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Separation membranes play a crucial role in the functioning of artificial organs, such as hemodialysis machines, membrane oxygenators, and artificial liver models. The current COVID-19 pandemic has highlighted the importance of these technologies in the medical community. However, membrane technology in artificial organs faces significant challenges, such as the clearance of low-middle-molecule and protein-bound toxins and limited blood compatibility. In this review, we will discuss the separation mechanisms, separation performance, and biocompatibility of different types of separation membranes used in artificial organs. We will also highlight the opportunities and challenges for next-generation membrane technology in this field, including the need for improved clearance of toxins and increased blood compatibility, as well as the potential for microfluidic devices.
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Urban parks provide a multitude of health benefits for citizens navigating the challenges of 21st-century living. And while this is well known by both scholars and practitioners, there is less understanding about the differential impacts of park size, type of facilities, community accessibility, and management. This is the central concern of the research reported here, which is a part of a larger project titled 'Better Parks, Healthier for All?' funded under the UKRI-NHMRC Built Environment and Prevention Research Scheme 2019. Within this broader context, the current paper discusses the results of a focus group to better understand how different park qualities promote physical and mental health. Using a COVID-safe research approach, we brought key park providers, park policymakers, and green and open space designers from New South Wales, Australia, together to participate in an online focus group in May 2021. The recruitment was based on the domain expertise and practitioner knowledge of the issues at hand. The ensuing discussion canvassed three areas of interest: What is park quality? How is park quality associated with health? How can we assess park quality and its ability to deliver health outcomes? A thematic analysis of the group's deliberations reveals a very holistic appreciation of park quality. The ability of a park network to provide a range of health outcomes is central to this view, with each park playing a role in delivering different benefits across the network. Our findings indicate that there are many opportunities to enhance the myriad of benefits and multiple ways to gain them. Co-design is essential to ensure that parks best suit the local context and provide relevant benefits to all stakeholders. In this way, local communities can gain ownership and enhanced agency in relation to using and enjoying their parks. We conclude that delivering locally networked parks and associated spaces for community health and wellbeing are essential in the broader context of global environmental sustainability.
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This paper focused on role-based public leadership's impact and internal mechanism on subordinate taking charge behavior (TCB). The explanatory model of rationality and value dual paths was proposed and verified through hierarchical regression and bootstrap tests, with the data from a questionnaire survey to the Bureau of Commerce. The main conclusions are as follows: (1) Public service motivation is a mediating variable between public leadership and TCB;(2) political skills have a double-edged sword effect. Political skills positively moderate the impact of public leadership on TCB. Meanwhile, it negatively moderates the effects of public leadership on public service motivation and the effects of public service motivation on TCB;(3) under the high political skill level of subordinates, public leadership has a direct impact on the TCB, while under the low political skill level of subordinates, the direct effect of public leadership on the TCB is insignificant.
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Objective: To study the clinical characteristics of diabetes mellitus with Coronavirus disease 2019 (COVID-19) and explore the possible mechanism of diabetes predisposition. Method(s): A single center, retrospective and observational study was used to collect 48 inpatients diagnosed with COVID-19 who were admitted to the first ward of the third department of infection, Raytheon hospital, Wuhan from February 23, 2020 to March 30, 2020. Demographic data, symptoms, laboratory tests, comorbidities, treatments and clinical outcomes have been collected. The patients were divided into non-diabetic group and diabetic group according to the combination of diabetes. The clinical data and laboratory test results of the two groups were observed, and the t test, non-parametric test and Chi square test were used for comparison. Result(s): All the 5 patients with COVID-19 diabetes mellitus had fever and respiratory symptoms, chest CT was consistent with typical COVID-19 imaging features, and novel coronavirus nucleic acid test results were positive. There were no statistically significant differences in age, gender composition, co-existing diseases, clinical symptoms, clinical typing, disease course and treatment plan between the diabetic group and the non-diabetic group (P>0.05).There was a statistically significant difference in fasting blood glucose between the non-diabetic group and the diabetic group (P<0.05).The difference of fasting blood glucose at discharge from the diabetes group compared with that at admission was also statistically significant (P<0.05).There was no statistically significant difference between the two groups in other laboratory examination indexes (P>0.05). Conclusion(s): COVID-19 patients with diabetes are mainly manifested by fever and respiratory symptoms.Chest CT shows typical COVID-19 imaging features.Copyright © 2020 by the Chinese Medical Association.
