NetWork
Innovation and Practice of Laboratory Safety Management in Colleges and Universities---Taking the Construction of Inter-Collegiate Cross-Inspection Mode at University Level as an Example
Zhang Chaoyang;Meng Min;Li Lun;Yuan Weibin;Li Jinli;[Objective]With the intensified scientific research innovation， more complex experimental projects， and deepened interdisciplinary cooperation in colleges and universities， laboratory safety risks have become diversified and diffused， posing severe challenges. Statistics on 176 laboratory safety accidents from 1984 to 2024 show that accidents caused by management defects have a significantly high mortality rate. Problems such as irregular storage of hazardous chemicals and lax implementation of access systems reflect systemic management failures. The traditional "college-independent self-inspection" model has inherent limitations: management barriers weaken system implementation， single professionalism leads to blind spots in hidden danger investigation， and insufficient technical support results in fragmented rectification， seriously restricting safety management efficiency. Thus， constructing a new safety management mechanism with cross-subject collaboration， standardized operation， and full-process closed-loop， and transforming from passive accident response to active risk prevention， has become an urgent task to ensure the safety of teachers and students and support the sustainable development of scientific and technological innovation in colleges and universities， with great practical significance.[Methods] This study combines literature research， system design， and empirical verification to address the pain points of laboratory safety management. It innovatively constructs a three-in-one university-college cross-inspection model of "system diagnosis - on-site penetration - hierarchical governance". An inter-college inspection team with "university-college-student-administrative department" collaboration is established， and a professional think tank of interdisciplinary experts is formed to formulate the "Standardized Manual for Laboratory Safety Inspection". Based on the PDCA cycle theory， a six-link standardized process ("overall planning - system diagnosis - on-site verification - hierarchical governance - feedback communication - closed-loop tracking") is designed， integrating the "four-question working method" and "AB corner responsibility system". Supporting facilities include a dual-track access education system， an inter-college resource sharing pool， and an intelligent laboratory safety management system， forming a full-chain "organization-process-technology-guarantee" solution， which has undergone a two-year practical verification in the university.[Results] The practice achieves remarkable results: quantitatively， the recurrence rate of hidden dangers drops from 60% to 10%， the average rectification cycle shortens from 14 to 5 days (65% acceleration)， the safety management compliance rate rises from 80% to 95%， and the missing rate of hazardous chemical records plummets from 35% to 10%. Qualitatively， safety responsibilities cover every student， the training coverage rate of new teachers reaches 99%， and the qualified rate of teachers' and students' emergency equipment operation increases from 65% to 95%. The conversion rate of excellent inter-college management experience hits 80%， forming norms like "clearing up after use". A responsibility system of "full participation and layered responsibility" and a safety culture of "learning from each other" are established， realizing a in-depth transformation from "passive supervision" to "active self-discipline". Its core innovation lies in breaking management barriers through inter-college collaboration， improving investigation accuracy with standardized processes and intelligent technologies， and ensuring rectification effectiveness via hierarchical governance and closed-loop tracking. [Conclusions] The constructed university-college cross-inspection model effectively solves the problems of weakened system implementation， investigation blind spots， and fragmented rectification in traditional laboratory safety management through methodological innovation， technology-driven upgrading， and mechanism restructuring， optimizing safety management efficiency systematically. Scientific， operable， and adaptable， this model integrates interdisciplinary resources and strengthens full-process closed-loop control， providing a replicable paradigm for agricultural， forestry， and comprehensive universities. Its promotion helps advance the long-term， scientific， and intelligent transformation of laboratory safety governance in colleges and universities， builds a solid safety barrier for scientific and technological innovation， and contributes to the construction of a powerful education and science and technology country.
