The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which ...The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which integration of Internet of Things(IoT)sensing,edge computing,and real-time analytics facilitates timely detection,interpretation,and prediction of the environmental conditions across the applications,such as urban air quality,watershed and coastal surveillance,industrial safety,agriculture,and disaster response.We define end-to-end architectural patterns to organize devices,edge nodes,and cloud services to satisfy latency,reliability,bandwidth,and governance constraints with emphasis on event-time processing,adaptive offloading,and hierarchical aggregation.Then we look at sensing and infrastructure foundations,emphasizing the effects of sensor modality and power autonomy,connectivity,and the practices of calibration on the practicable analytics and eventual plausibility.It is on this basis that we examine real-time analytics pipelines and Artificial Intelligence(AI)techniques to preprocess,sensor combine,anomaly detect,and short-horizon forecast,with a focus on edge-deployable models,quantification of uncertainties,and query resistance to drift and domain shift.Lastly,we address the realities of deployment that condition operational success,such as lifecycle engineering,provenance-aware data management,security and privacy risks,ethical governance,and evaluation methodologies,which place end-to-end latency and field generalization as a priority.This review offers cohesion to algorithmic capabilities and systems engineering and governance to define an overall framework,show open areas of research directions,and provide practical recommendations on how to design trustworthy,scalable,and sustainable environmental monitoring systems.展开更多
The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling...The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling and structural analysis were performed for the repair reinforcement of a steel pipeline with a composite bandage.A preliminary analysis of possible contact interaction schemes was implemented based on the theory of cylindrical shells,taking into account transverse shear deformations.The finite element method was used for a detailed study of the stress state of the composite bandage and the reinforced section of the pipeline.The limit state of the reinforced section was assessed based on the von Mises criterion for steel and the Tsai-Wu criterion for composites.The effectiveness of the repair was demonstrated on a pipeline whose wall thickness had decreased by 20%as a result of corrosion damage.At a nominal pressure of P=6 MPa,the maximum normal stress in the weakened area reached 381 MPa.The installation of a composite bandage reduced this stress to 312 MPa,making the repaired section virtually as strong as the undamaged pipeline.Due to the linearity of the problem,the results obtained can be easily used to find critical internal pressure values.展开更多
The severe shuttle effect and sluggish reaction kinetics in room-temperature sodium-sulfur(RT Na-S)batteries have been major bottlenecks hindering their practical application.To overcome these challenges,a straightfor...The severe shuttle effect and sluggish reaction kinetics in room-temperature sodium-sulfur(RT Na-S)batteries have been major bottlenecks hindering their practical application.To overcome these challenges,a straightforward reduction approach was employed to design three bimetallic alloy nanoparticles(FeNi,FeCo,and NiCo)supported on multistage porous carbon substrates.Experimental and theoretical calculations reveal that the charge transfer within the alloy catalyst influences the position of its d-band center and its degree of hybridization with sodium polysulfides(NaPSs).An increased charge transfer leads to a shift of the alloy’s d-band center closer to the Fermi energy level,thereby enhancing its adsorption and catalytic capabilities.Among the three alloy compositions,the FeNi alloy exhibits the highest charge transfer.Consequently,the FeNi alloy demonstrates the superior electrochemical performance,achieving a high reversible specific capacity of 848.2 mA h g^(−1),with an average capacity degradation rate of only 0.037%per cycle over 1000 cycles at 1.2 C.The S/FeNi/NC cathode exhibits a low electrolyte-to-sulfur(E/S)ratio of 6.6µL mg^(−1),while maintaining a high reversible specific capacity of 568.1 mA h g^(−1).This offers valuable insights for the application of alloy catalysts in the S/FeNi/NC cathode of RT Na-S batteries.展开更多
Due to their chiral structure,carbon nanosprings possess unique properties that are promising for nanotechnology applications.The structural transformations of carbon nanosprings in the form of spiral macromolecules d...Due to their chiral structure,carbon nanosprings possess unique properties that are promising for nanotechnology applications.The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar coronene and kekulene molecules(graphene helicoids and spiral nanoribbons)are analyzed using molecular dynamics simulations.The interatomic interactions are described by a force field including valence bonds,bond angles,torsional and dihedral angles,as well as van derWaals interactions.While the tension/compression of such nanosprings has been analyzed in the literature,this study investigates other modes of deformation,including bending and twisting.Depending on the geometric characteristics of the carbon nanosprings,the formation of structural and helix reversal topological defects is described.During these structural transformations of the nanosprings,only van der Waals bonds break and recover,but breaking or recovery of covalent bonds does not take place.It is found that nanosprings demonstrate a significantly higher coefficient of axial thermal expansion than many metals and alloys.Under axial compression,Euler instability leads to lateral bending with continuous deformation of the nanospring axis at relatively low compression,while at high compression,bending kinks form.Various types of topological defects form on the instantly released nanospring during its relaxation from a highly stretched configuration.These results are useful for the development of nanosensors operating over a wide temperature range.展开更多
Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper ...Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper equations are one of the main and most efficient methods for estimating stem volume to any merchantable limit of a species.There is currently no taper equation for Eucalyptus species in Nigeria.Therefore,this study developed taper equations for E.camaldulensis in northern Nigeria.Data for this study were obtained from a private plantation in Jalingo Local Government Area,Taraba State,Nigeria.68 trees were felled and sectioned into 1-m bolt across the stem to a merchantable limit of 5 cm,which were used as the fitting dataset.An additional 22 trees were felled and used to validate the taper equations for stem volume estimation.Seven taper equations were initially fitted to the dataset using nonlinear least squares.The best taper equation was then refitted using a nonlinear mixed-effects approach and calibrated using diameters of one to five sections from the butt end.The taper equations were numerically integrated to obtain the stem volume,which was compared with empirical volume equations.The result shows that the Kozak(Can J For Res 27(5):619-629.10.1139/x97-011,1997)equation,which included eight parameters,provided the best fit for predicting section diameters for under and over bark.The mixed-effects taper equation(NLME-TE)explained most stem diameter variations in the fitting dataset(pseudo-R2:0.986-0.987;RMSE:0.547-0.578 cm)without substantial residual trends.The validation showed that the prediction accuracy of the integrated NLME-TE improved as the number of sectional diameter measurements increased,with at least a 35%reduction in volume estimate error.For practical implementation,two calibration sectional diameter measurements taken from the butt end per tree are recommended.This approach would reduce measurement effort and cost while improving model performance.展开更多
