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An advanced experimental practical education system for basic disciplines through entropy reduction, foundation strengthening, and three-fusion sharing
ZHANG Dong;LI Bingzhao;LI Jungang;GENG Junming;[Objective] Education, technology, and talent are the foundational and strategic pillars of modernization in the Chinese context. Strong basic scientific research serves as the cornerstone for establishing a world scientific and technological power and is a crucial source of disruptive technologies in many fields. The experimental teaching system for basic disciplines plays a vital role in cultivating top-notch innovative talents. This study focuses on issues in the experimental practice of basic disciplines, such as the lack of a sound organizational mechanism and system for education through experimental practice, insufficient integration of high-quality scientific research into talent cultivation, and shallow horizontal and vertical assimilation into the educational process. It proposes an education system for basic disciplines that emphasizes progressive experimental practice, featuring entropy reduction, foundation strengthening, and three-fusion sharing. [Methods] This study focuses on the cultivation of the experimental and practical innovation capabilities of top-notch innovative talents, adherence to the combination of learning and thinking, and unity between knowledge and action. It conducts the construction and practice of a progressive experimental practice education system that features entropy reduction, foundation strengthening, and three-fusion sharing. Toward this end, and using a top-level design, it systematically reorganizes the curriculum system, talent team, and resource allocation of the university's experimental centers. Doing so breaks down barriers to the engagement of high-level talents in experimental courses, formulates a new framework for the formation of educational pathways for experimental practice in basic disciplines, and achieves entropy reduction. A bridge is established between key laboratories and experimental centers for basic disciplines. The contents of mathematics, physics, and chemistry experimental courses are reshaped by integrating cutting-edge technology and national defense characteristics, thereby underscoring an experimental practice education system composed of Type-A top-level competition courses, Type-B scientific research transformation courses, and Type-C basic innovation courses, which achieves foundation strengthening. Horizontal and vertical exchange and cooperation that emphasize the cultivation of the experimental capabilities of top-notch innovative talents are promoted. The study proposes strategies for knowledge integration within basic mathematics, physics, and chemistry; advantage integration of basic disciplines into engineering disciplines; and full-element path integration for the cultivation of leading talents, thus forming a new cross-disciplinary educational path in experimental practice and achieving three-fusion sharing. [Results] “Entropy reduction, foundation strengthening, and three-fusion sharing: An advanced experimental and practical education system for basic disciplines” focuses on the core objective of cultivating the experimental and practical innovation capabilities of top-notch innovative talents. Through years of exploration and practice, and since its application and promotion, this achievement has led to remarkable results with a wide scope of beneficiaries. The proposed cultivation of experimental and practical innovative talents has played a positive role in guiding undergraduates to achieve excellent results in various high-level disciplinary knowledge competitions and in obtaining landmark achievements in global top competitions, thus bravely winning the highest awards in such competitions. [Conclusions] Taking the reform of the experimental teaching center for basic disciplines of the Beijing Institute of Technology as an example, this study systematically analyzes the problems faced by the experimental and practical teaching systems of basic disciplines in institutions of higher learning, given the requirements of the new era. It systematically dissects the curriculum system, talent teams, and resource construction of the experimental teaching center of the university. It also formulates an experimental teaching curriculum system for basic disciplines that features multidisciplinary integration, shared superior resources, integration of cutting-edge technology, and national defense characteristics. It proposes a practical path for the progressive experimental and practical education system for basic disciplines—namely, entropy reduction, foundation strengthening, and three-fusion sharing. In this manner, it provides new ideas and methods for the construction of the experimental and practical education system for basic disciplines in colleges and universities and further promotes the cultivation of the practical innovation capabilities of top-notch innovative “Six Forces” talents.
