BACKGROUND Axial and coronal reformations have been a widely used image post-processing protocol for the ordinary multidetector computed tomography(MDCT)examination of patients with small bowel obstruction(SBO) or oth...BACKGROUND Axial and coronal reformations have been a widely used image post-processing protocol for the ordinary multidetector computed tomography(MDCT)examination of patients with small bowel obstruction(SBO) or other abdominal diseases. The diagnostic accuracy of MDCT for assessing SBO is expected to be further improved through the use of multiple post-processing techniques.AIM To systemically evaluate the diagnostic accuracy and efficiency of an optimized protocol using multiple post-processing techniques for MDCT assessment of SBO and secondary bowel ischemia.METHODS This retrospective cross-sectional study included 106 patients with clinically suspected SBO. Two readers applied three protocols to image post-processing and interpretation of patients' MDCT volume data. We compared the three protocols based on time spent, number of images, diagnostic self-confidence,agreement, detection rate, and accuracy of detection of SBO and secondary bowel ischemia.RESULTS Protocol 2 resulted in more time spent and number of images than protocols 1 and 3(P < 0.01), but the results of the two readers using the same protocol were not different(P > 0.05). Using protocol 3, both readers added multiple postprocessing techniques at frequencies of 29.2% and 34.9%, respectively, for obstruction cause, and 32.1% and 30.2%, respectively, for secondary bowel ischemia. Protocols 2 and 3 had higher total detection rates of obstruction cause and secondary bowel ischemia than protocol 1(P < 0.01), but no difference was detected between protocols 2 and 3(P > 0.05). The accuracy, sensitivity,specificity, positive predictive value and negative predictive value of protocols 2 and 3 were superior to those of protocol 1 for evaluating obstruction cause and secondary bowel ischemia.CONCLUSION Our optimized protocol of multiple post-processing techniques can both guarantee efficiency and improve diagnostic accuracy of MDCT for assessing SBO and secondary bowel ischemia.展开更多
Objective To assess the diagnostic value of the airway post-processing technique of multi-slice spiral CT(MSCT)in accessory cardiac bronchus(ACB)and to improve the understanding of this disease.Methods The original MS...Objective To assess the diagnostic value of the airway post-processing technique of multi-slice spiral CT(MSCT)in accessory cardiac bronchus(ACB)and to improve the understanding of this disease.Methods The original MSCT axial images and various post-processing reconstructed images of 9 ACB cases were retrospectively analyzed.Airway post-processing techniques,including multi-planar reformation(MPR),minimum intensity projection(MinIP),volume rendering technique(VRT),CT virtual endoscopy(CTVE)and tissue transition projection(TTP),were employed.Three-dimensional recombination images of bronchial trees were obtained and classified according to the Mangiulea classification.Results Among the 9 cases with ACB,there were 6 cases of accessory-lobed type,3 cases of long diverticular type,and no cases of short diverticular type.The lateral axial images,MPR,MinIP,VRT,CTVE,and TTP all clearly displayed ACB.Among the 6 cases of accessorylobed type,there were 5 cases with accessory lobe dysplasia and one case with pneumonia in an accessory lobe.One case was complicated with accessory lobe emphysema.Among the 3 cases with long diverticular type ACB,one had pneumonia.Among the 9 cases,there was 1 case with old tuberculous focus,1 case with pulmonary fibrous focus,1 case with pleural thickening and adhesion,and 1 case with tracheal diverticulum.Conclusion The airway post-processing technique of MSCT can not only clarify the diagnosis,origin and classification of ACB,but also measure the opening diameter,length and distance to the tracheal carina of ACB.It guides clinical treatment and tracheoscopy,etc,and can be used as the preferred examination method for ACB.展开更多
Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating th...Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.展开更多
With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comp...With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.展开更多
Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience...Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.展开更多
THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of...THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of the Yuan(1206-1368),Ming(1368-1644),and Qing(1616-1911)dynasties,and is still highly regarded to this day.展开更多
