With China's "Dual Carbon" goals (carbon peaking by 2030 and carbon neutrality by 2060) entering a critical implementation window, the next five years represent a decisive phase for determining the success of this transition. As one of the core supports of clean energy systems, electrochemical energy technology is witnessing unprecedented development opportunities. Based on the latest policy orientations and technological trends, this study analyzes the current status, target pathways, and strategic actions for electrochemical energy storage and conversion against the "countdown" backdrop of the Dual Carbon initiative. Against the escalating global climate crisis and growing energy security concerns, clean energy has emerged as a central direction for the worldwide energy transition. The development of clean energy not only helps reduce dependence on fossil fuels and cut greenhouse gas emissions but also promotes the diversification of energy mix and enhances energy security. Consequently, the clean energy sector is facing new development opportunities and challenges. This study aims to provide a systematic exploration of the development status, technological innovations, market trends, and application prospects across five key areas: electrocatalysis, solar cells, fuel cells, lithium batteries, and bioenergy, thereby offering insights to support the further deployment and sustainable development of clean energy.

The dual pressures of urbanization and climate change are intensifying the urban heat island effect, carbon emissions, and air pollution, posing significant challenges to environmental sustainability and urban livability. As the demand for multiobjective coordinated management of urban ecological environments continues to increase, integrating heat, carbon, and pollution into a unified framework for comprehensive assessment has become a key direction for future urban planning and policy−making. This article systematically compares and analyzes the consistency between global development agendas and the goals of reducing urban heat, carbon, and pollution, highlighting the significant potential and advantages of new−generation information technologies in intelligent optimization and coordinated scheduling, data fusion and analysis, real−time monitoring and feedback, and decision support and simulation. From the new perspective of urban spatial form, it comprehensively reviews the specific content, challenges, and future issues in conducting multi−scale, multi−dimensional "heat−carbon−pollution" multi−objective coordinated reduction planning. It provides innovative solutions for multi−objective coordinated management and sustainable development of "heat−carbon−pollution" in Chinese cities.

Hydrogen energy, recognized globally as a clean energy source, demonstrates significant potential in supporting climate commitments and energy transition. Driven by the "dual carbon" target, China's hydrogen energy industry has entered a rapid development phase. This paper focuses on emerging hydrogen energy application sectors, such as transportation, electricity, and construction. Relevant policies and cases from several developed countries in recent years are summarized. Current status and achievements of domestic hydrogen energy applications in the three sectors are reviewed and also some key issues. Finally, a development pathway for hydrogen energy which conforms to China's national conditions and some forward−looking recommendations are proposed. The purpose of this paper is to provide support for the steady development of hydrogen energy in China.

This paper systematically reviews the concept of green methanol fuel, and conducts a comparative analysis of the main manufacturing technology paths, emission reduction potential, as well as the advantages and disadvantages for the major routes, including the biomass path, the electricity−based path and the electricity−biomass coupling path, etc. We summarize the relevant policies on methanol fuel for the water transportation industry at the national and industry levels, clearly stating to promote the pilot application of methanol fuel in coastal and inland river vessels, and to accelerate the construction of methanol refueling stations, storage facilities and other supporting facilities. A review has been conducted of the current green methanol−related standards in China, including guidelines for methanol fuel for ships and group standards focusing on the evaluation of green methanol and the carbon footprint assessment of green methanol products. Related policies and standards are still in the initial stage. At the same time, based on the low−emission analysis platform LEAP, a comprehensive assessment model for carbon emissions prediction of China's water transportation industry is constructed to quantitatively calculate the total energy consumption and carbon emissions of China's water transportation industry in the medium and long term. It is estimated that the total energy consumption will be about 58~85 million tce, and the total emissions will decrease to 30~120 million tons CO₂. Based on the above analysis, suggestions for the future development of marine green methanol fuel industry in China are proposed, including: continuously tracking and deeply participating in the IMO’s negotiations on the net−zero framework and related rules construction; combining the internal and external water industry advantages to conduct in−depth quantitative research on the dual−carbon transformation path of the water industry; and taking the lead through trials and experiments, step by step to systematically promote the development of green methanol in China.

Methanol as fuel, particularly for the green methanol by its clean burning characteristics and easy availability with liquified energy as well as abundant application scenarios is assist it transform from shipping, transportation and industry and so on to the global energy transition as well as realization for the goal of "Double Carbon". According to the transformation of methanol from chemical to fuel, the review reports that various forms of methanol as fuel are used in industry and power units respectively, particularly introducing the status of usages in internal combustion engines and their technical characteristics in applications for reference in futural development. Taking the advantage of the huge productive capability of our country, and promoting the green methanol application as well as its development, many proposals are provided based on the following issues such as the policy support and technical improvements and so on.

Biological carbon fixation is crucial to the Earth's carbon cycle and is one of the effective ways to transform CO₂ and manage carbon emissions. Chemoautotrophs, with their unique metabolic strategies and environmental adaptability, play an important role in this process. They are able to convert CO₂ into valuable organic products, solving the problem of limited CO₂ utilization. However, the carbon fixation potential of chemoautotrophs in controlled systems has not been fully explored. This review illustrates the possible challenges of stable culture of chemoautotrophic bacteria in bioreactor. Based on this, a series of physical, chemical and biological methods are proposed to regulate the carbon metabolism of chemoautotrophic bacteria and improve their carbon fixation efficiency. Further, the application prospects of chemoautotrophic carbon fixation in controlled systems are expected, including improving the primary productivity of natural ecosystems, reducing carbon emissions in specific sites, and producing high−value microbial by−products. This review highlights the advantages and challenges of these applications, providing important insights into carbon capture, fixation and conversion by chemoautotrophs.

