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Information technology is a globally recognized new revolution in science and technology that is happening, which greatly improves the production efficiency. China began to develop information industry in the 1990s. After realizing the catch-up disadvantages of independent research and development, it started to open its market to exchange for technology. After decades of technological catch-up and game, some areas of China's information industry have been able to compete with the cutting-edge technologies in Europe and America. This paper mainly studies the adaptability of technological catch-up theory to the development of information industry in China; analyzes the tripartite game between catching-up firms, leading firms and government in the process of technological catch-up; and proves the validity of the theory through case studies. [ABSTRACT FROM AUTHOR]

Objectives: Traditional brain age estimation methods are based on the idea that uses the real age as the training label. However, these methods ignore that there is a deviation between the real age and the brain age due to the accelerated brain aging.Methods: This paper considers this deviation and obtains it by maximizing the correlation between the estimated brain age and the class label rather than by minimizing the difference between the estimated brain age and the real age. Firstly, set the search range of the deviation as the deviation candidates according to the prior knowledge. Secondly, use the support vector regression as the age estimation model to minimize the difference between the estimated age and the real age plus deviation rather than the real age itself. Thirdly, design the fitness function based on the correlation criterion. Fourthly, conduct age estimation on the validation dataset using the trained age estimation model, put the estimated age into the fitness function, and obtain the fitness value of the deviation candidate. Fifthly, repeat the iteration until all the deviation candidates are involved and get the optimal deviation with maximum fitness values. The real age plus the optimal deviation is taken as the brain pathological age.Results: The experimental results showed that the separability of the samples was apparently improved. For normal control- Alzheimer's disease (NC-AD), normal control- mild cognition impairment (NC-MCI), and mild cognition impairment-Alzheimer's disease (MCI-AD), the average improvements were 0.164 (31.66%), 0.1284 (34.29%), and 0.0206 (7.1%), respectively. For NC-MCI-AD, the average improvement was 0.2002 (50.39%). The estimated brain pathological age could be not only more helpful for the classification of AD but also more precisely reflect the accelerated brain aging.Conclusion: In conclusion, this paper proposes a new kind of brain age-brain pathological age and offers an estimation method for it that can distinguish different states of AD, thereby better reflecting accelerated brain aging. Besides, the brain pathological age is most helpful for feature reduction, thereby simplifying the relevant classification algorithm. [ABSTRACT FROM AUTHOR]

Background: Amyloid β-protein (Aβ) plaque deposition is an important prevention and treatment target for Alzheimer's disease (AD). As a noninvasive, nonradioactive and highly cost-effective clinical imaging method, magnetic resonance imaging (MRI) is the perfect imaging technology for the clinical diagnosis of AD, but it cannot display the plaque deposition directly. This paper resolves this problem based on pixel feature selection algorithms at the image level. Methods and Results: Firstly, the brain region was segmented from mouse model brain MR images. Secondly, the pixels in the segmented brain region were extracted as a feature vector (features). Thirdly, feature selection was conducted on the extracted features, and the optimal feature subset was obtained. Fourthly, the various optimal feature subsets were obtained by repeating the same processing above. Fifthly, based on the optimal feature subsets, the final optimal feature subset was obtained by voting mechanism. Finally, using the final optimal selected features, the corresponding pixels on the MR images could be found and marked to show the information about Aβ plaque deposition. The MR images and brain histological image slices of twenty-two model mice were used in the experiments. Four feature selection algorithms were used on the MR images and six kinds of classification experiments are conducted, thereby choosing a pixel feature selection algorithm for further study. The experimental results showed that by using the pixel features selected by the algorithms in this paper, the best classification accuracy between early AD and control slides could be as high as 80 %. The selected and marked MR pixels could show information of Aβ plaque deposition without missing most of the Aβ plaque deposition compared with brain histological slice images. The hit rate is over than 90 %. Conclusions: According to the experimental results, the proposed detection algorithm of the Aβ plaque deposition based on MR pixel feature selection algorithm is effective. The proposed algorithm can detect the information of the Aβ plaque deposition on MR images and the information can be useful for improving the classification accuracy as assistant MR biomarker. Besides, these findings firstly show the feasibility of detection of the Aβ plaque deposition on MR images and provide reference method for interested relevant researchers in public. [ABSTRACT FROM AUTHOR]

Background: Insulin-like growth factor I (IGF-I) is one important family of growth factors, which plays key role in intestinal growth, regeneration, and damage repair. However, the low natural abundance of IGF-I limits its research opportunities and practical application in the fields of medicine and animal husbandry. In this study, a tandem repeat strategy was used to express three copies of the same pIGF-I3 protein in L. lactis. The activity of recombinant pIGF-I3 (rpIGF-I3) was further examined by a mouse model of dextran sulfate sodium (DSS)-induced colitis. In addition, the potential of recombinant L. lactis expressing pIGF-I3 to reduce inflammatory disease was evaluated. Results: pIGF-I3 could be expressed in L. lactis by the detection of SDS-PAGE and Western blot. Experimental colitis was induced in BALB/c mice by administration of 5 % DSS in drinking water, and the clinical symptoms were observed in DSS-treated mice. Oral administration of recombinant L. lactis expressing pIGF-I3 improved the colonic architecture, and significantly reduced the increase of colonic damage score (P < 0.05). Furthermore, recombinant L. lactis expressing pIGF-I3 treatment significantly reduced serum DAO activity and colonic MPO level, and elevated colonic occludin level compared to the DSS group (P < 0.05). Conclusions: The pIGF-I3 expressed in L. lactis has good biological activity, and oral administration of recombinant L. lactis expressing pIGF-I3 attenuated the symptoms and development of DSS-induced colitis in mice. These suggested that L. lactis could be a potential host bacterium for production and delivery of IGF-I against intestinal diseases. [ABSTRACT FROM AUTHOR]

