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Domain shift problem is commonplace for ultrasound image analysis due to difference imaging setting and diverse medical centers, which lead to poor generalizability of deep learning-based methods. Multi-Source Domain Transformation (MSDT) provides a promising way to tackle the performance degeneration caused by the domain shift, which is more practical and challenging compared to conventional single-source transformation tasks. An effective unsupervised domain combination strategy is highly required to handle multiple domains without annotations. Fidelity and quality of generated images are also important to ensure the accuracy of computer-aided diagnosis. However, existing MSDT approaches underperform in above two areas. In this paper, an efficient domain transformation model named M2O-DiffGAN is introduced to achieve a unified mapping from multiple unlabeled source domains to the target domain. A cycle-consistent "many-to-one" adversarial learning architecture is introduced to model various unlabeled domains jointly. A condition adversarial diffusion process is employed to generate images with high-fidelity, combining an adversarial projector to capture reverse transition probabilities over large step sizes for accelerating sampling. Considering the limited perceptual information of ultrasound images, an ultrasound-specific content loss helps to capture more perceptual features for synthesizing high-quality ultrasound images. Massive comparisons on six clinical datasets covering thyroid, carotid and breast demonstrate the superiority of the M2O-DiffGAN in the performance of bridging the domain gaps and enlarging the generalization of downstream analysis methods compared to state-of-the-art algorithms. It improves the mean MI, Bhattacharyya Coefficient, dice and IoU assessments by 0.390, 0.120, 0.245 and 0.250, presenting promising clinical applications. • A multi-domain transformation model "M2O-DiffGAN" to standardize ultrasound images. • Bridging domain gaps to generalize downstream analysis methods to various source domains. • Many-to-one GANs scheme modeling multiple unlabeled ultrasound domains jointly. • Fast adversarial diffusive generation to produce high-fidelity images efficiently. [ABSTRACT FROM AUTHOR]

This paper discusses the periodicity and multi-periodicity in delayed Cohen–Grossberg-type neural networks (CGNNs) possessing impulsive effects, whose activation functions possess discontinuities and are allowed to be unbounded or nonmonotonic. Based on differential inclusion and cone expansion–compression fixed-point theory of set-valued mapping, several improved criteria are given to derive the positive solution with ω -periodicity and ω -multi-periodicity for delayed CGNNs under impulsive control. These ω -periodicity/ ω -multi-periodicity orbits are produced by impulses control. The analytical method and theoretical results presented in this paper are of certain significance to the design of neural network models or circuits possessing discontinuous neuron activation and impulsive effects in periodic environment. [ABSTRACT FROM AUTHOR]

• It is important to evaluate the early prognosis of patients with periodic discharges. • The prediction model based on the risk factors for death has high accuracy. • EEG feature classification is convenient for clinical application and verification. To investigate death-related factors in patients with electroencephalographic (EEG) periodic discharges (PDs) and to construct a model for death prediction. This case-control study enrolled a total of 80 severe neurological disease patients with EEG PDs within 72 h of admission to the neuroscience intensive care unit (NICU). According to modified Rankin scale (mRS) scores half a year after discharge, patients were divided into a survival group (<6 points) and a death group (6 points). Their relevant clinical and biochemical indicators as well as EEG characteristics were retrospectively analyzed. Logistic regression analysis was used to identify the risk factors associated with the death of patients with EEG PDs. A death risk prediction model and an individualized nomogram prediction model were constructed, and the prediction performance and concordance of the models were evaluated. Multivariate logistic regression analysis showed that the involvement of both gray and white matter in imaging, disappearance of EEG reactivity, occurrence of stimulus-induced rhythmic, periodic, or ictal discharges (SIRPIDs), and an interval time of 0.5–4 s were independent risk factors for death. A regression model was established according to the multivariate logistic regression analysis, and the area under the curve of this model was 0.9135. The accuracy of the model was 87.01%, the sensitivity was 87.17%, and the specificity was 89.17%. A nomogram model was constructed, and a concordance index of 0.914 was obtained after internal validation. The regression model based on risk factors has high accuracy in predicting the risk of death of patients with EEG PDs. This model can help clinicians in the early assessment of the prognosis of severe neurological disease patients with EEG PDs. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time synchronization of Memristor-based neural networks with time-delayed and coupled. In view of the retarded differential inclusions theory, drive–response concept, the authors give some sufficient conditions to ensure the fixed-time synchronization issue of Memristor-based neural networks. Two novel state-feedback controllers and adaptive controller are designed such that the system can realize fixed-time complete synchronization by means of inequality technique and non-smooth analysis theory. It is worth to point out that, without desiring values of the initial conditions or under the linear growth condition of the controller, the settling time of fixed-time synchronization is estimated. Finally, an example is given to further illustrate the benefits of the proposed switched control approach. [ABSTRACT FROM AUTHOR]

