Low Efficiency Research Articles

Generating Payloads of Power Monitoring Systems Compliant with Power Network Protocols Using Generative Adversarial Networks

In the network environment of power systems, payload generation is used to construct data packets, which are used to obtain data for the security management of network assets. Payloads generated by existing methods cannot satisfy the specifications of the protocols in power systems, resulting in low efficiency and information errors. In this paper, a payload generation model, LoadGAN, is proposed by using generative adversarial networks (GANs). Firstly, we find segmentation points to cut payloads into different segment sequences using sliding window schema based on Bayesian optimization. Then, we use different payload segments to train several child generators to generate corresponding parts of a whole payload. Segment sequences generated by these generators are assembled to form a whole new payload that is compliant with the specifications of the original network protocol. Experiments on the Mozi botnet dataset show that LoadGAN achieves precise payload segmentation while maintaining a high payload effectiveness of 85.5%, which is a 40% improvement compared to existing methods.

The role of international organizations in the protection and restoration of the cultural heritage of Ukraine in the conditions of armed aggression: Financial, economic and legal aspects

The article attempts to analyze the role of international organizations in the protection and restoration of the cultural heritage during war conflicts. The case of Ukrainian ongoing conflict is considered, based on systematization of UNESCO documents and activities, as well as the case of Syria as a ‘testing ground’ for UNESCO in efforts on protection and restoration of cultural heritage damaged due to hostilities. It is claimed that UNESCO in fact showed its low efficiency in protecting cultural heritage, but is capable of providing reasonable steps of post-war restoration and preventing illegal trade of stolen cultural heritage. The expedience of developing international law grounds for protection of cultural heritage is emphasized, together with employing mechanisms of public-private partnership in restoration projects.

Lipopolyplex-formulated mRNA cancer vaccine elicits strong neoantigen-specific T cell responses and antitumor activity.

mRNA neoantigen cancer vaccine inducing neoantigen-specific T cell responses holds great promise for cancer immunotherapy; however, its clinical translation remains challenging because of suboptimal neoantigen prediction accuracy and low delivery efficiency, which compromise the in vivo therapeutic efficacy. We present a lipopolyplex (LPP)-formulated mRNA cancer vaccine encoding tandem neoantigens as a cancer therapeutic regimen. The LPP-formulated mRNA vaccines elicited robust neoantigen-specific CD8+ T cell responses in three syngeneic murine tumor models (CT26, MC38, and B16F10) to suppress tumor growth. Prophylactic cancer vaccine treatment completely prevented tumor development, and long-lasting memory T cells protected mice from tumor cell rechallenge. Combining the vaccine with immune checkpoint inhibitor further boosted the antitumor activity. Of note, LPP-based personalized cancer vaccine was administered in two cancer patients and induced meaningful neoantigen-specific T cell and clinical responses. In conclusion, we demonstrated that the LPP-based mRNA vaccine can elicit strong antitumor immune responses, and the results support further clinical evaluation of the therapeutic mRNA cancer vaccine.

Regeneration and Genetic Transformation in Eucalyptus Species, Current Research and Future Perspectives

Eucalyptus is an important plantation tree with a high economic value in China. The tree contributes significantly to China’s timber production. The stable and efficient Eucalyptus regeneration system and genetic transformation system are of great significance for exploring the regulatory function and possible genetic breeding capacity of important genes in the species. However, as a woody plant, Eucalyptus has problems, such as a long generation cycle, strong specificity of the regeneration system, and a low genetic conversion rate, which seriously limit the rapid development of Eucalyptus genetics and breeding programs. The present review summarizes the status of research on Eucalyptus regeneration and genetic transformation, with a focus on the effects of explants, media, plant growth regulators (PGRs), and concentrations in the Eucalyptus regeneration process. In addition, the effects of genotype, Agrobacterium, antibiotics, preculture, and co-culture on the genetic transformation efficiency of Eucalyptus are discussed. Furthermore, the study also summarizes the problems encountered in Eucalyptus regeneration and genetic transformation, with reference to previous studies, and it outlines future developments and prospects. The aim was to provide a reference for solving the problems of genetic instability and the low transformation efficiency of eucalyptus, and to establish an efficient and stable eucalyptus regeneration and transformation system to accelerate the process of its genetic improvement.