Building scientific research platforms to attract talent and foster interdisciplinary innovation in quantum and micro/nano optomechatronics technologies
YU Jianyu;LI Jifeng;ZHANG Dong;GUO Hongwei;DUAN Jiahua;WANG Yang;LI Jiafang;[Objective] This study uses the Cross-Science Center for Optical Quantum and Nano-Electromechanical Integration at the Beijing Institute of Technology as a case study to comprehensively examine the critical function of advanced scientific research platforms in talent aggregation, interdisciplinary collaboration, and technological innovation. In the context of intense global competition in quantum technology and micro/nano optoelectromechanical systems(MOEMS), the center addresses critical technological bottlenecks in high-end chips and ultra-sensitive sensors that are currently constrained by foreign monopolies. By systematically integrating state-of-the-art resources in MOEMS and quantum technologies, a comprehensive innovation chain has been established, encompassing fundamental research, key technological breakthroughs, and applied transformations. [Methods] The center integrates the high-precision characteristics of optical quantum devices with the miniaturization advantages of nano-electromechanical systems, focusing on three key research directions: quantum functional materials, optical quantum state modulation, and nano optoelectromechanical systems. The center has been supported by three national and provincial-level research platforms, and it employs an innovative “talent-platform synergy” mechanism. As a result, the center has assembled a high-caliber research team comprising 16 core members(including 13 national-level talents). The team has achieved a series of groundbreaking accomplishments, including the publication of over 20 papers in prominent scientific journals such as Nature and Science, and their sub-journals. They have also successfully developed optoelectronic modulation chips with complete indigenous intellectual property rights, which were featured in special reports on CCTV. Furthermore, the team has undertaken more than 20 national key research and development projects and has secured a cumulative research funding exceeding 60 million yuan. These achievements have effectively resolved critical technological bottlenecks in quantum sensing and high-end chips, while also providing robust support for addressing national strategic demands and fostering interdisciplinary innovation. [Results] The center has achieved groundbreaking advances in several domains, such as(1) developing the world's first in-situ nano-kirigami three-dimensional micro/nano fabrication technology, thereby overcoming the limitations of conventional processing architectures;(2) fabricating optoelectronic modulation chips with complete domestic intellectual property, thereby disrupting foreign technological monopolies;(3) creating biological quantum trace detection technology, thereby enabling the rapid and precise identification of ultralow-concentration toxic agents and biological pathogens;(4) achieving the first experimental observation of pristine Majorana anyons in iron-based high-temperature superconductors, thereby establishing a fundamental basis for anyon research;(5) synthesizing exceptionally clean twisted graphene nanoribbons under ultrahigh vacuum conditions, thereby extending the scope of twistronics from two-dimensional(2D) to one-dimensional systems; and(6) developing an ultracompact, highly sensitive silicon-based graphene 2D nano-electromechanical accelerometer prototype, which represents the world's first functional graphene accelerometer. These accomplishments are of considerable scientific value and provide innovative solutions for strategic national domains, including advanced semiconductor chips and biosecurity. [Conclusions] A close examination of the extant research demonstrates that the platform has successfully established a unique research ecosystem through the implementation of optimized resource allocation strategies and innovative management mechanisms. This environment facilitates deep interdisciplinary integration between micro/nano photonics and quantum science at fundamental levels; it also effectively promotes breakthroughs in critical technologies for high-value industrial applications, such as high-end chips and ultra-sensitive sensors. The findings yielded valuable theoretical frameworks and practical insights for establishing next-generation interdisciplinary research platforms. These platforms are designed to address national strategic needs while promoting scientific excellence. Future research should prioritize the expansion of these platform models, the refinement of mechanisms for collaboration between industry and academia, and the development of multidimensional evaluation systems for assessing the impact of interdisciplinary research. These efforts will contribute to the enhancement of national scientific and technological innovation strategies.
Management mechanism research in state key laboratory:A case study of State Key Laboratory of Environment Characteristics and Effects for Near-space
ZHENG Dezhi;SHAO Nan;ZHANG Yanlin;TENG Honghui;QIN Tong;LIU Beibei;LIANG Xiao;[Objective] In response to the evolving requirements arising from the restructuring of the State Key Laboratory, this study examines innovations in management mechanisms. Using the State Key Laboratory of Environment Characteristics and Effects for Near-space as an example, we propose the dual-wheel-drive model integrating collaborative innovation management and “1-3-5” synergistic operation framework. [Methods] The innovative management mechanism aligns with the national mission through ideological and political construction by establishing the General Branch of the Communist Party of China to strengthen Party organization. Accountability is enhanced through a Director Responsibility System, in which the Laboratory Director, appointed for a five-year term, operates under the supervision of a Management Committee comprising representatives from Beijing Institute of Technology(BIT), the China Meteorological Administration, and Nanjing University of Information Science and Technology. The Director assumes full responsibility for research strategy, resource allocation, and personnel management. The new management mechanism ensures autonomy through substantive construction. The laboratory is embedded within BIT's “Double First-Class” university initiative and benefits from dedicated facilities, independent equipment, and its own management office. In addition, this mechanism introduces new requirements and methods for various aspects of management. The mechanism proposes an innovative dual-PI team structure, led by a chief scientist and supported by two co-leaders for each research direction. Research teams led by PIs will be created based on various task types, such as applied basic research, core technology breakthroughs, equipment development, and product development. Meanwhile, the new system will implement a differentiated approach to resource allocation and diversified personnel strategies to address issues related to scattered resources and innovation predicaments. This aims to ensure efficient resource circulation, facilitate personnel allocation, and build PI teams with different specifications tailored to different team types and task requirements. This method also accelerates technology transformation by using an innovative ecosystem. It integrates industry, academia, research, and application to jointly create industrial incubation platforms with leading enterprises in the industry and application units. This management mechanism focusing on developing the spirit of scientists in combination with the cultural heritage of universities, create a laboratory atmosphere that values being “people-oriented, truth-seeking and pragmatism, and striving for excellence,” and builds a positive, and healthy scientific research environment. [Results] The “1-3-5” synergistic operation mechanism provides the operational backbone: integrated party building, three-dimensional cross-cutting collaboration, and five-dimensional organization. This collaborative operation mechanism achieves efficient management through “three connections and three high efficiencies.” The “triple-mutuality for joint cultivation” training system enhances cross-school education by building platforms, cultivating talents, and sharing achievements. The three-dimensional synergy management creates a closed-loop collaborative ecosystem that promotes resource sharing, talent development, and shared success. The five-dimensional organization enhances efficiency and promotes optimization across five dimensions: scientific research innovation, discipline development, talent cultivation, engineering experiments, and industry services. [Conclusions] Through this innovative management model, the laboratory seeks to maximize its scientific productivity and transform the governance structure for national laboratories. It aims to effectively support the national innovation-driven development strategy and play a key role in achieving high-level scientific and technological independence.
