Kinetics of Aldehyde Oxidation on Platinum Anode In Aqueous Perchloric Acid & Sulphuric Acid

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Characteristics of Anodic Film on Aluminium in Borate Bath

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LIBRARY AND INFORMATION NEEDS OF DIFFERENTLY-ABLED STUDENTS IN KERALA: A STUDY

The study was conducted to investigate the information needs of differently-abled students in the school libraries of Kerala. The study was done among students belonging to the category of visually challenged (VC), hearing and speech impaired (HI), and physically challenged (PC) from special schools and schools under Inclusive Education of the Disabled at Secondary Stage (IEDSS). The study was based on a questionnaire survey, conducted in the three districts of Kerala state ie; Thiruvananthapuram, Ernakulum & Kozhikode. The analyses revealed that the information needs of differently-abled students have become complex and problematic due to the insufficiency of adequate information sources and services and there are quite a number of challenges faced by these students in accessing information from the libraries. The overall result of the study was that, though the library services provided in the school are useful for their studies, the respondents cannot make use of them because of barriers. The study comes out with some practical suggestions to improve the library services for differently-abled student

Application of Least Square Denoising to Improve ADMM Based Hyperspectral Image Classification

AbstractHyperspectral images contain a huge amount of spatial and spectral information so that, almost any type of Earth feature can be discriminated from any other feature. But, for this classification to be possible, it is to be ensured that there is as less noise as possible in the captured data. Unfortunately, noise is unavoidable in nature and most hyperspectral images need denoising before they can be processed for classification work. In this paper, we are presenting a new approach for denoising hyperspectral images based on Least Square Regularization. Then, the hyperspectral data is classified using Basis Pursuit classifier, a constrained L1 minimization problem. To improve the time requirement for classification, Alternating Direction Method of Multipliers (ADMM) solver is used instead of CVX (convex optimization) solver. The method proposed is compared with other existing denoising methods such as Legendre-Fenchel (LF), Wavelet thresholding and Total Variation (TV). It is observed that the proposed Least Square (LS) denoising method improves classification accuracy much better than other existing denoising techniques. Even with fewer training sets, the proposed denoising technique yields better classification accuracy, thus proving least square denoising to be a powerful denoising technique

Explainable AI Framework for COVID-19 Prediction in Different Provinces of India

In 2020, covid-19 virus had reached more than 200 countries. Till December 20th 2021, 221 nations in the world had collectively reported 275M confirmed cases of covid-19 & total death toll of 5.37M. Many countries which include United States, India, Brazil, United Kingdom, Russia etc were badly affected by covid-19 pandemic due to the large population. The total confirmed cases reported in this country are 51.7M, 34.7M, 22.2M, 11.3M, 10.2M respectively till December 20, 2021. This pandemic can be controlled with the help of precautionary steps by government & civilians of the country. The early prediction of covid-19 cases helps to track the transmission dynamics & alert the government to take the necessary precautions. Recurrent Deep learning algorithms is a data driven model which plays a key role to capture the patterns present in time series data. In many literatures, the Recurrent Neural Network (RNN) based model are proposed for the efficient prediction of COVID-19 cases for different provinces. The study in the literature doesnt involve the interpretation of the model behavior & robustness. In this study, The LSTM model is proposed for the efficient prediction of active cases in each provinces of India. The active cases dataset for each province in India is taken from John Hopkins publicly available dataset for the duration from 10th June, 2020 to 4th August, 2021. The proposed LSTM model is trained on one state i.e., Maharashtra and tested for rest of the provinces in India. The concept of Explainable AI is involved in this study for the better interpretation & understanding of the model behavior. The proposed model is used to forecast the active cases in India from 16th December, 2021 to 5th March, 2022. It is notated that there will be a emergence of third wave on January, 2022 in India.Comment: 12 page

Breeding for Adaptation to Environmental Stress?

Although breeding for adaptation to environmental stresses is a more complicated problem than breeding for adaptation to biotic stresses, the basic procedure is identical. Initial steps include understanding the specific problems, and establishing methods to identify better-adapted materials. This is followed by determining if useful genetic variability for adaptation exists, and if so, deciding upon the best mean1737s to select for improved adaptation in a breeding program. The results of these steps then allow a rational decision on whether breeding for better adaptation is justified. This procedure is illustrated using two different environmental stress problems in pearl millet: failure of stand establishment and drought stress during grain filling. Useful progress has been made on understanding the problems involved and developing screening and selection methods. Current efforts center on assessing the genetic variability for these traits and evaluating the response to direct selection for adaptation

