This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administratio...This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administration.The analysis reveals systematic improvements in both track and intensity forecasts over the decade,with distinct error characteristics observed across various forecast parameters.Track forecast errors have steadily decreased,particularly for longer lead times,while error magnitudes have increased with longer forecast lead times.Intensity forecasts show similar progressive enhancements,with maximum sustained wind speed errors decreasing by 0.26 m/s per year for 120 h forecasts.The study also identifies several key patterns in forecast performance:typhoon-grade or stronger TCs exhibit smaller track errors than week or weaker systems;intensity forecasts systematically overestimate weaker TCs while underestimating stronger systems;and spatial error distributions show greater track inaccuracies near landmasses and regional intensity biases.These findings highlight both the significant advances in TC forecasting capability achieved through improved modeling and observational systems,and the remaining challenges in predicting TC changes and landfall behavior,providing valuable benchmarks for future forecast system development.展开更多
The gain-noise model of a single-mode laser driven by correlated additive and multiplicative white noises is investigated theoretically.The analytical expressions of the time-dependent moments and correlation function...The gain-noise model of a single-mode laser driven by correlated additive and multiplicative white noises is investigated theoretically.The analytical expressions of the time-dependent moments and correlation function of the laser intensity are derived by means of linear approximation method.Some novel phenomena are found.In certain cases,instead of monotonic evolution,the evolution curves of the intensity correlation function versus time exhibit the negative minimum value,whereas a peak for the evolution of the normalized variance of the laser intensity with time emerges.展开更多
Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the corr...Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the correlations between energy poverty,energy intensity,resource abundance,and income inequality,as these factors have been theorized to play important roles in influencing energy poverty in developing countries.By observing that the dataset is heterogeneous across the countries and over the time frame,we use the Method of Moments Quantile Regression(MMQR)to analyze our developing countries’data from 2000 to 2019.Our findings indicate that energy intensity is a significant factor influencing energy poverty,suggesting that higher energy consumption relative to the sample countries can exacerbate this issue.Additionally,we observe that income inequality within the sample countries is a critical determinant of energy poverty levels,highlighting the dynamics between economic disparity and access to energy resources.Interestingly,our study reveals that resource abundance acts as a blessing rather than a curse in terms of energy poverty,implying that countries rich in natural resources may have better opportunities to combat energy deprivation.Finally,we emphasize the vital role of financial markets in addressing energy poverty on a global scale,suggesting that robust financial systems can facilitate investments and innovations aimed at improving energy access for vulnerable populations.The results from the robustness analysis support the empirical results obtained from the main estimation.The empirical findings of the present study advance important comprehensions for policymakers to adopt energy policies that address the complex challenges of energy poverty and promote inclusive energy access.展开更多
Catastrophic failure in engineering structures of island reefs would occur when the tertiary creep initiates in coral reef limestone with a transition from short-to long-term load.Due to the complexity of biological s...Catastrophic failure in engineering structures of island reefs would occur when the tertiary creep initiates in coral reef limestone with a transition from short-to long-term load.Due to the complexity of biological structures,the underlying micro-behaviors involving time-dependent deformation are poorly understood.For this,an abnormal phenomenon was observed where the axial and lateral creep deformations were mutually independent by a series of triaxial tests under constant stress and strain rate conditions.The significantly large lateral creep deformation implies that the creep process cannot be described in continuum mechanics regime.Herein,it is hypothesized that sliding mechanism of crystal cleavages dominates the lateral creep deformation in coral reef limestone.Then,approaches of polarizing microscope(PM)and scanning electronic microscope(SEM)are utilized to validate the hypothesis.It shows that the sliding behavior of crystal cleavages combats with conventional creep micro-mechanisms at certain condition.The former is sensitive to time and strain rate,and is merely activated in the creep regime.展开更多
Dispatched by the Chinese government,a multidisciplinary team of 30 researchers collaborated with a team from Myanmar to conduct a 14-day on-site investigation.The work encompassed seismic intensity assessments,field ...Dispatched by the Chinese government,a multidisciplinary team of 30 researchers collaborated with a team from Myanmar to conduct a 14-day on-site investigation.The work encompassed seismic intensity assessments,field surveys,and loss evaluations.The paper focuses on the intensity distribution and structural damage characteristics of the 2025 M7.9 Myanmar earthquake,yielding the following key findings.(1)The seismogenic fault rupture propagated in a nearly N-S direction,with a surface rupture length of approximately 450 km.The seismic impact zone exhibited an elongated N-S distribution and a shorter E-W span,distributed like a belt around the seismogenic fault.(2)Within the seismic impact zones,existing buildings comprised five primary structural types,with timber(bamboo)structures constituting the largest proportion(≈80%in rural areas,≈50%in urban areas).The relatively low disaster losses and casualties were primarily attributable to the good seismic performance and low damage ratio of timber(bamboo)structures across varying intensity zones.(3)An anomalous zone of intensityⅨwas located at the boundary between intensityⅥandⅦregions in Nay Pyi Taw.Here,ridge topography combined with soft soil layers significantly amplified ground motion,exacerbating structural damage.(4)Directional effects of ground motion were observed,with the structural damage phenomena and peak ground acceleration(PGA)values in the N-S direction exceeding those in the E-W direction.This validates that the maximum PGA distribution of strike-slip fault earthquakes aligns with the fault strike.The research is expected to provide technical support for post-disaster reconstruction planning,site selection,and disaster mitigation strategies in Myanmar.展开更多
