Knowledge, attitudes and practices of barbers about hepatitis B and C transmission in Hyderabad, Pakistan.

Hepatitis B and C virus (HBV/HCV) infections are serious global health problems. Shaving by barbers has been identified as the key risk factor for spread of HBV. We conducted a cross-sectional survey of barbers in Hyderabad city, Pakistan in 2007 to establish their knowledge and attitudes to the risk of HBV and HCV transmission and their working patterns. Observations showed that 96.2% washed razors with antiseptic after each client and 95.7% used a new blade with new clients. However, knowledge about the diseases and modes of transmission were poor and only 36.6% knew that hepatitis can be transmitted via shaving instruments. Only 3.2% of 186 barbers were vaccinated against HBV. Strategies are needed for raising awareness and regulations of barbers\u27 practices

Enhancing the renewable energy payback period of a photovoltaic power generation system by water flow cooling

A photovoltaic system which enjoys water flow cooling to enhance the performance is considered, and the impact of water flow rate variation on energy payback period is investigated. The investigation is done by developing a mathematical model to describe the heat transfer and fluid flow. A poly crystalline PV module with the nominal capacity of 150 W that is located in city Tehran, Iran, is chosen as the case study. The results show that by increasing water flow rate, EPBP declines first linearly, from the inlet water flow rate of 0 to 0.015 kg.s-1, and then, EPBP approaches a constant value. When there is no water flow cooling, EPBP is 8.88, while by applying the water flow rate of 0.015 kg.s-1, EPBP reaches 6.26 years. However, only 0.28 further years decrement in EPBP is observed when the inlet water mass flow rate becomes 0.015 kg.s-1. Consequently, an optimum limit for the inlet water mass flow rate could be defined, which is the point the linear trend turns into approaching a constant value. For this case, as indicated, this value is 0.015 kg.s-1

Modification of cellulose ether with organic carbonate for enhanced thermal and rheological properties: Characterization and analysis

Reduction in viscosity at higher temperatures is the main limitation of utilizing cellulose ethers in high thermal reservoir conditions for petroleum industry applications. In this study, cellulose ether (hydroxyethyl methyl cellulose (HEMC)) is modified using organic carbonates, i.e., propylene carbonate (PC) and diethyl carbonate (DEC), to overcome the limitation of reduced viscosity at high temperatures. The polymer composites were characterized through various analytical techniques, including Fourier-transform infrared (FTIR), H-NMR, X-ray diffraction (XRD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), -potential measurement, molecular weight determination, and rheology measurements. The experimental results of structural and morphological characterization confirm the modification and formation of a new organic carbonate-based cellulose ether. The thermal analysis revealed that the modified composites have greater stability, as the modified samples demonstrated higher vaporization and decomposition temperatures. -potential measurement indicates higher stability of DEC- and PC-modified composites. The relative viscometry measurement revealed that the modification increased the molecular weight of PC- and DEC-containing polymers, up to 93,000 and 99,000 g/moL, respectively. Moreover, the modified composites exhibited higher levels of stability, shear strength and thermal resistance as confirmed by viscosity measurement through rheology determination. The observed increase in viscosity is likely due to the enhanced inter- and intramolecular interaction and higher molecular weight of modified composites. The organic carbonate performed as a transesterification agent that improves the overall properties of cellulose ether (HEMC) at elevated temperatures as concluded from this study. The modification approach in this study will open the doors to new applications and will be beneficial for substantial development in the petroleum industry

Effects of lipoproteins on cyclo-oxygenase and lipoxygenase pathways in human platelets

The products of arachidonic acid (AA) metabolism in platelets play an important role in platelet shape change, adhesion and aggregation which may participate in the pathogenesis of ischemic heart disease and thrombosis. Since lipoproteins are also involved in the pathogenesis of thrombo-embolic disorders, the effect of human lipoproteins (HDL, LDL, VLDL) on AA metabolism in human platelets was investigated. Lipoproteins were separated by density gradient zonal ultracentrifugation. The effects of lipoproteins on production of AA metabolites in human platelets i.e., thromboxane A2 (TXA2) and hydroxy-eicosatetraenoic acids (HETEs) were examined using radiometric thin layer chromatography coupled with automated data integrator system. In human platelets, HDL inhibited 12-HETE and TXA2 formation in a concentration-dependent manner. LDL had a strong inhibitory effect on TXA2 production and a weak inhibitory effect on 12-HETE production. VLDL had no effect on platelet AA metabolism. These findings point to a new facet of lipoproteins action and suggest that lipoproteins may have a physiological role in the regulation of AA metabolism in platelets

Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic Conditions

Preparation of high-quality datasets for the urban scene understanding is a labor-intensive task, especially, for datasets designed for the autonomous driving applications. The application of the coarse ground truth (GT) annotations of these datasets without detriment to the accuracy of semantic image segmentation (by the mean intersection over union - mIoU) could simplify and speedup the dataset preparation and model fine tuning before its practical application. Here the results of the comparative analysis for semantic segmentation accuracy obtained by PSPNet deep learning architecture are presented for fine and coarse annotated images from Cityscapes dataset. Two scenarios were investigated: scenario 1 - the fine GT images for training and prediction, and scenario 2 - the fine GT images for training and the coarse GT images for prediction. The obtained results demonstrated that for the most important classes the mean accuracy values of semantic image segmentation for coarse GT annotations are higher than for the fine GT ones, and the standard deviation values are vice versa. It means that for some applications some unimportant classes can be excluded and the model can be tuned further for some classes and specific regions on the coarse GT dataset without loss of the accuracy even. Moreover, this opens the perspectives to use deep neural networks for the preparation of such coarse GT datasets.Comment: 10 pages, 6 figures, 2 tables, The Second International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2019) 26-27 January 2019, Kiev, Ukrain