Government Medical College

This is a tutorial on use of external-electric-fields (EEFs) as effectors of chemical change. The tutorial instructs readers how to conceptualize and design electric-field effects on bonds, structures, and reactions. Most effects can be comprehended as the field-induced stabilization of ionic structures. Thus, orienting the field along the "bond axis" will facilitate bond breaking. Similarly, orienting the field along the "reaction axis", the direction in which "electron pairs transform" from reactants- to products-like, will catalyse the reaction. Flipping the field's orientation along the reaction-axis will cause inhibition. Orienting the field off-reaction-axis will control stereo-selectivity and remove forbidden-orbital mixing. Two-directional fields may control both reactivity and selectivity. Increasing the field strength for concerted reactions (e.g., Diels-Alder's) will cause mechanistic-switchover to stepwise mechanisms with ionic intermediates. Examples of bond breaking and control of reactivity/selectivity and mechanisms are presented and analysed from the "ionic perspective". The tutorial projects the unity of EEF effects, "giving insight and numbers".

BACKGROUND: Reaction time (RT) is a measure of the response to a stimulus. RT plays a very important role in our lives as its practical implications may be of great consequences. Factors that can affect the average human RT include age, sex, left or right hand, central versus peripheral vision, practice, fatigue, fasting, breathing cycle, personality types, exercise, and intelligence of the subject. AIM: The aim was to compare visual RTs (VRTs) and auditory RTs (ARTs) on the basis of gender and physical activity levels of medical 1(st) year students. MATERIALS AND METHODS: The present cross-sectional study was conducted on 120 healthy medical students in age group of 18-20 years. RT for target stimulus that is, for the beep tone for measuring ART, and red circle for measuring VRT was determined using Inquisit 4.0 (Computer Software) in the laptop. The task was to press the spacebar as soon as the stimulus is presented. Five readings of each stimulus were taken, and their respective fastest RT's for each stimuli were recorded. Statistical analysis was done. RESULTS: In both the sexes' RT to the auditory stimulus was significantly less (P < 0.001) as compared to the visual stimulus. Significant difference was found between RT of male and female medical students (P < 0.001) as well as between sedentary and regularly exercising healthy medical 1(st) year students. CONCLUSION: The ART is faster than the VRT in medical students. Furthermore, male medical students have faster RTs as compared to female medical students for both auditory as well as visual stimuli. Regularly exercising medical students have faster RTs when compared with medical students with sedentary lifestyles.

Internet of Things (IoT) is one of the recent innovations in Information Technology, which intends to interconnect the physical and digital worlds. It introduces a vision of smartness by enabling communication between objects and humans through the Internet. IoT has diverse applications in almost all sectors like Smart Health, Smart Transportation, and Smart Cities, etc. In healthcare applications, IoT eases communication between doctors and patients as the latter can be diagnosed remotely in emergency scenarios through body sensor networks and wearable sensors. However, using IoT in healthcare systems can lead to violation of the privacy of patients. Thus, security should be taken into consideration. Blockchain is one of the trending research topics nowadays and can be applied to the majority of IoT scenarios. Few major reasons for using the Blockchain in healthcare systems are its prominent features, i.e., Decentralization, Immutability, Security and Privacy, and Transparency. This paper’s main objective was to enhance the functionality of healthcare systems using emerging and innovative computer technologies like IoT and Blockchain. So, initially, a brief introduction to the basic concepts of IoT and Blockchain is provided. After this, the applicability of IoT and Blockchain in the medical sector is explored in three major areas—drug traceability, remote patient-monitoring, and medical record management. At last, the challenges of deploying IoT and Blockchain in healthcare systems are discussed.

