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The synthesis of N-heterocycles of quinoxalines has been developed by an efficient protocol of one-pot annulation of alkynes with o-phenylenediamines. A variety of quinoxalines were prepared in good to high yields in the presence of catalytic amount of iodine as a catalyst. [ABSTRACT FROM AUTHOR]

A novel protocol for the transamidation of DMF and derivatives with weakly nucleophilic anilines has been developed, utilizing a catalytic amount of Pd(OAc) 2 and 2,2′-bipyridine, and with PivOH and BF 3 ·Et 2 O as additives. This methodology has a broad substrate scope, and various corresponding transamidation products were prepared in good to excellent yields from commercially available DMF derivatives and anilines. The synthetic utility of the reported protocol was further demonstrated with a gram-scale experiment. Control experiments suggested the efficient transformation of DMF and derivatives with anilines might owe to the synergistic effect of palladium complex, PivOH, and BF 3 ·Et 2 O. [ABSTRACT FROM AUTHOR]

In this paper, we present a nonlinear state estimation algorithm based on the fusion of an extendedH∞(EH∞F) and a cubature Kalman filter (CKF); the resulting estimator is called a cubatureH∞filter. The recently developed CKF is a Gaussian approximation of a Bayesian filter and its performance over non-Gaussian noises may degrade. In contrast, theH∞filter is capable of estimating the states of linear systems with non-Gaussian noises and the extendedH∞filter (EH∞F) can estimate the states of non-linear and non-Gaussian systems. Similar to theH∞filter, an EH∞F also does not make any assumptions about the statistics of the process or measurement noise, but it does require Jacobians during the state estimation of nonlinear systems, which degrade the overall performance when the nonlinearities are severe. The cubatureH∞filter is developed to have the desirable features of both CKF and EH∞F. For numerical accuracy, a square-root version of the cubatureH∞filter is developed usingJ-unitary transformation. The efficacy of the square-root cubatureH∞filter is verified on continuous stirred tank reactor and permanent magnet synchronous motor examples. [ABSTRACT FROM PUBLISHER]

In this study, a novel theoretical approach based on high-order shear deformation theory is proposed to investigate the damping properties of honeycomb panels partially filled with foam. The assessment of damping properties in composite materials is accomplished through finite element theory, which elucidates the theoretical underpinnings for determining damping parameters specific to these materials. Subsequently, the damping parameters of the partially foam-filled honeycomb panel are determined based on the ratio of dissipated energy to strain energy. Ultimately, a comprehensive theoretical testing methodology is established, with tests conducted concurrently on composite materials to benchmark against data obtained via theoretical approaches. The findings underscore the capability of the proposed approach to assess the damping characteristics of diverse materials and extract their corresponding damping parameters. This method provides an effective theoretical model for investigating the damping characteristics in partially foam-filled fully composite honeycomb core sandwich structures. The model can also be applied to assess the damping properties of similar structures, offering practical guidance. [ABSTRACT FROM AUTHOR]

Polypyrrole (PPy) nanoparticles formed by chemical in situ polymerization were deposited on the hydrophilic/hydrophobic surface of SiO2 substrates to give the diversely morphology, respectively. The morphologies of PPy nanoparticles deposit were investigated using optical microscope, scanning electron microscope (SEM), and atomic force microscope (AFM) imaging techniques. The morphology of Y- and T-shape wrinkles was observed on the hydrophilic surface of SiO2 substrate, while the morphology of polygon-shape wrinkles on the hydrophobic surface of SiO2 substrate, and this distinction is due to the difference of the surface energy between the hydrophilic and hydrophobic surface of SiO2 substrate and so-called “memory effect.” [ABSTRACT FROM PUBLISHER]

