The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces ...The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.展开更多
In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance.Central t...In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance.Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel,addressing a crucial gap in the integration of maintenance personnel dispatching and station selection.Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness.The core of our methodology is the NSGA Ⅲ+Dispatch,an advanced adaptation of the Non-Dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ),meticulously designed for the selection of maintenance stations and effective operator dispatching.This method integrates a comprehensive coding process,crossover operator,and mutation operator to efficiently manage multiple objectives.Rigorous empirical testing,including a detailed analysis from a taiwan region electronic equipment manufacturer,validated the effectiveness of our approach across various scenarios of machine failure frequencies and operator configurations.The findings reveal that the proposed model significantly outperforms current practices by reducing response times by up to 23%in low-frequency and 28.23%in high-frequency machine failure scenarios,leading to notable improvements in efficiency and cost reduction.Additionally,it demonstrates significant improvements in oper-ational efficiency,particularly in selective high-frequency failure contexts,while ensuring substantial manpower cost savings without compromising on operational effectiveness.This research significantly advances maintenance strategies in production environments,providing the manufacturing industry with practical,optimized solutions for diverse machine malfunction situations.Furthermore,the methodologies and principles developed in this study have potential applications in various other sectors,including healthcare,transportation,and energy,where maintenance efficiency and resource optimization are equally critical.展开更多
This paper introduces part of the content in the association standard,T/CAAM0002–2020 Nomenclature and Location of Acupuncture Points for Laboratory Animals Part 2:Rat.This standard was released by the China Associat...This paper introduces part of the content in the association standard,T/CAAM0002–2020 Nomenclature and Location of Acupuncture Points for Laboratory Animals Part 2:Rat.This standard was released by the China Association of Acupuncture and Moxibustion on May 15,2020,implemented on October 31,2020,and published by Standards Press of China.The standard was drafted by the Institute of Acupuncture and Moxibustion,China Academy of Chinese Medical Sciences,and the Nanjing University of Chinese Medicine.Principal draftsmen:Xiang-hong JING and Xing-bang HUA.Participating draftsmen:Wan-Zhu BAI,Bin XU,Dong-sheng XU,Yi GUO,Tie-ming MA,Xin-jun WANG,and Sheng-feng LU.展开更多
Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parame...Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parameters.The monitoring platform collected data on the internal environment of the solar greenhouse for one year,including temperature,humidity,and light intensity.Additionally,meteorological data,comprising outdoor temperature,outdoor humidity,and outdoor light intensity,was gathered during the same time frame.The characteristics and interrelationships among these parameters were investigated by a thorough analysis.The analysis revealed that environmental parameters in solar greenhouses displayed characteristics such as temporal variability,non-linearity,and periodicity.These parameters exhibited complex coupling relationships.Notably,these characteristics and coupling relationships exhibited pronounced seasonal variations.The multi-parameter multi-step prediction model for solar greenhouse(MPMS-SGH)was introduced,aiming to accurately predict three key greenhouse environmental parameters,and the model had certain seasonal adaptability.MPMS-SGH was structured with multiple layers,including an input layer,a preprocessing layer,a feature extraction layer,and a prediction layer.The input layer was used to generate the original sequence matrix,which included indoor temperature,indoor humidity,indoor light intensity,as well as outdoor temperature and outdoor light intensity.Then the preprocessing layer normalized,decomposed,and positionally encoded the original sequence matrix.In the feature extraction layer,the time attention mechanism and frequency attention mechanism were used to extract features from the trend component and the seasonal component,respectively.Finally,the prediction layer used a multi-layer perceptron to perform multi-step prediction of indoor environmental parameters(i.e.temperature,humidity,and light intensity).The parameter selection experiment evaluated the predictive performance of MPMS-SGH on input and output sequences of different lengths.The results indicated that with a constant output sequence length,the prediction accuracy of MPMS-SGH was firstly increased and then decreased with the increase of input sequence length.Specifically,when the input sequence length was 100,MPMS-SGH had the highest prediction accuracy,with RMSE of 0.22℃,0.28%,and 250lx for temperature,humidity,and light intensity,respectively.When the length of the input sequence remained constant,as the length of the output sequence increased,the accuracy of the model in predicting the three environmental parameters was continuously decreased.When the length of the output sequence exceeded 45,the prediction accuracy of MPMS-SGH was significantly decreased.In order to achieve the best balance between model size and performance,the input sequence length of MPMS-SGH was set to be 100,while the output sequence length was set to be 35.To assess MPMS-SGH’s performance,comparative experiments with four prediction models were conducted:SVR,STL-SVR,LSTM,and STL-LSTM.The results demonstrated that MPMS-SGH surpassed all other models,achieving RMSE of 0.15℃for temperature,0.38%for humidity,and 260lx for light intensity.Additionally,sequence decomposition can contribute to enhancing MPMS-SGH’s prediction performance.To further evaluate MPMS-SGH’s capabilities,its prediction accuracy was tested across different seasons for greenhouse environmental parameters.MPMS-SGH had the highest accuracy in predicting indoor temperature and the lowest accuracy in predicting humidity.And the accuracy of MPMS-SGH in predicting environmental parameters of the solar greenhouse fluctuated with seasons.MPMS-SGH had the highest accuracy in predicting the temperature inside the greenhouse on sunny days in spring(R^(2)=0.91),the highest accuracy in predicting the humidity inside the greenhouse on sunny days in winter(R^(2)=0.83),and the highest accuracy in predicting the light intensity inside the greenhouse on cloudy days in autumm(R^(2)=0.89).MPMS-SGH had the lowest accuracy in predicting three environmental parameters in a sunny summer greenhouse.展开更多