BACKGROUND: There is lack of information on the magnitude of depression among elderly population in India. This systematic review and meta-analysis aimed to estimate the prevalence of depression among elderly population in India. METHODS: PubMed, Scopus, Web of Science, Embase, PsycINFO, IndMed, and Google Scholar were searched to identify articles reported community-based prevalence of depression among elderly population using screening tools. This study included the articles published during the years 1997 to 2016. Studies conducted in the special population groups, hospitals, reported only a subcategory of depression, and not specified the screening tool were excluded. Data were extracted from published reports and any missing information was requested from authors. Estimates were pooled using random-effects meta-analyses. Subgroup and sensitivity analysis were performed. The publication bias was evaluated by using Egger's test and visual inspection of the symmetry in funnel plots. RESULTS: Fifty-one studies from 16 States of India were included as 56 datasets, which estimated the prevalence of depression among Indian elderly population as 34.4% (95% CI: 29.3-39.7). In sub-group analysis, the pooled prevalence was higher among females, rural populations, and in the eastern part of the country. Studies using non-probability sampling, and GDS and CES-D screening tool showed higher prevalence. Exclusion of the studies with sample size less than 100 and low-quality studies (score < 5/8) had no effect on the estimate of the prevalence. The studies that excluded dementia before assessment of depression had lower prevalence. CONCLUSION: About one third elderly population of India suffered from depression with female preponderance. The estimates varied with type of study tool, geographic region, sampling methods, and presence of dementia. The pooled estimate should be interpreted with caution as the studies included in this review had varied methodological approach and screening tools.

Abstract In its wake, the COVID‐19 pandemic has ushered in a surge in the number of cases of mucormycosis. Most cases are temporally linked to COVID‐19; hence, the entity is described as COVID‐19‐associated mucormycosis (CAM). The present systematic review was undertaken to provide an up‐to‐date summary of the hitherto available literature on CAM. PubMed, Scopus and Google Scholar databases were systematically searched using appropriate keywords till 14 May 2021, to identify case reports/case series pertaining to mucormycosis in patients with COVID‐19. Relevant data extracted included demographic characteristics, comorbidity profile, clinical category of mucormycosis, glucocorticoid use, treatment offered and patient outcome. We identified 30 case reports/case series, pooling data retrieved from 99 patients with CAM. Most cases were reported from India (72%). The majority of the patients was male (78%) and had diabetes mellitus (85%). A prior history of COVID‐19 was present in 37% patients with mucormycosis developing after an initial recovery. The median time interval between COVID‐19 diagnosis and the first evidence of mucormycosis infection or CAM diagnosis was 15 days. Glucocorticoid use was reported in 85% of cases. Rhino‐orbital mucormycosis was most common (42%), followed by rhino‐orbito‐cerebral mucormycosis (24%). Pulmonary mucormycosis was observed in 10 patients (10%). The mortality rate was 34%; the use of adjunct surgery, which was undertaken in 81% of patients, was associated with better clinical outcomes ( p &lt; .001). In conclusion, CAM is an emerging problem necessitating increased vigilance in COVID‐19 patients, even those who have recovered. CAM portends a poor prognosis and warrants early diagnosis and treatment.

THE pioneer worker in the study of the ophthalmic artery, particularly its branches and their variations, was Meyer (1887), whose observations on twenty cases have been accepted more or less as classical for the last three- quarters of a century. No detailed investigation has since been carried out in this field and the descriptions of the branches of this artery which appear in the various text-books of anatomy and ophthalmology merely reflect his conclusions. Moreover, little information regarding the branches and their anomalies is available in the literature. It was therefore thought desirable to study this problem afresh in detail.

Purpose This article offers a bibliometric analysis and explores the relationships among the documents on ecopreneurship by using relational techniques. The results highlight the publication trends; most cited documents, top contributing authors, countries and institutions with highest productivity and most contributing journals to the research field. Design/methodology/approach Initially, 216 documents were retrieved from the Thompson Reuters Web of Science Core Collection database with three document types: articles, review and book review. All the documents were considered for the analysis. Then VOSviewer and bibliometric analysis using R with an inbuilt utility Biblioshiny were used together for co-word analysis, co-citation network analysis, generating collaboration networks and also generating a unique three-field plot to analyze the evolution of a research field. Findings The results highlight the publication trends: most cited documents, top contributing authors, countries and institutions with highest productivity and most contributing journals to the research field. The network analysis of co-authorship, co-citation, keyword co-occurrence and bibliographic coupling reveals most prominent relationships between authors, documents, co-cited references, sources and countries for the available documents on the research field. Research limitations/implications The study helps not only in expansion of knowledgebase on the research topic but also in understanding the evolution of the ecopreneurship to provide research support further in this area. Originality/value Ecopreneurship is an emerging field of research connecting ecology and entrepreneurship together, making it a potential research area. The contributions made to this research field from 1989 to 2019 serve as a core for conducting this analysis. The study is an effort to help in coordinating research network across countries, authors and affiliating universities.