A novel biodegradable conducting polymer, PLA-b-AP-b-PLA (PAP) triblock copolymer of poly ( l -lactide) (PLA) and aniline pentamer (AP) with electroactivity and biodegradability, was synthesized and its potential application in cardiac tissue engineering was studied. The PAP copolymer presented better biocompatibility compared to PANi and PLA because of promoted cell adhesion and spreading of rat cardiac myoblasts (H9c2 cell line) on PAP/PLA thin film. After pulse electrical stimulation (5 V, 1 Hz, 500 ms) for 6 days, the proliferation ratio, and intracellular calcium concentration of H9c2 cells on PAP/PLA were improved significantly. Meanwhile, cell morphology changed by varying the pulse electrical signals. Especially, the oriented pseudopodia-like structure was observed from H9c2 cells on PAP/PLA after electrical stimulation. It is regarded that the novel conducting copolymer could enhance electronic signals transferring between cells because of its special electrochemical properties, which may result in the differentiation of cardiac myoblasts. [ABSTRACT FROM AUTHOR]

In this article, generalized pinning synchronization problem is investigated for a class of Cohen–Grossberg neural networks with discontinuous neuron activations and mixed delays. By designing generalized pinning state-feedback and adaptive controllers, several criteria for global exponential synchronization and global asymptotical synchronization of the drive–response based system are obtained in view of non-smooth analysis theory with generalized Lyapunov functional method, in which first pinning the neurons with very small self-inhibition and small amplification functions is pointed out. Some numerical examples are given to illustrate the feasibility of the obtained results. [ABSTRACT FROM AUTHOR]

In this paper, we study bifurcation of limit cycles from the equator of piecewise polynomial systems with no singular points at infinity. We develop a method for computing the Lyapunov constants at infinity of piecewise polynomial systems. In particular, we consider cubic piecewise polynomial systems and study limit cycle bifurcations in the neighborhood of the origin and infinity. Moreover, an example is presented to show 11 limit cycles bifurcating from infinity. [ABSTRACT FROM AUTHOR]

In this paper, we study a class of coupled time-delayed neural networks with discontinuous activations. Based on the new analysis techniques, framework of nonsmooth analysis, differential inclusion theory, both discontinuous controller and novel controller with continuous part are considered to realize the finite-time synchronization for discontinuous coupled neural networks. Some criteria are investigated in detail on constructing suitable Lyapunov functions cover 1-norm and quadratic-form, which were considered separately in the past. Finally, numerical examples are provided to show the correctness of our analysis. Our results are essentially new and they extend previously known researches. [ABSTRACT FROM AUTHOR]

This paper deals with the finite-time synchronization issue of time-varying delayed neural networks (DNNs) with discontinuous activations. Based on master-slave concept, several sufficient conditions are given to guarantee the finite-time synchronization of discontinuous DNNs. In order to control the synchronization error to converge zero in a finite time, we design three classes of novel switching state-feedback controllers which involve time-delays and discontinuous factors. The analysis in this paper employs the extended differential inclusion theory, the famous finite-time stability theorem, inequality techniques and generalized Lyapunov approach. Moreover, the upper bounds of the settling time of synchronization are estimated. Finally, the validity of proposed design method and theoretical results are illustrated by numerical examples. [ABSTRACT FROM AUTHOR]

High intracellular levels of reactive oxygen species (ROS) cause oxidative stress that results in numerous pathologies, including cell death. Transient potential receptor melastatin-2 (TRPM2), a Ca 2 + -permeable cation channel, is mainly activated by intracellular adenosine diphosphate ribose (ADPR) in response to oxidative stress. Here we studied the role and mechanisms of TRPM2-mediated Ca 2 + influx on oxidative stress-induced cell death in cancer cells. We found that oxidative stress activated the TRPM2-Ca 2 + -CaMKII cascade to inhibit early autophagy induction, which ultimately led to cell death in TRPM2 expressing cancer cells. On the other hand, TRPM2 knockdown switched cells from cell death to autophagy for survival in response to oxidative stress. Moreover, we found that oxidative stress activated the TRPM2-CaMKII cascade to further induce intracellular ROS production, which led to mitochondria fragmentation and loss of mitochondrial membrane potential. In summary, our data demonstrated that oxidative stress activates the TRPM2-Ca 2 + -CaMKII-ROS signal loop to inhibit autophagy and induce cell death. [ABSTRACT FROM AUTHOR]