With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic...With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential equation.The results in this paper depend on all the oceanic variable coefficients in that equation.展开更多
The 2025 M_(w)7.7 Myanmar earthquake highlighted the challenge of near-fault seismic intensity field reconstruction due to sparse seismic networks.To address this limitation,a framework was proposed integrating seismi...The 2025 M_(w)7.7 Myanmar earthquake highlighted the challenge of near-fault seismic intensity field reconstruction due to sparse seismic networks.To address this limitation,a framework was proposed integrating seismic wave simulation with a data-constrained finite-fault rupture model.The constraint is implemented by identifying the optimal ground motion models(GMMs)through a scoring system that selects the best-fit GMMs to mid-and far-field China Earthquake Networks Center(CENC)seismic network data;and applying the optimal GMMs to refine the rupture model parameters for near-fault intensity field simulation.The simulated near-fault seismic intensity field reproduces seismic intensities collected from Myanmar’s sparse seismic network and concentrated in≥Ⅷintensity zones within 50 km of the projected fault plane;and identifies abnormal intensity regions exhibiting≥Ⅹintensity along the Meiktila-Naypyidaw corridor and near Shwebo that are attributed to soft soil amplification effects and near-fault directivity.This framework can also be applied to post-earthquake assessments in other similar regions.展开更多
The field of diffusion micro structural magnetic resonance(MR)aims to probe timedependent diffusion,i.e.,an ensemble-averaged mean-squared displacement that is not linear in time.This time-dependence contains rich inf...The field of diffusion micro structural magnetic resonance(MR)aims to probe timedependent diffusion,i.e.,an ensemble-averaged mean-squared displacement that is not linear in time.This time-dependence contains rich information about the surrounding microenvironment.MR methods to measure time-dependent diffusion quantitatively,however,require either non-standard pulse sequences,such as oscillating gradients,or make non-physical assumptions,such as infinitely narrow gradient pulses.Here,we argue that standard spin echo and stimulated echo MR sequences can be used to probe directly.In particular,we propose a framework in which the log-signal ratio obtained from a pair of measurements with different inter-pulse spacingΔis proportional to the MSD between these twoΔvalues along the gradient direction x:-.The framework is quantitative for short,finite-duration gradient pulses and under the Gaussian phase approximation(GPA).To validate the framework,we consider onedimensional diffusion between impermeable,parallel planes,as well as periodicallyspaced,permeable planes.Excellent agreement is obtained between the estimation and the ground truth in the regime where the GPA is expected to hold.Importantly,the GPA can be made to hold for any underlying microstructure,making the proposed framework widely applicable.展开更多
One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are ...One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.展开更多
This article first outlines the fundamental definitions of Mycoplasma pneumoniae and the basic principles of antibiotics. It then analyzes and discusses the progress in antibiotic application and time-eff ect studies ...This article first outlines the fundamental definitions of Mycoplasma pneumoniae and the basic principles of antibiotics. It then analyzes and discusses the progress in antibiotic application and time-eff ect studies for neonatal pneumonia treatment, specifically comparing conventional antibiotic therapy with stepwise treatment regimens, and contrasting monotherapy with penicillin, monotherapy with cephalosporins, and combination therapy. Finally, it offers a prospective outlook on antibiotic application and time-effect research in neonatal pneumonia treatment, aiming to provide valuable reference for further scholarly investigations.展开更多
Tropical cyclones(TCs)are one of the most serious types of natural disasters,and accurate TC activity predictions are key to disaster prevention and mitigation.Recently,TC track predictions have made significant progr...Tropical cyclones(TCs)are one of the most serious types of natural disasters,and accurate TC activity predictions are key to disaster prevention and mitigation.Recently,TC track predictions have made significant progress,but the ability to predict their intensity is obviously lagging behind.At present,research on TC intensity prediction takes atmospheric reanalysis data as the research object and mines the relationship between TC-related environmental factors and intensity through deep learning.However,reanalysis data are non-real-time in nature,which does not meet the requirements for operational forecasting applications.Therefore,a TC intensity prediction model named TC-Rolling is proposed,which can simultaneously extract the degree of symmetry for strong TC convective cloud and convection intensity,and fuse the deviation-angle variance with satellite images to construct the correlation between TC convection structure and intensity.For TCs'complex dynamic processes,a convolutional neural network(CNN)is used to learn their temporal and spatial features.For real-time intensity estimation,multi-task learning acts as an implicit time-series enhancement.The model is designed with a rolling strategy that aims to moderate the long-term dependent decay problem and improve accuracy for short-term intensity predictions.Since multiple tasks are correlated,the loss function of 12 h and 24 h are corrected.After testing on a sample of TCs in the Northwest Pacific,with a 4.48 kt root-mean-square error(RMSE)of 6 h intensity prediction,5.78 kt for 12 h,and 13.94 kt for 24 h,TC records from official agencies are used to assess the validity of TC-Rolling.展开更多
