Search

Patients suffering from body integrity dysphoria (BID) desire to become disabled, arising from a mismatch between the desired body and the physical body. We focus here on the most common variant, characterized by the desire for amputation of a healthy limb. In most reported cases, amputation of the rejected limb entirely alleviates the distress of the condition and engenders substantial improvement in quality of life. Since BID can lead to life-long suffering, it is essential to identify an effective form of treatment that causes the least amount of alteration to the person’s anatomical structure and functionality. Treatment methods involving medications, psychotherapy, and vestibular stimulation have proven largely ineffective. In this hypothesis article, we briefly discuss the characteristics, etiology, and current treatment options available for BID before highlighting the need for new, theory driven approaches. Drawing on recent findings relating to functional and structural brain correlates of BID, we introduce the idea of brain–computer interface (BCI)/neurofeedback approaches to target altered patterns of brain activity, promote re-ownership of the limb, and/or attenuate stress and negativity associated with the altered body representation.

INTRODUCTION Brachial plexus block is a regional anesthesia technique that is sometimes employed as an alternative or as an adjunct to general anesthesia for surgery of the upper extremity. This technique involves the injection of local anesthetic agents in close proximity to the brachial plexus, temporarily blocking the sensation and ability to move the upper extremity. OBJECTIVES To compare time of onset and duration of sensory and motor block between two groups. To compare peri-operative and post-operative analgesia between two groups MATERIAL AND METHOD Orthopaedic operation theatre, post-anaesthesia care unit, orthopaedic post- operative ward of Nil Ratan Sircar Medical College and Hospital. All the ASA physical status I and II patients of either sex, age between 18-60 years undergoing upper limb orthopaedic surgery under supraclavicular brachial plexus block. CONCLUSION Addition of Dexmedetomidine to ropivacaine in supraclavicular brachial plexus block significantly prolongs the duration of analgesia and motor block in patients undergoing upper limb surgeries and is a remarkably safe and cost effective method of providing post-operative analgesia.

There is accumulating evidence of the neurological and neuropsychiatric features of infection with SARS-CoV-2. In this systematic review and meta-analysis, we aimed to describe the characteristics of the early literature and estimate point prevalences for neurological and neuropsychiatric manifestations. We searched MEDLINE, Embase, PsycINFO and CINAHL up to 18 July 2020 for randomised controlled trials, cohort studies, case-control studies, cross-sectional studies and case series. Studies reporting prevalences of neurological or neuropsychiatric symptoms were synthesised into meta-analyses to estimate pooled prevalence. 13 292 records were screened by at least two authors to identify 215 included studies, of which there were 37 cohort studies, 15 case-control studies, 80 cross-sectional studies and 83 case series from 30 countries. 147 studies were included in the meta-analysis. The symptoms with the highest prevalence were anosmia (43.1% (95% CI 35.2% to 51.3%), n=15 975, 63 studies), weakness (40.0% (95% CI 27.9% to 53.5%), n=221, 3 studies), fatigue (37.8% (95% CI 31.6% to 44.4%), n=21 101, 67 studies), dysgeusia (37.2% (95% CI 29.8% to 45.3%), n=13 686, 52 studies), myalgia (25.1% (95% CI 19.8% to 31.3%), n=66 268, 76 studies), depression (23.0% (95% CI 11.8% to 40.2%), n=43 128, 10 studies), headache (20.7% (95% CI 16.1% to 26.1%), n=64 613, 84 studies), anxiety (15.9% (5.6% to 37.7%), n=42 566, 9 studies) and altered mental status (8.2% (95% CI 4.4% to 14.8%), n=49 326, 19 studies). Heterogeneity for most clinical manifestations was high. Neurological and neuropsychiatric symptoms of COVID-19 in the pandemic’s early phase are varied and common. The neurological and psychiatric academic communities should develop systems to facilitate high-quality methodologies, including more rapid examination of the longitudinal course of neuropsychiatric complications of newly emerging diseases and their relationship to neuroimaging and inflammatory biomarkers.

