Sustainable liquid cooling solutions are recognized as the future of thermal management in the chip industry. Among them, phase change heat transfer devices such as heat pipes and vapor chambers have ...shown tremendous potential. These devices rely on the physics of capillary-driven thin-film evaporation, which is inherently coupled with the design and optimization of the evaporator wicks used in these devices. Here, we introduce a biomimetic evaporator wick design inspired by the peristome of the Nepenthes alata that can achieve significantly enhanced evaporative cooling. It consists of an array of micropillars with multiple wedges along the sidewall of each micropillar. The efficacy of the wedged micropillar is evaluated based on a validated numerical model on the metrics of dryout heat flux and effective heat transfer coefficient. The wedge angle is chosen such that wedged micropillars cause liquid filaments to rise along the micropillar vertical walls. This results in a significant increase in thin-film area for evaporation. Additionally, the large mean curvature of the liquid meniscus produces strong capillary pumping pressure and simultaneously, the wedges increase the overall permeability of the wick. Consequently, our model predicts that the wedged micropillar wick can attain ∼234% enhancement of dryout heat flux compared to a conventional cylindrical micropillar wick of similar geometrical dimensions. Moreover, the wedged micropillars can also attain a higher effective heat transfer coefficient under dryout conditions, thus outperforming the cylindrical micropillar in terms of heat transfer efficiency. Our study provides insight into the design and capability of the biomimetic wedged micropillars as an efficient evaporator wick for various thin-film evaporation applications.
•The proposed algorithm is an operationally practical unsupervised technique to identify the spatial-spectral homogeneous regions in large HSIs.•Extended morphological features are concatenated with ...spectral features to increase the discriminability between boundary pixels and the pixels belong to homogeneous areas.•Sparse-un-mixing has been applied to compute the fractional abundance map of vegetation, soil and crop residue and to mask the other targets. Mean value of the abundance of a segment can be used to identify bare fields, harvested fields with crop residues, and fields with high vegetation canopy cover.
Farm scale information is crucial for large scale agricultural monitoring and policymaking. Therefore, per-field agricultural land-use statistics is more informative than per-pixel statistics. However, per-field segmentation of hyperspectral image (HSI) is challenging due to the variability in spectral responses of different spectral bands within the neighbourhood. Moreover, manual digitization and modification of the field map or field boundaries at each airborne campaign (at different spatial resolution) or each growing season is a challenging task. To overcome this challenge, we developed an unsupervised method for segmenting the spatial-spectral homogeneous pixels and its fractional abundances in airborne HSIs. In the proposed approach, morphological operations based local spectral similarity measure combined with edge detector was applied to produce edge intensity map. Watershed segmentation was applied on the binary edge map to generate the spatially homogeneous land segments in the HSI. Then, online-dictionary-learning and sparse-unmixing have been performed on the HSI to compute the fractional abundance map of vegetation, soil and crop residue and to mask the other targets. The proposed method was tested on simulated HSI, benchmark HSIs as well as the image obtained from Airborne-Visible-and-Infra-Red-Imaging-Spectrometer Next-Generation (AVIRIS-NG) sensor. Figure-of-merit, false-alarm-count and miss-count were applied to evaluate the performance of boundary detection methods. The results indicate that the fractional-spectral-similarity outperformed other distance measures in detecting spectrally homogeneous regions. It was also observed that integration of fractional-similarity with Sobel-edge-filter improved the performance of the edge detector. Edge-intensity-map generated using the fractional-similarity approach was employed as seed points for the watershed segmentation, which showed significant improvement in terms of accuracy as compared to other segmentation methods. We also demonstrated the robustness of our method on multiple HSI datasets spanning different regions. Moreover, the integration of spectral un-mixing with segmentation technique enables the identification of bare fields, harvested fields with crop-residues, and the fields with high vegetation canopy cover. The proposed method is automated with few parameters and it is operationally practical for large HSIs.
•ANN framework is given to predict the fracture behavior of glass-filled epoxy under impact loading.•Effect of aspect ratio on the dynamic fracture behavior has been investigated.•Inputs are found to ...be important in the order, time > aspect ratio > elastic modulus > volume fraction.
The present study discusses about the effect of the aspect ratio of the fillers on the fracture toughness of the glass-filled epoxy composites under impact loading. Three different kinds of fillers (spheres, flakes and rods) were used with different volume fractions (5%, 10% and 15%). Experimental results for Stress Intensity Factor (SIF) were obtained using a gas gun setup and a high speed camera. Further experimental investigation was done using fractographs obtained from Scanning Electron Microscope (SEM). Then the potential of using Artificial Neural Network (ANN) in predicting the effect of filler shape on the fracture behavior is studied. The framework of Multi-Layer Perceptron (MLP) feed forward network was used to predict the SIF history using four input parameters viz. time, dynamic elastic modulus, aspect ratio and volume fraction of the glass fillers. Experimental results of fracture test under impact loading were fed to train the ANN network and later the predicted results were compared with the experimental ones. Owing to the fact that predicted values had an accuracy of 91%, crack initiation toughness was predicted corresponding to the intermediate values of aspect ratio for which the experiments were not performed. Among the four input parameters, aspect ratio (largest/shortest dimension) was found to be the most important parameter in the prediction of SIF after time, followed by the dynamic modulus and volume fraction. The significance of aspect ratio lies in increasing the surface area to volume ratio which is responsible for the interfacial strength between the matrix and the filler and hence affects the fracture toughness of the overall composite material.
