Bibliometric analysis and system review of vehicle routing optimization for emergency material distribution

Determining the optimal vehicle routing of emergency material distribution (VREMD) is one of the core issues of emergency management, which is strategically important to improve the effectiveness of emergency response and thus reduce the negative impact of large-scale emergency events. To summarize the latest research progress, we collected 511 VREMD-related articles published from 2010 to the present from the Scopus database and conducted a bibliometric analysis using VOSviewer software. Subsequently, we cautiously selected 49 articles from these publications for system review;sorted out the latest research progress in model construction and solution algorithms;and summarized the evolution trend of keywords, research gaps, and future works. The results show that do -mestic scholars and research organizations held an unqualified advantage regarding the number of published papers. However, these organizations with the most publications performed poorly regarding the number of literature citations. China and the US have contributed the vast majority of the literature, and there are close collaborations between researchers from both countries. The optimization model of VREMD can be divided into single-, multi-, and joint-objective models. The shortest travel time is the most common optimization objective in the single-objective optimization model. Several scholars focus on multiobjective optimization models to consider conflicting objectives simultaneously. In recent literature, scholars have focused on the impact of uncertainty and special events (e.g., COVID-19) on VREMD. Moreover, some scholars focus on joint optimization models to optimize vehicle routes and central locations (or material allocation) simultaneously. So-lution algorithms can be divided into two primary categories, i.e., mathematical planning methods and intelligent evolutionary algorithms. The branch and bound algorithm is the most dominant mathematical planning algorithm, while genetic algorithms and their enhancements are the most commonly used intelligent evolutionary algorithms. It is shown that the nondominated sorting genetic algorithm II (NSGA-II) can effectively solve the multiobjective model of VREMD. To further improve the algorithm's performance, re-searchers have proposed improved hybrid intelligent algorithms that combine the ad-vantages of NSGA-II and certain other algorithms. Scholars have also proposed a series of optimization algorithms for specific scenarios. With the development of new technologies and computation methods, it will be exciting to construct optimization models that consider uncertainty, heterogeneity, and temporality for large-scale real-world issues and develop generalized solution approaches rather than those applicable to specific scenarios.(c) 2022 Periodical Offices of Chang'an University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

A Secure Blockchain-Assisted Access Control Scheme for Smart Healthcare System in Fog Computing

IoT-based smart healthcare system allows doctors to monitor and diagnose patients remotely, which can greatly ease overcrowding in the hospitals and disequilibrium of medical resources, especially during the rage of COVID-19. However, the smart healthcare system generates enormous data which contains sensitive personal information. To protect patients’privacy, we propose a secure blockchain-assisted access control scheme for smart healthcare system in fog computing. All the operations of users are recorded on the blockchain by smart contract in order to ensure transparency and reliability of the system. We present a blockchain-assisted Multi-Authority Attribute-Based Encryption (MA-ABE) scheme with keyword search to ensure the confidentiality of the data, avoid single point of failure and implement fine-grained access control of the system. IoT devices are limited in resources, therefore it is not practical to apply the blockchain-assisted MA-ABE scheme directly. To reduce the burdens of IoT devices, We outsource most of the computational tasks to fog nodes. Finally, the security and performance analysis demonstrate that the proposed system is reliable, practical, and efficient. IEEE

Towards integrating quality in theoretical models of acceptance: An extended proposed model applied to e-learning services

The use of e-learning services is growing in different contexts, especially in the COVID-19 pandemic. This study aims to examine students' acceptance of and intention to use Learning Management Systems (LMSs) for university education in Brazil using the extended technology acceptance model, unified theory of acceptance and use of technology (UTAUT), integrating quality construct adapted from the Service Quality Evaluation Model (ServQual). Examining a large sample (n = 1237) of students in Brazil through questionnaires, we investigate the behaviour of the users concerning the factors that influence the technology acceptance and the intention of the use in an e-learning system. Results show that intention to use an LMS is affected by the facilitating conditions (skilful, workable and easy to use), social influence (remarkable, preference for use and relevance), habit (routine, enjoyable and entertaining) and quality (reliable, tangibility, responsiveness and assurance), but not for effort expectancy (agility, knowledge and productivity). Our research findings suggest fostering replicate the model in different universities and countries understanding potential differences. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Introduction to the Special Issue: Multispecies security and personhood

