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  1. Article: Distribution of 137Cs in soil along Ta-han River Valley in Tau-Yuan County in Taiwan.

    Nabyvanets, Y B / Gesell, T F / Jen, M H / Chang, W P

    Journal of environmental radioactivity

    2001  Volume 54, Issue 3, Page(s) 391–400

    Abstract: ... of a research reactor site in the Ta-han River valley in Taiwan. In order to further characterize ...

    Abstract Environmental 137Cs contamination was suspected from accidents at spent fuel storage pits of a research reactor site in the Ta-han River valley in Taiwan. In order to further characterize this contamination, soil samples were collected and measured by a gamma-spectroscopy system in 1999. It was found that 137Cs contamination is distributed up to 4 km from the reactor in an area covered mostly by rice and plant fields. 137Cs concentration in the topsoil ranged up to about 1000 Bq kg-1, as compared with soil beyond the contaminated area, which does not exceed 15 Bq kg-1. Spatial distribution of 137Cs was characterized by strong non-uniformity, which complicated our understanding of the distribution pathway of the radionuclides. The highest concentrations of 137Cs, up to more than 1000 Bq kg-1, were found within a few rice fields. The relative location of these rice fields and the water supplies from local streams suggested that the 137Cs was distributed along water pathways in the valley.
    MeSH term(s) Agriculture ; Cesium Radioisotopes/analysis ; Environmental Monitoring ; Radioactive Hazard Release ; Soil Pollutants, Radioactive/analysis ; Taiwan
    Chemical Substances Cesium Radioisotopes ; Soil Pollutants, Radioactive
    Language English
    Publishing date 2001-05-17
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1483112-0
    ISSN 1879-1700 ; 0265-931X
    ISSN (online) 1879-1700
    ISSN 0265-931X
    DOI 10.1016/s0265-931x(00)00161-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book: Intracellular cholesterol trafficking

    Chang, Ta-Yuan

    [meeting held in St. Louis, Missouri in April 1997]

    1998  

    Author's details ed. by T. Y. Chang
    Language English
    Size X, 294 S. : Ill., graph. Darst.
    Publisher Kluwer
    Publishing place Boston u.a.
    Publishing country United States
    Document type Book
    HBZ-ID HT009966706
    ISBN 0-7923-8365-6 ; 978-0-7923-8365-9
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    1999 A 1185 order for loan Magazin

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  3. Article ; Online: Associations of road traffic noise and its frequency spectrum with prevalent depression in Taichung, Taiwan.

    Lin, Jia-Yi / Cheng, Wan-Ju / Wu, Chang-Fu / Chang, Ta-Yuan

    Frontiers in public health

    2023  Volume 11, Page(s) 1116345

    Abstract: Introduction: Exposure to road traffic noise has been reported to be associated with depression in many epidemiological studies, but the association between noise frequency spectrum and depression remains unclear. This community-based study investigated ...

    Abstract Introduction: Exposure to road traffic noise has been reported to be associated with depression in many epidemiological studies, but the association between noise frequency spectrum and depression remains unclear. This community-based study investigated the associations between road traffic noise exposure and its frequency components with prevalent depression.
    Methods: A total of 3,191 residents living in Taichung who participated in the Taiwan Biobank between 2010 and 2017, were included as study participants. The land-use regression models were used to evaluate individual annual average values of A-weighted equivalent sound level over 24 h (L
    Results: An interquartile range increase in L
    Conclusion: Exposure to road traffic noise may be associated with an increased prevalence of depression, particularly at 1,000 and 2,000 Hz.
    MeSH term(s) Humans ; Noise, Transportation/adverse effects ; Depression/epidemiology ; Taiwan/epidemiology ; Particulate Matter/analysis ; Geographic Information Systems
    Chemical Substances Particulate Matter
    Language English
    Publishing date 2023-01-27
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2711781-9
    ISSN 2296-2565 ; 2296-2565
    ISSN (online) 2296-2565
    ISSN 2296-2565
    DOI 10.3389/fpubh.2023.1116345
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Exposure and health risk assessment of volatile organic compounds among drivers and passengers in long-distance buses.

