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
This article focuses on exploiting superconvergence to obtain more accurate multi-resolution analysis. Specifcally, we concentrate on enhancing the quality of passing of information between scales by implementing the ...This article focuses on exploiting superconvergence to obtain more accurate multi-resolution analysis. Specifcally, we concentrate on enhancing the quality of passing of information between scales by implementing the Smoothness-Increasing Accuracy-Conserving (SIAC) fltering combined with multi-wavelets. This allows for a more accurate approximation when passing information between meshes of diferent resolutions. Although this article presents the details of the SIAC flter using the standard discontinuous Galerkin method, these techniques are easily extendable to other types of data.展开更多
The accuracy of power system measurements directly affects the safe and stable operation of power grids. This study explores the application prospects of quantum sensing technology in power system measurements. The re...The accuracy of power system measurements directly affects the safe and stable operation of power grids. This study explores the application prospects of quantum sensing technology in power system measurements. The research first analyzes the limitations of traditional measurement techniques, such as electromagnetic interference sensitivity and measurement accuracy bottlenecks. It then introduces the basic principles of quantum sensing, including concepts like quantum entanglement and superposition states. Through theoretical analysis and numerical simulations, the study assesses the potential advantages of quantum sensors in current, voltage, and magnetic field measurements. Results show that quantum magnetometers offer significant improvements in accuracy and interference resistance for current measurements. The study also discusses the application of quantum optical technology in high-voltage measurements, demonstrating its unique advantages in improving measurement dynamic range. However, quantum sensing technology still faces challenges in practical applications, such as technological maturity and cost. To address these issues, the research proposes a phased implementation strategy and industry-academia collaboration model. Finally, the study envisions future directions combining quantum sensing with artificial intelligence. This research provides a theoretical foundation for innovative upgrades in power system measurement technology.展开更多
Introduction:Traditional dietary surveys are timeconsuming,and manual recording may lead to omissions.Improvement during data collection is essential to enhance accuracy of nutritional surveys.In recent years,large la...Introduction:Traditional dietary surveys are timeconsuming,and manual recording may lead to omissions.Improvement during data collection is essential to enhance accuracy of nutritional surveys.In recent years,large language models(LLMs)have been rapidly developed,which can provide text-processing functions and assist investigators in conducting dietary surveys.Methods:Thirty-eight participants from 15 families in the Huangpu and Jiading districts of Shanghai were selected.A standardized 24-hour dietary recall protocol was conducted using an intelligent recording pen that simultaneously captured audio data.These recordings were then transcribed into text.After preprocessing,we used GLM-4 for prompt engineering and chain-of-thought for collaborative reasoning,output structured data,and analyzed its integrity and consistency.Model performance was evaluated using precision and F1 scores.Results:The overall integrity rate of the LLMbased structured data reached 92.5%,and the overall consistency rate compared with manual recording was 86%.The LLM can accurately and completely recognize the names of ingredients and dining and production locations during the transcription.The LLM achieved 94%precision and an F1 score of 89.7%for the full dataset.Conclusion:LLM-based text recognition and structured data extraction can serve as effective auxiliary tools to improve efficiency and accuracy in traditional dietary surveys.With the rapid advancement of artificial intelligence,more accurate and efficient auxiliary tools can be developed for more precise and efficient data collection in nutrition research.展开更多
Gyroscopes are crucial components of inertial navigation systems,with ongoing development emphasizing miniaturization and enhanced accuracy.The recent advances in chip-scale optical gyroscopes utilizing integrated opt...Gyroscopes are crucial components of inertial navigation systems,with ongoing development emphasizing miniaturization and enhanced accuracy.The recent advances in chip-scale optical gyroscopes utilizing integrated optics have attracted considerable attention,demonstrating significant advantages in achieving tactical-grade accuracy.In this paper,a new,to our knowledge,integrated optical gyroscope scheme based on the multi-mode co-detection technology is proposed,which takes the high-Q microcavity as its core sensitive element and uses the multi-mode characteristics of the microcavity to achieve the measurement of rotational angular velocity.This detection scheme breaks the tradition of optical gyroscopes based on a single mode within the sensitive ring to detect the angular rotation rate,which not only greatly simplifies the optical and electrical system of the optical gyroscope,but also has a higher detection accuracy.The gyroscope based on this detection scheme has successfully detected the Earth's rotation on a 9.2 mm diameter microcavity with a bias instability as low as 1 deg/h,which is the best performance among the chip-scale integrated optical gyroscopes known to us.展开更多
Chinese technology company iFLYTEK Co.Ltd.launched an intelligent speech recognition system designed for humanoid robots this June.While traditional robotic performance suffers in noisy environments,this AI solution a...Chinese technology company iFLYTEK Co.Ltd.launched an intelligent speech recognition system designed for humanoid robots this June.While traditional robotic performance suffers in noisy environments,this AI solution achieves 92-percent environmental sensing accuracy-overcoming a key industry challenge.It enhances humanoid computers’ability to manage complex logistics and warehouse tasks.展开更多
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This work was motivated by discussions with Dr.Venke Sankaran(Edwards Air Force Research Lab,USA)and was performed while visiting the Applied Mathematics group at HeinrichHeine University,Düsseldorf,Germany.Research supported by the Air Force Ofce of Scientifc Research(AFOSR)Computational Mathematics Program(Program Manager:Dr.Fariba Fahroo)under Grant numbers FA9550-18-1-0486 and FA9550-19-S-0003.
