This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose detection.In additio...This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose detection.In addition,examines key strategies for designing glucose sensors that are multi-functional,reliable,and cost-effective in a variety of contexts.The unique features of effective diabetes management technology are highlighted,with a focus on using nano/biosensor devices that can quickly and accurately detect glucose levels in the blood,improving patient treatment and control of potential diabetes-related infections.The potential of next-generation wearable and touch-sensitive nano biomedical sensor engineering designs for providing full control in assessing implantable,continuous glucose monitoring is also explored.The challenges of standardizing drug or insulin delivery doses,low-cost,real-time detection of increased blood sugar levels in diabetics,and early digital health awareness controls for the adverse effects of injectable medication are identified as unmet needs.Also,the market for biosensors is expected to expand significantly due to the rising need for portable diagnostic equipment and an ever-increasing diabetic population.The paper concludes by emphasizing the need for further research and development of glucose biosensors to meet the stringent requirements for sensitivity and specificity imposed by clinical diagnostics while being cost-effective,stable,and durable.展开更多
Modern medicine is increasingly interested in advanced sensors to detect and analyze biochemical indicators.Ion sensors based on potentiometric methods are a promising platform for monitoring physiological ions in bio...Modern medicine is increasingly interested in advanced sensors to detect and analyze biochemical indicators.Ion sensors based on potentiometric methods are a promising platform for monitoring physiological ions in biological subjects.Current semi-implantable devices are mainly based on single-parameter detection.Miniaturized semi-implantable electrodes for multiparameter sensing have more restrictions on the electrode size due to biocompatibility considerations,but reducing the electrode surface area could potentially limit electrode sensitivity.This study developed a semi-implantable device system comprising a multiplexed microfilament electrode cluster(MMEC)and a printed circuit board for real-time monitoring of intra-tissue K^(+),Ca^(2+),and Na^(+)concentrations.The electrode surface area was less important for the potentiometric sensing mechanism,suggesting the feasibility of using a tiny fiber-like electrode for potentiometric sensing.The MMEC device exhibited a broad linear response(K^(+):2–32 mmol/L;Ca^(2+):0.5–4 mmol/L;Na^(+):10–160 mmol/L),high sensitivity(about 20–45 mV/decade),temporal stability(>2weeks),and good selectivity(>80%)for the above ions.In vitro detection and in vivo subcutaneous and brain experiment results showed that the MMEC system exhibits good multi-ion monitoring performance in several complex environments.This work provides a platform for the continuous real-time monitoring of ion fluctuations in different situations and has implications for developing smart sensors to monitor human health.展开更多
Arrhythmias are very common in the healthy populations as well as patients with cardiovascular diseases.Among them,atrial fibrillation(AF)and malignant ventricular arrhythmias are usually associated with some clinical...Arrhythmias are very common in the healthy populations as well as patients with cardiovascular diseases.Among them,atrial fibrillation(AF)and malignant ventricular arrhythmias are usually associated with some clinical events.Early diagnosis of arrhythmias,particularly AF and ventricular arrhythmias,is very important for the treatment and prognosis of patients.Holter is a gold standard commonly recommended for noninvasive detection of paroxysmal arrhythmia.However,it has some shortcomings such as fixed detection timings,delayed report and inability of remote real-time detection.To deal with such problems,we designed and applied a new wearable 72-hour triple-lead H3-electrocardiogram(ECG)device with a remote cloud-based ECG platform and an expertsupporting system.In this study,31 patients were recruited and 24-hour synchronous ECG data by H3-ECG and Holter were recorded.In the H3-ECG group,ECG signals were transmitted using remote real-time modes,and confirmed reports were made by doctors in the remote expert-supporting system,while the traditional modes and detection systems were used in the Holter group.The results showed no significant differences between the two groups in 24-hour total heart rate(HR),averaged HR,maximum HR,minimum HR,premature atrial complexes(PACs)and premature ventricular complexes(PVCs)(P>0.05).The sensitivity and specificity of capture and remote automatic cardiac events detection of PACs,PVCs,and AF by H3-ECG were 93%and 99%,98%and 99%,94%and 98%,respectively.Therefore,the long-term limb triple-lead H3-ECG device can be utilized for domiciliary ECG self-monitoring and remote management of patients with common arrhythmia under medical supervision.展开更多