    Chen, Jing-Jie / Wang, Tiffany B / Chang, Li-Te / Chuang, Kai-Jen / Chuang, Hsiao-Chi / Chang, Ta-Yuan

    Environmental research

    2024  Volume 252, Issue Pt 3, Page(s) 118959

    Abstract: Exposure to volatile organic compounds (VOCs) such as benzene, toluene, ethylbenzene, xylene, and formaldehyde from long-distance buses has been reported to adversely affect human health. This study investigates the concentrations of these five VOCs and ... ...

    Abstract Exposure to volatile organic compounds (VOCs) such as benzene, toluene, ethylbenzene, xylene, and formaldehyde from long-distance buses has been reported to adversely affect human health. This study investigates the concentrations of these five VOCs and evaluates their health risks to drivers and passengers on board. Ten trips from Taipei to Taichung were performed during the warm and cold seasons of 2021-2022. Two locations inside the bus were established to collect air samples by a 6-liter canister for drivers and passengers. Exposure concentrations of benzene, toluene, ethylbenzene, and xylene were analyzed via gas chromatography with a flame ionization detector and the formaldehyde concentration was monitored using a formaldehyde meter. Subsequently, a Monte Carlo simulation was conducted to evaluate the carcinogenic and non-carcinogenic risks of the five VOCs. Formaldehyde emerged as the highest detected compound (9.06 ± 3.77 μg/m
    Language English
    Publishing date 2024-04-23
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 205699-9
    ISSN 1096-0953 ; 0013-9351
    ISSN (online) 1096-0953
    ISSN 0013-9351
    DOI 10.1016/j.envres.2024.118959
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 726: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: Application of artificial intelligence algorithms and low-cost sensors to estimate respirable dust in the workplace.

    Chang, Ta-Yuan / Chen, Guan-Yu / Chen, Jing-Jie / Young, Li-Hao / Chang, Li-Te

    Environment international

    2023  Volume 182, Page(s) 108317

    Abstract: The Internet of Things (IoT) and low-cost sensor technology have become common tools for environmental exposure monitoring; however, their application in measuring respirable dust (RD) in the workplace remains limited. This study aimed to develop a ... ...

    Abstract The Internet of Things (IoT) and low-cost sensor technology have become common tools for environmental exposure monitoring; however, their application in measuring respirable dust (RD) in the workplace remains limited. This study aimed to develop a predictive model for RD using artificial intelligence (AI) algorithms and low-cost sensors and subsequently assess its validity using a standard sampling approach. Various low-cost sensors were combined into an RD sensor module and mounted on a portable aerosol monitor (GRIMM 11-D) for two weeks. AI algorithms were used to capture data per minute over 14 days to establish predictive RD models. The best-fitting model was validated using an aluminum cyclone equipped with an air pump and polytetrafluoroethylene filters to sample the 8-hour RD for 5 days at an aircraft manufacturing company. This module was continuously monitored for two weeks to evaluate its stability. The RD concentration measured by GRIMM 11-D in a general outdoor environment over two weeks was 28.1 ± 16.1 μg/m
    MeSH term(s) Dust/analysis ; Occupational Exposure/analysis ; Artificial Intelligence ; Environmental Exposure ; Environmental Monitoring/methods ; Workplace ; Air Pollutants, Occupational ; Inhalation Exposure/analysis
    Chemical Substances Dust ; Air Pollutants, Occupational
    Language English
    Publishing date 2023-11-08
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 554791-x
    ISSN 1873-6750 ; 0160-4120
    ISSN (online) 1873-6750
    ISSN 0160-4120
    DOI 10.1016/j.envint.2023.108317
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3131: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: Application of artificial intelligence algorithms and low-cost sensors to estimate respirable dust in the workplace

    Ta-Yuan Chang / Guan-Yu Chen / Jing-Jie Chen / Li-Hao Young / Li-Te Chang

    Environment International, Vol 182, Iss , Pp 108317- (2023)

    2023  

    Abstract: The Internet of Things (IoT) and low-cost sensor technology have become common tools for environmental exposure monitoring; however, their application in measuring respirable dust (RD) in the workplace remains limited. This study aimed to develop a ... ...