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This chapter, "Flexible Employment Development in Post-COVID Economic Revival” as it flows from the title, is devoted to flexible employment in post-pandemic period. The economic shock caused by the COVID-19 pandemic has had profound impacts on the labor market. Compared with regular employment, flexible employment represented by non-standard employment, part-time job, self-employment and other forms that rely on the Internet platform have played an increasingly more important role in China's economic revival. This chapter focuses on flexible employment development during the post-COVID economic recovery in China. Specifically, it summarizes the current situation of flexible employment in China in the post-COVID era first, and then further discusses the factors that may affect flexible employment as well as potential barriers under the global spread of COVID-19. On this basis, some possible suggestions are put forward. With a more flexible labor market in the future, greater attention should be paid to stabilizing employment;in addition, policies should be strengthened to support workers and enterprises, along with appropriate standards of flexible employment and comprehensive social protection systems. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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The current epidemic of Corona Virus Disease 2019 (COVID-19) poses a serious threat to people's health and lives. Following the national policies and deployment, medical community in China invests large amounts of medical resources to help Hubei. However, some hospitals nationwide have suspended outpatient and inpatient services. The authors analyze the underlying causes of suspension of medical services and its harm to patients, and summarize the optimization of disease diagnosis and treatment during the COVID-19 outbreak. In further, they propose reasonable suggestions on safe medical management in general hospitals outside the epidemic area, in order to attract the attention of medical institutions and medical colleagues.Copyright © 2020 by the Chinese Medical Association.
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Objective: To study the clinical characteristics of diabetes mellitus with Coronavirus disease 2019 (COVID-19) and explore the possible mechanism of diabetes predisposition. Method(s): A single center, retrospective and observational study was used to collect 48 inpatients diagnosed with COVID-19 who were admitted to the first ward of the third department of infection, Raytheon hospital, Wuhan from February 23, 2020 to March 30, 2020. Demographic data, symptoms, laboratory tests, comorbidities, treatments and clinical outcomes have been collected. The patients were divided into non-diabetic group and diabetic group according to the combination of diabetes. The clinical data and laboratory test results of the two groups were observed, and the t test, non-parametric test and Chi square test were used for comparison. Result(s): All the 5 patients with COVID-19 diabetes mellitus had fever and respiratory symptoms, chest CT was consistent with typical COVID-19 imaging features, and novel coronavirus nucleic acid test results were positive. There were no statistically significant differences in age, gender composition, co-existing diseases, clinical symptoms, clinical typing, disease course and treatment plan between the diabetic group and the non-diabetic group (P>0.05).There was a statistically significant difference in fasting blood glucose between the non-diabetic group and the diabetic group (P<0.05).The difference of fasting blood glucose at discharge from the diabetes group compared with that at admission was also statistically significant (P<0.05).There was no statistically significant difference between the two groups in other laboratory examination indexes (P>0.05). Conclusion(s): COVID-19 patients with diabetes are mainly manifested by fever and respiratory symptoms.Chest CT shows typical COVID-19 imaging features.Copyright © 2020 by the Chinese Medical Association.
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The root of Isatis tinctoria L. is highly appreciated as a Traditional Chinese herbal medicine for the prevention and adjuvant treatment of respiratory diseases caused by coronaviruses viruses such as SARS and COVID-19. I. tinctoria hairy root cultures (ITHRCs) provide a better alternative to field cultivation for the production of antiviral flavonoids. For the first time, ITHRCs were exposed to different colors of LED lights i.e., red, green, blue, red/green/blue (1/1/1, RGB), and white, in an attempt to promote the root growth and enhance the production of bioactive flavonoids. Results revealed that the biomass productivity (7.15 ± 0.63 g/L) in ITHRCs with an initial inoculum size of 0.2% cultured for 50 days under blue light increased by 1.86-fold relative to that under dark (control), and yields of rutin (320.49 ± 27.56 μg/g DW), quercetin (388.75 ± 9.17 μg/g DW), kaempferol (787.90 ± 83.43 μg/g DW), and isorhamnetin (269.11 ± 20.08 μg/g DW) increased by 4.15-fold, 9.31-fold, 9.09-fold, and 2.88-fold as compared with control, respectively. Interestingly, the emergence of adventitious buds was noticed in ITHRCs under all light treatments. Additionally, the enhanced densities of chloroplasts and root hairs were found in blue-light grown ITHRCs as against control, which might account for the elevated biomass productivity. Moreover, blue light induced oxidative stress in ITHRCs in terms of the overproduction of oxidation products and the enhancement of antioxidant enzyme activity. Furthermore, blue light significantly activated photoreceptor (CRY1) and key regulator of light signaling (HY5), thus leading to the up-regulated expression of MYB4 and structural genes (such as CHS and FLS) responsible for flavonoid biosynthesis. And, the transcriptional activation of CUC1 was likely related to the formation of adventitious buds in ITHRCs. Overall, the simple supplementation of blue LED light makes ITHRCs more attractive as plant factories for obtaining higher productivity of biomass and medicinally important flavonoids. © 2023 Elsevier B.V.
