Rescuing emergency cases of COVID-19 patients: An intelligent real-time MSC transfusion framework based on multicriteria decision-making methods

Applied Intelligence - Mesenchymal stem cells (MSCs) have shown promising ability to treat critical cases of coronavirus disease 2019 (COVID-19) by regenerating lung cells and reducing immune...     

Apparent inhibition of thermal decomposition of hydrogencarbonate ion by poly(acrylic acid). The effect of molar mass and end-group functionality

The thermal decomposition of the hydrogencarbonate ion has been previously described by a bimolecular mechanism or a unimolecular mechanism. In this work the Gibbs free energy of the competing reactions for both the unimolecular and bimolecular mechanisms was calculated for typical concentrations found in thermal desalination plants. Activity coefficients were estimated using the Pitzer equations. At low temperature the bimolecular mechanism is thermodynamically favored, while above 80 °C the unimolecular mechanism is favored, consistent with observations of alkaline scale formation in thermal desalination plants. The rate coefficient of thermal decomposition of HCO₃⁻ at 97.2 °C in the absence and presence of 10 ppm of poly(acrylic acid) (PAA) with different end groups and molar mass was determined. PAA was found to retard the rate of decomposition by up to 49% and for all end groups of PAA the rate coefficient of thermal decomposition of 40 ppm HCO₃⁻ increased with increasing molar mass. The results are consistent with PAA preventing heterogeneous decomposition of HCO₃⁻ on interfaces. The rate of partitioning of PAA to these interfaces should increase with decreasing molar mass and resulting mobility of PAA, and may also be affected by self-assembly behavior.     

Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.