As an important part of urban construction,elderly-friendly construction is crucial to the formation of an elderly-friendly society,which has been widely recognized internationally.Especially after the COVID-19 pandem...As an important part of urban construction,elderly-friendly construction is crucial to the formation of an elderly-friendly society,which has been widely recognized internationally.Especially after the COVID-19 pandemic,various organizations around the world have called for changes in public space and urban building planning,with an emphasis on the accessibility of green spaces.This underscores the complexity and difficulty of integrating vulnerable groups of the elderly into cities and using infrastructure and public space.展开更多
The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated...The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.展开更多
Injecting carbon dioxide(CO_(2))into coal seams may unlock substantial carbon sequestration potential.Since the coal acts like a carbon filter,it can preferentially absorb significant amounts of CO_(2).To explore this...Injecting carbon dioxide(CO_(2))into coal seams may unlock substantial carbon sequestration potential.Since the coal acts like a carbon filter,it can preferentially absorb significant amounts of CO_(2).To explore this further,desorption of the adsorbed gas due to pressure drop is investigated in this paper,to achieve an improved understanding of the long-term fate of injected CO_(2) during post-injection period.This paper presents a dual porosity model coupling gas flow,adsorption and geomechanics for studying coupled processes and effectiveness of CO_(2) sequestration in coals.A new adsorption?desorption model derived based on thermodynamics is incorporated,particularly,the desorption hysteresis is considered.The reliability of the proposed adsorption-desorption isotherm is examined via validation tests.It is indicated that occurrence of desorption hysteresis is attributed to the adsorption-induced pore deformation.After injection ceases,the injected gas continues to propagate further from the injection well,while the pressure in the vicinity of the injection well experiences a significant drop.Although the adsorbed gas near the well also decreases,this decrease is less compared to that in pressure because of desorption hysteresis.The unceasing spread of CO_(2) and drops of pressure and adsorbed gas depend on the degree of desorption hysteresis and heterogeneity of coals,which should be considered when designing CO_(2) sequestration into coal seams.展开更多
Submerged vegetation commonly grows and plays a vital role in aquatic ecosystems,but it is also regarded as a barrier to the passing flow.Numerical simulations of flow through and over submerged vegetation were carrie...Submerged vegetation commonly grows and plays a vital role in aquatic ecosystems,but it is also regarded as a barrier to the passing flow.Numerical simulations of flow through and over submerged vegetation were carried out to investigate the effect of vegetation density on flow field.Numerical simulations were computationally set up to replicate flume experiments,in which vegetation was mimicked with flexible plastic strips.The fluid-structure interaction between flow and flexible vegetation was solved by coupling the two modules of the COMSOL packages.Two cases with different vegetation densities were simulated,and the results were successfully validated against the experimental data.The contours of the simulated time-averaged streamwise velocity and Reynolds stress were extracted to highlight the differences in mean and turbulent flow statistics.The turbulence intensity was found to be more sensitive to vegetation density than the time-averaged velocity.The developing length increased with the spacing between plants.The snapshots of the bending vegetation under instantaneous velocity and vorticity revealed that flexible vegetation responded to the effects of eddies in the shear layer by swaying periodically.The first two rows of vegetation suffered stronger approaching flow and were prone to more streamlined postures.In addition,the origin of tip vortices was investigated via the distribution of vorticity.The results reveal the variation of flow properties with bending submerged vegetation and provide useful reference for optimizationofrestorationprojects.展开更多
Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the sim...Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled.This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image.Methods First,we transferred an input real-world portrait to a stylized cartoon image using StyleGAN.We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture.Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision.Finally,we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer.Conclusions Compared with prior arts,the qualitative and quantitative results show that our method achieves better accuracy,aesthetics,and similarity criteria.Furthermore,we demonstrated the capability of the proposed 3D model for real-time facial animation.展开更多
Cu catalysts,known for their unparalleled catalytic capabilities due to their unique electronic structure,have faced inherent challenges in maintaining long-term effectiveness under harsh hydrogenation conditions.Here...Cu catalysts,known for their unparalleled catalytic capabilities due to their unique electronic structure,have faced inherent challenges in maintaining long-term effectiveness under harsh hydrogenation conditions.Here,we demonstrate a molybdenum-mediated redispersion behavior of Cu under hightemperature oxidation conditions.The oxidized Cu nanoparticles with rich metal-support interfaces tend to dissolve into the MoO_(3)support upon heating to 600℃,which facilitates the subsequent regeneration in a reducing atmosphere.A similar redispersion phenomenon is observed for Cu nanoparticles supported on Zn O-modified MoO_(3).The modification of ZnO significantly improves the performance of the Cu catalyst for CO_(2)hydrogenation to methanol,with the high activity being well maintained after four repeated oxidation-reduction cycles.In situ spectroscopic and theoretical analyses suggest that the interaction involved in the formation of the copper molybdate-like compound is the driving force for the redispersion of Cu.This method is applicable to various Mo-based oxide supports,offering a practical strategy for the regeneration of sintered Cu particles in hydrogenation applications.展开更多
Efficient cellular fusion of mononuclear precursors is the prerequisite for the generation of fully functional multinucleated bone-resorbing osteoclasts.However,the exact molecular factors and mechanisms controlling o...Efficient cellular fusion of mononuclear precursors is the prerequisite for the generation of fully functional multinucleated bone-resorbing osteoclasts.However,the exact molecular factors and mechanisms controlling osteoclast fusion remain incompletely understood.Here we identify RANKL-mediated activation of caspase-8 as early key event during osteoclast fusion.展开更多