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Hospital ward is one of non-negligible potential places to occur cross-infection among patients and health workers. Air-borne transmission was regarded as the main infection route of the SARS-CoV-2. Preventing the air-borne transmission should be a significant measure, which could effectively mitigate the risk of the virus infection. Based on those consideration, in this study, the influence of different types of air distribution on ventilation effectiveness was modeled through Computational Fluid Dynamics (CFD) simulations. Several typical negative pressure wards same as the ward in Wuhan Thunder God Mountain hospital and conformed to the Chinese National Health Commission (NHC) guidelines were modelled. We simulated the influence of different locations of air supply inlets, analysed the influence of the buffer door and compared the contaminant concentration on different entry route for health workers. The results show that the air distribution required by NHC guidelines could retain a directional airflow from the bed-zone to the toilet, which also has a better accessibility of supply air, and health workers are safer to avoid standing closed to the air exhaust outlet in the downstream area of pollutants during ward rounds. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/)
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The problem of missing persons is a major global challenge, which causes serious harm to their families and societies. For this study, we collected 9,193 U.S. missing-persons records for the years 1996-2021 from the Doe Network platform. We used mathematical statistics and Moran's I index to analyze the sociodemographic characteristics, spatio-temporal distribution and its evolution patterns. Then the geodetector was applied to conduct an in-depth analysis of the influencing factors in socio-cultural, economic and demographic aspects. Based on above findings, a sociological theory of the formation mechanism of the missing-person phenomenon in the United States was proposed. Major findings included: (1) With age increasing, the number of missing persons initially increased and then dropped gradually. The highest missing rate was found among adolescents (13-18 years old) and adults (19-59 years old). Although more males than females were reported missing, the high-incidence period of males lagged slightly behind that of females. The high missing rate among adolescent females was linked to sexual crimes, including sex trafficking and rape, while that of adult men tended to be caused by family discord or debt problems. Among racial groups, black people faced the greatest risk of going missing. (2) From 1996, the number of missing-person incidents initially showed a wave upward trended and then fell sharply, after peaking in 2017, because of a series of immigration regulations. In 2020, it declined dramatically again, due to COVID-19. Influenced by the temperature, school holidays, and festivals, most people were reported missing during the months of June, August, and December. Only few missing incidents happened between February and April. (3) Spatially, at the state level, the missing population distribution decreased from the coastal border area to the inland area;over time, areas with a great number of missing-person incidents advanced simultaneously from the eastern and western coastal areas and the southern US-Mexico border to US inland areas. At the county level, they were concentrated on the edge and scattered internally. (4) Missing-person incidents were caused by the interaction of multiple factors;regional population mobility, fertility rate, and the number of vulnerable people had a positive impact on numbers of missing people, while per capital GDP had a negative impact. The power of population-based environmental factors was significantly enhanced after be interacted with social and economic factors, on explaining the missing-person spatial distribution, all of which were above 80%. (5) The underlying mechanism of missing-person incidents could be understood from the perspective of "social anomie". In other words, the disconnect between social goals and means led to social anomie, which then induced deviant behavior, including abduction, murder, and running away from home, increasing the likelihood of missing-person incidents. Finally, we offered suggestions for disappearance prevention and further study directions. The findings provided a basic understanding of the missing-person phenomenon, contributing to global scientific information, which could aid in preventing missing-person incidents. © Starobulgarska Literatura 2022.
