The Effects of Environmental Toxins on Allergic Inflammation

San-Nan Yang,Chong-Chao Hsieh,Hsuan-Fu Kuo,Min-Sheng Lee,Ming-Yii Huang,Chang-Hung Kuo,Chih-Hsing Hung 대한천식알레르기학회 2014 Allergy, Asthma & Immunology Research Vol.6 No.6

The prevalence of asthma and allergic disease has increased worldwide over the last few decades. Many common environmental factors are associated with this increase. Several theories have been proposed to account for this trend, especially those concerning the impact of environmental toxicants. The development of the immune system, particularly in the prenatal period, has far-reaching consequences for health during early childhood, and throughout adult life. One underlying mechanism for the increased levels of allergic responses, secondary to exposure, appears to be an imbalance in the T-helper function caused by exposure to the toxicants. Exposure to environmental endocrine-disrupting chemicals can result in dramatic changes in cytokine production, the activity of the immune system, the overall Th1 and Th2 balance, and in mediators of type 1 hypersensitivity mediators, such as IgE. Passive exposure to tobacco smoke is a common risk factor for wheezing and asthma in children. People living in urban areas and close to roads with a high volume of traffic, and high levels of diesel exhaust fumes, have the highest exposure to environmental compounds, and these people are strongly linked with type 1 hypersensitivity disorders and enhanced Th2 responses. These data are consistent with epidemiological research that has consistently detected increased incidences of allergies and asthma in people living in these locations. During recent decades more than 100,000 new chemicals have been used in common consumer products and are released into the everyday environment. Therefore, in this review, we discuss the environmental effects on allergies of indoor and outside exposure.

DL-RRT* Algorithm for Least Dose Path Re-planning in Dynamic Radioactive Environments

Nan Chao,Yong-kuo Liu,HONG XIA,Min-jun Peng,Abiodun Ayodeji 한국원자력학회 2019 Nuclear Engineering and Technology Vol.51 No.3

One of the most challenging safety precautions for workers in dynamic, radioactive environments isavoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm,DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupationalworkers in nuclear facilities to avoid unnecessary radiation exposure. The method combines theprinciple of random tree star (RRT*) and D* Lite, and uses the expansion strength of grid search strategyfrom D* Lite to quickly find a high-quality initial path to accelerate convergence rate in RRT*. The algorithminherits probabilistic completeness and asymptotic optimality from RRT* to refine the existingpaths continually by sampling the search-graph obtained from the grid search process. It can not only beapplied to continuous cost spaces, but also make full use of the last planning information to avoid globalre-planning, so as to improve the efficiency of path planning in frequently changing environments. Theeffectiveness and superiority of the proposed method was verified by simulating radiation field undervarying obstacles and radioactive environments, and the results were compared with RRT* algorithmoutput.

Bias Adjustment of Satellite Precipitation Estimation Using Ground-Based Observation: Mei-Yu Front Case Studies in Taiwan

Yeh Nan-Ching,Chuang Yao-Chung,Peng Hsin-Shuo,Hsu Kuo-Lin 한국기상학회 2020 Asia-Pacific Journal of Atmospheric Sciences Vol.56 No.3

The Global Satellite Mapping of Precipitation (GSMaP) was used to estimate the accumulated rainfall in May from the Mei-Yu front in Taiwan. Rainfall estimation from GSMaP during 2002–2017 were evaluated using more than 400 local gauge observations, collected from the Taiwan CentralWeather Bureau (CWB). Studies have demonstrated that the GSMaP rainfall estimation estimates can be biased, depending on the target region, elevation, and season. In this experiment, we have evaluated GSMaP over three elevation ranges. The GSMaP systemic errors for each elevation range were identified and corrected using regression analysis. The results indicated that GSMaP estimation can be improved significantly through adjustment over three elevation ranges (elevation less than 50 m, elevation of 50–100 m, and elevation higher than 100 m). For these three elevation ranges, the correlation coefficient between the GSMaP estimations and CWB rainfall data was 0.76, 0.78, and 0.59, respectively. This indicated that the GSMaP estimation was more accurate for low-elevation regions than high-elevation regions. After the proposed approaches were employed to correct the errors, the bias errors were respectively improved by 5.64(13.7%), 7.33(38.4%) and 10.52(31.2%)mmfor low-, mid- and high-elevation regions. This study demonstrated that the local correction approaches can be used to improve GSMaP estimation of Mei-Yu rainfall in Taiwan.