The contributions to this Special Issue examine multispecies perspectives on the political dynamics of international life. Building on this theme, I consider the complex and manifold ways in which the subject of security can be understood in terms of more-than-human personhood. First, by thinking of more-than-human animals as phenomenally conscious persons, we might better appreciate the multispecies complexity of security as an agentic and affective experience. Second, attending to the spiritual character of certain indigenous articulations of personhood presses us to decipher how spiritual claims might inform moral and legal dimensions of multispecies security-seeking behaviour. To illustrate the significance of these moves, I first draw on more-than-human experiences of war, pathogenic viruses, and the global factory farm. I then explore conceptions of spiritual personhood in the context of Ojibwe responsibilities to protect wolves. These perspectives on personhood demonstrate possibilities for cultivating greater interest in the multispecies experience of security. © The Author(s), 2023. Published by Cambridge University Press on behalf of the British International Studies Association.

Comparison of Clinical and Laboratory Findings at Different Clinical Stages in Cats Naturally Infected with Feline Coronavirus

Feline coronavirus (FCoV) infections occur commonly in cats, with entrocyte and monocyte-macrophage tropism. Most FCoV-infected cats remain asymp tomatic, but up to 10% develop fatal feline infectious peritonitis (FIP). This study aims to investigate the diagnostic utility of clinical and laboratory examinations including serum and effusion AGP levels in cats either with symptomatic effusive FIP or asymptomatic feline enteric coronavirus (FECV). The study included 40 cats with effusive FIP and 10 cats with FECV infection. The FIP group was divided into two subgroups: Abdominal (AE;n=30) and thoracic effusion (TE;n=10). Clinical and laboratory examinations, including serum or effusion AGP measurement, were performed. Among all the groups, TE group had higher body temperature, heart and respiratory rates (P<0.000). Compared with the FECV group, the FIP group had lower pH and HCO3 levels and higher base excess and lactate levels (P<0.05). The leukocyte and lymphocyte counts were higher and the hematocrit was lower in the AE group among all the groups (P<0.023). MCV was lower in the FIP group compared to the FECV group (P<0.002). In the AE group, total protein level was the lowest and the AST, GGT, total bilirubin and cholesterol levels were the highest (P<0.032) among all the groups. Magnesium level was lower in the FIP group compared to the FECV group (P<0.044). Although the serum AGP level was highest in the TE group among all groups (P<0.004), the AGP levels of cats with FECV were similar to the AE group (P>0.05). Since FECV-positive cats will likely develop FIP, differences in clinical and laboratory findings in FECV-positive cats were identified. Among them, pH, HCO3, base excess, lactate, MCV and magnesium were found to be important in the course of the disease, and AGP in the evaluation of the presence of an inflammatory state. It was concluded that clinical, laboratory and serum AGP evaluation could be used in the index of suspicion of development of FIP and FECV.Copyright © 2023 Erdem Gulersoy et al., published by Sciendo.

Treatment Effects of Integrated TCM and Western Medicine Treatment Scheme on COVID-19: A Single-armed Clinical Trial

Backgroud: The outbreak of COVID-19 has brought unprecedented perils to human health and raised public health concerns in more than two hundred countries. Safe and effective treatment scheme is needed urgently. Objective(s): To evaluate the effects of integratedTCM and western medicine treatment scheme on COVID-19. Method(s): A single-armed clinical trial was carried out in Hangzhou Xixi Hospital, an affiliated hospital with Zhejiang Chinese Medical University. 102 confirmed cases were screened out from 725 suspected cases and 93 of them were treated with integrated TCM and western medicine treatment scheme. Result(s): 83 cases were cured, 5 cases deteriorated, and 5 cases withdrew from the study. No deaths were reported. The mean relief time of fever, cough, diarrhea, and fatigue were (4.78 +/- 4.61) days, (7.22 +/- 4.99) days, (5.28 +/- 3.39) days, and (5.28 +/- 3.39) days, respectively. It took (14.84 +/- 5.50) days for SARS-CoV-2 by nucleic acid amplification-based testing to turn negative. Multivariable cox regression analysis revealed that age, BMI, PISCT, BPC, AST, CK, BS, and UPRO were independent risk factors for COVID-19 treatment. Conclusion(s): Our study suggested that integrated TCM and western medicine treatment scheme was effective for COVID-19.Copyright © 2021

