New data association technique based on ACO with directional information considered

Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information.

Research on spatial association rules mining in two-direction

In data mining from transaction DB, the relationships between the attributes have been focused, but the relationships between the tuples have not been taken into account. In spatial database, there are relationships between the attributes and the tuples, and most of the associations occur between the tuples, such as adjacent, intersection, overlap and other topological relationships. So the tasks of spatial data association rules mining include mining the relationships between attributes of spatial objects, which are called as vertical direction DM, and the relationships between the tuples, which are called as horizontal direction DM. This paper analyzes the storage models of spatial data, uses for reference the technologies of data mining in transaction DB, defines the spatial data association rule, including vertical direction association rule, horizontal direction association rule and two-direction association rule, discusses the measurement of spatial association rule interestingness, and puts forward the work flows of spatial association rule data mining. During two-direction spatial association rules mining, an algorithm is proposed to get non-spatial itemsets. By virtue of spatial analysis, the spatial relations were transferred into non-spatial associations and the non-spatial itemsets were gotten. Based on the non-spatial itemsets, the Apriori algorithm or other algorithms could be used to get the frequent itemsets and then the spatial association rules come into being. Using spatial DB, the spatial association rules were gotten to validate the algorithm, and the test results show that this algorithm is efficient and can mine the interesting spatial rules.

Properties and Stability of Max-Product Fuzzy Bi-Directional Associative Memory

In this paper, a fuzzy operator of max-product is defined at first, and the fuzzy bi-directional associative memory (FBAM) based on the fuzzy operator of max-product is given. Then the properties and the Lyapunov stability of equilibriums of the networks are studied.

Evaluation of the safety and effectiveness of direct oral anticoagulants and low molecular weight heparin in gastrointestinal cancer-associated venous thromboembolism

BACKGROUND Gastrointestinal cancer(GICA)is associated with a higher incidence of venous thromboembolism(VTE)compared to other solid tumors,moreover,recurrent VTE and major bleeding(MB)complications during anticoagulation treatment have an associated increase rate.GICA-VTE remains a challenging clinical scenario with MB concerns for utilization of direct oral anticoagulants(DOAC),especially with active cancer therapies.AIM To evaluate patient risk factors,effectiveness(VTE)and safety(MB)of DOACs and low molecular weight heparin(LMWH)in patients with active GICA-VTE.METHODS A retrospective chart review of patients receiving DOACs and LMWH with GICA and symptomatic or incidental VTE treated at comprehensive cancer center from November 2013 to February 2017 was performed.Inclusion criteria included active GI cancer diagnosed at any stage or treatment+/-6 mo of VTE diagnosis,whom were prescribed 6 mo or more of DOACs or LMWH.The Chi-squared test was used for overall and the Fisher exact test for pairwise comparisons of the proportions of patients experiencing recurrent VTE and MB events.Odds ratios were used to compare the relative odds of the occurrence of the outcome given exposure to the risk factor.RESULTS A total of 144 patients were prescribed anticoagulation,in which 106 fulfilled inclusion criteria apixaban(27.3%),rivaroxaban(34.9%)and enoxaparin(37.7%),and 38 were excluded.Patients median age was 66.5 years at GICA diagnosis and 67 years at CAVTE event,with 62%males,80%Caucasian,70%stage IV,pancreatic cancer(40.5%),30%Khorana Score(≥3 points),and 43.5%on active chemotherapy.Sixty-four percent of patients completed anticoagulation therapy(range 1 to 43 mo).Recurrent VTE at 6 mo was noted in 7.5%(n=3),6.8%(n=2)and 2.7%(n=1)of patients on enoxaparin,apixaban and rivaroxaban,respectively(all P=NS).MB at 6 mo were 5%(n=2)for enoxaparin,6.8%(n=2)for apixaban and 21.6%(n=8)for rivaroxaban(overall P=0.048;vs LMWH P=0.0423;all other P=NS).Significant predictors of a primary or secondary outcome for all anticoagulation therapies included:Active systemic treatment(OR=5.1,95%CI:1.3-19.3),high Khorana Score[≥3 points](OR=5.5,95%CI:1.7-17.1),active smoker(OR=6.7,95%CI:2.1-21.0),pancreatic cancer(OR=6.8,95%CI:1.9-23.2),and stage IV disease(OR=9.9,95%CI:1.2-79.1).CONCLUSION Rivaroxaban compared to apixaban and enoxaparin had a significantly higher risk of MB on GICA-VTE patients with equivocal efficacy.

