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
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
Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoo...Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.展开更多
Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)informati...Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.展开更多
This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later step...This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
BACKGROUND Proper antidepressant use can improve mood and reduce desire to drink alcohol in alcohol-induced-affective-disorder patients.Shugan Jieyu capsules(SJC)have various impacts on the central nervous system,prod...BACKGROUND Proper antidepressant use can improve mood and reduce desire to drink alcohol in alcohol-induced-affective-disorder patients.Shugan Jieyu capsules(SJC)have various impacts on the central nervous system,producing antidepressant effects.Traditional Chinese medicine(including Shugan Jieyu)is highly therapeutic in treating alcohol dependence,with few side-effects.However,research on its combination with Western antidepressants(e.g.,sertraline)to improve patients’depression is insufficient.AIM To evaluate the clinical efficacy and safety of SJC combined with sertraline vs sertraline monotherapy in alcohol-dependent patients with comorbid depression.METHODS We conducted a randomized,double-blind,placebo-controlled trial.Sixty patients(aged 18-65 years)were randomly assigned to two groups(n=30 per group).Primary outcome:Hamilton Depression Rating Scale(HAMD)-17 changes over 6 weeks.Benzodiazepines were permitted for severe insomnia.RESULTS The HAMD-17 score of the study(vs control)group was lower at treatment weeks 2,4,and 6(P<0.05).Regarding intra-group comparisons,the study group’s HAMD score was significantly lower than that before treatment from week 2(P<0.05),while that of the control group was significantly lower than that before treatment from week 4(P<0.05).The study and control groups’total efficacy rates were 90%and 73.3%,respectively,showing a significant difference in efficacy(χ^(2)=4.812,P=0.028).No significant difference was observed in adverse reactions’incidence between the groups at treatment weeks 2,4,and 6(P>0.05).CONCLUSION SJC-sertraline combination therapy accelerates depressive symptom relief(by 2 weeks)and improves response rates(+16.7%)in alcohol-dependent patients,without increasing adverse events.Clinical outcomes suggest potential synergistic mechanisms,though no biomarker analyses were performed.展开更多
Chairs are the most common furniture in household environments,and reclining chairs specifically cater to the functional needs of the elderly.With the gradually increasing aging population,our preliminary research has...Chairs are the most common furniture in household environments,and reclining chairs specifically cater to the functional needs of the elderly.With the gradually increasing aging population,our preliminary research has revealed that current reclining chair designs often fail to align with the physical dimensions and needs of older adults.Many designs appear to prioritize technology over usability,resulting in a homogenous product landscape.Using statistical analysis and the weighted average method,an elderly-friendly reclining chair that considers height,depth,and width is designed.The final design aims to meet the psychological and physiological needs of self-care,semi-dependent,and fully dependent elderly individuals.Adhering to the“people-oriented”design philosophy and targeting“convenience and efficiency,”our ultimate goal is to create a reclining chair that helps the elderly lie down,stand up,and sit down with dignity.This innovative approach offers a new perspective for the market of aging-friendly furniture.展开更多
Artificial intelligence,especially large language models(LLMs),is reshaping how we learn,communicate,and create.These systems provide students and professionals immediate access to fluent,context-aware language that c...Artificial intelligence,especially large language models(LLMs),is reshaping how we learn,communicate,and create.These systems provide students and professionals immediate access to fluent,context-aware language that can support learning,increase productivity,and spark creativity.But what happens when their use becomes excessive?This paper explores the potential long-term consequences of over-relying on LLMs-particularly memory,critical thinking,creativity,and motivation.Drawing on research in cognitive psychology,education,neuroscience,and media studies,it argues that LLMs are best understood as cognitive prostheses:incredibly valuable when used wisely,but risky when they replace rather than support human imagination.展开更多
