As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.展开更多
Objective:Triple-negative breast cancer(TNBC)is a highly aggressive subtype that lacks targeted therapies,leading to a poorer prognosis.However,some patients achieve long-term recurrence-free survival(RFS),offering va...Objective:Triple-negative breast cancer(TNBC)is a highly aggressive subtype that lacks targeted therapies,leading to a poorer prognosis.However,some patients achieve long-term recurrence-free survival(RFS),offering valuable insights into tumor biology and potential treatment strategies.Methods:We conducted a comprehensive multi-omics analysis of 132 patients with American Joint Committee on Cancer(AJCC)stage III TNBC,comprising 36 long-term survivors(RFS≥8 years),62 moderate-term survivors(RFS:3-8 years),and 34 short-term survivors(RFS<3 years).Analyses investigated clinicopathological factors,whole-exome sequencing,germline mutations,copy number alterations(CNAs),RNA sequences,and metabolomic profiles.Results:Long-term survivors exhibited fewer metastatic regional lymph nodes,along with tumors showing reduced stromal fibrosis and lower Ki67 index.Molecularly,these tumors exhibited multiple alterations in genes related to homologous recombination repair,with higher frequencies of germline mutations and somatic CNAs.Additionally,tumors from long-term survivors demonstrated significant downregulation of the RTK-RAS signaling pathway.Metabolomic profiling revealed decreased levels of lipids and carbohydrate,particularly those involved in glycerophospholipid,fructose,and mannose metabolism,in long-term survival group.Multivariate Cox analysis identified fibrosis[hazard ratio(HR):12.70,95%confidence interval(95%CI):2.19-73.54,P=0.005]and RAC1copy number loss/deletion(HR:0.22,95%CI:0.06-0.83,P=0.026)as independent predictors of RFS.Higher fructose/mannose metabolism was associated with worse overall survival(HR:1.30,95%CI:1.01-1.68,P=0.045).Our findings emphasize the association between biological determinants and prolonged survival in patients with TNBC.Conclusions:Our study systematically identified the key molecular and metabolic features associated with prolonged survival in AJCC stage III TNBC,suggesting potential therapeutic targets to improve patient outcomes.展开更多
The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficien...The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.展开更多
CO_(2)-responsive gels,which swell upon contact with CO_(2),are widely used for profile control to plug high-permeability gas flow channels in carbon capture,utilization,and storage(CCUS)applications in oil reser-voir...CO_(2)-responsive gels,which swell upon contact with CO_(2),are widely used for profile control to plug high-permeability gas flow channels in carbon capture,utilization,and storage(CCUS)applications in oil reser-voirs.However,the use of these gels in high-temperature CCUS applications is limited due to their rever-sible swelling behavior at elevated temperatures.In this study,a novel dispersed particle gel(DPG)suspension is developed for high-temperature profile control in CCUS applications.First,we synthesize a double-network hydrogel consisting of a crosslinked polyacrylamide(PAAm)network and a crosslinked sodium alginate(SA)network.The hydrogel is then sheared in water to form a pre-prepared DPG suspen-sion.To enhance its performance,the gel particles are modified by introducing potassium methylsilan-etriolate(PMS)upon CO_(2) exposure.Comparing the particle size distributions of the modified and pre-prepared DPG suspension reveals a significant swelling of gel particles,over twice their original size.Moreover,subjecting the new DPG suspension to a 100℃ environment for 24 h demonstrates that its gel particle sizes do not decrease,confirming irreversible swelling,which is a significant advantage over the traditional CO_(2)-responsive gels.Thermogravimetric analysis further indicates improved thermal sta-bility compared to the pre-prepared DPG particles.Core flooding experiments show that the new DPG suspension achieves a high plugging efficiency of 95.3%in plugging an ultra-high permeability sandpack,whereas the pre-prepared DPG suspension achieves only 82.8%.With its high swelling ratio,irreversible swelling at high temperatures,enhanced thermal stability,and superior plugging performance,the newly developed DPG suspension in this work presents a highly promising solution for profile control in high-temperature CCUS applications.展开更多
A segmented predictor-corrector method is proposed for hypersonic glide vehicles to address the issue of the slow computational speed of obtaining guidance commands using the traditional predictor-corrector guidance m...A segmented predictor-corrector method is proposed for hypersonic glide vehicles to address the issue of the slow computational speed of obtaining guidance commands using the traditional predictor-corrector guidance method.Firstly,an altitude-energy profile is designed,and the bank angle is derived analytically as the initial iteration value for the predictor-corrector method.The predictor-corrector guidance method has been improved by deriving an analytical form for predicting the range-to-go error,which greatly accelerates the iterative speed.Then,a segmented guidance algorithm is proposed.The above analytically predictor-corrector guidance method is adopted when the energy exceeds an energy threshold.When the energy is less than the threshold,the equidistant test method is used to calculate the bank angle command,which ensures guidance accuracy as well as computational efficiency.Additionally,an adaptive guidance cycle strategy is applied to reduce the computational time of the reentry guidance trajectory.Finally,the accuracy and robustness of the proposed method are verified through a series of simulations and Monte-Carlo experiments.Compared with the traditional integral method,the proposed method requires 75%less computation time on average and achieves a lower landing error.展开更多
