974 resultados para Quasi-Bilateral Generating Function


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The poison gland and Dufour's gland are the two glands associated with the sting apparatus in female Apocrita (Hymenoptera). While the poison gland usually functions as an integral part of the venom delivery system, the Dufour's gland has been found to differ in its function in various hymenopteran groups. Like all exocrine glands, the function of the Dufour's gland is to secrete chemicals, but the nature and function of the secretions varies in different taxa. Functions of the Dufour's gland secretions range from serving as a component of material used in nest building, larval food, and pheromones involved in communicative functions that are important for both solitary and social species. This review summarizes the different functions reported for the Dufour's gland in hymenopterans, illustrating how the Dufour's gland secretions can be adapted to give rise to various functions in response to different challenges posed by the ways of life followed by different taxa. Aspects of development, structure, chemistry and the evolution of different functions are also touched upon briefly.

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The basic requirement for an autopilot is fast response and minimum steady state error for better guidance performance. The highly nonlinear nature of the missile dynamics due to the severe kinematic and inertial coupling of the missile airframe as well as the aerodynamics has been a challenge for an autopilot that is required to have satisfactory performance for all flight conditions in probable engagements. Dynamic inversion is very popular nonlinear controller for this kind of scenario. But the drawback of this controller is that it is sensitive to parameter perturbation. To overcome this problem, neural network has been used to capture the parameter uncertainty on line. The choice of basis function plays the major role in capturing the unknown dynamics. Here in this paper, many basis function has been studied for approximation of unknown dynamics. Cosine basis function has yield the best response compared to any other basis function for capturing the unknown dynamics. Neural network with Cosine basis function has improved the autopilot performance as well as robustness compared to Dynamic inversion without Neural network.

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We generalize the method of A. M. Polyakov, Phys. Rev. E 52, 6183 (1995)] for obtaining structure-function relations in turbulence in the stochastically forced Burgers equation, to develop structure-function hierarchies for turbulence in three models for magnetohydrodynamics (MHD). These are the Burgers analogs of MHD in one dimension Eur. Phys. J.B 9, 725 (1999)], and in three dimensions (3DMHD and 3D Hall MHD). Our study provides a convenient and unified scheme for the development of structure-function hierarchies for turbulence in a variety of coupled hydrodynamical equations. For turbulence in the three sets of MHD equations mentioned above, we obtain exact relations for third-order structure functions and their derivatives; these expressions are the analogs of the von Karman-Howarth relations for fluid turbulence. We compare our work with earlier studies of such relations in 3DMHD and 3D Hall MHD.

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With the development of deep sequencing methodologies, it has become important to construct site saturation mutant (SSM) libraries in which every nucleotide/codon in a gene is individually randomized. We describe methodologies for the rapid, efficient, and economical construction of such libraries using inverse polymerase chain reaction (PCR). We show that if the degenerate codon is in the middle of the mutagenic primer, there is an inherent PCR bias due to the thermodynamic mismatch penalty, which decreases the proportion of unique mutants. Introducing a nucleotide bias in the primer can alleviate the problem. Alternatively, if the degenerate codon is placed at the 5' end, there is no PCR bias, which results in a higher proportion of unique mutants. This also facilitates detection of deletion mutants resulting from errors during primer synthesis. This method can be used to rapidly generate SSM libraries for any gene or nucleotide sequence, which can subsequently be screened and analyzed by deep sequencing. (C) 2013 Elsevier Inc. All rights reserved.

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We report results of the magnetization and ac susceptibility measurements down to very low fields on a single crystal of the perovskite manganite, La-0.82 Ca-0.18 MnO3. This composition falls in the intriguing ferromagnetic insulator region of the manganite phase diagram. In contrast to earlier beliefs, our investigations reveal that magnetically (and in every other sense), this is a single- phase system with a ferromagnetic ordering temperature of around 170 K. However, this ferromagnetic state is magnetically frustrated, and the system exhibits pronounced glassy dynamics below 90 K. Based on measured dynamical properties, we propose that this quasi-long-ranged ferromagnetic phase, and the associated superspin glass behavior, is the true magnetic state of the system, rather than being a macroscopic mixture of ferromagnetic and antiferromagnetic phases, as often suggested. Our results provide an understanding of the quantum phase transition from an antiferromagnetic insulator to a ferromagnetic metal via this ferromagnetic state as a function of x in La1-xCaxMnO3, in terms of the possible formation of magnetic polarons.