Exploration of the innovative talent cultivation model of the Belt and Road joint laboratory of crop science
MENG Min;YUAN Weibin;LI Lun;LI Jinli;DU Xiaoqian;ZHAGN Chaoyang;[Objective] Against the backdrop of global economic integration and the in-depth advancement of the Belt and Road Initiative, international agricultural cooperation has recently emerged as a vital link for developing countries along various routes. However, these nations are facing a dual challenge: the urgent need for agricultural modernization and a critical shortage of professional expertise. Traditional agricultural education suffers from structural issues, including insufficient curriculum articulation, inefficient resource allocation, and cultural cognitive biases, which fail to meet the demand for the array of skills required in international agricultural cooperation. Hence, this study focuses on the field of crop science, utilizing a joint laboratory platform and aiming to develop an innovative talent cultivation model that facilitates cooperation between agricultural science and technology under the Belt and Road Initiative. Through systematic reform, it aims to enhance the professional capabilities, practical skills, and cross-cultural literacy of students, thereby cultivating high-quality specialists for international agricultural cooperation. [Methods] This study constructs a “Three-Dimensional, Four-Stage” innovative talent cultivation model for the Belt and Road Joint Laboratory of Crop Science. Centered on three core dimensions, the curriculum system integrates cutting-edge agricultural theories and practical courses to cultivate students' professional competencies and cross-cultural communication skills. Knowledge Foundation: Advanced theories in crop genomics and digital agriculture are integrated using bilingual instruction and massive open online courses(MOOCs), with foundation courses in crop physiology and ecology strengthening students' professional grounding and international academic communication. Competency Advancement: A capability matrix encompassing scientific research, technical transfer, and international negotiation is established. Project-based learning, including AI-assisted breeding projects, is implemented to cultivate students' full-chain capabilities from laboratory research to industrial application. Cultural Empowerment: Courses such as “Comparative Study of Farming Civilizations,” combined with overseas field investigations and scenario simulations, enhance students' cross-cultural collaboration and international policy interpretation skills. The “Four-Stage” progressive cultivation path systematically improves students' ability to address practical agricultural problems through the following sequential phases: Basic Introduction—building a cognitive framework with standardized courses and basic experiments; Skills Enhancement—conducting complex experimental projects leveraging platforms such as molecular biology laboratories; Comprehensive Application—engaging in transnational breeding projects and regional agricultural engineering initiatives to integrate multidisciplinary knowledge; Innovation Expansion—exploring cutting-edge fields such as vertical agriculture and carbon sequestration to generate patents and policy recommendations. Additionally, a practical three-level linkage system, comprising campus smart farms, overseas joint experimental stations, and virtual simulation platforms, would be established to connect the entire research, learning, and application process, thereby facilitating the transformation and application of scientific research achievements. [Results] This model effectively alleviates the deficiencies of traditional agricultural education using strategies such as dynamic curriculum adjustment mechanisms and intelligent resource allocation, and the professional skills and cross-cultural collaboration abilities of students have improved significantly. With these cultivated talents, they can better adapt to the needs of international agricultural cooperation, promoting the transformation of scientific research achievements into practical productivity. [Conclusions] The Three-Dimensional, Four-Stage model constructed in this study provides a replicable talent cultivation paradigm for international agricultural cooperation under the Belt and Road Initiative. Its innovation lies in the deep integration of professional education with cross-cultural training, and scientific research with industrial application. In the future, a long-term follow-up evaluation will be necessary to assess the model's long-term impact on students' career development. The model should be expanded to fields such as animal husbandry and food science. Meanwhile, current plans include developing a meta-virtual laboratory platform and establishing a Belt and Road Agricultural Education Alliance to further integrate international resources and promote in-depth global agricultural education and scientific and technological cooperation.
