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Purpose: The present study aims to test the Quadratic Programming model for Optimal Portfolio selection empirically. Need for the Study: All the investors who buy financial products are motivated to obtain higher profits or, in other words, to maximise their returns. However, the high returns are often accompanied by higher risks, and avoiding such risks has become the primary concern for all investors. There is a great need for such a model to maximise profits and minimise risk, which can help design an investment portfolio with minimum risk and maximum return. The Quadratic Programming model is one such model which can be applied for selected shares to build an optimised portfolio. Methodology: This study optimises the stock samples using a two-level screening of correlation coefficient and coefficient of variation. The monthly closing prices of the NSE-listed Indian pharmaceutical stocks from December 2019 to January 2022 have been used as sample data. The Lagrange Multiplier method is used to apply the model to achieve the optimal portfolio solution. Based on the market reality, the transaction costs have also been considered. The Quadratic programming model is further optimised to achieve the optimal portfolio for the select stocks. Findings: The traditional portfolio theory and the modified quadratic model gives similar and consistent results. In other words, the modified quadratic model asserts the accuracy of the conventional portfolio model. The portfolio constructed in the present study gives a return much higher than the return of the benchmark portfolio of Nifty Fifty, indicating the usefulness of applying the Quadratic Programming model. Practical Implications: The construction of an optimal portfolio using the traditional or modified Quadratic model can help investors make rational investment decisions for better returns with lower risks. © 2023 by Chetna and Dhiraj Sharma.
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Nanofibers are a type of nanomaterial with a diameter ranging from ten to a few hundred nanometers with a high surface-to-volume ratio and porosity. They can build a network of high-porosity material with excellent connectivity within the pores, making them a preferred option for numerous applications. This review explores nanofibers from the synthesis techniques to fabricate nanofibers, with an emphasis on the technological applications of nanofibers like water and air filtration, photovoltaics, batteries and fuel cells, gas sensing, photocatalysis, and biomedical applications like wound dressing and drug delivery. The nanofiber production market has an expected compound annual growth rate (CAGR) of 6% and should reach around 26 million US $ in 2026. The limitations and potential opportunities for large-scale applications of nano-fibrous membranes are also discussed. We expect this review could provide enriched information to better understand Electrospun Polymer Nanofiber Technology and recent advances in this field. © 2023 Bentham Science Publishers.
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Background: Demonstration of safety is very significant with COVID-19 vaccines, not only for vaccine acceptance but also for trust in vaccination broadly. Therefore, it is crucial to understand various mistrusts regarding COVID-19 vaccine. The aim of the study was to investigate the knowledge and attitude regarding COVID-19 vaccine and its self-reported adverse effects among staffs and students of dental college in Himachal Pradesh. Materials and Methods: This was a descriptive, cross-sectional study conducted among the students and staff members of H. P. Government Dental College and Hospital, Shimla, Himachal Pradesh. All those who received the vaccine from January 22 to February 8, 2021, were included. The survey was divided into two sections. Section 1 of the questionnaire included 14 questions which were regarding the knowledge and attitude of COVID-19 vaccine, whereas Section 2 of the questionnaire included a table with 13 symptoms, and the participants were asked to check the postvaccine symptoms whichever they experienced with the duration. Results: Majority, i.e., 94 of the recipients had pain at the injection site which had a duration range of 24 h to 4-5 days. Of 111 participants, 88 had a symptom of chills lasting 8 h to 48-72 h. 74.5% were hesitant to treat patients due to COVID-19 infection worries. 75.4% considered the need to follow COVID-19 appropriate behaviors such as wearing mask, maintain social distancing, and not going to crowded places even after vaccination. Conclusion: Participants in this survey reported favorable attitudes toward vaccination. The commonly reported adverse effects of vaccination were pain at injection, chills, body ache, and fever.