Microplastics,resulting from human activities,are widespread environmental contaminants that threaten both ecosystems and human health.These particles,less than 5 mm in size,are found in air,soil,and water,originating...Microplastics,resulting from human activities,are widespread environmental contaminants that threaten both ecosystems and human health.These particles,less than 5 mm in size,are found in air,soil,and water,originating from industrial waste and everyday plastic products.They come in various shapes,sizes,and colors,with primary and secondary microplastics formed through degradation processes.Microplastics have entered the food chain,affecting all trophic levels,with detrimental effects on organisms such as plankton,fish,and corals.Research on microplastics is hindered by methodological biases and sampling inconsistencies,which impact the reliability and comparability of data,as different techniques often yield varying results.Current degradation methods,including bioremediation and filtration,show potential but remain limited.Detecting microplastics is challenging due to their small size,though advanced techniques like morphological and analytical analyses,particularly in fish guts,aid detection.Targeted studies on microplastic levels in aquatic species are crucial,and the development of biodegradable alternatives is essential to mitigate their long-term environmental impact.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by...The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by these interconnected devices,robust anomaly detection mechanisms are essential.Anomaly detection in this dynamic environment necessitates methods that can accurately distinguish between normal and anomalous behavior by learning intricate patterns.This paper presents a novel approach utilizing generative adversarial networks(GANs)for anomaly detection in IoT systems.However,optimizing GANs involves tuning hyper-parameters such as learning rate,batch size,and optimization algorithms,which can be challenging due to the non-convex nature of GAN loss functions.To address this,we propose a five-dimensional Gray wolf optimizer(5DGWO)to optimize GAN hyper-parameters.The 5DGWO introduces two new types of wolves:gamma(γ)for improved exploitation and convergence,and theta(θ)for enhanced exploration and escaping local minima.The proposed system framework comprises four key stages:1)preprocessing,2)generative model training,3)autoencoder(AE)training,and 4)predictive model training.The generative models are utilized to assist the AE training,and the final predictive models(including convolutional neural network(CNN),deep belief network(DBN),recurrent neural network(RNN),random forest(RF),and extreme gradient boosting(XGBoost))are trained using the generated data and AE-encoded features.We evaluated the system on three benchmark datasets:NSL-KDD,UNSW-NB15,and IoT-23.Experiments conducted on diverse IoT datasets show that our method outperforms existing anomaly detection strategies and significantly reduces false positives.The 5DGWO-GAN-CNNAE exhibits superior performance in various metrics,including accuracy,recall,precision,root mean square error(RMSE),and convergence trend.The proposed 5DGWO-GAN-CNNAE achieved the lowest RMSE values across the NSL-KDD,UNSW-NB15,and IoT-23 datasets,with values of 0.24,1.10,and 0.09,respectively.Additionally,it attained the highest accuracy,ranging from 94%to 100%.These results suggest a promising direction for future IoT security frameworks,offering a scalable and efficient solution to safeguard against evolving cyber threats.展开更多
Although the plastic loading can enhance creep deformation and yield strength,the anisotropic Stress Relaxation Aging(SRA)behavior and mechanism under plastic loading remain unclear,which presents a significant challe...Although the plastic loading can enhance creep deformation and yield strength,the anisotropic Stress Relaxation Aging(SRA)behavior and mechanism under plastic loading remain unclear,which presents a significant challenge in accurately shaping aluminum alloy panels.In this study,the SRA behavior of 2195-T4 Al-Cu-Li alloys were thoroughly studied under initial loading stresses within the elastic(210/250 MPa)and plastic(380/420 MPa)ranges at 180℃by stress relaxation and tensile tests as well as microstructure characterization.The findings reveal that compared with those under elastic loadings,in-plane anisotropy(IPA)values of the stress relaxation amount,yield strength and fracture elongation under plastic loadings are reduced by 60%–80%,70%–90% and 72%–89%,respectively.Similarly,IPA values of precipitate size in grains and PrecipitationFree Zones(PFZ)width at grain boundaries under plastic loading decrease by 31.4%and 94.4%respectively.These results indicate plastic loading significantly weakens the anisotropic SRA behavior,owing to numerous uniformly distributed fine T1phases and small IPA values of both T1precipitates size and PFZ width in various loading directions.Compared with those of elastic loadingaged alloys,yield strength of plastic loading-aged alloys shows high strength-ductility because of the combined effect of closely dispersed fine T1precipitates,narrowed PFZ and numerous sheared and rotated T1phases at different locations during tensile process.The uniformly distributed larger Kernel Average Misorientation(KAM)and Schmidt factor values of the plastic loading-aged alloy,as well as the cross-slip generated,also help to enhance the strength and ductility of the alloy.展开更多
P-glycoprotein(P-gp)is a transmembrane protein widely involved in the absorption,distribution,metabolism,excretion,and toxicity(ADMET)of drugs within the human body.Accurate prediction of Pgp inhibitors and substrates...P-glycoprotein(P-gp)is a transmembrane protein widely involved in the absorption,distribution,metabolism,excretion,and toxicity(ADMET)of drugs within the human body.Accurate prediction of Pgp inhibitors and substrates is crucial for drug discovery and toxicological assessment.However,existing models rely on limited molecular information,leading to suboptimal model performance for predicting P-gp inhibitors and substrates.To overcome this challenge,we compiled an extensive dataset from public databases and literature,consisting of 5,943 P-gp inhibitors and 4,018 substrates,notable for their high quantity,quality,and structural uniqueness.In addition,we curated two external test sets to validate the model's generalization capability.Subsequently,we developed a multimodal graph contrastive learning(GCL)model for the prediction of P-gp inhibitors and substrates(MC-PGP).This framework integrates three types of features from Simplified Molecular Input Line Entry System(SMILES)sequences,molecular fingerprints,and molecular graphs using an attention-based fusion strategy to generate a unified molecular representation.Furthermore,we employed a GCL approach to enhance structural representations by aligning local and global structures.Extensive experimental results highlight the superior performance of MC-PGP,which achieves improvements in the area under the curve of receiver operating characteristic(AUC-ROC)of 9.82%and 10.62%on the external P-gp inhibitor and external P-gp substrate datasets,respectively,compared with 12 state-of-the-art methods.Furthermore,the interpretability analysis of all three molecular feature types offers comprehensive and complementary insights,demonstrating that MC-PGP effectively identifies key functional groups involved in P-gp interactions.These chemically intuitive insights provide valuable guidance for the design and optimization of drug candidates.展开更多
