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Showing papers by "Griffith University published in 2021"


Journal ArticleDOI
TL;DR: The High-Resolution Network (HRNet) as mentioned in this paper maintains high-resolution representations through the whole process by connecting the high-to-low resolution convolution streams in parallel and repeatedly exchanging the information across resolutions.
Abstract: High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-the-art frameworks first encode the input image as a low-resolution representation through a subnetwork that is formed by connecting high-to-low resolution convolutions in series (e.g., ResNet, VGGNet), and then recover the high-resolution representation from the encoded low-resolution representation. Instead, our proposed network, named as High-Resolution Network (HRNet), maintains high-resolution representations through the whole process. There are two key characteristics: (i) Connect the high-to-low resolution convolution streams in parallel and (ii) repeatedly exchange the information across resolutions. The benefit is that the resulting representation is semantically richer and spatially more precise. We show the superiority of the proposed HRNet in a wide range of applications, including human pose estimation, semantic segmentation, and object detection, suggesting that the HRNet is a stronger backbone for computer vision problems. All the codes are available at https://github.com/HRNet .

1,162 citations


Journal ArticleDOI
16 Mar 2021-BMJ Open
TL;DR: In this paper, the extent and nature of changes in utilisation of healthcare services during the COVID-19 pandemic was determined by a systematic review of studies across 20 countries, reporting on >11 million services prepandemic and 6.9 million during the pandemic.
Abstract: Objectives To determine the extent and nature of changes in utilisation of healthcare services during COVID-19 pandemic. Design Systematic review. Eligibility Eligible studies compared utilisation of services during COVID-19 pandemic to at least one comparable period in prior years. Services included visits, admissions, diagnostics and therapeutics. Studies were excluded if from single centres or studied only patients with COVID-19. Data sources PubMed, Embase, Cochrane COVID-19 Study Register and preprints were searched, without language restrictions, until 10 August, using detailed searches with key concepts including COVID-19, health services and impact. Data analysis Risk of bias was assessed by adapting the Risk of Bias in Non-randomised Studies of Interventions tool, and a Cochrane Effective Practice and Organization of Care tool. Results were analysed using descriptive statistics, graphical figures and narrative synthesis. Outcome measures Primary outcome was change in service utilisation between prepandemic and pandemic periods. Secondary outcome was the change in proportions of users of healthcare services with milder or more severe illness (eg, triage scores). Results 3097 unique references were identified, and 81 studies across 20 countries included, reporting on >11 million services prepandemic and 6.9 million during pandemic. For the primary outcome, there were 143 estimates of changes, with a median 37% reduction in services overall (IQR −51% to −20%), comprising median reductions for visits of 42% (−53% to −32%), admissions 28% (−40% to −17%), diagnostics 31% (−53% to −24%) and for therapeutics 30% (−57% to −19%). Among 35 studies reporting secondary outcomes, there were 60 estimates, with 27 (45%) reporting larger reductions in utilisation among people with a milder spectrum of illness, and 33 (55%) reporting no difference. Conclusions Healthcare utilisation decreased by about a third during the pandemic, with considerable variation, and with greater reductions among people with less severe illness. While addressing unmet need remains a priority, studies of health impacts of reductions may help health systems reduce unnecessary care in the postpandemic recovery. PROSPERO registration number CRD42020203729.

452 citations


Journal ArticleDOI
TL;DR: It is essential to discuss the agricultural development process; the historical perspective, types and specific uses of pesticides; and pesticide behavior, its contamination, and adverse effects on the natural environment to provide the scientific information necessary for pesticide application and management in the future.
Abstract: Pesticides are indispensable in agricultural production. They have been used by farmers to control weeds and insects, and their remarkable increases in agricultural products have been reported. The increase in the world's population in the 20th century could not have been possible without a parallel increase in food production. About one-third of agricultural products are produced depending on the application of pesticides. Without the use of pesticides, there would be a 78% loss of fruit production, a 54% loss of vegetable production, and a 32% loss of cereal production. Therefore, pesticides play a critical role in reducing diseases and increasing crop yields worldwide. Thus, it is essential to discuss the agricultural development process; the historical perspective, types and specific uses of pesticides; and pesticide behavior, its contamination, and adverse effects on the natural environment. The review study indicates that agricultural development has a long history in many places around the world. The history of pesticide use can be divided into three periods of time. Pesticides are classified by different classification terms such as chemical classes, functional groups, modes of action, and toxicity. Pesticides are used to kill pests and control weeds using chemical ingredients; hence, they can also be toxic to other organisms, including birds, fish, beneficial insects, and non-target plants, as well as air, water, soil, and crops. Moreover, pesticide contamination moves away from the target plants, resulting in environmental pollution. Such chemical residues impact human health through environmental and food contamination. In addition, climate change-related factors also impact on pesticide application and result in increased pesticide usage and pesticide pollution. Therefore, this review will provide the scientific information necessary for pesticide application and management in the future.

