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Sonali Agarwal

Indian Institute of Information Technology Allahabad

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Sanjay Kumar Sonbhadra

Siksha O Anusandhan University

Narinder Singh Punn

Atal Bihari Vajpayee Indian Institute of Information Technology and Management

Divya Tomar

Galgotias University

Ritesh Chandra

Indian Institute of Information Technology Allahabad

Krisna Adiyarta

Universitas Budi Luhur

Bakshi Rohit Prasad

Indian Institute of Information Technology Allahabad

Mohammad Syafrullah

Universitas Budi Luhur

Sadhana Tiwari

Indian Institute of Information Technology Allahabad

Shashi Shekhar Kumar

Indian Institute of Information Technology Allahabad

P. Nagabhushan

Indian Institute of Information Technology Allahabad

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Weatherford College

Flint Institute Of Arts

Indian Institute of Information Technology Allahabad

Jaypee Institute of Information Technology

Centre Norbert Elias

University of California, Berkeley

University of Notre Dame

Oak Ridge National Laboratory

Indian Institute of Technology Delhi

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A Clinical Study of Thyroid Abnormalities and Autoantibodies in Patients Diagnosed With Anti-nuclear Antibody Positive Autoimmune Connective Tissue Disorders: An Observational Cross-Sectional Study

Saimounika Adapa Varsha Bhatt Govind Shiddapur Nilesh Jagdale Vutukuru Kalyan Kumar Reddy

Introduction: Autoimmune connective tissue disorders (CTDs) are characterized by inflammation of the connective tissue structures and immune system aberrations, such as autoantibody production. This study investigates the prevalence and clinical significance of thyroid abnormalities in patients with anti-nuclear antibody (ANA)-positive autoimmune CTDs. Methods: This prospective cross-sectional observational study was conducted at Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University), Pune, from September 2022 to June 2024. Eighty patients diagnosed with ANA-positive CTDs were included. Comprehensive histories were collected from them and clinical examinations and routine investigations were performed. Blood samples were collected for thyroid function tests and autoantibody tests. Thyroid ultrasound investigations were also performed. Ethical approval and informed consent were obtained. Results: The study revealed a significant prevalence of thyroid dysfunction among participants, with 39 (48.75%) exhibiting some form of thyroid abnormality. Subclinical hypothyroidism was the most common condition in 18 (22.50%) participants, predominantly affecting females. Thyroid autoantibodies were present in 32 (40%) participants, with thyroid peroxidase antibodies (anti-TPO Ab) being the most common seen in 17 (21.25%) participants. Systemic lupus erythematosus (SLE) was the most prevalent CTD among participants, seen in 44 (55%) participants, followed by Sjogren's syndrome (SS) seen in 19 (23.75%) participants. Conclusion: The study underscores the necessity of routine thyroid function screening in patients with ANA-positive CTDs to facilitate early detection and management of thyroid abnormalities, thereby preventing progression to overt hypothyroidism or hyperthyroidism. The findings highlight the significant association between thyroid dysfunction and autoimmune CTDs, advocating for a holistic approach to patient care.

Anti-thyroid autoantibodies

Cross-sectional study

Extractable nuclear antigens

10.7759/cureus.65950

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Roadmap To E Governance Data Management, Data Center, Data Warehousing and Data Mining

River Publishers eBooks (2022)

Sonali Agarwal Murli Dhar Tiwari Iti Tiwari

Data governance

Data center

Center (category theory)

10.1201/9781003357254-1

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Government Data Mining Case Studies on Education and Health

River Publishers eBooks (2022)

Sonali Agarwal Murli Dhar Tiwari Iti Tiwari

10.1201/9781003357254-8

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Decision support system for Forest fire management using Ontology with Big Data and LLMs

arXiv (Cornell University) (2024)

Ritesh Chandra Shashi Shekhar Kumar Rushil Patra Sonali Agarwal

Forests are crucial for ecological balance, but wildfires, a major cause of forest loss, pose significant risks. Fire weather indices, which assess wildfire risk and predict resource demands, are vital. With the rise of sensor networks in fields like healthcare and environmental monitoring, semantic sensor networks are increasingly used to gather climatic data such as wind speed, temperature, and humidity. However, processing these data streams to determine fire weather indices presents challenges, underscoring the growing importance of effective forest fire detection. This paper discusses using Apache Spark for early forest fire detection, enhancing fire risk prediction with meteorological and geographical data. Building on our previous development of Semantic Sensor Network (SSN) ontologies and Semantic Web Rules Language (SWRL) for managing forest fires in Monesterial Natural Park, we expanded SWRL to improve a Decision Support System (DSS) using a Large Language Models (LLMs) and Spark framework. We implemented real-time alerts with Spark streaming, tailored to various fire scenarios, and validated our approach using ontology metrics, query-based evaluations, LLMs score precision, F1 score, and recall measures.

