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As the ocean engineering structure serves in the critical underwater environment, a variety of defects, such as cracks and corrosions, always cause damage to the structure. It is still a key challenge to identify and evaluate these defects accurately in the underwater environment. In this paper, the visual and intelligent identification methods are presented for the inspection of defects in underwater structures using the alternating current field measurement (ACFM) technique. The current perturbation theory is developed to analyze the disturbed current field and the distorted magnetic field caused by defects. The gradient imaging algorithm is presented as an image preprocessing method to highlight the visual morphology of defects. The underwater intelligent ACFM system is set up. The experiments are carried out to verify the gradient imaging algorithm. The convolutional neural network (CNN) deep learning algorithm is presented to identify the grey-scale map samples preprocessed by the gradient imaging algorithm. The results show that the current perturbation theory clarifies the relationship between the characteristic signal and the morphology of various defects. The Bz image reflects the surface morphology of defects. The gradient imaging algorithm can achieve visual detection of defects. The single crack, the irregular crack and the corrosion can be identified intelligently by the CNN deep learning algorithm. These defects can be evaluated accurately after classification.

We present precise measurements of the quantum defects of cesium $n$F$_J$ Rydberg levels. We employ high-precision microwave spectroscopy of $(n+2)\mathrm{D}_{5/2}\rightarrow n\mathrm{F}_{5/2,7/2}$ transitions for $n=45$ to 50 in a cold-atom setup. Cold cesium $(n+2)$D$_{5/2}$ atoms, prepared via two-photon laser excitation, are probed by scanning weak microwave fields interacting with the atoms across the $n\mathrm{F}_{5/2,7/2}$ resonances. Transition spectra are acquired using state-selective electric-field ionization and time-gated ion detection. Transition-frequency intervals are obtained by Lorentzian fits to the measured spectral lines, which have linewidths ranging between 70~kHz and 190~kHz, corresponding to about one to three times the Fourier limit. A comprehensive analysis of relevant line-shift uncertainties and line-broadening effects is conducted. We find quantum defect parameters $\delta_{0}(\mathrm{F}_{5/2})=0.03341537(70)$ and $\delta_{2}(\mathrm{F}_{5/2})=-0.2014(16)$, as well as $\delta_{0}(\mathrm{F}_{7/2})=0.0335646(13)$ and $\delta_{2}(\mathrm{F}_{7/2})=-0.2052(29)$, for $J=5/2$ and $J=7/2$, respectively. Fine structure parameters $A_{FS}$ and $B_{FS}$ for Cs $n{\rm{F}}_J$ are also obtained. Results are discussed in context with previous works, and the significance of the results is discussed.

As an important connection method between drill pipes, the thread is prone to fatigue cracks and stress corrosion cracks due to long-term exposure to complex forces and corrosive environments. The thread crack detection system of drill pipe based on altering current field measurement (ACFM) is proposed. The crack detection model of the drill pipe thread using ACFM is developed by the finite element software COMSOL. The distribution of the induced magnetic field above the thread is extracted. The relationships between the characteristic signal and the depth and angle of the crack are analyzed. The drill pipe thread detection probes and the detection system are established, and different types of cracks on two different specifications of threads are detected. The experimental results show that the detection system can achieve full coverage detection of the thread crest and root, and cracks at different angle can be identified effectively on the thread.

The dynamic and static property assessment of industrial robot is of great significance to optimize its operation accuracy. A method for both the kinematic calibration and robot path error measurement based on camera-mirror binocular vision (CMBV) is proposed. First, the structural parameters of CMBV are investigated for identifying proper imaging parameters. Second, the high-accuracy all-in-one artifact, its image processing, and vision system calibration are introduced. Thereafter, a CMBV-matching model based on distance error constraint is proposed to identify robot kinematic parameters. Finally, by comparing the vision measured data and the nominal one, both the path error and kinematic model parameters are measured. The verification results based on artifact and laser tracker verify that the proposed vision system and method is accurate enough to assess the robot performance. The results of vision measurement show that at 1.5 m/min, the maximum circular trajectory error of vision measurement is 2.57 mm, and after compensating the determined robot kinematic model parameters, the average positioning accuracy of the robot end-effector is increased by more than 73.36%, which means that the CMBV-based method outperforms the monocular pose measurement (MPM) method.