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This paper emphasises the analysing sentiment of Indian citizens based on Twitter data using machine learning (ML) based approaches. The sentiment of about 1,51,798 tweets extracted from Twitter social networking and analysed based on tweets divided into six different segments, i.e., before lockdown, first lockdown, lockdown 2.0, lockdown 3.0, lockdown 4.0 and after lockdown (Unlock 1.0). Empirical results show that ML-based approach is efficient for sentiment analysis (SA) and producing better results, out of 10 ML-based models developed using N-Gram (N = 1,2,3,1-2,1-3) features for SA, linear regression model with term frequency - inverse term frequency (Tf-Idf) and 1-3 Gram features is outperforming with 81.35% of accuracy. Comparative study of the sentiment of the above six periods indicates that negative sentiment of Indians due to COVID-19 is increasing (About 4%) during first lockdown by 4.0% and then decreasing during lockdown 2.0 (34.10%) and 3.0 (34.12%) by 2% and suddenly increased again by 4% (36%) during 4.0 and finally reached to its highest value of 38.57% during unlock 1.0.
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Introduction: Crohn's disease (CD) and ulcerative colitis (UC) can be difficult to manage and, due to a lack of meaningful quality measures, patient (pt) care may vary by provider. To understand where gaps in care may exist for these pts, this study assessed specific healthcare resource utilization (HRU) and medication metrics that may be potential quality of care (QOC) indicators. Method(s): Using a large commercial US claims database (2019-2020), pts with CD or UC were identified. Potential QOC indicators were selected based on clinical guidelines and recommendations from measures of quality organizations and included CD or UC prevalence;gastroenterologist (GE) and IBD-related non-GE outpatient visits;IBD-related emergency department visits or hospitalizations;excessive steroid use (prednisone equivalent >=10 mg/day for >=60 consecutive days or a single prescription of >=600 mg prednisone);excessive steroid users on corticosteroid (CS)-sparing therapy;excessive steroid users with central dual-energy X-ray absorptiometry (DEXA) or osteoporosis pharmacologic treatment;use of targeted immunomodulators (TIMs) and oral mesalamine (CD only);imaging assessments;and assessment of inflammatory biomarkers. National percentages of pts achieving each metric are reported. Result(s): In total, 41,555 CD and 52,507 UC pts were identified in 2019, resulting in a 0.3% and 0.4% prevalence, respectively (Table). Over a third of CD pts (39.8%) and almost half of UC pts (45.5%) did not visit a GE in 2019. Around 10% CD pts, and up to 6.4% of UC pts, had IBD-related ED visits or hospitalizations. 17.1% CD and 14.5% UC pts were excessive steroid users, yet < 9% CD and UC pts, received DEXA scans and/or bone treatments. A third of excessive steroid users with CD (34.5%), and over half (53.0%) of those with UC, did not receive CS-sparing therapy. The rate of TIM use was over two times higher in CD vs UC pts (CD: 44.3%;UC: 18.9%). Despite evidence that mesalamine is ineffective in CD, 18.7% of pts with CD were prescribed it. Inflammatory biomarker level testing rates were < 50% in both CD and UC. Similar outcomes were reported in 2020, with lower HRU, possibly due to COVID-19. Conclusion(s): This analysis of QOC indicators highlights various areas for improvement that may provide better treatment outcomes and reduce HRU for pts with CD and UC. Future research is needed to assess outcomes in pts that are not being routinely monitored. (Table Presented).
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Background: The World Health Organization (WHO) designated SARS-CoV-2 infection as coronavirus disease 2019 (Covid-19).Due to the government implication of Covid-19 specific guideline of using mask, there could be a significant decrease in the allergic rhinitis. Objective(s): Present study aims to analyze the changes in the trends of nasal allergies from hilly regions of Himachal Pradesh following Covid-19 pandemic. Method(s): The prospective data obtained from January 2022 to November 2022 was compared from the retrospective data available between January 2019 to November 2019. Prospectively, a total of 596 patients were included in the study. All these patients underwent Skin prick tests for common allergens. All these patients also underwent testing for total IgE levels in biochemistry lab of the hospital by chemiluminescence method.The results were compared with retrospective dataof 728 age sex match patients. Result(s): A significant difference in the allergen sensitivity was observed. The number of patients who were sensitized during Covid was comparatively less than those during Pre covid period.Dust mite, Cockroach, Peanut and Wheat revealed a non-significant odds ratio indicating that they were not true predictors for sensitization and non-sensitization. Whereas Grass pollen, Mould mix and Pine mix revealed a significant odds ratio. Usage of mask found to have an impact on improvement in symptoms. Majority of the patients who did not use mask had no improvement in symptoms. Majority of the patients had high IgE levels in pre covid period whereas it was normal for majority of them during covid. Conclusion(s): In our study, allergic rhinitis incidence decreased throughout the pandemic period. After pandemic, there was a noticeably decreased level of sensitivity to grass pollen, mould, and pine mix. Use of face masks lead to significant decrease in symptoms of allergic rhinitis.Copyright © 2022, Anka Publishers. All rights reserved.