In this study,we performed a systematic analysis of the multiplicity dependence of hadron production at mid-rapidity(|y|<0.5),ranging from the light to the charm sector in proton-proton(pp)collisions at√s=13 TeV.T...In this study,we performed a systematic analysis of the multiplicity dependence of hadron production at mid-rapidity(|y|<0.5),ranging from the light to the charm sector in proton-proton(pp)collisions at√s=13 TeV.This study used a multi-phase transport(AMPT)model coupled with PYTHIA8 initial conditions.We investigated the baryon-to-meson and the strange-to-non-strange meson ratios varying with the charged particle density.By tuning the coalescence parameters,the AMPT model provides a reasonable description of the experimental data for the inclusive production of both light and charm hadrons,comparable to the string fragmentation model calculations with color reconnection effects.Additionally,we analyzed the relative production of hadrons by examining the self-normalized particle ratios as a function of the charged hadron density.Our findings suggest that parton evolution effects and the coalescence hadronization process in the AMPT model result in a strong flavor hierarchy in the multiplicity dependence of the baryon-to-meson ratio.Furthermore,our investigation of the p_(T) differential double ratio of the baryon-to-meson fraction between high-and low-multiplicity events revealed distinct modifications to the flavor associated baryon-to-meson ratio p_(T) shape in high-multiplicity events when comparing the coalescence hadronization model to the color reconnection model.These observations highlight the importance of understanding the hadronization process in high-energy pp collisions through comprehensive multiplicity-dependent multi-flavor analysis.展开更多
Heroin dependence is a serious substance use disorder that not only causes great harm to physical health but also significantly affects mental health.Addicts often experience a variety of psychological problems,such a...Heroin dependence is a serious substance use disorder that not only causes great harm to physical health but also significantly affects mental health.Addicts often experience a variety of psychological problems,such as depression,anxiety,personality disorders,and cognitive impairment.In recent years the mechanisms and intervention methods related to mental health problems in heroin addicts have received widespread research attention.This article reviews the current research into mental health problems in heroin addicts in order to provide a theoretical basis for optimizing drug addiction intervention strategies.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.
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.
基金supported by the National Key Research and Development Program of China(No.2022YFB4300902)。
文摘Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.
基金supported by the National Natural Science Foundation of China(Nos.U2441250,62301380,and 62231027)Natural Science Basic Research Program of Shaanxi,China(2024JC-JCQN-63)+3 种基金the Key Research and Development Program of Shaanxi,China(No.2023-YBGY-249)the Guangxi Key Research and Development Program,China(No.2022AB46002)the China Postdoctoral Science Foundation(No.2022M722504 and 2024T170696)the Innovation Capability Support Program of Shaanxi,China(No.2024RS-CXTD-01).
文摘Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.
文摘This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
文摘BACKGROUND Proper antidepressant use can improve mood and reduce desire to drink alcohol in alcohol-induced-affective-disorder patients.Shugan Jieyu capsules(SJC)have various impacts on the central nervous system,producing antidepressant effects.Traditional Chinese medicine(including Shugan Jieyu)is highly therapeutic in treating alcohol dependence,with few side-effects.However,research on its combination with Western antidepressants(e.g.,sertraline)to improve patients’depression is insufficient.AIM To evaluate the clinical efficacy and safety of SJC combined with sertraline vs sertraline monotherapy in alcohol-dependent patients with comorbid depression.METHODS We conducted a randomized,double-blind,placebo-controlled trial.Sixty patients(aged 18-65 years)were randomly assigned to two groups(n=30 per group).Primary outcome:Hamilton Depression Rating Scale(HAMD)-17 changes over 6 weeks.Benzodiazepines were permitted for severe insomnia.RESULTS The HAMD-17 score of the study(vs control)group was lower at treatment weeks 2,4,and 6(P<0.05).Regarding intra-group comparisons,the study group’s HAMD score was significantly lower than that before treatment from week 2(P<0.05),while that of the control group was significantly lower than that before treatment from week 4(P<0.05).The study and control groups’total efficacy rates were 90%and 73.3%,respectively,showing a significant difference in efficacy(χ^(2)=4.812,P=0.028).No significant difference was observed in adverse reactions’incidence between the groups at treatment weeks 2,4,and 6(P>0.05).CONCLUSION SJC-sertraline combination therapy accelerates depressive symptom relief(by 2 weeks)and improves response rates(+16.7%)in alcohol-dependent patients,without increasing adverse events.Clinical outcomes suggest potential synergistic mechanisms,though no biomarker analyses were performed.
