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
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
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
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
Nowadays,the development of effective bioplastics aims to combine traditional plastics’functionality with environmentally friendly properties.The most effective and durable modern bioplastics are made from the edible...Nowadays,the development of effective bioplastics aims to combine traditional plastics’functionality with environmentally friendly properties.The most effective and durable modern bioplastics are made from the edible part of crops.This forces bioplastics to competewith food production because the crops that produce bioplastics can also be used for human nutrition.That is why the article’s main focus is on creating bioplastics using renewable,non-food raw materials(cellulose,lignin,etc.).Eco-friendly composites based on a renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch,and poly(lactic acid)with reed and hemp waste as a filler.The physic-chemical features of the structure and surface,as well as the technological characteristics of reed and hemp waste as the organic fillers for renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch,and poly(lactic acid),were studied.Theeffect of the fractional composition analysis,morphology,and nature of reed and hempwaste on the quality of the design of eco-friendly biodegradable composites and their ability to disperse in the matrix of renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch and poly(lactic acid)was carried out.The influence of different content and morphology of reed and hemp waste on the composite characteristics was investigated.It is shown that the most optimal direction for obtaining strong eco-friendly biodegradable composites based on a renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch,and poly(lactic acid)is associated with the use of waste reed stalks,with its optimal content at the level of 50 wt.%.展开更多
Enhancing wastewater treatment efficiency through innovative technologies is paramount in addressing global environmental challenges.This study explores utilizing stereoscopic hydrogel evaporators combined with renewa...Enhancing wastewater treatment efficiency through innovative technologies is paramount in addressing global environmental challenges.This study explores utilizing stereoscopic hydrogel evaporators combined with renewable energy sources to optimize wastewater treatment processes.A cross-linked super absorbent polymer(SAP)hydrogel was synthesized using acrylic acid and 2-hydroxyethyl methacrylate monomers and integrated with a light-absorbing carbon membrane to form a solar-assisted evaporator(MSAP).The MSAP achieved a high evaporation rate of 3.08 kg m^(-2)·h^(-1)and a photothermal conversion efficiency of 94.27%.It demonstrated excellent removal efficiency for dye-polluted wastewater,significantly reducing concentrations of pollutants.The MSAP maintained high performance in outdoor conditions,showcasing its potential for real-world applications.This approach,incorporating both solar and wind energy,significantly boosts water evaporation rates and presents a promising,eco-friendly solution for sustainable wastewater treatment within the circular development framework.展开更多
Power converters are essential components in modern life,being widely used in industry,automation,transportation,and household appliances.In many critical applications,their failure can lead not only to financial loss...Power converters are essential components in modern life,being widely used in industry,automation,transportation,and household appliances.In many critical applications,their failure can lead not only to financial losses due to operational downtime but also to serious risks to human safety.The capacitors forming the output filter,typically aluminumelectrolytic capacitors(AECs),are among the most critical and susceptible components in power converters.The electrolyte in AECs often evaporates over time,causing the internal resistance to rise and the capacitance to drop,ultimately leading to component failure.Detecting this fault requires measuring the current in the capacitor,rendering the method invasive and frequently impractical due to spatial constraints or operational limitations imposed by the integration of a current sensor in the capacitor branch.This article proposes the implementation of an online noninvasive fault diagnosis technique for estimating the Equivalent Series Resistance(ESR)and Capacitance(C)values of the capacitor,employing a combination of signal processing techniques(SPT)and machine learning(ML)algorithms.This solution relies solely on the converter’s input and output signals,therefore making it a non-invasive approach.The ML algorithm used was linear regression,applied to 27 attributes,21 of which were generated through feature engineering to enhance the model’s performance.The proposed solution demonstrates an R^(2) score greater than 0.99 in the estimation of both ESR and C.展开更多
