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
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
Purpose-The design goal for the tracking interval of high-speed railway trains in China is 3 min,but it is difficult to achieve,and it is widely believed that it is mainly limited by the tracking interval of train arr...Purpose-The design goal for the tracking interval of high-speed railway trains in China is 3 min,but it is difficult to achieve,and it is widely believed that it is mainly limited by the tracking interval of train arrivals.If the train arrival tracking interval can be compressed,it will be beneficial for China's high-speed railway to achieve a 3-min train tracking interval.The goal of this article is to study how to compress the train arrival tracking interval.Design/methodologylapproach-By simulating the process of dense train groups arriving at the station and stopping,the headway between train arrivals at the station was calculated,and the pattern of train arrival headway was obtained,changing the traditional understanding that the train arrival headway is considered the main factor limiting the headway of trains.Findings-When the running speed of trains is high,the headway between trains is short,the length of the station approach throat area is considerable and frequent train arrivals at the station,the arrival headway for the first group or several groups of trains will exceed the headway,but the subsequent sets of trains will havea headway equal to the arrival headway.This convergence characteristic is obtained by appropriately increasing the running time.Originality/value-According to this pattern,there is no need to overly emphasize the impact of train arrival headway on the headway.This plays an important role in compressing train headway and improving high-speedrailwaycapacity.展开更多
In underwater acoustic applications,the conventional cyclic direction of arrival algorithm faces challenges,including a low signal-to-noise ratio and high bandwidth when compared with modulated frequencies.In response...In underwater acoustic applications,the conventional cyclic direction of arrival algorithm faces challenges,including a low signal-to-noise ratio and high bandwidth when compared with modulated frequencies.In response to these issues,this paper introduces a novel,robust,and broadband cyclic beamforming algorithm.The proposed method substitutes the conventional cyclic covariance matrix with the variance of the cyclic covariance matrix as its primary feature.Assuming that the same frequency band shares a common steering vector,the new algorithm achieves superior detection performance for targets with specific modulation frequencies while suppressing interference signals and background noise.Experimental results demonstrate a significant enhancement in the directibity index by 81%and 181%when compared with the traditional Capon beamforming algorithm and the traditional extended wideband spectral cyclic MUSIC(EWSCM)algorithm,respectively.Moreover,the proposed algorithm substantially reduces computational complexity to 1/40th of that of the EWSCM algorithm,employing frequency band statistical averaging and covariance matrix variance.展开更多
Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suf...Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.展开更多
Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based ...Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.展开更多
This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfac...This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.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
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
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
针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference ...针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival)无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory, DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution, TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。展开更多
Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capa...Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.展开更多
剑桥大学,作为全球顶尖学府,拥有着深厚底蕴与独特魅力,而“我”也在此开启了一场探索之旅。Peeping out of the porthole(飞机舷窗),I saw that a newborn sun gradually emerged on the distant horizon,reminding me that I was abou...剑桥大学,作为全球顶尖学府,拥有着深厚底蕴与独特魅力,而“我”也在此开启了一场探索之旅。Peeping out of the porthole(飞机舷窗),I saw that a newborn sun gradually emerged on the distant horizon,reminding me that I was about to arrive in the UK.It was 5 a.m.and it was a little foggy-the typical appearance of the country.After a long exhausting bus ride,we finally arrived at Cambridge.展开更多
Accurate estimation of the Direction-of-Arrival(DoA)of incident plane waves is essential for modern wireless communication,radar,sonar,and localization systems.Precise DoA information enables adaptive beamforming,spat...Accurate estimation of the Direction-of-Arrival(DoA)of incident plane waves is essential for modern wireless communication,radar,sonar,and localization systems.Precise DoA information enables adaptive beamforming,spatial filtering,and interference mitigation by steering antenna array beams toward desired sources while suppressing unwanted signals.Traditional one-dimensional Uniform Linear Arrays(ULAs)are limited to elevation angle estimation due to geometric constraints,typically within the range[0,π].To capture full spatial characteristics in environments with multipath and angular spread,joint estimation of both elevation and azimuth angles becomes necessary.However,existing 2D and 3D array geometries often entail increased hardware complexity and computational cost.This work proposes a novel and efficient framework for joint elevation and azimuth angle estimation using three spatially separated,parallel ULAs.The array configuration exploits spatial diversity and orthogonal projections to capture complete directional information with minimal structural overhead.A customized objective function based on the mean square error between measured and reconstructed array outputs is formulated to guide the estimation process.To solve the resulting non-convex optimization problem,three strategies are investigated:a global Genetic Algorithm(GA),a local Pattern Search(PS),and a hybrid GA-PS method that combines global exploration with local refinement.The proposed framework supports automatic pairing of elevation and azimuth angles,eliminating the need for manual post-processing.Extensive simulations validate the robustness,convergence,and accuracy of all three methods under varying signal-to-noise ratio conditions.Results confirm that the hybrid GA-PS approach achieves superior estimation performance and reduced computational complexity,making it well-suited for real-time and resource-constrained applications in next-generation sensing and communication systems.展开更多
