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author:("An, dongguk")
1.  Stress Detection and Classification of Laying Hens by Sound Analysis 
Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.
PMCID: PMC4341110  PMID: 25656176
Laying Hens; Stress Recognition; Sound Analysis; Monitoring System
2.  Changes in the Airborne Bacterial Community in Outdoor Environments following Asian Dust Events 
Microbes and Environments  2014;29(1):82-88.
Bacterial abundance and community compositions have been examined in aeolian dust in order to clarify their possible impacts on public health and ecosystems. The influence of transcontinentally transported bacterial cells on microbial communities in the outdoor environments of downwind areas should be determined because the rapid influx of a large amount of bacterial cells can disturb indigenous microbial ecosystems. In the present study, we analyzed bacteria in air samples (approximately 100 m3 d−1) that were collected on both Asian dust days and non-Asian dust days over 2 years (between November 2010 and July 2012). Changes in bacterial abundance and community composition were investigated based on their 16S rRNA gene amount and sequence diversity. Seasonal monitoring revealed that airborne bacterial abundance was more than 10-fold higher on severe dust days, while moderate dust events did not affect airborne bacterial abundance. A comparison of bacterial community compositions revealed that bacteria in Asian dust did not immediately disturb the airborne microbial community in areas 3,000–5,000 km downwind of dust source regions, even when a large amount of bacterial cells were transported by the atmospheric event. However, microbes in aeolian dust may have a greater impact on indigenous microbial communities in downwind areas near the dust source. Continuous temporal and spatial analyses from dust source regions to downwind regions (e.g., from the Gobi desert to China, Korea, Japan, and North America) will assist in estimating the impact of atmospherically transported bacteria on indigenous microbial ecosystems in downwind areas.
PMCID: PMC4041233  PMID: 24553107
bioaerosol; airborne bacteria; Asian dust; long-range transportation; bacterial community analysis
3.  Automatic Detection and Recognition of Pig Wasting Diseases Using Sound Data in Audio Surveillance Systems 
Sensors (Basel, Switzerland)  2013;13(10):12929-12942.
Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC) from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD) and the Sparse Representation Classifier (SRC) as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used) and accurately (94% detection and 91% classification accuracy), either as a standalone solution or to complement known methods to obtain a more accurate solution.
PMCID: PMC3859042  PMID: 24072029
pig wasting diseases; sound data; mel frequency cepstrum coefficient; support vector data description; sparse representation classifier
4.  Future of microbial polyesters 
Numerous microorganisms accumulate polyesters classified as polyhydroxyalkanoates (PHAs) as carbon and energy storage material when the growth condition is unfavorable in the presence of excess carbon source. Natural PHAs typically consist of various (R)-hydroxycarboxylic acids, and exhibit different material properties depending on the monomer composition. Such diversity comes from different metabolic pathways operating in the cell, and thus generating different monomers. Even more diverse PHAs can be produced by metabolically engineered microorganisms, which leads to the biosynthesis of non-natural polyesters containing lactate as a monomer. In order to make PHAs as useful polymers in our daily life, their production cost should be significantly lowered and material properties should be compatible with those produced by petrochemical industries. Metabolic engineering can address these issues by developing microbial strains capable of producing PHAs of desired material properties with high productivity and yield from inexpensive carbon sources. This commentary aims at peeking into the future of PHAs, focusing on the possible metabolic engineering strategies to be taken to achieve these goals.
PMCID: PMC3680211  PMID: 23714196
Polyester; Polyhydroxyalkanoate; Metabolic engineering
5.  A NAC transcription factor and SNI1 cooperatively suppress basal pathogen resistance in Arabidopsis thaliana 
Nucleic Acids Research  2012;40(18):9182-9192.
Transcriptional repression of pathogen defense-related genes is essential for plant growth and development. Several proteins are known to be involved in the transcriptional regulation of plant defense responses. However, mechanisms by which expression of defense-related genes are regulated by repressor proteins are poorly characterized. Here, we describe the in planta function of CBNAC, a calmodulin-regulated NAC transcriptional repressor in Arabidopsis. A T-DNA insertional mutant (cbnac1) displayed enhanced resistance to a virulent strain of the bacterial pathogen Pseudomonas syringae DC3000 (PstDC3000), whereas resistance was reduced in transgenic CBNAC overexpression lines. The observed changes in disease resistance were correlated with alterations in pathogenesis-related protein 1 (PR1) gene expression. CBNAC bound directly to the PR1 promoter. SNI1 (suppressor of nonexpressor of PR genes1, inducible 1) was identified as a CBNAC-binding protein. Basal resistance to PstDC3000 and derepression of PR1 expression was greater in the cbnac1 sni1 double mutant than in either cbnac1 or sni1 mutants. SNI1 enhanced binding of CBNAC to its cognate PR1 promoter element. CBNAC and SNI1 are hypothesized to work as repressor proteins in the cooperative suppression of plant basal defense.
PMCID: PMC3467076  PMID: 22826500
6.  High Doses of Bone Morphogenetic Protein 2 Induce Structurally Abnormal Bone and Inflammation In Vivo 
Tissue Engineering. Part A  2011;17(9-10):1389-1399.
The major Food and Drug Association–approved osteoinductive factors in wide clinical use are bone morphogenetic proteins (BMPs). Although BMPs can promote robust bone formation, they also induce adverse clinical effects, including cyst-like bone formation and significant soft tissue swelling. In this study, we evaluated multiple BMP2 doses in a rat femoral segmental defect model and in a minimally traumatic rat femoral onlay model to determine its dose-dependent effects. Results of our femoral segmental defect model established a low BMP2 concentration range (5 and 10 μg/mL, total dose 0.375 and 0.75 μg in 75 μg total volume) unable to induce defect fusion, a mid-range BMP2 concentration range able to fuse the defect without adverse effects (30 μg/mL, total dose 2.25 μg in 75 μg total volume), and a high BMP2 concentration range (150, 300, and 600 μg/mL, total dose 11.25, 22.5, and 45 μg in 75 μg total volume) able to fuse the defect, but with formation of cyst-like bony shells filled with histologically confirmed adipose tissue. In addition, compared to control, 4 mg/mL BMP2 also induced significant tissue inflammatory infiltrates and exudates in the femoral onlay model that was accompanied by increased numbers of osteoclast-like cells at 3, 7, and 14 days. Overall, we consistently reproduced BMP2 side effects of cyst-like bone and soft tissue swelling using high BMP2 concentration approaching the typical human 1500 μg/mL.
PMCID: PMC3079169  PMID: 21247344
7.  Current Situation and Issue of Industrial Accident Compensation Insurance 
Journal of Korean Medical Science  2012;27(Suppl):S47-S54.
Industrial Accident Compensation Insurance (IACI) has a history of about 50 yr, and is the oldest social insurance system in Korea. After more than 20 times of revision improvements in benefits, its contents and claim systems have been upgraded. It became the protector of injured workers and their families, and at the same time became the system which could cope with both financial burden of employers and their responsibilities. However, there are some issues to be reformed to upgrade the IACI: 1) the problems in the approval system of occupational diseases, 2) quality improvement of workers' compensation medical care, 3) vocational rehabilitation and return to work, 4) workers' compensation premiums and out-of-pocket money of injured workers, 5) issues in application of IACI. Growth of IACI cannot be achieved by an effort of an individual. Efforts by workers, owners, and government, in addition to physicians and welfare professionals toward the same goal are required for the next level improvement of IACI.
PMCID: PMC3360174  PMID: 22661871
Workers' Compensation; Occupational Disease; Occupational Injury; Medical Care; Return to Work

Results 1-7 (7)