Oxygen blast furnace (OBF) has many advantages such as a high coal injection rate, reduced coke ratio, lower CO₂ emissions, and improved production efficiency, and is considered one of the most promising low−carbon ironmaking processes for large−scale application. Therefore, it has received extensive research attention. This article analyzes the current state and development trends of OBF research from various aspects, including its development history, industrial experiments, physical models, and mathematical models. Carbon reduction potential of the OBF is analyzed from the perspectives of internal production state production indexes, material flow, and energy flow. It is found that OBF has significant carbon reduction advantages compared to traditional blast furnaces (TBF), and its carbon reduction potential can be further enhanced with CO₂ capture and storage technologies. Then, the progress made by China Baowu Hydrogen−enriched Carbonic oxide Recycling Oxygenate Furnace (HyCROF) was elaborated in more detail. This process achieved a utilization coefficient of 5.0 t/(m³·d), reducing the cost per ton of iron by approximately 150 yuan compared to previous stages. Finally, it looks ahead to accelerating the integration of the "blast furnace−converter" long process by replacing carbon with hydrogen, combining carbon capture and storage (CCS) technology and pure hydrogen reduction technology, so as to build an intelligent, efficient and high−yield development direction for the steel industry. Finally, the direction of low−carbon iron making in China is prospected.

This paper reviews low−carbon metallurgical technologies in China, Japan, and Europe, analyzing the EU's ULCOS project, Japan's COURSE50 project, and various low−carbon technological advancements in China. Countries are actively addressing the carbon reduction challenges in the iron and steel industry by developing technologies such as hydrogen direct reduction, molten reduction, and electrolytic steelmaking. For instance, the ULCOS project aims to reduce CO₂ emissions per ton of steel through top gas recycling and novel direct reduction processes. The COURSE50 project integrates hydrogen injection with CO₂ capture technologies to achieve its reduction targets. Under the "dual carbon" strategy, China has rapidly developed technologies such as hydrogen−rich carbon−circulating blast furnaces and gas−based direct reduction processes, demonstrating significant carbon reduction potential.

In order to achieve green, low carbon and high−quality development of the iron and steel industry, the development and application of low carbon emissions steelmaking technology should be noted. The study systematically analyzes the structural transformation of the current steelmaking process, with a focus on achieving low−carbon operation in the converter process through high scrap steel ratio smelting and the use of clean raw materials such as direct reduced iron (DRI). At the same time, an in−depth analysis was conducted on how electric arc furnace steelmaking technology can move towards the forefront of low−carbon and even "near zero carbon" smelting through technological solutions such as green electricity, intelligent power supply, biomass carbon sources, and reducing auxiliary material consumption. Finally, a systematic low−carbon emission steelmaking development path was proposed from the dimensions of technology integration, policy guidance, and energy structure transformation, providing theoretical support and practical reference for the high−quality and sustainable development of the steel industry.

The production of ferroalloys necessitates the consumption of substantial quantities of alloy materials. Achieving the national "dual carbon" strategic goals and reducing energy consumption in the steel industry necessitates the implementation of scientific and practical methods and approaches for ferroalloy charging. The objective of alloy reduction technology in the steelmaking alloying process is twofold: first, to minimize the use of alloying elements, and second, to reduce production costs, while ensuring that the final steel retains the required properties and characteristics. The present paper introduces the physicochemical properties of ferroalloys and employs drum tests to quantitatively evaluate their pulverization performance. During handling, alloys should be stored in tiered arrangements based on particle size and density to ensure absorption rates. It is imperative to mitigate the occurrence of collisions during storage, transportation, and utilization to avert pulverization losses prior to furnace entry. An intelligent control system for alloy reduction in steelmaking, developed using neural networks and big data models, has been successfully implemented in over ten domestic steel enterprises. The substitution of customized alloy recycling plans, derived from field operation data and process analysis, has been demonstrated to reduce ferroalloy usage costs for steel producers. In the process of smelting particular steel grades, it is imperative to exercise caution with regard to the presence of deleterious elements within the alloy. Concurrently, precise selection should be made based on changes in the main alloy components to reduce cost increases caused by fluctuations in alloy composition. By analyzing current alloy reduction technologies in steelmaking, this study proposes future improvement directions and trends for ferroalloy reduction methods. Initial efforts must concentrate on the enhancement of ferroalloy quality, with the objective of reducing the usage of superfluous alloy elements and averting the squandering of resources. Secondly, the advancement of digitalization and automation technologies has the potential to enhance the stability and controllability of steelmaking operations by enabling the monitoring and control of the alloying process.

