Arthuroh4534

A novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is causing the worldwide coronavirus disease 2019 (COVID-19) outbreak with high mortality. A unique finding among COVID-19 patients was a decline of eosinophil levels (eosinopenia). However, results from previous studies on the relationship between eosinopenia and disease severity were inconsistent. The objective of this study is to determine the relationship between eosinopenia and COVID-19 mortality as well as the clinical conditions that could potentially lead to mortality.

One hundred ninety patients diagnosed as moderate, severe, or critical COVID-19 at hospital admission were enrolled. PRT4165 price Data collected from patients' medical records on the second day after hospital admission included medical histories, clinical symptoms, chest images of computed tomography (CT), laboratory examinations, and outcomes.

Eosinophil levels were significantly lower in patients with critical disease, when compared to those with moderate and disorder and those of tissue damage in kidney, liver, and other tissues.The aim of the study was to explore emotional and cognitive aspects of subjective wellbeing and flow in music and sports students during the lockdown imposed by the COVID-19 pandemic. Participants (314 higher education sports and music students) answered questions about measure of flow, satisfaction with life, satisfaction with studying, positive and negative affect, and COVID-19 impact. The results revealed differences in eight flow dimensions and a global flow score in favor of sports students. Differences were also found in affect sports students experienced more positive affect and less negative affect than musicians. However, there were no significant differences with regard to satisfaction with life or satisfaction with study, and music and sports students perceived the COVID-19 impact equally. Gender differences were found for three flow dimensions and the global flow score (female students experienced flow less frequently than males) and satisfaction with studying (higher scores for female students). However, no gender differences were detected for satisfaction with life, positive and negative affect, or COVID-19 impact. The results of regression analyses showed that satisfaction with life and studying, positive and negative affect, and COVID-19 impact could all be predicted on the basis of flow dimensions.Coronavirus disease (Covid-19) has been spreading all over the world and its diagnosis is attracting more research every moment. It is need of the hour to develop automated methods, which could detect this disease at its early stage, in a non-invasive way and within lesser time. Currently, medical specialists are analyzing Computed Tomography (CT), X-Ray, and Ultrasound (US) images or conducting Polymerase Chain Reaction (PCR) for its confirmation on manual basis. In Pakistan, CT scanners are available in most hospitals at district level, while X-Ray machines are available in all tehsil (large urban towns) level hospitals. Being widely used imaging modalities to analyze chest related diseases, produce large volume of medical data each moment clinical environments. Since automatic, time efficient and reliable methods for Covid-19 detection are required as alternate methods, therefore an automatic method of Covid-19 detection using Convolutional Neural Networks (CNN) has been proposed. Three publically available and a locally developed dataset, obtained from Department of Radiology (Diagnostics), Bahawal Victoria Hospital, Bahawalpur (BVHB), Pakistan have been used. The proposed method achieved on average accuracy (96.68 %), specificity (95.65 %), and sensitivity (96.24 %). Proposed model is trained on a large dataset and is being used at the Radiology Department, (BVHB), Pakistan.In this paper, we explore a rationalistic orientation in Western society. We suggest that this orientation is one of the predominant ways in which Western society tends to frame, understand and deal with a majority of problems and questions - namely in terms of mathematical analysis, calculation and quantification, relying on logic, numbers, and statistics. Our main goal in this paper is to uncover the affective structure of this rationalistic orientation. In doing so, we illustrate how this orientation structures the way not only individuals but society as a whole frames and solves problems. We firstly point towards some exemplary instances of the rationalistic orientation, specifically regarding science, society, and lifeworld practice. Crucially, we argue that the rationalistic orientation is not merely based on a set of beliefs we could easily correct; but rather, that it is an affective condition tacitly shaping our engagement with the world in an encompassing way. Relating to the work of Martin Heidegger, we argue that what we have called an orientation in the beginning is in fact a rationalistic attunement. This attunement fundamentally shapes the pre-reflective level of how individuals approach the world. We elaborate this claim by showing how the rationalistic attunement concretely manifests in tangible socio-material affect dynamics. In the end, we motivate a critical stance towards this attunement, providing the ability to reflect upon and question instances where this way of framing and solving problems is counterproductive.In order to enhance the security of exchanged medical images in telemedicine, we propose in this paper a blind and robust approach for medical image protection. This approach consists in embedding patient information and image