This work explores the potential of a triple combination of meropenem(MEM),a novel metallo-blactamase(MBL)inhibitor(indole-2-carboxylate 58(InC58)),and a serine-b-lactamase(SBL)inhibitor(avibactam(AVI))for broad-spect...This work explores the potential of a triple combination of meropenem(MEM),a novel metallo-blactamase(MBL)inhibitor(indole-2-carboxylate 58(InC58)),and a serine-b-lactamase(SBL)inhibitor(avibactam(AVI))for broad-spectrum activity against carbapenemase-producing bacteria.A diverse panel comprising MBL-and SBL-producing strains was used for susceptibility testing of the triple combination using the agar dilution method.The frequency of resistance(FoR)to MEM combined with InC58 was investigated.Mutants were sequenced and tested for cross resistance,fitness,and the stability of the resistance phenotype.Compared with the double combinations of MEM plus an SBL or MBL inhibitor,the triple combination extended the spectrum of activity to most of the isolates bearing SBLs(oxacillinase-48(OXA-48)and Klebsiella pneumoniae carbapenemase-2(KPC-2))and MBLs(New Delhi metallo-blactamases(NDMs)),although it was not effective against Verona integron-encoded metallo-blactamase(VIM)-carrying Pseudomonas aeruginosa(P.aeruginosa)and OXA-23-carrying Acinetobacter baumannii(A.baumannii).The FoR to MEM plus InC58 ranged from 2.22×10^(-7)to 1.13×10^(-6).The resistance correlated with mutations to ompC and comR,affecting porin C and copper permeability,respectively.The mutants manifested a fitness cost,a decreased level of resistance during passage without antibiotic pressure,and cross resistance to another carbapenem(imipenem)and a b-lactamase inhibitor(taniborbactam).In conclusion,compared with the dual combinations,the triple combination of MEM with InC58 and AVI showed a much wider spectrum of activity against different carbapenemaseproducing bacteria,revealing a new strategy to combat b-lactamase-mediated antimicrobial resistance.展开更多
Electrical energy is essential for modern society to sustain economic growths.The soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shif...Electrical energy is essential for modern society to sustain economic growths.The soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shift towards the utilization of solar energy.However,traditional solar energy solutions often require extensive spaces for a panel installation,limiting their practicality in a dense urban environment.To overcome the spatial constraint,researchers have developed transparent photovoltaics(TPV),enabling windows and facades in vehicles and buildings to generate electric energy.Current TPV advancements are focused on improving both transparency and power output to rival commercially available silicon solar panels.In this review,we first briefly introduce wavelength-and non-wavelengthselective strategies to achieve transparency.Figures of merit and theoretical limits of TPVs are discussed to comprehensively understand the status of current TPV technology.Then we highlight recent progress in different types of TPVs,with a particular focus on solution-processed thin-film photovoltaics(PVs),including colloidal quantum dot PVs,metal halide perovskite PVs and organic PVs.The applications of TPVs are also reviewed,with emphasis on agrivoltaics,smart windows and facades.Finally,current challenges and future opportunities in TPV research are pointed out.展开更多
AIM:To examine the disparities in macular retinal vascular density between individuals with connective tissue disease-related interstitial lung disease(CTD-ILD)and healthy controls(HCs)by optical coherence tomography ...AIM:To examine the disparities in macular retinal vascular density between individuals with connective tissue disease-related interstitial lung disease(CTD-ILD)and healthy controls(HCs)by optical coherence tomography angiography(OCTA)and to investigate the changes in microvascular density in abnormal eyes.METHODS:For a retrospective case-control study,a total of 16 patients(32 eyes)diagnosed with CTD-ILD were selected as the ILD group.The 16 healthy volunteers with 32 eyes,matched in terms of age and sex with the patients,were recruited as control group.The macular retina’s superficial retinal layer(SRL)and deep retinal layer(DRL)were examined and scanned using OCTA in each individual eye.The densities of retinal microvascular(MIR),macrovascular(MAR),and total microvascular(TMI)were calculated and compared.Changes in retinal vascular density in the macular region were analyzed using three different segmentation methods:central annuli segmentation method(C1-C6),hemispheric segmentation method[uperior right(SR),superior left(SL),inferior left(IL),and inferior right(IR)],and Early Treatment Diabetic Retinopathy Study(ETDRS)methods[superior(S),inferior(I),left(L),and right(R)].The data were analyzed using Version 9.0 of GraphPad prism and Pearson analysis.RESULTS:The OCTA data demonstrated a statistically significant difference(P<0.05)in macular retinal microvessel density between the two groups.Specifically,in the SRL and DRL analyses,the ILD group exhibited significantly lower surface density of MIR and TMI compared to the HCs group(P<0.05).Furthermore,using the hemispheric segmentation method,the ILD group showed notable reductions in SL,SR,and IL in the superficial retina(P<0.05),as well as marked decreases in SL and IR in the deep retina(P<0.05).Similarly,when employing the ETDRS method,the ILD group displayed substantial drops in superficial retinal S and I(P<0.05),along with notable reductions in deep retinal L,I,and R(P<0.05).In the central annuli segmentation method,the ILD group exhibited a significant decrease in the superficial retinal C2-4 region(P<0.05),whereas the deep retina showed a notable reduction in the C3-5 region(P<0.05).Additionally,there was an observed higher positive likelihood ratio in the superficial SR region and deep MIR.Furthermore,there was a negative correlation between conjunctival vascular density and both deep and superficial retinal TMI(P<0.001).CONCLUSION:Patients with CTD-ILD exhibits a significantly higher conjunctival vascular density compared to the HCs group.Conversely,their fundus retinal microvascular density is significantly lower.Furthermore,CTD-ILD patients display notably lower superficial and deep retinal vascular density in comparison to the HCs group.The inverse correlation between conjunctival vascular density and both superficial and deep retinal TMI suggests that detecting subtle changes in ocular microcirculation could potentially serve as an early diagnostic indicator for connective tissue diseases,thereby enhancing disease management.展开更多
Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline...Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline system(DLAPS)for diagnosing LLNM in PTC using computed tomography(CT).Methods:A total of 1,266 lateral lymph nodes(LLNs)from 519 PTC patients who underwent CT examinations from January 2019 to November 2022 were included and divided into training and validation set,internal test set,pooled external test set,and prospective test set.The DLAPS consists of an auto-segmentation network based on RefineNet model and a classification network based on ensemble model(ResNet,Xception,and DenseNet).The performance of the DLAPS was compared with that of manually segmented DL models,the clinical model,and Node Reporting and Data System(Node-RADS).The improvement of radiologists’diagnostic performance under the DLAPS-assisted strategy was explored.In addition,bulk RNA-sequencing was conducted based on 12 LLNs to reveal the underlying biological basis of the DLAPS.Results:The DLAPS yielded good performance with area under the receiver operating characteristic curve(AUC)of 0.872,0.910,and 0.822 in the internal,pooled external,and prospective test sets,respectively.The DLAPS significantly outperformed clinical models(AUC 0.731,P<0.001)and Node-RADS(AUC 0.602,P<0.001)in the internal test set.Moreover,the performance of the DLAPS was comparable to that of the manually segmented deep learning(DL)model with AUCs ranging 0.814−0.901 in three test sets.Furthermore,the DLAPSassisted strategy improved the performance of radiologists and enhanced inter-observer consistency.In clinical situations,the rate of unnecessary LLN dissection decreased from 33.33%to 7.32%.Furthermore,the DLAPS was associated with the cell-cell conjunction in the microenvironment.Conclusions:Using CT images from PTC patients,the DLAPS could effectively segment and classify LLNs non-invasively,and this system had a good generalization ability and clinical applicability.展开更多