Sulfamethoxazole(SMZ)is a prevalent and recalcitrant micropollutant in water,posing a significant threat to both aquatic organisms and human health.Therefore,investigating the removal of SMZ is of critical importance....Sulfamethoxazole(SMZ)is a prevalent and recalcitrant micropollutant in water,posing a significant threat to both aquatic organisms and human health.Therefore,investigating the removal of SMZ is of critical importance.In order to investigate the effect of rare earth metal doping on the performance of activated persulfate oxidative degradation of SMZ,BiFeO_(3)with different Ce doping amounts was successfully prepared by a hydrothermal method.Then,it was characterized by X-ray diffraction(XRD),scanning electron microscopy(SEM),scanning transmission electro n microscopy(STEM)and Brunauer-Emmett-Teller(BET)method.The performance of porous Ce/BiFeO_(3)in the catalytic activation of persulfate(PMS)for the degradation of SMZ in water was investigated using SMZ solution as a simulated wastewater.The impact of Ce doping rate,catalyst dosage,temperature variations,common anions,natural organic matter,and PMS concentration on SMZ removal was systematically evaluated.The characterization results show that the octahedral rhombic structure of Ce can be observed on the surface of this doped catalyst,and Ce doping does not change the crystalline shape of Ce/BiFeO_(3).The specific surface area of the doped catalyst increases,accompanied by an enlargement of pore size,thereby enhancing the catalyst's adsorption capacity and resistance to contamination by SMZ.Under the optimal conditions of 25℃,SMZ concentration of 20 mg/L,0.8 g/L PMS and 0.3 g/L 0.05Ce/BiFeO_(3)catalyst,the removal rate of SMZ reaches approximately 95%within35 min of reaction time.Even after five cycles of reuse,the degradation rate of SMZ remains above 88%,demonstrating the catalyst's good stability and reusability.Bursting experiments show that SO_(4)^(·-),·OH,1O_(2)and O_(2)^(·-)are involved in the catalytic degradation process,with 1O_(2)playing a dominant role.展开更多
Sodium-ion batteries(SIBs) are promising electrochemical energy storage systems as lithium-ion batteries by virtue of their similar chemical properties and natural abundance and availability.However,the ionic radius o...Sodium-ion batteries(SIBs) are promising electrochemical energy storage systems as lithium-ion batteries by virtue of their similar chemical properties and natural abundance and availability.However,the ionic radius of Na^(+)is larger than that of Li^(+),leading to challenges in its insertion/extraction at anode side.As a class of anode materials,phosphorus allotropes(PAs,red,and black) and metal phosphides(MPs) have shown great prospects because of high theoretical gravimetric/volumetric capacity,high carrier mobility,and suitable redox potential.In this review,recent developments in the studies of PAs and MPs with particular emphasis on understanding sodium storage mechanisms,developing novel synthesis strategies,and performance validations have been manifested valuable solutions to address these challenges.We begin with the introduction and classification of the macroscopic sodiation mechanisms of PAs and MPs,and the various fabrication strategies of PAs and MPs are comprehensively summarized in second section.The third section thoroughly reviews the progresses on PAs and MPs-based advanced materials for their application in SIBs.Finally,we also discuss the significant challenges and outline a roadmap for future research directions.展开更多
Laser powder-bed fusion(LPBF)of Zn-0.8Cu(wt.%)alloys exhibits significant advantages in the customization of biodegradable bone implants.However,the formability of LPBFed Zn alloy is not sufficient due to the spheroid...Laser powder-bed fusion(LPBF)of Zn-0.8Cu(wt.%)alloys exhibits significant advantages in the customization of biodegradable bone implants.However,the formability of LPBFed Zn alloy is not sufficient due to the spheroidization during the interaction of powder and laser beam,of which the mechanism is still not well understood.In this study,the evolution of morphology and grain structure of the LPBFed Zn-Cu alloy was investigated based on single-track deposition experiments.As the scanning speed increases,the grain structure of a single track of Zn-Cu alloy gradually refines,but the formability deteriorates,leading to the defect’s formation in the subsequent fabrication.The Zn-Cu alloys fabricated by optimum processing parameters exhibit a tensile strength of 157.13 MPa,yield strength of 106.48 MPa and elongation of 14.7%.This work provides a comprehensive understanding of the processing optimization of Zn-Cu alloy,achieving LPBFed Zn-Cu alloy with high density and excellent mechanical properties.展开更多
The Jiuyishan granitic complex,located in the Nanling Range,South China,is composed of five granitic plutons(Xuehuading,Jinjiling,Pangxiemu,Shaziling and Xishan).Zircon U-Pb dating of four plutons(Jinjiling,Pangxiemu,...The Jiuyishan granitic complex,located in the Nanling Range,South China,is composed of five granitic plutons(Xuehuading,Jinjiling,Pangxiemu,Shaziling and Xishan).Zircon U-Pb dating of four plutons(Jinjiling,Pangxiemu,Shaziling and Xishan)yielded similar ages of approximately 153 Ma,indicating indistinguishable ages within error.Three plutons except the Shaziling pluton,have consistentε_(Nd)(t)(-7.8 to-5.8)andε_(Hf)(t)(-9.1 to-2.2)values,which are similar to those of the lower crustal granulitic metasedimentary and meta-igneous rocks in South China.Compared to other three plutons,the Shaziling pluton has consistentε_(Nd)(t)(-7.4 to-6.8)andε_(Hf)(t)(-7.5 to-4.7)values and shows similar source,but the Shaziling mafic microgranular enclaves(MMEs)show variableε_(Hf)(t)(-14.2 to 4.8)values,indicating a remarkable mantle magma injection of the Shaziling pluton.Zircon Ce/Sm-Yb/Gd,whole-rock CaO-P_(2)O_(5)and CaO-TiO_(2)linear trends reveal that from the Xishan to the Shaziling and from the Jinjiling to the Pangxiemu granites,they experienced apatite and titanite fractionation,respectively.Zircon Th,U,Nb,Ta,Hf,Ti,Y,P and rare earth element(REE)contents and whole-rock Sr,Ba and Rb contents also show that the Shaziling,Xishan,Jinjiling and Pangxiemu granites followed a discontinuous evolutionary series,but the Pangxiemu granites exhibit highly evolved nature.Four main controlling factors of W-Sn and rare metal mineralization in granitic rocks were discussed,and we found that the mineralization in Jiuyishan granitic complex was mainly controlled by the fractionation degree and crystallization temperature,but were rarely affected by oxygen fugacity and mantle material input.The Pangxiemu granites show particularly higher Rb and Ta contents than the other three plutons,implying that the ore deposits developed in the Jiuyishan Complex were directly related to the most evolved Pangxiemu pluton,with the occurrence of Rb and Ta as the most likely rare metal mineralization in the Jiuyishan District.A crystal mush model is proposed to interpret the petrogenetic and mineralizing processes of the Jiuyishan granitic complex.展开更多
GH4350(AEREX 350)is a Ni-based wrought superalloy for high-performance fasteners,with a maximum service temperature of 750℃.It has high tensile strength,fatigue resistance,stress rupture and relaxation resistance,cor...GH4350(AEREX 350)is a Ni-based wrought superalloy for high-performance fasteners,with a maximum service temperature of 750℃.It has high tensile strength,fatigue resistance,stress rupture and relaxation resistance,corrosion resistance,low thermal expansion,and notch sensitivity.The high strength of GH4350 is largely derived through solid solution strengthening and the γ′phase precipitation strengthening.During the precipitation of γ′phase,a minor amount ofηphase also precipitates.However,it is reported that the microstructure of alloy is sensitive to heat treatment parameters,including temperature and time.The γ′phases can be transformed intoηphases under certain conditions,potentially degrading the performance of the alloy.The chemical composition characteristics,heat treatment strategies,and strengthening mechanism of GH4350 were reviewed in this research,aiming to understand the factors behind its remarkable high-temperature performance,to guide the development of new alloys,and to further enhance its heat resistance.展开更多
