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  1. Article ; Online: Analysis of Noise Pollution during Dussehra Festival in Bhubaneswar Smart City in India

    Sourav Kumar Bhoi / Chittaranjan Mallick / Chitta Ranjan Mohanty / Ranjan Soumya Nayak

    Applied Computational Intelligence and Soft Computing, Vol

    A Study Using Machine Intelligence Models

    2022  Volume 2022

    Abstract: Controlling noise pollution in smart cities is a big challenge nowadays due to rise in urbanization and industrialization. As population mass grows, the celebration of yearly festivals such as Dussehra in Bhubaneswar city is also getting popular. However, ...

    Abstract Controlling noise pollution in smart cities is a big challenge nowadays due to rise in urbanization and industrialization. As population mass grows, the celebration of yearly festivals such as Dussehra in Bhubaneswar city is also getting popular. However, since this sound pollution is creating a risk to human health, regular monitoring is strictly needed. In this work, the noise pollution level of Bhubaneswar smart city during Dussehra 2020 is predicted using different supervised machine learning (ML) prediction models. The input parameters considered for this work are area or zones of Bhubaneswar city, time at which sound level recorded, equivalent continuous sound level (Leq in dBA), and noise level (high/low compared to the standard value). The data collected for training phase and testing phase by using different ML models is taken from State Pollution Control Board, Odisha, India, for the years 2015–2020. The supervised ML models taken in this work are Decision Tree (DT), Neural Network (NN), k-Nearest Neighbor (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Random Forest (RF). The predictions of the models are evaluated using Orange 3.26 data analytics tool. From the results, it was found that DT and RF show a higher classification accuracy, 92.5%, than that of other ML models. Moreover, it is observed that the probability of prediction of noise pollution level for the testing dataset for DT is higher for high noise level and for RF is higher for low noise level than other prediction models.
    Keywords Electronic computers. Computer science ; QA75.5-76.95
    Subject code 006
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Goldratt’s Theory Applied to the Problems Associated with an Emergency Department at a Hospital

    Soumya Nayak / Lloyd J. Taylor

    Administrative Sciences, Vol 2, Iss 4, Pp 235-

    2012  Volume 249

    Abstract: Healthcare costs continue to increase dramatically, while quality remains a significant problem. Reform measures initiated by the government will drive expansion of these costs, further stressing taxpayers and employers, and forcing hospitals to adopt ... ...

    Abstract Healthcare costs continue to increase dramatically, while quality remains a significant problem. Reform measures initiated by the government will drive expansion of these costs, further stressing taxpayers and employers, and forcing hospitals to adopt fundamental changes as they try to adjust to increased demands for services and to lessening reimbursements from all payers. This struggle is best seen at the point of entry for many at a hospital: the emergency department (ED). It is at the emergency department that patients’ expectations regarding staff communication with patients, wait times, the triage process, capacity and payment will determine a significant part of a hospital’s revenue. Using Dr. Eliyahu M. Goldratt’s Thinking Process, we will determine what core problem(s) are causing a 362-bed regional West Texas hospital emergency department to lose revenue. Evaluation of the current emergency department will determine the Undesirable Effects (UDE). Using that information will lead to the construction of the Current Reality Tree (CRT), which will bring focus to the core problem(s). To break the constraints, which are the core problem(s), an Evaporative Cloud (EC) is generated. And, the end result will be to construct a Future Reality Tree (FRT), which will validate the idea(s) generated in the EC. It was determined that there are ten major UDE’s that affected this hospital’s emergency department. They were focused around staff communication, wait times, triage process, information management, service provided and bill collections. A conclusion was made that the core problem dealt with triaging patients and utilization of the services provided by the hospital. Since the reimbursement rate is affected by the patient’s satisfaction, the areas to focus on would be: triage, education, communication and retention. Although it may be neither feasible nor desirable to meet all the patient’s expectations, increased focus on those areas may increase the emergency department’s efficiency and the hospital’s bottom line.
    Keywords emergency room management ; constraint management ; theory of constraints ; Goldratt’s thinking and problem solving process ; Management. Industrial management ; HD28-70 ; Industries. Land use. Labor ; HD28-9999 ; Social Sciences ; H ; DOAJ:Business and Management ; DOAJ:Business and Economics ; Political institutions and public administration (General) ; JF20-2112
    Subject code 360
    Language English
    Publishing date 2012-10-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Circulating HLA-DR+CD4+ effector memory T cells resistant to CCR5 and PD-L1 mediated suppression compromise regulatory T cell function in tuberculosis.

    Asma Ahmed / Vasista Adiga / Soumya Nayak / J Anto Jesuraj Uday Kumar / Chirag Dhar / Pravat Nalini Sahoo / Bharath K Sundararaj / George D Souza / Annapurna Vyakarnam

    PLoS Pathogens, Vol 14, Iss 9, p e

    2018  Volume 1007289

    Abstract: Chronic T cell activation is a hallmark of pulmonary tuberculosis (PTB). The mechanisms underpinning this important phenomenon are however, poorly elucidated, though known to rely on control of T effector cells (Teff) by regulatory T cells (Treg). Our ... ...

