Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerge...This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.展开更多
Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class at...Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.展开更多
BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To ...BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.展开更多
In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapi...In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.展开更多
Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero....Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.展开更多
This work uses refined first-order shear theory to analyze the free vibration and transient responses of double-curved sandwich two-layer shells made of auxetic honeycomb core and laminated three-phase polymer/GNP/fib...This work uses refined first-order shear theory to analyze the free vibration and transient responses of double-curved sandwich two-layer shells made of auxetic honeycomb core and laminated three-phase polymer/GNP/fiber surface subjected to the blast load.Each of the two layers that make up the double-curved shell structure is made up of an auxetic honeycomb core and two laminated sheets of three-phase polymer/GNP/fiber.The exterior is supported by a Kerr elastic foundation with three characteristics.The key innovation of the proposed theory is that the transverse shear stresses are zero at two free surfaces of each layer.In contrast to previous first-order shear deformation theories,no shear correction factor is required.Navier's exact solution was used to treat the double-curved shell problem with a single title boundary,while the finite element technique and an eight-node quadrilateral were used to address the other boundary requirements.To ensure the accuracy of these results,a thorough comparison technique is employed in conjunction with credible statements.The problem model's edge cases allow for this kind of analysis.The study's findings may be used in the post-construction evaluation of military and civil works structures for their ability to sustain explosive loads.In addition,this is also an important basis for the calculation and design of shell structures made of smart materials when subjected to shock waves or explosive loads.展开更多
Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain les...Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain less information.Many current methods,particularly those based on Feature Pyramid Network(FPN),address this challenge by leveraging multi-scale feature fusion.However,existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers,leading to suboptimal small object detection.To address this problem,we propose the Two-layerAttention Feature Pyramid Network(TA-FPN),featuring two key modules:the Two-layer Attention Module(TAM)and the Small Object Detail Enhancement Module(SODEM).TAM uses the attention module to make the network more focused on the semantic information of the object and fuse it to the lower layer,so that each layer contains similar semantic information,to alleviate the problem of small object information being submerged due to semantic gaps between different layers.At the same time,SODEM is introduced to strengthen the local features of the object,suppress background noise,enhance the information details of the small object,and fuse the enhanced features to other feature layers to ensure that each layer is rich in small object information,to improve small object detection accuracy.Our extensive experiments on challenging datasets such as Microsoft Common Objects inContext(MSCOCO)and Pattern Analysis Statistical Modelling and Computational Learning,Visual Object Classes(PASCAL VOC)demonstrate the validity of the proposedmethod.Experimental results show a significant improvement in small object detection accuracy compared to state-of-theart detectors.展开更多
In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the oper...In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.展开更多
Exploring efficient and nonprecious metal electrocatalysts of oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)is crucial for developing rechargeable zinc-air batteries(ZABs).Herein,an alloying-degree c...Exploring efficient and nonprecious metal electrocatalysts of oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)is crucial for developing rechargeable zinc-air batteries(ZABs).Herein,an alloying-degree control strategy was employed to fabricate nitrogen-doped carbon sphere(NCS)decorated with dual-phase Co/Co_(7)Fe_(3)heterojunctions(CoFe@NCS).The phase composition of materials has been adjusted by controlling the alloying degree.The optimal CoFe_(0.08)@NCS electrocatalyst displays a half-wave potential of 0.80 V for ORR and an overpotential of 283 mV at 10 mA·cm^(-2)for OER in an alkaline electrolyte.The intriguing bifunctional electrocatalytic activity and durability is attributed to the hierarchically porous structure and interfacial electron coupling of highly-active Co_(7)Fe_(3)alloy and metallic Co species.When the CoFe_(0.08)@NCS material is used as air-cathode catalyst of rechargeable liquid-state zinc-air battery(ZAB),the device shows a high peak power-density(157 mW·cm^(-2))and maintains a stable voltage gap over 150 h,outperforming those of the benchmark(Pt/C+RuO_(2))-based device.In particular,the as-fabricated solid-state flexible ZAB delivers a reliable compatibility under different bending conditions.Our work provides a promising strategy to develop metal/alloy-based electrocatalysts for the application in renewable energy conversion technologies.展开更多
