About: National Institute of Technology, Durgapur is a education organization based out in Durgapur, India. It is known for research contribution in the topics: Particle swarm optimization & Antenna (radio). The organization has 2590 authors who have published 5731 publications receiving 63466 citations. The organization is also known as: Regional Engineering College, Durgapur & NIT Durgapur.
Topics: Particle swarm optimization, Antenna (radio), Antenna array, Fuzzy logic, Electric power system
Papers published on a yearly basis
TL;DR: In this article, a review of available technologies for bioethanol production from agricultural wastes is discussed, which can increase concentrations of fermentable sugars after enzymatic saccharification, thereby improving the efficiency of the whole process.
Abstract: Due to rapid growth in population and industrialization, worldwide ethanol demand is increasing continuously. Conventional crops such as corn and sugarcane are unable to meet the global demand of bioethanol production due to their primary value of food and feed. Therefore, lignocellulosic substances such as agricultural wastes are attractive feedstocks for bioethanol production. Agricultural wastes are cost effective, renewable and abundant. Bioethanol from agricultural waste could be a promising technology though the process has several challenges and limitations such as biomass transport and handling, and efficient pretreatment methods for total delignification of lignocellulosics. Proper pretreatment methods can increase concentrations of fermentable sugars after enzymatic saccharification, thereby improving the efficiency of the whole process. Conversion of glucose as well as xylose to ethanol needs some new fermentation technologies, to make the whole process cost effective. In this review, available technologies for bioethanol production from agricultural wastes are discussed.
TL;DR: In this article, rice husk treated with NaOH was used as a low cost adsorbent for the removal of malachite green from aqueous solution in batch adsorption procedure.
Abstract: Rice husk treated with NaOH was tested as a low cost adsorbent for the removal of malachite green from aqueous solution in batch adsorption procedure. The adsorption experiments were carried out as a function of solution pH, initial dye concentration, contact time and temperature. The adsorption was found to be strongly dependent on pH of the medium. The Freundlich isotherm model showed good fit to the equilibrium adsorption data. The mean free energy (E) estimated from the Dubinin–Radushkevich model indicated that the main mechanism governing the sorption process was chemical ion-exchange. The kinetics of adsorption followed the pseudo-second-order model and the rate constant increased with increase in temperature indicating endothermic nature of adsorption. The Arrhenius and Eyring equations were used to obtain the activation parameters such as activation energy (Ea), and enthalpy (ΔH#), entropy (ΔS#) and free energy (ΔG#) of activation for the adsorption system. Thermodynamic studies suggested the spontaneous and endothermic nature of adsorption of malachite green by treated rice husk. The isosteric heat of adsorption (ΔHX) was also determined from the equilibrium information using the Clausius–Clapeyron equation. ΔHX increased with increase in surface loading indicating some lateral interactions between the adsorbed dye molecules.
TL;DR: Xena’s Visual Spreadsheet visualization integrates gene-centric and genomic-coordinate-centric views across multiple data modalities, providing a deep, comprehensive view of genomic events within a cohort of tumors.
Abstract: To the Editor — There is a great need for easy-to-use cancer genomics visualization tools for both large public data resources such as TCGA (The Cancer Genome Atlas)1 and the GDC (Genomic Data Commons)2, as well as smaller-scale datasets generated by individual labs. Commonly used interactive visualization tools are either web-based portals or desktop applications. Data portals have a dedicated back end and are a powerful means of viewing centrally hosted resource datasets (for example, Xena’s predecessor, the University of California, Santa Cruz (UCSC) Cancer Browser (currently retired3), cBioPortal4, ICGC (International Cancer Genomics Consortium) Data Portal5, GDC Data Portal2). However, researchers wishing to use a data portal to explore their own data have to either redeploy the entire platform, a difficult task even for bioinformaticians, or upload private data to a server outside the user’s control, a non-starter for protected patient data, such as germline variants (for example, MAGI (Mutation Annotation and Genome Interpretation6), WebMeV7 or Ordino8). Desktop tools can view a user’s own data securely (for example, Integrated Genomics Viewer (IGV)9, Gitools10), but lack well-maintained, prebuilt files for the ever-evolving and expanding public data resources. This dichotomy between data portals and desktop tools highlights the challenge of using a single platform for both large public data and smaller-scale datasets generated by individual labs. Complicating this dichotomy is the expanding amount, and complexity, of cancer genomics data resulting from numerous technological advances, including lower-cost high-throughput sequencing and single-cell-based technologies. Cancer genomics datasets are now being generated using new assays, such as whole-genome sequencing11, DNA methylation whole-genome bisulfite sequencing12 and ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing13). Visualizing and exploring these diverse data modalities is important but challenging, especially as many tools have traditionally specialized in only one or perhaps a few data types. And although these complex datasets generate insights individually, integration with other omics datasets is crucial to help researchers discover and validate findings. UCSC Xena was developed as a high-performance visualization and analysis tool for both large public repositories and private datasets. It was built to scale with the current and future data growth and complexity. Xena’s privacy-aware architecture enables cancer researchers of all computational backgrounds to explore large, diverse datasets. Researchers use the same system to securely explore their own data, together or separately from the public data, all the while keeping private data secure. The system easily supports many tens of thousands of samples and has been tested with up to a million cells. The simple and flexible architecture supports a variety of common and uncommon data types. Xena’s Visual Spreadsheet visualization integrates gene-centric and genomic-coordinate-centric views across multiple data modalities, providing a deep, comprehensive view of genomic events within a cohort of tumors. UCSC Xena (http://xena.ucsc.edu) has two components: the front end Xena Browser and the back end Xena Hubs (Fig. 1). The web-based Xena Browser empowers biologists to explore data across multiple Xena Hubs with a variety of visualizations and analyses. The back end Xena Hubs host genomics data from laptops, public servers, behind a firewall, or in the cloud, and can be public or private (Supplementary Fig. 1). The Xena Browser receives data simultaneously from multiple Xena Hubs and integrates them into a single coherent visualization within the browser. A private Xena Hub is a hub installed on a user’s own computer (Supplementary Fig. 2). It is configured to only respond to requests from the computer’s localhost network interface (that is, http://127.0.0.1). This ensures that the hub only communicates with the computer on which the hub is installed. A public hub is configured to respond to requests from external computers. There are two types of public Xena Hubs (Supplementary Fig. 2). The first type is an open-public hub, which is a public hub accessible by everyone. While we host several open-public hubs (Supplementary Table 1), users can also set up their own as a way to share data. An example of one is the Treehouse Hub set up by the Childhood Cancer Initiative to share pediatric cancer RNA-seq gene expression data (Supplementary Note). The second type W eb s er ve r
TL;DR: In this article, equilibrium, kinetics and thermodynamics of Crystal Violet (CV) adsorption onto NaOH-modified rice husk (NMRH) was investigated.
Abstract: In this study, equilibrium, kinetics and thermodynamics of Crystal Violet (CV) adsorption onto NaOH-modified rice husk (NMRH) was investigated. Experiments were carried out as function of contact time, initial solution pH (2–10), adsorbent dose (0.5–5 g) and temperature (293, 303 and 313 K). The adsorption was favoured at higher pHs and lower temperatures. Adsorption data were well described by the Freundlich model, although they could be modelled by the Langmuir model as well. The adsorption process followed the pseudo-second order kinetic model. The mass transfer model based on intraparticle diffusion was applied to the experimental data to examine the mechanisms of the rate controlling step. It was found that intraparticle diffusion was not the sole rate controlling step. The activation energy ( E a ) of the system was calculated as 50.51 kJ mol −1 . Thermodynamic parameters suggest that the adsorption is a typical chemical process, spontaneous, and exothermic in nature.
TL;DR: A review of the state of the art of gas sensors based on graphene and metal oxide hybrid nanostructures for detection of various common toxic gases is presented in this paper, where the authors have explored the hybrid architectures formed by blending of nanoparticles of metal-oxides with graphene or its derivatives.
Abstract: Sensing of gas molecules is critical to environmental monitoring, control of chemical processes, agricultural, and medical applications In particular, the detection of industrial toxic gases such as CO, NO x , and NH 3 is very important for many industries Metal oxides have been widely studied for the sensitivity of their properties to gases even though they do have some limitations Recently, graphene has been considered as a promising material for gas sensing since its electronic properties are strongly affected by the adsorption of foreign molecules Intrinsic graphene has high sensitivity at low gas concentrations; but the sensor selectivity is poor which limits its use in many practical applications Hence, hybrid architectures formed by blending of nanoparticles of metal–oxides with graphene or its derivatives have been explored by several researchers which showed improved gas sensing ability, especially the sensitivity and selectivity at room temperature Here we review the state of the art of gas sensors based on graphene and metal oxide hybrid nanostructures for detection of various common toxic gases
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|Chandra Sekhar Tiwary||41||273||6830|
|Provas Kumar Roy||36||176||4123|
|Sakti Prasad Ghoshal||32||293||3670|
|Mrinal Kanti Mandal||31||222||3143|
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