Early childhood caries (ECC) is major oral health problem, mainly in socially disadvantaged populations. ECC affects infants and preschool children worldwide. The prevalence of ECC differs according ...to the group examined, and a prevalence of up to 85% has been reported for disadvantaged groups. ECC is the presence of one or more decayed, missing, or filled primary teeth in children aged 71 months (5 years) or younger. It begins with white-spot lesions in the upper primary incisors along the margin of the gingiva. If the disease continues, caries can progress, leading to complete destruction of the crown. The main risk factors in the development of ECC can be categorized as microbiological, dietary, and environmental risk factors. Even though it is largely a preventable condition, ECC remains one of the most common childhood diseases. The major contributing factors for the for the high prevalence of ECC are improper feeding practices, familial socioeconomic background, lack of parental education, and lack of access to dental care. Oral health plays an important role in children to maintain the oral functions and is required for eating, speech development, and a positive self-image. The review will focus on the prevalence, risk factors, and preventive strategies and the management of ECC.
Optimization and decision making problems in various fields of engineering have a major impact in this current era. Processing time and utilizing memory is very high for the currently available data. ...This is due to its size and the need for scaling from zettabyte to yottabyte. Some problems need to find solutions and there are other types of issues that need to improve their current best solution. Modelling and implementing a new heuristic algorithm may be time consuming but has some strong primary motivation - like a minimal improvement in the solution itself can reduce the computational cost. The solution thus obtained was better. In both these situations, designing heuristics and meta-heuristics algorithm has proved it’s worth. Hyper heuristic solutions will be needed to compute solutions in a much better time and space complexities. It creates a solution by combining heuristics to generate automated search space from which generalized solutions can be tuned out. This paper provides in-depth knowledge on nature-inspired computing models, meta-heuristic models, hybrid meta heuristic models and hyper heuristic model. This work’s major contribution is on building a hyper heuristics approach from a meta-heuristic algorithm for any general problem domain. Various traditional algorithms and new generation meta heuristic algorithms has also been explained for giving readers a better understanding.
Clean and safe water is a fundamental human need for multi-faceted development of society and a thriving economy. Brisk rises in populations, expanding industrialization, urbanization and extensive ...agriculture practices have resulted in the generation of wastewater which have not only made the water dirty or polluted, but also deadly. Millions of people die every year due to diseases communicated through consumption of water contaminated by deleterious pathogens. Although various methods for wastewater treatment have been explored in the last few decades but their use is restrained by many limitations including use of chemicals, formation of disinfection by-products (DBPs), time consumption and expensiveness. Nanotechnology, manipulation of matter at a molecular or an atomic level to craft new structures, devices and systems having superior electronic, optical, magnetic, conductive and mechanical properties, is emerging as a promising technology, which has demonstrated remarkable feats in various fields including wastewater treatment. Nanomaterials encompass a high surface to volume ratio, a high sensitivity and reactivity, a high adsorption capacity, and ease of functionalization which makes them suitable for application in wastewater treatment. In this article we have reviewed the techniques being developed for wastewater treatment using nanotechnology based on adsorption and biosorption, nanofiltration, photocatalysis, disinfection and sensing technology. Furthermore, this review also highlights the fate of the nanomaterials in wastewater treatment as well as risks associated with their use.
Gravity is a fundamental interaction that permeates throughout our Universe. On Earth, gravity gives weight to physical objects, and has been a constant presence throughout terrestrial biological ...evolution. Thus, gravity has shaped all biological functions, some examples include the growth of plants (e.g., gravitropism), the structure and morphology of biological parts in multicellular organisms, to its effects on our physiological function when humans travel into space. Moreover, from an evolutionary perspective, gravity has been a constant force on biology, and life, to our understanding, should have no reason to not experience the effects of gravity. Interestingly, there appear to be specific biological mechanisms that activate in the absence of gravity, with the space environment the only location to study the effects of a lack of gravity on biological systems. Thus, in this perspective piece, biological adaptations from the cellular to the whole organism levels to the presence and absence of gravity will be organized and described, as well as outlining future areas of research for gravitational biological investigations to address. Up to now, we have observed and shown how gravity effects biology at different levels, with a few examples including genetic (e.g., cell cycle, metabolism, signal transduction associated pathways, etc.), biochemically (e.g., cytoskeleton, NADPH oxidase, Yes-associated protein, etc.), and functionally (e.g., astronauts experiencing musculoskeletal and cardiovascular deconditioning, immune dysfunction, etc., when traveling into space). Based from these observations, there appear to be gravity-sensitive and specific pathways across biological organisms, though knowledge gaps of the effects of gravity on biology remain, such as similarities and differences across species, reproduction, development, and evolutionary adaptations, sex-differences, etc. Thus, here an overview of the literature is provided for context of gravitational biology research to-date and consideration for future studies, as we prepare for long-term occupation of low-Earth Orbit and cis-Lunar space, and missions to the Moon and Mars, experiencing the effects of Lunar and Martian gravity on biology, respectively, through our Artemis program.