We demonstrate a continuous frequency electric field measurement based on the far off-resonant AC stark effect in a Rydberg atomic vapor cell. In this configuration, a strong far off-resonant field, denoted as a local oscillator (LO) field, acts as a gain shifting the Rydberg level to a high sensitivity region. An incident weak signal field with a few hundreds of kHz difference from the LO field is mixed with the LO field in Rydberg system to generate an intermediate frequency (IF) signal, which is read out by the Rydberg electromagnetically induced transparency (Rydberg-EIT) spectroscopy. Not like resonant EIT-AT spectra, we realize the electric field measurement of the signal frequency from 2 GHz to 5 GHz using a single Rydberg state. A minimum detectable filed strength is down to 2.31~$\mu$V/cm and a linear dynamic range is over 65~dB. The minimum detectable filed is comparable with a resonant microwave-dressed Rydberg heterodyne receiver using the same system, which is 1.45~$\mu$V/cm. We also show the system has an inherent polarization selectivity feature. Our method can provide a high sensitivity of electric field measurement and be extended to arbitrary frequency measurements., Comment: 5 pages, 4 figures

We study steady state phases of a one-dimensional array of Rydberg atoms coupled by a microwave (MW) field where the higher energy Rydberg state decays to the lower energy one via single-body and collective (superradiant) decay. Using mean-field approaches, we examine the interplay among the MW coupling, intra-state van der Waals (vdW) interaction, and single-body and collective dissipation between Rydberg states. A linear stability analysis reveals that a series of phases, including uniform, antiferromagnetic, oscillatory, and bistable and multistable phases can be obtained. Without the vdW interaction, only uniform phases are found. In the presence of the vdW interaction, multistable solutions are enhanced when increasing the strength of the superradiant decay rate. Our numerical simulations show that the bistable and multistable phases are stabilized by superradiance in a long chain. The critical point between the uniform and multistable phases and its scaling with the atom number is obtained. Through numerically solving the master equation of a finite chain, we show that the mean-field multistable phase could be characterized by expectation values of Rydberg populations and two-body correlations between Rydberg atoms in different sites.

In recent years, with the exploitation of shale gas, the amount of coiled tubing has increased dramatically. Due to the harsh working environment, the wall thickness of the coiled tubing is easily thinned. In this paper, The coiled tubing wall thickness evaluation system is proposed based on the pulsed alternating current field measurement technique. The coiled tubing wall thickness evaluation model using pulsed alternating current field is developed by the finite element software COMSOL. The Bx signal is selected as the characteristic signal of thickness evaluation, and the relationship between characteristic signal and wall thickness is analyzed. According to the detection characteristics of the coiled tubing, probe and system for the wall thickness evaluation of the coiled tubing are designed and established. And the test experiment is carried out on different thicknesses of coiled tubing. The test results show that the detecting system can quantitatively evaluate the wall thickness of the coiled tubing accurately.

Pipes are important components for well drilling, production, and transportation in petroleum industry. However, due to factors such as vibration, corrosion, fatigue damage, etc., pipes are prone to cracks. This paper presents a novel ACFM probe with flexible sensor array for the inspection of inner and outer cracks in pipes with different diameters. The simulation model of the ACFM probe with flexible sensor array is established by the finite element method. The influences of the crack length and the lift-off on the distance between the Bz peaks and troughs are analyzed respectively. The relationship between the offset distance of the crack from the pickup coil center and the detection sensitivity is studied. The probe made by flexible PCB and the testing system are developed. The experiments are carried out. The results of experiments and simulations show that the probe with flexible sensor array can detect inner and outer surface cracks for pipes with different diameters, and both circumferential and axial cracks can be identified. The distance between the Bz peaks and troughs can measure the crack length. When the crack is offset from the center of the pickup coil, the adjacent pickup coil can compensate for the detection sensitivity.