Unmanned aerial vehicle(UAV)swarm network consisting of a collection of micro UAVs can be used for many applications.It is well established that packet routing is a fundamental problem to achieve UAV collaboration.How...Unmanned aerial vehicle(UAV)swarm network consisting of a collection of micro UAVs can be used for many applications.It is well established that packet routing is a fundamental problem to achieve UAV collaboration.However,the highly dynamic nature of UAVs,frequently changing network topologies and security issues,poses significant challenges to packet forwarding in UAV networks.The existing topology-based routing protocols are not well suited in UAV network due to their high controlling overhead or excessive end-to-end delay.Geographic routing is regarded as a promising solution,as it only requires local information.In order to enhance the accuracy and security of geographic routing in highly dynamic UAV network,in this paper,we propose a new predictive geographic(PGeo)routing strategy with location verification.First,a detection mechanism is adopted to recognize malicious UAVs falsifying their location.Then,an accurate average service time of a packet in the medium access control(MAC)layer is derived to assist location prediction.The proposed delay model can provide a theoretical basis for future work,and our simulation results reveal that PGeo outstrips the existing geographic routing protocols in terms of packet delivery ratio in the presence of location spoofing behavior.展开更多
This paper introduces part of the content in the association standard,T/CAAM0002–2020 Nomenclature and Location of Acupuncture Points for Laboratory Animals Part 3:Mouse.This standard was released by the China Associ...This paper introduces part of the content in the association standard,T/CAAM0002–2020 Nomenclature and Location of Acupuncture Points for Laboratory Animals Part 3:Mouse.This standard was released by the China Association of Acupuncture and Moxibustion on May 15,2020,implemented on October 31,2020,and published by Standards Press of China.The standard was drafted by the Institute of Acupuncture and Moxibustion,China Academy of Chinese Medical Sciences,and the Nanjing University of Chinese Medicine.Principal draftsmen:Xiang-hong JING and Xing-bang HUA.Participating draftsmen:Wan-zhu BAI,Bin XU,Dong-sheng XU,Yi GUO,Tie-ming MA,Xin-jun WANG,and Sheng-feng LU.展开更多
The advantage distillation(AD)technology has been proven to effectively improve the secret key rate and the communication distance of quantum key distribution(QKD).The mode-pairing quantum key distribution(MP-QKD)prot...The advantage distillation(AD)technology has been proven to effectively improve the secret key rate and the communication distance of quantum key distribution(QKD).The mode-pairing quantum key distribution(MP-QKD)protocol can overcome a fundamental physical limit,known as the Pirandola-Laurenza-Ottaviani-Banchi bound,without requiring global phase-locking.In this work,we propose a method based on multi-step AD to further enhance the performance of MP-QKD.The simulation results show that,compared to one-step AD,multi-step AD achieves better performance in long-distance scenarios and can tolerate a higher quantum bit error rate.Specifically,when the difference between the communication distances from Alice and Bob to Charlie is 25 km,50 km and 75 km,and the corresponding transmission distance exceeds 523 km,512 km and 496 km,respectively,the secret key rate achieved by multi-step AD surpasses that of one-step AD.Our findings indicate that the proposed method can effectively promote the application of MP-QKD in scenarios with high loss and high error rate.展开更多
A novel method is developed by utilizing the fractional frequency based multirange rulers to precisely position the passive inter-modulation(PIM)sources within radio frequency(RF)cables.The proposed method employs a s...A novel method is developed by utilizing the fractional frequency based multirange rulers to precisely position the passive inter-modulation(PIM)sources within radio frequency(RF)cables.The proposed method employs a set of fractional frequencies to create multiple measuring rulers with different metric ranges to determine the values of the tens,ones,tenths,and hundredths digits of the distance.Among these rulers,the one with the lowest frequency determines the maximum metric range,while the one with the highest frequency decides the highest achievable accuracy of the position system.For all rulers,the metric accuracy is uniquely determined by the phase accuracy of the detected PIM signals.With the all-phase Fourier transform method,the phases of the PIM signals at all fractional frequencies maintain almost the same accuracy,approximately 1°(about 1/360 wavelength in the positioning accuracy)at the signal-to-noise ratio(SNR)of 10 d B.Numerical simulations verify the effectiveness of the proposed method,improving the positioning accuracy of the cable PIM up to a millimeter level with the highest fractional frequency operating at 200 MHz.展开更多
Accurate and rapid determination of source locations is of great significance for surface microseismic monitoring.Traditional methods,such as diffraction stacking,are time-consuming and challenging for real-time monit...Accurate and rapid determination of source locations is of great significance for surface microseismic monitoring.Traditional methods,such as diffraction stacking,are time-consuming and challenging for real-time monitoring.In this study,we propose an approach to locate microseismic events using a deep learning algorithm with surface data.A fully convolutional network is designed to predict source locations.The input data is the waveform of a microseismic event,and the output consists of three 1D Gaussian distributions representing the probability distribution of the source location in the x,y,and z dimensions.The theoretical dataset is generated to train the model,and several data augmentation methods are applied to reduce discrepancies between the theoretical and field data.After applying the trained model to field data,the results demonstrate that our method is fast and achieves comparable location accuracy to the traditional diffraction stacking location method,making it promising for real-time microseismic monitoring.展开更多