SUMMARYBackgroundThe nature and extent of persistent neuropsychiatric symptoms after COVID-19 are not established. To help inform mental health service planning in the pandemic recovery phase, we systematically determined the prevalence of neuropsychiatric symptoms in survivors of COVID-19.MethodsFor this pre-registered systematic review and meta-analysis (PROSPERO ID CRD42021239750) we searched PubMed, EMBASE, CINAHL and PsycINFO to 20th February 2021, plus our own curated database. We included peer-reviewed studies reporting neuropsychiatric symptoms at post-acute or later time-points after COVID-19 infection, and in control groups where available. For each study a minimum of two authors extracted summary data. For each symptom we calculated a primary pooled prevalence using generalised linear mixed models. Heterogeneity was measured withI2. Subgroup analyses were conducted for COVID-19 hospitalisation, severity, and duration of follow-up.FindingsFrom 2,844 unique titles we included 51 studies (n=18,917 patients). The mean duration of follow-up after COVID-19 was 77 days (range 14-182 days). Study quality was generally moderate. The most frequent neuropsychiatric symptom was sleep disturbance (pooled prevalence=27·4% [95%CI 21·4- 34·4%]), followed by fatigue (24·4% [17·5-32·9%]), objective cognitive impairment (20·2% [10·3-35·7%]), anxiety (19·1%[13·3-26·8%]), and post-traumatic stress (15·7% [9·9-24·1%]). Only two studies reported symptoms in control groups, both reporting higher frequencies in Covid-19 survivors versus controls. Between-study heterogeneity was high (I2=79·6%-98·6%). There was little or no evidence of differential symptom prevalence based on hospitalisation status, severity, or follow-up duration.InterpretationNeuropsychiatric symptoms are common and persistent after recovery from COVID-19. The literature on longer-term consequences is still maturing, but indicates a particularly high frequency of insomnia, fatigue, cognitive impairment, and anxiety disorders in the first six months after infection.FundingJPR is supported by the Wellcome Trust (102186/B/13/Z).IK is funded through the NIHR (Oxford Health Biomedical Research Facility, Development and Skills Enhancement Award) and the Medical Research Council (Dementias Platform UK and Deep and Frequent Phenotyping study project grants).HH is funded by the German Research Foundation (DFG, Grant: HO 1286/16-1). The funders played no role in the design, analysis or decision to publish.RESEARCH IN CONTEXTEvidence before this studyNeuropsychiatric symptoms like cognitive impairment, fatigue, insomnia, depression and anxiety can be highly disabling. Recently there has been increasing awareness of persistent neuropsychiatric symptoms after COVID-19 infection, but a systematic synthesis of these symptoms is not available. In this review we searched five databases up to 20th February 2021, to establish the pooled prevalence of individual neuropsychiatric symptoms up to six months after COVID-19.Added value of this studyThis study establishes which of a range of neuropsychiatric symptoms are the most common after COVID-19. We found high rates in general, with little convincing evidence that these symptoms lessen in frequency during the follow-up periods studied.ImplicationsPersistent neuropsychiatric symptoms are common and appear to be limited neither to the post-acute phase, nor to recovery only from severe COVID-19. Our results imply that health services should plan for high rates of requirement for multidisciplinary services (including neurological, neuropsychiatric and psychological management) as populations recover from the COVID-19 pandemic.

BACKGROUND Healthcare Information for All (HIFA) is a multidisciplinary global campaign consisting of more than 20,000 members worldwide committed to improving the availability and use of health care information in low- and middle-income countries (LMICs). During the COVID-19 pandemic, online HIFA forums saw a tremendous amount of discussion regarding the lack of information about COVID-19, the spread of misinformation, and the pandemic’s impact on different communities. OBJECTIVE This study aims to analyze the themes and perspectives shared in the COVID-19 discussion on English HIFA forums. METHODS Over a period of 8 months, a qualitative thematic content analysis of the COVID-19 discussion on English HIFA forums was conducted. In total, 865 posts between January 24 and October 31, 2020, from 246 unique study participants were included and analyzed. RESULTS In total, 6 major themes were identified: infodemic, health system, digital health literacy, economic consequences, marginalized peoples, and mental health. The geographical distribution of study participants involved in the discussion spanned across 46 different countries in every continent except Antarctica. Study participants’ professions included public health workers, health care providers, and researchers, among others. Study participants’ affiliation included nongovernment organizations (NGOs), commercial organizations, academic institutions, the United Nations (UN), the World Health Organization (WHO), and others. CONCLUSIONS The themes that emerged from this analysis highlight personal recounts, reflections, suggestions, and evidence around addressing COVID-19 related misinformation and might also help to understand the timeline of information evolution, focus, and needs surrounding the COVID-19 pandemic.