In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed p...In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.展开更多
Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.展开更多
This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer f...This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer for atmospheric chartography(SCIAMACHY).This technique is based on SaskMART(the combination of the multiplicative algebraic reconstruction technique and SaskTRAN radiative transfer model),which was originally developed for optical spectrometer and infrared imaging system(OSIRIS)data.One of the objectives of this study was to obtain consistent ozone profiles from the two satellites.In this study,the WMART algorithm is combined with a radiative transfer model(SCIATRAN),as well as a set of measurement vectors comprising five Hartley pairing vectors(HPVs)and one Chappuis triplet vector(CTV),to retrieve ozone profiles in the altitude range of 10–69 km.Considering that the weighting factors in WMART have a significant effect on the retrievals,we propose a novel approach to calculate the pair/triplet weighting factors using wavelength weighting functions.The results of the application of the proposed ozone retrieval scheme are compared with the SCIAMACHY v3.5 ozone product by University of Bremen and validated against profiles derived from other passive satellite observations or measured by ozonesondes.Between 18 and 55 km,the retrieved ozone profiles typically agree with data from the SCIAMACHY ozone product within 5%for tropics and middle latitudes,whereas a negative deviation exists between 35 and 50 km for northern high latitudes,with a deviation of less than 10%above 50 km.Comparison of the retrieved profiles with microwave limb sounder(MLS)v5.0 indicates that the difference is within±5%between 18 and 55 km,and an agreement within 10%is achieved in other altitudes for tropics and middle latitudes.Comparison of the retrieved profiles with OSIRIS v7.1 indicates that the average deviation is within±5%between 20 and 59 km,and difference of approximately 10%is achieved below 20 km.Compared with ozonesondes data,a general validity of the retrievals is no more than 5%between 15 and 30 km.展开更多
BACKGROUND Disorders of gut-brain interaction(DGBI)are common,but knowledge about their physiopathology is still poor,nor valid tools have been used to evaluate them in childhood.AIM To develop a psycho-gastroenterolo...BACKGROUND Disorders of gut-brain interaction(DGBI)are common,but knowledge about their physiopathology is still poor,nor valid tools have been used to evaluate them in childhood.AIM To develop a psycho-gastroenterological questionnaire(PGQ)to assess the psycho-gastroenterological profile and social characteristics of a pediatric population with and without DGBI.METHODS One hundred and nineteen Italian children(age 11-18)were included:28 outpatient patients with DGBI(Rome IV criteria)and 91 healthy controls.They filled the PGQ,faces pain scale revised(FPS-R),Bristol stool chart,ga-strointestinal symptoms rating scale,state-trait anxiety inventory,Toronto alexithymia scale 20,perceived self-efficacy in the management of negative emotions and expression of positive emotions(APEN-G,APEP-G),irritable bowel syndrome-quality of life questionnaire,school performances,tobacco use,early life events,degree of digital-ization.RESULTS Compared to controls,patients had more medical examinations(35%of them went to the doctor more than five times),a higher school performance(23%vs 13%,P<0.05),didn’t use tobacco(never vs 16%,P<0.05),had early life events(28%vs 1%P<0.05)and a higher percentage of pain classified as 4 in the FPS-R during the examination(14%vs 7%,P<0.05).CONCLUSION Pediatric outpatients with DGBI had a higher prevalence of early life events,a lower quality of life,more medical examinations rising health care costs,lower anxiety levels.展开更多