AIM:To study functional brain abnormalities in patients with hypertensive retinopathy(HR)and to discuss the pathophysiological mechanisms of HR by fractional amplitude of low-frequency fluctuations(fALFFs)method.METHO...AIM:To study functional brain abnormalities in patients with hypertensive retinopathy(HR)and to discuss the pathophysiological mechanisms of HR by fractional amplitude of low-frequency fluctuations(fALFFs)method.METHODS:Twenty HR patients and 20 healthy controls(HCs)were respectively recruited.The age,gender,and educational background characteristics of the two groups were similar.After functional magnetic resonance imaging(fMRI)scanning,the subjects’spontaneous brain activity was evaluated with the fALFF method.Receiver operating characteristic(ROC)curve analysis was used to classify the data.Further,we used Pearson’s correlation analysis to explore the relationship between fALFF values in specific brain regions and clinical behaviors in patients with HR.RESULTS:The brain areas of the HR group with lower fALFF values than HCs were the right orbital part of the middle frontal gyrus(RO-MFG)and right lingual gyrus.In contrast,the values of fALFFs in the left middle temporal gyrus(MTG),left superior temporal pole(STP),left middle frontal gyrus(MFG),left superior marginal gyrus(SMG),left superior parietal lobule(SPL),and right supplementary motor area(SMA)were higher in the HR group.The results of a t-test showed that the average values of fALFFs were statistically significantly different in the HR group and HC group(P<0.001).The fALFF values of the left middle frontal gyrus in HR patients were positively correlated with anxiety scores(r=0.9232;P<0.0001)and depression scores(r=0.9682;P<0.0001).CONCLUSION:fALFF values in multiple brain regions of HR patients are abnormal,suggesting that these brain regions in HR patients may be dysfunctional,which may help to reveal the pathophysiological mechanisms of HR.展开更多
In the era of the Internet of Things(IoT),the proliferation of connected devices has raised security concerns,increasing the risk of intrusions into diverse systems.Despite the convenience and efficiency offered by Io...In the era of the Internet of Things(IoT),the proliferation of connected devices has raised security concerns,increasing the risk of intrusions into diverse systems.Despite the convenience and efficiency offered by IoT technology,the growing number of IoT devices escalates the likelihood of attacks,emphasizing the need for robust security tools to automatically detect and explain threats.This paper introduces a deep learning methodology for detecting and classifying distributed denial of service(DDoS)attacks,addressing a significant security concern within IoT environments.An effective procedure of deep transfer learning is applied to utilize deep learning backbones,which is then evaluated on two benchmarking datasets of DDoS attacks in terms of accuracy and time complexity.By leveraging several deep architectures,the study conducts thorough binary and multiclass experiments,each varying in the complexity of classifying attack types and demonstrating real-world scenarios.Additionally,this study employs an explainable artificial intelligence(XAI)AI technique to elucidate the contribution of extracted features in the process of attack detection.The experimental results demonstrate the effectiveness of the proposed method,achieving a recall of 99.39%by the XAI bidirectional long short-term memory(XAI-BiLSTM)model.展开更多
In the United Kingdom, means of meeting domestic heating is being electrified to decarbonise in effort to reduce the greenhouse gases emissions from the burning of natural gas. Therefore, the uptake of heat pumps is o...In the United Kingdom, means of meeting domestic heating is being electrified to decarbonise in effort to reduce the greenhouse gases emissions from the burning of natural gas. Therefore, the uptake of heat pumps is on the increase. The operation and working principle of heat pumps must be well understood in the investigations of their impacts on the grid and the grid assets, especially distribution transformers which could be overloaded due to higher peak load demand. This work develops an operational model of heat pumps as combined space heating and domestic hot water provider implemented in MATLAB. The developed operational model of heat pumps is adaptable and repeatable for different input parameters. The developed model is used to generate daily average demand profiles of heat pumps for a typical winter weekday and a typical summer weekday. The generated demand profiles of heat pumps by the developed model compared well with the demand profiles of heat pumps generated from actual field projects which are usually expensive and time-tasking.展开更多
The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already begun.To realize its full potential over the next decade,6G will undoubt...The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already begun.To realize its full potential over the next decade,6G will undoubtedly necessitate additional improvements that integrate existing solutions with cutting-edge ones.However,the studies about 6G are mainly limited and scattered,whereas no bibliometric study covers the 6G field.Thus,this study aims to review,examine,and summarize existing studies and research activities in 6G.This study has examined the Scopus database through a bibliometric analysis of more than 1,000 papers published between 2017 and 2021.Then,we applied the bibliometric analysis methods by including(1)document type,(2)subject area,(3)author,and(4)country of publication.The study’s results reflect the research 6G community’s trends,highlight important research challenges,and elucidate potential directions for future research in this interesting area.展开更多
