The lattice parameter,measured with sufficient accuracy,can be utilized to evaluate the quality of single crystals and to determine the equation of state for materials.We propose an iterative method for obtaining more...The lattice parameter,measured with sufficient accuracy,can be utilized to evaluate the quality of single crystals and to determine the equation of state for materials.We propose an iterative method for obtaining more precise lattice parameters using the interaction points for the pseudo-Kossel pattern obtained from laser-induced X-ray diffraction(XRD).This method has been validated by the analysis of an XRD experiment conducted on iron single crystals.Furthermore,the method was used to calculate the compression ratio and rotated angle of an LiF sample under high pressure loading.This technique provides a robust tool for in-situ characterization of structural changes in single crystals under extreme conditions.It has significant implications for studying the equation of state and phase transitions.展开更多
The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool...The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool design and plays an essential role in determining the machining accuracy of the workpiece.Researchers have extensively studied methods to model,extract,optimize,and measure the geometric errors that affect the geometric accuracy of machine tools.This paper provides a comprehensive review of the state-of-the-art approaches and an overview of the latest research progress associated with geometric accuracy design in CNC machine tools.This paper explores the interrelated aspects of CNC machine tool accuracy design:modeling,analysis and optimization.Accuracy analysis,which includes geometric error modeling and sensitivity analysis,determines a machine tool’s output accuracy through its volumetric error model,given the known accuracy of its individual components.Conversely,accuracy allocation designs the accuracy of the machine tool components according to given output accuracy requirements to achieve optimization between the objectives of manufacturing cost,quality,reliability,and environmental impact.In addition to discussing design factors and evaluation methods,this paper outlines methods for verifying the accuracy of design results,aiming to provide a practical basis for ensuring that the designed accuracy is achieved.Finally,the challenges and future research directions in geometric accuracy design are highlighted.展开更多
BACKGROUND The accuracy of blind intra-articular injections in the shoulder is rather low.Inaccurate injections tend to lead to poorer treatment outcomes.The“Delaware posterior bone touch technique”has shown higher ...BACKGROUND The accuracy of blind intra-articular injections in the shoulder is rather low.Inaccurate injections tend to lead to poorer treatment outcomes.The“Delaware posterior bone touch technique”has shown higher accuracy in young,slender,healthy volunteers than the classical“Cyriax technique”.AIM To investigate whether the Delaware technique would also be more accurate in older patients with capsulitis.METHODS We analyzed the files of 100 consecutive patients with capsulitis who were treated with an intra-articular injection containing a mixture of triamcinolone,lidocaine,and air.After the injection,the shoulder was moved to determine whether a squishing sound could be produced.The squishing sound was interpreted as an accurate injection.The scores with the new Delaware technique were compared against those with the Cyriax technique in a previous study.RESULTS Squishing was heard after 87%of the injections.This was 13%(10%points)more than the 77%in the previous study(P=0.004).CONCLUSION The Delaware technique was significantly more accurate than the Cyriax technique also in middle aged patients with capsulitis.We hypothesize that the difference is caused by a lower risk that a part of the opening of the needle is still outside the capsule.展开更多
The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and...The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and statistical analysis methods.The travel-time corrections for the Pg phase of 72 stations range between-0.25 s and 0.14 s,while the corrections for the Sg phase range between 0.27 s and 0.35 s,and those for the Pn phase are between-0.86 s and 0.07 s.The spatial distribution of travel-time corrections for Pg,Sg,and Pn phases of 72 stations correlates well with the geological structure in this region.This indicates that the travel-time corrections for Pg and Sg phases are mainly caused by the discrepancy between the actual crustal velocity structure beneath the stations and the 1D South China travel-time model.These corrections empirically compensate for systematic travel-time errors arising from such discrepancies.The primary factor contributing to the travel-time corrections for the Pn phase is the Moho undulations or tilt.These corrections are intended to compensate for systematic errors in travel time caused by variations in the actual Moho.By integrating the obtained travel-time corrections into the HYPO-SAT location algorithm,test results showed an obvious improvement in location accuracy and origin time precision for explosion events.The variation of horizontal distance between repeating earthquake pairs has also improved,with 86%of the repeating earthquake pair spacing being more accurately estimated after correction.This suggests the crucial significance of travel-time correction in earthquake location,and the consideration of travel-time correction exerts a notable impact on enhancing earthquake location accuracy.展开更多
Objective:To analyze the significance of high-frequency ultrasound in differentiating benign and malignant breast micronodules.Methods:Eighty-five patients with breast micronodules admitted for diagnosis between Octob...Objective:To analyze the significance of high-frequency ultrasound in differentiating benign and malignant breast micronodules.Methods:Eighty-five patients with breast micronodules admitted for diagnosis between October 2022 and October 2024 were selected for high-frequency ultrasound diagnosis.The diagnostic efficacy of high-frequency ultrasound was evaluated by comparing it with the results of surgical pathology.Results:High-frequency ultrasound detected 50 benign nodules,primarily breast fibroadenomas,and 35 malignant nodules,mainly breast ductal carcinoma in situ.Based on surgical pathology results,the diagnostic accuracy of high-frequency ultrasound was 96.47%,specificity was 97.96%,and sensitivity was 94.44%.In high-frequency ultrasound diagnosis,the proportion of grade III and IV blood flow in malignant nodules was higher than that in benign nodules,while the proportion of regular shape and clear margins was lower.The proportion of microcalcifications and posterior echo attenuation was higher in malignant nodules,and the resistance index(RI)and peak blood flow velocity were lower than those in benign nodules(P<0.05).Conclusion:High-frequency ultrasound can effectively differentiate benign and malignant breast micronodules,determine specific nodule types,and exhibits high diagnostic accuracy and sensitivity.Additionally,benign and malignant nodules can be differentiated based on the grading of blood flow signals,sonographic features,and blood flow velocity,providing reasonable guidance for subsequent treatment plans.展开更多
Objective:To explore nursing measures for elderly patients with chronic obstructive pulmonary disease(COPD)and analyze the effect of continuous nursing pathways on improving the accuracy of aerosol use.Methods:From Ap...Objective:To explore nursing measures for elderly patients with chronic obstructive pulmonary disease(COPD)and analyze the effect of continuous nursing pathways on improving the accuracy of aerosol use.Methods:From April 2023 to April 2024,76 elderly COPD patients admitted to our hospital were randomly selected for nursing research.They were divided into two groups using a computer double-blind method,with 38 patients in each group.The control group received routine nursing,while the observation group applied the continuous nursing pathway.The nursing effects of the two groups were investigated and compared,including(1)aerosol accuracy;(2)cardiopulmonary function;(3)subjective well-being and self-care ability;(4)quality of life;and(5)nursing satisfaction.Results:Compared with the control group,the observation group had a significantly higher accuracy rate of aerosol use(P<0.05).Before nursing,there were no significant differences in cardiopulmonary function indicators,MUNSH scores,and ESCA scores between the two groups(P>0.05).After nursing,the patient's cardiopulmonary function improved significantly,and their subjective well-being and self-care ability increased.The observation group was significantly better than the control group in all the above indicators(P<0.05).The quality of life scores of the observation group were significantly higher than those of the control group(P<0.05).Conclusion:In the nursing of elderly patients with chronic obstructive pulmonary disease,the application of the continuous nursing pathway can effectively improve the accuracy of aerosol use and improve patients'cardiopulmonary function.展开更多