文摘This article focuses on exploiting superconvergence to obtain more accurate multi-resolution analysis. Specifcally, we concentrate on enhancing the quality of passing of information between scales by implementing the Smoothness-Increasing Accuracy-Conserving (SIAC) fltering combined with multi-wavelets. This allows for a more accurate approximation when passing information between meshes of diferent resolutions. Although this article presents the details of the SIAC flter using the standard discontinuous Galerkin method, these techniques are easily extendable to other types of data.
文摘The accuracy of power system measurements directly affects the safe and stable operation of power grids. This study explores the application prospects of quantum sensing technology in power system measurements. The research first analyzes the limitations of traditional measurement techniques, such as electromagnetic interference sensitivity and measurement accuracy bottlenecks. It then introduces the basic principles of quantum sensing, including concepts like quantum entanglement and superposition states. Through theoretical analysis and numerical simulations, the study assesses the potential advantages of quantum sensors in current, voltage, and magnetic field measurements. Results show that quantum magnetometers offer significant improvements in accuracy and interference resistance for current measurements. The study also discusses the application of quantum optical technology in high-voltage measurements, demonstrating its unique advantages in improving measurement dynamic range. However, quantum sensing technology still faces challenges in practical applications, such as technological maturity and cost. To address these issues, the research proposes a phased implementation strategy and industry-academia collaboration model. Finally, the study envisions future directions combining quantum sensing with artificial intelligence. This research provides a theoretical foundation for innovative upgrades in power system measurement technology.
基金Supported by the Ministry of Finance of the People’s Republic of China from 2022 to 2024(grant number 102393220020070000016).
文摘Introduction:Traditional dietary surveys are timeconsuming,and manual recording may lead to omissions.Improvement during data collection is essential to enhance accuracy of nutritional surveys.In recent years,large language models(LLMs)have been rapidly developed,which can provide text-processing functions and assist investigators in conducting dietary surveys.Methods:Thirty-eight participants from 15 families in the Huangpu and Jiading districts of Shanghai were selected.A standardized 24-hour dietary recall protocol was conducted using an intelligent recording pen that simultaneously captured audio data.These recordings were then transcribed into text.After preprocessing,we used GLM-4 for prompt engineering and chain-of-thought for collaborative reasoning,output structured data,and analyzed its integrity and consistency.Model performance was evaluated using precision and F1 scores.Results:The overall integrity rate of the LLMbased structured data reached 92.5%,and the overall consistency rate compared with manual recording was 86%.The LLM can accurately and completely recognize the names of ingredients and dining and production locations during the transcription.The LLM achieved 94%precision and an F1 score of 89.7%for the full dataset.Conclusion:LLM-based text recognition and structured data extraction can serve as effective auxiliary tools to improve efficiency and accuracy in traditional dietary surveys.With the rapid advancement of artificial intelligence,more accurate and efficient auxiliary tools can be developed for more precise and efficient data collection in nutrition research.
基金National Key Research and Development Program of China(2023YFB3906402)。
文摘Gyroscopes are crucial components of inertial navigation systems,with ongoing development emphasizing miniaturization and enhanced accuracy.The recent advances in chip-scale optical gyroscopes utilizing integrated optics have attracted considerable attention,demonstrating significant advantages in achieving tactical-grade accuracy.In this paper,a new,to our knowledge,integrated optical gyroscope scheme based on the multi-mode co-detection technology is proposed,which takes the high-Q microcavity as its core sensitive element and uses the multi-mode characteristics of the microcavity to achieve the measurement of rotational angular velocity.This detection scheme breaks the tradition of optical gyroscopes based on a single mode within the sensitive ring to detect the angular rotation rate,which not only greatly simplifies the optical and electrical system of the optical gyroscope,but also has a higher detection accuracy.The gyroscope based on this detection scheme has successfully detected the Earth's rotation on a 9.2 mm diameter microcavity with a bias instability as low as 1 deg/h,which is the best performance among the chip-scale integrated optical gyroscopes known to us.
文摘Chinese technology company iFLYTEK Co.Ltd.launched an intelligent speech recognition system designed for humanoid robots this June.While traditional robotic performance suffers in noisy environments,this AI solution achieves 92-percent environmental sensing accuracy-overcoming a key industry challenge.It enhances humanoid computers’ability to manage complex logistics and warehouse tasks.
