Remaining Useful Life Prediction of Rail Based on Improved Pulse Separable Convolution Enhanced Transformer Encoder

In order to prevent possible casualties and economic loss, it is critical to accurate prediction of the Remaining Useful Life (RUL) in rail prognostics health management. However, the traditional neural networks is difficult to capture the long-term dependency relationship of the time series in the modeling of the long time series of rail damage, due to the coupling relationship of multi-channel data from multiple sensors. Here, in this paper, a novel RUL prediction model with an enhanced pulse separable convolution is used to solve this issue. Firstly, a coding module based on the improved pulse separable convolutional network is established to effectively model the relationship between the data. To enhance the network, an alternate gradient back propagation method is implemented. And an efficient channel attention (ECA) mechanism is developed for better emphasizing the useful pulse characteristics. Secondly, an optimized Transformer encoder was designed to serve as the backbone of the model. It has the ability to efficiently understand relationship between the data itself and each other at each time step of long time series with a full life cycle. More importantly, the Transformer encoder is improved by integrating pulse maximum pooling to retain more pulse timing characteristics. Finally, based on the characteristics of the front layer, the final predicted RUL value was provided and served as the end-to-end solution. The empirical findings validate the efficacy of the suggested approach in forecasting the rail RUL, surpassing various existing data-driven prognostication techniques. Meanwhile, the proposed method also shows good generalization performance on PHM2012 bearing data set.

Multi-Body Dynamics Modeling of Heavy Goods Vehicle-Rail Interaction

Based on the principle of vehicle-track coupling dynamics, SIMPACK multi-body dynamics software is used to establish a C80 wagon line-coupled multi-body dynamics model with 73 degrees of freedom. And the reasonableness of the line-coupled dynamics model is verified by using the maximum residual acceleration, the nonlinear critical speed of the wagon. The experimental results show that the established vehicle line coupling dynamics model meets the requirements of vehicle line coupling dynamics modeling.

医用有机化学课程中的案例教学

“医用有机化学”是医学院各专业一年级学生的必修课,该课程难度较高,核心内容与临床实践相关性较低,容易使学生产生畏难情绪。我们在教学中通过引入真实临床案例,使学生认识到有机化学知识与临床的相关性,进而激发医学生们对课程学习的热情。

Digital Twin Modeling Enabled Machine Tool Intelligence:A Review

Machine tools,often referred to as the“mother machines”of the manufacturing industry,are crucial in developing smart manufacturing and are increasingly becoming more intelligent.Digital twin technology can promote machine tool intelligence and has attracted considerable research interest.However,there is a lack of clear and systematic analyses on how the digital twin technology enables machine tool intelligence.Herein,digital twin modeling was identified as an enabling technology for machine tool intelligence based on a comparative study of the characteristics of machine tool intelligence and digital twin.The review then delves into state-of-the-art digital twin modelingenabled machine tool intelligence,examining it from the aspects of data-based modeling and mechanism-data dual-driven modeling.Additionally,it highlights three bottleneck issues facing the field.Considering these problems,the architecture of a digital twin machine tool(DTMT)is proposed,and three key technologies are expounded in detail:Data perception and fusion technology,mechanism-data-knowledge hybrid-driven digital twin modeling and virtual-real synchronization technology,and dynamic optimization and collaborative control technology for multilevel parameters.Finally,future research directions for the DTMT are discussed.This work can provide a foundation basis for the research and implementation of digital-twin modeling-enabled machine tool intelligence,making it significant for developing intelligent machine tools.

Bearing fault diagnosis based on a multiple-constraint modal-invariant graph convolutional fusion network

Multisensor data fusionmethod can improve the accuracy of bearing fault diagnosis,in order to address the problems of single-sensor data types and the insufficient exploration of redundancy and complementarity between different modal data in most existing multisensor data fusion methods for bearing fault diagnosis,a bearing fault diagnosis method based on a Multiple-Constraint Modal-Invariant Graph Convolutional Fusion Network(MCMI-GCFN)is proposed in this paper.Firstly,a Convolutional Autoencoder(CAE)and Squeeze-and-Excitation Block(SE block)are used to extract features of raw current and vibration signals.Secondly,the model introduces source domain classifiers and domain discriminators to capture modal invariance between different modal data based on domain adversarial training,making use of the redundancy and complementarity between multimodal data.Then,the spatial aggregation property of Graph Convolutional Neural Networks(GCN)is utilized to capture the dependency relationship between current and vibration modes with similar time step features for accurately fusing contextual semantic information.Finally,the validation is conducted on the public bearing damage current and vibration dataset from Paderborn University.The experimental results showed that the delivered fusion method achieved a bearing fault diagnosis accuracy of 99.6%,which was about 9%–11.4%better than that with nonfusion methods.