Sample-Efficient Deep Reinforcement Learning with Directed Associative Graph

Reinforcement learning can be modeled as markov decision process mathematically.In consequence,the interaction samples as well as the connection relation between them are two main types of information for learning.However,most of recent works on deep reinforcement learning treat samples independently either in their own episode or between episodes.In this paper,in order to utilize more sample information,we propose another learning system based on directed associative graph(DAG).The DAG is built on all trajectories in real time,which includes the whole connection relation of all samples among all episodes.Through planning with directed edges on DAG,we offer another perspective to estimate stateaction pair,especially for the unknowns to deep neural network(DNN)as well as episodic memory(EM).Mixed loss function is generated by the three learning systems(DNN,EM and DAG)to improve the efficiency of the parameter update in the proposed algorithm.We show that our algorithm is significantly better than the state-of-the-art algorithm in performance and sample efficiency on testing environments.Furthermore,the convergence of our algorithm is proved in the appendix and its long-term performance as well as the effects of DAG are verified.

基于联合方向梯度和均值对比度的红外弱小目标检测方法

针对小目标在整幅图像中占比很低,且目标周围存在大量杂波,提出了一种基于联合方向梯度(Associated Directional Gradient,ADG)和均值对比度(Mean Contrast,MC)的红外弱小目标检测算法。该算法由两个模块组成:ADG利用红外弱小目标的高斯分布模型,将单一方向的梯度与一个相邻方向上的梯度相加组成新的联合梯度特征,增强真实目标、抑制背景杂波的同时能够消除高亮边缘对目标检测效果的影响;MC融入方向信息来计算目标的多方向对比度,选用多方向对比度的最小值抑制结构噪声,并将均值滤波的思想引入对比度的计算,抑制背景中的孤立噪声,进一步降低检测的虚警率。在实际红外图像上的实验结果表明,该算法在增强目标信噪比和抑制背景噪声方面,能够取得较好效果。

一种长基线被动传感器数据关联方法

为了提高测向交叉定位系统多目标环境下的去鬼点性能,提出了一种长基线被动传感器数据关联方法.首先利用被动传感器量测的视线矢量信息进行交叉定位并计算定位误差协方差矩阵,然后基于两个定位点构造了一个卡方分布的检验统计量,将多目标条件下的去鬼点问题转换为假设检验问题.为了分析该方法的性能,定义了真实目标的正确关联概率和鬼点目标的错误关联概率,并在使用两部和三部被动雷达的情况下分别与倾斜角方法进行了仿真对比.仿真结果表明所提出的方法在使用三部被动雷达或多目标与被动雷达共面时关联性能更好.

直接抗病毒药物治疗失败的慢性丙型肝炎患者临床特点及基因型分析

目的探索直接抗病毒药物(DAA)治疗失败的慢性丙型肝炎(CHC)患者的临床特点及基因型特征。方法选取2021年9月至2022年12月咸阳市第一人民医院DAA治疗失败的患者28例,同时期DAA治疗成功者100例。酶法检测肝功能、PCR-反向杂交法检测HCV基因型、Sanger测序法检测耐药相关替代突变(RAS)片段,分析DAA观察组患者临床特征及基因型特点。结果失败组和有效组HCV RNA>105 IU/mL分别为23例(82.1%)、34例(34.0%),差异有统计学意义(χ^(2)=20.526,P=0.001)。DAA治疗失败组男性患者TBil、DBil分别为14.61(10.98,20.78)μmol/L、4.94(3.08,7.48)μmol/L,均高于女性患者的6.65(4.90,8.40)μmol/L、2.50(1.78,3.07)μmol/L(Z=-2.018和-2.456,均P=0.01)。纳入患者共检测出3种HCV基因型,分别为1b、2a及3b,有26例未测出基因型,失败组HCV 1b、2a及3b基因型分别为11例(39.3%)、6例(21.4%)及5例(17.8%),有效组分别为56例(56.0%)、15例(15.0%)及9例(9.0%)。失败组检测出NS5A和NS5B2种基因片段,但是RAS发生率不同。结论DAA治疗失败者会受性别、病毒载量、基因型以及RAS种类影响。

