Significant temperature difference(300-77 K or even 4 K) can cause large deformations and displacements of the beam position monitors(BPMs),which affect BPMs measurement resolution or even cause their malfunction in c...Significant temperature difference(300-77 K or even 4 K) can cause large deformations and displacements of the beam position monitors(BPMs),which affect BPMs measurement resolution or even cause their malfunction in cryogenic situations.In this paper,to check the offset from the mechanical to electrical center in low temperature(77 K),Fourier's law and finite element method are used to simulate cryo-deformation.Laser tracker and micro-alignment telescope are employed in combined BPM calibration,installation and monitoring.The calibration error is<0.02 mm,and the installation and monitoring precision are 0.06 mm and 0.01 mm,respectively.The monitored cryo-deformation agrees well with the simulation results.These indicate that the combined alignment can improve performance of the BPM system.All these guaranteed the success of running the 9.55 MeV@2.14 mA cw protons.展开更多
Running composite insulators are prone to failure due to their harsh surrounding work environment, which directly affects the safe operation of transmission lines. This paper puts forward the method of using fiber Bra...Running composite insulators are prone to failure due to their harsh surrounding work environment, which directly affects the safe operation of transmission lines. This paper puts forward the method of using fiber Bragg grating(FBG) as the monitors to parameters correlated with thermal and stress of the composite insulators in transmission lines at working status. Firstly, monitoring points are found out by the mechanical test on composite insulator samples. Secondly, based on the monitoring theory, this paper introduces the feasibility design frame of the composite insulator with FBG implanted in the rod and the online monitor system. At last, it describes applications of this monitor system in the field of transmission lines.展开更多
This study investigates the use of Smart Energy Monitors (SEMs) technology which has been introduced to help electricity consumers conserve energy and to ensure energy efficiency among residents in Ashongman, a suburb...This study investigates the use of Smart Energy Monitors (SEMs) technology which has been introduced to help electricity consumers conserve energy and to ensure energy efficiency among residents in Ashongman, a suburb of Accra. Ghana as a developing country has gone through an energy crisis recently. There has been a shortfall of electricity generation capacity where demand has exceeded supply, which resulted in load shedding management. This study seeks to find out the energy conservation habits among Ghanaian residents at Ashongman and also to investigate the use of SEMs for energy conservation. The findings of the study showed 16% of respondents were aware of the benefits of SEMs in electricity conservation whilst 84% did not know. 72.7% of the respondents who were aware of SMEs have used it whilst 27.3% of respondents who aware of SEMs have not used it for energy conservation purposes. The findings also further indicated the challenges respondents face in conserving energy in their homes and the measures that need to be put in place to ensure energy efficiency. On the basis of the findings, it is recommended for the Energy Commission and Electricity Company of Ghana that, there should be effective policy to educate consumers on adapting SEMs technology for energy conservation.展开更多
Global efforts for environmental cleanliness through the control of gaseous emissions from vehicles are gaining momentum and attracting increasing attention. Calibration plays a crucial role in these efforts by ensuri...Global efforts for environmental cleanliness through the control of gaseous emissions from vehicles are gaining momentum and attracting increasing attention. Calibration plays a crucial role in these efforts by ensuring the quantitative assessment of emissions for informed decisions on environmental treatments. This paper describes a method for the calibration of CO/CO<sub>2</sub> monitors used for periodic inspections of vehicles in cites. The calibration was performed in the selected ranges: 900 - 12,000 µmol/mol for CO and 2000 - 20,000 µmol/mol for CO<sub>2</sub>. The traceability of the measurement results to the SI units was ensured by using certified reference materials from CO/N<sub>2</sub> and CO<sub>2</sub>/N<sub>2</sub> primary gas mixtures. The method performance was evaluated by assessing its linearity, accuracy, precision, bias, and uncertainty of the calibration results. The calibration data exhibited a strong linear trend with R² values close to 1, indicating an excellent fit between the measured values and the calibration lines. Precision, expressed as relative standard deviation (%RSD), ranged from 0.48 to 4.56% for CO and from 0.97 to 3.53% for CO<sub>2</sub>, staying well below the 5% threshold for reporting results at a 95% confidence level. Accuracy measured as percent recovery, was consistently high (≥ 99.1%) for CO and ranged from 84.90% to 101.54% across the calibration range for CO<sub>2</sub>. In addition, the method exhibited minimal bias for both CO and CO<sub>2</sub> calibrations and thus provided a reliable and accurate approach for calibrating CO/CO<sub>2</sub> monitors used in vehicle inspections. Thus, it ensures the effectiveness of exhaust emission control for better environment.展开更多