Predicting the mechanical behaviors of structure and perceiving the anomalies in advance are essential to ensuring the safe operation of infrastructures in the long run.In addition to the incomplete consideration of i...Predicting the mechanical behaviors of structure and perceiving the anomalies in advance are essential to ensuring the safe operation of infrastructures in the long run.In addition to the incomplete consideration of influencing factors,the prediction time scale of existing studies is rough.Therefore,this study focuses on the development of a real-time prediction model by coupling the spatio-temporal correlation with external load through autoencoder network(ATENet)based on structural health monitoring(SHM)data.An autoencoder mechanism is performed to acquire the high-level representation of raw monitoring data at different spatial positions,and the recurrent neural network is applied to understanding the temporal correlation from the time series.Then,the obtained temporal-spatial information is coupled with dynamic loads through a fully connected layer to predict structural performance in next 12 h.As a case study,the proposed model is formulated on the SHM data collected from a representative underwater shield tunnel.The robustness study is carried out to verify the reliability and the prediction capability of the proposed model.Finally,the ATENet model is compared with some typical models,and the results indicate that it has the best performance.ATENet model is of great value to predict the realtime evolution trend of tunnel structure.展开更多
Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the eff...Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.展开更多
This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design co...This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.展开更多
Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxi...Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxial creep test on deep coal at various pore pressures using a test system that combines in-situ mechanical loading with real-time nuclear magnetic resonance(NMR) detection was conducted.Full-scale quantitative characterization, online real-time detection, and visualization of MPFS during coal creep influenced by pore pressure and stress coupling were performed using NMR and NMR imaging(NMRI) techniques. The results revealed that seepage pores and microfractures(SPM) undergo the most significant changes during coal creep, with creep failure gradually expanding from dense primary pore fractures. Pore pressure presence promotes MPFS development primarily by inhibiting SPM compression and encouraging adsorption pores(AP) to evolve into SPM. Coal enters the accelerated creep stage earlier at lower stress levels, resulting in more pronounced creep deformation. The connection between the micro and macro values was established, demonstrating that increased porosity at different pore pressures leads to a negative exponential decay of the viscosity coefficient. The Newton dashpot in the ideal viscoplastic body and the Burgers model was improved using NMR experimental results, and a creep model that considers pore pressure and stress coupling using variable-order fractional operators was developed. The model’s reasonableness was confirmed using creep experimental data. The damagestate adjustment factors ω and β were identified through a parameter sensitivity analysis to characterize the effect of pore pressure and stress coupling on the creep damage characteristics(size and degree of difficulty) of coal.展开更多
BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is primarily caused by airway obstruction due to narrowing and blockage in the nasal and nasopha-ryngeal,oropharyngeal,soft palate,and tongue base areas.The m...BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is primarily caused by airway obstruction due to narrowing and blockage in the nasal and nasopha-ryngeal,oropharyngeal,soft palate,and tongue base areas.The mid-frequency anti-snoring device is a new technology based on sublingual nerve stimulation.Its principle is to improve the degree of oropharyngeal airway stenosis in OSAHS patients under mid-frequency wave stimulation.Nevertheless,there is a lack of clinical application and imaging evidence.METHODS We selected 50 patients diagnosed with moderate OSAHS in our hospital between July 2022 and August 2023.They underwent a 4-wk treatment regimen involving the mid-frequency anti-snoring device during nighttime sleep.Following the treatment,we monitored and assessed the sleep apnea quality of life index and Epworth Sleepiness Scale scores.Additionally,we performed computed tomo-graphy scans of the oropharynx in the awake state,during snoring,and while using the mid-frequency anti-snoring device.Cross-sectional area measurements in different states were taken at the narrowest airway point in the soft palate posterior and retrolingual areas.RESULTS Compared to pretreatment measurements,patients exhibited a significant reduction in the apnea-hypopnea index,the percentage of time with oxygen saturation below 90%,snoring frequency,and the duration of the most prolonged apnea event.The lowest oxygen saturation showed a notable increase,and both sleep apnea quality of life index and Epworth Sleepiness Scale scores improved.Oropharyngeal computed tomography scans revealed that in OSAHS patients cross-sectional areas of the oropharyngeal airway in the soft palate posterior area and retrolingual area decreased during snoring compared to the awake state.Conversely,during mid-frequency anti-snoring device treatment,these areas increased compared to snoring.CONCLUSION The mid-frequency anti-snoring device demonstrates the potential to enhance various sleep parameters in patients with moderate OSAHS,thereby improving their quality of life and reducing daytime sleepiness.These therapeutic effects are attributed to the device’s ability to ameliorate the narrowing of the oropharynx in OSAHS patients.展开更多
As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.D...As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.展开更多
The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In ...The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In recent years,with the continuous improvement of monitoring technology and increase of public demands,the original real-time monitoring system needs to be upgraded and improved in terms of timeliness,stability,accuracy and ease of operation.Therefore,by accessing a total of more than 1,000 seismic stations,reducing the seismic trigger threshold of the monitoring system,eliminating the false trigger stations and optimizing the seismic waveform display interface,the current earthquake monitoring demands can be satisfied on the basis of ensuring the stable operation of the system.展开更多
Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at ...Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun DTplus platform.First,power device condition monitoring data storage based on MaxCompute table and parallel permutation entropy feature extraction based on MaxCompute MapReduce are designed and implemented on DTplus platform.Then,Graph based k-means algorithm is implemented and used for massive condition monitoring data clustering analysis.Finally,performance tests are performed to compare the execution time between serial program and parallel program.Performance is analyzed from CPU cores consumption,memory utilization and parallel granularity.Experimental results show that the designed framework and parallel algorithms can efficiently process massive power device condition monitoring data.展开更多
A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake.Howeve...A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake.However,it is rather difficult for current seismic nodal stations to transmit data in real time for an extended period of time,and it usually takes a great amount of time to process the acquired data manually.To monitor earthquakes in real time flexibly,we develop a mobile integrated seismic monitoring system consisting of newly developed nodal units with 4G telemetry and a real-time AI-assisted automatic data processing workflow.The integrated system is convenient for deployment and has been successfully applied in monitoring the aftershocks of the Yangbi M_(S) 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali,Yunnan in southwest China.The acquired seismic data are transmitted almost in real time through the 4G cellular network,and then processed automat-ically for event detection,positioning,magnitude calculation and source mechanism inversion.From tens of seconds to a couple of minutes at most,the final seismic attributes can be presented remotely to the end users through the integrated system.From May 27 to June 17,the real-time system has detected and located 7905 aftershocks in the Yangbi area before the internal batteries exhausted,far more than the catalog provided by China Earthquake Networks Center using the regional permanent stations.The initial application of this inte-grated real-time monitoring system is promising,and we anticipate the advent of a new era for Real-time Intelligent Array Seismology(RIAS),for better monitoring and understanding the subsurface dynamic pro-cesses caused by Earth's internal forces as well as anthropogenic activities.展开更多
Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background...Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.展开更多
Strategic maintenance plays a key role in ensuring high availability and utilization of the haul trucks,and as equipment began to grow more complex towards the end of the 20th century,there was a need for a proactive ...Strategic maintenance plays a key role in ensuring high availability and utilization of the haul trucks,and as equipment began to grow more complex towards the end of the 20th century,there was a need for a proactive maintenance strategy,which led to the development of condition-based maintenance.Realtime condition monitoring(RTCM)is the ability to perform condition monitoring in real-time and has the ability to alert maintenance and operations of abnormal conditions.These alarms can be used as an indication leading to a problem,and if a suitable corrective action is initiated in time,it could result in significant savings of equipment downtime and repair costs.This study aims to compare some maintenance performance indicators prior to and after implementation of RTCM strategy at a mine site using some tests of statistical significance.The study also indicated the presence of seasonality in the data,and thus the data was deseasonalized and detrended prior to being subjected to the statistical tests.Finally,the results indicated that RTCM strategy has proven to be successful in improving the availability for some of the failure categories chosen in this study.展开更多
The municipalities of Ubatuba, Campos do Jord?o, and S?o José dos Campos are located in the region of S?o Paulo State (Brazil). These municipalities are recognized nationally for having an elevated number of reco...The municipalities of Ubatuba, Campos do Jord?o, and S?o José dos Campos are located in the region of S?o Paulo State (Brazil). These municipalities are recognized nationally for having an elevated number of recorded landslides on slopes and embankments. In addition, these municipalities contain multiple areas that are at risk for landslides. Various soil landslides occurred in these municipalities in January 2013, when real-time climactic and geotechnical variables were monitored by automatic rain gauges, humidity sensors and soil temperature and suction devices. The resulting data were used to understand the functions of each variable in the occurrence of land- slides. Analyses of rainfall, humidity and soil temperature were used with field investigations to formulate a hypothesis regarding the predominant rupture mechanism and the role of each monitored variable in the deflagration of the soil landslides that occurred in the three studied municipalities. The geotechnical variable data revealed that both temperature and soil moisture contents played fundamental roles in the deflagration of shallow planar landslides in urban areas. The hourly rain intensity and/or rainfall accumulation for 24 and/or 72 h were responsible for the deflagration of the landslides that occurred in the studied areas, along with the existing anthropic constraints in the risk areas. Significant variations did not occur in the soil suction data during the landslides, principally due to the unsatisfactory sensor precision when reading field suction between –10 and?–100 kPA (±25%).展开更多