Heat transfers at the interface of adjacent saturated soil primarily through the soil particles and the water in the voids.The presence of water induces the contraction of heat flow lines at the interface,leading to t...Heat transfers at the interface of adjacent saturated soil primarily through the soil particles and the water in the voids.The presence of water induces the contraction of heat flow lines at the interface,leading to the emergence of the thermal contact resistance effect.In this paper,four thermal contact models were developed to predict the thermal contact resistance at the interface of multilayered saturated soils.Based on the theory of thermal-hydro-mechanical coupling,semi-analytical solutions of thermal consolidation subjected to time-dependent heating and loading were obtained by employing Laplace transform and its inverse transformation.Thermal consolidation characteristics of multilayered saturated soils under four different thermal contact models were discussed,and the effects of thermal resistance coefficient,partition thermal contact coefficient,and temperature amplitude on the thermal consolidation process were investigated.The outcomes indicate that the general thermal contact model results in the most pronounced thermal gradient at the interface,which can be degenerated to the other three thermal contact models.The perfect thermal contact model overestimates the deformation of the saturated soil during the thermal consolidation.Moreover,the effect of temperature on consolidation properties decreases gradually with increasing interfacial contact thermal resistance.展开更多
Ultra-intense electromagnetic fields exceeding 10^(23)W∕cm^(2)are enabling breakthroughs in compact laser-driven particle accelerators and revealing new quantum electrodynamics(QED)phenomena.However,conventional lase...Ultra-intense electromagnetic fields exceeding 10^(23)W∕cm^(2)are enabling breakthroughs in compact laser-driven particle accelerators and revealing new quantum electrodynamics(QED)phenomena.However,conventional laser-focusing methods face considerable engineering challenges and require substantial costs.Focusing schemes utilizing plasma optics can produce sub-micrometer focus spots beyond the diffraction limit and substantially enhance the peak intensity;however,owing to significant energy dissipation,they may fail to simultaneously increase the laser fluence.To address these challenges,we propose a focusing scheme employing a near-critical-density hollow plasma fiber(HPF)that utilizes graded refractive index dynamics to boost both laser peak intensity and fluence at the same time.Three-dimensional particle-in-cell simulations demonstrate the HPF’s capability to focus a 4.5-μm-diameter Gaussian beam to a sub-diffraction-limited 0.6-μm-diameter spot.The peak intensity and laser fluence can be enhanced by factors of 22 and 10,respectively,marking a substantial improvement over existing plasma-based focusing schemes.Furthermore,the proposed scheme exhibits wide-range parameter adaptation and high robustness,making it suitable for direct implementation in PW-class ultra-intense laser experiments.展开更多
The Zagros Basin in southwestern Iran is a significant source of coal,with numerous coal mines operating in the region.Ensuring the stability of coal mines is crucial for safe and efficient mining operations.This stud...The Zagros Basin in southwestern Iran is a significant source of coal,with numerous coal mines operating in the region.Ensuring the stability of coal mines is crucial for safe and efficient mining operations.This study investigates the time-varying response of rocks and roof resistance in coal mines in the Zagros Mountains using a novel approach that combines numerical simulation,relaxation testing,and rock displacement studies.The results show that rocks exhibit significant time-dependent behavior,with changes in rock mechanical properties over time.A comprehensive viscoelastic-plastic model is devel-oped to accurately describe the time-varying strain-softening response of rocks and simulate laboratory tests.The model integrates the Burgers and strain-softening models,simulating stress relaxation curves and rock displacement over time.The study reveals that the rock mass displays significant nonlinear behavior,with changes in rock mechanical properties over time.The findings of this study highlight the importance of considering the time-varying response of rocks and roof resistance in coal mine stability analysis.The results provide valuable insights into the time-dependent behavior of rock mass in coal mines in Iran,which can inform mining practices and mitigate potential hazards.Results in this study can contribute to developing strategies for improving roof stability and reducing the likelihood of roof collapses.展开更多
High-Intensity Interval Training(HIIT)has gained prominence as a time-efficient and effective exercise modality to improve cardiovascular(CV)fitness,metabolic health,and physical performance.Therefore,our aim was to s...High-Intensity Interval Training(HIIT)has gained prominence as a time-efficient and effective exercise modality to improve cardiovascular(CV)fitness,metabolic health,and physical performance.Therefore,our aim was to synthesize current clinical research on the effects of HIIT on the Autonomic Nervous System.We conducted the search for studies in the Directory of Open Access Journals,Embase,Virtual Health Library,Pubmed,and Scielo databases,in January of 2024.We included a total of 20 studies in our review.This literature review highlights the potential of HIIT to modulate the Autonomic Nervous System,enhancing CV function and overall health.Despite the promising findings,the interpretation of the results is tempered by the variability in study designs,populations,and methodologies.Future research should address these limitations,aiming for a more nuanced understanding of the relationship between HIIT and Autonomic Nervous System function.The review indicates that standardized protocols need to consider individual characteristics and baseline autonomic states for clinical application.As the body of evidence grows,HIIT may emerge as a cornerstone of exercise prescriptions aimed at optimizing autonomic function and promoting CV health.展开更多
We investigated the effects of high-intensity intermittent cross-training(HIICT)on maximal oxygen uptake(VO_(2)max).The HIICT consisted of alternating intermittent 20-s treadmill running(1^(st),3^(rd),5^(th),and 7^(th...We investigated the effects of high-intensity intermittent cross-training(HIICT)on maximal oxygen uptake(VO_(2)max).The HIICT consisted of alternating intermittent 20-s treadmill running(1^(st),3^(rd),5^(th),and 7^(th) bouts)and 20-s bicycle exercise(2^(nd),4^(th),and 6^(th) bouts)with a 10-s rest period.Each intensity for running and bicycling of the HIICT corresponded to an oxygen demand of~160% and~170%of the VO_(2)max,respectively.Fifteen healthy young males(aged[24±1]yrs)were randomly assigned to training(TG,n?8)and non-training control(CG,n?7)groups.The TG completed this HIICT daily 4 days/week for 6 weeks.Significant group×time interactions were observed for both the running and bicycling VO_(2)max(p<0.001 each).After the training,the VO_(2)max for both running([57.4±4.8]mL·kg^(-1)·min^(-1))and bicycling([50.6±3.7]mL·kg^(-1)·min^(-1))in the TG were significantly higher than those for running([50.1±3.1]mL·kg^(-1)·min^(-1))and bicycling([43.7±3.6]mL·kg^(-1)·min^(-1))in the CG,respectively(p<0.01 each).Post-hoc tests revealed a significant increase in VO_(2)max for running and bicycling in the TG after the HIICT(p<0.001 each)but no significant difference in the CG.These results demonstrated that the newly developed HIICT increases the VO_(2)max for both running and bicycling.展开更多
