Strong Correlation of Abnormal Serum and Urinary Iodine Levels with Papillary Thyroid Cancer:A Case-control Study

Thyroid cancer is the most common malignancy of the endocrine system,and its incidence is increasing worldwide.In China,its incidence has increased from 1.78/104 in 1988 to 10.58/104 in2013.Thyroid cancers are mainly classified into papillary thyroid cancer(PTC),follicular thyroid cancer(FTC),medullary thyroid cancer(MTC).

3D prestack reverse time migration of ground penetrating radar data based on the normalized correlation imaging condition

The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment.To better handle the multi-off set GPR data,we propose a three-dimensional(3D)prestack RTM algorithm.The high-order fi nite diff erence time domian(FDTD)method,with the accuracy of eighth-order in space and second-order in time,is applied to simulate the forward and backward extrapolation electromagnetic fi elds.In addition,we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace fi lter to suppress the low frequency noise generated during the correlation process.The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model.Compared with 2D RTM image,the 3D RTM image can more clearly and accurately refl ect the 3D spatial distribution of the target,and the resolution of the imaging results is far better.Furthermore,the application of observed GPR data further validates the eff ectiveness of the proposed 3D GPR RTM algorithm,and its fi nal image can more reliably guide the subsequent interpretation.

Correlation between abnormal trends in the spontaneous fields of tectonic plates and strong seismicities

Tectonic activities, electrical structures, and electromagnetic environments are major factors that affect the stability of spontaneous fields. The method of corre- lating regional synchronization contrasts （CRSC） can determine the reliability of multi-site data trends or shortimpending anomalies. From 2008 to 2013, there were three strong earthquake cluster periods in the North-South seismic belt that lasted for 8-12 months. By applying the CRSC method to analyze the spontaneous field Esp at 25 sites of the region in the past 6 years, it was discovered that for each strong earthquake cluster period, the Esp strength of credible anomalous trends was present at minimum 30% of the stations. In the southern section of the Tan-Lu fault zone, the Esp at four main geoelectric field stations showed significant anomalous trends after June 2015, which could be associated with the major earthquakes of the East China Sea waters （Ms 7.2） in November 2015 and Japan＇s Kyushu island （Ms 7.3） in April 2016.

Transition Periods Between Sea Ice Concentration and Sea Surface Air Temperature in the Arctic Revealed by an Abnormal Running Correlation

This study used the synthetic running correlation coefficient calculation method to calculate the running correlation coefficients between the daily sea ice concentration(SIC) and sea surface air temperature(SSAT) in the Beaufort-Chukchi-East Siberian-Laptev Sea(BCEL Sea), Kara Sea and southern Chukchi Sea, with an aim to understand and measure the seasonally occurring changes in the Arctic climate system. The similarities and differences among these three regions were also discussed. There are periods in spring and autumn when the changes in SIC and SSAT are not synchronized, which is a result of the seasonally occurring variation in the climate system. These periods are referred to as transition periods. Spring transition periods can be found in all three regions, and the start and end dates of these periods have advancing trends. The multiyear average duration of the spring transition periods in the BCEL Sea, Kara Sea and southern Chukchi Sea is 74 days, 57 days and 34 days, respectively. In autumn, transition periods exist in only the southern Chukchi Sea, with a multiyear average duration of only 16 days. Moreover, in the Kara Sea, positive correlation events can be found in some years, which are caused by weather time scale processes.