Background:The aim of this study was to analyze the bi-directional causal relation-ship between lipid profile and characteristics related to muscle atrophy by using a bi-directional Mendelian randomization(MR)analysis...Background:The aim of this study was to analyze the bi-directional causal relation-ship between lipid profile and characteristics related to muscle atrophy by using a bi-directional Mendelian randomization(MR)analysis.Methods:The appendicular lean mass(ALM),whole body fat-free mass(WBFFM)and trunk fat-free mass(TFFM)were used as genome-wide association study(GWAS)data for evaluating muscle mass;the usual walking pace(UWP)and low grip strength(LGS)were used as GWAS data for evaluating muscle strength;and the triglycerides(TG),total cholesterol(TC),high density lipoprotein cholesterol(HDL),low density lipo-protein cholesterol(LDL),apolipoprotein A-1(Apo A-1),and apolipoprotein B(Apo B)were used as GWAS data for evaluating lipid profile.For specific investigations,we mainly employed inverse variance weighting for causal estimation and MR-Egger for pleiotropy analysis.Results:MR results showed that the lipid profile predicted by genetic variants was negatively correlated with muscle mass,positively correlated with UWP,and was not causally correlated with LGS.On the other hand,the muscle mass predicted by genetic variants was negatively correlated with lipid profile,the UWP predicted by genetic variants was mainly positively correlated with lipid profile,while the LGS pre-dicted by genetic variants had no relevant causal relationship with lipid profile.Conclusions:Findings of this MR analysis suggest that hyperlipidemia may affect muscle mass and lead to muscle atrophy,but has no significant effect on muscle strength.On the other hand,increased muscle mass may reduce the incidence of dyslipidemia.展开更多
Traditional manufacturing processes for lightweight curved profiles are often associated with lengthy procedures,high costs,low efficiency,and high energy consumption.In order to solve this problem,a new staggered ext...Traditional manufacturing processes for lightweight curved profiles are often associated with lengthy procedures,high costs,low efficiency,and high energy consumption.In order to solve this problem,a new staggered extrusion(SE)process was used to form the curved profile of AZ31 magnesium alloy in this paper.The study investigates the mapping relationship between the curvature,microstructure,and mechanical properties of the formed profiles by using different eccentricities of the die.Scanning electron microscopy(SEM)and electron backscatter diffraction techniques are employed to examine the effects of different eccentricity values(e)on grain morphology,recrystallization mechanisms,texture,and Schmid factors of the products.The results demonstrate that the staggered extrusion method promotes the deep refinement of grain size in the extruded products,with an average grain size of only 15%of the original billet,reaching 12.28μm.The tensile strength and elongation of the curved profiles after extrusion under the eccentricity value of 10 mm,20 mm and 30 mm are significantly higher than those of the billet,with the tensile strength is increased to 250,270,235 MPa,and the engineering strain elongation increased to 10.5%,12.1%,15.9%.This indicates that staggered extrusion enables curvature control of the profiles while improving their strength.展开更多
Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaboratio...Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.展开更多
Purpose It is essential to investigate the audiological profiles of Williams syndrome in a multicultural context.This study aims to examine the characteristics and management of hearing loss in Chinese children with W...Purpose It is essential to investigate the audiological profiles of Williams syndrome in a multicultural context.This study aims to examine the characteristics and management of hearing loss in Chinese children with Williams syndrome and provide references for future clinical management.Method Between January 2007 and March 2022,families with at least 1 WS patient was recruited from the Newborn Cohort Study of Hearing Loss.Audiological tests were performed,and then appropriate medical management was offered.Furthermore,an overview of the hearing loss phenotype in Williams syndrome in different locations was reviewed.Results A total of two families with at least 1 Williams syndrome patient were recruited from the Newborn Cohort Study of Hearing Loss(ChiCTR2100049765).We identified moderately severe sensorineural or conductive hearing loss that emerged as early as the infancy period in Williams syndrome subjects in Chinese children.Our results extended the reported onset ages of hearing loss in WS from late childhood or early adulthood to the infancy period.We also found that with early diagnosis,proper management,and regular monitoring,children with Williams syndrome could return to a normal or near-normal school life.Conclusions Our study demonstrated the distinct hearing profile in Chinese children with Williams syndrome for the first time.This cohort of WS subjects extends the reported onset ages of hearing loss in WS from late childhood or early adulthood to the infancy period,indicating the importance of clinicians screening and monitoring the hearing status of individuals with WS as early as possible.These data provide references for otolaryngologists and paediatricians to inform the clinical understanding and management of hearing loss in Williams syndrome.展开更多