Applying Minimum Message Length to the Clustering of Mutual Funds

Clustering has been widely studied to group data into clusters. Several methods have been used including Maximum Likelihood (ML), Information Criterion by Akaike (AIC), and Bayesian Information Criterion (BIC) by Schwarz. In this paper, Minimum Message Length (MML) is applied to the clustering of mutual funds data. In this application, data are assumed to come from multivariate correlated Gaussian distribution. For this, MML principle needs to be numerically approximated. The modeling results are contrasted with those obtained using alternative methods, in terms of probability-bit costings and clustering structures. The experiment's findings demonstrate that, in terms of the fitted probability bit costings, MML clustering provided a more trustworthy model than AIC and BIC with significantly less bits required in conveying the data given the model. MML clustering also handled overlapping clusters better compared to modeling using the combination of ML with AIC and BIC. Furthermore, mutual funds trading have shown changes of movements during the pandemic Covid-19 with performances of mutual funds tend to be decreasing across funds, especially during the first 15 months of the period. Only several funds were grouped differently compared to most funds analyzed. The latter have shown effect of pandemic Covid-19 the most with lower returns compared to the returns of most funds. © 2022 IEEE.

Comparison of the AmpFire and MA-6000 polymerase chain reaction platforms for high-risk human papillomavirus testing in cervical precancer screening.

High-risk human papillomavirus (hr-HPV) testing for primary cervical precancer screening offers an opportunity to improve screening in low-middle income countries (LMICs). This study aimed to compare the analytic performances of the AmpFire and MA-6000 platforms for hr-HPV DNA testing in three groups of women screened for hr-HPV types in Ghana: group 1 with 33 GeneXpert-archived ThinPrep/liquid-based samples subjected to both tests, group 2 with 50 AmpFire-archived dry brush samples subjected to MA-6000 testing, and group 3 involving 143 cotton swab samples simultaneously subjected to both tests without archiving. The overall agreement rates were 73 %, 92 %, and 84 %, for groups 1-3, respectively, and 84 % (95 % CI, 78.6-88.6) for the entire group. Neither AmpFire nor MA-6000 was more likely to test hr-HPV positive in all three groups and the combined group. Group 1 showed fair agreement without statistical significance (κ = 0.224, 95 % CI, -0.118 to 0.565), while group 3 showed significant moderate agreement (κ = 0.591, 95% CI, 0.442-0.741). Group 2 showed an almost perfect significant level of agreement (κ = 0.802; 95 % CI, 0.616-0.987). Thus, both platforms showed statistically significant moderate to near-perfect agreement for detecting hr-HPV in cervicovaginal samples, with variation according to archiving conditions and duration between sample collection and retesting. For LMICs using these platforms for COVID-19 testing, as the COVID-19 pandemic subsides, the platforms can become available for running other tests such as hr-HPV DNA testing for cervical precancer screening.

Wearable devices for anxiety & depression: A scoping review.

Background: The rates of mental health disorders such as anxiety and depression are at an all-time high especially since the onset of COVID-19, and the need for readily available digital health care solutions has never been greater. Wearable devices have increasingly incorporated sensors that were previously reserved for hospital settings. The availability of wearable device features that address anxiety and depression is still in its infancy, but consumers will soon have the potential to self-monitor moods and behaviors using everyday commercially-available devices. Objective: This study aims to explore the features of wearable devices that can be used for monitoring anxiety and depression. Methods: Six bibliographic databases, including MEDLINE, EMBASE, PsycINFO, IEEE Xplore, ACM Digital Library, and Google Scholar were used as search engines for this review. Two independent reviewers performed study selection and data extraction, while two other reviewers justified the cross-checking of extracted data. A narrative approach for synthesizing the data was utilized. Results: From 2408 initial results, 58 studies were assessed and highlighted according to our inclusion criteria. Wrist-worn devices were identified in the bulk of our studies (n = 42 or 71%). For the identification of anxiety and depression, we reported 26 methods for assessing mood, with the State-Trait Anxiety Inventory being the joint most common along with the Diagnostic and Statistical Manual of Mental Disorders (n = 8 or 14%). Finally, n = 26 or 46% of studies highlighted the smartphone as a wearable device host device. Conclusion: The emergence of affordable, consumer-grade biosensors offers the potential for new approaches to support mental health therapies for illnesses such as anxiety and depression. We believe that purposefully-designed wearable devices that combine the expertise of technologists and clinical experts can play a key role in self-care monitoring and diagnosis.

