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
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
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
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
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
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
Background There is a lack of research examining the interplay between objectively measured physical activity volume and intensity with life expectancy.The purpose of the study was to investigate the interplay between...Background There is a lack of research examining the interplay between objectively measured physical activity volume and intensity with life expectancy.The purpose of the study was to investigate the interplay between objectively measured PA volume and intensity profiles with modeled life expectancy in women and men within the UK Biobank cohort study and interpret findings in relation to brisk walking.Methods Individuals from UK Biobank with wrist-worn accelerometer data were included.The average acceleration and intensity gradient were extracted to describe the physical activity volume and intensity profile.Mortality data were obtained from national registries.Adjusted life expectancies were estimated using parametric flexible survival models.Results 40,953(57.1%)women(median age=61.9 years)and 30,820(42.9%)men(63.1 years)were included.Over a median follow-up of 6.9 years,there were 1719(2.4%)deaths(733 in women;986 in men).At 60 years,life expectancy was progressively longer for higher physical activity volume and intensity profiles,reaching 95.6 years in women and 94.5 years in men at the 90th centile for both volume and intensity,corresponding to 3.4 additional years(95%confidence interval(95%CI):2.4-4.4)in women and 4.6 additional years(95%CI:3.6-5.6)in men compared to those at the 10th centiles.An additional 10-min or 30-min daily brisk walk was associated with 0.9(95%CI:0.5-1.3)and 1.4 years(95%CI:0.9-1.9)longer life expectancy,respectively,in inactive women;and 1.4 years(95%CI:1.0-1.8)and 2.5(95%CI:1.9-3.1)in inactive men.Conclusion Higher physical activity volumes were associated with longer life expectancy,with a higher physical activity intensity profile further adding to a longer life.Adding as little as a 10-min brisk walk to daily activity patterns may result in a meaningful benefit to life expectancy.展开更多
Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribut...Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribution along railway routes,thereby achieving graded post-earthquake response measures.Design/methodology/approach–The seismic intensity monitoring system for railways adopts a two-level architecture,namely the seismic intensity monitoring equipment and the seismic intensity rapid reporting information center processing platform.The platform obtains measured instrumental intensity through the seismic intensity monitoring equipment deployed along railways and combines it with the National Seismic Network Earthquake Catalog to generate real-time railway seismic intensity distribution maps using the Kriging interpolation algorithm.A calculation method for railway seismic impact intervals is designed to calculate the mileage intervals where the intensity area corresponding to each contour line in the seismic intensity distribution map intersects with the railway line.Findings–The system was deployed for practical earthquake monitoring demonstration applications on the Nanjiang Railway Line in Xinjiang.During the operational period,the seismic intensity monitoring equipment calculated and uploaded instrumental intensity values to the seismic intensity rapid reporting information center processing platform a total of nine times.Among these,earthquakes triggering the Kriging interpolation algorithm occurred twice.The system operated stably throughout the application period and successfully visualized relevant seismic impact data,such as earthquake intensity distribution maps and affected railway mileage sections.These results validate the system’s practicality and effectiveness.Originality/value–The seismic intensity monitoring for the railway system designed in this study can integrate the measured instrumental intensity data along railways and the earthquake catalog of the National Seismic Network.It uses the Kriging interpolation method to calculate the intensity distribution and determine the seismic impact scope,thereby addressing the issue that the seismic intensity distribution calculated by traditional attenuation formulas deviates from reality.The system can provide clear graded interval recommendations for post-earthquake disposal,effectively improve the efficiency of post-earthquake recovery and inspection and offer a decision-making basis for restoring railway operations quickly.展开更多
Experimental validation of laser intensity is particularly important for the study of fundamental physics at extremely high intensities.However,reliable diagnosis of the focal spot and peak intensity faces huge challe...Experimental validation of laser intensity is particularly important for the study of fundamental physics at extremely high intensities.However,reliable diagnosis of the focal spot and peak intensity faces huge challenges.In this work,we demonstrate for the firs time that the coherent radiation farfiel patterns from laser–foil interactions can serve as an in situ,real-time,and easy-to-implement diagnostic for an ultraintense laser focus.The laser-driven electron sheets,curved by the spatially varying laser fiel and leaving the targets at nearly the speed of light,produce doughnut-shaped patterns depending on the shapes of the focal spot and the absolute laser intensities.Assisted by particle-in-cell simulations,we can achieve measurements of the intensity and the focal spot,and provide immediate feedback to optimize the focal spots for extremely high intensity.展开更多