This paper is concerned with a class of reaction–diffusion high-order Hopfield neural networks with time-varying delays subject to the Dirichlet boundary condition in a bounded domain. Easily verifiable delay-independent criteria are established to ensure the existence of periodic mild solutions, and the global exponential stability of the periodic mild solutions is also discussed by using the exponential dissipation property of semigroup of operators. The obtained results are easy to check and they effectually complement previously known results. A numerical example is given to show the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, a general framework named Filippov-framework and some new analytic techniques are presented for dealing with the exponential synchronization of memristor-based neural network system with time-varying delay. Several new sufficient conditions are established to guarantee two different types of exponential synchronization of the coupled networks based on master–slave (drive-response) concept and discontinuous state-feedback controller. In addition, we also provide an estimation of the exponential synchronization rate which depends on the time delay and system parameters. These conditions are good improvement and extension of the existing works on synchronization control of memristive or switching networks. Finally, the validity of our method and theoretical results is demonstrated by concrete examples with numerical simulations. [ABSTRACT FROM AUTHOR]

Half-Heusler (HH) thermoelectric (TE) materials have been attracting extensive research interest over the last two decades, owing to their thermal stability, mechanical strength, and moderate ZT . This material system are potential candidates for medium to high temperature applications, which is close to the temperature range of most industrial waste heat sources. In this mini-review article, we briefly summarize the recent progress and advances in HH thermoelectric materials. Some effectively available approaches, such as HH nanocomposites to reduce thermal conductivity, using larger atomic mass and size differences to enhance phonon scattering to further reduce the thermal conductivity, forming ternary systems following the cost effective approach. In addition, new thermoelectric HH members are also discussed in this article, which points out that many new HH compounds may be possible for TE applications. [ABSTRACT FROM AUTHOR]

This paper investigates the stability criteria for complex-valued bidirectional associative memory (BAM) with time delay. Firstly, based on the Lyapunov function method and mathematical analysis technique, sufficient conditions for the existence of unique equilibrium, and global asymptotic stability of the equilibrium are derived by separating complex-valued neural networks into real and imaginary parts. Secondly, we propose the delay-dependent stability criteria for the complex-valued BAM neural networks. Finally, numerical examples are given to show the effectiveness and merits of the present results. [ABSTRACT FROM AUTHOR]

In this study, without assuming the symmetry or irreducibility of the coupling configuration matrix, we investigate the synchronization of linearly coupled dynamical systems with discontinuous identical nodes and time delay. First, we design a feedback controller to realize the complete synchronization and exponential synchronization of discontinuous complex networks using a generalized Lyapunov approach. Second, we propose a set of adaptive controllers and adaptive laws to achieve complete synchronization. Third, we study the adaptive pinning synchronization of the discontinuous complex networks. The results of numerical simulations are presented to demonstrate the effectiveness of the controllers and the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

We surprisingly made a new n-type thermoelectric compound NbCoSb with half-Heusler (HH) structure having valence electron count of 19, different from the traditional 18, which opens up a new route to develop new half-Heusler thermoelectric materials not following the traditional valence electron count of 18. The samples are made by arc melting followed by ball milling and hot pressing. The effect of hot pressing temperature on the thermoelectric properties of NbCoSb samples has been studied. A maximum thermoelectric figure-of-merit ( ZT ) of ∼0.4 is achieved at 700 °C in NbCoSb sample that is hot pressed at 1000 °C. This work add a new member to HH compounds for thermoelectric applications, although the peak ZT of ∼0.4 is still lower than that of the traditional HHs. Moreover, it is very interesting to see that a traditionally thought of valence electron counts of 18 is not required. [ABSTRACT FROM AUTHOR]

This paper is concerned with the periodic synchronization problem for a general class of delayed neural networks (DNNs) with discontinuous neuron activation. One of the purposes is to analyze the problem of periodic orbits. To do so, we introduce new tools including inequality techniques and Kakutani’s fixed point theorem of set-valued maps to derive the existence of periodic solution. Another purpose is to design a switching state-feedback control for realizing global exponential synchronization of the drive–response network system with periodic coefficients. Unlike the previous works on periodic synchronization of neural network, both the neuron activations and controllers in this paper are allowed to be discontinuous. Moreover, owing to the occurrence of delays in neuron signal, the neural network model is described by the functional differential equation. So we introduce extended Filippov-framework to deal with the basic issues of solutions for discontinuous DNNs. Finally, two examples and simulation experiments are given to illustrate the proposed method and main results which have an important instructional significance in the design of periodic synchronized DNNs circuits involving discontinuous or switching factors. [ABSTRACT FROM AUTHOR]

