Recovery of frog and lizard communities following primary habitat alteration in Mizoram, Northeast India

Background Community recovery following primary habitat alteration can provide tests for various hypotheses in ecology and conservation biology. Prominent among these are questions related to the manner and rate of community assembly after habitat perturbation. Here we use space-for-time substitution to analyse frog and lizard community assembly along two gradients of habitat recovery following slash and burn agriculture (jhum) in Mizoram, Northeast India. One recovery gradient undergoes natural succession to mature tropical rainforest, while the other involves plantation of jhum fallows with teak Tectona grandis monoculture. Results Frog and lizard communities accumulated species steadily during natural succession, attaining characteristics similar to those from mature forest after 30 years of regeneration. Lizards showed higher turnover and lower augmentation of species relative to frogs. Niche based classification identified a number of guilds, some of which contained both frogs and lizards. Successional change in species richness was due to increase in the number of guilds as well as the number of species per guild. Phylogenetic structure increased with succession for some guilds. Communities along the teak plantation gradient on the other hand, did not show any sign of change with chronosere age. Factor analysis revealed independent sets of habita variables that determined changes in community and guild composition during habitat recovery. Conclusions The timescale of frog and lizard community recovery was comparable with that reported by previous studies on different faunal groups in other tropical regions. Both communities converged on primary habitat attributes during natural vegetation succession, the recovery being driven by deterministic, nonlinear changes in habitat characteristics. On the other hand, very little faunal recovery was seen even in relatively old teak stands. Generally, tree monocultures are unlikely to support recovery of natural forest communities and the combined effect of shortened jhum cultivation cycles and plantation forestry could result in landscapes without mature forest. Lack of source pools of genetic diversity will then lead to altered vegetation succession and faunal community reassembly. It is therefore important that the value of habitat mosaics containing even patches of primary forest and successional secondary habitats be taken into accoun

Improving circuit miniaturization and its efficiency using Rough Set Theory

High-speed, accuracy, meticulousness and quick response are notion of the vital necessities for modern digital world. An efficient electronic circuit unswervingly affects the maneuver of the whole system. Different tools are required to unravel different types of engineering tribulations. Improving the efficiency, accuracy and low power consumption in an electronic circuit is always been a bottle neck problem. So the need of circuit miniaturization is always there. It saves a lot of time and power that is wasted in switching of gates, the wiring-crises is reduced, cross-sectional area of chip is reduced, the number of transistors that can implemented in chip is multiplied many folds. Therefore to trounce with this problem we have proposed an Artificial intelligence (AI) based approach that make use of Rough Set Theory for its implementation. Theory of rough set has been proposed by Z Pawlak in the year 1982. Rough set theory is a new mathematical tool which deals with uncertainty and vagueness. Decisions can be generated using rough set theory by reducing the unwanted and superfluous data. We have condensed the number of gates without upsetting the productivity of the given circuit. This paper proposes an approach with the help of rough set theory which basically lessens the number of gates in the circuit, based on decision rules.Comment: The International Conference on Machine Intelligence Research and Advancement,ICMIRA-201

Deep attention network for pneumonia detection using chest X-ray images

In computer vision, object recognition and image categorization have proven to be difficult challenges. They have, nevertheless, generated responses to a wide range of difficult issues from a variety of fields. Convolution Neural Networks (CNNs) have recently been identified as the most widely proposed deep learning (DL) algorithms in the literature. CNNs have unquestionably delivered cutting-edge achievements, particularly in the areas of image classification, speech recognition, and video processing. However, it has been noticed that the CNN-training assignment demands a large amount of data, which is in low supply, especially in the medical industry, and as a result, the training process takes longer. In this paper, we describe an attention-aware CNN architecture for classifying chest X-ray images to diagnose Pneumonia in order to address the aforementioned difficulties. Attention Modules provide attention-aware properties to the Attention Network. The attention-aware features of various modules alter as the layers become deeper. Using a bottom-up top-down feedforward structure, the feedforward and feedback attention processes are integrated into a single feedforward process inside each attention module. In the present work, a deep neural network (DNN) is combined with an attention mechanism to test the prediction of Pneumonia disease using chest X-ray pictures. To produce attention-aware features, the suggested network was built by merging channel and spatial attention modules in DNN architecture. With this network, we worked on a publicly available Kaggle chest X-ray dataset. Extensive testing was carried out to validate the suggested model. In the experimental results, we attained an accuracy of 95.47% and an F- score of 0.92, indicating that the suggested model outperformed against the baseline models