Rhododendron micranthum Turcz.is a shrub esteemed for its ornamental and medicinal attributes within the Changbai Mountain range of China.We selected 3-year saplings and subjected them to four distinct light condi-tio...Rhododendron micranthum Turcz.is a shrub esteemed for its ornamental and medicinal attributes within the Changbai Mountain range of China.We selected 3-year saplings and subjected them to four distinct light condi-tions:full light(CK),70%light(L1),50%light(L2),and 30%light(L3)to investigate variations in morphology,photosynthetic responses,stomatal ultrastructure as well as the mechanisms through which these saplings adapt to differing lighting environments.The results indicate that L2 leaves exhibit significantly greater length,width,and petiole development compared to other treatments across varying intensities.Over time,chlorophyll content and PSII levels in L2-treated saplings surpass those observed in other treatments;Proline(PRO),malondialdehyde(MDA),and soluble protein(SP)contents are markedly lower under L2 treatment.Catalase(CAT)and superoxide dismutase(SOD)demonstrate significant correlations across various light con-ditions but respond differently among treatments,indicat-ing distinct species sensitivities to light intensity while both contribute to environmental stress resistance mechanisms.Findings reveal that R.micranthum saplings at 50%light intensity benefit from enhanced protection via antioxidant enzymes,and shading reduces osmotic adjustment sub-stances yet increases chlorophyll content.Stomatal length/width along with conductance rates and net photosynthesis rates for L2 exceed those of CK,suggesting an improved photosynthetic structure conducive to efficient photosynthe-sis under this condition.Thus,moderate shading represents optimal growth at 50%illumination,a critical factor promot-ing sapling development.This research elucidates the ideal environment for R.micranthum adaptation to varying light conditions supporting future conservation initiatives.展开更多
The study aims to develop an empirical model to predict the rainfall intensity in Al-Diwaniyah City,Iraq,according to a statistical analysis based on probability and the specific rainfall return period.Rainfall data w...The study aims to develop an empirical model to predict the rainfall intensity in Al-Diwaniyah City,Iraq,according to a statistical analysis based on probability and the specific rainfall return period.Rainfall data were collected daily for 25 years starting in 2000.Daily rainfall data were converted to rainfall intensity for five duration periods ranging from one to five hours.The extreme values were checked,and data that deviated from the group trend were removed for each period,and then arranged in descending order using the Weibull formula to calculate the probability.Statistically,the model performance with a return period of two years is considered good when compared with observed results and other methods such as Talbot and Sherman with a coefficient of determination(R2)>0.97 and Nash-Sutcliffe efficiency(NSE)>0.80.The results showed that a mathematical equation was obtained that describes the relationship between rainfall intensity,probability,and rainfall duration,which can be used for a confined return period with a 50% probability.Therefore,decision-makers can rely on the model to improve the performance of the city’s current drainage system during flood periods in the future.展开更多
BACKGROUND Surgery is the gold standard for gallstone treatment.Nevertheless,the complications associated with the surgical procedure can exert diverse and adverse impacts on patients’health and quality of life to va...BACKGROUND Surgery is the gold standard for gallstone treatment.Nevertheless,the complications associated with the surgical procedure can exert diverse and adverse impacts on patients’health and quality of life to varying extents.Hence,it is essential to offer perioperative care to patients undergoing gallstone surgery.AIM To examine the impact of perioperative comprehensive nursing on pain intensity,complication rates,and patient comfort in individuals undergoing gallstone surgery.METHODS From February 2022 to February 2024,195 patients who underwent gallstone surgery at Sanmen People’s Hospital were selected and divided into two groups:A control group receiving routine nursing care(95 patients)and a research group receiving perioperative comprehensive nursing(100 patients).Key postoperative recovery indicators,including time to first postoperative anal exhaust,oral food intake,and ambulation,were observed,along with pain intensity(measured by the numeric rating scale),complication rate(bleeding,incision infection,recurrence),patient comfort(assessed using the visual analogue scale),and quality of life(measured by the World Health Organization Quality of Life-BREF).RESULTS The research group