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Geological drilling is an important means for exploration of the earth. Due to the nonlinearity and coupling, geological drilling is accompanied by low efficiency and safety, and difficult to accurately predict the drilling states. Moreover, the vertical well trajectory needs to follow the plumb line. A novel optimization method is proposed to solve these problems. First, working conditions are identified by fuzzy C-means clustering method and corresponding adjustment ranges of operating variables are refined for optimization. Meanwhile, support vector regression and hybrid bat algorithm are employed to construct reliable models for mud pit volume (MPV) and rate of penetration (ROP). Then, how to improve safety and efficiency is converted to a two-objective problem, that is to suppress MPV fluctuations and improve ROP with vertical well constraints. Nondominated sorting genetic algorithm II is invoked to solve this problem, and the appropriate solution is selected by two references points. Moreover, a short-time scale and long-time scale optimization strategy is introduced to cope with different adjustment interval of operating variables. Finally, the simulation results based on actual drilling data, application results in a semi-physical experiment system and comparison results from a vertical well verify the effectiveness and practicability for the developed method. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of asymptotic tracking control of nonlinear robotic systems with prescribed performance. The control strategy is developed based on a modified prescribed performance function (PPF) to guarantee the transient behavior, while the requirements on the accurate initial tracking error in the classical PPF can be remedied. The fuzzy logic system (FLS) is used to approximate the unknown dynamics. In the existing PPF based adaptive control schemes with FLSs, the tracking error does not achieve asymptotic convergence. To address this issue, a robust integral of the sign of the error (RISE) term is incorporated into the control design to reject the FLS approximation errors and external disturbances, such that the asymptotic convergence is achieved. Finally, numerical simulation and experimental results validate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Measurement of the perceived quality of stereoscopic three-dimensional (S3D) images has attracted an increasing amount of research interest in recent years. This paper proposes a S3D image quality measurement (IQM) metric based on sparse representation and binocular combination. The proposed method involves learning binocular and monocular dictionaries from a training database such that the sparse features of binocular combination can be expressed by a linear combination of a few selected basis feature vectors. Following this, scores for the similarity of these sparse features between reference and distorted S3D images are measured. Based on the observation that sparse features are invariant against weak degradations, similarity scores of the features of the gradient magnitude of binocular combination are then computed and used as a complementary feature. Finally, by using kernel-based support vector regression (SVR), these similarity scores are integrated into an overall quality value. Experimental results on three public S3D-IQM datasets show that in comparison with the relevant existing metrics, the devised metric attains significantly high consistency alignment with subjective quality assessment. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we present a new insight into the simultaneous policy update algorithm (SPUA) for solving H ∞ control problems. From the perspective of practicability, a checkable criterion is presented for the initialization of SPUAs such that the initial guess can be chosen with clear rules and lie within a local domain of convergence. To further get a better convergence property, a novel initialization is developed such that the starting matrix does not need to lie in a neighborhood of the solution of H ∞ control problems in some cases and its convergence is established rigorously by mathematical induction principle. Subsequently, an improved SPUA is proposed, and its model-free variant based on reinforcement learning (RL) is also able to learn the solution online without any system dynamics. Finally, numerical results illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

The precision of reflector antenna on orbit is an important design specification, and the reasonable structure design can improve the reflector precision. By taking full advantages of the high strength, high modulus, low coefficient of thermal expansion of the composite material, and the surface precision of the antenna could be improved significantly. By using the artificial neural networks highly nonlinear mapping capability, and based on the principle of the minimum RMS, the design parameters were optimized. The calculation results indicate that the computing time can be effectively saved. The results show that the optimization method is reasonable, and the structure design meets the design requirements. The design scheme and analytical methods provide a direction for the structure design of the reflector. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of delay-dependent stability for a class of singular time-delay systems. By representing the singular system as a neutral form, using an augmented Lyapunov–Krasovskii functional and the Wirtinger-based integral inequality method, we obtain a new stability criterion in terms of a linear matrix inequality (LMI). The criterion is applicable for the stability test of both singular time-delay systems and neutral systems with constant time delays. Illustrative examples show the effectiveness and merits of the method. [ABSTRACT FROM AUTHOR]

Orbital maneuver accuracy analysis problem is studied by using linear covariance analysis techniques in this paper. Firstly, the main existing errors are analyzed and a closed-loop control system for orbit maneuver is established. Then, the models and equations for linear covariance orbit maneuver problem under both open-loop and closed-loop controls are developed respectively. And correction algorithm is presented based on orbit motion equation linearization. At last, the terminal state accuracies of high eccentric orbit maneuver under both open-loop and closed-loop controls is analyzed. And the validity of the results derived from linear covariance techniques is proved by using Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