Development and experimental teaching design of a distributed synchronous data acquisition platform for the industrial internet of things
MA Wenjian;XIAO Xing;ZHANG Yiguo;CHEN Kai;[Objective] This study aims to develop a distributed data acquisition platform with both high-precision time–frequency–phase synchronization and engineering practicality for the Industrial Internet of Things (IIoT). It also addresses the persistent teaching bottleneck where experiments in electronic information courses are disconnected from real engineering scenarios， failing to cultivate students’ abilities to solve complex engineering problems. Furthermore， it intends to systematically transform the platform's core technologies and research methods into experimental teaching resources， thereby enhancing students' capabilities in solving complex engineering problems and hardware–software codesign. [Methods] The platform takes the Fudan Micro Qing Long series Programmable Logic (PL) + Processing System (PS) heterogeneous System-on-Chip as the core and constructs a distributed synchronous data acquisition architecture based on the Precision Time Protocol (PTP). To address the key problems of substantial jitter in soft timestamps， poor scalability of hard timestamps， and lack of sampling synchronization in traditional PTP implementations， this study proposes a three-level clock synchronization mechanism， double-edge triggering technology， and a sampling clock phase alignment method. Through hardware–software codesign， high-precision synchronization in three dimensions (time， frequency， and phase) is achieved. Specifically， the PL section undertakes real-time logical tasks such as hardware timestamping， clock synthesis， and sampling triggering. In contrast， the PS section hosts the protocol stack and upper-layer control functions. A closed-loop regulation system composed of a digital-to-analog converter and a voltage-controlled crystal oscillator is adopted for fine frequency synchronization， and a mixed-mode clock manager is used to dynamically adjust the phase of the sampling clock， effectively solving core issues such as soft timestamp jitter， insufficient scalability of hard timestamps， and inconsistent sampling edges in traditional schemes. Meanwhile， a four-stage progressive experimental teaching system (basic verification， advanced testing， comprehensive evaluation， and open innovation) is constructed that centers on the developed platform， forming a 20-class-hour project-based teaching chain that covers the entire process of hardware deployment， core algorithm optimization， and overall system performance tuning. [Results] Test results show that the average time synchronization error between distributed nodes of the developed platform is 3.3 ns with a standard deviation of 4.9 ns and a maximum time deviation of 16.6 ns. Additionally， the frequency synchronization deviation converges to ±15 ppb， and the time deviation converted from the sampling phase deviation ranges from -12.2 ns to 16.4 ns. The comprehensive synchronization performance is superior to typical baseline methods and meets the requirements of industrial-grade high-precision data acquisition. Teaching practice verifies that hierarchical progressive project-based experiments can effectively guide students to complete the full-process training from system construction to algorithm optimization and performance evaluation， greatly improving their abilities in system integration， algorithm optimization， and engineering expression. [Conclusions] This study successfully develops a high-precision distributed synchronous data acquisition platform that meets IIoT requirements， and the proposed multiple synchronization methods effectively ensure the consistency of cross-node data in time， frequency， and phase. By systematically transforming scientific research achievements into a stepped experimental teaching chain， a virtuous cycle of technology development， educational empowerment， and competency enhancement is formed， providing a referenceable and scalable practical paradigm for industry–education integration in the IIoT field.
Application of a low-cost and high-efficiency PIV integrated measurement system in fluid mechanics
FU Xiaoli;QIN Jiasheng;ZHANG Zhen;SHEN Chao;MO Zicheng;[Objective] Particle image velocimetry (PIV) is a common noncontact technique for flow-field visualization and measurement. However， its application in educational contexts is often limited by the high cost of professional equipment， complex operation procedures， and substantial time delays between image acquisition and analysis. To address these challenges， this study develops an integrated， low-cost， and real-time PIV measurement system specifically designed for teaching fluid mechanics. The system provides a convenient and efficient image analysis platform， enabling students to quickly observe changes in flow patterns during experiments and deepen their understanding of fundamental fluid phenomena. [Methods] The proposed system integrates a smartphone camera as the image acquisition device with a custom Python-based analysis platform. The platform has a layered architecture comprising a user interface layer， a business logic layer， a data processing layer， and an infrastructure layer. The four key functional innovations include (1) real-time video stream acquisition via the IP camera application， enabling immediate capture and display of flow images; (2) an adaptive parameter module that automatically configures PIV analysis parameters (e.g.