The National Defense University (NDU) is an institution of higher education funded by the United States Department of Defense, intended to facilitate high-level education, training, and professional development of national security leaders. As a chairman's Controlled Activity, NDU operates under the guidance of the Chairman of the Joint Chiefs of Staff (CJCS), with Lieutenant General Michael T. Plehn, USAF, as president. It is located on the grounds of Fort Lesley J. McNair in Washington, D.C.
Accurate origin–destination (OD) matrix inference in urban traffic networks is difficult because of the challenges of limited sensor coverage and incomplete observations. To address this challenge, this study introduces a hybrid generative–analytical framework that integrates a generative adversarial network with a path flow proportion method to support OD inference by utilising partial intersection turning movement data. In this framework, the generative adversarial network learns statistically uniform path-choice proportions from sparse turning flow observations, which are subsequently translated into OD demand estimates through conditional inverse matrix operations. The proposed framework was evaluated on a simulated urban network at varying temporal aggregation levels and under different sensor coverage conditions. The results indicated that with moderate data constraints, the framework resulted in lower estimation errors compared with classical tomography-based estimators under identical observation conditions. As the observation windows shortened and sensor availability decreased, the accuracy of estimation progressively decreased, revealing observability limits inherent to turning-flow-based OD inference. By explicitly characterising these applicability boundaries, this study reveals how generative learning can improve data efficiency and mitigate error amplification under constrained but realistic sensing conditions.
2,4,6,8,10,12-Hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (HNIW, CL-20) is currently recognized as the energetic material with the highest energy density in the world and can replace traditional nitramine explosives RDX and HMX for mixed explosives and solid propellants. At present, the most commonly used method for synthesizing CL-20 is the nitration reaction using 2,6,8,12-tetraacetyl-2,4,6,8,10,12-hexaazaisowurtzitane (TAIW) as the nitration precursor and HNO3/H2SO4 mixed acid as the nitrating agent, and then the synthesized crude CL-20 is converted into epsilon-CL-20 through the solvent/anti-solvent recrystallization process. However, little is known about the optimal synthesis parameters for the nitration process. In this study, the Taguchi experimental design method was used to determine the optimal synthesis parameters for maximum yield of crude CL-20. The epsilon-CL-20 produced after crystal form conversion was identified by means of scanning electron microscopy, nuclear magnetic resonance spectrometry, Fourier-transform infrared spectrometry, X-ray diffraction, elemental analyzer, simultaneous thermogravimetry-differential scanning calorimetry, and high-performance liquid chromatography, and its sensitivity was measured using BAM fallhammer, friction sensitivity tester, and electrostatic spark sensitivity tester. The Taguchi analysis results indicated that the optimal synthesis parameters were as follows: the volume ratio of HNO3 to H2SO4 was 5:1, the nitration temperature was 82.5 degrees C, the reaction time was 40 min, and the amount of TAIW used was 9 g/100 mL mixed acid, and the maximum yield of crude CL-20 could reach 92.9%. The average yield of the process for converting crude CL-20 into epsilon-CL-20 was about 91.8%. In addition, the impact sensitivity, friction sensitivity, and electrostatic spark sensitivity of the synthesized epsilon-CL-20 were 4.23 J, 84 N, and 0.072 J, respectively.
PURPOSE:This study explores the experiences of school-age children with chronic illnesses in Türkiye. METHOD:The sample consisted of 27 students aged 8-14 in Türkiye: nine with type 1 diabetes, eight with asthma, eight with allergies, and two with epilepsy. Data were collected through semi-structured interviews using a form developed by the researcher and analyzed via Interpretative Phenomenological Analysis. RESULTS:The analysis revealed six categories: (1) school, (2) psychosocial factors, (3) friends, (4) teachers, (5) family, and (6) information and support resources. CONCLUSION:Students reported the need for supportive relationships and open communication for illness management. Concerns about school absenteeism during the diagnosis and treatment periods were common, with a call for greater tolerance from school personnel. Worries about the future-especially regarding careers-were frequently expressed. Some participants experienced peer bullying and expected counselor intervention, yet most had not received support due to a lack of counselor awareness. Mothers were typically identified as the main caregivers, and children expressed both gratitude and guilt. IMPLICATIONS FOR PRACTICE:Action plans involving all stakeholders should be developed for the management of chronic illnesses in schools, and school counseling services should be made more inclusive in order to provide psychosocial support to children.
