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Evaluating Critical Influencing Factors of Desalination by Membrane Distillation Process-Using Multi-Criteria Decision-Making.

ABSTRACT: Water desalination by membrane distillation (MD) can be affected by a wide range of operating parameters. The present work uses combinational approach of Analytical Hierarch process (AHP) and Fuzzy Analytical Hierarchy process (Fuzzy-AHP) to identify the most important parameters in the MD desalination. Five process parameters and key-performance indicators, named derivable outputs (DOs), are considered, along with the critical factors affecting these DOs in the current study. The DOs and the critical influencing factors (CIFs) are selected based on their experimental feasibility. The investigation involves five DOs, which are liquid entry pressure, thermal power consumption, permeate quality, permeate flux, and pumping (feed circulation) power. A total of twenty-five critical influencing factor were associated with the DOs. The identification of the DOs and CIFs was based on the literature review, and further analyses were performed. Both methods, AHP and Fuzzy-AHP, determined six extremely important CIFs in the desalination MD, which are feed temperature, feed concentration, or feed salinity; feed flow rate; membrane hydrophobicity; pore size; and membrane material. Moderately important CIFs are found to be four by both methods. These common CIFs are feed solution properties, membrane thickness, feed channel geometry, and pressure difference along the feed channel. Finally, the least preferred CIFs are four common in both methods that are MD configuration, duration of test, specific heat of feed solution, and viscosity.

SUBMITTER: Anqi AE

PROVIDER: S-EPMC7996794 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Chronic pain is one of the most common complaints of cancer patients. There are many pharmacological and non-pharmacological treatment modalities used for the treatment of pain. Nonetheless, non-pharmacological interventions are preferred because of potential side effects in cases resistant to medical therapy that require a dose increase or potent drug use. In most real-life situations, the decision on which technique to choose is based on the clinical but subjective decisions of the practitioners. This study aimed to find out the best non-pharmacological treatment option for patients with chronic cancer pain by following a rational and reasonable approach. METHODS:Since the evaluation of treatment options requires to make a comparison between a number of alternatives in the light of certain criteria, we utilize the order relation analysis (G1-method) which is a method for determining the weights based on the improved Analytic Hierarchy Process (AHP). The method uses the relative importances on prioritizing the four criteria and eight sub-criteria defined by the experts of three pain physicians, one oncologist, and one oncologic surgeon. Four alternatives are then compared according to the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) using the verbal subjective judgments of the practitioners. RESULTS:Obtained results indicate that the general medical condition of the patient and the stage of the cancer are the essential factors in the selection of the treatment method. It is followed by the extent of the pain and the level of evidence, respectively. According to the evaluations performed, spinal port and splanchnic nerve radiofrequency thermocoagulation treatments are the first and second priority methods for pain treatment, respectively, compared to lumbar epidural catheter and celiac plexus block. CONCLUSIONS:The results of this study emphasize the need to integrate critical criteria into the decision-making process objectively. This is the first study in which multi-criteria decision-making tools are used in the evaluation and selection of pain management methods in cancer patients.

Project description:The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding "by eye" may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

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Evaluating Critical Influencing Factors of Desalination by Membrane Distillation Process-Using Multi-Criteria Decision-Making.

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