Design and Implementation of GIS Data Production System for Expressway Video and Road Infostructure

The expressway is necessary for the development of the modern transportation industry, and the level of expressway construction reflects the overall grade of national or regional economic development. In order to process the expressway road property data information, based on the current mainstream Windows operating system, this study utilizes Geographic Information System (GIS) development technology, road video processing technology, and spatial data mining method to design and develop an expressway video and road infostructure GIS data production system. The system designs a multi-layer distributed application model in accordance with the ideas and methods of GIS engineering and the characteristics of road production data. In addition, according to the characteristics and specification requirements of basic geographic data, the road production database of spatial data and attribute data integrated storage is constructed by combining database and spatial data engine. Through the development of the GIS data production system for expressway video and road infostructure, various functions such as generation of road property data, dynamic management of road infostructure, and visualization of spatial information have been realized. The system focuses on improving the production efficiency and automation level of expressway production data and meets the construction requirements for modernization, informatization, and intelligence of expressways.

SnO_(2)表面卤化提高钙钛矿太阳能电池光伏性能

钙钛矿太阳能电池(PSCs)成为近几年来迅速发展的新型太阳能电池,其中将SnO_(2)纳米粒子层用作电子传输层(ETL)的钙钛矿太阳能电池器件得到了广泛的关注。SnO_(2)有着更低的制备温度,使其具备应用于柔性器件的潜力,但与钙钛矿层能级不匹配等问题限制着其发展。而在界面处加入钝化层,尤其是表面卤化的方法或可解决这一问题。本文综合研究了SnO_(2)表面卤化对钙钛矿太阳能电池光伏性能的影响,选用四丁基氯化铵(TBAC)、四丁基溴化铵(TBAB)和四丁基碘化铵(TBAI)三种钝化材料对SnO_(2)表面进行钝化处理,并对钝化材料溶液进行了浓度梯度研究。通过材料形貌、结构和光学性能表征以及电池器件性能测试分析等方法,证明了SnO_(2)表面卤化可提高钙钛矿层的质量和PSCs光伏性能,并从器件内部电荷传输动力学等角度解释了器件性能改善的原因。为进一步说明其性能改善的机理,采用基于密度泛函理论(DFT)的第一性原理计算方法对材料表面性质进行了深入研究,从能量、结构、电荷密度、态密度、功函数等角度解释了表面卤化提高SnO_(2)/钙钛矿界面处电子传输特性的原因。实验和理论计算均表明TBAC对于SnO_(2)具有较好的钝化效果,并随着溶液浓度的提升钝化作用越明显。SnO_(2)表面卤化作用的深入研究不仅对提高电池器件性能具有实际意义,还能够帮助理解太阳能电池界面现象,为界面改性提供新的研究思路。

Orthogonal analysis of water model study on the optimization of flow control devices in a six-strand tundish

Improper flow control devices in a multi-strand tundish can cause some problems, for example, liquid steel cannot reach every nozzle at the same time and the liquid steel in nozzles far away from the entry zone has a lower temperature. The water model experiment of a six-strand tundish of Tianjin Iron ＆ Steel Co. Ltd. was performed, a new ＂U＂ type baffle was obtained, and its parameters were defined by perpendicular analysis. The ＂U＂ baffle can not only improve those imperfections, but also prolong the residence time of nonmetallic inclusions, which is good for their flotation and separation.

Boosting Chemodynamic Therapy by the Synergistic Effect of Co‑Catalyze and Photothermal Effect Triggered by the Second Near‑Infrared Light

In spite of the tumor microenvironments responsive cancer therapy based on Fenton reaction(i.e.,chemodynamic therapy,CDT)has been attracted more attentions in recent years,the limited Fenton reaction efficiency is the important obstacle to further application in clinic.Herein,we synthesized novel FeO/MoS2 nanocomposites modified by bovine serum albumin(FeO/MoS2-BSA)with boosted Fenton reaction efficiency by the synergistic effect of co-catalyze and photothermal effect of MoS2 nanosheets triggered by the second near-infrared(NIR II)light.In the tumor microenvironments,the MoS2 nanosheets not only can accelerate the conversion of Fe3+ions to Fe2+ions by Mo4+ions on their surface to improve Fenton reaction efficiency,but also endow FeO/MoS2-BSA with good photothermal performances for photothermal-enhanced CDT and photothermal therapy(PTT).Consequently,benefiting from the synergetic-enhanced CDT/PTT,the tumors are eradicated completely in vivo.This work provides innovative synergistic strategy for constructing nanocomposites for highly efficient CDT.