Fe-Mo functionally graded materials(FGMs)with different composition-change rates from 100%304 stainless steel to 100%Mo along the composition gradient direction were prepared by electron beam-directed energy depositio...Fe-Mo functionally graded materials(FGMs)with different composition-change rates from 100%304 stainless steel to 100%Mo along the composition gradient direction were prepared by electron beam-directed energy deposition(EB-DED)technique,including three samples with composition mutation of 100%,composition change rate of 10%and 30%.Results show that the composition-change rate significantly affects the microstructure and mechanical properties of the samples.In the sample with abrupt change of composition,the sharp shift in composition between 304 stainless steel and Mo leads to a great difference in the microstructure and hardness near the interface between the two materials.With the increase in the number of gradient layers,the composition changes continuously along the direction of deposition height,and the microstructure morphology shows a smooth transition from 304 stainless steel to Mo,which is gradually transformed from columnar crystal to dendritic crystal.Elements Fe,Mo,and other major elements transform linearly along the gradient direction,with sufficient interlayer diffusion between the deposited layers,leading to good metallurgical bonding.The smaller the change in composition gradient,the greater the microhardness value along the deposition direction.When the composition gradient is 10%,the gradient layer exhibits higher hardness(940 HV)and excellent resistance to surface abrasion,and the overall compressive properties of the samples are better,with the compressive fracture stress in the top region reaching 750.05±14 MPa.展开更多
The application of legal texts in the context of digital television is a process that relies on several normative instruments,ranging from international treaties,such as those of the ITU(International Telecommunicatio...The application of legal texts in the context of digital television is a process that relies on several normative instruments,ranging from international treaties,such as those of the ITU(International Telecommunications Union),to national regulations defining the obligations of audiovisual operators and the modalities of consumer support.Many countries have introduced specific laws and regulations to organize the gradual switch-off of analog broadcasting and encourage the adoption of new digital standards.Consequently,the digitization of Guinea’s broadcasting network cannot be carried out without taking into account the legal framework:allocation of resources and broadcasting players.Analog and digital broadcasting,according to regulatory texts,shows the relationships between the different communication management structures.As for digital broadcasting,we note the appearance of a new service,multiplex.展开更多
Knowledge graphs (KGs) offer a structured, machine-readable format for organizing complex information. In heterogeneous catalysis, where data on catalytic materials, reaction conditions, mechanisms, and synthesis rout...Knowledge graphs (KGs) offer a structured, machine-readable format for organizing complex information. In heterogeneous catalysis, where data on catalytic materials, reaction conditions, mechanisms, and synthesis routes are dispersed across diverse sources, KGs provide a semantic framework that supports data integration under the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This review aims to survey recent developments in catalysis KGs, describe the main techniques for graph construction, and highlight how artificial intelligence, particularly large language models (LLMs), enhances graph generation and query. We conducted a systematic analysis of the literature, focusing on ontology-guided text mining pipelines, graph population methods, and maintenance strategies. Our review identifies key trends: ontology-based approaches enable the automated extraction of domain knowledge, LLM-driven retrieval-augmented generation supports natural-language queries, and scalable graph architectures range from a few thousand to over a million triples. We discuss state-of-the-art applications, such as catalyst recommendation systems and reaction mechanism discovery tools, and examine the major challenges, including data heterogeneity, ontology alignment, and long-term graph curation. We conclude that KGs, when combined with AI methods, hold significant promise for accelerating catalyst discovery and knowledge management, but progress depends on establishing community standards for ontology development and maintenance. This review provides a roadmap for researchers seeking to leverage KGs to advance heterogeneous catalysis research.展开更多
This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named C...This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named Clarion)has been justified by,and validated against,psychological data,findings,and theoretical constructs.One important theoretical background for it is the dual-process theories,which led to its overall two-level structuring in a hybrid neuro-symbolic way.Furthermore,given the recent advances in AI and computing technology,LLMs are being incorporated into the model to better capture human intuition and instinct(and implicit processes in general),in order to further enhance Clarion.Integrating Clarion and LLMs can also help to develop AI systems that are more capable,more reliable,and more human-like.Overall,the paper advocates a multidisciplinary approach towards developing better models for cognitive science and for AI.展开更多
Cashew processing in Côte d’Ivoire focuses only on the cashew nut, to the detriment of the apple. Only a very small proportion of the apple is processed into juice. The aim of this work is to enhance the value o...Cashew processing in Côte d’Ivoire focuses only on the cashew nut, to the detriment of the apple. Only a very small proportion of the apple is processed into juice. The aim of this work is to enhance the value of cashew apples by transforming them into jam. Specifically, the aim was first to characterize the sensory properties of cashew apple jam formulations using baobab powder as a source of pectin and then to optimise the formulations. A Box-Behken design with pH, Sugar, and Baobab as factors was used to model and characterize the jam sensory descriptors, and a multivariate analysis with SensomineR was used to characterize the jam formulations. The desirability function was used to optimise the formulations. The results show globally significant regressions at the 0.05 threshold for the sensory descriptors Gelling, Brilliance, Smell, Sweetness, and (-)Astringency, with the exception of (-)Salinity. The R2 coefficients are greater than 80%. The factors studied could have effects on the sensory descriptors of cashew jam formulations. The Baobab had the main effect on the gelling, smell, and astringency of the jams. Brilliance depended on the added sugar. A product effect (p < 0.001) was observed for the descriptors Smell, Gelling, Brilliance, and Sweetness, as these allowed the panelists to find differences between the formulations. Optimum jam formulation can be achieved with 51.56% sugar and 2.12% Baobab at a pH of 3.15. Cashew apple jam using Baobab offers opportunities to add value to apples that have long been abandoned in the field. It would be important to find conditions for prolonged storage of this jam.展开更多
基金supported by Jiangxi Polytechnic Institute Key Research Topics in Educational Reform 2025-JGJG-07.