Perovskite solar cells (PSCs) have become a promising photovoltaic (PV) technology, where the evolution of the electron‐selective layers (ESLs), an integral part of any PV device, has played a ...distinctive role to their progress. To date, the mesoporous titanium dioxide (TiO2)/compact TiO2 stack has been among the most used ESLs in state‐of‐the‐art PSCs. However, this material requires high‐temperature sintering and may induce hysteresis under operational conditions, raising concerns about its use toward commercialization. Recently, tin oxide (SnO2) has emerged as an attractive alternative ESL, thanks to its wide bandgap, high optical transmission, high carrier mobility, suitable band alignment with perovskites, and decent chemical stability. Additionally, its low‐temperature processability enables compatibility with temperature‐sensitive substrates, and thus flexible devices and tandem solar cells. Here, the notable developments of SnO2 as a perovskite‐relevant ESL are reviewed with emphasis placed on the various fabrication methods and interfacial passivation routes toward champion solar cells with high stability. Further, a techno‐economic analysis of SnO2 materials for large‐scale deployment, together with a processing‐toxicology assessment, is presented. Finally, a perspective on how SnO2 materials can be instrumental in successful large‐scale module and perovskite‐based tandem solar cell manufacturing is provided.
Notable developments of SnO2 as an electron‐selective layer for efficient perovskite solar cells (PSCs) are reviewed, along with an overview of the fabrication methods and interfacial passivation routes. Furthermore, techno‐economic and toxicology analyses of SnO2 are discussed for possible large‐scale deployment of PSCs. Finally, the role of SnO2 in scaled module and tandem solar cell production is revealed.
Preliminary clinical data indicate that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with neurological and neuropsychiatric illness. Responding to this, a ...weekly virtual coronavirus disease 19 (COVID-19) neurology multi-disciplinary meeting was established at the National Hospital, Queen Square, in early March 2020 in order to discuss and begin to understand neurological presentations in patients with suspected COVID-19-related neurological disorders. Detailed clinical and paraclinical data were collected from cases where the diagnosis of COVID-19 was confirmed through RNA PCR, or where the diagnosis was probable/possible according to World Health Organization criteria. Of 43 patients, 29 were SARS-CoV-2 PCR positive and definite, eight probable and six possible. Five major categories emerged: (i) encephalopathies (n = 10) with delirium/psychosis and no distinct MRI or CSF abnormalities, and with 9/10 making a full or partial recovery with supportive care only; (ii) inflammatory CNS syndromes (n = 12) including encephalitis (n = 2, para- or post-infectious), acute disseminated encephalomyelitis (n = 9), with haemorrhage in five, necrosis in one, and myelitis in two, and isolated myelitis (n = 1). Of these, 10 were treated with corticosteroids, and three of these patients also received intravenous immunoglobulin; one made a full recovery, 10 of 12 made a partial recovery, and one patient died; (iii) ischaemic strokes (n = 8) associated with a pro-thrombotic state (four with pulmonary thromboembolism), one of whom died; (iv) peripheral neurological disorders (n = 8), seven with Guillain-Barré syndrome, one with brachial plexopathy, six of eight making a partial and ongoing recovery; and (v) five patients with miscellaneous central disorders who did not fit these categories. SARS-CoV-2 infection is associated with a wide spectrum of neurological syndromes affecting the whole neuraxis, including the cerebral vasculature and, in some cases, responding to immunotherapies. The high incidence of acute disseminated encephalomyelitis, particularly with haemorrhagic change, is striking. This complication was not related to the severity of the respiratory COVID-19 disease. Early recognition, investigation and management of COVID-19-related neurological disease is challenging. Further clinical, neuroradiological, biomarker and neuropathological studies are essential to determine the underlying pathobiological mechanisms that will guide treatment. Longitudinal follow-up studies will be necessary to ascertain the long-term neurological and neuropsychological consequences of this pandemic.
In this study, a rectangular microstrip patch antenna (MSPA) with a low X-band radar cross section (RCS) is proposed. The existing RCS reduction involves many layers, which raises design complexity. ...The research challenge is to lower the X-band RCS of a patch antenna using single-layer while keeping the good radiation performance. A polarization rotation reflective surface (PRRS) made up of unit cells arranged in the same plane encircles the proposed MSPA. This MSPA's radiation pattern and scattering capabilities are investigated and the effective RCS reduction in the X-band frequency from 8 to 12 GHz is achieved by arranging the unit cells of the newly developed PRRS. The proposed MSPA, which has an impedance bandwidth (BW) of 8.98 GHz to 10.99 GHz and a low X-band RCS, eliminates the requirement for multiple layers in the antenna. In addition, the antenna has the length and width of 23 mm and 41 mm with 14 unit cells and radiating elements of antenna is 9 mm x 6 mm and the substrate have the thickness of h = 2 mm.
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