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The electronic structure of quasi-two-dimensional monophosphate tungsten bronze, P4W12O44, has been investigated by high-resolution angle-resolved photoemission spectroscopy and density functional theoretical calculations. Experimental electron-like bands around Gamma point and Fermi surfaces have similar shapes as predicted by calculations. Fermi surface mapping at different temperatures shows a depletion of density of states at low temperature in certain flat portions of the Fermi surfaces. These flat portions of the Fermi surfaces satisfy the partial nesting condition with incommensurate nesting vectors q(1) and q(2), which leads to the formation of charge density waves in this phosphate tungsten bronzes. The setting up of charge density wave in these bronzes can well explain the anomaly observed in its transport properties. Copyright (C) EPLA, 2014

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A robust suboptimal reentry guidance scheme is presented for a reusable launch vehicle using the recently developed, computationally efficient model predictive static programming. The formulation uses the nonlinear vehicle dynamics with a spherical and rotating Earth, hard constraints for desired terminal conditions, and an innovative cost function having several components with associated weighting factors that can account for path and control constraints in a soft constraint manner, thereby leading to smooth solutions of the guidance parameters. The proposed guidance essentially shapes the trajectory of the vehicle by computing the necessary angle of attack and bank angle that the vehicle should execute. The path constraints are the structural load constraint, thermal load constraint, bounds on the angle of attack, and bounds on the bank angle. In addition, the terminal constraints include the three-dimensional position and velocity vector components at the end of the reentry. Whereas the angle-of-attack command is generated directly, the bank angle command is generated by first generating the required heading angle history and then using it in a dynamic inversion loop considering the heading angle dynamics. Such a two-loop synthesis of bank angle leads to better management of the vehicle trajectory and avoids mathematical complexity as well. Moreover, all bank angle maneuvers have been confined to the middle of the trajectory and the vehicle ends the reentry segment with near-zero bank angle, which is quite desirable. It has also been demonstrated that the proposed guidance has sufficient robustness for state perturbations as well as parametric uncertainties in the model.

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Mitochondria are indispensable organelles implicated in multiple aspects of cellular processes, including tumorigenesis. Heat shock proteins play a critical regulatory role in accurately delivering the nucleus-encoded proteins through membrane-bound presequence translocase (Tim23 complex) machinery. Although altered expression of mammalian presequence translocase components had been previously associated with malignant phenotypes, the overall organization of Tim23 complexes is still unsolved. In this report, we show the existence of three distinct Tim23 complexes, namely, B1, B2, and A, involved in the maintenance of normal mitochondrial function. Our data highlight the importance of Magmas as a regulator of translocase function and in dynamically recruiting the J-proteins DnaJC19 and DnaJC15 to individual translocases. The basic housekeeping function involves translocases B1 and B2 composed of Tim17b isoforms along with DnaJC19, whereas translocase A is nonessential and has a central role in oncogenesis. Translocase B, having a normal import rate, is essential for constitutive mitochondrial functions such as maintenance of electron transport chain complex activity, organellar morphology, iron-sulfur cluster protein biogenesis, and mitochondrial DNA. In contrast, translocase A, though dispensable for housekeeping functions with a comparatively lower import rate, plays a specific role in translocating oncoproteins lacking presequence, leading to reprogrammed mitochondrial functions and hence establishing a possible link between the TIM23 complex and tumorigenicity.

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This paper presents a second order sliding mode observer (SOSMO) design for discrete time uncertain linear multi-output system. The design procedure is effective for both matched and unmatched bounded uncertainties and/or disturbances. A second order sliding function and corresponding sliding manifold for discrete time system are defined similar to the lines of continuous time counterpart. A boundary layer concept is employed to avoid switching across the defined sliding manifold and the sliding trajectory is confined to a boundary layer once it converges to it. The condition for existence of convergent quasi-sliding mode (QSM) is derived. The observer estimation errors satisfying given stability conditions converge to an ultimate finite bound (within the specified boundary layer) with thickness O(T-2) where T is the sampling period. A relation between sliding mode gain and boundary layer is established for the existence of second order discrete sliding motion. The design strategy is very simple to apply and is demonstrated for three examples with different class of disturbances (matched and unmatched) to show the effectiveness of the design. Simulation results to show the robustness with respect to the measurement noise are given for SOSMO and the performance is compared with pseudo-linear Kalman filter (PLKF). (C) 2013 Published by Elsevier Ltd. on behalf of The Franklin Institute

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Classification of pharmacologic activity of a chemical compound is an essential step in any drug discovery process. We develop two new atom-centered fragment descriptors (vertex indices) - one based solely on topological considerations without discriminating atomor bond types, and another based on topological and electronic features. We also assess their usefulness by devising a method to rank and classify molecules with regard to their antibacterial activity. Classification performances of our method are found to be superior compared to two previous studies on large heterogeneous data sets for hit finding and hit-to-lead studies even though we use much fewer parameters. It is found that for hit finding studies topological features (simple graph) alone provide significant discriminating power, and for hit-to-lead process small but consistent improvement can be made by additionally including electronic features (colored graph). Our approach is simple, interpretable, and suitable for design of molecules as we do not use any physicochemical properties. The singular use of vertex index as descriptor, novel range based feature extraction, and rigorous statistical validation are the key elements of this study.