Animal coloration has a wide range of biological functions and may be subject to different,sometimes conficting,selective pressures.In crustaceans,the evolution of coloration is relatively unstudied,despite the broad ...Animal coloration has a wide range of biological functions and may be subject to different,sometimes conficting,selective pressures.In crustaceans,the evolution of coloration is relatively unstudied,despite the broad range of colors and color patterns,which includes variability at multiple levels.Freshwater crayfsh are known to show color variability within species and populations,as well as intra-individual variability,but thefunction,if any,of crayfsh coloration is largely unknown.Here,I report on an experiment to understand patterns of color variability in the crayfsh Faxonius virilis and show that variation is strongly correlated to ontogenetic changes from a summer non-reproductive form to a fall reproductiveform.Crayfsh showed comparatively little inter-and intra-individual color variation in their non-reproductive form,but substantial variation at bothlevels in the reproductive form.Transition to the reproductive form was associated with the development of greener or bluer coloration localizedto the chelae on a subset of individuals,but these changes showed no clear correlation with sex or body size.Future investigations should focuson determining whether differences in color between individuals in the mating season are associated with any physiological or behavioral differences,or with differential susceptibility to predation.展开更多
In recent years,the new-style tea-drinking market has expanded rapidly.With the upgrading of consumer demands and the younger generation becoming the primary consumer group,the space experience centered around the“th...In recent years,the new-style tea-drinking market has expanded rapidly.With the upgrading of consumer demands and the younger generation becoming the primary consumer group,the space experience centered around the“third space”has become a crucial strategy for brands to differentiate themselves.This research focuses on the impact mechanism of spatial scenario design on the brand value of tea-drinking brands,aiming to explore the internal relationships among the key elements of spatial design,brand perception,consumers’emotional connection,and consumption willingness,providing theoretical support and practical references for scenario-based design in the industry.Through a combination of literature research and case-analysis methods,this study systematically reviews relevant domestic and international research on scenario-based design and brand value over the past five years.It selects representative brands as cases,deeply analyzes their spatial design strategies,user feedback,and market performance,and summarizes both successful experiences and existing problems.Scenario-based design is an important means to enhance the brand value of tea-drinking brands,but it needs to follow the four-in-one design principle of“brand consistency,functional diversity,experience coherence,and cost controllability.”In the future,brands should focus on the in-depth exploration and innovative expression of cultural elements,strengthen the multi-functional attributes of spaces,and achieve seamless integration of online and offline scenarios through digital means.In addition,it is recommended to adopt modular design to reduce scenario-updating costs and increase the return on investment.This research provides a theoretical basis and practical path for the optimization of the spatial design of tea-drinking brands,and has important reference value for promoting the high-quality development of the industry.展开更多
Steel cylindrical shells are widely used in engineering structures due to their high strength-to-weight ratio,but they are vulnerable to buckling under axial loads.To address this limitation,fiber-reinforced polymer(F...Steel cylindrical shells are widely used in engineering structures due to their high strength-to-weight ratio,but they are vulnerable to buckling under axial loads.To address this limitation,fiber-reinforced polymer(FRP)composites have emerged as promising materials for structural reinforcement.This study investigates the buckling behavior of steel cylindrical shells reinforced with inner and outer layers of polymer composite materials under axial compression.Using analytical and numerical modeling methods,the critical buckling loads for different reinforcement options were evaluated.Two-sided glass fiber reinforced plastic(GFRP)or carbon fiber reinforced plastic(CFRP)coatings,as well as combined coatings with layers of different composites,were considered.GFRP+CFRPIn the calculations,the coatings were treated as homogeneous orthotropic materials with equivalent averaged elastic characteristics.The numerical analysis revealed that CFRP reinforcement achieved the highest increase in buckling load,with improvements ranging from 9.84%to 47.29%,depending on the composite thickness and steel shell thickness.GFRP reinforcement,while beneficial,demonstrated a lower effectiveness,with buckling load increases between 5.89%and 19.30%.The hybrid reinforcement provided an optimal balance,improving buckling resistance by GFRP+CFRP6.94%to 43.95%.Statistical analysis further identified composite type and thickness as the most significant factors affecting buckling performance.The findings suggest that CFRP is the preferred reinforcement material,especially when applied to thin-walled cylindrical shells,while hybrid reinforcements can be effectively utilized for structures requiring a balance between stiffness and ductility.These insights provide a foundation for optimizing FRP reinforcement strategies to enhance the structural integrity of steel shells in engineering applications.展开更多
