Analysis of unsteady mixed convection of Cu–water nanofluid in an oscillatory, lid-driven enclosure using lattice Boltzmann method

The unsteady physics of laminar mixed convection in a lid-driven enclosure filled with Cu–water nanofluid is numerically investigated. The top wall moves with constant velocity or with a temporally sinusoidal function, while the other walls are fixed. The horizontal top and bottom walls are, respectively, held at the low and high temperatures, and the vertical walls are assumed to be adiabatic. The governing equations along with the boundary conditions are solved through D2Q9 fluid flow and D2Q5 thermal lattice Boltzmann network. The effects of Richardson number and volume fractions of nanoparticles on the fluid flow and heat transfer are investigated. For the first time in the literature, the current study considers the mechanical power required for moving the top wall of the enclosure under various conditions. This reveals that the power demand increases if the enclosure is filled with a nanofluid in comparison with that with a pure fluid. Keeping a constant heat transfer rate, the required power diminishes by implementing a temporally sinusoidal velocity on the top wall rather than a constant velocity. Reducing frequency of the wall oscillation leads to heat transfer enhancement. Similarly, dropping Richardson number and raising the volume fraction of the nanoparticles enhance the heat transfer rate. Through these analyses, the present study provides a physical insight into the less investigated problem of unsteady mixed convection in enclosures with oscillatory walls

Investigation the integration of heliostat solar receiver to gas and combined cycles by energy, exergy, and economic point of views

Due to the high amount of natural gas resources in Iran, the gas cycle as one of the main important power production system is used to produce electricity. The gas cycle has some disadvantages such as power consumption of air compressors, which is a major part of gas turbine electrical production and a considerable reduction in electrical power production by increasing the environment temperature due to a reduction in air density and constant volumetric airflow through a gas cycle. To overcome these weaknesses, several methods are applied such as cooling the inlet air of the system by different methods and integration heat recovery steam generator (HRSG) with the gas cycle. In this paper, using a heliostat solar receiver (HSR) in gas and combined cycles are investigated by energy, exergy, and economic analyses in Tehran city. The heliostat solar receiver is used to heat the pressurized exhaust air from the air compressor in gas and combined cycles. The key parameter of the three mentioned analyses was calculated and compared by writing computer code in MATLAB software. Results showed the use of HSR in gas and combined cycles increase the annual average energy efficiency from 28.4% and 48.5% to 44% and 76.5%, respectively. Additionally, for exergy efficiency, these increases are from 29.2% and 49.8% to 45.2% and 78.5%, respectively. However, from an economic point of view, adding the HRSG increases the payback period (PP) and it decreases the net present value (NPV) and internal rate of return (IRR)

Effects of Securigera securidaca (L.) Degen & Dorfl seed extract combined with glibenclamide on paraoxonase1 activity, lipid profile and peroxidation, and cardiovascular risk indices in diabetic rats

Introduction: Seeds of Securigera securidaca (L.) Degen & Dorfl are rich in flavonoids and phenolic acids which have potent biological effects. The current study was undertaken to evaluate the effects of hydroalcoholic extract of S. securidaca seeds (HESS) alone, and in combination with a standard drug, glibenclamide (GB) on paraoxonase1 (PON1) activity, lipid profile and peroxidation, and cardiovascular risk indices in streptozotocin (STZ) induced diabetic rats. Methods: Forty-eight male Wistar rats were randomly divided into eight equal groups and orally treated with various doses of HESS (100, 200, 400 mg/kg) alone and in combination with GB (5 mg/kg) for 35 consecutive days. After blood sampling, lipid profile including triglyceride (TG), cholesterol, high, low and very low-density lipoprotein-cholesterol (HDL-C, LDL-C, and VLDL-C), as well as serum PON1 activity, were assessed. Malondialdehyde (MDA), tumor necrosis factor-alpha (TNF-α), and high-sensitivity C-reactive protein (hs-CRP) levels were also measured. Several indices of cardiovascular risk and the correlation between PON1 activity and these indices were calculated based on the obtained results from the lipid profile. Results: Induction of diabetes could dramatically alter all of the parameters mentioned above, and the lower dose of HESS (100 mg/kg) was not effective in restoring the parameters. However, the higher doses (200 and 400 mg/kg) alone and in combination with GB could significantly improve lipid profile, restore PON1 activity, and decrease cardiovascular risk indices, MDA, as well. However, neither HESS nor GB could significantly reduce TNF-α and hs-CRP. A significant negative correlation also was detected between PON1 activity and cardiovascular risk indices. Conclusion: conclusively, HESS can be considered as a potent antihyperlipidemic agent with remarkable cardioprotective effects and can potentiate the antidiabetic effects of GB