451 citations


Journal ArticleDOI
TL;DR: In this article, the early effect of the COVID-19 pandemic on suicide rates around the world was assessed using real-time suicide data from countries or areas within countries through a systematic internet search and recourse to our networks and the published literature.

413 citations


Journal ArticleDOI
Zewen Li1, Fan Liu1, Wenjie Yang1, Shouheng Peng1, Jun Zhou2 
TL;DR: In this article, the authors provide an overview of various convolutional neural network (CNN) models and provide several rules of thumb for functions and hyperparameter selection, as well as open issues and promising directions for future work.
Abstract: A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted much attention from both industry and academia in the past few years. The existing reviews mainly focus on CNN's applications in different scenarios without considering CNN from a general perspective, and some novel ideas proposed recently are not covered. In this review, we aim to provide some novel ideas and prospects in this fast-growing field. Besides, not only 2-D convolution but also 1-D and multidimensional ones are involved. First, this review introduces the history of CNN. Second, we provide an overview of various convolutions. Third, some classic and advanced CNN models are introduced; especially those key points making them reach state-of-the-art results. Fourth, through experimental analysis, we draw some conclusions and provide several rules of thumb for functions and hyperparameter selection. Fifth, the applications of 1-D, 2-D, and multidimensional convolution are covered. Finally, some open issues and promising directions for CNN are discussed as guidelines for future work.

342 citations


Journal ArticleDOI
TL;DR: It is recommended the establishment of a global research consortium to further study the natural history of OPMDs based on the classification and nomenclature proposed here, and link them to evidence-based interventions, to facilitate the prevention and management of lip and oral cavity cancer.
Abstract: Oral potentially malignant disorders (OPMDs) are associated with an increased risk of occurrence of cancers of the lip or oral cavity. This paper presents an updated report on the nomenclature and the classification of OPMDs, based predominantly on their clinical features, following discussions by an expert group at a workshop held by the World Health Organization (WHO) Collaborating Centre for Oral Cancer in the UK. The first workshop held in London in 2005 considered a wide spectrum of disorders under the term "potentially malignant disorders of the oral mucosa" (PMD) (now referred to as oral potentially malignant disorders: OPMD) including leukoplakia, erythroplakia, proliferative verrucous leukoplakia, oral lichen planus, oral submucous fibrosis, palatal lesions in reverse smokers, lupus erythematosus, epidermolysis bullosa, and dyskeratosis congenita. Any new evidence published in the intervening period was considered to make essential changes to the 2007 classification. In the current update, most entities were retained with minor changes to their definition. There is sufficient evidence for an increased risk of oral cancer among patients diagnosed with "oral lichenoid lesions" and among those diagnosed with oral manifestations of 'chronic graft-versus-host disease'. These have now been added to the list of OPMDs. There is, to date, insufficient evidence concerning the malignant potential of chronic hyperplastic candidosis and of oral exophytic verrucous hyperplasia to consider these conditions as OPMDs. Furthermore, due to lack of clear evidence of an OPMD in epidermolysis bullosa this was moved to the category with limited evidence. We recommend the establishment of a global research consortium to further study the natural history of OPMDs based on the classification and nomenclature proposed here. This will require multi-center longitudinal studies with uniform diagnostic criteria to improve the identification and cancer risk stratification of patients with OPMDs, link them to evidence-based interventions, with a goal to facilitate the prevention and management of lip and oral cavity cancer.

306 citations


Journal ArticleDOI
TL;DR: Interest in natural fiber reinforced composites (NFRCs) is increasing rapidly thanks to their numerous advantages such as low cost, biodegradability, eco-friendly nature, relatively good mechanical properties as discussed by the authors.
Abstract: Interest in natural fiber–reinforced composites (NFRCs) is increasing rapidly thanks to their numerous advantages such as low cost, biodegradability, eco-friendly nature, relatively good mechanical...