Several optimization methods,such as Particle Swarm Optimization(PSO)and Genetic Algorithm(GA),are used to select the most suitable Static Synchronous Compensator(STATCOM)technology for the optimal operation of the po...Several optimization methods,such as Particle Swarm Optimization(PSO)and Genetic Algorithm(GA),are used to select the most suitable Static Synchronous Compensator(STATCOM)technology for the optimal operation of the power system,as well as to determine its optimal location and size to minimize power losses.An IEEE 14 bus system,integrating three wind turbines based on Squirrel Cage Induction Generators(SCIGs),is used to test the applicability of the proposed algorithms.The results demonstrate that these algorithms are capable of selecting the most appropriate technology while optimally sizing and locating the STATCOM to reduce power losses in the network.Specifically,the optimized STATCOM allocation using the Particle Swarm Optimization(PSO)achieves a 7.44%reduction in total active power loss compared to the optimized allocation using the Genetic Algorithm(GA).Furthermore,the voltage magnitudes at buses 4,9,and 10,which initially had exceeded the upper voltage limit,were reduced and brought within acceptable ranges,thereby improving the system’s overall voltage profile.Consequently,the optimal allocation of the STATCOM significantly enhances the efficiency and performance of the power network.展开更多
This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data a...This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.展开更多
The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a ...The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.展开更多
Vertical detection of volatile organic compounds(VOCs)is essential to expend our understanding of the distribution characteristics of VOCs and improve the predictive ability of existing air qualitymodels.In this work,...Vertical detection of volatile organic compounds(VOCs)is essential to expend our understanding of the distribution characteristics of VOCs and improve the predictive ability of existing air qualitymodels.In this work,we report the development of a sorbent tube sampler based on an unmanned aerial vehicle(UAV)platform.Vertical profile measurement of VOCs with a vertical resolution of 25mwas achieved.The sampler consists of five lightweight VOC sorbent tubes and a 5-way solenoid valve,making it available for collecting five atmospheric VOC samples in a single flight with a time response of less than 30min.The samplerweighed∼1.45 kg and had dimensions of 240mm×220mm×100mmwith small penetration loss(<10%)under 4-liter sampling conditions(flow rate of 200 mL/min).Commercialized SUMMA canisters were used as experimental controls to investigate the possible loss of self-made sampler for target compounds in the same sampling process.Comparison experiment on the ground showed that the concentration differences for all VOC species were lower than 0.14μg/m3,proving the good reliability for VOCs measurements using sorbent tube sampler.The UAV platform also incorporated online instruments for meteorological parameters and O_(3) measurement.The sampler was successfully applied to characterize the vertical profiles of VOCs up to 100 m in October 2023 in the Huaihe River Basin of China.The UAV platform and the sorbent tube sampler demonstrate good performance and will be a valuable and reliable tool for vertical VOCs measurement.展开更多
Objectives:Attachment is a profound and enduring connection to the emotion children progressively form with their parents as they mature.It significantly impacts the social and psychological development of kids and te...Objectives:Attachment is a profound and enduring connection to the emotion children progressively form with their parents as they mature.It significantly impacts the social and psychological development of kids and teenagers.This study aimed to explore the latent profiles and longitudinal transition patterns of parent-child and peer attachments among adolescents.Methods:A cohort of 914 participants from China completed the measures with a twelve-month interval.There were 46.8%boys and 53.2%girls in this survey.Latent profile analysis(LPA)was adopted to explore the distinct profiles reflecting different parent-child and peer attachment response patterns at each time point.Latent transition analysis(LTA)was used to examine the membership of distinct latent profiles and how individuals move between profiles over time.Results:Three latent profiles were found:the poor parent-child communication profile,the moderate attachment profile,and the good attachment profile.It was shown that the transition probability from the poor parent-child communication and good attachment profiles to the moderate attachment profile was higher than the transition probability between the poor parent-child communication and good attachment profiles.Patterns of parent-child and peer attachments were associated with depression and anxiety.Conclusion:This study demonstrates differences in adolescents’attachment to fathers,mothers,and peers and the need for targeted interventions for groups of adolescents with moderate levels of parent-child and peer attachment.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
基金supported by grants from the Medical Engineering Jiont Fund of the Fudan University(No.IDH2310117)。