During nearly 200 years of development in the knowledge of Brownian motion,the Janus sphere,as a typical Brownian particle with special surface properties,has been widely studied in the past few decades.A standard Jan...During nearly 200 years of development in the knowledge of Brownian motion,the Janus sphere,as a typical Brownian particle with special surface properties,has been widely studied in the past few decades.A standard Janus sphere possesses two distinct surfaces.These two surfaces elicit different hydrodynamic interactions with ambient fluids or other interactions in response to environmental stimuli,such as chemical gradients,magnetic fields,and even light.The diffusion of Janus spheres,particularly when controlled by a remotely applied field,has inspired various applications,ranging from the design of micro-swimmers and novel procedures for probing the mechanical properties of suspensions to the fabrication of composites with enhanced performance.In this work,we report a systematic analysis of field-controlled diffusion of Janus spheres.Commencing with stochastic differential equations of motion at the microscale,we derive a coarse-grained Fokker-Planck equation at the macroscale,describing the evolution of the probability distribution function of the Janus sphere in terms of its position and orientation.Leveraging the concept of the hydrodynamic center,we derive,for the first time,explicit generalized Stokes-Einstein relations for long-time effective diffusivity,incorporating the effects of both the surface discontinuity of the Janus sphere and the external fields.The formulae enable predictions of the effective diffusivity as it varies with the slip length and characteristic angle of Janus spheres,and reveal the impact of an aligning potential field on the diffusion coefficients both parallel and perpendicular to the direction of the field.This work not only deepens the understanding of field-controlled diffusion of Janus particles,but also holds a meaningful impact on the future applications in microfluidics and related fields.展开更多
The unique phase profile and polarization distribution of the vector vortex beam(VVB)have been a subject of increasing interest in classical and quantum optics.The development of higher-order Poincarésphere(HOPS)...The unique phase profile and polarization distribution of the vector vortex beam(VVB)have been a subject of increasing interest in classical and quantum optics.The development of higher-order Poincarésphere(HOPS)and hybrid-order Poincarésphere(HyOPS)has provided a systematic description of VVB.However,the generation of arbitrary VVBs on a HOPS and a HyOPS via a metasurface lacks a unified design framework,despite numerous reported approaches.We present a unified design framework incorporating all design parameters(e.g.,focal lengths and orders)of arbitrary HOPS and HyOPS beams into a single equation.In proof-of-concept experiments,we experimentally demonstrated four metasurfaces to generate arbitrary beams on the fifth-order HOPS(nonfocused and tightly focused,NA 0.89),0-2 order,and 0-1 order HyOPS.We showed HOPS beams’propagation and focusing properties,the superresolution focusing characteristics of the first-order cylindrical VVBs,and the different focusing properties of integerorder and fractional-order cylindrical VVBs.The simplicity and feasibility of the proposed design framework make it a potential catalyst for arbitrary VVBs using metasurfaces in applications of optical imaging,communication,and optical trapping.展开更多
We aim to find one highly nontrivial example of the solutions to the vortex fluid dynamical equation on the unit sphere(S^(2))and compare it with the numerical simulation.Since the rigid rotating steady solution for v...We aim to find one highly nontrivial example of the solutions to the vortex fluid dynamical equation on the unit sphere(S^(2))and compare it with the numerical simulation.Since the rigid rotating steady solution for vortex fluids on S^(2)is already known to us,we consider the perturbations above it.After decomposing the perturbation of the vortex number density and vortex charge density into spherical harmonics,we find that the perturbations are propagating waves.To be precise,the velocities for different single-mode vortex number density waves are all the same,while the velocities for single-mode vortex charge density waves depend on the degree of the spherical harmonics l,which is a signal of the existence of dispersion.Meanwhile,we find that there is a beat phenomenon for the positive(or negative)vortex density wave.Numerical simulation based on the canonical equations for the point vortex model agrees perfectly with our theoretical calculations.展开更多
Ceramic hollow spheres have great potential for deep-sea applications.However,the irregularity of the conventional molding process,among other reasons,results in low wall thickness uniformity of hollow spheres.To solv...Ceramic hollow spheres have great potential for deep-sea applications.However,the irregularity of the conventional molding process,among other reasons,results in low wall thickness uniformity of hollow spheres.To solve this problem,in this work,we developed a biaxial rotation grouting process for deep-sea ceramic hollow buoyancy spheres,which improves the drawbacks of the traditional rotary grouting method that results in poor wall thickness uniformity of the hollow spheres due to its irregular rotational processing.In this paper,an experimental study was carried out to investigate the effects of different rotational methods,rotational speeds,rotational time,solid phase content,etc.on the wall thickness uniformity of ceramic hollow spheres.The results show that the hollow floating balls prepared by the biaxial rotation method have the lowest wall thickness standard deviation(0.04)when the rotation speed is 60 rpm,the molding time is 8 min,and the solid phase content is 70 wt%.After the hydrostatic pressure test of 120 MPa,the hydrostatic compressive strength of hollow spheres prepared by the biaxial rotation method was increased by 31.67%compared with that of the traditional process.展开更多
