Effects of Continuous Non-Invasive Blood Pressure Monitoring on Intraoperative Hemodynamics and Postoperative Myocardial Injury in Craniotomy:Comparison Between Groups Based on Self-Control and Propensity Score Matching

Objective:To explore the effect of continuous non-invasive blood pressure monitoring on intraoperative hemodynamics and postoperative myocardial injury in craniotomy.Methods:120 cases of elective craniotomy were divided into the self-control group(continuous non-invasive blood pressure monitoring and intermittent cuff non-invasive blood pressure monitoring,CNAP group)and propensity score matching group(only intermittent cuff non-invasive blood pressure measurement in previous craniotomy,PSM group);Goal-directed hemodynamic management in CNAP group included heart rate(HR),blood pressure(BP),stroke volume(SV),stroke variability(SVV),and systemic vascular resistance index(SVRI).The main index is to compare the troponin level within 72 hours after operation between the CNAP group and the PSM group;The secondary indicators are the comparison of the hemodynamic conditions between the CNAP group and the PSM at 10 specific time points.Results:The incidence of postoperative myocardial injury in the CNAP group was significantly lower than that in the PSM group(12%vs.30%,P=0.01);in the CNAP group hypotensive episodes(6 vs.3,P=0.01),positive balance of fluid therapy(700 vs.500 mL,P<0.001),more use of vasoactive drugs(29 vs.18,P=0.04),more stable hemodynamics medical status(P=0.03)were recorded.Conclusion:The hemodynamic management strategy based on continuous non-invasive blood pressure monitoring can reduce the incidence of myocardial injury after elective craniotomy and maintain a more stable hemodynamic state.

Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe operation.Although Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively low.Moreover,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains unclear.Hence,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore platforms.To address these concerns,vibration table tests with different amplitudes and frequencies are conducted.The results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with GNSS-RTK.Furthermore,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of GNSS-PPP.Field monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN de-noising.By comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load action.The research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

Comparing a non-invasive hemodynamic monitor with minimally invasive monitoring during major open abdominal surgery

As part of the enhanced recovery after surgery （ERAS） protocol, the goal-directed fluid management with hemodynamic monitoring can effectively guide perioperative fluid use and significantly improve the outcomes in highrisk patients undergoing major surgeries. Several minimally invasive and non-invasive monitoring devices are commercially available for clinical use. As part of an internal evaluation, we reported the results from three different hemodynamic monitoring devices used in a patient undergoing a major abdominal surgery.

Microseismic monitoring and forecasting of dynamic disasters in underground hydropower projects in southwest China:A review

The underground hydropower projects in Southwest China is characterized by large excavation sizes,high geostresses,complicated geological conditions and multiple construction processes.Various disasters such as collapses,large deformations,rockbursts are frequently encountered,resulting in serious casualties and huge economic losses.This review mainly presents some representative results on microseismic(MS)monitoring and forecasting for disasters in hydropower underground engineering.First,a set of new denoising,spectral analysis,and location methods were developed for better identification and location of MS signals.Then,the tempo-spatial characteristics of MS events were analyzed to understand the relationship between field construction and damages of surrounding rocks.Combined with field construction,geological data,numerical simulation and parametric analysis of MS sources,the focal mechanism of MS events was revealed.A damage constitutive model considering MS fracturing size was put forward and feedback analysis considering the MS damage of underground surrounding rocks was conducted.Next,an MS multi-parameter based risk assessment and early warning method for dynamic disasters were proposed.The technology for control of the damage and deformation of underground surrounding rocks was proposed for underground caverns.Finally,two typical underground powerhouses were selected as case studies.These achievements can provide significant references for prevention and control of dynamic disasters for underground engineering with similar complicated geological conditions.

Analysis of rockburst mechanism and warning based on microseismic moment tensors and dynamic Bayesian networks

One of the major factors inhibiting the construction of deep underground projects is the risk posed by rockbursts.A study was conducted on the access tunnel of the Shuangjiangkou hydropower station to determine the evolutionary mechanism of microfractures within the surrounding rock mass during rockburst development and develop a rockburst warning model.The study area was chosen through the combination of field studies with an analysis of the spatial and temporal distribution of microseismic(MS)events.The moment tensor inversion method was adopted to study rockburst mechanism,and a dynamic Bayesian network(DBN)was applied to investigating the sensitivity of MS source parameters for rockburst warnings.A MS multivariable rockburst warning model was proposed and validated using two case studies.The results indicate that fractures in the surrounding rock mass during the development of strain-structure rockbursts initially show shear failure and are then followed by tensile failure.The effectiveness of the DBN-based rockburst warning model was demonstrated using self-validation and K-fold cross-validation.Moment magnitude and source radius are the most sensitive factors based on an investigation of the influence on the parent and child nodes in the model,which can serve as important standards for rockburst warnings.The proposed rockburst warning model was found to be effective when applied to two actual projects.

