Based on the EAM potential, a molecular dynamics study on the tensile properties of ultrathin nickel nanowires in the （100〉 orientation with diameters of 3.94, 4.95 and 5.99 nm was presented at different temperature...Based on the EAM potential, a molecular dynamics study on the tensile properties of ultrathin nickel nanowires in the （100〉 orientation with diameters of 3.94, 4.95 and 5.99 nm was presented at different temperatures and strain rates. The temperature and strain rate dependences of tensile properties were investigated. The simulation results show that the elastic modulus and the yield strength are gradually decreasing with the increase of temperature, while with the increase of the strain rate, the stress--strain curves fluctuate more intensely and the ultrathin nickel nanowires rupture at one smaller and smaller strain. At an ideal temperature of 0.01 K, the yield strength of the nanowires drops rapidly with the increase of strain rate, and at other temperatures the strain rate has a little influence on the elastic modulus and the yield strength. Finally, the effects of size on the tensile properties of ultrathin nickel nanowires were briefly discussed.展开更多
Osteocytes, the most abundant bone cells, form an interconnected network in the lacunar-canalicular pore system （LCS） buried within the mineralized matrix, which allows osteocytes to obtain nutrients from the blood ...Osteocytes, the most abundant bone cells, form an interconnected network in the lacunar-canalicular pore system （LCS） buried within the mineralized matrix, which allows osteocytes to obtain nutrients from the blood supply, sense external mechanical signals, and communicate among themselves and with other cells on bone surfaces. In this study, we examined key features of the LCS network including the topological parameter and the detailed structure of individual connections and their variations in cortical and cancellous compa~ tments, at different ages, and in two disease conditions with altered mechanosensing （perlecan deficiency and diabetes）. LCS network showed both topological stability, in terms of conservation of connectivity among osteocyte lacunae （similar to the ＂nodes＂ in a computer network）, and considerable variability the pericellular annular fluid gap surrounding lacunae and canaliculi （similar to the ＂bandwidth＂ of individual links in a computer network）. Age, in the range of our study （15-32 weeks）, affected only the pericellular fluid annulus in cortical bone but not in cancellous bone. Diabetes impacted the spacing of the lacunae, while the perlecan deficiency had a profound influence on the pericellular fluid annulus. The LCS network features play important roles in osteocyte signaling and regulation of bone growth and adaptation.展开更多
Thermal behavior of bulk amorphous sulfur is investigated by in situ temperature measurements at high pressures of 0.9, 1.4 and 2.1 GPa, and under different heating rates of 8, 10 and 12K/min at 0.9 GPa. The results s...Thermal behavior of bulk amorphous sulfur is investigated by in situ temperature measurements at high pressures of 0.9, 1.4 and 2.1 GPa, and under different heating rates of 8, 10 and 12K/min at 0.9 GPa. The results show that the onset temperature of the transition from the supercooled Hquid to the liquid state for sulfur increases with the pressure and the heating rate. It is deduced that the transition does not follow the Clapeyron equation, indicating considerable coupling of the molecular structure change in the transition. Along with the data at ambient pressure and high pressure, we present a dynamic diagram to demonstrate the relationship between the amorphous solid, supercooled liquid, liquid, and crystal phases of sulfur, and suggest an experimental approach to establish pressure-temperature-time transition diagrams for supercooled liquid and liquid.展开更多
In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, the...In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, then the temperature dependences are determined by the series of extracted temperature coefficients, based on the established temperature for- mulas for corresponding model parameters. The proposed method is validated by a 1x 0.2 x 16 μm2 SiGe HBT over a wide temperature range （from 218 K to 473 K）, and good matching is obtained between the extracted and modeled resuits. Therefore, we believe that the proposed extraction flow of model parameter temperature dependence is reliable for characterizing the transistor performance and guiding the circuit design over a wide temperature range.展开更多
First-order Raman scatterings of hexagonal GaN layers deposited by the hydride vapour phase epitaxy and by metal-organic chemical vapour deposition on SiC and sapphire substrates are studied in a temperature range bet...First-order Raman scatterings of hexagonal GaN layers deposited by the hydride vapour phase epitaxy and by metal-organic chemical vapour deposition on SiC and sapphire substrates are studied in a temperature range between 303 K and 503 K. The temperature dependences of two GaN Raman modes （Al （LO） and E2 （high）） are obtained. We focus our attention on the temperature dependence of E2 （high） mode and find that for different types of GaN epilayers their temperature dependences are somewhat different. We compare their differences and give them an explanation. The simplified formulas we obtained are in good accordance with experiment data. The results can be used to determine the temperature of a GaN sample.展开更多