文摘Objective:Triple-negative breast cancer(TNBC)is a highly aggressive subtype that lacks targeted therapies,leading to a poorer prognosis.However,some patients achieve long-term recurrence-free survival(RFS),offering valuable insights into tumor biology and potential treatment strategies.Methods:We conducted a comprehensive multi-omics analysis of 132 patients with American Joint Committee on Cancer(AJCC)stage III TNBC,comprising 36 long-term survivors(RFS≥8 years),62 moderate-term survivors(RFS:3-8 years),and 34 short-term survivors(RFS<3 years).Analyses investigated clinicopathological factors,whole-exome sequencing,germline mutations,copy number alterations(CNAs),RNA sequences,and metabolomic profiles.Results:Long-term survivors exhibited fewer metastatic regional lymph nodes,along with tumors showing reduced stromal fibrosis and lower Ki67 index.Molecularly,these tumors exhibited multiple alterations in genes related to homologous recombination repair,with higher frequencies of germline mutations and somatic CNAs.Additionally,tumors from long-term survivors demonstrated significant downregulation of the RTK-RAS signaling pathway.Metabolomic profiling revealed decreased levels of lipids and carbohydrate,particularly those involved in glycerophospholipid,fructose,and mannose metabolism,in long-term survival group.Multivariate Cox analysis identified fibrosis[hazard ratio(HR):12.70,95%confidence interval(95%CI):2.19-73.54,P=0.005]and RAC1copy number loss/deletion(HR:0.22,95%CI:0.06-0.83,P=0.026)as independent predictors of RFS.Higher fructose/mannose metabolism was associated with worse overall survival(HR:1.30,95%CI:1.01-1.68,P=0.045).Our findings emphasize the association between biological determinants and prolonged survival in patients with TNBC.Conclusions:Our study systematically identified the key molecular and metabolic features associated with prolonged survival in AJCC stage III TNBC,suggesting potential therapeutic targets to improve patient outcomes.
基金the National Natural Science Foundation of China(No.52275378)the National Key Laboratory for Precision Hot Processing of Metals(6142909200208)。
文摘The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.
基金Lin Du acknowledges the financial support provided by China Scholarship Council(CSC)via a Ph.D.Scholarship(202008510128)supported by Core Technology Project of China National Petroleum Corporation(CNPC)"Research on Thermal Miscible Flooding Technology"(2023ZG18)。
文摘CO_(2)-responsive gels,which swell upon contact with CO_(2),are widely used for profile control to plug high-permeability gas flow channels in carbon capture,utilization,and storage(CCUS)applications in oil reser-voirs.However,the use of these gels in high-temperature CCUS applications is limited due to their rever-sible swelling behavior at elevated temperatures.In this study,a novel dispersed particle gel(DPG)suspension is developed for high-temperature profile control in CCUS applications.First,we synthesize a double-network hydrogel consisting of a crosslinked polyacrylamide(PAAm)network and a crosslinked sodium alginate(SA)network.The hydrogel is then sheared in water to form a pre-prepared DPG suspen-sion.To enhance its performance,the gel particles are modified by introducing potassium methylsilan-etriolate(PMS)upon CO_(2) exposure.Comparing the particle size distributions of the modified and pre-prepared DPG suspension reveals a significant swelling of gel particles,over twice their original size.Moreover,subjecting the new DPG suspension to a 100℃ environment for 24 h demonstrates that its gel particle sizes do not decrease,confirming irreversible swelling,which is a significant advantage over the traditional CO_(2)-responsive gels.Thermogravimetric analysis further indicates improved thermal sta-bility compared to the pre-prepared DPG particles.Core flooding experiments show that the new DPG suspension achieves a high plugging efficiency of 95.3%in plugging an ultra-high permeability sandpack,whereas the pre-prepared DPG suspension achieves only 82.8%.With its high swelling ratio,irreversible swelling at high temperatures,enhanced thermal stability,and superior plugging performance,the newly developed DPG suspension in this work presents a highly promising solution for profile control in high-temperature CCUS applications.
基金National Natural Science Foundation of China(Nos.61773387 and 62022061).
文摘A segmented predictor-corrector method is proposed for hypersonic glide vehicles to address the issue of the slow computational speed of obtaining guidance commands using the traditional predictor-corrector guidance method.Firstly,an altitude-energy profile is designed,and the bank angle is derived analytically as the initial iteration value for the predictor-corrector method.The predictor-corrector guidance method has been improved by deriving an analytical form for predicting the range-to-go error,which greatly accelerates the iterative speed.Then,a segmented guidance algorithm is proposed.The above analytically predictor-corrector guidance method is adopted when the energy exceeds an energy threshold.When the energy is less than the threshold,the equidistant test method is used to calculate the bank angle command,which ensures guidance accuracy as well as computational efficiency.Additionally,an adaptive guidance cycle strategy is applied to reduce the computational time of the reentry guidance trajectory.Finally,the accuracy and robustness of the proposed method are verified through a series of simulations and Monte-Carlo experiments.Compared with the traditional integral method,the proposed method requires 75%less computation time on average and achieves a lower landing error.
