Chinese Culture University

Abstract This study evaluates the performance of CMIP6 models in simulating synoptic-scale fronts and their associated precipitation over East Asia, with a focus on winter, spring, and the Taiwan mei-yu season. A modified front detection method incorporating low-level cyclonic shear improves the identification of mei-yu fronts. Results show that CMIP6 models reasonably reproduce the spatial distribution of frontal activity but underestimate the frequency of fronts and frontal precipitation in southern China, while overestimating frontal activity over Japan during the Taiwan mei-yu season. Future projections under shared socioeconomic pathway 5-8.5 (SSP5-8.5) indicate a decline in front frequency and frontal precipitation over key regions, particularly southern China and Taiwan, especially during winter and spring. In contrast, the Taiwan mei-yu season exhibits an increasing front frequency near Taiwan through the midcentury, followed by a growing intermodel spread. Frontal precipitation generally follows these trends, while total precipitation increases more broadly across East Asia. The discrepancy between frontal and total precipitation suggests a shift in dominant precipitation regimes, with a decreasing contribution from frontal systems and a potential increase in convective or nonfrontal rainfall. These changes, linked to weakened temperature gradients and altered moisture transport, present challenges for regional water security and highlight the need for improved frontal representation to support reliable hydrological projections and climate adaptation in East Asia. Significance Statement Frontal systems play a crucial role in shaping seasonal rainfall; however, their frequency, location, and hydrological impacts remain difficult to simulate in global climate models. This study presents an improved front detection method that enhances the identification of mei-yu fronts. Using CMIP6 simulations, we evaluate model performance and future projections under a high-emission scenario. While frontal activity and precipitation are projected to decrease over regions of frequent fronts during winter and spring, mei-yu frontal precipitation is expected to increase over southern China and Taiwan. These results underscore the importance of enhancing frontal representation in climate models and provide valuable insights for water resource planning and climate adaptation in East Asia.

Urban regeneration frequently encounters a critical trade-off: whether to accelerate planning and implementation of design solutions or safeguard participation. To address this challenge, the paper introduces the concept of the governance “grey zone”—an informal yet institutional interface that flexibly reconfigures the relationship between planning and design to transcend the impasse. This perspective is grounded in an analysis of the recent urban regeneration of Hsinchu City, where a weekly, mayor-led coordination forum with external consultants functioned as an informal yet institutional organizational hub. This forum broke down departmental silos, unified multiple design teams under shared principles, and expedited implementation of numerous projects—all while maintaining public scrutiny and inclusivity. The study draws on interviews with high-profile administrators, planners, and designers involved in Hsinchu’s regeneration, as well as official documents. Elaborating on this, the paper finally advances a set of implications regarding urban regeneration scholarship with attention to aspects of urban design governance.

Abstract Stratosphere‐troposphere exchange (STE) plays a crucial role in Earth's climate; however, the significance of small‐scale processes such as midlatitude convection to global STE remains understudied. Midlatitude tropopause‐overshooting convection is especially important to climate because it can enhance stratospheric water vapor, which has its greatest radiative forcing sensitivity in the extratropical lower stratosphere. Thus, it is essential to understand what factors influence the strength and prevalence of overshooting storms and associated STE. The U.S. Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign during 2021 and 2022 was the first large‐scale airborne primarily focused on sampling stratospheric impacts from overshooting convection. Our research utilizes the extensive DCOTSS data set in combination with radar, satellite, and environmental observations to investigate relationships between observed stratosphere composition change and storm and environmental characteristics. Our results demonstrate greater magnitudes of STE for above‐anvil cirrus plume (AACP)‐producing storms and mesoscale convective systems (MCSs). In addition, the most extreme enhancements in water vapor and other tropospheric gases occur where the tropopause height is low and the depth of overshooting is high, especially for AACP‐producing storms. We also investigate the impact of storm and environmental characteristics on pathways for hydration (air mass transport and mixing vs. ice sublimation), finding that they also modulate the frequencies of each process at different altitudes. Namely, mixing is found to be most prevalent in AACP‐producing storms and MCSs, which can help explain transport differences between water vapor and other gases.