Intelligent Segmentation and Measurement Model for Asphalt Road Cracks Based on Modified Mask R-CNN Algorithm

Nowadays, asphalt road has dominated highways around the world. Among various defects of asphalt road, crackshave been paid more attention, since cracks often cause major engineering and personnel safety incidents. Currentmanual crack inspection methods are time-consuming and labor-intensive, and most segmentation methods cannot detect cracks at the pixel level. This paper proposes an intelligent segmentation and measurement model basedon the modified Mask R-CNN algorithm to automatically and accurately detect asphalt road cracks. The modelproposed in this paper mainly includes a convolutional neural network (CNN), an optimized region proposalnetwork (RPN), a region of interest (RoI) Align layer, a candidate area classification network and a Mask branch offully convolutional network (FCN). The ratio and size of anchors in the RPN are adjusted to improve the accuracyand efficiency of segmentation. Soft non-maximum suppression (Soft-NMS) algorithm is developed to improvethe segmentation accuracy. A dataset including 8,689 images (512× 512 pixels) of asphalt cracks is established andthe road crack is manually marked. Transfer learning is used to initialize the model parameters in the trainingprocess. To optimize the model training parameters, multiple comparison experiments are performed, and the testresults show that the mean average precision (mAP) value and F1-score of the optimal trained model are 0.952 and0.949. Subsequently, the robustness verification test and comparative test of the trained model are conducted andthe topological features of the crack are extracted. Then, the damage area, length and average width of the crackare measured automatically and accurately at pixel level. More importantly, this paper develops an automatic crackdetection platform for asphalt roads to automatically extract the number, area, length and average width of cracks,which can significantly improve the crack detection efficiency for the road maintenance industry.

Digital Twin-based Quality Management Method for the Assembly Process of Aerospace Products with the Grey-Markov Model and Apriori Algorithm

The assembly process of aerospace products such as satellites and rockets has the characteristics of single-or small-batch production,a long development period,high reliability,and frequent disturbances.How to predict and avoid quality abnormalities,quickly locate their causes,and improve product assembly quality and efficiency are urgent engineering issues.As the core technology to realize the integration of virtual and physical space,digital twin(DT)technology can make full use of the low cost,high efficiency,and predictable advantages of digital space to provide a feasible solution to such problems.Hence,a quality management method for the assembly process of aerospace products based on DT is proposed.Given that traditional quality control methods for the assembly process of aerospace products are mostly post-inspection,the Grey-Markov model and T-K control chart are used with a small sample of assembly quality data to predict the value of quality data and the status of an assembly system.The Apriori algorithm is applied to mine the strong association rules related to quality data anomalies and uncontrolled assembly systems so as to solve the issue that the causes of abnormal quality are complicated and difficult to trace.The implementation of the proposed approach is described,taking the collected centroid data of an aerospace product’s cabin,one of the key quality data in the assembly process of aerospace products,as an example.A DT-based quality management system for the assembly process of aerospace products is developed,which can effectively improve the efficiency of quality management for the assembly process of aerospace products and reduce quality abnormalities.

Model for seawater fouling and effects of temperature,flow velocity and surface free energy on seawater fouling

A kinetic model was proposed to predict the seawater fouling process in the seawater heat exchangers.The new model adopted an expression combining depositional and removal behaviors for seawater fouling based on the Kern–Seaton model.The present model parameters include the integrated kinetic rate of deposition(k d)and the integrated kinetic rate of removal(k r),which have clear physical signi ficance.A seawater-fouling monitoring device was established to validate the model.The experimental data were well fitted to the model,and the parameters were obtained in different conditions.SEM and EDX analyses were performed after the experiments,and the results show that the main components of seawater fouling are magnesium hydroxide and aluminum hydroxide.The effects of surface temperature,flow velocity and surface free energy were assessed by the model and the experimental data.The results indicate that the seawater fouling becomes aggravated as the surface temperature increased in a certain range,and the seawater fouling resistance reduced as the flow velocity of seawater increased.Furthermore,the effect of the surface free energy of metals was analyzed,showing that the lower surface free energy mitigates the seawater fouling accumulation.

