Notes

Enhanced Microstructure as well as Enhanced Permanent magnet Attributes regarding Pr-Dy-Al-Ga Diffused Sintered Nd-Fe-B Magnets.
The sensitivity of seven parameters has also been explored. The paper also examines the impact of immune response time delay and the importance of determining essential parameters such as the transmission rate using sensitivity indices analysis. The numerical experiment is calculated to illustrate the theoretical results.Contact Tracing is considered as the first and the most effective step towards containing an outbreak, as resources for mass testing and large quantity of vaccines are highly unlikely available for immediate utilization. Effective contact tracing can allow societies to reopen from lock-down even before availability of vaccines. The objective of mobile contact tracing is to speed up the manual interview based contact tracing process for containing an outbreak efficiently and quickly. In this article, we throw light on some of the issues and challenges pertaining to the adoption of mobile contact tracing solutions for fighting COVID-19. In essence, we proposed an Evaluation framework for mobile contact tracing solutions to determine their usability, feasibility, scalability and effectiveness. We evaluate some of the already proposed contact tracing solutions in light of our proposed framework. Furthermore, we present possible attacks that can be launched against contact tracing solutions along with their necessary countermeasures to thwart any possibility of such attacks.COVID-19 is a deadly viral infection that has brought a significant threat to human lives. Automatic diagnosis of COVID-19 from medical imaging enables precise medication, helps to control community outbreak, and reinforces coronavirus testing methods in place. While there exist several challenges in manually inferring traces of this viral infection from X-ray, Convolutional Neural Network (CNN) can mine data patterns that capture subtle distinctions between infected and normal X-rays. To enable automated learning of such latent features, a custom CNN architecture has been proposed in this research. It learns unique convolutional filter patterns for each kind of pneumonia. This is achieved by restricting certain filters in a convolutional layer to maximally respond only to a particular class of pneumonia/COVID-19. The CNN architecture integrates different convolution types to aid better context for learning robust features and strengthen gradient flow between layers. The proposed work also visualizes regions of saliency on the X-ray that have had the most influence on CNN's prediction outcome. To the best of our knowledge, this is the first attempt in deep learning to learn custom filters within a single convolutional layer for identifying specific pneumonia classes. Experimental results demonstrate that the proposed work has significant potential in augmenting current testing methods for COVID-19. It achieves an F1-score of 97.20% and an accuracy of 99.80% on the COVID-19 X-ray set.Internet platform enterprises have become one of the dominant organizational forms for internet-based businesses. Despite the strategically crucial role that openness decision plays for Internet platform enterprises, the results of existing research on the relationship between platform openness and platform performance are not conclusive. As to the nature of platform, its transaction attribute has been overemphasized while its innovation attribute is mostly neglected. Through decomposing platform openness into supply-side openness and demand-side openness, as well as introducing demand diversity and knowledge complexity as contextual variables, this study attempts to understand the impact of both types of attributes on performance by considering their configuration. Using fuzzy sets qualitative comparative analysis (fsQCA) method, we find that high demand diversity of platform users and high supply-side openness will lead to better platform performance. Moreover, the high knowledge complexity required for platform innovation together with high supply-side and demand-side openness will contribute to a high level of platform performance.We consider the standard model of distributed optimization of a sum of functions F ( z ) = ∑ i = 1 n f i ( z ) , where node i in a network holds the function fi (z). We allow for a harsh network model characterized by asynchronous updates, message delays, unpredictable message losses, and directed communication among nodes. In this setting, we analyze a modification of the Gradient-Push method for distributed optimization, assuming that (i) node i is capable of generating gradients of its function fi (z) corrupted by zero-mean bounded-support additive noise at each step, (ii) F(z) is strongly convex, and (iii) each fi (z) has Lipschitz gradients. We show that our proposed method asymptotically performs as well as the best bounds on centralized gradient descent that takes steps in the direction of the sum of the noisy gradients of all the functions f1(z), …, fn (z) at each step.Due to fast and deadly spread of corona virus (COVID-19), the Government of India implemented lockdown in the entire country from 25 April 2020. So, we studied the differences in the air quality index (AQI) of Delhi (DTU, Okhla and Patparganj), Haryana (Jind, Palwal and Hisar) and Uttar Pradesh (Agra, Kanpur and Greater Noida) from 17 February 2020 to 4 May 2020. The AQI was calculated by combination of individual sub-indices of seven pollutants, namely PM2.5, PM10, NO2, NH3, SO2, CO and O3, collected from the Central Pollution Control Board website. https://www.selleckchem.com/products/sodium-palmitate.html The AQI has improved by up to 30-46.67% after lockdown. The AQI slope values - 1.87, - 1.70 and - 1.35 were reported for Delhi, - 1.11, - 1.31 and - 1.04 were observed for Haryana and - 1.48, - 1.79 and - 1.78 were found for Uttar Pradesh (UP), which may be attributed to limited access of transportation and industrial facilities due to lockdown. The ozone (O3) concentration was high at Delhi because of lesser greenery as compared to UP and Haryana, which provides higher atmospheric temperature favourable for O3 formation. The air mass back trajectory (AMBT) analysis reveals the contribution of air mass from Europe, Africa and Gulf countries as well as local emissions from Indo-Gangetic Plain, Madhya Pradesh and Maharashtra states of India.
Website: https://www.selleckchem.com/products/sodium-palmitate.html