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A sandwich enzyme-linked immunosorbent assay (ELISA) was developed to detect the venom of Indian cobra (Naja naja naja) in various tissues (brain, heart, lungs, liver, spleen, blood, kidneys, and tissue at the site of injection) of mice after cobra venom injected at different time intervals (0, 2, 4, 6, 8, and 12 h intervals up to 24 h). Whole venom antiserum or individual venom protein antiserum (14, 29, 65, 72, and 99 kDa) could recognize N. n. naja venom by Western blotting and ELISA, and antibody titer was also assayed by ELISA. Antiserum raised against cobra venom in rabbit significantly neutralized the toxicity of venom-injected mice at different time intervals after treatment. The assay could detect N. n. naja venom levels up to 2.5 ng/ml of tissue homogenate, and the venom was detected up to 24 h after venom injection. Venom was detected in brain, heart, lungs, liver, spleen, kidneys, tissue at the bite area, and blood. As observed in mice, tissue at the site of bite area showed the highest concentration of venom and the brain showed the least. Moderate amounts of venoms were found in liver, spleen, kidneys, heart, and lungs. Development of a simple, rapid, and species-specific diagnostic kit based on this ELISA technique useful to clinicians is discussed. [ABSTRACT FROM AUTHOR]

In this paper, we provide evidence that the opening stock price contains noise on an everyday basis among all the NIFTY companies. However, we also find that the impact of noise does get eliminated from prices at the end of the trading day. We show how these seemingly contradictory twin empirical findings about the Indian stock market can be reconciled by proposing a Noise Trading Model in the framework of Kyle (1985). Given the clear importance of noise in opening prices, it becomes interesting to investigate whether or not we can come up with a trading strategy that can make use of noise. The paper A suggests a simple trading strategy for stocks that contain noise. The strategy suggests that when the overnight return is positive, we need to short the stock at the opening and buy it back at the closing. When overnight return is negative then simply buy at opening and sell at closing. [ABSTRACT FROM AUTHOR]

The isolated and identified triterpenoid, 1-hydroxytetratriacontane-4-one (C34H68O2), obtained from the methanolic leaf extract of Leucas aspera Linn. was explored for the first time for antisnake venom activity. The plant (L. aspera Linn.) extract significantly antagonized the spectacled cobra (Naja naja naja) venom induced lethal activity in a mouse model. It was compared with commercial antiserum obtained from King Institute of Preventive Medicine (Chennai, Tamil Nadu, India). N. naja naja venom induced a significant decrease in antioxidant superoxide dismutase, glutathione (GSH) peroxidase, catalase, reduced GSH and glutathione-S-transferase activities and increased lipid peroxidase (LPO) activity in different organs such as heart, liver, kidney and lungs. The histological changes following the antivenom treatment were also evaluated in all these organs. There were significant alterations in the histology. Triterpenoid from methanol extract of L. aspera Linn. at a dose level of 75 mg per mouse significantly attenuated (neutralized) the venom-induced antioxidant status and also the LPO activity in different organs. [ABSTRACT FROM AUTHOR]

COVID-19, the human coronavirus disease caused by SARS-CoV-2, was reported for the first time in Wuhan, China in late 2019. COVID-19 has no preventive vaccine or proven standard pharmacological treatment, and consequently, the outbreak swiftly became a pandemic affecting more than 215 countries around the world. For the diagnosis of COVID-19, the only reliable diagnostics is a qPCR assay. Among other diagnostic tools, the CRISPR-Cas system is being investigated for rapid and specific diagnosis of COVID-19. The CRISPR-Cas-based methods diagnose the SARS-CoV-2 infections within an hour. Apart from its diagnostic ability, CRISPR-Cas system is also being assessed for antiviral therapy development; however, till date, no CRISPR-based therapy has been approved for human use. The Prophylactic Antiviral CRISPR in huMAN cells (PAC-MAN), which is Cas 13 based strategy, has been developed against coronavirus. Although this strategy has the potential to be developed as a therapeutic modality, it may face significant challenges for approval in human clinical trials. This review is focused on describing potential use and challenges of CRISPR-Cas based approaches for the development of rapid and accurate diagnostic technique and/or a possible therapeutic alternative for combating COVID-19. The assessment of potential risks associated with use of CRISPR will be important for future clinical advancements.