High purity SiC crystal was used as a passive monitor to measure neutron irradiation temperature in the 49-2 research reactor.The SiC monitors were irradiated with fast neutrons at elevated temperatures to 3.2×10...High purity SiC crystal was used as a passive monitor to measure neutron irradiation temperature in the 49-2 research reactor.The SiC monitors were irradiated with fast neutrons at elevated temperatures to 3.2×10^(20)n/cm^(2).The isochronal and isothermal annealing behaviors of the irradiated SiC were investigated by x-ray diffraction and four-point probe techniques.Invisible point defects and defect clusters are found to be the dominating defect types in the neutron-irradiated SiC.The amount of defect recovery in SiC reaches a maximum value after isothermal annealing for 30 min.Based on the annealing temperature dependences of both lattice swelling and material resistivity,the irradiation temperature of the SiC monitors is determined to be~410℃,which is much higher than the thermocouple temperature of 275℃ recorded during neutron irradiation.The possible reasons for the difference are carefully discussed.展开更多
A front-end electronics of dose monitor has been developed for measuring irradiation dose to the patient in Shanghai Advanced Proton Therapy Facility.The parallel plate ionization chamber is used for the dose monitori...A front-end electronics of dose monitor has been developed for measuring irradiation dose to the patient in Shanghai Advanced Proton Therapy Facility.The parallel plate ionization chamber is used for the dose monitoring.Unlike the traditional method of recycling capacitor integration and voltage-to-frequency conversion,this dose monitor electronics uses the trans-impedance amplifier and analog-to-digital conversion method.It performs satisfactorily,with the integral nonlinearity of less than ±0.04 nA in the range of-400 to 50 nA and the resolution of about±0.6 nA.展开更多
Oscillatory failure cases(OFC)detection in the fly-by-wire(FBW)flight control system for civil aircraft is addressed in this paper.First,OFC is ranked four levels:Handling quality,static load,global structure fatigue ...Oscillatory failure cases(OFC)detection in the fly-by-wire(FBW)flight control system for civil aircraft is addressed in this paper.First,OFC is ranked four levels:Handling quality,static load,global structure fatigue and local fatigue,according to their respect impact on aircraft.Second,we present voting and comparing monitors based on un-similarity redundancy commands to detect OFC.Third,the associated performances,the thresholds and the counters of the monitors are calculated by the high fidelity nonlinear aircraft models.Finally,the monitors of OFC are verified by the Iron Bird Platform with real parameters of the flight control system.The results show that our approach can detect OFC rapidly.展开更多
The 13-MeV proton linac of the Compact Pulsed Hadron Source(CPHS) at Tsinghua University, China,is composed of a 50-keV electron cyclotron resonance proton source, a 3-MeV four-vane-type radio-frequency quadrupole(RFQ...The 13-MeV proton linac of the Compact Pulsed Hadron Source(CPHS) at Tsinghua University, China,is composed of a 50-keV electron cyclotron resonance proton source, a 3-MeV four-vane-type radio-frequency quadrupole(RFQ) accelerator, and a drift tube linac(DTL). Precise measurement of the beam energies at the exit of the RFQ and the DTL is critical for DTL commissioning. Two button-type beam position monitors(BPMs) installed downstream of the RFQ are used to perform the measurement using a time-of-flight method. The effects of several factors on phase measurement accuracy are analyzed. The phase measurement accuracy of the BPMs at CPHS is better than ± 1.03° at 325 MHz after corrections,corresponding to an energy measurement error of± 0.07%. The beam energy measured at the exit of the RFQ is 2.994 ± 0.0022 MeV,which is consistent with the design value.展开更多
Two models are defined for predicting the trajectory of a foam jet originating from a fire monitor(hydrant)and the related intensity drop point.An experimental framework is also defined and used accordingly to compare...Two models are defined for predicting the trajectory of a foam jet originating from a fire monitor(hydrant)and the related intensity drop point.An experimental framework is also defined and used accordingly to compare real-time data with the predictions of such models.This mixed theoretical-experimental approach is proven to be effective for the determination of otherwise unknown coefficients which take into account several important factors such as the operation pressure,the elevation angle and the nozzle diameter.It is shown that the mean absolute error is smaller than 20%.展开更多
Study Objective: To assess the accuracy of respiration rate measurements and the ability to detect apnea by capnometry, impedance pneumography and a new method, acoustic respiration rate monitoring, in anesthetized pa...Study Objective: To assess the accuracy of respiration rate measurements and the ability to detect apnea by capnometry, impedance pneumography and a new method, acoustic respiration rate monitoring, in anesthetized patients undergoing gastrointestinal endoscopy procedures. Design: Prospective observational study. Setting: Endoscopy procedures laboratory. Patients: 98 patients scheduled for upper gastrointestinal endoscopy with propofol-based anesthesia. Interventions: Patients were monitored for respiration rate with acoustic respiration rate monitoring, capnometry and impedance pneumography and values were compared to the manual counting of breaths by observation of chest wall movements. Additionally, when any respiration rate monitor indicated a cessation of breathing for 30 seconds or greater, the presumed apnea was confirmed by direct observation of the patient for absence of chest wall movements. Measurements and Main Results: Bias and precision for respiration rate measurement was 0 ± 1.0 bpm for acoustic monitoring, 4.8 ± 15.1 bpm for capnometry and 0.4 ± 5.9 bpm for impedance pneumography. Sensitivity and specificity for detection of apnea was 73% and 93% for acoustic monitoring, 73% and 12% for capnometry and 45% and 93% for impedance pneumography. Conclusions: Acoustic respiration rate monitoring was found to be accurate for assessment of respiration rate and to have similar or better sensitivity and specificity for detection of apnea compared to capnometry and impedance pneumography in the setting of upper GI endoscopy.展开更多
