Perihematoma Damage at Different Time Points in Experimental Intracerebral Hemorrhage

The damage degree of neurons in perilesion at different time points was observed in order to explore the optimal operation occasion. Piglet lobar hematomas were produced by pressure-controlled infusions of 2.5 mL autonomous blood into the right frontal hemispheric white matter over 15 min, and the metabolic changes were ambulatorily detected with MRS at 3rd, 12th, 24th and 48th h after hematoma induction. Brain tissues of perihematoma were also obtained at different time points. The transcription level of Bax gene was detected by in situ hybridization and apoptosis by TUNEL technique, and the pathologic change of neurons was observed under an electron microscope. The results showed that the number of Bax positive cells reached the peak at 24 h （79.00± 4.243/5 fields）. There was no significant difference in A values between 3 h and 6 h, 12 h （P〉 0. 05）, but there significant difference between 24 h and 3 h, 6 h, 12 h （P〈0. 05）. The number of apoptotic cells reached the peak at 24 h （P〈0. 001）, and there was no significant difference between 3 h and 6 h （P=0. 999）. The area of the apoptotic cells showed no significant difference between 3 h and 6 h or among 3 h, 6 h and 6 h （P〉0.05）. Lac peak mainly occurred at 24 h and 48 h, while on the healthy side, no Lac peak was detectable. The ratio of NAA/Cr presented a descent tendency, but there was no significant difference among the groups before 12 h （P〉0. 05）, there was very significant difference between 3, 6 and 24, 48 h （P〈0. 01）. Under electronic microscopy, the neuronal damage surrounding hematoma in 3 to 6 h was milder than in 24 h to 48 h. It was concluded that the secondary apoptosis, damage and metabolic disturbance of the neurons surround- ing hematoma was milder in 3-6 h in acute intracerebral hemorrhage, while obviously aggravated in 24-48 h. An effective intervention is needed to reduce secondary damage as soon as possible.

Study on the development and usage of a cardiopulmonary resuscitation time point recorder

BACKGROUND: To invent a novel cardiopulmonary resuscitation(CPR) time point recorder to synchronously and automatically record the time and to identify its effectiveness in humans.METHODS: A CPR time point recorder was invented after the doctors were familiar with the traditional Utstein recovery registration mode and mastered the registration time points required. The progress of CPR was simulated. The standard and correct times were recorded, and the doctors performing the recovery collected the data about the times using our CPR time point recorder or the memory registration mode.RESULTS: The deviation times were 21.4±24.7 seconds for the memory group and 3.57±4.58 seconds for CPR time point recorder group. The deviation of times increased signifi cantly depending on the increase of the operation items in the memory group. A similar phenomenon was found in the timer group but with a smaller difference(P<0.01).CONCLUSION: A CPR time point recorder could reduce the deviation of operate-time, especially after a long-time operation, and for procedures with more operating items, compared with the memory mode. It was a more advantageous and accurate method for the Utstein registration.

Optimal time point for the transplantation of neural stem cells induced to differentiate with retinoic acid

Previous studies have demonstrated that differentiated neural stem cells （NSCs） are more suitable for transplantation than non-differentiated NSCs. In this study, NSCs were expanded in vitro for two passages, induced with retinoic acid to differentiate, and harvested between 1 6 days later. They were subsequently cultured in artificial cerebrospinal fluid for an additional 3 days, dudng which their growth and morphology was monitored. NSCs induced for 4 days exhibited a peak rate of cells differentiating into neurons and robust growth. Our results indicate that the optimal time point for transplanting NSCs is following a 4-day period of induced differentiation.