基金supported by the National Office for Philosophy and Social Sciences(grant reference 22&ZD067).
文摘In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.
基金supported by the National Natural Science Foundation of China(Grant Nos.62472149,62376089,62202147)Hubei Provincial Science and Technology Plan Project(2023BCB04100).
文摘Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
基金supported by the National Science Foundations of China(No.61905256)the National Key Research and Development Program of China(No.2019YFC0214702)the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2020439)。
文摘This study describes the use of the weighted multiplicative algebraic reconstruction technique(WMART)to obtain vertical ozone profiles from limb observations performed by the scanning imaging absorption spectrometer for atmospheric chartography(SCIAMACHY).This technique is based on SaskMART(the combination of the multiplicative algebraic reconstruction technique and SaskTRAN radiative transfer model),which was originally developed for optical spectrometer and infrared imaging system(OSIRIS)data.One of the objectives of this study was to obtain consistent ozone profiles from the two satellites.In this study,the WMART algorithm is combined with a radiative transfer model(SCIATRAN),as well as a set of measurement vectors comprising five Hartley pairing vectors(HPVs)and one Chappuis triplet vector(CTV),to retrieve ozone profiles in the altitude range of 10–69 km.Considering that the weighting factors in WMART have a significant effect on the retrievals,we propose a novel approach to calculate the pair/triplet weighting factors using wavelength weighting functions.The results of the application of the proposed ozone retrieval scheme are compared with the SCIAMACHY v3.5 ozone product by University of Bremen and validated against profiles derived from other passive satellite observations or measured by ozonesondes.Between 18 and 55 km,the retrieved ozone profiles typically agree with data from the SCIAMACHY ozone product within 5%for tropics and middle latitudes,whereas a negative deviation exists between 35 and 50 km for northern high latitudes,with a deviation of less than 10%above 50 km.Comparison of the retrieved profiles with microwave limb sounder(MLS)v5.0 indicates that the difference is within±5%between 18 and 55 km,and an agreement within 10%is achieved in other altitudes for tropics and middle latitudes.Comparison of the retrieved profiles with OSIRIS v7.1 indicates that the average deviation is within±5%between 20 and 59 km,and difference of approximately 10%is achieved below 20 km.Compared with ozonesondes data,a general validity of the retrievals is no more than 5%between 15 and 30 km.
文摘BACKGROUND Disorders of gut-brain interaction(DGBI)are common,but knowledge about their physiopathology is still poor,nor valid tools have been used to evaluate them in childhood.AIM To develop a psycho-gastroenterological questionnaire(PGQ)to assess the psycho-gastroenterological profile and social characteristics of a pediatric population with and without DGBI.METHODS One hundred and nineteen Italian children(age 11-18)were included:28 outpatient patients with DGBI(Rome IV criteria)and 91 healthy controls.They filled the PGQ,faces pain scale revised(FPS-R),Bristol stool chart,ga-strointestinal symptoms rating scale,state-trait anxiety inventory,Toronto alexithymia scale 20,perceived self-efficacy in the management of negative emotions and expression of positive emotions(APEN-G,APEP-G),irritable bowel syndrome-quality of life questionnaire,school performances,tobacco use,early life events,degree of digital-ization.RESULTS Compared to controls,patients had more medical examinations(35%of them went to the doctor more than five times),a higher school performance(23%vs 13%,P<0.05),didn’t use tobacco(never vs 16%,P<0.05),had early life events(28%vs 1%P<0.05)and a higher percentage of pain classified as 4 in the FPS-R during the examination(14%vs 7%,P<0.05).CONCLUSION Pediatric outpatients with DGBI had a higher prevalence of early life events,a lower quality of life,more medical examinations rising health care costs,lower anxiety levels.
