Introduction: The objective of this work was to study maternal deaths noted on arrival in the Gynecology and Obstetrics Department at Fousseyni Daou Hospital in Kayes over a period of 10 years. Materials and Methods: ...Introduction: The objective of this work was to study maternal deaths noted on arrival in the Gynecology and Obstetrics Department at Fousseyni Daou Hospital in Kayes over a period of 10 years. Materials and Methods: This was a cross-sectional, descriptive study with data collection over a period of 10 years;The data collection was retrospective over nine years from January 1, 2013 to December 31, 2021 and prospective over one year from January 1, 2022 to December 31, 2022. This study focused on all patients whose death was noted on arrival during pregnancy, labor or in the postpartum period in the Gynecology-Obstetrics Department of Fousseyni Daou Hospital. Confidentiality and anonymity were respected. The processing and analysis of statistical data were carried out using SPSS 20.0 software. Results: During the study period, we recorded 93 cases of death noted on arrival out of a total of 606 maternal deaths, i.e., a frequency of 15.34%. The average age was 27 years with the extremes of 20 years and 34 years. They came mainly from rural areas at 74%, were married at 82%, uneducated at 51.6%, housewives at 87.1%. The profession of the spouses is worker at 37.6%. In our sample, evacuated patients were the most represented with 75.3%. Postpartum hemorrhage was the most frequent reason for admission with 22.6%. The deceased patients had no medical history at 86%. In our series, 59.5% of the deceased patients had not had antenatal consultations (CPN). Patients who died on arrival and who had given birth at home were the most represented with 54.8%. Deaths from immediate postpartum hemorrhage complicated by shock were the most frequent with 25.8% followed by severe anemia 8.6%. Deaths were mainly due to direct obstetric causes at 76.3%. In these deaths observed on arrival, the 2nd delay was identified at 48.4%. Conclusion: Maternal deaths observed on arrival remain frequent in the Kayes region. The main causes are immediate postpartum hemorrhage and anemia, which are almost all preventable causes of maternal death following the 1st and 2nd delay.展开更多
This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses.We exa...This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses.We examine the contemporaneous relationships using correlation coefficient analysis,and find apparent differences between the information flow-return volatility relationship and the information flowtrading volume relationship.The empirical evidence contradicts the mixture of distribution hypothesis(MDH)and suggests that the rate of information flow distinctly affects trading volume and volatility.We conducted linear and nonlinear Granger causality tests to explore the sequential information arrival hypothesis(SIAH).The empirical results prove that a lead-lag linear and nonlinear causality exists between the information flow and return volatility of commodity futures,which is consistent with SIAH.In other words,a partial equilibrium exists before reaching the ultimate equilibrium when the new information arrives in the market.Finally,these findings are robust to alternative measurement of return volatility and subperiod analysis.Our findings reject the MDH and support the SIAH in the context of Chinese commodity futures.展开更多
Serious stretch appears in shallow long offsset signals after NMO correction. In this article we study the generation mechanism of NMO stretch, demonstrate that the conventional travel time equation cannot accurately ...Serious stretch appears in shallow long offsset signals after NMO correction. In this article we study the generation mechanism of NMO stretch, demonstrate that the conventional travel time equation cannot accurately describe the travel time of the samples within the same reflection wavelet. As a result, conventional NMO inversion based on the travel time of the wavelet＇s central point occurs with errors. In this article, a travel time equation for the samples within the same wavelet is reconstructed through our theoretical derivation （the shifted first arrival point travel time equation）, a new NMO inversion method based on the wavelet＇s first arrival point is proposed. While dealing with synthetic data, the semblance coefficient algorithm equation is modified so that wavelet first arrival points can be extracted. After that, NMO inversion based on the new velocity analysis is adopted on shot offset records. The precision of the results is significantly improved compared with the traditional method. Finally, the block move NMO correction based on the first arrival points travel times is adopted on long offset records and non-stretched results are achieved, which verify the proposed new equation.展开更多