Objectives: Patients with hyperhidrosis suffer from an extreme perspiration that cannot be aligned with natural or situational standards. Endoscopic sympathectomy is a meaningful option for palmar and axillary hyperhi...Objectives: Patients with hyperhidrosis suffer from an extreme perspiration that cannot be aligned with natural or situational standards. Endoscopic sympathectomy is a meaningful option for palmar and axillary hyperhidrosis. A standardized method of monitoring the immediate intraoperative success has not been established yet. The presented investigation shows one proposed sollution by monitoring skin surface temperature. The main aspect is to demonstrate a significant rise in temperature with utility for monitoring the immediate success of surgery. Methods: Twenty patients with primary hyperhidrosis were observed and treated in a standardized setting against a control group (n = 10). We obtained diverse data that permit determination of a point of time of measurement of surface temperature and definition of a degree of temperature variance. Results: After 5 minutes a significant change of 0.5? Celcius was noted on the palms;after 10 minutes on average 1.2? Celcius. Axillary temperature had significantly changed after 10 minutes with a mean temperature variation of 0.8? Celcius on the right side and 0.6? Celcius on the left side. Conclusions: Under consideration of appropriate time intervals of measurement and determined changes in surface temperature an early control of correct clip application in ETS is possible. In the palmar aspect an increase of 0.5? Celcius at an 5 minutes interval, and more than 1? Celcius at 10 minutes after placement of the clip as compared to basic values before application of the clip can be proposed.展开更多
Locating the source of diffusion in complex networks is a critical and challenging problem,exemplified by tasks such as identifying the origin of power grid faults or detecting the source of computer viruses.The accur...Locating the source of diffusion in complex networks is a critical and challenging problem,exemplified by tasks such as identifying the origin of power grid faults or detecting the source of computer viruses.The accuracy of source localization in most existing methods is highly dependent on the number of infected nodes.When there are few infected nodes in the network,the accuracy is relatively limited.This poses a major challenge in identifying the source in the early stages of diffusion.This article presents a novel deep learning-based model for source localization under limited information conditions,denoted as GCN-MSL (Graph Convolutional Networks and network Monitor-based Source Localization model).The GCN-MSL model is less affected by the number of infected nodes and enables the efficient identification of the diffusion source in the early stages.First,pre-deployed monitor nodes,controlled by the network administrator,continuously report real-time data,including node states and the arrival time of anomalous signals.These data,along with the network topology,are used to construct node features.Graph convolutional networks are employed to aggregate information from multiple-order neighbors,thereby forming comprehensive node representations.Subsequently,the model is trained with the true source labeled as the target,allowing it to distinguish the source node from other nodes within the network.Once trained,the model can be applied to locate hidden sources in other diffusion networks.Experimental results across multiple data sets demonstrate the superiority of the GCN-MSL model,especially in the early stages of diffusion,where it significantly enhances both the accuracy and efficiency of source localization.Additionally,the GCN-MSL model exhibits strong robustness and adaptability to variations in external parameters of monitor nodes.The proposed method holds significant value in the timely detection of anomalous signals within complex networks and preventing the spread of harmful information.展开更多
The website of the Ministry of Ecology and Environment features a section on the national automatic monitoring system for surface water quality Every four hours,it releases real-time data on the water quality at the n...The website of the Ministry of Ecology and Environment features a section on the national automatic monitoring system for surface water quality Every four hours,it releases real-time data on the water quality at the nearly 10,000 moni-toring points across the country.At 2 p.m.on January 12,for instance,the system showed the proportion of monitoring points registering Grade Ⅲ quality or above surpassed 85 percent.展开更多
A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without in...A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.展开更多
Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods,which often demand extensive computational resources and stru...Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods,which often demand extensive computational resources and struggle with diverse data acquisition techniques.This research presents a novel approach for vehicle classification and recognition in aerial image sequences,integrating multiple advanced techniques to enhance detection accuracy.The proposed model begins with preprocessing using Multiscale Retinex(MSR)to enhance image quality,followed by Expectation-Maximization(EM)Segmentation for precise foreground object identification.Vehicle detection is performed using the state-of-the-art YOLOv10 framework,while feature extraction incorporates Maximally Stable Extremal Regions(MSER),Dense Scale-Invariant Feature Transform(Dense SIFT),and Zernike Moments Features to capture distinct object characteristics.Feature optimization is further refined through a Hybrid Swarm-based Optimization algorithm,ensuring optimal feature selection for improved classification performance.The final classification is conducted using a Vision Transformer,leveraging its robust learning capabilities for enhanced accuracy.Experimental evaluations on benchmark datasets,including UAVDT and the Unmanned Aerial Vehicle Intruder Dataset(UAVID),demonstrate the superiority of the proposed approach,achieving an accuracy of 94.40%on UAVDT and 93.57%on UAVID.The results highlight the efficacy of the model in significantly enhancing vehicle detection and classification in aerial imagery,outperforming existing methodologies and offering a statistically validated improvement for intelligent traffic monitoring systems compared to existing approaches.展开更多
Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-in...Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.展开更多
Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have g...Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have garnered considerable attention due to their softness,conformability,and biocompatibility.However,several challenges remain,including imperfect skin-device interfaces,limited breathability,and insufficient mechanoelectrical stability.On-skin epidermal electronics,distinguished by their excellent conformability,breathability,and mechanoelectrical robustness,offer a promising solution for high-fidelity,long-term health monitoring.These devices can seamlessly integrate with the human body,leading to transformative advancements in future personalized healthcare.This review provides a systematic examination of recent advancements in on-skin epidermal electronics,with particular emphasis on critical aspects including material science,structural design,desired properties,and practical applications.We explore various materials,considering their properties and the corresponding structural designs developed to construct high-performance epidermal electronics.We then discuss different approaches for achieving the desired device properties necessary for long-term health monitoring,including adhesiveness,breathability,and mechanoelectrical stability.Additionally,we summarize the diverse applications of these devices in monitoring biophysical and physiological signals.Finally,we address the challenges facing these devices and outline future prospects,offering insights into the ongoing development of on-skin epidermal electronics for long-term health monitoring.展开更多
Objective Evidence suggests that depleted gut microbialα-diversity is associated with hypertension;however,whether metabolic markers affect this relationship remains unknown.We aimed to determine the potential metabo...Objective Evidence suggests that depleted gut microbialα-diversity is associated with hypertension;however,whether metabolic markers affect this relationship remains unknown.We aimed to determine the potential metabolites mediating the associations ofα-diversity with blood pressure(BP)and BP variability(BPV).Methods Metagenomics and plasma targeted metabolomics were conducted on 523 Chinese participants from the MetaSalt study.The 24-hour,daytime,and nighttime BP and BPV were calculated based on ambulatory BP measurements.Linear mixed models were used to characterize the relationships betweenα-diversity(Shannon and Chao1 index)and BP indices.Mediation analyses were performed to assess the contribution of metabolites to the observed associations.The influence of key metabolites on hypertension was further evaluated in a prospective cohort of 2,169 participants.Results Gut microbial richness(Chao1)was negatively associated with 24-hour systolic BP,daytime systolic BP,daytime diastolic BP,24-hour systolic BPV,and nighttime systolic BPV(P<0.05).Moreover,26 metabolites were strongly associated with richness(Bonferroni P<0.05).Among them,four key metabolites(imidazole propionate,2-hydroxy-3-methylbutyric acid,homovanillic acid,and hydrocinnamic acid)mediated the associations between richness and BP indices(proportions of mediating effects:14.1%–67.4%).These key metabolites were also associated with hypertension in the prospective cohort.For example,each 1-standard deviation unit increase in hydrocinnamic acid significantly reduced the risk of prevalent(OR[95%CI]=0.90[0.82,0.99];P=0.03)and incident hypertension(HR[95%CI]=0.83[0.71,0.96];P=0.01).Conclusion Our results suggest that gut microbial richness correlates with lower BP and BPV,and that certain metabolites mediate these associations.These findings provide novel insights into the pathogenesis and prevention of hypertension.展开更多
The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show...The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.展开更多
Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetland...Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.展开更多
基金supported by the National Natural Science Foundation of China(No.11605262)
文摘Significant temperature difference(300-77 K or even 4 K) can cause large deformations and displacements of the beam position monitors(BPMs),which affect BPMs measurement resolution or even cause their malfunction in cryogenic situations.In this paper,to check the offset from the mechanical to electrical center in low temperature(77 K),Fourier's law and finite element method are used to simulate cryo-deformation.Laser tracker and micro-alignment telescope are employed in combined BPM calibration,installation and monitoring.The calibration error is<0.02 mm,and the installation and monitoring precision are 0.06 mm and 0.01 mm,respectively.The monitored cryo-deformation agrees well with the simulation results.These indicate that the combined alignment can improve performance of the BPM system.All these guaranteed the success of running the 9.55 MeV@2.14 mA cw protons.