， interrogation window size， overlap ratio， signal-to-noise threshold， and outlier replacement) based on image quality， thereby reducing the need for manual tuning; (3) direct processing of video inputs without preframe extraction， thereby streamlining the workflow; and (4) automated generation of multiple flow visualization outputs， including velocity vector plots， vorticity contour plots， and streamwise fluctuation intensity plots， eliminating additional postprocessing steps. The experimental setup consists of a small-scale circulating water channel， a low-power continuous wave laser sheet for illumination， a cylindrical obstacle， and seeded tracer particles. The system was evaluated in a cylinder flow experiment at low Reynolds numbers (Re = 100–400)， with a fixed frame rate of 30 fps to ensure image stability under low-velocity conditions. [Results] The system successfully captured the evolution of flow patterns around a cylinder across the Reynolds number range. At Re = 100， a stable laminar vortex pair was observed behind the cylinder with symmetrical vorticity distribution and low fluctuation intensity. As the Re increased to 200， periodic vortex shedding emerged， indicating the initial formation of a Kármán vortex street. At Re = 300 and Re = 400， the vortex shedding frequency markedly increased， the wake region broadened， and the vorticity distribution became more alternating and complex. Streamwise fluctuation intensity also increased markedly， reflecting enhanced flow instability. These observed stages—from steady vortex pairs to developed vortex streets—closely match classical fluid dynamics theories， confirming the system’s accuracy and reliability in capturing key transitional phenomena. Beyond the physical results， the system demonstrated clear educational benefits: it lowered the operational barrier for students， provided immediate visual feedback during experiments， and supported interactive learning through real-time analysis and multiformat outputs. [Conclusions] This work presents an integrated， smartphone-based PIV measurement system that effectively overcomes cost， complexity， and latency limitations associated with conventional PIV setups in teaching environments. By combining accessible hardware with intelligent， adaptive software， the system enables real-time flow-field capture， processing， and visualization. Experimental validation in a cylinder flow study shows that the system can accurately resolve flow evolution at low Reynolds numbers， making it a practical and effective tool for fluid mechanics education. The system not only enhances teaching efficiency and student engagement but also encourages hands-on experimentation and deeper conceptual understandings. Its low-cost and user-friendly design holds strong potential for widespread adoption in academic laboratories and instructional settings.
Experimental testing and numerical simulation of partially cohesive jet formation in high-energy high-entropy alloy liners
ZENG Hanlin;LIU Haoxuan;WANG Benpeng;JIN Ke;GUO Xun;SUI Mingbin;LIU Xudong;LI Tianxiang;XUE Yunfei;[Objective] The shaped charge warhead is a critical means of neutralizing armored and fortified targets. It primarily destroys the target through explosive detonation， which results in the liner being crushed to form a high-speed jet. Traditional copper liners form condensed jets， resulting in deep penetration but producing extremely limited post-target damage. Conversely， reactive materials such as Al/PTFE produce divergent particle jets with strong after-effects but suffer from insufficient penetration capability. Energetic high-entropy alloys (EHEAs) can form a “partially cohesive jet，” which is cohesive at the core to ensure penetration and divergent at the periphery to enhance behind-target damage， thereby offering a novel solution to the trade-off between penetration depth and post- effect damage. However， the jet coherence of EHEAs remains challenging to quantify， and no suitable simulation model currently exists. [Methods] An integrated test system for jet morphology and post-effect damage was designed. This system uses pulsed X-ray technology to capture the jet morphology and simultaneously assesses penetration and post-effect damage capabilities through the main and post-effect targets. The study proposes a “jet cohesion factor，” defined as the ratio of the area of the central condensed region in the jet X-ray image to the total area. This factor enables a quantitative description of the jet’s cohesive state. Additionally， the post-effect damage is calculated by analyzing the scattering angles formed by the perforation distribution on the target surface. To overcome the limitation that the current SPH method cannot quantitatively control the jet cohesion factor， this study develops a secondary correction algorithm for jet morphology based on the SPH algorithm. By introducing an improved Sigmoid function to regulate jet particles， the algorithm achieves a concentrated jet core and controllable edge divergence， thereby accurately reproducing the partially cohesive jet morphology observed in EHEAs. [Results] The present study focused on two Ti–Zr–V–Nb–Al EHEAs with different mechanical properties (Alloy A and Alloy B). The experimental findings demonstrated that Alloy A， characterized by its reduced plasticity (4.8%)， exhibited a lower jet cohesion degree (67.5%) and a larger post-effect scattering angle (31.2°). The post-effect target displayed a damage pattern consisting of a main hole accompanied by numerous small holes. In contrast， Alloy B， which demonstrated higher plasticity (8.4%)， exhibited a higher jet cohesion degree (78.6%) and a smaller scattering angle (29.6°). The post-effect damage consisted mainly of a main hole accompanied by several larger holes. By adjusting the algorithm parameters， the simulated jet cohesion factors for Alloys A and B were determined to be 67.9% and 77.8%， respectively. Additionally， the deviations of the simulation scattering angles from the experimental values were found to be less than 10%， the simulation results were highly consistent with the experimental data. [Conclusions] The present study successfully developed an integrated testing methodology and a numerical simulation method for the partially cohesive jets formed by EHEA liners. By incorporating the jet cohesion factor， a quantitative approach is provided for elucidating the jet’s cohesive state. Furthermore， the jet’s morphology control algorithm effectively addresses the lack of adequate simulation models. The high consistency (over 90% agreement) between experimental and simulation outcomes for critical parameters (cohesion factor， scattering angle) substantiates the efficacy of the proposed methodologies. These findings not only provide critical technical support for the rapid performance evaluation and compositional microstructure optimization of EHEA liners but also offer a novel scientific approach for assessing the multifunctional damage efficiency of shaped charge warheads.
