The interval-valued intuitionistic fuzzy geometric choquet aggregation operator based on the generalized banzhaf index and 2-additive measure

Based on the operational laws on interval-valued intuitionistic fuzzy sets, the generalized Banzhaf interval-valued intuitionistic fuzzy geometric Choquet (GBIVIFGC) operator is proposed, which is also an interval-valued intuitionistic fuzzy value. It is worth pointing out that the GBIVIFGC operator can be seen as an extension of some geometric mean operators. Since the fuzzy measure is defined on the power set, it makes the problem exponentially complex. In order to overall reflect the interaction among elements and reduce the complexity of solving a fuzzy measure, we further introduce the GBIVIFGC operator w.r.t. 2-additive measures. Furthermore, if the information about weights of experts and attributes is incompletely known, the models of obtaining the optimal 2-additive measures on criteria set and expert set are given by using the introduced cross entropy measure and the Banzhaf index. Finally, an approach to pattern recognition and multi-criteria group decision making under interval-valued intuitionistic fuzzy environment is developed, respectively

Interval linguistic fuzzy decision making in perspective of preference relations

Consistency analysis is a crucial topic for preference relations. This paper studies the consistency of interval linguistic fuzzy preference relations (ILFPRs) using the constrained interval linguistic arithmetic and introduces a new consistency definition. Then, several properties of this definition are researched. Meanwhile, the connection between this concept and a previous one is discussed. Following this concept, programming models for judging the consistency and for deriving consistent ILFPRs are constructed, respectively. Considering the case that incomplete ILFPRs may be obtained, a programming model for obtaining missing judgments following the consistency discussion is built. Afterwards, the consensus for group decision making (GDM) is studied and a model for adjusting individual ILFPRs to reach the consensus threshold is established. Consequently, an interactive procedure for GDM with ILFPRs is presented. A practical problem is provided to illustrate the utilization of the new algorithm and comparative discussion is offered

Prostacyclin post-treatment improves LPS-induced acute lung injury and endothelial barrier recovery via Rap1

Protective effects of prostacyclin (PC) or its stable analog beraprost against agonist-induced lung vascular inflammation have been associated with elevation of intracellular cAMP and Rac GTPase signaling which inhibited the RhoA GTPase-dependent pathway of endothelial barrier dysfunction. This study investigated a distinct mechanism of PC-stimulated lung vascular endothelial (EC) barrier recovery and resolution of LPS-induced inflammation mediated by small GTPase Rap1. Efficient barrier recovery was observed in LPS-challenged pulmonary EC after prostacyclin administration even after 15 h of initial inflammatory insult and was accompanied by the significant attenuation of p38 MAP kinase and NFκB signaling and decreased production of IL-8 and soluble ICAM1. These effects were reproduced in cells post-treated with 8CPT, a small molecule activator of Rap1-specific nucleotide exchange factor Epac. By contrast, pharmacologic Epac inhibitor, Rap1 knockdown, or knockdown of cell junction-associated Rap1 effector afadin attenuated EC recovery caused by PC or 8CPT post-treatment. The key role of Rap1 in lung barrier restoration was further confirmed in the murine model of LPS-induced acute lung injury. Lung injury was monitored by measurements of bronchoalveolar lavage protein content, cell count, and Evans blue extravasation and live imaging of vascular leak over 6 days using a fluorescent tracer. The data showed significant acceleration of lung recovery by PC and 8CPT post-treatment, which was abrogated in Rap1a(-/-) mice. These results suggest that post-treatment with PC triggers the Epac/Rap1/afadin-dependent mechanism of endothelial barrier restoration and downregulation of p38MAPK and NFκB inflammatory cascades, altogether leading to accelerated lung recovery

