Hyperglycemia Associated With Raynaud Phenomenon and Liver Dysfunction After COVID-19 Vaccination in Type 1 Diabetes Mellitus.

Background/Objective: The association of COVID-19 vaccinations and the changes in glycemic control remains debatable. We report a case of a patient with type 1 diabetes mellitus (DM) with previously well-controlled glucose on a hybrid closed-loop insulin pump who developed significant glucose variation, new onset Raynaud phenomenon, and liver dysfunction after the vaccination. Case Report: A 33-year-old man with type 1 DM since the age of 5 years was on an insulin pump for 17 years. He had a reasonable controlled glucose level with a hemoglobin A1c level of 6.8% (51 mmol/mol). Three days after he received the COVID-19 vaccination, his glucose level started to fluctuate in the range of 46 to 378 mg/dL with 3.5 times higher total daily insulin requirement. The patient developed white-pale cold hands, weight gain, fatigue, and liver dysfunction. Computed tomography of the abdomen revealed mild hepatomegaly, and laboratory workup was negative for hepatitis. One month later, his glucose level became better controlled, and his liver function improved. Continuous glucose monitoring revealed that his glucose profile returned to baseline after 6 weeks. Discussion: COVID-19 vaccination resulted in significant glucose variation and fluctuations in this patient. It could be explained by the vaccine-induced immune response causing an increase in insulin resistance, such as in adipose tissue and muscle cells. Immune stimulation could have also caused the abnormal liver function and explain his new onset Raynaud phenomenon. Conclusion: We described, for the first time, the long-term continuous glucose monitoring glucose profile with a hybrid closed-loop system in type 1 DM after COVID-19 vaccination. Clinicians need to keep alert to glycemic excursion and side effects after immunization in type 1 DM.

Modelling and Closed-Loop Control of Admissions in a Vaccination Center Through Tropical Algebra

This paper presents the development of a dynamical tropical algebra-based model of a vaccination center, which can be used to control and optimize the admission of users during center's operation. In addition, an analysis of closed-loop control methods designed to maximize the system performance in terms of service rate and minimize users' waiting time, while observing occupancy constraints due to social distancing protocols recommended by sanitary authorities due to Covid epidemic, is presented. © 2023, Brazilian Society for Automatics--SBA.

The impact of COVID-19 on maritime pilots: Evidence and lessons.

The COVID-19 pandemic led to port congestion and disruption to global logistics and supply chains. While previous research has examined the impact on port performance and economics, social issues, such as the impact on port personnel (including pilots), have been overlooked. In this context, this paper examines the challenges experienced by Chinese pilots during the pandemic through in-depth interviews with 28 pilots. It shows that the draconian pandemic control measures adopted in China, rather than the pandemic itself, impaired pilots' physical and mental health, reduced their availability, and introduced new safety hazards, which curtailed both the port's capacity and ability to provide efficient and safe pilotage and resulted in sub-standard services. The findings suggest that there is a serious issue regarding the absence of effective mechanisms for pilots to raise their health and safety concerns and how these might be addressed by port administrators and/or local authorities. Worker participation and involvement in occupational health and safety management was problematic. These findings have implications for pilot station management at both company and government administrative and legislative levels.

Closed-loop ventilation in COVID-19 patients with acute hypoxemic respiratory failure-A case series.

BACKGROUND: INTELLiVENT-adaptive support ventilation (ASV) is an automated closed-loop mode of invasive ventilation for use in critically ill patients. INTELLiVENT-ASV automatically adjusts, without the intervention of the caregiver, ventilator settings to achieve the lowest work and force of breathing. AIMS: The aim of this case series is to describe the specific adjustments of INTELLiVENT-ASV in patients with acute hypoxemic respiratory failure, who were intubated for invasive ventilation. STUDY DESIGN: We describe three patients with severe acute respiratory distress syndrome (ARDS) because of COVID-19 who received invasive ventilation in our intensive care unit (ICU) in the first year of the COVID-19 pandemic. RESULTS: INTELLiVENT-ASV could be used successfully, but only after certain adjustments in the settings of the ventilator. Specifically, the high oxygen targets that are automatically chosen by INTELLiVENT-ASV when the lung condition 'ARDS' is ticked had to be lowered, and the titration ranges for positive end expiratory pressure (PEEP) and inspired oxygen fraction (FiO2 ) had to be narrowed. CONCLUSION: The challenges taught us how to adjust the ventilator settings so that INTELLiVENT-ASV could be used in successive COVID-19 ARDS patients, and we experienced the benefits of this closed-loop ventilation in clinical practice. RELEVANCE TO CLINICAL PRACTICE: INTELLiVENT-ASV is attractive to use in clinical practice. It is safe and effective in providing lung-protective ventilation. A closely observing user always remains needed. INTELLiVENT-ASV has a strong potential to reduce the workload associated with ventilation because of the automated adjustments.

