Biomass burning (BB) is a significant air pollution source, with global, regional and local impacts on air quality, public health and climate. Worldwide an extensive range of studies has been ...conducted on almost all the aspects of BB, including its specific types, on quantification of emissions and on assessing its various impacts. China is one of the countries where the significance of BB has been recognized, and a lot of research efforts devoted to investigate it, however, so far no systematic reviews were conducted to synthesize the information which has been emerging. Therefore the aim of this work was to comprehensively review most of the studies published on this topic in China, including literature concerning field measurements, laboratory studies and the impacts of BB indoors and outdoors in China. In addition, this review provides insights into the role of wildfire and anthropogenic BB on air quality and health globally. Further, we attempted to provide a basis for formulation of policies and regulations by policy makers in China.
Open field biomass burning causes severe air pollution, public health risk and potential climate impact. a) Photo taken in Changzhou rural area on June 10, 2015; b) Photo taken in Hebei rural area on October 23, 2013; c) A traditional indoor burner in rural area in China; d) Tar ball emitted from biomass burning. Display omitted
•This review discusses wildfire and anthropogenic emission from biomass burning in China.•Field observations and laboratory studies on public health and climate impacts of biomass burning•Atmospheric process of biomass burning plumes and their transport•Proposed research priorities and insights about biomass burning in China
Broadband absorbers are required for solar energy harvesting because they efficiently absorb the incident photon in the wide-ranging solar spectrum. To ensure high absorption of photons, metamaterial ...absorbers (MMAs) have been a growing area of interest in recent years. In this article, an MMA is proposed using a metal-insulator-metal (MIM) structure (Ni-SiO
-Ni) that shows a near-unity broadband absorption of wavelengths from 300 to 1600 nm, with a 95.77% average absorption and a peak absorption of 99.999% at 772.82 nm. The MMA is polarization insensitive as well as wide incident angle stable. Analysis of the effects of mechanical bending on the absorption of the proposed structure shows that absorption holds satisfactory values at different degrees of mechanical loading. The suggested MMA unit cell structure was computationally simulated using the Finite Integration Technique (FIT) and verified using the Finite Element Method (FEM). To analyze the feasibility of the proposed MMA as a solar cell, it is investigated with the universal AM 1.5 solar spectrum characteristics. Besides solar energy harvesting, the proposed MMA unit cell may be employed in a variety of diverse optical applications, including sensors, detectors, and imaging.
Many short-lived and highly reactive oxygen species, such as superoxide anion (O
2
-
) and hydrogen peroxide (H
2
O
2
), are toxic or can create oxidative stress in cells, a response involved in the ...pathogenesis of numerous diseases depending on their concentration, location, and cellular conditions. Superoxide dismutase (SOD) activities as an endogenous and exogenous cell defense mechanism include the potential use in treating various diseases, improving the potential use in treating various diseases, and improving food-stuffs preparation dietary supplements human nutrition. Published work indicates that SOD regulates oxidative stress, lipid metabolism, inflammation, and oxidation in cells. It can prevent lipid peroxidation, the oxidation of low-density lipoprotein in macrophages, lipid droplets' formation, and the adhesion of inflammatory cells into endothelial monolayers. It also expresses antioxidant effects in numerous cancer-related processes. Additionally, different forms of SOD may also augment food processing and pharmaceutical applications, exhibit anticancer, antioxidant, and anti-inflammatory effects, and prevent arterial problems by protecting the proliferation of vascular smooth muscle cells. Many investigations in this review have reported the therapeutic ability and physiological importance of SOD. Because of their antioxidative effects, SODs are of great potential in the medicinal, cosmetic, food, farming and chemical industries. This review discusses the findings of human and animal studies that support the advantages of SOD enzyme regulations to reduce the formation of oxidative stress in various ways.
