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Purpose: To assess the efficacy and side effects of Traditional Chinese Medicine (TCM) in the management of triple negative breast cancer (TNBC). Methods: Full text data on randomized controlled trial (RCT) of TNBC treated with TCM or its combination with Western Medicine (WM) were retrieved from the Chinese biomedical literature database, Chinese periodicals, Chinese Science-Technology periodicals and VP and PubMed. The qualities of the RCTs were evaluated. Revman 5.3 was used to conduct the meta-analysis. Results: A total of 16 RCTs involving 1186 patients were included. Analysis of these RCTs showed significant differences in total effectiveness between WM and TCM or combination of TCM with WM {(OR = 2.63, 95 % CI = 1.37, 5.03), test of the combined effect (Z = 2.91, p ˂ 0.005)}. Conclusion: The results show that TCM is effective in the treatment TNBC

Organic-inorganic hybrid perovskites are ideal materials for photodetection owing to their high charge carrier mobility, long charge carrier diffusion length, low dark current density and sharp absorption edge. However, a relatively small band gap (1.6 eV) limits their photon-harvesting efficiency in the near-infrared region. In the present work, we demonstrate a hybrid methylamine iodide and Pb-Sn binary perovskite as the light absorption layer in photodetectors. Experimentally, the wavelength of photoresponse onset for the photodetectors can be extended to as great as 1,000 nm when the Sn content of the hybrid perovskite is increased to 30 mol%. In addition, the photodetectors exhibit a photoresponsivity of 0.39 A W−1, a specific detectivity of 7×1012 Jones, a fast photoresponse with rise and decay time constants and an external quantum efficiency greater than 50% in the wavelength range of 350–900 nm, with a maximum value of about 80% at 550 nm.

The production process of port enterprises is complex, and the operation contents are diversified and dynamic. Thus, the factors affecting the safety production risk are numerous and complex. To better grasp the risk state of the safety production of the port enterprises, based on the requirements of relevant laws and regulations and the actual situation of safe production of port enterprises, in this study, the diversified safety production data of port enterprises was collected and analyzed, the three-level index system of safety production data for port enterprises was constructed, the evaluation model of safe production state for port enterprises based on AHP-fuzzy comprehensive evaluation was established, and the practical application was carried out in a large port enterprise. The evaluation results were highly consistent with the actual situation of safe production of port enterprises. This evaluation method can be used to make full use of the existing data sources of safety production of port enterprises to discover the prominent risks affecting safety production and control them, and effectively improve the level of safety production of port enterprises.

In China’s port industry, there is currently a lack of sound, systematic guidance and standards for the assessment of emergency-response capability. Taking the current emergency-management situation in China’s port industry as a starting point, this study analyzed current problems in emergency-response capability and examined advanced domestic and foreign practices in emergency management. The elements of emergency-response capability assessment were then established based on the following four aspects: organizational system, legal basis, operation mechanism, and guarantee system. An emergency-response capability assessment method was then constructed using the Delphi method and applied in practice. This method can help guide port businesses in performing their emergency-management duties; improve their prevention, early warning, and emergency-management abilities; and play a guiding role in building emergency-response capability with regard to accident prevention and rescue operations.

Wind farms have large fluctuations in grid connection, imbalance between supply and demand, etc. In order to solve the above problems, this paper studies the capacity optimization configuration of wind farm energy storage system based on full life cycle economic analysis. Firstly, the optimization model of energy storage capacity is established in this paper for computing wind farms require minimal storage capacity for load shifting, reducing peak and valley fluctuation; considering the loss cost of wind discarded, the fixed costs of energy storage device and equipment maintenance, the cost of the battery is analyzed in the whole life cycle by the point of view of economics; multi-objective optimization of the minimized ratio of peak-valley fluctuations around peak load shifting volatility and maximized economic benefits, by the global particle swarm algorithm for getting the optimal solution, the system capacity optimization control scheme is proposed. By analyzing the actual data, it is proved that the rational capacity allocation of the energy storage system can effectively reduce the ratio of peak-valley fluctuations around peak load shifting volatility, improve the economic benefit of the wind power plant, and improve the economic benefits of wind power plant storage.