Despite advances in surgery,chemotherapy,and radiotherapy,the treatment of colorectal cancer(CRC)requires more personalized approaches based on tumor biology and molecular profiling.While some relevant mutations have ...Despite advances in surgery,chemotherapy,and radiotherapy,the treatment of colorectal cancer(CRC)requires more personalized approaches based on tumor biology and molecular profiling.While some relevant mutations have been associated with differential response to immunotherapy,such as RAS and BRAF mutations limiting response to anti-epithelial growth factor receptor drugs or microsatellite instability predisposing susceptibility to immune checkpoint inhibitors,the role of inflammation in dictating tumor progression and treatment response is still under investigation.Several inflammatory biomarkers have been identified to guide patient prognosis.These include the neutrophil-lymphocyte ratio,Glasgow prognostic score(GPS)and its modified version,lymphocyte-Creactive protein ratio,and platelet-lymphocyte ratio.However,these markers are not yet included in the standard clinical management of patients with CRC,and further research is needed to evaluate their efficacy in different patient populations.A recent study by Wang et al,published in the World Journal of Gastroenterology,sheds light on the prognostic significance of pan-immune-inflammation value(PIV)in CRC,particularly concerning primary tumor location.Specifically,the authors found that a high PIV was strongly correlated with worse disease-free survival in patients with left-sided colon cancer,whereas no such association was observed in patients with right-sided colon cancer.Integrating tumor location into the prognostic assessment of CRC may improve our ability to more accurately identify high-risk patients and develop personalized treatment plans that are more likely to improve patient outcomes.展开更多
Data centers operate as physical digital infrastructure for generating,storing,computing,transmitting,and utilizing massive data and information,constituting the backbone of the flourishing digital economy across the ...Data centers operate as physical digital infrastructure for generating,storing,computing,transmitting,and utilizing massive data and information,constituting the backbone of the flourishing digital economy across the world.Given the lack of a consistent analysis for studying the locational factors of data centers and empirical deficiencies in longitudinal investigations on spatial dynamics of heterogeneous data centers,this paper develops a comprehensive analytical framework to examine the dynamic geographies and locational factors of techno-environmentally heterogeneous data centers across Chinese cities in the period of 2006–2021.First,we develop a“supply-demand-environment trinity”analytical framework as well as an accompanying evaluation indicator system with Chinese characteristics.Second,the dynamic geographies of data centers in Chinese cities over the last decades are characterized as spatial polarization in economically leading urban agglomerations alongside persistent interregional gaps across eastern,central,and western regions.Data centers present dual spatial expansion trajectories featuring outward radiation from eastern core urban agglomerations to adjacent peripheries and leapfrog diffusion to strategic central and western digital infrastructural hubs.Third,it is empirically verified that data center construction in Chinese cities over the last decades has been jointly influenced by supply-,demand-,and environment-side locational factors,echoing the efficacy of the trinity analytical framework.Overall,our findings demonstrate the temporal variance,contextual contingency,and attribute-based differentiation of locational factors underlying techno-environmentally heterogeneous data centers in Chinese cities.展开更多
Microseismic (MS) source location plays an important role in MS monitoring. This paper proposes a MS source location method based on particle swarm optimization (PSO) and multi-sensor arrays, where a free weight joint...Microseismic (MS) source location plays an important role in MS monitoring. This paper proposes a MS source location method based on particle swarm optimization (PSO) and multi-sensor arrays, where a free weight joints the P-wave first arrival data. This method adaptively adjusts the preference for “superior” arrays and leverages “inferior” arrays to escape local optima, thereby improving the location accuracy. The effectiveness and stability of this method were validated through synthetic tests, pencil-lead break (PLB) experiments, and mining engineering applications. Specifically, for synthetic tests with 1 μs Gaussian noise and 100 μs large noise in rock samples, the location error of the multi-sensor arrays jointed location method is only 0.30 cm, which improves location accuracy by 97.51% compared to that using a single sensor array. The average location error of PLB events on three surfaces of a rock sample is reduced by 48.95%, 26.40%, and 55.84%, respectively. For mine blast event tests, the average location error of the dual sensor arrays jointed method is 62.74 m, 54.32% and 14.29% lower than that using only sensor arrays 1 and 2, respectively. In summary, the proposed multi-sensor arrays jointed location method demonstrates good noise resistance, stability, and accuracy, providing a compelling new solution for MS location in relevant mining scenarios.展开更多
The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availabilit...The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availability of fi xed seismic monitoring stations nearby. To address these challenges, a dense observation array was developed within the study area to monitor and analyze microseismic activity during hydraulic fracturing. Microseismic events generated by hydraulic fracturing typically exhibit low amplitude and signal-to-noise ratio, rendering traditional manual analysis methods impractical. To overcome these limitations, an innovative artifi cial intelligence method combining picking-association-location (PAL) and match-expand- shift-stack (MESS) techniques (PALM) has been utilized for automated seismic detection. Numerous factors influence the accuracy of microseismic detection and localization. To evaluate these factors, the effects of various velocity structure models, instrument types, and station distributions on seismic location were analyzed and compared. The results indicate that the PALM method significantly mitigates the influence of velocity structure models on seismic location accuracy. Additionally, the use of broadband seismic instruments and a uniform station distribution enhances the precision of seismic location results. Furthermore, by integrating data from diff erent types of observation instruments, a comprehensive seismic catalog for the study area was established. These fi ndings not only enhance seismic location accuracy but also provide valuable guidance for optimizing regional seismic monitoring network design and improving seismic risk assessment.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