Acetone is a common volatile organic compound that can cause harm to human health when inhaled in small amounts.Therefore,the development of fast response and low detection limit acetone sensors becomes crucial.In thi...Acetone is a common volatile organic compound that can cause harm to human health when inhaled in small amounts.Therefore,the development of fast response and low detection limit acetone sensors becomes crucial.In this study,a core-shell spherical TiO_(2) sensor with a rich pore structure was designed.This sensor exhibited excellent sensing properties,including higher responsiveness(100 ppm acetone,R_(a)/R_(g)=80),lower detection limit(10 ppb)and short response time(8 s).The problem is that the sensing mechanism between TiO_(2) and acetone is not thoroughly analyzed.To gain further insight,the interaction process of TiO_(2) core-shell spheres and acetone under varying oxygen content environments was investigated by dynamic testing,X-ray photoelectron spectroscopy,in-situ Fourier transform infrared spectroscopy and gas chromatography-mass spectrometry.The research results show that acetone not only adsorbs on the surface of the material and reacts with adsorbed oxygen,but also undergoes catalytic oxidation reaction with TiO_(2) core-shell spheres.Significantly,in high oxygen content environments,acetone undergoes oxidation to form intermediates such as acids and anhydrides that are difficult to desorpt on the surface of the material,thus prolonging the recovery time of the sensor.The discovery of this sensing process will provide some guidance for the design of acetone sensing materials in the future.Meanwhile,this also imparts valuable references and insights for the investigation of the mechanism and application of other sensitive metal oxide materials.展开更多
Spherical objects are widely used in target localization applications,and the existing sphere localization methods with cameras or total stations both have some limitations.A new high-precision sphere localization met...Spherical objects are widely used in target localization applications,and the existing sphere localization methods with cameras or total stations both have some limitations.A new high-precision sphere localization method with a theodolite is proposed in this paper.From the view point of the theodolite,the contour points of a sphere with a known radius are measured as latitude-longitude coordinates.It is observed that the center of the target sphere is located on a cylindrical surface constructed with the latitude-longitude coordinates,and therefore the latitude-longitude coordinates of at least three contour points can be used to construct a set of ternary quadratic equations.The Gröbner basis method is used to compute at most four real solutions of the sphere center coordinates.To distinguish the only meaningful solution from the other possible real solutions,a pre-processing of the measured longitude values is also proposed.The factors affecting the positioning accuracy of the sphere center are evaluated in simulation experiments,which are used to obtain an empirical estimation model of the positioning error.Real data experiments are also performed and the results show that the proposed method can achieve high localization precision.展开更多
This study presents a novel Li metal host material with a unique hollow nano-spherical structure that incorporates Ag nano-seeds into a graphitic carbon nitride(g-C_(3)N_(4))shell layer,referred to as g-C_(3)N_(4)@Ag ...This study presents a novel Li metal host material with a unique hollow nano-spherical structure that incorporates Ag nano-seeds into a graphitic carbon nitride(g-C_(3)N_(4))shell layer,referred to as g-C_(3)N_(4)@Ag hollow spheres.The g-C_(3)N_(4)@Ag spheres provide a managed internal site for Li metal encapsulation and promote stable Li plating.The g-C_(3)N_(4) spheres are uniformly coated using polydopamine,which has an adhesive nature,to enhance lithium plating/stripping stability.The strategic presence of Ag nano-seeds eliminates the nucleation barrier,properly directing Li growth within the hollow spheres.This design facilitates highly reversible and consistent lithium deposition,offering a promising direction for the production of high-performance lithium metal anodes.These well-designed g-C_(3)N_(4)@Ag hollow spheres ensure stable Li plating/stripping kinetics over more than 500 cycles with a high coulombic efficiency of over 97%.Furthermore,a full cell made using LiNi_(0.90)Co_(0.07)Mn_(0.03)O_(2) and Li-g-C_(3)N_(4)@Ag host electrodes demonstrated highly competitive performance over 200 cycles,providing a guide for the implementation of this technology in advanced lithium metal batteries.展开更多
BACKGROUND Aloe vera has been used as a traditional herbal therapy for wound management and dermatological conditions worldwide for thousands of years.Scientific evidence has confirmed that acemannan,the bioactive com...BACKGROUND Aloe vera has been used as a traditional herbal therapy for wound management and dermatological conditions worldwide for thousands of years.Scientific evidence has confirmed that acemannan,the bioactive compound in aloe vera gel,exhibits significant anti-inflammatory and immunomodulatory properties that enhance tissue regeneration.This case report describes the successful application of an innovative acemannan-enriched glycolipid sphere dressing derived from aloe vera gel in diabetic foot ulcer(DFU)treatment,which achieved a clinically remarkable outcome.CASE SUMMARY An 80-year-old female patient with a 20-year history of type 2 diabetes mellitus experienced recurrent diabetic foot pain for 15 years.She had