Migration estimation in India : a monsoon migration model

Rural-Urban and Rural-Rural migration has become one of the most common phenomena of population demographic changes. Several factors which contribute towards the improvement of the livelihood and opportunities to the migrated labourers have been studied. More than 69 per cent of the 1.21 billion people live in rural India (2011 Census) and agriculture is their main source of income. Agriculture contributes to 18 per cent to the GDP of India. Due to lack of adequate public irrigation facilities, most of these farmers are dependent heavily on monsoon as the main source of water for agriculture. Since a large percentage of these farmers are into subsistence farming, they lack the capital required to set up their own irrigation facilities. When the monsoon fails, or when there is excess rain, there is loss of crop and hence rural-to-urban migration results

Design and FPGA Prototyping of a Flood Prediction System

This paper explains the chip design of a flood prediction system based on piezoelectric pressure sensors, and its FPGA prototyping. The sensors are placed at different water levels and can dependably predict the occurrence of a flood. The main criteria considered in design of the system are low cost, low power consumption, ease of installation, autonomy, reliability, and most importantly, provision of early alerts. Predicting the flood before its actual occurrence can buy sufficient time for residents to evacuate nearby areas, preventing loss of life and property. The design has been prototyped on Altera\u27s Cyclone DE2 FPGA board

Active Site Detection by Spatial Conformity and Electrostatic Analysis—Unravelling a Proteolytic Function in Shrimp Alkaline Phosphatase

Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - CataLytic Active Site Prediction (CLASP). In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD) between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA) are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP), one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP), where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in vitro

Role of modifying genes on the severity of rare mutation of MYH7 gene in hypertrophic obstructive cardiomyopathy

Hypertrophic Cardiomyopathy (HCM) is an autosomal dominant disorder due to mutations in sacromeric genes with variable penetrance. Hypertrophic Obstructive Cardiomyopathy (HOCM) is a major complication of Hypertrophic Cardiomyopathy. Unexplained hypertrophy in the Left Ventricle (LV) or Intraventricular Septum (IVS) had been the diagnostic criterion for HCM which is more often confirmed by the echocardiography. The frequency of HCM in general population is 1:500 and about 60-70% genetic predisposition is known. It has been observed that mutations in the Cardiac myosin binding proteinC (MYBPC3) gene causes late onset of disease with mild symptoms while mutations in the Beta Myosin Heavy chain (MYH7) gene leads to early onset with severe symptoms. Apart from Epigenetic and Environmental factors, modifier genes further complicate the situation leading to altered clinical outcome even among the same family members having identical mutation

Hesperidin Ameliorates Immobilization-Stress-Induced Behavioral and Biochemical Alterations and Mitochondrial Dysfunction in Mice by Modulating Nitrergic Pathway

The present study was aimed to evaluate the protective effect of hesperidin against immobilization-stress-induced alterations in biochemical, behavioral, and mitochondrial functions in mice. In many instances neuroscientists have reported that acute immobilization stress for 6 h resulted in anxiety and impaired locomotor activity due to excess oxidative-nitrergic stress, depletion of antioxidant defense mechanisms, and mitochondrial dysfunction in animals. In the present study, 6 h of acute immobilization stress had significantly altered the behavioral (anxiety and memory) and biochemical parameters coupled with mitochondrial dysfunction in Swiss albino mice. Fourteen days of pretreatment with Hesperidin (50 and 100 mg/kg, p.o.) significantly and dose-dependently inhibited the behavioral and biochemical alterations and mitochondrial dysfunction caused by acute immobilization stress. Furthermore, pre-treatment of l-arginine (50 mg/kg, i.p.), a nitric oxide precursor, reversed the protective effect of Hesperidin (50 and 100 mg/kg) (P < 0.05). In contrast, pretreatment of l-NAME (5 mg/kg, i.p.), a nitric oxide synthase inhibitor, potentiated the protective effect of Hesperidin (P < 0.05). These results suggest the possible involvement of nitrergic pathway in the protective effect Hesperidin against immobilization-stress-induced behavioral, biochemical, and mitochondrial dysfunction in mice

Impact of Tannery Effluent, Chromium on Hematological Parameters in a Fresh Water Fish, Labeo Rohita (Hamilton)

Abstract Chromium is one of the heavy metals present in the Tanner

Chemical composition and isotopic signatures of ice and snow over a Himalayan Glacier (Satopanth) in India

This study reports the chemical composition and isotopic signatures of snow and ice over a Himalayan Glacier in India. An observational campaign was carried out from September 22, 2016, to October 2, 2016, over Satopanth in central Himalaya. The pH value of ice and snow, respectively, was 5.6 ± 0.4 and 5.9 ± 0.35 over the glacier, indicating moderate acidity of the glacier components. Calcium (Ca2+) was the dominant component in snow (35.2%), while sulfate (SO42−) was dominant in ice samples (52.7%). The neutralization factor was estimated to find the extent of neutralization of acidic fractions by basic components. It is found that Ca2+ was the prominent neutralizing factor both in snow and ice over the region. Oxygen and hydrogen isotopic analyses of snow, surface layer ice and debris-covered ice suggest that the moisture source is common for all three components. δD and d-excess values of snow at Satopanth are different than that of those for Chorabari, Dokriani and Tiprabank Glacier, indicating the plausibility of different sources of moisture for these glaciers. Limited observations suggest that the interaction of ice with the debris has no impact on the isotopic signatures of the ice over the region; such non-alteration of isotopic signatures makes the region important for ice core-based paleoclimatic studies

