Analysis of the joint detection capability of the SMILE satellite and EISCAT-3D radar

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.

A long-distance quantum key distribution scheme based on pre-detection of optical pulse with auxiliary state

We construct a circuit based on PBS and CNOT gates, which can be used to determine whether the input pulse is empty or not according to the detection result of the auxiliary state, while the input state will not be changed. The circuit can be treated as a pre-detection device. Equipping the pre-detection device in the front of the receiver of the quantum key distribution （QKD） can reduce the influence of the dark count of the detector, hence increasing the secure communication distance significantly. Simulation results show that the secure communication distance can reach 516 km and 479 km for QKD with perfect single photon source and decoy-state QKD with weak coherent photon source, respectively.

Multi-features Based Approach for Moving Shadow Detection

In the video-based surveillance application, moving shadows can affect the correct localization and detection of moving objects. This paper aims to present a method for shadow detection and suppression used for moving visual object detection. The major novelty of the shadow suppression is the integration of several features including photometric invariant color feature, motion edge feature, and spatial feature etc. By modifying process for false shadow detected, the averaging detection rate of moving object reaches above 90% in the test of Hall-Monitor sequence.

Clinical significance of serum tumor markers CA153, CA125, CA72-4 and FIB, IL-6 levels detection in ovarian cancer

Objective: To investigate the clinical significance of serum tumor markers CA153, CA125, CA72-4 and FIB, IL-6 levels in the detection of ovarian cancer. Methods: A total of 40 patients with ovarian carcinoma treated in our hospital from September 2015 to June 2017 were selected as the ovarian cancer group;40 patients with benign ovarian tumors in the same period were selected as the benign ovarian tumor group;40 healthy subjects were selected as the control group. The levels of tumor markers CA153, CA125, CA72-4 and FIB, IL-6 were compared between the three groups. Results: The CA153, CA125, CA72-4 and FIB, IL-6 levels of the ovarian cancer group were significantly higher than those in benign ovarian tumor group and the control group;these levels in the benign ovarian tumor group was not significantly different from those in the control group. With the increase of clinical phase, the levels of CA153, CA125 and CA72-4 in patients with ovarian cancer were gradually increased, and the levels in phase Ⅲ and Ⅳ were significantly higher than those in phase Ⅱ and in phase I;and the CA125 in phase Ⅱ was significantly higher than that in phase Ⅰ. The levels of FIB and IL-6 in phase Ⅱ and in phase Ⅲ, Ⅳ were significantly higher than those in phase I;the IL-6 level in phase Ⅲ, Ⅳ was significantly higher than that in phase Ⅱ. Conclusion: Serum tumor markers CA153, CA125, CA72-4 and FIB, IL-6 levels for ovarian cancer detection can be helpful for clinical diagnosis and worthy of promotion.

Protecting Against Address Space Layout Randomisation (ASLR) Compromises and Return-to-Libc Attacks Using Network Intrusion Detection Systems

Writable XOR executable （W⊕X） and address space layout randomisation （ASLR） have elevated the understanding necessary to perpetrate buffer overflow exploits [1] . However, they have not proved to be a panacea [1 3] , and so other mechanisms, such as stack guards and prelinking, have been introduced. In this paper, we show that host-based protection still does not offer a complete solution. To demonstrate the protection inadequacies, we perform an over the network brute force return-to-libc attack against a preforking concurrent server to gain remote access to a shell. The attack defeats host protection including W⊕X and ASLR. We then demonstrate that deploying a network intrusion detection systems （NIDS） with appropriate signatures can detect this attack efficiently.

BACKGROUND RECTIFICATION AND FEATURE EXTRACTION OF IMAGE IN A SPOT WELD OF AL ALLOY X-RAY DETECTION

A primary study on Processing in X - ray inspection of spot weld for aluminum alloy spot welding,in- cluding for background simulation,acquisition of ideal binary image, and extraction and identifi- cation of defect features was presented.