Manipulating Electrolyte Interface Chemistry Enables High-Performance TiO2 Anode for Sodium-Ion Batteries

Titanium dioxide (TiO2) has emerged as a candidate anode material for sodium-ion batteries (SIBs). However, their applications still face challenges of poor rate performance and low initial coulomb efficiency (ICE), which are induced by the unstable solid-electrolyte interface (SEI) and sluggish Na+ diffusion kinetics in conventional ester-based electrolytes. Herein, inspired by the electrode/electrolyte interfacial chemistry, tetrahydrofuran (THF) is exploited to construct an advanced electrolyte and reveal the relationship between the improved electrochemical performance and the derived SEI film on TiO2 anode. The robust and homogeneously distributed F-rich SEI film formed in THF electrolyte favors fast interfacial charge transfer dynamics and excellent interfacial stability. As a result, the THF electrolyte endows the TiO2 anode with greatly improved ICE (64.5%), exceptional rate capabilities (186 mAh g−1 at 5.0 A g−1), and remarkable cycling stability. This study elucidates the control of interfacial chemistry by rational electrolyte design and offers insights into the development of high-performance and long-lifetime TiO2 anode.

Improving indoor air quality and cooling efficiency: Indirect dew-point evaporative cooling in South China summers

The escalating impact of global warming and the increase in respiratory illnesses have heightened the demand for fresh air systems. However, the substantial power consumption and environmental harm associated with traditional air conditioning systems conflict with current international aspirations for carbon neutrality. To address these issues, a high-performance and compact counterflow indirect dew-point evaporative cooler have developed. This innovative design eliminates the U-turn of the working air seen in conventional M-cycle coolers, resulting in reduced pressure drop and enhanced energy efficiency. This study evaluates the performance of the newly developed dew-point cooler and explores its potential use in providing cool and fresh air for indoor spaces during the sub-tropical summer season in Zhenjiang city, Jiangsu province, China. The results indicate that despite the relatively low fan efficiency (ranging from 5% to 36%), a high cooling coefficient of performance (COP) between 5.2 and 9.3 was achieved. The cooler has demonstrated its effectiveness in improving both thermal comfort and air quality indoors. In Zhenjiang, the cooler can function as a standalone cooling device in June. However, during the hotter months of July and August, it is more suitable as an efficient pre-cooling device when used in conjunction with a conventional air conditioner. The developed cooler exhibited highly stable performance over a three-month test period, consistently maintaining effective cooling and fresh air supply. This study confirms the potential of the counterflow indirect dew-point evaporative cooler as a sustainable and efficient solution for improving indoor air ventilation and thermal comfort.

Numerical Analysis of A Two-Phase Turbine: A Comparative Study Between Barotropic and Mixture Models

Abstract Two-phase turbines offer the potential to significantly enhance the performance of power generation and refrigeration systems. However, their development has been hindered by comparatively lower efficiencies resulting from additional loss mechanisms absent in single-phase turbines. To date, most multiphase CFD studies on turbomachinery have focused on condensation in the final stages of steam turbines, and on cavitation in hydraulic pumps and turbines. These applications, however, are not representative of the conditions in two-phase turbines, where a liquid-dominated mixture undergoes a large expansion ratio, leading to a significant increase in the gas phase volume fraction throughout the entire flow. This paper aims to identify a suitable modeling methodology for two-phase turbines. Our evaluation is centered around two models: the mixture model and the barotropic model. The validity and accuracy of these two modeling approaches is assessed using existing experimental data from a single-stage impulse turbine operating with several mixtures of water and nitrogen as working fluid. The results indicate that both the mixture and barotropic models are consistent and accurately predict the nozzle mass flow rate, yet, both models systematically overpredict the nozzle exit velocity and rotor torque. Adding correction terms for windage and unsteady pumping losses significantly improves the torque predictions, bringing them within the uncertainty range of the experimental data. In addition, refining the models to account for the effect of slip presents a promising avenue to enhance the prediction of nozzle exit velocity and overall performance of two-phase turbines.