The problem of tracking error constrained adaptive fuzzy output feedback control is investigated for a class of single-input and single-output (SISO) stochastic nonlinear systems with actuator faults, unknowntime-delay, and unmeasured states. Theconsidered faults are modeled as both loss of effectiveness and lock-in-place. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy adaptive observer is designed for estimating the unmeasured states. By transforming the tracking errors into new virtual error variables and based on backstepping recursive design technique, a new fuzzy adaptive output feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin within the prescribed bounds. The simulation results are provided to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Fimbrial adhesin plays a critical role in the pathogenesis of enterotoxigenic Escherichia coli (ETEC)- induced piglet diarrhoea. Lactococcus lactis is an attractive food-grade host for the production of heterologous antigens. We previously demonstrated that fimbrial adhesin FaeG was expressed in L. lactis and that oral immunization in mice with recombinant L. lactis expressing FaeG induced F4-specific mucosal and systemic immune responses. In the present study, we explored the immune responses of piglets induced by intramuscular vaccination with recombinant L. lactis expressing rFaeG. Intramuscular vaccination resulted in significantly elevated serum IgG level and modest increases in serum IgA and IgM levels. In addition, IgG, IgA, and IgM antibody secreting cells were induced in the spleen, mesenteric lymph nodes, and jejunum. The growth performance of piglets was not influenced by intramuscular vaccination. The results suggest that L. lactis expressing FaeG is a promising candidate vaccine against ETEC. [ABSTRACT FROM AUTHOR]

The article reports on research which was conducted to investigate the electromyographic activity of the lower limbs of athletes who performed squatting on a Reebok core board and the ground. Researchers found that the electromyography revealed similar muscle activities in squatting on both surfaces.

This paper concerned the problem of delay-dependent asymptotic stability for neural networks with time-varying delay. A new class of Lyapunov functional dividing the interval delay is constructed to derive some new delay-dependent stability criteria. The obtained criteria are less conservative because free-weighting matrices method, a convex optimization approach, and a mixed dividing delay interval approach are considered. Finally, numerical examples are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to introduce a new system of nonlinear implicit fuzzy resolvent operators of (A,η)-monotone type and to develop a new iterative algorithm to approximate the solutions of the nonlinear implicit fuzzy resolvent operator systems. Further, by using Rus's results and some new analytic techniques, we also prove the existence of solutions and the convergence of the sequences generated by the algorithms. The results presented in this paper improve and generalize the corresponding results of recent works. [ABSTRACT FROM AUTHOR]

A highly specific and sensitive microplate chemiluminescent enzyme immunoassay (CLEIA) was established and validated for the detection of staphylococcal enterotoxin B (SEB). A pair of monoclonal antibodies (mAbs) that recognizes different epitopes of SEB was selected from 20 SEB-specific mAbs, and the experimental conditions were examined and optimized for the development of the CLEIA. This method exhibited high performance with a dynamic range of 0.01-5 ng/mL, and the measured limit of detection (LOD) was 0.01 ng/mL Intra- and interassay coefficient variations were all lower than 13% at three concentrations (0.2, 0.4, and 2 ng/mL). For specificity studies, when this method was applied to test staphylococcal enterotoxins A, C1, and D, no cross-reactivity was observed. It has been successfully applied to the analysis of SEB in a variety of environmental, biological and humoral matrices such as sewage, tap water, river water, roast beef, peanut butter, cured ham, 10% nonfat thy milk, milk, orange juice, and human urine and serum. The aim of this article is to show that the highly sensitive, specific, and simple microplate CLEIA, based on a pair of highly specific monoclonal antibodies, has potential applications for quantifying SEB in public health and military reconnaissance. [ABSTRACT FROM AUTHOR]

Background: Mechanical strain plays a significant role in the regulation of bone matrix turnover, which is mediated in part by matrix metalloproteinase (MMP)-13 and tissue inhibitors of matrix metalloproteinase (TIMP)-1. However, little is known about the correlation between mechanical strain and osteoblastic cell activities, including extracellular matrix (ECM) metabolism. Herein, we determined the effect of different magnitudes of cyclic tensile strain (0%, 6%, 12%, and 18%) on MMP-13 and TIMP-1 mRNA and protein expression in MC3T3-E1 osteoblasts. Furthermore, we employed specific inhibitors to examine the role of distinct signal transduction pathways known to mediate cellular responses to mechanical strain. Results: We identified a magnitude-dependent increase in MMP-13 and TIMP-1 mRNA and protein levels in response to mechanical strains corresponding to 6%, 12%, and 18% elongation. The strain-induced increases in MMP-13 and TIMP-1 mRNA expression were inhibited by PD098059 and cycloheximide, respectively. Conclusions: Our results suggest a mechanism for the regulation of bone matrix metabolism mediated by the differential expression of MMP-13 and TIMP-1 in response to increasing magnitudes of mechanical strain. [ABSTRACT FROM AUTHOR]