The laser shock processing implemented by a laser-induced high-pressure plasma which propagates into the sample as a shockwave is innovatively applied as a post-processing technique on HfO_(2)/SiO_(2) multilayer coati...The laser shock processing implemented by a laser-induced high-pressure plasma which propagates into the sample as a shockwave is innovatively applied as a post-processing technique on HfO_(2)/SiO_(2) multilayer coatings for the first time.The pure mechanical post-processing has provided evidence of a considerable promotion effect of the laser-induced damage threshold,which increased by a factor of about 4.6 with appropriate processing parameters.The promotion mechanism is confirmed to be the comprehensive modification of the intrinsic defects and the mechanical properties,which made the applicability of this novel post-processing technique on various types of coatings possible.Based on experiments,an interaction equation for the plasma pressure is established,which clarifies the existence of the critical pressure and provides a theoretical basis for selecting optimal processing parameters.In addition to the further clarification of the underlying damage mechanism,the laser shock post-processing provides a promising technique to realize the comprehensive and effective improvement of the laser-induced damage resistance of coatings.展开更多
The travel time data collection method is used to assist the congestion management. The use of traditional sensors (e.g. inductive loops, AVI sensors) or more recent Bluetooth sensors installed on major roads for coll...The travel time data collection method is used to assist the congestion management. The use of traditional sensors (e.g. inductive loops, AVI sensors) or more recent Bluetooth sensors installed on major roads for collecting data is not sufficient because of their limited coverage and expensive costs for installation and maintenance. Application of the Global Positioning Systems (GPS) in travel time and delay data collections is proven to be efficient in terms of accuracy, level of details for the data and required data collection of man-power. While data collection automation is improved by the GPS technique, human errors can easily find their way through the post-processing phase, and therefore data post-processing remains a challenge especially in case of big projects with high amount of data. This paper introduces a stand-alone post-processing tool called GPS Calculator, which provides an easy-to-use environment to carry out data post-processing. This is a Visual Basic application that processes the data files obtained in the field and integrates them into Geographic Information Systems (GIS) for analysis and representation. The results show that this tool obtains similar results to the currently used data post-processing method, reduces the post-processing effort, and also eliminates the need for the second person during the data collection.展开更多
Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.T...Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.展开更多
Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scannin...Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.展开更多
BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of th...BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.展开更多
A polarization-sensitive and flexible photodetector was fabricated through the precise alignment of perovskite nanowires(NWs)using a brush coating technique.The alignment of the NWs was meticulously examined,consideri...A polarization-sensitive and flexible photodetector was fabricated through the precise alignment of perovskite nanowires(NWs)using a brush coating technique.The alignment of the NWs was meticulously examined,considering various chemical properties of the solvent,such as boiling point,viscosity,and surface tension.Notably,when the NWs were brush-coated with toluene dispersion,the NWs were aligned in higher order than those processed from octane dispersion.The degree of alignment was correlated with the photodetector property.Especially,the well-aligned NW photodetector exhibited a two-fold disparity in current response contingent on the polarization direction.Furthermore,even after enduring 500 bending cycles,the device retained 80%of its photodetector performance.This approach underscores the potential of solution-processed flexible photodetectors for advanced optical applications under dynamic operating conditions.展开更多
This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,includin...This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.展开更多
With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed...With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.展开更多
Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we...Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we perform systematic studies on the elastic properties of the Cu–6wt% Ag alloy wire, which is a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques, i.e., resonant ultrasound spectroscopy(RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu–6wt% Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this opportunity to test the availability of our newly-built ultrasound pulse-echo facility at the Wuhan National High Magnetic Field Center(WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu–6wt% Ag alloy wire remains excellent without anomalous softening under extreme conditions,e.g., in ultra-high magnetic field up to 50 T and nitrogen or helium cryogenic liquids.展开更多
Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of suc...Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.展开更多
One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific object...One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.展开更多