Decision-Making Model to Support Agricultural Policies in Realizing Economic and Social Sustainability

Abstract Background Achieving economic and social sustainability is the goal of any policy when defining measures. We focus on the beef sector, where many challenges have arisen due to its structural characteristics, such as an unfavourable scale structure, high costs, low efficiency, and a low environmental footprint. This paper presents an example of the support provided by a mathematical programming model in the development of a Common Agricultural Policy Strategic Plan for the period 2023-2027. Methods/approach It is a model based on linear programming that allows such an ex-ante analysis by calculating production plans at the farm level and aggregating the results at the sector level. Objectives When defining the interventions, the question arose as to what the reform of the Common Agricultural Policy will bring and to what extent the sector should be supported in meeting these challenges. These were the concerns of agricultural policy that we sought to support by modelling different scenarios. Results The results show that the situation of the sector will worsen, especially for larger farms, but they also show the great importance of production-related payments to mitigate the negative trend. Conclusions The applied approach proves to be suitable for supporting the design of agricultural policy and achieving greater economic and social sustainability in the sector.

Hierarchically fibrillated spunlaced nonwovens from waste wool supported ionic liquid as solid amine adsorbents for CO2 capture

The environmental crisis caused by excessive emissions of carbon dioxide-based greenhouse gases has garnered widespread public concern. Solid amine is considered to be one of the most effective carbon dioxide (CO2) adsorbents. However, traditional solid amine carriers have problems such as structural collapse, low efficiency and poor regeneration. In this study, waste wool having hierarchical fibrous structure was spunlaced, fibrillated and later compounded with amino acid ionic liquids (AAIL) leading to the formation of the AAIL@feather-like wool nonwoven absorbents. A synergistic co-amine effect was observed after primary and secondary fibrillation without any sacrifice in the mechanical property of wool nonwovens. Also, the fibrillated nonwovens had high specific area which provided high loading rate (13.53 %) on AAIL. Compared with untreated wool nonwovens, the CO2 adsorption capacity of feather-like wool nonwovens was higher by 65 % (11.75 mmol/g) after loading AAIL. Furthermore, the CO2 adsorption capacity was retained (95.2 %) even after 12 cycles at 80 ℃, indicating that the AAIL@ feather-like wool nonwovens possess good long-term stability. This work paves the way for large scale manufacturing of biobased solid adsorbents with a hierarchical nonwoven structure for efficient CO2 capture.

Design and implementation of corrosion-resistant multitasking cell stainers.

Compared with machine staining, traditional manual staining faces various problems, such as a low preparation success rate, low efficiency, and harm to the human body due to corrosive gases. Therefore, a stainer that is of low cost, has strong corrosion resistance, and is suitable for small-batch preparation should be developed. In this study, by choosing a rotary scheme as the structural basis, a reusable container cover and a master-slave manipulator cooperation scheme are developed, which greatly improve the space utilization rate. Through material selection and structural design, in the designed stainer, effective protection against strong acids with high volatility and permeability is realized, thereby eliminating the corrosion issue. Using the designed splitting-running algorithm for the dyeing procedure, simultaneous multistaining is realized, which significantly improves the staining efficiency. Compared with large-sized stainers, the cost of the proposed stainer is very low, which will help popularize early screening for cervical cancer in low- and middle-income countries.

US/PA/MR multimodal imaging-guided multifunctional genetically engineered bio-targeted synergistic agent for tumor therapy

Focused ultrasound ablation surgery (FUAS) is a minimally invasive treatment option that has been utilized in various tumors. However, its clinical advancement has been hindered by issues such as low safety and efficiency, single image guidance mode, and postoperative tumor residue. To address these limitations, this study aimed to develop a novel multi-functional gas-producing engineering bacteria biological targeting cooperative system. Pulse-focused ultrasound (PFUS) could adjust the ratio of thermal effect to non-thermal effect by adjusting the duty cycle, and improve the safety and effectiveness of treatment.The genetic modification of Escherichia coli (E.coli) involved the insertion of an acoustic reporter gene to encode gas vesicles (GVs), resulting in gas-producing E.coli (GVs-E.coli) capable of targeting tumor anoxia. GVs-E.coli colonized and proliferated within the tumor while the GVs facilitated ultrasound imaging and cooperative PFUS. Additionally, multifunctional cationic polyethyleneimine (PEI)-poly (lactic-co-glycolic acid) (PLGA) nanoparticles (PEI-PLGA/EPI/PFH@Fe3O4) containing superparamagnetic iron oxide (SPIO, Fe3O4), perfluorohexane (PFH), and epirubicin (EPI) were developed. These nanoparticles offered synergistic PFUS, supplementary chemotherapy, and multimodal imaging capabilities.GVs-E.coli effectively directed the PEI-PLGA/EPI/PFH@Fe3O4 to accumulate within the tumor target area by means of electrostatic adsorption, resulting in a synergistic therapeutic impact on tumor eradication.In conclusion, GVs-E.coli-mediated multi-functional nanoparticles can synergize with PFUS and chemotherapy to effectively treat tumors, overcoming the limitations of current FUAS therapy and improving safety and efficacy. This approach presents a promising new strategy for tumor therapy.Graphical

Exploring an economic and highly efficient genetic transformation and genome-editing system for radish through developmental regulators and visible reporter.

