Impact of sleep disturbances and autonomic dysfunction on the quality of life of patients with fibromyalgia

Objectives: Fibromyalgia, a painful musculoskeletal disorder is associated with sleep disturbances as well as autonomic dysfunction. Pathophysiology of fibromyalgia is yet not clear and neuroanatomical proximity of sleep and autonomic centre prompts probable involvement of the two impacting the quality of life of fibromyalgia patients. Present study was done with the objective to explore the extent of sleep disturbances and/or autonomic dysfunction in fibromyalgia and asses their impact on quality of life of fibromyalgia patients. Method and materials: Thirty consecutive fibromyalgia patients (diagnosed by ACR 2010) from out-patient department and 30 age-gender matched controls were enrolled after the ethical clearance. All participants were evaluated for: (1) sleep using Pittsburgh sleep quality index and medical outcomes study sleep scale-12 Revised, (2) Quality of life by 36 item short-form health survey-36v2TM and revised fibromyalgia impact questionnaire (only patients). Autonomic functions of patients were evaluated by standard cardiovascular autonomic function tests by Ewing’s battery and heart rate variability (5-min) measurement. Results: Fibromyalgia patients had increased sleep disturbances compared to controls (39.46 ± 11, 59.61 ± 2.31; p=0.0001) and very poor sleep quality (13.63 ± 4.15, 3.03 ± 1.56; p=0.0001) as well as quality of life (p=0.0001) which further deteriorated with increasing severity of fibromyalgia. Twelve patients had autonomic dysfunction but it was neither associated with sleep disturbances nor with quality of life. Conclusions: Mild to moderate grade fibromyalgia patients have significant sleep disturbance, poor sleep quality which remarkably impacts their quality of life. Autonomic dysfunction is not an early feature of disease. The study suggests that full spectrum of sleep disturbances and sleep quality should be explored in fibromyalgia syndrome (FMS) patients

High Frequency Rule Synthesis in a Large Scale Multiple Database with MapReduce

Increasing development in information and communication technology leads to the generation of large amount of data from various sources. These collected data from multiple sources grows exponentially and may not be structurally uniform. In general, these are heterogeneous and distributed in multiple databases. Because of large volume, high velocity and variety of data mining knowledge in this environment becomes a big data challenge. Distributed Association Rule Mining(DARM) in these circumstances becomes a tedious task for an effective global Decision Support System(DSS). The DARM algorithms generate a large number of association rules and frequent itemset in the big data environment. In this situation synthesizing high-frequency rules from the big database becomes more challenging. Many  algorithms for synthesizing association rule have been proposed in multiple database mining environments. These are facing enormous challenges in terms of high availability, scalability, efficiency, high cost for the storage and processing of large intermediate results and multiple redundant rules. In this paper, we have proposed a model to collect data from multiple sources into a big data storage framework based on HDFS. Secondly, a weighted multi-partitioned method for synthesizing high-frequency rules using MapReduce programming paradigm has been proposed. Experiments have been conducted in a parallel and distributed environment by using commodity hardware. We ensure the efficiency, scalability, high availability and cost-effectiveness of our proposed method

High Frequency Rule Synthesis in a Large Scale Multiple Database with MapReduce

Increasing development in information and communication technology leads to the generation of large amount of data from various sources. These collected data from multiple sources grows exponentially and may not be structurally uniform. In general, these are heterogeneous and distributed in multiple databases. Because of large volume, high velocity and variety of data mining knowledge in this environment becomes a big data challenge. Distributed Association Rule Mining(DARM) in these circumstances becomes a tedious task for an effective global Decision Support System(DSS). The DARM algorithms generate a large number of association rules and frequent itemset in the big data environment. In this situation synthesizing highfrequency rules from the big database becomes more challenging. Many algorithms for synthesizing association rule have been proposed in multiple database mining environments. These are facing enormous challenges in terms of high availability, scalability, efficiency, high cost for the storage and processing of large intermediate results and multiple redundant rules. In this paper, we have proposed a model to collect data from multiple sources into a big data storage framework based on HDFS. Secondly, a weighted multi-partitioned method for synthesizing high-frequency rules using MapReduce programming paradigm has been proposed. Experiments have been conducted in a parallel and distributed environment by using commodity hardware. We ensure the efficiency, scalability, high availability and costeffectiveness of our proposed method

Genotype-phenotype correlation of β-thalassemia spectrum of mutations in an Indian population