acquisition data in the image. This imperceptible integration must generate the least possible distortion. The watermarked image must present the same clinical reading as the original image. The proposed approach is applied in the frequency domain. For this purpose, four transforms were used discrete wavelets transform, non-subsampled contourlet transform, non-subsampled shearlet transform and discreet cosine transform. All these transforms was combined with Schur decomposition and the watermark bits were integrated in the upper triangular matrix. To obtain a satisfactory compromise between robustness and imperceptibility, the integration was performed in the medium frequencies of the image. Imperceptibility and robustness experimental results shows that the proposed methods maintain a high quality of watermarked images and are remarkably robust against several conventional attacks.Nanocomposite Sn-Bi solders received noticeable attention for flexible electronics due to their improved mechanical properties. The main limitation is the dispersion of nanoparticles in the solder alloy. Accordingly, in this work, varying additions of ZnO nanoparticles were successfully dispersed into Sn57Bi solder via the liquid-state ultrasonic treatment. Nanocomposite solders were prepared using the melting and casting route. The solder alloys were then characterized for microstructure, spreading and mechanical properties. With increasing ZnO addition, the microstructure revealed significant refinement of Bi- and Sn-rich phases. Consequently, the eutectic lamellar spacing also decreases. The spreading improved up to 0.1 wt.% ZnO addition. For higher additions, nanocomposite solders experienced deterioration in spreading characteristics. The tensile strength of the solder increases with an increase in the amount of ZnO nanoparticles. High ductility is achieved for nanocomposite solder containing 0.05 wt.% ZnO. An attempt was made, to explain the effect of increasing ZnO nanoparticle addition on microstructural, spreading, and mechanical properties of Sn57Bi solder.Improved public understanding of the ocean and the importance of sustainable ocean use, or ocean literacy, is essential for achieving global commitments to sustainable development by 2030 and beyond. However, growing human populations (particularly in mega-cities), urbanisation and socio-economic disparity threaten opportunities for people to engage and connect directly with ocean environments. Thus, a major challenge in engaging the whole of society in achieving ocean sustainability by 2030 is to develop strategies to improve societal connections to the ocean. The concept of ocean literacy reflects public understanding of the ocean, but is also an indication of connections to, and attitudes and behaviours towards, the ocean. Improving and progressing global ocean literacy has potential to catalyse the behaviour changes necessary for achieving a sustainable future. As part of the Future Seas project (https//futureseas2030.org/), this paper aims to synthesise knowledge and perspectives on ocean literacy from a range of disciplines, including but not exclusive to marine biology, socio-ecology, philosophy, technology, psychology, oceanography and human health. Using examples from the literature, we outline the potential for positive change towards a sustainable future based on knowledge that already exists. We focus on four drivers that can influence and improve ocean literacy and societal connections to the ocean (1) education, (2) cultural connections, (3) technological developments, and (4) knowledge exchange and science-policy interconnections. We explore how each driver plays a role in improving perceptions of the ocean to engender more widespread societal support for effective ocean management and conservation. In doing so, we develop an ocean literacy toolkit, a practical resource for enhancing ocean connections across a broad range of contexts worldwide.In this paper, a new stochastic fractional Coronavirus (2019-nCov) model with modified parameters is presented. The proposed stochastic COVID-19 model describes well the real data of daily confirmed cases in Wuhan. Moreover, a novel fractional order operator is introduced, it is a linear combination of Caputo's fractional derivative and Riemann-Liouville integral. Milstein's higher order method is constructed with the new fractional order operator to study the model problem. The mean square stability of Milstein algorithm is proved. Numerical results and comparative studies are introduced.Coronaviruses are a family of viruses that majorly cause respiratory disorders in humans. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of coronavirus that causes the coronavirus disease 2019 (COVID-19). WHO has identified COVID-19 as a pandemic as it has spread across the globe due to its highly contagious nature. For early diagnosis of COVID-19, the reverse transcription-polymerase chain reaction (RT-PCR) test is commonly done. However, it suffers from a high false-negative rate of up to 67% if the test is done during the first five days of exposure. As an alternative, research on the efficacy of deep learning techniques employed in the identification of COVID-19 disease using chest X-ray images is intensely pursued. As pneumonia and COVID-19 exhibit similar/ overlapping symptoms and affect the human lungs, a distinction between the chest X-ray images of pneumonia patients and COVID-19 patients becomes challenging. In this work, we have modeled the COVID-19 classification probe using Grad-CAM localizations that serve as clinical evidence.