This article proposes a novel distributed predefined-time sliding mode controller (DPTSMC) to gain exceptional performances of power system under input saturation. Firstly, considering the saturation of excitation input to avoid the overvoltage of the coil, an auxiliary system is taken to compensate the effect of the excitation saturation. Then, the sliding mode control (SMC) and the predefined-time stability theory are taken to devise the DPTSMC to make the power system stable in a predefined time, which has an upper limit and is directly equivalent to an adjustable parameter, thus satisfying the high requirement of the power system for expected convergence time. Meanwhile, the estimated upper bound convergence time of the power system under the proposed DPTSMC is less conservative than some existing fixed-time control strategies. Moreover, the distributed control is taken to devise the DPTSMC and the controller can receive the real-time information from the phasor measurement units (PMU). Hence, the central controller is not required and the communication network is simple, thus releasing the pressure in complicated calculation and communication, and gaining rapid and coordinated response capacity. Next, the stabilization of the power system under the DPTSMC within a predefined upper limited time is proved through the Lyapunov function. Finally, the exceptional performance of the proposed DPTSMC than the existing control methods is verified through the simulation in the IEEE 39-bus 10-machine New England power system under different operation scenarios. [ABSTRACT FROM AUTHOR]

Protostemonamide ( 1), a new protostemonine-type alkaloid, and 12 known compounds were isolated from the roots of STEMONA SESSILIFOLIA. Their structures were elucidated by 1?D and 2?D NMR spectral and other spectroscopic studies. The main alkaloidal constituents, protostemonine ( 2), stemospironine ( 4), and maistemonine ( 7), showed significant antitussive activity in a citric acid-induced guinea pig cough model following peripheral administration; stemonamine ( 11) had antitussive activity following i.?c.?v. administration. [ABSTRACT FROM AUTHOR]

Reports on the popularity of cartoons in China. Impact of the growing number of adults who watch cartoons on the cartoon market; Lack of professionalism in dubbing and poor quality background music; Countries that have ventured into the Chinese cartoon markets; Efforts of the Shanghai Animated Film Studio to adapt its market operations to current trends; Increase of academic exchanges within the cartoon field.

To improve the robust characteristic and filtering accuracy of the traditional adaptive filtering algorithms (AFAs) under censored regression (CR) model in impulsive interference environments, some robust CR-type AFAs (R-CR-AFAs) have been developed. However, these exiting R-CR-AFAs may suffer from high steady-state misalignment in parameter estimation scenario. Therefore, in this paper, we first construct a unified framework to develop a class of R-CR-AFAs by adopting various robust strategies with error nonlinearities as cost functions. Then the mean and mean-square stability ranges and steady-state convergence behavior of the R-CR-AFAs are analyzed via resorting to some frequently-utilized assumptions and lemmas. In particular, a novel censored regression generalized modified Blake-Zisserman adaptive filtering (CR-GMBZ-AF) algorithm is presented to achieve higher steady-state estimation accuracy contrasted to related R-CR-AFAs benefiting from the advantages of the newly proposed GMBZ criterion based on the unified framework. Numerical simulation experiments manifest that the developed CR-GMBZ-AF algorithm arrives at better learning performance in comparison with state-of-the-art algorithms and the theoretical steady-state model demonstrates good agreement with simulation results under parameter estimation and acoustic echo cancellation scenarios. [ABSTRACT FROM AUTHOR]

In this research, free and forced vibrations of the functionally graded material (FGM) sandwich beams are investigated by using the scaled boundary finite element method (SBFEM). The innovation of this method is that the discretization only exists in the axial direction of the beam, which reduces the spatial dimension of problem by one, the time-consuming mesh generation processes are greatly reduced. The homogeneous second-order differential equations of the beams are derived by the method of virtual work principle with the radial coordinates as independent variables, which realizes the characteristics of the FGM changing along the radial direction. By using the state space method and the Padé series expansion method, the governing equations are further solved analytically, and the mass and stiffness matrices of each layer of the FGM sandwich beams are obtained. The combination between layers of the FGM sandwich beams is realized according to continuity conditions of displacement. Therefore, the free and forced vibrations using Newmark time integration method of the FGM sandwich beams are further realized. A special attention is given to two different types of the FGM sandwich beams, one is the beam with FGM face sheets and the other is the beam with FGM core. Three different types of dynamic loadings are considered in the analysis of forced vibration. The convergence of the proposed method for solving the dynamic characteristics of the beams is verified by increasing the order of the higher order spectral elements. In order to prove the numerical stability of the current method for dynamic analysis of the FGM sandwich beams, the frequency of the FGM sandwich beams under various parameters and the transient vertical displacement of the beam loading points under three different loadings are solved. The numerical results of the current method are compared with the results obtained by using different theories in the other literature, which shows a good agreement. In addition, on the basis of the research, the doped FGM core in the uniform core is discussed by using the current method, which provides some guidance for the optimal design of the dynamic characteristics of the beams. [ABSTRACT FROM AUTHOR]