Dual time point FDG PET imaging in evaluating pulmonary nodules with low FDG avidity

A standardized uptake value(SUV) of 2.5 is frequently used as criteria to evaluate pulmonary lesions.However,false results may occur.Some studies have shown the usefulness of delayed PET for improving accuracy,while others recently have shown fewer promising results.This study was designed to investigate the accuracy of dual time point(DTP) FDG PET imaging in the evaluation of pulmonary lesions with an initial SUV less than 2.5.DTP FDG PET studies were conducted about 1 and 2 hours after FDG injection,and pulmonary lesions with an initial SUV less than 2.5 were identified.Nodules with pathologic results or imaging follow up were included.The differences in SUV and retention index(RI) between benign and malignant pulmonary lesions were analyzed.Receiver operating characteristics(ROC) analysis was performed to evaluate the discriminating validity of SUV and RI.51 lesions were finally included.A RI greater than 0% was observed in 64% of the benign lesions;56% had a RI greater than 10%.Among the malignancies,80.8% had a RI greater than 0%,and 61.5% had a RI greater than 10%.We found no significant differences in SUV and RI between benign and malignant lesions.The area under the ROC curve did not differ from 0.5 whether using SUV or the retention index.Utilizing a SUV increase of 10%,the sensitivity was 61.5%,specificity 44% and accuracy was 52.9%.Dual time point FDG PET may not be of benefit in the evaluation of pulmonary nodules with low FDG avidity.

An Early-Stop Adjoint Transient Sensitivity Analysis Method for Objective Functions Associated with Many Time Points

Transient sensitivity analysis aims to obtain the gradients of objective functions(circuit performance)with respect to design or variation parameters in a simulator,which can be widely used in yield analysis and circuit optimization,among others.However,the traditional method has a computational complexity of O(N^(2))for objective functions containing circuit states at N time points.The computational complexity is too expensive for large N,especially in time-frequency transform.This paper proposes a many-time-point sensitivity method to reduce the computational complexity to O(N)in multiparameter many-time-point cases.The paper demonstrates a derivation process that improves efficiency by weighting the transfer chain and multiplexing the backpropagation process.We also proposed an early-stop method to improve efficiency further under the premise of ensuring accuracy.The algorithm enables sensitivity calculation of performances involving thousands of time points,such as signal-to-noise and distortion ratio and total harmonic distortion,with significant speed improvements.

Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Improving the detecting efficiency of suspected gastrointestinal tumors with dual-time-point 18F-FDG PET/CT

We conducted a retrospective analysis of 221 subjects with 256 suspected gastrointestinal lesions from2007 to 2015 to explore the detecting efficiency of dualtime-point fluorine-18 fludeoxyglucose(^(18)F-FDG) positron emission tomography/computed tomography(PET/CT)and pathology examination. The abdominal delayed PET/CT was performed within 45 min of the conventional scan.The change in maximum standardized uptake value(ASUV_(max)) and morphological features of the suspected lesions between the conventional and dual-time-point PET/CT were compared. The sensitivity, specificity, positive predictive value, and negative predictive value(NPV) of conventional PET/CT were 81.6%(84/103), 56.2%(86/153), 55.6%(84/151), and 81.9%(86/105), respectively.Those of dual-time-point PET/CT were 94.1%(97/103),78.4%(120/153), 74.6%(97/130), and 95.2%(120/126),respectively. There was a significant difference between the conventional and dual-time-point PET/CT(P < 0.005).The SUV_(early) and the %△SUV_(max) could not present more information in differential diagnoses, but the rate of tumors with increased SUVdelay accounted for 79.6%(82/103) and more than that of nonneoplastic lesions(15.5%, 29/187)(x^2= 115.5, P < 0.01). Therefore, the dual-time-point^(18)F-FDG PET/CT had a higher sensitivity and NPV than the conventional PET/CT to detect gastrointestinal tumors.The constant morphology and increased SUV_(delay) help to detect the tumors and adding delayed imaging on the locality will be an effective method when we accidentally find a suspected gastrointestinal tumor on the conventional PET/CT images.

Time Sequence Change-Point Model of Electrostatic State Parameters of Aircraft Engine

Electrostatic monitoring technology of particle charging information can facilitate online monitoring of aero-engine,which effectively enhances engine fault diagnosis and health managements.Unlike traditional engine state monitoring technologies,aircraft engine monitoring by gas path electrostatic monitoring not only covers the predicted information source itself,but also detects the information that can provide an early warnings for initial fault states through gas path charging levels.This paper establishes a non-stationary time sequence change-point model for anomaly recognition of electrostatic signals based on change-point theory combined with difference method of non-stationary time series.Finally,electrostatic induction data were utilized by the engine life test for a particular aircraft to validate the proposed algorithm.The results indicate that the activity level and the event rate were0.5—0.8(nc)and 50%,respectively,which were far greater than 4—12(pc)and 0—4% under normal working conditions of the engine.

