Notes

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68 ETB per year. Costs of preventive measures followed by costs of patients' time made the highest contribution while costs of diagnosis made the lowest contribution to the total economic burden of foodborne zoonotic diseases. From a total of 435 respondents, 305 (70.1%) had known the presence of zoonotic diseases. Level of education, number of families in the house and income were highly associated with awareness of zoonosis. Although majority of respondents had known zoonotic diseases exists (70.1%) and disease can be acquired from animal source food (63.2%), the health and economic burden associated to foodborne zoonotic diseases are still high. Therefore, changing mindset and practical training aiming in controlling foodborne zoonotic diseases may be suggested to the community in the health improvement extension service.Leukocyte (white blood cell, WBC) count is an essential factor that physicians use to diagnose infections and provide adequate treatment. Currently, WBC count is determined manually or semi-automatically, which often leads to miscounting. In this paper, we propose an automated method that uses a bioinspired segmentation mimicking the human perception of color. It is based on the claim that a person can locate WBCs in a blood smear image via the high chromatic contrast. First, by applying principal component analysis over RGB, HSV, and L*a*b* spaces, with specific combinations, pixels of leukocytes present high chromatic variance; this results in increased contrast with the average hue of the other blood smear elements. Second, chromaticity is processed as a feature, without separating hue components; this is different to most of the current automation that perform mathematical operations between hue components in an intuitive way. HOIPIN-8 purchase As a result of this systematic method, WBC recognition is computationally efficient, overlapping WBCs are separated, and the final count is more precise. In experiments with the ALL-IDB benchmark, the performance of the proposed segmentation was assessed by comparing the WBC from the processed images with the ground truth. Compared with previous methods, the proposed method achieved similar results in sensitivity and precision and approximately 0.2% higher specificity and 0.3% higher accuracy for pixel classification in the segmentation stage; as well, the counting results are similar to previous works.
To determine response to self-care practice message among patients with diabetes in Jimma University Medical center based on the Extended Parallel Process Model.

A facility-based cross-sectional study was conducted.

Jimma University Medical Center is found in Jimma town.

A total of 343 patients with diabetes participated in the study; making a response rate of 93.9%. All patients with diabetes who were 18 years and above and who were on follow up and registered were included in the study and those with Gestational DM were excluded.

Multivariable logistic regression analysis.

Responsive respondents scored high in self-care practice score as compared to other respondents. educational status, information sources, knowledge, and preferred message appeals were independent predictors of controlling the danger of diabetes.

