Sustainable supply chain management in stakeholders:supporting from sustainable supply and process management in the healthcare industry in Vietnam

© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. Prior studies presented the sustainable supply chain management practices, but an approach from stakeholders is still untapped. The interaction between forward and reverse flows also needs to be involved in investment recovery. Sustainable supply chain management is an increasing concern in the environmental, social and economic performance. This study uses fuzzy Delphi method to validate a set of criteria and uses exploratory factor analysis to confirm the aspects. This study applies stakeholder theory in combination with fuzzy set theory and decision-making trial and evaluation method to explore the interrelationships among attributes. The results show that sustainable supply management and process management are the major cause aspects. Investment recovery has not been noticed in the healthcare industry, reflected in the weak interaction. The top five criteria are supplier assessment, environmental management systems, green certification of supplier, supplier collaboration and health and safety certifications. This study provides theoretical and managerial implications

Toward Sustainability:Using Big Data to Explore Decisive Supply Chain Risk Factors Under Uncertainty

Rapid market changes aimed at sustainability have led to supply chain risks and uncertainties in the Taiwanese light-emitting diode industry. These risks and uncertainties can be captured by social media, quantitative and qualitative data (referred to herein as big data), but the industry has been unable to manage this information boom to respond to customer needs. These various types of data have their own characteristics that affect decision making about developing firm capabilities. This study aggregates the various data to undertake an extensive investigation of supply chain risks and uncertainties. Specifically, this study proposes using the fuzzy and grey Delphi methods to identify a set of reliable attributes and, based on these attributes, transforming big data to a manageable scale to consider their impacts. Subsequently, both the fuzzy and grey Decision Making Trial and Evaluation Laboratories applied to determine the causal relationships for supply chain risks and uncertainties. The results reveal that capacity and operations have greater influence than other supply chain attributes and that risks stemming from triggering events are difficult to diagnose and control. The implications, conclusions and findings are addressed

Modulating Microglia/Macrophage Activation by CDNF Promotes Transplantation of Fetal Ventral Mesencephalic Graft Survival and Function in a Hemiparkinsonian Rat Model

Parkinson's disease (PD) is characterized by the loss of dopaminergic neurons in substantia nigra pars compacta, which leads to the motor control deficits. Recently, cell transplantation is a cutting-edge technique for the therapy of PD. Nevertheless, one key bottleneck to realizing such potential is allogenic immune reaction of tissue grafts by recipients. Cerebral dopamine neurotrophic factor (CDNF) was shown to possess immune-modulatory properties that benefit neurodegenerative diseases. We hypothesized that co-administration of CDNF with fetal ventral mesencephalic (VM) tissue can improve the success of VM replacement therapies by attenuating immune responses. Hemiparkinsonian rats were generated by injecting 6-hydroxydopamine (6-OHDA) into the right medial forebrain bundle of Sprague Dawley (SD) rats. The rats were then intrastriatally transplanted with VM tissue from rats, with/without CDNF administration. Recovery of dopaminergic function and survival of the grafts were evaluated using the apomorphine-induced rotation test and smallanimal positron emission tomography (PET) coupled with [F-18] DOPA or [F-18] FE-PE2I, respectively. In addition, transplantation-related inflammatory response was determined by uptake of [F-18] FEPPA in the grafted side of striatum. Immunohistochemistry (IHC) examination was used to determine the survival of the grated dopaminergic neurons in the striatum and to investigate immune-modulatory effects of CDNF. The modulation of inflammatory responses caused by CDNF might involve enhancing M2 subset polarization and increasing fractal dimensions of 6-OHDA-treated BV2 microglial cell line. Analysis of CDNF-induced changes to gene expressions of 6-OHDA-stimulated BV2 cells implies that these alternations of the biomarkers and microglial morphology are implicated in the upregulation of protein kinase B signaling as well as regulation of catalytic, transferase, and protein serine/threonine kinase activity. The effects of CDNF on 6-OHDA-induced alternation of the canonical pathway in BV2 microglial cells is highly associated with PI3K-mediated phagosome formation. Our results are the first to show that CDNF administration enhances the survival of the grafted dopaminergic neurons and improves functional recovery in PD animal model. Modulation of the polarization, morphological characteristics, and transcriptional profiles of 6-OHDA-stimualted microglia by CDNF may possess these properties in transplantation-based regenerative therapies.Peer reviewe