Polyamines(PAs)and ethylene are involved in the modulation of plant growth and development.However,their roles in fruit-set,especially in exogenous gibberellin(GA_(3))-induced grape parthenocarpic berries,and the rela...Polyamines(PAs)and ethylene are involved in the modulation of plant growth and development.However,their roles in fruit-set,especially in exogenous gibberellin(GA_(3))-induced grape parthenocarpic berries,and the related competitive action mode are poorly understood.For this,we,here performed their content determination,bioinformatics and expression pattern analysis of genes to identify the key ones in the competitive network of polyamines metabolic and ethylene biosynthesis(PMEB)pathways.The content of putrescine(Put)significantly increased;while 1-aminocyclopropanecarboxylic acid(ACC)sharply decreased during the fruit-set process of GA_(3)-induced grape parthenocarpic seedless berries.Totally,twenty-five genes in PMEB pathways,including 20 polyamines metabolic(PM)genes and 5 ethylene biosynthesis(EB)ones were identified in grape,of which 8 PM and 2 EB genes possessed the motifs responsive to phytohormone GA.The expression levels of most PMEB genes kept changing during grape fruit-set generating a competitive action mode of GA_(3)-mediated two metabolic fluxes toward PAs and ethylene synthesis.Exogenous GA_(3)might enhance grape fruit-set of parthenocarpic berries via up-regulation of VvSAMS4,VvSAMDC1/2,VvODC1,VvSPDS1,and VvPAO1 to promote PAs accumulation,whereby repressing the ethylene synthesis by down-regulation of VvACS1 and VvACO_(2).Our findings provide novel insights into GA_(3)-mediated competitive inhibition of ethylene by PAs to promote the fruit-set of parthenocarpic berries in grape,which has important implications for molecular breeding of seedless grape with high fruit-setting rate.展开更多
Objective:To analyze the clinical characteristics of bone loss in hospitalized patients with Graves’disease.Methods:The clinical data of hospitalized patients with Graves’disease were collected.According to the resu...Objective:To analyze the clinical characteristics of bone loss in hospitalized patients with Graves’disease.Methods:The clinical data of hospitalized patients with Graves’disease were collected.According to the results of bone density examinations,they were divided into a normal bone density group,a low bone mass group,and an osteoporosis group.The normal bone density group was used as the control group to analyze the clinical characteristics of bone loss.Results:The incidence of bone loss in patients with Graves’disease was 80.72%,with osteoporosis accounting for 39.16%and low bone mass accounting for 41.57%.The incidences of hyperthyroid heart disease,Graves’ophthalmopathy,and leukopenia in the osteoporosis group and the low bone mass group were significantly higher than those in the normal bone density group,reaching 84.62%,60.87%,and 34.38%,respectively(P<0.05).The age of the osteoporosis group with Graves’disease was 50.88±12.03 years old,which was higher than that of the normal bone density group(40.03±12.58 years old).The disease course was 55.66±14.21 days,longer than that of the normal bone density group(43.38±8.55 days).FT4 was 61.69±8.42 pmol/L,higher than that of the normal bone density group(51.01±6.77 pmol/L),while TSH was 0.08±0.51μIU/ml,lower than that of the normal bone density group(0.22±0.55μIU/ml).The blood phosphorus was 1.25±0.29 mmol/L,lower than that of the normal bone density group(1.34±0.27 mmol/L),with statistical significance(P<0.05).In the low bone mass group,FT3(13.08±9.05 pmol/L)and FT4(46.14±3.46 pmol/L)were lower than those in the normal bone density group,with statistical significance(P<0.05).Logistic regression analysis revealed that age,disease course,and TSH were contributing factors to bone loss.Conclusion:Patients with Graves’disease are prone to bone loss,and age,disease course,and TSH are contributing factors to bone loss.展开更多
Designing high-performance high-entropy alloys(HEAs)with transformation-induced plasticity(TRIP)or twinning-induced plasticity(TWIP)effects requires precise control over stacking fault energy(SFE)and phase stability.H...Designing high-performance high-entropy alloys(HEAs)with transformation-induced plasticity(TRIP)or twinning-induced plasticity(TWIP)effects requires precise control over stacking fault energy(SFE)and phase stability.However,the vast complexity of multicomponent systems poses a major challenge for identifying promising candidates through conventional experimental or computational methods.A high-throughput CALPHAD framework is developed to identify compositions with potential TWIP/TRIP behaviors in the Cr-Co-Ni and Cr-Co-Ni-Fe systems through systematic screening of stacking fault energy(SFE),FCC phase stability,and FCC-to-HCP transition temperatures(T0).The approach combines TC-Python automation with parallel Gibbs energy calculations across hundreds of thousands of compositions,enabling efficient