Abnormal Event Correlation and Detection Based on Network Big Data Analysis

With the continuous development of network technology,various large-scale cyber-attacks continue to emerge.These attacks pose a severe threat to the security of systems,networks,and data.Therefore,how to mine attack patterns from massive data and detect attacks are urgent problems.In this paper,an approach for attack mining and detection is proposed that performs tasks of alarm correlation,false-positive elimination,attack mining,and attack prediction.Based on the idea of CluStream,the proposed approach implements a flow clustering method and a two-step algorithm that guarantees efficient streaming and clustering.The context of an alarm in the attack chain is analyzed and the LightGBM method is used to perform falsepositive recognition with high accuracy.To accelerate the search for the filtered alarm sequence data to mine attack patterns,the PrefixSpan algorithm is also updated in the store strategy.The updated PrefixSpan increases the processing efficiency and achieves a better result than the original one in experiments.With Bayesian theory,the transition probability for the sequence pattern string is calculated and the alarm transition probability table constructed to draw the attack graph.Finally,a long-short-term memory network and embedding word-vector method are used to perform online prediction.Results of numerical experiments show that the method proposed in this paper has a strong practical value for attack detection and prediction.

Relative ordering of square-norm distance correlations in open quantum systems

We investigate the square-norm distance correlation dynamics of the Bell-diagonal states under different local deco- herence channels, including phase flip, bit flip, and bit-phase flip channels by employing the geometric discord （GD） and its modified geometric discord （MGD）, as the measures of the square-norm distance correlations. Moreover, an explicit comparison between them is made in detail. The results show that there is no distinct dominant relative ordering between them. Furthermore, we obtain that the GD just gradually deceases to zero, while MGD initially has a large freezing interval, and then suddenly changes in evolution. The longer the freezing interval, the less the MGD is. Interestingly, it is shown that the dynamic behaviors of the two geometric discords under the three noisy environments for the Werner-type initial states are the same.

Evaluation of right ventricular volume and systolic function in normal fetuses using intelligent spatiotemporal image correlation

BACKGROUND Heart defects are the most common congenital malformations in fetuses.Fetal cardiac structure and function abnormalities lead to changes in ventricular volume.As ventricular volume is an important index for evaluating fetal cardiovascular development,an effective and reliable method for measuring fetal ventricular volume and cardiac function is necessary for accurate ultrasonic diagnosis and effective clinical treatment.The new intelligent spatiotemporal image correlation(iSTIC)technology acquires high-resolution volumetric images.In this study,the iSTIC technique was used to measure right ventricular volume and to evaluate right ventricular systolic function to provide a more accurate and convenient evaluation of fetal heart function.AIM To investigate the value of iSTIC in evaluating right ventricular volume and systolic function in normal fetuses.METHODS Between October 2014 and September 2015,a total of 123 pregnant women received prenatal ultrasound examinations in our hospital.iSTIC technology was used to acquire the entire fetal cardiac volume with off-line analysis using QLAB software.Cardiac systolic and diastolic phases were defined by opening of the atrioventricular valve and the subsequent closure of the atrioventricular valve.The volumetric data of the two phases were measured by manual tracking and summation of multiple slices and recording of the right ventricular end-systolic volume and the right ventricular end-diastolic volume.The data were used to calculate the right stroke volume,the right cardiac output,and the right ejection fraction.The correlations of changes between the above-mentioned indices and gestational age were analyzed.The right ventricular volumes of 30 randomly selected cases were measured twice by the same sonographer,and the intraobserver agreement measurements were calculated.RESULTS Among the 123 normal fetuses,the mean right ventricular end-diastolic volume increased from 0.99±0.34 mL at 22 wk gestation to 3.69±0.36 mL at 35+6 wk gestation.The mean right ventricular end-systolic volume increased from 0.43±0.18 mL at 22 wk gestation to 1.36±0.22 mL at 35+6 wk gestation.The mean right stroke volume increased from 0.62±0.29 mL at 22 wk gestation to 2.33±0.18 mL at 35+6 wk gestation.The mean right cardiac output increased from 92.23±40.67 mL/min at 22 wk gestation to 335.83±32.75 mL/min at 35+6 wk gestation.Right ventricular end-diastolic volume,right ventricular end-systolic volume,right stroke volume,and right cardiac output all increased with gestational age and the correlations were linear(P<0.01).Right ejection fraction had no apparent correlation with gestational age(P>0.05).CONCLUSION Fetal right ventricular volume can be quantitatively measured using iSTIC technology with relative ease and high repeatability.iSTIC technology is expected to provide a new method for clinical evaluation of fetal cardiac function.

