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A lower-hybrid frequency surface wave antenna called arch is designed and fabricated in this paper for the spherical tokamak named EXL-50. It is used to drive plasma current and heat plasma at 2.45 GHz. The arch antenna consists of 27 antenna elements. The left and right rectangular waveguides integrated with the antenna are used for microwave input and output, respectively. The refraction parallel index of this proposed antenna is 4.3 , which is favorable for the lower hybrid current drive. The measurement results in the absence of plasma show that the reflection and transmission coefficients ( S 11 and S 21 ) are − 12.5 dB and − 12.6 dB , respectively. The antenna was installed and tested on EXL-50. Up to a 35 kA plasma current was achieved using the arch antenna with a microwave of 70 kW .

Graphitic carbon nitride (g-C3N4) is a visible light-responsive photocatalytic material with important application prospects in many fields. However, the interaction between g-C3N4 monolayers makes it easy to aggregate and precipitate in aqueous solutions, and it is necessary to prepare stable g-C3N4 aqueous dispersions for their applications. Here we propose a facile, green, and low-cost method for the preparation of stable g-C3N4 dispersions by ultrasonicating g-C3N4 in lysozyme (LYZ) solution. The LYZ was adsorbed on the surface of g-C3N4 through non-covalent interactions such as electrostatic interaction, hydrogen bonding and π-cation interaction to prevent the aggregation of g-C3N4 nanolayers. The LYZ/g-C3N4 could quickly re-form a uniform aqueous dispersion solution after freeze-drying, and exhibit good stability. Further, the results of photocatalytic sterilization showed that the assisted dispersion of LYZ enhanced the bactericidal activity of g-C3N4 and exhibited promising application prospects in the field of biomedicine and water disinfection.

Rupturing the alumina shell (shell-breaking) is a prerequisite for releasing energy from aluminum powder. Thermal stress overload in a high-temperature environment is an important factor in the rupture of the alumina shell. COMSOL Multiphysics was used to simulate and analyze the shell-breaking response of micron-scale aluminum particles with different particle sizes at 650 °C in vacuum. The simulation results show that the thermal stability time and shell-breaking response time of 10 μm–100 μm aluminum particles are 0.15 μs–11.44 μs and 0.08 μs–3.94 μs, respectively. They also reveal the direct causes of shell breaking for aluminum particles with different particle sizes. When the particle size is less than 80 μm, the shell-breaking response is a direct result of compressive stress overload. When the particle size is between 80 μm and 100 μm, the shell-breaking response is a direct result of tensile stress overload. This article provides useful guidance for research into the energy release of aluminum powder.

For traditional human pose estimation models rely on a large amount of human body feature information, this paper proposes an optimization model using genetic algorithm to solve the problem of multiple person body part assembly. Different from other human body parts assembly method. The method proposed in this paper depends on the joints position information, namely the sum of the connection distances between the joints as the objective function, and finds the optimal value to obtain the best human pose assembly information. The simulation results show that compared with the traditional OpenPose model, the model proposed in this paper can obtain the same human skeleton using less position information.

Breast Cancer (BC) is the most common malignant tumor for women in the world. Histopathological examination serves as basis for breast cancer diagnosis. Due to the low accuracy of histopathological images through manual judgment, the classification of histopathological images of breast cancer has become a research hotspot in the field of medical image processing. Accurate classification of images can help doctors to properly diagnoses and improve the survival rate of patients. This paper reviews the existing works on histopathological image classification of breast cancer and analysis the advantages and disadvantages of related algorithms. Findings of the histopathological image classification of the Breast Cancer study are drawn, and the possible future directions are also discussed.

A modified Cuckoo search algorithm (MCS) is proposed in this paper to improve the accuracy of the algorithm’s convergence by implementing random operators and adapt the adjustment mechanism of the Levy Flight search step length. Comparative experiments reveal that MCS can effectively adjust the search mechanism in the high-dimensional function optimization and converge to the optimal global value.

Preionization has been widely employed to create initial plasma and help the toroidal plasma current formation. This research focuses on implementing a simple, economical and practical electron cyclotron resonance (ECR) preionization technique on the newly constructed EXL-50 spherical tokamak, and evaluating the effectiveness on improving the plasma current startup. Two types ECR microwave preionization experiments for the plasma initialization without the central solenoid are reported: (1) 2.45 GHz microwave preionization and current startup with 2.45 GHz ECR source; (2) 2.45 GHz microwave preionization and current startup with 28 GHz ECR source. Application of the 2.45 GHz ECR microwave preionization to the experiments has contributed to (1) getting rid of the plasma breakdown delay; (2) the significant improvement of the discharge quality: the discharge is much longer and more stable while the driven plasma current is larger, compared to the discharge without preionization.

