Piezoelectric Actuator/Sensor Wave Propagation Based Nondestructive Active Monitoring Method of Concrete Structures

In order to monitor the basic mechanical properties and interior damage of concrete structures,the piezoelectric actuator/sensor based wave propagation method was investigated experimentally in the laboratory using a specifically designed test setup.The energy attenuation of stress waves was measured by the relative index between the output voltage of sensors and the excitation voltage at the actuator.Based on the experimental results of concrete cube and cylinder specimens,the effect of excitation frequencies,excitation amplitude,wave propagation paths and the curing age on the output signals of sensors are evaluated.The results show that the relative voltage attenuation coefficient RVAC is an effective indicator for measuring the attenuation of stress waves through the interior of concrete.

Active source monitoring at the Wenchuan fault zone:coseismic velocity change associated with aftershock event and its implication

With the improvement of seismic observation system, more and more observations indicate that earthquakes may cause seismic velocity change. However, the amplitude and spatial distribution of the velocity variation remains a controversial issue. Recent active source monitoring carried out adjacent to Wenchuan Fault Scientific Drilling （WFSD） revealed unambiguous coseismic velocity change associated with a local M8 5.5 earthquake. Here, we carry out forward modeling using two-dimensional spectral element method to further investigate the amplitude and spatial distribution of observed velocity change. The model is well constrained by results from seismic reflection and WFSD coring. Our model strongly suggests that the observed coseismic velocity change is localized within the fault zone with width of ~ 120 m rather than dynamic strong ground shaking. And a velocity decrease of -2.0 % within the fault zone is required to fit the observed travel time delay distribution, which coincides with rock mechanical experiment and theoretical modeling.

A new early-warning prediction system for monitoring shear force of fault plane in the active fault

The most common method used to describe earthquake activity is based on the changes in physical parameters of the earth＇s surface such as displacement of active fault and seismic wave.However,such approach is not successful in forecasting the movement behaviors of faults.In the present study,a new mechanical model of fault activity,considering the shear strength on the fault plane and the influence of the resistance force,is established based on the occurrence condition of earthquake.A remote real-time monitoring system is correspondingly developed to obtain the changes in mechanical components within fault.Taking into consideration the local geological conditions and the history of fault activity in Zhangjiakou of China,an active fault exposed in the region of Zhangjiakou is selected to be directly monitored by the real-time monitoring technique.A thorough investigation on local fault structures results in the selection of two suitable sites for monitoring potential active tectonic movements of Zhangjiakou fault.Two monitoring curves of shear strength,recorded during a monitoring period of 6 months,turn out to be steady,which indicates that the potential seismic activities hardly occur in the adjacent region in the near future.This monitoring technique can be used for early-warning prediction of the movement of active fault,and can help to further gain an insight into the interaction between fault activity and relevant mechanisms.

Preface to the Special Issue on Advances in Seismic Exploration and Monitoring with Active Sources in China

Analyzing the information carriede by seismic waves is a major means for human beings to have an insight into the structure of the earth’s interior,and by using artificial seismic sources to excite seismic waves,we can obtain high-resolution images for the crustal and smaller scale medium.Artificial seismic exploration methods have been widely applied to fields such as

Artificial Intelligence and Internet of Things Enabled Intelligent Framework for Active and Healthy Living

Obesity poses several challenges to healthcare and the well-being of individuals.It can be linked to several life-threatening diseases.Surgery is a viable option in some instances to reduce obesity-related risks and enable weight loss.State-of-the-art technologies have the potential for long-term benefits in post-surgery living.In this work,an Internet of Things(IoT)framework is proposed to effectively communicate the daily living data and exercise routine of surgery patients and patients with excessive weight.The proposed IoT framework aims to enable seamless communications from wearable sensors and body networks to the cloud to create an accurate profile of the patients.It also attempts to automate the data analysis and represent the facts about a patient.The IoT framework proposes a co-channel interference avoidance mechanism and the ability to communicate higher activity data with minimal impact on the bandwidth requirements of the system.The proposed IoT framework also benefits from machine learning based activity classification systems,with relatively high accuracy,which allow the communicated data to be translated into meaningful information.