Short-term taxi demand forecasting is of great importance to incentivize vacant cars moving from over-supply regions to over-demand regions,which can minimize the wait time for passengers and drivers.With the consider...Short-term taxi demand forecasting is of great importance to incentivize vacant cars moving from over-supply regions to over-demand regions,which can minimize the wait time for passengers and drivers.With the consideration of spatiotemporal dependences,this study proposes a multi-task deep learning(MTDL)model to predict short-term taxi demand in multi-zone level.The nonlinear Granger causality test is applied to explore the causality relationships among various traffic zones,and long short-term memory(LSTM)is used as the core neural unit to construct the framework of the multi-task deep learning model.In addition,several hyperparameter optimization methods(e.g.,grid search,random search,Bayesian optimization,hyperopt)are used to tune the model.Using the taxi trip data in New York City for validation,the multi-task deep learning model considering spatiotemporal dependences(MTDL*)is compared with the single-task deep learning model(STDL),the full-connected multi-task deep learning model(MTDL#)and other benchmark algorithms(such as LSTM,support vector machine(SVM)and k-nearest neighbors(k-NN)).The experiment results show that the proposed MTDL model is promising to predict short-term taxi demand in multi-zone level,the nonlinear Granger causality analysis is able to capture the spatiotemporal correlations among various traffic zones,and the Bayesian optimization is superior to the other three methods,which verified the feasibility and adaptability of the proposed method.展开更多
A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescenc...A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescence(TADF)properties.All calculations were performed using density functional theory(DFT)and time‑dependent density functional theory(TDDFT).Calculations for electronic structures,frontier molecular orbital characteristics(which determine the efficiency roll‑off effect of the complexes),and photophysical properties were conducted using the Gaussian 09 software package.The calculation of spin‑orbit coupling matrix elements<T|HSOC|S>,which determine the TADF properties of the complexes,was performed using the ORCA software package.The calculation results show that the auxiliary ligand tetraphenylimidodiphosphinate(tpip),a strong electron‑withdrawing group,can mitigate the efficiency roll‑off effect of the complex.Furthermore,TADF is observed in one of the designed complexes,(F_(3)Phppy)_(2)Ir(tpip),where F_(3)Phppy=2‑[4‑(2,4,6‑trifluorophenyl)phenyl]pyridine.展开更多
Background:This study aims to investigate the underlying mechanisms between parental marital conflict and adolescent short video dependence by constructing a chain mediation model,focusing on the mediating roles of ex...Background:This study aims to investigate the underlying mechanisms between parental marital conflict and adolescent short video dependence by constructing a chain mediation model,focusing on the mediating roles of experiential avoidance and emotional disturbance(anxiety,depression,and stress).Methods:Conducted in January 2025,the research recruited 4125 adolescents from multiple Chinese provinces through convenience sampling;after data cleaning,3957 valid participants(1959 males,1998 females)were included.Using a cross-sectional design,measures included parental marital conflict,experiential avoidance,anxiety,depression,stress,and short video dependence.Results:Pearson correlation analysis revealed significant positive correlations among all variables.Mediation analysis using the SPSS PROCESS macro showed that parental marital conflict directly predicted short video dependence(β=0.269,p<0.001),and also significantly predicted experiential avoidance(β=0.519,p<0.001),anxiety(β=0.072,p<0.001),depression(β=0.067,p<0.001),and stress(β=0.048,p<0.05).Experiential avoidance further predicted anxiety(β=0.521,p<0.001),depression(β=0.489,p<0.001),stress(β=0.408,p<0.001),and short video dependence(β=0.244,p<0.001).While both anxiety(β=0.050,p<0.05)and depression(β=0.116,p<0.001)positively predicted short video dependence,stress did not(β=0.019,p=0.257).Overall,experiential avoidance,anxiety,depression,and stress significantly mediated the relationship between parental marital conflict and short video dependence.Conclusion:These findings confirm that parental marital conflict not only directly influences adolescent short video dependence but also operates through a chain mediation pathway involving experiential avoidance and emotional disturbance,highlighting central psychological mechanisms and providing theoretical support for integrated mental health and behavioral interventions.展开更多
Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is l...Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is limited.Through uniaxial compression tests and split Hopkinson pressure bar(SHPB)impact tests,the dynamic compressive mechanical properties and fracture mechanisms of conglomerate rock were studied.Nanoindentation and high-resolution X-ray computed tomography were employed to analyze the micro-mechanical behavior and internal structure of the conglomerate rock.Results indicate significant differences in mechanical properties between different gravel particles and cementing materials,with initial fractures primarily distributed at the gravel-cement interfaces.The dynamic mechanical properties of conglomerate rocks exhibit a clear strain rate dependency.Based on the stress−strain curves and failure characteristics,the dynamic compressive mechanical behavior can be categorized into two types using a critical strain rate.The dynamic compressive strength,peak strain,and toughness of conglomerate rock increased with the strain rate,with the strength at 54 s−1 being 2.6 times that at 6 s−1.The dynamic compressive fracture mechanism of conglomerate rock is related to the strain rate and microstructure;at low strain rates,gravel distribution is the key factor,whereas at high strain rates,gravel content becomes critical.展开更多
Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving re...Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving responsibilities often results in burnout,adding to the burden on caregivers.This issue also affects society and healthcare systems through increased costs and greater demands for support services.Understanding the factors contributing to caregiver burden is crucial for creating effective interventions to address these challenges.The aim of this study is to describe the extent of caregiver burden and identify some factors related to burden among caregivers of chronically ill elderly people.By gaining insight into these relationships,this study seeks to identify strategies to reduce the burden on caregivers.Methods:This study utilized a cross-sectional design to examine caregivers of the elderly with chronic diseases receiving treatment in the public healthcare facility.Data collection involved administering structured questionnaires that gathered information on the demographic characteristics of both the elderly and their caregivers,the level of social support received,the functional status of patients as measured by daily activity indices,and the level of caregiver burden.Description was used to elaborate the characteristics of participants.Mann-Whitney,Kruskal-Wallis,and Spearman's correlation test were applied to explore the relationship between variables.Statistical significance was determined at P value<0.05.Results:Caregivers of the elderly with chronic diseases had a moderate care burden score(22.62±11.24,CI:95%).The patients'level of dependence,relationship with the patients,and time spent as a caregiver were factors related to caregiver burden(P<0.05).Conclusions:Those who care for elderly people with chronic diseases suffered great burden.The finding had found a number of factors that influence the caregivers'weight loss.Healthcare providers should consider these relevant factors when developing intervention plans to reduce caregiver burden.展开更多
Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usu...Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.展开更多
Distributions of nuclear magnetic resonance(NMR)relaxation times provide detailed information about the water in wood.This study documents the water dynamics analysis of T_(2)and T_(1)distributions for saturated delig...Distributions of nuclear magnetic resonance(NMR)relaxation times provide detailed information about the water in wood.This study documents the water dynamics analysis of T_(2)and T_(1)distributions for saturated delignified sapwood(DSW),delignified heartwood(DHW)and lignocellulose(LC)samples at different temperatures.Results indicate that below the freezing point of bulk water,free water freezes,causing its signal to disappear from the distribution.Then,the low temperature distributions of the unfrozen bound water contain more information about its components,with DSW,DHW and LC containing two distinct states of bound water(OH bound water(B-water)and more freely bound water(C-water)).Furthermore,it was observed that within the temperature range of−3°C to−60°C,B-water in DSW,DHW and LC maintained a higher unfrozen water content(UWC)value than C-water,and the T_(1)/T_(2)ratios for B-water were consistently higher than that for C-water,indicating that B-water has a greater antifreeze capacity.T_(2)and T_(1)distributions offer different kinds of information about water components,and all peaks within the distribution have been assigned.展开更多
The coexistence of emerging containments,such as antibiotic resistant bacteria(ARB),antibiotic-resistant genes(ARGs)and antibiotics,potentially influence elimination efficiencies in UV light-emitting diode(UV-LED)alon...The coexistence of emerging containments,such as antibiotic resistant bacteria(ARB),antibiotic-resistant genes(ARGs)and antibiotics,potentially influence elimination efficiencies in UV light-emitting diode(UV-LED)alone and UV-LED/H_(2)O_(2) system as their complex interactions.Tetracycline(TC)degradation efficiency(kF)correlated closely with its UV molar absorbance(R^(2)=0.831)in UV-LED alone system and with·OH yield(R^(2)=0.999)in UV-LED/H_(2)O_(2) system across studied wavelengths(265,280 and 310 nm).The kF values for intracellular DNA(i-ARGs)also exhibited a high correlation with UV-LED wavelengths in both systems(R^(2)=0.997-0.999).The coexistence of TC and ARB/ARGs resulted in a mutual inhibition of their degradation efficiencies due to competition for photons and·OH,along with the consequent reduction in intracellular ROS within ARB,with their degradation efficiencies exhibiting marked dependence on wavelength in both systems.Notably,the UV-LED/H_(2)O_(2) system at 265 nm effectively achieved the simultaneous removal of TC,ARB and ARGs with minimal energy consumption,and successfully fragmented ARGs.The degradation pathway of TC was analyzed,and the biotoxicity of its degradation intermediates demonstrated the environmental friendliness and safety of UV-LED/H_(2)O_(2) technology.This study elucidated the competitive interactions between antibiotics and ARB/ARGs within UV-LED/H_(2)O_(2) system,providing a promising approach for their simultaneous removal while ensuring energy efficiency.展开更多
When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based ...When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based models offer strong baselines,they compromise syntactic awareness and the detection and man-agement of offensive content in cluttered,noisy,and informal text.In this paper,we present POSDEP-Offense-Trans,a multi-task NMT framework that combines Part-of-Speech(POS)and Dependency Parsing(DEP)methods with a robust offensive language classification module.Our architecture enriches the Transformer encoder with syntax-aware embeddings and provides syntax-guided attention mechanisms.The architecture incorporates a structure-aware contrastive loss that reinforces syntactic consistency and deploys auxiliary classification heads for POS tagging,dependency parsing,and multi-class offensive detection.The classifier for offensive words operates at both sentence and token levels and obtains guidance from syntactic features and formal finite automata rules that model offensive language structures-hate speech,profanity,sarcasm,and threats.Using this architecture,we construct a syntactically enriched,socially annotated corpus.Experimental results show improvements in translation quality,with a BLEU score of 33.5,UAS/LAS parsing accuracies of 92.4%and 90%,and a 4.5%Fl-score gain in offensive content detection compared with baseline POS+DEP+Offense models.Also,the proposed model achieved 92.3%in offensive content neutralization,as confirmed by ablation studies.This comprehensive English-Tamil NMT model that unifies syntactic modelling and ethical filtering-laying the groundwork for applications in social media moderation,hate speech mitigation,and policy-compliant multilingual content generation.展开更多
Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a ...Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.展开更多
Backfill is often employed in mining operations for ground support,with its positive impact on ground stability acknowledged in many underground mines.However,existing studies have predominantly focused only on the st...Backfill is often employed in mining operations for ground support,with its positive impact on ground stability acknowledged in many underground mines.However,existing studies have predominantly focused only on the stress development within the backfill material,leaving the influence of stope backfilling on stress distribution in surrounding rock mass and ground stability largely unexplored.Therefore,this paper presents numerical models in FLAC3D to investigate,for the first time,the time-dependent stress redistribution around a vertical backfilled stope and its implications on ground stability,considering the creep of surrounding rock mass.Using the Soft Soil constitutive model,the compressibility of backfill under large pressure was captured.It is found that the creep deformation of rock mass exercises compression on backfill and results in a less void ratio and increased modulus for fill material.The compacted backfill conversely influenced the stress distribution and ground stability of rock mass which was a combined effect of wall creep and compressibility of backfill.With the increase of time or/and creep deformation,the minimum principal stress in the rocks surrounding the backfilled stope increased towards the pre-mining stress state,while the deviatoric stress reduces leading to an increased factor of safety and improved ground stability.This improvement effect of backfill on ground stability increased with the increase of mine depth and stope height,while it is also more pronounced for the narrow stope,the backfill with a smaller compression index,and the soft rocks with a smaller viscosity coefficient.Furthermore,the results emphasize the importance of minimizing empty time and backfilling extracted stope as soon as possible for ground control.Reduction of filling gap height enhances the local stability around the roof of stope.展开更多
Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic inform...Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic information,they also pose completeness and resource requirements limitations.This paper proposes a template-based classification(TC)model to avoid lexicon issues and to identify nested entities.Template-based classification provides a template word for each entity type,which utilises contrastive learning to integrate the common characteristics among entities with the same category.Contrastive learning makes template words the centre points of their category in the vector space,thus improving generalisation ability.Additionally,TC presents a 2D tablefilling label scheme that classifies entities based on the attention distribution of template words.The proposed novel decoder algorithm enables TC recognition of both flat and nested entities simultaneously.Experimental results show that TC achieves the state-ofthe-art performance on five Chinese datasets.展开更多
Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with...Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with approximately 50% of patients showing no response to rTMS treatment.Many studies have personalized the stimulation parameters of rTMS(e.g.,location and intensity of stimulation)according to the anatomical and functional structure of the brain.In addition to these parameters,the internal states of the individual,such as circadian rhythm,behavior/cognition,neural oscillation,and neuroplasticity,also contribute to the variation in rTMS effects.In this review,we summarize the current literature on the interaction between rTMS and internal states.We propose two possible methods,multimodal treatment,and adaptive closed-loop treatment,to integrate patients'internal states to achieve better rTMS treatment for depression.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privac...Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.展开更多
基金Project(51205302)supported by the National Natural Science Foundation of ChinaProject(2013JM7017)supported by the Natural Science Basic Research Plan in Shanxi Province of ChinaProject(K5051304006)supported by the Fundamental Research Funds for the Central Universities,China
文摘Based on the EAM potential, a molecular dynamics study on the tensile properties of ultrathin nickel nanowires in the （100〉 orientation with diameters of 3.94, 4.95 and 5.99 nm was presented at different temperatures and strain rates. The temperature and strain rate dependences of tensile properties were investigated. The simulation results show that the elastic modulus and the yield strength are gradually decreasing with the increase of temperature, while with the increase of the strain rate, the stress--strain curves fluctuate more intensely and the ultrathin nickel nanowires rupture at one smaller and smaller strain. At an ideal temperature of 0.01 K, the yield strength of the nanowires drops rapidly with the increase of strain rate, and at other temperatures the strain rate has a little influence on the elastic modulus and the yield strength. Finally, the effects of size on the tensile properties of ultrathin nickel nanowires were briefly discussed.