Methods and Practices for Institutional Benchmarking based on Research Impact and Competitiveness: A Case Study of ShanghaiTech University

Purpose: To develop and test a mission-oriented and multi-dimensional benchmarking method for a small scale university aiming for internationally first-class basic research.Design/methodology/approach: An individualized evidence-based assessment scheme was employed to benchmark ShanghaiTech University against selected top research institutions,focusing on research impact and competitiveness at the institutional and disciplinary levels.Topic maps opposing ShanghaiTech and corresponding top institutions were produced for the main research disciplines of ShanghaiTech. This provides opportunities for further exploration of strengths and weakness. Findings: This study establishes a preliminary framework for assessing the mission of the university. It further provides assessment principles, assessment questions, and indicators.Analytical methods and data sources were tested and proved to be applicable and efficient.Research limitations: To better fit the selective research focuses of this university, its schema of research disciplines needs to be re-organized and benchmarking targets should include disciplinary top institutions and not necessarily those universities leading overall rankings.Current reliance on research articles and certain databases may neglect important research output types.Practical implications: This study provides a working framework and practical methods for mission-oriented, individual, and multi-dimensional benchmarking that ShanghaiTech decided to use for periodical assessments. It also offers a working reference for other institutions to adapt. Further needs are identified so that ShanghaiTech can tackle them for future benchmarking.Originality/value: This is an effort to develop a mission-oriented, individually designed,systematically structured, and multi-dimensional assessment methodology which differs from often used composite indices.

Wendan decoction improves learning and memory deficits in a rat model of schizophrenia

An experimental model of schizophrenia was established using dizocilpine （MK-801）. Rats were intragastrically administered with Wendan decoction or clozapine for 21 days prior to establishing the model. The results revealed that the latency of schizophrenia model rats to escape from the hidden platform in the Morris water maze was significantly shortened after administration of Wendan decoction or clozapine. In addition, the treated rats crossed the platform significantly more times than the untreated model rats. Moreover, the rate of successful long-term potentiation induction in the Wendan decoction group and clozapine group were also obviously increased compared with the model group, and the population spike peak latency was significantly shortened. These experimental findings suggest that Wendan decoction can improve the learning and memory ability of schizophrenic rats to the same extent as clozapine treatment.

含噻二唑季铵盐表面活性剂对Q235钢的缓蚀性能

通过表面张力法研究一种含噻二唑季铵盐表面活性剂(MTOTB)在1 mol/L HCl溶液中的表面活性;通过电化学测试、静态失重和表面形貌分析研究MTOTB及相应的2-巯基-5-甲基-1,3,4-噻二唑(MMTD)在1 mol/L HCl溶液中对Q235碳钢的缓蚀性能。结果表明,MTOTB在1 mol/L HCl溶液中的临界胶束浓度为0.36 mmol/L;当添加浓度为0.5 mmol/L时,MTOTB对在1 mol/L HCl溶液中浸泡48 h碳钢片的缓蚀率可达95.34%,同样条件下,MMTD对碳钢的缓蚀率为78.34%,说明MTOTB对碳钢的腐蚀抑制效率显著优于MMTD。SEM-EDS表明,MTOTB可以吸附在碳钢表面,有效抑制碳钢片的腐蚀。

Distribution and segregation of dissolved elements in pipeline slab

The chemical composition in a cross section of a high grade pipeline slab was measured point by point （in a scale of 1 μm） using original position statistic distribution analysis （OPA）. The result indicated that negative segregation strips of Si, Mn, Mo, Ni, Cr, Nb, Cu, Ti, and V exist in the two sides 24 mm away from the central line, with a width of 8-12 mm, Negative segregation inside the central line is more severe than that outside the central line, and the highest positive segregation of the elements appears closely by the inner sides of the negative segregation strips. No obvious negative segregation strip of S and P is found. Segregation of the elements in the central area is higher than that in the outer and inner arc areas. The segregation of C, Ti, S, and P is high and that of Cr, Cu, Si, and Mn is low in the slab.

Weakly-Supervised Single-view Dense 3D Point Cloud Reconstruction via Differentiable Renderer

In recent years,addressing ill-posed problems by leveraging prior knowledge contained in databases on learning techniques has gained much attention.In this paper,we focus on complete three-dimensional(3D)point cloud reconstruction based on a single red-green-blue(RGB)image,a task that cannot be approached using classical reconstruction techniques.For this purpose,we used an encoder-decoder framework to encode the RGB information in latent space,and to predict the 3D structure of the considered object from different viewpoints.The individual predictions are combined to yield a common representation that is used in a module combining camera pose estimation and rendering,thereby achieving differentiability with respect to imaging process and the camera pose,and optimization of the two-dimensional prediction error of novel viewpoints.Thus,our method allows end-to-end training and does not require supervision based on additional ground-truth(GT)mask annotations or ground-truth camera pose annotations.Our evaluation of synthetic and real-world data demonstrates the robustness of our approach to appearance changes and self-occlusions,through outperformance of current state-of-the-art methods in terms of accuracy,density,and model completeness.

