INTELLIGENT VEHICLE PARKING USING FUZZY-NEURAL NETWORKS

This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzyneural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model

Analysis of Views of Undergraduate Students towards Online and Offline Mode of Teaching, Learning and Examination

The COVID-19 pandemic has set new challenges before the world in all areas including education and India is not an exception The elementary secondary and higher education system of our country is severely affected with this deadly disease As such the schools colleges and universities have suspended their offline classes throughout the country since March last week of 2020 Amidst these challenges it has also opened up new opportunities for the teachers educators and technocrats etc to use online virtual learning strategies for imparting learning experiences to students across the world Thus techno-pedagogy is the need of the hour in India and especially in Higher Education However the nation is gradually moving towards normalcy and offline classes have been started by some of the states Hence it was necessary to assess how effective online teaching learning and evaluation in the context of offline teaching learning and examination The present paper highlights the views of the undergraduate students on the feasibility of online teaching learning and examination in the state of Arunachal Prades

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Metagenomics insights into Cr(VI) effects on structural and functional diversity of bacterial community in chromite mine soils of Sukinda Valley, Odisha

Soil contamination with heavy metal like chromium is a wide-spread environmental problem in mining and its periphery areas causing hazard to the plant, animal and human. Bacterial communities which resist the toxic effect of Cr(VI) can only survive under this hostile condition. In the study assessment of structural diversity of bacterial communities from four different locations of chromite mines area of Sukinda, Odisha (India) were carried out with 16S rRNA amplicon sequencing of V3 regions using illuminaMiSeq and functional diversity analysis from in situ mining site with whole genome metagenomics using illuminaHiSeq. The taxonomic classification was carried out through QIIME program. The samples differed from each other, both in terms of level of contamination and soil characteristics. The variations in pH were small (6.67-7.32) between the mine soils from in situ and overburden sites in comparison to forest soil (5.08). The forest soil contains higher amount of available N and K as well as organic carbon as compared to both the mine soils. Heavy metals like Fe, Cr, Ni, and Cd have been detected in higher concentrations in in situ sites than both overburden and forest soil samples. Whereas concentration of other heavy metals like Co and Mn is high in overburden than in situ and forest soil. In spite of the differences between the samples, they shared many common operational taxonomic units (OTUs) and it was possible to delineate the core microbiome of the soil samples. In general, Actinobacteria were the most dominant phyla with abundance of Deltaproteobacteria, Alphaproteobacteria, and Gammaproteobacteria within the soils. Certain bacterial genera like Acinetobacter, Pseudomonas, Lactobacillus, Bacillus, Clostridium and Corynebacterium were found to be predominant in in situ mining sites, whereas genera like Nitrospira, DA101, JG37-AG-70 and Nitrospira and DA101 were found to be abundant in overburden and forest soil respectively. In in situ soil, the bacterial genes are involved in membrane transport, DNA metabolism, Iron acquisition and metabolism, secondary metabolism, motility and chemotaxis. The results of this study add valuable information about the composition as well as structure and function of bacterial communities in chromite mine area soils and shed light on possible bioremediation transformations promoted by bacterial communities

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Not AvailableIn plants, GIGANTEA (GI) protein plays different biological functions including carbon and sucrose metabolism, cell wall deposition, transpiration and hypocotyl elongation. This suggests that GI is an important class of proteins. So far, the resource-intensive experimental methods have been mostly utilized for identification of GI proteins. Thus, we made an attempt in this study to develop a computational model for fast and accurate prediction of GI proteins. Ten different supervised learning algorithms i.e., SVM, RF, JRIP, J48, LMT, IBK, NB, PART, BAGG and LGB were employed for prediction, where the amino acid composition (AAC), FASGAI features and physico-chemical (PHYC) properties were used as numerical inputs for the learning algorithms. Higher accuracies i.e., 96.75% of AUC-ROC and 86.7% of AUC-PR were observed for SVM coupled with AAC + PHYC feature combination, while evaluated with five-fold cross validation. With leave-one-out cross validation, 97.29% of AUC-ROC and 87.89% of AUC-PR were respectively achieved. While the performance of the model was evaluated with an independent dataset of 18 GI sequences, 17 were observed as correctly predicted. We have also performed proteome-wide identification of GI proteins in wheat, followed by functional annotation using Gene Ontology terms. A prediction server “GIpred” is freely accessible at http://cabgrid.res.in:8080/gipred/ for proteome-wide recognition of GI proteins.Not Availabl

NOD1^CARD Might Be Using Multiple Interfaces for RIP2-Mediated CARD-CARD Interaction: Insights from Molecular Dynamics Simulation