showed significantly shorter times to first postoperative anal exhaust,oral intake,and ambulation.Moreover,numeric rating scale pain scores in the research group were markedly lower post-nursing,and the total complication rate was significantly reduced compared to the control group.Furthermore,comfort levels improved considerably in the research group,and World Health Organization Quality of Life-BREF scores across the physical,psychological,social,and environmental domains were significantly higher compared to the control group following nursing care.CONCLUSION Perioperative comprehensive nursing effectively enhances postoperative recovery in patients undergoing gallstone surgery,reducing pain,lowering complications,and improving patient comfort and quality of life,which deserves clinical application.展开更多
BACKGROUND Exercise plays a key role in managing chronic conditions such as diabetes mellitus(DM),a major contributor to end-stage renal disease(ESRD),a serious public health issue.AIM To investigate the relationship ...BACKGROUND Exercise plays a key role in managing chronic conditions such as diabetes mellitus(DM),a major contributor to end-stage renal disease(ESRD),a serious public health issue.AIM To investigate the relationship between exercise intensity,DM duration,and ESRD incidence.METHODS This retrospective cohort study analyzed data from 2495031 individuals with DM who underwent the Korean National Health Screening between 2015 and 2016,with follow-up through 2022.The Cox proportional hazards model was adjusted for confounders,including age,sex,income,smoking,and baseline comorbidities.RESULTS Longer DM duration was associated with a significantly higher risk of ESRD,with durations≥10 years showing the highest risk[hazard ratio(HR):2.624,95%confidence interval(CI):2.486-2.770].Increased exercise intensity reduced the risk of developing ESRD across all diabetes duration groups,with the highest exercise category(≥1500 metabolic equivalents of task-min/week)demonstrating a protective effect compared to that of no exercise(HR:0.837,95%CI:0.791-0.886).Exercise benefits were more pronounced in patients without hypertension,non-smokers,and those with lower alcohol consumption.Additionally,ESRD risk reduction was significant among patients with a body mass index≥25 and those without proteinuria or chronic kidney disease.CONCLUSION Longer diabetes duration is associated with increased ESRD risk,while high-intensity exercise may mitigate this risk.These findings suggest promoting exercise is important for managing diabetes to reduce renal complications.展开更多
Super-resolution structured illumination microscopy(SR-SIM)relies heavily on post-processing reconstruction to obtain high-quality SR images from raw data.Although many SIM reconstruction algorithms have been develope...Super-resolution structured illumination microscopy(SR-SIM)relies heavily on post-processing reconstruction to obtain high-quality SR images from raw data.Although many SIM reconstruction algorithms have been developed to recover fine cellular structures with high fidelity even from the noisy data,whether the pixel intensities of reconstructed SR images are still proportional to the original fluorescence intensity has been less explored.The linearity between the intensity before and after reconstruction is de fined as the intensity fidelity.Here,we proposed a method to evaluate the reconstructed SR image intensity fidelity at different spatial frequencies.With the proposed metric,we systematically investigated the impact of the key factors on the intensity fidelity in the standard Wiener-SIM reconstructions with simulated data,then evaluated the intensity fidelity of the SR images reconstructed by representative open-source packages.Our work provides a reference for SR-SIM image intensity fidelity improvement.展开更多
The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application value.However,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)...The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application value.However,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)technology rely on manual site setup to collect intensity training data at different distances and incidence angles,which is noisy and limited in sample quantity,restricting the improvement of model accuracy.To overcome this limitation,this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning(MLS)technology.The method utilizes the continuous scanning characteristics of MLS technology to obtain dense point cloud intensity data at various distances and incidence angles.Then,a fine-grained screening strategy is employed to accurately select distance-intensity and incidence angle-intensity modeling samples.Finally,based on these samples,a high-precision intensity correction model is established through polynomial fitting functions.To verify the effectiveness of the proposed method,comparative experiments were designed,and the MLS modeling method was validated against the traditional TLS modeling method on the same test set.The results show that on Test Set 1,where the distance values vary widely(i.e.,0.1–3 m),the intensity consistency after correction using the MLS modeling method reached 7.692 times the original intensity,while the traditional TLS modeling method only increased to 4.630 times the original intensity.On Test Set 2,where the incidence angle values vary widely(i.e.,0○–80○),the MLS modeling method,although with a relatively smaller advantage,still improved the intensity consistency to 3.937 times the original intensity,slightly better than the TLS modeling method’s 3.413 times.These results demonstrate the significant advantage of the modeling method proposed in this study in enhancing the accuracy of intensity correction models.展开更多
