Covid 19: Need of vaccine induced herd immunity in India

Introduction: Herd immunity is a traditional concept nothing but a form of indirect protection from contagious diseases. In a mass community, there is no need to be everyone immune. If a high proportion of members in the community are immune, spreading of the disease is reduced even to non-immunized patients. This study offers an overview of vaccine-induced herd immunity importance in this pandemic and how it will be achieved. Methodology: The data of basic reproduction number Ro values for COVID 19 of 10 weeks in India which were estimated by Ro package in R software are extracted from a research article (reference no.4) and taken the mean Ro value due to fluctuations as well as to avoid great errors by using MS Excel. Herd immunity is calculated by using a standard equation stated as R=(1-Pc )(1-P1)Ro   Results:  The mean basic reproduction number Ro for COVID 19 in India was calculated as 1.671 by using MS excel and the herd 3 determines that only 40.16% proportion of individuals need to immunized through a vaccine to achieve herd immunity towards COVID 19 in India. Conclusion: This study estimates mean base reproduction Ro as 1.671 and Herd Immunity Threshold (HIT) as 40.16% by using past data. This study concludes that vaccine-induced herd immunity helps us by playing a key role to eliminate novel coronavirus

Hierarchical urchin-shaped alpha-MnO2 on graphene-coated carbon microfibers: a binder-free electrode for rechargeable aqueous Na-air battery

With the increasing demand of cost-effective and high-energy devices, sodium-air (Na-air) batteries have attracted immense interest due to the natural abundance of sodium in contrast to lithium. In particular, an aqueous Na-air battery has fundamental advantage over non-aqueous batteries due to the formation of highly water-soluble discharge product, which improve the overall performance of the system in terms of energy density, cyclic stability and round-trip efficiency. Despite these advantages, the rechargeability of aqueous Na-air batteries has not yet been demonstrated when using non-precious metal catalysts. In this work, we rationally synthesized a binder-free and robust electrode by directly growing urchin-shaped MnO2 nanowires on porous reduced graphene oxide-coated carbon microfiber (MGC) mats and fabricated an aqueous Na-air cell using the MGC as an air electrode to demonstrate the rechargeability of an aqueous Na-air battery. The fabricated aqueous Na-air cell exhibited excellent rechargeability and rate capability with a low overpotential gap (0.7 V) and high round-trip efficiency (81%). We believe that our approach opens a new avenue for synthesizing robust and binder-free electrodes that can be utilized to build not only metal-air batteries but also other energy systems such as supercapacitors, metal-ion batteries and fuel cells.ope

Robust, metallic Pd17Se15 and Pd7Se4 phases from a single source precursor and their use as counter electrodes in dye sensitized solar cells

Thin films of conducting palladium selenide phases (Pd17Se15 and Pd7Se4) are prepared using a single source molecular precursor by thermolysis. Varying the mole ratios of palladium and selenium precursors results in palladium organo-selenolate complexes which on thermolysis at different temperatures yield Pd17Se15 and Pd7Se4 phases that are very stable and adherent to the substrate. The organo-selenolate complexes are characterized using small angle XRD, Se-77 NMR and thermogravimetric analysis (TGA). The palladium selenide films are characterized by various techniques such as XRD, XPS, TEM and SEM. Electrical conductivities of the films are determined using the four probe method. The strong adherence of the films to glass substrates coupled with high corrosion resistant behavior towards strong acid and alkaline environments render them to be very effective as electrocatalysts. The catalytic activity towards the I-3(-)/I- redox couple, which is an important reaction in the regeneration of the dye in a dye-sensitized solar cell, is studied. Between the two phases, the Pd17Se15 film shows superior activity as the counter electrode for dye sensitized solar cells with a photocurrent conversion efficiency of 7.45%

The effect of structural dimensionality on the electrocatalytic properties of the nickel selenide phase