INTRODUCTION: Over 90% of injuries and deaths still occur in low and middle-income countries like Tanzania due to Road traffic accidents. Available literature indicates that Tanzania suffers massive human and economic losses every year from RTAs despite several interventions that have been made to curb this scourge. To gain an insight into the current state of RTAs we examined the pre- historical case fatality rates from RTAs in Ilala and two other municipalities (Kinondoni and Temeke) in Dar es Salaam Region, Tanzania. METHODS: we conducted a retrospective study using the secondary data on road accidents from Road Accident Information System (RAIS) for the period 2014 to 2018.

In a recent trend, electric vehicles (EV) have been facing various power quality issues, so fuel cells (FC) are considered the best choice for integrating EV technology to enhance performance. A fuel cell electric vehicle (FCEV) is a type of EV that uses a fuel cell combined with a small battery or super-capacitor to power its on-board electric motor. However, the power obtained from the FC system is much less and is not enough to drive the EV. So, another energy source is required to deliver the demanded power, which should contain high voltage gain with high conversion efficiency. The traditional converter produces a high output voltage at a high duty cycle, which generates various problems, such as reverse recovery issues, voltage spikes, and less lifespan. High switching frequency and voltage gain are essential for the propulsion of FC-based EV. Therefore, this paper presents an improved radial basis function (RBF)-based high-gain converter (HGC) to enhance the voltage gain and conversion efficiency of the entire system. The RBF neural model was constructed using the fast recursive algorithm (FRA) strategy to prune redundant hidden-layer neurons. The improved RBF technique reduces the input current ripple and voltage stress on the power semiconductor devices to increase the conversion ratio of the HGC without changing the duty cycle value. In the end, the improved RBF with HGC achieved an efficiency of 98.272%, vehicle speed of 91 km/h, and total harmonic distortion (THD) of 3.12%, which was simulated using MATLAB, and its waveforms for steady-state operation were analyzed and compared with existing methods.

The paper empirically examines the fiscal equalization aspect of Finance Commission (FC) transfers in India using the fixed effect panel regression models. Per capita Net State Domestic Product (NSDP) is used as a proxy for fiscal capacity of the states. Total FC transfers, tax transfers and FC grant transfers in per capita terms are separately regressed on per capita NSDP for 15 major states for the period 1993-94 to 2007-08. Per capita NSDP is found to be significant and positively associated with Total FC transfers and it's components in per capita terms. This possibly indicates that FC transfers are regressive in nature and fails to equalize fiscal capacity of the states. The paper calls for appropriate design of transfers by adequately increasing the share of grants in the total FC transfers and rearranging weights in favour of redistributive criteria. [ABSTRACT FROM AUTHOR]

The article presents a study on the prevalence of respiratory diseases in chicken in the Namakkal area of Tamil Nadu, India. The researchers collected information regarding breed and strain of chicken, production performance, vaccination schedule, method of rearing and mortality from different farms having respiratory diseases. They found that young birds have higher severity of colibacillosis infection.

According to French and Roll (1986), there is greater volatility when the market is open than when it is closed. That is to say, the time series volatility of prices, where each stock is considered individually as a univariate time series, is higher when the market is open than when it is closed. We extend this result in this paper by showing that the cross-sectional analogue of this statement is true as well. Indeed, one of our major findings is that there is greater cross-sectional dispersion in prices when the market is open than when it is closed. [ABSTRACT FROM AUTHOR]

The Asset Liability Management (ALM) process in a bank is multidimensional in nature. The best possible trade off solution for profitability will have to strike an appropriate balance among the key drivers viz., advances, investments, deposits and other income (non-interest income), while simultaneously taking care of the regulatory and other constraints. The objective of this paper is to estimate, in a robust manner, the relative importance of advances, investments, deposits and other income in predicting profits. A comparative assessment is made of the two methods: Ordinary Least Square (OLS) and Robust Regression based on Least Absolute Deviation (LAD) in order to select the one that is appropriate in this situation. The results show that the robust regression outperforms OLS in terms of predictive accuracy, particularly in the context characterized by outliers and non-normal distribution with longer tails. Elasticity coefficients have been computed using the estimated slopes of the robust regression as inputs for arriving at the percentage relative importance of each driver of profitability. For this study, data filtering for inconsistencies warranted exclusion of some banks. Secondly, the focus is mainly on predictive accuracy and not hypothesis testing where OLS may still prove to be more useful. These are the two limitations of the study. [ABSTRACT FROM AUTHOR]