In this work, we reported a simple synthesis of submicron α-Fe 2 O 3 with rod-like structure. When it evaluated as electrode material for lithium ion battery, comparing with Cu foil and Ni foam, the as-prepared α-Fe 2 O 3 electrodes with Cu foam current collector exhibited higher reversible capacity of 415 mAh g −1 and more stable cycle performance after 30 cycles. Comparative researches on electrochemical performances of the α-Fe 2 O 3 employing different current collectors (Cu foil, Cu foam and Ni foam) were discussed here in detail. According to our results, the improved electrochemical behaviors of α-Fe 2 O 3 electrode with Cu foam current collector could be attributed to its particular electrode structure, i.e., porous, good electric conductivity, closed adhere to the electrode materials. Just because of that, it may make sure an easy accessibility of electrolytes and fast transportation of lithium ions, importantly, it could avoid the active materials falling off from the current collector on account of volume expansion. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of exponential synchronization of time-varying delayed neural networks with discontinuous neuron activations. Under the extended Filippov differential inclusion framework, by designing discontinuous state-feedback controller and using some analytic techniques, new testable algebraic criteria are obtained to realize two different kinds of global exponential synchronization of the drive–response system. Moreover, we give the estimated rate of exponential synchronization which depends on the delays and system parameters. The obtained results extend some previous works on synchronization of delayed neural networks not only with continuous activations but also with discontinuous activations. Finally, numerical examples are provided to show the correctness of our analysis via computer simulations. Our method and theoretical results have a leading significance in the design of synchronized neural network circuits involving discontinuous factors and time-varying delays. [ABSTRACT FROM AUTHOR]

Summary Objectives This investigation was a response to an outbreak of hepatitis A in rural China in 2013. The objectives were to identify the pattern of transmission and the risk factors. Methods A probable case was defined as an individual in/nearby the village of the outbreak with jaundice and/or an elevation of serum alanine aminotransferase (at or above 80 IU/l) plus at least three of the following symptoms: fever (axillary temperature ≥37 °C), headache, nausea, vomiting, anorexia, or abdominal pain in the upper right quadrant, during the outbreak period (from June 1 to August 11, 2013). Using a case–control study design, we compared exposures to suspected food items, water, and close contact with a patient or case with asymptomatic infection between 22 cases and 32 controls. Results We identified 22 cases, including 15 symptomatic cases and seven with asymptomatic infections. All cases were aged <15 years. Household clustering was apparent (Chi-square = 4.69, p < 0.05). Contact with symptomatic cases or cases with an asymptomatic infection was a major risk factor (59.09% in cases and 25.00% in the controls: odds ratio (OR) 4.33, 95% confidence interval (CI) 1.17–16.68). A good hand-washing habit (at least once per day) was found in 45.45% of cases vs. 78.13% of controls (OR 0.23, 95% CI 0.06–0.88). The dose–response analysis showed that the daily frequency of hand-washing was inversely associated with infection (trend Chi-square = 5.35, p = 0.021). Person-to-person transmission was deduced from the epidemic curves and the transmission chain of symptomatic cases. Conclusion The pattern of transmission in this outbreak was person-to-person, and the transmission route was indicated to be fecal–oral. In addition to close contact, insufficient hand-washing was a risk factor. Strengthening the management of the rural environmental sanitation services and enhancing awareness in the household are key to preventing outbreaks of hepatitis A in the future. [ABSTRACT FROM AUTHOR]

In this paper, the global stability has been investigated for a novel class of competitive neural networks with mixed time delays and discontinuous activations. Without presuming the boundedness of activation functions, we draw two set of sufficient conditions ensuring the existence, uniqueness of the equilibrium, global exponential asymptotic stability of the solution and the associated output of the solution converging to the output equilibrium point in measure, by linear matrix inequality, M -matrix, Leray–Schauder alternative theorem in multivalued analysis, general Lyapunov method, topological degree theory of set-valued map. Meanwhile, we present a result on the global convergence in finite time of given neural networks. The results in the literature are generalized and significantly improved. Finally, one example and simulations are presented to demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a novel and effective approach for establishing a quantified output sensitivity of Binary Feedforward Neural Networks to weight and input perturbations. Firstly, analytical formulae are derived for computing a neuron׳s sensitivity by means of matrix and probability theories. Then, based on the neuron׳s sensitivity and the network׳s architecture feature, a bottom-up strategy is followed to compute the entire network׳s sensitivity. The proposed approach has the obvious advantages of higher generality, lower computational complexity, and yet much higher accuracy. Experimental results verify the correctness and effectiveness of the approach. [Copyright &y& Elsevier]

