The Bioclimatic map of Southern Vietnam for tourism development

Văn, Nguyễn Thành; Oanh, Hoang Thi Kieu; Vu, Vuong Van; Hien, Le Thi Thuy

doi:10.15625/0866-7187/41/2/13692

Cited by 2 publications

(2 citation statements)

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“…In subtropical northern Vietnam, winter lasts usually two or three cold months and temperatures can fall below freezing in mountainous areas. In tropical southern Vietnam, the temperatures of coldest months rarely drop below 18°C 37 . This suggests that northern bats need to hibernate in winter, whereas their southern counterparts do not.…”

Section: Divergent Evolution Of Bat Sarbecoviruses In Subtropical Nor...mentioning

confidence: 99%

Phylogeographic evolution of horseshoe bat sarbecoviruses in Vietnam and implications for the origins of SARS-CoV and SARS-CoV-2

HASSANIN,

Tu,

Görföl

et al. 2023

Preprint

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Previous studies on horseshoe bats (Rhinolophus spp.) have described many coronaviruses related to SARS-CoV (SARSCoVr) in China and only a few coronaviruses related to SARS-CoV-2 (SARSCoV2r) in Yunnan, Cambodia, Laos and Thailand. Here, we report the results of several field missions carried out in 2017, 2021 and 2022 across Vietnam during which 1,218 horseshoe bats were sampled. We assemble 38 Sarbecovirus genomes: 26 SARSCoVr from R. thomasi; six SARSCoVr and four SARSCoV2r from R. affinis; and two recombinants of SARSCoVr and SARSCoV2r from R. pusillus, one showing a receptor-binding domain of the Spike protein very similar to SARS-CoV-2. We detected a bat co-infected with four coronaviruses, including two sarbecoviruses. Our phylogeographic analysis suggests a divergent evolution between sarbecoviruses from subtropical northern Vietnam and those from tropical southern Vietnam, emergence of SARS-CoV in horseshoe bats from northern Yunnan and emergence of SARS-CoV-2 in horseshoe bats from southern Yunnan.

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Section: Divergent Evolution Of Bat Sarbecoviruses In Subtropical Nor...mentioning

confidence: 99%

Phylogeographic evolution of horseshoe bat sarbecoviruses in Vietnam and implications for the origins of SARS-CoV and SARS-CoV-2

HASSANIN,

Tu,

Görföl

et al. 2023

Preprint

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“…In this study, the data of daily water level was collected from 18 stations located in the Mekong River delta where floods are one of ruinous normal risks in the region, which has an incredible force and potential to hurt characteristic territories and people [74,75]. Water in this delta is descending from the rivers originating from Tibetan plateau and flowing into South Vietnam Sea through distributary channels of Mekong Delta.…”

Section: Data Usedmentioning

confidence: 99%

Novel Time Series Bagging Based Hybrid Models for Predicting Historical Water Levels in the Mekong Delta Region, Vietnam

Hoan¹,

Dũng²,

Thu³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

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Water level predictions in the river, lake and delta play an important role in flood management. Every year Mekong River delta of Vietnam is experiencing flood due to heavy monsoon rains and high tides. Land subsidence may also aggravate flooding problems in this area. Therefore, accurate predictions of water levels in this region are very important to forewarn the people and authorities for taking timely adequate remedial measures to prevent losses of life and property. There are so many methods available to predict the water levels based on historical data but nowadays Machine Learning (ML) methods are considered the best tool for accurate prediction. In this study, we have used surface water level data of 18 water level measurement stations of the Mekong River delta from 2000 to 2018 to build novel time-series Bagging based hybrid ML models namely: Bagging (RF), Bagging (SOM) and Bagging (M5P) to predict historical water levels in the study area. Performances of the Bagging-based hybrid models were compared with Reduced Error Pruning Trees (REPT), which is a benchmark ML model. The data of 19 years period was divided into 70:30 ratio for the modeling. The data of the period 1/2000 to 5/2013 (which is about 70% of total data) was used for the training and for the period 5/2013 to 12/2018 (which is about 30% of total data) was used for testing (validating) the models. Performance of the models was evaluated using standard statistical measures: Coefficient of Determination (R2), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results show that the performance of all the developed models is good (R2 > 0.9) for the prediction of water levels in the study area. However, the Bagging-based hybrid models are slightly better than another model such as REPT. Thus, these Bagging-based hybrid time series models can be used for predicting water levels at Mekong data.

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The Bioclimatic map of Southern Vietnam for tourism development

Cited by 2 publications

References 0 publications

Phylogeographic evolution of horseshoe bat sarbecoviruses in Vietnam and implications for the origins of SARS-CoV and SARS-CoV-2

Phylogeographic evolution of horseshoe bat sarbecoviruses in Vietnam and implications for the origins of SARS-CoV and SARS-CoV-2

Novel Time Series Bagging Based Hybrid Models for Predicting Historical Water Levels in the Mekong Delta Region, Vietnam

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