The use of machine learning to predict acute hepatopancreatic necrosis disease (AHPND) in shrimp farmed on the east coast of the Mekong Delta of Vietnam

2020 ◽  
Vol 86 (4) ◽  
pp. 673-683
Author(s):  
Nguyen Minh Khiem ◽  
Yuki Takahashi ◽  
Dang Thi Hoang Oanh ◽  
Tran Ngoc Hai ◽  
Hiroki Yasuma ◽  
...  
Keyword(s):  
Machine Learning ◽  
East Coast ◽  
Mekong Delta ◽  
Acute Hepatopancreatic Necrosis Disease

Use of GIS and machine learning to predict disease in shrimp farmed on the east coast of the Mekong Delta, Vietnam

2022 ◽  
Author(s):  
Nguyen Minh Khiem ◽  
Yuki Takahashi ◽  
Hiroki Yasuma ◽  
Dang Thi Hoang Oanh ◽  
Tran Ngoc Hai ◽  
...  
Keyword(s):  
Machine Learning ◽  
East Coast ◽  
Mekong Delta

scholarly journals Draft Genome Sequence of the Shrimp Pathogen Vibrio parahaemolyticus ST17.P5-S1, Isolated in Peninsular Malaysia

2018 ◽  
Vol 7 (11) ◽  
Author(s):  
Sridevi Devadas ◽  
Subha Bhassu ◽  
Tze Chiew Christie Soo ◽  
Fatimah M. Yusoff ◽  
Mohamed Shariff
Keyword(s):  
Antibiotic Resistance ◽  
Resistance Genes ◽  
Vibrio Parahaemolyticus ◽  
East Coast ◽  
Draft Genome ◽  
Antibiotic Resistance Genes ◽  
Peninsular Malaysia ◽  
Penaeus Vannamei ◽  
Content Type ◽  
Acute Hepatopancreatic Necrosis Disease

We sequenced the genome of Vibrio parahaemolyticus strain ST17.P5-S1, isolated from Penaeus vannamei cultured in the east coast of Peninsular Malaysia. The strain contains several antibiotic resistance genes and a plasmid encoding the Photorhabdus insect-related (Pir) toxin-like genes, pirAvp and pirBvp, associated with acute hepatopancreatic necrosis disease (AHPND).

Salinity intrusion prediction using remote sensing and machine learning in data-limited regions: A case study in Vietnam's Mekong Delta

2021 ◽  
pp. e00424
Author(s):  
Tien Giang Nguyen ◽  
Ngoc Anh Tran ◽  
Phuong Lan Vu ◽  
Quoc-Huy Nguyen ◽  
Huu Duy Nguyen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Mekong Delta ◽  
Salinity Intrusion

scholarly journals Prevalence of Vibrio parahaemolyticus Causing Acute Hepatopancreatic Necrosis Disease of Shrimp in Shrimp, Molluscan Shellfish and Water Samples in the Mekong Delta, Vietnam

Biology ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 312
Author(s):  
Tran Thi Hong To ◽  
Haruka Yanagawa ◽  
Nguyen Khanh Thuan ◽  
Du Minh Hiep ◽  
Doan Van Cuong ◽  
...  
Keyword(s):  
High Resistance ◽  
Water Samples ◽  
Vibrio Parahaemolyticus ◽  
Mekong Delta ◽  
Shrimp Ponds ◽  
O Antigen ◽  
Acute Hepatopancreatic Necrosis Disease ◽  
Resistance Rates ◽  
Shellfish Farms

A total of 481 samples, including 417 shrimp and molluscan shellfish samples from retail shops and farms and 64 water samples from shrimp and molluscan shellfish farms in the Mekong Delta located the southern part of Vietnam, were examined for the presence of Vibrio parahaemolyticus (VpAHPND) caused acute haepatopancreatic necrosic disease (AHPND) in shrimp. VpAHPND strains were isolated in two of 298 (0.7%) molluscan shellfish samples from retail shops, seven of 71 (9.9%) shrimp samples from shrimp ponds, and two of 42 (4.8%) water samples from shrimp ponds. VpAHPND strains were classified into two types of O antigen, including O1 and O3, in which O1 was the predominant. VpAHPND strains isolated showed high resistance rates to colistin (100%), ampicillin (93.8%), and streptomycin (87.5%). These results indicate that VpAHPND is widely prevalent in environment in the Mekong Delta, Vietnam.

scholarly journals Current status of acute hepatopancreatic necrosis disease (AHPND) and result of isolating AHPND-causing strains of farmed shrimp in Mekong Delta Region of Vietnam

2021 ◽  
Vol 20 (02) ◽  
pp. 36-43
Author(s):  
Hieu V. Tran
Keyword(s):  
Mekong Delta ◽  
Early Mortality ◽  
Shrimp Farming ◽  
Disease Spread ◽  
Current Status ◽  
Effective Prevention ◽  
Early Mortality Syndrome ◽  
The World ◽  
Shrimp Industry ◽  
Acute Hepatopancreatic Necrosis Disease

Early mortality syndrome/acute hepatopancreatic necrosis (EMS/AHPND) was first detected in China in 2009. The disease spread rapidly to neighboring countries and emerged in almost major shrimp-producing regions in the world, including Vietnam. The disease has caused serious damage to the global shrimp industry and so far, there is no effective cure. In order to understand the current status of AHPND, and then to introduce effective prevention and detection measures, we collected data and shrimp samples in some provinces in the Mekong Delta to analyze and isolate the pathogenic strains. The results of our study conducted from 2014 - 2018 in four provinces (Ben Tre, Long An, Bac Lieu, Kien Giang) showed that AHPND damaged from 2.0 to 57.2% of the total shrimp farming area. In addition, we isolated 10 AHPND-positive strains via culturing and PCR. The results of representative sequencing of three strains LA1, LA5, and LA8 showed that they were 100% similarity with the previously published strain XN89. These isolated strains are used as a collection for further studies on the origin and mechanism of the disease by whole genome sequencing.

An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1

2020 ◽  
Vol 30 (4) ◽  
pp. 459-466
Author(s):  
Rajiv Gupta ◽  
Sanjith Prahas Krishnam ◽  
Pamela W. Schaefer ◽  
Michael H. Lev ◽  
R. Gilberto Gonzalez
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
East Coast

An East Coast Perspective on Artificial Intelligence and Machine Learning

2020 ◽  
Vol 30 (4) ◽  
pp. 467-478
Author(s):  
Rajiv Gupta ◽  
Sanjith Prahas Krishnam ◽  
Pamela W. Schaefer ◽  
Michael H. Lev ◽  
R. Gilberto Gonzalez
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
East Coast

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

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