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Li McCain posted an update 6 months, 3 weeks ago
KSHV seropositivity varied in the different populations. In children aged 5 years, EMaBS had the lowest prevalence of 15% followed by GPC at 35% and LaVIISWA at 54%. In adult women, seropositivity varied from 69% (EMaBS) to 80% (LaVIISWA) to 87% (GPC) to 90% (GHWP). The reasons for the variation in prevalence are unclear but may reflect differences in the prevalence of cofactors between these four geographically proximate populations.Blood centers in large hospitals in China are facing serious problems, including complex patient queues and inflexible nursing schedules. This study is aimed at developing a flexible scheduling method for blood center nurses. By systematically analyzing the constraints that affect scheduling, a flexible scheduling model is established based on queuing theory and mixed integer programming. This combined model can reasonably determine the number of nurses required during a given working period and flexibly arrange nursing schedules while ensuring sufficient rest periods for individual nurses. Results of numerical studies conducted using data from a large hospital in China show a significant improvement in patient waiting time performance metrics over the hospital’s current practice. In addition, the nurses’ workloads and rest periods are well balanced, indicating that the proposed method can effectively and flexibly arrange nursing shifts in blood centers.In sub-Saharan Africa, 72% of pregnant women received an antenatal care visit at least once in their pregnancy period. Ethiopia has one of the highest rates of maternal mortality in sub-Saharan African countries. So, this high maternal mortality levels remain a major public health problem. According to EDHS, 2016, the antenatal care (ANC), delivery care (DC), and postnatal care (PNC) were 62%, 73%, and 13%, respectively, indicating that ANC is in a low level. The main objective of this study was to examine the factors that affect the utilization of antenatal care services in Ethiopia using Bayesian multilevel logistic regression models. The data used for this study comes from the 2016 Ethiopian Demographic and Health Survey which was conducted by the Central Statistical Agency (CSA). The statistical method of data analysis used for this study is the Bayesian multilevel binary logistic regression model in general and the Bayesian multilevel logistic regression for the random coefficient model in particular. The convergences of parameters are estimated by using Markov chain Monte-Carlo (MCMC) using SPSS and MLwiN software. The descriptive result revealed that out of the 7171 women who are supposed to use ANC services, 2479 (34.6%) women were not receiving ANC services, while 4692 (65.4%) women were receiving ANC services. Moreover, women in the Somali and Afar regions are the least users of ANC. Using the Bayesian multilevel binary logistic regression of random coefficient model factors, place of residence, religion, educational attainment of women, husband educational level, employment status of husband, beat, household wealth index, and birth order were found to be the significant factors for usage of ANC. Regional variation in the usage of ANC was significant.Brain tumors are one of the most deadly diseases with a high mortality rate. The shape and size of the tumor are random during the growth process. Brain tumor segmentation is a brain tumor assisted diagnosis technology that separates different brain tumor structures such as edema and active and tumor necrosis tissues from normal brain tissue. Magnetic resonance imaging (MRI) technology has the advantages of no radiation impact on the human body, good imaging effect on structural tissues, and an ability to realize tomographic imaging of any orientation. read more Therefore, doctors often use MRI brain tumor images to analyze and process brain tumors. In these images, the tumor structure is only characterized by grayscale changes, and the developed images obtained by different equipment and different conditions may also be different. This makes it difficult for traditional image segmentation methods to deal well with the segmentation of brain tumor images. Considering that the traditional single-mode MRI brain tumor images contain incomplete brain tumor information, it is difficult to segment the single-mode brain tumor images to meet clinical needs. In this paper, a sparse subspace clustering (SSC) algorithm is introduced to process the diagnosis of multimodal MRI brain tumor images. In the absence of added noise, the proposed algorithm has better advantages than traditional methods. Compared with the top 15 in the Brats 2015 competition, the accuracy is not much different, being basically stable between 10 and 15. In order to verify the noise resistance of the proposed algorithm, this paper adds 5%, 10%, 15%, and 20% Gaussian noise to the test image. Experimental results show that the proposed algorithm has better noise immunity than a comparable algorithm.
In 2005, researchers from the French National Research Institute for Agriculture, Food and Environment (Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, INRAE) started a collaboration with the French farmers’ seed network Réseau Semences Paysannes (RSP) on bread wheat participatory breeding (PPB). The aims were (1) to study on-farm management of crop diversity, (2) to develop population-varieties adapted to organic and low-inputs agriculture, (3) to co-develop tools and methods adapted to on-farm experiments. In this project, researchers and farmers’ organizations needed to map the history and life cycle of the population-varieties using network formalism to represent relationships between seed lots. All this information had to be centralized and stored in a database.
We describe here SHiNeMaS (Seeds History and Network Management System) a web tool database. SHiNeMaS aims to provide useful interfaces to track seed lot history and related data (phenotyping, environmenttheir own information in the system.
Male C57BL/6J mice were used to establish AECOPD model by cigarette smoke and bacterial exposure. Mice were randomly divided into normal control (NC), AECOPD, XQLD, Compound C (Com C), Com C + XQLD, and Clarithromycin (CLA) groups. After treatment, the pulmonary function was evaluated by whole-body plethysmograph. The lung histopathology was observed by HE staining. The serum levels of IL-6, TNF-
, and COX-2 were detected by ELISA assay. The apoptotic index was measured by TUNEL assay, and the protein expressions of Bax, Bcl-2, Caspase-3, GRP78, and CHOP in the lung tissues were measured by western blot assay.
XQLD treatment can improve pulmonary function (PF), ameliorate lung injury, and suppress inflammation and apoptosis of lung tissues. In addition, XQLD also markedly attenuated endoplasmic reticulum stress (ERS) and activated AMPK/mTOR pathway in the lung tissues of mice with AECOPD. However, the AMPK inhibitor Compound C decreased the protective effect of XQLD in AECOPD mice.
These findings suggested that XQLD has protective effect against inflammation and apoptosis in AECOPD mice by attenuating ER stress via AMPK/mTOR pathway.