extraction of metastable FCC-dominant alloys.The high-throughput results find 214 compositions with desired properties from 160,000 candidates.Detailed analysis of the Gibbs energy distributions,phase fraction trends,and temperature-dependent SFE evolution reveals critical insights into the thermodynamic landscape governing plasticity mechanisms in HEAs.The results show that only a narrow region of the compositional space satisfies all screening criteria,emphasizing the necessity of an integrated approach.The screened compositions and trends provide a foundation for targeted experimental validation.Furthermore,this work demonstrates a scalable,composition-resolved strategy for predicting deformation mechanisms in multicomponent alloys and offers a blueprint for integrating thermodynamic screening with mechanistic understanding in HEA design.展开更多
This paper analyzes the current research status of job satisfaction among obstetric nurses at home and abroad,including research methods,influencing factors,correlation relationships,and countermeasures to improve job...This paper analyzes the current research status of job satisfaction among obstetric nurses at home and abroad,including research methods,influencing factors,correlation relationships,and countermeasures to improve job satisfaction of obstetric nurses.It aims to provide a reference for subsequent studies on job satisfaction of obstetric nurses.展开更多
In the dynamic scene of autonomous vehicles,the depth estimation of monocular cameras often faces the problem of inaccurate edge depth estimation.To solve this problem,we propose an unsupervised monocular depth estima...In the dynamic scene of autonomous vehicles,the depth estimation of monocular cameras often faces the problem of inaccurate edge depth estimation.To solve this problem,we propose an unsupervised monocular depth estimation model based on edge enhancement,which is specifically aimed at the depth perception challenge in dynamic scenes.The model consists of two core networks:a deep prediction network and a motion estimation network,both of which adopt an encoder-decoder architecture.The depth prediction network is based on the U-Net structure of ResNet18,which is responsible for generating the depth map of the scene.The motion estimation network is based on the U-Net structure of Flow-Net,focusing on the motion estimation of dynamic targets.In the decoding stage of the motion estimation network,we innovatively introduce an edge-enhanced decoder,which integrates a convolutional block attention module(CBAM)in the decoding process to enhance the recognition ability of the edge features of moving objects.In addition,we also designed a strip convolution module to improve the model’s capture efficiency of discrete moving targets.To further improve the performance of the model,we propose a novel edge regularization method based on the Laplace operator,which effectively accelerates the convergence process of themodel.Experimental results on the KITTI and Cityscapes datasets show that compared with the current advanced dynamic unsupervised monocular model,the proposed model has a significant improvement in depth estimation accuracy and convergence speed.Specifically,the rootmean square error(RMSE)is reduced by 4.8%compared with the DepthMotion algorithm,while the training convergence speed is increased by 36%,which shows the superior performance of the model in the depth estimation task in dynamic scenes.展开更多
As the number and complexity of sensors in autonomous vehicles continue to rise,multimodal fusionbased object detection algorithms are increasingly being used to detect 3D environmental information,significantly advan...As the number and complexity of sensors in autonomous vehicles continue to rise,multimodal fusionbased object detection algorithms are increasingly being used to detect 3D environmental information,significantly advancing the development of perception technology in autonomous driving.To further promote the development of fusion algorithms and improve detection performance,this paper discusses the advantages and recent advancements of multimodal fusion-based object detection algorithms.Starting fromsingle-modal sensor detection,the paper provides a detailed overview of typical sensors used in autonomous driving and introduces object detection methods based on images and point clouds.For image-based detection methods,they are categorized into monocular detection and binocular detection based on different input types.For point cloud-based detection methods,they are classified into projection-based,voxel-based,point cluster-based,pillar-based,and graph structure-based approaches based on the technical pathways for processing point cloud features.Additionally,multimodal fusion algorithms are divided into Camera-LiDAR fusion,Camera-Radar fusion,Camera-LiDAR-Radar fusion,and other sensor fusion methods based on the types of sensors involved.Furthermore,the paper identifies five key future research directions in this field,aiming to provide insights for researchers engaged in multimodal fusion-based object detection algorithms and to encourage broader attention to the research and application of multimodal fusion-based object detection.展开更多
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.