目的调查国内医学论文中涉及动物实验报告的规范现状,以提升医学科研论文的报告透明度。方法本研究以中国知网数据库(CNKI)中北大核心收录期刊为数据来源,采用预先确定的文献检索策略,筛选2019年和2022年发表的文献。对纳入文献中涉及...目的调查国内医学论文中涉及动物实验报告的规范现状,以提升医学科研论文的报告透明度。方法本研究以中国知网数据库(CNKI)中北大核心收录期刊为数据来源,采用预先确定的文献检索策略,筛选2019年和2022年发表的文献。对纳入文献中涉及《动物研究:体内实验报告》(Animal research:reporting of in vivo experiments,ARRIVE)指南关键10条中的6个项目(研究设计、样本量、随机化、盲法、统计方法和实验动物资料)以及推荐11条中的3个项目(摘要、伦理声明和利益冲突声明)共计22条主要信息的报告率进行统计分析。结果共纳入文献共4818篇,未发现任何一篇文献全面报告了本研究所调查的22条相关信息。2019年和2022年发表的绝大多数论文均报告了对照组,报告率分别为99.8%(2461/2467)和99.7%(2343/2351),样本量的报告率分别为79.2%(1954/2467)和77.2%(1815/2351),所有论文均未报告样本量的计算方法和依据,随机化方法报告率约为20%,盲法报告率约为1%;2022年对统计学方法的报告(96.4%)比2019年略有增加(91.8%);2019年和2022年对动物来源(93.8%vs.93.7%,P>0.05)、品种/品系(99.1%vs.99.2%,P=0.514)、性别(94.1%vs.92.7%,P=0.044)、年龄(58.1%vs.70.6%,P<0.001)、体质量(84.4%vs.81.9%,P=0.020)、健康证明(66.0%vs.75.5%,P<0.001)等实验动物资料信息的报告程度存在不同的差异。2019年和2022年文献报告动物伦理审查(15.8%vs.38.9%)或描述遵守的动物伦理原则(9.8%vs.21.3%)、利益冲突声明(2.3%vs.10.6%)、摘要中准确报告动物相关信息(9.16%vs.8.13%)程度均较低。其中,与2019年相比较,2022年动物伦理和利益冲突声明报告程度增加(P<0.001)。结论虽然自ARRIVE 2.0发布以来,大多数项目清单报告透明度明显改善。然而,随机化方法、盲法、动物伦理以及利益冲突的报告程度仍需进一步提升,这些是未来的重点努力方向。展开更多
This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the b...This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.展开更多
How to predict the bus arrival time accurately is a crucial problem to be solved in Internet of Vehicle. Existed methods cannot solve the problem effectively for ignoring the traffic delay jitter. In this paper,a thre...How to predict the bus arrival time accurately is a crucial problem to be solved in Internet of Vehicle. Existed methods cannot solve the problem effectively for ignoring the traffic delay jitter. In this paper,a three-stage mixed model is proposed for bus arrival time prediction. The first stage is pattern training. In this stage,the traffic delay jitter patterns(TDJP)are mined by K nearest neighbor and K-means in the historical traffic time data. The second stage is the single-step prediction,which is based on real-time adjusted Kalman filter with a modification of historical TDJP. In the third stage,as the influence of historical law is increasing in long distance prediction,we combine the single-step prediction dynamically with Markov historical transfer model to conduct the multi-step prediction. The experimental results show that the proposed single-step prediction model performs better in accuracy and efficiency than short-term traffic flow prediction and dynamic Kalman filter. The multi-step prediction provides a higher level veracity and reliability in travel time forecasting than short-term traffic flow and historical traffic pattern prediction models.展开更多
To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband ...To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.展开更多
目的通过评价中药复方防治胃癌前病变(PLGC)动物实验研究的方法学质量及报告质量,分析实验过程中的偏倚风险及研究报告的不足,为提高中药复方防治PLGC动物实验研究质量提供参考。方法计算机检索中国知识资源总库(CNKI)、万方数据知识服...目的通过评价中药复方防治胃癌前病变(PLGC)动物实验研究的方法学质量及报告质量,分析实验过程中的偏倚风险及研究报告的不足,为提高中药复方防治PLGC动物实验研究质量提供参考。方法计算机检索中国知识资源总库(CNKI)、万方数据知识服务平台(WanfangData)、中文科技期刊数据库(VIP)、中国生物医学文献数据库(CBM)、PubMed、Cochrane Library、Web of Science和Embase数据库2014年1月1日-2024年2月23日发表的关于中药复方防治PLGC动物实验文献,采用SYRCLE工具和ARRIVE2.0指南对纳入文献进行评分并计算各条目“低风险”符合率。结果共纳入文献213篇,其中中文文献189篇、英文文献24篇。SYRCLE工具评分为(12.86±1.29)分,“低风险”符合率为32.79%。ARRIVE2.0指南必备条目评分为(24.15±2.80)分,“低风险”符合率为49.08%;推荐条目评分为(11.28±3.40)分,“低风险”符合率为30.27%。SYRCLE工具评价中,144项(67.61%)研究未详细阐述分配序列产生的方法,所有研究均未描述分配隐藏充分与否及实施偏倚过程中的盲法,7项(3.29%)研究描述对结果评价者施盲。ARRIVE2.0指南中,所有研究均未报告样本量的确定方法、均未提供用于确定样本量的结局指标及实验方案注册声明,51项(23.94%)研究明确提出PLGC造模成功标准,66项(30.96%)研究提供所使用统计方法的详细信息,29项(13.62%)研究提供完整的伦理声明,22项(10.33%)报告了利益冲突。结论2014-2024年发表的中药复方防治PLGC动物实验文献方法学质量及报告质量存在较多问题,尤其是在实验过程中随机盲法策略的实施、样本量计算细节及纳入排除标准报告等方面存在缺陷,建议今后研究参考SYRCLE工具及ARRIVE2.0指南清单,以优化研究方案和报告,提高PLGC动物实验研究结果的可信度与规范性。展开更多
Free electron lasers provide high-power and ultrashort pulses with extreme brightness. In order to improve a facility's capabilities and explore the possibility of performing high-resolution time-resolved experime...Free electron lasers provide high-power and ultrashort pulses with extreme brightness. In order to improve a facility's capabilities and explore the possibility of performing high-resolution time-resolved experiments, a beam arrival time resolution under 100 fs is required. In this article, a novel beam arrival time monitor(BAM)equipped with two cavities has been designed and a beam flight time measurement scheme based on the BAM prototype has been proposed to estimate phase jitter in the signal measurement system. The two BAM cavities work at different frequencies and the frequency difference is designed to be 35 MHz. Therefore, a self-mixing intermediate frequency signal can be generated using the two cavities. The measured beam flight time shows a temporal deviation of 37 fs(rms).展开更多
Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current...Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.展开更多
In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of ...In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.展开更多
In seismic data processing,picking of the P-wave first arrivals takes up plenty of time and labor,and its accuracy plays a key role in imaging seismic structures.Based on the convolution neural network(CNN),we propose...In seismic data processing,picking of the P-wave first arrivals takes up plenty of time and labor,and its accuracy plays a key role in imaging seismic structures.Based on the convolution neural network(CNN),we propose a new method to pick up the P-wave first arrivals automatically.Emitted from MINI28 vibroseis in the Jingdezhen seismic experiment,the vertical component of seismic waveforms recorded by EPS 32-bit portable seismometers are used for manually picking up the first arrivals(a total of 7242).Based on these arrivals,we establish the training and testing sets,including 25,290 event samples and 710,616 noise samples(length of each sample:2 s).After 3,000 steps of training,we obtain a convergent CNN model,which can automatically classify seismic events and noise samples with high accuracy(>99%).With the trained CNN model,we scan continuous seismic records and take the maximum output(probability of a seismic event)as the P-wave first arrival time.Compared with STA/LTA(short time average/long time average),our method shows higher precision and stronger anti-noise ability,especially with the low SNR seismic data.This CNN method is of great significance for promoting the intellectualization of seismic data processing,improving the resolution of seismic imaging,and promoting the joint inversion of active and passive sources.展开更多
In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is prop...In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.展开更多
Fast and accurate P-wave arrival picking significantly affects the performance of earthquake early warning(EEW)systems.Automated P-wave picking algorithms used in EEW have encountered problems of falsely picking up no...Fast and accurate P-wave arrival picking significantly affects the performance of earthquake early warning(EEW)systems.Automated P-wave picking algorithms used in EEW have encountered problems of falsely picking up noise,missing P-waves and inaccurate P-wave arrival estimation.To address these issues,an automatic algorithm based on the convolution neural network(DPick)was developed,and trained with a moderate number of data sets of 17,717 accelerograms.Compared to the widely used approach of the short-term average/long-term average of signal characteristic function(STA/LTA),DPick is 1.6 times less likely to detect noise as a P-wave,and 76 times less likely to miss P-waves.In terms of estimating P-wave arrival time,when the detection task is completed within 1 s,DPick′s detection occurrence is 7.4 times that of STA/LTA in the 0.05 s error band,and 1.6 times when the error band is 0.10 s.This verified that the proposed method has the potential for wide applications in EEW.展开更多
Due to the significant effect of abnormal arrivals on localization accuracy,a novel acoustic emission(AE)source localization method using clustering detection to eliminate abnormal arrivals is proposed in the paper.Fi...Due to the significant effect of abnormal arrivals on localization accuracy,a novel acoustic emission(AE)source localization method using clustering detection to eliminate abnormal arrivals is proposed in the paper.Firstly,iterative weight estimation is utilized to obtain accurate equation residuals.Secondly,according to the distribution of equation residuals,clustering detection is used to identify and exclude abnormal arrivals.Thirdly,the AE source coordinate is recalculated with remaining normal arrivals.Experimental results of pencil-lead breaks indicate that the proposed method can achieve a better localization result with and without abnormal arrivals.The results of simulation tests further demonstrate that the proposed method possesses higher localization accuracy and robustness under different anomaly ratios and scales;even with abnormal arrivals as high as 30%,the proposed localization method still holds a correct detection rate of 91.85%.展开更多