基金supported partially by funds from the NIH (RO1AR054385, P30GM103333)
文摘Osteocytes, the most abundant bone cells, form an interconnected network in the lacunar-canalicular pore system （LCS） buried within the mineralized matrix, which allows osteocytes to obtain nutrients from the blood supply, sense external mechanical signals, and communicate among themselves and with other cells on bone surfaces. In this study, we examined key features of the LCS network including the topological parameter and the detailed structure of individual connections and their variations in cortical and cancellous compa~ tments, at different ages, and in two disease conditions with altered mechanosensing （perlecan deficiency and diabetes）. LCS network showed both topological stability, in terms of conservation of connectivity among osteocyte lacunae （similar to the ＂nodes＂ in a computer network）, and considerable variability the pericellular annular fluid gap surrounding lacunae and canaliculi （similar to the ＂bandwidth＂ of individual links in a computer network）. Age, in the range of our study （15-32 weeks）, affected only the pericellular fluid annulus in cortical bone but not in cancellous bone. Diabetes impacted the spacing of the lacunae, while the perlecan deficiency had a profound influence on the pericellular fluid annulus. The LCS network features play important roles in osteocyte signaling and regulation of bone growth and adaptation.
基金Supported by the National Natural Science Foundation of China under Grant No 11004163the Fundamental Research Funds for the Central Universities under Grant No 2682014ZT31
文摘Thermal behavior of bulk amorphous sulfur is investigated by in situ temperature measurements at high pressures of 0.9, 1.4 and 2.1 GPa, and under different heating rates of 8, 10 and 12K/min at 0.9 GPa. The results show that the onset temperature of the transition from the supercooled Hquid to the liquid state for sulfur increases with the pressure and the heating rate. It is deduced that the transition does not follow the Clapeyron equation, indicating considerable coupling of the molecular structure change in the transition. Along with the data at ambient pressure and high pressure, we present a dynamic diagram to demonstrate the relationship between the amorphous solid, supercooled liquid, liquid, and crystal phases of sulfur, and suggest an experimental approach to establish pressure-temperature-time transition diagrams for supercooled liquid and liquid.
基金supported partially by the Important National Science&Technology Specific Projects,China(Grant No.2013ZX02503003)
文摘In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, then the temperature dependences are determined by the series of extracted temperature coefficients, based on the established temperature for- mulas for corresponding model parameters. The proposed method is validated by a 1x 0.2 x 16 μm2 SiGe HBT over a wide temperature range （from 218 K to 473 K）, and good matching is obtained between the extracted and modeled resuits. Therefore, we believe that the proposed extraction flow of model parameter temperature dependence is reliable for characterizing the transistor performance and guiding the circuit design over a wide temperature range.
基金supported by the National Key Science & Technology Special Project (Grant No.2008ZX01002-002)the Fundamental Research Funds for the Central Universities (Grant No.JY10000904009)the Major Program and State Key Program of National Natural Science Foundation of China (Grant Nos.60890191 and 60736033)
文摘First-order Raman scatterings of hexagonal GaN layers deposited by the hydride vapour phase epitaxy and by metal-organic chemical vapour deposition on SiC and sapphire substrates are studied in a temperature range between 303 K and 503 K. The temperature dependences of two GaN Raman modes （Al （LO） and E2 （high）） are obtained. We focus our attention on the temperature dependence of E2 （high） mode and find that for different types of GaN epilayers their temperature dependences are somewhat different. We compare their differences and give them an explanation. The simplified formulas we obtained are in good accordance with experiment data. The results can be used to determine the temperature of a GaN sample.