Self-supervised scene flow estimation based on multiscale masked autoencoders
XIANG Xuezhi;WANG Xi;WANG Lu;BEN Xianye;QIAO Yulong;[Objective] Point cloud scene flow plays an important role in the field of autonomous driving. However, improving the accuracy of scene flow estimation is difficult because of the point cloud characteristics, such as disorder and uneven density distribution. In most previously reported methods, the models were trained on synthetic datasets because of the difficulty and cost of acquiring accurate scene flow labels for point clouds; additionally, complex situations, such as occlusion in real scenes, were ignored. To address these problems, a self-supervised scene flow estimation method based on multiscale masked autoencoders is proposed. [Methods] The proposed model divides the input point cloud into irregular point patches, performs large-ratio random masking and token embedding, and then simulates the spatial geometry of the point cloud through an asymmetric encoder–decoder architecture. In the encoding stage, the mask token is shifted to the input of the autoencoder's decoder to prevent position information from leaking to the mask token; in this way, the encoder can focus on learning high-level latent features obtained from the unmasked point cloud. In the decoding stage, the learned latent features and mask tokens are utilized to reconstruct the original point cloud. In addition, the model fuses details and global context information through a pyramid architecture and adopts a multiscale masking strategy to ensure consistent visible areas during feature extraction at different scales. [Results] Experiments were conducted on the FlyingThings3D and KITTI datasets, and the model was trained in a self-supervised manner. The results of model training and testing on the FT3Do and KITTIo datasets, respectively, show that despite using only one-tenth of the instance data used in other methods during model training, the proposed method outperforms all the existing self-supervised and fully supervised methods. The results of model training and testing on the FT3Ds and KITTIs datasets, respectively, show that all indicators are significantly improved compared with the baseline, especially the EPE indicator, which is improved by 10.5%. In addition, single-scale and multiscale masked autoencoders were added to the baseline network to conduct ablation experiments. For the single-scale architecture, the EPE indicator improved by 5.3% compared with that of the baseline network; for the multiscale architecture, the improvement was 10.5%. [Conclusions] The results of ablation experiments prove that the pyramid architecture can effectively integrate multiscale information and extract rich geometric features. Comparative experiments with other methods show the superiority of the proposed method. The multiscale masked autoencoder extracts powerful features by randomly masking and reconstructing the original point cloud, thereby reducing the impact of point cloud disorder and occlusion on the accuracy of scene flow estimation.
Developmental logic，functional positioning， and paradigm innovation of philosophy and social science laboratories in the digital-intelligence Era
LI Deli;XIONG Yan;[Objective]Philosophy and Social Science Laboratories (PSSLs) play a critical role in advancing the construction of New Liberal Arts， integrating social science resources， and driving research paradigm innovation. However， there remains no unified consensus on their functional positioning， while discussions on developmental paradigm innovation lack systematic analysis. This study proposes a dual-path development logic for PSSLs: "Critical Inheritance-Innovation through Historical-Realistic Evolution" and "Techno-Social Synergistic Co-Creation". It further clarifies PSSLs' functional positioning in: (1) cultivating interdisciplinarily innovative talents， (2) enabling cross-disciplinary scientific research innovation， (3) facilitating government-industry-academia-research interaction and translation， (4) supporting policy advisory and decision-making， and (5) promoting the global dissemination of Chinese discourse. A paradigm innovation framework encompassing data spaces， organizational development， pedagogical practices， scientific research， and knowledge production is constructed to provide insights for high-quality development of PSSLs in the Digital-Intelligence Era.[Methods]This study employed a literature analysis methodology to comprehensively review the current domestic research landscape on PSSLs. Through critical evaluation of existing scholarship， key research gaps were identified， leading to the proposition of PSSLs’ five core functional positioning dimensions:Cultivation of interdisciplinary innovative talents，Cross-disciplinary scientific research innovation，Government-industry-academia-research mutual translation，Policy advisory support for decision-making，Global dissemination of Chinese discourse.Subsequently， case analysis methodology was applied to examine developmental paradigm innovation in PSSLs. The research demonstrates that high-quality development of PSSLs can be advanced through innovations across five paradigm domains:Data spatial paradigms，Organizational developmental paradigms，Educational pedagogical paradigms，Scientific research paradigms，Knowledge production paradigms.[Results]Research Findings: PSSLs constitute vital institutional carriers for accelerating the establishment of China's self-directed philosophy and social science knowledge system， serving as new platforms for disciplinary prosperity. Their digitization-driven and intelligence-empowered qualitative transformation reflects a dialectical unity of historical and realistic logic， emerging from the synergy between technological and societal logic. theoretically， PSSLs are capable of integrating resources across diverse academic fields， dissolving disciplinary barriers， and generating theoretical insights that align with China’s national conditions and social development patterns. This provides foundational support for constructing an autonomous Chinese knowledge system in philosophy and social sciences.practically， PSSLs address complex challenges arising in the process of national governance by employing scientific research methods and advanced technical tools. They deliver forward-looking， targeted， and actionable policy recommendations and solutions， thereby supplying intellectual support for modernizing China’s governance system and governance capacity.[Conclusions]PSSL construction transcends the mere adoption of advanced technological tools; it represents key infrastructure driving disciplinary convergence， methodological renewal， knowledge production transformation， and social value creation. This shift marks an epistemological transition from small-data hypothesis verification to big-data pattern discovery， and from empirical summarization to simulation-based scenario projection. The evolution of PSSLs embodies continuous methodological innovation and provides pragmatic solutions for addressing complex societal challenges and enhancing modern governance. Current challenges include technological ethics and disciplinary discourse reconstruction. Future development requires strengthening humanistic guidance over technological applications to achieve systemic responses to complex social problems.