    Abstract Chronic T cell activation is a hallmark of pulmonary tuberculosis (PTB). The mechanisms underpinning this important phenomenon are however, poorly elucidated, though known to rely on control of T effector cells (Teff) by regulatory T cells (Treg). Our studies show that circulating natural Treg cells in adults with PTB preserve their suppressive potential but Teff cells from such subjects are resistant to Treg-mediated suppression. We found this to be due to expansion of an activated Teff subset identified by Human Leukocyte Antigen (HLA)-DR expression. Sensitivity to suppression was restored to control levels by depletion of this subset. Comparative transcriptome analysis of Teff cells that contain HLA-DR+ cells versus the fraction depleted of this population identified putative resistance mechanisms linked to IFNG, IL17A, IL22, PD-L1 and β-chemokines CCL3L3, CCL4 expression. Antibody blocking experiments confirmed HLA-DR+ Teff cells, but not the fraction depleted of HLA-DR+ effectors, to be resistant to Treg suppression mediated via CCR5 and PD-L1 associated pathways. In the presence of HLA-DR+ Teff cells, activation of NFκB downstream of CCR5 and PD-L1 was perturbed. In addition, HLA-DR+ Teff cells expressed significantly higher levels of Th1/Th17 cytokines that may regulate Treg function through a reciprocal counter-balancing relationship. Taken together, our study provides novel insight on how activated HLA-DR+CD4+ T cells may contribute to disease associated inflammation by compromising Treg-mediated suppression in PTB.
    Keywords Immunologic diseases. Allergy ; RC581-607 ; Biology (General) ; QH301-705.5
    Subject code 570
    Language English
    Publishing date 2018-09-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Unbiased Identification of Blood-based Biomarkers for Pulmonary Tuberculosis by Modeling and Mining Molecular Interaction Networks

    Awanti Sambarey / Abhinandan Devaprasad / Abhilash Mohan / Asma Ahmed / Soumya Nayak / Soumya Swaminathan / George D'Souza / Anto Jesuraj / Chirag Dhar / Subash Babu / Annapurna Vyakarnam / Nagasuma Chandra

    EBioMedicine, Vol 15, Iss C, Pp 112-

    2017  Volume 126

    Abstract: Efficient diagnosis of tuberculosis (TB) is met with multiple challenges, calling for a shift of focus from pathogen-centric diagnostics towards identification of host-based multi-marker signatures. Transcriptomics offer a list of differentially ... ...

    Abstract Efficient diagnosis of tuberculosis (TB) is met with multiple challenges, calling for a shift of focus from pathogen-centric diagnostics towards identification of host-based multi-marker signatures. Transcriptomics offer a list of differentially expressed genes, but cannot by itself identify the most influential contributors to the disease phenotype. Here, we describe a computational pipeline that adopts an unbiased approach to identify a biomarker signature. Data from RNA sequencing from whole blood samples of TB patients were integrated with a curated genome-wide molecular interaction network, from which we obtain a comprehensive perspective of variations that occur in the host due to TB. We then implement a sensitive network mining method to shortlist gene candidates that are most central to the disease alterations. We then apply a series of filters that include applicability to multiple publicly available datasets as well as additional validation on independent patient samples, and identify a signature comprising 10 genes — FCGR1A, HK3, RAB13, RBBP8, IFI44L, TIMM10, BCL6, SMARCD3, CYP4F3 and SLPI, that can discriminate between TB and healthy controls as well as distinguish TB from latent tuberculosis and HIV in most cases. The signature has the potential to serve as a diagnostic marker of TB.
    Keywords Tuberculosis ; Biomarkers ; Network biology ; Computational medicine ; Diagnostics ; Medicine ; R ; Medicine (General) ; R5-920
    Subject code 006
    Language English
    Publishing date 2017-02-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Circulating Mycobacterium tuberculosis DosR latency antigen-specific, polyfunctional, regulatory IL10+ Th17 CD4 T-cells differentiate latent from active tuberculosis

    Srabanti Rakshit / Vasista Adiga / Soumya Nayak / Pravat Nalini Sahoo / Prabhat Kumar Sharma / Krista E. van Meijgaarden / Anto Jesuraj UK J. / Chirag Dhar / George D. Souza / Greg Finak / Stephen C. De Rosa / Tom H. M. Ottenhoff / Annapurna Vyakarnam

    Scientific Reports, Vol 7, Iss 1, Pp 1-

    2017  Volume 15

    Abstract: Abstract The functional heterogeneity of T cell responses to diverse antigens expressed at different stages of Mycobacterium tuberculosis (Mtb) infection, in particular early secreted versus dormancy related latency antigens expressed later, that ... ...

    Abstract Abstract The functional heterogeneity of T cell responses to diverse antigens expressed at different stages of Mycobacterium tuberculosis (Mtb) infection, in particular early secreted versus dormancy related latency antigens expressed later, that distinguish subjects with latent (LTBI), pulmonary (PTB) or extrapulmonary (EPTB) tuberculosis remains unclear. Here we show blood central memory CD4 T-cell responses specific to Mtb dormancy related (DosR) latency, but not classical immunodominant secretory antigens, to clearly differentiate LTBI from EPTB and PTB. The polyfunctionality score integrating up to 31 DosR-specific CD4 T-cell functional profiles was significantly higher in LTBI than EPTB or PTB subjects. Further analysis of 256 DosR-specific T-cell functional profiles identified regulatory IL10 + Th17 cells (IL10+IL17A+IL17F+IL22+) to be significantly enriched in LTBI; in contrast to pro-inflammatory Th17 cells (IFNγ+IL17A+/IL10−) in the blood and lung of EPTB and PTB subjects respectively. A blood polyfunctional, Mtb DosR latency antigen specific, regulatory, central memory response is therefore a novel functional component of T-cell immunity in latent TB and potential correlate of protection.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2017-09-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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