基金supported by the National Natural Science Foundation of China(71871227)the Innovation Driven Plan of Central South University(20180016040002)。
文摘Short-term taxi demand forecasting is of great importance to incentivize vacant cars moving from over-supply regions to over-demand regions,which can minimize the wait time for passengers and drivers.With the consideration of spatiotemporal dependences,this study proposes a multi-task deep learning(MTDL)model to predict short-term taxi demand in multi-zone level.The nonlinear Granger causality test is applied to explore the causality relationships among various traffic zones,and long short-term memory(LSTM)is used as the core neural unit to construct the framework of the multi-task deep learning model.In addition,several hyperparameter optimization methods(e.g.,grid search,random search,Bayesian optimization,hyperopt)are used to tune the model.Using the taxi trip data in New York City for validation,the multi-task deep learning model considering spatiotemporal dependences(MTDL*)is compared with the single-task deep learning model(STDL),the full-connected multi-task deep learning model(MTDL#)and other benchmark algorithms(such as LSTM,support vector machine(SVM)and k-nearest neighbors(k-NN)).The experiment results show that the proposed MTDL model is promising to predict short-term taxi demand in multi-zone level,the nonlinear Granger causality analysis is able to capture the spatiotemporal correlations among various traffic zones,and the Bayesian optimization is superior to the other three methods,which verified the feasibility and adaptability of the proposed method.
文摘A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescence(TADF)properties.All calculations were performed using density functional theory(DFT)and time‑dependent density functional theory(TDDFT).Calculations for electronic structures,frontier molecular orbital characteristics(which determine the efficiency roll‑off effect of the complexes),and photophysical properties were conducted using the Gaussian 09 software package.The calculation of spin‑orbit coupling matrix elements<T|HSOC|S>,which determine the TADF properties of the complexes,was performed using the ORCA software package.The calculation results show that the auxiliary ligand tetraphenylimidodiphosphinate(tpip),a strong electron‑withdrawing group,can mitigate the efficiency roll‑off effect of the complex.Furthermore,TADF is observed in one of the designed complexes,(F_(3)Phppy)_(2)Ir(tpip),where F_(3)Phppy=2‑[4‑(2,4,6‑trifluorophenyl)phenyl]pyridine.
文摘Background:This study aims to investigate the underlying mechanisms between parental marital conflict and adolescent short video dependence by constructing a chain mediation model,focusing on the mediating roles of experiential avoidance and emotional disturbance(anxiety,depression,and stress).Methods:Conducted in January 2025,the research recruited 4125 adolescents from multiple Chinese provinces through convenience sampling;after data cleaning,3957 valid participants(1959 males,1998 females)were included.Using a cross-sectional design,measures included parental marital conflict,experiential avoidance,anxiety,depression,stress,and short video dependence.Results:Pearson correlation analysis revealed significant positive correlations among all variables.Mediation analysis using the SPSS PROCESS macro showed that parental marital conflict directly predicted short video dependence(β=0.269,p<0.001),and also significantly predicted experiential avoidance(β=0.519,p<0.001),anxiety(β=0.072,p<0.001),depression(β=0.067,p<0.001),and stress(β=0.048,p<0.05).Experiential avoidance further predicted anxiety(β=0.521,p<0.001),depression(β=0.489,p<0.001),stress(β=0.408,p<0.001),and short video dependence(β=0.244,p<0.001).While both anxiety(β=0.050,p<0.05)and depression(β=0.116,p<0.001)positively predicted short video dependence,stress did not(β=0.019,p=0.257).Overall,experiential avoidance,anxiety,depression,and stress significantly mediated the relationship between parental marital conflict and short video dependence.Conclusion:These findings confirm that parental marital conflict not only directly influences adolescent short video dependence but also operates through a chain mediation pathway involving experiential avoidance and emotional disturbance,highlighting central psychological mechanisms and providing theoretical support for integrated mental health and behavioral interventions.
基金Project(51978674)supported by the National Natural Science Foundation of China。
文摘Conglomerate rock's complex and heterogeneous microstructure significantly affects its mechanical properties,especially under dynamic loading.However,research on their dynamic behavior and fracture mechanisms is limited.Through uniaxial compression tests and split Hopkinson pressure bar(SHPB)impact tests,the dynamic compressive mechanical properties and fracture mechanisms of conglomerate rock were studied.Nanoindentation and high-resolution X-ray computed tomography were employed to analyze the micro-mechanical behavior and internal structure of the conglomerate rock.Results indicate significant differences in mechanical properties between different gravel particles and cementing materials,with initial fractures primarily distributed at the gravel-cement interfaces.The dynamic mechanical properties of conglomerate rocks exhibit a clear strain rate dependency.Based on the stress−strain curves and failure characteristics,the dynamic compressive mechanical behavior can be categorized into two types using a critical strain rate.The dynamic compressive strength,peak strain,and toughness of conglomerate rock increased with the strain rate,with the strength at 54 s−1 being 2.6 times that at 6 s−1.The dynamic compressive fracture mechanism of conglomerate rock is related to the strain rate and microstructure;at low strain rates,gravel distribution is the key factor,whereas at high strain rates,gravel content becomes critical.