ABSTRACT This study examines Environmental, Social, and Governance (ESG) performance as a context‐contingent strategic capability, whose efficiency payoffs depend on market rivalry and internationalization. Drawing on the Resource‐Based View and Stakeholder Theory, we investigate how competitive intensity (CI) and degree of internationalization (DOI) jointly shape the ESG–efficiency relationship in the global clothing industry. Using a two‐stage network data envelopment analysis (NDEA) on 280 firm‐year observations from 56 listed apparel firms between 2019 and 2023, we assess operational eco‐efficiency (OE) and profitability efficiency (PE). The results indicate that ESG is associated with stronger efficiency gains under intense market rivalry, but exhibits diminishing returns as internationalization increases, amplifying disclosure and legitimacy pressures without proportional operational improvements. This pattern reveals a legitimacy–efficiency gap in highly internationalized contexts. Further analysis shows that ESG delivers its strongest efficiency benefits when it is deeply embedded within firms and aligned with both competitive and global institutional conditions. Overall, the findings advance a context‐dependent capability view of ESG and provide strategic guidance for aligning sustainability investments with competitive and institutional environments to enhance operational and financial performance.

Rural sustainability is key to maintaining prosperity in developed rural areas, yet many existing evaluation methods focus on material resources while overlooking villagers’ perceptions. This study introduces an ecological–livelihood–perception ( ELP ) model that extends the sustainable livelihoods framework (SLF) by refining its natural capital dimension to explicitly incorporate ecological quality and villagers’ environmental perceptions, alongside a psychological perception derived from a self-fulfilling prophecy theory. We conducted a structured survey of 100 households in Guoliang village. Then, 21 standardized indicators spanning the natural, financial, physical, social, human, and ecological dimensions were introduced to evaluate the survey data. After reliability screening, principal component analysis (PCA) was applied to construct a single composite score for each capital, capturing the dominant variance in the data without multicollinearity. PCA combined with entropy-based weighting was applied to reduce collinearity and derive indicator weights. Descriptive results show that normalized indicator means range from 0.15 to 0.86, and indicator weights are relatively balanced, ranging from 0.044 to 0.051, with the highest-weight indicator reaching 0.051. The sustainable individual perception ( SIP ) index was calculated from qualitative items and was linked to the six capital scores through an ordinary least squares regression. The results reveal a threshold pattern: once a basic level of natural capital is met, it leads to further gains, especially in social and ecological assets, which are strongly associated with higher psychological optimism. Households exhibiting high SIP consistently possess balanced and multidimensional capital portfolios, whereas those with low SIP show deficits across most dimensions. The ELP model, therefore, provides a more comprehensive tool for rural sustainability evaluation by integrating objective livelihood assets with subjective perceptions, offering practical insights for targeted policy interventions and development strategies.

This study systematically investigated the influence of approach kinematics on the subsequent kinetics and power production strategies during the approach to running jumps with a single leg (ARJSL). Twenty-five physically active male university students performed ARJSL trials under two prescribed approach speeds (fast and slow) and three approach distances (3, 6, and 9 m) in a 2 × 3 within-subjects design. Three-dimensional motion capture synchronized with force platform data was used to quantify jump height (JH), vertical touchdown velocity (TDv), reactive strength index (RSI), peak joint power (hip, knee, and ankle), and joint stiffness. Significant approach speed × distance interactions were observed for JH (p = 0.006), TDv (p < 0.001), RSI (p = 0.014), ankle stiffness (p = 0.006), and peak power generation at all lower-limb joints (all p < 0.034). The results demonstrate that changes in approach strategy systematically alter the distribution of mechanical power among the hip, knee, and ankle joints, thereby influencing the effectiveness of horizontal-to-vertical momentum conversion during take-off. Notably, RSI and ankle stiffness were particularly sensitive to combined manipulations of speed and distance, highlighting their value as neuromechanical indicators of stretch–shortening cycle intensity and joint loading demands. In conclusion, ARJSL performance depends on finely tuned, speed- and distance-specific biomechanical adaptations within the lower extremity. These findings provide a constrained, joint-level mechanical characterization of how approach speed and distance interact to influence power redistribution and stiffness behavior during ARJSL, without implying optimal or performance-maximizing strategies.

Recent advances in computer-generated holography (CGH) have significantly improved visual quality through high-resolution rendering; however, the accompanying increase in data size has become a critical obstacle to practical deployment. Conventional image compression techniques such as JPEG and high efficiency video coding (HEVC) do not adequately account for the unique statistical and spectral characteristics of holograms, thereby limiting both compression efficiency and reconstruction quality. This study proposes an efficient compression framework specialized for digital holograms by integrating a ringing reduction technique for diffraction calculations with CompressAI, a deep learning-based image compression framework. We demonstrate that ringing artifacts are a major factor hindering efficient hologram compression, and show that neural networks can achieve superior performance by learning the intrinsic statistical and spectral features of holograms. Our method achieves a superior balance between compression efficiency and reconstruction quality compared to conventional approaches, particularly at low bit rates. Furthermore, by introducing a multi-channel input representation, our method achieves higher compression ratios.