Risk Modeling Framework for Strategic and Operational Intervention to Enhance the Effectiveness of a Closed-Loop Supply Chain

In a closed-loop supply chain (CLSC), acquiring end-of-life vehicles (ELVs) and their components from both primary and secondary markets has posed a huge uncertainty and risk. Moreover, the constant supply of ELV components with minimization of cost and exploitation of natural resources is another pressing challenge. To address the issues, the present study has developed a risk simulation framework to study market uncertainty/risk in a CLSC. In the first phase of the framework, a total of 12 important variables are identified from the existing studies. The total interpretive structural model (TISM) is used to develop a causal relationship network among the variables. Then, Matriced Impacts Cruoses Multiplication Applique a un Classement is used for determining the nature of relationships (i.e., driving or dependence power). In the second phase, the relationship of TISM is used to derive a Bayesian belief network model for determining the level of risks (i.e., high, medium, and low) associated with the CLSC through the generation of conditional probabilities across 1) multi-, 2) single-, and 3) without-parent nodes. The study findings will help decision-makers in adopting strategic and operational interventions to increase the effectiveness and resiliency of the network. Furthermore, it will help practitioners to make decisions on change management implementation for stakeholders'performance audits on the attributes of the ELV recovery program and developing resilience in the CLSC network. Overall, the present study holistically contributes to a broader investigation of the implications of strategic decisions in automobile manufacturers and resellers. IEEE

Glycemic Control in Type 1 Diabetes Mellitus During COVID-19 Quarantine and the Role of In-Home Physical Activity

Background: To limit the spread of coronavirus disease 2019 (COVID-19), governments have ordered a series of restrictions that may affect glycemic control in individuals with type 1 diabetes mellitus (T1DM), since physical activity (PA) was not allowed outside home. Methods: We retrospectively evaluated glycemic control of individuals with T1DM using hybrid closed loop (HCL) system in the period before the SARS-CoV-2 outbreak in Italy (February 10–23, 2020–Time 1), when movements were only reduced (February 24–March 8, 2020–Time 2) and during complete lockdown (March 9–22, 2020–Time 3). Information about regular PA (at least 3 h per week) prior and during the quarantine was collected. Results: The study included 13 individuals with a median age of 14.2 years and a good glycemic control at baseline (glucose management indicator of 7%, time in range [TIR] of 68%, time below range [TBR] of 2%). All individuals continued to show good glycemic control throughout the study period. There was an increase in TIR during the study period (+3%) and TIR was significantly higher during Time 3 (72%) than during Time 2 (66%). TBR was significantly lower during Time 3 (1%) both compared with Time 1 and Time 2 (2%). A meaningful variance in TIR at Time 3 between individuals who performed or not PA during quarantine and a significant increase in TIR between Time 2 and Time 3 in individuals both doing PA at baseline and during quarantine was found. At logistic regression, only the presence of PA during quarantine significantly predicted a TIR >70%. Conclusions: Glycemic control of T1DM in adolescents using HCL system did not worsen during the restrictions due to COVID-19 pandemics and further improved in those who continued PA during the quarantine. Maintaining regular PA in a safe home environment is an essential strategy for young individuals with T1DM during the COVID-19 crisis.

Psychological status of medical staff dedicated to nucleic acid collection in COVID-19 epidemic during closed-loop management: A cross-sectional study.