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.
文摘Nowadays,the development of effective bioplastics aims to combine traditional plastics’functionality with environmentally friendly properties.The most effective and durable modern bioplastics are made from the edible part of crops.This forces bioplastics to competewith food production because the crops that produce bioplastics can also be used for human nutrition.That is why the article’s main focus is on creating bioplastics using renewable,non-food raw materials(cellulose,lignin,etc.).Eco-friendly composites based on a renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch,and poly(lactic acid)with reed and hemp waste as a filler.The physic-chemical features of the structure and surface,as well as the technological characteristics of reed and hemp waste as the organic fillers for renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch,and poly(lactic acid),were studied.Theeffect of the fractional composition analysis,morphology,and nature of reed and hempwaste on the quality of the design of eco-friendly biodegradable composites and their ability to disperse in the matrix of renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch and poly(lactic acid)was carried out.The influence of different content and morphology of reed and hemp waste on the composite characteristics was investigated.It is shown that the most optimal direction for obtaining strong eco-friendly biodegradable composites based on a renewable bioplastic blend of polybutylene adipate-co-terephthalate,corn starch,and poly(lactic acid)is associated with the use of waste reed stalks,with its optimal content at the level of 50 wt.%.
基金financially supported by the“Qing-Lan”Project of Jiangsu ProvinceTop-notch Academic Programs Project of Jiangsu Higher Education Institutions(TAPP)the start-up fund from Yangzhou University。
文摘Enhancing wastewater treatment efficiency through innovative technologies is paramount in addressing global environmental challenges.This study explores utilizing stereoscopic hydrogel evaporators combined with renewable energy sources to optimize wastewater treatment processes.A cross-linked super absorbent polymer(SAP)hydrogel was synthesized using acrylic acid and 2-hydroxyethyl methacrylate monomers and integrated with a light-absorbing carbon membrane to form a solar-assisted evaporator(MSAP).The MSAP achieved a high evaporation rate of 3.08 kg m^(-2)·h^(-1)and a photothermal conversion efficiency of 94.27%.It demonstrated excellent removal efficiency for dye-polluted wastewater,significantly reducing concentrations of pollutants.The MSAP maintained high performance in outdoor conditions,showcasing its potential for real-world applications.This approach,incorporating both solar and wind energy,significantly boosts water evaporation rates and presents a promising,eco-friendly solution for sustainable wastewater treatment within the circular development framework.
文摘Power converters are essential components in modern life,being widely used in industry,automation,transportation,and household appliances.In many critical applications,their failure can lead not only to financial losses due to operational downtime but also to serious risks to human safety.The capacitors forming the output filter,typically aluminumelectrolytic capacitors(AECs),are among the most critical and susceptible components in power converters.The electrolyte in AECs often evaporates over time,causing the internal resistance to rise and the capacitance to drop,ultimately leading to component failure.Detecting this fault requires measuring the current in the capacitor,rendering the method invasive and frequently impractical due to spatial constraints or operational limitations imposed by the integration of a current sensor in the capacitor branch.This article proposes the implementation of an online noninvasive fault diagnosis technique for estimating the Equivalent Series Resistance(ESR)and Capacitance(C)values of the capacitor,employing a combination of signal processing techniques(SPT)and machine learning(ML)algorithms.This solution relies solely on the converter’s input and output signals,therefore making it a non-invasive approach.The ML algorithm used was linear regression,applied to 27 attributes,21 of which were generated through feature engineering to enhance the model’s performance.The proposed solution demonstrates an R^(2) score greater than 0.99 in the estimation of both ESR and C.