Positive emotional experiences can improve learning efficiency and cognitive ability,stimulate students’interest in learning,and improve teacher-student relationships.However,positive emotions in the classroom are pr...Positive emotional experiences can improve learning efficiency and cognitive ability,stimulate students’interest in learning,and improve teacher-student relationships.However,positive emotions in the classroom are primarily identified through teachers’observations and postclass questionnaires or interviews.The expression intensity of students,which is extremely important for fine-grained emotion analysis,is not considered.Hence,a novel method based on smile intensity estimation using sequence-relative key-frame labeling is presented.This method aims to recognize the positive emotion levels of a student in an end-to-end framework.First,the intensity label is generated robustly for each frame in the expression sequence based on the relative key frames to address the lack of annotations for smile intensity.Then,a deep-asymmetric convolutional neural network learns the expression model through dual neural networks,to enhance the stability of the network model and avoid the extreme attention region learned.Further,dual neural networks and the dual attention mechanism are integrated using the intensity label based on the relative key frames as the supervised information.Thus,diverse features are effectively extracted and subtle appearance differences between different smiles are perceived based on different perspectives.Finally,comparative experiments for the convergence speed,model-training parameters,confusion matrix,and classification probability are performed.The proposed method was applied to a real classroom scene to analyze the emotions of students.Numerous experiments validated that the proposed method is promising for analyzing the differences in the positive emotion of students while learning in a classroom.展开更多
In the implementation of quantum key distribution,Security certification is a prerequisite for social deployment.Trans-mitters in decoy-BB84 systems typically employ gain-switched semiconductor lasers(GSSLs)to generat...In the implementation of quantum key distribution,Security certification is a prerequisite for social deployment.Trans-mitters in decoy-BB84 systems typically employ gain-switched semiconductor lasers(GSSLs)to generate optical pulses for encod-ing quantum information.However,the working state of the laser may violate the assumption of pulse independence.Here,we explored the dependence of intensity fluctuation and high-order correlation distribution of optical pulses on driving cur-rents at 2.5 GHz.We found the intensity correlation distribution had a significant dependence on the driving currents,which would affect the final key rate.By utilizing rate equations in our simulation,we confirmed the fluctuation and correlation origi-nated from the instability of gain-switched laser driven at a GHz-repetitive frequency.Finally,we evaluated the impact of inten-sity fluctuation on the secure key rate.This work will provide valuable insights for assessing whether the transmitter is operat-ing at optimal state in practice.展开更多
Tropical cyclone(TC)intensity estimation is a fundamental aspect of TC monitoring and forecasting.Deep learning models have recently been employed to estimate TC intensity from satellite images and yield precise resul...Tropical cyclone(TC)intensity estimation is a fundamental aspect of TC monitoring and forecasting.Deep learning models have recently been employed to estimate TC intensity from satellite images and yield precise results.This work proposes the ViT-TC model based on the Vision Transformer(ViT)architecture.Satellite images of TCs,including infrared(IR),water vapor(WV),and passive microwave(PMW),are used as inputs for intensity estimation.Experiments indicate that combining IR,WV,and PMW as inputs yields more accurate estimations than other channel combinations.The ensemble mean technique is applied to enhance the model's estimations,reducing the root-mean-square error to 9.32 kt(knots,1 kt≈0.51 m s^(-1))and the mean absolute error to 6.49 kt,which outperforms traditional methods and is comparable to existing deep learning models.The model assigns high attention weights to areas with high PMW,indicating that PMW magnitude is essential information for the model's estimation.The model also allocates significance to the cloud-cover region,suggesting that the model utilizes the whole TC cloud structure and TC eye to determine TC intensity.展开更多
Reference-frame-independent quantum key distribution(RFI-QKD)can avoid real-time calibration operation of reference frames and improve the efficiency of the communication process.However,due to imperfections of optica...Reference-frame-independent quantum key distribution(RFI-QKD)can avoid real-time calibration operation of reference frames and improve the efficiency of the communication process.However,due to imperfections of optical devices,there will inevitably exist intensity fluctuations in the source side of the QKD system,which will affect the final secure key rate.To reduce the influence of intensity fluctuations,an improved 3-intensity RFI-QKD scheme is proposed in this paper.After considering statistical fluctuations and implementing global parameter optimization,we conduct corresponding simulation analysis.The results show that our present work can present both higher key rate and a farther transmission distance than the standard method.展开更多
基金supported by the National Key R&D Program of China [grant number 2023YFC3008004]。
文摘This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administration.The analysis reveals systematic improvements in both track and intensity forecasts over the decade,with distinct error characteristics observed across various forecast parameters.Track forecast errors have steadily decreased,particularly for longer lead times,while error magnitudes have increased with longer forecast lead times.Intensity forecasts show similar progressive enhancements,with maximum sustained wind speed errors decreasing by 0.26 m/s per year for 120 h forecasts.The study also identifies several key patterns in forecast performance:typhoon-grade or stronger TCs exhibit smaller track errors than week or weaker systems;intensity forecasts systematically overestimate weaker TCs while underestimating stronger systems;and spatial error distributions show greater track inaccuracies near landmasses and regional intensity biases.These findings highlight both the significant advances in TC forecasting capability achieved through improved modeling and observational systems,and the remaining challenges in predicting TC changes and landfall behavior,providing valuable benchmarks for future forecast system development.