Background: To investigate the depression, anxiety and somnipathy situation occurred in the nucleic acid collection staff during the closed-loop management period of COVID-19. And try to understand the influencing factors of related psychological status. Methods: A cross-sectional study of 1,014 nucleic acid collection staff from seven Chinese hospitals was conducted. Various investigation methods were involved in the questionnaires to collect data, including 12-items self-made questionnaire survey of basic demographic information, 9-items patient health questionnaire depression scale (PHQ-9), 7-items generalized anxiety disorder scale (GAD-7) and Pittsburgh sleep quality index (PSQI). Data analysis was performed using SPSS version 26.0 and Excel software. Mann-Whitney U-test, Chi-square test, correlation analysis, mono-factor analysis and binary logistic regression were applied accordingly for further analysis. Results: The positive rate of depression, anxiety and sleep disorder of 1,014 nucleic acid collectors under closed-loop management were 33.5, 27.2, and 50.1%, respectively. Depression was significantly positively correlated with anxiety and sleep (P < 0.05). The scores of depression scale were positively correlated with the age and the fear for infection (r = 0.106, 0.218, both P < 0.05); The scores of anxiety scale were also positively correlated with the age and the fear for infection (r = 0.124, 0.225, both P < 0.05); The length of service, collection time and the degree of worry about infection and was positively correlated with the score of sleep scale (r = 0.077, 0.074, 0.195, both P < 0.05); Education level had a significant negative association with PHQ-9, GAD-7 and PSQI (r = -0.167,-0.172, both P < 0.05). Binary logistic regression analysis showed that age, technical title, education level, collection time, collection frequency, collection location, fear for infection and external environment were important influencing factors of depression, anxiety and sleep disorders. Conclusion: The results of this study suggested that when carrying out nucleic acid collection mission, managers should intervene to optimize the collection location, control the duration of each collection mission, replace the collection staff in time and pay close attention to the psychological state of the collection staff.

Collaborative closed-loop supply chain framework for sustainable manufacturing: Evidence from the Indian packaging industry

Businesses reeling from the impact of COVID are struggling to achieve sustainability, amidst many other challenges, including finance and capacity shortfalls. One of the pathways to achieving 3BL in businesses is to create closed-loop supply chains (CLSC) covering the entire lifecycle of products. CLSC have proven to be important for sustainable supply chain (SC) operations, given the shortage of materials and labour globally following the COVID-19 pandemic. While it is widely acknowledged that the success of CLSC depends on successful collaboration between SC members, factors for successful CLSC collaboration are not sufficiently understood from the literature. Employing an observation-based case study and a survey of SC members, we develop our contribution in the context of an Indian packaging company, to delineate and verify a collaborative CLSC framework. The results confirm that the success of CLSC collaboration lies in the involvement and commitment of SC members. Collaboration for forward and reverse SC operations also facilitate the involvement of SC members in CLSC collaborations. Our research suggests that SC collaborations are enhanced by explicit incentive-sharing schemes and having the same SC members for both forward and reverse SC operations. © 2023 The Authors

Modeling a closed-loop vaccine supply chain with transshipments to minimize wastage and threats to the public: a system dynamics approach

Purpose: This study aims to focus on building a conceptual closed-loop vaccine supply chain (CLVSC) to decrease vaccine wastage and counterfeit/fake vaccines. Design/methodology/approach: Through a focused literature review, the framework for the CLVSC is described, and the system dynamics (SD) research methodology is used to build a causal loop diagram (CLD) of the proposed model. Findings: In the battle against COVID-19, waste management systems have become overwhelmed, which has created negative environmental and extremely hazardous societal impacts. A key contributing factor is unused vaccine doses, shown as a source for counterfeit/fake vaccines. The findings identify a CLVSC design and transshipment operations to decrease vaccine wastage and the potential for vaccine theft. Research limitations/implications: This study contributes to establishing a pandemic-specific VSC structure. The proposed model informs the current COVID-19 pandemic as well as potential future pandemics. Social implications: A large part of the negative impact of counterfeit/fake vaccines is on human well-being, and this can be avoided with proper CLVSC. Originality/value: This study develops a novel overarching SD CLD by integrating the epidemic model of disease transmission, VSC and closed-loop structure. This study enhances the policymakers' understanding of the importance of vaccine waste collection, proper handling and threats to the public, which are born through illicit activities that rely on stolen vaccine doses. © 2023, Esen Andiç-Mortan and Cigdem Gonul Kochan.

