Progress in etiological diagnosis of viral meningitis

In recent years, with the rapid development of molecular biology techniques such as polymerase chain reaction and molecular biochip, the etiological diagnosis of viral encephalitis has a very big step forward. At present, the etiological examination of viral meningitis mainly includes virus isolation, serological detection and molecular biological nucleic acid detection. This article reviews the progress in etiological diagnosis of viral meningitis

The 3rd Anti-UAV Workshop & Challenge: Methods and Results

The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UAV Challenge has been publicly released. There are two main differences between this year's competition and the previous two. First, we have expanded the existing dataset, and for the first time, released a training set so that participants can focus on improving their models. Second, we set up two tracks for the first time, i.e., Anti-UAV Tracking and Anti-UAV Detection & Tracking. Around 76 participating teams from the globe competed in the 3rd Anti-UAV Challenge. In this paper, we provide a brief summary of the 3rd Anti-UAV Workshop & Challenge including brief introductions to the top three methods in each track. The submission leaderboard will be reopened for researchers that are interested in the Anti-UAV challenge. The benchmark dataset and other information can be found at: https://anti-uav.github.io/.Comment: Technical report for 3rd Anti-UAV Workshop and Challenge. arXiv admin note: text overlap with arXiv:2108.0990

A blockchain and IoT-based lightweight framework for enabling information transparency in supply chain finance

Supply Chain Finance (SCF) refers to the financial service in which banks rely on core enterprises to manage the capital flow and logistics of upstream and downstream enterprises. SCF adopts a self-testing and closed-loop credit model to control funds and risks. The key factor in a successful SCF service is the deployment of SCF businessoriented information systems that allow businesses to form partnerships efficiently and expedite cash flows throughout the supply chain. Blockchain Technology (BCT), featuring decentralization, tamper-proofing, traceability, which is usually paired with the Internet of Things (IoT) in real-world contexts, has been widely adopted in the field of finance and is perfectly positioned to facilitate innovative collaborations among participants in supply chain networks. In this paper, we propose a BCT and IoT-based information management framework (named BC4Regu), which works as the regulatory to improve the information transparency in the business process of SCF. With BC4Regu, the operation cost of the whole supply chain can be significantly reduced through the coordination and integration of capital flow, information flow, logistics and trade flow in the supply chain. The contributions in this paper include: (1) proposing a novel information management framework which leverages Blockchain and IoT to solve the problem of information asymmetry in the trade of SCF; (2) proposing the technical design of BC4Regu, including the Blockchain infrastructure, distributed ledger-based integrated data flow service, and reshaped SCF process; and (3) applying BC4Regu to a group of scenarios and conducting theoretical analysis by introducing the principal-agent model to validate the BC4Regu

Research on Machining Error Compensation in High-precision Surface Grinding Machine for Optical Aspheric Elements

Conference Name:5th International Symposium on Advanced Optical Manufacturing and Testing Technologies - Advanced Optical Manufacturing Technologies. Conference Address: Dalian, PEOPLES R CHINA. Time:APR 26-29, 2010.Using aspheric component in optical system can correct optical aberration, acquire high imaging quality, improve the optical characteristic, simplify system structure, and reduce system volume. Nowadays, high-precision surface grinding machine is an important approach to processing optical aspheric elements. However, because of the characteristics of optical aspheric elements, the processing method makes a higher demand to whole performance of surface grinding machine, and hardly to achieve ideal machining effect. Taking high generality and efficiency into account, this paper presents a compensation method for machining errors of high-precision surface grinding machine, which bases on optical aspheric elements, to achieve high-precision machining for all kinds of optical aspheric elements. After compensation, the machining accuracy of grinding machine could reach 2um/200x200mm. The research bases on NC surface grinding machine which is self developed. First of all, this paper introduces machining principle for optical aspheric elements on the grinding machine. And then error sources which producing errors are analyzed. By contacting and non-contacting measurement sensors, measurement software which is self designed realizes on-position measure for grinded workpiece, then fits surface precision and machining errors. Through compensation software for machining error which is self designed, compensation algorithm is designed and translated compensation data into G-code for the high-precision grinding machine to achieve compensation machining. Finally, by comparison between machining error compensation before and after processing, the experiments for this purpose are done to validate the compensation machining accuracy

Research on Measuring Path and Surface Fitting Algorithm for Non-axisymmetric Aspheric

Conference Name:International Conference on Manufacturing Science and Engineering (ICMSE 2009). Conference Address: Zhuhai, PEOPLES R CHINA. Time:DEC 26-28, 2009.In accordance with the requirements and characteristics of non-axisymmetric aspheric surface measuring, three measuring paths were put forward and estimated. The applicant situations of the three paths were also analyzed. A data processing system was created for the measuring of non-axisymmetric aspheric surface. Levenberg-Marquardt method was adopted as the nonlinear least squares to fit the discrete data. The fitting result was assessed by the fitting residuals. The experimental results show that the fitting residuals was in the 10(-3)mm magnitude when convergence index parameter set as 1 x 10(-10) mm. Compared with the theory equation, it's shown that the method can not only be used for non-axisymmetric aspheric surface quality evaluation, but also can generate compensation data to improve machining precision

Deep Learning Approach for Deduction of 3D Non-Rigid Transformation Based on Multi-Control Point Perception Data