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The occurrence of Cryptosporidium species infection and its risk factors in neonatal goats is less explored. Also it is due to the fact that diseases like colibacillosis and neonatal viral enteritis complex caused by Group A rotaviruses and Bovine corona viruses can co-exist with Cryptosporidium and can lead to mixed infections and the latter is often overlooked. Therefore, in the current research we explored the cryptosporidial occurrence in neonatal goats of Mathura district of Uttar Pradesh, India. In this study, a total of 644 faecal samples were collected from neonatal goats at different villages and certain organized farms of Mathura district age-wise, season-wise and breed-wise, and were examined for Cryptosporidium based on modified Ziehl-Neelsen technique, conventional 18SSU rRNA nested PCR assay. The overall prevalence of Cryptosporidium infection in goats based on microscopy was 36.80% (237/644;p value <0.0001) and 18SSU rRNA nested PCR 52.95% (341/644;p value <0.0001) respectively. Cryptosporidium species typing was also done using 18SSU rRNA nested PCR-RFLP product using enzymes Mbo-II, Ssp-I and Vsp-I, which revealed species including C. parvum C. bovis, C. ryanae, C. hominis and C. andersoni. Also the infection was clinically associated based on age, gender and seasons to identify the causal relationships that precipitate the cryptosporidial infection in goat kids. Since mZN microscopy based screening requires expertise and may sometimes be confuse with other weak acid fast bodies and also due to low sensitivity, combination of diagnostic tests are used in this study to identify the best test combination that yields best statistical fit in terms of kappa-agreement and McNemar's test. Cryptosporidiosis is caused by an enteric protozoan parasite and the first report in sheep and goat was observed in early 1980s, with other important etiological agents for neonatal diarrhoea, mortality and morbidity in neonatal kids and lambs, responsible for economic losses.Copyright © 2023 Indian Veterinary Assocaition. All rights reserved.
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Recent research trends in the field image processing have focussed on challenges and few techniques for processing and classification tasks related to it. Image classification aims at classifying images based on several predefined categories. Several research works have been carried out to overcome shortcomings in image classification, nevertheless the output was restricted to the elementary low-level picture. Several deep neural network techniques are employed for image classification such as Convolutional Neural Network, Machine Learning Algorithms like Random Forest, SVM, etc. In this paper, we aim at designing a COVID-19 detection using the CNN model with support of Open-Source software such as Keras, Python, Google Colab, Google Drive, Kaggle, and Visual Studio for aggregate, design, create, train, visualize, and analyze bulk load of data on the cloud after programing a Deep neural network without a need for high-end processing hardware. We have made use of weights to test and analyse the accuracy, visualize and predict the condition of a lung using chest X-Rays at certain accuracy. This will help in identifying the problems of the patients at a faster rate, thus giving an appropriate treatment at an early stage itself to saving one life. © 2023 IEEE.
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More than one year since coronavirus disease 2019 was declared a deadly disease by World Health Organization, the deadly severe acute respiratory syndrome Coronavirus 2 continues to disrupt public life worldwide. Several nations have seen a two-wave design in revealed instances of COVID 19 pandemic, with a first wave of infection during early 2K20 followed by the ongoing second wave. An investigation of the predominance of COVID-19 in India from the first wave to the second wave was utilized to characterize critical contrasts, infection patterns, lethality, and therapeutic measures through extensive vaccination pan-India free of cost. The quantitative transmission brought about COVID-19, including meteorological boundaries and topographical locale information, was gathered using web search tools and available literature and substantiated by factual advanced numerical tools. Experimental information showed that the qualities of the infection impacts do change between the two-time frames. The examination between the first wave and second wave, where COVID-19 flare-ups were now turning out to be scourged, was contemplated. Contrasts in age reach and seriousness of the infection have been accounted for, albeit the relative qualities of the two waves remain to a great extent obscure. The present investigation recommends that variability in environmental temperature and moisture contents may not be the significant components influencing the COVID-19 mortality during different waves of infection. The second wave of COVID-19 is influencing a large portion of the world, and especially the middle age group person relies on the principal top. © 2022 by the authors.