The Effect of COVID-19 on Foreign Direct Investment

This study empirically examines how the coronavirus disease (COVID-19) has impacted foreign direct investment (FDI), using the quarterly data on bilateral FDI flows from 173 home to 192 host economies from the first quarter of 2019 to the second quarter of 2021. The severity of COVID-19 in host economies adversely affected FDI in the manufacturing sector regardless of the entry mode, but the effect of home economies' COVID-19 situation on FDI was insignificant. On the other hand, in the services sector, the severity of COVID-19 in both host and home economies has significantly negative impact on greenfield FDI, not on cross-border M&A.

A critical review on the inactivation of surface and airborne SARS-CoV-2 virus by ozone gas

COVID-19 pandemic has created chaos in almost every walk of life. The harsh impact of the disease is mainly rooted to the rapid and easy spread of SARS-CoV-2 virus through airborne and fomite routes. Thus, disinfection of contaminated surfaces and air is important to hamper COVID-19 disease transmission. Ozone being a potent gaseous disinfectant has been utilized to inactivate a wide-range of viruses and has more recently gained interest in the inactivation of SARS-CoV-2. This article critically reviews the current state-of-knowledge on disinfection of surface-adhered and airborne SARS-CoV-2 by ozone. The transmission and survival characteristics of SARS-CoV-2 alongside the specificity of ozone inactivation process are reviewed. Distinct focus is then given to reviewing the status of ozone inactivation of surface-adhered and airborne SARS-CoV-2 in terms of experimental investigations, kinetics, and influence of the operational factors on the inactivation process. Ozone inactivation of SARS-CoV-2 is compared to other enveloped viruses, and the challenges and future prospects of ozone inactivation of SARS-CoV-2 are also addressed. © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.

Simulated Learning Experiences Impact on Acute Care Confidence Development in Students with Low Resiliency

PURPOSE/HYPOTHESIS: The COVID-19 pandemic has taken a toll on the psychological resilience of healthcare workers across the world but has also had a significant impact on healthcare professionals in training. The pandemic has required educators to adapt how they teach but also to take into consideration innovative learning activities to increase students' resiliency. The purpose of this study was to assess the impact of high-fidelity human simulation (HFHS) sessions on acute care confidence in a critical care setting in physical therapy students' who rate their resiliency at low levels. NUMBER OF SUBJECTS: Eighty-one DPT students. MATERIALS AND METHODS: One week prior to the HFHS sessions each subject completed the Acute Care Confidence Survey (ACCS) and the Brief Resiliency Scale (BRS). All subjects participated in 2 HFHS sessions in a 3-member team and were given objectives and a case history 1 week prior to each HFHS experience. The HFHS used the Laerdal's SimMan 3G manikin equipped with an oxygen delivery system, lines and tubes and a monitor displaying vitals. The format for each simulation lab included a 15-minute pre-brief session, a 20-minute SimMan encounter and an immediate 15-minute debrief session. Following the completion of the HFHS learning experience each student completed a second ACCS. RESULT(S): A Kruskal-Wallis test was used to compare confidence score across low, normal, and high resilience groups. Low and normal resiliency level students had significantly lower confidence in manual skills prior to simulation (P< 05) compared to their high resiliency counterparts. Following simulation, all resiliency groups demonstrated confidence improvement that resulted in no significant differences between the groups. A Wilcoxon Signed Ranks Test revealed significant improvement in all confidence scores for each group following simulation. CONCLUSION(S): Resiliency levels did not impact students' ability to gain confidence from simulation training. HFHS when graded has been shown to increase stress and decrease confidence in students. These HFHS learning activity exposures were not graded which may have allowed those students with lower resiliency to learn in a less stressful environment and still develop confidence. A positive change in student confidence may be more related to a graded exposure to an acute care setting that allows skill development in a low stress environment. CLINICAL RELEVANCE: The simulation sessions increased student confidence by providing a realistic clinical environment and expectations, with confidence being less impacted by a student's resiliency. This low stake learning environment provided a valuable opportunity for students to improve clinical confidence regardless of their self-rated resiliency level.