The tire blowout or severe leakage real-time monitoring is one of key technologies for developing a tire blowout automatic braking system.An indirect real-time monitoring method to fuse analyses of tire vibration and ...The tire blowout or severe leakage real-time monitoring is one of key technologies for developing a tire blowout automatic braking system.An indirect real-time monitoring method to fuse analyses of tire vibration and effective radius is provided in this paper,and a monitoring system is developed.The calibration and related test results showthat the system can detect the tire blowout in low and middle vehicle speeds and the severe leakage in all speeds timely and accurately.展开更多
Klenow fragment(KF) uses the activity of a separate exonuclease to excise nucleotide, which is a crucial step in DNA replication and repair. Here is a novel sensitive and convenient method introduced for real-time m...Klenow fragment(KF) uses the activity of a separate exonuclease to excise nucleotide, which is a crucial step in DNA replication and repair. Here is a novel sensitive and convenient method introduced for real-time monitoring nucleotide excision by KF with a molecular beacon as a detecting probe in a homogeneous solution. This method, which overcomes the drawbacks of traditional methods such as discontinuity, time consuming and low sensitivity, was used to assay KF activity and the detection limit reached up to 0.4 U/mL. In addition, the method was applied to investigating the effects of metal ions and chemical drugs on the reaction. The results demonstrate that it is a potential high-throughput assay for screening inhibitors and activity analysis of KF in vitro.展开更多
A new system called alternate data acquisition and real-time monitoring system has been developed for long-time discharge in tokamak operation. It can support continuous on-line data acquisition at a high sampling rat...A new system called alternate data acquisition and real-time monitoring system has been developed for long-time discharge in tokamak operation. It can support continuous on-line data acquisition at a high sampling rate and a graphic display of the plasma parameters during the discharge. Thus operators can monitor and control the plasma state in real time. An application of this system has been demonstrated on the HT-7 tokamak.展开更多
Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real ti...Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real time. The method is based on the bistatic scattering theory and concerned more with the receiving and processing of multipath signal at high-frequency and small grazing angle. By use of the multipath propagation structure of underwater acoustic channel, the method obtains the silt thickness by calculating the relative time delay of acoustic signals between the direct and the shortest bottom reflected paths. Bistatic transducer pairs are employed to transmit and receive the acoustic signals, and the GPS time synchronization technology is introduced to synchronize the transmitter and receiver, The WRELAX (Weighted Fourier transforul and RELAX) algorithm is used to obtain the high resolution estimation of muhipath time delay. To examine the feasibility of the presented method and the accuracy and precision of the developed system, a series of sea trials are conducted in the southwest coast area of Dalian City, north of the Yellow Sea. The experimental results are compared with that using high-resolution dual echo sounder HydroBoxTM, and the uncertainty is smaller than + 0.06 m. Compared with the existing means for measuring the silt thickness, the present method is innovative, and the system is stable, efficient and provides a better real-time performance. It especially suits monitoring the narrow channel with rapid changes of siltation.展开更多
基金supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (No.2022M3J7A1062940,2021R1A5A6002853,and 2021R1A2C3011585)supported by the Technology Innovation Program (20015577)funded by the Ministry of Trade,Industry&Energy (MOTIE,Korea)。
文摘This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose detection.In addition,examines key strategies for designing glucose sensors that are multi-functional,reliable,and cost-effective in a variety of contexts.The unique features of effective diabetes management technology are highlighted,with a focus on using nano/biosensor devices that can quickly and accurately detect glucose levels in the blood,improving patient treatment and control of potential diabetes-related infections.The potential of next-generation wearable and touch-sensitive nano biomedical sensor engineering designs for providing full control in assessing implantable,continuous glucose monitoring is also explored.The challenges of standardizing drug or insulin delivery doses,low-cost,real-time detection of increased blood sugar levels in diabetics,and early digital health awareness controls for the adverse effects of injectable medication are identified as unmet needs.Also,the market for biosensors is expected to expand significantly due to the rising need for portable diagnostic equipment and an ever-increasing diabetic population.The paper concludes by emphasizing the need for further research and development of glucose biosensors to meet the stringent requirements for sensitivity and specificity imposed by clinical diagnostics while being cost-effective,stable,and durable.
