ABSTRACT
The global coronavirus pandemic (COVID-19) started in 2020 and is still ongoing today. Among the numerous insights the community has learned from the COVID-19 pandemic is the value of robust healthcare inventory management. The main cause of many casualties around the world is the lack of medical resources for those who need them. To inhibit the spread of COVID-19, it is therefore imperative to simulate the demand for desirable medical goods at the proper time. The estimation of the incidence of infections using the right epidemiological criteria has a significant impact on the number of medical supplies required. Modeling susceptibility, exposure, infection, hospitalization, isolation, and recovery in relation to the COVID-19 pandemic is indeed crucial for the management of healthcare inventories. The goal of this research is to examine the various inventory policies such as reorder point, periodic order, and just-in-time in order to minimize the inventory management cost for medical commodities. To accomplish this, a SEIHIsRS model has been employed to comprehend the dynamics of COVID-19 and determine the hospitalized percentage of infected people. Based on this information, various situations are developed, considering the lockdown, social awareness, etc., and an appropriate inventory policy is recommended to reduce inventory management costs. It is observed that the just-in-time inventory policy is found to be the most cost-effective when there is no lockdown or only a partial lockdown. When there is a complete lockdown, the periodic order policy is the best inventory policy. The periodic order and reorder policies are cost-effective strategies to apply when social awareness is high. It has also been noticed that periodic order and reorder policies are the best inventory strategies for uncertain vaccination efficacy. This effort will assist in developing the best healthcare inventory management strategies to ensure that the right healthcare requirements are available at a minimal cost. © 2023 by the authors.
ABSTRACT
COVID-19 has developed chaos and uncertainty for small and medium enterprises (SMEs) causing mass downsizing. Under such uncertainty, innovation is key to survival and agility to growth. This study examines role of knowledge coupling and business process digitization (BPD) in sustaining innovation through market capitalizing agility (MCA) besides downsizing strategy. Data have been collected from top and mid management of Chinese manufacturing SMEs and analyzed with knowledge-based view and self-tuning model through Smart-PLS 4. Knowledge coupling positively contributes to MCA and innovation irrespective of downsizing strategy. Effect of BPD on innovation performance is same;however, insignificant on MCA in no-downsizing sample. Likewise, MCA positively influences innovation performance and positively mediates between knowledge coupling (BPD) and innovation performance only during downsizing. This study is first of its kind to establish mediating effect of MCA between knowledge coupling (BPD) and innovation performance during downsizing phase and offers significant theoretical and practical implications. JEL Classification: J63, O31
ABSTRACT
Covid-19 pandemic has caused crisis and uncertainty which adversely influenced innovation performance of small and medium enterprises (SMEs). Innovation is a primary source of survival and growth in SMEs;therefore, this study aims to develop and empirically analyse conceptual model that sustains innovation performance of SMEs during the pandemic. This study integrates knowledge-based view (KBV) with a self-tuning model to examine Chinese manufacturing SMEs. Survey data of 306 responses were collected from the top and mid management and analysed through Smart-PLS 3. Results indicate a positive effect of knowledge coupling on innovation performance;besides, ambidexterity and market capitalising agility (MCA) positively mediate between knowledge coupling and SME innovation performance. This study contributes to KBV, self-tuning, strategy, innovation and crisis management literature. To practitioners, this study advises developing dynamic capabilities to sustain innovations during pandemic crisis. This is the earliest empirical examination to mediate the effect of knowledge coupling on innovation performance through ambidexterity and MCA during a crisis.
