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ObjectivesThe localization of core components of heavy-duty gas turbines holds significant importance for technological innovation, industrial upgrading, and even national security. As a typical hot-end component of heavy-duty gas turbines, the performance of the turbine first-stage rotor blade directly determines the efficiency and reliability of the gas turbine. Therefore, the structure of the first-stage turbine blades of a certain heavy-duty gas turbine was optimized.MethodsBy increasing the number of bamboo nodes in the blade body, the blade cooling hole structure was optimized, and the thermal barrier coating was used to improve the blade coating. The temperature, stress distribution and aerodynamic efficiency of the blades before and after optimization under the service condition of the blade were compared and analyzed by fluid calculation and finite element calculation.ResultsHeat transfer efficiency inside the blade is enhanced by optimization of turbulent structure. Under the condition of the same inlet pressure of the cooling air, the surface temperature of the optimized blade is reduced by more than 50 ℃. Since the shape of the blade is not changed, there is little influence on the aerodynamic efficiency. Compared with the blades without optimization, the maximum equivalent stress and equivalent total strain of the optimized blade during service are significantly reduced.ConclusionsBy optimizing the cooling structure and upgrading the protective coatings, the reliability of the blades in high-temperature can be significantly improved. The research results provide a theoretical basis for the localization of gas turbines.

Objective Accurate short term passenger flow prediction is of great significance to improve the operation and management efficiency of the ultra-large scale of urban rail transit network. However, the current research on deep exploration of the spatio-temporal correlations is still insufficient. Therefore, according to the spatio-temporal law of short term passenger flow, a STGCN (spatio-temporal graph convolutional neural network) model based on spatio-temporal correlation characteristics of passenger flow is proposed. Method Firstly, the spatial correlation of ultra-large scale urban rail transit network is captured by ChebyNet （Chebyshev graph convolutional network）, and the temporal correlation of the passenger flow under multi-temporal correlation characteristics is explored with the help of GRU (gated recurrent unit). Secondly, the correlation of the historical passenger flow data of the station to be predicted and that of OD (origin-destination) passenger flow data are analyzed to extract the spatio-temporal correlation deeply. Finally, a STGCN model is established in combination with the spatio-temporal correlation characteristics of the passenger flow. Result & Conclusion Taking Jiangsu Road Station of Shanghai Metro Line as an example, a short-term inbound passenger flow prediction is conducted. The result shows that the prediction accuracy with spatio-temporal correlation characteristic parameters is 16% higher than that without the parameters, indicating a better prediction effect.

Objective With the increasing automation levels in urban rail transit, drivers responsible for operation in GOA2 (semi-automated train operation) mode become the multitasking personnel responsible for monitoring and inspecting compartments in GOA4 (unattended train operation) mode. The emergency disposal operation procedure has changed as a result. To achieve a more refined analysis and evaluation of urban rail transit train operations in the GOA4 mode, it is necessary to conduct an in-depth study on the quantitative assessment method for the emergency disposal operation complexity in terms of key driving post personnel. Method Based on standardized operating procedures, the WDA (work domain analysis) method is used to establish an information structure diagram for key driving post personnel. The emergency disposal operation complexity in terms of key driving post personnel under both GOA2 and GOA4 modes is analyzed from four aspects of information quantity, operation logic, operational scale, and overall complexity. Using door malfunction emergency disposal operations as example, the emergency disposal operation complexity for key driving post personnel in both modes is calculated, and two-tailed Pearson test is carried out for site standardized operational score rate correlation verification. Result & Conclusion The correlation test results show that the correlation coefficient of vehicle door fault emergency disposal operations is -0.827, significance level is 0.042, the complexity of the operation and the score rate is negatively correlated, validating the effectiveness of the SC (step complexity) model.