Multi-Branch Cable Harness Layout Design Based on Genetic Algorithm with Probabilistic Roadmap Method

Current studies on cable harness layouts have mainly focused on cable harness route planning.However,the topological structure of a cable harness is also extremely complex,and the branch structure of the cable harness can affect the route of the cable harness layout.The topological structure design of the cable harness is a key to such a layout.In this paper,a novel multi-branch cable harness layout design method is presented,which unites the probabilistic roadmap method(PRM)and the genetic algorithm.First,the engineering constraints of the cable harness layout are presented.An obstacle-based PRM used to construct non-interference and near to the surface roadmap is then described.In addition,a new genetic algorithm is proposed,and the algorithm structure of which is redesigned.In addition,the operation probability formula related to fitness is proposed to promote the efficiency of the branch structure design of the cable harness.A prototype system of a cable harness layout design was developed based on the method described in this study,and the method is applied to two scenarios to verify that a quality cable harness layout can be efficiently obtained using the proposed method.In summary,the cable harness layout design method described in this study can be used to quickly design a reasonable topological structure of a cable harness and to search for the corresponding routes of such a harness.

Meta-analysis of 20 clinical,randomized,controlled trials of acupuncture for depression

OBJECTIVE： To determine the efficacy of acupuncture in the treatment of depression by performing systematical reviews and meta-analysis from 20 articles of clinical, randomized, controlled studies.DATA SOURCES： A computer-based online search of PubMed Database, Chinese Biological Medicine Database （VIP database）, China Knowledge Database, and Wanfang Database was performed to search articles published between January 1999 and September 2009. DATA SELECTION： Inclusion criteria： articles published in official academic journals; articles with definite diagnostic criteria and acknowledgment; articles involving subjects with depression or depressive disorders, with no limitations to age, sex, or source; articles involving acupuncture-related therapies （including acupuncture needle, electro-acupuncture, moxibustion, abdominal acupuncture, etc.） as the primary means of intervention; articles of randomized controlled trials or involving ＂randomized controlled＂, ＂randomized grouping＂, or ＂random＂. Jadad scores were utilized to evaluate quality of included articles. Review Manage 4.2.7 software was used to evaluate efficacy of acupuncture in treating depression, and Hamilton Depression Rating Scale （HAMD） score, Self-Rating Depression Scale （SDS） score, and meta-analysis were used to evaluate clinical efficacy. Meta-analysis of a fixed effect model was performed when P 〉 0.05 or P 〉 0.01 in the test for heterogeneity. Meta-analysis of the random effect model was performed when P≤0.05.MAIN OUTCOME MEASURES： Efficacy rate, HAMD scores, and SDS scores. RESULTS： Quality evaluation of the 20 selected clinical, randomized, controlled trials demonstrated baseline equilibrium and randomness, although a considerable number of randomized studies simply mentioned ＂random＂ without describing a specific method. Therefore, the reliability of randomness was relatively low. An envelope to hide the information was not used, and proper blinding was difficult to implement due to the innate features of acupuncture. The follow-up rate was low, and reasons for dropout were not explored. Therefore, it was not possible to objectively evaluate the study results. In addition, the study did not estimate sample size; it was unclear whether the sample was truly representative of general characteristics. Meta-analysis showed that acupuncture monotherapy exhibited similar efficacy to Western medicine for treating depression： combined effect size OR = 1.66, 95% CI： 0.59 -4.65, combined effect value test： Z= 0.97, P = 0.33. Comparison of the efficacy of acupuncture combination therapy with Western medicine demonstrated a combined effect size OR = 2.46, 95% CI： 1.64-3.71 and combined effect of the value of Z= 4.32 （P 〈 0.01）, implying that there was insufficient evidence to prove a superior effect of acupuncture combination therapy over Western medicine. In terms of HAMD and SDS scores, the weighted mean difference was -2.01 and -8.68, respectively, with 95% Cl： -3.48 to 0.53, -11.21 to -6.16 （P 〈 0.01）, suggesting that acupuncture efficacy was significantly better than the control group.CONCLUSION： The efficacy of acupuncture monotherapy was similar to Western medicine for treating depression. However, efficacy of combination therapy remains uncertain due to inadequate study design （implementation of randomization and blinding, sample size estimation, and data processing methods）.

医用有机化学在线考试的探索与实践

通过总结本团队2020年春季学期对"医用有机化学"在线考试的考试方法、试题题型的设计,试卷难度的调控及防作弊措施的实施,对有机化学在线考试优缺点进行了分析,为今后有机化学课程开展在线考试提供参考。