Obstacle detection using multi-sensor fusion

This paper presents an obstacle detection approach for blind pedestrians by fusing data from camera and laser sensor.For purely vision-based blind guidance system,it is difficult to discriminate low-level obstacles with cluttered road surface,while for purely laser-based system,it usually requires to scan the forward environment,which turns out to be very inconvenient.To overcome these inherent problems when using camera and laser sensor independently,a sensor-fusion model is proposed to associate range data from laser domain with edges from image domain.Based on this fusion model,obstacle's position,size and shape can be estimated.The proposed method is tested in several indoor scenes,and its efficiency is confirmed.

5-(2-Hydroxylphenyl)diazo-dipyrromethane:Synthesis,Structure and Fluoride Ion Detection

A new azopyrrole compound, 1, has been synthesized and characterized. The crystal of 1 is of monoclinic system, space group P21/c with a = 8.7167（9）, b = 17.5929（19）, c = 12.8096（15） ？, β = 97.565（2）o, V = 1947.3（4） ^3, Z = 4, C（20）H（26）N4O2, Mr = 354.45, Dc = 1.209 g/cm^3, F（000） = 760 and μ（Mo Kα） = 0.080 mm^-1. In the crystal, 1 binds one methanol molecule through N–H…O, O–H…O and O–H…π interactions. UV-Vis titration and 1H NMR titration studies reveal that compound 1 can selectively detect fluoride ion in the DMSO solution.

An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

Significance of combined detection of serum 25(OH)D3, hsa-miR-17-5p and HCV-RNA in the diagnosis of hepatitis C disease

Objective: Significance of combined detection of serum 25(OH)D3, hsa-miR-17-5p and HCV-RNA in diagnosis of hepatitis C disease. Methods: A total of 52 patients with benign ovarian tumor resection were selected from April 2016 to April 2018 in our hospital. We paid attention to the implementation of perioperative nursing intervention, and observed the prognosis and the occurrence of adverse reactions. Results: The expression of hsa-mir-17-5p in the observation group was significantly higher than that in the control group, the expression of 25(OH)D3 was lower than that in the control group, the expression of hsa-mir-17-5p in the HCV-RNA positive group was higher than that in the HCV-RNA negative group, and the expression of 25(OH) D3 was lower than that in the HCV-RNA negative group. The expression of HCV-RNA in the observation group was positively and negatively correlated with the expression of 25(OH) D3 and hsa-mir-17-5p in the 25(OH)D3 and the critical values of serum 25 (OH)D3, hsa-mir-17-5p and HCV-RNA were 24.23 ug/L, 1.89 relative expression and 1.22 × 103 IU/mL, respectively. The area of AUC detected by hsa-miR-17-5p+ 25 (OH) D3+25(OH)D3 is larger than that detected separately. Conclusion: The combined detection of serum 25(OH)D3, hsa-mir-17-5p and HCV-RNA has high diagnostic efficiency and sensitivity for hepatitis C. It is suggested that they be used in clinical practice.

Investigation of the factors affecting the limit of detection of laser-induced breakdown spectroscopy for surface inspection

Laser-induced breakdown spectroscopy(LIBS) was examined to detect a trace substance adhered onto Al alloys for the surface inspection of materials to be adhesively bonded. As an example of Si contamination, silicone oil was employed and sprayed onto substrates with a controlled surface concentration. LIBS measurements employing nanosecond UV pulses(λ?=?266 nm) and an off-axis emission collection system with different detecting heights were performed. Because surface contaminants are involved in the plasma formed by laser ablation of the substrates, the relative contribution of the surface contaminants and the substrates to the plasma emission could be changed depending on the conditions for plasma formation. The limit of detection(LOD) was evaluated under several detecting conditions for investigating the factors that affected the LOD. A significant factor was the standard deviation values of signal intensities obtained for the clean substrates. This value varied depending on the measurement conditions.For the Al alloy(A6061), the smallest LOD obtained was 0.529 μg?·?cm^(-2). Furthermore, an improved LOD(0.299 μg?·?cm^(-2)) was obtained for the Al alloy with a lower Si content.

