Purpose:To assess the clinical efficacy of integrating deep learning reconstruction(DLR)with contrast-enhancement-boost(CE-boost)in 80 kVp head and neck CT angiography(CTA)using substantially lowered radiation and con...Purpose:To assess the clinical efficacy of integrating deep learning reconstruction(DLR)with contrast-enhancement-boost(CE-boost)in 80 kVp head and neck CT angiography(CTA)using substantially lowered radiation and contrast medium(CM)doses,compared to the standard 100 kVp protocol using hybrid iterative reconstruction(HIR).Methods:Sixty-six patients were prospectively enrolled and randomly assigned to one of two groups:the low-dose group(n=33),receiving 80 kVp and 28 mL contrast medium(CM)with a noise index(NI)of 15;and the regular-dose group(n=33),receiving 100 kVp and 40 mL CM with an NI of 10.For the lowdose group,images underwent reconstruction using both hybrid iterative reconstruction(HIR)and deep learning reconstruction(DLR)at mild-,standard-,and strong-strength levels,both before and after combination with contrast enhancement-boost(CE-boost).This generated eight distinct datasets:L-HIR,L-DLR_(mild),L-DLR_(standard),L-DLR_(strong),L-HIR-CE,L-DLR_(mild)-CE,L-DLR_(standard)-CE,and L-DLR_(strong)-CE.Images for the regular-dose group were reconstructed solely with HIR(R-HIR).Quantitative analysis involved calculating and comparing CT attenuation,image noise,signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR)within six key vessels:the aortic arch(AA),internal carotid artery(ICA),external carotid artery(ECA),vertebral arteries(VA),basilar artery(BA),and middle cerebral artery(MCA).Two radiologists independently assessed subjective image quality using a 5-point scale,with statistical significance defined as P<0.05.Results:Compared to the regular-dose group,the low-dose protocol achieved a substantial reduction in contrast media volume(28 mL versus 40 mL,a 30%decrease)and radiation exposure((0.41±0.08)mSv versus(1.18±0.12)mSv,a 65%reduction).Both L-DLR_(standard) and L-DLR_(strong) delivered comparable or superior SNR and CNR across all vascular segments relative to R-HIR.However,subjective image quality scores for L-DLR at all strength levels fell below those for R-HIR(all P<0.05 for both readers).Combining CE-boost with the low-dose protocol significantly enhanced the objective image performance of L-DLR_(strong)-CE(all P<0.05)and produced subjective image scores comparable to R-HIR(reader 1:P=0.15;reader 2:P=0.06).Conclusion:When compared to the standard 100 kVp head and neck CTA,the combination of the DLR and CE-boost techniques at 80 kVp can achieve a 30%reduction in contrast dose and a 65%reduction in radiation dose,while maintaining both objective and subjective image quality.展开更多
Metal-nitrogen-carbon(M-N-C)single-atom catalysts are widely utilized in various energy-related catalytic processes,offering a highly efficient and cost-effective catalytic system with significant potential.Recently,c...Metal-nitrogen-carbon(M-N-C)single-atom catalysts are widely utilized in various energy-related catalytic processes,offering a highly efficient and cost-effective catalytic system with significant potential.Recently,curvature-induced strain has been extensively demonstrated as a powerful tool for modulating the catalytic performance of M-N-C catalysts.However,identifying optimal strain patterns using density functional theory(DFT)is computationally intractable due to the high-dimensional search space.Here,we developed a graph neural network(GNN)integrated with an advanced topological data analysis tool-persistent homology-to predict the adsorption energy response of adsorbate under proposed curvature patterns,using nitric oxide electroreduction(NORR)as an example.Our machine learning model achieves high accuracy in predicting the adsorption energy response to curvature,with a mean absolute error(MAE)of 0.126 eV.Furthermore,we elucidate general trends in curvature-modulated adsorption energies of intermediates across various metals and coordination environments.We recommend several promising catalysts for NORR that exhibit significant potential for performance optimization via curvature modulation.This methodology can be readily extended to describe other non-bonded interactions,such as lattice strain and surface stress,providing a versatile approach for advanced catalyst design.展开更多
In the event of nuclear accidents and incidents,when emergency resources are scarce,rapid and high-throughput biodosimeters for massive population triage and estimation are essential to guide medical treatment.Lymphoc...In the event of nuclear accidents and incidents,when emergency resources are scarce,rapid and high-throughput biodosimeters for massive population triage and estimation are essential to guide medical treatment.Lymphocyte dynamics,chromosome aberration analysis,and micronucleus assays are mainly used to estimate the biological dose of radiation[1].However,these technologies require highly trained personnel to perform and interpret and have the limitations of time consumption and low throughput,underscoring the urgent need for the development of radiation biomarkers and early classification.Dose and temporal responses as well as efficient triage models are important facets of radiation biodosimeters.展开更多
Both nMOS and pMOS transistors with two-edged and multi-finger layouts are fabricated in a standard commercial 0.6μm CMOS/bulk process to study their total ionizing dose （TID） radiation effects. The leakage current...Both nMOS and pMOS transistors with two-edged and multi-finger layouts are fabricated in a standard commercial 0.6μm CMOS/bulk process to study their total ionizing dose （TID） radiation effects. The leakage current, threshold voltage shift, and transconductance of the devices are monitored before and after T-ray irradiation. Different device bias conditions are used during irradiation. The experiment results show that TID radiation effects on nMOS devices are very sensitive to their layout structures. The impact of the layout on TID effects on pMOS devices is slight and can be neglected.展开更多
This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-a...This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-assisted junction termination extension(RA-JTE),multiple floating zone JTE(MFZ-JTE),and field limiting rings(FLR)were fabricated and irradiated with45 Me V protons at fluences ranging from 1×10^(12) to 1×10^(14) cm^(-2).Experimental results,supported by TCAD simulations,show that the RA-JTE structure maintained stable breakdown performance with less than 1%variation due to its effective electric field redistribution by multiple P+rings.In contrast,MFZ-JTE and FLR exhibit breakdown voltage shifts of 6.1%and 15.2%,respectively,under the highest fluence.These results demonstrate the superior radiation tolerance of the RA-JTE structure under TID conditions and provide practical design guidance for radiation-hardened Si C power devices in space and other highradiation environments.展开更多
Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility ar...Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.展开更多
With the rapid development of artificial intelligence,magnetocaloric materials as well as other materials are being developed with increased efficiency and enhanced performance.However,most studies do not take phase t...With the rapid development of artificial intelligence,magnetocaloric materials as well as other materials are being developed with increased efficiency and enhanced performance.However,most studies do not take phase transitions into account,and as a result,the predictions are usually not accurate enough.In this context,we have established an explicable relationship between alloy compositions and phase transition by feature imputation.A facile machine learning is proposed to screen candidate NiMn-based Heusler alloys with desired magnetic entropy change and magnetic transition temperature with a high accuracy R^(2)≈0.98.As expected,the measured properties of prepared NiMn-based alloys,including phase transition type,magnetic entropy changes and transition temperature,are all in good agreement with the ML predictions.As well as being the first to demonstrate an explicable relationship between alloy compositions,phase transitions and magnetocaloric properties,our proposed ML model is highly predictive and interpretable,which can provide a strong theoretical foundation for identifying high-performance magnetocaloric materials in the future.展开更多
The hydroponic culture experiments of soybean bean seedlings were conducted to investigate the effect of lanthanum （La） on nitrogen metabolism under two different levels of elevated UV-B radiation （UV-B, 280-320 nm...The hydroponic culture experiments of soybean bean seedlings were conducted to investigate the effect of lanthanum （La） on nitrogen metabolism under two different levels of elevated UV-B radiation （UV-B, 280-320 nm）. The whole process of nitrogen metabolism involves uptake and transport of nitrate, nitrate assimilation, ammonium assimilation, amino acid biosynthesis, and protein synthesis. Compared with the control, UV-B radiation with the intensity of low level 0.15 W/m^2 and high level 0.45 W/m^2 significantly affected the whole nitrogen metabolism in soybean seedlings （p 〈 0.05）. It restricted uptake and transport of NO3^-, inhibited activity of some key nitrogen-metabolism-related enzymes, such as： nitrate reductase （NR） to the nitrate reduction, glutamine systhetase （GS） and glutamine synthase （GOGAT） to the ammonia assimilation, while it increased the content of free amino acids and decreased that of soluble protein as well. The damage effect of high level of UV-B radiation on nitrogen metabolism was greater than that of low level. And UV-B radiation promoted the activity of the anti-adversity enzyme glutamate dehydrogenase （GDH）, which reduced the toxicity of excess ammonia in plant. After pretreatment with the optimum concentration of La （20 mg/L）, La could increase the activity of NR, GS, GOGAT, and GDH, and ammonia assimilation, but decrease nitrate and ammonia accumulation. In conclusion, La could relieve the damage effect of UV-B radiation on plant by regulating nitrogen metabolism process, and its alleviating effect under low level was better than that under the high one.展开更多
BACKGROUND： Conventional methods （such as occlusion therapy, fine manipulation, complementary, and alternative medicine） take effects slowly, are time and labor consuming, and have uncertain curative effects in the...BACKGROUND： Conventional methods （such as occlusion therapy, fine manipulation, complementary, and alternative medicine） take effects slowly, are time and labor consuming, and have uncertain curative effects in the treatment of amblyopia. Perceptual learning, a new method for treating amblyopia, improves the ability to process signals from the cerebral optic nerve system by specific visual stimulation and visual learning, as well as activation of the visual signal pathway utilizing brain nervous system plasticity. OBJECTIVE： This study investigated and evaluated the curative effects of perceptual learning, which can directionally increase brain plasticity, on the treatment of amblyopia in children. The relationship between curative effect and time was also analyzed. DESIGN： A self-control experiment. SETTING： Visual Science and Optometry Center, People＇s Hospital of Guangxi Zhuang Autonomous Region. PARTICIPANTS： A total of 125 amblyopic children （250 amblyopic eyes）, 73 males, 52 females, averaging （6±2） years of age, received treatment at the Visual Science and Optometry Center, People＇s Hospital of Guangxi Zhuang Autonomous Region between September 2006 and February 2007 and were recruited for this study. All children presented with no structural disease of the eyeballs. Written informed consent for therapeutic regiments was obtained from each child＇s parent. The protocol received approval from the Hospital＇s Ethics Committee. METHODS： Visual function was tested with a perceptual learning system （Research Center for Human Health and Development of Sun Yat-sen University, National Engineering Technique Research Center for Medical Care Implement） for visual noise, position noise, contour discrimination, contrast sensitivity, grating stereogram, and random-dot fusion. These tests helped to evaluate the efficiency of visual information processing of these children, and to determine the degree of defects of the optic nerve cells and the connections of visual cortical neurons. According to results of visual function tests, individualized treatment was adopted for each amblyopia patient using perceptual learning system. One course of treatment lasted one month, and treatment was performed twice every day with two training procedures （each training procedure lasted for ten minutes）. There was a ten-minute time interval between the two training procedures. The training treatment was performed in a quiet and dark environment. Visual acuity and recovery of visual function were tested every month. Original training procedure was continued or adjusted according to the results of visual function. MAIN OUTCOME MEASURES： Visual function change; relationship of curative effects and curative time. RESULTS： A total of 125 amblyopia children were included in the final analysis. The total efficiency of perceptual learning for treating amblyopia in children was 75.2%. Visual acuity began to greatly increase 3 months after treatment （P 〈 0.05）. Visual acuity was best corrected from 0.60 ± 0.23 before treatment to 0.86 ± 0.26 after treatment （P 〈 0.05）. The mean time to reach improved levels with curative effects was （2.82 ± 1.30） months, and to reach a basically cured level was （2.87 ±1.40） months. Percentage of improved visual acuity was the highest [98% （39/40）] in children that received 3 months of treatment and the lowest [55% （31/56）] in children that received 1 month of treatment （P 〈 0.05）. The percentage of basically cured levels with curative effects increased with length of learning time and was the greatest in children that received 4 months of treatment [67% （31/46）, P 〈 0.05]. CONCLUSION： Perceptual learning rapidly and remarkably improves visual function of amblyopia children; however, the curative effects are first apparent two and three months after intervention.展开更多