When the information of mutual coupling and shadowing effect of a conformal antenna array are unknown, the performance of direction of arrival （DOA） estimation will be seriously degraded by using some classical meth...When the information of mutual coupling and shadowing effect of a conformal antenna array are unknown, the performance of direction of arrival （DOA） estimation will be seriously degraded by using some classical methods, such as the multiple signal classification （MUSIC） algorithm. Meanwhile it is difficult to measure or estimate the shadowing effect. The DOA estimation for a conformal uniform circular array （UCA） is studied. Firstly, the azimuthal angle is separated from all the unknown information by transforming the UCA from the element space to the mode space. Then the rank reduction （RARE） algorithm is applied in the estima- tion of the azimuthal angle. The π ambiguity existed in the RARE is solved by the beam forming. The main advantage of this method is that it does not need to measure the mutual coupling and the shadowing effect. Compared with the subarray method, it will not decrease the aperture of the array. Simulation results validate the advantages of the method.展开更多
A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport s...A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport system is defined through in-depth analysis of the characteristics of arrival and departure operations.Then,several constraints are taken into account,such as wake vortex separation,transfer separation,release separation,and separation in different runway operational modes.Furthermore,the scheduling model is constructed and simulated annealing algorithm is proposed by minimizing the total delay.Finally,Shanghai multi-airport system is chosen to conduct the simulation and validation.And the simulation results indicate that the proposed method is able to effectively improve the efficiency of arrival and departure operations for multi-airport system.展开更多
A risk model with Markovian arrivals and tax payments is considered.When the insurer is in a profitable situation,the insurer may pay a certain proportion of the premium income as tax payments.First,the Laplace transf...A risk model with Markovian arrivals and tax payments is considered.When the insurer is in a profitable situation,the insurer may pay a certain proportion of the premium income as tax payments.First,the Laplace transform of the time to cross a certain level before ruin is discussed.Second,explicit formulas for a generalized Gerber-Shiu function are established in terms of the＇original＇Gerber-Shiu function without tax and the Laplace transform of the first passage time before ruin.Finally,the differential equations satisfied by the expected accumulated discounted tax payments until ruin are derived.An explicit expression for the discounted tax payments is also given.展开更多
In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localizati...In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localization algorithm. The TDOA/FDOA (Frequency Difference of Arrival) localization algorithm is used to optimize the GDOP (geometric dilution of precision) of four-Satellite localization. The simulation results show that the absolute position measurement accuracy has little influence on TDOA/FDOA localization accuracy as compared with TDOA localization. Under the same conditions, TDOA/FDOA localization has better accuracy and its GDOP shows more uniform distribution in diamond configuration case. The localization accuracy of four-Satellite TDOA/FDOA is better than the localization accuracy of four-Satellite TDOA.展开更多
To improve the accuracy of real-time public transport information release system, a collaborative prediction model was proposed based on cyber-physical systems architecture. In the model, the total bus travel time was...To improve the accuracy of real-time public transport information release system, a collaborative prediction model was proposed based on cyber-physical systems architecture. In the model, the total bus travel time was divided into three parts: running time, dwell time and intersection delay time, and the data were divided into three categories of historical data, static data and real-time data. The bus arrival time was obtained by fusion computing the real-time data in perception layer together with historical data and static data in collaborative layer. The validity of the collaborative model was verified by the data of a typical urban bus line in Shanghai, and 1538 sets of data were collected and analyzed from three different perspectives. By comparing the experimental results with the actual results, it is shown that the experimental results are with higher prediction accuracy, and the collaborative prediction model adopted is able to meet the demand for bus arrival prediction.展开更多