Objective Improving the service level to the passengers and ensuring safety are the core purpose of the facility layout and operation management of urban rail transit station. To design the station facility scientifically, the basic characteristics and patterns of the pedestrian following behavior need to be studied. Method Based on the pedestrian trajectory, a description model of pedestrian following behavior and its characteristic parameters are proposed, and a controllable experiment is designed to simulate the pedestrian following behavior in one way passage of the urban rail transit station. The pedestrian following trajectory is extracted from the collected video data, and the characteristics and patterns of the parameters such as pedestrian following speed difference, time interval, horizontal and longitudinal spacing are deeply analyzed when the following behavior occurs. The effects of the four factors i.e. pedestrian density, passage width, gender and familiarity to the environment on the pedestrian following behavior are studied. Result & Conclusion The lower the pedestrian density, the smaller the average following speed difference and the shorter the average following time distance. The passage width has no significant effect on the following behavior characteristic parameters. All the values of the characteristic parameters of the opposite sex are larger than those of the same sex. The values of the characteristic parameters of the pedestrians who are not familiar with the environment are more discrete than those familiar with the environment.

Abstract The cascading propagation and evolution of metro operation failures can significantly impact the safety of metro operation. To overcome this challenge, this study pre-processes a massive amount of metro operation log data through noise reduction. Moreover, a professional terminology dictionary is constructed along with a custom stop-word dictionary to segment the preprocessed data. Subsequently, the AFP-tree algorithm is employed to mine the segmented log data and identify key hazards. A weighted urban rail transit network is established, considering the effective path time cost, and the shortest travel OD path. To simulate the dynamic evolution of the failure chain propagation, a model based on disaster propagation theory is constructed. Taking the Shanghai Metro line as a case, multiple simulation scenarios are established with 25 key hazards as triggering points, and the number of cascade failure stations affected under different scenarios is outputted. The results indicate that the fault stations caused by the large passenger flow are the largest. Meanwhile, the number of stations affected by the door clamp is the smallest. The scale of fault stations reaches a maximum value in 16–20 min. Through case analysis, a positive correlation is found when the self-recovery factor is between 14 and 18, and the number of fault stations shows a significant increasing trend. The research results can provide decision-making support and theoretical guidance for rail transit operation safety management enterprises.

Background With the continuous improvement of diabetes prevention and treatment strategies, clinical guidelines recommend first-line hypoglycemic agents while emphasizing a "patient-centered", and the selection of appropriate second-line hypoglycemic agents based on patients' clinical characteristics and preferences. Objective To quantitatively analyze second-line hypoglycemic agents selection preferences in patients with type 2 diabetes mellitus (T2DM) by using a discrete choice experiment, so as to provide reference for clinical diagnosis and treatment for T2DM patients. Methods This study conducted a questionnaire survey on T2DM patients selected from Hainan and Shanxi provinces from October 2021 to January 2022 by using a combination of multi-stage random cluster sampling. The questionnaire included basic personal information of the respondents, information related to disease treatment and discrete choice experimental choice set (seven attributes of glycemic control, risk of hypoglycemic events, risk of gastrointestinal adverse events, body mass change within six months, cardiovascular protection, mode of medication administration, and out-of-pocket/monthly costs, each of which included a various levels were included through the literature review, focus group discussion, and pre-tests). A mixed Logit regression model was used to quantify the preference of T2DM patients for second-line hypoglycemic agents, and the regression coefficients reflected the direction and magnitude of the preference for second-line hypoglycemic agents among T2DM patients. Willingness to pay (WTP) reflected the monetary value of patients' willingness to pay or receive compensation after the changes in different attribute levels. Results A total of 1 443 questionnaires were distributed and 1 388 valid questionnaires were recovered, with an effective recovery rate of 96.2%. All seven attributes had an effect on medication preference of T2DM patients (P