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Silymarin, is a phytoactive constituent isolated from the fruits and seeds of Silybum maria-num L Gaetn.), also called milk thistle belonging to the family of Asteracease. The phytoactive has been used to treat several physiological disorders. The objective of this manuscript was to review the therapeutic prospective of silymarin due to its ability to treat several physiological disorders. The da-tabases such as Pubmed, Elsevier, and Google Scholar were reviewed for the investigations or reviews published related to the title. The discussion is focused on the immunomodulatory, chemopreventive, and anti-inflammatory mechanisms of silymarin in various metabolic and dermatological disorders. In addition, the review discusses the different therapeutic potentials of silymarin such as the management of the liver disorder, skin carcinogenesis, cardiovascular disorders, diabetes mellitus, neurodegenera-tive disorders, and several dermatological disorders such as melasma, anti-aging, acne, rosacea, atopic dermatitis, and psoriasis. Silymarin is safe even with a dose higher than the therapeutic dose. Si-lymarin had good potential for the safe and effective treatment of numerous metabolic and dermatological disorders. © 2023 Bentham Science Publishers.
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Purpose: This study aims to conduct a systematic literature review to investigate the mental health problems during COVID-19 and the role of nutrition in minimizing mental and health-related issues during COVID-19. Design/methodology/approach: A literature search was done electronically on April–May 2022 in the databases Google Scholar, PubMed and Cochrane Library, reviewing all the articles published in English. There were no limitations for the study (such as study design, region or any time frame). The quality assessment was done. The beginning database search picked out a total of 654 articles, 47 in PubMed, 575 in Google Scholar, 22 in Cochrane Library and 10 records from other sources. A total of 565 (duplicates found 89) were found after removing the duplicated articles, after reading the title and s were further decreased to 88 full-text articles. These 88 studies went for full-text analysis, which excluded 56 studies and generated a final 32 articles for systemic analysis. The quality of the included study for the systematic review was assessed in two ways: one is evidence-based and another one on the JBI checklist. Findings: People in social isolation and home quarantine suffer from severe anxiety, stress, depression, loneliness, anger and panic attack. During COVID-19, the vital role of diet and nutrients in mental health has been acknowledged and helps mitigate COVID-19 infection. Many studies showed stress and anxiety due to increased unhealthy eating and lifestyle practices. Originality/value: This review will explain the interlink between diet and mental health because what we eat and think is interconnected with the gut–brain axis. The dietary elements and psychobiotic help in improving the immune system and psychological distress during the pandemic. This paper describes the role of different nutrients, psychobiotics and phytochemicals, to minimize mental and health issues during the COVID-19 pandemic. This paper also contains a balanced diet plan to withstand COVID-19. © 2023, Emerald Publishing Limited.
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The coronavirus disease (COVID-19) was first detected in Wuhan, China, in the month of December 2019. Further, in March 2020, the COVID-19 epidemic was described by the World Health Organisation (WHO) as a global pandemic. COVID-19 quickly spread around the world in the following months, affecting about 2.5 million individuals by April 2020. World markets, including the pharmaceutical industry, were devastated by this pandemic. Although no specific solution for this emerging infectious disease is currently available, the pharmaceutical industry is helping policymakers meet unmet COVID-19 desires, ranging from research and advancement initiatives on possible prevention methods to the management of the supply chain of drugs in times of crisis. Changes in demand, commodity shortages, contact adjustments, etc., are hindering developments in the mechanism of technology, research and development and are putting an impact on the health market of COVID-19. Other implications of COVID-19 on the physical condition and pharmaceutical market may include acceptance delays, heading to self-sufficiency in the delivery chain, etc. In addition, the pharmaceutical markets are battling to sustain natural consumer flows, as the latest pandemic has had an effect on access to essential drugs at reasonable rates, which is the key priori-ty of all pharmaceutical systems.Copyright © 2022 Bentham Science Publishers.