<div><p>The nucleotide-binding and oligomerization domain (NOD)-containing protein 1 (NOD1) plays the pivotal role in host-pathogen interface of innate immunity and triggers immune signalling pathways for the maturation and release of pro-inflammatory cytokines. Upon the recognition of iE-DAP, NOD1 self-oligomerizes in an ATP-dependent fashion and interacts with adaptor molecule receptor-interacting protein 2 (RIP2) for the propagation of innate immune signalling and initiation of pro-inflammatory immune responses. This interaction (mediated by NOD1 and RIP2) helps in transmitting the downstream signals for the activation of NF-κB signalling pathway, and has been arbitrated by respective caspase-recruitment domains (CARDs). The so-called CARD-CARD interaction still remained contradictory due to inconsistent results. Henceforth, to understand the mode and the nature of the interaction, structural bioinformatics approaches were employed. MD simulation of modelled 1:1 heterodimeric complexes revealed that the type-Ia interface of NOD1^CARD and the type-Ib interface of RIP2^CARD might be the suitable interfaces for the said interaction. Moreover, we perceived three dynamically stable heterotrimeric complexes with an NOD1:RIP2 ratio of 1:2 (two numbers) and 2:1. Out of which, in the first trimeric complex, a type-I NOD1-RIP2 heterodimer was found interacting with an RIP2^CARD using their type-IIa and IIIa interfaces. However, in the second and third heterotrimer, we observed type-I homodimers of NOD1 and RIP2 CARDs were interacting individually with RIP2^CARD and NOD1^CARD (in type-II and type-III interface), respectively. Overall, this study provides structural and dynamic insights into the NOD1-RIP2 oligomer formation, which will be crucial in understanding the molecular basis of NOD1-mediated CARD-CARD interaction in higher and lower eukaryotes.</p></div

Drug Target Identification and Elucidation of Natural Inhibitors for : An Study

Environmental microbes like Bordetella petrii has been established as a causative agent for various infectious diseases in human. Again, development of drug resistance in B. petrii challenged to combat against the infection. Identification of potential drug target and proposing a novel lead compound against the pathogen has a great aid and value. In this study, bioinformatics tools and technology have been applied to suggest a potential drug target by screening the proteome information of B. petrii DSM 12804 (accession No. PRJNA28135) from genome database of National Centre for Biotechnology information. In this regards, the inhibitory effect of nine natural compounds like ajoene (Allium sativum), allicin (A. sativum), cinnamaldehyde (Cinnamomum cassia), curcumin (Curcuma longa), gallotannin (active component of green tea and red wine), isoorientin (Anthopterus wardii), isovitexin (A. wardii), neral (Melissa officinalis), and vitexin (A. wardii) have been acknowledged with anti-bacterial properties and hence tested against identified drug target of B. petrii by implicating computational approach. The in silico studies revealed the hypothesis that lpxD could be a potential drug target and with recommendation of a strong inhibitory effect of selected natural compounds against infection caused due to B. petrii, would be further validated through in vitro experiments

Study of miRNA Based Gene Regulation, Involved in Solid Cancer, by the Assistance of Argonaute Protein

Solid tumor is generally observed in tissues of epithelial or endothelial cells of lung, breast, prostate, pancreases, colorectal, stomach, and bladder, where several genes transcription is regulated by the microRNAs (miRNAs). Argonaute (AGO) protein is a family of protein which assists in miRNAs to bind with mRNAs of the target genes. Hence, study of the binding mechanism between AGO protein and miRNAs, and also with miRNAs-mRNAs duplex is crucial for understanding the RNA silencing mechanism. In the current work, 64 genes and 23 miRNAs have been selected from literatures, whose deregulation is well established in seven types of solid cancer like lung, breast, prostate, pancreases, colorectal, stomach, and bladder cancer. In silico study reveals, miRNAs namely, miR-106a, miR-21, and miR-29b-2 have a strong binding affinity towards PTEN, TGFBR2, and VEGFA genes, respectively, suggested as important factors in RNA silencing mechanism. Furthermore, interaction between AGO protein (PDB ID-3F73, chain A) with selected miRNAs and with miRNAs-mRNAs duplex were studied computationally to understand their binding at molecular level. The residual interaction and hydrogen bonding are inspected in Discovery Studio 3.5 suites. The current investigation throws light on understanding miRNAs based gene silencing mechanism in solid cancer

Illustration of homodimeric (type-I) mode of interaction.

<p>(A) NOD1^CARD, (B) RIP2^CARD; left panel shows the conserved interactions (acquired from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0170232#pone.0170232.s007" target="_blank">S7A</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0170232#pone.0170232.s008" target="_blank">S8A</a> Figs, respectively) mediated by type-I interfaces of NOD1 and RIP2 CARDs, and the middle panel indicates respective inter-residual/interatomic distances. Detailed 3D representation type-I (1:1 homodimeric) interaction modes were depicted in the right panel. Critical residues involved in intermolecular interactions were shown in ball and stick model, and were coloured based on physicochemical parameters. The black dotted lines represent the inter/intra-molecular polar contacts. The labelled black and red fonts represent the type-Ia and Ib interface residues, respectively.</p