Cattle brought to Veterinary College and Research Institute hospital for a period of one year were screened for signs of oesophageal disorders. The cattle with oesophageal disorders were subjected to clinical examination, haematology, radiography of oesophagus and oesophagoscopy. The predominant clinical signs noticed were salivation, tachypnoea, anorexia, bloat, regurgitation with extended head and neck. Leucocytosis with neutrophilia was observed in animals with oesophageal dilatation. Lateral radiograph of cervico-thoracic region showed uniform dilatation of oesophagus on plain radiography, while dilated oesophagus was outlined by barium in contrast radiography. The dilatation of the cervical and / or thoracic oesophageal region was appreciated through endoscope in animals with mega oesophagus. In choke, oesophagoscopy revealed fluid accumulation cranial to the obstructing foreign body. [ABSTRACT FROM AUTHOR]

The performance of inductively coupled plasma-atomic emission spectrometry (ICP-AES) for the determination of fourteen lanthanides and yttrium in monazite was evaluated in comparison with inductively coupled plasma-mass spectrometry (ICP-MS) analysis. Geochemical reference samples were analysed for checking the precision and reproducibility of the methods. Monazite was separated by gravity and magnetic separations from the mineral black sands that were collected from Manavalakurichi (MK) and Chavara (CH) deposits along the southwest coast of India. Effective dissolution was carried out. The rare earth elements were collectively separated from concomitant matrix elements by ion-exchange chromatographic separation using the resin Dowex 50 X-8. Monazite mineral of the SW coast of India, is a light lanthanide-enriched mineral with negative Europium anomaly. The average value of the ratio (ICP-AES)result/(ICPMS)result, was 0.933 and 0.897 for MK and CH samples respectively, demonstrating that ICP methods applied under proper working conditions give satisfactory results. [ABSTRACT FROM AUTHOR]

Connected autonomous vehicles (CAVs) currently promise cooperation between vehicles, providing abundant and real-time information through wireless communication technologies. In this paper, a two-level fusion of classifiers (TLFC) approach is proposed by using deep learning classifiers to perform accurate road detection (RD). The proposed TLFC-RD approach improves the classification by considering four key strategies such as cross fold operation at input and pre-processing using superpixel generation, adequate features, multi-classifier feature fusion and a deep learning classifier. Specifically, the road is classified as drivable and non-drivable areas by designing the TLFC using the deep learning classifiers, and the detected information using the TLFC-RD is exchanged between the autonomous vehicles for the ease of driving on the road. The TLFC-RD is analyzed in terms of its accuracy, sensitivity or recall, specificity, precision, F1-measure and max F measure. The TLFC- RD method is also evaluated compared to three existing methods: U-Net with the Domain Adaptation Model (DAM), Two-Scale Fully Convolutional Network (TFCN) and a cooperative machine learning approach (i.e., TAAUWN). Experimental results show that the accuracy of the TLFC-RD method for the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) dataset is 99.12% higher than its competitors.

Leptospirosis is responsible for hampering the productivity of swine husbandry worldwide. The aim of this study was to assess the efficacy of bioinformatics tools in predicting the three-dimensional structure and immunogenicity of recombinant LigBCon1-5 (rLigBCon1-5) antigen. A battery of bioinformatics tools such as I-TASSER, ProSA and SAVES v6.0 were used for the prediction and assessment of the predicted structure of rLigBCon1-5 antigen. Bepipred-2.0, DiscoTope v2.0 and ElliPro servers were used to predict linear and conformational epitopes while T-cell epitopes were predicted using NetMHCpan 4.1 and IEDB recommended 2.22 method for MHC Class I and II peptides respectively. The results obtained using various in silico methods were then compared with wet lab experiments comprising of both primary (IgG Dot ELISA Dipstick test) and secondary-binding assays (Latex Agglutination Test [LAT]) to screen 1153 porcine serum samples. The three-dimensional structure of rLigA/BCon1-5 protein as predicted by I-TASSER was found to be reliable by Ramachandran Plot and ProSA. The ElliPro server suggested 10 and three potential linear and conformational B-cell-epitopes, respectively, on the peptide backbone of the rLigA/BCon1-5 protein. The DiscoTope prediction server suggested 47 amino acid residues to be part of B-cell antigen. Ten of the most efficient peptides for MHC-I and II grooves were predicted by NetMHCpan 4.1 and IEDB recommended 2.22 method, respectively. Of these, three peptides can serve dual functions as it can fit both MHC I and II grooves, thereby eliciting both humoral-and cell-mediated immune responses. The prediction of these computational approaches proved to be reliable since rLigBCon1-5 antigen-based IgG Dot ELISA Dipstick test and LAT gave results in concordance to gold standard test, the Microscopic Agglutination Test (MAT), for serodiagnosis of leptospirosis. Both the IgG Dot ELISA Dipstick test and LAT were serodiagnostic assays ideally suited for peripheral level of animal health care system as “point of care” tests for the detection of porcine leptospirosis.