Seismic source locations can characterize the spatial and temporal distributions of seismic sources,and can provide important basic data for earthquake disaster monitoring,fault activity characterization,and fracture ...Seismic source locations can characterize the spatial and temporal distributions of seismic sources,and can provide important basic data for earthquake disaster monitoring,fault activity characterization,and fracture growth interpretation.Waveform stacking-based location methods invert the source locations by focusing the source energy with multichannel waveforms,and these methods exhibit a high level of automation and noise-resistance.Taking the cross-correlation stacking(CCS)method as an example,this work attempts to study the influential factors of waveform stacking-based methods,and introduces a comprehensive performance evaluation scheme based on multiple parameters and indicators.The waveform data are from field monitoring of induced microseismicity in the Changning region(southern Sichuan Basin of China).Synthetic and field data tests reveal the impacts of three categories of factors on waveform stacking-based location:velocity model,monitoring array,and waveform complexity.The location performance is evaluated and further improved in terms of the source imaging resolution and location error.Denser array monitoring contributes to better constraining source depth and location reliability,but the combined impact of multiple factors,such as velocity model uncertainty and multiple seismic phases,increases the complexity of locating field microseismic events.Finally,the aspects of location uncertainty,phase detection,and artificial intelligencebased location are discussed.展开更多
In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow e...In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow equation.The velocity and pressure are computed simultaneously.The accuracy of velocity is improved one order.The concentration equation is solved by using mixed finite element,multi-step difference and upwind approximation.A multi-step method is used to approximate time derivative for improving the accuracy.The upwind approximation and an expanded mixed finite element are adopted to solve the convection and diffusion,respectively.The composite method could compute the diffusion flux and its gradient.It possibly becomes an eficient tool for solving convection-dominated diffusion problems.Firstly,the conservation of mass holds.Secondly,the multi-step method has high accuracy.Thirdly,the upwind approximation could avoid numerical dispersion.Using numerical analysis of a priori estimates and special techniques of differential equations,we give an error estimates for a positive definite problem.Numerical experiments illustrate its computational efficiency and feasibility of application.展开更多
Effective isolation between the cement sheath and the sandstone is crucial for the development and production of oil and gas wells in sandstone formations.In this study,a cement-sandstone composite(CSC)was prepared,an...Effective isolation between the cement sheath and the sandstone is crucial for the development and production of oil and gas wells in sandstone formations.In this study,a cement-sandstone composite(CSC)was prepared,and based onμ-CT three-dimensional reconstruction imaging and finite element analysis(FEA)techniques,the stress distribution and potential failure mechanism at the cement-sandstone bonding interface under axial loading were analyzed.The key findings are as follows:(1)stress concentrations are highly likely to form at the gap between the cement and sandstone interface and around interfacial voids,with Von Mises stress reaching critical levels of 18.0-20.0 MPa at these locations,significantly exceeding the stress magnitudes in well-bonded regions;(2)the phenomenon of local stress concentration driven by interfacial defects can be identified as the main basis for predicting damage location in interfacial debonding and continuous shear under axial load;(3)ensuring tight cementation at the cement-sandstone interface and minimizing interfacial voids are paramount for preventing stress-induced failure;(4)the critical Von Mises stress value of 20 MPa at the interface defect can be used as a benchmark for material selection and designed to ensure long-term integrity in oil and gas well applications subjected to similar axial loads.These findings contribute to a more accurate understanding of the failure mechanism of the cement-sandstone interface and to the precise design of material properties,thereby ensuring the long-term integrity of oil and gas well applications subjected to similar axial loads.展开更多
This letter is a commentary on the findings of Huang et al,who emphasize the prognostic value of tumor location in gastric cancer.Analyzing data from 3287 patients using Kaplan-Meier and multivariate Cox models,the au...This letter is a commentary on the findings of Huang et al,who emphasize the prognostic value of tumor location in gastric cancer.Analyzing data from 3287 patients using Kaplan-Meier and multivariate Cox models,the authors found that the tumor location correlated with patient prognosis following surgery.Patients with tumors situated nearer to the stomach’s proximal end were associated with shorter survival periods and poorer outcomes.Notably,gender-based differences in tumor markers,particularly carbohydrate antigen 72-4,further highlight the need for sex-specific influence on the tumor location.Despite increasing recognition of tumor location as a prognostic factor,its role remains unclear in clinical prediction models for various cancers.This letter highlights the potential of incorporating tumor location into artificial intelligence-based prognostic tools to enhance prognostic models.It also outlines a stepwise framework for developing these models,from retrospective training to prospective multicenter validation and clinical implementation.In addition,it addresses the technical,ethical,and interoperability challenges critical to successful real-world prognosis.展开更多
基金the financial support of the National Key R&D Program of China(2021YFC3000701)the China Seismic Experimental Site in Sichuan-Yunnan(CSES-SY)for providing data for this study.
文摘The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.
基金support from the National Science and Technology Council of Taiwan(Contract Nos.112-2221-E-011-115 and 111-2622-E-011019)the support from Intelligent Manufacturing Innovation Center(IMIC),National Taiwan University of Science and Technology(NTUST),Taipei 10607,Taiwan,which is a Featured Areas Research Center in Higher Education Sprout Project of Ministry of Education(MOE),Taiwan(since 2023)was appreciated.