基金The authors would like to acknowledge financial support from the National Key R&D Program of China(Nos.2021YFF1200700 and 2021YFA0911100)the National Natural Science Foundation of China(Nos.T2225010,32171399,and 32171456)+4 种基金the Fundamental Research Funds for the Central Universities,Sun Yat-Sen University(No.22dfx02)Pazhou Lab,Guangzhou(No.PZL2021KF0003)The authors also would like to thank the funding support from the Opening Project of Key Laboratory of Microelectronic Devices&Integrated Technology,Institute of Microelectronics,Chinese Academy of Sciences,and State Key Laboratory of Precision Measuring Technology and Instruments(No.pilab2211)QQOY would like to thank the China Postdoctoral Science Foundation(No.2022M713645)JL would like to thank the National Natural Science Foundation of China(No.62105380)and the China Postdoctoral Science Foundation(No.2021M693686).
文摘Modern medicine is increasingly interested in advanced sensors to detect and analyze biochemical indicators.Ion sensors based on potentiometric methods are a promising platform for monitoring physiological ions in biological subjects.Current semi-implantable devices are mainly based on single-parameter detection.Miniaturized semi-implantable electrodes for multiparameter sensing have more restrictions on the electrode size due to biocompatibility considerations,but reducing the electrode surface area could potentially limit electrode sensitivity.This study developed a semi-implantable device system comprising a multiplexed microfilament electrode cluster(MMEC)and a printed circuit board for real-time monitoring of intra-tissue K^(+),Ca^(2+),and Na^(+)concentrations.The electrode surface area was less important for the potentiometric sensing mechanism,suggesting the feasibility of using a tiny fiber-like electrode for potentiometric sensing.The MMEC device exhibited a broad linear response(K^(+):2–32 mmol/L;Ca^(2+):0.5–4 mmol/L;Na^(+):10–160 mmol/L),high sensitivity(about 20–45 mV/decade),temporal stability(>2weeks),and good selectivity(>80%)for the above ions.In vitro detection and in vivo subcutaneous and brain experiment results showed that the MMEC system exhibits good multi-ion monitoring performance in several complex environments.This work provides a platform for the continuous real-time monitoring of ion fluctuations in different situations and has implications for developing smart sensors to monitor human health.
基金This research was funded by the Key Research and Development Plan of Jiangsu Province under grant BE2017735.Q.S.conceived the study and wrote the manuscript.Q.S.,C.C.,H.G.X.W.collected,analyzed,and interpreted the data.H.G.and X.W.contributed substantially to the development of ECG signal conversion Matlab software and remote automatic detection algorithm.J.L.,M.C.and C.L.revised the manuscript,evaluated and supervised the study.
文摘Arrhythmias are very common in the healthy populations as well as patients with cardiovascular diseases.Among them,atrial fibrillation(AF)and malignant ventricular arrhythmias are usually associated with some clinical events.Early diagnosis of arrhythmias,particularly AF and ventricular arrhythmias,is very important for the treatment and prognosis of patients.Holter is a gold standard commonly recommended for noninvasive detection of paroxysmal arrhythmia.However,it has some shortcomings such as fixed detection timings,delayed report and inability of remote real-time detection.To deal with such problems,we designed and applied a new wearable 72-hour triple-lead H3-electrocardiogram(ECG)device with a remote cloud-based ECG platform and an expertsupporting system.In this study,31 patients were recruited and 24-hour synchronous ECG data by H3-ECG and Holter were recorded.In the H3-ECG group,ECG signals were transmitted using remote real-time modes,and confirmed reports were made by doctors in the remote expert-supporting system,while the traditional modes and detection systems were used in the Holter group.The results showed no significant differences between the two groups in 24-hour total heart rate(HR),averaged HR,maximum HR,minimum HR,premature atrial complexes(PACs)and premature ventricular complexes(PVCs)(P>0.05).The sensitivity and specificity of capture and remote automatic cardiac events detection of PACs,PVCs,and AF by H3-ECG were 93%and 99%,98%and 99%,94%and 98%,respectively.Therefore,the long-term limb triple-lead H3-ECG device can be utilized for domiciliary ECG self-monitoring and remote management of patients with common arrhythmia under medical supervision.