Monitoring and analysis of nonlinear dynamic damage of transport roadway supported by composite hard rock materials in Linglong Gold Mine

The study concentrates mainly on the development of failure process incomposite rock mass. By use of acoustic emission (AE), convergence inspection, pressure monitoring,level measurement techniques and the modem signal analysis technology, as well as scan electronmicroscopy (SEM) experiment, various aspects of nonlinear dynamic damage of composite rock masssurrounding the transport roadway in Linglong gold mine are discussed. According to the monitoringresults, the stability of the rock mass can be synthetically evaluated, and the intrinsic relationbetween the damage and the characteristic parameters of acoustic emission can be determined. Thelocation of the damage of rock mass can also be detected based on the acoustic emission couplemonitoring signals. Finally, the key factors which influence the stability of the transport roadwaysupported by composite hard rock materials are found out.

Dynamic monitoring of menopause hormone therapy and defining the cut-off value of endometrial thickness during uterine bleeding

The aim of this study was to evaluate the effects of low-dose tibolone therapy on ovarian area, uterine volume and endometrial thickness, and define the cut-off value of endometrial thickness for curettage during uterine bleeding. We followed 619 postmenopausal women, aged 40-60 years, for two years. There were 301 subjects in the low-dose tibolone treatment group and 318 subjects in the control group. The ovarian area, uterine volume and endometrial thickness in all participants were measured by transvaginal ultrasound prior to, one and two years post enrollment, respectively. Endometrial specimens were collected from all subjects with abnormal uterine bleeding during the follow-up period. We found that the uterine volume in the treatment group was greater than that in the control group, and the difference was significant （P〈0.05）, but there were no significant differences in ovarian area and endometrial thickness between the two groups （P〉0.05）. When the cut-off value for endometrial thickness was 7.35 ram, the sensitivity and specificity were 100% and 79.07%, respectively, and 85.71% and 93.02% when 7.55 mm was set as the cut-offduring tibolone therapy. The results indicate that low-dose tibolone therapy may postpone uterine atrophy and the cut-off value of endometrial thickness may be appropriately adjusted for curettage.

Multi-parameter numerical simulation of dynamic monitoring of rock deformation in deep mining

The level of deformation development of surrounding rocks is a vital predictor to evaluate impending coal mine disasters and it is important to establish accurate measurements of the deformed status to ensure coal mine safety. Traditional deformation monitoring methods are mostly based on single parameter, in this paper, multiple approaches are integrated: firstly, both electric and elastic models are established,from which electric field distribution and seismic wave recording are calculated and finally, the resistivity profiles and source position information are determined using inversion methods, from which then the deformation and failure of mine floor are evaluated. According to the inversion results of both electric and seismic field signals, multiple-parameter dynamic monitoring of surrounding rock deformation in deep mine can be performed. The methodology is validated using numerical simulation results which shows that the multi-parameter dynamic monitoring methods have better results for surrounding rock deformation in deep mine monitoring than single parameter methods.

A combined finite element and deep learning network for structural dynamic response estimation on concrete gravity dam subjected to blast loads

Social infrastructures such as dams are likely to be exposed to high risk of terrorist and military attacks,leading to increasing attentions on their vulnerability and catastrophic consequences under such events.This paper tries to develop advanced deep learning approaches for structural dynamic response prediction and dam health diagnosis.At first,the improved long short-term memory(LSTM)networks are proposed for data-driven structural dynamic response analysis with the data generated by a single degree of freedom(SDOF)and the finite numerical simulation,due to the unavailability of abundant practical structural response data of concrete gravity dam under blast events.Three kinds of LSTM-based models are discussed with the various cases of noise-contaminated signals,and the results prove that LSTM-based models have the potential for quick structural response estimation under blast loads.Furthermore,the damage indicators(i.e.,peak vibration velocity and domain frequency)are extracted from the predicted velocity histories,and their relationship with the dam damage status from the numerical simulation is established.This study provides a deep-learning based structural health monitoring(SHM)framework for quick assessment of dam experienced underwater explosions through blastinduced monitoring data.