基金supported by National High-tech Research and Development Program of China (863 Program) (2013AA030701)Science and Technology Project of the State Grid Xinjiang Electric Power Corporation (5230DK15009L)
文摘Running composite insulators are prone to failure due to their harsh surrounding work environment, which directly affects the safe operation of transmission lines. This paper puts forward the method of using fiber Bragg grating(FBG) as the monitors to parameters correlated with thermal and stress of the composite insulators in transmission lines at working status. Firstly, monitoring points are found out by the mechanical test on composite insulator samples. Secondly, based on the monitoring theory, this paper introduces the feasibility design frame of the composite insulator with FBG implanted in the rod and the online monitor system. At last, it describes applications of this monitor system in the field of transmission lines.
文摘This study investigates the use of Smart Energy Monitors (SEMs) technology which has been introduced to help electricity consumers conserve energy and to ensure energy efficiency among residents in Ashongman, a suburb of Accra. Ghana as a developing country has gone through an energy crisis recently. There has been a shortfall of electricity generation capacity where demand has exceeded supply, which resulted in load shedding management. This study seeks to find out the energy conservation habits among Ghanaian residents at Ashongman and also to investigate the use of SEMs for energy conservation. The findings of the study showed 16% of respondents were aware of the benefits of SEMs in electricity conservation whilst 84% did not know. 72.7% of the respondents who were aware of SMEs have used it whilst 27.3% of respondents who aware of SEMs have not used it for energy conservation purposes. The findings also further indicated the challenges respondents face in conserving energy in their homes and the measures that need to be put in place to ensure energy efficiency. On the basis of the findings, it is recommended for the Energy Commission and Electricity Company of Ghana that, there should be effective policy to educate consumers on adapting SEMs technology for energy conservation.
文摘Global efforts for environmental cleanliness through the control of gaseous emissions from vehicles are gaining momentum and attracting increasing attention. Calibration plays a crucial role in these efforts by ensuring the quantitative assessment of emissions for informed decisions on environmental treatments. This paper describes a method for the calibration of CO/CO<sub>2</sub> monitors used for periodic inspections of vehicles in cites. The calibration was performed in the selected ranges: 900 - 12,000 µmol/mol for CO and 2000 - 20,000 µmol/mol for CO<sub>2</sub>. The traceability of the measurement results to the SI units was ensured by using certified reference materials from CO/N<sub>2</sub> and CO<sub>2</sub>/N<sub>2</sub> primary gas mixtures. The method performance was evaluated by assessing its linearity, accuracy, precision, bias, and uncertainty of the calibration results. The calibration data exhibited a strong linear trend with R² values close to 1, indicating an excellent fit between the measured values and the calibration lines. Precision, expressed as relative standard deviation (%RSD), ranged from 0.48 to 4.56% for CO and from 0.97 to 3.53% for CO<sub>2</sub>, staying well below the 5% threshold for reporting results at a 95% confidence level. Accuracy measured as percent recovery, was consistently high (≥ 99.1%) for CO and ranged from 84.90% to 101.54% across the calibration range for CO<sub>2</sub>. In addition, the method exhibited minimal bias for both CO and CO<sub>2</sub> calibrations and thus provided a reliable and accurate approach for calibrating CO/CO<sub>2</sub> monitors used in vehicle inspections. Thus, it ensures the effectiveness of exhaust emission control for better environment.
