This paper summarizes the recent progress of global nuclear energy science and technology, focusing on nuclear fission and fusion, coupling utilization of nuclear energy and other energies, frontier technology of nuclear energy informatization and nuclear waste treatment. The global research and development of nuclear energy is developing steadily. Nuclear power technology will gradually realize the development from the second generation to the third generation. Small reactors have good applications in the sea, land and air. The progress of nuclear fusion technology has been introduced, including high temperature superconducting fusion, laser ignition inertial confinement fusion, Tokamak fusion device, International Thermonuclear Experimental Reactor and Chinese Fusion Engineering Testing Reactor. The coupling utilization of nuclear energy and other energies such as hydrogen energy and solar energy, provides a new solution for the development of renewable energies and the realization of carbon peaking and carbon neutrality goals. High-precision multi-physical field coupling analysis and calculation, digital twin technology, informatization and database construction are important directions for sustainable development of nuclear energy in the future. The latest advances in radioactive waste treatment and disposal technologies have been summarized, including the reduction and solidification of low- and medium-level radioactive waste, radionuclide removal and vitrification of high-level radioactive waste, and treatment and disposal of spent fuel. The overall situation shows that nuclear energy is still an important part of the global energy structure.

The research analyzed the material treatment, career management, welfare, and other incentives for researchers in Japanese universities, research institutions, and enterprises. It concluded that the complementary relationship of research collaboration among Japanese universities, research institutions, and enterprises, leveraging their respective strengths, has played an important role in promoting the development of scientific and technological innovation in Japan. Japan's scientific research is well-funded, with diverse sources of funding. Additionally, Japan's research funds are allocated clearly and competitively, ensuring the high-quality development of its scientific research. While optimizing the efficiency of research funding allocation and other measures, Japan focuses on increasing opportunities for young scholars to obtain research grants, providing more possibilities for the future development of science in Japan. The stable and diverse income sources, combined with scientific management methods, have improved the welfare of researchers and promoted the formation of incentive mechanisms. This study of the current situation and its characteristics has important reference significance for China in optimizing the incentive system of its fundamental research team.

Navigation warfare has become one of the new electronic combat styles, and it effectively supports joint operations. However, the satellite navigation landing signal is weak and highly vulnerable to interference, which affects various command chains of joint operations and has a devastating impact on the war. This paper proposes an alternative defense style for unmanned aerial vehicle (UAV) pseudo satellite network navigation when satellite navigation is rejected. Then a multi-point navigation power intelligent enhanced defense style is presented when navigation signals are subject to electromagnetic interference. Next, an autonomous integrated navigation defense style is put forward when satellite navigation signals are unstable. Finally, this paper proposes in-orbit autonomous programming and navigation signal reconstruction defense styles when the satellite navigation signal frequency band is attacked. Thus, effective defense can be carried out from multiple perspectives, ensuring the normal broadcasting of navigation signals, and effectively supporting the smooth progress of various combat activities.

Intelligence is a systematic and ecological concept, involving knowledge and understanding in multiple disciplines and fields, with differences and characteristics in different cultural and historical backgrounds. Intelligence is systematic yet diverse. Different agents have different types, characteristics, and expressions of intelligence. Intelligence has both advanced and ordinary parts. Advanced intelligence includes complex technologies such as deep learning and natural language processing, while ordinary intelligence includes basic pattern recognition, data processing and other tasks. This multi-level intelligence covers different fields and application needs, and has a positive impact on human life and work. Intelligence is divided into a technological part and an artistic part. Intelligence is both materialistic and idealistic, and is a complex system involving the interaction of physical, biological and social factors. This article also explores the ontology, methodology and epistemology of intelligence, focusing on the nature and existence of intelligence, how to build and implement intelligent systems, and the interaction and cognitive process between intelligent agents and the external world. Researches at these three levels are interrelated and jointly promote the development of the field of intelligence. As a representation of the interaction between human-machine environment system, intelligent systems are composed of humans, machines and the environment. The interaction between them is the basis for the operation and development of intelligent systems. Intelligence has different influences on eastern and western cultures. Intelligence is the product of human evolution, shaping human thinking, behavior and civilization, making humans the most creative and adaptable species on earth. Intelligence contains both mathematical and nonmathematical parts, both changing and unchanging parts. The existence of these multiple components enables the intelligent agent to better adapt to and respond to different situations and achieve higher performance and efficiency.

In recent years, the rapid development of artificial intelligence has had an important impact on mental health services such as psychological counseling and psychological assessment. In this paper the accuracy and methods of artificial intelligence in psychological assessment as well as ethical issues are reviewed. Based on the development of multi-modal and psychological intervention technology, the future application research of artificial intelligence in psychological assessment is forecast. It is believed that the application of artificial intelligence in psychological assessment in the future will pay more attention to individual needs and interdisciplinary cooperation. It will be more widely used in information collection, data analysis, humancomputer interaction technology, and non-invasive regulatory technology cooperation, and the ethical research of artificial intelligence will play a more important role in the future.

The various risks caused by the development of artificial intelligence (AI) technology are increasingly pervasive in every stage of innovation activities. It is a vital factor that we should take prospective and proactive reflection on the potential risks associated with the development of artificial intelligence technologies as we strive for advancements in this field. Based on the global development of artificial intelligence technology, technological and industrial advancement and the theoretical perspective of AI technology catch-up, this article analyzes the relationship between technological catch-up in artificial intelligence and potential risks from three dimensions: cognition risk, Scenario risk, and competition risk. This study concludes that risk perception should be embedded into the theoretical framework of AI technology catch-up, and more attention should be paid on the diversity of technology catch-up modes under the risk segmentation spectrum of different AI application scenarios. In addition, game risk in AI has been another key factor in restricting the efficiency of AI technology catch-up as the increasing negative externality caused by the dynamic and complex interaction of "technology-political-risk".

