• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.125-134
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• 2024

The novel coronavirus 2019 is called COVID-19 has outspread swiftly worldwide. An early diagnosis is more important to control its quick spread. Medical imaging mechanics, chest calculated tomography or chest X-ray, are playing a vital character in the identification and testing of COVID-19 in this present epidemic. Chest X-ray is cost effective method for Covid-19 detection however the manual process of x-ray analysis is time consuming given that the number of infected individuals keep growing rapidly. For this reason, it is very important to develop an automated COVID-19 detection process to control this pandemic. In this study, we address the task of automatic detection of Covid-19 by using a popular deep learning model namely the VGG19 model. We used 1300 healthy and 1300 confirmed COVID-19 chest X-ray images in this experiment. We performed three experiments by freezing different blocks and layers of VGG19 and finally, we used a machine learning classifier SVM for detecting COVID-19. In every experiment, we used a five-fold cross-validation method to train and validated the model and finally achieved 98.1% overall classification accuracy. Experimental results show that our proposed method using the deep learning-based VGG19 model can be used as a tool to aid radiologists and play a crucial role in the timely diagnosis of Covid-19.

• Animal Bioscience
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• v.37 no.4_spc
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• pp.786-793
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• 2024

Latin America is a culturally, geographically, politically, and economically diverse region. Agriculture in Latin America is marked by a remarkable diversity of production systems, reflecting various agroecological zones, farm sizes, and technological levels. In the last decade, the swine industry increased by 30.6%, emerging as a great contributor to food security and economic development in Latin America. Brazil and Mexico dominate the pig production landscape, together accounting for 70% of sow inventory in the region. The swine industry in Latin America is predominantly comprised of small and medium-sized farms, however, in the past 30 years, the number of pig producers in Brazil dropped by 78%, whereas pork production increased by 326%. Similar to the global pork industry, the growing demand for pork, driven by population growth and changing dietary habits, presents an opportunity for the industry with an expected growth of 16% over the next decade. The export prospects are promising, however subject to potential disruptions from global market conditions and shifts in trade policies. Among the challenges faced by the swine industry, disease outbreaks, particularly African Swine Fever (ASF), present significant threats, necessitating enhanced biosecurity and surveillance systems. In 2023, ASF was reported to the Dominican Republic and Haiti, Porcine Reproductive and Respiratory Syndrome (PRRS) in Mexico, Costa Rica, the Dominican Republic, Colombia, and Venezuela, and Porcine Epidemic Diarrhea (PED) in Mexico, Peru, the Dominican Republic, Colombia, and Ecuador. Additionally, feed costs, supply chain disruptions, and energy expenses have affected mainly the smaller and less efficient producers. The swine industry is also transitioning towards more sustainable and environmentally friendly practices, including efficient feed usage, and precision farming. Ensuring long-term success in the swine industry in Latin America requires a holistic approach that prioritizes sustainability, animal welfare, and consumer preferences, ultimately positioning the industry to thrive in the evolving global market.

• Research in Plant Disease
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• v.30 no.1
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• pp.34-49
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• 2024

The development of sustainable smut management techniques requires an understanding of the impacts of smut on sugarcane growth and the relationships between smut intensity and meteorological variables, varieties, and crop types. Thus, assessments were made with the objectives to 1) determine the effect of smut on the above-ground growth of sugarcane, and 2) quantify the association of smut with weather variables, varieties and crop types. The effect of smut on above-ground growth was assessed in six fields planted with NCo 334 (wider coverage) having 6 months of age in Fincha and Metehara fields in 2021. Data on above-ground growth were taken from 20 randomly selected smut-affected and healthy stools from each field. Besides, 6 years' data (2015 to 2021) on the numbers of smut-affected stools and smut whips of 79 fields were collected. Furthermore, 10 years' (2011 to 2021) weather data were acquired from the sugar plantations. The results demonstrated reduction in the above-ground growth of sugarcane in the range of 18.39% and 73.42% due to smut. In addition, weather variables explained about 68.48% and 66.58% of the variability in the number of smut-affected stools and whips respectively. Smut intensity increased with crop types for susceptible varieties. The tight association between the smut epidemic and crop types, varieties, and weather, implied that these parameters must be carefully considered in management decisions. Continuous monitoring of smut disease, meteorological variables, varieties, and crop types in all the sugarcane plantations could be done as a part of integrated smut management in the future.

• Smart Media Journal
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• v.13 no.4
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• pp.48-56
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• 2024

In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.