Development of a compression-unloading apparatus for goaf gangue and its teaching applications
CHI Xiaolou;YANG Jiaxu;YANG Ke;CHANG Jucai;CHEN Denghong;PENG Zhiyan;LI Chuanming;[Objective] The coal mining face， comprising the goaf gangue and the regenerated roof， undergoes a continuous mechanical process involving compression， lateral confinement， unloading， deformation， and failure. Conventional triaxial testing equipment is primarily utilized for closed loading conditions. The lateral boundaries of the system are typically fixed， and the formation of a free surface during unloading is challenging to replicate. Consequently， it is challenging to simulate the entire mechanical trajectory from gangue compaction to single-sided unloading and instability failure. In experimental teaching methods， direct observation of this process can be challenging for students. The stress path， boundary transformation， crack development， and failure mode are often abstract and difficult to comprehend. To address these challenges， a novel apparatus for the compression and unloading of goaf gangue has been developed. The apparatus was utilized to formulate a teaching experiment that replicated the comprehensive process of gangue compression， lateral pressure loading， single-sided unloading， and failure. [Methods] The apparatus is composed of a top-loading system， a hydraulic pumping apparatus， a pressure-unloading chamber， a lateral confining pressure loading system， a loading monitoring and control apparatus， and an external monitoring system. The top-loading system exerts axial load and provides vertical support. The hydraulic pumping apparatus is responsible for the storage and transportation of hydraulic oil， in addition to providing power to the actuating cylinders. The pressure-unloading chamber is utilized for specimen placement， side boundary control， and single-sided unloading. The lateral confining pressure loading system exerts lateral pressure on the specimen， thereby simulating a three-dimensional stress state. The loading monitoring and control box is designed to facilitate connectivity among disparate loading channels， meticulously record pressure and displacement signals， and regulate the pressurization and pressure relief of each oil circuit. The external monitoring system is designed to record acoustic emission signals， surface deformation， and crack evolution during the compression and unloading processes. Mudstone and sandy mudstone from a typical mining area in Huainan were selected as aggregates， and local yellow mud was used as the cementing material. Considering the chamber size， size effect， and particle-size characteristics of broken gangue， the gangue aggregates were divided into five distinct particle-size ranges. The range of sizes includes 0–4， 4–8， 8–12， 12–16， and 16–20 mm. The mass ratio of gangue， yellow mud， and water was 20:6:3. The experiment comprised four stages: side-confined compression， initial stress loading， dynamic unloading， and failure loading. Throughout the process， the stress-strain response， acoustic emission characteristics， and full-field deformation of the unloading surface were meticulously documented. [Results] The apparatus demonstrated its efficacy by successfully recording the complete loading and unloading process of cemented gangue specimens. In the side-confined compression stage， the stress-displacement curves exhibited three phases: pore compaction， initial compression， and dense compression. The displacement is defined as the axial loading displacement recorded from the initial filling height of 150 mm. In the phase of pore compaction， the stress increased gradually and remained below 0.5 MPa. In the initial compression phase， the stress increased from 0.26–0.45 MPa to 0.46–1.19 MPa. In the dense compression phase， the stress increased rapidly， and the differences in bearing among the various particle-size groups became apparent. In the unloading and failure stage， the specimens exhibited four mechanical response phases: compaction elasticity， yield， plastic strengthening， and post-peak failure. The maximum tensile strength exhibited a decline from 3.8 MPa in the 0–4 mm group to 2.7 MPa in the 16–20 mm group. The acoustic emission monitoring system captured high-amplitude pulse clusters and high-energy release events during the peak stress drop. The detachable side plate facilitated observation of the unloading surface through digital image correlation. The small-particle specimens primarily exhibited relatively uniform mesh-like cracks， while the large-particle specimens displayed localized inclined shear bands， structural collapse， and substantial angular fragments. [Conclusions] The developed compression-unloading apparatus is capable of reproducing the mechanical process of goaf gangue from axial compression to lateral confinement， single-sided unloading， and final failure. This method effectively addresses the limitations of conventional triaxial equipment in simulating the formation of a free surface during unloading processes. The apparatus demonstrates notable compatibility with acoustic emission monitoring and digital image correlation techniques. The teaching experiment， based on this apparatus， includes specimen preparation， loading path design， monitoring system installation， data processing， result analysis， and group discussion. This approach assists students in comprehending the mechanical behavior of goaf gangue and the regenerated roof from the perspective of stress response， acoustic damage， and visible deformation. The experiment enhances the practical teaching content of mine pressure and strata control， improves students’ ability to analyze complex mining engineering problems， and provides a useful reference for transforming research equipment into undergraduate experimental teaching resources.