As the world's largest steel producer, China's steel industry generates over 1.4 trillion cubic meters of by−product gas annually, which contains energy equivalent to 266 million tons of standard coal. However, currently, the by−product gas from China's steel industry is mainly used as fuel for combustion, remaining at a stage with high carbon emissions and low comprehensive utilization rate. In view of this, to promote the improvement of the utilization efficiency of by−product gas in China's steel industry, this paper elaborates on the composition, calorific value and other characteristics and availability of three core by−product gases: blast furnace gas, coke oven gas and converter gas. It also analyzes the current utilization status and limitations mainly based on fuel combustion, and explores the high−value utilization pathways under the steel−chemical integration and hydrogen metallurgy approaches, including pressure swing adsorption (PSA) and chemical absorption for purifying CO/CO₂, as well as biological fermentation of converter gas and reforming of coke oven gas to produce methanol/ethanol and hydrogen energy. It focuses on the application advantages and practices of coke oven gas in Midrex and Energiron−ZR direct reduction ironmaking. Research shows that by−product gas can be transformed from a single fuel to a chemical raw material through technological upgrades, such as reducing emissions by 10%~20% through high−pressure injection of coke oven gas into blast furnaces, and the feasibility of Baowu's HyCROFTM hydrogen−rich carbon cycle blast furnace technology has been verified. Based on this, it is concluded that the core directions for efficient and low−carbon utilization are steel−chemical integration and synergy, hydrogen metallurgy coupling, and the integration of CCUS technology, which can drive the industry to shift from "carbon metallurgy" to "hydrogen metallurgy" and provide technical support for the green and low−carbon transformation of the steel industry.

Autonomous intelligent unmanned systems operating in real−world open environments—characterized by dynamic complexity, multi−agent coupling, incomplete information, and strong social constraints—face critical challenges such as insufficient compliance modeling, limited social risk perception, complex collaborative conflicts, and delayed abnormal response. To address these issues, this paper proposes an Embodied Social Perception Intelligence Framework, which integrates embodied perception (including proprioceptive, internal, exteroceptive, interactive, and intention perception) with social radar, and introduces Agentic AI as a top−level decision−making and control mechanism to achieve multi−level and autonomous cognitive decision−making. The framework adopts a five−layer architecture—perception, reasoning, execution, feedback, and meta−control—establishing a dynamic closed loop from multimodal perception to compliant behavior generation. By fusing physical and social environmental information, the proposed framework significantly enhances the task adaptability, collective coordination efficiency, and compliance reliability of autonomous intelligent unmanned systems in complex and uncertain scenarios such as urban governance, emergency rescue, and social security. This work provides a new technical pathway toward trustworthy, explainable, and sustainable autonomous intelligent systems.

Embodied intelligence represents a new stage in the evolution of artificial intelligence, marking a transition from "perception−cognition" to an integrated paradigm of "perception−cognition−action." The Vision−Language−Action (VLA) model provides a critical technological pathway for enabling autonomous agent operation in the real world by unifying visual perception, language understanding, and action generation. This paper systematically reviews the development trajectory and representative achievements of VLA technologies, and summarizes their architectural paradigm, which includes multi−modal perception, semantic fusion mechanisms, reinforcement and imitation learning, world models, and hierarchical action output. By considering application scenarios such as autonomous driving, human–computer interaction, and industrial equipment, we further analyze the core challenges faced by VLA development, including the scarcity of data resources, limited generalization and transferability, insufficient interpretability, and increasing computational demands, and we outline the future development trends.

With the convergence and innovation of emerging information technologies, Digital Twin (DT) technology has become a key enabler for digital transformation and the evolution of intelligent systems. It has been widely applied and received significant attention in fields such as industrial manufacturing, smart cities, and intelligent transportation. However, existing research on traditional DT technologies has predominantly focused on the modeling and analysis of physical entities ("objects"), with limited systematic integration of "human" and "environmental" factors. The lack of exploration into human−environment interactions makes it difficult for current digital twin frameworks to meet the advanced demands of complex intelligent systems for multi−level, comprehensive interaction capabilities. In view of this, this paper innovatively introduces the "object−human−environment" interactive vision and comprehensively and systematically analyzes the research frontiers and progress of digital twin technology from the three core dimensions of intelligent physical entity (object), intelligent individual (human), and virtual−real fusion environment (environment). Firstly, the paper analyzes the traditional digital twin technology system with "object" as the core and focuses on its theoretical origin, framework, and application. Secondly, it discusses the definition, development context, national policies, and core technologies of digital people driven by AI. Finally, expand the vision to the dimension of "environment" and explore the application practice of "environment" in multiple scenes of the meta−universe, deeply discuss the deep integration and interaction mechanism of the three elements of "object", "human" and "environment", reveal how the three interact and promote each other, and provide support for the construction of the meta−universe. Furthermore, this study discusses the current research challenges and future development trends of digital twin technology from the perspective of "Object−Human−Environment" interaction and proposes three key research directions: (1) developing an intelligent, multi−layered data fusion framework; (2) exploring AIGC−enabled intelligent virtual−real mapping and native virtual evolution; and (3) constructing novel virtual economy architectures and intelligent governance systems. The research outcomes provide both theoretical foundations and practical insights for building next−generation digital twin systems characterized by multi−agent collaborative perception, multimodal intelligent interaction, and closed−loop integration of virtual and real environments.

The intelligence of unmanned vessel systems is undergoing a profound transformation from remote control to embodied autonomous forms, with the core being the realization of advanced intelligent behavior through multimodal perception, environmental interaction, and closed−loop learning. This paper systematically reviews the key advances of embodied intelligence in unmanned vessels, highlighting that semantic control loops, digital twin validation, and evaluation systems are moving from methodological exploration to engineering integration, and have already begun to provide preliminary application support in port and inland waterway scenarios. However, current technologies still face bottlenecks in perception stability, rule interpretability, and deployment resources. Therefore, this paper recommends focusing on breakthroughs in strengthening autonomous closed−loop intelligence systems, establishing standard and trustworthy validation environments, and promoting lightweight and collaborative deployment to enhance system reliability, compliance, and scalability, providing support for the development of intelligent ship technology and the implementation of our marine strategy.