To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a de...To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a deep unfolded amplitude-phase error self-calibration network.Firstly,a sparse-based DOA model with an array convex error restriction is established,which gets resolved via an alternating iterative minimization(AIM)algo-rithm.The algorithm is then unrolled to a deep network known as AE-AIM Network(AE-AIM-Net),where all parameters are opti-mized through multi-task learning using the constructed com-plete dataset.The results of the simulation and theoretical analy-sis suggest that the proposed unfolded network achieves lower computational costs compared to typical sparse recovery meth-ods.Furthermore,it maintains excellent estimation performance even in the presence of array magnitude-phase errors.展开更多
In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaini...In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaining energy levels and battery replacement is both inadequate and costly.This paper introduces an energy management system for indoor IoT,which includes a mobile energy station(ES)for enabling on-demand wireless energy transfer(WET)in radio frequency(RF),some energy receivers(ERs),and a cloud server.By implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices,we robustly manage their energy storage.The experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.展开更多
Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the...Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the hole-filling strategy.Specifically,we first introduce the improved nested array(INA)and prove its properties.Subsequently,we extend the sum-difference coarray(SDCA)by adding an additional sensor to fill the holes.Thus the larger uniform degrees of freedom(uDOFs)and virtual array aperture(VAA)can be abtained,and the ENAFS is designed.Finally,the simulation results are given to verify the superiority of the proposed ENAFS in terms of DOF,mutual coupling and estimation performance.展开更多
Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as...Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as mutual coupling between array elements,array amplitude and phase errors,and array element position errors leads to defects in the array manifold,which makes the performance of the algorithm decline rapidly or even fail.In order to solve the problem of DOA estimation in the presence of amplitude and phase errors and array element position errors,this paper introduces the first-order Taylor expansion equivalent model of the received signal under the uniform linear array from the Bayesian point of view.In the solution,the amplitude and phase error parameters and the array element position error parameters are regarded as random variables obeying the Gaussian distribution.At the same time,the expectation-maximization algorithm is used to update the probability distribution parameters,and then the two error parameters are solved alternately to obtain more accurate DOA estimation results.Finally,the effectiveness of the proposed algorithm is verified by simulation and experiment.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State Railway Corporation of China Limited under the Science and Technology Research and Development Programme(2021X007)China Academy of Railway Research(2021YJ012)+1 种基金National Natural Science Foundation of China(52302417)Natural Science Foundation of Sichuan Province of China(2023NSFSC0906).
文摘Purpose-The design goal for the tracking interval of high-speed railway trains in China is 3 min,but it is difficult to achieve,and it is widely believed that it is mainly limited by the tracking interval of train arrivals.If the train arrival tracking interval can be compressed,it will be beneficial for China's high-speed railway to achieve a 3-min train tracking interval.The goal of this article is to study how to compress the train arrival tracking interval.Design/methodologylapproach-By simulating the process of dense train groups arriving at the station and stopping,the headway between train arrivals at the station was calculated,and the pattern of train arrival headway was obtained,changing the traditional understanding that the train arrival headway is considered the main factor limiting the headway of trains.Findings-When the running speed of trains is high,the headway between trains is short,the length of the station approach throat area is considerable and frequent train arrivals at the station,the arrival headway for the first group or several groups of trains will exceed the headway,but the subsequent sets of trains will havea headway equal to the arrival headway.This convergence characteristic is obtained by appropriately increasing the running time.Originality/value-According to this pattern,there is no need to overly emphasize the impact of train arrival headway on the headway.This plays an important role in compressing train headway and improving high-speedrailwaycapacity.
基金supported by the IOA Frontier Exploration Project (No.ZYTS202001)the Youth Innovation Promotion Association CAS。
文摘In underwater acoustic applications,the conventional cyclic direction of arrival algorithm faces challenges,including a low signal-to-noise ratio and high bandwidth when compared with modulated frequencies.In response to these issues,this paper introduces a novel,robust,and broadband cyclic beamforming algorithm.The proposed method substitutes the conventional cyclic covariance matrix with the variance of the cyclic covariance matrix as its primary feature.Assuming that the same frequency band shares a common steering vector,the new algorithm achieves superior detection performance for targets with specific modulation frequencies while suppressing interference signals and background noise.Experimental results demonstrate a significant enhancement in the directibity index by 81%and 181%when compared with the traditional Capon beamforming algorithm and the traditional extended wideband spectral cyclic MUSIC(EWSCM)algorithm,respectively.Moreover,the proposed algorithm substantially reduces computational complexity to 1/40th of that of the EWSCM algorithm,employing frequency band statistical averaging and covariance matrix variance.
基金National Natural Science Foundation of China(61973037)National 173 Program Project(2019-JCJQ-ZD-324)。
文摘Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.
基金supported by the National Natural Science Foundation of China(No.51279033).
文摘Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.
文摘This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.
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。
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.