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Proteomics analysis of plasma with hepatocellular carcinoma based on label-free quantitative technology
LI Yilan;YU Wenjing;SHI Wenchao;LI Lan;[Objective] Early symptoms of hepatocellular carcinoma (HCC) are often occult， most patients are diagnosed at advanced stages with poor prognosis. Therefore， it is of great significance to deeply analyze the molecular mechanism of HCC occurrence and development and to search for sensitive early diagnostic biomarkers. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) plays a pivotal role in proteomic research. To solve the problem of low coverage in protein identification， which is caused by the significant differences in abundance and the complex composition of plasma proteins. The influence of different liquid chromatography gradient separation conditions on the identification of plasma proteins was investigated. Furthermore， the developed method was applied to the proteomic analysis of plasma samples from HCC patients and healthy individuals， with the aim of identifying early diagnostic biomarkers for cancer and providing support for the molecular mechanism of disease occurrence and development. [Methods] In this study， to investigated the effects of different liquid chromatography gradient separation conditions on the identification of plasma proteins， the liquid chromatography separation gradients were set at 56， 85， and 130 min. A standardized plasma proteomics analytical workflow suitable for use in a public research platform was ultimately established based on the results. Furthermore， combined with the label-free quantitative proteomics technology， differential expression proteins in plasma samples from HCC patients and healthy individuals were screened. Bioinformatics analyses， including molecular function and biological process， were performed to elucidate molecular signatures associated with HCC pathogenesis. [Results] After extending the separation gradient from 56 minutes to 85 minutes and 130 minutes， the number of identified plasma proteins increased from 588 to 988 and 1 261. Also， 64.1% and 63.6% of the proteins identified under the 56 min and 85 min separation gradients could be identified under the 130 min separation gradient， and 563 proteins could be exclusively identified， approximately 3.8 times more than those individually obtained under the 130 min separation gradient， which was attributed to the fact that the better separation of complex peptide samples and higher protein identification coverage could be achieved by the long separation gradient. Based on the above-mentioned merits， label-free quantitative analysis of the proteins from HCC patients and healthy individuals has been investigated. The total 2 062 protein groups were successfully quantified. Using P < 0.05 (T test) and 1.5-fold differences as the cutoffs， 56 proteins were considered to be differentially expressed， of which 33 were up-regulated and 23 was down-regulated in human plasma from HCC patients. Among them， as high as 69.6% of the significantly regulated proteins， such as CA1， LBP， TTR， and VTN， etc.， were reported as HCC associated proteins. These results were highly consistent with the results reported in the literature. In addition， the other differential proteins were not previously reported as HCC indicators and were found to have significant association with liver cirrhosis， fatty liver， and liver fibrosis. Bioinformatics analysis indicated that the differential proteins were involved in functions and processes closely related to the occurrence and development of HCC， such as serine-type endopeptidase inhibitor activity， haptoglobin binding action， immune response， and lipid transport， etc. The results indicates that the differential proteins may play a crucial role in the development of HCC， further research is ongoing to explore the potential of these proteins as biomarkers. [Conclusions] The standardized plasma proteomics workflow established in this study not only provides a valuable methodological framework for subsequent investigations in this field but also offers diverse technical solutions for public research platforms conducting plasma proteome profiling. The quantitative results of the plasma protein profile obtained in the study provide data support for the subsequent research on the mechanism of HCC development and potential biomarkers for the disease.