Humanoid robots, benefiting from their human−like morphology and locomotion capability, are regarded as promising platforms for future service, rescue, and industrial applications; however, achieving stable and reliable walking in unstructured environments remains highly challenging. This paper provides a comprehensive review of recent advances in humanoid locomotion planning and control, with a focus on gait planning, trajectory generation, whole−body control, and learning−driven approaches. We summarize the core concepts and implementation frameworks of representative methods, compare their applicable scenarios, strengths, and limitations, and present a hierarchical categorization of existing research. Moreover, this work discusses key technical bottlenecks that hinder environmental adaptability and dynamic stability. Finally, we outline future research directions, including multimodal perception integration, co−optimization of learning and control, whole−body motion skill learning, and safety assurance, and offer suggestions toward standardization and large−scale deployment.

The Chinese Hα Solar Explorer (CHASE), dubbed "Xihe" – Goddess of the Sun, is China's first solar space mission for both scientific and technological experiments. Since its launch on October 14, 2021, it has been operating well in orbit with excellent scientific data quality. Based on a new type of satellite platform with ultra-high pointing accuracy and ultra-high stability, the Hα Imaging Spectrograph (HIS) onboard the CHASE mission has, for the first time in the world, achieved space-based spectroscopic observations in the solar Hα waveband. The pixel spectral resolution reaches~0.024 Å, the full-disk scanning time is~46 seconds, and the spatial resolution is~1.2 arcseconds. Using the high-quality data from CHASE, researchers have achieved a series of original scientific results in the dynamic processes of solar activities in the lower atmosphere, the formation, evolution, and eruption of solar filaments, as well as comparative studies of solar and stellar eruptions.

Kuafu-1, also known as the Advanced Space-based Solar Observatory (ASO-S), is China's first comprehensive solar exploration satellite. It was successfully launched on October 9, 2022, from the Jiuquan Satellite Launch Center. After nearly one year of in-orbit testing, the satellite was delivered to the Purple Mountain Observatory of the Chinese Academy of Sciences at the end of September 2023 and officially entered the scientific operation phase. This article summarizes in brief the preliminary observational research results achieved in less than one and a half years, up to February 2025, following the mission's delivery. Some findings are highlighted, including the pivotal role of magnetic cancellation in the dissipation of β-type sunspots, an exhaustive diagnostic on quasi-periodic pulsations (QPP) in flaring hard X-ray emissions, a joint analysis of dual-angle observed hard X-ray imagery, the features of white-light flares at 360 nm wavelength, Carriton maps in the Lyman-alpha (Lyα) band, and so on. In the future, by utilizing observation data from ASO-S and integrating it with data from other advanced solar observation satellites both domestically and internationally, joint research on multi-wavelength and even stereoscopic observations can be carried out. This is expected to yield significant progress in understanding the nature of and correlations between the "one magnetic field and two storms" (i.e., the solar magnetic field, solar flares, and coronal mass ejections).

A brief introduction is provided to the observational system of the 1-meter New Vacuum Solar Telescope (NVST) at Fuxian Lake, Chengjiang, operated by Yunnan Observatories, Chinese Academy of Sciences. Over the past decade, both domestic and international researchers have used NVST observational data to conduct outstanding scientific studies in several areas, including the observational characteristics and fine physical processes of magnetic reconnection, the structure, formation, and evolution of solar filaments, the fine structure and dynamic evolution of prominences, small-scale solar activities, fine physical processes of photospheric activities, as well as image processing and feature recognition methods. Prospects are also presented for the construction of large-aperture ground-based solar telescopes and the scientific issues they aim to address.

The paper introduces the growing trend of world solar radio researches and points out the importance and uniqueness of solar radio observations. The Mingantu Spectral Radioheliograph (MUSER) in China has been developed and constructed to image the solar atmosphere over continuous wide band radio spectrum in 3-D from the lower atmosphere up into the mid-corona to monitor solar activities. The results of solar radio bursts and multi-frequency (or 3-D) radio images are demonstrated, exhibiting the significant role of MUSER in solar physics and space weather studies.

During May 10-11, 2024, Solar Active Region (AR) 13664 experienced one of the most intense solar storm events since the Carrington Event of 1859, triggering a G5-level geomagnetic storm (Dst index reaching -412 nT) and global auroral displays. AR 13664 exhibited a dense and complex magnetic field distribution, accompanied by rapid magnetic field evolution and high activity such as abundant magnetic emergence, topological restructuring, and the generation of multiple flares and coronal mass ejections (CMEs). AR 13664 may represent a typical process of energy accumulation and release in intense solar eruptions, making it an ideal subject for studying magnetic complexity, energy storage and release mechanisms, and the causes of strong solar eruptions. This paper reviews current relevant research findings, focusing on multi-band observations, magnetohydrodynamic modeling, and nonlinear force-free field extrapolations, to reveal the full chain physical processes from magnetic flux emergence to near-Earth space responses of AR 13664. The research results around AR 13664 indicate: (1) the region exhibited an extremely high rate of magnetic flux emergence, peaking at 2.2×10²² Mx/day, rapidly forming a complex βγδ-type magnetic structure, with a total unsigned magnetic flux of up to 1.35×10²³ Mx, laying the magnetic topological foundation for efficient energy storage; (2) magnetic topology analysis indicates that the energy release process is closely related to the evolution of quasi-separatrix layers (QSLs) and the development of multiple current sheets, revealing the energy release mechanism in local non-potential energy regions; (3) multi-stage magnetic shearing processes were clearly observed, showing the gradual formation of magnetic rope structures and enhanced instability, closely associated with subsequent eruptions of 12 X-class flares and multiple halo CMEs; (4) the associated CMEs exhibit large-scale trans-equatorial source structures and propagate swiftly through solar-terrestrial space. Some of these CMEs reach projected speeds surpassing 2000 km/s and showcase pronounced southward magnetic fields (with the North-south magnetic field Bz dropping to a minimum of -50 nT) at 1 AU. These characteristics lead to significant impacts on Earth's magnetosphere, instigating intense magnetic storms and disturbances in the ionosphere. These studies systematically depict the full chain evolution process of extreme space weather events from the solar source to near-Earth space, providing innovative insights into the triggering, energy accumulation, release, and propagation mechanisms of solar eruptions, and offering an important research foundation for establishing more accurate and predictable space weather models.