Nickel selenide (NiSe) nanostructures possessing different morphologies of wires, spheres and hexagons are synthesized by varying the selenium precursors, selenourea, selenium dioxide (SeO2) and potassium selenocyanate (KSeCN), respectively, and are characterized using X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, transmission electron microscopy and scanning electron microscopy techniques. Electrical measurements of a single nanowire and a hexagon carried out on devices fabricated by the focused ion beam (FIB) technique depict the semiconducting nature of NiSe and its ability to act as a visible light photodetector. The three different morphologies are used as catalysts for hydrogen evolution (HER), oxygen reduction (ORR) and glucose oxidation reactions. The wire morphology is found to be better than that of spheres and hexagons for all the reactions. Among the reactions studied, NiSe is found to be good for HER and glucose oxidation while ORR seems to terminate at the peroxide stage

Electrically conducting palladium selenide (Pd4Se, Pd17Se15, Pd7Se4) phases: synthesis and activity towards hydrogen evolution reaction

Electrically conducting, continuous films of different phases of palladium selenides are synthesized by the thermolysis of single source molecular precursors. The films are found to be adherent on flat substrates such as glass, indium tin oxide and glassy carbon and are stable under electrochemical conditions. They are electrocatalytically active and in particular, for hydrogen evolution reaction. Catalytic activities with low Tafel slopes of 50-60 mV per decade are observed

Variance based fusion of VCI and TCI for efficient classification of agriculture drought using MODIS data

Overall health condition of the vegetation is obtained by combining satellite data derived moisture and thermal stresses present in vegetation condition index (VCI) and thermal condition index (TCI), respectively and improves the accuracy of drought classification. Although vegetation health index fuses the information present in VCI and TCI, the relative contribution of each index depends on prior knowledge of the study area. Therefore, the random weighing method is used to obtain optimal weights of VCI and TCI based on variances of individual indices. The obtained fusion results of a normal and drought year demonstrate that the random weighing fusion achieves better estimation of agriculture drought without requiring apriori information and the obtained drought classification results are in line with the available ground truth precipitation records. In addition, the correlation analysis of the obtained optimal weights and standardized precipitation evapotranspiration index exhibited a strong correlation with a Pearson’s correlation coefficient of above 0.8. The study also showed that the relative contribution of VCI is prevalent in normal conditions while TCI in dry to extreme dry conditions

An Efficient Machine Learning Enabled Non-Destructive Technique for Remote Monitoring of Sugarcane Crop Health

Crop health can be predicted based on various biochemical variables of crops, which include chlorophyll, phenol, carbohydrate, lipid, protein, hydrogen peroxide, and proline as these variables play a critical role in maintaining the intricate phytochemistry of crop plants. In-situ monitoring of the above- mentioned variables is very cumbersome and laborious, so it is atrociously needed to identify some alternatives to monitor these variables in crop plants. Assessing these variables using satellite data may be a good choice provided it has a high spatial and temporal resolution. Sentinel-2 satellite sensor contains VNIR/SWIR spectral region, two red-edge bands, and also has good spatial as well as temporal resolution so it may be the finest option. Precise information of the field is required for the development of a retrieval algorithm for which the drone data is used, as it is highly accurate ground truth reference data. In previous studies, the researchers have primarily focused on the monitoring of biophysical and morphological parameters of crop plants like leaf area index, plant height, and stomatal conductance using these spectral features. Because monitoring biochemical variables of crop plants using satellite derivatives is still a difficult undertaking for academics, just a few studies have been published. As a result, in this study, an attempt is made to establish a methodology for monitoring sugarcane crop biochemical characteristics utilising satellite-derived variables. Satellite derivatives, i.e., vegetation indices are extracted using Sentinel-2 data while biochemical variables of the crop (as mentioned above) are analyzed using leaf samples in the laboratory using optimized protocols. Subsequently, a Machine learning-based Gaussian process regression model is developed for all the biochemical variables using the different combinations of vegetation indices. The developed model showed promising results with R2 greater than 0.7 and normalized root mean square error (NRMSE) less than 0.2 thus holding good potential for effective monitoring the crop health condition remotely

Towards reproducible state-of-the-art energy disaggregation

by Nipun Batra, Rithwik Kukunuri, Ayush Pandey, Raktim Malakar, Rajat Kumar, Odysseas Krystalakos, Mingjun Zhong, Paulo Meira, and Oliver Parso