Self-noise is a very disadvantageous factor for underwater glider to observe ocean ambient noise, in which the noise caused by motor is very significant. In order to grasp the characteristics of the motor-noise and its influence on the measurement of ocean ambient noise, a long-term sea trial was conducted in the South China Sea in May 2020, and the self-noise data of underwater glider under different working conditions are obtained. By analyzing the noise level and spectrum level of the motor noise, we obtained the self-noise spectrum characteristics and know that the influence of control motor noise on the noise measurement of head and tail hydrophone is mainly below 5 kHz band, and the influence of full-frequency noise level brought by motor is within 10dB and 5dB respectively. The results lay an important foundation for further analysis of ocean ambient noise measured by underwater glider.

Benefit classification analysis is an important content for not only studying the benefit categories of different blocks in Oilfield, but also controlling and adjusting the negative benefit blocks. Due to the lack of comprehensive consideration of development stage and geological conditions, the classification of oil field development units has some limitations. Through comprehensive analysis of the influencing factors of oilfield development benefit, this paper classifies unit development by using system clustering method. DEA (Data Envelopment Analysis) model is used to analyze the relative validity of different development units. In the same geological and development condition units, the method of benefit classification based on validity analysis is used to realize the comprehensive classification of development and economy. Benefit classification analysis using the benefit evaluation data of a low permeability development unit in eastern oilfield shows that it can play a guiding role in benefit classification, negative effect management and operation strategy of the development unit.

The relation between microstructure characteristics and mechanical properties of X80 pipeline steels produced by ultra fast cooling process was investigated using energy dispersive spectrometer, scanning and transmission electron microscopy. Results showed that ultra fast cooling kept hot rolled austenitic work hardened, induced a large number of carbonitride precipitation, limited the growth of cementite. Therefore ultra fast cooling was beneficial to increase the steel strength and improve the steel ductility and toughness.

The technical problems and relating reasons of semi-endless rolling were introduced in this paper. Regarding the problems, we carried out a series of improvement towards these problems. The application of semi-endless rolling got a great success.

We have investigated the dynamics of a protomer coupled to two different decoherent environments, each in a configuration called the spin star configuration. Using the quantum mechanics method, in different situations, we obtain the analytical expressions for the transition probability in the protomer system. In thermal equilibrium, there exist well-defined ranges of parameters for which decoherent interaction between the protomer and the environment assists energy transfer in the protomer system, while in pure quantum mechanics states, the decoherent interaction assists energy transfer for an eigenstate but against energy transfer for quantum mechanics averages. In particular, we also find that the dimerization of two bacteriochlorophylls in protomer can always assist energy transfer in certain parameter range, and in the appropriate spin bath energy, the efficiency of energy transport is sensitively depended on the temperature of environments.

Harmony search (HS) algorithm has received widely attention in various fields because of simple operation and outstanding performance. However, there exists some bottlenecks which hinders the further development of HS algorithm, such as easy trapping into local optimum and slow convergence velocity.This paper proposes an improvement HS algorithm by using segmented search strategy (SHS) to overcome these drawbacks. Comparative experiments reveal the proposed SHS algorithm has perfect performance, especially in high dimensions.

This paper proposes a new sliding mode controller, as to enhance the performance of path tracking of three-wheeled mobile robot system. To begin with, backstepping design is used to construct a new sliding mode control law for better dynamic response and robustness. Next, in order to reduce chattering, the symbolic function is replaced with the critical saturation function in the conventional reaching law. At last, the simulation results show that backstepping design combined with saturation function can not only improve the response rate and robustness of the system, but also effectively reduce the chattering.

Part-of-speech (POS) tagging is a basic problem that needs to be solved in the informationization of Chinese-Hmong mixed text including square Hmong characters, so far no one has studied it. This paper proposes a POS tagging approach for Chinese-Hmong mixed text by utilizing improved Hidden Markov Model (HMM) to expand contextual information. The results of comparative experiments based on cross-validation reveal the proposed approach has perfect performance, and is able to obtain tagging results with good consistency and high coverage.