The evaluation of industrial robot path accuracy is significant for improving its dynamic operating performance. In this paper, a monocular stereo vision (MSV) based method is proposed for measuring the path error of robot end-effectors. Firstly, the structure parameters of the MSV system are analyzed to determine appropriate imaging parameters of the equivalent virtual binocular vision (VBV). Secondly, to save cost and measurement time, an all-in-one high-accuracy artifact, which integrates path representation and camera calibration, is designed. And accordingly, an improved decoding method is proposed to distinguish different tags on the artifact. After calibrating depth of field (DoF) dependent lens distortion, the path accuracy can be assessed with high-accuracy by the difference between path measured by the vision and the nominal one. Experimental results show that the MSV system with an average measurement accuracy of 0.012 mm can evaluate the path performance of the robot, and the maximum circular path error at 1.5 m/min is 0.252 mm.

Aluminum and alloy tubes are widely used in industrial fields because of the advantages of good corrosion resistance, high thermal conductivity and light weight. Due to the stress corrosion cracking (SCC) and fatigue corrosion cracking (FCC), both inner and outer cracks generate in the aluminum tube. It is still a challenge to inspect all inner and outer surface cracks in the thick-wall aluminum tube in real time by one pass scan using the nondestructive testing (NDT) method. A double frequency circumferential current field testing (CCFT) method is presented for the inspection of both inner and outer cracks in the aluminum tube by one pass scan. A simulation model is proposed to extract characteristic signals of inner and outer cracks at two excitation frequencies. The bobbin-type probe with sensor array is developed and excited by the synthetic double frequency excitation signal. Both inner and outer cracks are tested by the double frequency CCFT system. Results show that both inner and outer cracks can be identified, distinguished and evaluated by the double frequency CCFT method by one pass scan.

Mobile video communication and Internet of Things are playing a more and more important role in our daily life. Mobile Edge Computing (MEC), as the essential network architecture for the Internet, can significantly improve the quality of video streaming applications. The mobile devices transferring video flow are often exposed to hostile environment, where they would be damaged by different attackers. Accordingly, Mobile Edge Computing Network is often vulnerable under disruptions, against either natural disasters or human intentional attacks. Therefore, research on secure hub location in MEC, which could obviously enhance the robustness of the network, is highly invaluable. At present, most of the attacks encountered by edge nodes in MEC in the IoT are random attacks or random failures. According to network science, scale-free networks are more robust than the other types of network under the random failures. In this paper, an optimization algorithm is proposed to reorganize the structure of the network according to the amount of information transmitted between edge nodes. BA networks are more robust under random attacks, while WS networks behave better under human intentional attacks. Therefore, we change the structure of the network accordingly, when the attack type is different. Besides, in the MEC networks for mobile video communication, the capacity of each device and the size of the video data influence the structure significantly. The algorithm sufficiently takes the capability of edge nodes and the amount of the information between them into consideration. In robustness test, we set the number of network nodes to be 200 and 500 and increase the attack scale from 0% to 100% to observe the behaviours of the size of the giant component and the robustness calculated for each attack method. Evaluation results show that the proposed algorithm can significantly improve the robustness of the MEC networks and has good potential to be applied in real-world MEC systems.

IIoT (Industrial Internet of Things) has gained considerable attention and has been increasingly applied due to its ubiquitous sensing and communication. However, the sparse characteristic of sensing data in distributed IIoT networks may bring out tremendous challenges to implement the security protection measures. Based on the design of centralized data gathering and forwarding, this paper proposes a novel anomaly detection approach for IIoT sparse data, which can successfully collaborate the adaptive CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) feature exploitation with one intelligent optimizing classification. Furthermore, in the adaptive CEEMDAN feature exploitation, the CEEMDAN energy entropy based on adaptive IMF (Intrinsic Mode Function) selection is designed to extract the sensing features from IIoT sparse data; in the intelligent optimizing classification, one effective OCSVM (One-Class Support Vector Machine) classifier optimized by the IABC (Improved Artificial Bee Colony) swarm intelligence algorithm is introduced to detect various abnormal sensing features. The experimental results show that, not only does the CEEMDAN energy entropy based on adaptive IMF selection accurately describe the change of industrial production by analyzing the probability distribution and energy distribution of sparse sensing data, but also the proposed IABC-OCSVM classifier has higher detection efficiency compared with the OCSVM classifiers optimized by other swarm intelligence algorithms.

