New family of intuitionistic fuzzy operators for aggregation of information on interactive criteria/attributes in Multi-Criteria/attributes Decision Making (MCDM/MADM) problems are constructed. New aggregations are based on the Choquet integral and the associated probability class of a fuzzy measure. Propositions on the correctness of the extension are presented. Connections between the operators and the compositions of dual triangular norms [Formula: see text] and [Formula: see text] are described. The conjugate connections between the constructed operators are considered. It is known that when interactions between criteria/attributes are strong, aggregation operators based on Choquet integral reflect these interactions at a certain degree, but these operators consider only consonant structure of criteria/attributes. New operators reflect interactions among all the combinations of the criteria/attributes in the fuzzy MCDM/MADM process. Several variants of new operators are used in the decision making problem regarding the assessment of software development risks.

Three new versions of the most typical value (MTV)1,2 of the population (generalized weighted averages) are introduced. The first version, WFEVg, is a generalization of the weighted fuzzy expected value (WFEV)3 for any fuzzy measure g on a finite set and it coincides with the WFEV when a sampling probability distribution is used. The second and the third version are respectively the weighted fuzzy expected intervals WFEI and WFEIg which are generalizations of the WFEV, namely, MTV s of the population for a sampling distribution and for any fuzzy measure g on a finite set, respectively, when the fuzzy expected interval (FEI)4 exists but the fuzzy expected value (FEV)4 does not. The construction process is based on the Friedman-Schneider-Kandel (FSK)3 principle and results in the new MTV s called the WFEI and the WFEIg when the combinatorial interval extension of a function5 is used.

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The definitive version of the text was subsequently published in Energy Policy, 108, 2017-09 Published by Elsevier and found at http://dx. AbstractArmenia and Georgia are taking climate change agenda seriously and contributing to efforts for mitigating global climate change through various ways including preparation of low carbon development strategies for their future economic growth. The improvement of energy efficiency is one of the key elements of the low carbon development strategies. This study develops a methodology to estimate marginal abatement cost (MAC) curve for energy efficiency measures and apply in the building sector in both countries. The study finds that among the various energy efficiency measures considered, the replacement of energy inefficient light bulbs (i.e., incandescent lamps) with efficient light bulbs is the most cost effective measure in saving energy and reducing greenhouse gas (GHG) emissions from the building sector. Most energy efficiency improvement options considered in the study would produce net economic benefits even if the value of reduced carbon is not taken into account. While the MAC analysis conducted demonstrates the cost competitiveness of various energy efficiency measures in Armenia and Georgia, the study also offers a caution to policy makers to have supplemental analysis before prioritizing the implementation of these measures or introducing policies to support them.

Background: Acute kidney injury (AKI) is a common complication among SARS-CoV-2-positive patients who undergo hospitalization. Abundant evidence exists concerning the epidemiology of AKI in patients hospitalized in the ICU for COVID-19 but limited data are available about the occurrence of AKI in SARS-CoV-2-positive patients being hospitalized in a non-ICU setting. Aim and Methods: We have carried out a retrospective study to evaluate frequency and risk factors for AKI among patients consecutively admitted at a third-level university hospital starting from February 2020 (the beginning of the first wave of the SARS-CoV-2 pandemic); all patients were hospitalized outside the ICU. Results: A total of 387 SARS-CoV-2-positive patients were included in the current study; 372 (96.1%) had SARS-CoV-2-related pneumonia. In-hospital AKI onset was recorded in 119 (30.7%) patients, mainly with AKI stage 1 (n = 74, 62.2%); eighteen (4.6%) patients reported AKI stage 3 and six (1.5%) patients had HD-dependent AKI. There were 235 (60.7%) patients with severe COVID-19, and this was more common in patients developing AKI, 94.5% (86/119) vs. 86.1% (149/268), p = 0.02. Multivariate regression model (n = 144 patients) reported an independent and significant relationship between AKI occurrence and greater levels of ferritin (p = 0.036), IL-6 (p = 0.032), and azotemia at admission (p = 0.0001). A total of 69 (17.8%) SARS-CoV-2-positive patients died and strong predictors of in-hospital death resulted from age (p < 0.0001), serum ferritin (p < 0.0001) and white blood cells (p < 0.001). According to multivariable analysis (n = 163 patients), there was a consistent link between in-hospital death and AKI stage (1) (p = 0.021) and -stage (2) (p = 0.009). Our results support the notion that AKI occurs frequently among hospitalized COVID-19 patients even in a non-ICU setting and plays a pivotal role in the mortality of this population. Further studies are ongoing in order to clearly establish the frequency of AKI in patients with COVID-19; the mechanisms underlying kidney injury in this population are an area of active investigation. These data provide solid evidence to support close monitoring of COVID-19 patients for the development of AKI and measures taken to prevent this.