Abstract With the promotion of the major strategy of national transportation power, the super-large-scale metro operation network has become an inevitable trend, and operation safety has become increasingly prominent. Metro operation dispatch logs and accident reports were taken as the research object, the hazard sources were efficiently and accurately identified, the risk chains of hazard sources were mined, and the risk evolution mechanism was revealed. Firstly, the transportation lexicon was constructed to improve the accuracy of word segmentation, the text features were extracted based on the term frequency-inverse document frequency (TF-IDF) algorithm, and the key eigenvalues were mined to identify the key hazard sources. Secondly, pattern matching was used to extract explicit causality, and the Self-Attention BiLSTM extracted implicit causality and integrated event trigger word position identification to enhance the effectiveness of implicit causality extraction. Finally, an example was given to verify the efficiency and accuracy of the model, the experiments showed that the F value of extraction effect was increased by nearly 10%, the extraction accuracy was 87.53%, the identification of operational hazard sources was more accurate, and the visualization of risk evolution law was realized.

Based on the ANSYS Workbench finite element software, the ultimate static working state of the dental plate of clamping pliers when drilling the drill string is analyzed elastoadically. The stress of the contact between the dental tooth and the drill pipe was analyzed by linearization principle, and the classification was identified and evaluated. And then the key parameters of tooth plate as the object of study, through the orthogonal experiment results of the poor analysis, combined with the actual processing capacity to determine the final optimization program. Finally, the contact stress between the dental plate and the drill pipe was measured by the pressure film, and the rationality of the optimization scheme was verified, and the pressure applied is linearly related to the maximum stress of the tooth plate.The test method provides a new way for the same type of equipment. It is of great engineering significance to ensure the safe, reliable and effective operation.

While gearbox in power plant generator set often work in the environment of high speed,high load and poor lubrication,it is of great significance to study the effective monitor and fault diagnosis of working condition. As to nonstationary feature of fault signal in gearbox,the fault diagnosis method based on wavelet packet decomposition（ WPD） and BP neural network is presented. The measured fault signal is decomposed by the wavelet packet to obtain the energy feature information as the input vector,and the BP neural network is used as the classifier to identify and diagnose it. Through analysis of gearbox under four types of normal condition,tooth surface wear,missing teeth and compound fault,show that the fault diagnosis method can distinguish the fault type in gearbox.

In order to improve reliability of wind power unit drivetrain,a fault diagnosis model based on quantum genetic algorithm and support vector machine（ SVM） is presented. The model of SVM is conformed,and the penalty parameter and Kernel function coefficient are optimized by quantum genetic algorithm,which coding and renewal of initial population are completed with quantum encoding and rotation gate,the accuracy of optimal solution is improved. Through using the optimized SVM model,with the test and calculation for drivetrain in three types of normal condition,surface wear and missing teeth,the accuracy rate of fault diagnosis can be effectively solved.

Optimization research on reliability of the catenary system and preventive maintenance strategy is the key to ensure the safe operation of the electrical railway. The choice of preventive maintenance strategy is more conducive to develop maintenance program of catenary system. Analyzing the catenary system based on fault tree analysis model and using different parameters’ Weibull distribution to describe the device failure probability of the various parts of the catenary system. The optimization function of preventive maintenance strategy on the catenary system based on reliability constraints is deduced.According to three years’ measured fault data of Changsha section,the parameters of Weibull distribution which describe the various parts of the catenary system is fitted,the maintenance costs of the catenary system in Changsha section were calculated according to the model of optimization on preventive maintenance strategy. Conclusions showed that: appropriately increasing maintenance times can reduce maintenance costs; high reliability requires will increase maintenance times and repair costs significantly. The maintenance strategy optimization model and the calculated results provide a useful reference for the Maintenance of the catenary system.