Teaching experiment design for the preparation of an optical fiber cholesterol sensor based on surface plasmon resonance
LI Like;LI Xiang;HAN Bo;WANG Qiaoyun;ZHAO Yong;[Objective] Optical fiber surface plasmon resonance (SPR) sensors have received widespread attention in the fields of early disease diagnosis， biomolecule detection， and environmental monitoring due to their advantages of high sensitivity， label-free status， real-time monitoring， and strong anti-interference ability. Cholesterol is an important human biomolecule， and abnormal levels are closely related to major diseases such as cardiovascular disease and Alzheimer’s disease. The existing cholesterol detection methods have drawbacks such as high cost， complex operation， and limited sensitivity. Based on this， a teaching experiment integrating scientific research achievements for the design and preparation of an optical fiber SPR cholesterol sensor is introduced into an optical-fiber sensor course， helping students understand the cutting-edge dynamics of the discipline， cultivate scientific research thinking， and enhance their comprehensive professional competencies. [Methods] The experiments used a reflective structure of multimode fiber–single-mode fiber fusion as the optical-fiber SPR sensing structure， with cholesterol oxidase as the sensitive material. The fabrication of the sensing probe consists of three main steps: structure splicing， gold film coating， and cholesterol oxidase functionalization. The optical fiber structure fusion is accomplished using an optical fiber knife and S179 fusion. The gold film coating is completed by a small ion sputtering instrument JS1600， with a sputtering current of 7 mA， a sputtering time of 80–160 s， and a chamber vacuum of 0.1 mbar/Pa. Thus， a uniform and firm gold coating of approximately 30–70 nm is sputtered onto the fiber sensing area. The cholesterol oxidase functionalization is accomplished through covalent bonding. Firstly， the gold-coated optical-fiber probe is immersed in an 11-mercaptoundecanoic acid solution to achieve carboxylation of the gold film surface. Then， an N-hydroxysuccinate/1-ethyl-3- (3-dimethylaminopropyl)carbodiimide hydrochloride mixed solution is used to activate the carboxyl groups on the gold film surface， to reduce the binding energy between the amino and carboxyl groups. Finally， the probe is immersed in the cholesterol oxidase solution. Through the covalent bonding between the amino groups in the cholesterol oxidase and the carboxyl groups on the gold film surface， the cholesterol oxidase is uniformly and firmly modified on the surface of the optical fiber. During the detection process， the cholesterol oxidase undergoes an oxidation–reduction reaction with the cholesterol molecules in the test environment， thereby decomposing cholesterol into 4-cholesterene-3-one and H2O2. This changes the refractive index of the sensing probe surface， which in turn shifts the SPR wavelength. Therefore， by tracking the resonance wavelength shift in the SPR spectrogram， cholesterol concentration detection can be achieved. [Results] Experiments confirmed that the optimal gold plating time for the sensing probe is 140 s， at which point the sensing probe has the highest refractive index sensitivity of 2 678 nm/RIU. Scanning electron microscopy characterization of the fiber end face showed that when the coating time is 140 s， the thickness of the gold film is about 50 nm. In addition， experiments also confirmed that the optimal sensing area length of the sensing probe is 4–8 mm. By modifying cholesterol oxidase on the surface of the optical fiber， sensitive determination of cholesterol concentration can be achieved. As the cholesterol concentration increases， the SPR resonance wavelength gradually redshifts. Within the range of 0–50 nmol/L， there is a good linear fit between the cholesterol concentration and the resonance wavelength， with a linear sensitivity of 0.182 nm/nmol/L. Furthermore， the cholesterol sensor exhibits excellent stability in cholesterol solutions and good specificity for cholesterol molecules， without being affected by other biomolecules. [Conclusions] This teaching experiment design is characterized by its cutting-edge nature， comprehensiveness， and practicality. It not only enables students to deeply understand the principles and practical applications of optical fiber sensors but also helps them master the basic methods of nanomaterial preparation， sensor construction， and performance testing. Additionally， it cultivates students' scientific research thinking and innovative practical abilities， promotes the integration of interdisciplinary knowledge， and provides a feasible solution for teaching reform in the optical fiber sensor course.