This paper mainly describes the basic principles of extended Kalman filter and unscented Kalman filter and the application of them in target tracking based on observation distance At last the two algorithms are compared by Matlab software The simulation results show that unscented Kalman filter has better matching effect than extended Kalman filter and the former has smaller error variation and better convergence than the latter

As real systems become larger and complicated, the number of nodes of fuzzy Petri net (FPN) also increases rapidly, it further indicated that the algorithm complexity of related application using FPN grows up sharply. To solve this state-explosion issue, a decomposition algorithm using reachability tree is proposed to divide a large-scale FPN model into a series of sub-FPNs in this paper. Comparison experiments show that all obtained sub-FPNs do not destroy internal reasoning paths of the original large-scale FPN and represent a complete reasoning path from input place(s) to the output place.

Artificial bee colony algorithm (ABC) and particle swarm optimization (PSO) are both famous optimization algorithms that have been successfully applied to various optimization problems, especially in function optimization. Those two algorithms have been attracting more and more research interest because of their efficiency and simplicity. However, PSO has poor exploration capabilities and thus is easy to fall into the local optimum; Likewise, ABC has low convergence speed. To address these shortcomings, firstly, we improved the ABC with the combination of greedy selection and crossover, secondly, a sine-cosine method will be used to help PSO jump into local optimal. Finally, a new hybrid algorithm based on improved ABC and PSO are proposed. Moreover, four functions are used to verify the effectiveness of the proposed algorithm, and the results show that, compared with other well-known algorithms, ABC-PSO is more efficient, faster and more robust in function optimization.

Optimization technique are solutions for finding for specific problems and solved existing limitation on common problems. This are especially in improving the output of WEDM processing where it involves more than a single objective or multiple output to be optimized synchronously. WEDM machining process usage increased rapidly as its capability in cutting complicated design formation. Thus the precision of the work piece is required. Therefore, this paper aims to provide a quick conceptual view of optimizing WEDM process by providing fundamentals parameters involved. Henceforth, perspective on WEDM optimization process on this paper may be use for future reference.

Aiming at solving the problem of large tracking error in the tracking process of video moving targets with the unscented Kalman filtering method, a particle filter algorithm is proposed to track video moving targets to improve the tracking effect. Particle filtering is the minimum variance estimation of the system state through the posterior probability distribution. The applications of particle filtering and unscented Kalman filtering in tracking video moving target are compared by using Matlab simulation software. The results show that the particle filter has higher accuracy and better tracking performance than the unscented Kalman filter in tracking video moving target.

Nowadays, the analysis of university students is the main concern of educational institutions. In this paper, we investigate the problem of analysing students’ self-control ability. Our model focuses on the process of feature extraction, and then classification algorithms are applied. We propose the concept of behaviour chain to model the behavior of student. On this basis, we propose a spatial periodic feature extraction method based on the longest common sub-sequence(LCS). And we extract some statistics features from consumption data, access control data and others. Our model SCA(Self-Control Analysis) performs with the precision of 0.72, the recall of 0.78 and the Fl-score of 0.74. It means that it’s possible to analyse student’ self-control ability with campus big data.

We perhaps fantasized about reading the mind of the human brain directly and use it in other ways. In this paper, we tried to analyze human brain activity to identify the feature space employed by humans for visual classification. The brain signals driven by visual information were classified, and the visual information classifier were trained, and the visual information were decoded by the brain signals. The 64 channels EEG data induced by 40 types of images were collected, and recurrent neural network(RNN) was used for extracting features of electroencephalogram(EEG) signals and predicting the types of EEG signals. The accuracy of decoding could reach 80.90%. The technology of decoding of visual information based on brain EEG data could be applied to the brain-computer interface(BCI).

Breath analysis is used to detect the composition of exhaled gas. As a quick and non-invasive detection method, breath analysis provides deep insights into the progression of various kinds of diseases, especially those with metabolism disorders. Abundant information on volatile compounds in diabetic patients has been studied in numerous articles in the literature. However, exhaled gas in diabetic patients can be altered by various complications. So far, little attention has been paid to this alteration. In our paper, we found that under air pollution conditions, diabetic patients exhale more nitric oxide. Diabetic patients with heart failure exhale more acetone than those without heart failure. After 13C-labeled glucose intake, patients infected with Helicobacter pylori exhaled more 13C and less 18O than those without infection. Exhalation with chronic kidney disease changes volatile organic compounds on a large scale. Diabetic patients with ketoacidosis exhale more acetone than those without ketoacidosis. Some specific volatile organic compounds also emanate from diabetic feet. By monitoring breath frequency, diabetic patients with obstructive sleep apnea syndrome exhibit a unique breath pattern and rhythm as compared with other diabetic patients, and sleep apnea is prevalent among diabetic patients. In addition to clinical findings, we analyzed the underlying mechanisms at the levels of molecules, cells and whole bodies, and provided suggestions for further studies.