The fast proliferation of edge devices for the Internet of Things(IoT)has led to massive volumes of data explosion.The generated data is collected and shared using edge-based IoT structures at a considerably high freq...The fast proliferation of edge devices for the Internet of Things(IoT)has led to massive volumes of data explosion.The generated data is collected and shared using edge-based IoT structures at a considerably high frequency.Thus,the data-sharing privacy exposure issue is increasingly intimidating when IoT devices make malicious requests for filching sensitive information from a cloud storage system through edge nodes.To address the identified issue,we present evolutionary privacy preservation learning strategies for an edge computing-based IoT data sharing scheme.In particular,we introduce evolutionary game theory and construct a payoff matrix to symbolize intercommunication between IoT devices and edge nodes,where IoT devices and edge nodes are two parties of the game.IoT devices may make malicious requests to achieve their goals of stealing privacy.Accordingly,edge nodes should deny malicious IoT device requests to prevent IoT data from being disclosed.They dynamically adjust their own strategies according to the opponent's strategy and finally maximize the payoffs.Built upon a developed application framework to illustrate the concrete data sharing architecture,a novel algorithm is proposed that can derive the optimal evolutionary learning strategy.Furthermore,we numerically simulate evolutionarily stable strategies,and the final results experimentally verify the correctness of the IoT data sharing privacy preservation scheme.Therefore,the proposed model can effectively defeat malicious invasion and protect sensitive information from leaking when IoT data is shared.展开更多
Age-related macular degeneration is a major global cause of central visual impairment and seve re vision loss.With an aging population,the already immense economic burden of costly anti-vascular endothelial growth fa ...Age-related macular degeneration is a major global cause of central visual impairment and seve re vision loss.With an aging population,the already immense economic burden of costly anti-vascular endothelial growth fa ctor treatment is likely to increase.In addition,current conventional treatment is only available for the late neovascular stage of age-related macular degeneration,and injections can come with potentially devastating complications,introducing the need for more economical and ris kfree treatment.In recent years,exosomes,which are nano-sized extracellular vesicles of an endocytic origin,have shown immense potential as diagnostic biomarkers and in the therapeutic application,as they are bestowed with characte ristics including an expansive cargo that closely resembles their parent cell and exceptional ability of intercellular communication and targeting neighboring cells.Exosomes are currently undergoing clinical trials for various conditions such as type 1 diabetes and autoimmune diseases;however,exosomes as a potential therapy for seve ral retinal diseases have just begun to undergo scrutinizing investigation with little literature on age-related macular degeneration specifically.This article will focus on the limited literature availa ble on exosome transplantation treatment in age-related macular degeneration animal models and in vitro cell cultures,as well as briefly identify future research directions.Current literature on exosome therapy using agerelated macular degeneration rodent models includes laser retinal injury,N-methyl-N-nitrosourea,and royal college of surgeon models,which mimic inflammatory and degenerative aspects of agerelated macular degeneration.These have shown promising results in preserving retinal function and morphology,as well as protecting photoreceptors from apoptosis.Exosomes from their respective cellular origins may also act by regulating the expression of various inflammatory cyto kines,mRNAs,and proteins involved in photo receptor degeneration pathways to exert a therapeutic effect.Various findings have also opened exciting prospects for the involvement of cargo components in remedial effects on the damaged macula or retina.展开更多
Electrocatalyst designs based on oxophilic foreign atoms are considered a promising approach for developing efficient pH-universal hydrogen evolution reaction(HER)electrocatalysts by overcoming the sluggish alkaline H...Electrocatalyst designs based on oxophilic foreign atoms are considered a promising approach for developing efficient pH-universal hydrogen evolution reaction(HER)electrocatalysts by overcoming the sluggish alkaline HER kinetics.Here,we design ternary transition metals-based nickel telluride(Mo WNi Te)catalysts consisting of high valence non-3d Mo and W metals and oxophilic Te as a first demonstration of non-precious heterogeneous electrocatalysts following the bifunctional mechanism.The Mo WNi Te showed excellent HER catalytic performance with overpotentials of 72,125,and 182 mV to reach the current densities of 10,100,and 1000 mA cm^(-2),respectively,and the corresponding Tafel slope of 47,52,and 58 mV dec-1in alkaline media,which is much superior to commercial Pt/C.Additionally,the HER performance of Mo WNi Te is well maintained up to 3000 h at the current density of 100 mA cm^(-2).It is further demonstrated that the Mo WNi Te exhibits remarkable HER activities with an overpotential of 45 mV(31 mV)and Tafel slope of 60 mV dec-1(34 mV dec-1)at 10 mA cm^(-2)in neutral(acid)media.The superior HER performance of Mo WNi Te is attributed to the electronic structure modulation,inducing highly active low valence states by the incorporation of high valence non-3d transition metals.It is also attributed to the oxophilic effect of Te,accelerating water dissociation kinetics through a bifunctional catalytic mechanism in alkaline media.Density functional theory calculations further reveal that such synergistic effects lead to reduced free energy for an efficient water dissociation process,resulting in remarkable HER catalytic performances within universal pH environments.展开更多
Control of chemical composition and incorporation of multiple metallic elements into a single metal nanoparticle(NP)in an alloyed or a phase-segregated state hold potential scientific merit;however,developing librarie...Control of chemical composition and incorporation of multiple metallic elements into a single metal nanoparticle(NP)in an alloyed or a phase-segregated state hold potential scientific merit;however,developing libraries of such structures using effective strategies is challenging owing to the thermodynamic immiscibility of repelling constituent metallic elements.Herein,we present a one-pot interfacial plasma-discharge-driven(IP-D)synthesis strategy for fabricating stable high-entropy-alloy(HEA)NPs exhibiting ultrasmall size on a porous support surface.Accordingly,an electric field was applied for 120 s to enhance the incorporation of multiple metallic elements(i.e.,CuAgFe,CuAgNi,and CuAgNiFe)into ally HEA-NPs.Further,NPs were attached to a porous magnesium oxide surface via rapid cooling.With solar light as the sole energy input,the CuAgNiFe catalyst was investigated as a reusable and sustainable material exhibiting excellent catalytic performance(100%conversion and 99% selectivity within1 min for a hydrogenation reaction)and consistent activity even after 20 cycles for a reduction reaction,considerably outperforming the majority of the conventional photocatalysts.Thus,the proposed strategy establishes a novel method for designing and synthesizing highly efficient and stable catalysts for the convertion of nitroarenes to anilines via chemical reduction.展开更多
文摘As an important part of urban construction,elderly-friendly construction is crucial to the formation of an elderly-friendly society,which has been widely recognized internationally.Especially after the COVID-19 pandemic,various organizations around the world have called for changes in public space and urban building planning,with an emphasis on the accessibility of green spaces.This underscores the complexity and difficulty of integrating vulnerable groups of the elderly into cities and using infrastructure and public space.