THE INFLUENCE OF ELECTRO-ACUPUNCTURE AT NEIGUAN AND FIVE SHU POINTS OF TWELVE REGULAR MERIDIANS AT DIFFERENT TIME ON SYSTOLIC TIME INTERVAL OF NORMAL YOUNG ADULTS

The influence of electro-acupuncture at Neiguan (PC 6)and five shu points of twelve regular meridians at different time on systolic time interval (ST I) of normal young adultswere studied with 6×6 Latin square design in this work.In 12 groups according to 12 regular merldlans,the STIs were measured respectively just before and after electro-acupuncture on Neiguan andfive shu points at 00:00,04:00,08:00,12:00,16:00 and 20:00 of a day.It was found thatexcept the PEPI and PEPI/LVETI ratio among Shenmen(HT 7),Shaochong(HT 9)and Neiguan,Guanchong(TE)and Yemen(TE 2)points,the effects of electro-acupuncture at Neiguan pointand five shu points of twelve regular meridians on the indices of STI of normal young adults wereshowing no slgnificant differences.There also was no difference in different sex.But the indices ofSTI were changed when electroacupuncture on the different points of different meridians at differenttime.

On-line outlier and change point detection for time series

The detection of outliers and change points from time series has become research focus in the area of time series data mining since it can be used for fraud detection, rare event discovery, event/trend change detection, etc. In most previous works, outlier detection and change point detection have not been related explicitly and the change point detections did not consider the influence of outliers, in this work, a unified detection framework was presented to deal with both of them. The framework is based on ALARCON-AQUINO and BARRIA's change points detection method and adopts two-stage detection to divide the outliers and change points. The advantages of it lie in that: firstly, unified structure for change detection and outlier detection further reduces the computational complexity and make the detective procedure simple; Secondly, the detection strategy of outlier detection before change point detection avoids the influence of outliers to the change point detection, and thus improves the accuracy of the change point detection. The simulation experiments of the proposed method for both model data and actual application data have been made and gotten 100% detection accuracy. The comparisons between traditional detection method and the proposed method further demonstrate that the unified detection structure is more accurate when the time series are contaminated by outliers.

Analysis of Change Point in Surface Temperature Time Series Using Cumulative Sum Chart and Bootstrapping for Asansol Weather Observation Station, West Bengal, India

This paper aims to detect the short-term as well as long-term change point in the surface air temperature time series for Asansol weather observation station, West Bengal, India. Temperature data for the period from 1941 to 2010 of the said weather observatory have been collected from Indian Meteorological Department, Kolkata. Variations and trends of annual mean temperature, annual mean maximum temperature and annual minimum temperature time series were examined. The cumulative sum charts (CUSUM) and bootstrapping were used for the detection of abrupt changes in the time series data set. Statistically significant abrupt changes and trends have been detected. The major change point in the annual mean temperatures occurred around 1986 (0.57°C) at the period of 25 years in the long-term regional scale. On the other side, the annual mean maximum and annual mean minimum temperatures have distinct change points at level 1. There are abrupt changes in the year 1961 (Confidence interval 1961, 1963) for the annual mean maximum and 1994 (Confidence interval 1993, 1996) for the annual mean minimum temperatures at a confidence level of 100% and 98%, respectively. Before the change, the annual mean maximum and annual mean minimum temperatures were 30.90°C and 23.99°C, respectively, while after the change, the temperatures became 33.93°C and 24.84°C, respectively. Over the entire period of consideration (1941-2010), 11 forward and backward changes were found in total. Out of 11, there are 3 changes (1961, 1986 and 2001) in annual mean temperatures, 4 changes (1957, 1961, 1980 and 1994) in annual mean maximum temperatures, and rest 4 changes (1968, 1981, 1994 and 2001) are associated with annual mean minimum temperature data set.