multiple hospitalizations due to acute infections and poorly controlled hyperglycemia.Long-term treatments included metformin and gliclazide.Upon presentation,she had a nonhealing wound on her left dorsal foot,diagnosed as a severe DFU(Texas classification:Grade II,stage D).She declined amputation and opted for conservative treatment.The medical team applied an acemannan-enriched glycolipid sphere dressing five times daily to the left calf and foot,avoiding the wound area.Frequency was reduced to three times daily after scab formation.Weight-bearing on the injured foot was avoided.Through in-person and online consultations,the team managed her lifestyle and diet,emphasizing natural foods.After 5 months,the DFU healed without significant scarring or functional loss.No recurrence was observed during the 2-year follow-up.Acemannan-enriched glycolipid sphere dressings promote DFU healing.This suggests the potential of these dressings for treating other refractory wounds.展开更多
Development of efficient and stable metal catalysts for the selective aqueous phase hydrodeoxygenation(HDO)of biomass-derived oxygenates to value-added biofuels is highly desired.An innovative surface microenvironment...Development of efficient and stable metal catalysts for the selective aqueous phase hydrodeoxygenation(HDO)of biomass-derived oxygenates to value-added biofuels is highly desired.An innovative surface microenvironment modulation strategy was used to construct the nitrogen-doped hollow carbon sphere encapsulated with Pd(Pd@NHCS-X,X:600–800)nanoreactors for catalytic HDO of biomass-derived vanillin in water.The specific surface microenvironments of Pd@NHCS catalysts including the electronic property of active Pd centers and the surface wettability and porous structure of NHCS supports could be well-controlled by the calcination temperature of catalysts.Intrinsic kinetic evaluations demonstrated that the Pd@NHCS-600 catalyst presented a high turnover frequency of 337.77 h^(–1)and a low apparent activation energy of 18.63 kJ/mol.The excellent catalytic HDO performance was attributed to the unique surface microenvironment of Pd@NHCS catalyst based on structure-performance relationship analysis and DFT calculations.It revealed that pyridinic N species dominated the electronic property regulation of Pd sites through electronic metal-support interaction(EMSI)and produced numerous electron-rich active Pd centers,which not only intensified the dissociation and activation of H2 molecules,but also substantially improved the activation capability of vanillin via the enhanced adsorption of–C=O group.The fine hydrophilicity and abundant porous structure promoted the uniform dispersion of catalyst and ensured the effective access of reactants to catalytic active centers in water.Additionally,the Pd@NHCS-600 catalyst exhibited excellent catalytic stability and broad substrate applicability for the selective aqueous phase HDO of various biomass-derived carbonyl compounds.The proposed surface microenvironment modulation strategy will provide a new consideration for the rational design of high-performance nitrogen-doped carbon-supported metal catalysts for catalytic biomass transformation.展开更多
In this work,Dy_(2)O_(3)rods and layered Dy_(2)WO_(6)heterostructure were effectively interconnected by carbon spheres named Dy_(2)O_(3)/Dy_(2)WO_(6)/C-sph nanocomposite with a confined interface and it was fabricated...In this work,Dy_(2)O_(3)rods and layered Dy_(2)WO_(6)heterostructure were effectively interconnected by carbon spheres named Dy_(2)O_(3)/Dy_(2)WO_(6)/C-sph nanocomposite with a confined interface and it was fabricated using a simple solvothermal approach.These ternary nanocomposites were investigated by X-ray diffraction(XRD),UV-visible diffuse-reflectance spectroscopy(UV-DRS),Fourier transform-infrared spectroscopy(FT-IR),Raman,field emission scanning electron microscopy(FESEM)with energy disperse spectroscopy(EDS),high-resolution transmission electron microscopy(HRTEM),and X-ray photoelectron spectroscopy(XPS)analyses systematically.The XRD data expose that the synthesized materials are formed with a virtuous crystalline state.The charge storage properties and electrochemical performances of the as-synthesized nanocomposites and pure components were assessed with the help of cyclic voltammogram(CV),galvanostatic charge-discharge studies(GCD),and electrochemical impedance studies(EIS),respectively.The rare-earth-based novel Dy_(2)O_(3)/Dy_(2)WO_(6)/C-sph nanocomposite as wo rking electrodes established commendable electrochemical perfo rmances with a maximum specific capacitance value of 123 F/g at a current density of 0.4 A/g in 2.0 mol/L aqueous KOH solution.According to the stability measurements,it was observed that the initial capacitance was maintained at~93%even after 2500 cycles,indicating that good electrochemical stability with the lowest internal resistance values was obtained from EIS analysis.The electrochemical measurements suggest that the Dy_(2)O_(3)/Dy_(2)WO_(6)/C-sph nanocomposite enables great competence and can be used as alternative electrode material in supercapacitor devices to avail high energy efficiency in a sustainable approach.展开更多
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
基金supported by MHRD as researcher C.K.Neog received the MHRD Institute GATE scholarship from Govt.of India.
文摘This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)—Innovative Human Resource Development for Local Intellectualization program grant funded by the Korea government(MSIT)(IITP-2025-RS-2022-00156334)in part by Liaoning Province Nature Fund Project(2024-BSLH-214).
文摘Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.
基金Supported by Talent Scientific Research Start-up Foundation of Wannan Medical College,No.WYRCQD2023045.