This brief presents a cryogenic voltage reference circuit designed to operate effectively across a wide temperature range from 30 to 300 K.A key feature of the proposed design is utilizing a current subtraction techni...This brief presents a cryogenic voltage reference circuit designed to operate effectively across a wide temperature range from 30 to 300 K.A key feature of the proposed design is utilizing a current subtraction technique for temperature compensation of the reference current,avoiding the deployment of bipolar transistors to reduce area and power consumption.Implemented with a 0.18-μm CMOS process,the circuit achieves a temperature coefficient(TC)of 67.5 ppm/K,which was not achieved in previous works.The design can also attain a power supply rejection(PSR)of 58 d B at 10 k Hz.Meanwhile,the average reference voltage is 1.2 V within a 1.6%3σ-accuracy spread.Additionally,the design is characterized by a minimal power dissipation of 1μW at 30 K and a compact chip area of 0.0035 mm~2.展开更多
Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. ...Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. However, high-altitude and high-latitude lakes undergo seasonal freezing and melting, affecting satellite altimetry accuracy. This paper evaluates the accuracy of lake level height observations by the CryoSat-2, which uses synthetic aperture radar(SAR) across seasons. First, we used lake boundary based on optical remote sensing data to extract the footprints of CryoSat-2 that fall on Namco and Zhari Namco.After elevation conversion and anomaly identification, we obtained the time series of lake levels. These data were compared and verified against lake levels from in-situ measurements to assess the accuracy of CryoSat-2. The results show that CryoSat-2 can monitor lake level height with an accuracy of about 10-13 cm. The correlation coefficient between CryoSat-2 observations and in-situ measurements over Namco is 0.80(p < 0.01), with a Root Mean Square Error(RMSE) of 13 cm. For Zhari Namco, the correlation coefficient is 0.91, with an RMSE of 10 cm, indicating a better match. At the seasonal scale, the seasonal correlation coefficients between CryoSat-2 and in-situ measurement in Namco are 0.47(spring),0.79(summer), and 0.91(fall) with no observations available for winter. The lower correlation in spring may be due to incomplete ice melting. For Zhari Namco, the seasonal correlation coefficients are 0.89(spring), 0.93(summer), 0.89(fall), and 0.87(winter). The results show that CryoSat-2 accuracy is higher in summer and fall, while slightly lower in spring and winter, indicating that ice formation affects accuracy. Even during winter, the altimetry results do not significantly exceed the in-situ lake water level observations.展开更多
Position-sensitive detector(PSD)is widely used in precision measurement fields such as flatness detection,auto-collimator systems,and degrees of freedom testing.However,due to factors such as uneven surface resistance...Position-sensitive detector(PSD)is widely used in precision measurement fields such as flatness detection,auto-collimator systems,and degrees of freedom testing.However,due to factors such as uneven surface resistance and differences in electrode structures,the nonlinearity of PSD becomes increasingly severe as the photosensitive surface moves from the center toward the edges of the four electrodes.To address this issue,a PSD nonlinearity correction algorithm is proposed.The algorithm utilizes the particle swarm optimization(PSO)algorithm to determine the optimal weights and thresholds,providing better initial parameters for the back propagation(BP)neural network.The BP neural network then iterates continuously until the error conditions are met,completing the correction process.Furthermore,a PSD nonlinearity correction system was developed,and the influence of different spot sizes on PSD positioning accuracy was simulated based on the current equation under the Gaussian spot model.This validated the robustness of the correction algorithm under varying spot sizes.The results demonstrate that the overall optimized error is reduced by 84.51%,and for spot sizes smaller than 1 mm,the error reduction exceeds 93.89%.This method not only meets the measurement accuracy requirements but also extends the measurement range of PSD.展开更多
This review comprehensively analyzes advancements in artificial intelligence,particularly machine learning and deep learning,in medical imaging,focusing on their transformative role in enhancing diagnostic accuracy.Ou...This review comprehensively analyzes advancements in artificial intelligence,particularly machine learning and deep learning,in medical imaging,focusing on their transformative role in enhancing diagnostic accuracy.Our in-depth analysis of 138 selected studies reveals that artificial intelligence(AI)algorithms frequently achieve diagnostic performance comparable to,and often surpassing,that of human experts,excelling in complex pattern recognition.Key findings include earlier detection of conditions like skin cancer and diabetic retinopathy,alongside radiologist-level performance for pneumonia detection on chest X-rays.These technologies profoundly transform imaging by significantly improving processes in classification,segmentation,and sequential analysis across diversemodalities such as X-rays,Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and ultrasound.Specific advancements with Convolutional Neural Networks,Recurrent Neural Networks,and ensemble learning techniques have facilitated more precise diagnosis,prediction,and therapy planning.Notably,Generative Adversarial Networks address limited data through augmentation,while transfer learning efficiently adapts models for scarce labeled datasets,and Reinforcement Learning shows promise in optimizing treatment protocols,collectively advancing patient care.Methodologically,a systematic review(2015-2024)used Scopus and Web of Science databases,yielding 7982 initial records.Of these,1189 underwent bibliometric analysis using the R package‘Bibliometrix’,and 138 were comprehensively reviewed for specific findings.Research output surged over the decade,led by Institute of Electrical and Electronics Engineers(IEEE)Access(19.1%).China dominates publication volume(36.1%),while the United States of America(USA)leads total citations(5605),and Hong Kong exhibits the highest average(55.60).Challenges include rigorous validation,regulatory clarity,and fostering clinician trust.This study highlights significant emerging trends and crucial future research directions for successful AI implementation in healthcare.展开更多
Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring...Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring their functional integrity and performance.To achieve sustainable manufacturing in FDM,it is necessary to optimize the print quality and time efficiency concurrently.However,owing to the complex interactions of printing parameters,achieving a balanced optimization of both remains challenging.This study examines four key factors affecting dimensional accuracy and print time:printing speed,layer thickness,nozzle temperature,and bed temperature.Fifty parameter sets were generated using enhanced Latin hypercube sampling.A whale optimization algorithm(WOA)-enhanced support vector regression(SVR)model was developed to predict dimen-sional errors and print time effectively,with non-dominated sorting genetic algorithm Ⅲ(NSGA-Ⅲ)utilized for multi-objective optimization.The technique for Order Preference by Similarity to Ideal Solution(TOPSIS)was applied to select a balanced solution from the Pareto front.In experimental validation,the parts printed using the optimized parameters exhibited excellent dimensional accuracy and printing efficiency.This study comprehensively considered optimizing the printing time and size to meet quality requirements while achieving higher printing efficiency and aiding in the realization of sustainable manufacturing in the field of AM.In addition,the printing of a specific prosthetic component was used as a case study,highlighting the high demands on both dimensional precision and printing efficiency.The optimized process parameters required significantly less printing time,while satisfying the dimensional accuracy requirements.This study provides valuable insights for achieving sustainable AM using FDM.展开更多