Abstract: In this paper, we consider two problems which can be posed as spectral radius minimization problems. Firstly, we consider the fastest average agreement problem on multi-agent networks adopting a linear information exchange protocol. Mathematically, this problem can be cast as finding an optimal such that , , and . Here, is the value possessed by the agents at the th time step, is an all-one vector and is the set of real matrices in with zeros at the same positions specified by a network graph , where is the set of agents and is the set of communication links between agents. The optimal is such that the spectral radius is minimized. To this end, we consider two numerical solution schemes: one using the th-order spectral norm (2-norm) minimization (-SNM) and the other gradient sampling (GS), inspired by the methods proposed in [Burke, J., Lewis, A., & Overton, M. (2002). Two numerical methods for optimizing matrix stability. Linear Algebra and its Applications, 351–352, 117–145; Xiao, L., & Boyd, S. (2004). Fast linear iterations for distributed averaging. Systems & Control Letters, 53(1), 65–78]. In this context, we theoretically show that when is symmetric, i.e. no information flow from the th to the th agent implies no information flow from the th to the th agent, the solution from the 1-SNM method can be chosen to be symmetric and is a local minimum of the function . Numerically, we show that the -SNM method performs much better than the GS method when is not symmetric. Secondly, we consider the famous static output feedback stabilization problem, which is considered to be a hard problem (some think NP-hard): for a given linear system , find a stabilizing control gain such that all the real parts of the eigenvalues of are strictly negative. In spite of its computational complexity, we show numerically that -SNM successfully yields stabilizing controllers for several benchmark problems with little effort. [Copyright &y& Elsevier]

Abstract: We propose real-time path planning schemes employing limited information for fully autonomous unmanned air vehicles (UAVs) in a hostile environment. Two main algorithms are proposed under different assumptions on the information used and the threats involved. They consist of several simple (computationally tractable) deterministic rules for real-time applications. The first algorithm uses extremely limited information (only the probabilistic risk in the surrounding area with respect to the UAV''s current position) and memory, and the second utilizes more knowledge (the location and strength of threats within the UAV''s sensory range) and memory. Both algorithms provably converge to a given target point and produce a series of safe waypoints whose risk is almost less than a given threshold value. In particular, we characterize a class of dynamic threats (so-called, static-dependent threats) so that the second algorithm can efficiently handle such dynamic threats while guaranteeing its convergence to a given target. Challenging scenarios are used to test the proposed algorithms. [Copyright &y& Elsevier]

Abstract: This paper first presents an equivalent circuit model of a new disc-type ultrasonic motor and discusses its applications in evaluation of the stator’s frequency characteristics. The equivalent circuit analysis is based on the principle of ultrasonic motor operations and is conducted from the viewpoint of the mechanic vibration of the piezoelectric ceramic disk. Furthermore, because drift of the piezostator characteristics will cause variation of the motor speed, a controller is thus necessary in order to produce a constant output speed. In this research, the speed control scheme is implemented by using current modulation, so the revolutional speed will be kept constant. Meanwhile, the frequency behaviour of the proposed motor and its consequences on speed control scheme are discussed. Finally, a 3-D mechanical element with an extra electrical degree of freedom is employed to simulate the dynamic vibration modes of the linear piezoelectric, mechanical and piezoelectro-mechanic behaviours of a metal disc structure embedded with a piezoelectric actuator. In piezoelectric finite element formulation, a discretized equation of motion is developed and solved by using the integration scheme to explain why an adaptive boundary condition, a simple support condition with three non-equal-triangular (120°–90°–150°) fixed points near the edge for the mechanical design of a new disc-type piezoelectric ultrasonic stator, is defined so that a lateral elliptical motion of the contact point between stator and rotor can be realized for driving the rotor. [Copyright &y& Elsevier]

The direct oxidation of internal alkynes proceeds efficiently in the presence of CuI as a catalyst to afford the corresponding 1,2-diketones in good yields. This strategy offers a simple and efficient route for the synthesis of 1,2-diketones from an inexpensive copper catalyst and easily available internal alkynes. The advantage of present protocol is further demonstrated by the synthesis of quinoxaline derivatives from alkynes and 1,2-diaminobenzene via one-pot procedure. [ABSTRACT FROM AUTHOR]

An abstract of the article "Enantioselective Synthesis of 3-Alkynyl-3-hydroxyindolin-2-ones by Copper-Catalyzed Asymmetric Addition of Terminal Alkynes to Isatins" by Ning Xu and colleagues is presented.