Stroke and Bleeding Risk Assessment in Atrial Fibrillation: Where Are We Now?

Ling Kuo,Yi-Hsin Chan,Jo-Nan Liao,Shih-Ann Chen,Tze-Fan Chao 대한심장학회 2021 Korean Circulation Journal Vol.51 No.8

Most important international guidelines recommend the use of CHA2DS2-VASc and HAS-BLED scores for stroke and bleeding risk assessments in atrial fibrillation (AF) patients, respectively. The 2020 AF guidelines of European Society of Cardiology have revised the definition of “C: congestive heart failure (HF)” component, and now patients with either HF with reduced ejection fraction or preserved ejection fraction should be assigned 1 point. Hypertrophic cardiomyopathy was also included. Besides, the revised “V: vascular diseases” component included both prior myocardial infarction and “angiographically significant coronary artery disease”. It is important to understand that the stroke and bleeding risks of AF patients were not static and should be re-assessed regularly. A high HAS-BLED score itself should not be the only reason to withhold or discontinue oral anticoagulants, but remind physicians for the corrections of modifiable bleeding risk factors and more regular follow up. In the future, the AF duration and left atrial function may play an important role for personalized evaluation of individual stroke risk while more studies are necessary.

A multi-layer approach to DN 50 electric valve fault diagnosis using shallow-deep intelligent models

Liu, Yong-kuo,Zhou, Wen,Ayodeji, Abiodun,Zhou, Xin-qiu,Peng, Min-jun,Chao, Nan Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.1

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

The Protective Effect of Black Garlic Extracts on tBHP-induced Injury in Hepatocytes in vitro and in vivo

( Shih Rong Kuo ),( Hsin-i Chang ),( Cheng-nan Chen ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1

Black garlic has been reported to show multiple bioactivities against the development of different diseases. In this study, we investigated the hepatoprotective effect of black garlic on injured liver cells. Rat clone-9 hepatocytes were used for all the experiments. We used tert-Butyl hydroperoxide (tBHP) to induce injury of rat clone-9 hepatocytes. The contents of malondialdehyde (MDA) and glutathione (GSH), antioxidative enzyme activities of catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), and mRNA expressions of IL-6 and IL-8 in rat clone-9 hepatocytes were determined to evaluate the level of cell damage. We found that black garlic extracts significantly recovered tBHP-induced cell death of rat clone-9 hepatocytes. Pretreatment with black garlic extracts antagonized GSH depletion, tBHP-increased MDA accumulation, IL-6/IL-8 mRNA expressions, and tBHP-decreased antioxidative enzyme activities. Moreover, we further found that JNK signaling regulated black-garlic-inhibited tBHP effects in rat clone-9 hepatocytes. Our findings demonstrate that black garlic has great hepatoprotective potential to block tBHP-damaged effects on cell death, lipid peroxidation, oxidative stress, and inflammation in rat clone-9 hepatocytes. Thus, this study suggests that black garlic may be an excellent natural candidate in the development of adjuvant therapy and healthy foods for liver protection.