Machine learning-based Debris Flow Susceptibility Mapping(DFSM)has emerged as an effective approach for assessing debris flow likelihood,yet its application faces three critical challenges:insufficient reliability of ...Machine learning-based Debris Flow Susceptibility Mapping(DFSM)has emerged as an effective approach for assessing debris flow likelihood,yet its application faces three critical challenges:insufficient reliability of training samples caused by biased negative sampling,opaque decision-making mechanisms in models,and subjective susceptibility mapping methods that lack quantitative evaluation criteria.This study focuses on the Yalong River basin.By integrating high-resolution remote sensing interpretation and field surveys,we established a refined sample database that includes 1,736 debris flow gullies.To address spatial bias in traditional random negative sampling,we developed a semi-supervised optimization strategy based on iterative confidence screening.Comparative experiments with four treebased models(XGBoost,CatBoost,LGBM,and Random Forest)reveal that the optimized sampling strategy improved overall model performance by 8%-12%,with XGBoost achieving the highest accuracy(AUC=0.882)and RF performing the lowest(AUC=0.820).SHAP-based global-local interpretability analysis(applicable to all tree models)identifies elevation and short-duration rainfall as dominant controlling factors.Furthermore,among the tested tree-based models,XGBoost optimized with semisupervised sampling demonstrates the highest reliability in debris flow susceptibility mapping(DFSM),achieving a comprehensive accuracy of 83.64%due to its optimal generalization-stability equilibrium.展开更多
The low accuracy of wire arc additive manufacturing(WAAM)is one of the main factors limiting its development,and is detrimental to the mechanical properties of WAAM structures.This study primarily investigated the eff...The low accuracy of wire arc additive manufacturing(WAAM)is one of the main factors limiting its development,and is detrimental to the mechanical properties of WAAM structures.This study primarily investigated the effects of wire-feeding directions and positions of the molten pool on the quality and accuracy of unsupported WAAM.First,the three-dimensional(3D)morphology and volume of unsupported rods manufactured with different wirefeeding directions were quantitatively evaluated using a 3D scanning method.The effects of the wire-feeding direction and arc length on the volume and standard deviation of the unsupported rods are then discussed in detail.Finally,the influence of the wire-feeding direction on the quality and accuracy of unsupported WAAM is discussed and revealed by combining the temperature gradients,surface tension,and contact angles.The research revealed that feeding a wire into the high-temperature zone of the molten pool could reduce material spatter and achieve higher precision.The volume of the sample fed into the high-temperature zone was 120%of that fed into the low-temperature zone.This reduced not only the material waste but also the standard deviation of the diameter of the same group of samples.This research is of great significance and value for high-quality unsupported WAAM.展开更多
Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address th...Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.展开更多
Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagn...Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagnostic imaging,such as resolution,radiation efficiency,and real-time processing.Methods:This work used a mixed-methods strategy,including controlled phantom experiments,retrospective multi-center clinical data analysis,and quantum-classical hybrid processing to assess enhancements in resolution,dosage efficiency,and diagnostic confidence.Statistical validation included analysis of variance(ANOVA)and receiver-operating characteristic curve analysis,juxtaposing quantum-enhanced methodologies with conventional and deep learning approaches.Results:Quantum entanglement reconstruction enhanced magnetic resonance imaging spatial resolution by 33.2%(P<0.01),quantum noise suppression facilitated computed tomography scans with a 60%reduction in radiation,and quantum beamforming improved ultrasound contrast by 27%while preserving real-time processing(<2 ms delay).Inter-reader variability(12%in Diagnostic Confidence Scores)showed that systematic training is needed,even if the performance was better.The research presented(1)a reusable clinical quantum imaging framework,(2)enhanced hardware processes(field-programmable gate array/graphics processing unit acceleration),and(3)cost-benefit analyses demonstrating a 22-month return on investment breakeven point.Conclusion:Quantum-enhanced imaging has a lot of promise for use in medicine,especially in neurology and cancer.Future research should focus on multi-modal integration(e.g.,positron emission tomography–magnetic resonance imaging),cloud-based quantum simulations for enhanced accessibility,and extensive trials to confirm long-term diagnostic accuracy.This breakthrough gives healthcare systems a technology roadmap and a reason to spend money on quantum-enhanced diagnostics.展开更多
Given that Xinjiang Uygur Autonomous Region of China possesses exceptionally abundant solar radiation resources that can be harnessed to develop clean energy,accurately characterizing their spatiotemporal distribution...Given that Xinjiang Uygur Autonomous Region of China possesses exceptionally abundant solar radiation resources that can be harnessed to develop clean energy,accurately characterizing their spatiotemporal distribution is crucial.This study investigated the applicability of the Clouds and the Earth's Radiant Energy System(CERES)Single Scanner Footprint TOA/Surface Fluxes and Clouds(SSF)product downward surface shortwave radiation dataset(DSSRCER)under clear-sky conditions in Xinjiang.By integrating multi-source data and utilizing techniques like multivariate fitting and model simulation,we established a two-layer aerosol model and developed a clear-sky downward surface shortwave radiation(DSSR)retrieval model specific to Xinjiang using the Santa Barbara Discrete Atmospheric Radiative Transfer(SBDART)model.We further explored the spatiotemporal distribution characteristics of DSSR under clear-sky conditions in Xinjiang from 2017 to 2019 based on the localized DSSR retrieval model.Our findings revealed a significant discrepancy in DSSRCER under clear-sky conditions at the Xiaotang station in Xinjiang.By comparing,screening,and correcting core input parameters while incorporating the two-layer aerosol model,we achieved a more accurate SBDART simulated DSSR(DSSRSBD)compared to DSSRCER.The annual mean DSSR exhibited a distinct distribution pattern with high values in mountainous regions such as the Altay Mountains,Kunlun Mountains,and Tianshan Mountains and significantly lower values in adjacent lowland areas,including the Tarim River Basin and Junggar Basin.In the four typical administrative regions in northern Xinjiang,the annual mean DSSR(ranging from 551.60 to 586.09 W/m^(2))was lower than that in the five typical administrative regions in southern Xinjiang(ranging from 522.10 to 623.62 W/m^(2)).These spatial variations stem from a complex interplay of factors,including latitude,altitude,solar altitude angle,and sunshine duration.The variations in seasonal average DSSR aligned closely with variations in the solar altitude angle,with summer(774.76 W/m^(2))exhibiting the highest values,followed by spring(684.86 W/m^(2)),autumn(544.76 W/m^(2)),and winter(422.74 W/m^(2)).The monthly average DSSR showed a unimodal distribution,peaking in June(792.94 W/m^(2))and reaching its lowest level in December(363.06 W/m^(2)).Overall,our study findings enhance the current understanding of the spatiotemporal distribution characteristics of DSSR in Xinjiang and provide certain references for the management of clean energy development in this region.展开更多