文摘The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.
基金The research was conducted as part of the“Establishing a Research Observatory to Unlock European Coal Seams for CO_(2) Storage(ROCCS)”project(Grant No.899336)The work of the second author is also sponsored by Shanghai Pujiang Program(Grant No.23PJ1412600)。
文摘Injecting carbon dioxide(CO_(2))into coal seams may unlock substantial carbon sequestration potential.Since the coal acts like a carbon filter,it can preferentially absorb significant amounts of CO_(2).To explore this further,desorption of the adsorbed gas due to pressure drop is investigated in this paper,to achieve an improved understanding of the long-term fate of injected CO_(2) during post-injection period.This paper presents a dual porosity model coupling gas flow,adsorption and geomechanics for studying coupled processes and effectiveness of CO_(2) sequestration in coals.A new adsorption?desorption model derived based on thermodynamics is incorporated,particularly,the desorption hysteresis is considered.The reliability of the proposed adsorption-desorption isotherm is examined via validation tests.It is indicated that occurrence of desorption hysteresis is attributed to the adsorption-induced pore deformation.After injection ceases,the injected gas continues to propagate further from the injection well,while the pressure in the vicinity of the injection well experiences a significant drop.Although the adsorbed gas near the well also decreases,this decrease is less compared to that in pressure because of desorption hysteresis.The unceasing spread of CO_(2) and drops of pressure and adsorbed gas depend on the degree of desorption hysteresis and heterogeneity of coals,which should be considered when designing CO_(2) sequestration into coal seams.
基金supported by the National Natural Science Foundation of China(Grants No.2022YFC3202602,52109013,and U2040205)the China Postdoctoral Science Foundation(Grant No.2021M701049).
文摘Submerged vegetation commonly grows and plays a vital role in aquatic ecosystems,but it is also regarded as a barrier to the passing flow.Numerical simulations of flow through and over submerged vegetation were carried out to investigate the effect of vegetation density on flow field.Numerical simulations were computationally set up to replicate flume experiments,in which vegetation was mimicked with flexible plastic strips.The fluid-structure interaction between flow and flexible vegetation was solved by coupling the two modules of the COMSOL packages.Two cases with different vegetation densities were simulated,and the results were successfully validated against the experimental data.The contours of the simulated time-averaged streamwise velocity and Reynolds stress were extracted to highlight the differences in mean and turbulent flow statistics.The turbulence intensity was found to be more sensitive to vegetation density than the time-averaged velocity.The developing length increased with the spacing between plants.The snapshots of the bending vegetation under instantaneous velocity and vorticity revealed that flexible vegetation responded to the effects of eddies in the shear layer by swaying periodically.The first two rows of vegetation suffered stronger approaching flow and were prone to more streamlined postures.In addition,the origin of tip vortices was investigated via the distribution of vorticity.The results reveal the variation of flow properties with bending submerged vegetation and provide useful reference for optimizationofrestorationprojects.
文摘Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled.This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image.Methods First,we transferred an input real-world portrait to a stylized cartoon image using StyleGAN.We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture.Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision.Finally,we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer.Conclusions Compared with prior arts,the qualitative and quantitative results show that our method achieves better accuracy,aesthetics,and similarity criteria.Furthermore,we demonstrated the capability of the proposed 3D model for real-time facial animation.
基金the National Key Research and Development Program of China[No.2021YFB4000700]the CAS Project for Young Scientists in Basic Research[YSBR-022]+1 种基金the National Natural Science Foundation of China[22008136,21925803]the Welsh Government funded Taith Research Mobility Programme[No.524339]。
文摘Cu catalysts,known for their unparalleled catalytic capabilities due to their unique electronic structure,have faced inherent challenges in maintaining long-term effectiveness under harsh hydrogenation conditions.Here,we demonstrate a molybdenum-mediated redispersion behavior of Cu under hightemperature oxidation conditions.The oxidized Cu nanoparticles with rich metal-support interfaces tend to dissolve into the MoO_(3)support upon heating to 600℃,which facilitates the subsequent regeneration in a reducing atmosphere.A similar redispersion phenomenon is observed for Cu nanoparticles supported on Zn O-modified MoO_(3).The modification of ZnO significantly improves the performance of the Cu catalyst for CO_(2)hydrogenation to methanol,with the high activity being well maintained after four repeated oxidation-reduction cycles.In situ spectroscopic and theoretical analyses suggest that the interaction involved in the formation of the copper molybdate-like compound is the driving force for the redispersion of Cu.This method is applicable to various Mo-based oxide supports,offering a practical strategy for the regeneration of sintered Cu particles in hydrogenation applications.
基金supported by the Bayerische Forschungsstiftung to B.K.the Deutsche Forschungsgemeinschaft (CRC1181 to G.K.and G.S.+3 种基金SCHE 2062/1-1 to C.S.)funded by the Wellcome Trust Investigator Award (107964/Z/15/Z)the UK Dementia Research Institutefunded by BBSRC Discovery Fellowship (BB/T009543/1)。
文摘Efficient cellular fusion of mononuclear precursors is the prerequisite for the generation of fully functional multinucleated bone-resorbing osteoclasts.However,the exact molecular factors and mechanisms controlling osteoclast fusion remain incompletely understood.Here we identify RANKL-mediated activation of caspase-8 as early key event during osteoclast fusion.
基金supported by the Ineos Oxford Institute for Antimicrobial Research,the Biotechnology and Biological Sciences Research Council(BB/V003291/1)the WellcomeTrust(106244/Z/14/Z).