Nyssa yunnanensis is a deciduous tree species in family Nyssaceae within the order Cornales. As owning only eight individuals in two sites recorded in Yunnan province of China, this species was listed as the China’s national grade-I protection species in 1999, and also as one of 120 PSESP (Plant Species with Extremely Small Populations) in Implementation Plan of Rescuing and Conserving China’s Plant Species with extremely Small Populations(PSESP) (2011-2-15). N. yunnanensis was also been evaluated as Critically Endangered in IUCN red list and Threatened Species List of China's Higher Plants. Hence understanding the genomic characteristics of this highly endangered Tertiary relict tree species is essential, especially for developing conservation strategies. Here we present the draft genome assembly of N. yunnanensis. Using 10X genomics linked-reads sequencing data, we carried out the de novo assembly and annotation analysis. The N. yunnanensis genome assembly is 1475 Mb in length containing 288,519 scaffolds with a scaffold N50 length of 985.59 kb. 799.51 Mb of the assembled genome was identified as repetitive elements, accounting for 54.24% of the sequenced genome. And a total of 39,803 protein-coding genes were annotated. The genomic data of N. yunnanensis provided in this study will provide basic information for future genomic and evolutionary studies. With the genomic characteristics of N. yunnanensis available, our study might also facilitate in future conservation biology studies to help protecting this extremely threatened tree species.

Cs$_2$ Rydberg-ground molecules consisting of a Rydberg, $nD_{J}$ (33 $\leq$ $n$ $\leq$ 39), and a ground state atom, 6$S_{1/2} (F=$3 or 4$)$, are investigated by photo-association spectroscopy in a cold atomic gas. We observe vibrational spectra that correspond to triplet $^T\Sigma$ and mixed $^{S,T}\Sigma$ molecular states. We establish scaling laws for the energies of the lowest vibrational states vs principal quantum number and obtain zero-energy singlet and triplet $s$-wave scattering lengths from experimental data and a Fermi model. Line broadening in electric fields reveals the permanent molecular electric-dipole moments; measured values agree well with calculations. We discuss the negative polarity of the dipole moments, which differs from previously reported cases., Comment: 5 pages, 4 figures

Software Defined Networking (SDN) is a new type of network architecture, which provides an important way to implement automated network deployment and flexible management. However, security problems in SDN are also inevitable. DDoS attack belongs to one of the most serious attack types, which is fairly common for today’s Internet. In SDN security fields, DDoS attack detection research has been received more and more attention. In this paper, a DDoS attack detection method based on one-class SVM in SDN is proposed, which provides a better detection accuracy. Furthermore, two new feature vectors, including middle value of flow table item’s duration and protocol data traffic percentage, are extracted to integrate into the item of 11 feature vectors. Additionally, basing on selection and construction method of the 11 feature vectors, a DDoS attack behavior model is established by using one-class SVM algorithm, and the self-adaptation genetic algorithm is designed to optimize the corresponding parameters of the Gaussian kernel of one-class SVM. The experimental results in SDN show that, the proposed new feature vectors are shown to more better detection accuracy, and the proposed method is more feasible by comparing with the BP neural network and RBF neural network algorithms under the same 11 features vectors.