基金This work is supported by the National Natural Science Foundation of China(Grant No.51991392)Key Deployment Projects of Chinese Academy of Sciences(Grant No.ZDRW-ZS-2021-3-3)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0904).
文摘Predicting the mechanical behaviors of structure and perceiving the anomalies in advance are essential to ensuring the safe operation of infrastructures in the long run.In addition to the incomplete consideration of influencing factors,the prediction time scale of existing studies is rough.Therefore,this study focuses on the development of a real-time prediction model by coupling the spatio-temporal correlation with external load through autoencoder network(ATENet)based on structural health monitoring(SHM)data.An autoencoder mechanism is performed to acquire the high-level representation of raw monitoring data at different spatial positions,and the recurrent neural network is applied to understanding the temporal correlation from the time series.Then,the obtained temporal-spatial information is coupled with dynamic loads through a fully connected layer to predict structural performance in next 12 h.As a case study,the proposed model is formulated on the SHM data collected from a representative underwater shield tunnel.The robustness study is carried out to verify the reliability and the prediction capability of the proposed model.Finally,the ATENet model is compared with some typical models,and the results indicate that it has the best performance.ATENet model is of great value to predict the realtime evolution trend of tunnel structure.
基金supported by National Natural Science Foundation of China(NSFC)under Grant Number T2350710232.
文摘Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.
基金the NSF CCSS-2152638 and the IEN Center Grant from the Institute for Electronics and Nanotechnology at Georgia Tech.
文摘This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.
基金supported by the National Natural Science Foundation of China(Nos.52121003,51827901 and 52204110)China Postdoctoral Science Foundation(No.2022M722346)+1 种基金the 111 Project(No.B14006)the Yueqi Outstanding Scholar Program of CUMTB(No.2017A03).
文摘Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxial creep test on deep coal at various pore pressures using a test system that combines in-situ mechanical loading with real-time nuclear magnetic resonance(NMR) detection was conducted.Full-scale quantitative characterization, online real-time detection, and visualization of MPFS during coal creep influenced by pore pressure and stress coupling were performed using NMR and NMR imaging(NMRI) techniques. The results revealed that seepage pores and microfractures(SPM) undergo the most significant changes during coal creep, with creep failure gradually expanding from dense primary pore fractures. Pore pressure presence promotes MPFS development primarily by inhibiting SPM compression and encouraging adsorption pores(AP) to evolve into SPM. Coal enters the accelerated creep stage earlier at lower stress levels, resulting in more pronounced creep deformation. The connection between the micro and macro values was established, demonstrating that increased porosity at different pore pressures leads to a negative exponential decay of the viscosity coefficient. The Newton dashpot in the ideal viscoplastic body and the Burgers model was improved using NMR experimental results, and a creep model that considers pore pressure and stress coupling using variable-order fractional operators was developed. The model’s reasonableness was confirmed using creep experimental data. The damagestate adjustment factors ω and β were identified through a parameter sensitivity analysis to characterize the effect of pore pressure and stress coupling on the creep damage characteristics(size and degree of difficulty) of coal.
文摘BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is primarily caused by airway obstruction due to narrowing and blockage in the nasal and nasopha-ryngeal,oropharyngeal,soft palate,and tongue base areas.The mid-frequency anti-snoring device is a new technology based on sublingual nerve stimulation.Its principle is to improve the degree of oropharyngeal airway stenosis in OSAHS patients under mid-frequency wave stimulation.Nevertheless,there is a lack of clinical application and imaging evidence.METHODS We selected 50 patients diagnosed with moderate OSAHS in our hospital between July 2022 and August 2023.They underwent a 4-wk treatment regimen involving the mid-frequency anti-snoring device during nighttime sleep.Following the treatment,we monitored and assessed the sleep apnea quality of life index and Epworth Sleepiness Scale scores.Additionally,we performed computed tomo-graphy scans of the oropharynx in the awake state,during snoring,and while using the mid-frequency anti-snoring device.Cross-sectional area measurements in different states were taken at the narrowest airway point in the soft palate posterior and retrolingual areas.RESULTS Compared to pretreatment measurements,patients exhibited a significant reduction in the apnea-hypopnea index,the percentage of time with oxygen saturation below 90%,snoring frequency,and the duration of the most prolonged apnea event.The lowest oxygen saturation showed a notable increase,and both sleep apnea quality of life index and Epworth Sleepiness Scale scores improved.Oropharyngeal computed tomography scans revealed that in OSAHS patients cross-sectional areas of the oropharyngeal airway in the soft palate posterior area and retrolingual area decreased during snoring compared to the awake state.Conversely,during mid-frequency anti-snoring device treatment,these areas increased compared to snoring.CONCLUSION The mid-frequency anti-snoring device demonstrates the potential to enhance various sleep parameters in patients with moderate OSAHS,thereby improving their quality of life and reducing daytime sleepiness.These therapeutic effects are attributed to the device’s ability to ameliorate the narrowing of the oropharynx in OSAHS patients.