The terahertz(THz) band lies between microwave and infrared rays in wavelength and consists of non-ionizing radiation. Both domestic and foreign research institutions, including the army, have attached considerable im...The terahertz(THz) band lies between microwave and infrared rays in wavelength and consists of non-ionizing radiation. Both domestic and foreign research institutions, including the army, have attached considerable importance to the research and development of THz technology because this radiation exhibits both photon-like and electron-like properties, which grant it considerable application value and potential. With the rapid development of THz technology and related applications, studies of the biological effects of THz radiation have become a major focus in the field of life sciences. Research in this field has only just begun, both at home and abroad. In this paper, research progress with respect to THz radiation, including its biological effects, mechanisms and methods of protection, will be reviewed.展开更多
With the ever increasing application of electronic technology, our exposure to artificial electromagnetic energy is also rapidly increasing. Electromagnetic radiation （EMR） is the fourth largest source of pollution,...With the ever increasing application of electronic technology, our exposure to artificial electromagnetic energy is also rapidly increasing. Electromagnetic radiation （EMR） is the fourth largest source of pollution, after air, water, and noise.展开更多
Machine learning methods have proven to be powerful in various research fields.In this paper,we show that research on radiation effects could benefit from such methods and present a machine learning-based scientific d...Machine learning methods have proven to be powerful in various research fields.In this paper,we show that research on radiation effects could benefit from such methods and present a machine learning-based scientific discovery approach.The total ionizing dose(TID)effects usually cause gain degradation of bipolar junction transistors(BJTs),leading to functional failures of bipolar integrated circuits.Currently,many experiments of TID effects on BJTs have been conducted at different laboratories worldwide,producing a large amount of experimental data which provides a wealth of information.However,it is difficult to utilize these data effectively.In this study,we proposed a new artificial neural network(ANN)approach to analyze the experimental data of TID effects on BJTs An ANN model was built and trained using data collected from different experiments.The results indicate that the proposed ANN model has advantages in capturing nonlinear correlations and predicting the data.The trained ANN model suggests that the TID hardness of a BJT tends to increase with base current I.A possible cause for this finding was analyzed and confirmed through irradiation experiments.展开更多
With the increasing knowledge of shortwave radiation,it is widely used in wireless communications,radar observations,industrial manufacturing,and medical treatments.Despite of the benefits from shortwave,these wide ap...With the increasing knowledge of shortwave radiation,it is widely used in wireless communications,radar observations,industrial manufacturing,and medical treatments.Despite of the benefits from shortwave,these wide applications expose humans to the risk of shortwave electromagnetic radiation,which is alleged to cause potential damage to biological systems.This review focused on the exposure to shortwave electromagnetic radiation,considering in vitro,in vivo and epidemiological results that have provided insight into the biological effects and mechanisms of shortwave.Additionally,some protective measures and suggestions are discussed here in the hope of obtaining more benefits from shortwave with fewer health risks.展开更多
Background:Transrectal(TR)and transperineal(TP)biopsies are commonly used methods for diagnosing prostate cancer.However,their comparative effectiveness in conjunction with machine learning(ML)techniques remains under...Background:Transrectal(TR)and transperineal(TP)biopsies are commonly used methods for diagnosing prostate cancer.However,their comparative effectiveness in conjunction with machine learning(ML)techniques remains underexplored.This study aimed to evaluate the predictive accuracy of ML algorithms in detecting prostate cancer using data derived from TR and TP biopsies.Methods:The clinical records of patients who underwent prostate biopsy at King Saud University Medical City and King Faisal Specialist Hospital and Research Centerin Riyadh,Saudi Arabia,between 2018 and 2025 were analyzed.Data were used to train and testMLmodels,including eXtreme Gradient Boosting(XGBoost),Decision Tree,Random Forest,and Extra Trees.Results:The two datasets are comparable.The models demonstrated exceptional performance,achieving accuracies of up to 96.49%and 95.56%on TP and TR biopsy datasets,respectively.The area under the curve(AUC)values were also high,reaching 0.9988 for TP and 0.9903 for TR biopsy predictions.Conclusion:These findings highlight the potential of MLto enhance the diagnostic accuracy of prostate cancer detection irrespective of the biopsy method.However,TP biopsy data showed marginally higher accuracy,possibly because of the lower risk of contamination.While ML holds great promise for transforming prostate cancer care,further research is needed to address limitations.Collaboration between clinicians,data scientists,and researchers is crucial to ensure the clinical relevance and interpretability of ML models.展开更多
With the rapid development of artificial intelligence technology,the development of virtual reality technology has received increasing attention in various fields.Based on the difficulties in the course construction o...With the rapid development of artificial intelligence technology,the development of virtual reality technology has received increasing attention in various fields.Based on the difficulties in the course construction of“Virtual Reality Technology”,this paper adopts a questionnaire survey method to study the learning effects of students majoring in digital media technology at Guangxi University of Finance and Economics regarding the“Virtual Reality Technology”course.The research mainly involves four aspects:learning content,teaching effectiveness,learning experience,and future development needs.The research analysis in this paper not only provides strong support for the construction of a first-class course in“Virtual Reality Technology”but also offers references for the course construction of digital media technology majors in other universities.展开更多