Monitoring of Land-Cover Dynamic Change in Lancangjiang River Cascaded Hydropower Area

The analysis of the 3 stages＇ （1988,1996,2000） variation of land-cover is performed according to Thematic Mapper （TM） and Enhancement Thematic Mapper（ETM） satellite image by combining ground GIS database with GPS field collected data in the area of Xiaowan-Dachaoshan Reservoirs of Lancangjiang River cascaded Hydropower Area. Consequently, the land-cover is divided into five subclasses, namely water, paddy field and wetland, bare dryland and sparse shrub, secondary forest and density forest. The result showed that the areas of bare land, upland and secondary forest decreased in 1988-1996, whereas from 1996 to 2000, water body and density forest keep invariability while the areas of paddy field and wetland, bare dryland and sparse scrub increasing and the area of secondary forest decrease; Features of reciprocal transformation between density forest and other type of land-cover had two points, i.e. secondary forest, bare dryland and sparse shrub converted to density forest; and density forest converted to secondary forest and paddy field and wetland. It reflects the dynamic variation of density forest; the area which slope less than 8° and greater than 15° shows bigger variation, however, less change in 8°-15°.

On the problem of the dynamical reactions of a rolling wheelset to real track irregularities

We investigate numerically the dynamical reactions of a moving wheelset model to real measured track irregularities.The background is to examine whether the dynamics are suitable as the input to the inverse problem:determine the true track geometry from measured wheelset dynamical reactions.It is known that the method works well for the vertical position of the rails but the computed lateral position is often flawed.We find that the lateral motion of the wheelset often may differ from the track geometry.The cases are investigated closely but the reasons remain unknown.While the wheelset dynamics reflect the larger(>4-6 mm)aperiodic track disturbances and single large disturbances quite well,this does not seem to be the case for general smaller or periodic track irregularities or sections behind single large disturbances.The resulting dynamics of a wheelset to lateral track irregularities are in general not sufficiently accurate to be used as the basis for a description of the track irregularities.

Remote sensing-based dynamic monitoring and environmental change of wetlands in southern Mongolian Plateau in 2000‒2018

The environmental change in the wetlands in the southern Mongolian Plateau has important impacts on the environment of North China and even the entire Northeast Asia,from which the global climate change can be understood on a large scale,especially the climate change in the Mongolian Plateau.This study extracted the information on the wetlands from three stages of remote sensing images(also referred to as RS images)of the study area,including Enhanced Thematic Mapper Plus(ETM+)images of 2000,TM images of 2010,and Landsat 8 Operational Land Imager(OLI)images of 2018.As indicated by the extraction results,the area of wetlands decreased from 796.90 km^(2) of 2000 to 666.24 km^(2) of 2018 at a rate of 7.26 km^(2)/a.The reduced area is 130.66 km^(2),which is about 16.4%reduction.And the patch number of wetlands decreased from 731 of 2000 to 316 of 2018 in the study area,approximately 56.8%reduction(415 patches),and the decrease in the area of the wetlands mainly occurred in the northwest endorheic region.In terms of wetland types,the change of the wetlands was dominated by the decrease of lacustrine wetlands,of which the area and patch number decreased by 106.2 km^(2) and 242,respectively.Furthermore,the area of the lacustrine wetlands decreased at the highest rate of 8.70 km^(2)/a in 2010‒2018.From the perspective of spatial distribution,the wetlands in the western part shrunk more notably than those in the eastern part as a whole in the study area.According to local meteorological data,the precipitation gently decreased and the temperature increased(about 1.7℃)from 1975-2018.Overall,the decrease in the area of the wetlands and the temperature rises in the study area were mainly driven by the Mongolian monsoon climate,reduction in precipitation,and human activities.

Proactive Spectrum Monitoring for Suspicious Wireless Powered Communications in Dynamic Spectrum Sharing Networks

This paper studies the proactive spec-trum monitoring with one half-duplex spectrum moni-tor(SM)to cope with the potential suspicious wireless powered communications(SWPC)in dynamic spec-trum sharing networks.The jamming-assisted spec-trum monitoring scheme via spectrum monitoring data(SMD)transmission is proposed to maximize the sum ergodic monitoring rate at SM.In SWPC,the suspi-cious communications of each data block occupy mul-tiple independent blocks,with a block dedicated to the wireless energy transfer by the energy-constrained suspicious nodes with locations in a same cluster(symmetric scene)or randomly distributed(asymmet-ric scene)and the remaining blocks used for the in-formation transmission from suspicious transmitters(STs)to suspicious destination(SD).For the sym-metric scene,with a given number of blocks for SMD transmission,namely the jamming operation,we first reveal that SM should transmit SMD signal(jam the SD)with tolerable maximum power in the given blocks.The perceived suspicious signal power at SM could be maximized,and thus so does the correspond-ing sum ergodic monitoring rate.Then,we further reveal one fundamental trade-off in deciding the op-timal number of given blocks for SMD transmission.For the asymmetric scene,a low-complexity greedy block selection scheme is proposed to guarantee the optimal performance.Simulation results show that the jamming-assisted spectrum monitoring schemes via SMD transmission achieve much better perfor-mance than conventional passive spectrum monitor-ing,since the proposed schemes can obtain more accu-rate and effective spectrum characteristic parameters,which provide basic support for fine-grained spectrum management and a solution for spectrum security in dynamic spectrum sharing network.