184 citations


Journal ArticleDOI
TL;DR: In this article, a heat-ink-like evaporator (HSE) was developed to eliminate the energy loss to the surrounding environment during solar steam generation, leading to the absolute cold evaporation over the entire evaporator under 10 sun irradiation.
Abstract: Interfacial solar steam generation is a highly efficient and sustainable technology for clean water production and wastewater treatment Although great progress has been achieved in improving evaporation rate and energy efficiency, it's still challenging to fully eliminate the energy loss to the surrounding environment during solar steam generation To achieve this, a novel heatsink-like evaporator (HSE) is developed herein During solar evaporation, the temperature on the top solar evaporation surface can be regulated by the fin structures of the HSE For the evaporators with 5 to 7 heatsink fins, the temperature of the solar evaporation surface is decreased to be lower than the ambient temperature, which fully eliminates the radiation, convection, and conduction heat losses, leading to the absolute cold evaporation over the entire evaporator under 10 sun irradiation As a result, massive energy (426 W), which is over 170% of the received light energy, is harvested from the environment due to the temperature deficit, significantly enhancing the energy efficiency of solar steam generation An extremely high evaporation rate of 410 kg m-2 h-1 is realized with a 6-fin photothermal HSE, corresponding to an energy conversion efficiency far beyond the theoretical limit, assuming 100% light-to-vapor energy conversion

179 citations


Proceedings ArticleDOI
19 Apr 2021
TL;DR: Coder et al. as discussed by the authors proposed a multi-channel hypergraph convolutional network to enhance social recommendation by leveraging high-order user relations, where each channel in the network encodes a hypergraph that depicts a common highorder user relation pattern via hypergraph CNN.
Abstract: Social relations are often used to improve recommendation quality when user-item interaction data is sparse in recommender systems. Most existing social recommendation models exploit pairwise relations to mine potential user preferences. However, real-life interactions among users are very complex and user relations can be high-order. Hypergraph provides a natural way to model high-order relations, while its potentials for improving social recommendation are under-explored. In this paper, we fill this gap and propose a multi-channel hypergraph convolutional network to enhance social recommendation by leveraging high-order user relations. Technically, each channel in the network encodes a hypergraph that depicts a common high-order user relation pattern via hypergraph convolution. By aggregating the embeddings learned through multiple channels, we obtain comprehensive user representations to generate recommendation results. However, the aggregation operation might also obscure the inherent characteristics of different types of high-order connectivity information. To compensate for the aggregating loss, we innovatively integrate self-supervised learning into the training of the hypergraph convolutional network to regain the connectivity information with hierarchical mutual information maximization. Extensive experiments on multiple real-world datasets demonstrate the superiority of the proposed model over the current SOTA methods, and the ablation study verifies the effectiveness and rationale of the multi-channel setting and the self-supervised task. The implementation of our model is available via https://github.com/Coder-Yu/RecQ.

172 citations


Journal ArticleDOI
TL;DR: In this paper, the importance of different forces in nanofluid flows that exist in particulate flows such as drag, lift (Magnus and Saffman), Brownian, thermophoretic, Van der Waals, electrostatic double layer forces are considered.

165 citations


Journal ArticleDOI
23 Apr 2021
TL;DR: In this article, the authors present a framework for three categories of increasingly complex climate change risk that focus on interactions among the multiple drivers of risk, as well as among multiple risks.
Abstract: Real-world experience underscores the complexity of interactions among multiple drivers of climate change risk and of how multiple risks compound or cascade. However, a holistic framework for assessing such complex climate change risks has not yet been achieved. Clarity is needed regarding the interactions that generate risk, including the role of adaptation and mitigation responses. In this perspective, we present a framework for three categories of increasingly complex climate change risk that focus on interactions among the multiple drivers of risk, as well as among multiple risks. A significant innovation is recognizing that risks can arise both from potential impacts due to climate change and from responses to climate change. This approach encourages thinking that traverses sectoral and regional boundaries and links physical and socio-economic drivers of risk. Advancing climate change risk assessment in these ways is essential for more informed decision making that reduces negative climate change impacts. © 2021 The Authors