内在情感对癌症发生风险的影响:基于孟德尔随机化研究

目的探究内在情感(幸福感、抑郁情绪、忧虑和内疚感)与癌症(结直肠癌、肝癌、甲状腺癌、肺癌、乳腺癌)的因果关系。方法采用两样本双向孟德尔随机化方法。所有数据基于全基因关联研究(GWAS)汇总数据。逆方差加权法(IVW)得到的结果作为主要结局指标,加权中值法(WM)、MR-Egger法作为补充结果,评价指标为比值比(OR),并进行敏感性分析。结果对于抑郁情绪,提示与肺癌(OR=1.005,95%CI:1.001~1.009,P=0.015)显著相关。对于忧虑,提示与乳腺癌(OR=1.199,95%CI:1.011~1.423,P=0.038)显著相关。对于内疚感,提示与甲状腺癌(OR=2.083,95%CI:1.080~4.017,P=0.029)显著相关。在去除MR-PRESSO检测到的所有潜在多效性SNPs后,忧虑与乳腺癌的关联无统计学差异(P=0.064),忧虑与结直肠癌显著相关(OR=0.739,95%CI:0.571~0.956,P=0.021)。癌症与内在情感之间的关联未发现存在因果关系。结论抑郁情绪与肺癌发生风险增加相关,内疚感与甲状腺癌发生风险增加相关,忧虑可能与结直肠癌发生风险降低相关。

晋西黄土区不同坡向刺槐林下植物种间关联及群落稳定性

为了解人工林群落内物种的种间关系及群落稳定性,以晋西黄土区人工刺槐(Robinia pseudoacacia)林为研究对象,在样地调查的基础上,采用方差比率法、χ2检验、戈登·摩尔稳定性等方法,对林下植物的种间关系及群落稳定性进行分析。结果表明:(1)调查样地内共有植物30科56属62种。其中,灌木层植物10科18属19种,杠柳(Periploca sepium)为优势种;草本层植物22科38属43种,虉草(Phalaris arundinacea)为优势种。阳坡有14种灌木,阴坡有7种;阴坡有28种草本植物,阳坡有24种。(2)不同坡向刺槐人工林内植物种的关联性不同,阳坡黑麦草(Lolium perenne)和白首乌(Cynanchum bungei)的关联性极显著(P<0.01);半阳坡茜草(Rubia cordifolia)、虉草(Phalaris arundinacea)和北柴胡(Bupleurum chinense)的关联性极显著(P<0.01);阴坡蛇莓(Duchesnea indica)和芦苇(Phragmites australis)的关联性显著(P<0.05);半阴坡酸枣(Ziziphus jujuba)、卫矛(Euonymus alatus)、蒌蒿(Artemisia selengensis)和披针薹草(Carex lancifolia)的关联性极显著(P<0.01)。(3)阳坡和阴坡的林下植物群落整体稳定性强,半阳坡和半阴坡的林下灌木群落稳定性强。

湿法炼锌系统铜回收利用进展与展望

本文从锌精矿中伴生铜的赋存形态出发,阐述了铜在湿法炼锌焙烧、浸出、净化等核心工序中的分布规律与铜物相演变行为。研究结果表明:在沸腾焙烧过程中,铜从黄铜矿(CuFeS_(2))形态转变为CuO、Cu_(2)O、CuS形态,铜对硫的亲和力较大,导致焙砂中残硫高,从而影响铜浸出效率;湿法炼锌流程中约30%、56%和14%的铜分别进入铜镉渣(Cu^(0))、酸性浸出液(Cu^(2+))和浸出渣(CuSO_(4)、Cu_(3)As_(2))中;目前主要采用溶剂萃取、铁粉置换、离子交换树脂和电解沉积等方法分离回收酸性浸出液中的铜,其中溶剂萃取法选择性强、效率高,但引入萃取剂有机物给湿法炼锌主工艺产生不利影响;铁粉置换法成本较低,但后续除铁过程将产生危废铁渣;离子交换法清洁高效,投资成本较高;电解沉积法可直接获得阴极铜产品,但对电积前液成分要求高,电能消耗大。溶液中铜定向分离和富集工艺选择取决于浸出液成分特点、回收率、运行成本及与锌主系统协同性等因素。未来随着资源紧缺、环保要求、经济效益等诸多方面影响,湿法炼锌过程中伴生铜资源的短流程、低成本、高效率回收将成为趋势。