文摘The intelligent environmental sensing systems are quickly transforming the sparse and retrospective monitoring to dense and decision-oriented environmental intelligence.This review brings together the manner in which integration of Internet of Things(IoT)sensing,edge computing,and real-time analytics facilitates timely detection,interpretation,and prediction of the environmental conditions across the applications,such as urban air quality,watershed and coastal surveillance,industrial safety,agriculture,and disaster response.We define end-to-end architectural patterns to organize devices,edge nodes,and cloud services to satisfy latency,reliability,bandwidth,and governance constraints with emphasis on event-time processing,adaptive offloading,and hierarchical aggregation.Then we look at sensing and infrastructure foundations,emphasizing the effects of sensor modality and power autonomy,connectivity,and the practices of calibration on the practicable analytics and eventual plausibility.It is on this basis that we examine real-time analytics pipelines and Artificial Intelligence(AI)techniques to preprocess,sensor combine,anomaly detect,and short-horizon forecast,with a focus on edge-deployable models,quantification of uncertainties,and query resistance to drift and domain shift.Lastly,we address the realities of deployment that condition operational success,such as lifecycle engineering,provenance-aware data management,security and privacy risks,ethical governance,and evaluation methodologies,which place end-to-end latency and field generalization as a priority.This review offers cohesion to algorithmic capabilities and systems engineering and governance to define an overall framework,show open areas of research directions,and provide practical recommendations on how to design trustworthy,scalable,and sustainable environmental monitoring systems.
文摘The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling and structural analysis were performed for the repair reinforcement of a steel pipeline with a composite bandage.A preliminary analysis of possible contact interaction schemes was implemented based on the theory of cylindrical shells,taking into account transverse shear deformations.The finite element method was used for a detailed study of the stress state of the composite bandage and the reinforced section of the pipeline.The limit state of the reinforced section was assessed based on the von Mises criterion for steel and the Tsai-Wu criterion for composites.The effectiveness of the repair was demonstrated on a pipeline whose wall thickness had decreased by 20%as a result of corrosion damage.At a nominal pressure of P=6 MPa,the maximum normal stress in the weakened area reached 381 MPa.The installation of a composite bandage reduced this stress to 312 MPa,making the repaired section virtually as strong as the undamaged pipeline.Due to the linearity of the problem,the results obtained can be easily used to find critical internal pressure values.
基金supported by Shaanxi Fundamental Science Research Project for Chemistry and Biology(23JHQ011)Natural Science Foundation of Shaanxi(2024JC-YBMS-115)Natural Science Basic Research Plan in Shaanxi Province of China(2025JC-YBMS-141)。
文摘The severe shuttle effect and sluggish reaction kinetics in room-temperature sodium-sulfur(RT Na-S)batteries have been major bottlenecks hindering their practical application.To overcome these challenges,a straightforward reduction approach was employed to design three bimetallic alloy nanoparticles(FeNi,FeCo,and NiCo)supported on multistage porous carbon substrates.Experimental and theoretical calculations reveal that the charge transfer within the alloy catalyst influences the position of its d-band center and its degree of hybridization with sodium polysulfides(NaPSs).An increased charge transfer leads to a shift of the alloy’s d-band center closer to the Fermi energy level,thereby enhancing its adsorption and catalytic capabilities.Among the three alloy compositions,the FeNi alloy exhibits the highest charge transfer.Consequently,the FeNi alloy demonstrates the superior electrochemical performance,achieving a high reversible specific capacity of 848.2 mA h g^(−1),with an average capacity degradation rate of only 0.037%per cycle over 1000 cycles at 1.2 C.The S/FeNi/NC cathode exhibits a low electrolyte-to-sulfur(E/S)ratio of 6.6µL mg^(−1),while maintaining a high reversible specific capacity of 568.1 mA h g^(−1).This offers valuable insights for the application of alloy catalysts in the S/FeNi/NC cathode of RT Na-S batteries.
基金funded by the Russian Science Foundation(RSF),grant No.25-73-20038(conceptualization,methodology,manuscript writing).
文摘Due to their chiral structure,carbon nanosprings possess unique properties that are promising for nanotechnology applications.The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar coronene and kekulene molecules(graphene helicoids and spiral nanoribbons)are analyzed using molecular dynamics simulations.The interatomic interactions are described by a force field including valence bonds,bond angles,torsional and dihedral angles,as well as van derWaals interactions.While the tension/compression of such nanosprings has been analyzed in the literature,this study investigates other modes of deformation,including bending and twisting.Depending on the geometric characteristics of the carbon nanosprings,the formation of structural and helix reversal topological defects is described.During these structural transformations of the nanosprings,only van der Waals bonds break and recover,but breaking or recovery of covalent bonds does not take place.It is found that nanosprings demonstrate a significantly higher coefficient of axial thermal expansion than many metals and alloys.Under axial compression,Euler instability leads to lateral bending with continuous deformation of the nanospring axis at relatively low compression,while at high compression,bending kinks form.Various types of topological defects form on the instantly released nanospring during its relaxation from a highly stretched configuration.These results are useful for the development of nanosensors operating over a wide temperature range.
文摘Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper equations are one of the main and most efficient methods for estimating stem volume to any merchantable limit of a species.There is currently no taper equation for Eucalyptus species in Nigeria.Therefore,this study developed taper equations for E.camaldulensis in northern Nigeria.Data for this study were obtained from a private plantation in Jalingo Local Government Area,Taraba State,Nigeria.68 trees were felled and sectioned into 1-m bolt across the stem to a merchantable limit of 5 cm,which were used as the fitting dataset.An additional 22 trees were felled and used to validate the taper equations for stem volume estimation.Seven taper equations were initially fitted to the dataset using nonlinear least squares.The best taper equation was then refitted using a nonlinear mixed-effects approach and calibrated using diameters of one to five sections from the butt end.The taper equations were numerically integrated to obtain the stem volume,which was compared with empirical volume equations.The result shows that the Kozak(Can J For Res 27(5):619-629.10.1139/x97-011,1997)equation,which included eight parameters,provided the best fit for predicting section diameters for under and over bark.The mixed-effects taper equation(NLME-TE)explained most stem diameter variations in the fitting dataset(pseudo-R2:0.986-0.987;RMSE:0.547-0.578 cm)without substantial residual trends.The validation showed that the prediction accuracy of the integrated NLME-TE improved as the number of sectional diameter measurements increased,with at least a 35%reduction in volume estimate error.For practical implementation,two calibration sectional diameter measurements taken from the butt end per tree are recommended.This approach would reduce measurement effort and cost while improving model performance.
