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Incidence laptop or computer Eye-sight Affliction and Linked Factors among Teachers in Ethiopian Colleges: A Web-Based Cross-Sectional Study.
This paper discusses the behaviour of different thermophysical properties of CuO water-based nanofluids, including the thermal and hydraulic performance and pumping power. Different experimental and theoretical studies that investigated each property of CuO/water in terms of thermal and fluid mechanics are reviewed. Classical theories cannot describe the thermal conductivity and viscosity. The concentration, material, and size of nanoparticles have important roles in the heat transfer coefficient of CuO/water nanofluids. Thermal conductivity increases with large particle size, whereas viscosity increases with small particle size. The Nusselt number depends on the flow rate and volume fraction of nanoparticles. The causes for these behaviour are discussed. The magnitude of heat transfer rate is influenced by the use of CuO/water nanofluids. The use of CuO/water nanofluids has many issues and challenges that need to be classified through additional studies.The needles of conifer trees are one of the richest sources of natural polyprenols. Polyprenol homologs from Abies sibirica L. lipophilic 80% purified extract were analyzed and quantified. In total, 10 peaks (Prenol-11 to Prenol-20) were observed in the ultra-high-performance liquid chromatography-diode array detector (UHPLC-DAD) chromatogram of Siberian fir with the most abundant compound being Prenol-15 (relative amount 37.23 + 0.56% of the total polyprenol yield). Abies sibirica L. polyprenol solubility and incorporation efficiency into liposomes were studied in various commercially available lecithin mixtures (Phosal IP40, Phosal 75SA, and Lipoid P45). The resulting multilamellar polyprenol liposomes were morphologically characterized by Light and Transmission Electron Microscopy, and the liposome size was discovered to be polymodal with the main peak at 1360 nm (90% of the volume). learn more As polyprenols are fully soluble only in lipids, a liposomal formulation based upon co-solubilization and a modified ethanol injection method of polyprenols into the ethanol-phospholipid system was developed for the entrapment and delivery of polyprenols for potential commercial applications in food supplement and cosmetic industries.Plants are able to sense their mechanical environment. This mechanical signal is used by the plant to determine its phenotypic features. This is true also at a smaller scale. Morphogenesis, both at the cell and tissue level, involves mechanical signals that influence specific patterns of gene expression and trigger signaling pathways. How a mechanical stress is perceived and how this signal is transduced into the cell remains a challenging question in the plant community. Among the structural components of plant cells, the plasma membrane has received very little attention. Yet, its position at the interface between the cell wall and the interior of the cell makes it a key factor at the nexus between biochemical and mechanical cues. So far, most of the key players that are described to perceive and maintain mechanical cell status and to respond to a mechanical stress are localized at or close to the plasma membrane. In this review, we will focus on the importance of the plasma membrane in mechano-sensing and try to illustrate how the composition of this dynamic compartment is involved in the regulatory processes of a cell to respond to mechanical stress.Metabolic correlation networks have been used in several instances to obtain a deeper insight into the complexity of plant metabolism as a whole. In tomato (Solanum lycopersicum), metabolites have a major influence on taste and overall fruit quality traits. Previously a broad spectrum of metabolic and phenotypic traits has been described using a Solanum pennellii introgression-lines (ILs) population. To obtain insights into tomato fruit metabolism, we performed metabolic network analysis from existing data, covering a wide range of metabolic traits, including lipophilic and volatile compounds, for the first time. We provide a comprehensive fruit correlation network and show how primary, secondary, lipophilic, and volatile compounds connect to each other and how the individual metabolic classes are linked to yield-related phenotypic traits. Results revealed a high connectivity within and between different classes of lipophilic compounds, as well as between lipophilic and secondary metabolites. We focused on lipid metabolism and generated a gene-expression network with lipophilic metabolites to identify new putative lipid-related genes. Metabolite-transcript correlation analysis revealed key putative genes involved in lipid biosynthesis pathways. The overall results will help to deepen our understanding of tomato metabolism and provide candidate genes for transgenic approaches toward improving nutritional qualities in tomato.Diamond particle-reinforced copper matrix composites (Diamond/Cu) are recognized as promising electronic packaging materials due to their excellent thermophysical properties. It is necessary to investigate the reliability of Diamond/Cu composites under extreme environmental conditions. The corrosion behavior of Diamond/Cu composites was studied in a 5 wt% NaCl neutral salt spray. Surface morphology, thermal conductivity, bending strength, corrosion rate, and corrosion depth resulting from corrosion were researched in this paper. The results showed that the corrosion phenomenon mainly occurs on the copper matrix, and the diamond and interface products do not corrode. The corrosion mechanism of Diamond/Cu composites was micro-galvanic corrosion. The corrosion product formed was Cu2Cl(OH)3. The salt spray environment had a great influence on the composite surface, but the composite properties were not significantly