Biosafety Risk Control Strategies in Laboratory Animal Research

Weng Shun-tai,Li Qu-wen,Gao Ya-dong,Qiu Yu-feng 한국산업안전보건공단 산업안전보건연구원 2024 Safety and health at work Vol.15 No.1

To understand biosafety's current situation in laboratory animal research and risk factors affecting occupational health. Compliance surveys were conducted by questionnaire via Questionnaire Star (an application app on the Internet) in Chinese. Thirty-nine anonymous questionnaires were collected. The surveyed institution has established 24 types of ABSL (Animal Biosafety Laboratory) and biosafety management organizations and systems equipped with safety equipment. Our study also suggests that the principal of the laboratory establishment fails to perform supervision and inspection responsibilities, the inappropriate design of the animal biosafety laboratory, non-standardized personnel training and health management, non-strict waste management, and insufficient emergency management. The administrative department and work units should address certain safety and occupational health risks in laboratory animal research. The author proposes control strategies based on organizational guarantee, personnel management, emergency management, etc., to help prevent risks and ensure occupational health. Due to regional limitations and small sample size, the results may not be generalisable to all parts of the world. However, some of the key common issues may also be present in other regions, so we believe that this research still has some relevance.

Detection of multi-type data anomaly for structural health monitoring using pattern recognition neural network

Shun Weng,Ke Gao,Zhi-Dan Chen,Hong Ping Zhu,Li-Ying Wu 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.1

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

Reverse Transformation From α' to γ in Lightly and Heavily Cold-Drawn Austenitic Stainless Steel Fibers

Shun-Tung Yang,Weng-Sing Hwang,Tien-Wei Shyr 대한금속·재료학회 2013 METALS AND MATERIALS International Vol.19 No.6

The reverse transformation of the strain-induced martensite phase (α') to the austenite phase (γ) is studied in lightly and heavily cold-drawn 316 L stainless steel fibers using thermomagnetic analysis. The transformation mechanisms of the two types of fiber are different. A three-region reverse transformation process for α' to γ during the heating process in the two types of fiber is established. Throughout the reverse process, the transformation is dominated by a diffusion-controlled mechanism for the two types of fiber. Shear reversion occurs for the lightly cold-drawn 316 L fiber in region II. A shoulder appears in the TMA curve at around 625 °C for the heavily colddrawn 316 L fiber Transformations of existing α' and reformed α' via the diffusion-controlled and shear mechanisms occur in the temperature range of 625-640°C for the heavily cold-drawn 316L fiber. The transformation is attributed to the reformed α' containing low Nieq content, which retards the reverse transformation of the phase via shear mechanisms until around 625°C.

STATEMENT : Seminar Report From the 2014 Taiwan Society of Inflammatory Bowel Disease (TSIBD) Spring Forum (May 24th, 2014): Crohn`s Disease Versus Intestinal Tuberculosis Infection

( Meng Tzu Weng ),( Shu Chen Wei ),( Chun Che Lin ),( Yuk Min Tsang ),( Chia Tung Shun ),( Jann Yuan Wang ),( Ming Jium Shieh ),( Cheng Yi Wang ),( Jau Min Wong ) 대한장연구학회 2015 Intestinal Research Vol.13 No.1

Since Taiwan is an endemic area for tuberculosis (TB), differential diagnosis between the intestinal TB and Crohn`s disease is an important issue. The steering committee of Taiwan Society of Inflammatory Bowel Disease (TSIBD) has arranged a seminar accordingly on May 24th, 2014 and the different point of views by gastroenterologist, radiologist, pathologist and infectious dis-ease specialist were suggested to help the proper diagnosis and management of these two diseases. (Intest Res 2015;13:6-10)

Calculation of eigenvalue and eigenvector derivatives with the improved Kron's substructuring method

Xia, Yong,Weng, Shun,Xu, You-Lin,Zhu, Hong-Ping Techno-Press 2010 Structural Engineering and Mechanics, An Int'l Jou Vol.36 No.1

For large-scale structures, the calculation of the eigensolution and the eigensensitivity is usually very time-consuming. This paper develops the Kron's substructuring method to compute the first-order derivatives of the eigenvalues and eigenvectors with respect to the structural parameters. The global structure is divided into several substructures. The eigensensitivity of the substructures are calculated via the conventional manner, and then assembled into the eigensensitivity of the global structure by performing some constraints on the derivative matrices of the substructures. With the proposed substructuring method, the eigenvalue and eigenvector derivatives with respect to an elemental parameter are computed within the substructure solely which contains the element, while the derivative matrices of all other substructures with respect to the parameter are zero. Consequently this can reduce the computation cost significantly. The proposed substructuring method is applied to the GARTEUR AG-11 frame and a highway bridge, which is proved to be computationally efficient and accurate for calculation of the eigensensitivity. The influence of the master modes and the division formations are also discussed.