This article focuses on the triggering process of an X1.0 class flare that occurred on May 8, which is the first event in a series of solar eruptions related to the massive geomagnetic storm event on May 10-11, 2024. Multi-wavelength observations show that the solar source region of this event is composed of two closely-related active regions, AR 13668 and AR 13664. There are four filaments in the core area of the activity, and the corresponding high-temperature observations exhibit four sets of bright corona loops, corresponding to one twisted magnetic flux rope and three weakly twisted sheared magnetic arcades in the nonlinear force-free field model. The complex triggering process of X1.0 class flares is analyzed, and it is found that they are associated with the eruption of two M-class flares and two hot channels. The eruption of the hot channel HC1 during the first M-class flare provides favorable conditions for the fast rise of the hot channel HC2 after its formation, which in turn propels the fast rise of HC1. Eventually, the two hot channels merge and successfully erupt, forming a halo coronal mass ejections. The joint analysis of multi-wavelength observations and nonlinear force-free field shows that the formation of the hot channel HC2 is caused by the tether-cutting magnetic reconnection of two sheared magnetic arcades triggered by the magnetic flux cancellation. This process occurs during the second M-class flare, and the fast rise of the hot channel HC2 subsequently triggers the onset of the X1.0 class flare. The study reveals the complex triggering process of the first X-class solar flare related to the massive geomagnetic storm in 2024 May, which involves coupling between multiple flares and hot channel eruptions, deepening our understanding of the triggering process of extreme space weather events in the source region.

Organizational resilience is fundamental for an organization to maintain its survival and achieve sustainable development when encountering severe risks. The study of organizational resilience in disaster scenarios aims to establish a dialogue channel between theoretical research on resilience and emergency management practice, and to guide the research and practice of disaster emergency management with the rich achievements and management inspirations of organizational resilience research. Therefore, based on raising the research issues of organizational resilience in disaster scenarios, this paper uses Citespace software to sort out the core literature in the field of disaster resilience, sort out the research topics of concern, and form an organizational resilience research and analysis framework based on the entire process of disaster emergency management, and then proposes future research prospects.

Post−disaster restoration and reconstruction after major disasters is an open and complex mega−system project. This paper attempts to interpret the historical development of post−disaster restoration and reconstruction in China from the system engineering perspective. First, we define major disaster events and provide classification and outline significant catastrophic events since 1949. Secondly, we use Hall's three−dimensional morphology and Wuli−Shili−Renli system approach to construct the system structure of post−disaster restoration and reconstruction from three dimensions: development stages, critical activities, and science and technology. Then, by examining the specific measures of post−disaster restoration and reconstruction in typical catastrophic events and their relationship with the evolution of human−environment interactions, the traditional, sustainable and intelligent patterns of post−disaster restoration and reconstruction systems are revealed. Finally, the historical experiences of China's post−disaster restoration and reconstruction are summarized in five aspects: institutional advantages and legal guarantees, cross−departmental coordination and information sharing, intelligent monitoring and precise needs assessment, infrastructure and cultural construction, and catastrophe relief and insurance.

As global climate change accelerates and urbanization progresses, natural disasters such as floods, earthquakes, and typhoons pose serious threats to human society. The development of information technology provides new momentum and possibilities for disaster prevention, reduction, and relief systems, greatly enhancing the efficiency and effectiveness of disaster management. This paper analyzes the key applications of information technology in modern disaster management systems and discusses its potential to improve disaster response speed and reduce casualties. The application of information technology significantly enhances the precision and speed of disaster warnings, offering technical support to reduce disaster losses. With further advancements in information technology and the integration of multi−source data, the intelligence and precision of disaster management will continue to improve, providing more robust security for society.

After a major disaster, the recovery and reconstruction of housing are related to the stability of urban and rural society and the level of governance. It is not only the reconstruction of the survival foundation but also the reconstruction of social relationships and governance capabilities. It must be planned with a focus on the restoration of real social governance capabilities and how to reduce losses in the event of another major disaster in the future. From the practice of housing recovery and reconstruction, it cannot be separated from the joint promotion of the government and the market. The market can efficiently solve the incentive problem of social forces participating in reconstruction, and the government can more effectively address the restoration of social governance capabilities and future disaster prevention and reduction issues. At the same time, practice has shown that only through cooperation between the government and the market can both aspects be optimally resolved. In the process of "normal society–extraordinary society–reconstruction of normal society", it is necessary to fairly and harmoniously handle the supply of private and public goods in the housing reconstruction process and achieve the modernization of urban and rural governance as the guiding principle of social reconstruction. The analysis of the experience of three sample areas based on housing recovery and reconstruction also demonstrates the value of this understanding. It can be seen that in the process of housing reconstruction after a major disaster, the modernization of urban and rural social governance should be the basic consideration. By establishing a post−disaster housing reconstruction funding support system combining national subsidies and market post−disaster insurance systems, it can incentivize market forces such as enterprises to participate in housing reconstruction and simultaneously regulate housing reconstruction and social reconstruction from the policy and legal levels.

