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The spatial coupling and its influencing mechanism between rural human-habitat heritage and key rural tourism villages in China
Exploring the influencing factors and its influencing mechanism of the spatial coupling between rural human-habitat heritage (RHH) and key rural tourism villages (RTV) at county scale from the perspective of space can expand the theoretical research on the spatial coupling mechanism between RHH and RTV, and further provide theoretical reference and data support for the coordinated development and high-quality development of RHH and RTV in China. At the same time, previous studies have failed to systematically analyze the influencing factors and influencing mechanisms of the spatial coupling between RHH and RTV at the county scale, which restricted decision makers from formulating coordinated development measures between RHH and RTV at the macro level. In this study, bivariate spatial autocorrelation model and spatial coupling coordination model were used to quantitatively analyze the spatial coupling level between RHH and RTV at the county scale in China. Then, the linear regression (OLS) model, geographically weighted regression (GWR) model, and optimal parameter GeoDetector (OPGD) model were integrated to systematically analyze the linear influencing, spatial heterogeneity effect and interactive effect of natural environment and socioeconomic factors on the spatial coupling level between RHH and RTV in China, and explore the interactive influencing mechanism. The results show that the spatial coupling level of RHH and RTV in China show a significant east-west differentiation. There were 2024, 473, 293, 55 and 6 areas of severe, moderate, mild, basic and moderate coordination between RHH and RTV, respectively. Among them, severe and moderate discoordination areas are mainly distributed in Northeast China, arid and semi-arid areas in Western China, plateau areas in Southwest China, densely populated urban agglomerations and plains agricultural areas in the Middle East China. Mild discoordination areas and basic and moderate coordination areas are mainly located in transition zones in mountainous and plain areas, economically developed mountainous and hilly counties along the southeastern coast, and coastal tourist cities. Economic and population factors are the fundamental factors that affect the spatial coupling between RHH and RTV. Rural tourism facilities and rural public service facilities are important external driving forces for the coupling development of RHH and RTV, and Sociocultural environment factors are the important internal driving forces. Different surface forms, different climate conditions and different ecological environment conditions can form different natural textures and spatial organizations. Suitable climate conditions, sufficient water sources and ecological environment conditions can form more suitable rural settlement construction conditions and production and living conditions, and ultimately affect the protection and activation of rural human settlement heritage and the development and layout of key tourist villages. The spatial coupling relationship between RHH and RTV is the result of the complex interaction between the natural directivity law caused by natural environmental factors and the humanistic directivity law caused by human social and economic activities.
Efficient computation using spatial-photonic Ising machines with low-rank and circulant matrix constraints
Spatial-photonic Ising machines (SPIMs) have shown promise as an energy-efficient Ising machine, but currently can only solve a limited set of Ising problems. There is currently limited understanding on what experimental constraints may impact the performance of SPIM, and what computationally intensive problems can be efficiently solved by SPIM. Our results indicate that the performance of SPIMs is critically affected by the rank and precision of the coupling matrices. By developing and assessing advanced decomposition techniques, we expand the range of problems SPIMs can solve, overcoming the limitations of traditional Mattis-type matrices. Our approach accommodates a diverse array of coupling matrices, including those with inherently low ranks, applicable to complex NP-complete problems. We explore the practical benefits of the low-rank approximation in optimisation tasks, particularly in financial optimisation, to demonstrate the real-world applications of SPIMs. Finally, we evaluate the computational limitations imposed by SPIM hardware precision and suggest strategies to optimise the performance of these systems within these constraints.
Human-structure and human-structure-human interaction in electro-quasistatic regime
Augmented living equipped with electronic devices requires widespread connectivity and a low-loss communication medium for humans to interact with ambient technologies. However, traditional radiative radio frequency-based communications require wireless pairing to ensure specificity during information exchange, and with their broadcasting nature, these incur energy absorption from the surroundings. Recent advancements in electroquasistatic body-coupled communication have shown great promise by utilizing conductive objects like the human body as a communication medium. Here we propose a fundamental set of modalities of non-radiative interaction by guiding electroquasistatic signals through conductive structures between humans and surrounding electronic devices. Our approach offers pairing-free communication specificity and lower path loss during touch. Here, we propose two modalities: Human-Structure Interaction and Human-Structure Human Interaction with wearable devices. We validate our theoretical understanding with numerical electromagnetic simulations and experiments to show the feasibility of the proposed approach. A demonstration of the real-time transfer of an audio signal employing an human body communications-based Human-Structure Interaction link is presented to highlight the practical impact of this work. The proposed techniques can potentially influence Human-Machine Interaction research, including the development of assistive technology for augmented living and personalized healthcare.
DeepPrep: an accelerated, scalable and robust pipeline for neuroimaging preprocessing empowered by deep learning
Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing substantial computational challenges. Here we present DeepPrep, a pipeline empowered by deep learning and a workflow manager. Evaluated on over 55,000 scans, DeepPrep demonstrates tenfold acceleration, scalability and robustness compared to the state-of-the-art pipeline, thereby meeting the scalability requirements of neuroimaging.
Dissecting the complexity of local and systemic circadian communication in plants
The plant circadian clock regulates daily and seasonal rhythms of key biological processes, from growth and development to metabolism and physiology. Recent circadian research is moving beyond whole plants to specific cells, tissues, and organs. In this review, we summarize our understanding of circadian organization in plants, with a focus on communication and synchronization between circadian oscillators, also known as circadian coupling. We describe the different strengths of intercellular coupling and highlight recent advances supporting interorgan communication. Experimental and mathematical evidence suggests that plants precisely balance both the circadian autonomy of individual cellular clocks and synchronization between neighboring cells and across distal tissues and organs. This complex organization has probably evolved to optimize the specific functions of each cell type, tissue, or organ while sustaining global circadian coordination. Circadian coordination may be essential for proper regulation of growth, development, and responses to specific environmental conditions.
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