Abstract: In this paper, under the assumption that the activation functions only satisfy global Lipschitz conditions, a novel LMI-based sufficient condition for global asymptotic stability of equilibrium point of a class of BAM neural networks with reaction–diffusion terms and distributed delays is obtained by using degree theory, LMI method, inequalities technique and constructing Lyapunov functionals. In our results, the assumptions for boundedness and monotonicity in existing papers on the activation functions are removed. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the following Kirchhoff-type variational inclusion system with , where and is a locally Lipschitz function and are the partial generalized gradients in the sense of Clarke. Under proper growth conditions on the nonlinearity F, the existence of nontrivial solutions for the above system is established. Our approach is variational based on the theories of nonsmooth analysis. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen–Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and the fixed point theorem of multi-valued maps, the existence of periodic solutions for the neural networks is obtained. After that, we derive some sufficient conditions for the global exponential stability and convergence of the neural networks, in terms of nonsmooth analysis theory with generalized Lyapunov approach. Without assuming the boundedness (or the growth condition) and monotonicity of the discontinuous neuron activation functions, our results will also be valid. Moreover, our results extend previous works not only on discrete time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete time-varying and distributed delayed neural networks with discontinuous activations. We give some numerical examples to show the applicability and effectiveness of our main results. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate the global dynamics of equilibrium point for delayed competitive neural networks with different time scales and discontinuous activations. Employing the Leray–Schauder alternative theorem in multivalued analysis, linear matrix inequality technique and generalized Lyapunov-like method, we obtain some new sufficient conditions ensuring the existence, uniqueness and global stability and the global convergence in finite time of the equilibrium point, the results of this paper improve and extend previously known results. Finally, two examples and numerical simulations are conducted to validate the theoretical results. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate a class of neural networks with mixed time-varying delays and discontinuous activations, new criteria for the existence and exponential stability of the periodic solution are established by using the Mawhin-like coincidence theorem, M-matrix theory, differential inequality techniques and Lyapunov functional. The obtained results are new and complement previously known results. Finally, we present a numerical example with simulations to demonstrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate the dynamical behaviors of a novel class of Cohen–Grossberg neural networks with not only mixed time delays, i.e., time varying delays and distributed delays, but also discontinuous activations, which may be unbounded or nonmonotonic. Some sufficient conditions are derived to ensure the existence, uniqueness of the equilibrium, global exponential asymptotic stability of the solution and the associated output of the solution converging to the output equilibrium point in measure by using the Leray–Schauder alternative theorem in multivalued analysis, matrix theory and generalized Lyapunov-like approach. Some recent results in the literature are generalized and significantly improved. One example is provided to demonstrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

Abstract: This paper is concerned with the periodic dynamics of a class of delayed neural networks with discontinuous neural activation functions. Under the Filippov framework, the cone expansion and compression fixed point theorems of set-valued maps are successfully employed to derive the existence of the -periodic positive solution. However, before the discussion of the periodicity, there still remains a fundamental issue about viability to be solved due to the presence of general mixed time-delays involving both time-varying delays and distributed delays. This difficulty can be overcome by a transformation and the continuation theorem. Then, for the discontinuous and delayed neural network system with time-periodic coefficients, the uniqueness and global exponential stability of the periodic state solution are proved by using non-smooth analysis theory with generalized Lyapunov approach. Furthermore, the global convergence in measure of the periodic output is also investigated. The obtained results are a very good extension and improvement of previous works on discontinuous dynamical neuron systems with a broad range of neuron activations dropping the assumption of boundedness or monotonicity. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