The scalable reaction tolerates a broad range of functional groups. [ABSTRACT FROM AUTHOR]

The efficient title reaction uses catalytic amounts of an inexpensive copper catalyst and shows a good functional group tolerance of aryl alkynes. [ABSTRACT FROM AUTHOR]

Review: 178 refs. [ABSTRACT FROM AUTHOR]

In this paper, a model for truncated conical shells made of fiber-reinforced composite materials (FRCTWTCS) is advanced considering the material nonlinearity and strain dependency. This model is capable of predicting the natural frequencies, vibration responses, and damping ratios under different excitation amplitudes. Firstly, based on the Jones-Nelson nonlinear material theory and complex modulus method, the nonlinear elastic modulus, and shear modulus are characterized. Subsequently, considering the influence of semi-cone angle and excitation direction deflection angle, a comprehensive set of dynamic control equations is established using the Ritz method. Furthermore, to illustrate the effectiveness of the advanced modeling approach, a series of experiments are conducted using TC300/epoxy resin truncated conical shells as an example. The experimental results validate the effectiveness of the advanced modeling method. The comparative results indicate that the advanced nonlinear model outperforms the model that neglects strain dependency in terms of accuracy. The maximum errors between the predicted and measured values for the natural frequencies, vibration responses, and damping ratios are 1.7%, 3.4%, and 8.5%, respectively. Finally, the impact of various constrained boundary lengths, semi-cone angles, and fiber layup angles on the nonlinear vibration characteristics of the model is discussed. • A nonlinear vibration model for truncated conical shells made of fiber-reinforced composite materials (FRCTWTCS) is advanced considering the material nonlinearity and strain dependency. • The accuracy of the proposed model is validated by establishing a test bed to investigate the nonlinear vibration characteristics of the FRCTWTCS. • The impact of various constrained boundary lengths, semi-cone angles and fiber layup angles on the nonlinear vibration characteristics of the model is discussed. [ABSTRACT FROM AUTHOR]

In this study, two novel vanadate with different dimensions were prepared by hydrothermal synthesis using 3-quinuclidinol as the structural templating agent, namely, zero-dimensional decavanadate [(C 7 H 14 NO) 6 (V 10 O 28)]·2H 2 O (1) and two-dimensional vanadate [C 7 H 14 NO][V 3 O 7 ]·H 2 O (2). At a low reaction temperature of 373 K, only crystal 1 is produced. As the reaction temperature is increased in the range of 393–473 K, {V 10 O 28 }6- clusters can transform into {V 3 O 7 }- layers and the ratio of the transformation gradually increases, resulting in the formation of crystal 2. To our knowledge, this is the first study to achieve a controllable transformation of the vanadium-oxygen anion structure with different dimensions solely through adjusting the reaction temperature, without changing the reactant type and feed ratio. The transformation mechanism also was investigated. The results show that the transformation is caused by the redox reaction between 3-quinuclidinol with {V 10 O 28 }6- polyoxoanion. Moreover, 2 possesses a large layer spacing due to the large 3-quinuclidinol cations acting as the "pillar", resulting in exhibiting good capacity performance (262.4 mAh g−1 at 0.1 A g−1) as the cathode material for aqueous zinc ion batteries. This study not only provides a viable approach for the temperature-tuned transformation of different dimensional vanadium-oxygen anion structures, but also proves that layered vanadate containing large cations are potential high-capacity cathode materials for AZIBs. Temperature-dependent transformation of {V 10 O 28 }6- clusters into {V 3 O 7 }- layers mediated by 3-quinuclidinol as a structural templating agent. The 2D vanadate, formed by {V 3 O 7 }- layers and 3-quinuclidinol cations, shows a high capacity performance as the cathode material for aqueous zinc ion batteries. [Display omitted] • Two novel vanadate with different dimensions were prepared by 3-quinuclidinol as a structural templating agent. • This study achieves a controllable transformation of vanadium-oxygen anion structure in different dimensions solely by adjusting the reaction temperature. • Due to the large interlayer spacing, compound 2 exhibits high-capacity performance as the cathode material for aqueous zinc ion batteries. [ABSTRACT FROM AUTHOR]

