• Korean Journal of Veterinary Service
• /
• v.43 no.2
• /
• pp.107-112
• /
• 2020

Foot-and-mouth disease (FMD) and avian influenza (AI) are highly pathogenic viral disease which affects the livestock industry worldwide. Outbreak of these viruses causes great impact in the livestock industry; thus, disease infected animals were immediately disposed. Burial is the commonly used disposal method for deceased animals. However, there is potential for secondary environmental contamination, as well as the risk that infectious agents persisting in the environment due to the limited environmental controls in livestock burial sites during the decomposition of the carcasses. Therefore, this study aimed to investigate the detection of FMD and AI viruses from animal carcass disposal sites using real-time reverse transcription PCR. Soil samples of more than three years post-burial from livestock carcass disposal sites were collected and processed RNA isolation using a commercial extraction kit. The isolated RNA of the samples was used for the detection of FMDV and AIV using qRT-PCR. Based on the qPCR assay result, no viral particle was detected in the soil samples collected from the animal disposal sites. This indicates that 3 years of burial and their carcass disposal method is efficient for the control or at least reduction of spread infections in the surrounding environment.

• Journal of Veterinary Science
• /
• v.22 no.3
• /
• pp.35.1-35.13
• /
• 2021

Background: African swine fever (ASF) is an infectious viral disease of domestic pigs that presents as a hemorrhagic fever, and for which no effective vaccine is available. The disease has a serious negative social and economic impact on pig keepers. There is limited information on the potential risk factors responsible for the spread of ASF in South Kivu. Objective: The aim of this study was to determine the potential risk factors associated with ASF infection in suspected ASF virus (ASFV)-infected pigs. Methods: We sampled whole blood from 391 pigs. Additionally, 300 pig farmers were interviewed using a structured questionnaire. Viral DNA was detected by using the real-time polymerase chain reaction technique. Results: The majority of pigs sampled, 78% (95% confidence interval [CI], 74.4-82.6), were of local breeds. Over half, 60.4% (95% CI, 55.5-65.2), were female, and most of them, 90.5% (95% CI, 87.6-93.4), were adult pigs (> 1 year old). Viral DNA was detected in 72 of the 391 sampled pigs, indicating an overall infection rate of 18.4% (95% CI, 14.5-22.4). Multivariable logistic regression analysis revealed several risk factors positively associated with ASFV infection: feeding with swill in pen (odds ratio [OR], 3.8; 95% CI, 2.12-6.77); mixed ages of pigs in the same pen (OR, 3.3; 95% CI, 1.99-5.57); introduction of new animals to the farm (OR, 5.4; 95% CI, 1.91-15.28). The risk factors that were negatively (protective) correlated with ASFV positivity were the presence of male animals and the use of an in-pen breeding system. Conclusion: Local pig farmers should be encouraged to adopt proper husbandry and feeding practices in order to increase the number of ASF-free farms.

• The Plant Pathology Journal
• /
• v.35 no.3
• /
• pp.243-256
• /
• 2019

Field surveys for Plum pox virus (PPV) infection were conducted in stone fruit orchards all over Bulgaria. In total, 1168 out of 3020 leaf samples from cultivated Prunus spp. and wildly growing P. cerasifera trees reacted positive for PPV in DASI-ELISA with the universal monoclonal antibody (MAb) 5B. Further ELISA analyses showed that 987 and 127 isolates belonged to PPV-M and PPV-D serotypes, respectively. The plum and P. cerasifera showed 82.0% and 50.5% levels of infection, respectively followed by the peach (40.0%) and the apricot (32.0%). Five hundred fifty one PPV isolates were further typed by IC-RT-PCR with PPV-Rec, -M and -D-specific primers, targeting (Cter)NIb-(Nter) CP genome region, as 125 isolates were sequenced. The results revealed the presence of PPV-Rec, PPV-M and PPV-D and mixed infections of these strains. PPV-Rec was the most prevalent strain (49.0%), followed by PPV-M (40.1%), while PPV-D was the less spread strain (8.2%). PPV-Rec was the most common strain in plums, including the eight "old-aged" trees from the region of the first Sharka discovery. PPV-M was the most prevalent strain in peach and apricot. Phylogenetic analyses on (Cter)NIb-(Nter)CP of the isolates were performed. PPV-Rec isolates formed a homogeneous group, while PPV-M isolates split into PPV-Ma and PPV-Mb subgroups. Five separated clades were formed by the analyzed PPV-D isolates. Nucleotide sequences of the partial CP coding region of the analyzed isolates revealed a slightly higher intra-strain genetic variability in PPV-Rec and PPV-M isolates, while that of PPV-D strain isolates was higher from the reported for these strains.