Participating in the bidding of the electricity market is a new profit way for electric energy storage system. In the existing electricity market, the calculation model of bidding strategy for electricity energy storage technology is relatively single, and the dynamic energy characteristics of battery energy storage are neglected. Therefore, taking the battery energy storage system as the research object, a bidding strategy based on energy distribution for battery energy storage power market is proposed in the paper. Firstly, the dynamic energy model of battery is established. Secondly, the energy of batteries is allocated according to the time-of-use (TOU) electricity price policy. With the maximum economic benefit of electricity energy storage system and bidding income of the energy storage market in the day as the optimization targets, the energy bidding strategy of battery energy storage system was formulated. Finally, the power, state of charging (SOC) and revenue of lithium battery energy storage under different bidding strategies are calculated and analyzed according to the TOU price of a certain area. The case study results show that the energy market's revenue can be increased by 57.8% using the energy bidding strategy proposed in the paper. The research results can provide a reference for bidding strategy of electric energy storage market, and it also provide a theoretical basis for economic evaluation of energy storage technology.

The fuel assembly is the core component of the nuclear energy system, and its excessive deformation will affect the normal insertion of the fuel rod and endanger safe operation of the reactor. In this paper, we present an underwater fuel assembly deformation measurement system based on 10 sets of visual measurement units. Benefitting from the waterproof design, the shielding-radiation design, the reflective structure design, the dual-optical line laser triangulation principle, and the underwater multilayer refractive geometry, the measurement system has shorter measurement time, higher measurement accuracy, and better environmental adaptability. Through the underwater field measurement and verification of the standard rod and fuel assembly, the bow deformation measurement accuracy of the measurement system is better than 0.3 mm, and the twist deformation measurement accuracy of the system is better than 0.15°. The proposed method allows transient and high-precision measurement in a certain irradiation dose and certain depth water, which provides a strong guarantee for measurement of fuel assembly deformation parameters in deep water and high radiation.

In order to improve the controllability and stability of the isolation switch breaking test for mine and to improve the intelligence level of the test and inspection device, the software program of the motor mechanism control system was developed based on PLC. Based on the analysis of the present situation of the operation mechanism of mine isolation switch breaking test, the demand of mine isolation switch breaking test control system is put forward. Based on cx-one 4.2 software and ladder diagram language, the control software program of motor mechanism is developed. The practical application shows that the software runs well and lays a foundation for the development of intelligent inspection technology.

According to the security of watermark, holographic watermark, wavelet transform and information hiding are combined to make watermark embedded into the carrier image with better encryption and anti-cutting ability. In this paper, the original color image is transformed to produce hologram, and then the hologram is embedded in the color image according to the wavelet transform method. Firstly, the hologram is embedded into the decomposition of the high-frequency details, produced by one-dimensional wavelet decomposition of carrier image. This not only improves the robustness of image clipping and the invisibility of watermark, but also enhances the security of information transmission.

Collaborative filtering is one of the most successful and widely used recommendation systems. A hybrid collaborative filtering method called data sensitive recommendation based on community detection (DSRCD) is proposed as a solution to cold start and data sparsity problems in CF. Data sensitive similarity is combined with Pearson similarity to calculate the similarity between users. α is the control parameter. A predicted rating mechanism is used to solve data sparsity problem and to obtain more accurate recommendation. Both user-user similarity and item-item similarity are considered in predicted rating mechanism. β is the control parameter. Moreover, in the constructed K-nearest neighbour set, both user-community similarity and user-user similarity are considered. The target user is either in the community or has some correlation to the community. Calculating the user-community similarity can cope with cold start problem. To calculate the recommendation, movielens data sets are used in the experiments. First, parameters α and β are tested and DSRCD is compared with traditional collaborative filtering recommendation algorithm (TCF) and Zhao’s algorithm. DSRCD always has better results than TCF. When K = 30, we have better performance results than Zhao’s algorithm.

Fast capacity estimation is a key enabling technique for second-life of lithium-ion batteries due to the hard work involved in determining the capacity of a large number of used electric vehicle (EV) batteries. This paper tries to make three contributions to the existing literature through a robust and advanced algorithm: (1) a three layer back propagation artificial neural network (BP ANN) model is developed to estimate the battery capacity. The model employs internal resistance expressing the battery’s kinetics as the model input, which can realize fast capacity estimation, (2) an estimation error model is established to investigate the relationship between the robustness coefficient and regression coefficient. It is revealed that commonly used ANN capacity estimation algorithm is flawed in providing robustness of parameter measurement uncertainties, (3) the law of large numbers is used as the basis for a proposed robust estimation approach, which optimally balances the relationship between estimation accuracy and disturbance rejection. An optimal range of the threshold for robustness coefficient is also discussed and proposed. Experimental results demonstrate the efficacy and the robustness of the BP ANN model together with the proposed identification approach, which can provide an important basis for large scale applications of second-life of batteries.