文摘Microplastics,resulting from human activities,are widespread environmental contaminants that threaten both ecosystems and human health.These particles,less than 5 mm in size,are found in air,soil,and water,originating from industrial waste and everyday plastic products.They come in various shapes,sizes,and colors,with primary and secondary microplastics formed through degradation processes.Microplastics have entered the food chain,affecting all trophic levels,with detrimental effects on organisms such as plankton,fish,and corals.Research on microplastics is hindered by methodological biases and sampling inconsistencies,which impact the reliability and comparability of data,as different techniques often yield varying results.Current degradation methods,including bioremediation and filtration,show potential but remain limited.Detecting microplastics is challenging due to their small size,though advanced techniques like morphological and analytical analyses,particularly in fish guts,aid detection.Targeted studies on microplastic levels in aquatic species are crucial,and the development of biodegradable alternatives is essential to mitigate their long-term environmental impact.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
基金described in this paper has been developed with in the project PRESECREL(PID2021-124502OB-C43)。
文摘The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by these interconnected devices,robust anomaly detection mechanisms are essential.Anomaly detection in this dynamic environment necessitates methods that can accurately distinguish between normal and anomalous behavior by learning intricate patterns.This paper presents a novel approach utilizing generative adversarial networks(GANs)for anomaly detection in IoT systems.However,optimizing GANs involves tuning hyper-parameters such as learning rate,batch size,and optimization algorithms,which can be challenging due to the non-convex nature of GAN loss functions.To address this,we propose a five-dimensional Gray wolf optimizer(5DGWO)to optimize GAN hyper-parameters.The 5DGWO introduces two new types of wolves:gamma(γ)for improved exploitation and convergence,and theta(θ)for enhanced exploration and escaping local minima.The proposed system framework comprises four key stages:1)preprocessing,2)generative model training,3)autoencoder(AE)training,and 4)predictive model training.The generative models are utilized to assist the AE training,and the final predictive models(including convolutional neural network(CNN),deep belief network(DBN),recurrent neural network(RNN),random forest(RF),and extreme gradient boosting(XGBoost))are trained using the generated data and AE-encoded features.We evaluated the system on three benchmark datasets:NSL-KDD,UNSW-NB15,and IoT-23.Experiments conducted on diverse IoT datasets show that our method outperforms existing anomaly detection strategies and significantly reduces false positives.The 5DGWO-GAN-CNNAE exhibits superior performance in various metrics,including accuracy,recall,precision,root mean square error(RMSE),and convergence trend.The proposed 5DGWO-GAN-CNNAE achieved the lowest RMSE values across the NSL-KDD,UNSW-NB15,and IoT-23 datasets,with values of 0.24,1.10,and 0.09,respectively.Additionally,it attained the highest accuracy,ranging from 94%to 100%.These results suggest a promising direction for future IoT security frameworks,offering a scalable and efficient solution to safeguard against evolving cyber threats.
基金support from the Key Program of the National Natural Science Foundation of China(No.51235010)。
文摘Although the plastic loading can enhance creep deformation and yield strength,the anisotropic Stress Relaxation Aging(SRA)behavior and mechanism under plastic loading remain unclear,which presents a significant challenge in accurately shaping aluminum alloy panels.In this study,the SRA behavior of 2195-T4 Al-Cu-Li alloys were thoroughly studied under initial loading stresses within the elastic(210/250 MPa)and plastic(380/420 MPa)ranges at 180℃by stress relaxation and tensile tests as well as microstructure characterization.The findings reveal that compared with those under elastic loadings,in-plane anisotropy(IPA)values of the stress relaxation amount,yield strength and fracture elongation under plastic loadings are reduced by 60%–80%,70%–90% and 72%–89%,respectively.Similarly,IPA values of precipitate size in grains and PrecipitationFree Zones(PFZ)width at grain boundaries under plastic loading decrease by 31.4%and 94.4%respectively.These results indicate plastic loading significantly weakens the anisotropic SRA behavior,owing to numerous uniformly distributed fine T1phases and small IPA values of both T1precipitates size and PFZ width in various loading directions.Compared with those of elastic loadingaged alloys,yield strength of plastic loading-aged alloys shows high strength-ductility because of the combined effect of closely dispersed fine T1precipitates,narrowed PFZ and numerous sheared and rotated T1phases at different locations during tensile process.The uniformly distributed larger Kernel Average Misorientation(KAM)and Schmidt factor values of the plastic loading-aged alloy,as well as the cross-slip generated,also help to enhance the strength and ductility of the alloy.
基金supported by the National Key Research and Development Program of China(Program No.:2022YFF1203003)the National Natural Science Foundation of China(Grant No.:82373791).
文摘P-glycoprotein(P-gp)is a transmembrane protein widely involved in the absorption,distribution,metabolism,excretion,and toxicity(ADMET)of drugs within the human body.Accurate prediction of Pgp inhibitors and substrates is crucial for drug discovery and toxicological assessment.However,existing models rely on limited molecular information,leading to suboptimal model performance for predicting P-gp inhibitors and substrates.To overcome this challenge,we compiled an extensive dataset from public databases and literature,consisting of 5,943 P-gp inhibitors and 4,018 substrates,notable for their high quantity,quality,and structural uniqueness.In addition,we curated two external test sets to validate the model's generalization capability.Subsequently,we developed a multimodal graph contrastive learning(GCL)model for the prediction of P-gp inhibitors and substrates(MC-PGP).This framework integrates three types of features from Simplified Molecular Input Line Entry System(SMILES)sequences,molecular fingerprints,and molecular graphs using an attention-based fusion strategy to generate a unified molecular representation.Furthermore,we employed a GCL approach to enhance structural representations by aligning local and global structures.Extensive experimental results highlight the superior performance of MC-PGP,which achieves improvements in the area under the curve of receiver operating characteristic(AUC-ROC)of 9.82%and 10.62%on the external P-gp inhibitor and external P-gp substrate datasets,respectively,compared with 12 state-of-the-art methods.Furthermore,the interpretability analysis of all three molecular feature types offers comprehensive and complementary insights,demonstrating that MC-PGP effectively identifies key functional groups involved in P-gp interactions.These chemically intuitive insights provide valuable guidance for the design and optimization of drug candidates.