文摘This work explores the potential of a triple combination of meropenem(MEM),a novel metallo-blactamase(MBL)inhibitor(indole-2-carboxylate 58(InC58)),and a serine-b-lactamase(SBL)inhibitor(avibactam(AVI))for broad-spectrum activity against carbapenemase-producing bacteria.A diverse panel comprising MBL-and SBL-producing strains was used for susceptibility testing of the triple combination using the agar dilution method.The frequency of resistance(FoR)to MEM combined with InC58 was investigated.Mutants were sequenced and tested for cross resistance,fitness,and the stability of the resistance phenotype.Compared with the double combinations of MEM plus an SBL or MBL inhibitor,the triple combination extended the spectrum of activity to most of the isolates bearing SBLs(oxacillinase-48(OXA-48)and Klebsiella pneumoniae carbapenemase-2(KPC-2))and MBLs(New Delhi metallo-blactamases(NDMs)),although it was not effective against Verona integron-encoded metallo-blactamase(VIM)-carrying Pseudomonas aeruginosa(P.aeruginosa)and OXA-23-carrying Acinetobacter baumannii(A.baumannii).The FoR to MEM plus InC58 ranged from 2.22×10^(-7)to 1.13×10^(-6).The resistance correlated with mutations to ompC and comR,affecting porin C and copper permeability,respectively.The mutants manifested a fitness cost,a decreased level of resistance during passage without antibiotic pressure,and cross resistance to another carbapenem(imipenem)and a b-lactamase inhibitor(taniborbactam).In conclusion,compared with the dual combinations,the triple combination of MEM with InC58 and AVI showed a much wider spectrum of activity against different carbapenemaseproducing bacteria,revealing a new strategy to combat b-lactamase-mediated antimicrobial resistance.
基金supported by the National Natural Science Foundation of China(Grant number W2432035)financial support from the EPSRC SWIMS(EP/V039717/1)+3 种基金Royal Society(RGS\R1\221009 and IEC\NSFC\211201)Leverhulme Trust(RPG-2022-263)Ser Cymru programme–Enhancing Competitiveness Equipment Awards 2022-23(MA/VG/2715/22-PN66)the financial support from Kingdom of Saudi Arabia Ministry of Higher Education.
文摘Electrical energy is essential for modern society to sustain economic growths.The soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shift towards the utilization of solar energy.However,traditional solar energy solutions often require extensive spaces for a panel installation,limiting their practicality in a dense urban environment.To overcome the spatial constraint,researchers have developed transparent photovoltaics(TPV),enabling windows and facades in vehicles and buildings to generate electric energy.Current TPV advancements are focused on improving both transparency and power output to rival commercially available silicon solar panels.In this review,we first briefly introduce wavelength-and non-wavelengthselective strategies to achieve transparency.Figures of merit and theoretical limits of TPVs are discussed to comprehensively understand the status of current TPV technology.Then we highlight recent progress in different types of TPVs,with a particular focus on solution-processed thin-film photovoltaics(PVs),including colloidal quantum dot PVs,metal halide perovskite PVs and organic PVs.The applications of TPVs are also reviewed,with emphasis on agrivoltaics,smart windows and facades.Finally,current challenges and future opportunities in TPV research are pointed out.
基金Supported by National Natural Science Foundation of China(No.82160195)Key R&D Program of Jiangxi Province(No.20223BBH80014)General Science and Technology Program of the Department of Traditional Chinese Medicine,Jiangxi Provincial Health Commission(No.2017A241).
文摘AIM:To examine the disparities in macular retinal vascular density between individuals with connective tissue disease-related interstitial lung disease(CTD-ILD)and healthy controls(HCs)by optical coherence tomography angiography(OCTA)and to investigate the changes in microvascular density in abnormal eyes.METHODS:For a retrospective case-control study,a total of 16 patients(32 eyes)diagnosed with CTD-ILD were selected as the ILD group.The 16 healthy volunteers with 32 eyes,matched in terms of age and sex with the patients,were recruited as control group.The macular retina’s superficial retinal layer(SRL)and deep retinal layer(DRL)were examined and scanned using OCTA in each individual eye.The densities of retinal microvascular(MIR),macrovascular(MAR),and total microvascular(TMI)were calculated and compared.Changes in retinal vascular density in the macular region were analyzed using three different segmentation methods:central annuli segmentation method(C1-C6),hemispheric segmentation method[uperior right(SR),superior left(SL),inferior left(IL),and inferior right(IR)],and Early Treatment Diabetic Retinopathy Study(ETDRS)methods[superior(S),inferior(I),left(L),and right(R)].The data were analyzed using Version 9.0 of GraphPad prism and Pearson analysis.RESULTS:The OCTA data demonstrated a statistically significant difference(P<0.05)in macular retinal microvessel density between the two groups.Specifically,in the SRL and DRL analyses,the ILD group exhibited significantly lower surface density of MIR and TMI compared to the HCs group(P<0.05).Furthermore,using the hemispheric segmentation method,the ILD group showed notable reductions in SL,SR,and IL in the superficial retina(P<0.05),as well as marked decreases in SL and IR in the deep retina(P<0.05).Similarly,when employing the ETDRS method,the ILD group displayed substantial drops in superficial retinal S and I(P<0.05),along with notable reductions in deep retinal L,I,and R(P<0.05).In the central annuli segmentation method,the ILD group exhibited a significant decrease in the superficial retinal C2-4 region(P<0.05),whereas the deep retina showed a notable reduction in the C3-5 region(P<0.05).Additionally,there was an observed higher positive likelihood ratio in the superficial SR region and deep MIR.Furthermore,there was a negative correlation between conjunctival vascular density and both deep and superficial retinal TMI(P<0.001).CONCLUSION:Patients with CTD-ILD exhibits a significantly higher conjunctival vascular density compared to the HCs group.Conversely,their fundus retinal microvascular density is significantly lower.Furthermore,CTD-ILD patients display notably lower superficial and deep retinal vascular density in comparison to the HCs group.The inverse correlation between conjunctival vascular density and both superficial and deep retinal TMI suggests that detecting subtle changes in ocular microcirculation could potentially serve as an early diagnostic indicator for connective tissue diseases,thereby enhancing disease management.