100例HBV血清标志物、HBV-DNA、HBVpreS_1-Ag对比监测与临床分析

探讨临床监测HBVpreS1-Ag对乙肝患者诊断和预后的意义。对 10 0例乙型病毒性肝炎患者HBV血清标志物、HBV -DNA及preS1-Ag进行定量、定性跟踪监测并加以临床分析。 10 0例患者中HBsAg阳性者 91例 ,preS1-Ag阳性者 5 7例 ,HBeAg阳性者 4 3例 ,HBV -DNA阳性者 5 6例 ,preS1-Ag阳性率与HBV -DNA相似且略高于HBeAg。preS1-Ag比HBeAg更为精确地反映了HBV在人体内感染和复制的情况 ,动态监测

HBV PreS2+S/IFN-α融合基因真核表达载体的构建及其表达

构建含HBVPrdS2 +S和IFN α融合基因的真核表达载体pcDNA3.1.S2S/IFN α并在真核细胞中进行表达。应用重叠延伸剪切技术 (splicingbyoverlappingextension ,简称SOE)经两次PCR获得嵌合基因片段S2S/IFN α ,回收后直接克隆到 pcDNA3.1V5 /HisTOPOTA克隆载体 ,得到真核重组载体pcDNA3.1.S2S/IFN α。然后用脂质体法转染VeroE6细胞。对重组载体进行了限制性酶切及PCR鉴定 ,证明连接正确 ;经间接免疫荧光检测证实该重组载体能在真核细胞中表达插入的外源性基因编码的融合蛋白。真核表达载体pcDNA3.1.S2S/IFN α的成功构建及在VeroE6细胞中的有效表达 。

Preβ-1高密度脂蛋白与心血管疾病关系的研究进展

动脉粥样硬化是心血管疾病重要的病理生理基础,延缓和防治动脉粥样硬化对于减少和降低心血管疾病的发病率及病死率具有重要意义。高密度脂蛋白(high density lipoprotein,HDL)通过参与介导胆固醇逆向转运(reverse cholesterol transport,RCT)在抗动脉粥样硬化的形成和进展中发挥了重要作用。Preβ-1高密度脂蛋白(prebeta-1 high density lipoprotein,Preβ-1HDL)作为HDL的一种亚类,是外周细胞移出胆固醇的最初接受体,直接参与了RCT的起始步骤,并在随后的胆固醇酯化及转运中起着重要作用。本文就Preβ-1HDL的结构、代谢及其与心血管疾病的关系作一简要综述。

乙肝表面抗原、e抗原定量检测与Pre-S1Ag的相关性分析

目的:探讨HBsAg、HBeAg定量检测与Pre-S1Ag的相关性和临床意义。方法:540例乙肝患者血清,经处理,分别进行酶联免疫吸附试验(ELISA)法检测Pre-S1Ag和时间分辨荧光定量PCR法检测HBsAg、HBeAg。对HBsAg、HBeAg(-)组别、HBeAg(+)组别以及Pre-S1Ag进行χ2检验。结果:540份血清标本定量检测显示:(1)E抗原HBeAg(+)组的HBeAg浓度为(49.77±30.78)PEIU/ml,Pre-S1Ag(+)率为81.12%;E抗原HBeAg(-)组的HBeAg浓度为(0.14±0.33)PEIU/ml,Pre-S1Ag(+)率为21.60%;乙肝表面抗原HBsAg(+)组的HBsAg浓度为(139.78±89.10)PEIU/ml,Pre-S1Ag(+)率为35.00%。HBeAg(+)组和Pre-S1Ag无统计学意义,P>0.05;HBeAg(-)组、HBsAg(+)组和Pre-S1Ag具有统计学差异,P<0.05。(2)HBeAg(+)HBsAg(+)HBcAb(+),HBsAg浓度为(212.30±46.90)PEIU/ml,Pre-S1Ag(+)率为81.12%;HBeAb(+)HBsAg(+)HBcAb(+),HBsAg浓度为(139.78±89.10)PEIU/ml,Pre-S1Ag(+)率为27.95%。结论:通过检测Pre-S1Ag可以了解乙肝患者体内是否存在病毒复制情况。