The z-axis-inclined 3D printing process using short carbon fiber-reinforced thermoplastic composites offers the potential for the support-free fabrication of complex structures and theoretically unlimited extension of...The z-axis-inclined 3D printing process using short carbon fiber-reinforced thermoplastic composites offers the potential for the support-free fabrication of complex structures and theoretically unlimited extension of printed components.It has emerged as a promising approach for in-orbit manufacturing of high-performance thermoplastic composite truss structures.However,extreme conditions of the space environment,such as high vacuum and fluctuating high-low temperatures,significantly alter the heat-transfer behavior during the printing process,often resulting in dimensional inaccuracies and degraded mechanical performance.Existing process optimization strategies fail to account for the coupled effects of vacuum and thermal extremes,limiting their applicability in guiding process design under varying vacuum temperature conditions.To address this gap,this study establishes a truss3D printing experimental platform with in situ temperature-monitoring capability under ground-simulated space conditions.It systematically investigates the effects of printing speed and structural geometry on the pre-bonding surface temperature and forming quality of truss structures in high-low temperature vacuum environments.This study reveals the mechanism by which processing and structural parameters affect the component performance through their influence on the pre-bonding surface temperature and dimensional accuracy.The experimental results show that under high-temperature vacuum conditions,the pre-bonding surface temperature is relatively high,resulting in good interfacial bonding.However,increasing the printing speed reduces the forming accuracy and leads to a decline in mechanical performance.In contrast,under low-temperature vacuum conditions,where the pre-bonding surface temperatures are lower,increasing the printing speed within a specific range effectively increases the surface temperature and bonding quality,thereby improving mechanical properties.Additionally,owing to frequent path transitions,the diagonal-strut truss exhibits a lower forming accuracy and pre-bonding surface temperature than the infilling truss,resulting in inferior mechanical performance in high-low temperature vacuum environments.展开更多
BACKGROUND The FreeStyle Libre flash glucose monitoring(FGM)system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose.Due to its increased usage in clinics,the number of studies inve...BACKGROUND The FreeStyle Libre flash glucose monitoring(FGM)system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose.Due to its increased usage in clinics,the number of studies investigating its accuracy has increased.However,its accuracy has not been investigated in highland populations in China.AIM To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes(T2D)who had migrated within 3 mo from highlands to plains.METHODS Overall,68 patients with T2D,selected from those who had recently migrated from highlands to plains(within 3 mo),were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring(CGM)with the FreeStyle Libre FGM system for 14 d.Throughout the study period,fingertip capillary blood glucose was measured daily using the enzyme electrode method(Super GL,China),and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals.Moreover,the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to<5 min.The accuracy of the FGM system was evaluated according to the CGM guidelines.Subsequently,the factors influencing the mean absolute relative difference(MARD)of this system were analyzed by a multiple linear regression method.RESULTS Pearson’s correlation analysis showed that the fingertip and scanned glucose levels were positively correlated(R=0.86,P=0.00).The aggregated MARD of scanned glucose was 14.28±13.40%.Parker's error analysis showed that 99.30%of the data pairs were located in areas A and B.According to the probe wear time of the FreeStyle Libre FGM system,MARD_(1 d) and MARD_(2-14 d) were 16.55%and 14.35%,respectively(t=1.23,P=0.22).Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion(LAGE)was<5.80 mmol/L but negatively correlated with blood glucose when the LAGE was≥5.80 mmol/L.CONCLUSION The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains.This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains.MARD is mainly influenced by glucose levels and fluctuations,and the accuracy of the system is higher when the blood glucose fluctuation is small.In case of higher blood glucose level fluctuations,deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.展开更多
BACKGROUND Helicobacter pylori(H.pylori)infection has been well-established as a significant risk factor for several gastrointestinal disorders.The urea breath test(UBT)has emerged as a leading non-invasive method for...BACKGROUND Helicobacter pylori(H.pylori)infection has been well-established as a significant risk factor for several gastrointestinal disorders.The urea breath test(UBT)has emerged as a leading non-invasive method for detecting H.pylori.Despite numerous studies confirming its substantial accuracy,the reliability of UBT results is often compromised by inherent limitations.These findings underscore the need for a rigorous statistical synthesis to clarify and reconcile the diagnostic accuracy of the UBT for the diagnosis of H.pylori infection.AIM To determine and compare the diagnostic accuracy of 13C-UBT and 14C-UBT for H.pylori infection in adult patients with dyspepsia.METHODS We conducted an independent search of the PubMed/MEDLINE,EMBASE,and Cochrane Central databases until April 2022.Our search included diagnostic accuracy studies that evaluated at least one of the index tests(^(13)C-UBT or ^(14)C-UBT)against a reference standard.We used the QUADAS-2 tool to assess the methodo-logical quality of the studies.We utilized the bivariate random-effects model to calculate sensitivity,specificity,positive and negative test likelihood ratios(LR+and LR-),as well as the diagnostic odds ratio(DOR),and their 95%confidence intervals.We conducted subgroup analyses based on urea dosing,time after urea administration,and assessment technique.To investigate a possible threshold effect,we conducted Spearman correlation analysis,and we generated summary receiver operating characteristic(SROC)curves to assess heterogeneity.Finally,we visually inspected a funnel plot and used Egger’s test to evaluate publication bias.endorsing both as reliable diagnostic tools in clinical practice.CONCLUSION In summary,our study has demonstrated that ^(13)C-UBT has been found to outperform the ^(14)C-UBT,making it the preferred diagnostic approach.Additionally,our results emphasize the significance of carefully considering urea dosage,assessment timing,and measurement techniques for both tests to enhance diagnostic precision.Nevertheless,it is crucial for researchers and clinicians to evaluate the strengths and limitations of our findings before implementing them in practice.展开更多
基金National Natural Science Foundation of China(12102410)Fund of National Key Laboratory of Shock Wave and Detonation Physics(JCKYS2022212005)。
文摘The lattice parameter,measured with sufficient accuracy,can be utilized to evaluate the quality of single crystals and to determine the equation of state for materials.We propose an iterative method for obtaining more precise lattice parameters using the interaction points for the pseudo-Kossel pattern obtained from laser-induced X-ray diffraction(XRD).This method has been validated by the analysis of an XRD experiment conducted on iron single crystals.Furthermore,the method was used to calculate the compression ratio and rotated angle of an LiF sample under high pressure loading.This technique provides a robust tool for in-situ characterization of structural changes in single crystals under extreme conditions.It has significant implications for studying the equation of state and phase transitions.