Journal ArticleDOI
20 Apr 2021-Polymers
TL;DR: This review aims to provide compact information of the synthesis to the advanced applications of this material in various fields and covers the insights of future CMC research that could guide researchers working in this prominent field.
Abstract: Carboxymethyl cellulose (CMC) is one of the most promising cellulose derivatives. Due to its characteristic surface properties, mechanical strength, tunable hydrophilicity, viscous properties, availability and abundance of raw materials, low-cost synthesis process, and likewise many contrasting aspects, it is now widely used in various advanced application fields, for example, food, paper, textile, and pharmaceutical industries, biomedical engineering, wastewater treatment, energy production, and storage energy production, and storage and so on. Many research articles have been reported on CMC, depending on their sources and application fields. Thus, a comprehensive and well-organized review is in great demand that can provide an up-to-date and in-depth review on CMC. Herein, this review aims to provide compact information of the synthesis to the advanced applications of this material in various fields. Finally, this article covers the insights of future CMC research that could guide researchers working in this prominent field.

Journal ArticleDOI
TL;DR: In this article, a facile and controllable vacuum-calcination strategy is utilized to convert Co(OH)2 into oxygen-defective amorphous-crystalline CoO (namely ODAC•CoO) nanosheets.
Abstract: Efficient oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) processes highly rely on the rational design and synthesis of high‐performance electrocatalysts. Herein, comprehensive characterizations and density functional theory (DFT) calculations are combined to verify the important roles of the crystallinity and oxygen vacancy levels of Co(II) oxide (CoO) on ORR and OER activities. A facile and controllable vacuum‐calcination strategy is utilized to convert Co(OH)2 into oxygen‐defective amorphous‐crystalline CoO (namely ODAC‐CoO) nanosheets. With the carefully controlled crystallinity and oxygen vacancy levels, the optimal ODAC‐CoO sample exhibits dramatically enhanced ORR and OER electrocatalytic activities compared with the pure crystalline CoO counterpart. The assembled liquid and quasi‐solid‐state Zn–air batteries with ODAC‐CoO as cathode material achieve remarkable specific capacity, power density, and excellent cycling stability, outperforming the benchmark Pt/C+IrO2 catalysts. This study theoretically proposes and experimentally demonstrates that the simultaneous introduction of amorphous structures and oxygen vacancies could be an effective avenue towards high‐performance electrocatalytic ORR and OER.

Journal ArticleDOI
07 Apr 2021-Neuron
TL;DR: In this paper, the authors demonstrate that SARM1 is activated by an increase in the ratio of nicotinamide mononucleotide (NMN) to NAD+ and show that both metabolites compete for binding to the auto-inhibitory N-terminal armadillo repeat (ARM) domain.

Journal ArticleDOI
09 Feb 2021-Mbio
TL;DR: In this article, a systematic review was conducted using data from MEDLINE, Scopus, Web of Science, and EMBASE databases published from 1 December 2019 to 15 September 2020 to evaluate the correlation between comorbidities and their role in the exacerbation of disease in COVID-19 patients leading to fatal outcomes.
Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread across the globe at unprecedented speed and is showing no signs of slowing down The outbreak of coronavirus disease 2019 (COVID-19) has led to significant health burden in infected patients especially in those with underlying comorbidities The aim of this study was to evaluate the correlation between comorbidities and their role in the exacerbation of disease in COVID-19 patients leading to fatal outcomes A systematic review was conducted using data from MEDLINE, Scopus, Web of Science, and EMBASE databases published from 1 December 2019 to 15 September 2020 Fifty-three articles were included in the systematic review Of those 53 articles, 8 articles were eligible for meta-analysis Hypertension, obesity, and diabetes mellitus were identified to be the most prevalent comorbidities in COVID-19 patients Our meta-analysis showed that cancer, chronic kidney diseases, diabetes mellitus, and hypertension were independently associated with mortality in COVID-19 patients Chronic kidney disease was statistically the most prominent comorbidity leading to death However, despite having high prevalence, obesity was not associated with mortality in COVID-19 patientsIMPORTANCE COVID-19 has plagued the world since it was first identified in December 2019 Previous systematic reviews and meta-analysis were limited by various factors such as the usage of non-peer reviewed data and were also limited by the lack of clinical data on a global scale Comorbidities are frequently cited as risk factors for severe COVID-19 outcomes However, the degree to which specific comorbidities impact the disease is debatable Our study selection involves a global reach and covers all comorbidities that were reported to be involved in the exacerbation of COVID-19 leading to fatal outcomes, which allows us to identify the specific comorbidities that have higher risk in patients The study highlights COVID-19 high-risk groups However, further research should focus on the status of comorbidities and prognosis in COVID-19 patients

Journal ArticleDOI
TL;DR: The findings reveal that employees’ deep compliance with safety procedures includes a four-stage psychological process, and this process is underpinned by both management safety practices and organizational crisis strategies.