基金Project supported by the National Key Research and Development Program(2022YFC3204900)Jiangsu Province Construction System Technology Project(2023ZD108)。
文摘Sulfamethoxazole(SMZ)is a prevalent and recalcitrant micropollutant in water,posing a significant threat to both aquatic organisms and human health.Therefore,investigating the removal of SMZ is of critical importance.In order to investigate the effect of rare earth metal doping on the performance of activated persulfate oxidative degradation of SMZ,BiFeO_(3)with different Ce doping amounts was successfully prepared by a hydrothermal method.Then,it was characterized by X-ray diffraction(XRD),scanning electron microscopy(SEM),scanning transmission electro n microscopy(STEM)and Brunauer-Emmett-Teller(BET)method.The performance of porous Ce/BiFeO_(3)in the catalytic activation of persulfate(PMS)for the degradation of SMZ in water was investigated using SMZ solution as a simulated wastewater.The impact of Ce doping rate,catalyst dosage,temperature variations,common anions,natural organic matter,and PMS concentration on SMZ removal was systematically evaluated.The characterization results show that the octahedral rhombic structure of Ce can be observed on the surface of this doped catalyst,and Ce doping does not change the crystalline shape of Ce/BiFeO_(3).The specific surface area of the doped catalyst increases,accompanied by an enlargement of pore size,thereby enhancing the catalyst's adsorption capacity and resistance to contamination by SMZ.Under the optimal conditions of 25℃,SMZ concentration of 20 mg/L,0.8 g/L PMS and 0.3 g/L 0.05Ce/BiFeO_(3)catalyst,the removal rate of SMZ reaches approximately 95%within35 min of reaction time.Even after five cycles of reuse,the degradation rate of SMZ remains above 88%,demonstrating the catalyst's good stability and reusability.Bursting experiments show that SO_(4)^(·-),·OH,1O_(2)and O_(2)^(·-)are involved in the catalytic degradation process,with 1O_(2)playing a dominant role.
基金financially supported by the Natural Science Foundation of China(Nos.22208214,22005190,and 21938005)the Science&Technology Commission of Shanghai Municipality(Nos.20QB1405700,and 19DZ1205500)Zhejiang Key Research and Development Program(No.2020C01128)
文摘Sodium-ion batteries(SIBs) are promising electrochemical energy storage systems as lithium-ion batteries by virtue of their similar chemical properties and natural abundance and availability.However,the ionic radius of Na^(+)is larger than that of Li^(+),leading to challenges in its insertion/extraction at anode side.As a class of anode materials,phosphorus allotropes(PAs,red,and black) and metal phosphides(MPs) have shown great prospects because of high theoretical gravimetric/volumetric capacity,high carrier mobility,and suitable redox potential.In this review,recent developments in the studies of PAs and MPs with particular emphasis on understanding sodium storage mechanisms,developing novel synthesis strategies,and performance validations have been manifested valuable solutions to address these challenges.We begin with the introduction and classification of the macroscopic sodiation mechanisms of PAs and MPs,and the various fabrication strategies of PAs and MPs are comprehensively summarized in second section.The third section thoroughly reviews the progresses on PAs and MPs-based advanced materials for their application in SIBs.Finally,we also discuss the significant challenges and outline a roadmap for future research directions.
基金Project(2022YFC2406000)supported by the National Key R&D Program,ChinaProject(2022GDASZH-2022010107)supported by the Guangdong Academy of Science,China+4 种基金Project(2019BT02C629)supported by the Guangdong Special Support Program,ChinaProject(2022GDASZH-2022010203-003)supported by the GDAS’project of Science and Technology Development,ChinaProjects(2023B1212120008,2023B1212060045)supported by the Guangdong Province Science and Technology Plan Projects,ChinaProject(2023TQ07Z559)supported by the Special Support Foundation of Guangdong Province,ChinaProject(52105293)supported by the National Natural Science Foundation of China。
文摘Laser powder-bed fusion(LPBF)of Zn-0.8Cu(wt.%)alloys exhibits significant advantages in the customization of biodegradable bone implants.However,the formability of LPBFed Zn alloy is not sufficient due to the spheroidization during the interaction of powder and laser beam,of which the mechanism is still not well understood.In this study,the evolution of morphology and grain structure of the LPBFed Zn-Cu alloy was investigated based on single-track deposition experiments.As the scanning speed increases,the grain structure of a single track of Zn-Cu alloy gradually refines,but the formability deteriorates,leading to the defect’s formation in the subsequent fabrication.The Zn-Cu alloys fabricated by optimum processing parameters exhibit a tensile strength of 157.13 MPa,yield strength of 106.48 MPa and elongation of 14.7%.This work provides a comprehensive understanding of the processing optimization of Zn-Cu alloy,achieving LPBFed Zn-Cu alloy with high density and excellent mechanical properties.
基金financially supported by the Provincial Natural Science Foundation of Hunan(Nos.2019JJ50831,2023JJ30505 and 2023JJ40541)the China Postdoctoral Science Foundation(Nos.2017M622597 and 2021M690591)+2 种基金the Open Research Fund Program of Fundamental Science on Radioactive Geology and Exploration Technology Laboratory(East China University of Technology)(No.2022RGET04)the National Foreign Expert Project(No.G2022029012L)the National Nature Science Foundation of China(No.41002022)。
文摘The Jiuyishan granitic complex,located in the Nanling Range,South China,is composed of five granitic plutons(Xuehuading,Jinjiling,Pangxiemu,Shaziling and Xishan).Zircon U-Pb dating of four plutons(Jinjiling,Pangxiemu,Shaziling and Xishan)yielded similar ages of approximately 153 Ma,indicating indistinguishable ages within error.Three plutons except the Shaziling pluton,have consistentε_(Nd)(t)(-7.8 to-5.8)andε_(Hf)(t)(-9.1 to-2.2)values,which are similar to those of the lower crustal granulitic metasedimentary and meta-igneous rocks in South China.Compared to other three plutons,the Shaziling pluton has consistentε_(Nd)(t)(-7.4 to-6.8)andε_(Hf)(t)(-7.5 to-4.7)values and shows similar source,but the Shaziling mafic microgranular enclaves(MMEs)show variableε_(Hf)(t)(-14.2 to 4.8)values,indicating a remarkable mantle magma injection of the Shaziling pluton.Zircon Ce/Sm-Yb/Gd,whole-rock CaO-P_(2)O_(5)and CaO-TiO_(2)linear trends reveal that from the Xishan to the Shaziling and from the Jinjiling to the Pangxiemu granites,they experienced apatite and titanite fractionation,respectively.Zircon Th,U,Nb,Ta,Hf,Ti,Y,P and rare earth element(REE)contents and whole-rock Sr,Ba and Rb contents also show that the Shaziling,Xishan,Jinjiling and Pangxiemu granites followed a discontinuous evolutionary series,but the Pangxiemu granites exhibit highly evolved nature.Four main controlling factors of W-Sn and rare metal mineralization in granitic rocks were discussed,and we found that the mineralization in Jiuyishan granitic complex was mainly controlled by the fractionation degree and crystallization temperature,but were rarely affected by oxygen fugacity and mantle material input.The Pangxiemu granites show particularly higher Rb and Ta contents than the other three plutons,implying that the ore deposits developed in the Jiuyishan Complex were directly related to the most evolved Pangxiemu pluton,with the occurrence of Rb and Ta as the most likely rare metal mineralization in the Jiuyishan District.A crystal mush model is proposed to interpret the petrogenetic and mineralizing processes of the Jiuyishan granitic complex.