In this paper, we generalize Ying's model of linguistic quantifiers [M.S. Ying, Linguistic quantifiers modeled by Sugeno integrals, Artificial Intelligence, 170 (2006) 581-606] to intuitionistic linguistic quantifiers. An intuitionistic linguistic quantifier is represented by a family of intuitionistic fuzzy-valued fuzzy measures and the intuitionistic truth value (the degrees of satisfaction and non-satisfaction) of a quantified proposition is calculated by using intuitionistic fuzzy-valued fuzzy integral. Description of a quantifier by intuitionistic fuzzy-valued fuzzy measures allows us to take into account differences in understanding the meaning of the quantifier by different persons. If the intuitionistic fuzzy linguistic quantifiers are taken to be linguistic fuzzy quantifiers, then our model reduces to Ying's model. Some excellent logical properties of intuitionistic linguistic quantifiers are obtained including a prenex norm form theorem. A simple example is presented to illustrate the use of intuitionistic linguistic quantifiers. [ABSTRACT FROM AUTHOR]

In this paper, we define weakly regular quantum grammars (WRQG), regular quantum grammars (RQG), asynchronous quantum automata (AQA) and synchronous quantum automata (SQA). Moreover, we investigate the relationships between quantum languages generated by weakly quantum regular grammars and by asynchronous quantum automata. At the mean time, we discuss the relationships between regular quantum grammars and synchronous quantum automata. [ABSTRACT FROM AUTHOR]

Abstract  In this paper, the algebraic operations on the cuts of lattice-valued regular languages are studied. Some sufficient conditions are given to guarantee the family of the cuts of lattice-valued regular languages to be closed under such algebraic operations as union, intersection, complement, quotient, homomorphism, inverse homomorphism, concatennation, reversal, etc. [ABSTRACT FROM AUTHOR]

Single-walled carbon nanotubes (SWNTs) were incorporated into precursor-derived ceramics made from a polysilazane. To improve the dispersion of the nanotubes in the liquid precursor and finally in the ceramic matrix, the SWNTs were chemically modified by (iodomethyl)trimethylsilane via a radical reaction. The functionalization degree of the modified SWNTs was determined to be 3 atom %. Microscopic investigation combined with viscosity measurements and thixotropy tests demonstrated that the functionalized SWNTs are more homogeneously dispersed in the liquid SWNT/polymer mixtures and the solid cross-linked precursor, as compared to pristine nanotubes. SWNT/Si−C−N ceramics with nanotube contents of up to 1 wt % were obtained through pyrolysis of cross-linked SWNT/polymer composites at 1000 °C. The presence of intact nanotubes in these composites could be verified by scanning transmission electron microscopy. The high viscosity of the SWNT/polysilazane mixtures was identified as an important prerequisite for attaining good nanotube dispersion in the Si−C−N matrix. [ABSTRACT FROM AUTHOR]

Abstract??In this paper we introduce the definitions of generalized ideals and generalized filters in pseudo effect algebras. From the generalized ideals (filters), we obtain some equivalent characterization of ideals (filters). The relationships among generalized ideals, ideals and local ideals are studied in detail. We also establish an isomorphism between the set of supports and the set of generalized ideals of pseudo effect algebras. [ABSTRACT FROM AUTHOR]

The definitions of sharply approximating effect algebras, anti-BZ-effect algebras, central approximating effect algebras, and S-anti-BZ-effect algebras are given, the relationships between sharply approximating effect algebras and anti-BZ-effect algebras, between central approximating effect algebras and anti-BZ-effect algebras are established, and the set of anti-BZ-sharp elements in S-anti-BZ-effect algebras is proved to be an orthomodular lattice. [ABSTRACT FROM AUTHOR]

In this Letter a new algorithm to compute the corner-point field components of a two-dimensional (2-D) Mur absorbing boundary condition (ABC) in the finite-difference–time-domain (FDTD) method is presented. It is shown that field value calculation at the corner points of the truncation domain affects the accuracy of the FDTD. The proposed scheme overcomes the drawbacks of reflection on the truncated boundary and computation divergence that may occur when the existing scheme is used. Numerical examples are illustrated to validate the effectiveness of the proposed scheme. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 33: 437–440, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10344 [ABSTRACT FROM AUTHOR]

In this paper, the electromagnetic scattering property of a square tabular conductor coated with anisotropic material in three-dimension is studied via Finite-Difference Time-Domain (FDTD) method. From the results, one can find that if the parameters of the anisotropic material change, the backward scattered field will also change. And lower backward scattered field can be obtained by adjusting the parameters of coated anisotropic material. [ABSTRACT FROM AUTHOR]

In this paper, we mainly study the asymptotic normality of wavelet estimators in the heteroscedastic regression model with φ-mixing errors. Under some suitable conditions, the asymptotic normality of the wavelet estimators of g and f in the heteroscedastic regression model with φ-mixing errors are obtained, which generalize or improve the corresponding ones for α-mixing random variables and martingale difference sequence in some sense. Also, the simulation study of the finite samples provided in this paper shows the validity of our results. [ABSTRACT FROM AUTHOR]

In this paper, some kinds of very extensive free completely distributive lattices generated by posers are constructed, they generalize some well known results of free objects in completely distributive lattices and take them in a universal form. [ABSTRACT FROM AUTHOR]

Presents a study of the theory of fuzzy topology and point set topology in topological molecular lattices. Relations among the categories of topological molecular lattice and certain related categories; Difficulty in developing a theory of topological molecular lattices by means of methods in classical topology; Definition of a topological space; Information on a mapping between topological spaces.