Dataset of Large Gathering Images for Person Identification and Tracking

This paper presents a large gathering dataset of images extracted from publicly filmed videos by 24 cameras installed on the premises of Masjid Al-Nabvi,Madinah,Saudi Arabia.This dataset consists of raw and processed images reflecting a highly challenging and unconstraint environment.The methodology for building the dataset consists of four core phases;that include acquisition of videos,extraction of frames,localization of face regions,and cropping and resizing of detected face regions.The raw images in the dataset consist of a total of 4613 frames obtained fromvideo sequences.The processed images in the dataset consist of the face regions of 250 persons extracted from raw data images to ensure the authenticity of the presented data.The dataset further consists of 8 images corresponding to each of the 250 subjects(persons)for a total of 2000 images.It portrays a highly unconstrained and challenging environment with human faces of varying sizes and pixel quality(resolution).Since the face regions in video sequences are severely degraded due to various unavoidable factors,it can be used as a benchmark to test and evaluate face detection and recognition algorithms for research purposes.We have also gathered and displayed records of the presence of subjects who appear in presented frames;in a temporal context.This can also be used as a temporal benchmark for tracking,finding persons,activity monitoring,and crowd counting in large crowd scenarios.

互联网医疗在我国新型冠状病毒肺炎疫情防控中的探索与实践

从控制传染源、切断传播途径、保护易感人群3个关键环节分析互联网医疗在此次疫情防控中的应用价值和典型场景:基于大数据和云计算技术实施主动监测,识别预警疑似病例;互联网医院简化服务流程,开展远程会诊和药事服务,减少人员聚集交叉感染;基于云平台实现门诊全流程自助服务和病历无纸化管理。梳理我国互联网医疗建设过程中遇到的瓶颈并提出发展建议,为突发公共卫生事件应急响应信息化建设提供参考。

Validity and Reliability of the Wristband Activity Monitor in Free-living Children Aged 10-17 Years

Objective In this study we aimed to examine the reliability and validity of the wristband activity monitor against the accelerometer for children.Methods A total of 99 children(mean age = 13.0 ± 2.5 y) wore the two monitors in a free-living context for 7 days. Reliability was measured by intraclass correlation to evaluate consistency over time.Repeated-measures analyses of variance was used to detect differences across days. Spearman’s correlation coefficient(rho), median of absolute percentage error, and Bland-Altman analyses were performed to assess the validity of the wristband against the Acti Graph accelerometer. The optimal number of repeated measures for the wristband was calculated by using the Spearman-Brown prophecy formula.Results The wristband had high reliability for all variables, although physical activity data were different across 7 days. A strong correlation for steps(rho: 0.72, P < 0.001), and moderate correlations for time spent on total physical activity(rho: 0.63, P < 0.001) and physical activity energy expenditure(rho: 0.57, P < 0.001) were observed between the wristband and the accelerometer. For different intensities of physical activity, weak to moderate correlations were found(rho: 0.38 to 0.55, P < 0.001).Conclusion The wristband activity monitor seems to be reliable and valid for measurement of overall children’s physical activity, providing a feasible objective method of physical activity surveillance in children.

Label-Free,Versatile,Real-Time,and High-Throughput Monitoring of Tyrosine Phosphorylation Based on Reversible Configuration Freeze

Tyrosine Phosphorylation(pTyr)is a critical and ubiquitous regulation mechanism in biology that plays a central role in controlling intracellular signaling networks.Precise recognition and specific detection of pTyr peptides have been of great importance for both discoveries of disease biomarkers and screening of therapeutic drugs,especially cancers.Here we report a label-free,versatile,realtime,and high-throughput detection strategy for phosphopeptide(PP)based on reversible configuration freeze of a unique hemicyanine-labeled 2-(2′-hydroxyphenyl)-4-methyloxazole(H-HPMO).By taking advantage of the“OFF–ON”transition of fluorescence,H-HPMO–Cu^(2+)complex displays a highly sensitive and selective response to PPs with modified sites on serine,threonine,and tyrosine.Specific recognition of Tyr PPs is achieved by performing a simple logic gate operation and introducing Ca^(2+)interference as an input.This PP detection approach is universal for various peptide sequences and displays high potential in large-scale kinase inhibitor screening,which will promote the development of targeted anticancer drugs.