基金supported by the Taishan Scholar Project(No.ts20190991,No.tsqn202211378)the Key R&D Project of Shandong Province(No.2022CXPT023)+1 种基金the General Program of National Natural Science Foundation of China(No.82371933)the Medical and Health Technology Project of Shandong Province(No.202307010677)。
文摘Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline system(DLAPS)for diagnosing LLNM in PTC using computed tomography(CT).Methods:A total of 1,266 lateral lymph nodes(LLNs)from 519 PTC patients who underwent CT examinations from January 2019 to November 2022 were included and divided into training and validation set,internal test set,pooled external test set,and prospective test set.The DLAPS consists of an auto-segmentation network based on RefineNet model and a classification network based on ensemble model(ResNet,Xception,and DenseNet).The performance of the DLAPS was compared with that of manually segmented DL models,the clinical model,and Node Reporting and Data System(Node-RADS).The improvement of radiologists’diagnostic performance under the DLAPS-assisted strategy was explored.In addition,bulk RNA-sequencing was conducted based on 12 LLNs to reveal the underlying biological basis of the DLAPS.Results:The DLAPS yielded good performance with area under the receiver operating characteristic curve(AUC)of 0.872,0.910,and 0.822 in the internal,pooled external,and prospective test sets,respectively.The DLAPS significantly outperformed clinical models(AUC 0.731,P<0.001)and Node-RADS(AUC 0.602,P<0.001)in the internal test set.Moreover,the performance of the DLAPS was comparable to that of the manually segmented deep learning(DL)model with AUCs ranging 0.814−0.901 in three test sets.Furthermore,the DLAPSassisted strategy improved the performance of radiologists and enhanced inter-observer consistency.In clinical situations,the rate of unnecessary LLN dissection decreased from 33.33%to 7.32%.Furthermore,the DLAPS was associated with the cell-cell conjunction in the microenvironment.Conclusions:Using CT images from PTC patients,the DLAPS could effectively segment and classify LLNs non-invasively,and this system had a good generalization ability and clinical applicability.
基金Supported by National Natural Science Foundation of China(No.82160195)Jiangxi Double-Thousand Plan High-Level Talent Project of Science and Technology Innovation(No.jxsq2023201036)+2 种基金Key R&D Program of Jiangxi Province(No.20223BBH80014)Science and Technology Project of Jiangxi Province Health Commission of Traditional Chinese Medicine(No.2022B258)Science and Technology Project of Jiangxi Health Commission(No.202210017).
文摘AIM:To study functional brain abnormalities in patients with hypertensive retinopathy(HR)and to discuss the pathophysiological mechanisms of HR by fractional amplitude of low-frequency fluctuations(fALFFs)method.METHODS:Twenty HR patients and 20 healthy controls(HCs)were respectively recruited.The age,gender,and educational background characteristics of the two groups were similar.After functional magnetic resonance imaging(fMRI)scanning,the subjects’spontaneous brain activity was evaluated with the fALFF method.Receiver operating characteristic(ROC)curve analysis was used to classify the data.Further,we used Pearson’s correlation analysis to explore the relationship between fALFF values in specific brain regions and clinical behaviors in patients with HR.RESULTS:The brain areas of the HR group with lower fALFF values than HCs were the right orbital part of the middle frontal gyrus(RO-MFG)and right lingual gyrus.In contrast,the values of fALFFs in the left middle temporal gyrus(MTG),left superior temporal pole(STP),left middle frontal gyrus(MFG),left superior marginal gyrus(SMG),left superior parietal lobule(SPL),and right supplementary motor area(SMA)were higher in the HR group.The results of a t-test showed that the average values of fALFFs were statistically significantly different in the HR group and HC group(P<0.001).The fALFF values of the left middle frontal gyrus in HR patients were positively correlated with anxiety scores(r=0.9232;P<0.0001)and depression scores(r=0.9682;P<0.0001).CONCLUSION:fALFF values in multiple brain regions of HR patients are abnormal,suggesting that these brain regions in HR patients may be dysfunctional,which may help to reveal the pathophysiological mechanisms of HR.
文摘In the era of the Internet of Things(IoT),the proliferation of connected devices has raised security concerns,increasing the risk of intrusions into diverse systems.Despite the convenience and efficiency offered by IoT technology,the growing number of IoT devices escalates the likelihood of attacks,emphasizing the need for robust security tools to automatically detect and explain threats.This paper introduces a deep learning methodology for detecting and classifying distributed denial of service(DDoS)attacks,addressing a significant security concern within IoT environments.An effective procedure of deep transfer learning is applied to utilize deep learning backbones,which is then evaluated on two benchmarking datasets of DDoS attacks in terms of accuracy and time complexity.By leveraging several deep architectures,the study conducts thorough binary and multiclass experiments,each varying in the complexity of classifying attack types and demonstrating real-world scenarios.Additionally,this study employs an explainable artificial intelligence(XAI)AI technique to elucidate the contribution of extracted features in the process of attack detection.The experimental results demonstrate the effectiveness of the proposed method,achieving a recall of 99.39%by the XAI bidirectional long short-term memory(XAI-BiLSTM)model.
文摘In the United Kingdom, means of meeting domestic heating is being electrified to decarbonise in effort to reduce the greenhouse gases emissions from the burning of natural gas. Therefore, the uptake of heat pumps is on the increase. The operation and working principle of heat pumps must be well understood in the investigations of their impacts on the grid and the grid assets, especially distribution transformers which could be overloaded due to higher peak load demand. This work develops an operational model of heat pumps as combined space heating and domestic hot water provider implemented in MATLAB. The developed operational model of heat pumps is adaptable and repeatable for different input parameters. The developed model is used to generate daily average demand profiles of heat pumps for a typical winter weekday and a typical summer weekday. The generated demand profiles of heat pumps by the developed model compared well with the demand profiles of heat pumps generated from actual field projects which are usually expensive and time-tasking.
基金The authors received Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)grant under Internal Research Grant with Grant Number PDU223209.Author received grant is:Ahmad Firdaus Website of the sponsor:https://www.ump.edu.my/en.
文摘The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already begun.To realize its full potential over the next decade,6G will undoubtedly necessitate additional improvements that integrate existing solutions with cutting-edge ones.However,the studies about 6G are mainly limited and scattered,whereas no bibliometric study covers the 6G field.Thus,this study aims to review,examine,and summarize existing studies and research activities in 6G.This study has examined the Scopus database through a bibliometric analysis of more than 1,000 papers published between 2017 and 2021.Then,we applied the bibliometric analysis methods by including(1)document type,(2)subject area,(3)author,and(4)country of publication.The study’s results reflect the research 6G community’s trends,highlight important research challenges,and elucidate potential directions for future research in this interesting area.