Journal ArticleDOI
TL;DR: In this paper, the authors highlight the specific considerations needed when employing women (i.e., from athletes to non-athletes) as participants in sport and exercise science-based research and address the diversity and complexities associated with female reproductive endocrinology across the lifespan.
Abstract: Until recently, there has been less demand for and interest in female-specific sport and exercise science data. As a result, the vast majority of high-quality sport and exercise science data have been derived from studies with men as participants, which reduces the application of these data due to the known physiological differences between the sexes, specifically with regard to reproductive endocrinology. Furthermore, a shortage of specialist knowledge on female physiology in the sport science community, coupled with a reluctance to effectively adapt experimental designs to incorporate female-specific considerations, such as the menstrual cycle, hormonal contraceptive use, pregnancy and the menopause, has slowed the pursuit of knowledge in this field of research. In addition, a lack of agreement on the terminology and methodological approaches (i.e., gold-standard techniques) used within this research area has further hindered the ability of researchers to adequately develop evidenced-based guidelines for female exercisers. The purpose of this paper was to highlight the specific considerations needed when employing women (i.e., from athletes to non-athletes) as participants in sport and exercise science-based research. These considerations relate to participant selection criteria and adaptations for experimental design and address the diversity and complexities associated with female reproductive endocrinology across the lifespan. This statement intends to promote an increase in the inclusion of women as participants in studies related to sport and exercise science and an enhanced execution of these studies resulting in more high-quality female-specific data.

Journal ArticleDOI
TL;DR: The SARS-CoV-2 reverse genetics toolkit as discussed by the authors can be used to rescue infectious virus through transient transfection (without in vitro transcription or additional expression plasmids).
Abstract: The recent emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the underlying cause of Coronavirus Disease 2019 (COVID-19), has led to a worldwide pandemic causing substantial morbidity, mortality, and economic devastation. In response, many laboratories have redirected attention to SARS-CoV-2, meaning there is an urgent need for tools that can be used in laboratories unaccustomed to working with coronaviruses. Here we report a range of tools for SARS-CoV-2 research. First, we describe a facile single plasmid SARS-CoV-2 reverse genetics system that is simple to genetically manipulate and can be used to rescue infectious virus through transient transfection (without in vitro transcription or additional expression plasmids). The rescue system is accompanied by our panel of SARS-CoV-2 antibodies (against nearly every viral protein), SARS-CoV-2 clinical isolates, and SARS-CoV-2 permissive cell lines, which are all openly available to the scientific community. Using these tools, we demonstrate here that the controversial ORF10 protein is expressed in infected cells. Furthermore, we show that the promising repurposed antiviral activity of apilimod is dependent on TMPRSS2 expression. Altogether, our SARS-CoV-2 toolkit, which can be directly accessed via our website at https://mrcppu-covid.bio/, constitutes a resource with considerable potential to advance COVID-19 vaccine design, drug testing, and discovery science.

Journal ArticleDOI
TL;DR: The consensus provides an assessment of evidence for efficacy and safety of an important therapeutic class with guidance on issues of practical management of Janus kinase inhibitors.
Abstract: Objectives: Janus kinase inhibitors (JAKi) have been approved for use in various immune-mediated inflammatory diseases. With five agents licensed, it was timely to summarise the current understanding of JAKi use based on a systematic literature review (SLR) on efficacy and safety. Methods: Existing data were evaluated by a steering committee and subsequently reviewed by a 29 person expert committee leading to the formulation of a consensus statement that may assist the clinicians, patients and other stakeholders once the decision is made to commence a JAKi. The committee included patients, rheumatologists, a gastroenterologist, a haematologist, a dermatologist, an infectious disease specialist and a health professional. The SLR informed the Task Force on controlled and open clinical trials, registry data, phase 4 trials and meta-analyses. In addition, approval of new compounds by, and warnings from regulators that were issued after the end of the SLR search date were taken into consideration. Results: The Task Force agreed on and developed four general principles and a total of 26 points for consideration which were grouped into six areas addressing indications, treatment dose and comedication, contraindications, pretreatment screening and risks, laboratory and clinical follow-up examinations, and adverse events. Levels of evidence and strengths of recommendations were determined based on the SLR and levels of agreement were voted on for every point, reaching a range between 8.8 and 9.9 on a 10-point scale. Conclusion: The consensus provides an assessment of evidence for efficacy and safety of an important therapeutic class with guidance on issues of practical management.