Designing an IoT-enabled supply chain network considering the perspective of the Fifth Industrial Revolution: Application in the medical devices industry

The rapid growth of technology, environmental concerns, and disruptions caused by the COVID-19 pandemic have led researchers to pay more attention to an emerging concept called the fifth industrial revolution (I5.0). Despite the high importance of the I5.0, the literature shows that no study investigated the supply chain network design problem based on the I5.0 pillars. Hence, this research develops a multi-stage decision-making framework to configure a closed-loop supply chain based on I5.0 dimensions to cover this gap. In the first stage, the score of technologies that utilized in the supply chain is calculated using the analytic hierarchy process method. Afterwards, in the second stage, a mathematical model is proposed to configure the supply chain. Then, Furthermore, an efficient solution method, named the fuzzy lexicographic multi-choice Chebyshev goal programming method, is developed to obtain the optimal solution. In general, the main contributions of the current study can be divided into two major parts as follows: (i) the current study is the first research that incorporates the dimensions of the I5.0 into the supply chain network design problem, and (ii) this work develops a novel and efficient solution method. In this regard, the major problems and challenges that existed include the limitation of available resources in relation to Industry 5, especially in the field of the supply chain, as well as quantifying the elements of Industry 5.0 in the form of a mathematical programming model. © 2023

Information technology and artificial intelligence support in management experiences of the pediatric designated hospital during the COVID-19 2022 epidemic in Shanghai.

Objective: To describe the information technology and artificial intelligence support in management experiences of the pediatric designated hospital in the wave of COVID-19 in Shanghai. Methods: : We retrospectively concluded the management experiences at the largest pediatric designated hospital from March 1st to May 11th in Shanghai. We summarized the application of Internet hospital, face recognition technology in outpatient department, critical illness warning system and remote consultation system in the ward and the structed electronic medical record in the inpatient system. We illustrated the role of the information system through the number and prognosis of patients treated. Results: The COVID-19 designated hospitals were built particularly for critical patients requiring high-level medical care, responded quickly and scientifically to prevent and control the epidemic situation. From March 1st to May 11th 2022, we received and treated 768 children confirmed by positive RT-PCR and treated at our center. In our management, we use Internet Information on the Internet Hospital, face recognition technology in outpatient department, critical illness warning system and remote consultation system in the ward, structed electronic medical record in the inpatient system. No deaths or nosocomial infections occurred. The number of offline outpatient visits dropped, from March to May 2022, 146,106, 48,379, 57,686 respectively. But the outpatient volume on the internet hospital increased significantly (3,347 in March 2022 vs. 372 in March 2021; 4,465 in April 2022 vs. 409 in April 2021; 4,677 in May 2022 vs. 538 in May 2021). Conclusions: Information technology and artificial intelligence has provided significant supports in the management. The system optimizes the admission screening process, increases the communication inside and outside the ward, achieves early detection and diagnosis, timely isolates patients, and timely treatment of various types of children.

Managing Diabetes in Pregnancy Before, During, and After COVID-19.

Background: Pregnant women with diabetes are identified as being more vulnerable to the severe effects of COVID-19 and advised to stringently follow social distancing measures. Here, we review the management of diabetes in pregnancy before and during the lockdown. Methods: Majority of antenatal diabetes and obstetric visits are provided remotely, with pregnant women attending hospital clinics only for essential ultrasound scans and labor and delivery. Online resources for supporting women planning pregnancy and for self-management of pregnant women with type 1 diabetes (T1D) using intermittent or continuous glucose monitoring are provided. Retinal screening procedures, intrapartum care, and the varying impact of lockdown on maternal glycemic control are considered. Alternative screening procedures for diagnosing hyperglycemia during pregnancy and gestational diabetes mellitus (GDM) are discussed. Case histories describe the remote initiation of insulin pump therapy and automated insulin delivery in T1D pregnancy. Results: Initial feedback suggests that video consultations are well received and that the patient experiences for women requiring face-to-face visits are greatly improved. As the pandemic eases, formal evaluation of remote models of diabetes education and technology implementation, including women's views, will be important. Conclusions: Research and audit activities will resume and we will find new ways for supporting pregnant women with diabetes to choose their preferred glucose monitoring and insulin delivery.