Calculation of eigenvalue and eigenvector derivatives with the improved Kron’s substructuring method

Yong Xia,Shun Weng,You-Lin Xu,Hong-Ping Zhu 국제구조공학회 2010 Structural Engineering and Mechanics, An Int'l Jou Vol.36 No.1

For large-scale structures, the calculation of the eigensolution and the eigensensitivity is usually very time-consuming. This paper develops the Kron’s substructuring method to compute the firstorder derivatives of the eigenvalues and eigenvectors with respect to the structural parameters. The global structure is divided into several substructures. The eigensensitivity of the substructures are calculated via the conventional manner, and then assembled into the eigensensitivity of the global structure by performing some constraints on the derivative matrices of the substructures. With the proposed substructuring method, the eigenvalue and eigenvector derivatives with respect to an elemental parameter are computed within the substructure solely which contains the element, while the derivative matrices of all other substructures with respect to the parameter are zero. Consequently this can reduce the computation cost significantly. The proposed substructuring method is applied to the GARTEUR AG-11 frame and a highway bridge, which is proved to be computationally efficient and accurate for calculation of the eigensensitivity. The influence of the master modes and the division formations are also discussed.

Structural damage and force identification under moving load

Hongping Zhu,Ling Mao,Shun Weng,Yong Xia 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.53 No.2

Structural damage and moving load identification are the two aspects of structural system identification. However, they universally coexist in the damaged structures subject to unknown moving load. This paper proposed a dynamic response sensitivity-based model updating method to simultaneously identify the structural damage and moving force. The moving force which is equivalent as the nodal force of the structure can be expressed as a series of orthogonal polynomial. Based on the system Markov parameters by the state space method, the dynamic response and the dynamic response derivatives with respect to the force parameters and elemental variations are analytically derived. Afterwards, the damage and force parameters are obtained by minimizing the difference between measured and analytical response in the sensitivity-based updating procedure. A numerical example for a simply supported beam under the moving load is employed to verify the accuracy of the proposed method.

Structural damage and force identification under moving load

Zhu, Hongping,Mao, Ling,Weng, Shun,Xia, Yong Techno-Press 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.53 No.2

Structural damage and moving load identification are the two aspects of structural system identification. However, they universally coexist in the damaged structures subject to unknown moving load. This paper proposed a dynamic response sensitivity-based model updating method to simultaneously identify the structural damage and moving force. The moving force which is equivalent as the nodal force of the structure can be expressed as a series of orthogonal polynomial. Based on the system Markov parameters by the state space method, the dynamic response and the dynamic response derivatives with respect to the force parameters and elemental variations are analytically derived. Afterwards, the damage and force parameters are obtained by minimizing the difference between measured and analytical response in the sensitivity-based updating procedure. A numerical example for a simply supported beam under the moving load is employed to verify the accuracy of the proposed method.

Damage identification of vehicle-track coupling system from dynamic responses of moving vehicles

Zhu, Hong-Ping,Ye, Ling,Weng, Shun,Tian, Wei Techno-Press 2018 Smart Structures and Systems, An International Jou Vol.21 No.5

The structural responses are often used to identify the structural local damages. However, it is usually difficult to gain the responses of the track, as the sensors cannot be installed on the track directly. The vehicles running on a track excite track vibration and can also serve as response receivers because the vehicle dynamic response contains the vibration information of the track. A damage identification method using the vehicle responses and sensitivity analysis is proposed for the vehicle-track coupling system in this paper. Different from most damage identification methods of vehicle-track coupling system, which require the structural responses, only the vehicle responses are required in the proposed method. The local damages are identified by a sensitivity-based model updating process. In the vehicle-track coupling system, the track is modeled as a discrete point supported Euler-Bernoulli beam, and two vehicle models are proposed to investigate the accuracy and efficiency of damage identification. The measured track irregularity is considered in the calculation of vehicle dynamic responses. The measurement noises are also considered to study their effects to the damage identification results. The identified results demonstrate that the proposed method is capable to identify the local damages of the track accurately in different noise levels with only the vehicle responses.

Damage detection of subway tunnel lining through statistical pattern recognition

Yu, Hong,Zhu, Hong P.,Weng, Shun,Gao, Fei,Luo, Hui,Ai, De M. Techno-Press 2018 Structural monitoring and maintenance Vol.5 No.2

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.