ObjectivesThere is accumulating evidence of the neurological and neuropsychiatric features of infection with SARS-CoV-2. In this systematic review and meta-analysis, we aimed to describe the characteristics of the early literature and estimate point prevalences for neurological and neuropsychiatric manifestations.MethodsWe searched MEDLINE, Embase, PsycInfo and CINAHL up to 18 July 2020 for randomised controlled trials, cohort studies, case-control studies, cross-sectional studies and case series. Studies reporting prevalences of neurological or neuropsychiatric symptoms were synthesised into meta-analyses to estimate pooled prevalence.Results13,292 records were screened by at least two authors to identify 215 included studies, of which there were 37 cohort studies, 15 case-control studies, 80 cross-sectional studies and 83 case series from 30 countries. 147 studies were included in the meta-analysis. The symptoms with the highest prevalence were anosmia (43.1% [35.2—51.3], n=15,975, 63 studies), weakness (40.0% [27.9—53.5], n=221, 3 studies), fatigue (37.8% [31.6—44.4], n=21,101, 67 studies), dysgeusia (37.2% [30.0—45.3], n=13,686, 52 studies), myalgia (25.1% [19.8—31.3], n=66.268, 76 studies), depression (23.0 % [11.8—40.2], n=43,128, 10 studies), headache (20.7% [95% CI 16.1—26.1], n=64,613, 84 studies), anxiety (15.9% [5.6—37.7], n=42,566, 9 studies) and altered mental status (8.2% [4.4—14.8], n=49,326, 19 studies). Heterogeneity for most clinical manifestations was high.ConclusionsNeurological and neuropsychiatric symptoms of COVID-19 in the pandemic’s early phase are varied and common. The neurological and psychiatric academic communities should develop systems to facilitate high-quality methodologies, including more rapid examination of the longitudinal course of neuropsychiatric complications of newly emerging diseases and their relationship to neuroimaging and inflammatory biomarkers.

Non-communicable diseases (NCDs) is an umbrella term used to describe a cluster of diseases constituting of Cardiovascular and Chronic Respiratory complications, Cancer, Diabetes and Mental Health conditions. The World Health Organisation (WHO) estimates that nearly 71% of all deaths worldwide (41 million people) can be attributed to inadequate and untimely intervention for Non-communicable diseases. Out of the 41 million people affected, the most vulnerable groups placed at the epicentre to face the repercussions of the growing impacts of NCDs are children, young people, people of lower socio-economic status (SES) and those belonging to lower and lower-middle income countries (LMICs). We call for policies to be more youth-inclusive and suggest further recommendations to incorporate youth voices and interventions to combat the global burden of NCDs as young people constitute of a major demographic widely affected by NCDs yet remain underrepresented in their say on tackling NCDs across local, regional, national and global levels.

Assistive technologies are used to enhance the day-to-day functionality of people with disabilities by improving their quality of life and by reducing the impact of disability in their lives. Various socio-economic, cultural, contextual, medical, personal, and family-related factors determine the feasibility and outcomes of using assistive technologies. While various forms of assistive technologies are being widely used for rehabilitation, recreational, or personal purposes around the world many still remain inaccessible and vastly unaffordable in countries around the world. Literature suggests that, when comparing high income countries with low and lower-middle income countries, differences among the longevity, availability, ease of users, affordability and, most importantly, the recognition of the need for an assistive technology, are common, with those measures lagging in low and lower-middle income countries. Certain targeted interventions have been suggested to provide insight into how discrepancies in promoting the use of assistive technologies between developed and developing nations can be minimised with the goal of reducing the global impacts of disability.

This paper manages with the modelling of quadruple junction solar cell (qjsc) constructed by using the semiconductor material of AlGaInP-GaAs-GaInAs-Ge at a particular value solar irradiance, temperature. Comparison of output I-V and P-V curve of quadruple junction solar cell is done with triple junction solar cell made up of InGaP-InGaAs-Ge semiconductor material and also single junction solar cell (sjsc) made of a Ge semiconductor by using MATLAB/SIMULINK. It has been found higher value of output voltage and power in quadruple junction solar cell as compared to single, dual or triple junction solar cell. The above described quadruple junction solar cell is made by using the material having a same lattice structure which helps to ease the flow of current in all the four junctions and analysis is done at solar irradiance (1000-800-500) W/cm2. The whole analysis is done through pessimistic approach on the basis of the single exponential model.