Research on The Index System of Laboratory Assets Digitization

Under the influence of the fifth industrial revolution and the outbreak of COVID-19, the digital transformation of enterprises has entered a new stage of rapid development. Digital transformation has become the trend of enterprise operation in the digital economy era. In this context, enterprise laboratory asset operation has also become an important aspect of enterprise digital operation. It is urgent to build a set of enterprise laboratory asset digital evaluation system to assist the implementation of enterprise digital strategy. Based on the characteristics of laboratory assets and the closed-loop theory of asset operation management, this paper analyzes and studies the laboratory asset management, establishes a targeted evaluation index system of digital asset management, focuses on the composition of the digital operation system of laboratory assets, and constructs a management index evaluation system of assets, efficiency, cost and other dimensions, so as to create a real-time, comprehensive and comprehensive evaluation system The closed-loop and full cycle digital management ecological environment realizes the effective integration of laboratory resource fragmentation information and the complete embodiment of digitization, provides service support for continuously improving asset management performance, and provides support for further improving enterprise economic efficiency and operation level. © 2022 SPIE.

A multi-objective optimization modelling for design and planning a robust closed-loop supply chain network under supplying disruption due to crises

Global crises such as COVID-19 pandemic and the Russian-Ukrainian war pose many challenges for closed-loop supply chain networks (CLSCN) due to the lack of supplies of raw materials and returned products. Therefore, this research focused on developing a multi-objective MILP mathematical model for the design and planning of CLSCN to help overcome these challenges considering the uncertainty in both the supplying capacity of the raw materials and the return rate of the used products.The developed models aim to maximize total profit, minimize total cost, and maximize overall cus-tomer service level (OCSL) using the e-lexicographic procedure.The effect of variation in both the supply capacity and return rate of the used products on the design and performance of the CLSCN have been studied. It is recommended to optimize the profit then the total cost with a maximum allowable deviation of 5%, and finally optimize the OCSL.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams Uni-versity. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).

A novel separate chance-constrained programming model to design a sustainable medical ventilator supply chain network during the Covid-19 pandemic

Providing new models or designing sustainable networks in recent studies represents a growing trend. However, there is still a gap in the simultaneous modeling of the three dimensions of sustainability in the electronic medical device supply chain (SC). In this paper, a novel hybrid chance-constrained programming and cost function model is presented for a green and sustainable closed-loop medical ventilator SC network design. To bring the problem closer to reality, a wide range of parameters including all cost parameters, demands, the upper bound of the released co2, and the minimum percentage of the units of product to be disposed and collected from a customer and to be dismantled and shipped from DCs are modeled as uncertain along with the normal probability distribution. The problem was first formulated into the framework of a bi-objective stochastic mixed-integer linear programming (MILP) model;then, it was reformulated into a tri-objective deterministic mixed-integer nonlinear programming (MINLP) one. In order to model the environmental sustainability dimension, in addition to handling the total greenhouse gas emissions, the total waste products were also controlled. The efficiency and applicability of the proposed model were tested in an Iranian medical ventilator production and distribution network. For sensitivity analyses, the effect of some critical parameters on the values of the objective functions was carefully examined. Finally, valuable managerial insights into the challenges of companies during the COVID-19 pandemic were presented. Numerical results showed that with the increase in the number of customers in the COVID-19 crisis, social responsibility could improve cost mean by up to 8%.

The relationship between mindfulness and mental health among Chinese college students during the closed-loop management of the COVID-19 pandemic: A moderated mediation model.

To prevent the spread of the COVID-19 epidemic on campus, universities in outbreak areas in China can implement closed-loop management. OBJECTS: This study aimed to explore the relationship between mindfulness and mental health of college students under closed-loop management. MEASURES: 11,939 college students from a university in Changsha, China participated in the online survey during the closed-loop management period. The Chinese version of Perceived Stress Scale, the Emotion Regulation Questionnaire-Cognitive Reappraisal, the Mindful Attention Awareness Scale, the 7-item General Anxiety Disorder questionnaire, and the 9-item Patient Health Questionnaire were administered to the college students. RESULTS: We found that mindfulness was negative association with mental health during the closed-loop management period. Perceived stress mediated the relationship between mindfulness and mental health. Cognitive reappraisal moderated the relationship between mindfulness and perceived stress. Specifically, when the level of mindfulness is the same, individuals with more cognitive reappraisal tend to experience a less perceived stress. CONCLUSION: The results of this study are of great significance to improve the mental health of college students during closed-loop management period.