degenerated. link2 After a 168-h test, the bending strength was unaltered and the thermal conductivity of gold-plated composites showed a slight decrease of 1-2%. Surface gold plating can effectively improve the surface state and thermal conductivity of Diamond/Cu composites in a salt spray environment.In order to study the influence of scratch direction on the deformation characteristics and material removal mechanism of optical glass BK7, nanoscratching experiments were conducted on a Nano indenter using Vickers indenter. Results indicate that the face-forward scratch is more likely to induce the initiation and propagation of lateral cracks, which is found to be more beneficial to material removal processes; in contrast, small chips and debris are released from the machined grooves without introducing lateral cracks in the edge-forward condition, leading to poor material removal efficiency. In addition, the choice of scratch direction can make differences to the elastic recovery rate of optical glass BK7. The results revealed that both the elastic recovery rate and the residual stresses of the material under the face-forward scratching are greater than those of the edge-forward scratching. A theoretical model for coefficient of friction (COF) under different scratch directions was established. It is found that the COF between indenter and workpiece in the edge-forward scratching is larger than the face-forward scratching under otherwise identical conditions, this finding is consistent with experimental results. A stress field analysis using finite element method (FEM) was conducted to understand the different crack initiation and propagation behaviors from different scratch directions. The current study discusses the significance of scratch direction on material removal behavior of optical glass BK7, and the results would encourage further research on investigating the connections between tool geometry and material removal mechanism.A series of carbon nanotubes doped with Fe and/or Cu, Fe100‒xCux/CNT (x = 0, 25, 50, 75 and 100) has been prepared by an easy method of wetness impregnation of commercial multiwalled carbon nanotubes previously oxidized with nitric acid. The wide characterization of the solids by different techniques demonstrates that the incorporation of Fe and Cu to the CNTs has been successfully produced. Fe100-xCux/CNT samples were tested as catalysts in the removal of paracetamol from aqueous solution by a combined process of adsorption and Fenton-like oxidation. Under mild conditions, 25 °C and natural pH of solution, i.e., nearly neutral, values of oxidation of paracetamol between 90.2% and 98.3% were achieved after 5 h of reaction in most of cases. link3 Furthermore, with the samples containing higher amounts of copper, i.e., Cu100/CNT and Fe25Cu75/CNT, only 2 h were necessary to produce depletion values of 73.2% and 87.8%, respectively. The influence of pH and dosage of H2O2 on the performance has also been studied. A synergic effect between both Cu+/Cu2+ and Fe2+/Fe3+ in Fenton-like reaction was observed. These results demonstrate that Fe100-xCux/CNT are powerful Fenton-like catalyst for degradation of paracetamol from aqueous solution and they could be extended to the removal of other organic pollutants.In the absence of accurate medical records, it is critical to correctly classify implant fixture systems using periapical radiographs to provide accurate diagnoses and treatments to patients or to respond to complications. The purpose of this study was to evaluate whether deep neural networks can identify four different types of implants on intraoral radiographs. In this study, images of 801 patients who underwent periapical radiographs between 2005 and 2019 at Yonsei University Dental Hospital were used. Images containing the following four types of implants were selected Brånemark Mk TiUnite, Dentium Implantium, Straumann Bone Level, and Straumann Tissue Level. SqueezeNet, GoogLeNet, ResNet-18, MobileNet-v2, and ResNet-50 were tested to determine the optimal pre-trained network architecture. The accuracy, precision, recall, and F1 score were calculated for each network using a confusion matrix. All five models showed a test accuracy exceeding 90%. SqueezeNet and MobileNet-v2, which are small networks with less than four million parameters, showed an accuracy of approximately 96% and 97%, respectively. The results of this study confirmed that convolutional neural networks can classify the four implant fixtures with high accuracy even with a relatively small network and a small number of images. This may solve the inconveniences associated with unnecessary treatments and medical expenses caused by lack of knowledge about the exact type of implant.Use of thermoplastic material in orthodontics, either as aligner or as retainer appliances, is common practice and is likely to increase in the years to come. However, no systematic assessment on safety considerations of these adjuncts has been implemented up to date. The aim of this systematic review was to collectively appraise the existing evidence from both clinical and laboratory studies, on whether these appliances are associated with any estrogenic/cytotoxic effects or bisphenol-A (BPA) and monomer leaching. Eight electronic databases were searched with no limits in December 22, 2019, for published and unpublished research. Eligibility criteria comprised of studies of any design, describing use of any type of thermoplastic aligner. Study selection, data extraction and risk of bias (RoB) assessment was done independently, either in duplicate or confirmed by a second reviewer. Random effects meta-analyses of weighted mean differences (WMD) with associated 95% Confidence Intervals (CIs) were planned. Quality of the evidence was evaluated with Grading of Recommendations Assessment, Development and Evaluation (GRADE).
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