Radish (Raphanus sativus L.) is one of the most important root vegetable crops worldwide. However, gene function exploration and germplasm innovation still face tremendous challenges due to its extremely low transformation efficiency. Here, an economic and highly efficient genetic transformation method for radish was explored by Agrobacterium rhizogenes-mediated transformation with the help of combining special developmental regulator (DR) genes and the visual identification reporter. Firstly, the RUBY gene, a betalain biosynthesis system, could result in a visual red-violet color used as a convenient and effective reporter for monitoring transgenic hairy roots screening of radish. However, the hairy roots-to-shoots conversion system of radish still stands as a barrier to the obtainment of whole transgenic plants, although different hormone combinations and various culture conditions were tried. Following, two DR genes including Wuschel2 (Wus2) and isopentenyl transferase (ipt), as well as their combination Wus2-ipt were introduced for the shoot regeneration capacity improvement. The results showed that the transgenic shoots could be directly generated without externally supplying any hormones in the presence of a Wus2-ipt combination. Then, Wus2-ipt along with the RUBY reporter was employed to establish an efficient genetic transformation system of radish. Moreover, this system was applied in generating gene-edited radish plants and the phytoene desaturase (RsPDS) gene was effectively knockout through albino phenotype observation and sequencing analysis. These findings have the potential to be widely applied in genetic transformation and genome-editing genetic improvement of other vegetable species.

Optimizing secure multimedia communication in embedded systems a parallel convolutional neural network approach to RIS and D2D resource allocation

With the rapid development of Internet of Things (IoT) services, technologies that leverage multimedia computer communication for information sharing in embedded systems have become a research focus. To address the challenges of low spectral efficiency and poor network flexibility in multimedia computer communications, this paper proposes a resource allocation scheme based on parallel Convolutional Neural Network (CNN). The scheme optimizes the base station beamforming vector and the Reconfigurable Intelligent Surface (RIS) phase shifts to maximize the secure transmission rate for cellular users (CUs), while ensuring normal and secure communication for device-to-device (D2D) users. First, to mitigate interference caused by D2D users reusing CU spectrum resources, the RIS phase shifts and beamforming vectors are optimized to suppress interference and enhance system secrecy rates. Second, to maximize the CU secrecy rate, the paper proposes a parallel CNN-based resource allocation model that considers base station transmission power, RIS reflection coefficients, and D2D communication rate constraints, incorporating multi-scale residual modules in the convolutional layers of the model. Simulation results demonstrate that the proposed CNN-based resource allocation scheme significantly improves the secrecy rate of embedded system communications, ensuring secure multimedia computing, and outperforms traditional methods.

Experimental study on the operating characteristics of multiple collector direct expansion solar-assisted heat pump

Solar thermal application is one of the most important ways to replace fossil energy. The discontinuous heating character and low heating efficiency are two key factors that limit the large-scale promotion of solar thermal application. Large-scale direct expansion solar heat pump systems (DX-SAHP) can provide high efficiency and low-cost continuous heating. However, the characteristics of multiple collector arrays and the system's performance still need more research and exploration. In this paper, a DX-SAHP system with multiple solar collectors was constructed and the work process of the system under different operation conditions was expressed. An experimental platform with two DX-SAHP system was built and studied, and each system contained a 10HP compressor, 16 set solar collectors and one fin evaporator in parallel. The results show that the coefficient of performance (COP) of the system running with solar collectors was nearly 30 % higher than that with the fin evaporator under constant frequency mode, and nearly 45 % under variable frequency mode, indicating that such a system has better performance under variable frequency operation mode. The refrigerant in the collector/evaporators were distributed uniformly in equal-path connection mode, which was beneficial in promoting the system's performance. The heating performance of the system under sunny and cloudy weather conditions was analyzed and discussed, respectively. The test results indicated that the COP of the system on sunny or cloudy days was higher than 4.0, and the maximum hourly COP can reach 11.3 and the maximum hourly heating capacity was 27 kW.