Imaging and evaluation of inner-wall cracks are significant for the integrity management of aluminum tubes. In this paper, a novel bobbin coil probe with sensor arrays is presented for the imaging and evaluation of longitudinal cracks inside aluminum tubes. The finite element method model is developed to analyze the characteristic signals of the crack. The bobbin coil probe with inside tunnel magneto resistance (TMR) sensor arrays is developed for imaging of inner-wall longitudinal cracks. The depth and length of longitudinal cracks are evaluated by the characteristic signals. The results show that the detection sensitivity of the longitudinal crack can be improved greatly when the lift-off of the bobbin coil decreases with inside TMR sensors. The inner-wall cracks inside the aluminum tube can be imaged visually using the bobbin coil with inside TMR sensor arrays. The crack depth and length can be evaluated accurately by the detection sensitivity of the Bx in and the distance between the peaks of the Bz in respectively.

The feasibility and accuracy of four-mirror-based monocular stereo vision (FMSV) are related to the system layout and calibration accuracy, respectively. In this study, a spatial light path analysis method and a calibration method are proposed for an FMSV system. As two-dimensional light path analysis cannot fully characterize the imaging parameters, a spatial light path model is proposed, which allows refinement of the system design. Then, considering the relationship between the lens distortion and the imaging depth of field (DoF), a DoF-distortion equal-partition-based model is established. In the traditional calibration method, the optical axis must be perpendicular to the chessboard. Here, an accurate and practical FMSV calibration method without this constraint is proposed based on the above model. Using the proposed spatial light path analysis technique, a high-accuracy, high-portability FMSV system is constructed and calibrated, for which the average error of the vision-reconstructed distance is 0.0298 mm. In addition, robot path accuracy is evaluated by the system and compared to laser-tracker measurement results. Hence, high accuracy of 0.031 mm is determined for the proposed vision system.

We investigate a long-range interaction between $64D_{5/2}$ Rydberg-atom pairs and antiblockade effect employing a two-color excitation scheme. The first color (pulse A) is set to resonantly excite the Rydberg transition and prepare a few seed atoms, which establish a blockade region due to strong long-range interaction between Rydberg-atom pairs. The second color (pulse B) is blue detuned relative to Rydberg transition and enables further Rydberg excitation of atoms by counteracting the blockade effect. It is found that a few seed atoms lead to a huge difference of the Rydberg excitation with pulse B. The dynamic evolution of antiblockade excitation by varying the pulse-B duration at 30-MHz blue detuning is also investigated. The evolution result reveals that a small amount of seed atoms can trigger an avalanche Rydberg excitation. A modified superatom model is used to simulate the antiblockade effect and relevant dynamic evolution. The simulations are consistent with the experimental measurements., 6 pages, 4 figures

At present, in the relevant design specifications for earth-rock fill dams in China, the filling standard of rockfill materials is expressed by porosity. Although the mechanical properties of coarse-grained soil are closely related to its porosity, the properties of coarse-grained soil with different gradations are not the same even if the porosity is the same. Porosity can’t express compactness, while relative density can represent compactness of coarse-grained soil. In order to control the deformation of dams reasonably, it is necessary to carry out the field relative density test of rockfill materials. In this paper, limestone rockfill is used to test. The results show that: (1) the bucket diameter of relative density tests has a certain influence on the maximum and minimum dry density of limestone rockfill. (2) In the range of test gradation lines, with the increase of the content of P 5, the maximum and minimum dry density all show the trend of increasing first and then decreasing. (3) When the content of P 5 is the same, the maximum and minimum dry density of limestone rockfill increase with the increase of the maximum particle size, and the particle size has a significant impact on the maximum and minimum dry density.

The reinforced material can increase the stability of soil material, improve its shear strength and reduce the residual deformation. In this paper, the vibration triaxial tests of coarse-grained soil under different confining pressure, consolidation ratio and dynamic stress are carried out by using the 100t electro-hydraulic servo large-scale static and dynamic triaxial testing machine of Institute of Water Resources and Hydropower Research. The results show that the average reduction ratio of the axial residual deformation of reinforced soil to that of unreinforced soil is 40%-50%, and the average reduction of the volumetric residual deformation is 30-40% It has a good inhibitory effect. With the increase of confining pressure, consolidation ratio and dynamic shear stress ratio, the axial residual deformation and volumetric residual deformation of reinforced soil increase in varying degrees. The reinforcement effect of geogrid material on soil sample under different conditions is analyzed. The lower the dynamic shear stress ratio and the higher the consolidation ratio, the better the reinforcement effect. The lower the confining pressure is, the lower the reduction ratio of the reinforcement to the volumetric strain is.