基金financially supported by the National Key Research and Development Program of China(No.2019YFC1805400)。
文摘As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.
基金the China Earthquake Network Center Seismic Network Department Daily Operation and Maintenance Funding Support(1950411001)
文摘The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In recent years,with the continuous improvement of monitoring technology and increase of public demands,the original real-time monitoring system needs to be upgraded and improved in terms of timeliness,stability,accuracy and ease of operation.Therefore,by accessing a total of more than 1,000 seismic stations,reducing the seismic trigger threshold of the monitoring system,eliminating the false trigger stations and optimizing the seismic waveform display interface,the current earthquake monitoring demands can be satisfied on the basis of ensuring the stable operation of the system.
基金This work has been supported by.Central University Research Fund(No.2016MS116,No.2016MS117,No.2018MS074)the National Natural Science Foundation(51677072).
文摘Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun DTplus platform.First,power device condition monitoring data storage based on MaxCompute table and parallel permutation entropy feature extraction based on MaxCompute MapReduce are designed and implemented on DTplus platform.Then,Graph based k-means algorithm is implemented and used for massive condition monitoring data clustering analysis.Finally,performance tests are performed to compare the execution time between serial program and parallel program.Performance is analyzed from CPU cores consumption,memory utilization and parallel granularity.Experimental results show that the designed framework and parallel algorithms can efficiently process massive power device condition monitoring data.
基金supported by the National Natural Science Foundation of China (under grants 41874048,41790464,41790462).
文摘A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake.However,it is rather difficult for current seismic nodal stations to transmit data in real time for an extended period of time,and it usually takes a great amount of time to process the acquired data manually.To monitor earthquakes in real time flexibly,we develop a mobile integrated seismic monitoring system consisting of newly developed nodal units with 4G telemetry and a real-time AI-assisted automatic data processing workflow.The integrated system is convenient for deployment and has been successfully applied in monitoring the aftershocks of the Yangbi M_(S) 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali,Yunnan in southwest China.The acquired seismic data are transmitted almost in real time through the 4G cellular network,and then processed automat-ically for event detection,positioning,magnitude calculation and source mechanism inversion.From tens of seconds to a couple of minutes at most,the final seismic attributes can be presented remotely to the end users through the integrated system.From May 27 to June 17,the real-time system has detected and located 7905 aftershocks in the Yangbi area before the internal batteries exhausted,far more than the catalog provided by China Earthquake Networks Center using the regional permanent stations.The initial application of this inte-grated real-time monitoring system is promising,and we anticipate the advent of a new era for Real-time Intelligent Array Seismology(RIAS),for better monitoring and understanding the subsurface dynamic pro-cesses caused by Earth's internal forces as well as anthropogenic activities.
基金The Science and Technoloav Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2020-A11-02)is appreciated for supporting this study.
文摘Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.
文摘Strategic maintenance plays a key role in ensuring high availability and utilization of the haul trucks,and as equipment began to grow more complex towards the end of the 20th century,there was a need for a proactive maintenance strategy,which led to the development of condition-based maintenance.Realtime condition monitoring(RTCM)is the ability to perform condition monitoring in real-time and has the ability to alert maintenance and operations of abnormal conditions.These alarms can be used as an indication leading to a problem,and if a suitable corrective action is initiated in time,it could result in significant savings of equipment downtime and repair costs.This study aims to compare some maintenance performance indicators prior to and after implementation of RTCM strategy at a mine site using some tests of statistical significance.The study also indicated the presence of seasonality in the data,and thus the data was deseasonalized and detrended prior to being subjected to the statistical tests.Finally,the results indicated that RTCM strategy has proven to be successful in improving the availability for some of the failure categories chosen in this study.