ABSTRACT
Objective: The increasing frequency of PRES during the COVID-19 pandemic, and a possible causal relationship between the two necessitates the review of available literature so that knowledge of practicing physicians is up to date in terms of the likely presentation and management of this clinical association. Background: The surge in COVID-19 cases is bringing with it an array of unique neurological manifestations. Clinicians report a possible association with Posterior Reversible Encephalopathy Syndrome (PRES). PRES is an otherwise rare disease that usually arises as part of greater complications such as hypertension and renal failure. Design/Methods: We conducted a systematic literature search on four databases namely PubMed/MEDLINE, Cochrane, Google Scholar, and ScienceDirect. A total of 34 articles describing 56 cases of PRES in COVID-19 were selected as a part of this review. Results: The mean age of the patients was 56.6 ± 15.3 years. The most common clinical presentation of PRES was altered mental status (53.6%) followed by seizures (46.4%) and visual disturbances (23.2%) while hypertension (28.6%) and diabetes mellitus (23.2%) were the most commonly reported predisposing comorbidities. 16.1% of the patients were treated for COVID19 with Tocilizumab, another predisposing factor for PRES. Symptomatic management was employed in most of the cases and 44 patients (78.5%) were reported to fully or partially recover. Conclusions: When COVID-19 is developed on a background of hypertension and diabetes, there is a possibility that all these factors play an additive role in the development of PRES. Therefore, neurologists and radiologists must consider PRES as a probable diagnosis when encountering COVID-19 patients with suggestive clinical and radiographic findings. The risk of using tocilizumab, a potential trigger of PRES, must be weighed against its potential benefit in mitigating the COVID-19 cytokine storm. Timely diagnosis and treatment report a good prognosis.
ABSTRACT
AIM: Endoscopic Ultrasound (EUS) is well-established mode of intervention for tissue acquisition in solid organs with rapid on-site evaluation (ROSE). In the Covid-19 era implementation of infection control mechanisms has led modified hybrid technique to get high diagnostic yield for tissue sampling. Combination of Covid-19 SOPs and tissue acquisition method outline this hybrid technique to get high diagnostic Yield.We share our initial experience of EUS cases performed with this approach without ROSE. METHODS: All 84 cases who underwent EUS guided biopsy from June 2020 till December 2021 were included. The Procedure was done in a negative pressure room with all SOPs as per institutional guidelines for patient and staff safety with a minimum number of persons during procedure. RESULTS: Among these cases, 55 were male, mean age 56 years (range 22-90), Mean duration of procedure 25 min mean (10-90 min). 63 came for organ targeted for malignant pathology include pancreas 35, liver 02, lymph nodes 17, subepithelial lesions 06, mediastinal lesions 08, common-bile duct/gall bladder 04. 17 cases had a multi-targeted biopsy for the additional staging of disease. The number of 'passes' with the needle was average 02 with single pass 17, two pass 39, three passes 11, multitarget single pass in 17. Needle size (Franseen design) used for procedures was 22G in 78 cases and 25G in 6. Common tissue diagnoses include pancreatic adenocarcinoma 26, neuroendocrine tumours 04, tuberculosis 05, gastrointestinal stromal tumours 02, leiomyoma 03, lymphoma 03, metastatic renal cell carcinoma 04, squamous cell carcinoma 04, cholangiocarcinoma/ gall bladder adenocarcinoma 07, Sarcoma 02 and solid pseudopapillary epithelial neoplasm of pancreas (SPEN) 01. There were no immediate or early complications in all cases. CONCLUSIONS: Hybrid EUS in Covid 19 Era has emerged as a useful/cost-effective and safe approach to get tissue yield without the need for ROSE.
ABSTRACT
In this research, by analysis the problem for detection of corona virus (COVID-19) in person by fuzzy method.as the virus is spreading very quickly in last few months around the world. So, in this all scenario the artificial intelligence is trying to involve helping the world for detection and predication of virus with different method and its algorithms. The algorithms that are used for solving out this problem is many like form fuzzy or Neural Network. But here in this paper trying to solve out this by fuzzy implementation and its techniques on the basis of some inputs and get the output as result or prediction level for our problem. © 2022 IEEE.
