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A numerical procedure for calculating the inverse of LR fuzzy numbers matrix is designed and a sufficient condition for the existence of fuzzy inverse is derived. As a application, the paper considers the solution of fully fuzzy linear systems by the approximate fuzzy inverse. Some examples are given to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

In paper a general complex fuzzy matrix equation Z ˜ C = W ˜ in which C is a n × p complex matrix and W ˜ is a m × p complex LR fuzzy numbers one, is investigated. A numerical procedure for calculating the solution is designed in detail and a sufficient condition for the existence of strong complex LR fuzzy solution is derived. Some examples are given to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

In paper a general complex fuzzy matrix equation Z ˜ C = W ˜ in which C is a n × p complex matrix and W ˜ is a m × p complex LR fuzzy numbers one, is investigated. A numerical procedure for calculating the solution is designed in detail and a sufficient condition for the existence of strong complex LR fuzzy solution is derived. Some examples are given to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

Background: Obesity is an uncontrolled global epidemic and one of the leading global public health challenges. Maternal exposure to ambient fine particulate matter (PM2.5) may adversely program offspring's adiposity, suggesting a specialized role of PM2.5 pollution in the global obesity epidemic. However, the vulnerable window for this adverse programming and how it is cross-generationally transmitted have not been determined. Therefore, in the present study, female C57Bl/6 J mice were exposed to filtered air (FA) or concentrated ambient PM2.5 (CAP) during different periods, and the development and adulthood adiposity of their four-generational offspring were assessed. Results: Our data show that the pre-conceptional but not gestational exposure to CAP was sufficient to cause male but not female offspring's low birth weight, accelerated postnatal weight gain, and increased adulthood adiposity. These adverse developmental traits were transmitted into the F2 offspring born by the female but not male F1 offspring of CAP-exposed dams. In contrast, no adverse development was noted in the F3 offspring. Conclusions: The present study identified a pre-conceptional window for the adverse programming of adiposity by maternal exposure to PM2.5, and showed that it was maternally transmitted into the third generation. These data not only call special attention to the protection of women from exposure to PM2.5, but also may facilitate the development of intervention to prevent this adverse programming. [ABSTRACT FROM AUTHOR]

A numerical procedure for calculating the inverse of LR fuzzy numbers matrix is designed and a sufficient condition for the existence of fuzzy inverse is derived. As a application, the paper considers the solution of fully fuzzy linear systems by the approximate fuzzy inverse. Some examples are given to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

Aim: Ambient fine particulate matter (PM 2.5 ) consists of various components, and their respective contributions to the toxicity of PM 2.5 remains to be determined. To provide specific recommendations for preventing adverse effects due to PM 2.5 pollution, we determined whether the induction of pulmonary inflammation, the putative pathogenesis for the morbidity and mortality due to PM 2.5 exposure, was fractioned through solubility-dependent fractioning., Methods: In the present study, the water and heptane solubilities-dependent serial fractioning of diesel exhaust particulate matter (DEP), a prominent source of urban PM 2.5 pollution, was performed. The pro-inflammatory actions of these resultant fractions were then determined using both an intratracheal instillation mouse model and cultured BEAS-2B cells, a human bronchial epithelial cell line., Results: Instillation of the water-insoluble, but not -soluble fraction elicited significant pulmonary inflammatory and acute phase responses, comparable to those induced by instillation of DEP. The water-insoluble fraction was further fractioned using heptane, a polar organic solvent, and instillation of heptane-insoluble, but not -soluble fraction elicited significant pulmonary inflammation and acute phase responses. Furthermore, we showed that DEP and water-insoluble DEP, but not water-soluble DEP, activated pro-inflammatory signaling in cultured BEAS-2B cells, ruling out the possibility that the solubility impacts the in vivo distribution and thus the pulmonary inflammatory response., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Ambient fine particulate matter (PM 2.5 ) exposure correlates with adverse cardiometabolic effects. The underlying mechanisms have not yet been fully understood. Hypothalamic-pituitary-adrenal (HPA) axis, as the central stress response system, regulates cardiometabolic homeostasis and is implicated in the progression of various adverse health effects caused by inhalational airborne pollutant exposure. In this study, we investigated whether ambient PM 2.5 exposure activates HPA axis and its effect mediating PM 2.5 -induced pulmonary inflammation. C57Bl/6 J mice were intratracheally instilled with different concentrations of diesel exhaust PM 2.5 (DEP), and plasma was harvested at different times. Assessments of plasma stress hormones revealed that DEP instillation dose- and time-dependently increased mouse circulating corticosterone and adrenocorticotropic hormone (ACTH) levels, strongly supporting that DEP instillation activates HPA axis. To determine which components of DEP activate HPA axis, C57Bl/6J mice were intratracheally instilled with water-soluble and -insoluble fractions of DEP. Plasma analyses showed that water-insoluble but not -soluble fraction of DEP increased circulating corticosterone and ACTH levels. Consistently, concentrated ambient PM 2.5 (CAP) exposure significantly increased mouse urine and hair corticosterone levels, corroborating the activation of HPA axis by ambient PM 2.5 . Furthermore, deletion of stress hormones by total bilateral adrenalectomy alleviated PM 2.5 -induced pulmonary inflammation, providing insights into the contribution of central neurohormonal mechanisms in modulating adverse health effects caused by exposure to PM 2.5 ., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Obesity is an uncontrolled global epidemic and one of the leading global public health challenges. Maternal exposure to ambient fine particulate matter (PM 2.5 ) may adversely program offspring's adiposity, suggesting a specialized role of PM 2.5 pollution in the global obesity epidemic. However, the vulnerable window for this adverse programming and how it is cross-generationally transmitted have not been determined. Therefore, in the present study, female C57Bl/6 J mice were exposed to filtered air (FA) or concentrated ambient PM 2.5 (CAP) during different periods, and the development and adulthood adiposity of their four-generational offspring were assessed., Results: Our data show that the pre-conceptional but not gestational exposure to CAP was sufficient to cause male but not female offspring's low birth weight, accelerated postnatal weight gain, and increased adulthood adiposity. These adverse developmental traits were transmitted into the F 2 offspring born by the female but not male F 1 offspring of CAP-exposed dams. In contrast, no adverse development was noted in the F 3 offspring., Conclusions: The present study identified a pre-conceptional window for the adverse programming of adiposity by maternal exposure to PM 2.5 , and showed that it was maternally transmitted into the third generation. These data not only call special attention to the protection of women from exposure to PM 2.5 , but also may facilitate the development of intervention to prevent this adverse programming.

Clustering methods become increasingly important in analyzing heterogeneity of treatment effects, especially in longitudinal behavioral intervention studies. Methods such as K-means and Fuzzy C-means (FCM) have been widely endorsed to identify distinct groups of different types of data. Build upon our MIFuzzy [1], our goal is to concurrently handle multiple methodological issues in studying high dimensional longitudinal intervention data with missing values. Particularly, this paper focuses on the initialization issue of FCM and proposes a new initialization method to overcome the local optimal problem and decrease the convergence time in handling high-dimensional data with missing values for overlapping clusters. Based on the idea of K-means++ [9], we proposed an enhanced Fuzzy C-means clustering (eFCM) and incorporated it into our MIFuzzy. This method was evaluated using real longitudinal intervention data, classic and generic datasets. Compared to conventional FCM, our findings indicate eFCM can improve computational efficiency and avoid the local optimization.