文摘The gain-noise model of a single-mode laser driven by correlated additive and multiplicative white noises is investigated theoretically.The analytical expressions of the time-dependent moments and correlation function of the laser intensity are derived by means of linear approximation method.Some novel phenomena are found.In certain cases,instead of monotonic evolution,the evolution curves of the intensity correlation function versus time exhibit the negative minimum value,whereas a peak for the evolution of the normalized variance of the laser intensity with time emerges.
文摘Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the correlations between energy poverty,energy intensity,resource abundance,and income inequality,as these factors have been theorized to play important roles in influencing energy poverty in developing countries.By observing that the dataset is heterogeneous across the countries and over the time frame,we use the Method of Moments Quantile Regression(MMQR)to analyze our developing countries’data from 2000 to 2019.Our findings indicate that energy intensity is a significant factor influencing energy poverty,suggesting that higher energy consumption relative to the sample countries can exacerbate this issue.Additionally,we observe that income inequality within the sample countries is a critical determinant of energy poverty levels,highlighting the dynamics between economic disparity and access to energy resources.Interestingly,our study reveals that resource abundance acts as a blessing rather than a curse in terms of energy poverty,implying that countries rich in natural resources may have better opportunities to combat energy deprivation.Finally,we emphasize the vital role of financial markets in addressing energy poverty on a global scale,suggesting that robust financial systems can facilitate investments and innovations aimed at improving energy access for vulnerable populations.The results from the robustness analysis support the empirical results obtained from the main estimation.The empirical findings of the present study advance important comprehensions for policymakers to adopt energy policies that address the complex challenges of energy poverty and promote inclusive energy access.
基金supported by the National Natural Science Foundation of China(Grant Nos.41877267,41877260)the Priority Research Program of the Chinese Academy of Science(Grant No.XDA13010201).
文摘Catastrophic failure in engineering structures of island reefs would occur when the tertiary creep initiates in coral reef limestone with a transition from short-to long-term load.Due to the complexity of biological structures,the underlying micro-behaviors involving time-dependent deformation are poorly understood.For this,an abnormal phenomenon was observed where the axial and lateral creep deformations were mutually independent by a series of triaxial tests under constant stress and strain rate conditions.The significantly large lateral creep deformation implies that the creep process cannot be described in continuum mechanics regime.Herein,it is hypothesized that sliding mechanism of crystal cleavages dominates the lateral creep deformation in coral reef limestone.Then,approaches of polarizing microscope(PM)and scanning electronic microscope(SEM)are utilized to validate the hypothesis.It shows that the sliding behavior of crystal cleavages combats with conventional creep micro-mechanisms at certain condition.The former is sensitive to time and strain rate,and is merely activated in the creep regime.
基金National Natural Science Foundation of China under Grant No.U2239252National Natural Science Foundation of China under Grant No.52279128Natural Science Foundation of Heilongjiang Province of China under Grant No.YQ2022E013。
文摘Dispatched by the Chinese government,a multidisciplinary team of 30 researchers collaborated with a team from Myanmar to conduct a 14-day on-site investigation.The work encompassed seismic intensity assessments,field surveys,and loss evaluations.The paper focuses on the intensity distribution and structural damage characteristics of the 2025 M7.9 Myanmar earthquake,yielding the following key findings.(1)The seismogenic fault rupture propagated in a nearly N-S direction,with a surface rupture length of approximately 450 km.The seismic impact zone exhibited an elongated N-S distribution and a shorter E-W span,distributed like a belt around the seismogenic fault.(2)Within the seismic impact zones,existing buildings comprised five primary structural types,with timber(bamboo)structures constituting the largest proportion(≈80%in rural areas,≈50%in urban areas).The relatively low disaster losses and casualties were primarily attributable to the good seismic performance and low damage ratio of timber(bamboo)structures across varying intensity zones.(3)An anomalous zone of intensityⅨwas located at the boundary between intensityⅥandⅦregions in Nay Pyi Taw.Here,ridge topography combined with soft soil layers significantly amplified ground motion,exacerbating structural damage.(4)Directional effects of ground motion were observed,with the structural damage phenomena and peak ground acceleration(PGA)values in the N-S direction exceeding those in the E-W direction.This validates that the maximum PGA distribution of strike-slip fault earthquakes aligns with the fault strike.The research is expected to provide technical support for post-disaster reconstruction planning,site selection,and disaster mitigation strategies in Myanmar.