Research on The Index System of Laboratory Assets Digitization

Under the influence of the fifth industrial revolution and the outbreak of COVID-19, the digital transformation of enterprises has entered a new stage of rapid development. Digital transformation has become the trend of enterprise operation in the digital economy era. In this context, enterprise laboratory asset operation has also become an important aspect of enterprise digital operation. It is urgent to build a set of enterprise laboratory asset digital evaluation system to assist the implementation of enterprise digital strategy. Based on the characteristics of laboratory assets and the closed-loop theory of asset operation management, this paper analyzes and studies the laboratory asset management, establishes a targeted evaluation index system of digital asset management, focuses on the composition of the digital operation system of laboratory assets, and constructs a management index evaluation system of assets, efficiency, cost and other dimensions, so as to create a real-time, comprehensive and comprehensive evaluation system The closed-loop and full cycle digital management ecological environment realizes the effective integration of laboratory resource fragmentation information and the complete embodiment of digitization, provides service support for continuously improving asset management performance, and provides support for further improving enterprise economic efficiency and operation level. © 2022 SPIE.

Analysis and Performance of Solar Photovoltaic Energy System in India: Case Study

There are seven types of renewable energy, of which only five will generate electricity. The most extensively utilized renewable energy source for residential usage is solar photovoltaic energy. With over 486GW of generation capacity, solar PV remains as the third largest renewable power source, with advanced photovoltaic (PV) innovation. The United States and China have the most solar plant installations. India holds the third place as the country's solar area is expected to recover completely after the COVID-19 epidemic, wherein the energy from solar PV is expected to overtake coal before 2040. To examine and observe the various processes carried out by solar PV, several experimental studies have been carried out. This research article presents the different case studies of solar PV systems and observes the characteristics of voltage and current or voltage and power for different solar radiations and temperature, respectively. Secondly, the proposed study has observed and analyzed the performance of PV module in series or parallel connections concerning I-V and V-P characteristics. In third section, the shading effects on solar PV module output power is observed. In the fourth and fifth sections, methods to solve the shading module's output power constraint has been studied and finally the MPP is observed by varying the duty cycle of the converter. In the sixth and seventh section, the performance of SEPIC converter is evaluated based on the open and closed-loop systems, and the challenges in buck-boost converter are solved. © 2022 IEEE.

Optimization of Transport Services Based on the K Shortest Path Algorithm

The link between the supply and demand sides of manufacturing has become increasingly frail as a result of the COVID-19 outbreak. In this paper, we analyze the key path nodes and propose a closed-loop path value-added strategy for logistics services to optimize the path cost on the supply and demand side under the influence of the COVID-19 epidemic. First, the k shortest path algorithm determines the optional paths in accordance with the structure of the road network made up of all path nodes. Second, closed-loop transportation routes for both forward and reverse transit are constructed using the optional paths. Finally, the transportation service strategy with the optimal choice of transportation cost and transportation time under a multi-stage epidemic is obtained. The method can provide a reference for logistics services. © 2022 IEEE.

An Optical Guidance Method for Robotic Intramuscular Injection System

Intramuscular (IM) injection is mainly performed manually at present. Large-scale COVID-19 vaccination has exposed various problems of manual IM injection. In addition, the clinical success rate of manual IM injection is also unsatisfactory. Using robotic intramuscular injection system (RIMIS) is expected to realize automated vaccination and improve the success rate of IM injection. The existing robotic needle insertion system based on image guidance is not a practical option for IM injection because of the time-consuming medical imaging process. In this paper, an optical guidance method for RIMIS is proposed, which uses near-infrared optical tracking system and retro-reflective patch to achieve rapid acquisition of surface normal vector. A closed loop formed by six coordinate systems is used to realize the accurate control of the injection angle and depth. Experimental results show that the RIMIS based on the proposed method can complete the simulated IM injection operation without image guidance and possess accurate control of the injection angle and depth. © 2022 IEEE.