文摘Animal coloration has a wide range of biological functions and may be subject to different,sometimes conficting,selective pressures.In crustaceans,the evolution of coloration is relatively unstudied,despite the broad range of colors and color patterns,which includes variability at multiple levels.Freshwater crayfsh are known to show color variability within species and populations,as well as intra-individual variability,but thefunction,if any,of crayfsh coloration is largely unknown.Here,I report on an experiment to understand patterns of color variability in the crayfsh Faxonius virilis and show that variation is strongly correlated to ontogenetic changes from a summer non-reproductive form to a fall reproductiveform.Crayfsh showed comparatively little inter-and intra-individual color variation in their non-reproductive form,but substantial variation at bothlevels in the reproductive form.Transition to the reproductive form was associated with the development of greener or bluer coloration localizedto the chelae on a subset of individuals,but these changes showed no clear correlation with sex or body size.Future investigations should focuson determining whether differences in color between individuals in the mating season are associated with any physiological or behavioral differences,or with differential susceptibility to predation.
文摘In recent years,the new-style tea-drinking market has expanded rapidly.With the upgrading of consumer demands and the younger generation becoming the primary consumer group,the space experience centered around the“third space”has become a crucial strategy for brands to differentiate themselves.This research focuses on the impact mechanism of spatial scenario design on the brand value of tea-drinking brands,aiming to explore the internal relationships among the key elements of spatial design,brand perception,consumers’emotional connection,and consumption willingness,providing theoretical support and practical references for scenario-based design in the industry.Through a combination of literature research and case-analysis methods,this study systematically reviews relevant domestic and international research on scenario-based design and brand value over the past five years.It selects representative brands as cases,deeply analyzes their spatial design strategies,user feedback,and market performance,and summarizes both successful experiences and existing problems.Scenario-based design is an important means to enhance the brand value of tea-drinking brands,but it needs to follow the four-in-one design principle of“brand consistency,functional diversity,experience coherence,and cost controllability.”In the future,brands should focus on the in-depth exploration and innovative expression of cultural elements,strengthen the multi-functional attributes of spaces,and achieve seamless integration of online and offline scenarios through digital means.In addition,it is recommended to adopt modular design to reduce scenario-updating costs and increase the return on investment.This research provides a theoretical basis and practical path for the optimization of the spatial design of tea-drinking brands,and has important reference value for promoting the high-quality development of the industry.
文摘Steel cylindrical shells are widely used in engineering structures due to their high strength-to-weight ratio,but they are vulnerable to buckling under axial loads.To address this limitation,fiber-reinforced polymer(FRP)composites have emerged as promising materials for structural reinforcement.This study investigates the buckling behavior of steel cylindrical shells reinforced with inner and outer layers of polymer composite materials under axial compression.Using analytical and numerical modeling methods,the critical buckling loads for different reinforcement options were evaluated.Two-sided glass fiber reinforced plastic(GFRP)or carbon fiber reinforced plastic(CFRP)coatings,as well as combined coatings with layers of different composites,were considered.GFRP+CFRPIn the calculations,the coatings were treated as homogeneous orthotropic materials with equivalent averaged elastic characteristics.The numerical analysis revealed that CFRP reinforcement achieved the highest increase in buckling load,with improvements ranging from 9.84%to 47.29%,depending on the composite thickness and steel shell thickness.GFRP reinforcement,while beneficial,demonstrated a lower effectiveness,with buckling load increases between 5.89%and 19.30%.The hybrid reinforcement provided an optimal balance,improving buckling resistance by GFRP+CFRP6.94%to 43.95%.Statistical analysis further identified composite type and thickness as the most significant factors affecting buckling performance.The findings suggest that CFRP is the preferred reinforcement material,especially when applied to thin-walled cylindrical shells,while hybrid reinforcements can be effectively utilized for structures requiring a balance between stiffness and ductility.These insights provide a foundation for optimizing FRP reinforcement strategies to enhance the structural integrity of steel shells in engineering applications.
基金supported by grants from Jiangsu province seed industry revitalization of the leading project(JBGS[2021]086)the National Natural Science Funds(31972373,32272647,32202433)+1 种基金the Provincial Natural Science Foundation of Jiangsu(BK20200541)the Priority Academic Program Development of Jiangsu Higher Education Institutions,China(PAPD),and Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(KYCX22_0754,SJCX23-0209).