(La,Ce)–Al–Cu alloys with different La/Ce ratios were employed as the diffusion sources for grain boundary diffusion of sintered NdFeB magnets. The coercivity changed from 990 kA m−1 to 984, 1021 and 1031 kA m−1 after diffusion by (La x Ce1−x )–Al–Cu alloys with La/Ce ratio (x) of 0, 0.5 and 1, respectively. Varied magnetic properties resulted from different effects of La and Ce on the microstructure, in particular the formation and amount of the REFe2 phase. REFe2 phase formed after diffusion deteriorated the magnetic properties but improved the wettability between grain boundary and main phase. After (La,Ce)–Al–Cu alloys diffusion, the corrosion resistance was reduced but the mechanical properties were improved. The underlying mechanisms have been discussed in this paper.

Artificial Bee Colony (ABC) algorithm has received wide attention due to the outstanding performance in solving complex optimization problems. However, the further application of ABC is still hindered due to some bottlenecks, such as slow convergence velocity, poor global search ability and low accuracy of solution. To overcome these problems, an improved ABC (CT-ABC) is proposed in this paper by using both a chaotic map and a tolerance based search equation (TSE). Some standard test functions are chosen to verify the performance by implementing the proposed modified ABC algorithm, basic ABC and another modified ABC (WABC). Simulation results reveal the proposed CT-ABC algorithm is able to obtain the faster convergence speeds and better accurate approximate solution.

A miniature quad-channel optically pumped atomic magnetometer (OPM) has been developed based on the spin-exchange relaxation-free (SERF) mechanism. With a vapor cell of size 8 mm×8 mm×8 mm, we have incorporated four SERF magnetometer channels, which provides sufficient spatial resolution for magnetoencephalography (MEG). The four channels share the same laser beam for the best cancellation of common mode noise due to laser fluctuations. With gradient measurement, the sensitivities of the four sensors are better than 6 fT/Hz1/2, which is also good enough for MEG measurement. The vapor cell is heated to 160 °C by a novel nonmagnetic current-heating structure. Our sensor with high spatial resolution and compact size is particularly suitable for MEG systems.

Brain function in the resting state can be decomposed into independent spontaneous subactivities representing brain intrinsic modes. A brain task-performing activity can also be decomposed into independent modes. Previous research has shown a high spatial correspondence between the resting-state and task-present modes, but how the brain task and resting states are related remains elusive. We propose to establish a framework spanned by universal intrinsic modes (generated from a resting data analysis) to represent a brain task state through task-specific modification on a subset of intrinsic modes. We demonstrate our model and method through experimental data analysis on one group of task fMRI data and another group of rest fMRI data (from 40 different subjects). Our fingertapping experiment results show that the primary motor task only modulates a few intrinsic modes in the functional framework. The brain functional framework (spanned by universal intrinsic modes) offers a unification representation of brain task and resting states for simplifying brain functional organization

We propose an efficient protocol for rapidly generating quantum entangled states between a transmon qubit and microwave photons via shortcuts to adiabaticity. For a dispersive coupling between the qubit and cavity mode, three composite qubit-photon states constitute our system. Two microwave drivings are applied to the three-level system, leading to a Λ-type interaction. Based on shortcut-like quantum state transfer, the maximally entangled states can be controllably generated in a non-adiabatic manner. We address the dependence of the needed time for generating entangled states on the Rabi couplings, and further analyse the robustness of quantum operations. The present scheme opens up an opportunity for fast creating entangled states of the superconducting qubit-cavity systems.

The HSn70-1 copper alloy was used as propeller material due to its excellent properties. It would be degraded by erosion wear when working in the multiphase flow. But its erosion wear behavior is still remained unclear. In this study, the erosion wear behavior of HSn70-1 copper alloy in multiphase flow (water with SiC particles) was investigated by changing the flow velocity, the impact angle and the particle size. The mass loss rate, surface micrograph and surface roughness of alloys after eroded under different conditions were tested. The results showed that the cumulative mass loss of the HSn70-1 alloys increased as the flow velocity and particle size increased. The mass loss initially increased and reached a maximum value at 30°. Subsequently it decreased as the impact angle increased. The surface features demonstrated that the erosion mechanism of HSn70-1 copper alloy in multiphase flow was micro-machining. The SiC particles with high kinetic energy would lead to the deformation of the alloy surface and the damage of the passive film.