基金financially supported by the Scientific Research Foundation of North China University of Technology(Grant Nos.11005136024XN147-87 and 110051360024XN151-86).
文摘With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential equation.The results in this paper depend on all the oceanic variable coefficients in that equation.
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant No.2023C01National Natural Science Foundation of China under Grant No.52478570Distinguished Young Scholars Program of the Natural Science Foundation of Heilongjiang Province,China under Grant No.JQ2024E002。
文摘The 2025 M_(w)7.7 Myanmar earthquake highlighted the challenge of near-fault seismic intensity field reconstruction due to sparse seismic networks.To address this limitation,a framework was proposed integrating seismic wave simulation with a data-constrained finite-fault rupture model.The constraint is implemented by identifying the optimal ground motion models(GMMs)through a scoring system that selects the best-fit GMMs to mid-and far-field China Earthquake Networks Center(CENC)seismic network data;and applying the optimal GMMs to refine the rupture model parameters for near-fault intensity field simulation.The simulated near-fault seismic intensity field reproduces seismic intensities collected from Myanmar’s sparse seismic network and concentrated in≥Ⅷintensity zones within 50 km of the projected fault plane;and identifies abnormal intensity regions exhibiting≥Ⅹintensity along the Meiktila-Naypyidaw corridor and near Shwebo that are attributed to soft soil amplification effects and near-fault directivity.This framework can also be applied to post-earthquake assessments in other similar regions.
基金supported by the intramural research program(IRP)of the Eunice Kennedy Shriver National Institute of Child Health and Human Development。
文摘The field of diffusion micro structural magnetic resonance(MR)aims to probe timedependent diffusion,i.e.,an ensemble-averaged mean-squared displacement that is not linear in time.This time-dependence contains rich information about the surrounding microenvironment.MR methods to measure time-dependent diffusion quantitatively,however,require either non-standard pulse sequences,such as oscillating gradients,or make non-physical assumptions,such as infinitely narrow gradient pulses.Here,we argue that standard spin echo and stimulated echo MR sequences can be used to probe directly.In particular,we propose a framework in which the log-signal ratio obtained from a pair of measurements with different inter-pulse spacingΔis proportional to the MSD between these twoΔvalues along the gradient direction x:-.The framework is quantitative for short,finite-duration gradient pulses and under the Gaussian phase approximation(GPA).To validate the framework,we consider onedimensional diffusion between impermeable,parallel planes,as well as periodicallyspaced,permeable planes.Excellent agreement is obtained between the estimation and the ground truth in the regime where the GPA is expected to hold.Importantly,the GPA can be made to hold for any underlying microstructure,making the proposed framework widely applicable.
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant No.2024B08。
文摘One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.
文摘This article first outlines the fundamental definitions of Mycoplasma pneumoniae and the basic principles of antibiotics. It then analyzes and discusses the progress in antibiotic application and time-eff ect studies for neonatal pneumonia treatment, specifically comparing conventional antibiotic therapy with stepwise treatment regimens, and contrasting monotherapy with penicillin, monotherapy with cephalosporins, and combination therapy. Finally, it offers a prospective outlook on antibiotic application and time-effect research in neonatal pneumonia treatment, aiming to provide valuable reference for further scholarly investigations.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.42075138 and 42375147)the Program on Key Basic Research Project of Jiangsu(Grant No.BE2023829)。
文摘Tropical cyclones(TCs)are one of the most serious types of natural disasters,and accurate TC activity predictions are key to disaster prevention and mitigation.Recently,TC track predictions have made significant progress,but the ability to predict their intensity is obviously lagging behind.At present,research on TC intensity prediction takes atmospheric reanalysis data as the research object and mines the relationship between TC-related environmental factors and intensity through deep learning.However,reanalysis data are non-real-time in nature,which does not meet the requirements for operational forecasting applications.Therefore,a TC intensity prediction model named TC-Rolling is proposed,which can simultaneously extract the degree of symmetry for strong TC convective cloud and convection intensity,and fuse the deviation-angle variance with satellite images to construct the correlation between TC convection structure and intensity.For TCs'complex dynamic processes,a convolutional neural network(CNN)is used to learn their temporal and spatial features.For real-time intensity estimation,multi-task learning acts as an implicit time-series enhancement.The model is designed with a rolling strategy that aims to moderate the long-term dependent decay problem and improve accuracy for short-term intensity predictions.Since multiple tasks are correlated,the loss function of 12 h and 24 h are corrected.After testing on a sample of TCs in the Northwest Pacific,with a 4.48 kt root-mean-square error(RMSE)of 6 h intensity prediction,5.78 kt for 12 h,and 13.94 kt for 24 h,TC records from official agencies are used to assess the validity of TC-Rolling.