It is still a big challenge to identify tiny surface cracks in a rugged weld due to the lift-off variations using the nondestructive testing (NDT) method. In this paper, the signal gradient algorithm is presented to identify the tiny surface crack in the rugged weld using the alternating current field measurement (ACFM) technique. The ACFM simulation model and testing system was set up to obtain the insensitive signal to the lift-off variations. The signal gradient algorithm was presented to process the insensitive signal for the identification of the tiny surface crack in the rugged weld. The results show that the Bz signal is the insensitive signal to lift-off variations caused by the rugged weld. The signal to noise ratio (SNR) of the crack identification signal was greatly improved by the signal gradient algorithm, and a tiny surface crack can be identified effectively in the weld and the heat affected zone (HAZ).

In order to solve the problem of virus and Trojan attacking the application layer network protocol of industrial control system, the rule of Modbus/TCP communication protocol is analyzed. An intrusion detection method based on clustering and support vector machine is proposed. The method combines unsupervised fuzzy C-means clustering (FCM) with supervised support vector (SVM) machine to calculate the distance between industrial control network communication data and cluster center. Partial data satisfying the threshold condition is further classified by support vector machine. Experimental results show that compared with the traditional intrusion detection method, this method can effectively reduce the training time and improve the classification accuracy without needing to know the class label in advance.

An optical probe of cesium Rydberg atoms generated in a thermal vapor cell is used to retrieve a baseband signal modulated onto a 16.98-GHz carrier wave in real-time, demonstrating an atom-based quantum receiver suitable for microwave communication. The 60$S_{1/2}$ Rydberg level of cesium atoms in the cell is tracked via electromagnetically induced transparency (EIT), an established laser-spectroscopic method. The microwave carrier is resonant with the 60$S_{1/2}$ $\rightarrow$ 60$P_{1/2}$ Rydberg transition, resulting in an Autler-Townes (AT) splitting of the EIT signal. Amplitude modulation of the carrier wave results in a corresponding modulation in the optically retrieved AT splitting. Frequency modulation causes a change in relative height of the two AT peaks, which can be optically detected and processed to retrieve the modulation signal. The optical retrieval of the baseband signal does not require electronic demodulation. The method is suitable for carrier frequencies within a range from $\sim 1$~GHz to hundreds of GHz. The baseband bandwidth, which is $\sim$~20~Hz in the present demonstration, can be increased by faster spectroscopic sampling., Comment: 5 pages, 5 figures

Software Defined Networking (SDN) is a new type of network architecture, which provides an important way to implement automated network deployment and flexible management. However, security problems in SDN are also inevitable in industrial networks. In the research area of SDN security and traditional network security, feasibility and influence of defense in depth in industrial networks should thus be explored. In this paper, a security classification transmission method based on SDN in industrial networks is proposed, which provides a better security level of transmission paths. In the proposed method, the security classification transmission system is first presented. By designing five service mechanisms, including request, strategy generation, distribution/maintenance, updating/loading and execution, the security classification transmission service model is defined. In an experimental study, the proposed method is shown to be feasible in industrial heterogeneous networks and provide better security paths without affecting availability in the multi-domain and multi-nodes case of industrial networks.