The effect of aminoguanidine on sperm motility and mitochondrial membrane potential in varicocelized rats

Objective(s): Increased levels of nitric oxide (NO) in the testicular veins of people suffering from varicocele have already been reported. However, the role of NO-synthase (NOS) isozymes and their inhibitors have not been extensively studied. We aimed to evaluate the inhibitory effects of aminoguanidine (AG), on sperm motility, vitality, and mitochondrial membrane potential (MMP) in varicocelized rats. Materials and Methods: Twenty fore male Wister rats were divided into control, sham, varicocele, and treatment groups. Varicocele and treatment groups underwent partial ligation of left renal vein. Rats in the sham group underwent the same procedures as the varicocele group with the exception of vein ligation. 10 weeks after varicocele induction, sperm parameters were evaluated in all groups. The treatment group received 50 mg/kg AG injection daily for 10 weeks after which they were sacrificed prior to assessment of the parameters. Sperm viability and MMP were assessed by flow cytometry using propidium iodide (PI) and rhodamine 123 (Rh123), respectively. Results: The results of this study show a decrease in sperm viability, motility and MMP in the varicocele group compared with the other groups. After AG injection, we observed that all the parameters were significantly enhanced in the treatment group compared with the other groups. Rh123 staining revealed a positive relation between MMP and sperm motility, whereas PI staining showed a positive relation between sperm motility and viability. Conclusion: The findings of our study show that AG improves sperm motility and MMP, and thus, might be useful in the management of varicocele-related infertility. © 2016, Mashhad University of Medical Sciences. All rights reserved

Evaluation of testicular glycogen storage, FGF21 and LDH expression and physiological parameters of sperm in hyperglycemic rats treated with hydroalcoholic extract of Securigera Securidaca seeds, and Glibenclamide

Structural and physiological changes in sperm and semen parameters reduce fertility in diabetic patients. Securigera Securidaca (S. Securidaca) seed is a herbal medicine with hypoglycemic, antioxidant, and anti-hypertensive effects. The question now is whether this herbal medicine improves fertility in diabetic males. The study aimed to evaluate the effects of hydroalcoholic extract of S. Securidaca seeds (HESS), glibenclamide and a combination of both on fertility in hyperglycemic rats by comparing histological and some biochemical changes in testicular tissue and sperm parameters. The treatment protocol included administration of three doses of HESS and one dose of glibenclamide, as well as treatment with both in diabetic Wistar diabetic rats and comparison of the results with untrated groups. The quality of the testicular tissue as well as histometric parameters and spermatogenesis indices were evaluated during histopathological examination. Epididymal sperm analysis including sperm motility, viability, abnormalities, maturity, and chromatin structure were studied. The effect of HESS on the expression of LDH and FGF21 genes and tissue levels of glycogen, lactate, and total antioxidant capacity in testicular tissue was investigated and compared with glibenclamide. HESS improved sperm parameters in diabetic rats but showed little restorative effect on damaged testicular tissue. In this regard, glibenclamide was more effective than the highest dose of HESS and its combination with HESS enhanced its effectiveness so that histological tissue characteristics and sperm parameters were were comparable to those of healthy rats. The expression level of testicular FGF21 gene increased in diabetic rats, which intensified after treatment with HESS as well as glibenclamide. The combination of HESS and glibenclamide restored the expression level of testicular LDH gene, as well as tissue storage of glycogen, lactate and LDH activity, and serum testosterone to the levels near healthy control. S. Securidaca seeds can be considered as an effective supplement in combination with hypoglycemic drugs to prevent infertility complications in diabetes

Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review

Coronavirus, or COVID-19, is a hazardous disease that has endangered the health of many people around the world by directly affecting the lungs. COVID-19 is a medium-sized, coated virus with a single-stranded RNA. This virus has one of the largest RNA genomes and is approximately 120 nm. The X-Ray and computed tomography (CT) imaging modalities are widely used to obtain a fast and accurate medical diagnosis. Identifying COVID-19 from these medical images is extremely challenging as it is time-consuming, demanding, and prone to human errors. Hence, artificial intelligence (AI) methodologies can be used to obtain consistent high performance. Among the AI methodologies, deep learning (DL) networks have gained much popularity compared to traditional machine learning (ML) methods. Unlike ML techniques, all stages of feature extraction, feature selection, and classification are accomplished automatically in DL models. In this paper, a complete survey of studies on the application of DL techniques for COVID-19 diagnostic and automated segmentation of lungs is discussed, concentrating on works that used X-Ray and CT images. Additionally, a review of papers on the forecasting of coronavirus prevalence in different parts of the world with DL techniques is presented. Lastly, the challenges faced in the automated detection of COVID-19 using DL techniques and directions for future research are discussed

Uncertainty-Aware Semi-supervised Method using Large Unlabelled and Limited Labeled COVID-19 Data

This work was partly supported by the MINECO/ FEDER under the RTI2018-098913-B100, CV20-45250 and A-TIC-080-UGR18 projects.The new coronavirus has caused more than 1 million deaths and continues to spread rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe. The X-ray or computed tomography (CT) images of lungs can reveal whether the patient is infected with COVID-19 or not. Many researchers are trying to improve COVID-19 detection using artificial intelligence. In this paper, relying on Generative Adversarial Networks (GAN), we propose a Semi-supervised Classification using Limited Labelled Data (SCLLD) for automated COVID-19 detection. Our motivation is to develop learning method which can cope with scenarios that preparing labelled data is time consuming or expensive. We further improved the detection accuracy of the proposed method by applying Sobel edge detection. The GAN discriminator output is a probability value which is used for classification in this work. The proposed system is trained using 10,000 CT scans collected from Omid hospital. Also, we validate our system using the public dataset. The proposed method is compared with other state of the art supervised methods such as Gaussian processes. To the best of our knowledge, this is the first time a COVID-19 semi-supervised detection method is presented. Our method is capable of learning from a mixture of limited labelled and unlabelled data where supervised learners fail due to lack of sufficient amount of labelled data. Our semi-supervised training method significantly outperforms the supervised training of Convolutional Neural Network (CNN) in case labelled training data is scarce. Our method has achieved an accuracy of 99.60%, sensitivity of 99.39%, and specificity of 99.80% where CNN (trained supervised) has achieved an accuracy of 69.87%, sensitivity of 94%, and specificity of 46.40%.Spanish Government RTI2018-098913-B100 CV20-45250 A-TIC-080UGR1

Combining a convolutional neural network with autoencoders to predict the survival chance of COVID-19 patients.

COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classification performance on image datasets. To date, it appears that COVID computer-aided diagnosis systems based on CNNs and clinical information have not yet been analysed or explored. We propose a novel method, named the CNN-AE, to predict the survival chance of COVID-19 patients using a CNN trained with clinical information. Notably, the required resources to prepare CT images are expensive and limited compared to those required to collect clinical data, such as blood pressure, liver disease, etc. We evaluated our method using a publicly available clinical dataset that we collected. The dataset properties were carefully analysed to extract important features and compute the correlations of features. A data augmentation procedure based on autoencoders (AEs) was proposed to balance the dataset. The experimental results revealed that the average accuracy of the CNN-AE (96.05%) was higher than that of the CNN (92.49%). To demonstrate the generality of our augmentation method, we trained some existing mortality risk prediction methods on our dataset (with and without data augmentation) and compared their performances. We also evaluated our method using another dataset for further generality verification. To show that clinical data can be used for COVID-19 survival chance prediction, the CNN-AE was compared with multiple pre-trained deep models that were tuned based on CT images

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

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