全面健康教育对女性体检者两癌防治知识认知及自检行为依从性的影响

目的探讨全面健康教育在女性体检者两癌防治中的应用效果。方法选择2018年10月—2020年10月于我院体检的女性68例,按随机数字表法分为2组,各34例。对照组实施常规健康教育,观察组在对照组基础上实施全面健康教育,对比2组两癌防治知识认知、癌症筛查信念及自检行为依从性。结果观察组教育后癌症预防一般知识、乳腺癌相关知识及宫颈癌评分均高于对照组,差异有统计学意义(P<0.05);观察组教育满意度(94.12%)高于对照组(76.47%),差异有统计学意义(P<0.05);观察组教育后感知益处、感知障碍、感知易感性、感知严重性及自我效能评分均高于对照组,差异有统计学意义(P<0.05);观察组自检行为依从性高于对照组,差异有统计学意义(P<0.05)。结论针对女性体检者实施全面健康教育能够提升其两癌防治知识认知水平与筛查信念,增强自检依从性。

智能超速制动矿车的试验研究

介绍了智能超速制动矿车制动装置的组成结构和工作原理,总结出了智能超速制动矿车的特点,并对应用前景进行了预测分析。

NEW ALGORITHM FOR RECEIVER AUTONOMOUS INTEGRITY MONITORING

A new integrity metric for navigation systems is proposed based on the measurement domain. Proba-hilistic optimization design offers tools for fault detection by considering the required navigation performance （RNP） parameter and the uncertainty noise. The choice of the proper performance parameter provided the single-valued mapping with the missed detection probability estimates the probability of failure. The desirable characteristics of the residual sensitivity matrix are exploited to increase the efficiency for identifying erroneous observations. The algorithm can be used to support the performance specification and the efficient calculation of the integrity monitoring process. The simulation for non-precision approach （NPA） validates both the viability and the effectiveness of the proposed algorithm.

Vision-based long-distance lane perception and front vehicle location for full autonomous vehicles on highway roads

A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.

Endoscopic ultrasonography findings in autoimmune pancreatitis

Endoscopic ultrasonography is an established diagnostic tool for pancreatic masses and chronic pancreatitis.In recent years there has been a growing interest in the worldwide medical community in autoimmune pancreatitis (AIP),a form of chronic pancreatitis caused by an autoimmune process.This paper reviews the current available literature about the endoscopic ultrasonographic findings of AIP and the role of this imaging technique in the management of this protean disease.

A method for constraining the end effect of EMD based on sequential similarity detection and adaptive filter

Aimed at the problem of the end effect when using empirical mode decomposition(EMD),a method for constraining the end effect of EMD is proposed based on sequential similarity detection and adaptive filter.The method divides the signal into many wavelets,and it changes the initial wavelet length to select the best initial wavelet that has the minimum error and maximum number of matching seed wavelets,and the wavelet slopes are used for pre-matching and secondary matching to speed up the matching speed.Then,folded self-adaptive threshold is used to select multiple seed wavelets,and finally the end waveform is predicted and expanded according to the adaptive filter method.The proposed method is used to analyze the non-stationary nonlinear simulation signal and experimental signal,and it is compared with the mirror extension and RBF extension methods.The orthogonality index and similarity index of the EMD results of the extended signal after the proposed method are better than those of the other methods.The results show that the proposed method can better constrain the end effect,and has certain validity,accuracy and stability in solving the end effect problem.

A Review of the Application of Computer Vision to the Inspection and Assessment of Textiles Apparent Properties

Due to its advantages of objectiveness, automation, accuracy and fastness in various applications, the technology of computer vision has become one of the studying hotspots in the area of the objective inspection and assessment of textiles apparent properties during the past two decades in the world. Both a brief review of its applications in the recent decade both at home and abroad to the automatic inspection and assessment of the various apparent properties of the textiles, such as yarn, woven fabrics and knitting fabrics, carpet fabrics, nonwoven fabrics and textile webs, etc., and a detailed introduction to the research work including the objective evaluation of fabric wrinkle grade, automatic fabric defects detection and assessment of fabric pilling grade, etc., that was conducted by our research section, i.e., Computer Vision’s Textiles Application Research Section, College of Textiles, Dong Hua University, have been provided. Experimental results have proved the feasibilities of the approaches used by us in the applications to the objective inspection and assessment of fabric apparent properties, and also indicated that the technology of computer vision is a power tool for the objective and automatic inspection and assessment of textiles apparent properties, and that it has a bright application future.