Abstract: Model-based sensor fault detection, isolation and accommodation (SFDIA) is a direction of development in particular with UAVs where sensor redundancy may not be an option due to weight, cost and space implications. SFDIA via neural networks (NNs) have been proposed over the years due to their nonlinear structures and online learning capabilities. The majority of papers tend to consider single sensor faults. While useful, this assumption can limit application to real systems where sensor faults can occur simultaneously or consecutively. In this paper we consider the latter scenario, where it is assumed that a 1s time gap is present between consecutive faults. Furthermore few applications have considered fixed-wing UAVs where full autonomy is most needed. In this paper an EMRAN RBF NN is chosen for modelling purposes due to its ability to adapt well to nonlinear environments while maintaining high computational speeds. A nonlinear UAV model is used for demonstration, where decoupled longitudinal motion is considered. System and measurement noise is also included in the UAV model as wind gust disturbances on the angle of attack and sensor noise, respectively. The UAV is assumed to operate at an initial trimmed condition of speed, 32m/s and altitude, 1000m. After 30 separate SFDIA tests implemented on a 1.6GHz Pentium processor, the NN-SFDIA scheme detected all but 2 faults and the NN processing time was 97% lower than the flight data sampling time. [Copyright &y& Elsevier]

Neural network based sensor fault detection, isolation and accommodation (NN-SFDIA) is becoming a popular alternative to traditional linear time-invariant model-based sensor fault detection, isolation and accommodation (SFDIA) schemes, such as observer-based methods. Their online training capabilities and ability to model complex nonlinear systems have attracted much research interest in the applications area of neural networks. In this article, we design an NN-SFDIA scheme to detect multiple sensor faults in an unmanned air vehicle (UAV). Model-based SFDIA is a direction of development in particular with UAVs where sensor redundancy may not be an option due to weight, cost and space implications. In this article, a maximum of three consecutive faults are assumed in the pitch gyro, normal accelerometer and angle of attack sensor of a nonlinear UAV model. Furthermore, a novel residual generator which is designed to minimise the false alarm rates and missed faults, is implemented. After 33 separate SFDIA tests implemented on a 1.6 GHz Pentium processor, the NN-SFDIA scheme detected all but three faults with a fast execution time of 0.55 ms per flight data sample. [ABSTRACT FROM AUTHOR]

In this article, we propose two schemes for sensor fault detection and accommodation (SFDA): one based on a neural network (NN) and the other on an extended Kalman filter (EKF). The objective of this article is to compare both approaches in terms of execution time, robustness to poorly modelled dynamics and sensitivity to different fault types. The schemes are tested on an unmanned air vehicle (UAV) application where traditional sensor redundancy methods can be too heavy and/or costly. In an attempt to reduce the false alarm rates and the number of undetected faults, a modified residual generator, originally proposed in Samy, Postlethwaite, and Gu in 2008 (Samy, I., Postlethwaite, I., and Gu, D.-W. (2008a). Neural Network Sensor Validation Scheme Demonstrated on a UAV Model, in IEEE Proceedings of CDC, Cancun, Mexico, pp. 1237-1242) is implemented. Simulation work is presented for use on a UAV demonstrator under construction with support from BAE systems and EPSRC. Results have shown that the NN-SFDA scheme outperforms the EKF-SFDA scheme with only one missed fault, zero false alarms and an average estimation error of 0.31°/s for 112 different test conditions. [ABSTRACT FROM AUTHOR]