基于网络有向关系的节点重要性排序方法

针对因网络多重分流导致的节点重要性特征分布混乱、差异性较大的问题,提出一种基于网络有向关系的节点重要性排序方法。建立多重分流复杂网络结构的动态模型,根据节点的线性变化关系,动态计算节点在网络流域中的实时状态值。根据节点的实时状态值,通过效率矩阵求得预设节点与任意点间重要性贡献参数,其可以反映两个节点间的关联程度,根据关联指向大小实施重要性排序。实验结果表明,所提方法可以精准排序全局重要度值在0.021~0.085范围内的节点,可以在1s内完成重要性较低的节点排序。

Challenge to overcome: Nonstructural protein 5A-P32 deletion in direct-acting antiviral-based therapy for hepatitis C virus

Interferon(IFN)-based therapy for hepatitis C virus(HCV) infection has recently been replaced by IFNfree direct-acting antiviral(DAA)-based therapy, which has been established as a 1^(st) line therapy with high efficacy and tolerability due to its reasonable safety profile. Resistance-associated substitutions(RASs) have been a weakness of DAA-based therapy. For example, combination therapy with daclatasvir and asunaprevir(DCV/ASV) is less effective for HCV genotype 1-infected patients with Y93H as a nonstructural protein 5A RAS. However, the problem regarding RASs has been gradually overcome with the advent of recently developed DAAs, such as sofosbuvir-based regimens or combination therapy with glecaprevir and pibrentasvir. Despite the high efficiency of DAA-based therapy, some cases fail to achieve viral eradication. P32 deletion, an NS5A RAS, has been gradually noticed in patients with DCV/ASV failure. P32 deletion has been sporadically reported and the prevalence of this RAS has been considered to be low in patients with DCV/ASV failure. Thus, the picture of P32 deletion has not been fully evaluated. Importantly, currently-commercialized DAA-based combination therapy was not likely to be effective for patients with P32 deletion. Exploring and overcoming this RAS is essential for antiviral therapy for chronic hepatitis C.

ON DIRECT METHOD OF SOLUTION FOR A CLASS OF SINGULAR INTEGRAL EQUATIONS

In this article, by introducing characteristic singular integral operator and associate singular integral equations （SIEs）, the authors discuss the direct method of solution for a class of singular integral equations with certain analytic inputs. They obtain both the conditions of solvability and the solutions in closed form. It is noteworthy that the method is different from the classical one that is due to Lu.

Factors Associated with Maternal Mortality at Gynecology and Obstetrics Department in Departmental University Hospital Center of Borgou

Introduction: Maternal mortality is a robust indicator of human development. Most of it occurs in developing countries. Objectives: This study aims to determine the factors associated with maternal mortality in Gynecology and Obstetrics Department of Borgou Departmental University Hospital Center (CHUD-B). Study method: Our study took place at Gynecology and Obstetrics Department in Borgou Departmental University Hospital Center. This was a descriptive and analytical case-control study, covering a period of 7 years from January 1, 2012 to December 31, 2018. Results: Two hundred and twelve patients have been recruited consisting of 106 deceased women and 106 controls. The intra-hospital mortality ratio was 1100 deaths per 100,000 live births (LB). The mean age of deceased women was 27.06 ± 6.45 years with the extremes of 15 and 45 years. Direct obstetric causes were the most frequent causes of maternal death. They were dominated by immediate postpartum hemorrhage (32.93%), followed by High Blood Pressure (26.83%) and infections (17.07%). The general condition of patients on admission (p-0.000) and inadequate management (p-0.001) was associated with maternal mortality. Conclusion: Patients’ general condition on admission and inadequate management was factors associated with maternal mortality.