文摘Introduction: The objective of this work was to study maternal deaths noted on arrival in the Gynecology and Obstetrics Department at Fousseyni Daou Hospital in Kayes over a period of 10 years. Materials and Methods: This was a cross-sectional, descriptive study with data collection over a period of 10 years;The data collection was retrospective over nine years from January 1, 2013 to December 31, 2021 and prospective over one year from January 1, 2022 to December 31, 2022. This study focused on all patients whose death was noted on arrival during pregnancy, labor or in the postpartum period in the Gynecology-Obstetrics Department of Fousseyni Daou Hospital. Confidentiality and anonymity were respected. The processing and analysis of statistical data were carried out using SPSS 20.0 software. Results: During the study period, we recorded 93 cases of death noted on arrival out of a total of 606 maternal deaths, i.e., a frequency of 15.34%. The average age was 27 years with the extremes of 20 years and 34 years. They came mainly from rural areas at 74%, were married at 82%, uneducated at 51.6%, housewives at 87.1%. The profession of the spouses is worker at 37.6%. In our sample, evacuated patients were the most represented with 75.3%. Postpartum hemorrhage was the most frequent reason for admission with 22.6%. The deceased patients had no medical history at 86%. In our series, 59.5% of the deceased patients had not had antenatal consultations (CPN). Patients who died on arrival and who had given birth at home were the most represented with 54.8%. Deaths from immediate postpartum hemorrhage complicated by shock were the most frequent with 25.8% followed by severe anemia 8.6%. Deaths were mainly due to direct obstetric causes at 76.3%. In these deaths observed on arrival, the 2nd delay was identified at 48.4%. Conclusion: Maternal deaths observed on arrival remain frequent in the Kayes region. The main causes are immediate postpartum hemorrhage and anemia, which are almost all preventable causes of maternal death following the 1st and 2nd delay.
基金supported by the National Social Science Fund of China(24CGL027)the National Natural Science Foundation of China(72101009,72141304,72201122)National Key Research and Development Program of China(2022YFC3303304).
文摘This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses.We examine the contemporaneous relationships using correlation coefficient analysis,and find apparent differences between the information flow-return volatility relationship and the information flowtrading volume relationship.The empirical evidence contradicts the mixture of distribution hypothesis(MDH)and suggests that the rate of information flow distinctly affects trading volume and volatility.We conducted linear and nonlinear Granger causality tests to explore the sequential information arrival hypothesis(SIAH).The empirical results prove that a lead-lag linear and nonlinear causality exists between the information flow and return volatility of commodity futures,which is consistent with SIAH.In other words,a partial equilibrium exists before reaching the ultimate equilibrium when the new information arrives in the market.Finally,these findings are robust to alternative measurement of return volatility and subperiod analysis.Our findings reject the MDH and support the SIAH in the context of Chinese commodity futures.
基金sponsored by the National Natural Science Foundation of China (No. 41074075)
文摘Serious stretch appears in shallow long offsset signals after NMO correction. In this article we study the generation mechanism of NMO stretch, demonstrate that the conventional travel time equation cannot accurately describe the travel time of the samples within the same reflection wavelet. As a result, conventional NMO inversion based on the travel time of the wavelet＇s central point occurs with errors. In this article, a travel time equation for the samples within the same wavelet is reconstructed through our theoretical derivation （the shifted first arrival point travel time equation）, a new NMO inversion method based on the wavelet＇s first arrival point is proposed. While dealing with synthetic data, the semblance coefficient algorithm equation is modified so that wavelet first arrival points can be extracted. After that, NMO inversion based on the new velocity analysis is adopted on shot offset records. The precision of the results is significantly improved compared with the traditional method. Finally, the block move NMO correction based on the first arrival points travel times is adopted on long offset records and non-stretched results are achieved, which verify the proposed new equation.