• IMMUNE NETWORK
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• v.21 no.1
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• pp.11.1-11.10
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• 2021

Coronavirus causes an infectious disease in various species and crosses the species barriers leading to the outbreak of zoonotic diseases. Due to the respiratory diseases are mainly caused in humans and viruses are replicated and excreted through the respiratory tract, the nasal fluid and sputum are mainly used for diagnosis. Early diagnosis of coronavirus plays an important role in preventing its spread and is essential for quarantine policies. For rapid decision and prompt triage of infected host, the immunochromatographic assay (ICA) has been widely used for point of care testing. However, when the ICA is applied to an expectorated sputum in which antigens are present, the viscosity of sputum interferes with the migration of the antigens on the test strip. To overcome this limitation, it is necessary to use a mucolytic agent without affecting the antigens. In this study, we combined known mucolytic agents to lower the viscosity of sputum and applied that to alpha and beta coronavirus, porcine epidemic diarrhea virus (PEDV) and Middle East respiratory syndrome coronavirus (MERS-CoV), respectively, spiked in sputum to find optimal pretreatment conditions. The pretreatment method using tris(2-carboxyethyl)phosphine (TCEP) and BSA was suitable for ICA diagnosis of sputum samples spiked with PEDV and MERS-CoV. This sensitive assay for the detection of coronavirus in sputum provides an useful information for the diagnosis of pathogen in low respiratory tract.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1478-1499
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• 2024

Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. COVID-19 become an active epidemic disease due to its spread around the globe. The main causes of the spread are through interaction and transmission of the droplets through coughing and sneezing. The spread can be minimized by isolating the susceptible patients. However, it necessitates remote monitoring to check the breathing issues of the patient remotely to minimize the interactions for spread minimization. Thus, in this article, we offer a wearable-IoTs-centered framework for remote monitoring and recognition of the breathing pattern and abnormal breath detection for timely providing the proper oxygen level required. We propose wearable sensors accelerometer and gyroscope-based breathing time-series data acquisition, temporal features extraction, and machine learning algorithms for pattern detection and abnormality identification. The sensors provide the data through Bluetooth and receive it at the server for further processing and recognition. We collect the six breathing patterns from the twenty subjects and each pattern is recorded for about five minutes. We match prediction accuracies of all machine learning models under study (i.e. Random forest, Gradient boosting tree, Decision tree, and K-nearest neighbor. Our results show that normal breathing and Bradypnea are the most correctly recognized breathing patterns. However, in some cases, algorithm recognizes kussmaul well also. Collectively, the classification outcomes of Random Forest and Gradient Boost Trees are better than the other two algorithms.

• Journal of Life Science
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• v.30 no.3
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• pp.313-319
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• 2020

Recently, cattle epidemic diseases are caused by a pathogen such as a virus or bacterium. Such diseases can spread through various pathways, such as feed intake, respiration, and contact between livestock. Diagnosis based on the ELISA (Enzyme-linked immunosorbent assay) and PCR (Polymerase chain reaction) methods has limitations because these traditional diagnostic methods are time consuming assays that require multiple steps and dedicated equipment. In this review, we propose the use of the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) Cas system based on DNA and RNA levels for early point-of-care diagnosis in cattle. In the CRISPR/Cas system, Cas effectors are classified into two classes and six subtypes. The Cas effectors included in class 2 are typically Cas9 in type II, Cas12 in type V (Cas12a and Cas12b) and Cas13 in type VI (Cas13a and Cas13b). The CRISPR/Cas system uses reporter molecules that are attached to the ssDNA strands. When the Cas enzyme cuts the ssDNA, these reporters either fluoresce or change color, indicating the presence of a specific disease marker. There are several steps in the development of a CRISPR/Cas system. The first is to select the Cas enzyme depending on DNA or RNA from pathogens (viruses or bacteria). Based on that, the next step is to integrate the optimal amplification, transducing method, and signal reporter. The CRISPR/Cas system is a powerful diagnostic tool using a gene-editing method, which is faster, better, and cheaper than traditional methods. This system could be used for early diagnosis of epidemic cattle diseases and help to control their spread.

• Pediatric Infection and Vaccine
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• v.4 no.1
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• pp.126-132
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• 1997

Measles outbreak in the world was decreased since measles vaccine had been introduced. Although vaccination rate is high, measles was not eradicated and measles reappeared among vaccinated children. We measured measles-specific antibody from the vaccinated and unvaccinated groups who had experienced apparent measles in the Seongnam city in 1993. The results were as follows. 1) The data included total 126 children (M:F=1 : 1). Age distribution of measles outbreak revealed 6 children in 5yr, 11 in 6yr, 20 in 7yr, 39 in 8yr, 22 in 9yr, 11 in 10yr, 11 in 11yr, and 6 in 12yr. 2) MMR vaccination rate was 78.6%(99/126) in the children who had experienced measles. Positive rate of measles-specific IgM Ab was 80.8% (80/99) among the vaccinated group and among 9E.6.% (25/27) the unvaccinated. 3) Positive rate of measles-specific IgG Ab was 90.9% (90/99) among MMR-vaccinated group, and 85.2% (23/27) in unvaccinated group. In conclusion, measles-specific IgM antibody have been detected more than 1 month in most patients. The relatively high proportion of measles-specific IgM positivity may mean primary vaccine failure. To booster the antibody titers and to prevent measles epidemic in school-aged children, revaccination of measles should be considered.