文摘BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.
基金supported by the Basic Scientific Research Business Fund Project of Higher Education Institutions in Heilongjiang Province(145409601)the First Batch of Experimental Teaching and Teaching Laboratory Construction Research Projects in Heilongjiang Province(SJGZ20240038).
文摘In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.
基金supported by the Scientific Research Project of Xiang Jiang Lab(22XJ02003)the University Fundamental Research Fund(23-ZZCX-JDZ-28)+5 种基金the National Science Fund for Outstanding Young Scholars(62122093)the National Natural Science Foundation of China(72071205)the Hunan Graduate Research Innovation Project(ZC23112101-10)the Hunan Natural Science Foundation Regional Joint Project(2023JJ50490)the Science and Technology Project for Young and Middle-aged Talents of Hunan(2023TJ-Z03)the Science and Technology Innovation Program of Humnan Province(2023RC1002)。
文摘Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.
文摘This work uses refined first-order shear theory to analyze the free vibration and transient responses of double-curved sandwich two-layer shells made of auxetic honeycomb core and laminated three-phase polymer/GNP/fiber surface subjected to the blast load.Each of the two layers that make up the double-curved shell structure is made up of an auxetic honeycomb core and two laminated sheets of three-phase polymer/GNP/fiber.The exterior is supported by a Kerr elastic foundation with three characteristics.The key innovation of the proposed theory is that the transverse shear stresses are zero at two free surfaces of each layer.In contrast to previous first-order shear deformation theories,no shear correction factor is required.Navier's exact solution was used to treat the double-curved shell problem with a single title boundary,while the finite element technique and an eight-node quadrilateral were used to address the other boundary requirements.To ensure the accuracy of these results,a thorough comparison technique is employed in conjunction with credible statements.The problem model's edge cases allow for this kind of analysis.The study's findings may be used in the post-construction evaluation of military and civil works structures for their ability to sustain explosive loads.In addition,this is also an important basis for the calculation and design of shell structures made of smart materials when subjected to shock waves or explosive loads.
文摘Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain less information.Many current methods,particularly those based on Feature Pyramid Network(FPN),address this challenge by leveraging multi-scale feature fusion.However,existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers,leading to suboptimal small object detection.To address this problem,we propose the Two-layerAttention Feature Pyramid Network(TA-FPN),featuring two key modules:the Two-layer Attention Module(TAM)and the Small Object Detail Enhancement Module(SODEM).TAM uses the attention module to make the network more focused on the semantic information of the object and fuse it to the lower layer,so that each layer contains similar semantic information,to alleviate the problem of small object information being submerged due to semantic gaps between different layers.At the same time,SODEM is introduced to strengthen the local features of the object,suppress background noise,enhance the information details of the small object,and fuse the enhanced features to other feature layers to ensure that each layer is rich in small object information,to improve small object detection accuracy.Our extensive experiments on challenging datasets such as Microsoft Common Objects inContext(MSCOCO)and Pattern Analysis Statistical Modelling and Computational Learning,Visual Object Classes(PASCAL VOC)demonstrate the validity of the proposedmethod.Experimental results show a significant improvement in small object detection accuracy compared to state-of-theart detectors.
文摘In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.
基金financially supported by the National Natural Science Foundation of China(No.22279047)the Instrumental Analysis Center of Jiangsu University of Science and Technology。
文摘Exploring efficient and nonprecious metal electrocatalysts of oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)is crucial for developing rechargeable zinc-air batteries(ZABs).Herein,an alloying-degree control strategy was employed to fabricate nitrogen-doped carbon sphere(NCS)decorated with dual-phase Co/Co_(7)Fe_(3)heterojunctions(CoFe@NCS).The phase composition of materials has been adjusted by controlling the alloying degree.The optimal CoFe_(0.08)@NCS electrocatalyst displays a half-wave potential of 0.80 V for ORR and an overpotential of 283 mV at 10 mA·cm^(-2)for OER in an alkaline electrolyte.The intriguing bifunctional electrocatalytic activity and durability is attributed to the hierarchically porous structure and interfacial electron coupling of highly-active Co_(7)Fe_(3)alloy and metallic Co species.When the CoFe_(0.08)@NCS material is used as air-cathode catalyst of rechargeable liquid-state zinc-air battery(ZAB),the device shows a high peak power-density(157 mW·cm^(-2))and maintains a stable voltage gap over 150 h,outperforming those of the benchmark(Pt/C+RuO_(2))-based device.In particular,the as-fabricated solid-state flexible ZAB delivers a reliable compatibility under different bending conditions.Our work provides a promising strategy to develop metal/alloy-based electrocatalysts for the application in renewable energy conversion technologies.