In complex measurement systems, scanning the shape data of solid models is time consuming, and real-time solutions are required. Therefore, we developed a 3D non-rigid transformation deduction model based on multi-control point perception data. We combined a convolutional neural network (CNN), gated recurrent unit (GRU), and self-attention mechanism (SA) to develop the CNN-GRU-SA deduction network, which can deduce 3D non-rigid transformations based on multiple control points. We compared the proposed network to several other networks, with the experimental results indicating that the maximum improvements in terms of loss and root-mean-squared error (RMSE) on the training set were 39% and 49%, respectively; the corresponding values for the testing set were 48% and 29%. Moreover, the average deviation of the inference results and average inference time were 0.55 mm and 0.021 s, respectively. Hence, the proposed deep learning method provides an effective method to simulate and deduce the 3D non-rigid transformation processes of entities in the measurement system space, thus highlighting its practical significance in optimizing entity deformation

Study on method and compensation technology of off-axis wedge aspheric parallel grinding

To satisfy the machining requirement of high-precision off-axis wedge aspheric lens in precision optical system, a grinding method of off-axis wedge aspheric with high efficiency using the coordination of the 3-axis computer numerical control(CNC) clamp and high-precision CNC grinding system is presented. The structure of 3-axis rotation CNC clamp and the control software are designed and achieved. The parallel grinding method of off-axis wedge aspheric lens is realized in the CNC plane grinding machine by using the proposed clamp. It simplifies the grinding process and improves machining efficiency. The interpolation error and machining profile error are simulated according to the principle of parallel grinding. The simulation results show that the rotation errors of clamp and the workpiece's sharp have an effect on the machining accuracy remarkably. Based on the simulation results and the principle of parallel grinding, the onsite compensation method is implemented. The machining and compensation experimental results show that the machining accuracy can be improved effectively through compensation method. ?2011 Journal of Mechanical Engineering

Protein-Based Fingerprint Analysis for the Identification of Ranae Oviductus Using RP-HPLC

This work demonstrated a method combining reversed-phase high-performance liquid chromatography (RP-HPLC) with chemometrics analysis to identify the authenticity of Ranae Oviductus. The fingerprint chromatograms of the Ranae Oviductus protein were established through an Agilent Zorbax 300SB-C8 column and diode array detection at 215 nm, using 0.085% TFA (v/v) in acetonitrile (A) and 0.1% TFA in ultrapure water (B) as mobile phase. The similarity was in the range of 0.779–0.980. The fingerprint chromatogram of Ranae Oviductus showed a significant difference with counterfeit products. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) successfully identified Ranae Oviductus from the samples. These results indicated that the method established in this work was reliable

Genetic polymorphism and forensic application of 23 autosomal STR loci in the Han population of Panjin City, Liaoning Province, Northeastern China

Background Short tandem repeats (STRs) are consecutive repetition of a repeat motif and widely used in forensic medicine and human genetics because of their high polymorphism. Subjects and methods In the current study, 23 autosomal STR loci were genotyped from 1263 unrelated healthy individuals living in Panjin City, Liaoning Province, Northeastern China using the VeriFilerTM Express PCR Amplification Kit. The population comparison was performed between the Panjin Han population and the other relevant groups to further explore the structure of Panjin Han and its relationship with the other groups. Results The results found 316 alleles across the 23 STRs and the corresponding allelic frequencies ranged from 0.5198 to 0.0004. Except for D3S1358, TPOX, TH01, and D3S1358, all STR loci were highly polymorphic (PIC > 0.7), with the Penta E locus having the highest degree of polymorphism (0.9147). For population comparison, the exact test of population differentiation found that no significant difference was observed between the Panjin Han and the other Han populations, except for Guangdong Han and Jiangxi Han. Conclusion The Panjin Han population showed significant differences with the other ethnic groups in China (Bouyei, Dong, Hui, Miao, Tibetan, and Uygur) and the foreign ethnic groups

Rana chensinensis Ovum Oil Based on CO2 Supercritical Fluid Extraction: Response Surface Methodology Optimization and Unsaturated Fatty Acid Ingredient Analysis

Rana chensinensis ovum oil (RCOO) is an emerging source of unsaturated fatty acids (UFAs), but it is lacking in green and efficient extraction methods. In this work, using the response surface strategy, we developed a green and efficient CO2 supercritical fluid extraction (CO2-SFE) technology for RCOO. The response surface methodology (RSM), based on the Box–Behnken Design (BBD), was used to investigate the influence of four independent factors (pressure, flow, temperature, and time) on the yield of RCOO in the CO2-SFE process, and UPLC-ESI-Q-TOP-MS and HPLC were used to identify and analyze the principal UFA components of RCOO. According to the BBD response surface model, the optimal CO2-SFE condition of RCOO was pressure 29 MPa, flow 82 L/h, temperature 50 °C, and time 132 min, and the corresponding predicted optimal yield was 13.61%. The actual optimal yield obtained from the model verification was 13.29 ± 0.37%, and the average error with the predicted value was 0.38 ± 0.27%. The six principal UFAs identified in RCOO included eicosapentaenoic acid (EPA), α-linolenic acid (ALA), docosahexaenoic acid (DHA), arachidonic acid (ARA), linoleic acid (LA), and oleic acid (OA), which were important biologically active ingredients in RCOO. Pearson correlation analysis showed that the yield of these UFAs was closely related to the yield of RCOO (the correlation coefficients were greater than 0.9). Therefore, under optimal conditions, the yield of RCOO and principal UFAs always reached the optimal value at the same time. Based on the above results, this work realized the optimization of CO2-SFE green extraction process and the confirmation of principal bioactive ingredients of the extract, which laid a foundation for the green production of RCOO