Ultra-high strength steels (UHSS) have been regarded as one of the most attractive alternatives for lightweight parts in automotive industry. In this study, the tube hot gas forming process is introduced to implement high temperatures forming for UHSS tubular components. In the proposed process, the tube blank is first heated up to 900 °C for several minutes to achieve homogeneous austenitization and then quickly transferred to a press for forming. Nitrogen gas replaces? water in traditional hydro-forming process as media to apply internal pressure in a heated tube. To enhance the energy absorption capability of the components, a one-step quenching and partitioning (Q&P) process is conducted by the die cooling during deforming simultaneously to increase the elongation and ductility of the material. Moreover, a numerical investigation on a tube component fabricated from 22MnB5 steel is performed. The temperature distribution and microstructure evolutions are studied, which demonstrates the forming quantity advantages of tube gas forming process.

We present here an adaptive control scheme with a feedback delay to achieve elimination of synchronization in a large population of coupled and synchronized oscillators. We validate the feasibility of this scheme not only in the coupled Kuramoto's oscillators with a unimodal or bimodal distribution of natural frequency, but also in two representative models of neuronal networks, namely, the FitzHugh–Nagumo spiking oscillators and the Hindmarsh–Rose bursting oscillators. More significantly, we analytically illustrate the feasibility of the proposed scheme with a feedback delay and reveal how the exact topological form of the bimodal natural frequency distribution influences the scheme performance. We anticipate that our developed scheme will deepen the understanding and refinement of those controllers, e.g. techniques of deep brain stimulation, which have been implemented in remedying some synchronization-induced mental disorders including Parkinson disease and epilepsy.

We propose an effective scheme for implementing tunable photon transmission through a coplanar waveguide cavity. An electron spin ensemble of nitrogen-vacancy centers, behaving as a spin-boson mode, is coupled to the cavity mode. It is found that the transmittance of an incident photon depends on the coupling strength between the two modes, both with dissipative effects. In particular, the photon transmittance can be controlled at will by adjusting the external driving-induced detunings. This proposal could offer a promising avenue to coherently control photon propagation and is highly preferable for the experimental manipulations.

The third-order nonlinear optical properties of water-soluble Cu Se nanocrystals are studied in the near infrared range of 700–980 nm using a femtosecond pulsed laser by the Z-scan technique. It is observed that the nonlinear optical response of Cu Se nanocrystals is sensitively dependent on the excitation wavelength and exhibits the enhanced nonlinearity compared with other selenides such as ZnSe and CdSe. The W-shaped Z-scan trace, a mixture of the reversed saturated absorption and saturated absorption, is observed near the plasmon resonance band of Cu Se nanocrystals, which is attributed to the state-filling of free carriers generated by copper vacancies (self-doping effect) of Cu Se nanocrystals as well as the hot carrier thermal effect upon intense femtosecond laser excitation. The large nonlinear optical response and tunable plasmonic band make Cu Se nanocrystals promising materials for applications in ultra-fast all-optical switching devices as well as nonlinear nanosensors.

The laser-pumped potassium spin-exchange relaxation free (SERF) magnetometer is the most sensitive detector of magnetic field and has many important applications. We present the experimental results of our potassium SERF magnetometer. A pump–probe approach is used to identify the unique spin dynamics of the atomic ensemble in the SERF regime. A single channel sensitivity of 8 fTHz−1/2 is achieved with our SERF magnetometer.

Efficient calculation of the electrostatic interactions including repulsive force between charged molecules in a biomolecule system or charged particles in a colloidal system is necessary for the molecular scale or particle scale mechanical analyses of these systems. The electrostatic repulsive force depends on the mid-plane potential between two charged particles. Previous analytical solutions of the mid-plane potential, including those based on simplified assumptions and modern mathematic methods, are reviewed. It is shown that none of these solutions applies to wide ranges of inter-particle distance from 0 to 10 and surface potential from 1 to 10. Three previous analytical solutions are chosen to develop a semi-analytical solution which is proven to have more extensive applications. Furthermore, an empirical closed-form expression of mid-plane potential is proposed based on plenty of numerical solutions. This empirical solution has extensive applications, as well as high computational efficiency.