• Journal of Preventive Medicine and Public Health
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• v.22 no.2 s.26
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• pp.290-301
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• 1989

This is preliminary report on anthrax epidemic occurred in an island with about 100 residents. Since 1982 there had been sudden deaths among all kinds of domestic animals including cattle, dogs, ducks, chicken and goat but only a few among cats in an isolated island about three hours distance away by ferry boat from Mokpo city. From 1986 through 1988 nine human deaths and four patients occurred, which made the government intervene for investigation on June 25 1988. The epidemiological investigation consisted of interview survey and medical examination, medical record analysis, laboratory work to isolate the pathogens under the direction of hypothesis derived from the study and further confirmation of the pathogens by international institute. The summarized results are as followings: 1. According to the interview survey there were many deaths among domestic animals usually in cold and dry season such as January through March and September through November; 36 heads of cattle leaving one head, more than 40 hogs(all), hundreds of chicken leaving few alive, goats that had taken home from mountain and two or three cats out of around 40 had sudden deaths from 1982 till 1985, when the residents stopped to purchase and take them into the island anymore. Also there were eleven persons who had experienced the similar syndrome complex to those of admitted and expired patients and four of them revealed typical chest X-ray findings; from one of these four patients(Rho) B. anthracis is isolated. 2. Medical record on patients who had been admitted, showed common characteristics of the disease course. On admission they had either gastrointestinal or upper respiratory infection symptoms which invariably progressed to septicemic nature with pulmonary interstitial infiltration and mediastinal widening/bulging, and then to deadly acute respiratory distress syndrome. At the end stage chest X-ray revealed multiple bullous emphysema. One of another characteristics was oral ulceration with bleeding occurred in about 50% of the patients. Laboratory test results in common were leukocytosis with left shift and abnormal liver and kidney functions, particularly at the later stage of the illness. 3. Epidemiological characteristics was striking in that both mortality and incidence rates were high: the mortality rate was 8.7% average, male being three times higher than females but there was no distictive clustering by age group. The incidence rate for both sexes was 28.2% and there was no sex difference although a tendency of higher incidence among older ages was noticed. The highest mortality and incidence were observed in Won village where the first death of animal occurred and with the highest frequency among three villages of the island. 4. Among twelve bacilli species isolated from various specimens, two strains, one from patient and the other from soil where the recently died cow is hurried, were confirmed as B. anthracis by Pasteur Institute and CDC of USA(strain from soil). CDC reported that the strain did not produce capsule in bicarbonate media but reacted with the bacteriophage and one of five sera taken from the patients. Mode of transmission as well as incubation period of the agent has not been established yet, which needs further investigation in relation to the antigenic structure of the variant when it is confirmed.

• Clinical and Experimental Pediatrics
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• v.45 no.8
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• pp.980-986
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• 2002

Purpose : Although the number of patients with measles have dramatically decreased since the introduction of measles vaccines in 1965, measles outbreaks have occurred periodically every 4-6 years during the 1990s(1989-1990 and 1993-1994). During 2000-2001, measles prevailed all over the country again. A characteristic of current epidemics is that the majority of affected population was infants and school-aged children. This study was designed to analyze the epidemic and clinical features of measles prevalence during 2000-2001 and to find ways to overcome vaccination failure. Methods : We reviewed the records of 59 patients with mealses admitted in the Pediatric Department of Pusan National University Hospital from January 2000 to October 2001 for patient's age, month of admission, history of vaccination, clinical features and complications. Antibody titers of measles-specific IgM and IgG were measured by enzyme immunoassay. Results : The epidemic show two peaks in the age distribution. Forty three patients(72.9%) were under 2-years of age and 14 patients(23.7%) were over 5-years of age. Outbreaks had high incidence in July to August, 2000 and March to April, 2001, then faded away after July, 2001. Vaccinated group comprised 30.5% and unvaccinated group comprised 69.5% and their mean age was $9.25{\pm}4.27$ years old and $0.95{\pm}0.30$ years old respectively. Positive rate of IgM was 86.7% in vaccinated group and 90.3% in unvaccinated group. This means there was primary vaccine failure; 13 cases of 15 vaccinated patients were positive in IgM antibody. During the prevalence, two patients died with mealses complication. One of them was immunocompromised. Conclusion : To prevent another prevalence of measles in the future, we must enhance revaccination at ages 4-6 and check vaccination status when children enter elementary school. These will produce over 95% of herd immunity, with catch-up MMR vaccination which has been completed already.