We investigate the non-Markovian behavior in open quantum systems from an information-theoretic perspective. Our main tool is the max-relative entropy, which quantifies the maximum probability with which a state ρ can appear in a convex decomposition of a state σ. This operational interpretation provides a new view for the non-Markovian process. We also find that max-relative entropy can be the witness and measure of non-Markovian processes. As applications, some examples are also given and compared with other measures in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we discuss quantum uncertainty relations of quantum coherence through a different method from Ref. [52]. Some lower bounds with parameters and their minimal bounds are obtained. Moreover, we find that for two pairs of measurement bases with the same maximum overlap, quantum uncertainty relations and lower bounds with parameters are different, but the minimal bounds are the same. In addition, we discuss the dynamics of quantum uncertainty relations of quantum coherence and their lower bounds under the amplitude damping channel (ADC). We find that the ADC will change the uncertainty relations and their lower bounds, and their tendencies depend on the initial state. [ABSTRACT FROM AUTHOR]

In this paper, we present an inequality of characteristic functions for ψ-mixing random vectors, and derive an upper bound for the supremum of the absolute value of the difference of two multivariate probability density functions based on ψ-mixing random vectors. For its application, we discuss the Berry-Esseen type bounds for conditional value-at-risk estimator based on ψ-mixing sequences, by the suitable choice of some constants, the Berry-Esseen type bounds of the estimator can attain O ( n − 1 / 6 ). [ABSTRACT FROM AUTHOR]

Traditional age estimation methods are based on the same idea that uses the real age as the training label. However, these methods ignore that there is a deviation between the real age and the brain age due to accelerated brain aging. This paper considers this deviation and searches for it by maximizing the separability distance value rather than by minimizing the difference between the estimated brain age and the real age. Firstly, set the search range of the deviation as the deviation candidates according to prior knowledge. Secondly, use the support vector regression (SVR) as the age estimation model to minimize the difference between the estimated age and the real age plus deviation rather than the real age itself. Thirdly, design the fitness function based on the separability distance criterion. Fourthly, conduct age estimation on the validation dataset using the trained age estimation model, put the estimated age into the fitness function, and obtain the fitness value of the deviation candidate. Fifthly, repeat the iteration until all the deviation candidates are involved and get the optimal deviation with maximum fitness values. The real age plus the optimal deviation is taken as the brain pathological age. The experimental results showed that the separability was apparently improved. For normal control-Alzheimer’s disease (NC-AD), normal control-mild cognition impairment (NC-MCI), and MCI-AD, the average improvements were 0.178 (35.11%), 0.033 (14.47%), and 0.017 (39.53%), respectively. For NC-MCI-AD, the average improvement was 0.2287 (64.22%). The estimated brain pathological age could be not only more helpful to the classification of AD but also more precisely reflect accelerated brain aging. In conclusion, this paper offers a new method for brain age estimation that can distinguish different states of AD and can better reflect the extent of accelerated aging. [ABSTRACT FROM AUTHOR]

The article focuses on the study about the coplanar oligo(p-phenylenedisilenylene)s (Si-OPVs) based on the octaethyl-substituted s-hydrindacenyl groups. Intricately, the researchers have synthesized planar Si-OPVs, disilastilbene 1 and tetrasiladistyrylbenzene 2, by introduction of a newly developed Eind ligand, which not only efficiently protects the reactive Si=Si bridge but also controls the Si-OPV framework to coplanar structure.

This study develops a scheme of an adaptive fuzzy dynamic surface control (DSC) for a non-linear non-strict feedback system with immeasurable states. By utilising the universal approximation property of a fuzzy logic system, a state observer is designed to estimate the unmeasured states. Based on the back-stepping DSC design technique, an adaptive fuzzy output feedback control design method is developed. The proposed method can overcome the 'explosion of complexity' problem, and also can eliminate the limitation of the measurable states. It is proved that the control method can guarantee that all the signals in the closed-loop system are bounded and the system output can track the given reference signal well. The simulation results are provided to demonstrate the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