Polytetrafluoroethylene (Teflon), a widely used spacecraft material, isstudied to investigate the vacuum ultraviolet (VUV) effects and its synergistic effects with atomicoxygen (AO) in a ground-based simulation facili...Polytetrafluoroethylene (Teflon), a widely used spacecraft material, isstudied to investigate the vacuum ultraviolet (VUV) effects and its synergistic effects with atomicoxygen (AO) in a ground-based simulation facility. The samples before and after the experiments arecompared in appearance, mass, optical properties and surface composition. The reactioncharacteristics of Teflon are summarized and the reaction mechanisms are analyzed. The followingconclusion can be drawn: at the action of VUV the Teflon sample surface is darkened for theaccumulation of carbon; and when the sample is exposed to AO, the carbon is oxidized and thedarkening surface is bleached; the synergistic effects of VUV and AO may cause the erosion of Teflonmore severe.展开更多
The backwater effect caused by tributary inflow can significantly elevate the water level profile upstream of a confluence point.However,the influence of mainstream and confluence discharges on the backwater effect in...The backwater effect caused by tributary inflow can significantly elevate the water level profile upstream of a confluence point.However,the influence of mainstream and confluence discharges on the backwater effect in a river reach remains unclear.In this study,various hydrological data collected from the Jingjiang Reach of the Yangtze River in China were statistically analyzed to determine the backwater degree and range with three representative mainstream discharges.The results indicated that the backwater degree increased with mainstream discharge,and a positive relationship was observed between the runoff ratio and backwater degree at specific representative mainstream discharges.Following the operation of the Three Gorges Project,the backwater effect in the Jingjiang Reach diminished.For instance,mean backwater degrees for low,moderate,and high mainstream discharges were recorded as 0.83 m,1.61 m,and 2.41 m during the period from 1990 to 2002,whereas these values decreased to 0.30 m,0.95 m,and 2.08 m from 2009 to 2020.The backwater range extended upstream as mainstream discharge increased from 7000 m3/s to 30000 m3/s.Moreover,a random forest-based machine learning model was used to quantify the backwater effect with varying mainstream and confluence discharges,accounting for the impacts of mainstream discharge,confluence discharge,and channel degradation in the Jingjiang Reach.At the Jianli Hydrological Station,a decrease in mainstream discharge during flood seasons resulted in a 7%–15%increase in monthly mean backwater degree,while an increase in mainstream discharge during dry seasons led to a 1%–15%decrease in monthly mean backwater degree.Furthermore,increasing confluence discharge from Dongting Lake during June to July and September to November resulted in an 11%–42%increase in monthly mean backwater degree.Continuous channel degradation in the Jingjiang Reach contributed to a 6%–19%decrease in monthly mean backwater degree.Under the influence of these factors,the monthly mean backwater degree in 2017 varied from a decrease of 53%to an increase of 37%compared to corresponding values in 1991.展开更多
To improve the total-dose radiation hardness,silicon-on-insulator （SOI） wafers fabricated by the separation-by-implanted-oxygen （SIMOX） method are modified by Si ion implantation into the buried oxide with a post ...To improve the total-dose radiation hardness,silicon-on-insulator （SOI） wafers fabricated by the separation-by-implanted-oxygen （SIMOX） method are modified by Si ion implantation into the buried oxide with a post anneal. The ID- VG characteristics can be tested with the pseudo-MOSFET method before and after radiation. The results show that a proper Si-ion-implantation method can enhance the total-dose radiation tolerance of the materials.展开更多
Microwave radiation has been widely used in various fields,such as communication,industry,medical treatment,and military applications.Microwave radiation may cause injuries to both the structures and functions of vari...Microwave radiation has been widely used in various fields,such as communication,industry,medical treatment,and military applications.Microwave radiation may cause injuries to both the structures and functions of various organs,such as the brain,heart,reproductive organs,and endocrine organs,which endanger human health.Therefore,it is both theoretically and clinically important to conduct studies on the biological effects induced by microwave radiation.The successful establishment of injury models is of great importance to the reliability and reproducibility of these studies.In this article,we review the microwave exposure conditions,subjects used to establish injury models,the methods used for the assessment of the injuries,and the indicators implemented to evaluate the success of injury model establishment in studies on biological effects induced by microwave radiation.展开更多
This paper studies the total ionizing dose radiation effects on MOS （metal-oxide-semiconductor） transistors with normal and enclosed gate layout in a standard commercial CMOS （compensate MOS） bulk process. The lea...This paper studies the total ionizing dose radiation effects on MOS （metal-oxide-semiconductor） transistors with normal and enclosed gate layout in a standard commercial CMOS （compensate MOS） bulk process. The leakage current, threshold voltage shift, and transconductance of the devices were monitored before and after γ-ray irradiation. The parameters of the devices with different layout under different bias condition during irradiation at different total dose are investigated. The results show that the enclosed layout not only effectively eliminates the leakage but also improves the performance of threshold voltage and transconductance for NMOS （n-type channel MOS） transistors. The experimental results also indicate that analogue bias during irradiation is the worst case for enclosed gate NMOS. There is no evident different behaviour observed between normal PMOS （p-type channel MOS） transistors and enclosed gate PMOS transistors.展开更多
基金National Natural Science Foundation of China(82001814)National High Level Hospital Clinical Research Funding(grant number 2022-PUMCH-B-067)+1 种基金National High Level Hospital Clinical Research Funding(grant number 2022-PUMCH-B-068)2021 SKY Imaging Research Fund of the Chinese Internatinal Medical Foundation(Z-2014-07-2101).