Stereo Matching of Planar Curves Composed of Time Stamped Points

Matching features such as curve segments in stereo images play a very important role in scene recomtruction. In this paper, a stereo matching algorithm for the trajectories composed of time stamped points is proposed. Based on time stamped points, planar curve match measurements are given first, such as time constraint, cross-ratio invariant constraint and eplpolar geometry constraint; then, a trajectory matching method is proposed based on epipolar geometry constraint and cross-ratio invariant constraint. In order to match the planar curve segments projected by perspective projection system, the curve start time and end time are selected first to prepare match candidates. Then, the epipolar equation is used to discard the unmatched curve segment candidates. At last, a cross ratio invariant constxaint is used to find the most matched curve segments. If their match measurement is higher than the specialized threshold, a candidate with the least cross ratio difference is then selected as the match result; otherwise, no match is found. Unlike the conventional planar curve segments matching algorithm, this paper presents a weakly calibrated binocular stereo vision system which is based on wide baseline. The stamped points are obtained by targets detecting method of flying objects from image sequences. Due to wide baseline, there must exist the projection not in epipolar monotonic order or the curve segments located in very short distance and keeping the epipolar monotonic order. By using the method mentioned above, experiments are made to match planar curve segments not only in epipolar monotonic order but also not in epipolar monotonic order. The results show that the performance of our curve matching algorithm is effective for matching the arc-like planar trajectories composed of time stamped points.

Automatic Feature Point Detection and Tracking of Human Actions in Time-of-flight Videos

Detecting feature points on the human body in video frames is a key step for tracking human movements. There have been methods developed that leverage models of human pose and classification of pixels of the body image. Yet, occlusion and robustness are still open challenges. In this paper, we present an automatic, model-free feature point detection and action tracking method using a time-of-flight camera. Our method automatically detects feature points for movement abstraction. To overcome errors caused by miss-detection and occlusion, a refinement method is devised that uses the trajectory of the feature points to correct the erroneous detections. Experiments were conducted using videos acquired with a Microsoft Kinect camera and a publicly available video set and comparisons were conducted with the state-of-the-art methods. The results demonstrated that our proposed method delivered improved and reliable performance with an average accuracy in the range of 90 %.The trajectorybased refinement also demonstrated satisfactory effectiveness that recovers the detection with a success rate of 93.7 %. Our method processed a frame in an average time of 71.1 ms.

Data point selection for weighted least square fitting of cavity decay time constant

For the accurate extraction of cavity decay time, a selection of data points is supplemented to the weighted least square method. We derive the expected precision, accuracy and computation cost of this improved method, and examine these performances by simulation. By comparing this method with the nonlinear least square fitting （NLSF） method and the linear regression of the sum （LRS） method in derivations and simulations, we find that this method can achieve the same or even better precision, comparable accuracy, and lower computation cost. We test this method by experimental decay signals. The results are in agreement with the ones obtained from the nonlinear least square fitting method.

Polynomial-time interior-point algorithm based on a local self-concordant finite barrier function

The choice of self-concordant functions is the key to efficient algorithms for linear and quadratic convex optimizations, which provide a method with polynomial-time iterations to solve linear and quadratic convex optimization problems. The parameters of a self-concordant barrier function can be used to compute the complexity bound of the proposed algorithm. In this paper, it is proved that the finite barrier function is a local self-concordant barrier function. By deriving the local values of parameters of this barrier function, the desired complexity bound of an interior-point algorithm based on this local self-concordant function for linear optimization problem is obtained. The bound matches the best known bound for small-update methods.

Simulation on the Time Progress of the Non-Point Source Pollution Load in Initial Stage Runoff for Small Watershed

Taking a reservoir in South China as an example, we use rainfall-runoff unit hydrograph method to analyze the time changing process of surface runoff inflow, which generated by typical design rainfall. On the basis of time series data of flow and water quality in control section of the main rivers in Xili Reservoir, we establish mathematical response relation between non-point source pollutants flux, such as flux of COD, flux of NH3-H, in catchment area of control section and runoff. Then we simulate the time dynamic change progress of non-point source pollution load which generate with the initial stage runoff that generated by design rainfall and flow into reservoir. It can provide technical parameters for the design of non-point source which generate from early runoff treatment project.