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Bipolar disorder (BD) is a highly pathological disorder that is often misdiagnosed or undiagnosed. The main treatment is a combination of psychotherapy and medication. Traditional psychotherapy is affected by factors such as time, space, shortage of professional psychotherapists and patients' stigma, and has low availability. In terms of drug therapy, patients' medication compliance is poor, leading to repeated illness. The epidemic of coronavirus in 2019, closed management and telemedicine provide new ideas for the treatment of BD. Telemedicine can provide convenient medical services, promote disease rehabilitation, effectively guide patients' self-management, improve patients' treatment compliance, and prevent disease recurrence. This paper analyzes and summarizes the research related to telemedicine in BD, including the origin and significance, technical methods and application effects. To provide a reference for the application of telemedicine in patients with BD. © 2022 ACM.
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While the immunogenicity of inactivated vaccines against coronavirus disease 2019 (COVID-19) has been characterized in several well-conducted clinical trials, real-world evidence concerning immune responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) raised by such vaccines is currently missing. Here, we comprehensively characterized various parameters of SARS-CoV-2-specific cellular and humoral immune responses induced by inactivated COVID-19 vaccines in 126 individuals under real-world conditions. After two doses of vaccination, S-receptor binding domain IgG (S-RBD IgG) and neutralizing antibody (NAb) were detected in 87.06% (74/85) and 78.82% (67/85) of individuals, respectively. Female participants developed higher concentrations of S-RBD IgG and NAb compared to male vaccinees. Interestingly, a longer dosing interval between the first and second vaccination resulted in a better long-term SARS-CoV-2 S-RBD IgG response. The frequencies of CD4+ T cells that produce effector cytokines (IFN-gamma, IL-2, and TNF-alpha) in response to stimulation with peptide pools corresponding to the SARS-CoV-2 spike (S), nucleocapsid (N) or membrane (M) protein were significantly higher in individuals received two doses of vaccine than those received one dose of vaccine and unvaccinated individuals. S, N, or M-specific CD4+ and CD8+ T cell responses were detectable in 95.83% (69/72) and 54.16% (39/72) of double-vaccinated individuals, respectively. The longitudinal analysis demonstrated that CD4+ T cell responses recognizing S, N, and M waned quickly after a single vaccine dose, but were boosted and became more sustained following a second dose. Overall, we provide a comprehensive characterization of immune responses induced by inactivated COVID-19 vaccines in real-world settings, suggesting that both humoral and cellular SARS-CoV-2 specific immunity are elicited in the majority of individuals after two doses of inactivated COVID-19 vaccines.
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The immense reduction in aerosol levels during the COVID-19 pandemic provides an opportunity to reveal how atmospheric chemistry is regulating our climate, among which the effect of aerosols on climate is a phenomenon of great interest but still in hot debate. The Intergovernmental Panel on Climate Change (IPCC) has continually identified the effect of aerosols on climate to have the largest uncertainty among the factors contributing to global climate change. Several studies indicate an inverse relationship between aerosol presence in the atmosphere and the diurnal surface air temperature range (DTR). Herein, we test this relationship by analyzing the DTR values from in situ weather station records for periods before and during the COVID-19 epidemic in Chinawhere aerosol levels have substantially reduced, compared with the climatological mean levels for a 19 year period.Our analyses find that DTRs fromFebruary to June during the COVID-19 pandemic are greater than 3 standard deviations above the climatological mean DTR. This anomaly has never occurred before in the 21st century and is at least in part associated with the observed reduction in aerosols. © 2021 The Author(s).
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COVID-19 is a severe global epidemic in human history. Even though there are particular medications and vaccines to curb the epidemic, tracing and isolating the infection source is the best option to slow the virus spread and reduce infection and death rates. There are three disadvantages to the existing contact tracing system: 1. User data is stored in a centralized database that could be stolen and tampered with, 2. User's confidential personal identity may be revealed to a third party or organization, 3. Existing contact tracing systems [1] [2] only focus on information sharing from one dimension, such as location-based tracing, which significantly limits the effectiveness of such systems. We propose a global COVID-19 information sharing and risk notification system that utilizes the Blockchain, Smart Contract, and Bluetooth. To protect user privacy, we design a novel Blockchain-based platform that can share consistent and non-tampered contact tracing information from multiple dimensions, such as location-based for indirect contact and Bluetooth-based for direct contact. Hierarchical smart contract architecture is also designed to achieve global agreements from users about how to process and utilize user data, thereby enhancing the data usage transparency. Furthermore, we propose a mechanism to protect user identity privacy from multiple aspects. More importantly, our system can notify the users about the exposure risk via smart contracts. We implement a prototype system to conduct extensive measurements to demonstrate the feasibility and effectiveness of our system.