基金Projects(U24B20113,42477162) supported by the National Natural Science Foundation of ChinaProject(2025C02228) supported by the Primary Research and Development Plan of Zhejiang Province,China。
文摘Heat transfers at the interface of adjacent saturated soil primarily through the soil particles and the water in the voids.The presence of water induces the contraction of heat flow lines at the interface,leading to the emergence of the thermal contact resistance effect.In this paper,four thermal contact models were developed to predict the thermal contact resistance at the interface of multilayered saturated soils.Based on the theory of thermal-hydro-mechanical coupling,semi-analytical solutions of thermal consolidation subjected to time-dependent heating and loading were obtained by employing Laplace transform and its inverse transformation.Thermal consolidation characteristics of multilayered saturated soils under four different thermal contact models were discussed,and the effects of thermal resistance coefficient,partition thermal contact coefficient,and temperature amplitude on the thermal consolidation process were investigated.The outcomes indicate that the general thermal contact model results in the most pronounced thermal gradient at the interface,which can be degenerated to the other three thermal contact models.The perfect thermal contact model overestimates the deformation of the saturated soil during the thermal consolidation.Moreover,the effect of temperature on consolidation properties decreases gradually with increasing interfacial contact thermal resistance.
基金supported by the National Grand Instrument Project(Grant No.2019YFF01014402)the National Key Research and Development Program of China(Grant No.2024YFF0726304)+2 种基金the Guangdong High Level Innovation Research Institute(Grant No.2021B0909050006)the National Natural Science Foundation of China(Grant No.12205008)W.Ma acknowledges support from the National Science Fund for Distinguished Young Scholars(Grant No.12225501)。
文摘Ultra-intense electromagnetic fields exceeding 10^(23)W∕cm^(2)are enabling breakthroughs in compact laser-driven particle accelerators and revealing new quantum electrodynamics(QED)phenomena.However,conventional laser-focusing methods face considerable engineering challenges and require substantial costs.Focusing schemes utilizing plasma optics can produce sub-micrometer focus spots beyond the diffraction limit and substantially enhance the peak intensity;however,owing to significant energy dissipation,they may fail to simultaneously increase the laser fluence.To address these challenges,we propose a focusing scheme employing a near-critical-density hollow plasma fiber(HPF)that utilizes graded refractive index dynamics to boost both laser peak intensity and fluence at the same time.Three-dimensional particle-in-cell simulations demonstrate the HPF’s capability to focus a 4.5-μm-diameter Gaussian beam to a sub-diffraction-limited 0.6-μm-diameter spot.The peak intensity and laser fluence can be enhanced by factors of 22 and 10,respectively,marking a substantial improvement over existing plasma-based focusing schemes.Furthermore,the proposed scheme exhibits wide-range parameter adaptation and high robustness,making it suitable for direct implementation in PW-class ultra-intense laser experiments.
文摘The Zagros Basin in southwestern Iran is a significant source of coal,with numerous coal mines operating in the region.Ensuring the stability of coal mines is crucial for safe and efficient mining operations.This study investigates the time-varying response of rocks and roof resistance in coal mines in the Zagros Mountains using a novel approach that combines numerical simulation,relaxation testing,and rock displacement studies.The results show that rocks exhibit significant time-dependent behavior,with changes in rock mechanical properties over time.A comprehensive viscoelastic-plastic model is devel-oped to accurately describe the time-varying strain-softening response of rocks and simulate laboratory tests.The model integrates the Burgers and strain-softening models,simulating stress relaxation curves and rock displacement over time.The study reveals that the rock mass displays significant nonlinear behavior,with changes in rock mechanical properties over time.The findings of this study highlight the importance of considering the time-varying response of rocks and roof resistance in coal mine stability analysis.The results provide valuable insights into the time-dependent behavior of rock mass in coal mines in Iran,which can inform mining practices and mitigate potential hazards.Results in this study can contribute to developing strategies for improving roof stability and reducing the likelihood of roof collapses.
文摘High-Intensity Interval Training(HIIT)has gained prominence as a time-efficient and effective exercise modality to improve cardiovascular(CV)fitness,metabolic health,and physical performance.Therefore,our aim was to synthesize current clinical research on the effects of HIIT on the Autonomic Nervous System.We conducted the search for studies in the Directory of Open Access Journals,Embase,Virtual Health Library,Pubmed,and Scielo databases,in January of 2024.We included a total of 20 studies in our review.This literature review highlights the potential of HIIT to modulate the Autonomic Nervous System,enhancing CV function and overall health.Despite the promising findings,the interpretation of the results is tempered by the variability in study designs,populations,and methodologies.Future research should address these limitations,aiming for a more nuanced understanding of the relationship between HIIT and Autonomic Nervous System function.The review indicates that standardized protocols need to consider individual characteristics and baseline autonomic states for clinical application.As the body of evidence grows,HIIT may emerge as a cornerstone of exercise prescriptions aimed at optimizing autonomic function and promoting CV health.
基金supported in part by a Grant-in-Aid for Scientific Research(C)(no.24K14417)from the Japan Society for the Promotion of Sciences(JSPS)KAKENHI.
文摘We investigated the effects of high-intensity intermittent cross-training(HIICT)on maximal oxygen uptake(VO_(2)max).The HIICT consisted of alternating intermittent 20-s treadmill running(1^(st),3^(rd),5^(th),and 7^(th) bouts)and 20-s bicycle exercise(2^(nd),4^(th),and 6^(th) bouts)with a 10-s rest period.Each intensity for running and bicycling of the HIICT corresponded to an oxygen demand of~160% and~170%of the VO_(2)max,respectively.Fifteen healthy young males(aged[24±1]yrs)were randomly assigned to training(TG,n?8)and non-training control(CG,n?7)groups.The TG completed this HIICT daily 4 days/week for 6 weeks.Significant group×time interactions were observed for both the running and bicycling VO_(2)max(p<0.001 each).After the training,the VO_(2)max for both running([57.4±4.8]mL·kg^(-1)·min^(-1))and bicycling([50.6±3.7]mL·kg^(-1)·min^(-1))in the TG were significantly higher than those for running([50.1±3.1]mL·kg^(-1)·min^(-1))and bicycling([43.7±3.6]mL·kg^(-1)·min^(-1))in the CG,respectively(p<0.01 each).Post-hoc tests revealed a significant increase in VO_(2)max for running and bicycling in the TG after the HIICT(p<0.001 each)but no significant difference in the CG.These results demonstrated that the newly developed HIICT increases the VO_(2)max for both running and bicycling.