Experimental Design for Dynamic Impedance Analysis of Alkaline Water Electrolysis under Wind and Solar Fluctuations Conditions
Chang Zheng;Wang Qi;Hu Yichao;Lu Jinshu;He Xiangming;[Objective] Conventional laboratory instruction in alkaline water electrolysis is mainly based on steady-state operation， such as polarization curves and gas production measurements， which cannot adequately explain the dynamic response of electrolyzes under fluctuating renewable power. Under wind and photovoltaic coupling conditions， hydrogen production is strongly affected by gas–liquid two-phase transport， bubble accumulation on electrode surfaces， and mass-transfer limitations in porous structures. These phenomena are difficult to interpret through traditional confirmatory experiments， so students have limited opportunities to analyze noisy electrochemical signals or connect data with physical mechanisms. To address the gap between laboratory teaching and practical engineering scenarios， this study develops a research-oriented comprehensive experiment for dynamic impedance analysis of alkaline water electrolysis under wind and solar fluctuation conditions. [Methods] The experiment was designed around the idea of using impedance spectroscopy as an “electrochemical microscope.” A modular alkaline water electrolysis platform was constructed with a near-zero-gap cell， nickel-based electrodes， electrolyte circulation， temperature regulation， and gas–liquid separation units. To simulate fluctuating renewable input in a controllable way， a stepwise AC-DC superimposed excitation strategy was adopted. Different DC bias currents were applied sequentially， and a small sinusoidal perturbation was introduced at each operating stage to obtain full-frequency electrochemical impedance spectra. Students were guided to interpret the response in different frequency regions and distinguish ohmic loss， charge-transfer behavior， interfacial capacitance， and diffusion-related impedance. Because dynamic gas evolution caused random noise in the raw signals， Python-based processing was introduced for signal cleaning， including high-frequency artifact correction， abnormal-point elimination， and low-frequency smoothing. After preprocessing， equivalent-circuit modeling was carried out. A conventional model and a dynamic correction model containing a Warburg diffusion element were compared to reveal the effects of bubble shielding and pore blocking on hydrogen production efficiency. [Results] Teaching practice and model analysis showed that the proposed experiment effectively transformed abstract dynamic hydrogen production behavior into an observable and analyzable process. After signal cleaning， the electrochemical spectra became more regular and the reliability of subsequent fitting was improved. Compared with the conventional circuit， the corrected model including the Warburg element described the impedance characteristics under high-current dynamic conditions more accurately， especially in the low-frequency region associated with mass transfer. At relatively low current densities， both models could characterize the interfacial electrochemical process reasonably well. However， as current increased， the conventional model gradually failed to reproduce the diffusion tail， whereas the corrected model maintained high fitting quality. Parameter evolution indicated that the solution resistance changed little with increasing current， while the charge-transfer resistance decreased gradually. In contrast， bubble-related resistance and diffusion-related impedance increased significantly in the high-current region， indicating that the limiting step shifted from interfacial kinetics to transport restriction caused by intensified bubble accumulation and pore blockage. [Conclusions] The proposed experiment extends alkaline water electrolysis teaching from steady-state verification to dynamic diagnosis and mechanism-oriented analysis. By integrating dynamic excitation， signal cleaning， and physically interpretable modeling into one framework， it enables students to identify transport bottlenecks in renewable-powered hydrogen production and understand the coupling between electrochemical reaction and two-phase flow. The experiment also promotes interdisciplinary training by combining chemical engineering， electrochemical testing， automatic control， and Python-based data analysis. It provides an effective teaching approach for cultivating students’ data-driven thinking， model-based reasoning， and innovation capability in hydrogen energy under the background of emerging engineering education.
