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Displaying publications 61 - 66 of 66 in total

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GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models

Chen W, Li H, Hou E, Wang S, Wang G, Panahi M, et al.

Sci Total Environ, 2018 Sep 01;634:853-867.
PMID: 29653429 DOI: 10.1016/j.scitotenv.2018.04.055

The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers.
Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods

Chen W, Li Y, Xue W, Shahabi H, Li S, Hong H, et al.

Sci Total Environ, 2020 Jan 20;701:134979.
PMID: 31733400 DOI: 10.1016/j.scitotenv.2019.134979

Floods are one of the most devastating types of disasters that cause loss of lives and property worldwide each year. This study aimed to evaluate and compare the prediction capability of the naïve Bayes tree (NBTree), alternating decision tree (ADTree), and random forest (RF) methods for the spatial prediction of flood occurrence in the Quannan area, China. A flood inventory map with 363 flood locations was produced and partitioned into training and validation datasets through random selection with a ratio of 70/30. The spatial flood database was constructed using thirteen flood explanatory factors. The probability certainty factor (PCF) method was used to analyze the correlation between the factors and flood occurrences. Consequently, three flood susceptibility maps were produced using the NBTree, ADTree, and RF methods. Finally, the area under the curve (AUC) and statistical measures were used to validate the flood susceptibility models. The results indicated that the RF method is an efficient and reliable model in flood susceptibility assessment, with the highest AUC values, positive predictive rate, negative predictive rate, sensitivity, specificity, and accuracy for the training (0.951, 0.892, 0.941, 0.945, 0.886, and 0.915, respectively) and validation (0.925, 0.851, 0.938, 0.945, 0.835, and 0.890, respectively) datasets.
Utility of Simulation via Instant Messaging - Birmingham Advance (SIMBA) in medical education during COVID-19 pandemic

Morgan G, Melson E, Davitadze M, Ooi E, Zhou D, Hanania T, et al.

J R Coll Physicians Edinb, 2021 06;51(2):168-172.
PMID: 34131679 DOI: 10.4997/JRCPE.2021.218

BACKGROUND: Simulation via Instant Messaging - Birmingham Advance (SIMBA) aimed to improve clinicians' confidence in managing various clinical scenarios during the COVID-19 pandemic.
METHODS: Five SIMBA sessions were conducted between May and August 2020. Each session included simulation of scenarios and interactive discussion. Participants' self-reported confidence, acceptance, and relevance of the simulated cases were measured.
RESULTS: Significant improvement was observed in participants' self-reported confidence (overall n = 204, p<0.001; adrenal n = 33, p<0.001; thyroid n = 37, p<0.001; pituitary n = 79, p<0.001; inflammatory bowel disease n = 17, p<0.001; acute medicine n = 38, p<0.001). Participants reported improvements in clinical competencies: patient care 52.0% (n = 106/204), professionalism 30.9% (n = 63/204), knowledge on patient management 84.8% (n = 173/204), systems-based practice 48.0% (n = 98/204), practice-based learning 69.6% (n = 142/204) and communication skills 25.5% (n = 52/204).
CONCLUSION: SIMBA is a novel pedagogical virtual simulation-based learning model that improves clinicians' confidence in managing conditions across various specialties.
Fulltext Health-care data collecting, sharing, and using in Thailand, China mainland, South Korea, Taiwan, Japan, and Malaysia

Aljunid SM, Srithamrongsawat S, Chen W, Bae SJ, Pwu RF, Ikeda S, et al.