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To explore the effect of Multi-Disciplinary Team (MDT) mode in the diagnosis and treatment of Coronavirus Disease 2019 (COVID-19) Pneumonia. A total of 65 patients with suspected COVID-19 pneumonia were included. On February 8, 2020, our hospital officially became a designated hospital for the treatment of COVID-19, and the MDT mode was implemented throughout the diagnosis and treatment for newly admitted patients with suspected COVID-19. The patients were divided into control group and observation group according to whether received MDT mode. Our results showed that the diagnosis time in the observation group was significantly shortened than that in the control group (2.51 days vs. 3.47 days) (p < 0.05). The average daily hospitalization costs in the observation group was significantly decreased in comparison with the control group (¥766.1 vs. ¥1190.4) (p < 0.001). The average daily cost of protective materials in the observation group was significantly reduced in comparison with the control group (¥4226.90 vs. ¥5308.20) (p < 0.001). Compared with the control group, the subjective symptoms of patients in the observation group were significantly improved (p < 0.001). In conclusion, the MDT mode shortens the diagnosis time of, reduces the hospitalization costs, and improves the subjective symptoms of COVID-19. © 2022, Sociedade Brasileira de Ciencia e Tecnologia de Alimentos, SBCTA. All rights reserved.
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Purpose: The sudden COVID-19 epidemic in 2019 has frustrated China's overall economy, and the implementation and development of the National Fitness Program has encountered huge obstacles. At a new historical starting point, in order to realize the dream of becoming a powerful country in sports, it is necessary to transform the successful experience gained since the reform and opening up into regular understanding and systematic theories, so as to make a theoretical response to the new contradictions and challenges faced in development and give full play to the National Fitness has comprehensive values and multiple functions in improving people's health, promoting people's all-round development, promoting economic and social development and demonstrating the country's cultural soft power. Design/methodology/approach: Taking the topic of national fitness as an example, this paper sets out from the three dimensions of knowledge input, knowledge output and knowledge production, using citation analysis, social network analysis, co-word analysis and cluster analysis, to measure the characteristics and knowledge structure of interdisciplinary knowledge exchange. Findings: China's national fitness is still in the primary development stage, and the strong boost of the national top-level policy is the biggest driving force of its development, driven by the policy together with the settlement of many major events, constantly improving and enriching the wings. The main body of knowledge production on the topic of national fitness is mainly colleges and universities, with low participation of government and enterprises, high degree of cooperation among authors, obvious interdisciplinary characteristics and strong application of research themes. Originality/value: This study provides a strong theoretical basis for the promotion of the Healthy China strategy. Especially under the influence of COVID-19, this paper can contribute to the comprehensive value and multimodal functions of national fitness in improving the health of people, promoting economic and social development and demonstrating the soft power of national culture. © 2022, Emerald Publishing Limited.
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The worldwide spread of COVID-19 has made a severe impact on human health and life. It has shown rapid propagation, long in vitro survival, and a long incubation period. More seriously, COVID-19 is more susceptible to variation, as it is an RNA virus. Mutations of COVID-19 have been reported in multiple countries worldwide, which makes drug and vaccine development a significant challenge. To search for potential drugs and vaccines and reveal the atlas of COVID-19 evolution, we extract information from massive unstructured data and construct a COVID-19 knowledge graph using the COVID-19 data. Based on machine learning approaches, we infer and predict novel coronavirus pneumonia-related diseases, drug action targets, etc. to speculate on new and more effective treatment methods. In addition, to study transcriptome of SARS-CoV-2, new ideas can be provided to biomedical experts with flexible responses to viral variation. An in-depth analysis of the COVID-19 pathomechanism at the pharmaceutical, genetic, and protein levels provides effective means and tools for novel coronavirus pneumonia vaccines, drug development, and therapeutic program design. © 2021 IEEE.