文摘Purpose:To assess the clinical efficacy of integrating deep learning reconstruction(DLR)with contrast-enhancement-boost(CE-boost)in 80 kVp head and neck CT angiography(CTA)using substantially lowered radiation and contrast medium(CM)doses,compared to the standard 100 kVp protocol using hybrid iterative reconstruction(HIR).Methods:Sixty-six patients were prospectively enrolled and randomly assigned to one of two groups:the low-dose group(n=33),receiving 80 kVp and 28 mL contrast medium(CM)with a noise index(NI)of 15;and the regular-dose group(n=33),receiving 100 kVp and 40 mL CM with an NI of 10.For the lowdose group,images underwent reconstruction using both hybrid iterative reconstruction(HIR)and deep learning reconstruction(DLR)at mild-,standard-,and strong-strength levels,both before and after combination with contrast enhancement-boost(CE-boost).This generated eight distinct datasets:L-HIR,L-DLR_(mild),L-DLR_(standard),L-DLR_(strong),L-HIR-CE,L-DLR_(mild)-CE,L-DLR_(standard)-CE,and L-DLR_(strong)-CE.Images for the regular-dose group were reconstructed solely with HIR(R-HIR).Quantitative analysis involved calculating and comparing CT attenuation,image noise,signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR)within six key vessels:the aortic arch(AA),internal carotid artery(ICA),external carotid artery(ECA),vertebral arteries(VA),basilar artery(BA),and middle cerebral artery(MCA).Two radiologists independently assessed subjective image quality using a 5-point scale,with statistical significance defined as P<0.05.Results:Compared to the regular-dose group,the low-dose protocol achieved a substantial reduction in contrast media volume(28 mL versus 40 mL,a 30%decrease)and radiation exposure((0.41±0.08)mSv versus(1.18±0.12)mSv,a 65%reduction).Both L-DLR_(standard) and L-DLR_(strong) delivered comparable or superior SNR and CNR across all vascular segments relative to R-HIR.However,subjective image quality scores for L-DLR at all strength levels fell below those for R-HIR(all P<0.05 for both readers).Combining CE-boost with the low-dose protocol significantly enhanced the objective image performance of L-DLR_(strong)-CE(all P<0.05)and produced subjective image scores comparable to R-HIR(reader 1:P=0.15;reader 2:P=0.06).Conclusion:When compared to the standard 100 kVp head and neck CTA,the combination of the DLR and CE-boost techniques at 80 kVp can achieve a 30%reduction in contrast dose and a 65%reduction in radiation dose,while maintaining both objective and subjective image quality.
基金supported by the Natural Science Foundation of Xiamen,China(3502Z202472001)the National Natural Science Foundation of China(22402163,22021001,21925404,T2293692,and 22361132532)。
文摘Metal-nitrogen-carbon(M-N-C)single-atom catalysts are widely utilized in various energy-related catalytic processes,offering a highly efficient and cost-effective catalytic system with significant potential.Recently,curvature-induced strain has been extensively demonstrated as a powerful tool for modulating the catalytic performance of M-N-C catalysts.However,identifying optimal strain patterns using density functional theory(DFT)is computationally intractable due to the high-dimensional search space.Here,we developed a graph neural network(GNN)integrated with an advanced topological data analysis tool-persistent homology-to predict the adsorption energy response of adsorbate under proposed curvature patterns,using nitric oxide electroreduction(NORR)as an example.Our machine learning model achieves high accuracy in predicting the adsorption energy response to curvature,with a mean absolute error(MAE)of 0.126 eV.Furthermore,we elucidate general trends in curvature-modulated adsorption energies of intermediates across various metals and coordination environments.We recommend several promising catalysts for NORR that exhibit significant potential for performance optimization via curvature modulation.This methodology can be readily extended to describe other non-bonded interactions,such as lattice strain and surface stress,providing a versatile approach for advanced catalyst design.
基金supported by the National Natural Science Foundation of China(No.82173463)the Young Scholar Science Foundation of China CDC(No.2023A204)the NIRP Research Fund for Young Scholars(No.2024NB01).
文摘In the event of nuclear accidents and incidents,when emergency resources are scarce,rapid and high-throughput biodosimeters for massive population triage and estimation are essential to guide medical treatment.Lymphocyte dynamics,chromosome aberration analysis,and micronucleus assays are mainly used to estimate the biological dose of radiation[1].However,these technologies require highly trained personnel to perform and interpret and have the limitations of time consumption and low throughput,underscoring the urgent need for the development of radiation biomarkers and early classification.Dose and temporal responses as well as efficient triage models are important facets of radiation biodosimeters.
文摘Both nMOS and pMOS transistors with two-edged and multi-finger layouts are fabricated in a standard commercial 0.6μm CMOS/bulk process to study their total ionizing dose （TID） radiation effects. The leakage current, threshold voltage shift, and transconductance of the devices are monitored before and after T-ray irradiation. Different device bias conditions are used during irradiation. The experiment results show that TID radiation effects on nMOS devices are very sensitive to their layout structures. The impact of the layout on TID effects on pMOS devices is slight and can be neglected.