Grass carp hemorrhagic disease, caused by the grass carp reovirus (GCRV), is a major disease that hampers the development of grass carp aquaculture in China. The mechanism underlying GCRV infection is still largely unknown. Circular RNAs (circRNAs) are important regulators involved in various biological processes. In the present study, grass carp were infected with GCRV, and spleen samples were collected at 0 (control), 1, 3, 5, and 7 days post-infection (dpi). Samples were used to construct and sequence circRNA libraries, and a total of 5052 circRNAs were identified before and after GCRV infection, of which 41 exhibited differential expression compared with controls. Many parental genes of the differentially expressed circRNAs are involved in metal ion binding, protein ubiquitination, enzyme activity, and nucleotide binding. Moreover, 72 binding miRNAs were predicted from the differentially expressed circRNAs, of which eight targeted genes were predicted to be involved in immune responses, blood coagulation, hemostasis, and complement and coagulation cascades. Upregulation of these genes may lead to endothelial and blood cell damage and hemorrhagic symptoms. Our results indicate that an mRNA-miRNA-circRNA network may be present in grass carp infected with GCRV, providing new insight into the mechanism underlying grass carp reovirus infection. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive fuzzy output-feedback dynamic surface control (DSC) design with prescribed performance is investigated for a class of uncertain nonlinear systems in strict-feedback form. The considered nonlinear systems contain unknown nonlinear functions, unmodeled dynamics and immeasurable states. The fuzzy logic systems are used to model the unknown nonlinear system, and a fuzzy state observer is designed to estimate the immeasurable states. By transforming the errors into new virtual error variables, and based on DSC backstepping design technique and changing supply function, a new robust adaptive fuzzy output feedback control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded, and the dynamic surface errors are confined within the prescribed bounds for all times. Two simulation examples are provided to show the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing is regarded as one of the essential techniques for developing shale reservoirs at present. During fracturing, propagation of multi-fractures and complex fracture network is developed as result of interactions between preexisting natural fractures and hydraulic fractures, as evidenced by microseismic event patterns. This paper introduces a new mathematic model for analyzing the growth and geometry of fracture network in association with criterions of dilation and propagation based on the theory of fracture mechanics. The solution method concentrates on both extension description and dimensions calculation of every branching fracture through local explicit computation and iteration improvement. Simulation results indicate that the complex fracture network significantly depends on the features of preexisting natural fractures, optimization of fracturing parameters and materials for realizing simultaneous extension at higher net pressure. The areas with less horizontal stress contrast would increase curvature radius of fracture propagation path, which facilitates interconnection with more natural fractures on the lateral plane, and also expands network volume. Propagating angle and pressure at fracture tip for further propagation and dimensions computation are influenced by the properties of natural fractures, such as length and orientation. By using actual treatment parameters, complex fracture model is corrected against microseismic monitoring patterns by matching the distribution and density of interpretation data with geometry and complexity of simulation results; it is also applicable to fracturing design. [ABSTRACT FROM AUTHOR]

This study investigates the adaptive fuzzy fault-tolerant control (FTC) problem for a class of uncertain non-linear strict-feedback systems with unmeasured states. The considered non-linear systems contain unknown continuous functions and do not satisfy the matching condition. The actuator failures under study are types of both abrupt faults and lock-in-place and loss of effectiveness. The fuzzy logic systems are employed to approximate the unknown continuous functions, and a fuzzy state observer is developed and the unmeasured states are obtained. Under the framework of the backstepping design technique and incorporated by the dynamic surface control approach and predefined performance bounds, an adaptive fuzzy FTC method has been presented. From the Lyapunov stability analysis, it is shown that all the signals of the resulting closed-loop system are bounded and the tracking error surfaces remain within the prescribed performance bounds in the presence of unknown non-linear actuator faults. The simulation results and comparisons with the previous methods indicate the effectiveness of the proposed adaptive fuzzy FTC. [ABSTRACT FROM AUTHOR]

Through the analysis of the impact of changes in the cotton planting industry on cotton production structure and benefit in Shandong under the national cotton production pattern in past ten years, based on the guarantee of food security and the overall ecological regional layout of Shandong's agricultural characteristic and advantageous industries, we proposed that through the development of high-quality short-season cotton and the industrial application of high-efficiency technologies, a green and high-efficiency farming system should be established to comprehensively reduce cotton planting costs, improve comparative benefits, and realize green and efficient optimization technologies that unify the stable production of cotton and high-quality cotton supply and the industrial path supported by the new industrial model. It is aimed to speed up the upgrading and transformation of the existing traditional cotton cropping system, reconstruct a ternary structure of grains, economic crops and fodder in the ecological suitable cotton areas and sub-suitable cotton areas in Shandong, and maintain a series of new green and ecological cotton rotation industrial models including the "double security" of the grain and cotton industries, the ecological "double superiority" of cotton and fodder", and the high-efficiency "double increase" of cotton and garlic, providing a certain foundation for the research on technological integration innovation and industrial structure optimization of the green, efficient and high-quality development and transformation of the cotton industry in Shandong during the "14th Five-Year Plan" period. [ABSTRACT FROM AUTHOR]

This article extends the application of the adaptive neural network control to a new class of uncertain MIMO non-linear systems, which are composed of interconnected subsystems where each interconnected subsystem is in the non-affine pure-feedback form. Because both the variables which are used as virtual controllers and the actual controllers appear non-linearly in unknown functions of the MIMO systems, thus, this class of systems is difficult to control. The radial basis function neural networks are utilised to approximate the desired virtual controllers and the desired actual controllers which are obtained by using implicit function theorem. The salient property of the proposed approach is that the number of the adjustable parameters is less than the numerous alternative approaches existing in the literature. It is proven that, under appropriate assumptions, all the signals in the closed-loop system are uniformly bounded and the tracking errors converge to a small neighbourhood of the origin by appropriately choosing design parameters. The feasibility of the developed approach is verified by two simulation examples. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a fuzzy adaptive backstepping output feedback control approach is developed for a class of multi-input and multi-output (MIMO) nonlinear systems with unmeasured states. Using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive observer is designed for state estimation as well as system identification. Combining with the backstepping design techniques, a fuzzy adaptive output feedback control is constructed recursively. It is proved that the proposed fuzzy adaptive control approach can guarantee the semi-global uniform ultimate boundedness for all the signals and the tracking error to a small neighborhood of the origin. Simulation studies illustrate the effectiveness of the proposed approach. [Copyright &y& Elsevier]