10.48550/arxiv.2405.11346

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RCA-IUnet: a residual cross-spatial attention-guided inception U-Net model for tumor segmentation in breast ultrasound imaging

Machine Vision and Applications (2022)

Narinder Singh Punn Sonali Agarwal

Breast ultrasound

Ultrasound imaging

Breast imaging

10.1007/s00138-022-01280-3

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Classification of Physiological Signals for Emotion Recognition using IoT

Proceeding of the Electrical Engineering Computer Science and Informatics (2019)

Sadhana Tiwari Sonali Agarwal Mohammad Syafrullah Krisna Adiyarta

10.11591/eecsi.v6i0.1943

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Machine Learning Equipped Web-Based Disease Prediction and Recommender System

Lecture notes in electrical engineering (2022)

Harish Rajora Narinder Singh Punn Sanjay Kumar Sonbhadra Sonali Agarwal

10.1007/978-981-19-0840-8_23

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One-class support vector classifiers: A survey

Knowledge-Based Systems (2020)

Shamshe Alam Sanjay Kumar Sonbhadra Sonali Agarwal P. Nagabhushan

Feature vector

Sample (material)

Feature (linguistics)

10.1016/j.knosys.2020.105754

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Effects of Bristle Hardness & Duration of Manual Tooth brushing on Plaque Control

Indian Journal of Community Health (2017)

Sunny Sharma Vipin Agarwal Sonali Agarwal Rohit Ranjan

Background: Oral health is an integral part of general health. Poor oral health can have adverse effect on general health hence a good oral health is very essential, which in turn is achieved by good oral hygiene. Even though, the concept of good oral hygiene evolved 5000 years back, it is only in the beginning of 19th century it gained more importance. (1) Dental caries and periodontal disease are the most commonly occurring diseases affecting mankind. Dental plaque is a very important factor in the causation of both the diseases. (2) Aims & Objectives: To evaluate efficacy of four different types of toothbrushes, with difference in duration of brushing along with different bristle hardness in removal of microbial plaque. Material & Methods: In a randomized controlled trial, four groups with 40 subjects used manual toothbrushes with either hard, medium, soft and ultra-soft bristles. On baseline examination, clinical parameter plaque index (Sillness & Loe, 1964) was recorded. Selected subjects were refrained from all kinds of oral hygiene measures for 24 hrs before clinical appointment. On the day of clinical appointment scores of pre and post brushing were recorded in each patient when brushing time was set for 1 minute and same procedure was repeated after a wash off period of 3 days and similar recordings were made with brushing time of 11/2minute. Primary outcome was measured with differences in the plaque index (Sillness & Loe, 1964) compared to baseline. Results: Significant reduction in mean value of plaque score was observed on comparing pre-brushing and post-brushing data in all the subjects irrespective of bristle hardness in both 1 minute and 11/2 minute groups. On increasing time duration from 1 minute to 11/2 minute intergroup comparison revealed that significant correlation exist in mean plaque score reduction in subjects using medium bristle brush, soft bristle brush, ultra-soft bristle brush. However, no significant reduction in plaque score was observed on increasing duration from 1 minute to 11/2 minute in subjects using hard bristle brush. Conclusion: Manual toothbrushes with hard bristles better remove plaque, but may also cause more soft tissue trauma compared to brushes with softer bristles.

Tooth brushing

Dental plaque

10.47203/ijch.2017.v29i01.019

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Modeling of Temperature Data of Coal Samples by Event-Time Continuum Analysis

OmniScience A Multi-disciplinary Journal (2016)

Sayantan Nath Sonali Agarwal Garima Pandey

Time-event based analysis of temperature data modeling for coal samples by thermal camera and type-k thermocouple in algebraic approach are presented in this paper. Obtaining of different value for an identical factor, temperature (T), from coal and analysis of their acquiring mechanism in the light of mathematical morphism (→) are required to be defined with respect to time yet. Without proper interconnective function between two individual data modeling techniques of coal temperature, the working mechanism between these methodologies depending upon time-axis could not be signified separately. Different values of a same parameter (T) for a common coal sample due to two individual techniques inter-connected in abstract morphism approach to describe the occurring of events for both processes with respect to time-frame model of the universe are described in this paper. Whereas, thermal and thermocouple data, completely two different physical procedures for monitoring of temperature have produced two distinct numerical values whereas the temperature of the coal sample would always be equal at any certain moment. The designing of connected bond between those distinct monitoring processes with respect to time-frame based analysis of events in physical world shown in algebraic pattern are the basic defining factors of this investigation. Keywords: Morphism analysis, Kan functor, thermal data modeling, time-fragment structure, work-event relation, occurrence calculus Cite this Article Sayantan Nath, Sonali Agarwal, Pandey GN. Modeling of Temperature Data of Coal Samples by Event-Time Continuum Analysis. Omniscience: A Multi-disciplinary Journal . 2016; 6(1): 16–35p.

Morphism

Thermocouple

10.37591/.v6i1.2209

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