The development of modern engineering components and equipment features large size,intricate shape and long service life,which places greater demands on valid methods for fatigue performance analysis.Achieving a smoot...The development of modern engineering components and equipment features large size,intricate shape and long service life,which places greater demands on valid methods for fatigue performance analysis.Achieving a smooth transformation between small-scale laboratory specimens’fatigue properties and full-scale engineering components’fatigue strength has been a long-term challenge.In this work,two dominant factors impeding the smooth transformation—notch and size effect were experimentally studied,in which fatigue tests on Al 7075-T6511(a very high-strength aviation alloy)notched specimens of different scales were carried out.Fractography analyses identified the evidence of the size effect on notch fatigue damage evolution.Accordingly,the Energy Field Intensity(EFI)initially developed for multiaxial notch fatigue analysis was improved by utilizing the volume ratio of the Effective Damage Zones(EDZs)for size effect correction.In particular,it was extended to a probabilistic model considering the inherent variability of the fatigue phenomenon.The experimental data of Al 7075-T6511 notched specimens and the model-predicted results were compared,indicating the high potential of the proposed approach in fatigue evaluation under combined notch and size effects.展开更多
Suitable temperature and light intensity play important roles in the formation of harmful algae blooms(HABs),which can pose serious threats to aquatic ecosystems and human health.In this study,we measured the growth,p...Suitable temperature and light intensity play important roles in the formation of harmful algae blooms(HABs),which can pose serious threats to aquatic ecosystems and human health.In this study,we measured the growth,physiological function,and paralytic shellfish toxins(PSTs)production of Alexandrium pacificum(CCMA-272),a strain isolated from East China Sea,at different temperatures(15,20,and 25℃)and light intensities(30,60,and 90μmol photons/(m^(2)·s)).Results indicate that temperature and light intensity significantly affected the growth,physiology,and toxigenic potentials of A.pacificum.The optimal conditions for the growth of A.pacificum were observed at 20℃ under60μmol photons/(m^(2)·s).Regarding the production of PSTs,this strain of A.pacificum produced 12 PSTs,including carbamate toxins:saxitoxin(STX),neosaxitoxin(NEO),and gonyautoxin 1–4(GTX1,GTX2,GTX3,GTX4);dicarbamoyl toxins:dicarbamoylsaxitoxin(dcSTX),dicarbamoylgonyautoxin 2,3(dcGTX2,dcGTX3);and N-sulfocarbamoyl toxins:N-sulfocarbamoylgonyautoxin 1,2(C1,C2),and gonyautoxin 5(GTX5).Among all the PSTs,C2 was the most abundant.Low temperature(15℃)and high light intensity(90μmol photons/(m^(2)·s))were beneficial for the production of PSTs in A.pacificum.When cultured at 20 and 25℃,A.pacificum generated comparable total quantities of PSTs,yet the toxicity levels were lower at 25℃.Intra-cellular PSTs contents were greater than extra-cellular PSTs contents,except those under the condition of 25℃ with 30μmol photons/(m^(2)·s).However,as the increase of temperature,A.pacificum released more amounts of analogues with higher toxicity levels(e.g.,STX and dcGTX_(2))into the environment than intracellularly.These findings emphasize the significant sensitivity of A.pacificum to temperature and light intensity,highlighting the importance of evaluating both intra-cellular and extra-cellular PSTs for assessing its toxicity and aiding in the prediction and management of HABs.展开更多
As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst ...As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst intensity,the problem of rockburst intensity prediction has not been well solved until now.In this study,we collect 292 sets of rockburst data including eight parameters,such as the maximum tangential stress of the surrounding rock σ_(θ),the uniaxial compressive strength of the rockσc,the uniaxial tensile strength of the rock σ_(t),and the strain energy storage index W_(et),etc.from more than 20 underground projects as training sets and establish two new rockburst prediction models based on the kernel extreme learning machine(KELM)combined with the genetic algorithm(KELM-GA)and cross-entropy method(KELM-CEM).To further verify the effect of the two models,ten sets of rockburst data from Shuangjiangkou Hydropower Station are selected for analysis and the results show that new models are more accurate compared with five traditional empirical criteria,especially the model based on KELM-CEM which has the accuracy rate of 90%.Meanwhile,the results of 10 consecutive runs of the model based on KELM-CEM are almost the same,meaning that the model has good stability and reliability for engineering applications.展开更多
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.
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.