Catalytic partial oxidation (CPOX) of n-butanol is an alternative route for hydrogen production from bio-mass. An analysis on the thermodynamics using Gibbs free energy minimization method was carried out, and the results indicated that a higher H2 yield can be obtained near 700 °C or above with O2/butanol = 1.5–2.0. Layered double hydroxide (LDH) derived catalysts were proved effective in CPOX, and the Ni0.35Mg2.65Al0.5Fe0.5O4.5±δ catalyst produced about 4.03 mol-H2/mol-butanol at 700 °C with a feed of O2/butanol = 2.0. This higher activity can be attributed to the structural and electronic properties: there is a higher surface area of 178.2 m2/g, and more Ni0 atoms were obtained and remained stable in the 31-h CPOX test. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen–Grossberg BAM neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of differential inclusions theory and the topological degree theory in set-valued analysis, the existence of periodic solution for the neural networks is obtained. Moreover, our results extend previous works not only on time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on time-varying and distributed delayed neural networks with discontinuous activations. Finally, we give some numerical examples to show the applicability and effectiveness of our main results. [Copyright &y& Elsevier]

Abstract: Based on the tangency or non-tangency of the periodic solution to certain surface, this paper gives a set of conditions ensuring global convergence in finite time toward a unique periodic solution for Hopfield neural networks with discontinuous activations. Moreover, two numerical examples are provided to illustrate the theoretical results. [Copyright &y& Elsevier]

Abstract: The manganese-promoted nickel-based catalysts were prepared via wet-incipient impregnation, and tested in auto-thermal reforming (ATR) of ethanol for hydrogen production. The Ni/Al2O3 catalyst, in which Ni existed as NiAl2O4, produced a low H2 yield near 1.85 mol H2/mol ethanol. The Ni–Mn/Al2O3 catalyst showed a better performance in a 30-h test: the conversion of ethanol reached 100%, and a higher H2 yield remained stable near 3.1–3.2 mol H2/mol ethanol. This improvement can be attributed to the promotion of Mn: With Mn, the ilmenite-type NiMnO3 was formed, the reducibility of Ni–Mn/Al2O3 was thus improved, and there were more Ni0 over the surface of catalysts. Moreover, these Ni0 species were stable in the ATR test, as indicated by XRD and XPS. [Copyright &y& Elsevier]

Abstract: This paper investigates the periodic dynamics of a general class of time-varying delayed neural networks with discontinuous right-hand sides. By employing the topological degree theory in set-valued analysis, differential inclusions theory and Lyapunov-like approach, we perform a thorough analysis of the existence, uniqueness and global exponential stability of the periodic solution for the neural networks. Especially, some sufficient conditions are derived to guarantee the existence, uniqueness and global exponential stability of the equilibrium point for the autonomous systems corresponding to the non-autonomous neural networks. Furthermore, the global convergence of the output and the convergence in finite time of the state are also discussed. Without assuming the boundedness or monotonicity of the discontinuous neuron activation functions, the obtained results improve and extend previous works on discontinuous or continuous neural network dynamical systems. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results. [Copyright &y& Elsevier]

Abstract: Iron-doped LaNiO3 catalysts with a perovskite structure were prepared via self-combustion and tested in auto-thermal reforming (ATR) of ethanol. Characterizations of temperature-programmed surface reaction (TPSR), X-ray diffraction (XRD), physical N2 adsorption, and temperature-programmed reduction (TPR) were carried out. The results indicate that LaNiO3 perovskite structure was successfully formed via self-combustion. With iron-doping in LaNiO3, the perovskite structure still remains, in the form of solid solution La(Ni, Fe)O3, where iron is reducible and the nickel-iron alloy forms after the reduction. In addition, the surface area of the iron-doped samples increased. The TPSR results indicate that with iron-doping, the activity for adsorbed ethanol species is modified and a higher activity for methane transformation is achieved. As a result, an LNF10 sample (LaNi0.90Fe0.10O3) with both nickel and nickel-iron alloy shows better performance in ATR: the ethanol conversion is near 100%, while the selectivity to by-products, such as ethylene, ethane, acetaldehyde and methane, is decreased, and CO2 is the main carbon-containing product; consequently, a hydrogen yield near 3.0 mol H2/mol EtOH is obtained and remains stable in the 30-h test of ATR. [Copyright &y& Elsevier]

Abstract: This paper deals with the robust control problem for stochastic Hopfield neural networks subject to uncertainties and time-varying delays. A robust decentralized adaptive sliding mode controller is designed to guarantee the uncertain stochastic delayed Hopfield neural networks is globally asymptotically stable in probability. A numerical example is given to show the effectiveness of the proposed controller. [Copyright &y& Elsevier]