文摘Polyamines(PAs)and ethylene are involved in the modulation of plant growth and development.However,their roles in fruit-set,especially in exogenous gibberellin(GA_(3))-induced grape parthenocarpic berries,and the related competitive action mode are poorly understood.For this,we,here performed their content determination,bioinformatics and expression pattern analysis of genes to identify the key ones in the competitive network of polyamines metabolic and ethylene biosynthesis(PMEB)pathways.The content of putrescine(Put)significantly increased;while 1-aminocyclopropanecarboxylic acid(ACC)sharply decreased during the fruit-set process of GA_(3)-induced grape parthenocarpic seedless berries.Totally,twenty-five genes in PMEB pathways,including 20 polyamines metabolic(PM)genes and 5 ethylene biosynthesis(EB)ones were identified in grape,of which 8 PM and 2 EB genes possessed the motifs responsive to phytohormone GA.The expression levels of most PMEB genes kept changing during grape fruit-set generating a competitive action mode of GA_(3)-mediated two metabolic fluxes toward PAs and ethylene synthesis.Exogenous GA_(3)might enhance grape fruit-set of parthenocarpic berries via up-regulation of VvSAMS4,VvSAMDC1/2,VvODC1,VvSPDS1,and VvPAO1 to promote PAs accumulation,whereby repressing the ethylene synthesis by down-regulation of VvACS1 and VvACO_(2).Our findings provide novel insights into GA_(3)-mediated competitive inhibition of ethylene by PAs to promote the fruit-set of parthenocarpic berries in grape,which has important implications for molecular breeding of seedless grape with high fruit-setting rate.
文摘Objective:To analyze the clinical characteristics of bone loss in hospitalized patients with Graves’disease.Methods:The clinical data of hospitalized patients with Graves’disease were collected.According to the results of bone density examinations,they were divided into a normal bone density group,a low bone mass group,and an osteoporosis group.The normal bone density group was used as the control group to analyze the clinical characteristics of bone loss.Results:The incidence of bone loss in patients with Graves’disease was 80.72%,with osteoporosis accounting for 39.16%and low bone mass accounting for 41.57%.The incidences of hyperthyroid heart disease,Graves’ophthalmopathy,and leukopenia in the osteoporosis group and the low bone mass group were significantly higher than those in the normal bone density group,reaching 84.62%,60.87%,and 34.38%,respectively(P<0.05).The age of the osteoporosis group with Graves’disease was 50.88±12.03 years old,which was higher than that of the normal bone density group(40.03±12.58 years old).The disease course was 55.66±14.21 days,longer than that of the normal bone density group(43.38±8.55 days).FT4 was 61.69±8.42 pmol/L,higher than that of the normal bone density group(51.01±6.77 pmol/L),while TSH was 0.08±0.51μIU/ml,lower than that of the normal bone density group(0.22±0.55μIU/ml).The blood phosphorus was 1.25±0.29 mmol/L,lower than that of the normal bone density group(1.34±0.27 mmol/L),with statistical significance(P<0.05).In the low bone mass group,FT3(13.08±9.05 pmol/L)and FT4(46.14±3.46 pmol/L)were lower than those in the normal bone density group,with statistical significance(P<0.05).Logistic regression analysis revealed that age,disease course,and TSH were contributing factors to bone loss.Conclusion:Patients with Graves’disease are prone to bone loss,and age,disease course,and TSH are contributing factors to bone loss.
基金supported by the U.S.Army Research Laboratory through their award#W911NF-22-2-0040the Ministry of Education,Youth and Sports of the Czech Republic through the e-INFRA CZ(ID:90254).