Induction of Endothelial Cell Apoptosis by Anti-alpha-enolase Antibody

Objective To assess the prevalence of anti-alpha-enolase antibody in systemic autoimmune diseases in Chinese patients and its role in endothelial cell apoptosis.Methods The reactivity of anti-alpha-enolase antibody in a variety of autoimmune disorders in Chinese patients was evaluated by dot blot assay.Endothelial cell apoptosis was investigated by in vitro incubation of endothelial cells with IgG purified from anti-alpha-enolase antibody-positive sera,with or without pre-incubation with recombinant alpha-enolase.Results Anti-alpha-enolase antibody was prevalent in different systemic autoimmune diseases with relatively high reactivity in Chinese patients.In vitro incubation of endothelial cells with IgG containing anti-alpha-enolase antibody induced apoptosis in a time-and dose-dependent manner.Apoptosis was partly inhibited by pre-incubation of the endothelial cells with recombinant alpha-enolase.Conclusions Our data suggest that alpha-enolase is a common auto-antigen recognized by anti-endothelial cell antibodies in connective tissue disease.Interaction between alpha-enolase and its autoantibody plays a role in endothelial cell apoptosis.Changes other than cell killing may contribute to the pathogenesis of endothelial damage and microvascular lesions.

Adaptive multi-modal feature fusion for far and hard object detection

In order to solve difficult detection of far and hard objects due to the sparseness and insufficient semantic information of LiDAR point cloud,a 3D object detection network with multi-modal data adaptive fusion is proposed,which makes use of multi-neighborhood information of voxel and image information.Firstly,design an improved ResNet that maintains the structure information of far and hard objects in low-resolution feature maps,which is more suitable for detection task.Meanwhile,semantema of each image feature map is enhanced by semantic information from all subsequent feature maps.Secondly,extract multi-neighborhood context information with different receptive field sizes to make up for the defect of sparseness of point cloud which improves the ability of voxel features to represent the spatial structure and semantic information of objects.Finally,propose a multi-modal feature adaptive fusion strategy which uses learnable weights to express the contribution of different modal features to the detection task,and voxel attention further enhances the fused feature expression of effective target objects.The experimental results on the KITTI benchmark show that this method outperforms VoxelNet with remarkable margins,i.e.increasing the AP by 8.78%and 5.49%on medium and hard difficulty levels.Meanwhile,our method achieves greater detection performance compared with many mainstream multi-modal methods,i.e.outperforming the AP by 1%compared with that of MVX-Net on medium and hard difficulty levels.

Is enteroscopy necessary for diagnosis of celiac disease?

Celiac disease （CD） is an autoimmune inflammatory disease of the small intestine as a result of reaction to wheat protein, gluten. Exclusion of dietary gluten is the mainstay of the treatment that necessitates a precise diagnosis of the disease. Serological screen ing may aid in identifying patients with suspected CD, which should be confirmed by intestinal biopsy. It has been shown that duodenal biopsies are good for de- tection of the disease in most patients. However, there is a group of patients with positive serology and incon- clusive pathology. As a result of the widespread use of serology, many patients with equivocal findings grow quickly. Unfortunately current endoscopic methods can only diagnose villous atrophy, which can be present in the later grades of disease （i.e., Marsh m）. To diag- nose CD correctly, going deeper in the intestine may be necessary. Enteroscopy can reveal changes in CD in the intestinal mucosa in 10%-17% of cases that have negative histology at initial workup. Invasiveness of the method limits its use. Capsule endoscopy may be a good substitute for enteroscopy. However, both tech- niques should be reserved for patients with suspected diagnosis of complications. This paper reviews the cur- rent literature in terms of the value of enteroscopy for diagnosis of CD.