Singular spectrum analysis (SSA) has been verified to be an effective method for decomposing non-stationary signals. The decomposition and reconstruction stages can be interpreted as a zero-phase filtering process where reconstructed components are obtained by inputting a signal through moving average filters. However, mathematical analysis indicates that the use of a default rectangular window in the embedding stage would corrupt the frequency characteristics of the trajectory matrix, resulting in spectral leakage. To attenuate the effect of spectral leakage and to obtain more concentrated SSA components, this study introduces a windowing technique in SSA, called generalized singular spectrum analysis (GSSA). In GSSA, the default rectangular window is replaced with adjustable taper windows, which are widely used for attenuating spectral leakage. Through windowing, GSSA can achieve less spectral leakage, and produce more energy-concentrated reconstructed components compared with conventional SSA. Grouped spectral entropy (GSE) is used as the metric for evaluating the performance of the proposed GSSA algorithm. Results from experiments, which were conducted on a synthetic signal and two real electroencephalogram signals, show that GSSA outperforms the conventional SSA and the baseline in the reduction of spectral leakage. Compared with the baseline, the proposed GSSA achieves a lower averaged GSE, resulting in reduction of 0.4 for eigenfilters and 0.11 for reconstructed components, respectively. Our results reveal the effectiveness of GSSA in the decomposition and analysis of non-stationary signals. [ABSTRACT FROM AUTHOR]

Ten new triterpene saponins (1-10) have been isolated from the stems of Entada phaseoloides. Their structures were elucidated by spectroscopic analysis and chemical methods. Among these compounds, the aglycons of 6-10 are being reported for the first time, in this study, including 3β, 15α, 16α-trihydroxy-11 α, 12α-epoxy olean- 28, 13β-olide (6), 3β,15α,16α-trihydroxy-11-oxo-olean-12-en-28-oic acids (7 and 8), and 3β, 15α, 16α-trihydroxy-oleana-11, 13(18)-dien-28-oic acids (9 and 10). The cytotoxic activities of all of these compounds were evaluated against HepG-2, A549, and Ec-1 cell lines. [ABSTRACT FROM AUTHOR]

A fundamental premise of an accelerated testing is that the failure mechanism under elevated and normal stress levels should remain the same. Thus, verification of the consistency of failure mechanisms is essential during an accelerated testing. A new consistency analysis method based on the gray theory is proposed for complex products. First of all, existing consistency analysis methods are reviewed with a focus on the comparison of the differences among them. Then, the proposed consistency analysis method is introduced. Two effective gray prediction models, gray dynamic model and new information and equal dimensional (NIED) model, are adapted in the proposed method. The process to determine the dimension of NIED model is also discussed, and a decision rule is expanded. Based on that, the procedure of applying the new consistent analysis method is developed. Finally, a case study of the consistency analysis of a reliability enhancement testing is conducted to demonstrate and validate the proposed method. [ABSTRACT FROM AUTHOR]

The aim of the present study was to investigate the cytotoxic and antitumour effects of baicalin in human chondrosarcoma both in vivo and in vitro. We examined the effects of baicalin on the growth and apoptosis of human chondrosarcoma cells. Baicalin inhibited the growth of SW1353 and CH2879 cells in a dose- and time-dependent manner, but did not inhibit the growth of normal chondrocytes. Baicalin reduced tumour growth and induced apoptotic death in SW1353-transplanted nude mice without reducing their body weight. Further studies showed that baicalin reduced the mitochondrial membrane potential, upregulated the expression of Bax and cytoplasmic cytochrome c, downregulated the expression of Bcl-2 and mitochondrial cytochromes, and activated caspase-3 and caspase-9. Baicalin inhibited the phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin pathway by decreasing the expression of phosphorylated phosphoinositide 3-kinase, phosphorylated protein kinase B, and phosphorylated mammalian target of rapamycin both in vivo and in vitro. Moreover, the mice that received SC79 and baicalin exhibited a greater tumour size compared with the mice that received baicalin. The mice that received LY294002 and baicalin showed a smaller tumour size compared with the mice that received baicalin. In the in vitro study, SC79 and LY294002 affected the baicalin-induced cytotoxic effects on chondrosarcoma cells in the same manner. Our data suggest baicalin has therapeutic efficacy in human chondrosarcoma through the induction of apoptosis and inhibition of the phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin pathway. Baicalin can be considered a potential therapeutic agent for treating chondrosarcomas. [ABSTRACT FROM AUTHOR]

Gradient features are known to be effective for full-reference (FR) image quality assessment (IQA). However, only a few metrics utilize gradient features for no-reference (NR) IQA. To investigate the potential benefits of gradient magnitude and phase for NR-IQA, we propose a novel and effective local-statistical-feature extraction metric, namely Local Gradient Patterns (LGP), for general-purpose NR-IQA. Using a Gaussian partial derivative filter, the image is first decomposed into two complementary components: gradient magnitude and phase. The local statistical features (e.g., the conditional probability distributions) are then extracted from the complementary components, using the derived local gradient magnitude and phase pattern operators. Finally, to facilitate NR-IQA, local statistical features that convey important structural information are mapped to the subjective mean opinion score of the image, using a support vector regression (SVR) procedure. We evaluated our proposed LGP metric using images from two publicly available test databases; the results confirm that the proposed LGP metric provides predictive performance that is superior to most state-of-the-art NR-IQA metrics and has an acceptable level of computational complexity. [ABSTRACT FROM AUTHOR]