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In the prevention and treatment of various diseases, a variety of preparations based on medicinal plants are now generally acknowledged and well-documented. The main advantages of traditional medicine in underdeveloped nations are safety and affordability. As diferuloylmethane, curcumin is a naturally occurring polyphenol that is mostly produced in the rhizomes of plant roots. Curcumin has a long history of usage in conventional medicine, although its therapeutic effects and health advantages are still little understood. The therapeutic benefits of curcumin include the treatment of malignancies, neurodegenerative, ocular, and COVID diseases as well as inflammatory and digestive disorders, rheumatic and skin issues, and tumors. Apoptosis-related genes, cytokines, enzymes, and other targets have all been found in certain studies to be modulated by curcumin. Furthermore, little is known about the biological mechanisms that underlie these activities. We will examine some of the known molecular targets and biological processes of curcumin in this chapter. The processes through which curcumin functions in neuroprotection and/or mental health disorders will be covered in this chapter. We will also talk about curcumin's protective role in how bone may impact neurological function. © 2023 Nova Science Publishers, Inc.
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Objectives: The purpose of the short study was to know the type of sterilization and disinfection procedures followed by general practicing Prosthodontists, faculty, and postgraduate students in the state of Madhya Pradesh. Material and Methods: The questionnaire was prepared in google forms and was circulated in social media to students pursuing their MDS, Faculty, and Prosthodontists who are into private practice. The questionnaire mainly included questions that were related to sterilization and disinfection for Prosthodontic procedures which was done to check the sterilization and disinfection procedures followed in clinics and college. The questionnaire was circulated using Google forms and the filled forms were obtained. Statistical analysis was done with Statistical product and service solution (SPSS) version 21 software. Results:The participants were divided into groups of 3,Group 1-consists of MDS students,Group 2-consists of clinical practitioners, and Group 3-consists of academicians.A total of 500 participants took part which includes 242 MDS students, 97 academicians, and 162Prosthodontists who are doing private practice. Conclusion: A higher percentage of responses were from post-graduate students and MDS professionals which stated that most of them use proper sterilizationa and disinfection. This study shows that there is a strong need to implement periodic educational interventions and training programs on infection control practices for COVID-19 across dental care professionals.This study was done to find out what are the sterilization and disinfection protocols followed by Prosthodontists in their clinics and instititutions.
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GSK algorithm is based on the concept of how humans acquire and share knowledge through their lifespan. Discrete binary version of GSK named novel binary gaining sharing knowledge-based optimization algorithm (DBGSK) depends on mainly two binary stages: binary junior gaining sharing stage and binary senior gaining sharing stage with knowledge factor 1. These two stages enable BGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space. One of these practical applications is to optimally schedule the flights for residual stranded citizens due to COVID-19. The problem is defined for a decision maker who wants to schedule a multiple stepped trip for a subset of candidate airports to return the maximum number of residuals of stranded citizens remaining in listed airports while comprising the minimization of the total travelled distances for a carrying airplane. A nonlinear binary mathematical programming model for the problem is introduced with a real application case study. The case study is solved using DBGSK.