基金funded by the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre (BRC)the Applied Research Collaborations East Midlands (ARC-EM)supported by a UKRI project grant (MR/T031816/1)。
文摘Background There is a lack of research examining the interplay between objectively measured physical activity volume and intensity with life expectancy.The purpose of the study was to investigate the interplay between objectively measured PA volume and intensity profiles with modeled life expectancy in women and men within the UK Biobank cohort study and interpret findings in relation to brisk walking.Methods Individuals from UK Biobank with wrist-worn accelerometer data were included.The average acceleration and intensity gradient were extracted to describe the physical activity volume and intensity profile.Mortality data were obtained from national registries.Adjusted life expectancies were estimated using parametric flexible survival models.Results 40,953(57.1%)women(median age=61.9 years)and 30,820(42.9%)men(63.1 years)were included.Over a median follow-up of 6.9 years,there were 1719(2.4%)deaths(733 in women;986 in men).At 60 years,life expectancy was progressively longer for higher physical activity volume and intensity profiles,reaching 95.6 years in women and 94.5 years in men at the 90th centile for both volume and intensity,corresponding to 3.4 additional years(95%confidence interval(95%CI):2.4-4.4)in women and 4.6 additional years(95%CI:3.6-5.6)in men compared to those at the 10th centiles.An additional 10-min or 30-min daily brisk walk was associated with 0.9(95%CI:0.5-1.3)and 1.4 years(95%CI:0.9-1.9)longer life expectancy,respectively,in inactive women;and 1.4 years(95%CI:1.0-1.8)and 2.5(95%CI:1.9-3.1)in inactive men.Conclusion Higher physical activity volumes were associated with longer life expectancy,with a higher physical activity intensity profile further adding to a longer life.Adding as little as a 10-min brisk walk to daily activity patterns may result in a meaningful benefit to life expectancy.
基金funded by the Research and Development Fund Project of China Academy of Railway Science Group Co.,Ltd.,(No:2023YJ259)the Science and Technology Research and Development Program Project of China State Railway Group Co.,Ltd.(No:J2024G008).
文摘Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribution along railway routes,thereby achieving graded post-earthquake response measures.Design/methodology/approach–The seismic intensity monitoring system for railways adopts a two-level architecture,namely the seismic intensity monitoring equipment and the seismic intensity rapid reporting information center processing platform.The platform obtains measured instrumental intensity through the seismic intensity monitoring equipment deployed along railways and combines it with the National Seismic Network Earthquake Catalog to generate real-time railway seismic intensity distribution maps using the Kriging interpolation algorithm.A calculation method for railway seismic impact intervals is designed to calculate the mileage intervals where the intensity area corresponding to each contour line in the seismic intensity distribution map intersects with the railway line.Findings–The system was deployed for practical earthquake monitoring demonstration applications on the Nanjiang Railway Line in Xinjiang.During the operational period,the seismic intensity monitoring equipment calculated and uploaded instrumental intensity values to the seismic intensity rapid reporting information center processing platform a total of nine times.Among these,earthquakes triggering the Kriging interpolation algorithm occurred twice.The system operated stably throughout the application period and successfully visualized relevant seismic impact data,such as earthquake intensity distribution maps and affected railway mileage sections.These results validate the system’s practicality and effectiveness.Originality/value–The seismic intensity monitoring for the railway system designed in this study can integrate the measured instrumental intensity data along railways and the earthquake catalog of the National Seismic Network.It uses the Kriging interpolation method to calculate the intensity distribution and determine the seismic impact scope,thereby addressing the issue that the seismic intensity distribution calculated by traditional attenuation formulas deviates from reality.The system can provide clear graded interval recommendations for post-earthquake disposal,effectively improve the efficiency of post-earthquake recovery and inspection and offer a decision-making basis for restoring railway operations quickly.
基金supported by the Guangdong High Level Innovation Research Institute(Grant No.2021B0909050006)the National Grand Instrument Project(Grant No.2019YFF01014402)+1 种基金the National Natural Science Foundation of China(Grant No.12205008)support from the National Science Fund for Distinguished Young Scholars(Grant No.12225501)。
文摘Experimental validation of laser intensity is particularly important for the study of fundamental physics at extremely high intensities.However,reliable diagnosis of the focal spot and peak intensity faces huge challenges.In this work,we demonstrate for the firs time that the coherent radiation farfiel patterns from laser–foil interactions can serve as an in situ,real-time,and easy-to-implement diagnostic for an ultraintense laser focus.The laser-driven electron sheets,curved by the spatially varying laser fiel and leaving the targets at nearly the speed of light,produce doughnut-shaped patterns depending on the shapes of the focal spot and the absolute laser intensities.Assisted by particle-in-cell simulations,we can achieve measurements of the intensity and the focal spot,and provide immediate feedback to optimize the focal spots for extremely high intensity.