Electron-correlation-induced band renormalization and Mott transition in Ca_(1-x)Sr_xVO_3

We present the local density approximate＋Gutzwiller results for the electronic structure of Cal-xSrxVOa. The substitution of Sr2＋ by Ca2＋ reduces the bandwidth, as the V-O-V bond angle decreases from 180° for SrVO3 to about 160° for CaVO3. However, we find that the bandwidth decrease induced by the V-O-V bond angle decrease is smaller as compared to that induced by electron correlation. In correlated electron systems, such as Cal-=Sr=VOa, the correlation effect of 3d electrons plays a leading role in determining the bandwidth. The electron correlation effect and crystal field splitting collaboratively determine whether the compounds will be in a metal state or in a Mort-insulator phase.

Classical Correlations vs Quantum Correlations—Similarities, Differences, Opportunities

Classical Correlations were founded in 1900 by Karl Pearson and have since been applied as a statistical tool in virtually all sciences. Quantum correlations go back to Albert Einstein et al. in 1935 and Erwin Schrödinger’s responses shortly after. In this paper, we contrast classical with quantum correlations. We find that classical correlations are weaker than quantum correlations in the CHSH framework. With respect to correlation matrices, the trace of classical correlation matrices is dissimilar to quantum density matrices. However, the off-diagonal terms have equivalent interpretations. We contrast classical dynamic (i.e., time evolving) stochastic correlation with dynamic quantum density matrices and find that the off-diagonal elements, while different in nature, have similar interpretations. So far, due to the laws of quantum physics, no classical correlations are applied to the quantum spectrum. However, conversely, quantum correlations are applied in classical environments such as quantum computing, cryptography, metrology, teleportation, medical imaging, laser technology, the quantum Internet and more.

Structural identification and antioxidative activity evaluation of flaxseed lignan macromolecules: structure-activity correlation

Flaxseed lignan macromolecules(FLM)are a class of important secondary metabolites in fl axseed,which have been widely concerned due to their biological and pharmacological properties,especially for their antioxidative activity.For the composition and structure of FLM,our results confirmed that ferulic acid glycoside(FerAG)was directly ester-linked with herbacetin diglucoside(HDG)or pinoresinol diglucoside(PDG),which might determine the beginning of FLM biosynthesis.Additionally,p-coumaric acid glycoside(CouAG)might determine the end of chain extension during FLM synthesis in fl axseed.FLM exhibited higher antioxidative activity in polar systems,as shown by its superior 1,1-diphenyl-2-picrylhydrazyl(DPPH)free radical scavenging capacity compared to the 2,2’-azinobis(3-ehtylbenzothiazolin-6-sulfnic acid)(ABTS)cation free radical scavenging capacity in non-polar systems.Moreover,the antioxidative activity of FLM was found to be highly dependent on its composition and structure.In particular,it was positively correlated with the number of phenolic hydroxyl groups(longer FLM chains)and inversely related to the steric hindrance at the ends(lower levels of FerAG and CouAG).These fi ndings verifi ed the potential application of FLM in nonpolar systems,particularly in functional food emulsions。

Track correlation algorithm based on CNN-LSTM for swarm targets

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for correlation.In this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm targets.Precisely, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

基于最弱t-norm算法模糊贝叶斯网络土石坝渗漏风险分析

针对土石坝工程渗漏影响要素多,风险评估体系不完善的问题,提出一种基于最弱t-norm算法模糊贝叶斯网络的土石坝渗漏风险分析模型。首先基于土石坝渗漏破坏成因构建土石坝渗漏风险分析网络,再基于层次分析法和最弱t-norm聚合算法求解不同专家判断的相似性结果,最后将相似性结果转化为概率后代入贝叶斯理论计算水库渗漏破坏风险。以2005年英德尔水库渗漏破坏事件为例,计算得到该库渗漏破坏概率为0.08,属于不可接受风险,并通过反向诊断验证了该模型的可靠性与灵敏性优于传统算法。研究结果可为土石坝渗流风险分析与处置决策提供参考。