基于定位二维码技术构建急性缺血性脑卒中流程管理模式

目的基于定位二维码技术构建急性缺血性脑卒中流程管理模式,并探索其临床应用价值。方法比较管理模式应用前后急性缺血性脑卒中患者静脉溶栓总用时及各时间节点用时、住院天数及住院费用等,同时比较模式应用前后急诊科护士护理记录书写用时、书写错误及缺陷等。结果基于定位二维码技术构建的急性缺血性脑卒中流程能有效缩短DNT(P<0.001),模式应用后护理记录书写时间明显缩短(P<0.001),书写质量提高。结论通过定位二维码技术可实现流程数据精确抓取,在生成流程时间轴的同时可生成相应护理记录,为卒中流程质量改进提供了数据支持,对高级卒中中心的建立有借鉴价值。

实时PPP离岸潮位遥测方法与试验

为降低离岸潮位实时遥测成本,提高适用性,提出了基于实时精密单点定位的离岸潮位数据获取与提取方法,利用小型浮标搭载具有实时PPP和远程通讯功能的GNSS接收机进行离岸潮位遥测,原始观测数据经粗差剔除、均值化处理、S-G滤波后,较好地剔除了风、浪、流等引起浮标姿态变化所带来的测量误差。研发了相应软硬件,并在天津港外海进行了试验,测试结果优于±8cm,整体中误差为±3.7cm,满足海洋观测规范要求。相较基于压力式传感器加声学通信的现行数据采集方式,该方法具有建设成本较低、观测方式简单、后期维护方便、产业化前景好等特点,可进一步在实际项目中推广使用。

基于射频识别技术的笼养雏鸡运动监测研究

为了解笼养雏鸡的运动行为和健康状况,研究设计了一种基于射频识别技术(RFID)的笼养鸡个体实时运动监测系统。研究首先搭建了一个模拟的试验环境,其包括一个超高频的射频识别读写器,三个天线和若干标签,一台计算机以及射频识别读写软件;随后使用机器学习的方法拟合出当前环境下不同天线接收信号强度与距离之间的关系,并进行性能比较;通过对数据进行预处理,使用获得的距离模型计算出标签与不同天线之间的距离,使用多点定位计算出所建立坐标系下标签的位置信息,实现对不同标签的运动轨迹可视化。结果显示,选定的6个电子标签测试时间为30 min,标签的计算位置与真实位置的最小欧式误差距离为4.52 cm,所有测试点的平均误差距离为9.56 cm;对比标签的真实运动轨迹和计算运动轨迹,RFID监测系统能够动态地识别活动量减少或不活动的病鸡。研究表明,基于RFID建立的笼养鸡个体实时运动检测系统能够实时监测笼养鸡个体活动情况,为家禽健康监测和疾病预防提供技术支持。

碳排放权交易政策降低了高污染行业企业债务融资成本吗——基于多时点DID的检验

自2013年始实施碳排放权交易政策以来,高污染行业企业生产发展受到显著影响。采用多时点DID模型,以2009-2020年A股上市高污染行业企业数据为基础,检验碳排放权交易政策对高污染行业企业债务融资成本的影响。研究发现:碳排放权交易政策的实施对高污染行业企业债务融资成本起到了节约作用;碳排放权交易政策能够通过缓解融资约束和促进企业技术创新降低高污染行业企业的融资成本;内部控制质量高和媒体关注度高的高污染行业企业债务融资成本相对更低;中西部地区、中小规模高污染行业企业债务融资成本对碳排放权交易政策反应更为灵敏。本研究从企业微观经济视角补充了碳排放权交易政策的试行成果,为完善碳排放权交易运行机制,实现高污染行业企业减排、降本增效设计提供了理论依据。