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Laboratory Safety Classification and Grading Based on Protection Level and Random Forest Algorithm
Hu Xinjie;Xia Qi;Liu Zhe;Song Xiaofei;Yan Jin;Liu Yuhuan;[Objective] The classification and grading of laboratory safety is a fundamental prerequisite for safety management in higher education institutions. In recent years， this aspect has gradually become a focal point in the safety inspection work conducted by the Ministry of Education in China. Currently， research on laboratory safety classification and grading primarily concentrates on a single dimension of hazard sources， specifically utilizing hazard sources and their quantities to evaluate risks and determine safety levels. However， the risk level of laboratories is essentially a composite function of both the probability of hazard source release and protective efficacy. Recent laboratory accidents have also indicated that incidents do not typically occur in the most hazardous laboratories but rather in those with the poorest protective measures. Therefore， constructing a dual-dimensional evaluation model based on "hazard sources - protective levels" holds significant theoretical value and practical implications. [Methods] The study adopts big data analytics based on the random forest algorithm as the final risk evaluation method. The research data consists of two parts: 19 hazard source parameters and 7 protection level parameters.Gradually optimize the classification method through the following three comparative methods: (1) the gauge evaluation method that only considers the hazard source; (2) the expert evaluation method based on the level of protection， where the full-time safety supervisor provides the classification results based on the protection level parameters and hazard source parameters; (3) the big data method based on the random forest， which uses the classification results from the expert evaluation method as the original data and obtains the results after modeling according to the random forest algorithm. Compare the three sets of data twice. Compare the gauge evaluation method with the expert evaluation method to study the changes in classification results based on the protection level parameters. Compare the expert evaluation method with the big data method to investigate whether the big data method based on the random forest algorithm can effectively replace the expert evaluation method. [Results]The grading results of the regulatory evaluation method and the expert assessment method show significant differences. The expert assessment method considers safety supporting facilities， relevant regulations and systems， and safety training and drills as core indicators for risk evaluation. Laboratories with fewer hazards exhibit an upward trend in risk levels due to incomplete protective systems， while laboratories with a high concentration of hazards， which generally prioritize the development of protective measures， show relatively lower risk leve. This leads to a concentration of safety evaluation results in the moderate risk category. Optimized big data methods have demonstrated the feasibility to replace traditional expert evaluation methods， achieving a classification accuracy of 95.7% and grading accuracy of 94.8%. [Conclusions](1) The expert evaluation method based on protection levels is more aligned with the actual needs of laboratory safety management compared to the rating scale evaluation method. Its risk grading results show a significant correlation with the concentration distribution pattern of potential hazards， aiding in precisely identifying high-risk laboratories that require enhanced supervision.(2) The big data method constructed using the random forest algorithm has demonstrated technical feasibility to replace expert evaluations. The accompanying graphical user interface (GUI) software overcomes professional barriers， enabling personnel from non-safety domains and computer professionals to perform classification and grading operations at any time. This approach ensures the scientific nature of evaluations while significantly improving work efficiency.(3) The future development directions for laboratory safety classification and grading work include an integrated information management platform， 3D visualization technology， efficient workflows， and fine-grained management.
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Solving Model and Experiment for Large-Scale Traveling Salesman Problems Based on Cluster Strategies
JIAO Dongbin;CHEN Zhiqing;WANG Fanghua;LI Ying;YANG Weibo;YAN Shi;[Objective]Integrating theory and practice is essential for training proficient AI professionals within the Emerging Engineering Education (3E) framework. This AI experiment employs the large-scale Traveling Salesman Problem (TSP)， which is a classic NP-hard challenge demonstrating the impracticality of exact methods at scale and the inconsistency of heuristic solutions， to connect abstract AI principles with hands-on implementation， offering a valuable learning opportunity for AI students. To address the high complexity， slow convergence， and poor scalability of existing approaches when applied to TSP instances with thousands of nodes， a novel cluster-based TSP framework， termed ClusterTSP， is proposed. [Methods]The proposed methodology strategically decomposes large-scale TSP instances into smaller subproblems via a clustering algorithm. This decomposition significantly reduces the computational burden compared to solving a single large instance.This "divide and conquer" strategy， aligning with efficient algorithm design principles， enables sophisticated optimization of the resulting subproblems. Following decomposition， ClusterTSP utilizes the representational power of deep learning， specifically employing Pointerformer， a cutting-edge method with notable TSP success， to optimize these smaller problems.Leveraging the Transformer network and its attention mechanisms， Pointerformer efficiently learns complex sequential dependencies to generate high-quality TSP tours. Applying it to clustered subproblems harnesses deep learning's ability to identify near-optimal local routes. This integration within a decomposition framework mitigates scalability issues common in end-to-end deep learning for very large TSPs. To construct a high-quality final tour that encompasses all the nodes of the original TSP instance， ClusterTSP incorporates a carefully orchestrated sequence of post-processing algorithms. These algorithms are designed to effectively merge the optimized subproblem solutions and further refine the resulting global path. Initially， an efficient multi-entry/exit greedy algorithm is employed to construct an initial global tour by intelligently connecting the optimized sub-tours generated by Pointerformer. This greedy approach provides a computationally inexpensive yet reasonably good starting point for subsequent optimization. Subsequently， a cluster boundary optimization algorithm is applied to specifically address the connections between nodes residing in different clusters， aiming to smooth transitions and eliminate potential suboptimal edges introduced by the initial decomposition. Finally， a 2-opt local search algorithm， a widely recognized and effective local optimization technique for the TSP， is implemented to iteratively improve the overall tour quality by systematically exploring small perturbations to the current solution and accepting those that lead to a shorter path. The synergistic interplay of these post-processing algorithms ensures enhanced solution quality by combining Pointerformer's localized optimization with the global coherence enforced by refinement steps. [Results]Extensive experiments on large-scale TSP instances (node size ≥103) demonstrate that ClusterTSP exhibits significant advantages in accuracy， efficiency， and scalability compared to the state-of-the-art deep learning benchmarks， including ACO， DRL＿PtrNet and Pointerformer.This advantage in solution quality becomes more pronounced with increasing problem size， and ClusterTSP effectively addresses the scalability limitations of traditional deep learning methods for large-scale scenarios. [Conclusions]Beyond its technical contributions， this research adopts a research-led teaching initiative， actively engaging students in the entire algorithm development and evaluation process.This hands-on experience fosters a deeper understanding of theoretical concepts， enhances practical skills， and significantly improves students' independent problem-solving abilities， exemplifying the "3E" initiative's emphasis on integrating theory and practice in AI education within an experimental teaching context.