• ANNALS OF ANIMAL RESOURCE SCIENCES
• /
• v.28 no.2
• /
• pp.78-96
• /
• 2017

Foot-and-mouth disease (FMD) is a infection that can easily spread when it occurs and causes serious economic damage because of the existence of multiple serotypes of the virus and extreme contagiousness. The most effective method in preventing the transmission of FMD virus (FMDV) is the culling of livestock and additional vaccination in the other areas depending on the spreading rate and situation. Diagnostic methods are utilized not only for the definite diagnosis of FMD but also for identification of serotype, and confirmation of antibody production after vaccination. Although many methods have been developed to diagnose, they are not still enough to detect accurately the disease in a short time. Therefore, it has been needed new diagnostic methods improved from existing methods. Previous methods were based on the enzyme-linked immunosorbent assay (ELISA) as a serological diagnostic method, or polymerase chain reaction (PCR), which is a molecular genetic method. The recent technology has been performing about the combination of both methods and how to make it faster, less costly, more sensitive and accurate way.

• International Journal of Computer Science & Network Security
• /
• v.21 no.2
• /
• pp.110-119
• /
• 2021

The Coronavirus or COVID-19 is contagiousness virus that infected almost every single part of the world. This pandemic forced a major country did lockdown and stay at a home policy to reduce virus spread and the number of victims. Interactions between humans and robots form a popular subject of research worldwide. In medical robotics, the primary challenge is to implement natural interactions between robots and human users. Human communication consists of dynamic processes that involve joint attention and attracting each other. Coordinated care involves sharing among agents of behaviours, events, interests, and contexts in the world from time to time. The robotics arm is an expensive and complicated system because robot simulators are widely used instead of for rehabilitation purposes in medicine. Interaction in natural ways is necessary for disabled persons to work with the robot simulator. This article proposes a low-cost rehabilitation system by building an arm gesture tracking system based on a depth camera that can capture and interpret human gestures and use them as interactive commands for a robot simulator to perform specific tasks on the 3D block. The results show that the proposed system can help patients control the rotation and movement of the 3D arm using their hands. The pilot testing with healthy subjects yielded encouraging results. They could synchronize their actions with a 3D robotic arm to perform several repetitive tasks and exerting 19920 J of energy (kg.m².S^-2). The average of consumed energy mentioned before is in medium scale. Therefore, we relate this energy with rehabilitation performance as an initial stage and can be improved further with extra repetitive exercise to speed up the recovery process.

• Particle and aerosol research
• /
• v.18 no.1
• /
• pp.1-8
• /
• 2022

Since 2019, the corona virus has been continuously affect human life. In particular, in the indoor space where people live, infection by airborne transmission of viruses is a problem. Among them, the spread in the subway, which is the main mode of transport for humans, can be serious. To solve this problem, our research team developed an ionic wind collector to collect and remove corona virus using an ionic wind collector and ozone. In order to apply the ionic wind collector to the subway, it must operate in two modes. Because large amounts of ozone are harmful to the human body. There is a mode that collects bio-aerosol from the air using ionic wind and a mode that inactivates viruses floating in the air by generating a large amount of ozone. As the applied voltage increased, the cleaning ability of the ionic wind collector increased, and the farther the distance between the discharge electrode and the ground plate, the higher the cleaning ability even at low current. In addition, clean air delivery rate (CADR) of an ionic wind collector was up to 5.5 m³/min. As a result of measuring the amount of ozone generated, it was confirmed that 50 ppb to 250 ppb was generated, and it was confirmed that ozone generation was controllable in the ionic wind dust collector.