The cycloid drive usually has a cycloidal wheel meshing with pins to achieve transmission. The profile of the cycloidal wheel is generally a curve derived from an epitrochoid. This paper presents two design types of cycloid drive, the cycloidal wheel profile of one is internal offset of epicycloid and the other is external offset of hypocycloid. Parametric 3-D models of the two design types are constructed in AutoCAD. Dynamics simulation is carried out using machinery system dynamics simulation technology, and the correctness of the dynamics model is verified by the motion curve. The dynamic meshing force between the cycloidal wheel and the pins of the two design types is solved, and transmission characteristics are compared. The results show that the hypocycloidal drive design produces more stable output speed, and can improve meshing force.

Precision reducer is one of the key parts of an industrial robot, which generally incorporates two-stage cycloidal planetary drive. The theoretical engagement of cycloidal wheel and pin is a gapless engagement, but in practice, there is a gap between the cycloidal wheel and the pins due to manufacturing errors. Most of the previous research on the gap only involves the impact on the transmission accuracy, the force of engagement between the cycloidal wheel and pins is the main form of the transmission torque of the reducer. Thus, this paper aims to use the finite element method to explore the specific impact on meshing force caused by the gap due to manufacturing error of the pins, and obtain the general rule, provides guidance for the precision requirement in the manufacture of the pins.

In this paper, vibration properties of main parts of a RV reducer are investigated by modal analysis and theoretical calculation.Their natural frequency, vibration mode, and meshing frequency are obtained. This paper provides guidance for RV reducer design.

Community detection as a branch of social network analysis has been a hot topic in the past decade. This paper reviews the research about the community detection these years and focuses on the community detection relevant classical algorithms as well as the classic real network datasets.

To predict the key performance index (compressive strength) of Iron ore pellets, a prediction model based on Kernel principal component analysis (KPCA) and RBF neural network was proposed. This paper determined the input variable through the analysis of the chain grate machine — rotary kiln — ring cold pellet production process, deal with the sample data and simplified the model structure with Kernel principal component analysis algorithm (KPCA) and then established the pellet compression strength prediction model with RBF neural network. Using a global optimization performance of the simulated annealing algorithm to optimize the parameters of the network model, obtain the high precision prediction model of the system. The simulation results show that the proposed model can accurately predict the compressive strength of pellets, can overcome the disadvantage of large lag in the original compressive strength test method. The prediction model laid a foundation for the automatic control of the pellets compressive strength.

Capacities of li-ion batteries are difficult to estimate quickly and accurately when second use batteries are in large scale with dispersed parameters. This may result in costing too much time and money to reuse batteries. By analyzing the capacity and resistance characteristics, there is no functional relationship between them. In order to solve this nonlinear problem, a SVM model with 3 parameters (i.e. penalty coefficient, kernel function parameter and loss function parameter) is established. The inputs are five calculated values of resistance and the output is the capacity value of batteries. Data of 70 battery modules are adopted to train the model while data of other 30 battery modules are used to test the model. In this process, two parameters optimization methods using genetic algorithm have been proposed. By comparison, the coefficient of determination (COD) value of method 2 is higher than method 1 both in training model and testing model. The average error of method 2 between measured values and estimated values is 0.67% whereas that of method 1 is 1.35%. In method 2, 90% of the estimation errors are under 2.5%. The results provide valuable insights for large-scale retired li-ion batteries into second use.

LOD model based on quad-trees is improved on the basis of former researches. This model is applied to manage and organize terrain data. Node judgment rule is established to determine the detail degree of the present visual area. A new bidirectional way was given to recover the cracks according to distance. By programming, this method is proved to be able to generate multi-resolution terrain model continuously, improve the efficiency of terrain navigation, and realize smooth transition of the models with different resolution.

Giant resonance enhancement is demonstrated to be due to the Fano interference in a grating waveguide composed of gain-assisted silicon slabs. The Fano mode is characterized by its ultra-narrow asymmetric spectrum, different from that of a pure electric or magnetic dipole. The simulation indicates that a sharp Fano-interfered lineshape is responsible for the giant resonance enhancement featuring the small-gain requirements.