Knowledge, attitude and practices regarding World Health Organization surgical safety checklist and the challenges in its implementation at a teaching hospital in North India

Background: The WHO in 2009 published the surgical safety checklist (SSC) for reducing the surgical complications. For its successful implementation it is imperative to identify the current knowledge, attitude and practices of the involved personnel and explore the anticipated barriers. Objective of this study was to evaluate the knowledge, attitude and practices of the participants about the SSC and determine the possible challenges in its implementation.Methods: This study is a descriptive, cross-sectional study involving the use of a pre-tested questionnaire carried out in a teaching hospital. All personnel involved in the operation theater who gave their written consent were enrolled.Results: Awareness regarding the SSC is high and existing practices are favorable towards patient safety amongst Hospital personnel. Attempts should be made to educate all personnel to gain complete knowledge regarding the checklist. The anticipated barriers, of which lack of knowledge was found to be the most prominent, should be dealt with.Conclusions: A strategy aimed at proper education, stepwise implementation, alleviating the hindrances and regular feedbacks can result in decreasing the surgery related complications and morbidities through implementation of the surgical safety checklist

Twitter Sentiment Analysis of Current Affairs

Sentiment Analysis is an important type of text analysis that aims to support judgment making by extracting &analyzing opinion oriented text. Identifying positive & negative opinions & measuring how positively & negatively an entity is regarded. sentiment analysis on social media data while the use of machine learning classifier for predicting the sentiment orientation provide a useful tool for users to monitor brand or product sentiment. File level sentiment analysis is used which consists of Term Frequency (TF) and Inverse Document Frequency (IDF) values as features along with Fuzzy Clustering which results in positive and negative sentiments. As more & more user articulate their views & opinion on twitter. So twitter becomes valuable sources of people?s opinions. Tweets data can be used to infer people?s outlook for marketing & social studies. Twitter sentiment analysis that can stain the general people?s opinion in regard to social event which are going to be in current on twitter. In this research will take current scenarios which are going to be on twitter as an example for sentiment analysis. In these will use the proposed feature extraction model with emoticons and Synonym using SVM classifier. Using this can obtain greater accuracy as compared to previous research work. This research is the comparative analysis with different classifiers to identify public?s opinion

Married women migrating from rural Uttar Pradesh and Bihar: juggling family duty and aspirations

This article traces the experiences of accompanying wives who had migrated with their husbands from southern Bihar and Uttar Pradesh and returned to their villages during the COVID-19 pandemic. It dwells on post-marriage migration and work which is an under-researched aspect of women’s migration. Our study offers insights into the ways in which married women navigate power relations within the family as well as their places of work to fulfil their family obligations and personal aspirations. The analysis shows how they juggle multiple family roles as wives, mothers, daughters-in-law and daughters in their decisions related to (im)mobility, work and earning. Theoretically, the article speaks to the production of gendered and racialised work and how these fit into capitalist accumulation, women’s productive and reproductive labour, and the tensions between family duties and personal aspirations. The women in the study were ‘factory’ workers, home-based workers and ‘homeworkers’, all with different subjectivities. Although women’s work and mobility are shaped by patriarchal norms in both states, the women in our study were pushing the boundaries of tradition and asserting their views within the family. Work in cities has given them the means of fulfilling aspirations, especially related to their children’s education

Radiation Induced Gastrointestinal Damage and Protection: Nigella Sativa Seed Extract and Thymoquinone

Ionising radiation therapy is a common treatment for different types of cancers. The side effects associated with radiation includes destruction of normal cells, especially the dividing cells. The cells in the gastrointestinal (GI) tract and bone marrow are the primary targets. The GI damage is reflected by early histological changes, functional alterations and symptoms of nausea, vomiting and diarrhea. This has been designated as the radiation syndrome. Many synthetic drugs have been used to treat GI disorders but a definite cure has not been discovered so far and these available medications also cause several side effects. The herbal extracts are being tested for long time as preventive food supplement/drug in this disease. The radio protective effects of Nigella sativa (black cumin, (Ranunculacea) is already reported but its mechanism of action is not well established. Here in this review this aspect has been explored with special reference to various in vitro and in vivo models

Association of ADAM33 gene polymorphisms with adult-onset asthma and its severity in an Indian adult population