1.Introduction Various geological phenomena on the surface and in the interior of the Earth,as well as their associated physical and chemical pro-cesses,are closely correlated with the action of in situ rock stress[1-...1.Introduction Various geological phenomena on the surface and in the interior of the Earth,as well as their associated physical and chemical pro-cesses,are closely correlated with the action of in situ rock stress[1-5].Understanding the rock stress state at great depths is not only an indispensable foundation for solving scientific problems associated with geology,geophysics,and geodynamics-such as plate-driving mechanisms,the earth’s energy equilibrium,earth-quake mechanisms,and tectonic activities-but also a necessary prerequisite for the evaluation,exploitation,and disposal of deep energy and resources,such as coal and metal minerals.Due to the complexity and uncertainty of the origin of in situ rock stress,it is a difficult quantity to evaluate,in comparison with other rock properties.Currently,reliable information on the stress state in a region can only be determined through field stress measurement.Therefore,a variety of stress measurement techniques have been developed and applied worldwide to provide information on crus-tal contemporary stress at specific depth ranges[6].展开更多
Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We dis...Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.展开更多
Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradi...Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.展开更多
基金the National Natural Science Foundation of China,No.81671943
文摘BACKGROUND Axial and coronal reformations have been a widely used image post-processing protocol for the ordinary multidetector computed tomography(MDCT)examination of patients with small bowel obstruction(SBO) or other abdominal diseases. The diagnostic accuracy of MDCT for assessing SBO is expected to be further improved through the use of multiple post-processing techniques.AIM To systemically evaluate the diagnostic accuracy and efficiency of an optimized protocol using multiple post-processing techniques for MDCT assessment of SBO and secondary bowel ischemia.METHODS This retrospective cross-sectional study included 106 patients with clinically suspected SBO. Two readers applied three protocols to image post-processing and interpretation of patients' MDCT volume data. We compared the three protocols based on time spent, number of images, diagnostic self-confidence,agreement, detection rate, and accuracy of detection of SBO and secondary bowel ischemia.RESULTS Protocol 2 resulted in more time spent and number of images than protocols 1 and 3(P < 0.01), but the results of the two readers using the same protocol were not different(P > 0.05). Using protocol 3, both readers added multiple postprocessing techniques at frequencies of 29.2% and 34.9%, respectively, for obstruction cause, and 32.1% and 30.2%, respectively, for secondary bowel ischemia. Protocols 2 and 3 had higher total detection rates of obstruction cause and secondary bowel ischemia than protocol 1(P < 0.01), but no difference was detected between protocols 2 and 3(P > 0.05). The accuracy, sensitivity,specificity, positive predictive value and negative predictive value of protocols 2 and 3 were superior to those of protocol 1 for evaluating obstruction cause and secondary bowel ischemia.CONCLUSION Our optimized protocol of multiple post-processing techniques can both guarantee efficiency and improve diagnostic accuracy of MDCT for assessing SBO and secondary bowel ischemia.
文摘Objective To assess the diagnostic value of the airway post-processing technique of multi-slice spiral CT(MSCT)in accessory cardiac bronchus(ACB)and to improve the understanding of this disease.Methods The original MSCT axial images and various post-processing reconstructed images of 9 ACB cases were retrospectively analyzed.Airway post-processing techniques,including multi-planar reformation(MPR),minimum intensity projection(MinIP),volume rendering technique(VRT),CT virtual endoscopy(CTVE)and tissue transition projection(TTP),were employed.Three-dimensional recombination images of bronchial trees were obtained and classified according to the Mangiulea classification.Results Among the 9 cases with ACB,there were 6 cases of accessory-lobed type,3 cases of long diverticular type,and no cases of short diverticular type.The lateral axial images,MPR,MinIP,VRT,CTVE,and TTP all clearly displayed ACB.Among the 6 cases of accessorylobed type,there were 5 cases with accessory lobe dysplasia and one case with pneumonia in an accessory lobe.One case was complicated with accessory lobe emphysema.Among the 3 cases with long diverticular type ACB,one had pneumonia.Among the 9 cases,there was 1 case with old tuberculous focus,1 case with pulmonary fibrous focus,1 case with pleural thickening and adhesion,and 1 case with tracheal diverticulum.Conclusion The airway post-processing technique of MSCT can not only clarify the diagnosis,origin and classification of ACB,but also measure the opening diameter,length and distance to the tracheal carina of ACB.It guides clinical treatment and tracheoscopy,etc,and can be used as the preferred examination method for ACB.