基金Supported by the National Natural Science Foundation of China(Grant Nos.52375448,52275440).
文摘The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool design and plays an essential role in determining the machining accuracy of the workpiece.Researchers have extensively studied methods to model,extract,optimize,and measure the geometric errors that affect the geometric accuracy of machine tools.This paper provides a comprehensive review of the state-of-the-art approaches and an overview of the latest research progress associated with geometric accuracy design in CNC machine tools.This paper explores the interrelated aspects of CNC machine tool accuracy design:modeling,analysis and optimization.Accuracy analysis,which includes geometric error modeling and sensitivity analysis,determines a machine tool’s output accuracy through its volumetric error model,given the known accuracy of its individual components.Conversely,accuracy allocation designs the accuracy of the machine tool components according to given output accuracy requirements to achieve optimization between the objectives of manufacturing cost,quality,reliability,and environmental impact.In addition to discussing design factors and evaluation methods,this paper outlines methods for verifying the accuracy of design results,aiming to provide a practical basis for ensuring that the designed accuracy is achieved.Finally,the challenges and future research directions in geometric accuracy design are highlighted.
文摘BACKGROUND The accuracy of blind intra-articular injections in the shoulder is rather low.Inaccurate injections tend to lead to poorer treatment outcomes.The“Delaware posterior bone touch technique”has shown higher accuracy in young,slender,healthy volunteers than the classical“Cyriax technique”.AIM To investigate whether the Delaware technique would also be more accurate in older patients with capsulitis.METHODS We analyzed the files of 100 consecutive patients with capsulitis who were treated with an intra-articular injection containing a mixture of triamcinolone,lidocaine,and air.After the injection,the shoulder was moved to determine whether a squishing sound could be produced.The squishing sound was interpreted as an accurate injection.The scores with the new Delaware technique were compared against those with the Cyriax technique in a previous study.RESULTS Squishing was heard after 87%of the injections.This was 13%(10%points)more than the 77%in the previous study(P=0.004).CONCLUSION The Delaware technique was significantly more accurate than the Cyriax technique also in middle aged patients with capsulitis.We hypothesize that the difference is caused by a lower risk that a part of the opening of the needle is still outside the capsule.
基金supported by the National Key Research and Development Program of China(2023YFC3008605)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021002)the Seismological Research Foundation for Youths of Guangdong Earthquake Agency(Open Funding Project of Key Laboratory of Earthquake Monitoring and Disaster Mitigation Technology,China Earthquake Administration)(GDDZY202309)。
文摘The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and statistical analysis methods.The travel-time corrections for the Pg phase of 72 stations range between-0.25 s and 0.14 s,while the corrections for the Sg phase range between 0.27 s and 0.35 s,and those for the Pn phase are between-0.86 s and 0.07 s.The spatial distribution of travel-time corrections for Pg,Sg,and Pn phases of 72 stations correlates well with the geological structure in this region.This indicates that the travel-time corrections for Pg and Sg phases are mainly caused by the discrepancy between the actual crustal velocity structure beneath the stations and the 1D South China travel-time model.These corrections empirically compensate for systematic travel-time errors arising from such discrepancies.The primary factor contributing to the travel-time corrections for the Pn phase is the Moho undulations or tilt.These corrections are intended to compensate for systematic errors in travel time caused by variations in the actual Moho.By integrating the obtained travel-time corrections into the HYPO-SAT location algorithm,test results showed an obvious improvement in location accuracy and origin time precision for explosion events.The variation of horizontal distance between repeating earthquake pairs has also improved,with 86%of the repeating earthquake pair spacing being more accurately estimated after correction.This suggests the crucial significance of travel-time correction in earthquake location,and the consideration of travel-time correction exerts a notable impact on enhancing earthquake location accuracy.
文摘Objective:To analyze the significance of high-frequency ultrasound in differentiating benign and malignant breast micronodules.Methods:Eighty-five patients with breast micronodules admitted for diagnosis between October 2022 and October 2024 were selected for high-frequency ultrasound diagnosis.The diagnostic efficacy of high-frequency ultrasound was evaluated by comparing it with the results of surgical pathology.Results:High-frequency ultrasound detected 50 benign nodules,primarily breast fibroadenomas,and 35 malignant nodules,mainly breast ductal carcinoma in situ.Based on surgical pathology results,the diagnostic accuracy of high-frequency ultrasound was 96.47%,specificity was 97.96%,and sensitivity was 94.44%.In high-frequency ultrasound diagnosis,the proportion of grade III and IV blood flow in malignant nodules was higher than that in benign nodules,while the proportion of regular shape and clear margins was lower.The proportion of microcalcifications and posterior echo attenuation was higher in malignant nodules,and the resistance index(RI)and peak blood flow velocity were lower than those in benign nodules(P<0.05).Conclusion:High-frequency ultrasound can effectively differentiate benign and malignant breast micronodules,determine specific nodule types,and exhibits high diagnostic accuracy and sensitivity.Additionally,benign and malignant nodules can be differentiated based on the grading of blood flow signals,sonographic features,and blood flow velocity,providing reasonable guidance for subsequent treatment plans.
文摘Objective:To explore nursing measures for elderly patients with chronic obstructive pulmonary disease(COPD)and analyze the effect of continuous nursing pathways on improving the accuracy of aerosol use.Methods:From April 2023 to April 2024,76 elderly COPD patients admitted to our hospital were randomly selected for nursing research.They were divided into two groups using a computer double-blind method,with 38 patients in each group.The control group received routine nursing,while the observation group applied the continuous nursing pathway.The nursing effects of the two groups were investigated and compared,including(1)aerosol accuracy;(2)cardiopulmonary function;(3)subjective well-being and self-care ability;(4)quality of life;and(5)nursing satisfaction.Results:Compared with the control group,the observation group had a significantly higher accuracy rate of aerosol use(P<0.05).Before nursing,there were no significant differences in cardiopulmonary function indicators,MUNSH scores,and ESCA scores between the two groups(P>0.05).After nursing,the patient's cardiopulmonary function improved significantly,and their subjective well-being and self-care ability increased.The observation group was significantly better than the control group in all the above indicators(P<0.05).The quality of life scores of the observation group were significantly higher than those of the control group(P<0.05).Conclusion:In the nursing of elderly patients with chronic obstructive pulmonary disease,the application of the continuous nursing pathway can effectively improve the accuracy of aerosol use and improve patients'cardiopulmonary function.