This paper presents a test method of twin-fibre single-lap joint bonded with a micro-droplet of epoxy and subjected to tensile loading for determining fibre-matrix interfacial shear strength (IFSS). ...Twenty-five carbon fibre (CF)/epoxy specimens and fifty-six carbon nanotube (CNT)-grafted CF/epoxy specimens were prepared and tested. The average IFSS measured for specimens with a mean grafting density of 10.9, 25.8, 35.1 or 58.8 CNTs per μm2 can be improved by 51%, 101%, 155% and 273% (223%) respectively comparing to that without grafted CNTs. A multi-scale analytical model that relates micro-scale IFSS to nanoscale CNT grafting strength and density is developed and then used for predicting the IFSS of CNT-CF reinforced composites. There exists a good correlation between the measured and predicted IFSS of specimens with different grafting densities.
In response to prevailing classification inconsistency between land cover maps, developed by different organizations in different times at different scales, an object-based National Land ...Representation System (NLRS) for Bangladesh has been developed. The process, which began in 2013 and was completed in 2016, brought together several national organizations and involved an extensive process of consultation, data collection, translation, and analysis of existing land cover/use classification systems. The process focused on the interpretation of three legends from historic national land cover/use maps. Field inventory data were collected from over 1000 sites across the country to assist the process of land characterization and the development of a dynamic and representative overview of land cover and land use in Bangladesh. The system has been applied to the development of a wall-to-wall national land cover map for the year 2015. In this article, the methodological process and results of NLRS formulation and land cover map 2015 are presented. We also provide examples of how this interoperable system and the land cover dataset are being used for variety of applications including national forest resources assessment, estimation of REDD+ activity data, integration of biophysical and socioeconomic information, and semantic similarity assessment.
The paper presents a novel fixed switching frequency predictive current control method for switched reluctance machines (SRM). The proposed deadbeat predictive current controller accurately predicts ...the required duty ratio for the PWM pulse for a given reference current in each digital time step over the entire speed range of operation. The pulse width depends on the operating conditions, machine parameters and the rotor position. The controller utilizes the machine inductance profile as a function of current and rotor position to accurately predict the required voltage. The control method is studied through computer simulation and followed by experimental validation. The method is suitable for torque ripple sensitive applications requiring accurate tracking of a given current profile and mitigating the audible noise due to the switching of the inverter.
Abstract
Metal hydrides (MH) are known as one of the most suitable material groups for hydrogen energy storage because of their large hydrogen storage capacity, low operating pressure, and high ...safety. However, their slow hydrogen absorption kinetics significantly decreases storage performance. Faster heat removal from MH storage can play an essential role to enhance its hydrogen absorption rate, resulting in better storage performance. In this regard, the present study aims to improve heat transfer performance to positively impact the hydrogen absorption rate of MH storage systems. A novel semi-cylindrical coil is first designed and optimized for hydrogen storage and embedded as an internal heat exchanger with air as the heat transfer fluid (HTF). The effect of novel heat exchanger configurations is analyzed and compared with normal helical coil geometry, based on various pitch sizes. Furthermore, the operating parameters of MH storage and HTF are numerically investigated to obtain optimal values. ANSYS Fluent 2020 R2 is utilized for the numerical simulations. Results from this study demonstrate that MH storage performance is significantly improved by using a semi-cylindrical coil heat exchanger (SCHE). The hydrogen absorption duration reduces by 59% compared to a normal helical coil heat exchanger. The lowest coil pitch from SCHE leads to a 61% reduction of the absorption time. In terms of operating parameters for the MH storage with SCHE, all selected parameters provide a major improvement in the hydrogen absorption process, especially the inlet temperature of the HTF.
•Thorough thermal analysis for two modified flat plate heat exchangers (FPHEm1), and (FPHEm2).•Flow distribution inside channels of FPHEm2 is the best.•Thermal stresses in the plates of FPHEm2 are ...the lowest.•Overall thermal performance of FPHEm2 outperforms its counterparts.•Numerical model is verified with experimental studies.