基金supported by Healthy China initiative of Traditional Chinese Medicine(No.889042).
文摘Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2023-00235509Development of security monitoring technology based network behavior against encrypted cyber threats in ICT convergence environment).
文摘With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.
基金supported by the National Natural Science Foundation of China,No.31760290,82160688the Key Development Areas Project of Ganzhou Science and Technology,No.2022B-SF9554(all to XL)。
文摘Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.
文摘THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of the Yuan(1206-1368),Ming(1368-1644),and Qing(1616-1911)dynasties,and is still highly regarded to this day.
基金the National Natural Science Foundation of China(NSFC)(No.11704285)the Natural Science Foundation of Zhejiang Province(No.LY20E050027)the Wenzhou Science and Technology Plan Projects(No.G20170012).
文摘The laser shock processing implemented by a laser-induced high-pressure plasma which propagates into the sample as a shockwave is innovatively applied as a post-processing technique on HfO_(2)/SiO_(2) multilayer coatings for the first time.The pure mechanical post-processing has provided evidence of a considerable promotion effect of the laser-induced damage threshold,which increased by a factor of about 4.6 with appropriate processing parameters.The promotion mechanism is confirmed to be the comprehensive modification of the intrinsic defects and the mechanical properties,which made the applicability of this novel post-processing technique on various types of coatings possible.Based on experiments,an interaction equation for the plasma pressure is established,which clarifies the existence of the critical pressure and provides a theoretical basis for selecting optimal processing parameters.In addition to the further clarification of the underlying damage mechanism,the laser shock post-processing provides a promising technique to realize the comprehensive and effective improvement of the laser-induced damage resistance of coatings.
文摘The travel time data collection method is used to assist the congestion management. The use of traditional sensors (e.g. inductive loops, AVI sensors) or more recent Bluetooth sensors installed on major roads for collecting data is not sufficient because of their limited coverage and expensive costs for installation and maintenance. Application of the Global Positioning Systems (GPS) in travel time and delay data collections is proven to be efficient in terms of accuracy, level of details for the data and required data collection of man-power. While data collection automation is improved by the GPS technique, human errors can easily find their way through the post-processing phase, and therefore data post-processing remains a challenge especially in case of big projects with high amount of data. This paper introduces a stand-alone post-processing tool called GPS Calculator, which provides an easy-to-use environment to carry out data post-processing. This is a Visual Basic application that processes the data files obtained in the field and integrates them into Geographic Information Systems (GIS) for analysis and representation. The results show that this tool obtains similar results to the currently used data post-processing method, reduces the post-processing effort, and also eliminates the need for the second person during the data collection.
基金funded by the project of Guangdong Provincial Basic and Applied Basic Research Fund Committee(2022A1515240073)the Pearl River Talent Recruitment Program(2019CX01G338),Guangdong Province.
文摘Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.
基金supported by the National Natural Science Foundation of China(Nos.12341501 and 11905074)。
文摘Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.
文摘BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.
基金supported by a Commercialization Promotion Agency for R&D Outcomes(COMPA)Grant funded by the Korean Government(Ministry of Science and ICT)(No.RS-2023-00304743)the National Research Foundation of Korea(NRF)Grant funded by the Korean Government(MSIT)(No.2022M3J7A1066428)"Regional Innovation Strategy(RIS)"through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(No.2023RIS-008).