基金supported by the IITP(Institute for Information&Communications Technology Planning&Evaluation)under the ITRC(Information Technology Research Center)support program(IITP-2025-RS-2024-00438288)grant funded by the Korea government(MSIT)+1 种基金National Research Council of Science&Technology(NST)grant by the MSIT(Aerospace Semiconductor Strategy Research Project No.GTL25051-000)supported by the IC Design Education Center(IDEC),Korea。
文摘This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-assisted junction termination extension(RA-JTE),multiple floating zone JTE(MFZ-JTE),and field limiting rings(FLR)were fabricated and irradiated with45 Me V protons at fluences ranging from 1×10^(12) to 1×10^(14) cm^(-2).Experimental results,supported by TCAD simulations,show that the RA-JTE structure maintained stable breakdown performance with less than 1%variation due to its effective electric field redistribution by multiple P+rings.In contrast,MFZ-JTE and FLR exhibit breakdown voltage shifts of 6.1%and 15.2%,respectively,under the highest fluence.These results demonstrate the superior radiation tolerance of the RA-JTE structure under TID conditions and provide practical design guidance for radiation-hardened Si C power devices in space and other highradiation environments.
基金The National Key Research and Development Program of China,No.2023YFC3206601。
文摘Landslides pose a formidable natural hazard across the Qinghai-Tibet Plateau(QTP),endangering both ecosystems and human life.Identifying the driving factors behind landslides and accurately assessing susceptibility are key to mitigating disaster risk.This study integrated multi-source historical landslide data with 15 predictive factors and used several machine learning models—Random Forest(RF),Gradient Boosting Regression Trees(GBRT),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost)—to generate susceptibility maps.The Shapley additive explanation(SHAP)method was applied to quantify factor importance and explore their nonlinear effects.The results showed that:(1)CatBoost was the best-performing model(CA=0.938,AUC=0.980)in assessing landslide susceptibility,with altitude emerging as the most significant factor,followed by distance to roads and earthquake sites,precipitation,and slope;(2)the SHAP method revealed critical nonlinear thresholds,demonstrating that historical landslides were concentrated at mid-altitudes(1400-4000 m)and decreased markedly above 4000 m,with a parallel reduction in probability beyond 700 m from roads;and(3)landslide-prone areas,comprising 13%of the QTP,were concentrated in the southeastern and northeastern parts of the plateau.By integrating machine learning and SHAP analysis,this study revealed landslide hazard-prone areas and their driving factors,providing insights to support disaster management strategies and sustainable regional planning.
基金supported by the National Key R&D Program of China(No.2022YFE0109500)the National Natural Science Foundation of China(Nos.52071255,52301250,52171190 and 12304027)+2 种基金the Key R&D Project of Shaanxi Province(No.2022GXLH-01-07)the Fundamental Research Funds for the Central Universities(China)the World-Class Universities(Disciplines)and the Characteristic Development Guidance Funds for the Central Universities.
文摘With the rapid development of artificial intelligence,magnetocaloric materials as well as other materials are being developed with increased efficiency and enhanced performance.However,most studies do not take phase transitions into account,and as a result,the predictions are usually not accurate enough.In this context,we have established an explicable relationship between alloy compositions and phase transition by feature imputation.A facile machine learning is proposed to screen candidate NiMn-based Heusler alloys with desired magnetic entropy change and magnetic transition temperature with a high accuracy R^(2)≈0.98.As expected,the measured properties of prepared NiMn-based alloys,including phase transition type,magnetic entropy changes and transition temperature,are all in good agreement with the ML predictions.As well as being the first to demonstrate an explicable relationship between alloy compositions,phase transitions and magnetocaloric properties,our proposed ML model is highly predictive and interpretable,which can provide a strong theoretical foundation for identifying high-performance magnetocaloric materials in the future.
基金Project supported by the National Natural Science Foundation of China(No.30570323)Foundation of State Developing and Reforming Committee(No.IFZ20051210)
文摘The hydroponic culture experiments of soybean bean seedlings were conducted to investigate the effect of lanthanum （La） on nitrogen metabolism under two different levels of elevated UV-B radiation （UV-B, 280-320 nm）. The whole process of nitrogen metabolism involves uptake and transport of nitrate, nitrate assimilation, ammonium assimilation, amino acid biosynthesis, and protein synthesis. Compared with the control, UV-B radiation with the intensity of low level 0.15 W/m^2 and high level 0.45 W/m^2 significantly affected the whole nitrogen metabolism in soybean seedlings （p 〈 0.05）. It restricted uptake and transport of NO3^-, inhibited activity of some key nitrogen-metabolism-related enzymes, such as： nitrate reductase （NR） to the nitrate reduction, glutamine systhetase （GS） and glutamine synthase （GOGAT） to the ammonia assimilation, while it increased the content of free amino acids and decreased that of soluble protein as well. The damage effect of high level of UV-B radiation on nitrogen metabolism was greater than that of low level. And UV-B radiation promoted the activity of the anti-adversity enzyme glutamate dehydrogenase （GDH）, which reduced the toxicity of excess ammonia in plant. After pretreatment with the optimum concentration of La （20 mg/L）, La could increase the activity of NR, GS, GOGAT, and GDH, and ammonia assimilation, but decrease nitrate and ammonia accumulation. In conclusion, La could relieve the damage effect of UV-B radiation on plant by regulating nitrogen metabolism process, and its alleviating effect under low level was better than that under the high one.