Quantum finite automata (QFA) can be divided into four kinds depend upon the head-directions and the measure times. They are measure-once one way QFA (MO-1QFA) introduced by Moore and Crutchfield (Theor Comput Sci 237: 275–306, 2000); measure-many one way QFA (MM-1QFA) and measure-many two-way QFA (MM-2QFA) introduced by Kondacs and Watrous (Proceedings of the 38th IEEE annual symposium on 433 foundations of computer science, 66–75, 1997); and measure-once two-way QFA (MO-2QFA) which were not given until now. The purpose of this work is mainly to discuss one kind of QFA, which is called MO-2QFA for brief. First of all, the definition of MO-2QFA is given and the conditions for preserving unitary properties are shown. Then, we analysis the basic algebraic properties of the class of languages which can be recognized by MO-2QFA, such as the union, intersection, complement and reversal operations. As well, we consider the catenation operation on the class of quantum languages recognized by MO-2QFA is closed in the generalized conditions. [ABSTRACT FROM AUTHOR]

Region Connection Calculus (RCC) is the most widely studied formalism of Qualitative Spatial Reasoning. It has been known for some time that each connected regular topological space provides an RCC model. These 'standard' models are inevitable uncountable and regions there cannot be represented finitely. This paper, however, draws researchers' attention to RCC models that can be constructed from finite models hierarchically. Compared with those 'standard' models, these countable models have the nice property that regions where can be constructed in finite steps from basic ones. We first investigate properties of three countable models introduced by Düuntsch, Stell, Li and Ying, resp. In particular, we show that (i) the contact relation algebra of our minimal model is not atomic complete; and (ii) these three models are non-isomorphic. Second, for each n>0, we construct a countable RCC model that is a sub-model of the standard model over the Euclidean unit n-cube; and show that all these countable models are non-isomorphic. Third, we show that every finite model can be isomorphically embedded in any RCC model. This leads to a simple proof for the result that each consistent spatial network has a realization in any RCC model. [ABSTRACT FROM AUTHOR]

Injuries to upper and lower extremities comprise more than 70% of the total injuries in collegiate athletes. Establishing normative data of upper and lower extremity strength and balance may help guide postinjury rehabilitation and return-to-play decisions. The purposes of the current study were to develop the normative data of performance and bilateral asymmetries during 4 upper and lower extremity strength and balance tests in collegiate athletes and to quantify the correlations between strength and balance performance and bilateral asymmetries. A total of 304 male and 195 female Division I athletes from 14 sports performed a maximum push-up test to assess upper extremity strength, a countermovement jump test to assess lower extremity strength, an upper extremity reaching test to assess upper extremity balance, and a lower extremity reaching test to assess lower extremity balance. Bilateral ground reaction forces were collected for the push-up and jump tests. Reaching distances were measured for the 2 balance tests. Bilateral asymmetries were generally less than 10%. Significant sports effects were observed for all 5 performance variables ( p < 0.001) but not for asymmetry variables ( p ≥ 0.36). Weak correlations were found between strength and balance performance and asymmetries ( r < 0.3). Normative data are sex and sports specific in collegiate athletes. Increased asymmetries could be more individualized rather than sex and sports specific. When return-to-play decisions are made, athletes following injuries need to demonstrate less than 10% of asymmetries to be consistent with the normative data. Strength and balance should be evaluated and improved with specific focuses. [ABSTRACT FROM AUTHOR]

In this paper, a new target classification algorithm based on adaptive local aspect dictionary pair learning for synthetic aperture radar (SAR) images is developed. To that end, first, the aspect sector of one testing sample is determined adaptively by a regularized non-negative sparse learning method. Second, a synthesis dictionary and an analysis dictionary are jointly learned from the corresponding training subset located in the aspect sector. By doing so, the local aspect dictionary pair is obtained. Finally, the class label of the testing sample is inferred by a use of the minimum reconstruction residual under the representation with the local aspect dictionary pair. Using the local aspect sector training subset rather than the global aspect training set reduces the interference of a large amount of unrelated training samples, which leads to a more discriminative local aspect dictionary pair for target classification. The experiments are conducted with the Moving and Stationary Target Acquisition and Recognition (MSTAR) database, and the results demonstrate that the proposed approach is effective and superior to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Grass carp reovirus (GCRV) causes huge economic loss to the grass carp cultivation industry but the mechanism remains largely unknown. In this study, we investigated the global and complement gene-specific DNA methylation in grass carp after GCRV infection aimed to uncover the mechanism underlying GCRV infection. The global DNA methylation level was increased after GCRV infection. Expression levels of enzymes involved in DNA methylation including DNA methyltransferase (DNMT), ten-eleven translocation proteins (TETs), and glycine N-methyltransferase (GNMT) were significantly altered after GCRV infection. In order to investigate the relationship between the gene expression level and DNA methylation level, two representative complement genes, complement component 3 (C3) and kininogen-1 (KNG1), were selected for further analysis. mRNA expression levels of the two genes were significantly increased at 5 and 7 days after GCRV infection, whereas the DNA methylation level at the 5' flanking regions of the two genes were down-regulated at the same time-points. Moreover, a negative correlation was detected between gene expression levels and DNA methylation levels of the two genes. Therefore, the current data revealed a global and complement gene-specific DNA methylation profile after GCRV infection. Our study would provide new insights into understanding the mechanism underlying GCRV infection. [ABSTRACT FROM AUTHOR]