文摘A polarization-sensitive and flexible photodetector was fabricated through the precise alignment of perovskite nanowires(NWs)using a brush coating technique.The alignment of the NWs was meticulously examined,considering various chemical properties of the solvent,such as boiling point,viscosity,and surface tension.Notably,when the NWs were brush-coated with toluene dispersion,the NWs were aligned in higher order than those processed from octane dispersion.The degree of alignment was correlated with the photodetector property.Especially,the well-aligned NW photodetector exhibited a two-fold disparity in current response contingent on the polarization direction.Furthermore,even after enduring 500 bending cycles,the device retained 80%of its photodetector performance.This approach underscores the potential of solution-processed flexible photodetectors for advanced optical applications under dynamic operating conditions.
文摘This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.
基金supported by the National Fund Cultivation Project from China People’s Police University(Grant Number:JJPY202402)National Natural Science Foundation of China(Grant Number:62172165).
文摘With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.
基金Project supported by the National Key R&D Program of China (Grant Nos. 2022YFA1602602 and 2023YFA1609600)the National Natural Science Foundation of China (Grant No. U23A20580)+3 种基金the open research fund of Songshan Lake Materials Laboratory (Grant No. 2022SLABFN27)Beijing National Laboratory for Condensed Matter Physics (Grant No. 2024BNLCMPKF004)Guangdong Basic and Applied Basic Research Foundation (Grant No. 2022B1515120020)the interdisciplinary program of Wuhan National High Magnetic Field Center at Huazhong University of Science and Technology (Grant No. WHMFC202132)。
文摘Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we perform systematic studies on the elastic properties of the Cu–6wt% Ag alloy wire, which is a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques, i.e., resonant ultrasound spectroscopy(RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu–6wt% Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this opportunity to test the availability of our newly-built ultrasound pulse-echo facility at the Wuhan National High Magnetic Field Center(WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu–6wt% Ag alloy wire remains excellent without anomalous softening under extreme conditions,e.g., in ultra-high magnetic field up to 50 T and nitrogen or helium cryogenic liquids.
文摘Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.
基金Supported by the National Natural Science Foundation of China(42474239,41204128)China National Space Administration(Pre-research project on Civil Aerospace Technologies No.D010301)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA17010303)。
文摘One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.
基金financially supported by the National Key Research and Development Program of China(2022YFC3004601)the National Natural Science Foundation of China(52204084)the Science,Technology and Innovation Project of Xiongan New Area(2023XAGG0061).
文摘1.Introduction Various geological phenomena on the surface and in the interior of the Earth,as well as their associated physical and chemical pro-cesses,are closely correlated with the action of in situ rock stress[1-5].Understanding the rock stress state at great depths is not only an indispensable foundation for solving scientific problems associated with geology,geophysics,and geodynamics-such as plate-driving mechanisms,the earth’s energy equilibrium,earth-quake mechanisms,and tectonic activities-but also a necessary prerequisite for the evaluation,exploitation,and disposal of deep energy and resources,such as coal and metal minerals.Due to the complexity and uncertainty of the origin of in situ rock stress,it is a difficult quantity to evaluate,in comparison with other rock properties.Currently,reliable information on the stress state in a region can only be determined through field stress measurement.Therefore,a variety of stress measurement techniques have been developed and applied worldwide to provide information on crus-tal contemporary stress at specific depth ranges[6].
文摘Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.
基金the Young Investigator Group“Artificial Intelligence for Probabilistic Weather Forecasting”funded by the Vector Stiftungfunding from the Federal Ministry of Education and Research(BMBF)and the Baden-Württemberg Ministry of Science as part of the Excellence Strategy of the German Federal and State Governments。
文摘Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.
