existing literature is mixed with variability in study settings, design, and POCUS examination types, providing an initial understanding of POCUS applications. Most studies are in RLS or prehospital settings. Additional high-quality studies are needed to guide POCUS training, disseminate use in non-hospital settings, and maximize impact for improved clinical outcomes in diverse austere environments.
Abstract Exercise is usually regarded to have short-term beneficial effects on immune health. Here we show that early-life regular exercise exerts long-term beneficial effects on inflammatory immunity. Swimming training for 3 months in male mice starting from 1-month-old curbs cytokine response and mitigates sepsis when exposed to lipopolysaccharide challenge, even after an 11-month interval of detraining. Metabolomics analysis of serum and liver identifies pipecolic acid, a non-encoded amino acid, as a pivotal metabolite responding to early-life regular exercise. Importantly, pipecolic acid reduces inflammatory cytokines in bone marrow-derived macrophages and alleviates sepsis via inhibiting mTOR complex 1 signaling. Moreover, early-life exercise increases histone 3 lysine 4 trimethylation at the promoter of Crym in the liver, an enzyme responsible for catalyzing pipecolic acid production. Liver-specific knockdown of Crym in adult mice abolishes this early exercise-induced protective effects. Our findings demonstrate that early-life regular exercise enhances anti-inflammatory immunity during middle-aged phase in male mice via epigenetic immunometabolic modulation, in which hepatic pipecolic acid production has a pivotal function.
Patrick Bassner, Eduard Frankford, Stephan Krusche
Integrating AI-driven tools in higher education is an emerging area with transformative potential. This paper introduces Iris, a chat-based virtual tutor integrated into the interactive learning platform Artemis that offers personalized, context-aware assistance in large-scale educational settings. Iris supports computer science students by guiding them through programming exercises and is designed to act as a tutor in a didactically meaningful way. Its calibrated assistance avoids revealing complete solutions, offering subtle hints or counter-questions to foster independent problem-solving skills. For each question, it issues multiple prompts in a Chain-of-Thought to GPT-3.5-Turbo. The prompts include a tutor role description and examples of meaningful answers through few-shot learning. Iris employs contextual awareness by accessing the problem statement, student code, and automated feedback to provide tailored advice. An empirical evaluation shows that students perceive Iris as effective because it understands their questions, provides relevant support, and contributes to the learning process. While students consider Iris a valuable tool for programming exercises and homework, they also feel confident solving programming tasks in computer-based exams without Iris. The findings underscore students' appreciation for Iris' immediate and personalized support, though students predominantly view it as a complement to, rather than a replacement for, human tutors. Nevertheless, Iris creates a space for students to ask questions without being judged by others.
The current Special Issue entitled “Highlights of Ukrainian Molecular Biosciences” is dedicated to presenting recent contributions in the areas of biochemistry and biophysics, molecular biology and genetics, molecular and cellular physiology, and physical chemistry of biological macromolecules made by researchers either currently working in Ukraine or those who have obtained their training in Ukrainian institutions. Obviously, such a collection can present only a small sample of relevant studies, making the editorial task a particular challenge, as inevitably many deserving research groups were missed. In addition, we are greatly sorrowed that some of the invitees were unable to contribute due to the continued bombardments and military attacks perpetrated by Russia in Ukraine since 2014, and especially in 2022. This Introduction is also intended to provide a broader context for understanding of Ukraine's decolonization struggle, both in science and on the battlefield, and outlines suggestions for the global scientific community.
Laura Magrini, Thomas Bensby, Anna Brucalassi
et al.
The High-Resolution Multi-Object Spectrograph (HRMOS) is a facility instrument that we plan to propose for the Very Large Telescope (VLT) of the European Southern Observatory (ESO), following the initial presentation at the VLT 2030 workshop held at ESO in June 2019. HRMOS provides a combination of capabilities that are essential to carry out breakthrough science across a broad range of active research areas from stellar astrophysics and exoplanet studies to Galactic and Local Group archaeology. HRMOS fills a gap in capabilities amongst the landscape of future instrumentation planned for the next decade. The key characteristics of HRMOS will be high spectral resolution (R = 60000 - 80000) combined with multi-object (20-100) capabilities and long term stability that will provide excellent radial velocity precision and accuracy (10m/s). Initial designs predict that a SNR~100 will be achievable in about one hour for a star with mag(AB) = 15, while with the same exposure time a SNR~ 30 will be reached for a star with mag(AB) = 17. The combination of high resolution and multiplexing with wavelength coverage extending to relatively blue wavelengths (down to 380\,nm), makes HRMOS a spectrograph that will push the boundaries of our knowledge and that is envisioned as a workhorse instrument in the future. The science cases presented in this White Paper include topics and ideas developed by the Core Science Team with the contributions from the astronomical community, also through the wide participation in the first HRMOS Workshop (https://indico.ict.inaf.it/event/1547/) that took place in Firenze (Italy) in October 2021.
Abstract The concept of military science represents the interaction of the system of military disciplines, civilian and military educational institutions and their researchers, whose work is focused on the most important societal value - security. In the context of interpretations by various authors, dictionaries and encyclopedias, the article critically examines the conceptualisation of military science, which has not received much attention in the Slovenian literature. In addition to conceptual challenges, the paper also answers the question of what military science is and how it should be understood in the context of contemporary interdisciplinary approaches and efforts of educational and other institutions that analytically grapple with a wide variety of insights, objects or topics related to the military as a phenomenon, practice or idea.
