An Enhanced Bully Algorithm for Electing a Coordinator in Distributed Systems

In a distributed system for accomplishing a large complex task, the task is divided into subtask and distributed among processes and coordination among processes done via message passing. To make proper coordination and functioning we need a leader node or coordinator node which acts as a centralized control node. Leader election is the most challenging task in distributed system because it is not necessary that leader node is always same because of crash failure or out of service may occur in the system. Tremendous algorithms have been proposed for elect the new leader. These algorithms use a different technique to elect a leader in distributed system. Bully election algorithm is one of the traditional algorithms for electing a leader, in which the highest node Id is elected as a leader but this algorithm requires lots of message passing for electing a leader that imposes heavy network traffic. Due to heavy network traffic, it creates complexity in message passing and takes more time. In this paper, we introduce a new approach which overcomes the drawback of existing Bully election algorithm. Our proposed algorithm is an enhanced version of Bully election algorithm. Our analytical result shows that our algorithm is more efficient than original Bully Algorithm

EVALUATION OF PHYTOCONSTITUENTS, AND ANTIMICROBIAL AND ANTIOXIDANT ACTIVITY OF JUGLANS REGIA FROM KASHMIR REGION

Objectives: The main focus of the present study was to evaluate the antimicrobial efficacy (against oral pathogenic bacteria), free radical scavenging activity, and total phenolic and flavonoids content (TPC and TFC) of methanolic extract (ME) of J. regia obtained from Kashmir region. Methods: The plant part was collected and its ME was prepared. ME was subjected to antibacterial activity against oral bacteria such as Staphylococcus aureus, Streptococcus mutans, and Pseudomonas aeruginosa. The free radical scavenging activity was determined using 2,2-diphenyl- 1-picrylhydrazylhydrate (DPPH) assay. TPC and TFC were also determined using a standard curve equation of gallic acid and quercetin. A standard curve using different concentrations of gallic acid and quercetin was drawn from which the concentration of phenols in the test sample was calculated and expressed in mg/g. Results: The ME of J. regia was found effective against all the strains of microorganisms responsible for oral infection understudy. It was also observed that scavenging of DPPH increased with the increase in concentration for both standard ascorbic and methanolic bark extract of J. regia showing its antioxidant potential. The TPC and TFC of ME was found to be 43.35±0.079 and 17.28±0.125. Conclusions: The results obtained from the study clearly indicate that the walnut bark from Kashmir region can be a good candidate for employment as an antibacterial against oral pathogens. J. regia bark was found to be a good source of healthy compounds such as phenolic and flavonoids, suggesting that its bark could be useful to prevent diseases in which free radicals are present

Production and optimization of Pectinase enzyme using Aspergillus niger strains in Solid State fermentation

Solid state fermentation was carried out with 4 fungal strains, obtained from different sources. Among 4 isolates Aspergillus niger, ATCC 16404 was found as effective pectinase producer. Maximum enzymatic activity (1.62 IU ml-1) was observed after 7 days incubation at 30‹C temperature in 250 ml Erlenmeyer conical flask. In this study 1% dextrose was used as arbon source, although citric acid as a carbon source showed better result (2.73 IU ml-1) but starch was not cost effective. As a substrate, combination of wheat bran and fresh mosambi, orange and lemon peel in ratio of 9:1:1:1 showed good result (5.38 IU ml-1) in solid state culture. Addition of 5% pectin was found to increase the enzyme production as (3.38 IU ml-1) Pectinase production was optimum in 65% moisture thus the wild strain Aspergillus niger ATCC16404 has outstanding pectinase producing capability at 30.C in 65% moisture content for 7 days of incubation in solid state fermentation

Knowledge attitude and practice of contraception in Barabanki district of Uttar Pradesh: how far are we from meeting the unmet needs of contraception