基金supported in part by the National Key Research and Development Program of China(2021YFA0715503)。
文摘This brief presents a cryogenic voltage reference circuit designed to operate effectively across a wide temperature range from 30 to 300 K.A key feature of the proposed design is utilizing a current subtraction technique for temperature compensation of the reference current,avoiding the deployment of bipolar transistors to reduce area and power consumption.Implemented with a 0.18-μm CMOS process,the circuit achieves a temperature coefficient(TC)of 67.5 ppm/K,which was not achieved in previous works.The design can also attain a power supply rejection(PSR)of 58 d B at 10 k Hz.Meanwhile,the average reference voltage is 1.2 V within a 1.6%3σ-accuracy spread.Additionally,the design is characterized by a minimal power dissipation of 1μW at 30 K and a compact chip area of 0.0035 mm~2.
基金financial supported by National Natural Science Foundation of China (42104010, 42174097, 41974093, and 41774088)the Fundamental Research Funds for the Central Universities
文摘Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. However, high-altitude and high-latitude lakes undergo seasonal freezing and melting, affecting satellite altimetry accuracy. This paper evaluates the accuracy of lake level height observations by the CryoSat-2, which uses synthetic aperture radar(SAR) across seasons. First, we used lake boundary based on optical remote sensing data to extract the footprints of CryoSat-2 that fall on Namco and Zhari Namco.After elevation conversion and anomaly identification, we obtained the time series of lake levels. These data were compared and verified against lake levels from in-situ measurements to assess the accuracy of CryoSat-2. The results show that CryoSat-2 can monitor lake level height with an accuracy of about 10-13 cm. The correlation coefficient between CryoSat-2 observations and in-situ measurements over Namco is 0.80(p < 0.01), with a Root Mean Square Error(RMSE) of 13 cm. For Zhari Namco, the correlation coefficient is 0.91, with an RMSE of 10 cm, indicating a better match. At the seasonal scale, the seasonal correlation coefficients between CryoSat-2 and in-situ measurement in Namco are 0.47(spring),0.79(summer), and 0.91(fall) with no observations available for winter. The lower correlation in spring may be due to incomplete ice melting. For Zhari Namco, the seasonal correlation coefficients are 0.89(spring), 0.93(summer), 0.89(fall), and 0.87(winter). The results show that CryoSat-2 accuracy is higher in summer and fall, while slightly lower in spring and winter, indicating that ice formation affects accuracy. Even during winter, the altimetry results do not significantly exceed the in-situ lake water level observations.
基金Supported by the National Natural Science Foundation of China(U1831133)Open Fund of Key Laboratory of Space Active Optoelectronics Technology,Chinese Academy of Sciences(2021ZDKF4)。
文摘Position-sensitive detector(PSD)is widely used in precision measurement fields such as flatness detection,auto-collimator systems,and degrees of freedom testing.However,due to factors such as uneven surface resistance and differences in electrode structures,the nonlinearity of PSD becomes increasingly severe as the photosensitive surface moves from the center toward the edges of the four electrodes.To address this issue,a PSD nonlinearity correction algorithm is proposed.The algorithm utilizes the particle swarm optimization(PSO)algorithm to determine the optimal weights and thresholds,providing better initial parameters for the back propagation(BP)neural network.The BP neural network then iterates continuously until the error conditions are met,completing the correction process.Furthermore,a PSD nonlinearity correction system was developed,and the influence of different spot sizes on PSD positioning accuracy was simulated based on the current equation under the Gaussian spot model.This validated the robustness of the correction algorithm under varying spot sizes.The results demonstrate that the overall optimized error is reduced by 84.51%,and for spot sizes smaller than 1 mm,the error reduction exceeds 93.89%.This method not only meets the measurement accuracy requirements but also extends the measurement range of PSD.
文摘This review comprehensively analyzes advancements in artificial intelligence,particularly machine learning and deep learning,in medical imaging,focusing on their transformative role in enhancing diagnostic accuracy.Our in-depth analysis of 138 selected studies reveals that artificial intelligence(AI)algorithms frequently achieve diagnostic performance comparable to,and often surpassing,that of human experts,excelling in complex pattern recognition.Key findings include earlier detection of conditions like skin cancer and diabetic retinopathy,alongside radiologist-level performance for pneumonia detection on chest X-rays.These technologies profoundly transform imaging by significantly improving processes in classification,segmentation,and sequential analysis across diversemodalities such as X-rays,Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and ultrasound.Specific advancements with Convolutional Neural Networks,Recurrent Neural Networks,and ensemble learning techniques have facilitated more precise diagnosis,prediction,and therapy planning.Notably,Generative Adversarial Networks address limited data through augmentation,while transfer learning efficiently adapts models for scarce labeled datasets,and Reinforcement Learning shows promise in optimizing treatment protocols,collectively advancing patient care.Methodologically,a systematic review(2015-2024)used Scopus and Web of Science databases,yielding 7982 initial records.Of these,1189 underwent bibliometric analysis using the R package‘Bibliometrix’,and 138 were comprehensively reviewed for specific findings.Research output surged over the decade,led by Institute of Electrical and Electronics Engineers(IEEE)Access(19.1%).China dominates publication volume(36.1%),while the United States of America(USA)leads total citations(5605),and Hong Kong exhibits the highest average(55.60).Challenges include rigorous validation,regulatory clarity,and fostering clinician trust.This study highlights significant emerging trends and crucial future research directions for successful AI implementation in healthcare.
基金supporteded by Natural Science Foundation of Shanghai(Grant No.22ZR1463900)State Key Laboratory of Mechanical System and Vibration(Grant No.MSV202318)the Fundamental Research Funds for the Central Universities(Grant No.22120220649).
文摘Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring their functional integrity and performance.To achieve sustainable manufacturing in FDM,it is necessary to optimize the print quality and time efficiency concurrently.However,owing to the complex interactions of printing parameters,achieving a balanced optimization of both remains challenging.This study examines four key factors affecting dimensional accuracy and print time:printing speed,layer thickness,nozzle temperature,and bed temperature.Fifty parameter sets were generated using enhanced Latin hypercube sampling.A whale optimization algorithm(WOA)-enhanced support vector regression(SVR)model was developed to predict dimen-sional errors and print time effectively,with non-dominated sorting genetic algorithm Ⅲ(NSGA-Ⅲ)utilized for multi-objective optimization.The technique for Order Preference by Similarity to Ideal Solution(TOPSIS)was applied to select a balanced solution from the Pareto front.In experimental validation,the parts printed using the optimized parameters exhibited excellent dimensional accuracy and printing efficiency.This study comprehensively considered optimizing the printing time and size to meet quality requirements while achieving higher printing efficiency and aiding in the realization of sustainable manufacturing in the field of AM.In addition,the printing of a specific prosthetic component was used as a case study,highlighting the high demands on both dimensional precision and printing efficiency.The optimized process parameters required significantly less printing time,while satisfying the dimensional accuracy requirements.This study provides valuable insights for achieving sustainable AM using FDM.