A Real-Time System for Monitoring Distant Dynamic Displacement of Structures

把技术基于数字图象处理，一个即时系统被开发监视并且检测设计结构的动态排水量。由用一个自我规划的软件处理图画，在某个坐标系统的一个目标的即时坐标能也被获得，并且推进动态排水量数据和目标罐头的曲线被完成。数据的也就是说自动的聚会并且即时处理能被这个系统同时执行。首先，为这个系统，一种未触动过的监视技术被采用，罐头它监视或检测目标几到几百米分开；第二，它有灵活安装状况和亚毫米度的好监视精确；第三，它是合适的为动态、伪动态、静态大工程结构监视。通过大桥的几测试和应用程序，系统的好可靠性和优势被证明。

Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.

Current Working Situation and Countermeasures of Dynamic Monitoring of Geothermal Resource Exploitation and Utilization in Tianjin

Dynamic monitoring is an important basic work in the sustainable exploitation and utilization of geothermal resources.It offers basic data for geothermal management department to make out the plan of geothermal resources by collecting and analyzing the outdoor dynamic monitoring data. Tianjin is one of the earliest cities in exploiting and utilizing geothermal resources,and the

DESIGN AND APPLICATION OF DYNAMIC MONITORING AND VISUALIZATION MANAGEMENT INFORMATION SYSTEM OF KARST LAND ROCKY DESERTIFICATION

In order to study the spatial-temporal change and environmental management of regional karst LUCC (land use and land cover change) and its causative environmental effect-rocky desertification by integrating qualitative analysis and quantitative analysis, and relying on RS, GIS and GPS (3S) techniques, karst land rocky derification dynamic monitoring and visualization management information system (KLRD.DMVM.IS) is framed, which includes design aim and structure model, function design, database design and model system design. The model system design gives priority to dynamic monitoring, drive force diagnosis, comprehensive evaluation and decision support of karst rocky desertification. From the viewpoint of model type, mathematic expression and its meaning, the dynamic monitoring models are concretely devised to reflect the spatial and temporal changing features and the trend of karst LUCC and rocky desertification. Taking Du'an Yao Autonomic County of Guangxi as an example, the KLRD.DMVM.IS is systematically analyzed in the application of the process and trend of karst LUCC and rocky desertification in Du'an County, and it provides the technical support for the study on karst land rocky desertification.

Dynamic model for landsliding monitoring under rigid body assumption

Based on the assumption that the slope bodies are rigid, the dynamic model of the landsiding (forward model) was put forward. According to the dynamic model, the system equations of Kalman filter were constituted. The mechanical status of a slope was hence combined with the monitoring data by Kalman filter. The model uncertainties or model errors could also be considered through some fictitious observation equations. Different from existed methods, the presented method can make use for not only the statistic information contained in the data but also the information provided by the mechanical and geological aspect of slopes. At last a numerical example was given out to show the feasibility of the method. [

Non-derivative solution to nonlinear dynamic optimal design of class two for deformation network monitoring

Based on the nonlinear error equation of deformation network monitoring, the mathematical model of nonlinear dynamic optimal design of class two was put forward for the deformation network monitoring, in which the target function is the accuracy criterion and the constraint conditions are the network’s sensitivity, reliability and observing cost. Meanwhile a new non derivative solution to the nonlinear dynamic optimal design of class two was also put forward. The solving model uses the difference to stand for the first derivative of functions and solves the revised feasible direction to get the optimal solution to unknown parameters. It can not only make the solution to converge on the minimum point of the constraint problem, but decrease the calculating load.

A RESEARCH ON THE DYNAMIC MONITORING SYSTEM FOR FORAGE-LIVESTOCK BALANCE IN THE TEMPERATE CRASSLAND OF CHINA

Some principles and methods for the dynamic monitoring of forage-livestock bal-ance in the grazing system on the temperate grassland of China were discussed in thispaper. To prepare a dynamic monitoring system or the forage livestock balance of grazingrangeland system, the following theoretical bases will be observed in this work.