文摘High purity SiC crystal was used as a passive monitor to measure neutron irradiation temperature in the 49-2 research reactor.The SiC monitors were irradiated with fast neutrons at elevated temperatures to 3.2×10^(20)n/cm^(2).The isochronal and isothermal annealing behaviors of the irradiated SiC were investigated by x-ray diffraction and four-point probe techniques.Invisible point defects and defect clusters are found to be the dominating defect types in the neutron-irradiated SiC.The amount of defect recovery in SiC reaches a maximum value after isothermal annealing for 30 min.Based on the annealing temperature dependences of both lattice swelling and material resistivity,the irradiation temperature of the SiC monitors is determined to be~410℃,which is much higher than the thermocouple temperature of 275℃ recorded during neutron irradiation.The possible reasons for the difference are carefully discussed.
文摘A front-end electronics of dose monitor has been developed for measuring irradiation dose to the patient in Shanghai Advanced Proton Therapy Facility.The parallel plate ionization chamber is used for the dose monitoring.Unlike the traditional method of recycling capacitor integration and voltage-to-frequency conversion,this dose monitor electronics uses the trans-impedance amplifier and analog-to-digital conversion method.It performs satisfactorily,with the integral nonlinearity of less than ±0.04 nA in the range of-400 to 50 nA and the resolution of about±0.6 nA.
文摘Oscillatory failure cases(OFC)detection in the fly-by-wire(FBW)flight control system for civil aircraft is addressed in this paper.First,OFC is ranked four levels:Handling quality,static load,global structure fatigue and local fatigue,according to their respect impact on aircraft.Second,we present voting and comparing monitors based on un-similarity redundancy commands to detect OFC.Third,the associated performances,the thresholds and the counters of the monitors are calculated by the high fidelity nonlinear aircraft models.Finally,the monitors of OFC are verified by the Iron Bird Platform with real parameters of the flight control system.The results show that our approach can detect OFC rapidly.
文摘The 13-MeV proton linac of the Compact Pulsed Hadron Source(CPHS) at Tsinghua University, China,is composed of a 50-keV electron cyclotron resonance proton source, a 3-MeV four-vane-type radio-frequency quadrupole(RFQ) accelerator, and a drift tube linac(DTL). Precise measurement of the beam energies at the exit of the RFQ and the DTL is critical for DTL commissioning. Two button-type beam position monitors(BPMs) installed downstream of the RFQ are used to perform the measurement using a time-of-flight method. The effects of several factors on phase measurement accuracy are analyzed. The phase measurement accuracy of the BPMs at CPHS is better than ± 1.03° at 325 MHz after corrections,corresponding to an energy measurement error of± 0.07%. The beam energy measured at the exit of the RFQ is 2.994 ± 0.0022 MeV,which is consistent with the design value.
基金the National Key Research and Development Plan(Grant No.2016YFC0801300).
文摘Two models are defined for predicting the trajectory of a foam jet originating from a fire monitor(hydrant)and the related intensity drop point.An experimental framework is also defined and used accordingly to compare real-time data with the predictions of such models.This mixed theoretical-experimental approach is proven to be effective for the determination of otherwise unknown coefficients which take into account several important factors such as the operation pressure,the elevation angle and the nozzle diameter.It is shown that the mean absolute error is smaller than 20%.
文摘Study Objective: To assess the accuracy of respiration rate measurements and the ability to detect apnea by capnometry, impedance pneumography and a new method, acoustic respiration rate monitoring, in anesthetized patients undergoing gastrointestinal endoscopy procedures. Design: Prospective observational study. Setting: Endoscopy procedures laboratory. Patients: 98 patients scheduled for upper gastrointestinal endoscopy with propofol-based anesthesia. Interventions: Patients were monitored for respiration rate with acoustic respiration rate monitoring, capnometry and impedance pneumography and values were compared to the manual counting of breaths by observation of chest wall movements. Additionally, when any respiration rate monitor indicated a cessation of breathing for 30 seconds or greater, the presumed apnea was confirmed by direct observation of the patient for absence of chest wall movements. Measurements and Main Results: Bias and precision for respiration rate measurement was 0 ± 1.0 bpm for acoustic monitoring, 4.8 ± 15.1 bpm for capnometry and 0.4 ± 5.9 bpm for impedance pneumography. Sensitivity and specificity for detection of apnea was 73% and 93% for acoustic monitoring, 73% and 12% for capnometry and 45% and 93% for impedance pneumography. Conclusions: Acoustic respiration rate monitoring was found to be accurate for assessment of respiration rate and to have similar or better sensitivity and specificity for detection of apnea compared to capnometry and impedance pneumography in the setting of upper GI endoscopy.