The BCL2A1 gene as a pre–T cell receptor–induced regulator of thymocyte survival

The pre–T cell receptor (TCR) is expressed early during T cell development and imposes a tight selection for differentiating T cell progenitors. Pre-TCR–expressing cells are selected to survive and differentiate further, whereas pre-TCR− cells are “negatively” selected to die. The mechanisms of pre-TCR–mediated survival are poorly understood. Here, we describe the induction of the antiapoptotic gene BCL2A1 (A1) as a potential mechanism regulating inhibition of pre–T cell death. We characterize in detail the signaling pathway involved in A1 induction and show that A1 expression can induce pre–T cell survival by inhibiting activation of caspase-3. Moreover, we show that in vitro “knockdown” of A1 expression can compromise survival even in the presence of a functional pre-TCR. Finally, we suggest that pre-TCR–induced A1 overexpression can contribute to T cell leukemia in both mice and humans

PLZF induces an intravascular surveillance program mediated by long-lived LFA-1–ICAM-1 interactions

PLZF-expressing NKT cells establish residence at intravascular locations, failing to enter the circulation because of constitutive interactions with LFA-1 and ICAM-1

Computed tomography in process engineering

Computed tomography (CT), as a non-invasive measurement technique for obtaining digital sectional information, has achieved tremendous success in medical imaging and industrial fields. In process engineering, the primary concern is temporal resolution instead of spatial and density resolution, which is the key difference between process CT and traditional CT. To make this technique more suitable for dynamic and flexible measurement, quite a number of studies have been conducted, and various new tomographic techniques were put forward. In this paper, the general principle of assorted CT used in process engineering is formulated from hardware and algorithm two aspects, and state-of-the-art CT technologies are reviewed with an emphasis on key features concerned by researchers in this field. Challenges like the lack of process-orientated calibration and validation methods and data analysis algorithms for dynamic measurement are presented, together with discussions of the limitations such as high cost, safety concerns, data deluge, and other miscellaneous topics. With the breakthrough of innovative hardware and data-driven approaches like deep learning, CT will undoubtedly play an even bigger role in serving both academia and industry in process engineering. (C) 2021 Elsevier Ltd. All rights reserved

Computed tomography in process engineering

Computed tomography (CT), as a non-invasive measurement technique for obtaining digital sectional information, has achieved tremendous success in medical imaging and industrial fields. In process engineering, the primary concern is temporal resolution instead of spatial and density resolution, which is the key difference between process CT and traditional CT. To make this technique more suitable for dynamic and flexible measurement, quite a number of studies have been conducted, and various new tomographic techniques were put forward. In this paper, the general principle of assorted CT used in process engineering is formulated from hardware and algorithm two aspects, and state-of-the-art CT technologies are reviewed with an emphasis on key features concerned by researchers in this field. Challenges like the lack of process-orientated calibration and validation methods and data analysis algorithms for dynamic measurement are presented, together with discussions of the limitations such as high cost, safety concerns, data deluge, and other miscellaneous topics. With the breakthrough of innovative hardware and data-driven approaches like deep learning, CT will undoubtedly play an even bigger role in serving both academia and industry in process engineering. (C) 2021 Elsevier Ltd. All rights reserved

The probabilistic Harsanyi power solutions for probabilistic graph games

This paper analyzes t he probabilistic Harsanyi power solutions (PHPSs) for probabilistic graph games (PGGs), which distribute the Harsanyi dividends proportional to weights determined by a probabilistic power measure for probabilistic graph structure. The probabilistic power measure considers the role of players in all possible deterministic graphs, which can reflect the powers of players more effectively.  Three axiomatic systems of the PHPSs on PGGs and cycle-free probabilistic graph games (CFPGGs) are provided to show the rationality of the PHPSs, and their independence is analyzed

A Coalitional Value for Multichoice Games with a Coalition Structure

In this paper a new model of multichoice games with a coalition structure is proposed, which can be seen as an extension of the Owen coalition structure. A coalitional value on the given model is defined, which can be seen as an extension of the Owen value. Three axiomatic systems are studied. The first one is enlightened by Owen’s characterization for the Owen value and Faigle and Kern’s characterization for the Shapley value on games under precedence constraints. The second one is inspired by Bilbao’s characterization for the Shapley value on games on convex geometries. The last one is an extension of Young’s characterization for the Shapley value on traditional games. Furthermore, the relationship between the given coalitional value and the core of multichoice games with a coalition structure is discussed