文摘The municipalities of Ubatuba, Campos do Jord?o, and S?o José dos Campos are located in the region of S?o Paulo State (Brazil). These municipalities are recognized nationally for having an elevated number of recorded landslides on slopes and embankments. In addition, these municipalities contain multiple areas that are at risk for landslides. Various soil landslides occurred in these municipalities in January 2013, when real-time climactic and geotechnical variables were monitored by automatic rain gauges, humidity sensors and soil temperature and suction devices. The resulting data were used to understand the functions of each variable in the occurrence of land- slides. Analyses of rainfall, humidity and soil temperature were used with field investigations to formulate a hypothesis regarding the predominant rupture mechanism and the role of each monitored variable in the deflagration of the soil landslides that occurred in the three studied municipalities. The geotechnical variable data revealed that both temperature and soil moisture contents played fundamental roles in the deflagration of shallow planar landslides in urban areas. The hourly rain intensity and/or rainfall accumulation for 24 and/or 72 h were responsible for the deflagration of the landslides that occurred in the studied areas, along with the existing anthropic constraints in the risk areas. Significant variations did not occur in the soil suction data during the landslides, principally due to the unsatisfactory sensor precision when reading field suction between –10 and?–100 kPA (±25%).
基金Sponsored by the Applied Foundation Research Project of Suzhou(SYFG0932)
文摘The tire blowout or severe leakage real-time monitoring is one of key technologies for developing a tire blowout automatic braking system.An indirect real-time monitoring method to fuse analyses of tire vibration and effective radius is provided in this paper,and a monitoring system is developed.The calibration and related test results showthat the system can detect the tire blowout in low and middle vehicle speeds and the severe leakage in all speeds timely and accurately.
基金Supported by the Key Project of Natural Science Foundation of China(No.90606003)the Hunan Provincial Natural Science Foundation, China(No.08JJ1002)+1 种基金the National High-Tech Research and Development Program(No.2007AA022007)the Changjiang Scholars and Innovative Research Team in University, China
文摘Klenow fragment(KF) uses the activity of a separate exonuclease to excise nucleotide, which is a crucial step in DNA replication and repair. Here is a novel sensitive and convenient method introduced for real-time monitoring nucleotide excision by KF with a molecular beacon as a detecting probe in a homogeneous solution. This method, which overcomes the drawbacks of traditional methods such as discontinuity, time consuming and low sensitivity, was used to assay KF activity and the detection limit reached up to 0.4 U/mL. In addition, the method was applied to investigating the effects of metal ions and chemical drugs on the reaction. The results demonstrate that it is a potential high-throughput assay for screening inhibitors and activity analysis of KF in vitro.
基金Meg-science Program of the Chinese Academy of Sciences (No. 19981303)
文摘A new system called alternate data acquisition and real-time monitoring system has been developed for long-time discharge in tokamak operation. It can support continuous on-line data acquisition at a high sampling rate and a graphic display of the plasma parameters during the discharge. Thus operators can monitor and control the plasma state in real time. An application of this system has been demonstrated on the HT-7 tokamak.
基金supported by the National Key Technology Research and Development Program of China(863 Program, Grant No.2009BAG18B03)
文摘Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real time. The method is based on the bistatic scattering theory and concerned more with the receiving and processing of multipath signal at high-frequency and small grazing angle. By use of the multipath propagation structure of underwater acoustic channel, the method obtains the silt thickness by calculating the relative time delay of acoustic signals between the direct and the shortest bottom reflected paths. Bistatic transducer pairs are employed to transmit and receive the acoustic signals, and the GPS time synchronization technology is introduced to synchronize the transmitter and receiver, The WRELAX (Weighted Fourier transforul and RELAX) algorithm is used to obtain the high resolution estimation of muhipath time delay. To examine the feasibility of the presented method and the accuracy and precision of the developed system, a series of sea trials are conducted in the southwest coast area of Dalian City, north of the Yellow Sea. The experimental results are compared with that using high-resolution dual echo sounder HydroBoxTM, and the uncertainty is smaller than + 0.06 m. Compared with the existing means for measuring the silt thickness, the present method is innovative, and the system is stable, efficient and provides a better real-time performance. It especially suits monitoring the narrow channel with rapid changes of siltation.