基金Grant from Major Scientific Research Program of Medical Treatment and Public Health of Guangxi Zhuang Autonomous Region, No.200730
文摘BACKGROUND： Conventional methods （such as occlusion therapy, fine manipulation, complementary, and alternative medicine） take effects slowly, are time and labor consuming, and have uncertain curative effects in the treatment of amblyopia. Perceptual learning, a new method for treating amblyopia, improves the ability to process signals from the cerebral optic nerve system by specific visual stimulation and visual learning, as well as activation of the visual signal pathway utilizing brain nervous system plasticity. OBJECTIVE： This study investigated and evaluated the curative effects of perceptual learning, which can directionally increase brain plasticity, on the treatment of amblyopia in children. The relationship between curative effect and time was also analyzed. DESIGN： A self-control experiment. SETTING： Visual Science and Optometry Center, People＇s Hospital of Guangxi Zhuang Autonomous Region. PARTICIPANTS： A total of 125 amblyopic children （250 amblyopic eyes）, 73 males, 52 females, averaging （6±2） years of age, received treatment at the Visual Science and Optometry Center, People＇s Hospital of Guangxi Zhuang Autonomous Region between September 2006 and February 2007 and were recruited for this study. All children presented with no structural disease of the eyeballs. Written informed consent for therapeutic regiments was obtained from each child＇s parent. The protocol received approval from the Hospital＇s Ethics Committee. METHODS： Visual function was tested with a perceptual learning system （Research Center for Human Health and Development of Sun Yat-sen University, National Engineering Technique Research Center for Medical Care Implement） for visual noise, position noise, contour discrimination, contrast sensitivity, grating stereogram, and random-dot fusion. These tests helped to evaluate the efficiency of visual information processing of these children, and to determine the degree of defects of the optic nerve cells and the connections of visual cortical neurons. According to results of visual function tests, individualized treatment was adopted for each amblyopia patient using perceptual learning system. One course of treatment lasted one month, and treatment was performed twice every day with two training procedures （each training procedure lasted for ten minutes）. There was a ten-minute time interval between the two training procedures. The training treatment was performed in a quiet and dark environment. Visual acuity and recovery of visual function were tested every month. Original training procedure was continued or adjusted according to the results of visual function. MAIN OUTCOME MEASURES： Visual function change; relationship of curative effects and curative time. RESULTS： A total of 125 amblyopia children were included in the final analysis. The total efficiency of perceptual learning for treating amblyopia in children was 75.2%. Visual acuity began to greatly increase 3 months after treatment （P 〈 0.05）. Visual acuity was best corrected from 0.60 ± 0.23 before treatment to 0.86 ± 0.26 after treatment （P 〈 0.05）. The mean time to reach improved levels with curative effects was （2.82 ± 1.30） months, and to reach a basically cured level was （2.87 ±1.40） months. Percentage of improved visual acuity was the highest [98% （39/40）] in children that received 3 months of treatment and the lowest [55% （31/56）] in children that received 1 month of treatment （P 〈 0.05）. The percentage of basically cured levels with curative effects increased with length of learning time and was the greatest in children that received 4 months of treatment [67% （31/46）, P 〈 0.05]. CONCLUSION： Perceptual learning rapidly and remarkably improves visual function of amblyopia children; however, the curative effects are first apparent two and three months after intervention.
文摘The terahertz(THz) band lies between microwave and infrared rays in wavelength and consists of non-ionizing radiation. Both domestic and foreign research institutions, including the army, have attached considerable importance to the research and development of THz technology because this radiation exhibits both photon-like and electron-like properties, which grant it considerable application value and potential. With the rapid development of THz technology and related applications, studies of the biological effects of THz radiation have become a major focus in the field of life sciences. Research in this field has only just begun, both at home and abroad. In this paper, research progress with respect to THz radiation, including its biological effects, mechanisms and methods of protection, will be reviewed.
基金supported by the National Natural Science Foundation of China[No.31570847]
文摘With the ever increasing application of electronic technology, our exposure to artificial electromagnetic energy is also rapidly increasing. Electromagnetic radiation （EMR） is the fourth largest source of pollution, after air, water, and noise.
基金supported by the National Natural Science Foundation of China (Nos. 11690040 and 11690043)。
文摘Machine learning methods have proven to be powerful in various research fields.In this paper,we show that research on radiation effects could benefit from such methods and present a machine learning-based scientific discovery approach.The total ionizing dose(TID)effects usually cause gain degradation of bipolar junction transistors(BJTs),leading to functional failures of bipolar integrated circuits.Currently,many experiments of TID effects on BJTs have been conducted at different laboratories worldwide,producing a large amount of experimental data which provides a wealth of information.However,it is difficult to utilize these data effectively.In this study,we proposed a new artificial neural network(ANN)approach to analyze the experimental data of TID effects on BJTs An ANN model was built and trained using data collected from different experiments.The results indicate that the proposed ANN model has advantages in capturing nonlinear correlations and predicting the data.The trained ANN model suggests that the TID hardness of a BJT tends to increase with base current I.A possible cause for this finding was analyzed and confirmed through irradiation experiments.
文摘With the increasing knowledge of shortwave radiation,it is widely used in wireless communications,radar observations,industrial manufacturing,and medical treatments.Despite of the benefits from shortwave,these wide applications expose humans to the risk of shortwave electromagnetic radiation,which is alleged to cause potential damage to biological systems.This review focused on the exposure to shortwave electromagnetic radiation,considering in vitro,in vivo and epidemiological results that have provided insight into the biological effects and mechanisms of shortwave.Additionally,some protective measures and suggestions are discussed here in the hope of obtaining more benefits from shortwave with fewer health risks.
文摘Background:Transrectal(TR)and transperineal(TP)biopsies are commonly used methods for diagnosing prostate cancer.However,their comparative effectiveness in conjunction with machine learning(ML)techniques remains underexplored.This study aimed to evaluate the predictive accuracy of ML algorithms in detecting prostate cancer using data derived from TR and TP biopsies.Methods:The clinical records of patients who underwent prostate biopsy at King Saud University Medical City and King Faisal Specialist Hospital and Research Centerin Riyadh,Saudi Arabia,between 2018 and 2025 were analyzed.Data were used to train and testMLmodels,including eXtreme Gradient Boosting(XGBoost),Decision Tree,Random Forest,and Extra Trees.Results:The two datasets are comparable.The models demonstrated exceptional performance,achieving accuracies of up to 96.49%and 95.56%on TP and TR biopsy datasets,respectively.The area under the curve(AUC)values were also high,reaching 0.9988 for TP and 0.9903 for TR biopsy predictions.Conclusion:These findings highlight the potential of MLto enhance the diagnostic accuracy of prostate cancer detection irrespective of the biopsy method.However,TP biopsy data showed marginally higher accuracy,possibly because of the lower risk of contamination.While ML holds great promise for transforming prostate cancer care,further research is needed to address limitations.Collaboration between clinicians,data scientists,and researchers is crucial to ensure the clinical relevance and interpretability of ML models.