    Abstract The Internet of Things (IoT) and low-cost sensor technology have become common tools for environmental exposure monitoring; however, their application in measuring respirable dust (RD) in the workplace remains limited. This study aimed to develop a predictive model for RD using artificial intelligence (AI) algorithms and low-cost sensors and subsequently assess its validity using a standard sampling approach. Various low-cost sensors were combined into an RD sensor module and mounted on a portable aerosol monitor (GRIMM 11-D) for two weeks. AI algorithms were used to capture data per minute over 14 days to establish predictive RD models. The best-fitting model was validated using an aluminum cyclone equipped with an air pump and polytetrafluoroethylene filters to sample the 8-hour RD for 5 days at an aircraft manufacturing company. This module was continuously monitored for two weeks to evaluate its stability. The RD concentration measured by GRIMM 11-D in a general outdoor environment over two weeks was 28.1 ± 16.1 μg/m3 (range: 2.4–85.3 μg/m3). Among the various established models, random forest regression was observed to have the best prediction capacity (R2 = 0.97 and root mean square error = 2.82 μg/m3) in comparison to the other 19 methods. Field-based validation revealed that the predicted RD concentration (35.9 ± 4.1 μg/m3, range: 32.7–42.9 μg/m3) closely approximated the results obtained by the traditional method (38.1 ± 8.9 μg/m3, range: 28.1–52.5 μg/m3), and a strong positive Spearman correlation was observed between the two (rs = 0.70). The average bias was −2.2 μg/m3 and the precision was 5.8 μg/m3, resulting in an accuracy of 6.2 μg/m3 (94.2 %). Data completeness was 99.7 % during the continuous two-week monitoring period. The developed sensor module of RD exhibited excellent predictive performance and good data stability that can be applied to exposure assessments in occupational epidemiological studies.
    Keywords Artificial intelligence ; Internet of things ; Low-cost sensor ; Random forest method ; Respirable dust ; Environmental sciences ; GE1-350
    Subject code 333
    Language English
    Publishing date 2023-12-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: ApoE and Lipid Homeostasis in Alzheimer's Disease: Introduction to the Thematic Review Series.

    Chang, Ta-Yuan / Chang, Catherine

    Journal of lipid research

    2017  Volume 58, Issue 5, Page(s) 823

    MeSH term(s) Alzheimer Disease/metabolism ; Apolipoproteins E/metabolism ; Homeostasis ; Humans ; Lipid Metabolism ; Systematic Reviews as Topic
    Chemical Substances Apolipoproteins E
    Language English
    Publishing date 2017-03-02
    Publishing country United States
    Document type Introductory Journal Article
    ZDB-ID 80154-9
    ISSN 1539-7262 ; 0022-2275
    ISSN (online) 1539-7262
    ISSN 0022-2275
    DOI 10.1194/jlr.R075697
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 175: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Associations of particulate matter, gaseous pollutants, and road traffic noise with the prevalence of asthma in children.

    Cho, Chih-I / Chen, Jing-Jie / Chuang, Kai-Jen / Chuang, Hsiao-Chi / Wang, I-Jen / Chang, Ta-Yuan

    Chemosphere

    2023  Volume 338, Page(s) 139523

    Abstract: The purposes of this study were to elucidate the associations between exposure to particulate matter, gaseous pollutants, and road traffic noise and asthma prevalence and to determine the interaction between exposure to multiple pollutants and asthma in ... ...