基金supported in part by the National Natural Science Foundation of China(62067003,61967010,62262030)Key Project of Science and Technology Research of Education Department of Jiangxi Province(GJJ210309)Jiangxi Provincial Natural Science Foundation Youth Foundation(2024BAB20047).
文摘Positive emotional experiences can improve learning efficiency and cognitive ability,stimulate students’interest in learning,and improve teacher-student relationships.However,positive emotions in the classroom are primarily identified through teachers’observations and postclass questionnaires or interviews.The expression intensity of students,which is extremely important for fine-grained emotion analysis,is not considered.Hence,a novel method based on smile intensity estimation using sequence-relative key-frame labeling is presented.This method aims to recognize the positive emotion levels of a student in an end-to-end framework.First,the intensity label is generated robustly for each frame in the expression sequence based on the relative key frames to address the lack of annotations for smile intensity.Then,a deep-asymmetric convolutional neural network learns the expression model through dual neural networks,to enhance the stability of the network model and avoid the extreme attention region learned.Further,dual neural networks and the dual attention mechanism are integrated using the intensity label based on the relative key frames as the supervised information.Thus,diverse features are effectively extracted and subtle appearance differences between different smiles are perceived based on different perspectives.Finally,comparative experiments for the convergence speed,model-training parameters,confusion matrix,and classification probability are performed.The proposed method was applied to a real classroom scene to analyze the emotions of students.Numerous experiments validated that the proposed method is promising for analyzing the differences in the positive emotion of students while learning in a classroom.
基金support from the National Natural Science Foundation of China(62250710162).
文摘In the implementation of quantum key distribution,Security certification is a prerequisite for social deployment.Trans-mitters in decoy-BB84 systems typically employ gain-switched semiconductor lasers(GSSLs)to generate optical pulses for encod-ing quantum information.However,the working state of the laser may violate the assumption of pulse independence.Here,we explored the dependence of intensity fluctuation and high-order correlation distribution of optical pulses on driving cur-rents at 2.5 GHz.We found the intensity correlation distribution had a significant dependence on the driving currents,which would affect the final key rate.By utilizing rate equations in our simulation,we confirmed the fluctuation and correlation origi-nated from the instability of gain-switched laser driven at a GHz-repetitive frequency.Finally,we evaluated the impact of inten-sity fluctuation on the secure key rate.This work will provide valuable insights for assessing whether the transmitter is operat-ing at optimal state in practice.
基金Research funding for this project was provided by the National Natural Science Foundation of China(Grant Nos.42192563 and 42120104001)the Hong Kong RGC General Research Fund(Grant No.11300920)+1 种基金Anhui Provincial Natural Science Foundation(Grant Nos.2208085UQ12,2308085US01)Anhui&Huaihe River Institute of Hydraulic Research(Grant Nos.KJGG202201,KY202306)。
文摘Tropical cyclone(TC)intensity estimation is a fundamental aspect of TC monitoring and forecasting.Deep learning models have recently been employed to estimate TC intensity from satellite images and yield precise results.This work proposes the ViT-TC model based on the Vision Transformer(ViT)architecture.Satellite images of TCs,including infrared(IR),water vapor(WV),and passive microwave(PMW),are used as inputs for intensity estimation.Experiments indicate that combining IR,WV,and PMW as inputs yields more accurate estimations than other channel combinations.The ensemble mean technique is applied to enhance the model's estimations,reducing the root-mean-square error to 9.32 kt(knots,1 kt≈0.51 m s^(-1))and the mean absolute error to 6.49 kt,which outperforms traditional methods and is comparable to existing deep learning models.The model assigns high attention weights to areas with high PMW,indicating that PMW magnitude is essential information for the model's estimation.The model also allocates significance to the cloud-cover region,suggesting that the model utilizes the whole TC cloud structure and TC eye to determine TC intensity.
基金financial support from the Industrial Prospect and Key Core Technology Projects of Jiangsu Provincial Key R&D Program(Grant No.BE2022071)the Natural Science Foundation of Jiangsu Province(Grant No.BK20192001)+1 种基金the National Natural Science Foundation of China(Grant No.12074194)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX220954)。
文摘Reference-frame-independent quantum key distribution(RFI-QKD)can avoid real-time calibration operation of reference frames and improve the efficiency of the communication process.However,due to imperfections of optical devices,there will inevitably exist intensity fluctuations in the source side of the QKD system,which will affect the final secure key rate.To reduce the influence of intensity fluctuations,an improved 3-intensity RFI-QKD scheme is proposed in this paper.After considering statistical fluctuations and implementing global parameter optimization,we conduct corresponding simulation analysis.The results show that our present work can present both higher key rate and a farther transmission distance than the standard method.