基金Guangdong Basic and Applied Basic Research Foundation,Grant/Award Number:2021A1515220030Hunan Provincial Clinical Medical Technology Innovation Guiding Project,Grant/Award Number:2020SK53307+2 种基金Hunan Provincial Health Commission,Grant/Award Number:20201902Natural Science Foundation of Hunan Province,Grant/Award Number:2020JJ8043Project of Hunan Provincial Health,Grant/Award Number:c2019133。
文摘Background:The aim of this study was to analyze the bi-directional causal relation-ship between lipid profile and characteristics related to muscle atrophy by using a bi-directional Mendelian randomization(MR)analysis.Methods:The appendicular lean mass(ALM),whole body fat-free mass(WBFFM)and trunk fat-free mass(TFFM)were used as genome-wide association study(GWAS)data for evaluating muscle mass;the usual walking pace(UWP)and low grip strength(LGS)were used as GWAS data for evaluating muscle strength;and the triglycerides(TG),total cholesterol(TC),high density lipoprotein cholesterol(HDL),low density lipo-protein cholesterol(LDL),apolipoprotein A-1(Apo A-1),and apolipoprotein B(Apo B)were used as GWAS data for evaluating lipid profile.For specific investigations,we mainly employed inverse variance weighting for causal estimation and MR-Egger for pleiotropy analysis.Results:MR results showed that the lipid profile predicted by genetic variants was negatively correlated with muscle mass,positively correlated with UWP,and was not causally correlated with LGS.On the other hand,the muscle mass predicted by genetic variants was negatively correlated with lipid profile,the UWP predicted by genetic variants was mainly positively correlated with lipid profile,while the LGS pre-dicted by genetic variants had no relevant causal relationship with lipid profile.Conclusions:Findings of this MR analysis suggest that hyperlipidemia may affect muscle mass and lead to muscle atrophy,but has no significant effect on muscle strength.On the other hand,increased muscle mass may reduce the incidence of dyslipidemia.
基金Project(JQ2022E004)supported by the Natural Science Foundation of Heilongjiang Province,China。
文摘Traditional manufacturing processes for lightweight curved profiles are often associated with lengthy procedures,high costs,low efficiency,and high energy consumption.In order to solve this problem,a new staggered extrusion(SE)process was used to form the curved profile of AZ31 magnesium alloy in this paper.The study investigates the mapping relationship between the curvature,microstructure,and mechanical properties of the formed profiles by using different eccentricities of the die.Scanning electron microscopy(SEM)and electron backscatter diffraction techniques are employed to examine the effects of different eccentricity values(e)on grain morphology,recrystallization mechanisms,texture,and Schmid factors of the products.The results demonstrate that the staggered extrusion method promotes the deep refinement of grain size in the extruded products,with an average grain size of only 15%of the original billet,reaching 12.28μm.The tensile strength and elongation of the curved profiles after extrusion under the eccentricity value of 10 mm,20 mm and 30 mm are significantly higher than those of the billet,with the tensile strength is increased to 250,270,235 MPa,and the engineering strain elongation increased to 10.5%,12.1%,15.9%.This indicates that staggered extrusion enables curvature control of the profiles while improving their strength.
基金supported by the Beijing Natural Science Foundation(Certificate Number:L234025).
文摘Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.
基金supported by the grants of the National Key Research and Development Program of China(Grant No.2023YFC2508400)the National Natural Science Foundation of China(Grant No.82350005).
文摘Purpose It is essential to investigate the audiological profiles of Williams syndrome in a multicultural context.This study aims to examine the characteristics and management of hearing loss in Chinese children with Williams syndrome and provide references for future clinical management.Method Between January 2007 and March 2022,families with at least 1 WS patient was recruited from the Newborn Cohort Study of Hearing Loss.Audiological tests were performed,and then appropriate medical management was offered.Furthermore,an overview of the hearing loss phenotype in Williams syndrome in different locations was reviewed.Results A total of two families with at least 1 Williams syndrome patient were recruited from the Newborn Cohort Study of Hearing Loss(ChiCTR2100049765).We identified moderately severe sensorineural or conductive hearing loss that emerged as early as the infancy period in Williams syndrome subjects in Chinese children.Our results extended the reported onset ages of hearing loss in WS from late childhood or early adulthood to the infancy period.We also found that with early diagnosis,proper management,and regular monitoring,children with Williams syndrome could return to a normal or near-normal school life.Conclusions Our study demonstrated the distinct hearing profile in Chinese children with Williams syndrome for the first time.This cohort of WS subjects extends the reported onset ages of hearing loss in WS from late childhood or early adulthood to the infancy period,indicating the importance of clinicians screening and monitoring the hearing status of individuals with WS as early as possible.These data provide references for otolaryngologists and paediatricians to inform the clinical understanding and management of hearing loss in Williams syndrome.