Background: Barabanki one of the most populous districts of Uttar Pradesh with population growth rate being much higher than the national population growth rate. The objective of this study was to gain the knowledge about awareness and contraceptive practices in married women residing in Barabanki. To identify socio-demographic factors associated with unmet needs for contraceptionand also to ascertain the participation of husband in family planning.Methods: A cross sectional study was conducted in outpatient department of Obstetrics Gynecology and Department of Pediatrics in Medical college hospital in Barabanki. 144 females were enrolled in the study during the study period of one year. They were interviewed on the basis of a pre-structured proforma. Data obtained was then analyzed.Results: A total 144 women in the age group 18-45 years participated in the study of which 53% had knowledge of contraception. More than two thirds were not using any form of contraception. The most common method of contraception was barrier method followed by Depot medroxy progesterone acetate. Copper T was least used mode of contraception. The most common source of knowledge regarding contraception was from electronic media followed by friends and family. The most common reason behind the absence of contraception was lack of knowledge of contraception and husband disapproval.Conclusions: Poor knowledge of contraception led to decreased usage of contraceptive measures. Husband participation is virtually absent in family planning leading to high fertility. In order to make our family planning programs successful we must incorporate media for wider coverage to increase awareness and husbands for better implementation

Dementia Detection Using LSTM and GRU

Neuro-degenerative infections, like dementia, can affect discourse, language, and the ability of correspondence.A new report to work on the precision of dementia identification examined the utilization of conversation analysis(CA) of meetings between patients and nervous system specialists to recognize reformist neuro-degenerative(ND) memory issues patients and those with (non-reformist) FMD (Functional Memory Disorder). In any case,manual CA is expensive for routine clinical use and hard proportional. In this work, we present an early dementiadiscovery framework utilizing discourse acknowledgment and examination dependent on NLP method andacoustic component handling strategy apply on various element extraction and learning using LSTM (LongShort-Term Memory) and GRU which strikingly catches the transient provisions and long haul conditions fromauthentic information to demonstrate the abilities of grouping models over a feed-forward neural organization inestimating discourse investigation related issues. Dementia dataset is taken where the audio file is considered forspeech recognition analysis on basis of that data is generated and it is predefined given in dementia data databank.That audio file is converted to text based on speech analysis. Using LSTM and GRU gives efficient results

A Study to Assess the Effectiveness of E-Module on High-Alert Medications in Terms of Knowledge among Student Nurses in a Selected College of Nursing in Delhi

Introduction: Use of medications is central to modern healthcare, and nearly all patients visiting a hospitalwill receive one or more medicines during their hospital stay or upon discharge. Medication use is a complexprocess and includes intervention by several health personnel, for example, physicians, pharmacists,nurses and student nurses to ensure safety of the patient.1.High-alert medicines have been proven to besafe and effective when taken properly. But they can cause injury if a mistake happens while taking them.This means that it is vitally important to know about these medicines and take them exactly as intended.2Methodology: The research approach selected for the study was quantitative approach with pretestposttestdesign. Convenient sampling was used for the selection of 60 student nurses from Rufaida Collegeof Nursing to evaluate their knowledge on high-alert medications. The tool developed and used for datacollection was a structured knowledge questionnaire on high-alert medications to assess the knowledgeof student nurses on high-alert medications. E-module on high-alert medications was developed by theresearcher and administered to student nurses.Results: The present study revealed that the e-module was an effective method of teaching in nursing.The mean posttest knowledge score (44.03) was higher than the mean pretest knowledge score (30.23)with a mean difference of (13.8). It indicated gain in knowledge by the student nurses. The obtained meandifference was found to be statistically significant as evident from the ‘z’ value of 8.8193 at 0.05 level ofsignificance. There was no significant association between knowledge of student nurses on high-alertmedications with their selected demographic variables like age, educational qualification, percentage inclass attendance, marks obtained in previous exam, and area of domicile.Conclusion: E-module on high-alert medications was found to be effective in improving the knowledgeof student nurses on high-alert medications. There was significant difference found in the pretest andposttest mean scores of student nurses. It shows that the e-module on high-alert medications was effectivein enhancing the knowledge of student nurses on high-alert medications

How effective and cost-effective are behaviour change interventions in improving the prescription and use of antibiotics in low-income and middle-income countries? A protocol for a systematic review.