文摘Designing high-performance high-entropy alloys(HEAs)with transformation-induced plasticity(TRIP)or twinning-induced plasticity(TWIP)effects requires precise control over stacking fault energy(SFE)and phase stability.However,the vast complexity of multicomponent systems poses a major challenge for identifying promising candidates through conventional experimental or computational methods.A high-throughput CALPHAD framework is developed to identify compositions with potential TWIP/TRIP behaviors in the Cr-Co-Ni and Cr-Co-Ni-Fe systems through systematic screening of stacking fault energy(SFE),FCC phase stability,and FCC-to-HCP transition temperatures(T0).The approach combines TC-Python automation with parallel Gibbs energy calculations across hundreds of thousands of compositions,enabling efficient extraction of metastable FCC-dominant alloys.The high-throughput results find 214 compositions with desired properties from 160,000 candidates.Detailed analysis of the Gibbs energy distributions,phase fraction trends,and temperature-dependent SFE evolution reveals critical insights into the thermodynamic landscape governing plasticity mechanisms in HEAs.The results show that only a narrow region of the compositional space satisfies all screening criteria,emphasizing the necessity of an integrated approach.The screened compositions and trends provide a foundation for targeted experimental validation.Furthermore,this work demonstrates a scalable,composition-resolved strategy for predicting deformation mechanisms in multicomponent alloys and offers a blueprint for integrating thermodynamic screening with mechanistic understanding in HEA design.
文摘This paper analyzes the current research status of job satisfaction among obstetric nurses at home and abroad,including research methods,influencing factors,correlation relationships,and countermeasures to improve job satisfaction of obstetric nurses.It aims to provide a reference for subsequent studies on job satisfaction of obstetric nurses.
基金funded by the Yangtze River Delta Science and Technology Innovation Community Joint Research Project(2023CSJGG1600)the Natural Science Foundation of Anhui Province(2208085MF173)Wuhu“ChiZhu Light”Major Science and Technology Project(2023ZD01,2023ZD03).
文摘In the dynamic scene of autonomous vehicles,the depth estimation of monocular cameras often faces the problem of inaccurate edge depth estimation.To solve this problem,we propose an unsupervised monocular depth estimation model based on edge enhancement,which is specifically aimed at the depth perception challenge in dynamic scenes.The model consists of two core networks:a deep prediction network and a motion estimation network,both of which adopt an encoder-decoder architecture.The depth prediction network is based on the U-Net structure of ResNet18,which is responsible for generating the depth map of the scene.The motion estimation network is based on the U-Net structure of Flow-Net,focusing on the motion estimation of dynamic targets.In the decoding stage of the motion estimation network,we innovatively introduce an edge-enhanced decoder,which integrates a convolutional block attention module(CBAM)in the decoding process to enhance the recognition ability of the edge features of moving objects.In addition,we also designed a strip convolution module to improve the model’s capture efficiency of discrete moving targets.To further improve the performance of the model,we propose a novel edge regularization method based on the Laplace operator,which effectively accelerates the convergence process of themodel.Experimental results on the KITTI and Cityscapes datasets show that compared with the current advanced dynamic unsupervised monocular model,the proposed model has a significant improvement in depth estimation accuracy and convergence speed.Specifically,the rootmean square error(RMSE)is reduced by 4.8%compared with the DepthMotion algorithm,while the training convergence speed is increased by 36%,which shows the superior performance of the model in the depth estimation task in dynamic scenes.
基金funded by the Yangtze River Delta Science and Technology Innovation Community Joint Research Project(2023CSJGG1600)the Natural Science Foundation of Anhui Province(2208085MF173)Wuhu“ChiZhu Light”Major Science and Technology Project(2023ZD01,2023ZD03).
文摘As the number and complexity of sensors in autonomous vehicles continue to rise,multimodal fusionbased object detection algorithms are increasingly being used to detect 3D environmental information,significantly advancing the development of perception technology in autonomous driving.To further promote the development of fusion algorithms and improve detection performance,this paper discusses the advantages and recent advancements of multimodal fusion-based object detection algorithms.Starting fromsingle-modal sensor detection,the paper provides a detailed overview of typical sensors used in autonomous driving and introduces object detection methods based on images and point clouds.For image-based detection methods,they are categorized into monocular detection and binocular detection based on different input types.For point cloud-based detection methods,they are classified into projection-based,voxel-based,point cluster-based,pillar-based,and graph structure-based approaches based on the technical pathways for processing point cloud features.Additionally,multimodal fusion algorithms are divided into Camera-LiDAR fusion,Camera-Radar fusion,Camera-LiDAR-Radar fusion,and other sensor fusion methods based on the types of sensors involved.Furthermore,the paper identifies five key future research directions in this field,aiming to provide insights for researchers engaged in multimodal fusion-based object detection algorithms and to encourage broader attention to the research and application of multimodal fusion-based object detection.