文摘Objectives: Patients with hyperhidrosis suffer from an extreme perspiration that cannot be aligned with natural or situational standards. Endoscopic sympathectomy is a meaningful option for palmar and axillary hyperhidrosis. A standardized method of monitoring the immediate intraoperative success has not been established yet. The presented investigation shows one proposed sollution by monitoring skin surface temperature. The main aspect is to demonstrate a significant rise in temperature with utility for monitoring the immediate success of surgery. Methods: Twenty patients with primary hyperhidrosis were observed and treated in a standardized setting against a control group (n = 10). We obtained diverse data that permit determination of a point of time of measurement of surface temperature and definition of a degree of temperature variance. Results: After 5 minutes a significant change of 0.5? Celcius was noted on the palms;after 10 minutes on average 1.2? Celcius. Axillary temperature had significantly changed after 10 minutes with a mean temperature variation of 0.8? Celcius on the right side and 0.6? Celcius on the left side. Conclusions: Under consideration of appropriate time intervals of measurement and determined changes in surface temperature an early control of correct clip application in ETS is possible. In the palmar aspect an increase of 0.5? Celcius at an 5 minutes interval, and more than 1? Celcius at 10 minutes after placement of the clip as compared to basic values before application of the clip can be proposed.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.72371244,72231011,72301286,72431011 and 72421002).
文摘Locating the source of diffusion in complex networks is a critical and challenging problem,exemplified by tasks such as identifying the origin of power grid faults or detecting the source of computer viruses.The accuracy of source localization in most existing methods is highly dependent on the number of infected nodes.When there are few infected nodes in the network,the accuracy is relatively limited.This poses a major challenge in identifying the source in the early stages of diffusion.This article presents a novel deep learning-based model for source localization under limited information conditions,denoted as GCN-MSL (Graph Convolutional Networks and network Monitor-based Source Localization model).The GCN-MSL model is less affected by the number of infected nodes and enables the efficient identification of the diffusion source in the early stages.First,pre-deployed monitor nodes,controlled by the network administrator,continuously report real-time data,including node states and the arrival time of anomalous signals.These data,along with the network topology,are used to construct node features.Graph convolutional networks are employed to aggregate information from multiple-order neighbors,thereby forming comprehensive node representations.Subsequently,the model is trained with the true source labeled as the target,allowing it to distinguish the source node from other nodes within the network.Once trained,the model can be applied to locate hidden sources in other diffusion networks.Experimental results across multiple data sets demonstrate the superiority of the GCN-MSL model,especially in the early stages of diffusion,where it significantly enhances both the accuracy and efficiency of source localization.Additionally,the GCN-MSL model exhibits strong robustness and adaptability to variations in external parameters of monitor nodes.The proposed method holds significant value in the timely detection of anomalous signals within complex networks and preventing the spread of harmful information.
文摘The website of the Ministry of Ecology and Environment features a section on the national automatic monitoring system for surface water quality Every four hours,it releases real-time data on the water quality at the nearly 10,000 moni-toring points across the country.At 2 p.m.on January 12,for instance,the system showed the proportion of monitoring points registering Grade Ⅲ quality or above surpassed 85 percent.
基金supported by the National Natural Science Foundation of China(22074072,22274083,52376199)the Shandong Provincial Natural Science Foundation(ZR2023LZY005)+1 种基金the Exploration Project of the State Key Laboratory of BioFibers and EcoTextiles of Qingdao University(TSKT202101)the Fundamental Research Funds for the Central Universities(2022BLRD13,2023BLRD01).
文摘A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness.However,a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations,as well as mechanical motion artifacts.Herein,a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode,featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness,thereby realizing the long-term breath-induced pressure detection.Notably,molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration,driven by shear forces and interfacial interactions,which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer.The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation(0-120°,~2.8×10^(-3) A)and sensing accuracy without crosstalk(humidity 50%-100%and temperature 30-80).Besides,the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages(average prediction accuracy~90%).It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.
文摘Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods,which often demand extensive computational resources and struggle with diverse data acquisition techniques.This research presents a novel approach for vehicle classification and recognition in aerial image sequences,integrating multiple advanced techniques to enhance detection accuracy.The proposed model begins with preprocessing using Multiscale Retinex(MSR)to enhance image quality,followed by Expectation-Maximization(EM)Segmentation for precise foreground object identification.Vehicle detection is performed using the state-of-the-art YOLOv10 framework,while feature extraction incorporates Maximally Stable Extremal Regions(MSER),Dense Scale-Invariant Feature Transform(Dense SIFT),and Zernike Moments Features to capture distinct object characteristics.Feature optimization is further refined through a Hybrid Swarm-based Optimization algorithm,ensuring optimal feature selection for improved classification performance.The final classification is conducted using a Vision Transformer,leveraging its robust learning capabilities for enhanced accuracy.Experimental evaluations on benchmark datasets,including UAVDT and the Unmanned Aerial Vehicle Intruder Dataset(UAVID),demonstrate the superiority of the proposed approach,achieving an accuracy of 94.40%on UAVDT and 93.57%on UAVID.The results highlight the efficacy of the model in significantly enhancing vehicle detection and classification in aerial imagery,outperforming existing methodologies and offering a statistically validated improvement for intelligent traffic monitoring systems compared to existing approaches.