The application of artificial intelligence, represented by face recognition payment, has improved efficiency and optimized user experience, but it has also introduced various risks. In order to regulate its development, it is essential to investigate the factors that influence the adoption of face recognition payment. Current research on the impact of perceived risk facets on face recognition payment remains limited. This study, based on the UTAUT model, analyses the key factors influencing the intention to use face recognition payment (performance expectancy, effort expectancy, social influence, and facilitating conditions) and further examines the influence of five perceived risk facets (time risk, privacy risk, legal risk, financial risk, and health risk) on performance expectancy and effort expectancy. A structural equation analysis of 412 valid survey responses shows that the four factors in the UTAUT model have a significant positive impact on the behavioral intention to use face recognition payment. Privacy risk and financial risk are the facets of users' greatest concern, and both have a significant negative impact on performance expectancy and effort expectancy. This study identifies the specific mechanisms through which different risks affect the adoption of face recognition payment, providing reference and empirical evidence for its risk management and governance.

The research and development of new reagents are of great significance for organic synthesis. In recent years, some new reagents with universal applicability have been constantly emerging. This article introduces the latest research progress on new reagents for difluoromethylation and trifluoromethylation. Introduced some new sulfur-containing reagents. New reagents DMSO-I₂ and DMSO-TsCl for sulfur methylation were introduced detailedly, The sulfur-containing reagent Na₂S₂O₄-TBHP (TBHP, t-butylhydroperoxide) is a new reagent used for selective oxidation of aromatic alcohols to aldehydes which was also known as Wang's reagent.

In order to improve the service performance of oil pipeline for oilfield development, this paper takes Ф73×5.51 mm J55 oil pipeline as the substrate, and uses self-spreading high-temperature synthesis technology (SHS) to add 4wt%Nb₂O₅, 8wt% ZrO 2, 13wt% CrO₃, and 5wt% SiO₂ to the basic aluminum thermal system of Al+Fe₂O₃ (B component) as a new type of SHS material system, and prepares a new type of ceramic lined wear-resistant coated oil pipe (A component). Using SEM analysis, EDS analysis, XRD analysis, FTIR analysis and other analytical means to test the acid corrosion resistance, bonding strength, bending strength and crush strength and other properties, comparative analysis results show that: the corrosion resistance, bending strength, bonding strength and crushing strength of the ceramic lining layer prepared by component A are better than that of component B. The flow corrosion weight loss rate of component A coating and component B coating at 1200 h is 0.42% and 0.54%, respectively, which is better than that of J55 tubing substrate, and the bending strength of ceramic lined tubing prepared by component A is 15.9% higher than that of component B. Based on the observation of the slip position, the transition temperature between the strength of partial metallurgical bonding at the Fe-Fe interface and the mechanical bonding at the FeAl₂O₃ interface was determined to be about 200℃, with the mechanical bonding strength being greater than the metallurgical bonding strength at low temperatures, and the mechanical bonding strength being less than the metallurgical bonding strength at high temperatures. Both the bond strength and the crush strength properties of the ceramic lining layer showed a significant decreasing trend with increasing temperature.

In response to clear understanding of reservoir rock-forming and pore evolution characteristics，this study takes the tight sandstone reservoir of the Lower Cretaceous Yingcheng Formation and Shahezi Formation in the Longfengshan Sub-sag of the Changling Fault depression in the Songliao Basin as the research object, and the pore evolution process of the main rockforming phases is quantitatively recovered on the basis of reservoir characteristics and rock-forming phase delineation. The conclusions are as follows. The main rock type of the target formation is rock chip sandstone with low structural maturity and poor sorting and rounding; the typical type of reservoir diagenesis is compaction and cementation, the diagenetic stage is intermediate diagenetic stage B, and the diagenetic coeval sequence is: early compaction - chlorite cementation - turbidite cementation - early calcareous cementation - phase I dissolution - siliceous cementation - phase II dissolution - late calcareous cementation; the typical diagenetic phases include chlorite cementation diagenetic phase, turbidite cementation diagenetic phase and acidic dissolution diagenetic phase, and each diagenetic phase has undergone the process of compaction and cementation to reduce pore size, and two stages of dissolution to increase pore size; the pore evolution characteristics and the understanding of tight gas reservoir formation period are integrated, and two reservoir evolution models are established, namely the first tight and then reservoir formation model and the tight unresolved reservoir model.

Information processing of ancient Chinese seldom uses unearthed documents as corpus to carry out relevant research. The number of Liye Qin bamboo manuscripts reached ten times that of all the Qin slips unearthed before, which can fill many gaps in the historical records of the Qin Dynasty. In this paper, we used them as experimental corpus and explored the automatic sentence segmentation and word segmentation of unearthed documents based on the CRF model. We combined the actual characteristics of the corpus and set up different feature templates to verify the generalization ability of model sequence labeling on different tasks. We set up a joint approach to sentence segmentation and word segmentation as comparative experiment to select a better performance processing plan. At the same time, a comparative experiment was designed between deep learning methods and pretrained models. The results proved that the overall performance of the joint approach in each task was improved and that the F1-score of automatic sentence segmentation and word segmentation reached 75.79% and 94.44%, respectively. Since it's faster and takes less time, this approach is more suitable for the Liye Qin bamboo slips. The research results can serve the proofreading work of the last three volumes of Liye Qin bamboo slips and the in-depth processing and construction of the corpus.