Purpose - The business process outsourcing (BPO) industry in India is evolving rapidly, and one of the key characteristics of this industry is the emergence of high-end services offered by knowledge processing outsourcing (KPO) organizations. These organizations are set to grow at a tremendous pace. Given the people-intensive nature of this industry, efficient employee management is bound to play a critical role. The literature lacks studies offering insights into the HR challenges involved and the ways in which they are addressed by KPOs. The purpose of this paper is to attempt to fill this gap by presenting findings from an in-depth case study of a KPO organization. Design/methodology/approach - To achieve the research objective we adopted an in-depth case study approach. The research setting was that of a KPO organization in India, which specialises in offering complex analytics, accounting and support services to the real estate and financial services industries. Findings - The results of this study highlight the differences in the nature of work characteristics in such organizations as compared to call centres. The study also highlights some of the key people management challenges that these organizations face like attracting and retaining talent. The case company adopts formal, structured, transparent and innovative human resource practices. The study also highlights that such enlightened human resource practices stand on the foundations laid by an open work environment and facilitative leadership. Research limitations/implications - One of the key limitations is that the analysis is based on primary data from a single case study and only 18 interviews. The analysis contributes to the fields of KPO, HRM and India and has key messages for policy makers. Originality/value - The literature on outsourcing has in general focused on call centres established in the developed world. However, the booming BPO industry in India is also beginning to offer high-end services, which are far above the typical call centres. These KPOs and their people management challenges are relatively unexplored territories in the literature. By conducting this study in an emerging market (India) and focusing on people-related challenges in KPOs, this study attempts to provide a fresh perspective to the extant BPO literature. [ABSTRACT FROM AUTHOR]

The response and measurable effects of simulated acid rain at different pH levels of 3.5, 4.5, 5.5, 6.5 and 7.0 on Acacia nilotica seedlings grown on black and red soils were investigated for six months. A set of 10 potted seedlings in each treatment was exposed to 15 min foliar spray of 125 ml simulated rain acidified with sulphuric and nitric acids at a ratio of 2:1. The simulated rain was sprayed in 10 spells from 45-70 days after planting. The study was conducted in the non-monsoon season to exclude ambient rain. Increasing acidity of simulated acid rain resulted in a general decrease in all growth characters of seedlings in both soils, namely, plant height, root length, leaf number, total dry matter accumulation, leaf dry weight, stem dry weight, root dry weight, leaf area, single leaf size, specific leaf area, leaf area index, leaf area ratio and crop growth rate. However, A. nilotica on red soil showed deleterious morphological and growth characters when exposed to simulated rain at pH 3.5 compared with those on black soil. [ABSTRACT FROM AUTHOR]

Abstract: Twenty species of Indian traditional medicinal plants were selected for this study. They were Aegle marmelos, Allium sativum, Aristolochia indica, Azadirachta indica, Cassia fistula, Catharanthus roseus, Curcuma longa, Cynodon dactylon, Lantana camara, Melia azedarach, Mimosa pudica, Momordica charantia, Morus alba, Ocimum americanum, Phyllanthus amarus, Phyllanthus emblica, Psidium guajava, Solanum nigrum, Tridax procumban and Tylophora indica. These plants were used to extract antiviral substances with petroleum ether, benzene, diethyl ether, chloroform, ethyl acetate, methanol, ethanol and distilled water separately using a Soxhlet apparatus. Each extract was tested for its activity against WSSV in marine shrimp and fresh water crabs. Only five plants among these twenty (A. marmelos, C. dactylon, L. camara, M. charantia and P. amarus) showed antiviral activity against WSSV. The aqueous extract of C. dactylon showed strong antiviral activity at the concentration of 100 mg/kg of animal body. The methanol extract of M. charantia showed significant antiviral activity at the concentration of 150 mg/kg of animal body weight. The aqueous extract of L. camara and P. amarus and methanol extract of A. marmelos showed partial antiviral activity at the concentration of 150 mg/kg of animal body weight. [Copyright &y& Elsevier]