Pro-environmental attitudes, altruism, and COVID-19 risk management behavior. (Special Issue: COVID-19: feeling and confronting pandemic risk challenges.)

Limiting the spread of COVID-19 during the pandemic is a collective action problem that calls on individuals to act, not just for their benefit but also for the benefit of others in their community. Many environmental problems, especially climate change, share this characteristic, which invites inquiry on whether those predisposed to act to solve environmental problems may also be predisposed to act to solve health-focused collective action problems. In this study, we use a survey instrument to examine how pro-environmental attitudes and two types of altruism relate to the tendency to follow social distancing guidelines and limit voluntary social exposure during the pandemic. We find that pro-environmental behaviors predict a feeling of moral obligation to reduce COVID-19 risk and a lower level of voluntary social exposure. Voluntary, individual-level altruism has no relationship with social exposure. These findings point to important insights about the connections between different types of collective action and the nuances in altruistic behavior. These insights may lead to essential guidance for public health and environmental messaging that respects and leverages the differences in voluntary, individual-level altruism and collective altruism.

Mouse-Adapted SARS-CoV-2 MA10 Strain Displays Differential Pulmonary Tropism and Accelerated Viral Replication, Neurodissemination, and Pulmonary Host Responses in K18-hACE2 Mice.

Several models were developed to study the pathogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as well as the in vivo efficacy of vaccines and therapeutics. Since wild-type mice are naturally resistant to infection by ancestral SARS-CoV-2 strains, several transgenic mouse models expressing human angiotensin-converting enzyme 2 (hACE2) were developed. An alternative approach has been to develop mouse-adapted SARS-CoV-2 strains. Here, we compared the clinical progression, viral replication kinetics and dissemination, pulmonary tropism, and host innate immune response dynamics between the mouse-adapted MA10 strain and its parental strain (USA-WA1/2020) following intranasal inoculation of K18-hACE2 mice, a widely used model. Compared to its parental counterpart, the MA10 strain induced earlier clinical decline with significantly higher viral replication and earlier neurodissemination. Importantly, the MA10 strain also showed a wider tropism, with infection of bronchiolar epithelia. While both SARS-CoV-2 strains induced comparable pulmonary cytokine/chemokine responses, many proinflammatory and monocyte-recruitment chemokines, such as interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), IP-10/CXCL10, and MCP-1/CCL2, showed an earlier peak in MA10-infected mice. Furthermore, both strains induced a similar downregulation of murine Ace2, with only a transient downregulation of Tmprss2 and no alterations in hACE2 expression. Overall, these data demonstrate that in K18-hACE2 mice, the MA10 strain has a pulmonary tropism that more closely resembles SARS-CoV-2 tropism in humans (airways and pneumocytes) than its parental strain. Its rapid replication and neurodissemination and early host pulmonary responses can have a significant impact on the clinical outcomes of infection and are, therefore, critical features to consider for study designs using these strains and mouse model. IMPORTANCE The COVID-19 pandemic, caused by SARS-CoV-2, is still significantly impacting health care systems around the globe. Refined animal models are needed to study SARS-CoV-2 pathogenicity as well as efficacy of vaccines and therapeutics. In line with this, thorough evaluation of animal models and virus strains/variants are paramount for standardization and meaningful comparisons. Here, we demonstrated differences in replication dynamics between the Wuhan-like USA-WA1/2020 strain and the derivative mouse-adapted MA10 strain in K18-hACE2 mice. The MA10 strain showed accelerated viral replication and neurodissemination, differential pulmonary tropism, and earlier pulmonary innate immune responses. The observed differences allow us to better refine experimental designs when considering the use of the MA10 strain in the widely utilized K18-hACE2 murine model.