Fabrication of high-quality microlens arrays on fused silica based on combined rapid evaporative ablation and precision melting polishing of CO2 lasers

Microlens arrays (MLAs) made from fused silica possess broad applications in wavefront sensing, optical focusing, beam shaping, etc. However, it is challenging to fabricate the hard-brittle silica MLAs with high accuracy and low cost by conventional manufacturing techniques efficiently. In this work, a novel two-step method, which consists of rapid evaporative ablation and precision melting polishing by CO2 lasers, is proposed to fabricate high-quality MLAs. The first step is to rapidly ablate and engrave micro-pillar arrays (MPAs) with flat groove bottom by high-energy density CO2 lasers. The second step is to precisely polish and shape the flat-topped MPAs into the dome-topped MLAs with good surface roughness (Sa) by low-energy density CO2 lasers. The whole preparation process could be achieved through a set of machining system. Firstly, the geometric dimension (period, p and height, h) of the microlens is determined by the Monte Carlo ray tracing method. Secondly, to diminish the groove depth inconsistency caused by heat accumulation, the multiple ablation compensation strategy is developed. The MPAs (p = 200–400 μm), of which maximum height error is 7.1%, are prepared in 1 s by the proposed compensation strategy. Then, the MPAs are smoothed into the MLAs by low-energy density CO2 lasers, and the average Sa is improved from 960 nm to 32.56 nm. Finally, the optical performances of the MLAs are verified from the effectiveness of imaging, focusing and homogenization. The proposed two-step processing method paves a new way to fabricate high-performance MLAs on hard-brittle fused silica with low cost and high efficiency.

Entropy-Stabilized Multication Fluorides as a Conversion-Type Cathode for Li-Ion Batteries-Impact of Element Selection.

Metal fluorides (e.g., FeF2 and FeF3) have received attention as conversion-type cathode materials for Li-ion batteries due to their higher theoretical capacity compared to that of common intercalation materials. However, their practical use has been hindered by low round-trip efficiency, voltage hysteresis, and capacity fading. Cation substitution has been proposed to address these challenges, and recent advancements in battery performance involve the introduction of entropy stabilization in an attempt to facilitate reversible conversion reactions by increasing configurational entropy. Building on this concept, high entropy fluorides with five cations were synthesized by using a simple mechanochemical route. In order to examine the impact of element selection, Co0.2Cu0.2Ni0.2Zn0.2Fe0.2F2 (HEF-Fe) was compared with Co0.2Cu0.2Ni0.2Zn0.2Mg0.2F2 (HEF-Mg), replacing electrochemically inactive Mg with Fe as an active participant in the conversion reaction. Combining electrochemical measurements with first-principles calculations, high-resolution electron microscopy, and synchrotron X-ray analysis, HEFs' battery performances and conversion reaction mechanisms were investigated in detail. The results highlighted that replacement of Mg with Fe was beneficial, with enhanced capacity, rate capability, and surface stability. In addition, it was found that HEF-Fe showed similar cycle stability without an electrochemically inactive element. These findings provide valuable insights for the design of high entropy multielement fluorides for improved Li-ion battery performance.

Al-etching-induced defect engineering in NiAl LDHs for promoting multifunctional electrocatalytic oxidations: Water oxidation and urea oxidation

Electrocatalytic water splitting is a promising avenue to produce green hydrogen for future sustainable development. Developing multifunctional catalysts with high-performance toward urea oxidation reaction (UOR) and oxygen evolution reaction (OER) offers a unique approach for simultaneously achieving the degradation of urea-containing wastewater and energy-saving hydrogen production. Ni-based materials are a kind of promising materials for electrocatalysis, since its abundant reserve and tolerance. However, low intrinsic activity and catalytic efficiency hinder its wide application. Here, a defect engineering strategy is developed to create vacancies on NiAl layer double hydroxides (LDHs) catalysts by selectively etching Al ions in strong alkaline solution. The obtained NiAl LDHs with rich defects (D-NiAl LDHs) exhibit good OER performance with overpotential of 264 mV to achieve a current density of 10 mA cm−2 and a Tafel slope of 39.8 mV dec−1. In addition, the D-NiAl LDHs catalysts also show excellent UOR activity using a potential of 1.328 V vs. RHE @ 10 mA cm−2 in alkaline solution. In comparation to NiAl LDHs, the enhanced performance of D-NiAl LDHs toward oxidation of small-molecule OH− and urea could be attributed to electronic regulation of defects and a larger electrochemical surface area. Partially replacing the OER with the UOR, the driving voltage of overall water splitting reduces effectively from 1.856 V to 1.688 V at a current of 100 mA cm−2.