Near infrared (NIR) spectroscopy can effectively detect the changes in the burned tissue. However, due to the complex relationship between the spectral signals and the burn depth, simple methods of data analysis are difficult to solve this problem effectively. Therefore, in this paper, a machine learning method is introduced into the NIR spectral signal analysis, which is used to establish the relationship between NIR spectral signals and burn depth. First, based on the intensity of the spectral signal and the diffuse reflection theory, the optical properties that can reflect the change of burned tissue are extracted. And then the chained-agent genetic algorithm (CAGA) optimized support vector regression (SVR) is applied to establish a regression model between the optical property parameters and burn depth. Finally, the porcine model was used for verification. The experimental results demonstrate that the proposed CAGA-SVR integrated inversion model with optical properties can perform accurate inversion of burn depth and provide a reference for doctors. [ABSTRACT FROM AUTHOR]

In this paper, we propose a two-stage multi-task learning representation method for the classification of synthetic aperture radar (SAR) target images. The first stage of the proposed approach uses multi-features joint sparse representation learning, modeled as a l2,1-norm regularized multi-task sparse learning problem, to find an effective subset of training samples. Then, a new dictionary is constructed based on the training subset. The second stage of the method is to perform target images classification based on the new dictionary, utilizing multi-task collaborative representation. The proposed algorithm not only exploits the discrimination ability of multiple features but also greatly reduces the interference of atoms that are irrelevant to the test sample, thus effectively improving classification performance. Conducted with the Moving and Stationary Target Acquisition and Recognition (MSTAR) public SAR database, experimental results show that the proposed approach is effective and superior to many state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Background: Grass carp is an important farmed fish in China that is affected by serious disease, especially hemorrhagic disease caused by grass carp reovirus (GCRV). The mechanism underlying the hemorrhagic symptoms in infected fish remains to be elucidated. Although GCRV can be divided into three distinct subtypes, differences in the pathogenesis and host immune responses to the different subtypes are still unclear. The aim of this study was to provide a comprehensive insight into the grass carp response to different GCRV subtypes and to elucidate the mechanism underlying the hemorrhagic symptoms. Results: Following infection of grass carp, GCRV-I was associated with a long latent period and low mortality (42.5%), while GCRV-II was associated with a short latent period and high mortality (81.4%). The relative copy number of GCRV-I remained consistent or decreased slightly throughout the first 7 days post-infection, whereas a marked increase in GCRV-II high copy number was detected at 5 days post-infection. Transcriptome sequencing revealed 211 differentially expressed genes (DEGs) in Group I (66 up-regulated, 145 down-regulated) and 670 (386 up-regulated, 284 down-regulated) in Group II. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed significant enrichment in the terms or pathways involved in immune responses and correlating with blood or platelets. Most of the DEGs in Group I were also present in Group II, although the expression profiles differed, with most DEGs showing mild changes in Group I, while marked changes were observed in Group II, especially the interferon-related genes. Many of the genes involved in the complement pathway and coagulation cascades were significantly up-regulated at 7 days post-infection in Group II, suggesting activation of these pathways. Conclusion: GCRV-I is associated with low virulence and a long latent period prior to the induction of a mild host immune response, whereas GCRV-II is associated with high virulence, a short latent period and stimulates a strong and extensive host immune response. The complement and coagulation pathways are significantly activated at 7 days post-infection, leading to the endothelial cell and blood cell damage that result in hemorrhagic symptoms. [ABSTRACT FROM AUTHOR]