半监督SBERT-SP微博热点话题检测方法

在话题检测任务中,面对微博这类短文本时,针对SBERT模型的特征提取能力的局限性,以及在聚类阶段,单遍聚类算法存在的小簇问题和效率问题,对两者改进,提出一种基于半监督SBERT与SinglePass(semi-supervised SBERT with SinglePass clustering,Semi-SBERT-SP)的微博热点话题检测方法,将SBERT模型结合半监督训练,提高其短文本特征提取能力。在聚类阶段过程中引入时间窗口和降维,提高算法效率,增加一个合并层,处理算法产生的小簇。在话题表示层,提出一种融入词热度的词贡献指标,用于提取话题簇中的关键词。实验结果表明,该方法在准确率、F1、互信息3个指标上均优于对比模型或方法,能够有效检测出微博中包含的热点话题。

Cooperative Spectrum Sensing over Generalized Fading Channels Based on Energy Detection

This paper analyzes the unified performance of energy detection(ED) of spectrum sensing(SS) over generalized fading channels in cognitive radios(CRs). The detective performance of SS will be obviously affected by fading channels among communication nodes, and ED has the advantages of fast implementation, no requirement of priori received information and low complexity, so it is meaningful to investigate ED over various fading channels. The probability density function(p.d.f.) of α-κ-μ distribution is derived to evaluate energy efficiency for sensing systems.The detection probability with Marcum-Q function has been derived and the close-form expressions with moment generating function(MGF) method are deduced to achieve SS.Furthermore, exact closed-form analytic expressions for average area under the receiver operating characteristics curve( AUC) also have been deduced to analyze the performance characteristics of ED over α-κ-μ fading channels.Besides, cooperative spectrum sensing(CSS) with diversity reception has been applied to improve the detection accuracy and mitigate the shadowed fading features with OR-rule. At last, the results show that the detection capacity of ED will be evidently affected by α-κ-μ fading channels, but appropriate channel parameters can improve sensing performance. In addition, the establishedED-fading pattern is approved by simulations,and it can significantly enhance the detection performance of proposed algorithms.

Test analysis of detection of damage to a complicated spatial model structure

A two-stage damage detection approach is proposed and experimentally demonstrated on a complicated spatial model structure with a limited number of measurements. In the experiment,five known damage patterns,including 3 brace damage cases and 2 joint damage cases,were simulated by removing braces and weakening beam鈥揷olumn connections in the structure. The limited acceleration response data generated by hammer impact were used for system identification,and modal parameters were extracted by using the eigensystem realization algorithm. In the first stage,the possible damaged locations are determined by using the damage index and the characteristics of the analytical model itself,and the extent of damage for those substructures identified at stage I is estimated in the second stage by using a second-order eigen-sensitivity approximation method. The main contribution of this paper is to test the two-stage method by using the real dynamic data of a complicated spatial model structure with limited sensors. The analysis results indicate that the two-stage approach is ableto detect the location of both damage cases,only the severity of brace damage cases can be assessed,and the reasonable analytical model is critical for successful damage detection.

3D obstacle detection of indoor mobile robots by floor detection and rejection

Obstacle detection is essential for mobile robots to avoid collision with obstacles.Mobile robots usually operate in indoor environments,where they encounter various kinds of obstacles;however,2D range sensor can sense obstacles only in 2D plane.In contrast,by using 3D range sensor,it is possible to detect ground and aerial obstacles that 2D range sensor cannot sense.In this paper,we present a 3D obstacle detection method that will help overcome the limitations of 2D range sensor with regard to obstacle detection.The indoor environment typically consists of a flat floor.The position of the floor can be determined by estimating the plane using the least squares method.Having determined the position of the floor,the points of obstacles can be known by rejecting the points of the floor.In the experimental section,we show the results of this approach using a Kinect sensor.