Analysis of the EMCCD point-source response using x-rays

Electron Multiplying Charge Coupled Devices, EMCCD are used as x-ray detectors. The NSLS-II Soft Inelastic x-ray Scattering (SIX) beam line has two EMCCDs for x-ray detection in the spectrometer arm. The spectrometer with high resolving power disperses x-rays vertically. The x-ray vertical position on the sensor plane is related to its energy. This allows for very accurate x-ray energy measurements through x-ray coordinates. X-rays interact with silicon and create a number of electron–hole pairs proportional to the x-ray energy. Electrons drift and diffuse toward pixel gates and are collected there. The diffused electrons form a charge cloud distributed over several neighboring pixels. This charge sharing enables coordinate measurements with accuracy better than the pixel pitch. The charge distribution shape has to be taken into account to achieve ultimate accuracy in coordinate measurements. In this paper, we present a method of the charge distribution shape analysis and demonstrate its applications. The drift and diffusion of electrons from the point of generation to pixel gates results in the bell-shaped electron cloud usually approximated by Gaussian shape. The number of electrons collected under a pixel is proportional to the shape function integral. These electron packets get transferred to the sense node of the output amplifier. The transfer process could introduce distortions to the original charge distribution. For example, during transfers, electrons in the packet could be exposed to traps if they are present in the sensor. The trapping and later the release processes distort the apparent shape of the charge distribution. Therefore, deviations of the charge distribution shape from the originally symmetrical form can indicate the presence of trap centers in the sensor and can be used for sensor diagnostics

Resistance in sorghum to shoot fly Atherigona soccata: Evidence for the source of leaf surface wetness

Leaf surface wetness (LSW) of the central whorl leaf of sorghum seedlings has been associated with susceptibility to shoot fly. Previous physical and physiological evidence suggested that LSW originates from the plant. This was confirmed by radioactive labelling methods using tritium and carbon-14. Tritiated water applied to the soil of potted seedlings was translocated to the surface of the whorl leaf. There were significant differences in the amount of tritiated water collected from susceptible (CSH 5) and resistant (IS 18551) genotypes. Studies with carbon-14 labelling of sorghum seedlings indicated the presence of (small amounts of) solutes in the surface water that may affect larval movement and survival

Beneficial health effects of cumin (Cuminum cyminum) seeds upon incorporation as a potential feed additive in livestock and poultry: A mini-review

Cumin (Cuminum cyminum Linn) is an annual plant of the family Umbelliferae, with its use dating back to ancient times when it was cultivated for its medicinal and culinary potential. Cumin seeds could contain a wide variety of phytochemicals, including alkaloids, coumarins, anthraquinones, flavonoids, glycosides, proteins, resins, saponins, tannins, and steroids. In particular, linoleic acid, one of the unsaturated fatty acids found in abundance in cumin oleoresin, is credited with promoting good health. Many of cumin's purported biological actions in livestock and poultry have been attributed to flavonoids such as apigenin, luteolin, and glycosides. Cumin has several healthful qualities, such as antibacterial, insecticidal, anti-inflammatory, analgesic, antioxidant, anticancer, anti-diabetic, anti-platelet aggregation, hypotensive, bronchodilatory, immunological, anti-amyloidogenic, and anti-osteoporotic properties. Cumin supplementation may improve milk production and reproductive function in dairy cows by altering the feeding pattern of bacteria in the rumen, encouraging the growth of beneficial microbes, or stimulating the secretion of certain digestive enzymes. Because of the low price of cumin seed, it could be concluded that its inclusion in the diet might be beneficial to the commercial poultry industry and reduce the overall cost of egg and meat production. In recent years a rise in cumin's popularity has been seen as a result of the herbal movement spearheaded by naturopaths, yoga gurus, advocates of alternative medicine, and manufacturers of feed additives. Animal nutritionists are exploring the use of cumin for its potential to boost growth, improve nutrient usage efficiency, and reduce greenhouse gas emissions. This mini-review discusses how cumin could be used as a feed ingredient to boost productivity and ensure healthy animal reproduction

Possible robust insulator-superconductor transition on solid inert gas and other substrates

We present observations of the insulator-superconductor transition in ultrathin films of Bi on amorphous quartz, quartz coated with Ge, and for the first time, solid xenon condensed on quartz. The relative permeability $\epsilon_r$ ranges from 1.5 for Xe to 15 for Ge. Though we find screening effects as expected, the I-S transition is robust, and unmodified by the substrate. The resistance separatrix is found to be close to h/4e^2 and the crossover thickness close to $\rm 25 \AA$ for all substrates. I-V studies and Aslamazov-Larkin analyses indicate superconductivity is inhomogeneous. The transition can be understood in terms of a percolation model.Comment: accepted in Physical Review