文摘目的调查国内医学论文中涉及动物实验报告的规范现状,以提升医学科研论文的报告透明度。方法本研究以中国知网数据库(CNKI)中北大核心收录期刊为数据来源,采用预先确定的文献检索策略,筛选2019年和2022年发表的文献。对纳入文献中涉及《动物研究:体内实验报告》(Animal research:reporting of in vivo experiments,ARRIVE)指南关键10条中的6个项目(研究设计、样本量、随机化、盲法、统计方法和实验动物资料)以及推荐11条中的3个项目(摘要、伦理声明和利益冲突声明)共计22条主要信息的报告率进行统计分析。结果共纳入文献共4818篇,未发现任何一篇文献全面报告了本研究所调查的22条相关信息。2019年和2022年发表的绝大多数论文均报告了对照组,报告率分别为99.8%(2461/2467)和99.7%(2343/2351),样本量的报告率分别为79.2%(1954/2467)和77.2%(1815/2351),所有论文均未报告样本量的计算方法和依据,随机化方法报告率约为20%,盲法报告率约为1%;2022年对统计学方法的报告(96.4%)比2019年略有增加(91.8%);2019年和2022年对动物来源(93.8%vs.93.7%,P>0.05)、品种/品系(99.1%vs.99.2%,P=0.514)、性别(94.1%vs.92.7%,P=0.044)、年龄(58.1%vs.70.6%,P<0.001)、体质量(84.4%vs.81.9%,P=0.020)、健康证明(66.0%vs.75.5%,P<0.001)等实验动物资料信息的报告程度存在不同的差异。2019年和2022年文献报告动物伦理审查(15.8%vs.38.9%)或描述遵守的动物伦理原则(9.8%vs.21.3%)、利益冲突声明(2.3%vs.10.6%)、摘要中准确报告动物相关信息(9.16%vs.8.13%)程度均较低。其中,与2019年相比较,2022年动物伦理和利益冲突声明报告程度增加(P<0.001)。结论虽然自ARRIVE 2.0发布以来,大多数项目清单报告透明度明显改善。然而,随机化方法、盲法、动物伦理以及利益冲突的报告程度仍需进一步提升,这些是未来的重点努力方向。
基金supported by the National Natural Science Foundation of China(Grant Nos.61071163,61271327,and 61471191)the Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics,China(Grant No.BCXJ14-08)+2 种基金the Funding of Innovation Program for Graduate Education of Jiangsu Province,China(Grant No.KYLX 0277)the Fundamental Research Funds for the Central Universities,China(Grant No.3082015NP2015504)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PADA),China
文摘This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.
基金National Science and Technology Major Project(2016ZX03001025-003)Special Found for Beijing Common Construction Project
文摘How to predict the bus arrival time accurately is a crucial problem to be solved in Internet of Vehicle. Existed methods cannot solve the problem effectively for ignoring the traffic delay jitter. In this paper,a three-stage mixed model is proposed for bus arrival time prediction. The first stage is pattern training. In this stage,the traffic delay jitter patterns(TDJP)are mined by K nearest neighbor and K-means in the historical traffic time data. The second stage is the single-step prediction,which is based on real-time adjusted Kalman filter with a modification of historical TDJP. In the third stage,as the influence of historical law is increasing in long distance prediction,we combine the single-step prediction dynamically with Markov historical transfer model to conduct the multi-step prediction. The experimental results show that the proposed single-step prediction model performs better in accuracy and efficiency than short-term traffic flow prediction and dynamic Kalman filter. The multi-step prediction provides a higher level veracity and reliability in travel time forecasting than short-term traffic flow and historical traffic pattern prediction models.
文摘To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.
文摘目的通过评价中药复方防治胃癌前病变(PLGC)动物实验研究的方法学质量及报告质量,分析实验过程中的偏倚风险及研究报告的不足,为提高中药复方防治PLGC动物实验研究质量提供参考。方法计算机检索中国知识资源总库(CNKI)、万方数据知识服务平台(WanfangData)、中文科技期刊数据库(VIP)、中国生物医学文献数据库(CBM)、PubMed、Cochrane Library、Web of Science和Embase数据库2014年1月1日-2024年2月23日发表的关于中药复方防治PLGC动物实验文献,采用SYRCLE工具和ARRIVE2.0指南对纳入文献进行评分并计算各条目“低风险”符合率。结果共纳入文献213篇,其中中文文献189篇、英文文献24篇。SYRCLE工具评分为(12.86±1.29)分,“低风险”符合率为32.79%。ARRIVE2.0指南必备条目评分为(24.15±2.80)分,“低风险”符合率为49.08%;推荐条目评分为(11.28±3.40)分,“低风险”符合率为30.27%。SYRCLE工具评价中,144项(67.61%)研究未详细阐述分配序列产生的方法,所有研究均未描述分配隐藏充分与否及实施偏倚过程中的盲法,7项(3.29%)研究描述对结果评价者施盲。ARRIVE2.0指南中,所有研究均未报告样本量的确定方法、均未提供用于确定样本量的结局指标及实验方案注册声明,51项(23.94%)研究明确提出PLGC造模成功标准,66项(30.96%)研究提供所使用统计方法的详细信息,29项(13.62%)研究提供完整的伦理声明,22项(10.33%)报告了利益冲突。结论2014-2024年发表的中药复方防治PLGC动物实验文献方法学质量及报告质量存在较多问题,尤其是在实验过程中随机盲法策略的实施、样本量计算细节及纳入排除标准报告等方面存在缺陷,建议今后研究参考SYRCLE工具及ARRIVE2.0指南清单,以优化研究方案和报告,提高PLGC动物实验研究结果的可信度与规范性。
基金supported by the National Natural Science Foundation of China(No.11575282)
文摘Free electron lasers provide high-power and ultrashort pulses with extreme brightness. In order to improve a facility's capabilities and explore the possibility of performing high-resolution time-resolved experiments, a beam arrival time resolution under 100 fs is required. In this article, a novel beam arrival time monitor(BAM)equipped with two cavities has been designed and a beam flight time measurement scheme based on the BAM prototype has been proposed to estimate phase jitter in the signal measurement system. The two BAM cavities work at different frequencies and the frequency difference is designed to be 35 MHz. Therefore, a self-mixing intermediate frequency signal can be generated using the two cavities. The measured beam flight time shows a temporal deviation of 37 fs(rms).