• Korean Journal of Veterinary Service
• /
• v.45 no.4
• /
• pp.285-292
• /
• 2022

Avian influenza viruses (AIVs) cause contagious diseases and have the potential to infect not only birds but also mammals. Wild birds are the natural reservoir of AIVs and spread them worldwide while migrating. Here we collected active AIV surveillance data from wild bird habitats during the 2019 to 2022 winter seasons (from September to March of the following year) in South Korea. We isolated 97 AIVs from a total of 7,590 fecal samples and found the yearly prevalence of AIVs was 0.83, 1.48, and 1.27, respectively. The prevalence of AIVs were generally higher from September to November. These findings demonstrate that a high number of wild birds that carry AIVs migrate into South Korea during the autumn season. The highest virus numbers were isolated from the species Anas platyrhynchos (72%; n=70), followed by Anas poecilorhyncha (15.4%; n=15), suggesting that each is an important host for these pathogens. Twenty-five hemagglutinin-neuraminidase subtypes were isolated, and all AIVs except the H5N8 subtype were found to be low-pathogenic avian influenza viruses (LPAIVs). Active surveillance of AIVs in wild birds could benefit public health because it could help to estimate their risk for introduction into animals and humans. Moreover, considering that 132 cases of human AIV infections have been reported worldwide within the last 5 years, active surveillance of AIVs is necessary to avoid outbreaks.

• Journal of Internet Computing and Services
• /
• v.24 no.4
• /
• pp.107-115
• /
• 2023

This study analyzes the content of YouTube Vlog videos created by patients of Coronavirus disease 2019 ("COVID-19") in South Korea and viewer comments on those videos. As this new infectious disease started to sweep the world in late 2019 and early 2020, the public started facing fear and uncertainty stemming from the lack of sufficient and accurate information about the virus. At the same time, as COVID-19 patients in South Korea were treated in isolation to prevent the spread of the virus, the patients themselves were experiencing anxiety and exclusion from the society. During this period, there was an increase in YouTube Vlog videos created by the patients in which they shared their experiences going through the treatment and recovery processes. To understand how these YouTube Vlog videos were being used by the patients to connect with the society and seek support in a state of isolation and anxiety, this study conducted a qualitative multi-case analysis of three sample YouTube Vlog video channels to analyze their content, as well as a lexicon-based sentiment analysis of viewer comments to understand the experiences and reactions of viewers. The patients' YouTube Vlog videos showed that they shared similar stages of progress, despite each emphasizing a different main theme. Overall, the tone of the viewer comments became increasingly positive over time, although with some variance among different patient cases and stages. The results confirmed that Vlogs of patients played a significant role in reducing the uncertainty around COVID-19 and strengthening social support for the patients. The findings of this study can improve an understanding of the psychological and behavioral aspects of patient experience in isolated treatment and the impact of shared communication among members of society in times of crisis.

• Journal of Korean Society of Rural Planning
• /
• v.21 no.4
• /
• pp.35-43
• /
• 2015

The purpose of the research is to analyze damages of TYLCV (Tomato Yellow Leaf Curl Virus) in the context of climate changes and to find the spatial distribution of the damages and characteristics of regions. A TYLCV is generally known for a plant disease related to temperature. Its occurrence rate increases when temperature rises. This disease first occurred in 2008 and rapidly spread nationwide. Due to the spread of a TYLCV, a number of Tomato farms in Korea were damaged severely. To analyze damages of the pest in the context of climate changes, this research estimated production loss under the current situation and RCP scenarios. Additionally, Hot Spot Analysis, LISA, and Cluster analysis were conducted to find spatial distribution and properties of largely damaged regions under RCP scenarios. The results explained that additional production loss was estimated differently by regions with the same temperature rising scenario. Also, largely damaged regions are spatially clustered and factors causing large damages were different across regional cluster groups. It means that certain regions can be damaged more than others by diseases and pests. Furthermore, pest management policy should reflect the properties of each region such as climate conditions, cultivate environment and production technologies. The findings from this research can be utilized for developing rural management plans and pest protection policies.

• The Journal of Bigdata
• /
• v.5 no.1
• /
• pp.1-9
• /
• 2020

The study was conducted with funding from the government (Ministry of Agriculture, Food and Rural Affairs) in 2018 with support from the Agricultural, Food, and Rural Affairs Agency, 318069-03-HD040, and in based on artificial intelligence-based HPAI spread analysis and patterning. The model that is actively used in time series and text mining recently is LSTM (Long Short-Term Memory Models) model utilizing deep learning model structure. The LSTM model is a model that emerged to resolve the Long-Term Dependency Problem that occurs during the Backpropagation Through Time (BPTT) process of RNN. LSTM models have resolved the problem of forecasting very well using variable sequence data, and are still widely used.In this paper study, we used the data of the Call Detailed Record (CDR) provided by KT to identify the migration path of people who are expected to be closely related to the virus. Introduce the results of predicting the path of movement by learning the LSTM model using the path of the person concerned. The results of this study could be used to predict the route of HPAI propagation and to select routes or areas to focus on quarantine and to reduce HPAI spread.