基金supported in part by Zhejiang Provincial Natural Science Foundation of China under Grant nos.LZ22F020002 and LY22F020003National Natural Science Foundation of China under Grant nos.61772018 and 62002226the key project of Humanities and Social Sciences in Colleges and Universities of Zhejiang Province under Grant no.2021GH017.
文摘The fast proliferation of edge devices for the Internet of Things(IoT)has led to massive volumes of data explosion.The generated data is collected and shared using edge-based IoT structures at a considerably high frequency.Thus,the data-sharing privacy exposure issue is increasingly intimidating when IoT devices make malicious requests for filching sensitive information from a cloud storage system through edge nodes.To address the identified issue,we present evolutionary privacy preservation learning strategies for an edge computing-based IoT data sharing scheme.In particular,we introduce evolutionary game theory and construct a payoff matrix to symbolize intercommunication between IoT devices and edge nodes,where IoT devices and edge nodes are two parties of the game.IoT devices may make malicious requests to achieve their goals of stealing privacy.Accordingly,edge nodes should deny malicious IoT device requests to prevent IoT data from being disclosed.They dynamically adjust their own strategies according to the opponent's strategy and finally maximize the payoffs.Built upon a developed application framework to illustrate the concrete data sharing architecture,a novel algorithm is proposed that can derive the optimal evolutionary learning strategy.Furthermore,we numerically simulate evolutionarily stable strategies,and the final results experimentally verify the correctness of the IoT data sharing privacy preservation scheme.Therefore,the proposed model can effectively defeat malicious invasion and protect sensitive information from leaking when IoT data is shared.
文摘Age-related macular degeneration is a major global cause of central visual impairment and seve re vision loss.With an aging population,the already immense economic burden of costly anti-vascular endothelial growth fa ctor treatment is likely to increase.In addition,current conventional treatment is only available for the late neovascular stage of age-related macular degeneration,and injections can come with potentially devastating complications,introducing the need for more economical and ris kfree treatment.In recent years,exosomes,which are nano-sized extracellular vesicles of an endocytic origin,have shown immense potential as diagnostic biomarkers and in the therapeutic application,as they are bestowed with characte ristics including an expansive cargo that closely resembles their parent cell and exceptional ability of intercellular communication and targeting neighboring cells.Exosomes are currently undergoing clinical trials for various conditions such as type 1 diabetes and autoimmune diseases;however,exosomes as a potential therapy for seve ral retinal diseases have just begun to undergo scrutinizing investigation with little literature on age-related macular degeneration specifically.This article will focus on the limited literature availa ble on exosome transplantation treatment in age-related macular degeneration animal models and in vitro cell cultures,as well as briefly identify future research directions.Current literature on exosome therapy using agerelated macular degeneration rodent models includes laser retinal injury,N-methyl-N-nitrosourea,and royal college of surgeon models,which mimic inflammatory and degenerative aspects of agerelated macular degeneration.These have shown promising results in preserving retinal function and morphology,as well as protecting photoreceptors from apoptosis.Exosomes from their respective cellular origins may also act by regulating the expression of various inflammatory cyto kines,mRNAs,and proteins involved in photo receptor degeneration pathways to exert a therapeutic effect.Various findings have also opened exciting prospects for the involvement of cargo components in remedial effects on the damaged macula or retina.
基金supported through the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(2022M3H4A1A04096478)the support from the Supercomputing Center of Wuhan University。
文摘Electrocatalyst designs based on oxophilic foreign atoms are considered a promising approach for developing efficient pH-universal hydrogen evolution reaction(HER)electrocatalysts by overcoming the sluggish alkaline HER kinetics.Here,we design ternary transition metals-based nickel telluride(Mo WNi Te)catalysts consisting of high valence non-3d Mo and W metals and oxophilic Te as a first demonstration of non-precious heterogeneous electrocatalysts following the bifunctional mechanism.The Mo WNi Te showed excellent HER catalytic performance with overpotentials of 72,125,and 182 mV to reach the current densities of 10,100,and 1000 mA cm^(-2),respectively,and the corresponding Tafel slope of 47,52,and 58 mV dec-1in alkaline media,which is much superior to commercial Pt/C.Additionally,the HER performance of Mo WNi Te is well maintained up to 3000 h at the current density of 100 mA cm^(-2).It is further demonstrated that the Mo WNi Te exhibits remarkable HER activities with an overpotential of 45 mV(31 mV)and Tafel slope of 60 mV dec-1(34 mV dec-1)at 10 mA cm^(-2)in neutral(acid)media.The superior HER performance of Mo WNi Te is attributed to the electronic structure modulation,inducing highly active low valence states by the incorporation of high valence non-3d transition metals.It is also attributed to the oxophilic effect of Te,accelerating water dissociation kinetics through a bifunctional catalytic mechanism in alkaline media.Density functional theory calculations further reveal that such synergistic effects lead to reduced free energy for an efficient water dissociation process,resulting in remarkable HER catalytic performances within universal pH environments.
基金supported by the National Research Foundation (NRF)of South Korea (2022R1A2C1004392)。
文摘Control of chemical composition and incorporation of multiple metallic elements into a single metal nanoparticle(NP)in an alloyed or a phase-segregated state hold potential scientific merit;however,developing libraries of such structures using effective strategies is challenging owing to the thermodynamic immiscibility of repelling constituent metallic elements.Herein,we present a one-pot interfacial plasma-discharge-driven(IP-D)synthesis strategy for fabricating stable high-entropy-alloy(HEA)NPs exhibiting ultrasmall size on a porous support surface.Accordingly,an electric field was applied for 120 s to enhance the incorporation of multiple metallic elements(i.e.,CuAgFe,CuAgNi,and CuAgNiFe)into ally HEA-NPs.Further,NPs were attached to a porous magnesium oxide surface via rapid cooling.With solar light as the sole energy input,the CuAgNiFe catalyst was investigated as a reusable and sustainable material exhibiting excellent catalytic performance(100%conversion and 99% selectivity within1 min for a hydrogenation reaction)and consistent activity even after 20 cycles for a reduction reaction,considerably outperforming the majority of the conventional photocatalysts.Thus,the proposed strategy establishes a novel method for designing and synthesizing highly efficient and stable catalysts for the convertion of nitroarenes to anilines via chemical reduction.