文摘In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance.Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel,addressing a crucial gap in the integration of maintenance personnel dispatching and station selection.Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness.The core of our methodology is the NSGA Ⅲ+Dispatch,an advanced adaptation of the Non-Dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ),meticulously designed for the selection of maintenance stations and effective operator dispatching.This method integrates a comprehensive coding process,crossover operator,and mutation operator to efficiently manage multiple objectives.Rigorous empirical testing,including a detailed analysis from a taiwan region electronic equipment manufacturer,validated the effectiveness of our approach across various scenarios of machine failure frequencies and operator configurations.The findings reveal that the proposed model significantly outperforms current practices by reducing response times by up to 23%in low-frequency and 28.23%in high-frequency machine failure scenarios,leading to notable improvements in efficiency and cost reduction.Additionally,it demonstrates significant improvements in oper-ational efficiency,particularly in selective high-frequency failure contexts,while ensuring substantial manpower cost savings without compromising on operational effectiveness.This research significantly advances maintenance strategies in production environments,providing the manufacturing industry with practical,optimized solutions for diverse machine malfunction situations.Furthermore,the methodologies and principles developed in this study have potential applications in various other sectors,including healthcare,transportation,and energy,where maintenance efficiency and resource optimization are equally critical.
文摘This paper introduces part of the content in the association standard,T/CAAM0002–2020 Nomenclature and Location of Acupuncture Points for Laboratory Animals Part 2:Rat.This standard was released by the China Association of Acupuncture and Moxibustion on May 15,2020,implemented on October 31,2020,and published by Standards Press of China.The standard was drafted by the Institute of Acupuncture and Moxibustion,China Academy of Chinese Medical Sciences,and the Nanjing University of Chinese Medicine.Principal draftsmen:Xiang-hong JING and Xing-bang HUA.Participating draftsmen:Wan-Zhu BAI,Bin XU,Dong-sheng XU,Yi GUO,Tie-ming MA,Xin-jun WANG,and Sheng-feng LU.
文摘Accurately predicting environmental parameters in solar greenhouses is crucial for achieving precise environmental control.In solar greenhouses,temperature,humidity,and light intensity are crucial environmental parameters.The monitoring platform collected data on the internal environment of the solar greenhouse for one year,including temperature,humidity,and light intensity.Additionally,meteorological data,comprising outdoor temperature,outdoor humidity,and outdoor light intensity,was gathered during the same time frame.The characteristics and interrelationships among these parameters were investigated by a thorough analysis.The analysis revealed that environmental parameters in solar greenhouses displayed characteristics such as temporal variability,non-linearity,and periodicity.These parameters exhibited complex coupling relationships.Notably,these characteristics and coupling relationships exhibited pronounced seasonal variations.The multi-parameter multi-step prediction model for solar greenhouse(MPMS-SGH)was introduced,aiming to accurately predict three key greenhouse environmental parameters,and the model had certain seasonal adaptability.MPMS-SGH was structured with multiple layers,including an input layer,a preprocessing layer,a feature extraction layer,and a prediction layer.The input layer was used to generate the original sequence matrix,which included indoor temperature,indoor humidity,indoor light intensity,as well as outdoor temperature and outdoor light intensity.Then the preprocessing layer normalized,decomposed,and positionally encoded the original sequence matrix.In the feature extraction layer,the time attention mechanism and frequency attention mechanism were used to extract features from the trend component and the seasonal component,respectively.Finally,the prediction layer used a multi-layer perceptron to perform multi-step prediction of indoor environmental parameters(i.e.temperature,humidity,and light intensity).The parameter selection experiment evaluated the predictive performance of MPMS-SGH on input and output sequences of different lengths.The results indicated that with a constant output sequence length,the prediction accuracy of MPMS-SGH was firstly increased and then decreased with the increase of input sequence length.Specifically,when the input sequence length was 100,MPMS-SGH had the highest prediction accuracy,with RMSE of 0.22℃,0.28%,and 250lx for temperature,humidity,and light intensity,respectively.When the length of the input sequence remained constant,as the length of the output sequence increased,the accuracy of the model in predicting the three environmental parameters was continuously decreased.When the length of the output sequence exceeded 45,the prediction accuracy of MPMS-SGH was significantly decreased.In order to achieve the best balance between model size and performance,the input sequence length of MPMS-SGH was set to be 100,while the output sequence length was set to be 35.To assess MPMS-SGH’s performance,comparative experiments with four prediction models were conducted:SVR,STL-SVR,LSTM,and STL-LSTM.The results demonstrated that MPMS-SGH surpassed all other models,achieving RMSE of 0.15℃for temperature,0.38%for humidity,and 260lx for light intensity.Additionally,sequence decomposition can contribute to enhancing MPMS-SGH’s prediction performance.To further evaluate MPMS-SGH’s capabilities,its prediction accuracy was tested across different seasons for greenhouse environmental parameters.MPMS-SGH had the highest accuracy in predicting indoor temperature and the lowest accuracy in predicting humidity.And the accuracy of MPMS-SGH in predicting environmental parameters of the solar greenhouse fluctuated with seasons.MPMS-SGH had the highest accuracy in predicting the temperature inside the greenhouse on sunny days in spring(R^(2)=0.91),the highest accuracy in predicting the humidity inside the greenhouse on sunny days in winter(R^(2)=0.83),and the highest accuracy in predicting the light intensity inside the greenhouse on cloudy days in autumm(R^(2)=0.89).MPMS-SGH had the lowest accuracy in predicting three environmental parameters in a sunny summer greenhouse.