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A Study on the Comprehensive Performance Evaluation of University Laboratories under the Drive of Informatization
Shang Lei;Wang Haijie;Yin Ruitao;He Rui;[Objective] The objective of this study is to address the critical issues faced by university laboratories， which are central to academic research and educational activities. The main challenges are the low level of informatization in performance evaluation， frequent safety incidents， and uneven resource distribution. These issues not only hinder the laboratories' operational efficiency but also pose significant risks to the safety of faculty， students， and the integrity of research outcomes. The importance of this study lies in its potential to enhance the management and operational efficiency of laboratories， thereby fostering a safer and more productive research environment that is capable of meeting the demands of modern academic research. [Methods] The development of the performance evaluation index system is based on an integrated laboratory data platform. This system employs the Fuzzy Analytic Hierarchy Process-Entropy Weight Method (FAHP-EWM) to determine the weights of various performance indicators. This method is chosen for its ability to integrate expert opinions with objective entropy measures， ensuring a balanced assessment. Experts evaluate the importance of different performance indicators， and entropy is used to measure the amount of information each indicator provides， helping to identify which indicators are most informative. This dual approach allows for a more nuanced understanding of each indicator's contribution to overall performance. The Fuzzy Comprehensive Evaluation approach is then applied to assess the overall performance of the laboratories. This approach involves defining evaluation criteria and membership functions for each criterion， converting performance data into fuzzy values， and aggregating these values to provide an overall performance score. This method is particularly useful for handling uncertainty and imprecision in performance data， which is common in real-world scenarios. It allows for a more flexible and comprehensive evaluation that can adapt to varying conditions and data quality. Additionally， input-output analysis is integrated to assess the operational efficiency of laboratories. This involves analyzing the inputs (resources， time， etc.) and outputs (research outcomes， publications， etc.) of the laboratories to determine their efficiency. This analysis reveals underutilized resources and inefficiencies， providing clear directions for process optimization. This method provides a quantitative measure of how well the laboratories are converting inputs into valuable outputs， which is crucial for optimizing resource use and improving overall performance. The system is designed to be scalable and adaptable， making it suitable for laboratories of different sizes and with varying research focuses. This adaptability ensures that the system can be tailored to the specific needs of each laboratory， enhancing its applicability and effectiveness. The integration of these methods into a single system allows for a comprehensive evaluation that considers multiple aspects of laboratory performance， from safety and resource management to research output. [Results] The empirical results from the implementation of this system demonstrate significant improvements in evaluation informatization. There is a notable reduction in the probability of safety accidents， and enhanced protection of national assets and the safety of faculty and students. The system also contributes to the optimization of resource allocation， ensuring that resources are used efficiently and effectively， which is crucial for the long-term sustainability of laboratories. These results highlight the system's ability to provide innovative insights into the management of university laboratories， offering a scientific， standardized， and efficient approach to laboratory management. [Conclusions] This study presents a robust and comprehensive framework for evaluating and enhancing the performance of university laboratories. The integration of advanced analytical techniques with practical management strategies has resulted in a system that is both scientifically sound and operationally feasible. The findings and methodologies presented here are expected to serve as a valuable reference for academic institutions and researchers worldwide， promoting the continuous improvement of laboratory management practices. By providing a structured and systematic approach to laboratory performance evaluation， this study aims to facilitate the transition towards more efficient， safe， and sustainable laboratory practices， ultimately contributing to the advancement of knowledge and innovation in the academic sphere.
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Study on the design and analysis methods of orthogonal experiment
Liu Ruijiang,Zhang Yewang,Wen Chongwei,Tang Jian(School of Pharmaceutics,Jiangsu University,Zhenjiang 212013,China)The importance of orthogonal experimental design and analysis is introduced briefly.The principle and characteristic are expounded.The design methods of orthogonal experiment and analysis methods of orthogonal experimental results are analyzed in detail,which afford fully systemic methods for orthogonal experimental design and analysis.Problems in orthogonal experimental design and analysis and development of software for orthogonal experimental design and analysis are also pointed out in the end.