基金We acknowledge the funding support from National Natural Science Foundation of China(Grant No.42077263).
文摘Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.
基金supported by Nanjing University of Aeronautics and Astronautics Graduate Innovation Base(Laboratory)Open Fund(No.kfjj20200717).
文摘In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.
基金sponsored by the National Key Research and Development Project(2018YFC1503202-01)the Emergency Management Project of the National Natural Science Foundation of China(41842042)
文摘In seismic data processing,picking of the P-wave first arrivals takes up plenty of time and labor,and its accuracy plays a key role in imaging seismic structures.Based on the convolution neural network(CNN),we propose a new method to pick up the P-wave first arrivals automatically.Emitted from MINI28 vibroseis in the Jingdezhen seismic experiment,the vertical component of seismic waveforms recorded by EPS 32-bit portable seismometers are used for manually picking up the first arrivals(a total of 7242).Based on these arrivals,we establish the training and testing sets,including 25,290 event samples and 710,616 noise samples(length of each sample:2 s).After 3,000 steps of training,we obtain a convergent CNN model,which can automatically classify seismic events and noise samples with high accuracy(>99%).With the trained CNN model,we scan continuous seismic records and take the maximum output(probability of a seismic event)as the P-wave first arrival time.Compared with STA/LTA(short time average/long time average),our method shows higher precision and stronger anti-noise ability,especially with the low SNR seismic data.This CNN method is of great significance for promoting the intellectualization of seismic data processing,improving the resolution of seismic imaging,and promoting the joint inversion of active and passive sources.
基金supported by the National Natural Science Foundation of China(No.61039001)the State Technology Supporting Plan(No.2011BAH24B08)the Fundamental Research Funds for the Central Universities (No.ZXH2011A002)
文摘In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.
基金National Natural Science Foundation of China under Grant Nos.51968016 and 5197083806the Guangxi Innovation Driven Development Project(Science and Technology Major Project,Grant No.Guike AA18118008).
文摘Fast and accurate P-wave arrival picking significantly affects the performance of earthquake early warning(EEW)systems.Automated P-wave picking algorithms used in EEW have encountered problems of falsely picking up noise,missing P-waves and inaccurate P-wave arrival estimation.To address these issues,an automatic algorithm based on the convolution neural network(DPick)was developed,and trained with a moderate number of data sets of 17,717 accelerograms.Compared to the widely used approach of the short-term average/long-term average of signal characteristic function(STA/LTA),DPick is 1.6 times less likely to detect noise as a P-wave,and 76 times less likely to miss P-waves.In terms of estimating P-wave arrival time,when the detection task is completed within 1 s,DPick′s detection occurrence is 7.4 times that of STA/LTA in the 0.05 s error band,and 1.6 times when the error band is 0.10 s.This verified that the proposed method has the potential for wide applications in EEW.
基金financial support provided by the National Natural Science Foundation of China(Grant No.41772313)Hunan Science and Technology Planning Project(Grant No.2019RS3001).