Journal ArticleDOI
TL;DR: It is shown for the first time that most microplastics are retained during the initial screening and grit removal process with the load of microplastic going to landfill an order of magnitude greater than that in biosolids.

Journal ArticleDOI
TL;DR: Li et al. as discussed by the authors synthesized a self-healing poly(ether-thioureas) (SHPET) polymer with balanced rigidity and softness for the silicon anode.

Journal ArticleDOI
TL;DR: This work introduces a novel pairwise loss function that enables ReID models to learn the fine-grained features by adaptively enforcing an exponential penalization on the images of small differences and a bounded penalization of large differences.
Abstract: Person Re-IDentification (ReID) aims at re-identifying persons from different viewpoints across multiple cameras. Capturing the fine-grained appearance differences is often the key to accurate person ReID, because many identities can be differentiated only when looking into these fine-grained differences. However, most state-of-the-art person ReID approaches, typically driven by a triplet loss, fail to effectively learn the fine-grained features as they are focused more on differentiating large appearance differences. To address this issue, we introduce a novel pairwise loss function that enables ReID models to learn the fine-grained features by adaptively enforcing an exponential penalization on the images of small differences and a bounded penalization on the images of large differences. The proposed loss is generic and can be used as a plugin to replace the triplet loss to significantly enhance different types of state-of-the-art approaches. Experimental results on four benchmark datasets show that the proposed loss substantially outperforms a number of popular loss functions by large margins; and it also enables significantly improved data efficiency.

Journal ArticleDOI
TL;DR: There does not yet appear to be an overall change in the suspected suicide rate in the 7 months since Queensland declared a public health emergency, which reinforces the need for governments to maintain the monitoring and reporting of suicide mortality in real time.

Journal ArticleDOI
TL;DR: Panic buying emerged as a significant phenomenon during the COVID-19 pandemic as discussed by the authors, where government measures, media and peer influence had a significant influence on panic buyers' psychological outcomes.
Abstract: Panic buying emerged as a significant phenomenon during the COVID-19 pandemic This study draws on the scarcity principle, crowd psychology and contagion theory to investigate the antecedents and consequences of panic buying The antecedents included in this study are government measures, media and peer influence and the fear of missing out The consequences are founded on a sense of security and guilt Retailer intervention is included as a moderator to the proposed main effects Data were collected from 341 consumers who engaged in panic buying and were residents of the United States and Australia during the COVID-19 pandemic Structural equation modelling was employed to test the proposed model The results show that the proposed antecedents (except fear of missing out) were significantly related to panic buying, which in turn had a significant influence on panic buyers' psychological outcomes The moderating effects of retailer intervention varied across different product categories Discussion and implications of these findings are provided for policy makers, customers and practitioners (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Journal ArticleDOI
TL;DR: In this article, a defective graphene (DG) substrate with 585 defects was used for charge redistribution of the attached exfoliated monolayer Iron Phthalocyanine (FePc) by using density functional theory (DFT) calculation.
Abstract: The intrinsic activity of transition metal catalytic centers for oxygen reduction reaction (ORR) depends heavily on its electronic structure, which with an electron-rich environment will boost the ORR performance. In this work, we firstly revealed the defective graphene (DG) substrate with 585 defects could efficiently mediate charge redistribution of the attached exfoliated monolayer Iron Phthalocyanine (FePc) by using density functional theory (DFT) calculation. The electrons transfer to FePc from 585 defects forms an electron-rich region on Fe atom, and high-density electrons further raise the d-band center of Fe atom. Apparently, this adjustment of electronic structure for Fe atoms is beneficial to the adsorption and reaction of O2 molecules, inducing more positive initial potential and larger current density for ORR. Based on this finding, DG obtained by the heat treatment was prepared to couple exfoliated monolayer FePc through stable π-π stacking. As expected, FePc/DG hybrid exhibits outstanding electrocatalytic ORR performance with a positive initial potential (0.98 V vs. RHE) and a high current density (5.45 mA·cm−2) in 0.1 M KOH electrolytes. In addition, the FePc/DG hybrid was utilized to assemble a zinc-air battery device, which reveals the power density of 190 mW·cm−2.