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This chapter is devoted to present a generalized model for scheduling multiple ambulance vehicles from multiple ambulance centers assigned to evacuate COVID-19 patients. The proposed formulation is a multi-objective multiple 0–1 mathematical model as a new application of the multi-objective multiple 0/1 knapsack problem. The scheduling aims at achieving the best utilization of the time shift as a planning time window. The best utilization of time is evaluated by a compromise between maximizing the number of evacuated people who might be infected with the virus to the isolation hospitals and maximizing the evacuated patients having higher relative priorities measured according to their health status. The complete mathematical model for the problem is formulated including the representation of binary decision variables, the problem constraints, and the multi-objective functions. The proposed multi-objective multiple ambulances model is applied to an illustrated case study in Great Cairo, Egypt, the case study aims at improving the scheduling of ambulance vehicles in the back-and-forth shuttle movements between patient locations and the available multiple isolation hospitals with multiple ambulance vehicles. The solution procedure is illustrated while two efficient solutions for the case study with different numbers of evacuated patients are obtained. The proposed mathematical model is so general that it can be applied to cases covering the whole Governorates and even the whole country all over the world. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Background: Unexpectedly and unfortunately the end of the year 2019 has proved to be the start of a deadliest era of Coronavirus disease 19. Spread of this lethal disease has remained uninhibited so far. How rapidly it has wrapped up the whole world is dangerously alarming. Aim: To determine frequency of Covid outcome in Covid patients with preexisting different co-morbid conditions. Methods: This descriptive study was conducted from July 2020 to January 2021 in two tertiary care hospital i.e. Services hospital, Lahore (Punjab) and hospital, Quetta (Baluchistan). After ethical approval and informed consent from the patients, data from PCR positive patients was recorded. The demographic parameters, travel or exposure history, duration of stay in the hospital and co morbidities including diabetes, hypertension, stroke and ischemic heart diseases of the patients were collected. Results: In our study, total 124 patients including 84(67.7%) male and 40(32.3%) female. The mean ages was 41.29±20.21 years, mean weight and height 83.46±15.1, 174.2±8.31. 82%patients were discharged, and 42%patients suffered death. Among the patients included in this study, 51(%) patients presented with diabetes, 55(%) patients presented with hypertension, 52% had ischemic heart diseases and 1.6% had stroke. Conclusion: The conclusion of this study, there is a significant impact of pre-existing co-morbidities on Covid outcomes. Thus, it can be inferred that by modifying the comorbidities, positive outcome can be observed.
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The spread of the novel coronavirus (COVID-19) has caused trillions of dollars of damages to the governments and health authorities by affecting the global economies. It is essential to identify, track and trace COVID-19 spread at its earliest detection. Timely action can not only reduce further spread but also help in providing an efficient medical response. Existing schemes rely on volunteer participation, and/or mobile traceability, which leads to delays in containing the spread. There is a need for an autonomous, connected, and centralized paradigm that can identify, trace and inform connected personals. We propose a novel connected Internet of Things (IoT) based paradigm using convolution neural networks (CNN), smart wearable, and connected E-Health to help governments resume normal life again. Our autonomous scheme provides three-level detection: Inter-object distance for social distancing violations using CNN, area-based monitoring of active smartphone users and their current state of illness using connected E-Health, and smart wearable. Our exhaustive performance evaluation identifies that the proposed scheme with CNN YOLOv3 achieves up to 90% mean average precision in detecting social distancing violations, as compared to existing YOLOv2 achieving 70% and faster R-CNN with 76%. Our evaluation also identifies that wearing protective gear reduces spread by 50%, and timely actions in the first hour can help avoid three times COVID-19 exposure. © 2021 Turkiye Klinikleri. All rights reserved.
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The aim of this paper is to introduce an improved strategy for controlling COVID-19 and other pandemic episodes as an environmental disinfection culture for public places. The scheduling aims at achieving the best utilization of the available working day-time hours, which is calculated as the total consumed disinfection times minus the total loosed transportation times. The proposed problem in network optimization identifies a disinfection group who is likely to select a route to reach a subset of predetermined public places to be regularly disinfected with the most utilization of the available day-working hours. A Nonlinear Binary Model is introduced with a detailed real application case study involving improving the scheduling of Coronavirus disinfection process for some Educational Institutions as an example of crowded public places in Cairo, Egypt. The case study mathematical model is solved using a novel Discrete Binary Gaining-Sharing knowledge-based optimization algorithm (DBGSK). The results of this study show that the novel optimization algorithm can efficiently solve the proposed Problem. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The psychological impact on marriage and family counsellors during the outbreak of COVID-19 pandemic is an important deliberation. This study aimed to examine the relationships between burnout, resilience, and self-care among marriage and family counsellors in Malaysia. A total of 96 marriage and family counsellors in Malaysia were selected by using simple random sampling technique to participate in the present study. Data were collected by using three self-report instruments to measure the burnout, resilience and self-care. The findings demonstrated significant relationships between the constructs in which burnout and resilience as well as burnout and self-care were negatively correlated. Self-care and resilience were positively correlated. Multiple regression analysis revealed that burnout could not be significantly predicted by self-care and resilience. Findings of the study implied that emphasis must be given to burnout, resilience, and self-care and among marriage and family counsellors to enhance their personal and professional development.