ADAM33, a member of the ADAM(a disintegrin and metalloprotease) gene family, is an asthma susceptibility gene originally identified by positional cloning. In the present study, we investigated the possible association of five single-nucleotide polymorphisms (SNPs) in the ADAM33 (rs511898, rs528557, rs44707, rs597980 and rs2787094) with adult-onset asthma in an Indian population. The study included 175 patients with mild intermittent (n=44), mild persistent (n=108) or moderate persistent (n=23) subgroups of asthma, and 253 nonasthmatic control individuals. SNPs were genotyped with the help of restriction fragment length polymorphism polymerase chain reaction (RFLP-PCR) method, and data were analysed using chi-square test and logistic regression model. Bonferroni’s correction for multiple comparisons was applied for each hypothesis. Genotypes and allele frequencies of SNPs rs511898 and rs528557 were significantly associated with adult-onset asthma(P=0.010-<0.001). A significant association of the homozygous mutant genotype and mutant alleles of SNPs rs2787094, rs44707 and rs597980 with the asthma was also observed (P=0.020-<0.001). A positive association between asthma and haplotypes AGCCT, GGCCT, AGACT, GCAGT, GGACT, ACCCC and AGACC were also found (P=0.036-<0.001,OR=2.07–8.49). Haplotypes AGCGT, GCAGC, ACAGC, ACAGT, GGAGC and GGCGT appear to protect against asthma (P=0.013-<0.0001, OR=0.34–0.10). Our data suggest that ADAM33 gene polymorphisms serve as genetic risk factors for asthma in Indian adult population

A New Paradigm Unifying the Concepts in Particle Abrasion and Breakage

This study introduces a new paradigm that unifies abrasion and breakage concepts, allowing for a holistic understanding of the comminution process. The significance of this paradigm lies in its ability to present both abrasion and breakage in a single big picture because both processes can co-occur under loading as particles are subjected to friction as well as collision. A comprehensive descriptive framework is employed to this end, which operates in a log-transformed surface-area-to-volume ratio ($A/V$) and volume ($V$) space. This space facilitates a holistic characterization of the four-dimensional particle geometry features, i.e., volume ($V$), surface area ($A$), size ($D$), and shape (${\beta}$). Consequently, this approach enables to systematically relate the co-occurring abrasion and breakage process to co-evolving particle shape and size. Transformative concepts including the breakage line, sphere line, and average shape-conserving line are introduced to describe the limit states and a special comminution process. This approach also uncovers a self-similar nature in evolving particle geometry during comminution, which will be a significant discovery for the granular materials research community given the most fundamental properties observed in natural phenomena.Comment: 10 pages, 5 figures; No difference from arXiv:2306.04635v1 except the first page stam

Prevalence and causes of blindness in patients coming to a tertiary eye care centre in western Uttar Pradesh

Background: Objective of the research was to study the prevalence of blindness in adult patients coming to a tertiary eye care centre in Western Uttar Pradesh and assess their causes. Methods: A cross-sectional study was conducted on adult patients coming to the outpatient department of a tertiary eye care centre over a period of 3 months and 375 patients were identified as having blindness. Complete ophthalmological examination was conducted to find out the cause for the same. Results: The prevalence of blindness was found out to be 4.096%. The major causes for blindness in adults were identified as cataract (33.06%), glaucoma (13.6%), ARMD (5.6%), diabetic retinopathy (5.06%), corneal scar/opacity/dystrophy (26.93%), amblyopia (3.2%) and trauma (2.13%). Conclusions: Knowledge of prevalence of blindness in a region is important in developing and implementing eye care services. Avoidable blindness needs to be identified and treated as soon as possible

A Parameter Based Comparative Study of Deep Learning Algorithms for Stock Price Prediction

Stock exchanges are places where buyers and sellers meet to trade shares in public companies. Stock exchanges encourage investment. Companies can grow, expand, and generate jobs in the economy by raising cash. These investments play a crucial role in promoting trade, economic expansion, and prosperity. We compare the three well-known deep learning algorithms, LSTM, GRU, and CNN, in this work. Our goal is to provide a thorough study of each algorithm and identify the best strategy when taking into account elements like accuracy, memory utilization, interpretability, and more. To do this, we recommend the usage of hybrid models, which combine the advantages of the various methods while also evaluating the performance of each approach separately. Aim of research is to investigate model with the highest accuracy and the best outcomes with respect to stock price prediction