基金funded by the National Natural Science Foundation of China(No.32171770)Natural Science Foundation Program of Jilin Provincial Department of Education(No.JJKH20230074KJ).
文摘Rhododendron micranthum Turcz.is a shrub esteemed for its ornamental and medicinal attributes within the Changbai Mountain range of China.We selected 3-year saplings and subjected them to four distinct light condi-tions:full light(CK),70%light(L1),50%light(L2),and 30%light(L3)to investigate variations in morphology,photosynthetic responses,stomatal ultrastructure as well as the mechanisms through which these saplings adapt to differing lighting environments.The results indicate that L2 leaves exhibit significantly greater length,width,and petiole development compared to other treatments across varying intensities.Over time,chlorophyll content and PSII levels in L2-treated saplings surpass those observed in other treatments;Proline(PRO),malondialdehyde(MDA),and soluble protein(SP)contents are markedly lower under L2 treatment.Catalase(CAT)and superoxide dismutase(SOD)demonstrate significant correlations across various light con-ditions but respond differently among treatments,indicat-ing distinct species sensitivities to light intensity while both contribute to environmental stress resistance mechanisms.Findings reveal that R.micranthum saplings at 50%light intensity benefit from enhanced protection via antioxidant enzymes,and shading reduces osmotic adjustment sub-stances yet increases chlorophyll content.Stomatal length/width along with conductance rates and net photosynthesis rates for L2 exceed those of CK,suggesting an improved photosynthetic structure conducive to efficient photosynthe-sis under this condition.Thus,moderate shading represents optimal growth at 50%illumination,a critical factor promot-ing sapling development.This research elucidates the ideal environment for R.micranthum adaptation to varying light conditions supporting future conservation initiatives.
文摘The study aims to develop an empirical model to predict the rainfall intensity in Al-Diwaniyah City,Iraq,according to a statistical analysis based on probability and the specific rainfall return period.Rainfall data were collected daily for 25 years starting in 2000.Daily rainfall data were converted to rainfall intensity for five duration periods ranging from one to five hours.The extreme values were checked,and data that deviated from the group trend were removed for each period,and then arranged in descending order using the Weibull formula to calculate the probability.Statistically,the model performance with a return period of two years is considered good when compared with observed results and other methods such as Talbot and Sherman with a coefficient of determination(R2)>0.97 and Nash-Sutcliffe efficiency(NSE)>0.80.The results showed that a mathematical equation was obtained that describes the relationship between rainfall intensity,probability,and rainfall duration,which can be used for a confined return period with a 50% probability.Therefore,decision-makers can rely on the model to improve the performance of the city’s current drainage system during flood periods in the future.
基金Supported by Science and Technology Program of Sanmen County Public Technology Social Development Project,No.24227.
文摘BACKGROUND Surgery is the gold standard for gallstone treatment.Nevertheless,the complications associated with the surgical procedure can exert diverse and adverse impacts on patients’health and quality of life to varying extents.Hence,it is essential to offer perioperative care to patients undergoing gallstone surgery.AIM To examine the impact of perioperative comprehensive nursing on pain intensity,complication rates,and patient comfort in individuals undergoing gallstone surgery.METHODS From February 2022 to February 2024,195 patients who underwent gallstone surgery at Sanmen People’s Hospital were selected and divided into two groups:A control group receiving routine nursing care(95 patients)and a research group receiving perioperative comprehensive nursing(100 patients).Key postoperative recovery indicators,including time to first postoperative anal exhaust,oral food intake,and ambulation,were observed,along with pain intensity(measured by the numeric rating scale),complication rate(bleeding,incision infection,recurrence),patient comfort(assessed using the visual analogue scale),and quality of life(measured by the World Health Organization Quality of Life-BREF).RESULTS The research group showed significantly shorter times to first postoperative anal exhaust,oral intake,and ambulation.Moreover,numeric rating scale pain scores in the research group were markedly lower post-nursing,and the total complication rate was significantly reduced compared to the control group.Furthermore,comfort levels improved considerably in the research group,and World Health Organization Quality of Life-BREF scores across the physical,psychological,social,and environmental domains were significantly higher compared to the control group following nursing care.CONCLUSION Perioperative comprehensive nursing effectively enhances postoperative recovery in patients undergoing gallstone surgery,reducing pain,lowering complications,and improving patient comfort and quality of life,which deserves clinical application.