A high-throughput multiplex RT-qPCR assay for detecting eight pathogens in experimental mice
Liu Huiru;Tang Yuxin;Ding Wanping;Xu Yuanyuan;Xiao Junhua;[Objective] This study aimed to establish an efficient multiplex， broad-spectrum real-time quantitative polymerase chain reaction (RT-qPCR) assay for the simultaneous screening of eight important pathogens prevalent in experimental rats and mice. These included murine rotavirus， Filobacterium rodentium， Cryptosporidium spp.， Bordetella pertussis， Klebsiella oxytoca， Demodex spp.， Campylobacter jejuni， and Helicobacter rodentium. This assay was developed to address the throughput， speed， and coverage limitations inherent to conventional detection methods.[Methods] Specific primers and TaqMan probes were designed based on conserved genomic sequences of the target pathogens using bioinformatic analysis. These components were integrated using a “three-channel fluorescence grouping” strategy to establish a one-step multiplex RT-qPCR workflow. A comprehensive methodological validation was performed， including assessments of the linear range， limit of detection (LOD)， specificity， and robustness.[Results] The assay demonstrated a broad linear range of 101–10? copies/μL， excellent amplification efficiency of 91%–109% (R > 0.99)， and a low LOD of 12.5 copies. The coefficient of variation for all technical replicates was <1%. Cross-reactivity testing confirmed high specificity， as amplification was obstructed by potentially interfering DNA from mouse intestinal contents or the Escherichia coli genome. Furthermore， performance remained stable without any pronounced degradation of the reaction mixture after repeated freeze–thaw cycles.[Conclusions] The established octoplex RT-qPCR method is characterized by its simplicity， rapidity， high sensitivity， specificity， and robustness. It enables simultaneous detection of pathogens across categories， including viruses， bacteria， and parasites， thereby providing an efficient and reliable molecular tool for large-scale health monitoring， early disease diagnosis， and microbiological quality control in experimental rats and mice.
Design and teaching application of mechanical property testing device based on indentation method
YANG Bin;WANG Yansong;JIANG Wenchun;SHAO Xiaoming;SUN Guanghua;SONG Huiwei;[Objective] Conventional mechanical property testing methods， including uniaxial tensile and impact tests， are predominantly destructive. These methods are inherently disruptive， cumbersome to perform， and often impractical for the in-service inspection of pressure vessels in engineering environments. While the indentation technique has demonstrated potential as a micro-destructive testing method that derives mechanical properties from load–displacement curves， its application remains largely limited to industrial evaluations. Consequently， current engineering education frameworks are not fully aligned with modern practices， resulting in students receiving limited exposure to modern mechanical property testing technologies. To address this critical discrepancy， the present study developed an integrated mechanical testing apparatus based on the continuous spherical indentation method. The objective was to establish a unified platform that integrates laboratory validation with real-world field operations， thereby enhancing the practical and innovative skills of engineering students. [Methods] To achieve these objectives， the experimental device was designed with a highly modular configuration， encompassing mechanical， control， and data processing modules. The mechanical module features a lightweight alloy frame that is integrated with versatile fixtures， including U-shaped and magnetic clamps. These fixtures are suitable for both flat and curved specimens commonly encountered in engineering environments. The control module employs a hybrid software-hardware configuration， integrating a microcontroller with high-precision sensors for displacement and tension-compression measurements. This configuration ensures accurate signal capture while mitigating electromagnetic interference. The data processing unit incorporates a continuous spherical indentation algorithm that facilitates the automated conversion of raw load-depth data into true stress-strain curves. This capability enables the direct extraction of critical mechanical parameters. Validation was conducted through a series of comparative experiments on three representative pressure vessel steels. The following materials were utilized: Q235B， 45 steel， and Q345R. A spherical indenter with a diameter of 1.5 mm was used under a preload of 5 N， and the loading rate was maintained at 0.4 mm/min. Eight consecutive loading-unloading cycles were executed， and the outcomes were systematically compared with those of standard uniaxial tensile tests. Furthermore， a simulated field experiment was designed to assess a large-scale Q245 carbon steel pressure vessel to evaluate local mechanical properties across the base metal， heat-affected zone， and weld seam. [Results] The validation experiments demonstrated the high accuracy and reliability of the developed indentation testing device. A comparison was made between the indentation-derived data and the corresponding standard uniaxial tensile test outcomes for the three selected vessel steels. The relative errors for yield strength ranged from -4.29% to 4.08%， while those for tensile strength ranged from -2.78% to 3.32%. The maximum recorded deviation remained below 5% threshold， thereby satisfying the stringent precision requirements for both academic experiments and engineering applications. Furthermore， the on-site simulation experiment successfully differentiated the mechanical properties variations within the welded