Retreatment of patients with treatment failure of directacting antivirals: Focus on hepatitis C virus genotype 1b

The recent development of direct-acting antiviral agents(DAAs) against hepatitis C virus(HCV) infection could lead to higher sustained virological response(SVR) rates, with shorter treatment durations and fewer adverse events compared with regimens that include interferon. However, a relatively small proportion of patients cannot achieve SVR in the first treatment, including DAAs with or without peginterferon and/or ribavirin. Although retreatment with a combination of DAAs should be conducted for these patients, it is more difficult to achieve SVR when retreating these patients because of resistance-associated substitutions(RASs) or treatment-emergent substitutions. In Japan, HCV genotype 1 b(GT1 b) is founded in 70% of HCVinfected individuals. In this minireview, we summarize the retreatment regimens and their SVR rates for HCV GT1 b. It is important to avoid drugs that target the regions targeted by initial drugs, but next-generation combinations of DAAs, such as sofosbuvir/velpatasvir/voxilaprevir for 12 wk or glecaprevir/pibrentasvir for 12 wk, are proposed to be potential solution for the HCV GT1 b-infected patients with treatment failure, mainly on a basis of targeting distinctive regions. Clinicians should follow the new information and resources for DAAs and select the proper combination of DAAs for the retreatment of HCV GT1 b-infected patients with treatment failure.

基于路侧多机视频目标关联与轨迹拼接的车辆连续轨迹构建方法

针对单个相机覆盖区域有限的问题,本文提出了通过路侧多个相机获取车辆连续轨迹数据的方法。在路侧端布置多台固定相机采集视频数据,采用直接线性变换算法解决相机外参造成的画面畸变问题;通过全时域抽帧提取图片训练样本,采用YOLOv5训练车辆检测模型;针对偶发的车辆漏检情形,通过完整性检查可以筛查出此类情况并修复;针对连续多帧漏检或误检导致的目标关联问题,通过异常轨迹核查算法及数据修复工具解决;针对相机斜下方区域的车辆轮廓变形问题,采用车辆检测轮廓修复算法解决车辆在不同路段检测框大小不一的问题;提出了基于车辆质心坐标匹配的方法实现相邻机位间的车辆轨迹拼接。基于上述多机视频目标关联与轨迹拼接方法,在多机位时间同步下构建了覆盖武汉珞狮路高架桥的车辆连续轨迹数据集,轨迹数据集验证结果表明:数据集涵盖从畅通到拥堵的各种交通状态,包含多段分合流区域,数据集连续时长达到3.5 h,覆盖区域1.41 km;车辆检测模型的召回率达到93.23%,准确率达到98.51%,F1分数为95.80%;数据集包含主路及各处匝道汇入的轨迹共25734条,其中覆盖道路全域的完整长轨迹15004条。本研究丰富了路侧多机视频目标关联与轨迹拼接方法,有助于路侧宽域车辆连续轨迹构建及交通管理与控制。

一种基于被动探测的双机雷达协同定位方法

针对有源探测易被发现及干扰的问题,设计基于被动探测的双机协同射频隐身定位方法。通过测向交叉定位处理获得目标的距离信息,利用属性数据关联消除“鬼影”,从而完成对目标稳定有效的探测。所设计的双机雷达协同定位方法具有目标定位精度高和隐蔽性良好等优点,并通过仿真验证了算法的有效性和实用性。

手卫生依从性管理系统在医院感染管理中的效果评价

目的评价手卫生依从性管理系统控制医院感染的效果。方法选取某大型三甲医院2020年7月—2021年6月呼吸ICU工作人员为研究对象,观察并分析应用手卫生依从性管理系统前后工作人员手卫生依从率和各项医院感染管理指标的变化。结果应用手卫生依从性管理系统后,不同岗位工作人员(含医生、护士和保洁)及整体手卫生依从率均提高(P<0.05);试验组医院感染发病率和多重耐药菌(MDROs)医院感染发生率均低于对照组(P<0.05)。结论应用手卫生依从性管理系统可有效提高工作人员手卫生依从率,减少医院感染的发生。

Detecting direct associations in a network by information theoretic approaches

Detecting direct associations or inferring networks based on the observed data is an important issue in many fields, including biology, physics, engineering and social studies. In this work, we focus on the information theoretic approaches in the network reconstruction or the direct association detection, in particular,for biological networks. We not only review the traditional approaches or measurements on the associations among the observed variables, such as correlation coefficient, mutual information and conditional mutual information(CMI), but also summarize recently developed theories and methods. The new theoretic works include:information geometry to give a unified framework in detecting causality/association, the partial independence to alleviate the singularity of CMI, and multiscale analysis of CMI to avoid the underestimation issue of CMI.The new methods include part mutual information(PMI) and partial associations(PA), which improve the old measurements in avoiding both overestimation and underestimation. All those theories and methods make important contributions as major advances in the development of network inference.