Recent emergence of the SARS-CoV-2 variant as OMICRON has become a global concern. This short note highlights the identification and global spread of OMICRON which has spread over 77 nations by now, which resulted in many hypotheses about its origin and degree of infectivity. The detection of mutations in the RBD region of Spike protein is a concern by surpassing vaccine immunity. The ahead will speak about its transmission potentiality, infectivity, disease morbidity as well as its effect on COVID-19 vaccines.

Abstract The emergence of smart cities and sustainable development has become a globally accepted form of urbanization. The epitome of smart city development has become possible due to the latest innovative integration of information and communication technology. Citizens of smart cities can enjoy the benefits of a smart living environment, ubiquitous connectivity, seamless access to services, intelligent decision making through smart governance, and optimized resource management. The widespread acceptance of smart cities has raised data security issues, authentication, unauthorized access, device‐level vulnerability, and sustainability. This article focuses on the holistic overview and conceptual development of smart city. Initially, the work discusses the smart city idea and fundamentals explored in various pieces of literature. Further various smart city applications along with notable implementations, are put forth to understand the quality of living standards. Finally, the article depicts a solid understanding of different security and privacy issues, including some crucial future research directions.

EXTENSIVE accounts of the blood vessels of the orbit are to be found in various text-books of ophthalmology and anatomy, but there are few systematic descriptions of the anomalies. The various authors differ very little from one another in their descriptions, and deal almost exclusively with the so- called normal pattern of the ophthalmic artery. It was therefore considered desirable to study the origin, course, branches, and anastomoses of the ophthalmic artery in detail.

Regulated cell death (RCD) is an ordered and tightly orchestrated set of changes/signaling events in both gene expression and protein activity and is responsible for normal development as well as maintenance of tissue homeostasis. Aberrant activation of this pathway results in cell death by various mechanisms including apoptosis, necroptosis, pyroptosis, ferroptosis, and autophagy-dependent cell death. Such pathological changes in neurons alone or in combination have been observed in the pathogenesis of various neurodegenerative diseases including Alzheimer's disease (AD). Pathological hallmarks of AD focus primarily on the accumulation of two main protein markers: amyloid β peptides and abnormally phosphorylated tau proteins. These protein aggregates result in the formation of A-β plaques and neuro-fibrillary tangles (NFTs) and induce neuroinflammation and neurodegeneration over years to decades leading to a multitude of cognitive and behavioral deficits. Autopsy findings of AD reveal massive neuronal death manifested in the form of cortical volume shrinkage, reduction in sizes of gyri to up to 50% and an increase in the sizes of sulci. Multiple forms of cell death have been recorded in neurons from different studies conducted so far. However, understanding the mechanism/s of neuronal cell death in AD patients remains a mystery as the trigger that results in aberrant activation of RCD is unknown and because of the limited availability of dying neurons. This review attempts to elucidate the process of Regulated cell death, how it gets unregulated in response to different intra and extracellular stressors, various forms of unregulated cell death, their interplay and their role in pathogenesis of Alzheimer's Disease in both human and experimental models of AD. Further we plan to explore the correlation of both amyloid-beta and Tau with neuronal loss as seen in AD.

In the modern era, the cyberbullying (CB) is an intentional and aggressive action of an individual or a group against a victim via electronic media. The consequence of CB is increasing alarmingly, affecting the victim either physically or psychologically. This allows the use of automated detection tools, but research on such automated tools is limited due to poor datasets or elimination of wide features during the CB detection. In this paper, an integrated model is proposed that combines both the feature extraction engine and classification engine from the input raw text datasets from a social media engine. The feature extraction engine extracts the psychological features, user comments, and the context into consideration for CB detection. The classification engine using artificial neural network (ANN) classifies the results, and it is provided with an evaluation system that either rewards or penalizes the classified output. The evaluation is carried out using Deep Reinforcement Learning (DRL) that improves the performance of classification. The simulation is carried out to validate the efficacy of the ANN-DRL model against various metrics that include accuracy, precision, recall, and f-measure. The results of the simulation show that the ANN-DRL has higher classification results than conventional machine learning classifiers.