基金funded by the Second Tibetan Plateau Scientific Expedition and Research,Ministry of Science and Technology(Project No.2019QZKK0902)the West Light Foundation of the Chinese Academy of Sciences(Project No.E3R2120)the Research Programme of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Project No.IMHE-ZDRW-01).
文摘Machine learning-based Debris Flow Susceptibility Mapping(DFSM)has emerged as an effective approach for assessing debris flow likelihood,yet its application faces three critical challenges:insufficient reliability of training samples caused by biased negative sampling,opaque decision-making mechanisms in models,and subjective susceptibility mapping methods that lack quantitative evaluation criteria.This study focuses on the Yalong River basin.By integrating high-resolution remote sensing interpretation and field surveys,we established a refined sample database that includes 1,736 debris flow gullies.To address spatial bias in traditional random negative sampling,we developed a semi-supervised optimization strategy based on iterative confidence screening.Comparative experiments with four treebased models(XGBoost,CatBoost,LGBM,and Random Forest)reveal that the optimized sampling strategy improved overall model performance by 8%-12%,with XGBoost achieving the highest accuracy(AUC=0.882)and RF performing the lowest(AUC=0.820).SHAP-based global-local interpretability analysis(applicable to all tree models)identifies elevation and short-duration rainfall as dominant controlling factors.Furthermore,among the tested tree-based models,XGBoost optimized with semisupervised sampling demonstrates the highest reliability in debris flow susceptibility mapping(DFSM),achieving a comprehensive accuracy of 83.64%due to its optimal generalization-stability equilibrium.
基金supported by National Natural Science Foundation of China(Grant No.12102219)National Key Research and Development Program of China(Grant No.2022YFB4601900)。
文摘The low accuracy of wire arc additive manufacturing(WAAM)is one of the main factors limiting its development,and is detrimental to the mechanical properties of WAAM structures.This study primarily investigated the effects of wire-feeding directions and positions of the molten pool on the quality and accuracy of unsupported WAAM.First,the three-dimensional(3D)morphology and volume of unsupported rods manufactured with different wirefeeding directions were quantitatively evaluated using a 3D scanning method.The effects of the wire-feeding direction and arc length on the volume and standard deviation of the unsupported rods are then discussed in detail.Finally,the influence of the wire-feeding direction on the quality and accuracy of unsupported WAAM is discussed and revealed by combining the temperature gradients,surface tension,and contact angles.The research revealed that feeding a wire into the high-temperature zone of the molten pool could reduce material spatter and achieve higher precision.The volume of the sample fed into the high-temperature zone was 120%of that fed into the low-temperature zone.This reduced not only the material waste but also the standard deviation of the diameter of the same group of samples.This research is of great significance and value for high-quality unsupported WAAM.
基金supported by the Key R&D Program of Zhejiang Province(Nos.2023C01166 and 2024SJCZX0046)the Zhejiang Provincial Natural Science Foundation of China(Nos.LDT23E05013E05 and LD24E050009)the Natural Science Foundation of Ningbo(No.2021J150),China.
文摘Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.
文摘Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagnostic imaging,such as resolution,radiation efficiency,and real-time processing.Methods:This work used a mixed-methods strategy,including controlled phantom experiments,retrospective multi-center clinical data analysis,and quantum-classical hybrid processing to assess enhancements in resolution,dosage efficiency,and diagnostic confidence.Statistical validation included analysis of variance(ANOVA)and receiver-operating characteristic curve analysis,juxtaposing quantum-enhanced methodologies with conventional and deep learning approaches.Results:Quantum entanglement reconstruction enhanced magnetic resonance imaging spatial resolution by 33.2%(P<0.01),quantum noise suppression facilitated computed tomography scans with a 60%reduction in radiation,and quantum beamforming improved ultrasound contrast by 27%while preserving real-time processing(<2 ms delay).Inter-reader variability(12%in Diagnostic Confidence Scores)showed that systematic training is needed,even if the performance was better.The research presented(1)a reusable clinical quantum imaging framework,(2)enhanced hardware processes(field-programmable gate array/graphics processing unit acceleration),and(3)cost-benefit analyses demonstrating a 22-month return on investment breakeven point.Conclusion:Quantum-enhanced imaging has a lot of promise for use in medicine,especially in neurology and cancer.Future research should focus on multi-modal integration(e.g.,positron emission tomography–magnetic resonance imaging),cloud-based quantum simulations for enhanced accessibility,and extensive trials to confirm long-term diagnostic accuracy.This breakthrough gives healthcare systems a technology roadmap and a reason to spend money on quantum-enhanced diagnostics.
基金supported by the Science and Technology Planning Program of Xinjiang,China(2022E01047)the Natural Science Basic Research Program of Shaanxi(2025JC-YBQN-404)+2 种基金the 2025 Shaanxi Special Research Project of Philosophy and Social Sciences(2025QN0573)the Scientific Research Program Funded by Education Department of Shaanxi Provincial Government(23JK0625)the National Natural Science Foundation of China(42030612)。
文摘Given that Xinjiang Uygur Autonomous Region of China possesses exceptionally abundant solar radiation resources that can be harnessed to develop clean energy,accurately characterizing their spatiotemporal distribution is crucial.This study investigated the applicability of the Clouds and the Earth's Radiant Energy System(CERES)Single Scanner Footprint TOA/Surface Fluxes and Clouds(SSF)product downward surface shortwave radiation dataset(DSSRCER)under clear-sky conditions in Xinjiang.By integrating multi-source data and utilizing techniques like multivariate fitting and model simulation,we established a two-layer aerosol model and developed a clear-sky downward surface shortwave radiation(DSSR)retrieval model specific to Xinjiang using the Santa Barbara Discrete Atmospheric Radiative Transfer(SBDART)model.We further explored the spatiotemporal distribution characteristics of DSSR under clear-sky conditions in Xinjiang from 2017 to 2019 based on the localized DSSR retrieval model.Our findings revealed a significant discrepancy in DSSRCER under clear-sky conditions at the Xiaotang station in Xinjiang.By comparing,screening,and correcting core input parameters while incorporating the two-layer aerosol model,we achieved a more accurate SBDART simulated DSSR(DSSRSBD)compared to DSSRCER.The annual mean DSSR exhibited a distinct distribution pattern with high values in mountainous regions such as the Altay Mountains,Kunlun Mountains,and Tianshan Mountains and significantly lower values in adjacent lowland areas,including the Tarim River Basin and Junggar Basin.In the four typical administrative regions in northern Xinjiang,the annual mean DSSR(ranging from 551.60 to 586.09 W/m^(2))was lower than that in the five typical administrative regions in southern Xinjiang(ranging from 522.10 to 623.62 W/m^(2)).These spatial variations stem from a complex interplay of factors,including latitude,altitude,solar altitude angle,and sunshine duration.The variations in seasonal average DSSR aligned closely with variations in the solar altitude angle,with summer(774.76 W/m^(2))exhibiting the highest values,followed by spring(684.86 W/m^(2)),autumn(544.76 W/m^(2)),and winter(422.74 W/m^(2)).The monthly average DSSR showed a unimodal distribution,peaking in June(792.94 W/m^(2))and reaching its lowest level in December(363.06 W/m^(2)).Overall,our study findings enhance the current understanding of the spatiotemporal distribution characteristics of DSSR in Xinjiang and provide certain references for the management of clean energy development in this region.