    Abstract The purposes of this study were to elucidate the associations between exposure to particulate matter, gaseous pollutants, and road traffic noise and asthma prevalence and to determine the interaction between exposure to multiple pollutants and asthma in children. A total of 3,246 children were recruited from 11 kindergartens in New Taipei City, Taiwan. Land use regression (LUR) was used to establish predictive models for estimating individual exposure levels of particulate matter, gaseous pollutants, and the 24 h A-weighted equivalent sound pressure level (L
    MeSH term(s) Humans ; Particulate Matter/analysis ; Air Pollution/analysis ; Environmental Pollutants ; Gases ; Noise, Transportation ; Prevalence ; Environmental Exposure/analysis ; Air Pollutants/analysis ; Asthma/epidemiology ; Nitrogen Dioxide/analysis
    Chemical Substances Particulate Matter ; Environmental Pollutants ; Gases ; Air Pollutants ; Nitrogen Dioxide (S7G510RUBH)
    Language English
    Publishing date 2023-07-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 120089-6
    ISSN 1879-1298 ; 0045-6535 ; 0366-7111
    ISSN (online) 1879-1298
    ISSN 0045-6535 ; 0366-7111
    DOI 10.1016/j.chemosphere.2023.139523
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2540: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  9. Article: Development and performance evaluation of a mixed-sensor system for fine particles and road traffic noise

    Wu, Chia-Chi / Tsai, Cheng-Yu / Chuang, Hsiao-Chi / Chang, Ta-Yuan

    Environmental technology & innovation. 2022 Nov., v. 28

    2022  

    Abstract: In recent years, the Internet of Things and low-cost sensor technologies have been applied to establish low-cost sensor networks for monitoring single pollutants in the environment. Few studies have developed a mixed-sensor system for simultaneous ... ...

    Abstract In recent years, the Internet of Things and low-cost sensor technologies have been applied to establish low-cost sensor networks for monitoring single pollutants in the environment. Few studies have developed a mixed-sensor system for simultaneous measurements of particles and noise, but the influences of meteorology and other pollutants are not taken into account. This study aimed to develop a mixed-sensor system for fine particles and noise with low-cost sensor technologies for considering effects of temperature, relative humidity, and carbon dioxide (CO₂). This mixed-sensor system was evaluated in the laboratory and field by using regular direct-reading instruments, including a portable dust monitor for fine particles and a class 1 sound level meter for noise measurements. Linear regression models were used to establish the relationships between measured values in the direct-reading instruments and sensor values. The present study established a predictive model of PM2.5 concentration with a high predictive capacity (R2=0.89) and good accuracy (bias and precision of 0.74±1.67μg/m³; accuracy of 1.82μg/m³ based on relative humidity, CO₂ levels, and PM2.5 sensor values). A predictive model of noise levels was built with a high predictive capacity (R2=0.96) and moderate accuracy (bias and precision of 2.92 ± 2.96 dBA; accuracy of 4.16 dBA based on temperature, relative humidity, CO₂ levels, and noise sensor values). The developed predictive models with the high and moderate accuracy for a mixed-sensor system can be applied to monitor PM2.5 and noise levels simultaneously for exposure assessment in exposure studies.
    Keywords Internet ; carbon dioxide ; dust ; environmental technology ; exposure assessment ; meteorology ; models ; regression analysis ; relative humidity ; sound level meters ; temperature ; traffic
    Language English
    Dates of publication 2022-11
    Publishing place Elsevier B.V.
    Document type Article
    ISSN 2352-1864
    DOI 10.1016/j.eti.2022.102902
    Database NAL-Catalogue (AGRICOLA)

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  10. Article: Cholesterol, Atherosclerosis, and APOE in Vascular Contributions to Cognitive Impairment and Dementia (VCID): Potential Mechanisms and Therapy.

    Duong, Michael Tran / Nasrallah, Ilya M / Wolk, David A / Chang, Catherine C Y / Chang, Ta-Yuan

    Frontiers in aging neuroscience

    2021  Volume 13, Page(s) 647990

    Abstract: Vascular contributions to cognitive impairment and dementia (VCID) are a common cause of cognitive decline, yet limited therapies exist. This cerebrovascular disease results in ... ...

    Abstract Vascular contributions to cognitive impairment and dementia (VCID) are a common cause of cognitive decline, yet limited therapies exist. This cerebrovascular disease results in neurodegeneration
    Language English
    Publishing date 2021-03-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2558898-9
    ISSN 1663-4365
    ISSN 1663-4365
    DOI 10.3389/fnagi.2021.647990
    Database MEDical Literature Analysis and Retrieval System OnLINE

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