基金Project supported by the National Natural Science Foundation of China(Nos.12302079 and 11521202)the National Natural Science Foundation of U.S.A.(No.DMS-2306254)。
文摘During nearly 200 years of development in the knowledge of Brownian motion,the Janus sphere,as a typical Brownian particle with special surface properties,has been widely studied in the past few decades.A standard Janus sphere possesses two distinct surfaces.These two surfaces elicit different hydrodynamic interactions with ambient fluids or other interactions in response to environmental stimuli,such as chemical gradients,magnetic fields,and even light.The diffusion of Janus spheres,particularly when controlled by a remotely applied field,has inspired various applications,ranging from the design of micro-swimmers and novel procedures for probing the mechanical properties of suspensions to the fabrication of composites with enhanced performance.In this work,we report a systematic analysis of field-controlled diffusion of Janus spheres.Commencing with stochastic differential equations of motion at the microscale,we derive a coarse-grained Fokker-Planck equation at the macroscale,describing the evolution of the probability distribution function of the Janus sphere in terms of its position and orientation.Leveraging the concept of the hydrodynamic center,we derive,for the first time,explicit generalized Stokes-Einstein relations for long-time effective diffusivity,incorporating the effects of both the surface discontinuity of the Janus sphere and the external fields.The formulae enable predictions of the effective diffusivity as it varies with the slip length and characteristic angle of Janus spheres,and reveal the impact of an aligning potential field on the diffusion coefficients both parallel and perpendicular to the direction of the field.This work not only deepens the understanding of field-controlled diffusion of Janus particles,but also holds a meaningful impact on the future applications in microfluidics and related fields.
基金the Chinese Scholarship Council is acknowledged.This work was supported by the UK’s Engineering and Physical Sciences Research Council(Grant Nos.EP/V000624/1,EP/X03495X/1,EP/X041166/1,and EP/T02643X/1)the Royal Society(Grant No.RG\R2\232531).
文摘The unique phase profile and polarization distribution of the vector vortex beam(VVB)have been a subject of increasing interest in classical and quantum optics.The development of higher-order Poincarésphere(HOPS)and hybrid-order Poincarésphere(HyOPS)has provided a systematic description of VVB.However,the generation of arbitrary VVBs on a HOPS and a HyOPS via a metasurface lacks a unified design framework,despite numerous reported approaches.We present a unified design framework incorporating all design parameters(e.g.,focal lengths and orders)of arbitrary HOPS and HyOPS beams into a single equation.In proof-of-concept experiments,we experimentally demonstrated four metasurfaces to generate arbitrary beams on the fifth-order HOPS(nonfocused and tightly focused,NA 0.89),0-2 order,and 0-1 order HyOPS.We showed HOPS beams’propagation and focusing properties,the superresolution focusing characteristics of the first-order cylindrical VVBs,and the different focusing properties of integerorder and fractional-order cylindrical VVBs.The simplicity and feasibility of the proposed design framework make it a potential catalyst for arbitrary VVBs using metasurfaces in applications of optical imaging,communication,and optical trapping.
基金supported by the Scientific research projects of Hunan Provincial Department of Education(Grant Nos.22A0477 and 20B273)。
文摘We aim to find one highly nontrivial example of the solutions to the vortex fluid dynamical equation on the unit sphere(S^(2))and compare it with the numerical simulation.Since the rigid rotating steady solution for vortex fluids on S^(2)is already known to us,we consider the perturbations above it.After decomposing the perturbation of the vortex number density and vortex charge density into spherical harmonics,we find that the perturbations are propagating waves.To be precise,the velocities for different single-mode vortex number density waves are all the same,while the velocities for single-mode vortex charge density waves depend on the degree of the spherical harmonics l,which is a signal of the existence of dispersion.Meanwhile,we find that there is a beat phenomenon for the positive(or negative)vortex density wave.Numerical simulation based on the canonical equations for the point vortex model agrees perfectly with our theoretical calculations.
基金Funded by the Key Research and Development Program of Shandong Province(No.2020JMRH0101)。
文摘Ceramic hollow spheres have great potential for deep-sea applications.However,the irregularity of the conventional molding process,among other reasons,results in low wall thickness uniformity of hollow spheres.To solve this problem,in this work,we developed a biaxial rotation grouting process for deep-sea ceramic hollow buoyancy spheres,which improves the drawbacks of the traditional rotary grouting method that results in poor wall thickness uniformity of the hollow spheres due to its irregular rotational processing.In this paper,an experimental study was carried out to investigate the effects of different rotational methods,rotational speeds,rotational time,solid phase content,etc.on the wall thickness uniformity of ceramic hollow spheres.The results show that the hollow floating balls prepared by the biaxial rotation method have the lowest wall thickness standard deviation(0.04)when the rotation speed is 60 rpm,the molding time is 8 min,and the solid phase content is 70 wt%.After the hydrostatic pressure test of 120 MPa,the hydrostatic compressive strength of hollow spheres prepared by the biaxial rotation method was increased by 31.67%compared with that of the traditional process.