Value Health, 2012 2 1;15(1 Suppl):S132-8.
PMID: 22265060 DOI: 10.1016/j.jval.2011.11.004

This article sought to describe the health-care data situation in six selected economies in the Asia-Pacific region. Authors from Thailand, China mainland, South Korea, Taiwan, Japan, and Malaysia present their analyses in three parts. The first part of the article describes the data-collection process and the sources of data. The second part of the article presents issues around policies of data sharing with the stakeholders. The third and final part of the article focuses on the extent of health-care data use for policy reform in these different economies. Even though these economies differ in their economic structure and population size, they share some similarities on issues related to health-care data. There are two main institutions that collect and manage the health-care data in these economies. In Thailand, China mainland, Taiwan, and Malaysia, the Ministry of Health is responsible through its various agencies for collecting and managing the health-care data. On the other hand, health insurance is the main institution that collects and stores health-care data in South Korea and Japan. In all economies, sharing of and access to data is an issue. The reasons for limited access to some data are privacy protection, fragmented health-care system, poor quality of routinely collected data, unclear policies and procedures to access the data, and control on the freedom on publication. The primary objective of collecting health-care data in these economies is to aid the policymakers and researchers in policy decision making as well as create an awareness on health-care issues for the general public. The usage of data in monitoring the performance of the heath system is still in the process of development. In conclusion, for the region under discussion, health-care data collection is under the responsibility of the Ministry of Health and health insurance agencies. Data are collected from health-care providers mainly from the public sector. Routinely collected data are supplemented by national surveys. Accessibility to the data is a major issue in most of the economies under discussion. Accurate health-care data are required mainly to support policy making and evidence-based decisions.
Effects of different types of biochar on methane and ammonia mitigation during layer manure composting

Chen W, Liao X, Wu Y, Liang JB, Mi J, Huang J, et al.

Waste Manag, 2017 Mar;61:506-515.
PMID: 28117129 DOI: 10.1016/j.wasman.2017.01.014

Biochar, because of its unique physiochemical properties and sorption capacity, may be an ideal amendment in reducing gaseous emissions during composting process but there has been little information on the potential effects of different types of biochar on undesired gaseous emissions. The objective of this study was to examine the ability and mechanism of different types of biochar, as co-substrate, in mitigating gaseous emission from composting of layer hen manure. The study was conducted in small-scale laboratory composters with the addition of 10% of one of the following biochars: cornstalk biochar, bamboo biochar, woody biochar, layer manure biochar and coir biochar. The results showed that the cumulative NH3 production was significantly reduced by 24.8±2.9, 9.2±1.3, 20.1±2.6, 14.2±1.6, 11.8±1.7% (corrected for initial total N) in the cornstalk biochar, bamboo biochar, woody biochar, layer manure biochar and coir biochar treatments, respectively, compared to the control. Total CH4 emissions was significantly reduced by 26.1±2.3, 15.5±2.1, 22.4±3.1, 17.1±2.1% (corrected for the initial total carbon) for cornstalk biochar, bamboo biochar, woody biochar and coir biochar treatments than the control. Moreover, addition of cornstalk biochar increased the temperature and NO3(-)-N concentration and decreased the pH, NH4(+)-N and organic matter content throughout the composting process. The results suggested that total volatilization of NH3 and CH4 in cornstalk biochar treatment was lower than the other treatments; which could be due to (i) decrease of pH and higher nitrification, (ii) high sorption capacity for gases and their precursors, such as ammonium nitrogen from composting mixtures, because of the higher surface area, pore volumes, total acidic functional groups and CEC of cornstalk biochar.
[Invasion of Drosophila albomicans into Shanghai and areas nearby and a study on its mitochondrial DNA polymorphism]

Chen W, Zhang J, Geng Z, Zhu D

Yi Chuan Xue Bao, 1994;21(3):179-87.
PMID: 7917431

We report the fact that D. albomicans invaded into Shanghai suddenly in the autumn of 1991. Using 9 restriction enzymes, we analyse the RFLPs of mitochondrial DNA of 29 isofemale lines belonging to 4 populations of Shanghai, Jiading, Qinpu and Nanhui. We find that all 29 haplotypes are different from each other. Comparing with the populations of Canton, Kunming, Sanhutan (Taiwan), Sumoto (Japan), and Kuala Lumper (Malaysia), we come to the conclusion that D. albomicans caught in Shanghai and areas nearby is from a few of places in the south of China-mainland. This conclusion agrees with the viewpoint that this species is on the speciation stage of migration towards north. We also discuss the mtDNA polymorphism within the species.