•Nanomaterial deposition on heating surface are used to attain reduction in wall superheat, enhancing nucleate boiling HTC and CHF.•Different working fluid is used such as de-ionized water, ...fluorocarbon fluid, hydofluoroethers and refrigeration-based fluid for enhancing CHF.•The surface modification enhanced the CHF due to the reduction in wall superheat temperature, increased nucleation site, porosity rise, enhanced surface wettability, small nano-pores/cavities generation, rise in bubble release frequency.•Nanoparticle size, nanofluid preparation techniques and concentration of nanofluid mainly influenced the CHF.
Boiling is the most significant phase change phenomena for various applications such as cooling of electronic devices, heat pipes, cooling in nuclear reactor, different industrial application and plenty more. Due to its wide scope of application, any enhancement in this domain leads to remarkable economic and energy efficient consequences. Augmentations in boiling heat transfer performance are very crucial which establishes the various industrial applications further energy efficient. To reduce the energy dissipation in heat transfer equipment, boiling heat transfer augmentation is one of the significant techniques used by researchers. This paper demonstrates a thorough review and investigation of published articles describing the various surface modification method (nanomaterial coating, nano/micro porous coating, nano/micro structured surface) for pool boiling and flow boiling heat transfer enhancement as well as the effect of surface modification on wettability, porosity, surface roughness, nucleation sites are studied. Various augmentation methods are utilized to attain three apparent heat transfer desire: reducing wall superheat temperature, enhancing pool boiling heat transfer coefficient (HTC) and improving critical heat flux (CHF).
Intrauterine growth restriction (IUGR), a condition that occurs due to various reasons, is an important cause of fetal and neonatal morbidity and mortality. It has been defined as a rate of fetal ...growth that is less than normal in light of the growth potential of that specific infant. Usually, IUGR and small for gestational age (SGA) are used interchangeably in literature, even though there exist minute differences between them. SGA has been defined as having birth weight less than two standard deviations below the mean or less than the 10th percentile of a population-specific birth weight for specific gestational age. These infants have many acute neonatal problems that include perinatal asphyxia, hypothermia, hypoglycemia, and polycythemia. The likely long-term complications that are prone to develop when IUGR infants grow up includes growth retardation, major and subtle neurodevelopmental handicaps, and developmental origin of health and disease. In this review, we have covered various antenatal and postnatal aspects of IUGR.
The measurement of sustainability is actively used today as one of the main preventative instruments in order to reduce the decline of the environment. Sustainable decision-making in solving energy ...issues can be supported and contradictory effects can be evaluated by scientific achievements of multi-criteria decision-making (MCDM) techniques. The main goal of this paper is to overview the application of decision-making methods in dealing with sustainable energy development issues. In this study, 105 published papers from the Web of Science Core Collection (WSCC) database are selected and reviewed, from 2004 to 2017, related to energy sustainability issues and MCDM methods. All the selected papers were categorized into 9 fields by the application area and into 10 fields by the used method. After the categorization of the scientific articles and detailed analysis, SWOT analysis of MCDM approaches in dealing with sustainable energy development issues is provided. The widespread application and use of MCDM methods confirm that MCDM methods can help decision-makers in solving energy sustainability problems and are highly popular and used in practice.
As most of the countries have already passed the peaks of the second or third wave of infections, COVID-19 is (finally) on the wane and will soon touch the baseline persistence with a reduced death ...rate. The Case Fatality Ratio (CFR) or lethality is presently only ~2.0%, which is relatively low in comparison to the high of 14% in April 2020. More importantly, the lethality in healthy people is 20 times lower. In addition, successful vaccination programs are currently underway in several countries. Thus, although new pathogenic variants as well as a few isolated cases of resurgence, will continue to emerge, the worst seems to be over and we will surely win this battle soon.