文摘Several optimization methods,such as Particle Swarm Optimization(PSO)and Genetic Algorithm(GA),are used to select the most suitable Static Synchronous Compensator(STATCOM)technology for the optimal operation of the power system,as well as to determine its optimal location and size to minimize power losses.An IEEE 14 bus system,integrating three wind turbines based on Squirrel Cage Induction Generators(SCIGs),is used to test the applicability of the proposed algorithms.The results demonstrate that these algorithms are capable of selecting the most appropriate technology while optimally sizing and locating the STATCOM to reduce power losses in the network.Specifically,the optimized STATCOM allocation using the Particle Swarm Optimization(PSO)achieves a 7.44%reduction in total active power loss compared to the optimized allocation using the Genetic Algorithm(GA).Furthermore,the voltage magnitudes at buses 4,9,and 10,which initially had exceeded the upper voltage limit,were reduced and brought within acceptable ranges,thereby improving the system’s overall voltage profile.Consequently,the optimal allocation of the STATCOM significantly enhances the efficiency and performance of the power network.
基金This work is supported by the Ministry of Education of Humanities and Social Science projects in China(No.20YJCZH124)Guangdong Province Education and Teaching Reform Project No.640:Research on the Teaching Practice and Application of Online Peer Assessment Methods in the Context of Artificial Intelligence.
文摘This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.
基金supported in part by the National Natural Science Foundation of China(Nos.61873196,62373030,61772187)the Innovation Program for Quantum Science and Technology(No.2021ZD0303400)。
文摘The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.
基金supported by the National Natural Science Foundation of China(Nos.42022051,U21A2028,and 42305124)the Youth Innovation Promotion Association CAS(No.Y202089)the HFIPS Director’s Fund(Nos.BJPY2023A02,YZJJ202101,and YZJJ2023QN01).
文摘Vertical detection of volatile organic compounds(VOCs)is essential to expend our understanding of the distribution characteristics of VOCs and improve the predictive ability of existing air qualitymodels.In this work,we report the development of a sorbent tube sampler based on an unmanned aerial vehicle(UAV)platform.Vertical profile measurement of VOCs with a vertical resolution of 25mwas achieved.The sampler consists of five lightweight VOC sorbent tubes and a 5-way solenoid valve,making it available for collecting five atmospheric VOC samples in a single flight with a time response of less than 30min.The samplerweighed∼1.45 kg and had dimensions of 240mm×220mm×100mmwith small penetration loss(<10%)under 4-liter sampling conditions(flow rate of 200 mL/min).Commercialized SUMMA canisters were used as experimental controls to investigate the possible loss of self-made sampler for target compounds in the same sampling process.Comparison experiment on the ground showed that the concentration differences for all VOC species were lower than 0.14μg/m3,proving the good reliability for VOCs measurements using sorbent tube sampler.The UAV platform also incorporated online instruments for meteorological parameters and O_(3) measurement.The sampler was successfully applied to characterize the vertical profiles of VOCs up to 100 m in October 2023 in the Huaihe River Basin of China.The UAV platform and the sorbent tube sampler demonstrate good performance and will be a valuable and reliable tool for vertical VOCs measurement.
基金funded by the Shihezi University Innovation and Development Special Project“Research and Application of Knowledge Graph Based Big Data Platform for the Development Trend of College Students’Mental Health”(CXFZSK202205)by the China Young Pioneers Research Topic General Topic(2022YB16).
文摘Objectives:Attachment is a profound and enduring connection to the emotion children progressively form with their parents as they mature.It significantly impacts the social and psychological development of kids and teenagers.This study aimed to explore the latent profiles and longitudinal transition patterns of parent-child and peer attachments among adolescents.Methods:A cohort of 914 participants from China completed the measures with a twelve-month interval.There were 46.8%boys and 53.2%girls in this survey.Latent profile analysis(LPA)was adopted to explore the distinct profiles reflecting different parent-child and peer attachment response patterns at each time point.Latent transition analysis(LTA)was used to examine the membership of distinct latent profiles and how individuals move between profiles over time.Results:Three latent profiles were found:the poor parent-child communication profile,the moderate attachment profile,and the good attachment profile.It was shown that the transition probability from the poor parent-child communication and good attachment profiles to the moderate attachment profile was higher than the transition probability between the poor parent-child communication and good attachment profiles.Patterns of parent-child and peer attachments were associated with depression and anxiety.Conclusion:This study demonstrates differences in adolescents’attachment to fathers,mothers,and peers and the need for targeted interventions for groups of adolescents with moderate levels of parent-child and peer attachment.