Wearable sensors for activity monitoring and motion control:A review

Wearable sensors for activity monitoring currently are being designed and developed,driven by an increasing demand in health care for noninvasive patient monitoring and rehabilitation training.This article reviews state-of-the-art wearable sensors for activity monitoring and motion control.Different technologies,including electromechanical,bioelectrical,and biomechanical sensors,are reviewed,along with their broad applications.Moreover,an overview of existing commercial wearable products and the computation methods for motion analysis are provided.Future research issues are identified and discussed.

Multifunctional mesoporous bioactive glass/upconversion nanoparticle nanocomposites with strong red emission to monitor drug delivery and stimulate osteogenic differentiation of stem cells

For the therapy and regeneration of bone defects resulting from malignant bone tumors, it is necessary to develop multifunctional biomaterials that are able to deliver therapeutic drugs, monitor drug release, and stimulate bone formation. Herein, a multifunctional mesoporous bioactive glass （MBG）/upconversion nanoparticle （UCNP） nanocomposite [UCNPs@SiO2@mSiO2-XCa （X = 0, 5, 10, 15, and 20）] with the ability to deliver anti-cancer drugs, monitor drug release, and stimulate osteogenic differentiation of bone marrow stromal cells （BMSCs） was successfully prepared using a layer-by-layer strategy. The nanocomposite spheres possess a core--sheU structure composed of UCNPs and a mesoporous SiO2/Ca layer with a uniform size distribution of 100 nm. The incorporation of Ca into the nanocomposites induced phase transformation from a pure hexagonal phase to a cubic phase, and facilitated the occurrence of red emission, which significantly improved fluorescence penetration for deep tissue imaging. In addition, since the red emission strongly overlaps with the maximum absorbance of the anti-cancer drug zinc phthalocyanine （ZnPc）, red luminescence could be strongly quenched by ZnPc. Consequently, drug release could be quantified by monitoring changes in fluorescence intensity. Furthermore, the incorporation of Ca into MBG/UCNP nanocomposites remarkably improved bioactivity, i.e., it stimulated apatite mineralization in simulated body fluids and enhanced cell proliferation and bone-related gene expression in BMSCs for the concentration range of 200-500 ~g/mL. Our results suggest that the prepared MBG/UCNP nanocomposites are useful for the therapy and regeneration of bone defects resulting from malignant bone tumors owing to their distinct multifunctionality, including strong red emission and functions in drug-delivery monitoring and osteostimulation.

An eco-friendly and highly sensitive loofah@CF/CNT 3D piezoresistive sensor for human activity monitoring and mechanical cotrol

Three-dimensional(3D)porous piezoresistive sensors are widely used because of their simple fabrication and convenient signal acquisition.However,because of the dependence on organic skeleton materials and the complexity of conductive coating preparation,the electrical and mechanical properties of 3D wearable piezoresistive sensors have gradually failed to accommodate many emerging fields.Here,a new flexible 3D piezoresistive sensor(NF3PS)with high sensitivity and a wide measurement range is proposed,which comprises a natural porous loofah as a flexible framework and carbon fiber/carbon nanotube(CF/CNT)multiscale composite as a conductive coating.Composed of cellulose and lignin,the irregular,porous loofah has excellent mechanical strength,elasticity,and toughness,ensuring a repeated compression/recovery behavior of the NF3PS.In addition,compared with the single-size carbon coating,the coupling of multiscale CF/CNT composite coating improves sensitivities over a range of pressures.The NF3PS demonstrates a sensitivity of 6.94 kPa^(-1) with good linearity in the pressure range of 0–11.2 kPa and maintains a sensitivity of 0.28 kPa^(-1) in an ultrawide measurement range of 11.2–84.6 kPa.Considering flexibility,robustness,and wide-ranging linear resistance variation,the feasibility of the NF3PS in human activity monitoring,mechanical control,and smart homes is verified.This work provides a novel strategy for a new generation of 3D flexible pressure sensors for improving sensitivity and measurement range and demonstrates attractive applications in wearable sensors.