Defence Responses of Arabidopsis thaliana to Infection by Pseudomonas syringae Are Regulated by the Circadian Clock

The circadian clock allows plants to anticipate predictable daily changes in abiotic stimuli, such as light; however, whether the clock similarly allows plants to anticipate interactions with other organisms is unknown. Here we show that Arabidopsis thaliana (Arabidopsis) has circadian clock-mediated variation in resistance to the virulent bacterial pathogen Pseudomonas syringae pv. tomato DC3000 (Pst DC3000), with plants being least susceptible to infection in the subjective morning. We suggest that the increased resistance to Pst DC3000 observed in the morning in Col-0 plants results from clock-mediated modulation of pathogen associated molecular pattern (PAMP)-triggered immunity. Analysis of publicly available microarray data revealed that a large number of Arabidopsis defence-related genes showed both diurnal- and circadian-regulation, including genes involved in the perception of the PAMP flagellin which exhibit a peak in expression in the morning. Accordingly, we observed that PAMP-triggered callose deposition was significantly higher in wild-type plants inoculated with Pst DC3000 hrpA in the subjective morning than in the evening, while no such temporal difference was evident in arrhythmic plants. Our results suggest that PAMP-triggered immune responses are modulated by the circadian clock and that temporal regulation allows plants to anticipate and respond more effectively to pathogen challenges in the daytime

Thermal Stability of the Human Immunodeficiency Virus Type 1 (HIV-1) Receptors, CD4 and CXCR4, Reconstituted in Proteoliposomes

BACKGROUND: The entry of human immunodeficiency virus (HIV-1) into host cells involves the interaction of the viral exterior envelope glycoprotein, gp120, and receptors on the target cell. The HIV-1 receptors are CD4 and one of two chemokine receptors, CCR5 or CXCR4. METHODOLOGY/PRINCIPAL FINDINGS: We created proteoliposomes that contain CD4, the primary HIV-1 receptor, and one of the coreceptors, CXCR4. Antibodies against CD4 and CXCR4 specifically bound the proteoliposomes. CXCL12, the natural ligand for CXCR4, and the small-molecule CXCR4 antagonist, AMD3100, bound the proteoliposomes with affinities close to those associated with the binding of these molecules to cells expressing CXCR4 and CD4. The HIV-1 gp120 exterior envelope glycoprotein bound tightly to proteoliposomes expressing only CD4 and, in the presence of soluble CD4, bound weakly to proteoliposomes expressing only CXCR4. The thermal stability of CD4 and CXCR4 inserted into liposomes was examined. Thermal denaturation of CXCR4 followed second-order kinetics, with an activation energy (E(a)) of 269 kJ/mol (64.3 kcal/mol) and an inactivation temperature (T(i)) of 56°C. Thermal inactivation of CD4 exhibited a reaction order of 1.3, an E(a) of 278 kJ/mol (66.5 kcal/mol), and a T(i) of 52.2°C. The second-order denaturation kinetics of CXCR4 is unusual among G protein-coupled receptors, and may result from dimeric interactions between CXCR4 molecules. CONCLUSIONS/SIGNIFICANCE: Our studies with proteoliposomes containing the native HIV-1 receptors allowed an examination of the binding of biologically important ligands and revealed the higher-order denaturation kinetics of these receptors. CD4/CXCR4-proteoliposomes may be useful for the study of virus-target cell interactions and for the identification of inhibitors