Davron Aslonqulovich Juraev, Ali Shokri, Daniela Marian
In this paper, the Carleman matrix is constructed, and based on it we found explicitly a regularized solution of the Cauchy problem for the matrix factorization of the Helmholtz equation in a multidimensional unbounded domain in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi mathvariant="double-struck">R</mi></mrow><mi>m</mi></msup><mspace width="4pt"></mspace><mo>,</mo><mrow><mo>(</mo><mi>m</mi><mo>=</mo><mn>2</mn><mi>k</mi><mo>,</mo><mspace width="0.166667em"></mspace><mi>k</mi><mo>≥</mo><mn>2</mn><mo>)</mo></mrow></mrow></semantics></math></inline-formula>. The corresponding theorems on the stability of the solution of problems are proved.
Distributed machine learning (DML) can be an important capability for modern military to take advantage of data and devices distributed at multiple vantage points to adapt and learn. The existing distributed machine learning frameworks, however, cannot realize the full benefits of DML, because they are all based on the simple linear aggregation framework, but linear aggregation cannot handle the $\textit{divergence challenges}$ arising in military settings: the learning data at different devices can be heterogeneous ($\textit{i.e.}$, Non-IID data), leading to model divergence, but the ability for devices to communicate is substantially limited ($\textit{i.e.}$, weak connectivity due to sparse and dynamic communications), reducing the ability for devices to reconcile model divergence. In this paper, we introduce a novel DML framework called aggregation in the mirror space (AIMS) that allows a DML system to introduce a general mirror function to map a model into a mirror space to conduct aggregation and gradient descent. Adapting the convexity of the mirror function according to the divergence force, AIMS allows automatic optimization of DML. We conduct both rigorous analysis and extensive experimental evaluations to demonstrate the benefits of AIMS. For example, we prove that AIMS achieves a loss of $O\left((\frac{m^{r+1}}{T})^{\frac1r}\right)$ after $T$ network-wide updates, where $m$ is the number of devices and $r$ the convexity of the mirror function, with existing linear aggregation frameworks being a special case with $r=2$. Our experimental evaluations using EMANE (Extendable Mobile Ad-hoc Network Emulator) for military communications settings show similar results: AIMS can improve DML convergence rate by up to 57\% and scale well to more devices with weak connectivity, all with little additional computation overhead compared to traditional linear aggregation.
Walter Maurício Costa de Miranda, Alexandre Rocha Violante, Marcelo Mello Valença
Uma Grande Estratégia envolve a coordenação e direção de todos os recursos de uma nação para alcançar objetivos políticos, ou o uso do poder militar, a teoria e a prática do uso e a ameaça de uso da força organizada para fins políticos. Privilegiando este último viés, a “Grande Estratégia do Barão do Rio Branco”, posta em prática no período em que esteve à frente do Itamaraty, utilizou, por vezes, o poder militar de forma coercitiva e dissuasória. A Grande Estratégia do Barão é distinta da Grande Estratégia de Amorim, principalmente na forma de articular diplomacia com o Poder Militar. As diferenças nessas articulações, bem como os ganhos concretos advindos de cada uma, são percebidas, inicialmente pelo viés mais realista – do Barão – e pela conjugação de várias teorias internacionalistas – de Amorim. A “Grande Estratégia do Barão” foi pautada no incremento do hard power, que resultou em ganhos concretos, como na questão do Acre, já a “Grande Estratégia” de Amorim se pautou mais pelo incremento de seu “soft power”, mas que não chegaram a concretizar uma síntese perfeita entre diplomacia e defesa. Assim, este trabalho tem como objetivo evidenciar as “diferentes formas de articulação” entre a diplomacia e a defesa.
Abstract Background Scarring alopecia in systemic lupus erythematosus (SLE) patients caused reduced life quality and prolonged disease course. This case-control study aims to survey the prevalence of scarring alopecia during the disease course of SLE and evaluate the risk factors for scarring alopecia in Chinese SLE patients. Methods SLE patients in Chinese SLE treatment and Research group (CSTAR) were recruited. Scarring alopecia was defined according to SLICC/ACR-DI which was collected during follow-up visits or via self-reported questionnaires. We collected demographic characteristics, common comorbidities, autoantibody profiles, disease activity status, major organ involvements, and treatment strategies of these patients at registry. Univariate and multivariate logistic regression analyses were used to investigate the risk factors for scarring alopecia. Results We recruited 4792 SLE patients, and 374 (7.80%) patients had scarring alopecia. Mucocutaneous lesions (OR 2.062, p < 0.001), high SLICC/ACR-DI (OR 1.409, p < 0.001), and positive anti-Sm (OR 1.374, p = 0.029) were risk factors for scarring alopecia, while renal (OR 0.714, p = 0.028) and cardio-respiratory involvements (OR 0.347, p = 0.044), and immunosuppressant treatment (OR 0.675, p < 0.001) were significantly negative associated with it. Conclusions The prevalence of scarring alopecia in SLE patients is 7.80%. Active treatment strategies should be adopted to prevent scarring alopecia occurring.
This paper explores how the Turkish case speaks to the contemporary discussions regarding the relations between the police and the military. These discussions have been at the forefront of newly emerging literature which has fundamentally focused on explaining the evolution of the police-military relations in a Western context, seen from a global perspective. This paper, on the other hand, suggests that besides global trends, internal power struggles among security institutions should also be taken into consideration. Turkey provides a unique case for such research as it has experienced a long period of military involvement in domestic issues; yet, this military tutelage is effectively challenged by the civilianization process currently conducted by the political power. This paper investigates the political evolution of these two institutions during the period from 1980 up until now. The conclusion, it claims, is that there are 'competing' rather than 'blurring' boundaries between these two institutions.