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The disruptive effects of the COVID-19 pandemic has rapidly shifted how individuals navigate in cities. Governments are concerned that travel behavior will shift toward a car-driven and homeworking future, shifting demand away from public transport use. These concerns place the recovery of public transport in a possible crisis. A resilience perspective may aid the discussion around recovery–particularly one that deviates from pre-pandemic behavior. This paper presents an empirical study of London's public transport demand and introduces a perspective of spatial resilience to the existing body of research on post-pandemic public transport demand. This study defines spatial resilience as the rate of recovery in public transport demand within census boundaries over a period after lockdown restrictions were lifted. The relationship between spatial resilience and urban socioeconomic factors was investigated by a global spatial regression model and a localized perspective through Geographically Weighted Regression (GWR) model. In this case study of London, the analysis focuses on the period after the first COVID-19 lockdown restrictions were lifted (June 2020) and before the new restrictions in mid-September 2020. The analysis shows that outer London generally recovered faster than inner London. Factors of income, car ownership and density of public transport infrastructure were found to have the greatest influence on spatial patterns in resilience. Furthermore, influential relationships vary locally, inviting future research to examine the drivers of this spatial heterogeneity. Thus, this research recommends transport policymakers capture the influences of homeworking, ensure funding for a minimum level of service, and advocate for a polycentric recovery post-pandemic. © 2023 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.
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COVID-19 has greatly disturbed life in many ways and has changed the way we live. Various surveys have been conducted in different fields, and the teaching-learning process has been affected to a great extent. During this pandemic, various online tools and technologies have been available for guiding students without attending school. Many governments, corporations, and research fields have officially ordered to use of online media for the teaching-learning process. Platforms such as Google Meet, Microsoft Team, and Web-e-X have allowed and arranged for online video conferencing mediums to achieve the goal of the teaching-learning process. However, as mentioned above, there are some serious issues with the online teaching-learning process. These include problems with continuous network bandwidth during sessions, physical and mental presence in the class, difficulties handling mathematics classes, and the potential for non-sense activities that may disturb the entire class. In order to discover knowledge, I am using a new approach to data mining technology called CRISP-DM. This study addresses the effectiveness of online teaching mode and learning and the challenges faced by students and teachers who are taking online classes during COVID-19. According to this study, 88.2% of students did not have proper internet or technology facilities, 58.30% of students were not satisfied with online learning, 85.3% of students complained about eyesight issues from taking online classes on devices, and 50.01% of students were unable to manage university affairs © 2023 Manmohan Singh, Vinod Patidar, Shaheen Ayyub, Anita Soni, Monika Vyas Dharmendra Sharma and Amol Ranadive. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license
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The World Health Organization declared the Coronavirus disease in 2019;that was a very hard time for people, and every single day, a new crisis emerged. In that case, everyone shares their stories on the social media platform on a daily basis, but no one is sure that information is true or misleading, and that becomes a challenge to detect differences between them. And to tackle this problem, this paper has explored the veracity of social media stories using some machine learning models. The goal of this paper is to test three different BERT base pre-trained transform learning models (BERT, DistilBERT, and RoBERTa) on an English COVID-19 fake news dataset to detect the fake and true news separately. We explore their capability with precision, recall, and F1-score to achieve better results compared with the previous research. © 2022 IEEE.