This paper presents a non‐linear square‐root estimation scheme for brushless DC (BLDC) motors. The cubature Kalman filter (CKF) is the main estimation tool for the presented approach. The CKF is a recently proposed estimator for highly non‐linear systems and its efficacy has been verified on several applications. The square‐root version of the CKF is preferred over the conventional CKF for real‐time applications. Despite of having several advantages over other non‐linear filters, the CKF has not yet been explored for state estimation of electric drives in the electric drives community. In this study, the authors present a square‐root CKF for the speed and rotor position estimation of a highly non‐linear and high fidelity BLDC motor, these estimated speed and rotor position are then fed back to control the speed of the BLDC motor. The efficacy of the presented approach for low and high reference speeds, and in the presence of parametric uncertainties, is demonstrated by real‐time experiments. [ABSTRACT FROM AUTHOR]

Abstract: Three new ion-pair complexes, consisting of 1-benzyl-4-aminopyridinium with [M(mnt)2]2− where mnt2− =maleonitriledithiolate and M=Ni2+, Pd2+ or Pt2+ for complexes 1–3, have been synthesized and structurally characterized. X-ray single crystal studies revealed that three complexes are isostructural and crystallize in monoclinic space group C2/c, and there exist weak H-bonding interactions between –NH2 groups of cation and –CN group of anion as well as weak M…H-bonding interactions between anions and cations. The calculations of charge density distribution disclosed that the M…H-bonding interaction in crystals of 1–3 is mainly attributed to static electric interactions. Two types of H-bonding interactions lead to the formation of two-dimensional sheet structure which is parallel to the crystallographic bc-plane in the crystals of 1–3. A near-IR absorbance appears in the UV–vis-NIR spectra of 1 and 3, respectively, while does not come out in the spectra of 2. [Copyright &y& Elsevier]

Abstract: Five ion-pair complexes, consisting of R-benzylidene-1-aminopyridinium derivatives and [Ni(mnt)2]2− (R= p-nitro (1), p-methyl (2), p-bromo (3), p-chloro (4) and m-nitro (5); mnt2− =maleonitriledithiolate), were synthesized and structurally characterized. As for 1, it is interesting to observe a large deviation from square-planar coordination geometry for the Ni atom, while no deviation is observed in the other four complexes. In the solid state, UV–Vis–NIR spectra of 2–5 show similar properties with intense absorption in the 200–750nm and moderate near IR absorption in the 750–1000nm region, whereas 1 exhibits an intense absorption from UV/Visible to near-IR region (200–1100nm). This unique spectral feature of 1 is attributed to its distinctive structural differences from 2 to 5, namely the strong intermolecular packing interactions between anions and cations, as well as a significant deviation from the planarity of the anion. Based on DFT and TDDFT calculations, near-IR absorbance bands in 1–5 were assigned to combined transitions of d–d, MLCT and π–π∗ in the [Ni(mnt)2]2− anion as well as the ion-pair charge transfer (IPCT) from the anionic HOMO to the cationic LUMO. The IPCT band position in acetonitrile is independent of the substituent group feature in benzene ring of cations for 1–5, which could be interpreted that the substituent group in benzene ring only has a minor contribution to the cationic LUMO. [Copyright &y& Elsevier]

Flush air data sensing systems have been widely applied to large (manned) aircraft, where pressure orifices are typically located at the nosetip. This paper investigates the feasibility of a flush air data sensing system designed to estimate the air data states of a small unmanned air vehicle flown at speeds as low as Mach 0.07. Furthermore, due to the presence of a nose propeller, the pressure orifices are located at the wing leading edge. The motivation behind this project is the fact that traditional air data booms are physically impractical for small unmanned air vehicles. Overall, an 80 and 97% reduction in instrumentation weight and cost, respectively, were achieved. Both parametric and multilayer perceptron neural network models have been previously applied in the literature to model the aerodynamic relationship between aircraft surface pressure and the air data states. In this paper, an extended minimum resource allocating network radial basis function neural network is used as the flush air data sensing system model, due to its good generalization capabilities and compact structure. Computational fluid dynamic simulations are implemented to identify the ideal pressure port locations, and wind-tunnel tests are carried out to train and test the extended minimum resource allocating network radial basis function neural network. [ABSTRACT FROM AUTHOR]