Korea Military Academy

A bstract We present theoretical predictions for the transverse-momentum distribution of J/ψ produced within jets at the upcoming Electron-Ion Collider (EIC). Utilizing the semi-inclusive fragmenting jet function (FJF) framework, our calculation achieves next-to-leading order (NLO) accuracy in the strong coupling and leading-logarithmic (LL) accuracy by resumming both collinear and threshold logarithms. In contrast to the gluon-dominated regime of the LHC, EIC photoproduction is characterized by an enhanced quark-initiated component, offering a complementary probe into the charmonium production mechanism governed by nonperturbative long-distance matrix elements (LDMEs). We examine the impact of representative LDME sets, demonstrating the EIC’s distinct discriminating power for the mechanisms. We find that quark contributions are particularly significant in the small momentum fraction region. This region is also shown to be sensitive to both the jet radius R and the experimental muon identification criteria for the J/ψ → μ + μ − decay channel. These findings establish quarkonium-in-jet observables at the EIC as a vital, independent probe for constraining the production mechanisms and advancing our understanding of heavy quarkonium formation.

Accurate prediction of 15N NMR chemical shifts in flexible peptide systems remains challenging. We present an ensemble-based computation protocol combining density functional theory with replica-exchange molecular dynamics. This approach outperformed single-structure predictions with deviations of 2.5-5.6 ppm for most residues and 1.1 ppm for leucine in a model peptide.

Early Detection of Social Exclusion Through Sentiment Analysis: Today, cyberbullying is growing rapidly at a startling rate, causing serious emotional and psychological harm to children and young adults. Social exclusion in online settings is recognized as one of the primary driving forces to this issue which is why it is essential to be able to identify these exclusionary signs early on is crucial to successful intervention. Thus, this study evaluates the potential of AI models like Open AI’s ChatGPT in detecting early signals that indicate social isolation in simulated social networking services (SNS). A dataset of 6 conversational scenarios (bullying, neutral, and positive) with a total of 24 utterances were created and assessed with sentiment labels, risk categories, and sentiment intensity scores. The evaluations from ChatGPT’s algorithm were then compared to human-coded annotations. Bullying scenarios consistently scored higher in the risk range (0.7-1.0) with strongly negative sentiment tables, whereas neutral and positive scenarios clustered near zero, demonstrating clear polarizations. Additionally, there was a high degree of agreement between human annotations and model evaluations especially when it came to distinguishing between neural encounters and high-risk bullying. Contrastingly, it failed to show an accuracy with identifying more subtle kinds of exclusion capturing the nuances behind expression. Results reflected that GPT’s model served to be an effective system for early warning toward dangerous interactions in social media settings. Although there is limited ecological validity due to the conversation data being simulated, the results act as a fundamental paradigm for using sentiment analysis to reduce cyberbullying.

This study investigates the rationale behind North Korean dictators’ use of seemingly contradictory forms of military control—influence and domination—to solidify regime stability during periods of power transition. In this analysis, North Korean dictators are assumed to navigate their decision-making within the constraints of existing institutional structures. Unlike Kim Jong-Il (KJI), who could capitalize on the established “old boy network” comprised of his predecessor’s military protégés, Kim Jong-un (KJU) was compelled to replace this entrenched nepotism with bureaucratic regulations to consolidate his control over the military. Then, this study hypothesizes that dictators’ use of praise or threats toward the military reflects shifts in the network structure in which they are embedded. By tracing the career trajectories of 184 North Korean generals who held 55 key command and staff positions in the Korean People’s Army (KPA) from 1989 to 2023, this study examined how variations in loyalty norms and resulting network structures shaped the dictators’ speech to the military. Results from a structural topic modeling analysis show that KJI was more likely to speak on complimentary topics, while KJU was more likely to speak on reprimanding topics when addressing the KPA. These findings underscore how shifts in the military leadership network decide the distinct military control strategies employed by dictators.

This chapter explains the general concepts of quantum computing and digital twins using technological terminology. Specifically, considering the development of modern semiconductor technology and quantum computing technology, this chapter explores the interconnected domains of quantum computing, digital twins, and semiconductor development (especially non-memory semiconductor development), analyzing their combined influence on technological progress. This chapter investigates the basics and fundamentals of quantum computing, the progression and utilization of digital twins in diverse industries, and the essential role of emerging semiconductor technologies in making them operational. Through a multidisciplinary approach, this chapter reveals the synergies, obstacles, and potential uses in various applications, illuminating the considerable impact of these technologies across a wide range of fields. Furthermore, we address ethical concerns and outline future research directions and collaborative opportunities, offering informative insights into the technological landscape of the future.

ABSTRACT Glass fiber-reinforced polymer (GFRP) bars are increasingly recognized as a promising alternative to conventional steel reinforcement in concrete structures due to their corrosion resistance, high tensile strength, and eco-friendly production. Their application in continuously reinforced concrete pavement (CRCP) systems offers an opportunity to leverage these advantages. However, challenges remain, including GFRP’s relatively low elastic modulus, thermal incompatibility with concrete, and manufacturing limitations. To address these issues, this study integrates a comprehensive literature review with three-dimensional finite element simulations. The review highlights GFRP’s superior durability against chloride-induced corrosion and its ability to reduce local stress concentrations. Nonetheless, concerns remain regarding its lower stiffness, which may result in increased deflection and crack width in flexural members. Numerical analyses further suggest that the reduced modulus of GFRP lowers effective stresses, thereby potentially mitigating horizontal cracking. Consequently, GFRP bars demonstrate considerable promise as a substitute for conventional steel in CRCP applications. This study provides insights into the structural feasibility and performance benefits of GFRP reinforcement in pavement systems, contributing to the development of more durable and corrosion-resistant designs.

Abstract We present another way to teach the least-action principle in classical mechanics. Beginning with Newton’s second law of motion, we keep finding equivalent propositions based mainly on the method of undetermined coefficients in a multivariable-dependent identity to arrive at the Euler–Lagrange equations and the conventional principle of stationary action $$\delta S=0$$ δ S = 0 with the boundary condition for the variation of the physical path. Pedagogically, by following the logical steps that we show, students can easily learn that Lagrangian mechanics naturally arises from Newtonian mechanics. This approach makes it further clear that Newton’s laws do not require the minimum action—true for a free particle, just as the shortest path between two points is a straight line. However, the action is not always the minimum once the potential energy is turned on. The derivation of the least-action principle from Newton’s second law may resemble Euclid’s approach to geometric axioms.

Roadway anti-icing requires low-carbon alternatives to chloride salts and electric heating. This study evaluated a seasonal thermal energy storage system that couples a geothermal hydronic heated pavement (HHPS-G) with borehole thermal energy storage (BTES), operated without auxiliary heat. A coupled transient HHPS-G–BTES model was developed and validated against independent experimental data. A continuous cycle was then simulated, consisting of three months of summer pavement heat harvesting and BTES, followed by three months of winter heat discharge. A parametric analysis varied borehole depth (10, 20, and 40 m) and number of units (1, 2, and 4). Results indicated that depth is consistently more effective than unit number. Deeper fields produced larger summer pavement surface cooling with less long-term drift and yielded more persistent winter anti-icing performance. The 40 m 4-unit case lowered the end-of-summer surface temperature by 3.8 °C relative to the no-operation case and kept the surface at or above 0 °C throughout winter. In contrast, the 10 m–1-unit case was near 0 °C by late winter. A depth-first BTES design, supplemented by spacing or edge placement to limit interference, showed practical potential for anti-icing without auxiliary heat.