This study examines how research and development (R D) activities influence firm efficiency and how human capital moderates his relationship within Taiwan’s 5G industry. Motivated by limited empirical evidence on how R D translates into operational outcomes through workforce capabilities, the research draws on the resource-based view and human capital theory. A dynamic network Data Envelopment Analysis (DEA) model is applied to evaluate innovation, profitability, and overall efficiency using panel data from 27 publicly listed 5G-concept firms over 2013–2023. Patent data were obtained from the Taiwan Intellectual Property Office, and financial data from the Taiwan Economic Journal, while human capital was measured by the average years of employee service. The findings show that firms with higher innovation efficiency exhibit significantly greater profitability efficiency, and that human capital amplifies this positive relationship. These results highlight the pivotal role of experienced and stable workforces in transforming R D inputs into profitable outcomes, particularly during periods of technological and environmental uncertainty. Theoretically, the study advances the innovation and efficiency literature by integrating dynamic efficiency measurement with a moderating perspective of human capital. Practically, it underscores the need for strategic investment in workforce retention and development to maximize the returns from R D. The study’s novelty lies in combining a dynamic network DEA framework with moderation analysis to capture the compounded effects of innovation and human capital in a rapidly evolving high-tech industry.
We present a systematic QCD sum-rule analysis of the in-medium properties of the charged kaon doublet K-+/- over the full (T, rho) plane relevant to current and forthcoming heavy-ion experiments. Working within the QCD sum-rule framework and incorporating temperature- and density-dependent quark, gluon, and mixed condensates, we derive Borel-transformed sum rules for the effective masses m(K +/-), the pseudoscalar decay constants f(K +/-), and the vector self-energy Sigma(nu) of both charged states simultaneously. Our vacuum results, m(K)- = 494.6(-6.9)(+4.9) MeV and f(K)- = 157.3(-2.9)(+4.1) MeV (with near-degenerate Kthorn values), are in excellent agreement with Particle Data Group values at the subpercent level. In the medium, m(K)+/- decreases monotonically with increasing baryon density and temperature, signaling progressive partial restoration of chiral symmetry. A pronounced mass splitting Delta m = m(K-) - m(K+) mKthorn develops in baryonic matter, driven by the opposite sign of theWeinberg-Tomozawa vector interaction for the two charge states; it reaches vertical bar Delta m vertical bar similar to 0.35 GeV near rho similar or equal to 3.2 rho(sat) at T = 0 and is partially quenched by thermal fluctuations. A central outcome of this study is the extraction of the critical onset density rho(c), defined as the threshold beyond which the in-medium modifications of K- properties signal the onset of the transition toward the chirally restored phase. We stress that rho(c)(T) should not be interpreted as a precise determination of the QCD critical point-a task beyond the reach of any current effective framework-but rather as an indicator of the density regime where hadronic descriptions begin to break down and quark degrees of freedom become increasingly relevant. With this interpretation, our results reveal a pronounced temperature dependence: rho(c) similar or equal to (1.2-1.4)rho(sat) for T less than or similar to 100 MeV, reflecting the robustness of the hadronic phase under cold compression, and a sharp reduction to rho(c) similar or equal to 0.45 rho(sat) near the pseudocritical temperature T-c similar or equal to 155 MeV. This dramatic downward shift reflects the synergistic destabilization of the chiral condensate by combined thermal and density fluctuations, and establishes temperature as a more efficient driver of chiral restoration than baryon density alone in the regime accessible to current experiments. Our findings provide quantitative, QCD-based theoretical input for interpreting kaon observables at HADES/GSI, CBM/FAIR, STAR/RHIC, and NA61/SHINE/CERN-SPS, and carry direct implications for kaon condensation in neutron star matter and the hadronic equation of state at supranuclear densities.