INTRODUCTION: Antibiotic resistance endangers effective prevention and treatment of infections, and places significant burden on patients, families, communities and healthcare systems. Low-income and middle-income countries (LMICs) are especially vulnerable to antibiotic resistance, owing to high infectious disease burden, and limited resources for treatment. High prevalence of antibiotic prescription and use due to lack of provider's knowledge, prescriber's habits and perceived patient needs further exacerbate the situation. Interventions implemented to address the inappropriate prescription and use of antibiotics in LMICs must address different determinants of antibiotic resistance through sustainable and scalable interventions. The aim of this protocol is to provide a comprehensive overview of the methods that will be used to identify and appraise evidence on the effectiveness and cost-effectiveness of behaviour change interventions implemented in LMICs to improve the prescription and use of antibiotics. METHODS AND ANALYSIS: Two databases (Web of Science and PubMed) will be searched based on a strategy developed in consultation with an essential medicines and health systems researcher. Additional studies will be identified using the same search strategy in Google Scholar. To be included, a study must describe a behaviour change intervention and use an experimental design to estimate effectiveness and/or cost-effectiveness in an LMIC. Following systematic screening of titles, abstracts and keywords, and full-text appraisal, data will be extracted using a customised extraction form. Studies will be categorised by type of behaviour change intervention and experimental design. A meta-analysis or narrative synthesis will be conducted as appropriate, along with an appraisal of quality of studies using the Grading of Recommendation, Assessment, Development and Evaluation (GRADE) checklist. ETHICS AND DISSEMINATION: No individual patient data are used, so ethical approval is not required. The systematic review will be disseminated in a peer-reviewed journal and presented at a relevant international conference. PROSPERO REGISTRATION NUMBER: CRD42017075596

Utilization of Augmented Reality for Human Organ Analysis

This research paper investigates the utilization of augmented reality (AR) technology for human organ analysis in medical education. The study aims to develop and evaluate an AR application that provides an immersive and interactive learning experience for medical students. The research follows a quantitative methodology, to develop and test the effectiveness of the AR application in improving learning outcomes. The research examines the impact of the AR application on student engagement, retention of information, and performance on assessments. The results show that the AR application has a significant positive impact on learning outcomes. The use of AR technology improves student engagement, retention of information, and performance on assessments. The application's design and functionality were found to be intuitive and user-friendly, making it accessible for both students and educators. The research highlights the potential of AR technology in medical education and provides insights into its effectiveness in improving learning outcomes. The findings suggest that AR technology can be a valuable tool in medical education, enhancing the way students learn about human anatomy. This research can contribute to the existing literature on the use of AR technology in education, paving the way for future research and innovation in the field. Ultimately, the study shows that the integration of AR technology in medical education can significantly enhance the learning experience for students, providing them with an immersive and interactive approach to learning about human anatomy

Silent ovarian ectopic pregnancy: a case report

In clinical practice, an ovarian pregnancy is considered one of the most challenging diagnoses faced by an obstetrician/gynecologist. In this article, we report a 31-year-old Asian-Pakistani female, who presented to the ObsGynae clinic with 8 weeks of amenorrhea, a positive urine pregnancy test, and very high serum β-hCG levels. Transvaginal ultrasonography ruled out a tubal pregnancy, and the patient was sent for repeat β-hCG levels. The patient was hemodynamically stable and displayed no characteristic signs and symptoms of an ectopic pregnancy. Upon repeat scans and β-hCG levels, a diagnosis of ovarian ectopic pregnancy was made. The patient was managed on medication; a single dose of I/M 50 mg/m2 methotrexate was administered and the resultant decline in β-hCG levels proved the success of conservative treatment in this case. An ovarian ectopic can present as a life-threatening condition, and a high index of suspicion can prevent morbidity as well as mortality. Ovarian pregnancy, without any alarming signs despite very high β-hCG levels, as reported in this case, is one of the rarest clinical cases observed