Fault-Tolerant Control of Nonlinear Systems Based on Fuzzy Neural Networks

Due to its great potentisl value in theory and application, fault-tolerant control atrategies of nonlinear systems, especially combining with intelligent control methods, have been a focus in the academe. A fault-tolerant control method based on fuzzy neural networks was presented for nonlinear systems in this paper. The fault parameters were designed to detect the fault, adaptive updating method was introduced to estimate and track fault, and fuzzy neural networks were used to adjust the fault parameters and construct automated fault diagnosis. And the fault compeusation control force, which was given by fault estimation, was used to realize adaptive fault-tolerant control. This framework leaded to a simple structure, an accurate detection, and a high robusmess. The simulation results in induction motor show that it is still able to work well with high dynamic performance and control precision under the condition of motor parameters＇ variation fault and load torque disturbance.

Frame Detection Based on Cyclic Autocorrelation and Constant False Alarm Rate in Burst Communication Systems

Frame detection is important in burst communication systems for its contribu- tions in frame synchronization. It locates the information bits in the received data stream at receivers. To realize frame detection in the presence of additive white Gaussian noise （AWGN） and frequency offset, a constant false alarm rate （CFAR） detector is proposed through exploitation of cyclic autocorrelation feature implied in the preamble. The frame detection can be achieved prior to bit timing recovery. The threshold setting is independent of the signal level and noise level by utilizing CFAR method. Mathematical expressions is derived in AWGN channel by considering the probability of false alarm and probability of detection, separately. Given the probability of false alarm, the mathematical relationship between the frame detection performance and EJNo of received signals is established. Ex- perimental results are also presented in accor- dance with analysis.

A NEW TEST FOR NORMALITY IN LINEAR AUTOREGRESSIVE MODELS

A nonparametric test for normality of linear autoregressive time series is proposed in this paper.The test is based on the best one-step forecast in mean square with time reverse.Some asymptotic theory is developed for the test,and it is shown that the test is easy to use and has good powers.The empirical percentage points to conduct the test in practice are provided and three examples using real data are included.

Exploring the genetic characteristics of 93-11 and Nipponbare recombination inbred lines based on the Golden Gate SNP assay

Understanding genetic characteristics in rice populations will facilitate exploring evolutionary mechanisms and gene cloning. Numerous molecular markers have been utilized in linkage map construction and quantitative trait locus （QTL） mappings. However, segregation-distorted markers were rarely considered, which prevented understanding genetic characteristics in many populations. In this study, we designed a 384-marker GoldenGate SNP array to genotype 283 recombination inbred lines （RILs） derived from 93-11 and Nipponbare Oryza sativa crosses. Using 294 markers that were highly polymorpbic between parents, a linkage map with a total genetic distance of 1,583.2 cM was constructed, including 231 segregation-distorted mark- ers. This linkage map was consistent with maps generated by other methods in previous studies. In total, 85 significant quanti- tative trait loci （QTLs） with phenotypic variation explained （PVE） values〉5% were identified. Among them, 34 QTLs were overlapped with reported genes/QTLs relevant to corresponding traits, and 17 QTLs were overlapped with reported sterili- ty-related genes/QTLs. Our study provides evidence that segregation-distorted markers can be used in linkage map construc- tion and QTL mapping. Moreover, genetic information resulting from this study will help us to understand recombination events and segregation distortion. Furthermore, this study will facilitate gene cloning and understanding mechanism of in- ter-subspecies hybrid sterility and correlations with important agronomic traits in rice.

Detection of topological symmetry in the one-dimensional Afeck-Kennedy-Lieb-Tasaki model of integer spin with ultracold spinor atoms in optical lattices

A scheme is proposed for detection of the topology in the one-dimensional Afeck-Kennedy-Lieb-Tasaki model,based on ultracold spinor atomic gas in an optical lattice.For this purpose,a global operation O(θ)is introduced with respect to the breaking of spinrotational symmetry.Consequently,the topology can be manifested unambiguously by identifying the special values ofθwhere the expectation value of the global operator with degenerate ground states is vanishing.Furthermore,experimentallyθcan be detected readily by the interference of ultracold atomic gases.This scheme can be implemented readily in experiment since it does not need the addressing of individual atoms or the probing of a boundary.