Coexistence of thalassemia, hemoglobinopathies and malaria has interested geneticists over many decades. The present study represents such a population from the eastern Indian state of Orissa. Children and their siblings (n=38) were genotyped for β-thalassemia mutations and genotype-phenotype correlation was determined. The major genotype was IVS 1.5 mutation: 26% homozygous (n=10) and 37% (n=14) double heterozygous with other mutations or hemoglobinopathies. Sickle hemoglobin was the major associated hemoglobinopathy (n=12, 32%). Other mutations found were Cd 8/9, HbE and Cd 41/42. The study population did not contain any IVS 1.1 mutations which is the second major Indo- Asian genotype. Genotype-phenotype correlation revealed that genotypes of IVS 1.5, Cd 8/9 Cd 41/42 alone or in association, exhibit severe, moderate and mild severity of thalassemia, respectively. Identification of the mutation at an early age as a part of new born screening and early intervention may help reduce the thalassemia-related morbidity

A Study of Thyroid Profile and Vitamin D Levels in Type 2 Diabetes Mellitus Patients

Introduction: Non-communicable disease continues to be an imperative public health problem in India, leading to substantial increase in mortality and morbidity. Among these, Type-2 diabetes mellitus (T2DM) and hypertension are increasing at an alarming rate. T2DM increases the risk of thyroid dysfunction in the long-term.T2DM and hypothyroidism is the primary reasons for mortality and morbidity in most high income and developing countries. Materials and Methods: A cross-sectional single centre study was conducted among 100 patients with T2DM attending a tertiary care centre between January 2019 to June 2019. Eligible patients were 20 years or older. Exclusion criteria were known hepatic or renal disease, metabolic bone disease, malabsorption, hypercortisolism, pregnancy and medications influencing bone metabolism. The serum concentration of 25-OHD was measured by competitive protein binding assay using kits (Immunodiagnostic, Bensheim, Germany). Vitamin D Deficiency (VDD) was defined as serum 25-OHD concentration <50 nmol/L.Glycosylated hemoglobin (HbA1c) was measured by the high performance liquid chromatography method (Bio-Rad Laboratories, Waters, MA, USA). TSH levels between 0.22-4.2 mIU/L were regarded normal. Participants were divided to three subgroups according to their TSH level (below <0.22 mIU/L, 0.22-4.2 mIU/L and >4.2 mIU/L). Study was approved by the Institutional Ethical Review Board. Data are presented as means±standard deviation (SD) and numbers. Results: A total of 100 participants were included in this study. Average age of the study population was 50.1±17.3 years and females predominated males. Vitamin D Deficiency was found in 49% of the participants. In 5% of the cases, TSH was lower than 0.22 mIU/L and in 75%, TSH was within normal reference range. Abnormally high levels of TSH (>4.2 mIU/L) were reported in 20% of participants. Conclusion: The present study shows high prevalence of Vitamin D Deficiency levels among diabetic patients and there was a positive association between the VDD and TSH level among T2DM patients

Proceedings of the International Conference on Frontiers in Desalination, Energy, Environment and Material Sciences for Sustainable Development

This proceeding contains articles on the various ideas of the academic community presented at the International Conference on Frontiers in Desalination, Energy, Environment and Material Sciences for Sustainable Development (FEEMSSD-2023) & Annual Congress of InDA (InDACON-2023) jointly organized by the Madan Mohan Malaviya University of Technology Gorakhpur, KIPM-College of Engineering and Technology Gida Gorakhpur, and Indian Desalination Association, India on 16th-17th March 2023.  FEEMSSD-2023 & InDACON-2023 focuses on addressing issues and concerns related to sustainability in all domains of Energy, Environment, Desalination, and Material Science and attempts to present the research and innovative outputs in a global platform. The conference aims to bring together leading academicians, researchers, technocrats, practitioners, and students to exchange and share their experiences and research outputs in Energy, Environment, Desalination, and Material Science.  Conference Title: International Conference on Frontiers in Desalination, Energy, Environment and Material Sciences for Sustainable Development & Annual Congress of InDAConference Acronyms: FEEMSSD-2023 & InDACON-2023Conference Date: 16th-17th March 2023Conference Location: Madan Mohan Malaviya University of Technology, GorakhpurConference Organizers: Madan Mohan Malaviya University of Technology Gorakhpur, KIPM-College of Engineering and Technology Gida Gorakhpur, and Indian Desalination Association, Indi

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-