There is a significant gap in controlling the danger of diabetes. Variables like the level of education, knowledge of diabetes mellitus, information sources, and message appeals were independent predictors of controlling the danger of diabetes. Designing message having higher efficacy while maintaining the level of threat is the best that fits the existing audience's message processing to bring about desired diabetic self-care Practice.
There is a significant gap in controlling the danger of diabetes. Variables like the level of education, knowledge of diabetes mellitus, information sources, and message appeals were independent predictors of controlling the danger of diabetes. Designing message having higher efficacy while maintaining the level of threat is the best that fits the existing audience's message processing to bring about desired diabetic self-care Practice.The coronavirus disease 2019 (COVID-19) pandemic is disturbing and overwhelming a regular medical care in the world. We evaluated the clinical characteristics of patients with primary rhegmatogenous retinal detachment (RRD) during the state of emergency for COVID-19 pandemic in Japan. We also reviewed measures against the COVID-19 pandemic in our institute with a focus on RRD treatment. Retrospectively, patients who underwent initial RRD surgery during the state of emergency between April 7, 2020 and May 25, 2020 were included. For comparison, we recruited patients who underwent surgery for initial RRD during the same period in the last 2 years (2018 and 2019). Data related to the number of surgeries, age, gender, macular detachment, proliferative vitreoretinopathy (PVR), preoperative visual acuity, surgical techniques, the time between the onset and hospitalization and/or surgery of the 2020 cohort were analyzed and compared with those of the 2018 and 2019 cohorts. Furthermore, we reviewed measures taken against COVID-19 in our institute. The number of RRD patients during the state of emergency tended to be lower than that within the last 2 years. Relatively lesser female (vs. male) patients were observed in the 2020 cohort than in the last 2 years (P = 0.084). In contrast, among all cohorts, no significant differences were observed in the incidence of macula-off and PVR, preoperative visual acuity, and the time period between symptom onset and hospitalization and/or surgery. This is the first report to show the clinical patterns of RRD during COVID-19 pandemic in Japan. Despite the state of emergency for the COVID-19 pandemic, no delay in the patient's initial visit to the hospital and surgery was observed. Further studies, including multicenter researches, are important for investigating the influence of COVID-19 on urgent ocular diseases.This study evaluated the efficacy of Cryptocarya spp extracts on biofilm of Candida albicans and its biocompatibility. Mature biofilm of C. albicans was formed on denture base acrylic resin samples and the fungicidal effect of the extracts was evaluated by Alamar Blue® assay, counting colony-forming units (CFU/mL) and confocal laser scanning microscopy (CLSM). Cytotoxicity of extracts from Cryptocarya species was evaluated by AlamarBlue® assay, using normal oral keratinocytes (NOK) cells. In additional, Analysis of plant extracts by ultra-high-performance liquid chromatography-diode array detector-tandem mass spectrometry (UPLC-DAD-MS) was performed. The results showed significant reduction in the cellular metabolism and in the number of CFU/mL of C. albicans (p less then 0.05). The concentration of 0.045 g/mL completely inhibited the number of CFU/mL. Regarding cytotoxicity, all extracts decreased cell viability compared to the control group. CLSM analysis showed predominance of live cells, but with a great difference between the groups. Antimicrobial activity of extracts from Cryptocarya on C. albicans biofilm was confirmed. However, all extracts showed toxicity on NOK cells.Diagnostic tests for hearing impairment not only determines the presence (or absence) of hearing loss, but also evaluates its degree and type, and provides physicians with essential data for future treatment and rehabilitation. Therefore, accurately measuring hearing loss conditions is very important for proper patient understanding and treatment. In current-day practice, to quantify the level of hearing loss, physicians exploit specialized test scores such as the pure-tone audiometry (PTA) thresholds and speech discrimination scores (SDS) as quantitative metrics in examining a patient's auditory function. However, given that these metrics can be easily affected by various human factors, which includes intentional (or accidental) patient intervention, there are needs to cross validate the accuracy of each metric. By understanding a "normal" relationship between the SDS and PTA, physicians can reveal the need for re-testing, additional testing in different dimensions, and also potential malingering cases. For this purpose, in this work, we propose a prediction model for estimating the SDS of a patient by using PTA thresholds via a Random Forest-based machine learning approach to overcome the limitations of the conventional statistical (or even manual) methods. For designing and evaluating the Random Forest-based prediction model, we collected a large-scale dataset from 12,697 subjects, and report a SDS level prediction accuracy of 95.05% and 96.64% for the left and right ears, respectively. We also present comparisons with other widely-used machine learning algorithms (e.g., Support Vector Machine, Multi-layer Perceptron) to show the effectiveness of our proposed Random Forest-based approach. Results obtained from this study provides implications and potential feasibility in providing a practically-applicable screening tool for identifying patient-intended malingering in hearing loss-related tests.Accurately predicting the crown photosynthesis of trees is necessary for better understanding the C circle in terrestrial ecosystem. However, modeling crown for individual tree is still challenging with the complex crown structure and changeable environmental conditions. This study was conducted to explore model in modeling the photosynthesis light response curve of the tree crown of young Larix principis-rupprechtii Mayr. Plantation. The rectangular hyperbolic model (RHM), non-rectangular hyperbolic model (NRHM), exponential model (EM) and modified rectangular hyperbolic model (MRHM) were used to model the photosynthetic light response curves. The fitting accuracy of these models was tested by comparing determinants coefficients (R2), mean square errors (MSE) and Akaike information criterion (AIC). The results showed that the mean value of R2 of MRHM (R2 = 0.9687) was the highest, whereas MSE value (MSE = 0.0748) and AIC value (AIC = -39.21) were the lowest. The order of fitting accuracy of the four models for Pn-PAR response curve was as follows MRHM > EM > NRHM > RHM. In addition, the light saturation point (LSP) obtained by MRHM was slightly lower than the observed values, whereas the maximum net photosynthetic rates (Pmax) modeled by the four models were close to the measured values. Therefore, MRHM was superior to other three models in describing the photosynthetic response curve, the accurate values were that the quantum efficiency (α), maximum net photosynthetic rate (Pmax), light saturation point (LSP), light compensation point (LCP) and respiration rate (Rd) were 0.06, 6.06 μmol·m-2s-1, 802.68 μmol·m-2s-1, 10.76 μmol·m-2s-1 and 0.60 μmol·m-2s-1. Moreover, the photosynthetic response parameters values among different layers were also significant. Our findings have critical implications for parameter calibration of photosynthetic models and thus robust prediction of photosynthetic response in forests.
Domestic violence (DV) is a universal issue and an important public health priority. Establishing a DV Registry System (DVRS) can help to systematically integrate data from several sources and provide valid and reliable information on the scope and severity of harms. The main objective of this study was to develop, validate, and pilot-test a minimum datasheet for a DVRS to register DV victims in medical facilities.

This study was conducted in two main phases. Phase one includes developing the datasheet for registration of DV in the DVRS. In phase two, the datasheet designed in the previous step was used in a pilot implementation of the DVRS for 12 months to find practical challenges. The preliminary datasheet was first developed using information on similar registry programs and guidelines of the World Health Organization (WHO) and then reviewed by four expert panels. Through a two-round Delphi technique, experts evaluated the instrument using the Content Validity Index (CVI) and Content Validity Ratio (CVR).
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