The reliability of colorimetry is precise(ly) as expected.

Figure S6. Gene ontology (GO) analysis of the differentially expressed genes between C1 and C2. (JPG 403 kb

A multi-criteria group decision-making method with fuzzy preference relations based on filtration-and-weighting-based triangular bounded consistency

In multi-criteria group decision-making (MCGDM) problems with incomplete fuzzy preference relations (FPRs), the consistency based on bounded rationality is preferred to depend on the historical preferences of decision makers to generate complete FPR matrices. There are two factors in influencing the effect of historical preferences on complete FPR matrices and further decision makers’ satisfaction of group solutions. One is the effectiveness of historical preferences and the other is their relative weights. On this basis, this paper proposes a new MCGDM method with FPRs based on the filtration-and-weighting-based triangular bounded consistency (FWBTBC), where historical FPRs between three adjacent pairs of alternatives are characterized by triangles and these two factors are considered comprehensively. A triangle filtration process is designed based on the Grubbs criterion to filter the abnormal triangles in the collected ones. A weight determination process is developed, where a distance measure between remaining triangles is constructed to calculate their weights. Based on the combination of the two processes, the FWBTBC of FPRs is created and then the proposed method is presented. The validity of the proposed method is demonstrated by its application in analyzing a drainage tube supplier selection problem for a tertiary hospital located in Hefei, Anhui, China.</p

Exergy Analysis and Heat Integration of a Coal-Based Oxy-combustion Power Plant

Oxy-combustion is a competitive technology to enable the capture of CO₂ from coal-based power plants. The main challenge to implement this technology is the large energy penalty and investment cost related to CO₂ capture. A comprehensive exergy analysis has been performed for an entire coal-based oxy-combustion power plant. The exergy flows and irreversibilities are presented. The thermal efficiency penalty related to CO₂ capture is about 9.4 percentage points (on the basis of the higher heating value) and is mainly caused by the air separation unit and the CO₂ compression and purification unit. The theoretical minimum is 3.4 percentage points when the two units are assumed to be reversible, where the air separation unit contributes 1.4 percentage points and the CO₂ compression and purification unit is responsible for 2.0 percentage points. The compression processes are causing the largest exergy losses related to CO₂ capture. The case studies show that the integration of the compression heat with the steam cycle can increase the thermal efficiency by up to 0.72 percentage points

Aggregated IDPRs between neighboring candidates in the manager selection problem.

<p>Aggregated IDPRs between neighboring candidates in the manager selection problem.</p

The comparison of the combinations of <i>b</i>_<i>j</i> generated by using the four sets of functions for the manager selection problem.

<p>The comparison of the combinations of <i>b</i>_<i>j</i> generated by using the four sets of functions for the manager selection problem.</p

Possibility matrix of the five candidates in the manager selection problem.

<p>Possibility matrix of the five candidates in the manager selection problem.</p

The comparison of the combinations of <i>a</i>_<i>j</i> generated by using the four sets of functions for the manager selection problem.

<p>The comparison of the combinations of <i>a</i>_<i>j</i> generated by using the four sets of functions for the manager selection problem.</p

The six sets of functions for the least square method and their relevant optimization results.

<p>The six sets of functions for the least square method and their relevant optimization results.</p

Process of generating a solution to the MCGDM problem with IDPRs.

<p>Process of generating a solution to the MCGDM problem with IDPRs.</p

Score intervals of the group IDPRs between neighboring candidates in the manager selection problem.

<p>Score intervals of the group IDPRs between neighboring candidates in the manager selection problem.</p