Cu−based bimetallic sites' p-d orbital hybridization promotes CO asymmetric coupling conversion to C2 products

Hampered by sluggish C−C coupling kinetics, the low selectivity and efficiency have limited industrial applications of CO2 reduction into valuable multi-carbon products. A direct coupling of CO molecules or their coupling after hydrogenation, followed by the final synthesis of C2 products, can help to overcome these limitations potentially. In this study, a detailed high-throughput screening of bimetallic site catalysts comprising copper (Cu) and 28 other metal (M) atoms was conducted. The metal atoms Cu and M were anchored on a carbon nanotube (CNT) with six nitrogen (N6) defects (CuMN6@CNT), which possesses effective dual active sites for C−C coupling. The calculated results demonstrate that the CuGaN6@CNT catalyst exhibited favorable selectivity, with low theoretical overpotentials of −0.23 and −0.34 eV for ethanol and ethylene, respectively, surpassing most reported catalysts. The synergistic effect of Ga and Cu sites, along with their p-d states hybridization, results in an enhancement of Cu's d state dispersion and energy barriers reduction for C−C coupling. Additionally, the strain effect of the substrate CNT exhibits a direct correlation with the catalytic performance of CuGaN6@CNT by adjusting the d-band center of the Cu site and p-band center of the Ga site. These findings provide a novel insights into the electrocatalytic reduction of CO into valuable C2 products using bimetallic single atom catalyst, offering significant guidance for future research endeavors in this field.

EEG synchronization patterns during a Go/No-Go task in individuals with aphasia in subacute and chronic phases of stroke

Stroke and subsequent neuroregenerative processes cause changes in neural organization of attentional functions. In this study, we attempted to identify differences in neural synchronization patterns during a visual Go/No-Go task in people with post-stroke aphasia in both subacute and chronic stroke phases. To identify neuronal underpinnings of the behavioral differences we investigated pairwise connectivity patterns using corrected imaginary phase locking value and graph-theoretic measures (efficiency, modularity and clustering coefficient) at global and local level in subacute (n = 13) and chronic stroke phases (n = 14) during a Go/No-Go task. We observed significantly lower phase synchronization in the Subacute Group in the alpha band in the connections spanning frontal and central areas of both hemispheres alongside lower local efficiency and clustering coefficient in the left frontal region. Additionally, we observed higher modularity in the beta band in the unaffected right parietal region in the Subacute Group which may denote inhibition of motor and attention functions. Those mechanisms could serve to align cognitive abilities between the damaged and healthy hemispheres, harmonizing the activity of the neuronal networks of both hemispheres disrupted by the effects of the stroke. Our findings have potential implications for rehabilitation therapies, which should take into account the pattern of connectivity changes during different phases of reovery.

The Impact of Machine Learning-based Student Behaviour Detection on Teaching in Teaching Classroom Scenarios

The purpose of this study is to address the issue of low efficiency and time-consuming monitoring of student classroom behaviour in teaching classroom scenarios, as well as how to apply deep learning to student classroom behaviour detection. Classroom teaching is the main way for students to acquire and master knowledge, and teachers need to pay attention to students’ behaviour in the classroom and make timely corrections. In this study, the teaching classroom of undergraduate students was used as an example for application and analysis. Based on the You Only Look Once v5s network, a student behaviour detection algorithm was designed by combining the ghosting module and optimised feature fusion structure, and a student behaviour association technology suitable for continuous teaching classrooms was designed. Through the visualisation results, it can be seen that the research method can accurately detect the behaviour categories of students, and the effect is better in target dense scenes. Through quantitative analysis using correlation technology, it can be concluded that there are very few students with the lowest level of seriousness, while the majority of students have a level of seriousness above the qualified level. The overall situation of the teaching classroom is good. These student behaviour analyses can energy the level of seriousness of students, form effective and objective classroom feedback, provide teachers with objective and accurate reference value, and promote the construction of smart classrooms.