• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.336-341
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• 2014

In order to determine the residual characteristics of pesticides in fruits and their effects on human health, monitoring of pesticide residues were conducted in apples, peaches, pears, grapes and citrus from the major cultivation areas in 2010. Safeties of the pesticides detected from the fruits were evaluated using the amounts of pesticide residue detected and dietary risk index (DRI). Samples were taken from 4-5 major fruit cultivation areas and then pesticide residues in the test fruits were analyzed with a liquid chromatographymass spectrometry (LC-MS/MS). Mean residue levels of the pesticides in fruits were 0.001-0.144 mg/kg. The DRIs were 0.55 for apple, 0.066 for peach, 0.008 for pear, 0.025 for grape, and 0.37 for citrus, respectively. The results indicated that the amounts of pesticide residues in domestic fruits might be safe, considering the regulatory concerning level 1.0.

• Journal of Radiation Protection and Research
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• v.48 no.2
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• pp.84-89
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• 2023

Background: Food consumption is one of the most important routes for radionuclide intake for the public; therefore, there is the need to have a comprehensive understanding of the amount of radioactivity in food products. Consumption of radionuclide-contaminated food could increase potential health risks associated with exposure to radiation such as cancers. The present study aims to determine radioactivity levels in some food products (milk, rice, sugar, and wheat flour) consumed in Mali and to evaluate the radiological effect on the public health from these radionuclides. Materials and Methods: The health impact due to ingestion of radionuclides from these foods was evaluated by the determination of activity concentration of radionuclides ²³⁸U, ²³²Th, ⁴⁰K, and ¹³⁷Cs using gamma spectrometry system with high-purity germanium detector and radiological hazards index in 16 samples collected in some markets, mall, and shops of Bamako-Mali. Results and Discussion: The average activity concentrations were 9.8±0.6 Bq/kg for ²³⁸U, 8.7±0.5 Bq/kg for ²³²Th, 162.9±7.9 Bq/kg for ⁴⁰K, and 0.0035±0.0005 Bq/kg for ¹³⁷Cs. The mean values of radiological hazard parameters such as annual committed effective dose, internal hazard index, and risk assessment from this work were within the dose criteria limits given by international organizations (International Commission on Radiological Protection and United Nations Scientific Committee on the Effects of Atomic Radiation) and national standards. Conclusion: The results show low public exposure to radioactivity and associated radiological impact on public health. Nevertheless, this study stipulates vital data for future research and regulatory authorities in Mali.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.3
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• pp.309-315
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• 2018

Objective: This study aimed to test the expression patterns of ERBB receptor feedback inhibitor 1 (ERRFI1) before and after exercise and the association of non-synonymous single-nucleotide polymorphisms (nsSNPs) of horse ERRFI1 with racing traits in Thoroughbreds. Methods: We performed bioinformatics and gene expression analyses for horse ERRFI1. Transcription factor (TF) binding sites in the 5'-regulatory region of this gene were identified through a tool for prediction of TF-binding site (PROMO). A general linear model was used to detect the association between the nsSNP (LOC42830758 A to G) and race performance. Results: Quantitative polymerase chain reaction analysis showed that expression level of ERRFI1 after exercise was 1.6 times higher than that before exercise. Ten transcription factors were predicted from the ERRFI1 regulatory region. A novel nsSNP (LOC42830758 A to G) was found in ERRFI1, which was associated with three racing traits including average prize money, average racing index, and 3-year-old starts percentile ranking. Conclusion: Our analysis will be helpful as a basis for studying genes and SNPs that affect race performance in racehorses.

