The convergence of communication and intelligence is initiating a revolutionary and disruptive transformation of the communication system. This paper first analyzes the current research of communication and artificial intelligence technologies, highlighting the necessity of their deep integration. It then presents an original paradigm called ComAI, and discusses on its guiding theory, namely semantic information theory, which reveals that synonymy is the essential characteristic of semantic information. Starting from the concept of synonymous mapping, a semantic information measurement system is constructed, and the semantic source coding theorem, semantic channel coding theorem, and semantic rate-distortion coding theorem, semantic channel coding, and semantic rate−distortion coding are proved. Furthermore, a series of key technologies of the ComAI system are discussed. Finally, it outlines the future application prospects of ComAI. To support the construction of China's intelligent communication infrastructure system, it is imperative to achieve breakthroughs in core technologies and enhance China's overall competitiveness in the field of information and communication.

With the acceleration of urbanization, light pollution caused by the widespread use of artificial light at night (ALAN) has become a global environmental issue. Early research on the ecological impacts of light pollution primarily focused on a limited number of vertebrate taxa but has since expanded to encompass diverse taxonomic and ecological groups. Here, we systematically review the impacts of light pollution across different ecological groups, including potential threats to human health, disruptions of animal circadian rhythms and behavior, alterations in plant phenology and physiological processes, and changes in microbial community composition and function. The ecological effects of light pollution exhibit strong species specificity and context dependence, with response intensity being influenced by light intensity, spectral composition, and exposure conditions. Despite considerable advances, our understanding of the mechanisms underlying ecological responses to light pollution and its long−term consequences at higher levels of ecological organization remains limited. Future research should further elucidate the mechanisms driving ecological responses to light pollution, improve our capacity to predict ecological risks, and advance ecologically friendly lighting technologies and management strategies to address the growing challenges posed by light pollution.

Light exposure is a critical environmental factor influencing human circadian rhythms, emotional regulation, and metabolic health. In recent years, it has become a central variable in the field of healthful lighting research. As relevant studies continue to accumulate, methodological paradigms are evolving from static to dynamic approaches, and from environment−based to individual−centered models. This paper reviews the development of light exposure research across four dimensions: theoretical mechanisms, indicator systems, measurement techniques, and health−related evidence. By summarizing five mainstream research paradigms, the paper identifies an ongoing shift from short−term experiments based on predefined lighting conditions to dynamic modeling of ocular light exposure in real−life settings, namely the concept of personal light exposure history. Further analysis reveals three major challenges facing the field: insufficient tools for measuring long−term health effects, a lack of standardized data frameworks for individualized exposure, and the high cost of accurate exposure history acquisition. In response to these issues, the paper proposes a development pathway focusing on high−fidelity measurement, data structure design, and predictive modeling. On this basis, a framework for light pollution assessment and governance is further developed, with personal light exposure history as its core. This framework proposes using individual health risk as the basis for quantifying pollution intensity, enabling a shift from measurability to evaluability and controllability in lighting governance. The study provides a theoretical foundation and methodological support for advancing both the mechanistic understanding and practical implementation of healthful lighting.

Global urbanization has intensified exposure to artificial light at night (ALAN), which has emerged as a public health concern due to its threats to human health. This paper reviews domestic and international studies over the past two decades, summarizing research progress on the health effects of nighttime light pollution from three perspectives: macro−level spatial associations, individual health effects, and underlying mechanisms. At the macro level, we focus on studies using nighttime light remote sensing data to assess the association between ALAN exposure and disease risk, as well as related methodologies. Findings reveal significant spatial heterogeneity in nighttime light exposure, with higher exposure levels in densely built−up urban areas, potentially increasing health risks. At the individual level, existing research concentrates on vulnerable populations such as pregnant women, adolescents, the elderly, and night−shift workers, who are more sensitive to nighttime light exposure. The risk for night−shift workers increases with length of service. Across different populations, a clear trend emerges: higher exposure levels are associated with greater health damage risk, with spectral composition, exposure timing, and exposure duration further influencing the magnitude of health effects. At the mechanistic level, ALAN can disrupt suprachiasmatic nucleus (SCN) function via the non−image−forming visual pathway, suppress melatonin secretion, and trigger metabolic disorders, mental health impairment, and increased tumor risk through pathways including immune−inflammatory imbalance, sleep disturbance, hypothalamic−pituitary−adrenal (HPA) axis stress response, and metabolic circadian desynchrony. Finally, the paper proposes constructing a multi−scale exposure assessment system that integrates multi−source data to elucidate mechanisms and thresholds, and to promote a shift in light pollution prevention and control toward coordinated management encompassing spectral optimization, temporal control, spatial zoning, and protection of sensitive populations.