Chaperonin-containing T-complex polypeptide 1 (CCT) is a molecular chaperone in the cytoplasm of eukaryotic cells involved in the correct folding and assembly of proteins, which plays an important role in cold-stress response. This study cloned two transcripts of Pinctada maxima CCT-beta composed of 1,829 bp (CCT-betal) and 2,289 bp (CCT-beta2), respectively, using rapid amplification of cDNA ends. Both transcripts possess 105 bp of 5' noncoding region and the same coding region, bul contain different 3' noncoding regions of 591 bp (CCT-betal) and 131 bp (CCT-beta2), respectively. The open reading framework (ORF) consisted of 1,593 bp that encodes 530 amino acids. The CCT-beta protein has three conserved functional domains (equatorial, apical, and intermediate domains), three CCT-family signature sequences, nine conserved ATP-binding sites, one DEAD box motif, and three protein-binding sites. The CCT-beta is highly conserved, with the cDNA homologies between P. maxima and Crassostrea gigas, Danio rerio, and Homo sapiens being 90.4%. 76.8%, and 75.8%, respectively. Real-time quantitative PCR showed that CCT-beta was differentially expressed in different organs of P. maxima, with mRNA contents declining from the gill, adductor muscle, foot, labial palps, mantle, and heart to hepatopancreas. Under cold stress, CCT-beta mRNA expression in various organs increased, but the patterns of increase varied among organs. The transcriptional level of CCT-beta peaked at 6h in the heart and hepatopancreas, and decreased significantly at 12h. In the adductor muscle, gill, and mantle, CCT-beta mRNA increased significantly at 12h and declined markedly at 24h in cold stress-exposed animals. These results indicate that CCT-beta is a cold-stress response gene, but the response pattern varies among organs. Organs with low CCT-beta basal expression may be more sensitive to cold stress than the organs with relatively high basal expression content. KEY WORDS: Pinctada maxima, CCT-beta, cDNA, cold stress, INTRODUCTION Chaperonin-containing T-complex polypeptide 1 (CCT) is a kind of type II chaperonin that is localized in the cytoplasm of eukaryotes (Frydman et al. 1992, Gao et al. 1992, Lewis [...]

In this case, RGO (graphene reduced load) aggregates (3, 4-ethylenedioxythiophene) were used to prepare basic films by chemical deposition method. Optimize electrochemical deposition (3, 4-ethylene dioxide) and rGO voltage Windows and electrolytes. SEM observation confirmed that PEDOT/rGO did synthesize the necessary composites. Electrochemical tests showed that the electrochemical performance of PEDOT electrode was improved by adding rGO. The mixed PEDOT/rGO electrode has a high specific capacitance (134 F/g, 0.8 mA/cm2).

Microcystin-LR (MC-LR) is one of the most notorious toxins liberated from cyanobacteria in drinking water sources. In this study, a skillful method access to new nanozero-valent iron @chitosan (nZVIMC) was synthesized by a facile one step method. The as-prepared nZVIMC was employed as an adsorbent for the effective removal MC-LR from aqueous solution. Transmission electron microscopy (TEM) demonstrates that nZVIMC is in quasi-spherical shape with size of around 50 nm, effect of variable parameters such as pH, contact time, initial concentration of MC-LR and adsorption properties of nZVIMC on MC-LR was further investigated. Scanning electron microscope (SEM) reveals that the particles are nearly spherical in shape with agglomeration. The results indicated that good adsorption performance was achieved at an initial pH of 5. The adsorption kinetics of nZVIMC was better fitted by pseudo-secondorder kinetics. The adsorption isotherm data was fitted well to Langmuir isotherm and then to Freundlich model, with an adsorption capacity of 68.9 mg/g at 300K. Thus, we believe that nZVIMC can be used as a low cost material for efficient removal of MC-LR from water.

Abstract This work reports a newly developed two-step hydrothermal method for the synthesis of monodispersed colloidal carbon spheres (CCS) under mild conditions. Using this approach, monodispersed CCS with diameters ranging from 160 to 400 nm were synthesized with a standard deviation around 8%. The monomer concentration ranging from 0.1 to 0.4 M is in favor of generation of narrower size distribution of CCS. The particle characteristics (e.g., shape, size, and distribution) and chemical stability were then characterized by using various techniques, including scanning electron microscopy (SEM), FT-IR spectrum analysis, and thermalgravity analysis (TGA). The possible nucleation and growth mechanism of colloidal carbon spheres were also discussed. The findings would be useful for the synthesis of more monodispersed nanoparticles and for the functional assembly.