joints of the Q245 steel vessel. Micro-destructive testing revealed the performance gradient， indicating a stable and uniform base metal， as well as pronounced performance fluctuations within the weld seam due to thermal processing. These findings were accompanied by intermediate properties observed in the heat-affected zone. From a pedagogical perspective， these practical implementations enabled students to develop a nuanced understanding of the discrepancies between idealized laboratory conditions and the intricate dynamics present in complex field environments. This enhanced their awareness of engineering norms and rapid deployment strategies， thereby fostering a more comprehensive and nuanced understanding of engineering practices. [Conclusions] The development and deployment of this indentation-based testing apparatus effectively addresses the prevalent limitations associated with conventional destructive testing in educational settings. The integration of interdisciplinary methodologies and advanced sensing technologies enables the device to serve a dual purpose， supporting fundamental experimental teaching and complex engineering field simulations. The high-precision acquisition of load-depth information， in conjunction with flexible structural adaptations， demonstrates significant practical engineering value. The integration of this apparatus into the curriculum has been demonstrated to have a substantial impact on students’ technical proficiency and problem-solving skills. It offers a robust and innovative instructional paradigm that has been tailored to the contemporary engineering education landscape.
ROS-based experimental platform for network attack and detection in networked multi-robots
MA Lei;GUO Tilei;WANG Guoqing;DAI Wei;YANG Chunyu;[Objective]Networked robot cooperative control systems operating over open networks are vulnerable to cyber-attacks such as false data injection， replay， and denial-of-service， which can undermine leader–follower formation stability and control performance and complicate systematic security experiments. To address this issue， this paper designs and implements a ROS-based experimental platform for network attacks and threat detection in networked robots， integrating cooperative control， attack injection， and intelligent detection into a unified framework for teaching and research. [Methods]Built on the ROS communication framework and the Gazebo simulation environment， this platform includes a leader–follower formation control subsystem， a network attack injection subsystem， and a network attack detection subsystem. The leader–follower formation control subsystem facilitates the exchange of position and velocity information between a leader robot and multiple followers through ROS topics， supports common motion tasks like straight-line and circular trajectory tracking and various formation patterns， and offers a visualization interface that displays robot poses， inter-robot distances， and formation errors in real time. This provides an intuitive way to observe how cooperative behavior degrades under malicious interference. The network attack injection subsystem utilizes standard network analysis tools to identify host and traffic characteristics， creates a man-in-the-middle environment between the control workstation and the robots， and employs script-based configuration of packet payloads， sending rates， and target ports to simulate representative attack scenarios， including falsified state information， replay of historical data， and flooding-based denial-of-service， with adjustable intensity and duration. On the defense side， the detection subsystem constructs temporal samples by jointly analyzing network traffic statistics and the physical states of the robots， aligns and segments these heterogeneous data streams using timestamps and sliding time windows， and performs deep multimodal data fusion through feature-level concatenation and normalization before inputting them into a proposed CNN–BiLSTM–Attention model. In this model， convolutional layers extract local spatiotemporal patterns from the fused features， the bidirectional LSTM captures long-term dependencies between network conditions and cooperative movement， and an attention mechanism highlights time segments more indicative of abnormal behavior. The system then classifies attacks through a softmax output layer. Training involves weighted loss functions and regularization to address class imbalance and enhance generalization. [Results]Experimental results from datasets collected under normal operation and multiple attack scenarios demonstrate that the platform can reliably support multi-robot leader–follower formation simulations and accurately reproduce phenomena such as formation divergence， follower lag， increased communication delay， and higher packet loss. Compared to baseline models that only use network traffic or physical states as inputs， the proposed CNN–BiLSTM–Attention detector with deep multimodal data fusion achieves higher overall accuracy， precision， and F1-scores， and exhibits more balanced performance across attack types， especially those that are hard to distinguish using a single modality. These results show that combining attack injection experiments with multimodal learning significantly improves attack detection sensitivity and robustness. [Conclusions]Overall， the platform provides a comprehensive experimental chain—from theoretical explanation and attack simulation to intelligent defense—for network security education in cooperative robotic systems. Additionally， it offers a scalable and easily extendable testbed for investigating complex attack scenarios and developing cyber-physical defense strategies in realistic networked robot environments.