Abstract: In this paper, we study a general class of neural networks with discrete and distributed time-varying delays, whose neuron activations are discontinuous and may be unbounded or nonmonotonic. By using the Leray–Schauder alternative theorem in multivalued analysis, matrix theory and generalized Lyapunov-like approach, we obtain some sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the periodic solution. Moreover, when all the variable coefficients and time delays are real constants, we discuss the global convergence in finite time of the neural network dynamical system. Our results extend previous works not only on discrete and distributed time-varying delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete and distributed time-varying delayed neural networks with discontinuous activations. Two numerical examples are given to illustrate the effectiveness of our main results. [Copyright &y& Elsevier]

Abstract: To overcome the staircasing effects and simultaneously avoid edge blurring, this paper describes a fourth-order partial differential equation based edge-preserving regularization filter for noise removal. This technique is closely related to the nonlinear anisotropic diffusion. Compared results distinctly demonstrate the superiority of our proposed scheme over the LLT model, in terms of removing noise while sharply maintaining the edge features. [Copyright &y& Elsevier]

Abstract: This paper studies the H ∞ performance for the uncertain recurrent neural networks with both nonlinear external disturbance and Markovian jump parameters, in which the time delay is varying. Our objective is to design robust controllers, that are independent of the time delay, such that the uncertain system is stochastic stable with a generalized H ∞ disturbance attenuation level γ. For the given uncertain stochastic system, new controllers which are composed of a linear controller and an adaptive controller are proposed to realize H ∞ control by introducing a switching function and using the idea of completing square. Based on It’s differential formula and Lyapunov stability theory, new sufficient conditions are obtained in terms of linear matrices inequalities. A numerical example is constructed to show effectiveness of the designed controller in this paper. [Copyright &y& Elsevier]

Abstract: Ni-based layered double hydroxide (LDH)-derived catalysts with Ni–Mg–Al–Fe–O were prepared via co-precipitation, and were tested in auto-thermal reforming (ATR) of ethanol for hydrogen production. The Ni0.35Mg2.65AlO4.5±δ catalyst showed poor stability and a low H2 yield, near 2.51mol H2/mol EtOH. The tetra-component catalyst of Ni0.35Mg2.65Al0.50Fe0.50O4.5±δ, in which the trivalent component consists of both aluminum and iron, showed a promising performance in ATR of ethanol: not only did the H2 yield remain stable near 3.7mol H2/mol EtOH during the 30-h test, but the CH4 reforming activity also improved and C2H4 disappeared in product gases. These improvements can be attributed to the synergic effect by both iron and nickel on the structural and electronic properties: the BET surface area was increased, the reducibility of the Ni metal and its resistance to oxidation in ATR were improved, and the acidity was constrained as well. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a delayed multispecies ecological competition-predator system with Holling-III functional response is studied. By using the continuation theorem of coincidence degree theory and constructing suitable Lyapunov functionals, some sufficient conditions are derived for the existence, uniqueness and global asymptotic stability of positive periodic solutions to the system. [ABSTRACT FROM AUTHOR]

Abstract: Layered double hydroxide-derived Co0.3 Mg2.7Al1-xFexO4.5±δ catalysts were prepared via co-precipitation and tested in auto-thermal reforming of ethanol for hydrogen production. The layered double hydroxide precursors show typical hydrotalcite-like structures and form a similar MgO cubic structure after calcination. Compared with iron-free catalyst, the Co0.3 Mg2.7Al0.9Fe0.1O4.5±δ performs better in auto-thermal reforming of ethanol: the conversion of ethanol remains near 100%, and the H2 yield stays above 3.2mol H2/mol EtOH throughout the 30-h test. The improved performance can be attributed to the stable Cobalt species within Mg(Al)O matrix, the higher surface area, and the synergic effects of Co and Fe. [ABSTRACT FROM AUTHOR]

Abstract: Considered is a system of delay differential equations modeling a time-delayed connecting network of three neurons without self-feedback. Discussing the change of the number of eigenvalues with zero real part, we locate the boundary of the stability region and finally determine the largest stability region of trivial solution. We investigate the existence of bifurcation phenomena of codimension one/two of the trivial equilibrium by considering the intersections of some parameter curves, which, in the aτ-half parameter plane, correspond to zero root or pure imaginary roots. In particular, the equivariant bifurcation is studied because of the equivariance of the system. We also present numerical simulations to demonstrate the rich dynamical behavior near the equivariant Pitchfork–Hopf bifurcation points, Hopf–Hopf bifurcation points, and some higher codimension bifurcation points. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the local dynamics around the trivial solution of suspension system of maglev train with time-delayed feedback signals. With characteristic root method, the linear stability analysis of the maglev system is obtained, which implies that a Hopf bifurcation may occur when time delay exceeds a critical value. To gain insight into the periodic motion, the pseudo-oscillator analysis is used to calculate the bifurcated periodic solution, and to determine the direction of the bifurcation. Unlike the widely used methods such as manifold reduction, the pseudo-oscillator analysis involves simple computation and gives prediction of the local dynamics with high accuracy. Numerical simulation results show that the existence of the Hopf bifurcation and the amplitude of the periodic solution can be determined by time delay and control parameters. So appropriately selecting them can restrain vibration between vehicle and guideway of the system effectively. [Copyright &y& Elsevier]