基金Supported by National Research Foundation of Korea(NRF)grant funded by the Korean Government(MSIT),No.RS-2023-00217317Chonnam National University Grant,No.2024-0444-01and Chonnam National University Hospital Institute for Biomedical Science,No.BCRI24032.
文摘BACKGROUND Exercise plays a key role in managing chronic conditions such as diabetes mellitus(DM),a major contributor to end-stage renal disease(ESRD),a serious public health issue.AIM To investigate the relationship between exercise intensity,DM duration,and ESRD incidence.METHODS This retrospective cohort study analyzed data from 2495031 individuals with DM who underwent the Korean National Health Screening between 2015 and 2016,with follow-up through 2022.The Cox proportional hazards model was adjusted for confounders,including age,sex,income,smoking,and baseline comorbidities.RESULTS Longer DM duration was associated with a significantly higher risk of ESRD,with durations≥10 years showing the highest risk[hazard ratio(HR):2.624,95%confidence interval(CI):2.486-2.770].Increased exercise intensity reduced the risk of developing ESRD across all diabetes duration groups,with the highest exercise category(≥1500 metabolic equivalents of task-min/week)demonstrating a protective effect compared to that of no exercise(HR:0.837,95%CI:0.791-0.886).Exercise benefits were more pronounced in patients without hypertension,non-smokers,and those with lower alcohol consumption.Additionally,ESRD risk reduction was significant among patients with a body mass index≥25 and those without proteinuria or chronic kidney disease.CONCLUSION Longer diabetes duration is associated with increased ESRD risk,while high-intensity exercise may mitigate this risk.These findings suggest promoting exercise is important for managing diabetes to reduce renal complications.
基金supported by the National Natural Science Foundation of China[Grant Nos.62205367 and 62141506]Suzhou Basic Research Pilot Project[Grant Nos.SSD2023006 and SJC2021013]Jiangsu Provincial Key Research and Development Program[Grant No.BE2020664].
文摘Super-resolution structured illumination microscopy(SR-SIM)relies heavily on post-processing reconstruction to obtain high-quality SR images from raw data.Although many SIM reconstruction algorithms have been developed to recover fine cellular structures with high fidelity even from the noisy data,whether the pixel intensities of reconstructed SR images are still proportional to the original fluorescence intensity has been less explored.The linearity between the intensity before and after reconstruction is de fined as the intensity fidelity.Here,we proposed a method to evaluate the reconstructed SR image intensity fidelity at different spatial frequencies.With the proposed metric,we systematically investigated the impact of the key factors on the intensity fidelity in the standard Wiener-SIM reconstructions with simulated data,then evaluated the intensity fidelity of the SR images reconstructed by representative open-source packages.Our work provides a reference for SR-SIM image intensity fidelity improvement.
基金supported in part by the National Natural Science Foundation of China under grant number 31901239funded by Researchers Supporting Project Number(RSPD2025R947),King Saud University,Riyadh,Saudi Arabia.
文摘The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application value.However,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)technology rely on manual site setup to collect intensity training data at different distances and incidence angles,which is noisy and limited in sample quantity,restricting the improvement of model accuracy.To overcome this limitation,this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning(MLS)technology.The method utilizes the continuous scanning characteristics of MLS technology to obtain dense point cloud intensity data at various distances and incidence angles.Then,a fine-grained screening strategy is employed to accurately select distance-intensity and incidence angle-intensity modeling samples.Finally,based on these samples,a high-precision intensity correction model is established through polynomial fitting functions.To verify the effectiveness of the proposed method,comparative experiments were designed,and the MLS modeling method was validated against the traditional TLS modeling method on the same test set.The results show that on Test Set 1,where the distance values vary widely(i.e.,0.1–3 m),the intensity consistency after correction using the MLS modeling method reached 7.692 times the original intensity,while the traditional TLS modeling method only increased to 4.630 times the original intensity.On Test Set 2,where the incidence angle values vary widely(i.e.,0○–80○),the MLS modeling method,although with a relatively smaller advantage,still improved the intensity consistency to 3.937 times the original intensity,slightly better than the TLS modeling method’s 3.413 times.These results demonstrate the significant advantage of the modeling method proposed in this study in enhancing the accuracy of intensity correction models.
基金support from the Key Program of the National Natural Science Foundation of China(No.12232004)the Training Program of the Sichuan Province Science and the Technology Innovation Seedling Project(No.MZGC20230012)are acknowledged.