基金co-supported by the National Key Research and Development Program of China(No.2024YFE0107900)the National Natural Science Foundation of China(No.62222105)+1 种基金the Natural Science Foundation of Guangdong Province,China(No.2024A1515010235)the 2024 China Unicom Guangdong low-altitude communication and sensing key technology research and digital twin platform research and development project(No.20241890).
文摘Unmanned aerial vehicle(UAV)swarm network consisting of a collection of micro UAVs can be used for many applications.It is well established that packet routing is a fundamental problem to achieve UAV collaboration.However,the highly dynamic nature of UAVs,frequently changing network topologies and security issues,poses significant challenges to packet forwarding in UAV networks.The existing topology-based routing protocols are not well suited in UAV network due to their high controlling overhead or excessive end-to-end delay.Geographic routing is regarded as a promising solution,as it only requires local information.In order to enhance the accuracy and security of geographic routing in highly dynamic UAV network,in this paper,we propose a new predictive geographic(PGeo)routing strategy with location verification.First,a detection mechanism is adopted to recognize malicious UAVs falsifying their location.Then,an accurate average service time of a packet in the medium access control(MAC)layer is derived to assist location prediction.The proposed delay model can provide a theoretical basis for future work,and our simulation results reveal that PGeo outstrips the existing geographic routing protocols in terms of packet delivery ratio in the presence of location spoofing behavior.
文摘This paper introduces part of the content in the association standard,T/CAAM0002–2020 Nomenclature and Location of Acupuncture Points for Laboratory Animals Part 3:Mouse.This standard was released by the China Association of Acupuncture and Moxibustion on May 15,2020,implemented on October 31,2020,and published by Standards Press of China.The standard was drafted by the Institute of Acupuncture and Moxibustion,China Academy of Chinese Medical Sciences,and the Nanjing University of Chinese Medicine.Principal draftsmen:Xiang-hong JING and Xing-bang HUA.Participating draftsmen:Wan-zhu BAI,Bin XU,Dong-sheng XU,Yi GUO,Tie-ming MA,Xin-jun WANG,and Sheng-feng LU.
基金supported by the National Natural Science Foundation of China(Grant Nos.62171144and 62031024)Guangxi Science Foundation(Grant Nos.2025GXNSFAA069137 and GXR-1BGQ2424005)Innovation Project of Guangxi Graduate Education(Grant No.YCBZ2025064)。
文摘The advantage distillation(AD)technology has been proven to effectively improve the secret key rate and the communication distance of quantum key distribution(QKD).The mode-pairing quantum key distribution(MP-QKD)protocol can overcome a fundamental physical limit,known as the Pirandola-Laurenza-Ottaviani-Banchi bound,without requiring global phase-locking.In this work,we propose a method based on multi-step AD to further enhance the performance of MP-QKD.The simulation results show that,compared to one-step AD,multi-step AD achieves better performance in long-distance scenarios and can tolerate a higher quantum bit error rate.Specifically,when the difference between the communication distances from Alice and Bob to Charlie is 25 km,50 km and 75 km,and the corresponding transmission distance exceeds 523 km,512 km and 496 km,respectively,the secret key rate achieved by multi-step AD surpasses that of one-step AD.Our findings indicate that the proposed method can effectively promote the application of MP-QKD in scenarios with high loss and high error rate.
文摘A novel method is developed by utilizing the fractional frequency based multirange rulers to precisely position the passive inter-modulation(PIM)sources within radio frequency(RF)cables.The proposed method employs a set of fractional frequencies to create multiple measuring rulers with different metric ranges to determine the values of the tens,ones,tenths,and hundredths digits of the distance.Among these rulers,the one with the lowest frequency determines the maximum metric range,while the one with the highest frequency decides the highest achievable accuracy of the position system.For all rulers,the metric accuracy is uniquely determined by the phase accuracy of the detected PIM signals.With the all-phase Fourier transform method,the phases of the PIM signals at all fractional frequencies maintain almost the same accuracy,approximately 1°(about 1/360 wavelength in the positioning accuracy)at the signal-to-noise ratio(SNR)of 10 d B.Numerical simulations verify the effectiveness of the proposed method,improving the positioning accuracy of the cable PIM up to a millimeter level with the highest fractional frequency operating at 200 MHz.
基金supported by National Natural Science Foundation of China Grant(No.42004040,42474092,U2239204,and 42304145)Natural Science Foundation of Jiangxi Province Grant(20242BAB25190 and 20232BAB213077).
文摘Accurate and rapid determination of source locations is of great significance for surface microseismic monitoring.Traditional methods,such as diffraction stacking,are time-consuming and challenging for real-time monitoring.In this study,we propose an approach to locate microseismic events using a deep learning algorithm with surface data.A fully convolutional network is designed to predict source locations.The input data is the waveform of a microseismic event,and the output consists of three 1D Gaussian distributions representing the probability distribution of the source location in the x,y,and z dimensions.The theoretical dataset is generated to train the model,and several data augmentation methods are applied to reduce discrepancies between the theoretical and field data.After applying the trained model to field data,the results demonstrate that our method is fast and achieves comparable location accuracy to the traditional diffraction stacking location method,making it promising for real-time microseismic monitoring.