The origin and course of the central artery of the retina have not been studied in detail and the literature pertaining to those aspects is scanty. It was there- fore considered desirable to investigate the subject more thoroughly.

Blood cell count is highly useful in identifying the occurrence of a particular disease or ailment. To successfully measure the blood cell count, sophisticated equipment that makes use of invasive methods to acquire the blood cell slides or images is utilized. These blood cell images are subjected to various data analyzing techniques that count and classify the different types of blood cells. Nowadays, deep learning-based methods are in practice to analyze the data. These methods are less time-consuming and require less sophisticated equipment. This paper implements a deep learning (D.L) model that uses the DenseNet121 model to classify the different types of white blood cells (WBC). The DenseNet121 model is optimized with the preprocessing techniques of normalization and data augmentation. This model yielded an accuracy of 98.84%, a precision of 99.33%, a sensitivity of 98.85%, and a specificity of 99.61%. The proposed model is simulated with four batch sizes (BS) along with the Adam optimizer and 10 epochs. It is concluded from the results that the DenseNet121 model has outperformed with batch size 8 as compared to other batch sizes. The dataset has been taken from the Kaggle having 12,444 images with the images of 3120 eosinophils, 3103 lymphocytes, 3098 monocytes, and 3123 neutrophils. With such results, these models could be utilized for developing clinically useful solutions that are able to detect WBC in blood cell images.

FRET is a nonradiative process of energy transfer that is based on the dipole-dipole interactions between molecules that are fluorescent. Transfer of energy takes place rapidly from a donor molecule to an acceptor molecule in juxtaposition such as 0 to 10 nm without photonic radiation. FRET has occupied a center stage in biotechnology and biological studies. It is used to gain information on conformation changes in single molecules. The pharmaceutical industry has also developed large fluorescence detection systems with very small sample sizes, at the level of single molecules, using fluorescence correlation spectroscopy.

BACKGROUND: We describe the early experiences of adults with systemic rheumatic disease who received the COVID-19 vaccine. METHODS: From 2 April to 30 April 2021, we conducted an online, international survey of adults with systemic rheumatic disease who received COVID-19 vaccination. We collected patient-reported data on clinician communication, beliefs and intent about discontinuing disease-modifying antirheumatic drugs (DMARDs) around the time of vaccination, and patient-reported adverse events after vaccination. RESULTS: We analysed 2860 adults with systemic rheumatic diseases who received COVID-19 vaccination (mean age 55.3 years, 86.7% female, 86.3% white). Types of COVID-19 vaccines were Pfizer-BioNTech (53.2%), Oxford/AstraZeneca (22.6%), Moderna (21.3%), Janssen/Johnson & Johnson (1.7%) and others (1.2%). The most common rheumatic disease was rheumatoid arthritis (42.3%), and 81.2% of respondents were on a DMARD. The majority (81.9%) reported communicating with clinicians about vaccination. Most (66.9%) were willing to temporarily discontinue DMARDs to improve vaccine efficacy, although many (44.3%) were concerned about rheumatic disease flares. After vaccination, the most reported patient-reported adverse events were fatigue/somnolence (33.4%), headache (27.7%), muscle/joint pains (22.8%) and fever/chills (19.9%). Rheumatic disease flares that required medication changes occurred in 4.6%. CONCLUSION: Among adults with systemic rheumatic disease who received COVID-19 vaccination, patient-reported adverse events were typical of those reported in the general population. Most patients were willing to temporarily discontinue DMARDs to improve vaccine efficacy. The relatively low frequency of rheumatic disease flare requiring medications was reassuring.

by using various techniques with different limits of detection are also summarized. This review provides progressive trends in the development of heteroatom doped GQDs and their various applications.