The performance of inductively coupled plasma–atomic emission spectrometry (ICP‐AES) for the determination of 14 lanthanides and Yttrium was evaluated by comparison with inductively coupled plasma–mass spectral (ICP‐MS) analysis. The geochemical reference samples (GRS), DNC‐1(diabase), AGV‐1(andesite), Sy‐2(syenite), MRG‐1(gabbro), AN‐G(anorthosite), AC‐E(granite), and MAG‐1(marine mud) were chosen as test materials and analyzed for checking the precision and reproducibility of the methods. The mineral garnet is separated from the black sands of the southwest coast of India, and the combined cation exchange–ICP method of AES analysis and MS analysis were carried out for the determination of rare earth elements. Both techniques are within the requirements needed for garnet minerals. The determination of rare‐earth elements in these minerals, which contain other elements as major contribution and trace distribution of rare‐earth elements, shows that ICP applied under the proper working condition lives up to the expectations. Major element analysis gives the formula of garnet of Manavalakurichi (MK) as (FeCaMg) 2.79 Al 2.07 Si 3.05 O 12 approximated to Fe 3 Al 2 Si 3 O 12 , hence of almandine-type garnet. The enrichment of heavy lanthanides compared to the light lanthanides indicates that these lanthanides occupy the coordinaton site of Fe 2+ by replacement. Both techniques are excellent in determining the very low concentration of lanthanides in geological materials, specifically garnet. [ABSTRACT FROM AUTHOR]

A non-stop, single tube and semi-nested polymerase chain reaction (PCR) technique with simple procedure was developed for simultaneous detection and grading the level of white spot syndrome infection in penaeid shrimp, Penaeus monodon. In this PCR procedure, three sense primers and one antisense primer with uniform annealing temperature of 55 °C were used. These primers amplify three PCR products (500, 300 and 200 base pairs [bp]) depending upon the severity of infection. Quantities of WSSV-DNA at 10 pg and greater gave three PCR products of 500, 300, 200 bp. A moderate concentration of WSSV-DNA, around 100 fg, gave two products of 300 and 200 bp and a low concentration of 1 fg or more gave only one PCR product of 200 bp. This PCR technique was assessed for early detection of WSSV in shrimp. In time-course infectivity experiments conducted on shrimp with WSSV, one PCR product (200 bp) was seen in hemolymph, tail tissue and gill at 3 h post infection (p.i.); two PCR products (300 and 200 bp) were seen in tail tissue, hemolymph, heart tissue and gill at 18 h p.i. At 30 h p.i., three PCR products (500, 300, 200 bp) were seen in all the organs tested. The samples collected from control animals showed negative for WSSV. [ABSTRACT FROM AUTHOR]

A coupled map lattice (CML) with self-learning features is developed to model flow over freely vibrating cables and stationary cylinders at low Reynolds numbers. Coupled map lattices that combine a series of low-dimensional circle maps with a diffusion model have been used previously to predict qualitative features of these flows. However, the simple nature of these CML models implies that there will be unmodeled wake features if a detailed, quantitative comparison is made with laboratory or simulated wake flows. Motivated by a desire to develop an improved CML model, we incorporate self-learning features into a new CML that is first trained to precisely estimate wake patterns from a target numerical simulation. A new convective–diffusive map that includes additional wake dynamics is developed. The new self-learning CML uses an adaptive estimation scheme (multivariable least-squares algorithm). Studies of this approach are conducted using wake patterns from a Navier–Stokes solution (spectral element-based NEKTAR simulation) of freely vibrating cable wakes at Reynolds numbers Re=100. It is shown that the self-learning model accurately and efficiently estimates the simulated wake patterns. The self-learning scheme is then successfully applied to vortex shedding patterns obtained from experiments on stationary cylinders. This constitutes a first step toward the use of the self-learning CML as a wake model in flow control studies of laboratory wake flows. © 2004 American Institute of Physics. [ABSTRACT FROM AUTHOR]