Flat plate heat exchanger (FPHE) can tolerate more mass flow rate, significantly yield lesser pressure drop, and it is easier for manufacturing than the corrugated plate heat exchanger (CPHE). However, the overall thermal performance of FPHE is poor due to its low heat transfer rate. Therefore, the aim of the current study is to improve the thermal performance of the existing conventional FPHE (FPHEC). Thus, two newly developed modified FPHEs are introduced (FPHEm1 and FPHEm2). A computational fluid dynamics (CFD) technique is applied to numerically test the performance of the heat exchangers (HEs). Moreover, experiments are carried out to confirm the validity of the numerical results obtained in this study. The performance of FPHEm2 significantly outperforms that of FPHEC and FPHEm1. Hence, the results of FPHEm2 are compared with those of the conventional corrugated plate heat exchanger (CPHEC). Data of Nusselt number (Nu), fanning friction factor (f), turbulence intensity, JF factor, severity of temperature gradient of the plate (ΔTp), and average temperature through the plate (Tp,avg) are employed to quantify the best performance among all four HEs. The numerical results show that FPHEm2 has the best temperature uniformity and average temperature (the lowest values), and it has the highest Nu, JF, and turbulence intensity among all four HEs. Also, the f data of the FPHEm2 are 18.7% to 33.2% lower than those of the CPHEC. Thus, FPHEm2 could be a probable replacement of its counterparts of both FPHEC and CPHEC. Critical Reynolds numbers (Recr) of FPHEm2, heat transfer correlations and the flow distribution along with other details have been analysed numerically.
Internet-of-Things (IoT)-based wireless body area networks (WBANs) play an important role in modern medical systems for patient-health monitoring. WBANs have the capability to collect real-time ...biological information from the patients' body using intelligent sensors and then send the collected information to the remote doctors or medical experts using the Internet. In recent years, numerous anonymous authentication schemes were proposed to provide security in WBANs. However, many of these schemes are not computationally efficient during anonymous authentication. Moreover, the previous schemes did not provide location privacy for both doctors and patients. In order to overcome these limitations, in this article, we propose an efficient and secure anonymous authentication framework with location privacy preservation for IoT-based WBANs. The comprehensive analysis section shows that the proposed scheme overcomes the security weaknesses in the existing schemes and also provides low computation cost during anonymous authentication.
The monkeypox virus poses a new pandemic threat while we are still recovering from COVID-19. Despite the fact that monkeypox is not as lethal and contagious as COVID-19, new patient cases are ...recorded every day. If preparations are not made, a global pandemic is likely. Deep learning (DL) techniques are now showing promise in medical imaging for figuring out what diseases a person has. The monkeypox virus-infected human skin and the region of the skin can be used to diagnose the monkeypox early because an image has been used to learn more about the disease. But there is still no reliable Monkeypox database that is available to the public that can be used to train and test DL models. As a result, it is essential to collect images of monkeypox patients. The “MSID” dataset, short form of “Monkeypox Skin Images Dataset”, which was developed for this research, is free to use and can be downloaded from the Mendeley Data database by anyone who wants to use it. DL models can be built and used with more confidence using the images in this dataset. These images come from a variety of open-source and online sources and can be used for research purposes without any restrictions. Furthermore, we proposed and evaluated a modified DenseNet-201 deep learning-based CNN model named MonkeyNet. Using the original and augmented datasets, this study suggested a deep convolutional neural network that was able to correctly identify monkeypox disease with an accuracy of 93.19% and 98.91% respectively. This implementation also shows the Grad-CAM which indicates the level of the model’s effectiveness and identifies the infected regions in each class image, which will help the clinicians. The proposed model will also help doctors make accurate early diagnoses of monkeypox disease and protect against the spread of the disease.
•A first-ever multiclass image-based database has been developed named “Monkeypox Skin Images Dataset” for the detection and classification of monkeypox disease.•A new modified DenseNet-201 based deep CNN model named “MonkeyNet” has been proposed.•The proposed model has been evaluated with precision, recall, F1-score, accuracy, and AUC metrics and obtained 94.04% and 99.85% accuracy on original and augmented datasets respectively.•Deep learning and machine learning approaches have been applied to the developed dataset also.•A real-time framework has been developed based on the proposed method that helps clinicians to make quick and effective diagnoses and treatments.
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