Highly stable capacitive tactile sensors with tunable sensitivity facilitated by electrostatic interaction of layered double hydroxide,MXene,and Ag NWs

A capacitive tactile sensor(CTS)has been developed by assembling a double-sided patterned dielectric layer and novel electrodes.The patterned aluminium foil-supported electrode comprises zinc-aluminium layered double hydroxides(Zn AlLDH),MXene,and Ag NWs via electrostatic interaction.This flexible device enables greater structural deformation,thereby enhancing sensitivity to a wide range of pressure.The sensitivity of the CTS can be customized to meet specific requirements by matching the microstructured electrodes with the patterned dielectric layer.An optimized sensor exhibits a sensitivity of 2.752 kPa^(–1)within 30 kPa,a response time of approximately 100 ms,and a wide detection range of 0–300 kPa.The strong physical interaction among the electrode materials ensures a reliable conductive network,ensuring the long-term stability of the sensor,even after 7500 loading and unloading cycles.Furthermore,the fabricated CTS device presents a promising prospect for the integration into wearable electronics,with the ability to effectively respond to both human activities and external physical stimuli.

Performance of Forearm FMG and sEMG for Estimating Elbow, Forearm and Wrist Positions

The ability to track upper extremity movement during activity of daily living has the potential to facilitate the recovery of individuals with neurological or physical injuries. Hence, the use of Surface Electromyography （sEMG） signals to predict upper extremity movement is an area of interest in the research community. A less established technique, Force Myography （FMG）, which uses force sensors to detect forearm muscle contraction patterns, is also able to detect some movements of the arm. This paper investigates the comparative performance of sEMG and FMG when predicting wrist, forearm and elbow positions using signals extracted from the forearm only. Support Vector Machine （SVM） and Linear Discriminant Analysis （LDA） classifiers were used to evaluate the prediction performance of both FMG and sEMG data. Ten healthy volunteers participated in this study. Under a cross validation across a repetition evaluation scheme, the SVM classifier obtained averaged accuracies of 84.3%, 82.4% and 71.0%, respectively, for predicting elbow, forearm and wrist positions using FMG; while sEMG yielded 75.4%, 83.4% and 92.4% accuracies for predicting the same respective positions. The accuracies obtained using SVM are slightly, but statistical significantly, higher than the ones obtained using LDA. However, the trends on the classification performances between FMG and sEMG are consistent. These results also indicate that the forearm FMG pattern is highly influenced by the change of elbow position, while the forearm sEMG is less subjected to the change. Overall, both forearm FMG and sEMG techniques provide abundant information that can be utilized for tracking the upper extremity movements.

Habitual sedentary time and stationary time are inversely related to aerobic fitness

A one metabolic-equivalent-of-task increase in peak aerobic fitness(peak MET)is associated with a clinically relevant improvement in survival risk and all-cause mortality.The co-dependent impact of free-living physical behaviours on aerobic fitness are poorly understood.The purpose of this study was to investigate the impact of theoretically re-allocating time spent in physical behaviours on aerobic fitness.We hypothesized that substituting sedentary time with any physical activity(at any intensity)would be associated with a predicted improvement in aerobic fitness.Peak volume rate of oxygen uptake(VO_(2)peak)was assessed via indirect calorimetry during a progressive,maximal cycle ergometer protocol in 103 adults(52 females;[38±21]years;[25.0±3.8]kg/m^(2);VO_(2)peak:[35.4±11.5]ml⋅kg^(-1)⋅min^(-1)).Habitual sedentary time,standing time,light-(LPA),moderate-(MPA),and vigorous-physical activity(VPA)were assessed 24-h/day via thigh-worn inclinometry for up to one week(average:[6.3±0.9]days).Isotemporal substitution modelling examined the impact of replacing one physical behaviour with another.Sedentary time(β=0.8,95%CI:[-1.3,-0.2])and standing time(β=0.9,95%CI:[-1.6,-0.2])were negatively associated with VO_(2)peak,whereas VPA was positively associated with relative VO_(2)peak(β=9.2,95%CI:[0.9,17.6]).Substituting 30-min/day of VPA with any other behaviour was associated with a 2.4–3.4 higher peak MET.Higher standing time was associated with a lower aerobic fitness.As little as 10-min/day of VPA predicted a clinically relevant 0.8–1.1 peak MET increase.Theoretically,replacing any time with relatively small amounts of VPA is associated with improvements in aerobic fitness.