In recent years, economic development has driven rapid progress in urban and rural construction, alongside a growing public demand for stargazing activities, which have also become an important way to cultivate the spirit of exploration in young people. Due to the absence of national standards such as the Specification for Limiting Interference Light from Outdoor Lighting, the construction industry has used outdoor lighting in industrial, civil, and cultural landscape projects with considerable flexibility. This has led to the rapid expansion of light pollution caused by excessive artificial lighting at an annual rate of 7% to 10%. Light pollution not only exerts widespread effects on natural ecosystems but also poses a serious threat to scientific research that depends on dark skies—particularly astronomical observation—while diminishing the public stargazing experience. Monitoring in urban areas relies on costly fixed−point observation, whereas astronomical observatories have established continuous monitoring systems. This paper takes China's Xinglong, Lijiang, and Lenghu observatories as case studies to analyze the impact of light pollution on the efficiency and effectiveness of astronomical observation and compares their distinct approaches to light pollution control. The findings reveal that light pollution significantly reduces observatory performance and impairs the detection efficiency of deep−sky objects. The three sites have adopted different control strategies: Xinglong Observatory employs a mitigation model through light shielding and source optimization, Lijiang Observatory has developed a coordination model integrating with tourism development, and Lenghu Observatory has implemented a rigid governance model based on local legislation. By synthesizing these practical pathways, this study offers valuable experience and policy references for the protection of dark night skies amidst global urbanization.

With the widespread application of artificial nighttime lighting in urban areas, light pollution has become a global environmental issue, posing serious threats to human physical and mental health, the living rhythms of flora and fauna, and the stability and balance of entire ecosystems. Scientific, precise, and efficient light environment monitoring plays a crucial supporting role in source prevention and control, governance improvement, and long−term management. A review of frontier advances in technical innovation and monitoring network construction, both domestically and internationally, indicates that space−air−ground integrated monitoring is becoming the mainstream approach, and the application of emerging intelligent technologies will enhance the accuracy of light environment identification and classification. Future light environment measurement technologies are evolving towards greater precision, standardization, coordination, and intelligence. In view of the current state of light pollution monitoring in China, it is necessary to further refine policies and standards, promote the application of monitoring technologies, and accelerate the construction of a “space−air−ground” integrated monitoring network, thereby providing Chinese technical solutions for the modernization of light pollution governance.

With the rapid development of urbanization, the problem of light pollution is becoming increasingly prominent and receiving widespread attention from the whole society. Satellite remote sensing, due to its technological advantages such as large−scale continuous dynamic observation, has become an important technical means for monitoring and regulating light pollution. This article analyzes the existing problems and challenges in three aspects: stereoscopic detection capability, monitoring and assessment analysis, and precise source tracing applications through satellite remote sensing monitoring in light pollution regulation and prevention. It also proposes that in the future, by improving the standard system for light pollution monitoring and evaluation, optimizing the three−dimensional monitoring network, and developing intelligent traceability technology, China's urban light pollution satellite remote sensing monitoring and supervision capabilities can be further enhanced to support zoning control and targeted governance of light pollution.

In large cities, glass curtain walls are widely used owing to their advantages such as aesthetic appeal, energy efficiency and practicality. However, the negative impacts of their reflected light on the surrounding environment have become increasingly prominent, mainly reflected in glare interference on windows of sensitive buildings including residences, hospitals and schools, as well as potential hazards to traffic safety on main roads. To effectively control the impacts of reflected light, China currently requires newly built glass curtain wall projects to conduct light reflection impact assessment. By calculating and predicting the incident angle, influence region and duration time of reflected light, the assessment verifies whether relevant standards are met and formulates targeted prevention and control measures. This paper reviews the standard systems, analytical methods and regulatory requirements concerning light reflection from glass curtain walls, and distinguishes the impact mechanism and typical scene of light reflection. It also systematically introduces the current calculation methods and assessment procedures for light reflection impact assessment in China. Finally, in view of the management deficiencies and technical bottlenecks encountered in assessment practice, this paper puts forward optimization suggestions and future research directions.

With the acceleration process of urbanization, artificial light at night(ALAN) has become an essential supporting component for the operational and sustainable development of modern cities. Nevertheless, the widespread prevalence of ALAN has triggered increasingly severe urban light pollution problems. Existing research on light pollution has long been confined to the paradigm of localized monitoring and single−dimensional evaluation, lacking cross−scale and multi−dimensional systematic integration. This limitation has become a critical bottleneck hindering the refined governance of urban light pollution. This paper systematically reviews the research background and current progress of urban nighttime light pollution studies, and identifies the prominent challenges in current research: an incomplete evaluation index system that fails to fully cover the diverse and complex receptors of the light pollution, fragmented technical research methods, and the lack of a comprehensive monitoring mechanism.