基金supported by the National Natural Science Foundation of China(Nos.21771060 and 61271126)the International Science&Technology Cooperation Program of China(No.2016YFE0115100)+2 种基金Heilongjiang Provincial Natural Science Foundation of China(No.LH_(2)023B021)Reform and Development Fund Project of Local University supported by the Central Government,Heilongjiang Touyan Innovation Team Program,New Era Excellent Master’s and Doctoral Dissertations of Heilongjiang Province(No.LJYXL2023-020)Basic Scientific Research Project for Heilongjiang Provincial Colleges and Universities(No.2023-KYYWF-1482).
文摘Acetone is a common volatile organic compound that can cause harm to human health when inhaled in small amounts.Therefore,the development of fast response and low detection limit acetone sensors becomes crucial.In this study,a core-shell spherical TiO_(2) sensor with a rich pore structure was designed.This sensor exhibited excellent sensing properties,including higher responsiveness(100 ppm acetone,R_(a)/R_(g)=80),lower detection limit(10 ppb)and short response time(8 s).The problem is that the sensing mechanism between TiO_(2) and acetone is not thoroughly analyzed.To gain further insight,the interaction process of TiO_(2) core-shell spheres and acetone under varying oxygen content environments was investigated by dynamic testing,X-ray photoelectron spectroscopy,in-situ Fourier transform infrared spectroscopy and gas chromatography-mass spectrometry.The research results show that acetone not only adsorbs on the surface of the material and reacts with adsorbed oxygen,but also undergoes catalytic oxidation reaction with TiO_(2) core-shell spheres.Significantly,in high oxygen content environments,acetone undergoes oxidation to form intermediates such as acids and anhydrides that are difficult to desorpt on the surface of the material,thus prolonging the recovery time of the sensor.The discovery of this sensing process will provide some guidance for the design of acetone sensing materials in the future.Meanwhile,this also imparts valuable references and insights for the investigation of the mechanism and application of other sensitive metal oxide materials.
基金supported in part by the National Natural Science Foundation of China under Grants 61703373,61873246,U1504604in part by the Key research project of Henan Province Universities under Grant 19A413014.
文摘Spherical objects are widely used in target localization applications,and the existing sphere localization methods with cameras or total stations both have some limitations.A new high-precision sphere localization method with a theodolite is proposed in this paper.From the view point of the theodolite,the contour points of a sphere with a known radius are measured as latitude-longitude coordinates.It is observed that the center of the target sphere is located on a cylindrical surface constructed with the latitude-longitude coordinates,and therefore the latitude-longitude coordinates of at least three contour points can be used to construct a set of ternary quadratic equations.The Gröbner basis method is used to compute at most four real solutions of the sphere center coordinates.To distinguish the only meaningful solution from the other possible real solutions,a pre-processing of the measured longitude values is also proposed.The factors affecting the positioning accuracy of the sphere center are evaluated in simulation experiments,which are used to obtain an empirical estimation model of the positioning error.Real data experiments are also performed and the results show that the proposed method can achieve high localization precision.
基金supported by the National Research Council of Science&Technology(NST)grant by the Korea government(MSIT)(No.GTL24011-000)supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.RS-2023-00272863)supported by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(P0012748,HRD Program for Industrial Innovation)。
文摘This study presents a novel Li metal host material with a unique hollow nano-spherical structure that incorporates Ag nano-seeds into a graphitic carbon nitride(g-C_(3)N_(4))shell layer,referred to as g-C_(3)N_(4)@Ag hollow spheres.The g-C_(3)N_(4)@Ag spheres provide a managed internal site for Li metal encapsulation and promote stable Li plating.The g-C_(3)N_(4) spheres are uniformly coated using polydopamine,which has an adhesive nature,to enhance lithium plating/stripping stability.The strategic presence of Ag nano-seeds eliminates the nucleation barrier,properly directing Li growth within the hollow spheres.This design facilitates highly reversible and consistent lithium deposition,offering a promising direction for the production of high-performance lithium metal anodes.These well-designed g-C_(3)N_(4)@Ag hollow spheres ensure stable Li plating/stripping kinetics over more than 500 cycles with a high coulombic efficiency of over 97%.Furthermore,a full cell made using LiNi_(0.90)Co_(0.07)Mn_(0.03)O_(2) and Li-g-C_(3)N_(4)@Ag host electrodes demonstrated highly competitive performance over 200 cycles,providing a guide for the implementation of this technology in advanced lithium metal batteries.