We investigate atom-based electric-field calibration and polarization measurement of a 100-MHz linearly polarized radio-frequency (RF) field using cesium Rydberg-atom electromagnetically induced transparency (EIT) in a room-temperature vapor cell. The calibration method is based on matching experimental data with the results of a theoretical Floquet model. The utilized 60$D_J$ fine structure Floquet levels exhibit $J$- and $m_j$-dependent AC Stark shifts and splittings, and develop even-order RF-modulation sidebands. The Floquet map of cesium 60$D_J$ fine structure states exhibits a series of exact crossings between states of different $m_j$, which are not RF-coupled. These exact level crossings are employed to perform a rapid and precise ($\pm 0.5\%$) calibration of the RF electric field. We also map out three series of narrow avoided crossings between fine structure Floquet levels of equal $m_j$ and different $J$, which are weakly coupled by the RF field via a Raman process. The coupling leads to narrow avoided crossings that can also be applied as spectroscopic markers for RF field calibration. We further find that the line-strength ratio of intersecting Floquet levels with different $m_j$ provides a fast and robust measurement of the RF field's polarization., Comment: 7 pages, 4 figures

Long-range macrodimers formed by D-state cesium Rydberg atoms are studied in experiments and in calculations. Cesium 62DJ-62DJ Rydberg-atom macrodimers, bonded via long-range multipole interaction, are prepared by two-color photo-association in a cesium atom trap. The first color (pulse A) resonantly excites seed Rydberg atoms, while the second (pulse B, detuned by the molecular binding energy) resonantly excites the Rydberg-atom macrodimer states below the 62DJ pair asymptotes. The Rydberg-atom molecules are measured by extraction of auto-ionization products and Rydberg-atom electric-field ionization, and ion detection. Molecular spectra are compared with calculations of adiabatic molecular potentials. The lifetime of the molecules is obtained from exponential fits to the dependence of the molecular signal on the detection delay time; lifetimes of about 6 us are found.

We perform Zeeman spectroscopy on a Rydberg electromagnetically induced transparency (EIT) system in a room-temperature Cs vapor cell, in magnetic fields up to 50~Gauss and for several polarization configurations. The magnetic interactions of the $\vert 6S_{1/2}, F_g=4 \rangle$ ground, $\vert 6P_{3/2}, F_e=5 \rangle$ intermediate, and $\vert 33S_{1/2} \rangle$ Rydberg states that form the ladder-type EIT system are in the linear Zeeman, quadratic Zeeman, and the deep hyperfine Paschen-Back regimes, respectively. Starting in magnetic fields of about 5~Gauss, the spectra develop an asymmetry that becomes paramount in fields $\gtrsim40$~Gauss. We use a quantum Monte Carlo wave-function approach to quantitatively model the spectra. Simulated spectra are in good agreement with experimental data. The asymmetry in the spectra is, in part, due to level shifts caused by the quadratic Zeeman effect, but it also reflects the complicated interplay between optical pumping and EIT in the magnetic field. Relevance to measurement applications is discussed. %The simulations are also used to study optical pumping in the magnetic field and to investigate the interplay between optical pumping and EIT, which reduces photon scattering and optical pumping.

For the secure two-way communication and forwarding, this paper proposes SRDA, a secure routing and data aggregation approach for wireless smart meter. This approach introduces the unique wireless smart meter identifier to represent its public identity information, and gives a secure routing architecture based on control and forwarding separation. In this architecture, SRDA uses the proxy re-encryption data aggregation algorithm to protect security of data transmission. By using the routing algorithm according to distance and link quality, SRDA achieves the best routing path and provides several alternative paths which have different priorities. Besides, the identifier-based cryptography mechanism is used to issue and update the routing information in security, and the proxy re-encryption mechanism is designed to preserve the data privacy. In conclusion, this paper gives an analysis for the relatively excellent security, scalability and energy efficiency.

With the application to assess the network and system security in some key fields, penetration testing assessment methods have been evolving into a popular research topic. However, the automation degree of penetration testing is at a lower level, and many parameters of security assessment method is uncertain. For these two problems above, we use rule trees method to achieve the automation process of penetration testing, and each chain of rule trees stores a complete the attack process. By using the result of penetration testing, we propose the security assessment process to meet the NIST guidelines, and it can make some uncertain parameters of security assessment clear. With the constant expansion of rule trees, the proposed method can improve the accuracy and effectiveness of security assessment.