文摘The development of modern engineering components and equipment features large size,intricate shape and long service life,which places greater demands on valid methods for fatigue performance analysis.Achieving a smooth transformation between small-scale laboratory specimens’fatigue properties and full-scale engineering components’fatigue strength has been a long-term challenge.In this work,two dominant factors impeding the smooth transformation—notch and size effect were experimentally studied,in which fatigue tests on Al 7075-T6511(a very high-strength aviation alloy)notched specimens of different scales were carried out.Fractography analyses identified the evidence of the size effect on notch fatigue damage evolution.Accordingly,the Energy Field Intensity(EFI)initially developed for multiaxial notch fatigue analysis was improved by utilizing the volume ratio of the Effective Damage Zones(EDZs)for size effect correction.In particular,it was extended to a probabilistic model considering the inherent variability of the fatigue phenomenon.The experimental data of Al 7075-T6511 notched specimens and the model-predicted results were compared,indicating the high potential of the proposed approach in fatigue evaluation under combined notch and size effects.
基金Supported by the National Natural Science Foundation of China(Nos.32101290,52009082)the Natural Science Foundation of Jiangsu Province(No.BK20210364)the Fundamental Research Funds for the Central Universities(No.B220202044)。
文摘Suitable temperature and light intensity play important roles in the formation of harmful algae blooms(HABs),which can pose serious threats to aquatic ecosystems and human health.In this study,we measured the growth,physiological function,and paralytic shellfish toxins(PSTs)production of Alexandrium pacificum(CCMA-272),a strain isolated from East China Sea,at different temperatures(15,20,and 25℃)and light intensities(30,60,and 90μmol photons/(m^(2)·s)).Results indicate that temperature and light intensity significantly affected the growth,physiology,and toxigenic potentials of A.pacificum.The optimal conditions for the growth of A.pacificum were observed at 20℃ under60μmol photons/(m^(2)·s).Regarding the production of PSTs,this strain of A.pacificum produced 12 PSTs,including carbamate toxins:saxitoxin(STX),neosaxitoxin(NEO),and gonyautoxin 1–4(GTX1,GTX2,GTX3,GTX4);dicarbamoyl toxins:dicarbamoylsaxitoxin(dcSTX),dicarbamoylgonyautoxin 2,3(dcGTX2,dcGTX3);and N-sulfocarbamoyl toxins:N-sulfocarbamoylgonyautoxin 1,2(C1,C2),and gonyautoxin 5(GTX5).Among all the PSTs,C2 was the most abundant.Low temperature(15℃)and high light intensity(90μmol photons/(m^(2)·s))were beneficial for the production of PSTs in A.pacificum.When cultured at 20 and 25℃,A.pacificum generated comparable total quantities of PSTs,yet the toxicity levels were lower at 25℃.Intra-cellular PSTs contents were greater than extra-cellular PSTs contents,except those under the condition of 25℃ with 30μmol photons/(m^(2)·s).However,as the increase of temperature,A.pacificum released more amounts of analogues with higher toxicity levels(e.g.,STX and dcGTX_(2))into the environment than intracellularly.These findings emphasize the significant sensitivity of A.pacificum to temperature and light intensity,highlighting the importance of evaluating both intra-cellular and extra-cellular PSTs for assessing its toxicity and aiding in the prediction and management of HABs.
基金funded by National Natural Science Foundation of China(Grants Nos.41825018 and 42141009)the Second Tibetan Plateau Scientific Expedition and Research Program(Grants No.2019QZKK0904)。
文摘As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst intensity,the problem of rockburst intensity prediction has not been well solved until now.In this study,we collect 292 sets of rockburst data including eight parameters,such as the maximum tangential stress of the surrounding rock σ_(θ),the uniaxial compressive strength of the rockσc,the uniaxial tensile strength of the rock σ_(t),and the strain energy storage index W_(et),etc.from more than 20 underground projects as training sets and establish two new rockburst prediction models based on the kernel extreme learning machine(KELM)combined with the genetic algorithm(KELM-GA)and cross-entropy method(KELM-CEM).To further verify the effect of the two models,ten sets of rockburst data from Shuangjiangkou Hydropower Station are selected for analysis and the results show that new models are more accurate compared with five traditional empirical criteria,especially the model based on KELM-CEM which has the accuracy rate of 90%.Meanwhile,the results of 10 consecutive runs of the model based on KELM-CEM are almost the same,meaning that the model has good stability and reliability for engineering applications.