Structure-Function Relations in Oxaloacetate Decarboxylase Complex. Fluorescence and Infrared Approaches to Monitor Oxomalonate and Na+ Binding Effect

ions across the membrane, which drives endergonic membrane reactions such as ATP synthesis, transport and motility. OAD is a membrane-bound enzyme composed of α, β and γ subunits. The α subunit contains the carboxyltransferase catalytic site. characteristic of a high content of α helix structures. Addition of oxomalonate induced a shift of the amide-I band of OAD toward higher wavenumbers, interpreted as a slight decrease of β sheet structures and a concomitant increase of α helix structures. Oxomalonate binding to αγand α subunits also provoked secondary structure variations, but these effects were negligible compared to OAD complex. alters the tryptophan environment of the β subunit, consistent with the function of these subunits within the enzyme complex. Formation of a complex between OAD and its substrates elicits structural changes in the α-helical as well as β-strand secondary structure elements

Fog computing security: a review of current applications and security solutions

Fog computing is a new paradigm that extends the Cloud platform model by providing computing resources on the edges of a network. It can be described as a cloud-like platform having similar data, computation, storage and application services, but is fundamentally different in that it is decentralized. In addition, Fog systems are capable of processing large amounts of data locally, operate on-premise, are fully portable, and can be installed on heterogeneous hardware. These features make the Fog platform highly suitable for time and location-sensitive applications. For example, Internet of Things (IoT) devices are required to quickly process a large amount of data. This wide range of functionality driven applications intensifies many security issues regarding data, virtualization, segregation, network, malware and monitoring. This paper surveys existing literature on Fog computing applications to identify common security gaps. Similar technologies like Edge computing, Cloudlets and Micro-data centres have also been included to provide a holistic review process. The majority of Fog applications are motivated by the desire for functionality and end-user requirements, while the security aspects are often ignored or considered as an afterthought. This paper also determines the impact of those security issues and possible solutions, providing future security-relevant directions to those responsible for designing, developing, and maintaining Fog systems

Quantifying Intramolecular Binding in Multivalent Interactions: A Structure-Based Synergistic Study on Grb2-Sos1 Complex

Numerous signaling proteins use multivalent binding to increase the specificity and affinity of their interactions within the cell. Enhancement arises because the effective binding constant for multivalent binding is larger than the binding constants for each individual interaction. We seek to gain both qualitative and quantitative understanding of the multivalent interactions of an adaptor protein, growth factor receptor bound protein-2 (Grb2), containing two SH3 domains interacting with the nucleotide exchange factor son-of-sevenless 1 (Sos1) containing multiple polyproline motifs separated by flexible unstructured regions. Grb2 mediates the recruitment of Sos1 from the cytosol to the plasma membrane where it activates Ras by inducing the exchange of GDP for GTP. First, using a combination of evolutionary information and binding energy calculations, we predict an additional polyproline motif in Sos1 that binds to the SH3 domains of Grb2. This gives rise to a total of five polyproline motifs in Sos1 that are capable of binding to the two SH3 domains of Grb2. Then, using a hybrid method combining molecular dynamics simulations and polymer models, we estimate the enhancement in local concentration of a polyproline motif on Sos1 near an unbound SH3 domain of Grb2 when its other SH3 domain is bound to a different polyproline motif on Sos1. We show that the local concentration of the Sos1 motifs that a Grb2 SH3 domain experiences is approximately 1000 times greater than the cellular concentration of Sos1. Finally, we calculate the intramolecular equilibrium constants for the crosslinking of Grb2 on Sos1 and use thermodynamic modeling to calculate the stoichiometry. With these equilibrium constants, we are able to predict the distribution of complexes that form at physiological concentrations. We believe this is the first systematic analysis that combines sequence, structure, and thermodynamic analyses to determine the stoichiometry of the complexes that are dominant in the cellular environment