文摘BACKGROUND Aloe vera has been used as a traditional herbal therapy for wound management and dermatological conditions worldwide for thousands of years.Scientific evidence has confirmed that acemannan,the bioactive compound in aloe vera gel,exhibits significant anti-inflammatory and immunomodulatory properties that enhance tissue regeneration.This case report describes the successful application of an innovative acemannan-enriched glycolipid sphere dressing derived from aloe vera gel in diabetic foot ulcer(DFU)treatment,which achieved a clinically remarkable outcome.CASE SUMMARY An 80-year-old female patient with a 20-year history of type 2 diabetes mellitus experienced recurrent diabetic foot pain for 15 years.She had multiple hospitalizations due to acute infections and poorly controlled hyperglycemia.Long-term treatments included metformin and gliclazide.Upon presentation,she had a nonhealing wound on her left dorsal foot,diagnosed as a severe DFU(Texas classification:Grade II,stage D).She declined amputation and opted for conservative treatment.The medical team applied an acemannan-enriched glycolipid sphere dressing five times daily to the left calf and foot,avoiding the wound area.Frequency was reduced to three times daily after scab formation.Weight-bearing on the injured foot was avoided.Through in-person and online consultations,the team managed her lifestyle and diet,emphasizing natural foods.After 5 months,the DFU healed without significant scarring or functional loss.No recurrence was observed during the 2-year follow-up.Acemannan-enriched glycolipid sphere dressings promote DFU healing.This suggests the potential of these dressings for treating other refractory wounds.
文摘Development of efficient and stable metal catalysts for the selective aqueous phase hydrodeoxygenation(HDO)of biomass-derived oxygenates to value-added biofuels is highly desired.An innovative surface microenvironment modulation strategy was used to construct the nitrogen-doped hollow carbon sphere encapsulated with Pd(Pd@NHCS-X,X:600–800)nanoreactors for catalytic HDO of biomass-derived vanillin in water.The specific surface microenvironments of Pd@NHCS catalysts including the electronic property of active Pd centers and the surface wettability and porous structure of NHCS supports could be well-controlled by the calcination temperature of catalysts.Intrinsic kinetic evaluations demonstrated that the Pd@NHCS-600 catalyst presented a high turnover frequency of 337.77 h^(–1)and a low apparent activation energy of 18.63 kJ/mol.The excellent catalytic HDO performance was attributed to the unique surface microenvironment of Pd@NHCS catalyst based on structure-performance relationship analysis and DFT calculations.It revealed that pyridinic N species dominated the electronic property regulation of Pd sites through electronic metal-support interaction(EMSI)and produced numerous electron-rich active Pd centers,which not only intensified the dissociation and activation of H2 molecules,but also substantially improved the activation capability of vanillin via the enhanced adsorption of–C=O group.The fine hydrophilicity and abundant porous structure promoted the uniform dispersion of catalyst and ensured the effective access of reactants to catalytic active centers in water.Additionally,the Pd@NHCS-600 catalyst exhibited excellent catalytic stability and broad substrate applicability for the selective aqueous phase HDO of various biomass-derived carbonyl compounds.The proposed surface microenvironment modulation strategy will provide a new consideration for the rational design of high-performance nitrogen-doped carbon-supported metal catalysts for catalytic biomass transformation.
基金supported by Selective Excellence Research Initiative-2023,SRM Institute of Science and Technology(SRMIST/R/AR(A)/SERI2023/174/26-3944)。
文摘In this work,Dy_(2)O_(3)rods and layered Dy_(2)WO_(6)heterostructure were effectively interconnected by carbon spheres named Dy_(2)O_(3)/Dy_(2)WO_(6)/C-sph nanocomposite with a confined interface and it was fabricated using a simple solvothermal approach.These ternary nanocomposites were investigated by X-ray diffraction(XRD),UV-visible diffuse-reflectance spectroscopy(UV-DRS),Fourier transform-infrared spectroscopy(FT-IR),Raman,field emission scanning electron microscopy(FESEM)with energy disperse spectroscopy(EDS),high-resolution transmission electron microscopy(HRTEM),and X-ray photoelectron spectroscopy(XPS)analyses systematically.The XRD data expose that the synthesized materials are formed with a virtuous crystalline state.The charge storage properties and electrochemical performances of the as-synthesized nanocomposites and pure components were assessed with the help of cyclic voltammogram(CV),galvanostatic charge-discharge studies(GCD),and electrochemical impedance studies(EIS),respectively.The rare-earth-based novel Dy_(2)O_(3)/Dy_(2)WO_(6)/C-sph nanocomposite as wo rking electrodes established commendable electrochemical perfo rmances with a maximum specific capacitance value of 123 F/g at a current density of 0.4 A/g in 2.0 mol/L aqueous KOH solution.According to the stability measurements,it was observed that the initial capacitance was maintained at~93%even after 2500 cycles,indicating that good electrochemical stability with the lowest internal resistance values was obtained from EIS analysis.The electrochemical measurements suggest that the Dy_(2)O_(3)/Dy_(2)WO_(6)/C-sph nanocomposite enables great competence and can be used as alternative electrode material in supercapacitor devices to avail high energy efficiency in a sustainable approach.