• Environmental Analysis Health and Toxicology
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• v.30
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• pp.10.1-10.14
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• 2015

Recent cohort studies have relied on exposure prediction models to estimate individual-level air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.349-360
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• 2020

The study aims to empirically examine the determinants of bank margins from Pakistan, an emerging South Asian economy. To elucidate the importance of the Pakistani banking sector, secondary data has been used, which was extracted from the annual accounts of twenty-four Pakistani scheduled commercial banks (20 conventional, four full-fledged Islamic) over a sample period of 2006 to 2017. The factors identified in the dealership model and the subsequent empirical developments in the dealership model categorized as bank-specific, diversification, regulatory, and industry concentration are analyzed by applying the most-common linear dynamic panel-data estimator, the Generalized Method of Moments (GMM) estimator, developed by Arellano and Bond (1991). The findings reveal that, among the bank-specific variables, funding cost, credit risk, managerial efficiency, market share, and operating cost are significant predictors of bank margins. For diversification variables employed in the study, both variables including net non-interest income and asset diversity are as well significant predictors of bank margins. It is also found that the market concentration variable proxied by the Herfindahl-Hirschman Index (HHI) is significantly predicting bank margins. Subsequently, one of the regulatory variables, the opportunity cost of holding reserves, and one bank-specific variable, the degree of risk aversion, are insignificant in the model.

• Journal of Gastric Cancer
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• v.17 no.4
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• pp.384-393
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• 2017

Purpose: The tumor microenvironment is known to be associated with the metabolic activity of cancer cells and local immune reactions. We hypothesized that glucose metabolism measured by 2-deoxy-2-($^{18}F$)fluoro-D-glucose ($^{18}F-FDG$) positron emission tomography (PET)-computed tomography (CT) ($^{18}F-FDG$ PET-CT) would be associated with local immune responses evaluated according to the presence of tumor infiltrating lymphocytes (TILs). Materials and Methods: We retrospectively reviewed 56 patients who underwent $^{18}F-FDG$ PET-CT prior to gastrectomy. In resected tumor specimens, TIL subsets, including cluster of differentiation (CD) 3, CD4, CD8, Forkhead box P3 (Foxp3), and granzyme B, were subjected to immunohistochemical analysis. The prognostic nutritional index (PNI) was calculated as: ($10{\times}serum$ albumin value)+($0.005{\times}peripheral$ lymphocyte counts). Additionally, the maximum standard uptake value ($SUV_{max}$) was calculated to evaluate the metabolic activity of cancer cells. Results: The $SUV_{max}$ was positively correlated with larger tumor size (R=0.293; P=0.029) and negatively correlated with PNI (R=-0.407; P=0.002). A higher $SUV_{max}$ showed a marginal association with higher CD3 (+) T lymphocyte counts (R=0.227; P=0.092) and a significant association with higher Foxp3 (+) T lymphocyte counts (R=0.431; P=0.009). No other clinicopathological characteristics were associated with $SUV_{max}$ or TILs. Survival analysis, however, indicated that neither $SUV_{max}$ nor Foxp3 held prognostic significance. Conclusions: FDG uptake on PET-CT could be associated with TILs, especially regulatory T cells, in gastric cancer. This finding may suggest that PET-CT could be of use as a non-invasive tool for monitoring the tumor microenvironment in patients with gastric cancer.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.332-338
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• 2021

Civil aviation cybersecurity challenges are global in nature and must be addressed using global best practices and the combined efforts of all stakeholders. This requires the development of comprehensive international strategies and detailed plans for their implementation, with appropriate resources. It is important to build such strategies on a common methodology that can be applied to civil aviation and other interrelated critical infrastructure sectors. The goal of the study was to determine the methodological basis for developing an international civil aviation cybersecurity strategy, taking into account existing experience in strategic planning at the level of international specialized organizations. The research was conducted using general scientific and theoretical research methods: observation, description, formalization, analysis, synthesis, generalization, explanation As a result of the study, it was established the specifics of the approach to formulating strategic goals in civil aviation cybersecurity programs in the documents of intergovernmental and international non-governmental organizations in the aviation sphere, generally based on a comprehensive vision of cybersecurity management. A comparative analysis of strategic priorities, objectives, and planned activities for their implementation revealed common characteristics based on a single methodological sense of cybersecurity as a symbiosis of five components: human capacity, processes, technologies, communications, and its regulatory support. It was found that additional branching and detailing of priority areas in the strategic documents of international civil aviation organizations (by the example of Cybersecurity Strategy and Cybersecurity Action Plan) does not always contribute to compliance with a unified methodological framework. It is argued that to develop an international civil aviation cybersecurity strategy, it is advisable to use the methodological basis of the Cyber Security Index.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.65-81
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• 2015