基金supported by National Key Research and Development Program of China(Grant No.2023YFB4605301)the National Natural Science Foundation of China(Grant No.52130506)。
文摘The z-axis-inclined 3D printing process using short carbon fiber-reinforced thermoplastic composites offers the potential for the support-free fabrication of complex structures and theoretically unlimited extension of printed components.It has emerged as a promising approach for in-orbit manufacturing of high-performance thermoplastic composite truss structures.However,extreme conditions of the space environment,such as high vacuum and fluctuating high-low temperatures,significantly alter the heat-transfer behavior during the printing process,often resulting in dimensional inaccuracies and degraded mechanical performance.Existing process optimization strategies fail to account for the coupled effects of vacuum and thermal extremes,limiting their applicability in guiding process design under varying vacuum temperature conditions.To address this gap,this study establishes a truss3D printing experimental platform with in situ temperature-monitoring capability under ground-simulated space conditions.It systematically investigates the effects of printing speed and structural geometry on the pre-bonding surface temperature and forming quality of truss structures in high-low temperature vacuum environments.This study reveals the mechanism by which processing and structural parameters affect the component performance through their influence on the pre-bonding surface temperature and dimensional accuracy.The experimental results show that under high-temperature vacuum conditions,the pre-bonding surface temperature is relatively high,resulting in good interfacial bonding.However,increasing the printing speed reduces the forming accuracy and leads to a decline in mechanical performance.In contrast,under low-temperature vacuum conditions,where the pre-bonding surface temperatures are lower,increasing the printing speed within a specific range effectively increases the surface temperature and bonding quality,thereby improving mechanical properties.Additionally,owing to frequent path transitions,the diagonal-strut truss exhibits a lower forming accuracy and pre-bonding surface temperature than the infilling truss,resulting in inferior mechanical performance in high-low temperature vacuum environments.
基金Supported by Health and Family Planning Project of Sichuan Province,No.17PJ069Tibet Autonomous Region Science and Technology Program,No.XZ202303ZY0011G.
文摘BACKGROUND The FreeStyle Libre flash glucose monitoring(FGM)system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose.Due to its increased usage in clinics,the number of studies investigating its accuracy has increased.However,its accuracy has not been investigated in highland populations in China.AIM To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes(T2D)who had migrated within 3 mo from highlands to plains.METHODS Overall,68 patients with T2D,selected from those who had recently migrated from highlands to plains(within 3 mo),were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring(CGM)with the FreeStyle Libre FGM system for 14 d.Throughout the study period,fingertip capillary blood glucose was measured daily using the enzyme electrode method(Super GL,China),and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals.Moreover,the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to<5 min.The accuracy of the FGM system was evaluated according to the CGM guidelines.Subsequently,the factors influencing the mean absolute relative difference(MARD)of this system were analyzed by a multiple linear regression method.RESULTS Pearson’s correlation analysis showed that the fingertip and scanned glucose levels were positively correlated(R=0.86,P=0.00).The aggregated MARD of scanned glucose was 14.28±13.40%.Parker's error analysis showed that 99.30%of the data pairs were located in areas A and B.According to the probe wear time of the FreeStyle Libre FGM system,MARD_(1 d) and MARD_(2-14 d) were 16.55%and 14.35%,respectively(t=1.23,P=0.22).Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion(LAGE)was<5.80 mmol/L but negatively correlated with blood glucose when the LAGE was≥5.80 mmol/L.CONCLUSION The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains.This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains.MARD is mainly influenced by glucose levels and fluctuations,and the accuracy of the system is higher when the blood glucose fluctuation is small.In case of higher blood glucose level fluctuations,deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.
基金Supported by Scientific Initiation Scholarship Programme(PIBIC)of the Bahia State Research Support Foundationthe Doctorate Scholarship Program of the Coordination of Improvement of Higher Education Personnel+1 种基金the Scientific Initiation Scholarship Programme(PIBIC)of the National Council for Scientific and Technological Developmentand the CNPq Research Productivity Fellowship.
文摘BACKGROUND Helicobacter pylori(H.pylori)infection has been well-established as a significant risk factor for several gastrointestinal disorders.The urea breath test(UBT)has emerged as a leading non-invasive method for detecting H.pylori.Despite numerous studies confirming its substantial accuracy,the reliability of UBT results is often compromised by inherent limitations.These findings underscore the need for a rigorous statistical synthesis to clarify and reconcile the diagnostic accuracy of the UBT for the diagnosis of H.pylori infection.AIM To determine and compare the diagnostic accuracy of 13C-UBT and 14C-UBT for H.pylori infection in adult patients with dyspepsia.METHODS We conducted an independent search of the PubMed/MEDLINE,EMBASE,and Cochrane Central databases until April 2022.Our search included diagnostic accuracy studies that evaluated at least one of the index tests(^(13)C-UBT or ^(14)C-UBT)against a reference standard.We used the QUADAS-2 tool to assess the methodo-logical quality of the studies.We utilized the bivariate random-effects model to calculate sensitivity,specificity,positive and negative test likelihood ratios(LR+and LR-),as well as the diagnostic odds ratio(DOR),and their 95%confidence intervals.We conducted subgroup analyses based on urea dosing,time after urea administration,and assessment technique.To investigate a possible threshold effect,we conducted Spearman correlation analysis,and we generated summary receiver operating characteristic(SROC)curves to assess heterogeneity.Finally,we visually inspected a funnel plot and used Egger’s test to evaluate publication bias.endorsing both as reliable diagnostic tools in clinical practice.CONCLUSION In summary,our study has demonstrated that ^(13)C-UBT has been found to outperform the ^(14)C-UBT,making it the preferred diagnostic approach.Additionally,our results emphasize the significance of carefully considering urea dosage,assessment timing,and measurement techniques for both tests to enhance diagnostic precision.Nevertheless,it is crucial for researchers and clinicians to evaluate the strengths and limitations of our findings before implementing them in practice.