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

REFINEMENTS OF THE NORM OF TWO ORTHOGONAL PROJECTIONS

In this paper,some refinements of norm equalities and inequalities of combination of two orthogonal projections are established.We use certain norm inequalities for positive contraction operator to establish norm inequalities for combination of orthogonal projections on a Hilbert space.Furthermore,we give necessary and sufficient conditions under which the norm of the above combination of o`rthogonal projections attains its optimal value.

First results of turbulence investigation on Globus-M2 using radial correlation Doppler reflectometry

The first results of investigation of the turbulence structure using Doppler backscattering(DBS)on the Globus-M2 tokamak are presented.A one-channel DBS system with a variable probing frequency within the 18–26 GHz range was installed to investigate the edge plasma at normalized minor radiiρ=0.9–1.1.Radial correlation Doppler reflectometry was used to study the changes in turbulence eddies after the LH transition.Correlation analysis was applied to the phase derivative of complex in-phase and quadrature(IQ)signals of the DBS diagnostic as it contains information about the poloidal plasma rotation velocity.In L-mode,the radial correlation length L_(r)is estimated to be 3 cm and after transition to H-mode reduces to approximately 2 cm.Gyrokinetic modelling in a linear local approximation using code GENE indicates that the instability with positive growth rate at the normalized minor radiusρ=0.75 in L-mode and H-mode on Globus-M2 was the ion temperature gradient(ITG)mode.

A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.

Filling dependence of correlation exponents and metal-Mott insulator transition in strongly correlated electron systems

Using a universal relation between electron filling factor and ground state energy, this paper studies the dependence of correlation exponents on the electron filling factor of one-dimensional extended Hubbard model in a strong coupling regime, and demonstrates that in contrast to the usual Hubbard model （gc = 1/2）, the dimensionless coupling strength parameter gc heavily depends on the electron filling, and it has a ＂particle-hole＂ symmetry about electron quarter filling point. As increasing the nearest neighbouring repulsive interaction, the single particle spectral weight is transferred from low energy to high energy regimes. Moreover, at electron quarter filling, there is a metal-Mott insulator transition at the strong coupling point gc = 1/4, and this transition is a continuous phase transition.

Study of baryon number transport dynamics and strangeness conservation effects using Ω-hadron correlations

In nuclear collisions at RHIC energies, an excess of Ω hyperons over ■ is observed, indicating that Ω has a net baryon number despite s and s quarks being produced in pairs. The baryon number in Ω may have been transported from the incident nuclei and/or produced in the baryon-pair production of Ω with other types of anti-hyperons such as Ξ. To investigate these two scenarios, we propose to measure the correlations between Ω and K and between Ω and anti-hyperons. We use two versions, the default and string-melting, of a multiphase transport(AMPT) model to illustrate the method for measuring the correlation and to demonstrate the general shape of the correlation. We present the Ω-hadron correlations from simulated Au+Au collisions at ■ =7.7 and 14.6 Ge V and discuss the dependence on the collision energy and on the hadronization scheme in these two AMPT versions. These correlations can be used to explore the mechanism of baryon number transport and the effects of baryon number and strangeness conservation on nuclear collisions.

Dynamics of Non-Markovianity, Quantum Correlations and Information Scrambling of Three Qubits Systems Interacting via Rashba Interaction

The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate between their upper and lower bounds, where the number of oscillations increases as the Rashba interaction strength increases. The exchanging rate of these three quantities depends on the Rashba strength, and whether the entangled state is generated via direct/indirect interaction. Moreover, the coherence parameter can be used as a control parameter to maximize or minimize the three physical quantities.