BACKGROUND: Withania somnifera (ashwagandha) is a prominent herb in Ayurveda. This study was conducted to examine the possible effects of ashwagandha root extract consumption on muscle mass and strength in healthy young men engaged in resistance training. METHODS: In this 8-week, randomized, prospective, double-blind, placebo-controlled clinical study, 57 young male subjects (18-50 years old) with little experience in resistance training were randomized into treatment (29 subjects) and placebo (28 subjects) groups. Subjects in the treatment group consumed 300 mg of ashwagandha root extract twice daily, while the control group consumed starch placebos. Following baseline measurements, both groups of subjects underwent resistance training for 8 weeks and measurements were repeated at the end of week 8. The primary efficacy measure was muscle strength. The secondary efficacy measures were muscle size, body composition, serum testosterone levels and muscle recovery. Muscle strength was evaluated using the 1-RM load for the bench press and leg extension exercises. Muscle recovery was evaluated by using serum creatine kinase level as a marker of muscle injury from the effects of exercise. RESULTS: Compared to the placebo subjects, the group treated with ashwagandha had significantly greater increases in muscle strength on the bench-press exercise (Placebo: 26.4 kg, 95% CI, 19.5, 33.3 vs. Ashwagandha: 46.0 kg, 95% CI 36.6, 55.5; p = 0.001) and the leg-extension exercise (Placebo: 9.8 kg, 95% CI, 7.2,12.3 vs. Ashwagandha: 14.5 kg, 95 % CI, 10.8,18.2; p = 0.04), and significantly greater muscle size increase at the arms (Placebo: 5.3 cm(2), 95% CI, 3.3,7.2 vs. Ashwagandha: 8.6 cm(2), 95% CI, 6.9,10.8; p = 0.01) and chest (Placebo: 1.4 cm, 95% CI, 0.8, 2.0 vs. Ashwagandha: 3.3 cm, 95% CI, 2.6, 4.1; p < 0.001). Compared to the placebo subjects, the subjects receiving ashwagandha also had significantly greater reduction of exercise-induced muscle damage as indicated by the stabilization of serum creatine kinase (Placebo: 1307.5 U/L, 95% CI, 1202.8, 1412.1, vs. Ashwagandha: 1462.6 U/L, 95% CI, 1366.2, 1559.1; p = 0.03), significantly greater increase in testosterone level (Placebo: 18.0 ng/dL, 95% CI, -15.8, 51.8 vs. Ashwagandha: 96.2 ng/dL, 95% CI, 54.7, 137.5; p = 0.004), and a significantly greater decrease in body fat percentage (Placebo: 1.5%, 95% CI, 0.4%, 2.6% vs. Ashwagandha: 3.5%, 95% CI, 2.0%, 4.9%; p = 0.03). CONCLUSION: This study reports that ashwagandha supplementation is associated with significant increases in muscle mass and strength and suggests that ashwagandha supplementation may be useful in conjunction with a resistance training program.

<b>Objective:</b> To study the effect of various maternal factors on the prevalence of underweight and stunting among 1-5-year-old children in urban slum population. <b>Design:</b> Cross-sectional study. <b>Materials and Methods:</b> The study was carried out in three urban slums of Tripuri Town, Patiala. All 1-5-year children living in these slums were included, whose mother's demographic profile, weight and height were recorded. <b>Results:</b> Out of 482 children who participated in the study, 185 (38.38%) had low weight for age whereas 222 (46.06%) had low height for age. Both kinds of malnutrition were common in females than in males. Prevalence of malnutrition was more where mother's age was less than 20 years. Children of educated mothers were better nourished as compared to illiterate ones. <b>Conclusion:</b> Maternal factors significantly affect a child's nutritional status, thus encouraging the improvement in the social status of women so as to have healthy children and thereby a healthy future.

At present, optimization algorithms are used extensively. One particular type of such algorithms includes random-based heuristic population optimization algorithms, which may be created by modeling scientific phenomena, like, for example, physical processes. The present article proposes a novel optimization algorithm based on Hooke’s law, called the spring search algorithm (SSA), which aims to solve single-objective constrained optimization problems. In the SSA, search agents are weights joined through springs, which, as Hooke’s law states, possess a force that corresponds to its length. The mathematics behind the algorithm are presented in the text. In order to test its functionality, it is executed on 38 established benchmark test functions and weighed against eight other optimization algorithms: a genetic algorithm (GA), a gravitational search algorithm (GSA), a grasshopper optimization algorithm (GOA), particle swarm optimization (PSO), teaching–learning-based optimization (TLBO), a grey wolf optimizer (GWO), a spotted hyena optimizer (SHO), as well as an emperor penguin optimizer (EPO). To test the SSA’s usability, it is employed on five engineering optimization problems. The SSA delivered better fitting results than the other algorithms in unimodal objective function, multimodal objective functions, CEC 2015, in addition to the optimization problems in engineering.