Beyond the Cost of Price Adjustment: Investments in Pricing Capital

Abstract The literature on costs of price adjustment has long argued that changing prices is a complex and costly process. In fact, some authors have suggested that we should think of firms&apos; price-setting activities as &quot;producing&quot; prices, similar to the way firms use production processes to produce goods and services. In this paper we explore one natural extension of this view, that besides observing costs of price adjustment, we should also expect to see firm-level investments in capital expenditures into these &quot;pricing&quot; production processes. We coin the term &quot;pricing capital&quot; for these investments, and suggest that they can improve the efficiency of the &quot;pricing production&quot; activities by both reducing the costs of adjusting prices, and improving the effectiveness of price adjustments in future periods. Using two types of data sources, we find compelling evidence of the existence as well as the importance of pricing capital in firms. The existence of firm-level &quot;pricing capital&quot; has the potential of fundamentally altering the way we think about pricing and price adjustment in many areas of economics. It suggests looking toward the &quot;pricing capital&quot; to decipher the likely degree and causes of price rigidity and its variation across price setters, markets, and industries. Moreover, &quot;pricing capital&quot; introduces a new, higher-level, pricing decision made by individual firms. Decisions to invest in pricing capital compete with traditional capital investment decisions that have long been studied in economics, such as capital investments in plant, equipment, and R&amp;D. Furthermore, since pricing capital is a choice variable, it implies that costs of price adjustment often used in models of price rigidity are endogenous. As such, pricing capital offers new insights into the micro-foundations of the costs of price adjustment. The most provocative implication of the new theory of pricing, however, is that the allocative efficiency of the price system itself may be determined endogenously by individual price setters who choose whether and how much to invest in pricing capital.

Re-evaluating soil moisture-based drought criteria for rainfed crops in peninsular India

Background: Peninsular India, being completely under the influence of monsoonal climate, suffers crop yield variability due to rainfall distribution-induced soil moisture constraints. Timely and appropriate assessment of this rainfall and soil moisture-induced crop yield variability serves as a key for exemplary relief assistance. Per cent available soil moisture (PASM) is one among several drought declaration indices followed by stakeholders in India for declaration of drought, needs re-evaluation as the existing criteria in unable to capture the yield loss due to ineffective classification of PASM categories. This study attempts to revise the agricultural drought classes by PASM based on relationships established between yield of major rainfed crops of the study region and PASM.Methods: Analysis of yield variability due to PASM was carried out based on long term observations in experiments conducted at five dry farming locations (Akola, Parbhani, Kovilpatti, Ananthapuramu and Bengaluru) of peninsular India. The average yield for each category of PASM was calculated and tabulated for regression analysis. The PASM versus yield in each group was correlated and regression equations were developed if significant positive correlations were established.Results: The range of available soil moisture to obtain at least 50 percent of optimum yield in cereals (maize: 26 and finger millet: 52.9 PASM), pulses (pigeon pea: 37.2 PASM), oilseeds (soybean: 26.8 to 30.5, groundnut: 53.8 to 61.7 PASM) and commercial crops (cotton: 26.3 PASM) was 26–61 percent.Conclusion: The revised PASM-based drought classes (0–50 severe; 51–75 mild and 76–100 no drought) would help in drought declaration and precise identification of drought-hit areas for meaningful relief assistance. However, there is further investigation is needed to include a soil component for further fine-tuning of the criteria

A Measure of the Promiscuity of Proteins and Characteristics of Residues in the Vicinity of the Catalytic Site That Regulate Promiscuity

Promiscuity, the basis for the evolution of new functions through ‘tinkering’ of residues in the vicinity of the catalytic site, is yet to be quantitatively defined. We present a computational method Promiscuity Indices Estimator (PROMISE) - based on signatures derived from the spatial and electrostatic properties of the catalytic residues, to estimate the promiscuity (PromIndex) of proteins with known active site residues and 3D structure. PromIndex reflects the number of different active site signatures that have congruent matches in close proximity of its native catalytic site, the quality of the matches and difference in the enzymatic activity. Promiscuity in proteins is observed to follow a lognormal distribution (μ = 0.28, σ = 1.1 reduced chi-square = 3.0E-5). The PROMISE predicted promiscuous functions in any protein can serve as the starting point for directed evolution experiments. PROMISE ranks carboxypeptidase A and ribonuclease A amongst the more promiscuous proteins. We have also investigated the properties of the residues in the vicinity of the catalytic site that regulates its promiscuity. Linear regression establishes a weak correlation (R2∼0.1) between certain properties of the residues (charge, polar, etc) in the neighborhood of the catalytic residues and PromIndex. A stronger relationship states that most proteins with high promiscuity have high percentages of charged and polar residues within a radius of 3 Å of the catalytic site, which is validated using one-tailed hypothesis tests (P-values∼0.05). Since it is known that these characteristics are key factors in catalysis, their relationship with the promiscuity index cross validates the methodology of PROMISE