文摘针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival)无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory, DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution, TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。
基金the financial support from the National Key Research and Development Program of China(No.2023YFB3907001)the National Natural Science Foundation of China(Nos.U2233217,62371029)the UK Engineering and Physical Sciences Research Council(EPSRC),China(Nos.EP/M026981/1,EP/T021063/1 and EP/T024917/)。
文摘Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.
文摘剑桥大学,作为全球顶尖学府,拥有着深厚底蕴与独特魅力,而“我”也在此开启了一场探索之旅。Peeping out of the porthole(飞机舷窗),I saw that a newborn sun gradually emerged on the distant horizon,reminding me that I was about to arrive in the UK.It was 5 a.m.and it was a little foggy-the typical appearance of the country.After a long exhausting bus ride,we finally arrived at Cambridge.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2504)。
文摘Accurate estimation of the Direction-of-Arrival(DoA)of incident plane waves is essential for modern wireless communication,radar,sonar,and localization systems.Precise DoA information enables adaptive beamforming,spatial filtering,and interference mitigation by steering antenna array beams toward desired sources while suppressing unwanted signals.Traditional one-dimensional Uniform Linear Arrays(ULAs)are limited to elevation angle estimation due to geometric constraints,typically within the range[0,π].To capture full spatial characteristics in environments with multipath and angular spread,joint estimation of both elevation and azimuth angles becomes necessary.However,existing 2D and 3D array geometries often entail increased hardware complexity and computational cost.This work proposes a novel and efficient framework for joint elevation and azimuth angle estimation using three spatially separated,parallel ULAs.The array configuration exploits spatial diversity and orthogonal projections to capture complete directional information with minimal structural overhead.A customized objective function based on the mean square error between measured and reconstructed array outputs is formulated to guide the estimation process.To solve the resulting non-convex optimization problem,three strategies are investigated:a global Genetic Algorithm(GA),a local Pattern Search(PS),and a hybrid GA-PS method that combines global exploration with local refinement.The proposed framework supports automatic pairing of elevation and azimuth angles,eliminating the need for manual post-processing.Extensive simulations validate the robustness,convergence,and accuracy of all three methods under varying signal-to-noise ratio conditions.Results confirm that the hybrid GA-PS approach achieves superior estimation performance and reduced computational complexity,making it well-suited for real-time and resource-constrained applications in next-generation sensing and communication systems.
基金supported by the National Natural Science Foundation of China(62301598).
文摘To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a deep unfolded amplitude-phase error self-calibration network.Firstly,a sparse-based DOA model with an array convex error restriction is established,which gets resolved via an alternating iterative minimization(AIM)algo-rithm.The algorithm is then unrolled to a deep network known as AE-AIM Network(AE-AIM-Net),where all parameters are opti-mized through multi-task learning using the constructed com-plete dataset.The results of the simulation and theoretical analy-sis suggest that the proposed unfolded network achieves lower computational costs compared to typical sparse recovery meth-ods.Furthermore,it maintains excellent estimation performance even in the presence of array magnitude-phase errors.
基金supported in part by the Natural Science Foundation of China(NSFC)under Grant 61971102in part by the Key Research and Development Program of Zhejiang Province under Grant 2022C01093.
文摘In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaining energy levels and battery replacement is both inadequate and costly.This paper introduces an energy management system for indoor IoT,which includes a mobile energy station(ES)for enabling on-demand wireless energy transfer(WET)in radio frequency(RF),some energy receivers(ERs),and a cloud server.By implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices,we robustly manage their energy storage.The experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.
基金supported by China National Science Foundations(Nos.62371225,62371227)。
文摘Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the hole-filling strategy.Specifically,we first introduce the improved nested array(INA)and prove its properties.Subsequently,we extend the sum-difference coarray(SDCA)by adding an additional sensor to fill the holes.Thus the larger uniform degrees of freedom(uDOFs)and virtual array aperture(VAA)can be abtained,and the ENAFS is designed.Finally,the simulation results are given to verify the superiority of the proposed ENAFS in terms of DOF,mutual coupling and estimation performance.
基金supported by the National Natural Science Foundation of China (62071144)
文摘Most of the existing direction of arrival(DOA)estimation algorithms are applied under the assumption that the array manifold is ideal.In practical engineering applications,the existence of non-ideal conditions such as mutual coupling between array elements,array amplitude and phase errors,and array element position errors leads to defects in the array manifold,which makes the performance of the algorithm decline rapidly or even fail.In order to solve the problem of DOA estimation in the presence of amplitude and phase errors and array element position errors,this paper introduces the first-order Taylor expansion equivalent model of the received signal under the uniform linear array from the Bayesian point of view.In the solution,the amplitude and phase error parameters and the array element position error parameters are regarded as random variables obeying the Gaussian distribution.At the same time,the expectation-maximization algorithm is used to update the probability distribution parameters,and then the two error parameters are solved alternately to obtain more accurate DOA estimation results.Finally,the effectiveness of the proposed algorithm is verified by simulation and experiment.