文摘Despite advances in surgery,chemotherapy,and radiotherapy,the treatment of colorectal cancer(CRC)requires more personalized approaches based on tumor biology and molecular profiling.While some relevant mutations have been associated with differential response to immunotherapy,such as RAS and BRAF mutations limiting response to anti-epithelial growth factor receptor drugs or microsatellite instability predisposing susceptibility to immune checkpoint inhibitors,the role of inflammation in dictating tumor progression and treatment response is still under investigation.Several inflammatory biomarkers have been identified to guide patient prognosis.These include the neutrophil-lymphocyte ratio,Glasgow prognostic score(GPS)and its modified version,lymphocyte-Creactive protein ratio,and platelet-lymphocyte ratio.However,these markers are not yet included in the standard clinical management of patients with CRC,and further research is needed to evaluate their efficacy in different patient populations.A recent study by Wang et al,published in the World Journal of Gastroenterology,sheds light on the prognostic significance of pan-immune-inflammation value(PIV)in CRC,particularly concerning primary tumor location.Specifically,the authors found that a high PIV was strongly correlated with worse disease-free survival in patients with left-sided colon cancer,whereas no such association was observed in patients with right-sided colon cancer.Integrating tumor location into the prognostic assessment of CRC may improve our ability to more accurately identify high-risk patients and develop personalized treatment plans that are more likely to improve patient outcomes.
基金Major Program of National Social Science Foundation of China,No.21&ZD107。
文摘Data centers operate as physical digital infrastructure for generating,storing,computing,transmitting,and utilizing massive data and information,constituting the backbone of the flourishing digital economy across the world.Given the lack of a consistent analysis for studying the locational factors of data centers and empirical deficiencies in longitudinal investigations on spatial dynamics of heterogeneous data centers,this paper develops a comprehensive analytical framework to examine the dynamic geographies and locational factors of techno-environmentally heterogeneous data centers across Chinese cities in the period of 2006–2021.First,we develop a“supply-demand-environment trinity”analytical framework as well as an accompanying evaluation indicator system with Chinese characteristics.Second,the dynamic geographies of data centers in Chinese cities over the last decades are characterized as spatial polarization in economically leading urban agglomerations alongside persistent interregional gaps across eastern,central,and western regions.Data centers present dual spatial expansion trajectories featuring outward radiation from eastern core urban agglomerations to adjacent peripheries and leapfrog diffusion to strategic central and western digital infrastructural hubs.Third,it is empirically verified that data center construction in Chinese cities over the last decades has been jointly influenced by supply-,demand-,and environment-side locational factors,echoing the efficacy of the trinity analytical framework.Overall,our findings demonstrate the temporal variance,contextual contingency,and attribute-based differentiation of locational factors underlying techno-environmentally heterogeneous data centers in Chinese cities.
基金Project(SICGM2023301) supported by the State Key Laboratory of Strata Intelligent Control and Green Mining Co-founded by Shandong Province and the Ministry of Science and Technology,ChinaProject(SMDPC202202) supported by the Key Laboratory of Mining Disaster Prevention and Control,ChinaProject(U21A2030) supported by the National Natural Science Foundation of China。
文摘Microseismic (MS) source location plays an important role in MS monitoring. This paper proposes a MS source location method based on particle swarm optimization (PSO) and multi-sensor arrays, where a free weight joints the P-wave first arrival data. This method adaptively adjusts the preference for “superior” arrays and leverages “inferior” arrays to escape local optima, thereby improving the location accuracy. The effectiveness and stability of this method were validated through synthetic tests, pencil-lead break (PLB) experiments, and mining engineering applications. Specifically, for synthetic tests with 1 μs Gaussian noise and 100 μs large noise in rock samples, the location error of the multi-sensor arrays jointed location method is only 0.30 cm, which improves location accuracy by 97.51% compared to that using a single sensor array. The average location error of PLB events on three surfaces of a rock sample is reduced by 48.95%, 26.40%, and 55.84%, respectively. For mine blast event tests, the average location error of the dual sensor arrays jointed method is 62.74 m, 54.32% and 14.29% lower than that using only sensor arrays 1 and 2, respectively. In summary, the proposed multi-sensor arrays jointed location method demonstrates good noise resistance, stability, and accuracy, providing a compelling new solution for MS location in relevant mining scenarios.
基金the support of the China Three Gorges Corporation Science and Technology Fund, with the numbers 0799275the support of the National Natural Science Foundation of China, with the numbers 42174177 and 62106239。
文摘The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availability of fi xed seismic monitoring stations nearby. To address these challenges, a dense observation array was developed within the study area to monitor and analyze microseismic activity during hydraulic fracturing. Microseismic events generated by hydraulic fracturing typically exhibit low amplitude and signal-to-noise ratio, rendering traditional manual analysis methods impractical. To overcome these limitations, an innovative artifi cial intelligence method combining picking-association-location (PAL) and match-expand- shift-stack (MESS) techniques (PALM) has been utilized for automated seismic detection. Numerous factors influence the accuracy of microseismic detection and localization. To evaluate these factors, the effects of various velocity structure models, instrument types, and station distributions on seismic location were analyzed and compared. The results indicate that the PALM method significantly mitigates the influence of velocity structure models on seismic location accuracy. Additionally, the use of broadband seismic instruments and a uniform station distribution enhances the precision of seismic location results. Furthermore, by integrating data from diff erent types of observation instruments, a comprehensive seismic catalog for the study area was established. These fi ndings not only enhance seismic location accuracy but also provide valuable guidance for optimizing regional seismic monitoring network design and improving seismic risk assessment.