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IntroductionRubber band ligation (RBL) is a procedure commonly performed in colorectal clinics for internal haemorrhoids. Overall, 90% of patients experience pain following RBL. We aimed to complete a feasibility randomised control trial assessing the role of topical anaesthetic before RBL of internal haemorrhoids.MethodsWe performed a prospective, single-centre, single blinded, randomised (1:1) control feasibility trial. Patients presenting with symptomatic haemorrhoids suitable for banding were randomised to undergo the procedure with local anaesthetic or without (control). Pain scores and vasovagal symptoms were assessed at 0 minutes, 30 minutes, 4 hours and 72 hours after the procedure. Primary outcome measures were recruitment rate, participant retention rate and patient and surgeon acceptability. Secondary outcome measures were pain scores up to 72 hours, vasovagal episodes, new use of analgesia and adverse outcomes.ResultsIn total, 35 patients (18 topical anaesthetic, group A;17 no anaesthetic gel, group B) were recruited. Mean recruitment rate was 11.7 participants per month. Thirty-three (94%) participants remained in the study until completion, with two patients lost to telephone follow-up. The treatment was acceptable for 35 (97%) eligible patients. One patient declined enrolment. The treatment was acceptable to all surgeons (100%). There was a significant difference in median pain scores of −2 (95% CI −4.0 to −1.0, p=0.0006) at the 30-minute time point only. There was no significant difference in vasovagal symptoms (p=0.10) or new analgesia use (p=0.85).ConclusionWe have shown that a phase III clinical trial is feasible for assessing the role of topical anaesthetic before RBL of internal haemorrhoids. We have demonstrated excellent patient recruitment and retention as well as patient and surgeon acceptability.
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COVID-19 is currently threatening the globe. SARS-CoV-2 is the cause of COVID-19, which spreads via droplets/airborne and direct contact. Health care workers (HCWs) are the front-line workers, which are directly involved in taking care of patients affected by COVID-19. HCWs are at a higher risk of infection during the caring of COVID-19 patients. This focused review high-lighted the higher risk for COVID-19 infection among health care professionals during close contact with patients and their preventive management in COVID-19 pandemic.Copyright © 2021 Bentham Science Publishers.
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During this pandemic and Post Pandemic Volatility of the world economics and the various war like situations in different parts of the world, the stock markets around the globe are on a roller coaster. The level of uncertainty, and emotional turmoil, has increased among Indian stock traders. This has led to an enormous level of increase of the stress that the traders are under, while continuing to trade. The main objective of this research study is to evaluate the impact of trading stress on the mental health, lifestyle, and financial condition of stock traders. This study includes respondents of required sample size. A purposive sampling technique was used to consider only active Indian stock traders for the study. A 5-point Likert scale questionnaire which was developed by Manda & Sana, 2021 was given to respondents using Google forms. The simple linear regression statistical method was used. The results indicate that general trading stress has an impact on the mental health, lifestyle and financial condition of stock traders.
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In difficult times, people turn to poetry, reading, and writing for solace and peace. In emotionally intense and traumatic times, people use poetry to process and understand the lived eyepieces. The havoc wreaked by the COVID-19 pandemic has affected the emotional and psychological well-being of individuals all across the world. Poetry has emerged as a savior in these difficult times. A phenomenon, "lockdown poems”, came into existence as individuals all across the globe processed and shared their lived experiences of isolation, pain, and suffering through poems. In the present paper, students of a management program process and share their experiences of the COVID-19 pandemic, the subsequent lockdowns, and their community work experience. Poetry as a therapeutic and hope-building tool is discussed in the paper along with the original poems written by the students. © 2023 National Association for Poetry Therapy.
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COVID-19 has posed formidable challenges including overwhelming bio-medical waste. Guidelines have been rapidly changing along with mounting pressure of waste generation. These challenges were managed by smart re-engineering of structure and processes for desired outcomes. Dedicated staff in PPE with appropriate training were deployed to collect waste using dedicated trolleys. A dedicated route plan was drawn with a dedicated lift meant for COVID-19. A new temporary holding area was created. Dedicated trucks with requisite labels were deployed to transport COVID-19 waste to CBWTF. Communication challenge was addressed through timely circulars, which were further reinforced and reiterated during various on-going training programs.Before the onset of COVID-19 pandemic Bio-Medical Waste generated was 1.93kg/Bed/Day and currently the quantum of COVID-19 biomedical waste generated is 7.76Kg/COVID Bed/Day. Daily COVID-19 waste generation data is maintained and uploaded in an android Application. Till date none of the worker handling COVID-19 waste has acquired Healthcare associated COVID-19 infection which reflects on the soundness of the new system and the infection control practices in the Institute. A responsive leadership harmonizing with a robust communication and training system has augmented timely re-engineering of structure and processes for better outcomes in the war on waste.