With the advancement of urbanization, the impact of catastrophe on socio−economic systems in increasing. This paper takes 12 counties (cities) in the hard−hit areas of Wenchuan earthquake in 2008 as the research object, and discusses the temporal and spatial evolution of economic, social and institutional resilience before and after the disaster. The results show that although the Wenchuan earthquake has caused serious damage to various regions, the level of economic, social and institutional resilience in various regions has increased year by year under effective policy support and resource allocation. Based on the research results, this paper proposes strategies such as optimizing resource allocation and infrastructure restoration, improving community participation and self−recovery capabilities, in order to further enhance the economic, social and institutional resilience of geological disaster−prone areas and achieve safer and sustainable development. This study provides an empirical basis for the government and decision makers to formulate more effective disaster response and recovery strategies, and promotes the scientific and systematic development of disaster management and resilience building.

With the frequent occurrence of extreme rainfall events around the world in recent years, the floods caused by them seriously threaten the safety of human life and property. Due to the abundant rainfall, undulating terrain, and good runoff conditions in mountainous areas. After rain, the flood flow of rivers rises sharply. Serious floods often form in the plains in front of mountains where human activities are frequent. To reduce the impact of floods on the human living environment, it is urgent to research the risk of heavy rainfall floods in the plains in front of mountains. This research will provide scientific guidance for flood prevention and mitigation. In this paper, the Piedmont area in northwestern Balochistan, severely affected by the 2022 floods in Pakistan, is taken as the study area. Two factors were selected as the flood indicators: substrate and climate. The weights of hierarchical analysis and mean squared difference decision method is assigned using the combination of weighting rules. The risk of the study area is calculated by combining the flood hazard resistance of different surface types, infrastructure, and economic development levels. The results show that the flood inundation prediction based on the combined weighting rule is consistent with reality. The predicted inundation area encompasses 90.31% of the actual inundated area. The results indicate that areas of very high risk are primarily located in regions with abundant farmland, low topography, and weak flood resistance. In these areas, floodwaters tend to accumulate.The study demonstrates that this inundation model can accurately predict flood inundation areas. The evaluation results can guide disaster prevention and mitigation efforts in the study area and similar regions along the "Belt and Road" to reduce the risk of flooding.

In recent years, major maritime countries and international organizations such as the United States, Russia, Japan, South Korea, the United Nations, and the European Union have issued multiple medium − and long−term ocean strategies and plans, intensifying efforts to promote the development of key marine science and technology fields, striving to make breakthroughs and progress in marine basic research, deep−sea technology, Arctic technology, shipping industry, marine renewable energy, and marine electronic information technology. In the medium to long term, the world's marine technology will present many new development trends. From the perspective of planning issued by major developed countries and international organizations involved in the ocean, this article summarizes and analyzes the main trends in the development of world ocean technology in areas such as ocean basic research, deep−sea fields, shipping industry, marine renewable energy development, and global ocean observation. It also summarizes that there are still many shortcomings in China's ocean technology, such as the gap between its basic research level and that of a world ocean technology powerhouse, insufficient innovation in deep−sea technology equipment, and reliance on imports for key core technologies. On this basis, it is suggested to strengthen the basic research of marine science and technology, and enhance the research and development efforts in key marine technology fields.

Based on the background and authoritative definition of "new quality productivity, " this study systematically examines the concept, connotation, theoretical framework, and implementation pathways of marine new quality productivity. The research highlights that marine new quality productivity is driven by marine scientific and technological innovation, relying on significant advancements in marine technology to achieve innovative allocation of marine production factors and promote deep transformation and upgrading of the marine industry, thereby fostering modern marine advanced productivity. The core connotation of marine new quality productivity is analyzed from three dimensions: macro, meso, and micro levels. Its fundamental characteristics encompass innovation–driven development, openness and integration, green and low–carbon practices, and efficient innovation. Guided by innovation, with "new" and "quality" as its starting and ending points respectively, the framework centers on "factor deepening, technological change, and industrial iteration" as its main trunk, supported by channels including the industrial system, green production, production relations, education, and technology, all underpinned by the "new development concept." This study proposes a pathway for realizing marine new quality productivity, prioritizing high–quality development, with scientific and technological innovation as the core driving force, high–quality labor force as the mainstay, and green development as the sole path.

The Global Ocean Observing System (GOOS), as a globally vital ocean observing network, is dedicated to integrating sustained ocean observing activities to provide unified data support for key areas such as climate policy, disaster early warning, weather forecasting, and marine resource management. With the continuous development of technologies, international scientific community and policy circles claim that the observation based on buoys, ocean gliders, ships, sea level, high−frequency radar, as well as animal sensors also faces a number of governance challenges, especially in areas under national jurisdiction. These challenges include the lack of coordination between legal procedures and actual operations, difficulties in advance notification, issues with the 'consent' process in disputed areas, and the absence of a domestic 'consent' process for the application of new technologies. Currently, international bodies such as the Intergovernmental Oceanographic Commission (IOC) have begun to take measures to address these challenges. In response, the author suggests that China accelerate the innovation and development of marine observation technology, actively participate in global marine observation affairs, and accelerate the cultivation of professional talents for international marine science and technology governance, in order to effectively respond to potential changes in global ocean governance.