This study reports a preliminary finding of the types and numbers of graphs being presented in the annual reports of about thirty top listed companies trading publicly in the stock markets of three countries-Thailand (SET), Malaysia (BM), and Singapore (SGX)-that were chosen based on their inclusion in the ASEAN Stars Index under the ASEAN Trading Link project. A total of 6,753 graphs from nineteen sectors were extracted and examined. Banking, real estate, and telecommunications are ranked the three most condense sectors, accounting for 50.2% of the total number of graphs observed. The three most used graphs are the Conservative Bar, Donut graph and Stack Bar. Less than one percent of Infographic type graphs were used. The five most depicted graphed variables are Asset, Revenue, Net profit, Liability, and Dividend. Using rudimentary framework to detect distorted or misleading statistical graphs, the study found 60.6% of the graphs distorted across the three markets, SET, BM, and SGX. BM ranked first in percentages of graphs being distortedly presented (73%). The other two markets, SET and SGX, have about the same proportions, 53.88% and 53.03%, respectively. Likewise, the proportions of Well-designed versus Inappropriate-designed graphs of the latter two markets are a little over one time (SET = 1 : 1.17; SGX = 1 : 1.13), whereas the proportion is almost triple for the BM market (BM = 1 : 2.70). In addition, the trend of distorted graphs found is slightly increasing as the longevity of the ASEAN Stars Index increases. One possible explanation for the relatively equal proportion of inappropriate graphs found is that SET is the smallest market and SGX, though the largest, is the most regulated market. BM, on the other hand, may want to present their financial data in the most attractive manner to prospective investors, thus, regulatory constraints and governance structure are still lenient.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6419-6425
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• 2013

Background: Neoadjuvant chemotherapy (NACT) is a treatment modality whereby chemotherapy is used as the initial treatment of HNSCC in patients presenting with advanced cancer that cannot be treated by other means. It leads to shrinkage of tumours to an operable size without significant compromise to essential oro-facial organs of the patients. The molecular mechanisms behind shrinkage due to NACT is not well elucidated. Materials and Methods: Eleven pairs of primary HNSCCs and adjacent normal epithelium, before and after chemotherapy were screened for cell proliferation and apoptosis. This was followed by immunohistochemical analysis of some cell cycle (LIMD1, RBSP3, CDC25A, CCND1, cMYC, RB, pRB), DNA repair (MLH1, p53) and apoptosis (BAX, BCL2) associated proteins in the same set of samples. Results: Significant decrease in proliferation index and increase in apoptotic index was observed in post-therapy tumors compared to pre-therapy. Increase in the RB/pRB ratio, along with higher expression of RBSP3 and LIMD1 and lower expression of cMYC were observed in post-therapy tumours, while CCND1 and CDC25A remained unchanged. While MLH1 remained unchanged, p53 showed higher expression in post-therapy tumors, indicating inhibition of cell proliferation and induction of apoptosis. Increase in the BAX/BCL2 ratio was observed in post-therapy tumours, indicating up-regulation of apoptosis in response to therapy. Conclusions: Thus, modulation of the G1/S cell cycle regulatory proteins and apoptosis associated proteins might play an important role in tumour shrinkage due to NACT.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.287-295
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• 2017

Since Google's AlphaGo defeated a world champion of Go players in 2016, there have been many interests in the deep learning. In the financial sector, a Robo-Advisor using deep learning gains a significant attention, which builds and manages portfolios of financial instruments for investors.In this paper, we have proposed the a deep learning algorithm geared toward identification and forecast of the KOSPI index direction,and we also have compared the accuracy of the prediction.In an application of forecasting the financial market index direction, we have shown that the Robo-Advisor using deep learning has a significant effect on finance industry. The Robo-Advisor collects a massive data such as earnings statements, news reports and regulatory filings, analyzes those and recommends investors how to view market trends and identify the best time to purchase financial assets. On the other hand, the Robo-Advisor allows businesses to learn more about their customers, develop better marketing strategies, increase sales and decrease costs.