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The COVID-19 that emerged at the end of 2019 is the biggest public health emergency encountered by human in the past 100 years. In the face of COVID-19, people need to get correct, comprehensive and clear information. However, traditional information retrieval methods only return a collection of related web pages, and users need to distinguish the authenticity from redundant and complicated information. Therefore, such information acquisition methods are inefficient and cannot serve users well. To meet the needs of users for related information, it is necessary to study the question answering system for the COVID-19. This paper studies and builds a COVID-19 question answering system based on knowledge graph. In the System, the question answering function is realized by template matching, which based on the Naive Bayes algorithm. For the input questions, the system firstly performs entity recognition, using entity type labeling combined with entity similarity matching to identify entities in the user's questions. Then the system predicts the user's question intention and use the trained question classifier to predict the category number. Finally Cypher is utilized to query graph database to generate and output the answer. The system implemented in this paper can help users quickly obtain the information they want and improve the user's information acquisition efficiency. The system can provide people convenient and fast ways of obtaining information about COVID-19, such as medical treatment, health, materials, prevention and control, scientific research, so as to help people take precautions against diseases and decrease the incidence of COVID-19. © 2021 IEEE.
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Purpose The outbreak and continuation of COVID-19 have spawned the transformation of traditional teaching models to a certain extent. The Chinese Ministry of Education's guidance on "keep learning and teaching during class suspension" has made OTC and learning (OTC) become routinized, and the public's emotional attitudes toward OTC have also evolved over time. The purpose of this study is to segment the emotional text data and introduce it into the topic model to reveal the evolution process and stage characteristics of public emotional polarity and public opinion of OTC topics during public health emergencies in the context of social media participation. The research has important guiding significance for the development of OTC and can influence and improve the efficiency and effect of OTC to a certain extent. The analysis of online public opinion can provide suggestions for the government and media to guide the trend of public opinion and optimize the OTC model. Design/methodology/approach This paper takes the topic of "OTC" on Zhihu during the COVID-19 epidemic as an example, combined with the characteristics of public opinion changes, chooses Boson emotional dictionary and time series analysis method to build an OTC network public opinion theme evolution analysis framework that integrates emotional analysis and topic mining. Finally, an empirical analysis of the dynamic evolution of the communication network for each stage of the life cycle of a specific topic is realized. Findings This paper draws the following conclusions: (1) Through the emotional value table and the change trend chart of the number of comments, the analysis found that the number of positive comments is greater than the number of negative comments, which can be inferred that the public gradually accepts "OTC" and presents a positive emotional state. (2) By observing the changing trend of the average daily emotional value of the public, it is found that the overall emotional value shows a stable development trend after a large fluctuation. From the actual emotional value and the fitted emotional value curve, it can be seen that the overall curve fit is good, so ARIMA (12, 1, 6) can accurately predict the dynamic trend of the daily average emotional value in this paper. Therefore, based on the above-mentioned public opinion, emotional analysis research, relevant countermeasures and suggestions are put forward, which is conducive to guiding the development direction of public opinion in a positive way. Originality/value Taking the topic of "OTC" in Zhihu as an example, this paper combines Boson emotional dictionary and time series to conduct a series of research analyses. Boson emotional dictionary can analyze the public's emotional tendency, and time series can well analyze the intrinsic structure and complex features of the data to predict the future values. The combination of the two research methods allows for an adequate and unique study of public emotional polarization and the evolution of public opinion.
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Since the inception of China's Belt and Road Initiative (BRI) in 2013, the associated infrastructure and transport and economic corridor developments have been widely addressed in the research field of transportation, logistics and supply chain management. Such developments open windows of opportunity for accommodating trade flows in new or upgraded intermediate hub nodes and gateway locations along the BRI corridors. This paper aims to propose strategic locations for global logistics distribution centers (LDCs) along the Belt and Road from the viewpoint of China, considering regional economic and trade blocks, maritime transport routes, China's overseas port developments, China Railway Express services, trade conflicts between China and US, and deteriorated mobility of resources and human power caused by COVID-19. We present a set of strategic locations for establishing LDCs by analyzing qualitative and quantitative facility location factors supported by the findings in existing literature. Eight locations for global LDCs are identified in the Sub-Saharan region, Sri Lanka, the Middle East, Northern Oceania, Southern Europe, Northern Europe, and key dry hub port locations in Minsk, Belarus and Northeast Asia along the Silk Road Economic Belt. Furthermore, we present a research agenda with applicable methods. © 2021 Elsevier Ltd