The level of marine science and technology is an important indicator of a country's scientific and technological strength. Under the global trend of green energy and low−carbon transformation and the guidance of the "dual carbon goals", marine energy resources have become an important growth pole for ensuring China's energy security. This paper selects six representative subfields in the marine field, comprehensively analyzes the development trends, demands and challenges of engineering science and technology, and uses the strategic research method of technology foresight. Combined with the vision of economic and social development, it innovatively distills 10 key technologies, 10 common technologies and 3 disruptive technologies. It proposes a three−in−one strategic framework for China's marine engineering science and technology development in 2040: "possessing an advanced and independent marine equipment and technology system, enhancing the green development capacity of marine energy and resources, and establishing a technical guarantee system for marine security and strategic interests", as well as six major marine science and technology projects: demonstration of comprehensive development of offshore energy, global intelligent space−air−ground−sea integrated marine information networking, green development of marine mineral resources, construction of an all−round marine environment monitoring network, development of biological resources in polar and oceanic high seas, and green development of China's exclusive economic zone fishery. The research suggests: strengthening the top−level design in the field of marine engineering science and technology, and doing a good job in overall planning; giving full play to the advantages of the system and mechanism, and realizing the integrated application of industry− university−research− use; strengthening independent innovation, and forming high−quality development of technology and equipment; deepening international exchanges and cooperation, and enhancing international discourse power; innovating the mechanism and system of marine talents, and strengthening talent cultivation and transformation of achievements; increasing investment in research and development, seizing new opportunities for leapfrog development, and helping China realize the grand blueprint of a marine power as soon as possible.

Biodiversity monitoring is essential for the conservation of biodiversity. Traditional methods of biodiversity monitoring are often time-consuming, costly, inefficient, and heavily influenced by human activity. These limitations hinder large-scale and long-term continuous monitoring, making it difficult to support the operational requirements and the goals of building a beautiful China. To address these challenges, this study proposes the concept of an intelligent biodiversity monitoring system, leveraging new equipment and advanced technologies. The system integrates ground-based and remote sensing monitoring, primarily utilizing passive survey equipment such as infrared cameras and audio recorders. It relies on cutting-edge technologies, including the Internet of Things (IoT), artificial intelligence (AI), and environmental DNA (eDNA), to achieve automated data collection and intelligent species identification. This system supports biodiversity surveys, monitoring, assessments, and early warning mechanisms. This paper summarizes the progress of the pilot project for the intelligent biodiversity monitoring system in Lishui City, Zhejiang Province. The project has successfully implemented intelligent monitoring of plants, mammals, birds, amphibians, reptiles, insects, and aquatic organisms. It provides practical case studies and theoretical support for the operational implementation of intelligent biodiversity monitoring systems.

With the rapid development of human society and economy, factors such as climate change have prompted the sharp loss of global biodiversity. Plants are a core component of biodiversity, and ex situ conservation to save endangered plants has become the core work of botanical gardens. At present, ex situ conservation based on protecting the genetic diversity of endangered plants remains a challenge. Genomic technologies have made it possible to accurately identify the taxonomic status of endangered plants, explore the population evolutionary dynamics and endangering causes of endangered plants and analyze genetic diversity at the whole-genome level and its adaptability to future climates. This paper summarizes the development of genomic sequencing technologies for plant conservation and the effectiveness and current status of ex situ conservation, as well as the research progress of genomics in helping protect endangered plants in terms of mining functional and adaptive variant genes, species identification, genetic risk assessment, and regulation of growth, development, and secondary metabolism. In response to how to promote future ex situ conservation in the genomic era, countermeasures, suggestions, and future development trends are proposed.

Multi-omics data, including genomics, transcriptomics, and epigenomics, contain a wealth of genetic information and are crucial for the study of biological genetic diversity and the conservation of biodiversity. However, the integration and reuse of multi-omics data remain challenging due to their massive volume and fragmented distribution across disparate databases and published literature. To facilitate timely submission and sharing of multi-omics data in life science, National Genomics Data Center (NGDC) has established multiple foundational data submission platforms. Additionally, to fully integrate and explore existing omics data resources, NGDC has developed several multi-omics integration resources and knowledge bases for domesticated animals and plants. Currently, NGDC has preliminarily formed a comprehensive multi-omics big data framework, which will significantly contribute to the conservation of biodiversity, including species identification, the protection of endangered species, breeding programs, and monitoring changes in habitats.

