University of Technology, Iraq

About: University of Technology, Iraq is a education organization based out in Baghdad, Iraq. It is known for research contribution in the topics: Thin film & Ultimate tensile strength. The organization has 2717 authors who have published 3605 publications receiving 26883 citations. The organization is also known as: University of Technology, Baghdad.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

Abstract: In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance. One of the benefits of DL is the ability to learn massive amounts of data. The DL field has grown fast in the last few years and it has been extensively used to successfully address a wide range of traditional applications. More importantly, DL has outperformed well-known ML techniques in many domains, e.g., cybersecurity, natural language processing, bioinformatics, robotics and control, and medical information processing, among many others. Despite it has been contributed several works reviewing the State-of-the-Art on DL, all of them only tackled one aspect of the DL, which leads to an overall lack of knowledge about it. Therefore, in this contribution, we propose using a more holistic approach in order to provide a more suitable starting point from which to develop a full understanding of DL. Specifically, this review attempts to provide a more comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field. In particular, this paper outlines the importance of DL, presents the types of DL techniques and networks. It then presents convolutional neural networks (CNNs) which the most utilized DL network type and describes the development of CNNs architectures together with their main features, e.g., starting with the AlexNet network and closing with the High-Resolution network (HR.Net). Finally, we further present the challenges and suggested solutions to help researchers understand the existing research gaps. It is followed by a list of the major DL applications. Computational tools including FPGA, GPU, and CPU are summarized along with a description of their influence on DL. The paper ends with the evolution matrix, benchmark datasets, and summary and conclusion.

Photovoltaic/Thermal (PV/T) systems: Status and future prospects

Abstract: In the last four decades, greater attention has been paid to PV/T systems due to their advantages compared with PV or solar thermal systems alone. This paper aims to study various aspects of PV/T systems through the existing literature in order to highlight key points as future work in this field as well as illustrate different techniques used for such systems. In addition, PV/T systems are reviewed in terms of thermal and electrical side views. Furthermore, the analysis of solar thermal systems, various system applications such as air, water, air/water, phase change material PCM and Nanofluid systems are summarized. In light of most attempts to improve the PV/T system, more focus has been paid to the thermal rather than the electrical side. Furthermore, comparisons between PV/T systems in terms of performance parameters and efficiencies are presented. A critical review of many findings of previously conducted research is also discussed. It is found that the PV/T air heater system is promising for future preheating air applications. Moreover, it is suggested that the use of nanoparticles and water as base fluid improves the overall system efficiency. Furthermore, the PV side views require more attention in technical and cost terms. However, more research is essential to reduce the cost and, improve the effectiveness and technical design of such systems.

IL-33 promotes ST2-dependent lung fibrosis by the induction of alternatively activated macrophages and innate lymphoid cells in mice

Abstract: Background The initiation and regulation of pulmonary fibrosis are not well understood. IL-33, an important cytokine for respiratory diseases, is overexpressed in the lungs of patients with idiopathic pulmonary fibrosis. Objectives We aimed to determine the effects and mechanism of IL-33 on the development and severity of pulmonary fibrosis in murine bleomycin-induced fibrosis. Methods Lung fibrosis was induced by bleomycin in wild-type or Il33r ( St2 ) −/− C57BL/6 mice treated with the recombinant mature form of IL-33 or anti–IL-33 antibody or transferred with type 2 innate lymphoid cells (ILC2s). The development and severity of fibrosis was evaluated based on lung histology, collagen levels, and lavage cytology. Cytokine and chemokine levels were quantified by using quantitative PCR, ELISA, and cytometry. Results IL-33 is constitutively expressed in lung epithelial cells but is induced in macrophages by bleomycin. Bleomycin enhanced the production of the mature but reduced full-length form of IL-33 in lung tissue. ST2 deficiency, anti–IL-33 antibody treatment, or alveolar macrophage depletion attenuated and exogenous IL-33 or adoptive transfer of ILC2s enhanced bleomycin-induced lung inflammation and fibrosis. These pathologic changes were accompanied, respectively, by reduced or increased IL-33, IL-13, TGF-β1, and inflammatory chemokine production in the lung. Furthermore, IL-33 polarized M2 macrophages to produce IL-13 and TGF-β1 and induced the expansion of ILC2s to produce IL-13 in vitro and in vivo . Conclusions IL-33 is a novel profibrogenic cytokine that signals through ST2 to promote the initiation and progression of pulmonary fibrosis by recruiting and directing inflammatory cell function and enhancing profibrogenic cytokine production in an ST2- and macrophage-dependent manner.