•This paper explores the use of TCNs for predicting failures in industrial machines.•It presents comparative experiments between TCNs and CNN/LSTM networks.•Models are evaluated under different ...conditions and their performances are presented.•Results show that TCNs can outperform LSTMs/CNNs for long time sequence forecasting.
Cyber-physical systems (CPS) are an indispensable aspect of the modern age’s data driven industrial systems. These systems can be controlled and monitored with the help of computer-oriented devices and software that are responsible for integrating the physical environment with cyber frameworks. Owing to the nature of operations in any physical process industry, it becomes imperative to deal with potential failures before they occur. To avoid downtime and losses, predictive maintenance is one relevant policy that utilizes prior information and domain knowledge to help in scheduling operations and maintenance. Predictive maintenance (PdM) in industrial applications is known to improve the efficiency, lifetime, and reliability of the machines and thereby reducing the maintenance cost. With the advances in machine learning approaches in cyber physical systems, reliable predictions can be performed to significantly reduce downtime and operational losses associated with the physical processes. In this paper, usefulness of Temporal Convolutional Networks (TCNs) is investigated with the aim of forecasting the remaining useful life (RUL) for Turbofan engines. This paper demonstrates the effectiveness of using TCNs for prognosis under various evaluation conditions and also provides comparison of their performance with hybrid architectures like CNN-LSTM networks and meta-heuristically optimized LSTM networks. The proposed methods were able to achieve upto 94.47% accuracy in case of binary classification tasks and upto 98.7% precision in case of multi-label classification. The cumulative results in accordance to elaborated test cases are presented with the conclusion of the study.
A metal‐free formylation of imidazopyridines by direct decarboxylative cross‐coupling of glyoxylic acid in presence of K2S2O8 as oxidant under mild and neutral conditions is described. This reaction ...features a broad substrate scope, good functional group tolerance, and generates products in good yields between 68–85 %. The translational capacity of the reaction from a laboratory methodology to gram‐scale synthesis has also been ensured. The involvement of a radical pathway has been demonstrated by radical trapping experiments with 2,2,6,6‐tetramethylpiperidine‐1‐oxyl (TEMPO) and 2,6‐di‐tert‐butyl‐4‐methylphenol (BHT).
A metal‐free formylation of imidazopyridines with K2S2O8 by direct decarboxylative cross‐coupling of glyoxylic acid is described. This reaction features broad substrate scope, good functional group tolerance, and generate products in good yields.
Neurodegenerative diseases (NDDs) are the primary cause of disabilities in the elderly people. Growing evidence indicates that oxidative stress, mitochondrial dysfunction, neuroinflammation and ...apoptosis are associated with aging and the basis of most neurodegenerative disorders. Quercetin is a flavonoid with significant pharmacological effects and promising therapeutic potential. It is widely distributed among plants and typically found in daily diets mainly in fruits and vegetables. It shows a number of biological properties connected to its antioxidant activity. Neuroprotection by quercetin has been reported in many in vitro as well as in in vivo studies. However, the exact mechanism of action is still mystery and similarly there are a number of hypothesis exploring the mechanism of neuroprotection. Quercetin enhances neuronal longevity and neurogenesis by modulating and inhibiting wide number of pathways. This review assesses the food sources of quercetin, its pharmacokinetic profile, structure activity relationship and its pathophysiological role in various NDDs and it also provides a synopsis of the literature exploring the relationship between quercetin and various downstream signalling pathways modulated by quercetin for neuroprotection for eg. nuclear factor erythroid 2-related factor 2 (Nrf2), Paraoxonase-2 (PON2), c-Jun N-terminal kinase (JNK), Tumour Necrosis Factor alpha (TNF-α), Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha (PGC-1α), Sirtuins, Mitogen-activated protein kinases (MAPKs) signalling cascades, CREB (Cyclic AMP response element binding protein) and Phosphoinositide 3- kinase(PI3K/Akt). Therefore, the aim of the present review was to elaborate on the cellular and molecular mechanisms of the quercetin involved in the protection against NDDs.
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