文摘Due to the significant effect of abnormal arrivals on localization accuracy,a novel acoustic emission(AE)source localization method using clustering detection to eliminate abnormal arrivals is proposed in the paper.Firstly,iterative weight estimation is utilized to obtain accurate equation residuals.Secondly,according to the distribution of equation residuals,clustering detection is used to identify and exclude abnormal arrivals.Thirdly,the AE source coordinate is recalculated with remaining normal arrivals.Experimental results of pencil-lead breaks indicate that the proposed method can achieve a better localization result with and without abnormal arrivals.The results of simulation tests further demonstrate that the proposed method possesses higher localization accuracy and robustness under different anomaly ratios and scales;even with abnormal arrivals as high as 30%,the proposed localization method still holds a correct detection rate of 91.85%.
基金supported by the National Natural Science Foundation of China (60771042 60728101+2 种基金 60927002)the NSAF (10776003)the "111" Project (B07046)
文摘When the information of mutual coupling and shadowing effect of a conformal antenna array are unknown, the performance of direction of arrival （DOA） estimation will be seriously degraded by using some classical methods, such as the multiple signal classification （MUSIC） algorithm. Meanwhile it is difficult to measure or estimate the shadowing effect. The DOA estimation for a conformal uniform circular array （UCA） is studied. Firstly, the azimuthal angle is separated from all the unknown information by transforming the UCA from the element space to the mode space. Then the rank reduction （RARE） algorithm is applied in the estima- tion of the azimuthal angle. The π ambiguity existed in the RARE is solved by the beam forming. The main advantage of this method is that it does not need to measure the mutual coupling and the shadowing effect. Compared with the subarray method, it will not decrease the aperture of the array. Simulation results validate the advantages of the method.
基金supported by the National Natural Science Foundation of China(No.71401072)the National Natural Science Foundation of Jiangsu Province(No.BK20130814)the Foundation of Jiangsu Innovation Program for Graduate Education(the Fundamental Research Funds for the Central Universities,No.SJLX15_0128)
文摘A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport system is defined through in-depth analysis of the characteristics of arrival and departure operations.Then,several constraints are taken into account,such as wake vortex separation,transfer separation,release separation,and separation in different runway operational modes.Furthermore,the scheduling model is constructed and simulated annealing algorithm is proposed by minimizing the total delay.Finally,Shanghai multi-airport system is chosen to conduct the simulation and validation.And the simulation results indicate that the proposed method is able to effectively improve the efficiency of arrival and departure operations for multi-airport system.
基金Supported by the National Natural Science Foundation of China(10971230,11171179)the Natural Science Foundation of Shandong Province(ZR2010AQ015)the Tianyuan Fund for Mathematics(11126232)
文摘A risk model with Markovian arrivals and tax payments is considered.When the insurer is in a profitable situation,the insurer may pay a certain proportion of the premium income as tax payments.First,the Laplace transform of the time to cross a certain level before ruin is discussed.Second,explicit formulas for a generalized Gerber-Shiu function are established in terms of the＇original＇Gerber-Shiu function without tax and the Laplace transform of the first passage time before ruin.Finally,the differential equations satisfied by the expected accumulated discounted tax payments until ruin are derived.An explicit expression for the discounted tax payments is also given.
文摘In order to improve the accuracy and engineering feasibility of four-Satellite localization system, the frequency difference measurement is introduced to the four-Satellite TDOA (Time Difference of Arrival) localization algorithm. The TDOA/FDOA (Frequency Difference of Arrival) localization algorithm is used to optimize the GDOP (geometric dilution of precision) of four-Satellite localization. The simulation results show that the absolute position measurement accuracy has little influence on TDOA/FDOA localization accuracy as compared with TDOA localization. Under the same conditions, TDOA/FDOA localization has better accuracy and its GDOP shows more uniform distribution in diamond configuration case. The localization accuracy of four-Satellite TDOA/FDOA is better than the localization accuracy of four-Satellite TDOA.
基金Project(2011AA010101) supported by the National High Technology Research and Development Program of China
文摘To improve the accuracy of real-time public transport information release system, a collaborative prediction model was proposed based on cyber-physical systems architecture. In the model, the total bus travel time was divided into three parts: running time, dwell time and intersection delay time, and the data were divided into three categories of historical data, static data and real-time data. The bus arrival time was obtained by fusion computing the real-time data in perception layer together with historical data and static data in collaborative layer. The validity of the collaborative model was verified by the data of a typical urban bus line in Shanghai, and 1538 sets of data were collected and analyzed from three different perspectives. By comparing the experimental results with the actual results, it is shown that the experimental results are with higher prediction accuracy, and the collaborative prediction model adopted is able to meet the demand for bus arrival prediction.