As river geomorphology research increasingly relies on large−scale literature integration and analysis, the challenge of extracting structured knowledge from unstructured texts has become central to advancing digital and semantic approaches in geomorphological science. This study proposes a GPT−based method for automatic knowledge extraction in the field of fluvial geomorphology. A structured Few−shot prompt framework was designed to guide the model in identifying geomorphic entities and their relations, enabling the generation of standardized knowledge triples in the form of <entity₁, relation, entity₂>. The workflow consists of corpus preparation, prompt engineering, model invocation, and structured output. Applied to 30 high−quality English−language journal articles, the approach extracted a total of 7605 knowledge triples, encompassing 22815 entities and relations. Evaluation results demonstrate that the method achieves high accuracy (Precision=0.834), good recall (Recall=0.789), and stable overall performance (F1=0.862). Nonetheless, limitations remain in the handling of abstract logic, long−range dependencies, and relation directionality. Future improvements may involve domain−specific model fine−tuning, integration of geographic ontologies, and multimodal data fusion. This research provides a practical solution for intelligent knowledge construction in fluvial geomorphology and expands the methodological toolkit at the intersection of geographic information science and artificial intelligence.

Rocky desertification is a core issue restricting the coordinated development of the ecological environment and socio−economy in the karst regions of southwestern China. To address the limitations of traditional evaluation methods—such as high subjectivity and difficulty in quantification—this study proposes an intelligent quantitative evaluation model for rocky desertification by integrating logistic regression and spatial analysis techniques. A case study was conducted in Bijie City, Guizhou Province. Based on the evolution process and formation mechanism of rocky desertification, this study selects 12 candidate factors from both natural and human dimensions. Logistic regression models are then used to analyze the significance of these factors' influence on rocky desertification and the threshold for classifying its states. Ultimately, five key factors—vegetation cover, bedrock exposure, slope, surface roughness, and profile curvature—are identified as the foundation for model construction. The evaluation model integrates the entropy weight method to adaptively assign weights to the factors, and intelligently accomplishes the spatial distribution and severity classification of rocky desertification on the GIS platform. Accuracy validation shows a classification accuracy of 82.6% and a Kappa coefficient of 0.76, effectively revealing the spatial distribution and differentiation patterns of rocky desertification in Bijie. This method, through threshold quantification, weight optimization, and multi−source data fusion, provides foundational data for dynamic monitoring and differentiated management of rocky desertification in karst areas. It holds significant practical value for advancing ecological restoration and regional sustainable development.

The problem of urban light pollution in China is becoming increasingly prominent, and accelerating the improvement of the system for preventing and controlling light pollution has become an urgent need. This article systematically reviews the regulations, policies, and practical experience of light pollution prevention and control in typical international countries and regions, and deeply analyzes the current situation, management system, and institutional standards of light pollution prevention and control in China. The study proposes to strengthen joint supervision among multiple departments, clarify the responsibilities of departments such as ecological environment, housing and construction, and transportation, and implement the responsibilities of source prevention and control and local government zoning management; Accelerate the improvement of the institutional system centered on overall planning, source prevention and control, classified management, and zoning control (requiring strict protection of special protection areas), and strengthen the promotion of green lighting and public participation supervision; synchronize and improve key standards such as light environment quality, emission limits, monitoring and evaluation, and zoning control, build a scientific, rigorous, collaborative and efficient light pollution prevention and control system, and continuously enhance governance capabilities and levels.

Wang Mianzhi, a recipient of the inaugural title of "Master of Chinese Medicine" and a tenured professor at Beijing University of Chinese Medicine, was the principal founder and pioneer of the discipline of Formulas of Chinese Medicine in China. Born into a distinguished family of traditional Chinese medicine practitioners in Nantong, Jiangsu Province, he was the 19th−generation heir of the Wang family's medical tradition. He served as editor−in−chief of the first nationally unified textbook of Formulas of Chinese Medicine, established the organizational principle of "formulas governed by therapeutic methods," and made the discipline a core course in Chinese medicine education. Academically, he advocated that "formulas derive from therapeutic methods, and methods are established according to pattern differentiation," emphasizing the study of formula theory and the flexible modification of classical formulas. He was highly skilled in treating refractory and serious diseases such as immune−related infertility and aplastic anemia. He also introduced traditional Chinese medicine into China's manned spaceflight program by developing the "Taikong Yangxin Wan" (Space Heart−Nourishing Pill), which effectively improved astronauts' cardiovascular function and metabolic status, contributing to the success of the Shenzhou−5 and Shenzhou−6 missions. Throughout his life, Wang Mianzhi devoted himself to theoretical research, clinical practice, textbook development, and the training of talent in the field of Formulas of Chinese Medicine, making indelible contributions to the establishment and advancement of this discipline and to the modernization and internationalization of traditional Chinese medicine.