Abstract: We consider a predator–prey system of Lotka–Volterra type with time delays and stage structure for prey. By analyzing the corresponding characteristic equations, the local stability of the equilibria is investigated and Hopf bifurcations occurring at the positive equilibrium under some conditions are demonstrated. The mathematical tools which enable us to obtain the sufficient conditions, guaranteeing the global asymptotical stability of the equilibria, are the well-known Kamke comparison theorem and an iteration technique. Numerical simulations are carried out to illustrate our theoretical results. [Copyright &y& Elsevier]

Abstract: This paper considers the robust control problem for a class of uncertain time-varying delayed neural networks, in which the activation function may be a discontinuous function. A robust decentralized adaptive sliding mode controller is proposed to guarantee the asymptotically stability of the system. The proposed controller, which does not dependent on the time delay, ensures the occurrence of the sliding manifold even when the system is undergoing parameter uncertainties and nonlinear input. Two numerical examples are given to show the effectiveness of the proposed controller. [Copyright &y& Elsevier]

Abstract: Auto-thermal reforming (ATR) of bio-ethanol is a promising process for hydrogen production, which can lead to the possibility of directly using low concentration ethanol from fermentation plants without going through the energy-consuming distillation and dehydration processes, saving both energy and cost. Co-based catalysts are active for hydrogen production in ATR, where the hydrogen yield and stability are important factors to be considered. To address the concerns of selectivity and deactivation, iron was introduced into Co-based catalysts via wet-impregnation. The catalysts were characterized with TPR, XRD, XPS, and Raman spectra, and tested in ATR of ethanol. The XPS, XRD, and TPR results show that with iron-promotion, more Co metal is obtained over the catalyst surface, which remains stable during the oxidative atmosphere of ATR. Meanwhile, iron promotes the ethanol dehydrogenation pathway in ATR reactions. This synergic effect contributes to the higher activity and stability of Co-based catalysts in the ATR process: A higher hydrogen yield remains around 3.13mol H2/mol EtOH at 600°C and stays stable in a 30-h test. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the dynamical behavior of delayed Cohen–Grossberg neural networks with discontinuous activation functions. Some sufficient conditions are derived to guarantee the existence, uniqueness and global stability of the equilibrium point of the neural network. Convergence behavior for both state and output is discussed. The constraints imposed on the interconnection matrices, which concern the theory of M-matrices, are easily verifiable and independent of the delay parameter. The obtained results improve and extend the previous results. Finally, we give an numerical example to illustrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

Abstract: Nanorod alumina-supported Ni–Zr–Fe/Al2O3 catalysts were prepared by co-impregnation, characterized by TEM, TPR, XRD, XPS, and TPD-pyridine, and tested in auto-thermal reforming of ethanol. The characterization results indicate that, with iron and zirconia promotion, the Ni x Fe1−x Al2O4 mixture spinel forms, the valence of the surface Ni species is modified, and the acidity decreases. As a result, during a 30-h test over the Ni–Zr–Fe/Al2O3 catalyst, sintering is restrained, and the selectivity to hydrogen remains around 85.79% without obvious loss, while the un-promoted Ni/Al2O3 shows poor stability and selectivity. [Copyright &y& Elsevier]

Abstract: This paper investigates the dynamics of a class of recurrent neural networks where the neural activations are modeled by discontinuous functions. Without presuming the boundedness of activation functions, the sufficient conditions to ensure the existence, uniqueness, global exponential stability and global convergence of state equilibrium point and output equilibrium point are derived, respectively. Furthermore, under certain conditions we prove that the system is convergent globally in finite time. The analysis in the paper is based on the properties of -matrix, Lyapunov-like approach, and the theories of differential equations with discontinuous right-hand side as introduced by Filippov. The obtained results extend previous works on global stability of recurrent neural networks with not only Lipschitz continuous but also discontinuous neural activation functions. [Copyright &y& Elsevier]