COVID-19 in cancer patients - higher inflammatory response in patients with active cancer

Background: Active cancer has been identified as an independent risk factor for severity and mortality in COVID-19. However, direct comparisons of SARS-CoV-2 infected patients (pts) with active and non-active cancers remain scarce. Method(s): We retrospectively analyzed a cohort of pts with cancer with confirmed SARS-CoV-2 infection, enrolled 03/16/2020 - 07/31/2021. Data on demographics, cancer and laboratory findings were collected. Descriptive and subsequent regression analysis was performed. Endpoints were progression to severe COVID-19 and infection-associated mortality. Result(s): In total, 987 pts with cancer (510 active vs 477 non-active) were included in our analysis. Majority was male and > 55 years, with a higher number of elderly pts with non-active cancer. CCI was 4.75 vs 3.85 in pts with active and non-active cancer (p<0.001). Localized solid tumors were reported in 38 vs 79% (p<0.001), metastasized in 37.5 vs 5.5% (p<0.001) and hematological diseases in 37.5 vs 19.5% (p<0.001) pts with active and non-active cancer, respectively. At virus detection, majority of pts showed mild to moderate symptoms, while deterioration to severe COVID-19 was slightly more common in pts with active cancer (19% vs 16%;p=0.284). COVID-19 related mortality was significantly higher in pts with active cancer (24% vs 17.5%, p<0.001). In line, severe cytopenia and an increase of inflammatory markers were common findings in pts with active cancer at baseline, particularly in those who developed severe infection or died. Multivariate analysis revealed that ferritin (14.24 [2.1-96], p=0.006) and CRP (2.85 [1.02-8.02], p=0.046) were associated with severe COVID-19 and infection-related mortality. In pts with non-active cancer, association was seen for ferritin only (4.1 [1.51-11.17], p=0.006). Conclusion(s): Comparing pts with active and non-active cancer, mortality rate was significantly higher in pts with active cancer. Also inflammatory markers were significantly increased assuming higher levels of inflammation may play a role in adverse outcome of COVID-19 in pts with active cancer.

Can Investors Profit from Utilizing Technical Trading Rules During the COVID-19 Pandemic?

In the past, it was believed that investors may generate abnormal returns (AR) for trading stocks by employing technical trading rules. However, since the COVID-19 pandemic broke out, stock markets around the world seem to suffer a serious impact. Therefore, whether investors can beat the markets by applying technical trading rules during the period of COVID-19 pandemic becomes an important issue for market participants. The purpose of this study is to examine the profitability of trading stocks with the use of technical trading rules under the COVID-19 pandemic. By trading the constituent stocks of DJ 30 and NASDAQ 100, we find that almost all of the trading rules employed in this study fail to beat the market during the COVID-19 pandemic period, which is different from the results in 2019. The revealed findings of this study may shed light on that investors should adopt technical trading with care when stock markets are seriously affected by black swan events like COVID-19.

Sentiment Analysis of Covid-19 Tweets using Twitter Database-A Global Scenario

Sentiment analysis falls within the category of Natural Language Processing (NLP) technology. Behaviour analysis and recommendation employ sentiment analysis. On the dataset of COVID-19 tweets, random forest Classifier, Decision Tree, Support Vector Machine (SVM), and Random Forest are the machine learning methods under consideration for sentiment analysis. The total number of tweets used for this research is 179108. Pre-Processing is used to clean and analyze these tweets. The sentiment analysis of COVID-19 tweets used in this study reveals the individual experiences of those affected by the epidemic. The primary goal of this survey is to analyze people's experiences. It helps to better understand the emotions of people, especially during an epidemic period. Twitter, a microblogging platform, contains a sizable collection of datasets that illustrate a wide range of human emotions, including fear, happy, sad, anger, and joy etc. Sentiment analysis is crucial for gauging the consensus of the populace. This research can help us assess the potential impact of a pandemic on the general public's decision-making. © 2022 IEEE.