文摘Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.
基金supported by National Natural Science Foundation of China(Grant Nos.52025055,52375576,52350349)Key Research and Development Program of Shaanxi(Program No.2022GXLH-01-12)+2 种基金Joint Fund of Ministry of Education for Equipment Pre-research(No.8091B03012304)Aeronautical Science Foundation of China(No.2022004607001)the Fundamental Research Funds for the Central Universities(No.xtr072024031).
文摘Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have garnered considerable attention due to their softness,conformability,and biocompatibility.However,several challenges remain,including imperfect skin-device interfaces,limited breathability,and insufficient mechanoelectrical stability.On-skin epidermal electronics,distinguished by their excellent conformability,breathability,and mechanoelectrical robustness,offer a promising solution for high-fidelity,long-term health monitoring.These devices can seamlessly integrate with the human body,leading to transformative advancements in future personalized healthcare.This review provides a systematic examination of recent advancements in on-skin epidermal electronics,with particular emphasis on critical aspects including material science,structural design,desired properties,and practical applications.We explore various materials,considering their properties and the corresponding structural designs developed to construct high-performance epidermal electronics.We then discuss different approaches for achieving the desired device properties necessary for long-term health monitoring,including adhesiveness,breathability,and mechanoelectrical stability.Additionally,we summarize the diverse applications of these devices in monitoring biophysical and physiological signals.Finally,we address the challenges facing these devices and outline future prospects,offering insights into the ongoing development of on-skin epidermal electronics for long-term health monitoring.
基金supported by the National Science and Technology Major Program for Noncommunicable Chronic Diseases(2023ZD0503500)the National Natural Science Foundation of China(82030102,12126602,91857118)+1 种基金the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences(2021-I2M-1-010,2019-I2M-2-003)the National High Level Hospital Clinical Research Funding(2022-GSP-GG-1,2022-GSP-GG-2)。
文摘Objective Evidence suggests that depleted gut microbialα-diversity is associated with hypertension;however,whether metabolic markers affect this relationship remains unknown.We aimed to determine the potential metabolites mediating the associations ofα-diversity with blood pressure(BP)and BP variability(BPV).Methods Metagenomics and plasma targeted metabolomics were conducted on 523 Chinese participants from the MetaSalt study.The 24-hour,daytime,and nighttime BP and BPV were calculated based on ambulatory BP measurements.Linear mixed models were used to characterize the relationships betweenα-diversity(Shannon and Chao1 index)and BP indices.Mediation analyses were performed to assess the contribution of metabolites to the observed associations.The influence of key metabolites on hypertension was further evaluated in a prospective cohort of 2,169 participants.Results Gut microbial richness(Chao1)was negatively associated with 24-hour systolic BP,daytime systolic BP,daytime diastolic BP,24-hour systolic BPV,and nighttime systolic BPV(P<0.05).Moreover,26 metabolites were strongly associated with richness(Bonferroni P<0.05).Among them,four key metabolites(imidazole propionate,2-hydroxy-3-methylbutyric acid,homovanillic acid,and hydrocinnamic acid)mediated the associations between richness and BP indices(proportions of mediating effects:14.1%–67.4%).These key metabolites were also associated with hypertension in the prospective cohort.For example,each 1-standard deviation unit increase in hydrocinnamic acid significantly reduced the risk of prevalent(OR[95%CI]=0.90[0.82,0.99];P=0.03)and incident hypertension(HR[95%CI]=0.83[0.71,0.96];P=0.01).Conclusion Our results suggest that gut microbial richness correlates with lower BP and BPV,and that certain metabolites mediate these associations.These findings provide novel insights into the pathogenesis and prevention of hypertension.
基金supported by the National Natural Science Foundation of China(NSFC 52175281,52475315)Youth Innovation Promotion Association of CAS(2021382)。
文摘The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.
基金support through the“Trans-Disciplinary Research”Grant(No.R/Dev/IoE/TDRProjects/2023-24/61658),which played a crucial role in enabling this research endeavor.
文摘Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.