Journal ArticleDOI
TL;DR: In this article, the authors conducted a systematic literature review with the aim of establishing a consensus on the existence, or nonexistence, of a green premium in the green bond market and found that the green premium varies widely for the primary market; however, an average greenium of −1 to −9 basis points on the secondary market is observed.

Journal ArticleDOI
TL;DR: A review of energy systems for light-duty vehicles and highlights the main characteristics of electric and hybrid vehicles based on power train structure, environmental perspective, and cost is presented in this paper.
Abstract: Reduction in fossil fuel dependency has been an issue worldwide for several years. One of the solutions in the transportation sector to reduce the GHG, is the replacement of combustion engine vehicles with electric and hybrid vehicles. Furthermore, to make EVs competitive with ICEV, it is imperative to reduce the relatively high manufacturing cost, increase the range of those vehicles and find solutions to drastically reduce recharge times to a comparable ICEV refuelling time. Battery, Fuel Cell, and Super Capacitor are energy storage solutions implemented in electric vehicles, which possess different advantages and disadvantages. The combination of these Energy Storage Systems, rather than the sole use of one solution, has the potential to meet the required performance results, with regards to high energy density, lower energy consumption and a longer driving range of EVs, to replace ICEVs permanently. However, challenges such as energy management, size and cost of the energy storage systems, are essential concerns and need to be focused on for the production and adoption of EVs. Furthermore, limitations and requirements for changing power train configurations of conventional vehicles stimulate a market for biofuels and synthetic fuels, which also show potential to reduce greenhouse gas emission. This paper provides a review of energy systems for light-duty vehicles and highlights the main characteristics of electric and hybrid vehicles based on power train structure, environmental perspective, and cost. The review provides an overview of different solutions possible, which have the potential to significantly reduce GHG emissions in the transportation sector.

Journal ArticleDOI
TL;DR: In this paper, a review summarizes recent progress in different MOFs as outstanding adsorbents to remove heavy metal oxoanions from water, including typical SeO32−/SeO42−, HAsO42+/H2AsO4−/H3AsO3, and CrO42++/Cr2O72−.

Journal ArticleDOI
TL;DR: The definition of rural tourism remains unclear and only a few studies have mapped the current state of knowledge in this field as mentioned in this paper, which suggests several directions for future research in this domain, and response to the pandemic.

Journal ArticleDOI
TL;DR: Density functional theory calculations and experimental results confirm the enhanced electrocatalytic performances via the proposed interface engineering of heterogeneous CoS/CoO nanocrystals and N-doped graphene composite, which exhibits excellent performances in rechargeable Zn–air batteries.
Abstract: Low cost and green fabrication of high-performance electrocatalysts with earth-abundant resources for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are crucial for the large-scale application of rechargeable Zn–air batteries (ZABs). In this work, our density functional theory calculations on the electrocatalyst suggest that the rational construction of interfacial structure can induce local charge redistribution, improve the electronic conductivity and enhance the catalyst stability. In order to realize such a structure, we spatially immobilize heterogeneous CoS/CoO nanocrystals onto N-doped graphene to synthesize a bifunctional electrocatalyst (CoS/CoO@NGNs). The optimization of the composition, interfacial structure and conductivity of the electrocatalyst is conducted to achieve bifunctional catalytic activity and deliver outstanding efficiency and stability for both ORR and OER. The aqueous ZAB with the as-prepared CoS/CoO@NGNs cathode displays a high maximum power density of 137.8 mW cm−2, a specific capacity of 723.9 mAh g−1 and excellent cycling stability (continuous operating for 100 h) with a high round-trip efficiency. In addition, the assembled quasi-solid-state ZAB also exhibits outstanding mechanical flexibility besides high battery performances, showing great potential for applications in flexible and wearable electronic devices. Highlights: 1 Interface engineering of heterogeneous CoS/CoO nanocrystals and N-doped graphene composite facilitates high-performance oxygen reduction reaction and oxygen evolution reaction.2 Density functional theory calculations and experimental results confirm the enhanced electrocatalytic performances via the proposed interface engineering.3 The bifunctional oxygen electrocatalyst exhibits excellent performances in rechargeable Zn–air batteries.