Serotonin Modulates the Correlations between Obsessive-compulsive Trait and Heart Rate Variability in Normal Healthy Subjects: A SPECT Study with [123I]ADAM and Heart Rate Variability Measurement

Che Yu Kuo,Kao Chin Chen,I Hui Lee,Huai-Hsuan Tseng,Nan Tsing Chiu,Po See Chen,Yen Kuang Yang,Wei Hung Chang 대한정신약물학회 2022 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.20 No.2

Objective: The impact of serotonergic system on obsessive-compulsive disorder (OCD) is well studied. However, the correlation between OC presentations and autonomic nervous system (ANS) is still unclear. Furthermore, whether the correlation might be modulated by serotonin is also uncertain. Methods: We recruited eighty-nine healthy subjects. Serotonin transporter (SERT) availability by [123I]ADAM and heart rate variability (HRV) tests were measured. Symptoms checklist-90 was measured for the OC presentations. The interaction between HRV and SERT availability were calculated and the correlation between HRV and OC symptoms were analyzed after stratified SERT level into two groups, split at medium. Results: The interactions were significant in the factors of low frequency (LF), high frequency (HF), and root mean square of successive differences (RMSSD). Furthermore, the significantly negative correlations between OC symptoms and the above HRV indexes existed only in subjects with higher SERT availability. Conclusion: OC symptoms might be correlated with ANS regulations in subjects with higher SERT availability.

A new perspective towards the development of robust data-driven intrusion detection for industrial control systems

Ayodeji, Abiodun,Liu, Yong-kuo,Chao, Nan,Yang, Li-qun Korean Nuclear Society 2020 Nuclear Engineering and Technology Vol.52 No.12

Most of the machine learning-based intrusion detection tools developed for Industrial Control Systems (ICS) are trained on network packet captures, and they rely on monitoring network layer traffic alone for intrusion detection. This approach produces weak intrusion detection systems, as ICS cyber-attacks have a real and significant impact on the process variables. A limited number of researchers consider integrating process measurements. However, in complex systems, process variable changes could result from different combinations of abnormal occurrences. This paper examines recent advances in intrusion detection algorithms, their limitations, challenges and the status of their application in critical infrastructures. We also introduce the discussion on the similarities and conflicts observed in the development of machine learning tools and techniques for fault diagnosis and cybersecurity in the protection of complex systems and the need to establish a clear difference between them. As a case study, we discuss special characteristics in nuclear power control systems and the factors that constraint the direct integration of security algorithms. Moreover, we discuss data reliability issues and present references and direct URL to recent open-source data repositories to aid researchers in developing data-driven ICS intrusion detection systems.

A Fast Gamma-Ray Dose Rate Assessment Method for Complex Geometries Based on Stylized Model Reconstruction

Li-qun Yang,Yong-kuo Liu,Min-jun Peng,Meng-kun Li,Nan Chao 한국원자력학회 2019 Nuclear Engineering and Technology Vol.51 No.5

A fast gamma-ray dose rate assessment method for complex geometries based on stylized modelreconstruction and point-kernel method is proposed in this paper. The complex three-dimensional (3D)geometries are imported as a 3DS format file from 3dsMax software with material and radiometric attributes. Based on 3D stylized model reconstruction of solid mesh, the 3D-geometrical solids are automaticallyconverted into stylized models. In point-kernel calculation, the stylized source models aredivided into point kernels and the mean free paths (mfp) are calculated by the intersections betweenshield stylized models and tracing ray. Compared with MCNP, the proposed method can implementcomplex 3D geometries visually, and the dose rate calculation is accurate and fast.

Real-World Effectiveness and Safety of SOF/LDV for Pa-tients with Chronic Hepatitis C in Taiwan

( Ching-chu Lo ),( Pin-nan Cheng ),( Chi-yi Chen ),( Chung-feng Huang ),( Hsing-tao Kuo ),( Kuo-chih Tseng ),( Yi-hsiang Huang ),( Chi-ming Tai ),( Cheng-yuan Peng ),( Ming-jong Bair ),( Chien-hung Ch 대한간학회 2021 춘·추계 학술대회 (KASL) Vol.2021 No.1