Basin ecological security is a major issue for human survival and development and has become an important branch in the field of social security research. This paper applies the principles and analytical methods of landscape ecology to evaluate the ecological security of the Chahannaoer Basin. Starting from the perspective of landscape structure, the ecological security status of the basin in 2010 and 2024 was evaluated using metrics such as Patch Density (PD), Landscape Shape Index (LSI), Landscape Division Index (DIVISION), and Landscape Aggregation Index (AI). Furthermore, a dynamic change analysis is conducted. Meanwhile, the study calculated the intensity of mutual transitions between ecosystem types and the overall dynamic degree of the watershed within the specified time period. The results indicate that between 2010 and 2024, the forest area and construction land in the basin showed an upward trend, while the grassland area showed a downward trend, and the saline-alkali land area increased significantly. A comprehensive analysis of the spatial distribution patterns of the indices PD, LSI, DIVISION, and AI reveals that the fragmentation of most landscapes decreased. Notably, the fragmentation of croplands and forests showed a significant decline, whereas the fragmentation of wetlands increased sharply. During this period, the land cover transition index and the comprehensive land cover change rate in the Chahannaoer Basin were 47.36% and 20.54%, respectively, indicating that land cover types are still transitioning towards a more favorable state.

Drug discovery, as the core driving force of the modern pharmaceutical industry, faces the difficulty of the traditional model's "high investment, long cycle, and low output, " urgently requiring breakthroughs to address increasingly complex health demands. The rapid development of artificial intelligence (AI) technology has brought revolutionary changes to drug discovery, significantly enhancing efficiency and success rates in areas such as protein structure prediction, protein design, antibody drug design, and small molecule drug development. This article focuses on the domestic and international progress of AI in these key domains, providing an in-depth analysis of AI breakthrough in protein structure prediction and its potential applications in target discovery and virtual screening. It explores the closed-loop model of AI-driven protein design, from structure prediction to functional innovation, and examines AI's role in antibody sequence optimization, affinity maturation, and novel antibody design. Additionally, it reviews the latest achievements of AI in small molecule drug target identification, virtual screening, and ADMET optimization. The article also highlights challenges in AI applications, including data quality, model interpretability, and experimental validation, while envisioning future directions such as multimodal data integration, dynamic behavior prediction, and automated platforms. By comprehensively analyzing the current state and challenges of AI-enabled drug discovery, this article aims to offer scientific perspectives and insights to accelerate new drug creation and enhance human health and well-being. It seeks to provide readers with a thorough and insightful view of technological issues in AI-empowered drug discovery, stimulate thinking about future directions, and promote the more effective application of AI technologies in this field, ultimately benefiting human health through an accelerated drug development process.

Deep-sea exploration is a key technology for developing marine resources, studying the evolution of the Earth, and protecting the Earth's ecosystem. This paper reviews the main progress of deep-sea exploration technology in the past seven years (2019–2025), including the fields of submersibles, sensors, communication, energy, etc., and looks ahead to the development trends in the next 5~10 years. Firstly, the importance and challenges of deep-sea exploration are introduced. Then, the current status of technologies in various aspects such as deep-sea submersibles, sensors and observations, sampling and analysis, communication and navigation, energy, as well as big data and artificial intelligence are described in detail. The analysis shows that intelligentization, long endurance, and in-situ experimental technologies will become the core directions, but the adaptability to high-pressure environments, energy supply, and data transmission remain the main bottlenecks. Subsequently, the future development trends such as intelligentization and autonomy, long endurance and energy innovation, and the cost revolution are discussed. It is expected that this paper will play a certain guiding role in promoting the sustainable development of deep-sea exploration technology.

In the context of global efforts to address climate change and China's determined march toward the twin goals of carbon peak and carbon neutrality, methane control and emission reduction have become key links in achieving sustainable development and climate targets. This paper analyzes the strategic layout for methane management and mitigation under these twin carbon objectives. To date, preliminary achievements have been made: A three-dimensional "air–space–ground" monitoring system enables precise localization of emission sources; upstream recovery rates in energy extraction have improved; source-control technologies for rice cultivation and livestock farming in agriculture have matured; and a methane-focused climate finance framework has injected fresh capital into reduction efforts. However, methane mitigation challenges remain severe. In the energy sector, methane leaks in traditional coal mining and fugitive emissions in oil and gas systems hinder the green transition; in agriculture, anaerobic processes in rice paddies and enteric fermentation and manure management in livestock farming lead to significant methane release; and in waste treatment, landfill disposal and anaerobic treatment of industrial wastewater generate large methane volumes. In response, this paper proposes a cross-sectoral collaboration that breaks down the boundaries among the energy, agriculture, and waste-treatment industries to build an integrated mitigation system. This approach balances energy security with the twin carbon goals by steadily steering the energy mix toward greener, lower-carbon sources while ensuring supply reliability. It also calls for leveraging educational, research, and talent advantages to establish national-level science and innovation platforms to tackle key technological challenges in methane control. Looking ahead, with sustained technological innovation, targeted policy optimization, and deep international cooperation, China is poised to overcome current methane-control obstacles, achieve substantial emission reductions, support its carbon-peak and neutrality goals, and contribute meaningfully to global climate governance.

Optical vacuum measurement technology, with its remarkable advantages in expanding measurement ranges and breaking through uncertainty limitations, has emerged as a key technology supporting innovation in strategic fields such as deep space exploration, semiconductor manufacturing, and advanced equipment development. This paper initiates from the interaction mechanism between photons and gas molecules, comprehensively introducing theoretical model innovations and experimental setup breakthroughs in quantum optical methods for retrieving vacuum parameters, including Fabry−Perot cavity optical interferometry, cold atom collisional loss, and spectral absorption. It systematically reviews the latest developments from fundamental research to engineering applications by international research institutions in this field. In-depth analysis reveals existing bottleneck issues within current quantum vacuum measurement technology systems. Subsequently, potential evolution directions for quantum vacuum measurement technology are prospected through technical pathways such as quantum vacuum standard establishment and miniaturized device integration.