文摘GH4350(AEREX 350)is a Ni-based wrought superalloy for high-performance fasteners,with a maximum service temperature of 750℃.It has high tensile strength,fatigue resistance,stress rupture and relaxation resistance,corrosion resistance,low thermal expansion,and notch sensitivity.The high strength of GH4350 is largely derived through solid solution strengthening and the γ′phase precipitation strengthening.During the precipitation of γ′phase,a minor amount ofηphase also precipitates.However,it is reported that the microstructure of alloy is sensitive to heat treatment parameters,including temperature and time.The γ′phases can be transformed intoηphases under certain conditions,potentially degrading the performance of the alloy.The chemical composition characteristics,heat treatment strategies,and strengthening mechanism of GH4350 were reviewed in this research,aiming to understand the factors behind its remarkable high-temperature performance,to guide the development of new alloys,and to further enhance its heat resistance.
基金National Natural Science Foundation of China(51975286)。
文摘Fe-Mo functionally graded materials(FGMs)with different composition-change rates from 100%304 stainless steel to 100%Mo along the composition gradient direction were prepared by electron beam-directed energy deposition(EB-DED)technique,including three samples with composition mutation of 100%,composition change rate of 10%and 30%.Results show that the composition-change rate significantly affects the microstructure and mechanical properties of the samples.In the sample with abrupt change of composition,the sharp shift in composition between 304 stainless steel and Mo leads to a great difference in the microstructure and hardness near the interface between the two materials.With the increase in the number of gradient layers,the composition changes continuously along the direction of deposition height,and the microstructure morphology shows a smooth transition from 304 stainless steel to Mo,which is gradually transformed from columnar crystal to dendritic crystal.Elements Fe,Mo,and other major elements transform linearly along the gradient direction,with sufficient interlayer diffusion between the deposited layers,leading to good metallurgical bonding.The smaller the change in composition gradient,the greater the microhardness value along the deposition direction.When the composition gradient is 10%,the gradient layer exhibits higher hardness(940 HV)and excellent resistance to surface abrasion,and the overall compressive properties of the samples are better,with the compressive fracture stress in the top region reaching 750.05±14 MPa.
文摘The application of legal texts in the context of digital television is a process that relies on several normative instruments,ranging from international treaties,such as those of the ITU(International Telecommunications Union),to national regulations defining the obligations of audiovisual operators and the modalities of consumer support.Many countries have introduced specific laws and regulations to organize the gradual switch-off of analog broadcasting and encourage the adoption of new digital standards.Consequently,the digitization of Guinea’s broadcasting network cannot be carried out without taking into account the legal framework:allocation of resources and broadcasting players.Analog and digital broadcasting,according to regulatory texts,shows the relationships between the different communication management structures.As for digital broadcasting,we note the appearance of a new service,multiplex.
基金support from the Full Bridge Fellowship for enabling the research stay at Virginia Tech.H.Xin acknowledge the financial support from the US Department of Energy,Office of Basic Energy Sciences under contract no.DE-SC0023323from the National Science Foundation through the grant 2245402 from CBET Catalysis and CDS&E programs.
文摘Knowledge graphs (KGs) offer a structured, machine-readable format for organizing complex information. In heterogeneous catalysis, where data on catalytic materials, reaction conditions, mechanisms, and synthesis routes are dispersed across diverse sources, KGs provide a semantic framework that supports data integration under the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This review aims to survey recent developments in catalysis KGs, describe the main techniques for graph construction, and highlight how artificial intelligence, particularly large language models (LLMs), enhances graph generation and query. We conducted a systematic analysis of the literature, focusing on ontology-guided text mining pipelines, graph population methods, and maintenance strategies. Our review identifies key trends: ontology-based approaches enable the automated extraction of domain knowledge, LLM-driven retrieval-augmented generation supports natural-language queries, and scalable graph architectures range from a few thousand to over a million triples. We discuss state-of-the-art applications, such as catalyst recommendation systems and reaction mechanism discovery tools, and examine the major challenges, including data heterogeneity, ontology alignment, and long-term graph curation. We conclude that KGs, when combined with AI methods, hold significant promise for accelerating catalyst discovery and knowledge management, but progress depends on establishing community standards for ontology development and maintenance. This review provides a roadmap for researchers seeking to leverage KGs to advance heterogeneous catalysis research.
文摘This paper introduces a computational cognitive architecture that serves as a comprehensive computational theory of the human mind,from cognitive science and computational psychology.The cognitive architecture(named Clarion)has been justified by,and validated against,psychological data,findings,and theoretical constructs.One important theoretical background for it is the dual-process theories,which led to its overall two-level structuring in a hybrid neuro-symbolic way.Furthermore,given the recent advances in AI and computing technology,LLMs are being incorporated into the model to better capture human intuition and instinct(and implicit processes in general),in order to further enhance Clarion.Integrating Clarion and LLMs can also help to develop AI systems that are more capable,more reliable,and more human-like.Overall,the paper advocates a multidisciplinary approach towards developing better models for cognitive science and for AI.
文摘Cashew processing in Côte d’Ivoire focuses only on the cashew nut, to the detriment of the apple. Only a very small proportion of the apple is processed into juice. The aim of this work is to enhance the value of cashew apples by transforming them into jam. Specifically, the aim was first to characterize the sensory properties of cashew apple jam formulations using baobab powder as a source of pectin and then to optimise the formulations. A Box-Behken design with pH, Sugar, and Baobab as factors was used to model and characterize the jam sensory descriptors, and a multivariate analysis with SensomineR was used to characterize the jam formulations. The desirability function was used to optimise the formulations. The results show globally significant regressions at the 0.05 threshold for the sensory descriptors Gelling, Brilliance, Smell, Sweetness, and (-)Astringency, with the exception of (-)Salinity. The R2 coefficients are greater than 80%. The factors studied could have effects on the sensory descriptors of cashew jam formulations. The Baobab had the main effect on the gelling, smell, and astringency of the jams. Brilliance depended on the added sugar. A product effect (p < 0.001) was observed for the descriptors Smell, Gelling, Brilliance, and Sweetness, as these allowed the panelists to find differences between the formulations. Optimum jam formulation can be achieved with 51.56% sugar and 2.12% Baobab at a pH of 3.15. Cashew apple jam using Baobab offers opportunities to add value to apples that have long been abandoned in the field. It would be important to find conditions for prolonged storage of this jam.