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During the current Covid-19 pandemic, the social relationship between humans has changed. As noticed, lockdowns and social distancing have become new norms. Unavoidably, counselling services were also affected with social distancing rules, especially in the school setting. Thus, online counselling or e-counselling has begun to gain in popularity, allowing counsellors to offer their services in an alternative way. In order to evaluate the suitability of e-counselling during the current pandemic, a client's satisfaction towards e-counselling and face-to-face counselling needs to be investigated. This study aims to explore the effectiveness of these two counselling approaches using the level of the client's satisfaction and its implication towards counselling practises during the outbreak. Quantitative data were obtained using the Client's Satisfaction Inventory Short-Form (CSI-SF) questionnaire. The experimental design consisted of a total of 60 study subjects in two groups, namely the control group using the face-to-face Counselling method and the experimental group using the e-Counselling method. Based on the results, the difference in mean score showed that the mean difference in the experimental group was slightly higher than the control group. This finding indicates that e-counselling clients have a higher satisfaction compared to the face-to-face approach. The implications of this data are discussed on the role of school, school counsellor, and the government in enhancing the service of e-counselling during the current pandemic.
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Many application problems are formulated as nonlinear binary programming models which are hard to be solved using exact algorithms especially in large dimensions. One of these practical applications is to optimally distribute protective materials for the newly emerged COVID-19. It is defined for a decision-maker who wants to choose a subset of candidate hospitals comprising the maximization of the distributed quantities of protective materials to a set of chosen hospitals within a specific time shift. A nonlinear binary mathematical programming model for the problem is introduced with a real application case study;the case study is solved using a novel discrete binary gaining-sharing knowledge-based optimization algorithm (DBGSK). The solution algorithm proposes a novel binary adaptation of a recently developed gaining-sharing knowledge-based optimization algorithm (GSK) to solve binary optimization problems. GSK algorithm is based on the concept of how humans acquire and share knowledge through their life span. Discrete binary version of GSK named novel binary gaining-sharing knowledge-based optimization algorithm (DBGSK) depends mainly on two binary stages: binary junior gaining-sharing stage and binary senior gaining-sharing stage with knowledge factor 1. These two stages enable DBGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space. © Springer Nature Switzerland AG 2021.
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The biological diversity of SARS-CoV-2 was assessed by investigating the genetic variations of the spike glycoprotein of patients with COVID-19 in Iraq. Sequencing identified fifteen novel nucleic acid variations with a variety of distributions within the investigated samples. The electropherograms of all identified variations showed obvious co-infections with two different viral strains per sample. Most samples exhibited three nonsense single nucleotide polymorphism (SNPs), p.301Cdel, p.380Ydel and p.436del, which yielded three truncated spike glycoproteins, respectively. Network and phylogenetic analyses indicated that all viral infections were derived from multiple viral origins. Results inferred from the specific clade-based tree showed that some viral strains were derived from European G-clade sequences. Our data demonstrated the absence of single-strain infection among all investigated samples in the studied area, which entails a higher risk of SARS-CoV-2 in this country. The identified high frequency of truncated spike proteins suggests that defective SARS-CoV-2 depend on helper strains possessing intact spikes during infection. Alternatively, another putative ACE2-independent route of viral infection is suggested. To the best of our knowledge, this is the first report to describe co-infection with multiple strains of SARS-CoV-2 in patients with COVID-19.
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Following the COVID 19 pandemic outbreak, mental health and wellbeing of employed women are at stake. The Movement Control Order (MCO) has forced the majority employed women to play multiple roles in a 24/7 situation with little break if ever for her own self-care. Therefore, we propose a new employment scheme called DAMAI (Domestic Assistant Malaysian Affectionate Initiative) along with mobile and web applications online housekeepers and caregivers to improve the well-being of working women by including computer implemented genogram as mental health screening. To provide a comprehensive solution to the problem, human ecological theory, family systems theory and women well-being model are discussed. While the theory of planned behavior (TBP) and technology acceptance models are referred to in the development of web and mobile applications called MyDAMAI HOME. Finally, the presentation of the Mock Up MyDAMAI Home mark the end this paper with conclusion. © 2020 by Advance Scientific Research. This is an open-access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)