基金Chongqing University of Engineering Internal Fund Key Project in Natural Sciences:Research on Spatial Syntax Parameters and Combination Patterns of Elderly Care Centers in Urban and Rural Communities from a Multidimensional Logical Perspective(Project No:XJXM202412014)。
文摘Chairs are the most common furniture in household environments,and reclining chairs specifically cater to the functional needs of the elderly.With the gradually increasing aging population,our preliminary research has revealed that current reclining chair designs often fail to align with the physical dimensions and needs of older adults.Many designs appear to prioritize technology over usability,resulting in a homogenous product landscape.Using statistical analysis and the weighted average method,an elderly-friendly reclining chair that considers height,depth,and width is designed.The final design aims to meet the psychological and physiological needs of self-care,semi-dependent,and fully dependent elderly individuals.Adhering to the“people-oriented”design philosophy and targeting“convenience and efficiency,”our ultimate goal is to create a reclining chair that helps the elderly lie down,stand up,and sit down with dignity.This innovative approach offers a new perspective for the market of aging-friendly furniture.
文摘Artificial intelligence,especially large language models(LLMs),is reshaping how we learn,communicate,and create.These systems provide students and professionals immediate access to fluent,context-aware language that can support learning,increase productivity,and spark creativity.But what happens when their use becomes excessive?This paper explores the potential long-term consequences of over-relying on LLMs-particularly memory,critical thinking,creativity,and motivation.Drawing on research in cognitive psychology,education,neuroscience,and media studies,it argues that LLMs are best understood as cognitive prostheses:incredibly valuable when used wisely,but risky when they replace rather than support human imagination.
基金supported by the National Natural Science Foundation of China(Nos.12205259 and 12147101)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)with No.G1323523064.
文摘In this study,we performed a systematic analysis of the multiplicity dependence of hadron production at mid-rapidity(|y|<0.5),ranging from the light to the charm sector in proton-proton(pp)collisions at√s=13 TeV.This study used a multi-phase transport(AMPT)model coupled with PYTHIA8 initial conditions.We investigated the baryon-to-meson and the strange-to-non-strange meson ratios varying with the charged particle density.By tuning the coalescence parameters,the AMPT model provides a reasonable description of the experimental data for the inclusive production of both light and charm hadrons,comparable to the string fragmentation model calculations with color reconnection effects.Additionally,we analyzed the relative production of hadrons by examining the self-normalized particle ratios as a function of the charged hadron density.Our findings suggest that parton evolution effects and the coalescence hadronization process in the AMPT model result in a strong flavor hierarchy in the multiplicity dependence of the baryon-to-meson ratio.Furthermore,our investigation of the p_(T) differential double ratio of the baryon-to-meson fraction between high-and low-multiplicity events revealed distinct modifications to the flavor associated baryon-to-meson ratio p_(T) shape in high-multiplicity events when comparing the coalescence hadronization model to the color reconnection model.These observations highlight the importance of understanding the hadronization process in high-energy pp collisions through comprehensive multiplicity-dependent multi-flavor analysis.
基金Mental Hospital of Yunnan Province Scientific Research Fund Project(shengjingkeyan2022-11).
文摘Heroin dependence is a serious substance use disorder that not only causes great harm to physical health but also significantly affects mental health.Addicts often experience a variety of psychological problems,such as depression,anxiety,personality disorders,and cognitive impairment.In recent years the mechanisms and intervention methods related to mental health problems in heroin addicts have received widespread research attention.This article reviews the current research into mental health problems in heroin addicts in order to provide a theoretical basis for optimizing drug addiction intervention strategies.