Application of the lean method in designing the layout of face mask manufacturing plants for the prevention of covid-19

The prolonged global coronavirus pandemic (Covid-19) has affected all aspects of life, economy, and society, especially small and medium businesses. To meet this challenge, many companies are transforming models and reorganizing production and operations to adapt to this situation. These companies have adopted a variety of philosophies to remove non-value-Added activities from their production processes to maintain efficiency, flexibility, and profitability. In the context of Industry 4.0, solutions are ready to combine automation technology together with the Lean manufacturing approach. Furthermore, when it comes to efficient use of resources (financial, labor, materials, machine, and equipment), Industry 4.0 should be applied to Lean Processes. Thus, this article shows how to apply the Lean method to optimize plant design to cut waste, improve the efficiency of input resources, increase labor productivity by reducing labor costs, waiting (man-To-man;man-machine), reduced movement, and redundancy of operations in the workflow. Especially, the paper uses the SLP (Systematic Layout Planning) method to arrange the areas, material flow, and supply chain in the factory, Lean application to visualize the factory and combines IoT (Internet of Things). Moreover, using automation and Lean Production theory will support much for factory construction in the future, minimizing irrationalities when applied in practice. The result of the paper will mention a case study on the design and simulation of a face mask plant © 2022 IEEE.

Diagnostic Value of Hematological Parameters in COVID-19 Patients

Background: Covid-19 was fulminant and had a rapid spread in China and many other areas around the globe. This is a life threatening problem at present as it causes the severe acute respiratory syndrome corona virus (SARS-CoV). Aim(s): To explore the diagnostic value of hematological parameters in COVID-19 patients. Study Design: Comparative Cross-Sectional Study. Methodology: Patients (n=200) having COVID-19 were enrolled. All patients had CBC and inflammatory markers. Various hematological markers were used as prognostic markers. SPSS software, v 23 analyzed data. Independent t-test and Chi square were applied and p value of <0.05 was taken significant. Result(s): Mean age for patients having COVID was 47+/- 15.48 years. Mean values of hematological parameters and platelet count were significantly low among COVID patients when compared with non-COVID patients thus having significant difference. Practical Implication: This study highlighted simple, cost-effective hematological parameters that can be useful diagnostic tools for COVI-19. This study indicated that routine tests can guide towards disease like COVID-19. Conclusion(s): We concluded that hematological parameters (TLC, ANC, AMC, NLR and platelet count) play a vital role as diagnostic tool for COVID-19 patients. Copyright © 2022 Lahore Medical And Dental College. All rights reserved.

Lower Serum Calcium Levels In Covid-19 Patients: A Case-Control Study In A Tertiary Care Centre

Background: The novel coronavirus disease (COVID-19) has affected over 50 million people and has inflicted more than 1.2 million casualties ever since its inception in December 2019. Besides, multiple hematological and biochemical parameters have emerged as potential biomarkers to predict severe disease and mortality in COVID-19. One such biochemical biomarker is hypocalcemia. Hypocalcemia is associated with severe disease, organ failure, increased likelihood of hospitalization, admission to the intensive care unit, need for mechanical ventilation, and death from COVID-19. Hence, the present study was undertaken to compare the serum total calcium in patients infected with COVID-19 and a normal healthy population. Aim(s): To compare serum total calcium in patients infected with COVID-19 and normal healthy populations. Material(s) and Method(s): This is a case-control study with 50 COVID-19 patients and 50 normal healthy individuals as controls. Serum calcium was determined by Arsenazo III method using Vitros 5600 autoanalyser. Result(s): Chi-square analysis was done and the p-value between cases and control was < 0.05 which is significant. 20% of the COVID -19 patients had very severe hypocalcemia ranging between 4.5-6 mg/dl, 47% of the COVID-19 patients had moderate to severe hypocalcemia with values between 6.6-8.5 mg/dl, and 33% of the COVID -19 patients had normal calcium levels ranging from 8.6-10 mg/dl. Conclusion(s): Hypocalcemia is highly prevalent in COVID-19 patients implying that hypocalcemia is intrinsic to the disease. Prospective studies with a larger number of patients are required to prove this hypothesis and unravel the underlying pathophysiological mechanisms. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.