Background: The grass carp hemorrhagic disease caused by the grass carp reovirus (GCRV) is a major disease that hampers the development of grass carp aquaculture. The mechanism underlying GCRV pathogenesis and hemorrhagic symptoms is still unknown. MicroRNAs (miRNAs) are key regulators involved in various biological processes. The aim of this study was to identify conserved and novel miRNAs in grass carp in response to GCRV infection, as well as attempt to reveal the mechanism underlying GCRV pathogenesis and hemorrhagic symptoms. Results: Grass carp were infected with GCRV, and spleen samples were collected at 0 (control), 1, 3, 5, 7, and 9 days post-infection (dpi). These samples were used to construct and sequence small RNA libraries. A total of 1208 miRNAs were identified, of which 278 were known miRNAs and 930 were novel miRNAs. Thirty-six miRNAs were identified to exhibit differential expression when compared with the control, and 536 target genes were predicted for the 36 miRNAs. GO and KEGG enrichment analyses of these target genes showed that many of the significantly enriched terms were associated with immune response, blood coagulation, hemostasis, and complement and coagulation cascades, especially the GO term "blood coagulation" and pathway "complement and coagulation cascades." Ten representative target genes involved in "complement and coagulation cascades" were selected for qPCR analysis, and the results showed that the expression patterns of these target genes were significantly upregulated at 7 dpi, suggesting that the pathway "complement and coagulation cascades" was strongly activated. Conclusion: Conserved and novel miRNAs in response to GCRV infection were identified in grass carp, of which 278 were known miRNAs and 930 were novel miRNAs. Many of the target genes involved in immune response, blood coagulation, hemostasis, and complement and coagulation cascades. Strong activation of the pathway "complement and coagulation cascades" may have led to endothelial-cell and blood-cell damage and hemorrhagic symptoms. The present study provides a new insight into understanding the mechanism underlying GCRV pathogenesis and hemorrhagic symptoms. [ABSTRACT FROM AUTHOR]

Background: The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of classification in recent years. Thus, there has been an increased interest in speech pattern analysis methods applicable to Parkinsonism for building predictive tele-diagnosis and tele-monitoring models. One of the obstacles in optimizing classifications is to reduce noise within the collected speech samples, thus ensuring better classification accuracy and stability. While the currently used methods are effect, the ability to invoke instance selection has been seldomly examined. Methods: In this study, a PD classification algorithm was proposed and examined that combines a multi-edit-nearest-neighbor (MENN) algorithm and an ensemble learning algorithm. First, the MENN algorithm is applied for selecting optimal training speech samples iteratively, thereby obtaining samples with high separability. Next, an ensemble learning algorithm, random forest (RF) or decorrelated neural network ensembles (DNNE), is used to generate trained samples from the collected training samples. Lastly, the trained ensemble learning algorithms are applied to the test samples for PD classification. This proposed method was examined using a more recently deposited public datasets and compared against other currently used algorithms for validation. Results: Experimental results showed that the proposed algorithm obtained the highest degree of improved classification accuracy (29.44%) compared with the other algorithm that was examined. Furthermore, the MENN algorithm alone was found to improve classification accuracy by as much as 45.72%. Moreover, the proposed algorithm was found to exhibit a higher stability, particularly when combining the MENN and RF algorithms. Conclusions: This study showed that the proposed method could improve PD classification when using speech data and can be applied to future studies seeking to improve PD classification methods. [ABSTRACT FROM AUTHOR]

Background: Compensatory growth is accelerated compared with normal growth and occurs when growth-limiting conditions are overcome. Most animals, especially fish, are capable of compensatory growth, but the mechanisms remain unclear. Further investigation of the mechanism of compensatory growth in fish is needed to improve feeding efficiency, reduce cost, and explore growth-related genes. Results: In the study, grass carp, an important farmed fish in China, were subjected to a compensatory growth experiment followed by transcriptome analysis by RNA-sequencing. Samples of fish from starved and re-feeding conditions were compared with the control. Under starved conditions, 4061 and 1988 differentially expressed genes (DEGs) were detected in muscle and liver tissue when compared the experimental group with control group, respectively. After re-feeding, 349 and 247 DEGs were identified in muscle and liver when the two groups were compared. Moreover, when samples from experimental group in starved and re-feeding conditions were compared, 4903 and 2444 DEGs were found in muscle and liver. Most of these DEGs were involved in metabolic processes, or encoded enzymes or proteins with catalytic activity or binding functions, or involved in metabolic and biosynthetic pathways. A number of the more significant DEGs were subjected to further analysis. Under fasting conditions, many up-regulated genes were associated with protein ubiquitination or degradation, whereas many down-regulated genes were involved in the metabolism of glucose and fatty acids. Under re-feeding conditions, genes participating in muscle synthesis and fatty acid metabolism were up-regulated significantly, and genes related to protein ubiquitination or degradation were down-regulated. Moreover, Several DEGs were random selected for confirmation by real-time quantitative PCR. Conclusions: Global gene expression patterns of grass carp during compensatory growth were determined. To our knowledge, this is a first reported for a teleost fish. The results will enhance our understanding of the mechanism of compensatory growth in teleost fish. [ABSTRACT FROM AUTHOR]

Music is known to be capable of reducing perceived exertion during strenuous physical activity. The current interpretation of this modulating effect of music is that music may be perceived as a diversion from unpleasant proprioceptive sensations that go along with exhaustion. Here we investigated the effects of music on perceived exertion during a physically strenuous task, varying musical agency, a task that relies on the experience of body proprioception, rather than simply diverting from it. For this we measured psychologically indicated exertion during physical workout with and without musical agency while simultaneously acquiring metabolic values with spirometry. Results showed that musical agency significantly decreased perceived exertion during workout, indicating that musical agency may actually facilitate physically strenuous activities. This indicates that the positive effect of music on perceived exertion cannot always be explained by an effect of diversion from proprioceptive feedback. Furthermore, this finding suggests that the down-modulating effect of musical agency on perceived exertion may be a previously unacknowledged driving force for the development of music in humans: making music makes strenuous physical activities less exhausting. [ABSTRACT FROM AUTHOR]