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.
基金supported by National Natural Science Foundation of China(Nos.42374076,42174128 and 42004115)Natural Science Foundation for Excellent Young Scholars of Hunan Province,China(No.2022JJ 20057)+1 种基金Central South University Innovation-Driven Research Programme(No.2023CXQD063)the Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Technology(No.2022B1212010002).
文摘Seismic source locations can characterize the spatial and temporal distributions of seismic sources,and can provide important basic data for earthquake disaster monitoring,fault activity characterization,and fracture growth interpretation.Waveform stacking-based location methods invert the source locations by focusing the source energy with multichannel waveforms,and these methods exhibit a high level of automation and noise-resistance.Taking the cross-correlation stacking(CCS)method as an example,this work attempts to study the influential factors of waveform stacking-based methods,and introduces a comprehensive performance evaluation scheme based on multiple parameters and indicators.The waveform data are from field monitoring of induced microseismicity in the Changning region(southern Sichuan Basin of China).Synthetic and field data tests reveal the impacts of three categories of factors on waveform stacking-based location:velocity model,monitoring array,and waveform complexity.The location performance is evaluated and further improved in terms of the source imaging resolution and location error.Denser array monitoring contributes to better constraining source depth and location reliability,but the combined impact of multiple factors,such as velocity model uncertainty and multiple seismic phases,increases the complexity of locating field microseismic events.Finally,the aspects of location uncertainty,phase detection,and artificial intelligencebased location are discussed.
基金supported by the Natural Science Foundation of Shandong Province(ZR2021MA019)the National Natural Science Foundation of China(11871312)。
文摘In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow equation.The velocity and pressure are computed simultaneously.The accuracy of velocity is improved one order.The concentration equation is solved by using mixed finite element,multi-step difference and upwind approximation.A multi-step method is used to approximate time derivative for improving the accuracy.The upwind approximation and an expanded mixed finite element are adopted to solve the convection and diffusion,respectively.The composite method could compute the diffusion flux and its gradient.It possibly becomes an eficient tool for solving convection-dominated diffusion problems.Firstly,the conservation of mass holds.Secondly,the multi-step method has high accuracy.Thirdly,the upwind approximation could avoid numerical dispersion.Using numerical analysis of a priori estimates and special techniques of differential equations,we give an error estimates for a positive definite problem.Numerical experiments illustrate its computational efficiency and feasibility of application.
基金supported by the National Natural Science Foundation of China(No.52274026)the National Key Research and Development Program(No.2022YFC2806504)the CNOOC Research Project(No.KJGG-2022-17-04 and NO.KJGG-2022-17-05).
文摘Effective isolation between the cement sheath and the sandstone is crucial for the development and production of oil and gas wells in sandstone formations.In this study,a cement-sandstone composite(CSC)was prepared,and based onμ-CT three-dimensional reconstruction imaging and finite element analysis(FEA)techniques,the stress distribution and potential failure mechanism at the cement-sandstone bonding interface under axial loading were analyzed.The key findings are as follows:(1)stress concentrations are highly likely to form at the gap between the cement and sandstone interface and around interfacial voids,with Von Mises stress reaching critical levels of 18.0-20.0 MPa at these locations,significantly exceeding the stress magnitudes in well-bonded regions;(2)the phenomenon of local stress concentration driven by interfacial defects can be identified as the main basis for predicting damage location in interfacial debonding and continuous shear under axial load;(3)ensuring tight cementation at the cement-sandstone interface and minimizing interfacial voids are paramount for preventing stress-induced failure;(4)the critical Von Mises stress value of 20 MPa at the interface defect can be used as a benchmark for material selection and designed to ensure long-term integrity in oil and gas well applications subjected to similar axial loads.These findings contribute to a more accurate understanding of the failure mechanism of the cement-sandstone interface and to the precise design of material properties,thereby ensuring the long-term integrity of oil and gas well applications subjected to similar axial loads.
基金Supported by Natural Science Foundation of the Science and Technology Commission of Shanghai Municipality,No.23ZR1458300Key Discipline Project of Shanghai Municipal Health System,No.2024ZDXK0004+1 种基金Doctoral Innovation Talent Base Project for Diagnosis and Treatment of Chronic Liver Diseases,No.RCJD2021B02Pujiang Project of Shanghai Magnolia Talent Plan,No.24PJD098.
文摘This letter is a commentary on the findings of Huang et al,who emphasize the prognostic value of tumor location in gastric cancer.Analyzing data from 3287 patients using Kaplan-Meier and multivariate Cox models,the authors found that the tumor location correlated with patient prognosis following surgery.Patients with tumors situated nearer to the stomach’s proximal end were associated with shorter survival periods and poorer outcomes.Notably,gender-based differences in tumor markers,particularly carbohydrate antigen 72-4,further highlight the need for sex-specific influence on the tumor location.Despite increasing recognition of tumor location as a prognostic factor,its role remains unclear in clinical prediction models for various cancers.This letter highlights the potential of incorporating tumor location into artificial intelligence-based prognostic tools to enhance prognostic models.It also outlines a stepwise framework for developing these models,from retrospective training to prospective multicenter validation and clinical implementation.In addition,it addresses the technical,ethical,and interoperability challenges critical to successful real-world prognosis.