Background: People with neurological dysfunction have been significantly affected by the ongoing coronavirus disease 2019 (COVID-19) crisis in receiving adequate and quality rehabilitation services. There are no clear guidelines or recommendations for rehabilitation providers in dealing with patients with neurological dysfunction during a pandemic situation especially in low- and middle-income countries. The objective of this paper was to develop consensus-based expert recommendations for in-hospital based neurorehabilitation during the COVID-19 pandemic for low- and middle-income countries based on available evidence. Methods: A group of experts in neurorehabilitation consisting of neurologists, physiotherapists and occupational therapists were identified for the consensus groups. A scoping review was conducted to identify existing evidence and recommendations for neurorehabilitation during COVID-19. Specific statements with level 2b evidence from studies identified were developed. These statements were circulated to 13 experts for consensus. The statements that received ≥80% agreement were grouped in different themes and the recommendations were developed. Results: 75 statements for expert consensus were generated. 72 statements received consensus from 13 experts. These statements were thematically grouped as recommendations for neurorehabilitation service providers, patients, formal and informal caregivers of affected individuals, rehabilitation service organizations, and administrators. Conclusions: The development of this consensus statement is of fundamental significance to neurological rehabilitation service providers and people living with neurological disabilities. It is crucial that governments, health systems, clinicians and stakeholders involved in upholding the standard of neurorehabilitation practice in low- and middle-income countries consider conversion of the consensus statement to minimum standard requirements within the context of the pandemic as well as for the future.

The recent outbreak of COVID-19, declared a pandemic, has affected medical education globally. The scenario is no different for medical students in India as they find themselves at a crossroads in their careers, with clinical and elective postings called off. Missing out on the opportunity to learn from “first-hand” clinical observation stands to threaten the quality of medical education and learning procured by Indian medical students which is extremely essential to deal with the vast patient load that awaits them in their impending future as healthcare professionals. Is the Indian medical education system being able to cope with the challenges imposed by the increasing burden of COVID-19? The authors propose few administrative and on-ground interventions that must seek to work collectively with all government and private medical institutions in order to help students/interns and residents in coping with stress, anxiety or academic losses incurred due to the pandemic.

This paper introduces the reproduction of managed DC voltage sources. The DC source primary supply is a sun based PV demonstrate which creates a flimsy yield voltage. The model is done with the end goal that the info parameters are the light and the temperature and the yield is the unsteady voltage. The yield current is an imperative parameter to accomplish exact yield voltage, that current is estimated and encouraged to the contribution of the model to be utilized for condition assessment. Voltage direction i.e regulation is expected to make the created voltage usable. A straightforward buck converter with PID controller used to manage the yield voltage. SIMULINK is utilized to mimic the general framework. Reenactment result is given to confirm the operation of the model. The experimental and simulation results demonstrate the effectiveness of the presented analysis, design, and implementation

In the world of widely available mobile phones and tablets, electronic field guides for the identification of different biodiversity components are emerging as a reality. This project aims to classify butterfly images based on their species using a convolutional neural network in TensorFlow. The goal is to get an accuracy of 80% or above on a butterfly data set. The result of this project includes a testing accuracy of 0.47 by a model that was trained for only 18 hours, i.e. partially trained. Another additional goal is to show that a neural network once trained can be used to identify the species of the butterfly in rather short time, which will make identification and tracking of different butterfly species much easier and efficient.

This paper manages with the modelling of quadruple junction solar cell (qjsc) constructed by using the semiconductor material of AlGaInP-GaAs-GaInAs-Ge at a particular value solar irradiance, temperature. Comparison of output I-V and P-V curve of the quadruple junction solar cell is done with triple junction cell made of semiconductor material InGaP-InGaAs-Ge and single junction solar cell (sjsc) made of a Ge semiconductor by using MATLAB/SIMULINK. It has been found a higher value of output voltage and power in quadruple junction solar cell as compared to single or triple junction solar cell. The above described quadruple junction solar cell is made by using the material having a same lattice structure which helps to ease the flow of current in all the four junctions and analysis is done at solar irradiance (1000-800-500) w/cm2. The whole analysis is done through pessimistic approach on the basis of the single exponential

Since the first decade of this century, the focus of research institutes has shifted to developing efficient renewable energy sources. Solar radiation is one of the primary sources of energy on this planet. For this reason photovoltaic (PV) system remains a popular subject of study. Due to its non-linear I-V and P-V characteristics, the PV Generator output varies with both solar radiation and temperature. In order to compensate for the low conversion efficiency, various MPPT algorithms are developed that provide automated control over power interfaces to generate optimal power efficiency. It is used to adjust the panels in order to promote solar operating voltage close to MPP under changing day to day weather conditions. There are libraries that simulate the results of such MPPT algorithms in MATLAB and Python. This paper aims to summarize the use of Python as a tool for forecasting and simulation method for solar energy resource and possible work that can be done to increase the efficiency of the same using ML.