The prognosis of salivary gland adenoid cystic carcinoma (ACC) depends on the clinical stage, the location of the primary tumor, and the histologic growth pattern. ACCs with a cribriform growth pattern have a better prognosis than those with a solid growth pattern; however, clear-cut grading criteria have not yet been established, and therefore prognostic indicators on a molecular level are of special interest. In order to analyze tumor tissue with different growth patterns, cribriform and solid tumor areas of 25 patients were microdissected and separately analyzed for loss of heterozygosity (LOH) at nine polymorphic microsatellite markers located between 6q14 and 6q27. LOH was detected in 19/25 (76%) patients and LOH rates were highest at markers D6S441, D6S310, D6S311 and UTRN, which are located at 6q23-25. Combined analysis of LOH at these four markers shows that in primary tumor subtype foci with cribriform growth pattern LOH is associated with high TNM stages (P0.01), high T stages (P=0.01), positive lymph node status (P=0.03), an unfavorable disease course (P=0.02), and the presence of10% solid growth pattern (P=0.05). In contrast, in primary tumor subtype foci with solid growth pattern, no significant differences in LOH rates were found in patients from prognostically and histologically favorable versus unfavorable patient groups. The frequent occurrence of LOH at 6q23-25 and the correlation of LOH rates with prognostic parameters indicate that a prognostically important tumor suppressor gene is located in this chromosomal area.

Vibrational properties of ultralong Rydberg Cs$_2$ molecules are investigated on corresponding potential curves obtained by perturbation theory. The Rydberg Cs$_2$ molecules are associated by a Rydberg Cs($nS/nP$) atom $(n=30-70)$ and a ground state Cs($6s$) atom. The starting point for the perturbation treatment of corresponding Rydberg molecular potential curves is to generate accurate atomic Rydberg states from realistic {\it ab initio} effective core potential. The calculated results have similar characteristics with available experimental and theoretical investigations on Rydberg Rb$_2$ molecules. And this is the first time that Rydberg molecules are studied at the {\it ab initio} level.

As a key technology of Intelligent Transportation System(ITS), short-term traffic flow prediction is fundamental to traffic control and management. This paper proposes a prediction method based on nearest trajectory segments in reconstructed phase space. First, phase space reconstruction is introduced to recover dynamics traffic flow time series. Then a optimized metric which integrates Euclidean distant and cosine similarly of trajectory segments is proposed to select nearest trajectory segments in phase space. Finally, the predicted traffic flow value is obtained from the predicted vector computed with nearest trajectory segments. Case study with traffic flow data collected from Guangshen Freeway proves prediction accuracy.

A novel approach for the power quality (PQ) disturbances classification based on the wavelet transform and self-organizing learning array (SOLAR) system is proposed. Wavelet network is utilized to extract feature vectors for various PQ disturbances and the wavelet transform can accurately localizes the characteristics of a signal both in the time and frequency domains. These feature vectors then are applied to a SOLAR system for training and disturbance pattern classification. By comparing with a classic neural network, it is concluded that SOLAR has better data driven learning and local interconnections performance. The research results between the proposed method and the other existing method are discussed and the proposed method can provide accurate classification results. On the basis of hypothesis test of the averages, it is shown that corresponding to different wavelets selection, there is no statistically significant difference in performance of PQ disturbances classification and the relationship between the wavelet decomposition level and classification performance is discussed. The simulation results demonstrate the proposed method gives a new way for identification and classification of dynamic power quality disturbances.

High resolution laser excitation of np Rydberg states of cesium atoms shows a dipole blockade at F\"{o}rster resonances corresponding to the resonant dipole-dipole energy transfer of the np + np → ns + (n + 1)s reaction. The dipole-dipole interaction can be tuned on and off by the Stark effect, and such a process observed for relatively low n (25 − 41) is promising for quantum gate devices. Both Penning ionization and saturation in the laser excitation can limit the range of observation of the dipole blockade, Comment: number of pages:5