基金Da Nang University of Medical Technology and PharmacyDa Nang C Hospital for the invaluable support they provided in facilitating this research。
文摘Objective:The aging population is growing rapidly,leading to a rise in chronic diseases and placing significant physical,emotional,and financial strain on caregivers.Managing chronic conditions alongside caregiving responsibilities often results in burnout,adding to the burden on caregivers.This issue also affects society and healthcare systems through increased costs and greater demands for support services.Understanding the factors contributing to caregiver burden is crucial for creating effective interventions to address these challenges.The aim of this study is to describe the extent of caregiver burden and identify some factors related to burden among caregivers of chronically ill elderly people.By gaining insight into these relationships,this study seeks to identify strategies to reduce the burden on caregivers.Methods:This study utilized a cross-sectional design to examine caregivers of the elderly with chronic diseases receiving treatment in the public healthcare facility.Data collection involved administering structured questionnaires that gathered information on the demographic characteristics of both the elderly and their caregivers,the level of social support received,the functional status of patients as measured by daily activity indices,and the level of caregiver burden.Description was used to elaborate the characteristics of participants.Mann-Whitney,Kruskal-Wallis,and Spearman's correlation test were applied to explore the relationship between variables.Statistical significance was determined at P value<0.05.Results:Caregivers of the elderly with chronic diseases had a moderate care burden score(22.62±11.24,CI:95%).The patients'level of dependence,relationship with the patients,and time spent as a caregiver were factors related to caregiver burden(P<0.05).Conclusions:Those who care for elderly people with chronic diseases suffered great burden.The finding had found a number of factors that influence the caregivers'weight loss.Healthcare providers should consider these relevant factors when developing intervention plans to reduce caregiver burden.
基金financially supported by the National Natural Science Foundation of China(Nos.22475057 and No.52373262).
文摘Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.
基金supported by Natural Science Foundation of Inner Mongolia Autonomous Region of China (2023MS03027)the National Natural Science Foundation of China (31860185 and 31160141)
文摘Distributions of nuclear magnetic resonance(NMR)relaxation times provide detailed information about the water in wood.This study documents the water dynamics analysis of T_(2)and T_(1)distributions for saturated delignified sapwood(DSW),delignified heartwood(DHW)and lignocellulose(LC)samples at different temperatures.Results indicate that below the freezing point of bulk water,free water freezes,causing its signal to disappear from the distribution.Then,the low temperature distributions of the unfrozen bound water contain more information about its components,with DSW,DHW and LC containing two distinct states of bound water(OH bound water(B-water)and more freely bound water(C-water)).Furthermore,it was observed that within the temperature range of−3°C to−60°C,B-water in DSW,DHW and LC maintained a higher unfrozen water content(UWC)value than C-water,and the T_(1)/T_(2)ratios for B-water were consistently higher than that for C-water,indicating that B-water has a greater antifreeze capacity.T_(2)and T_(1)distributions offer different kinds of information about water components,and all peaks within the distribution have been assigned.
基金supported by Major Scientific and Technological Innovation Project of Shandong Province(No.2020CXGC011204)Qingdao Natural Science Foundation(No.23-2-1-234-zyyd-jch).
文摘The coexistence of emerging containments,such as antibiotic resistant bacteria(ARB),antibiotic-resistant genes(ARGs)and antibiotics,potentially influence elimination efficiencies in UV light-emitting diode(UV-LED)alone and UV-LED/H_(2)O_(2) system as their complex interactions.Tetracycline(TC)degradation efficiency(kF)correlated closely with its UV molar absorbance(R^(2)=0.831)in UV-LED alone system and with·OH yield(R^(2)=0.999)in UV-LED/H_(2)O_(2) system across studied wavelengths(265,280 and 310 nm).The kF values for intracellular DNA(i-ARGs)also exhibited a high correlation with UV-LED wavelengths in both systems(R^(2)=0.997-0.999).The coexistence of TC and ARB/ARGs resulted in a mutual inhibition of their degradation efficiencies due to competition for photons and·OH,along with the consequent reduction in intracellular ROS within ARB,with their degradation efficiencies exhibiting marked dependence on wavelength in both systems.Notably,the UV-LED/H_(2)O_(2) system at 265 nm effectively achieved the simultaneous removal of TC,ARB and ARGs with minimal energy consumption,and successfully fragmented ARGs.The degradation pathway of TC was analyzed,and the biotoxicity of its degradation intermediates demonstrated the environmental friendliness and safety of UV-LED/H_(2)O_(2) technology.This study elucidated the competitive interactions between antibiotics and ARB/ARGs within UV-LED/H_(2)O_(2) system,providing a promising approach for their simultaneous removal while ensuring energy efficiency.