ABSTRACT
Indigenous communities throughout the globe respond to COVID-19 by their traditional medicinal systems as primary health care. Our lab was part of an international study that discusses the outcomes of a rapid response, preliminary survey during the first phase of the pandemic among social and community contacts in five metropolises heavily affected by the COVID-19 health crisis (Wuhan, Milan, Madrid, New York, and Rio de Janeiro) and in twelve rural areas or countries initially less affected by the pandemic (Appalachia, Jamaica, Bolivia, Romania, Belarus, Lithuania, Poland, Georgia, Turkey, Pakistan, Cambodia, and South Africa). Primarily, people have relied on teas and spices (“food-medicines”) to prevent and mitigate its symptoms. Urban diasporas and rural households seem to have repurposed homemade plant-based remedies that they use on daily basis to treat the flu and other respiratory problems and hence consider among the healthy foods. The most remarkable shift in many areas has been increased in the consumption of ginger and garlic, followed by onion, turmeric, lemon, chamomile, black tea, nettle, chili pepper, and apple. This study serves as a baseline for future systematic ethnobotanical studies countering COVID-19 and other vicious types of viruses. It aims to inspire in-depth research on how use patterns of plant-based foods and beverages, both “traditional” and “new,” are changing during and after the COVID-19 pandemic. Our reflections in this study call attention to the importance of ethnobiology, ethnomedicine, and ethno-gastronomy research into domestic health care strategies for improving community health. Some of these economically important plants are suggested to be extensively analyzed experimentally, for active ingredients, phytochemicals, and the precursor of vaccines and probable remedy of SARS including COVID-19. © Pakistan Academy of Sciences.
ABSTRACT
The literature on sustainable tourism is scant, particularly in the least developed countries. Very few studies touch upon the concept and no holistic theoretical or conceptual frameworks around the idea of sustainable tourism have been formulated. This study aims at exploring the role of tour operators in developing sustainable tourism in Pakistan and how the tour operators (TOs) conceive their role in this regard. TOs were reached through phone calls, emails, and virtual sources as face-to-face interviews were not possible due to COVID-19 pandemic and restrictions on travel by the government. In-depth interviews were conducted to gather data. Results suggest that the TOs although realize the importance of social, environmental, and economic dimensions of tourism on the communities but have no management systems in place to cater accordingly. There are no incentives in place by the government facilitate TOs to design and implement such systems. The TOs do not select a destination based on Global Sustainable Tourism Council criterion, but rather the selection of destination is mostly demand-based and profit-oriented. The study suggests that corporate profit motive is the sole criterion for decision making and is one of the major causes impeding sustainable tourism in Pakistan. The role of TOs in developing sustainable tourism is vague as the TOs do not have any systems in place to implement sustainable models. The study recommends that efforts need to be put in place to incentivize sustainable tourism in Pakistan and proper laws should be set forth by the authorities to comply by the TOs. The role of TOs is important and understood, however, there is a need to put proper systems in place. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
ABSTRACT
World has experienced a new potent challenge in the shape of Coronavirus disease 2019 (COVID-19). Rapid screening and detection of infected patients is important step in fighting against this disease, so that proper measures can be taken to stop it from further spreading. Majority of the countries who have been successful in controlling the disease, have done it through effective early detection. The same factor is very evident in the countries where COVID-19 has gone out of control that they were or are not successful in early detection of suspected patients. This paper presents an artificial intelligence-based approach to provide new screening approach to detect COVID-19 from X-ray images. More than thirty-five thousand local/international negative and positive corona X-ray images were obtained to train VGG-16 model. Proposed method has two classifiers, first classifier distinguishes between negative cases and other infected cases, second classifier identifies pneumonia and other infected cases. These other infected cases will be recognized as COVID-19. Experimental evaluation on different X-ray imaging were conducted where this method classified positive and negative cases very effectively. A comparative study with publicly available network such as COVID-NET is also carried out. Proposed method outperformed COVID-NET in all three major areas such as overall accuracy, sensitivity and specificity. Overall accuracy for our technique is 95.08%, while sensitivity and specificity values are 100% and 93.15% respectively, while overall accuracy, sensitivity, specificity values for COVID-NET are 52.36%, 86.79% and 27.39% respectively. © 2021 IEEE.