Modulating Microglia/Macrophage Activation by CDNF Promotes Transplantation of Fetal Ventral Mesencephalic Graft Survival and Function in a Hemiparkinsonian Rat Model

Parkinson’s disease (PD) is characterized by the loss of dopaminergic neurons in substantia nigra pars compacta, which leads to the motor control deficits. Recently, cell transplantation is a cutting-edge technique for the therapy of PD. Nevertheless, one key bottleneck to realizing such potential is allogenic immune reaction of tissue grafts by recipients. Cerebral dopamine neurotrophic factor (CDNF) was shown to possess immune-modulatory properties that benefit neurodegenerative diseases. We hypothesized that co-administration of CDNF with fetal ventral mesencephalic (VM) tissue can improve the success of VM replacement therapies by attenuating immune responses. Hemiparkinsonian rats were generated by injecting 6-hydroxydopamine (6-OHDA) into the right medial forebrain bundle of Sprague Dawley (SD) rats. The rats were then intrastriatally transplanted with VM tissue from rats, with/without CDNF administration. Recovery of dopaminergic function and survival of the grafts were evaluated using the apomorphine-induced rotation test and small-animal positron emission tomography (PET) coupled with [18F] DOPA or [18F] FE-PE2I, respectively. In addition, transplantation-related inflammatory response was determined by uptake of [18F] FEPPA in the grafted side of striatum. Immunohistochemistry (IHC) examination was used to determine the survival of the grated dopaminergic neurons in the striatum and to investigate immune-modulatory effects of CDNF. The modulation of inflammatory responses caused by CDNF might involve enhancing M2 subset polarization and increasing fractal dimensions of 6-OHDA-treated BV2 microglial cell line. Analysis of CDNF-induced changes to gene expressions of 6-OHDA-stimulated BV2 cells implies that these alternations of the biomarkers and microglial morphology are implicated in the upregulation of protein kinase B signaling as well as regulation of catalytic, transferase, and protein serine/threonine kinase activity. The effects of CDNF on 6-OHDA-induced alternation of the canonical pathway in BV2 microglial cells is highly associated with PI3K-mediated phagosome formation. Our results are the first to show that CDNF administration enhances the survival of the grafted dopaminergic neurons and improves functional recovery in PD animal model. Modulation of the polarization, morphological characteristics, and transcriptional profiles of 6-OHDA-stimualted microglia by CDNF may possess these properties in transplantation-based regenerative therapies

Assessing a hierarchical sustainable solid waste management structure with qualitative information:policy and regulations drive social impacts and stakeholder participation

This study contributes to building a valid hierarchical sustainable solid waste management (SSWM) attribute set with qualitative information, which is a complicated and ambiguous problem with uncertainties. Few studies have provided qualitative information and have addressed the interrelationships and interdependencies among the hierarchical SSWM attributes. SSWM has recently become a difficult problem to solve due to urbanization, inequality, and economic growth. This study aims to propose an SSWM attribute set and identify a causal model through linguistic preferences by using a fuzzy decision-making trial and evaluation laboratory approach to simultaneously handle the uncertainty and the interrelationships. The analytic network process is used to develop the hierarchical structure to weigh the aspects and criteria. Qualitative information is transformed into crisp and comparable values to examine the causal relationships between attributes and confirm the consistency between the theoretical structure and industry phenomena. The results indicate that policy and regulations, stakeholder participation, and social impacts play essential roles in these causal interrelationships. Political leadership in SSWM is required to drive stakeholder participation and achieve social impacts. Population growth and migration, institutional settings, waste recycling and energy recovery, households, and private contractors are the main aspects involved in improving SSWM in Vietnam

A Hybrid Approach to Explore the Risk Dependency Structure among Agribusiness Firms

Although the risk management of agricultural firms is important, studies on the extreme risk dependence among agribusiness firms are minimal due to the diversity and complexity of the risks faced by agricultural firms. In this study, we developed a hybrid approach to analyse and uncover the potential risk dependence among agricultural firms. We examined thirty-two agricultural companies to study their dependence structure for risk losses. Three primary findings emerged. First, risk dependence is strong with an average value of 0.96. Second, the dependence structure is hierarchical and includes two network communities. Third, some key agricultural firms were identified in the dependence structure. These key firms are critical for the transmission of negative impacts across agricultural firms. Correspondingly, we suggest measures and strategies (such as improving the level of technological innovation and joint risk resistance capability) to reduce the impact of risk dependence