文摘When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based models offer strong baselines,they compromise syntactic awareness and the detection and man-agement of offensive content in cluttered,noisy,and informal text.In this paper,we present POSDEP-Offense-Trans,a multi-task NMT framework that combines Part-of-Speech(POS)and Dependency Parsing(DEP)methods with a robust offensive language classification module.Our architecture enriches the Transformer encoder with syntax-aware embeddings and provides syntax-guided attention mechanisms.The architecture incorporates a structure-aware contrastive loss that reinforces syntactic consistency and deploys auxiliary classification heads for POS tagging,dependency parsing,and multi-class offensive detection.The classifier for offensive words operates at both sentence and token levels and obtains guidance from syntactic features and formal finite automata rules that model offensive language structures-hate speech,profanity,sarcasm,and threats.Using this architecture,we construct a syntactically enriched,socially annotated corpus.Experimental results show improvements in translation quality,with a BLEU score of 33.5,UAS/LAS parsing accuracies of 92.4%and 90%,and a 4.5%Fl-score gain in offensive content detection compared with baseline POS+DEP+Offense models.Also,the proposed model achieved 92.3%in offensive content neutralization,as confirmed by ablation studies.This comprehensive English-Tamil NMT model that unifies syntactic modelling and ethical filtering-laying the groundwork for applications in social media moderation,hate speech mitigation,and policy-compliant multilingual content generation.
文摘Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.
基金the funding support from the National Natural Science Foundation of China(Grant Nos.52304101 and 52004206)the China Postdoctoral Science Foundation(Grant No.2023MD734215)。
文摘Backfill is often employed in mining operations for ground support,with its positive impact on ground stability acknowledged in many underground mines.However,existing studies have predominantly focused only on the stress development within the backfill material,leaving the influence of stope backfilling on stress distribution in surrounding rock mass and ground stability largely unexplored.Therefore,this paper presents numerical models in FLAC3D to investigate,for the first time,the time-dependent stress redistribution around a vertical backfilled stope and its implications on ground stability,considering the creep of surrounding rock mass.Using the Soft Soil constitutive model,the compressibility of backfill under large pressure was captured.It is found that the creep deformation of rock mass exercises compression on backfill and results in a less void ratio and increased modulus for fill material.The compacted backfill conversely influenced the stress distribution and ground stability of rock mass which was a combined effect of wall creep and compressibility of backfill.With the increase of time or/and creep deformation,the minimum principal stress in the rocks surrounding the backfilled stope increased towards the pre-mining stress state,while the deviatoric stress reduces leading to an increased factor of safety and improved ground stability.This improvement effect of backfill on ground stability increased with the increase of mine depth and stope height,while it is also more pronounced for the narrow stope,the backfill with a smaller compression index,and the soft rocks with a smaller viscosity coefficient.Furthermore,the results emphasize the importance of minimizing empty time and backfilling extracted stope as soon as possible for ground control.Reduction of filling gap height enhances the local stability around the roof of stope.
基金Sichuan Provincial Science and Technology Support Program,Grant/Award Number:2023YFG0151National Natural Science Foundation of China,Grant/Award Numbers:U22B2061,U2336204。
文摘Existing Chinese named entity recognition(NER)research utilises 1D lexicon-based sequence labelling frameworks,which can only recognise flat entities.While lexicons serve as prior knowledge and enhance semantic information,they also pose completeness and resource requirements limitations.This paper proposes a template-based classification(TC)model to avoid lexicon issues and to identify nested entities.Template-based classification provides a template word for each entity type,which utilises contrastive learning to integrate the common characteristics among entities with the same category.Contrastive learning makes template words the centre points of their category in the vector space,thus improving generalisation ability.Additionally,TC presents a 2D tablefilling label scheme that classifies entities based on the attention distribution of template words.The proposed novel decoder algorithm enables TC recognition of both flat and nested entities simultaneously.Experimental results show that TC achieves the state-ofthe-art performance on five Chinese datasets.
基金supported by STI2030-Major Projects(2021ZD0204300 and 2021ZD0200800)the National Natural Science Foundation of China(82271528)the Fundamental Research Funds for the Central Universities(Peking University Medicine Fund for World's Leading Discipline or Discipline Cluster Development,BMU2022DJXK007).
文摘Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with approximately 50% of patients showing no response to rTMS treatment.Many studies have personalized the stimulation parameters of rTMS(e.g.,location and intensity of stimulation)according to the anatomical and functional structure of the brain.In addition to these parameters,the internal states of the individual,such as circadian rhythm,behavior/cognition,neural oscillation,and neuroplasticity,also contribute to the variation in rTMS effects.In this review,we summarize the current literature on the interaction between rTMS and internal states.We propose two possible methods,multimodal treatment,and adaptive closed-loop treatment,to integrate patients'internal states to achieve better rTMS treatment for depression.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
文摘Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.