基金Exploration and Research on the Construction of Teaching Resources for the“Virtual Reality Technology”Course in the Context of Artificial Intelligence。
文摘With the rapid development of artificial intelligence technology,the development of virtual reality technology has received increasing attention in various fields.Based on the difficulties in the course construction of“Virtual Reality Technology”,this paper adopts a questionnaire survey method to study the learning effects of students majoring in digital media technology at Guangxi University of Finance and Economics regarding the“Virtual Reality Technology”course.The research mainly involves four aspects:learning content,teaching effectiveness,learning experience,and future development needs.The research analysis in this paper not only provides strong support for the construction of a first-class course in“Virtual Reality Technology”but also offers references for the course construction of digital media technology majors in other universities.
文摘Polytetrafluoroethylene (Teflon), a widely used spacecraft material, isstudied to investigate the vacuum ultraviolet (VUV) effects and its synergistic effects with atomicoxygen (AO) in a ground-based simulation facility. The samples before and after the experiments arecompared in appearance, mass, optical properties and surface composition. The reactioncharacteristics of Teflon are summarized and the reaction mechanisms are analyzed. The followingconclusion can be drawn: at the action of VUV the Teflon sample surface is darkened for theaccumulation of carbon; and when the sample is exposed to AO, the carbon is oxidized and thedarkening surface is bleached; the synergistic effects of VUV and AO may cause the erosion of Teflonmore severe.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFC3209504)the National Natural Science Foundation of China(Grants No.U2040215 and 52479075)the Natural Science Foundation of Hubei Province(Grant No.2021CFA029).
文摘The backwater effect caused by tributary inflow can significantly elevate the water level profile upstream of a confluence point.However,the influence of mainstream and confluence discharges on the backwater effect in a river reach remains unclear.In this study,various hydrological data collected from the Jingjiang Reach of the Yangtze River in China were statistically analyzed to determine the backwater degree and range with three representative mainstream discharges.The results indicated that the backwater degree increased with mainstream discharge,and a positive relationship was observed between the runoff ratio and backwater degree at specific representative mainstream discharges.Following the operation of the Three Gorges Project,the backwater effect in the Jingjiang Reach diminished.For instance,mean backwater degrees for low,moderate,and high mainstream discharges were recorded as 0.83 m,1.61 m,and 2.41 m during the period from 1990 to 2002,whereas these values decreased to 0.30 m,0.95 m,and 2.08 m from 2009 to 2020.The backwater range extended upstream as mainstream discharge increased from 7000 m3/s to 30000 m3/s.Moreover,a random forest-based machine learning model was used to quantify the backwater effect with varying mainstream and confluence discharges,accounting for the impacts of mainstream discharge,confluence discharge,and channel degradation in the Jingjiang Reach.At the Jianli Hydrological Station,a decrease in mainstream discharge during flood seasons resulted in a 7%–15%increase in monthly mean backwater degree,while an increase in mainstream discharge during dry seasons led to a 1%–15%decrease in monthly mean backwater degree.Furthermore,increasing confluence discharge from Dongting Lake during June to July and September to November resulted in an 11%–42%increase in monthly mean backwater degree.Continuous channel degradation in the Jingjiang Reach contributed to a 6%–19%decrease in monthly mean backwater degree.Under the influence of these factors,the monthly mean backwater degree in 2017 varied from a decrease of 53%to an increase of 37%compared to corresponding values in 1991.
文摘To improve the total-dose radiation hardness,silicon-on-insulator （SOI） wafers fabricated by the separation-by-implanted-oxygen （SIMOX） method are modified by Si ion implantation into the buried oxide with a post anneal. The ID- VG characteristics can be tested with the pseudo-MOSFET method before and after radiation. The results show that a proper Si-ion-implantation method can enhance the total-dose radiation tolerance of the materials.
基金supported by the National Natural Science Foundation of China(61801506)。
文摘Microwave radiation has been widely used in various fields,such as communication,industry,medical treatment,and military applications.Microwave radiation may cause injuries to both the structures and functions of various organs,such as the brain,heart,reproductive organs,and endocrine organs,which endanger human health.Therefore,it is both theoretically and clinically important to conduct studies on the biological effects induced by microwave radiation.The successful establishment of injury models is of great importance to the reliability and reproducibility of these studies.In this article,we review the microwave exposure conditions,subjects used to establish injury models,the methods used for the assessment of the injuries,and the indicators implemented to evaluate the success of injury model establishment in studies on biological effects induced by microwave radiation.
基金Project supported by the National Natural Science Foundation of China （Grant No 6037202/F010204）.
文摘This paper studies the total ionizing dose radiation effects on MOS （metal-oxide-semiconductor） transistors with normal and enclosed gate layout in a standard commercial CMOS （compensate MOS） bulk process. The leakage current, threshold voltage shift, and transconductance of the devices were monitored before and after γ-ray irradiation. The parameters of the devices with different layout under different bias condition during irradiation at different total dose are investigated. The results show that the enclosed layout not only effectively eliminates the leakage but also improves the performance of threshold voltage and transconductance for NMOS （n-type channel MOS） transistors. The experimental results also indicate that analogue bias during irradiation is the worst case for enclosed gate NMOS. There is no evident different behaviour observed between normal PMOS （p-type channel MOS） transistors and enclosed gate PMOS transistors.