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Research on statistical analyses and countermeasures of 100 laboratory accidents
Li Zhihong;Training Department,Kunming Fire Command School;This paper summarizes 100typical cases of laboratory accidents from 2001and analyzes the cases in fields of accident type,accident link,accident cause,dangerous substance category,etc.The result shows as follows:the fire disasters and explosive accidents are the main types of laboratory accidents;the dangerous chemicals,instruments and equipment,and pressure vessels are main dangerous substances;the instruments and equipment and reagent application processes are the main links of accidents;the violation of rules,improper operation,carelessness,wire short circuit and aging are the main reasons of accidents.It also puts forward the countermeasures and suggestions for the prevention and control of laboratory accidents in the following aspects:establishing complete safety management system,actively promoting standard construction of laboratory safety,strengthening laboratory safety education and training,and formulating and improving emergency plans for laboratory accidents.
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Constructing practice teaching system focusing on ability training
Zhang Zhongfu(Zengcheng College,South China Normal University,Guangzhou 511363,China)The economic and social development has given rise to an increasing demand for applied talents,and people have attached more and more importance to practice teaching.The practice teaching system should focus on ability training,build practice teaching system,adjust the practice teaching contents,reform practicing teaching pattern,coordinate practicing teaching administrating system,and constructing a scientific and reasonable quality ensuring system and a practicing teaching evaluation system.
[Downloads: 4,161 ] [Citations: 253 ] [Reads: 86 ] HTML PDF Cite this article
The application of studying fluorescence spectroscopy on protein
Yin Yanxia,Xiang Benqiong,Tong Li(College of Life Science,Beijing Normal University,Beijing 100875,China)Fluorescence spectroscopy is very important for studying protein structure and conformation changes.The concept and principle of fluorescence spectroscopy are introduced at first,then the application of studying fluorescence spectroscopy on protein is explained.
[Downloads: 5,113 ] [Citations: 252 ] [Reads: 67 ] HTML PDF Cite this article
The CNC machine tool with systematic work process and its application of teaching design
Li Yanxian(Department of Mechanical and Electronic Engineering,Nanjing Communications Institute of Technology,Nanjing 211188,China)According to professional training objectives and the main jobs of the structure of vocational skills and knowledge required to "CNC machine tools and spare parts" for the carrier,taking the CNC programming and operation of capacity-building as the center,this paper shows the design of the "knowledge of CNC machine tools,observation and analysis of CNC lathes,CNC milling machine to observe and analyze the processing center,programming and processing stepped shaft,threaded shaft of the programming and processing,hand wheel slot programming and processing,convex programming and processing of the template,the base of the programming and processing"of 9 items,25 learning environment,67 tasks,and one of the "convex template programming and processing" learning environment for the teaching unit design.
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Study on the design and analysis methods of orthogonal experiment
Liu Ruijiang,Zhang Yewang,Wen Chongwei,Tang Jian(School of Pharmaceutics,Jiangsu University,Zhenjiang 212013,China)The importance of orthogonal experimental design and analysis is introduced briefly.The principle and characteristic are expounded.The design methods of orthogonal experiment and analysis methods of orthogonal experimental results are analyzed in detail,which afford fully systemic methods for orthogonal experimental design and analysis.Problems in orthogonal experimental design and analysis and development of software for orthogonal experimental design and analysis are also pointed out in the end.
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Construction and actualization of new experimental teaching system for chemical specialty
YANG Jin-tian(Institute of Life Science,Huzhou Normal College,Huzhou 313000,China)The new system of chemical experiment teaching is constructed,and the comprehensive experiments,open experiments and research-oriented experiments are set up to improve the degree of source sharing,the efficiency of using equipment and the quality of experimental teaching,hence efficiently optimizing the practical abilities and fostering innovative spirit for the undergraduates are achieved.
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Practice and thinking of education of“College Students' Innovative and Entrepreneurial Training Program”based on tutor system
Qian Xiaoming;Rong Huawei;Qian Jingzhu;Office of Academic Affairs,Nanjing University of Technology;The innovation and entrepreneurship education has been included in the teaching and education program of college schools."College Students' Innovative and Entrepreneurship Training Program "has become an"Excellent Program"as one of the most important reform tasks in Ministry of Education.The tutor system is an effective way of innovative education and pilot training for both college schools and students.Students learn the method of innovation researches and technique of entrepreneurial process through the program.In the meanwhile,teachers in college schools find a new stage to improve their teaching ability.This article focuses on the project,practice and feasibility of the"College Students' Innovative and Entrepreneurial Training Program "under the tutor system.
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Experimental research on protein immunoblot assay
ZHANG Yan-wan,YE Jue,SHI Na,MENG Xian-min,WANG Lai-yuan(Central Laboratory,Fuwai Hospital for Cardiology,Chinese Academy of Medical Sciences,Beijing 100037,China)The paper discribes the important significance of protein immunoblot assay(Western blotting) in the research on protein,the experiment principle and the methods of protein immunoblot assay.A few main aspects of experiment technology methods are analyzed and discussed,and the research experience of protein immunoblot assay is also discribed.
[Downloads: 9,231 ] [Citations: 105 ] [Reads: 87 ] HTML PDF Cite this article