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In this paper we establish that the Lovasz theta function on a graph can be restated as a kernel learning problem. We introduce the notion of SVM-theta graphs, on which Lovasz theta function can be approximated well by a Support vector machine (SVM). We show that Erdos-Renyi random G(n, p) graphs are SVM-theta graphs for log(4)n/n <= p < 1. Even if we embed a large clique of size Theta(root np/1-p) in a G(n, p) graph the resultant graph still remains a SVM-theta graph. This immediately suggests an SVM based algorithm for recovering a large planted clique in random graphs. Associated with the theta function is the notion of orthogonal labellings. We introduce common orthogonal labellings which extends the idea of orthogonal labellings to multiple graphs. This allows us to propose a Multiple Kernel learning (MKL) based solution which is capable of identifying a large common dense subgraph in multiple graphs. Both in the planted clique case and common subgraph detection problem the proposed solutions beat the state of the art by an order of magnitude.

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The design of a non-traditional cam and roller-follower mechanism is described here. In this mechanism, the roller-crank rather than the cam is used as the continuous input member, while both complete a full rotation in each revolution and remain in contact throughout. It is noted that in order to have the cam fully rotate for every full rotation of the roller-crank, the cam cannot be a closed profile, rather the roller traverses the open cam profile twice in each cycle. Using kinematic analysis, the angular velocity of the cam when the roller traverses the cam profile in one direction, is related to the angular velocity of the cam when the roller retraces its path on the cam in the other direction. Thus, one can specify any arbitrary function relating the motion of the cam to the motion of the roller-crank for only 180 degrees of rotation in the angular velocity space. The motion of the cam in the remaining portion is then automatically determined. In specifying the arbitrary motion, many desirable characteristics such as multiple dwells, low acceleration and jerk, etc., can be obtained. Useful design equations are derived for this purpose. Using the kinematic inversion technique, the cam profile is readily obtained once the motion is specified in the angular velocity space. The only limitation to the arbitrary motion specification is making sure that the transmission angle never gets too low, so that the force will be transmitted efficiently from roller to cam. This is addressed by incorporating a transmission index into the motion specification in the synthesis process. Consequently, in this method we can specify any arbitrary motion within a permissible rone, such that the transmission index is higher than the specified minimum value. Single-dwell, double-dwell and a long hesitation motion are used as examples to demonstrate the ffectiveness of the design method. Force closure using an optimally located spring and quasi-kinetostatic analysis are also discussed. (C) 2001 Elsevier Science Ltd. All rights reserved.

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The effect of structure height on the lightning striking distance is estimated using a lightning strike model that takes into account the effect of connecting leaders. According to the results, the lightning striking distance may differ significantly from the values assumed in the IEC standard for structure heights beyond 30m. However, for structure heights smaller than about 30m, the results show that the values assumed by IEC do not differ significantly from the predictions based on a lightning attachment model taking into account the effect of connecting leaders. However, since IEC assumes a smaller striking distance than the ones predicted by the adopted model one can conclude that the safety is not compromised in adhering to the IEC standard. Results obtained from the model are also compared with Collection Volume Method (CVM) and other commonly used lightning attachment models available in the literature. The results show that in the case of CVM the calculated attractive distances are much larger than the ones obtained using the physically based lightning attachment models. This indicates the possibility of compromising the lightning protection procedures when using CVM. (C) 2014 Elsevier B.V. All rights reserved.

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Programming for parallel architectures that do not have a shared address space is extremely difficult due to the need for explicit communication between memories of different compute devices. A heterogeneous system with CPUs and multiple GPUs, or a distributed-memory cluster are examples of such systems. Past works that try to automate data movement for distributed-memory architectures can lead to excessive redundant communication. In this paper, we propose an automatic data movement scheme that minimizes the volume of communication between compute devices in heterogeneous and distributed-memory systems. We show that by partitioning data dependences in a particular non-trivial way, one can generate data movement code that results in the minimum volume for a vast majority of cases. The techniques are applicable to any sequence of affine loop nests and works on top of any choice of loop transformations, parallelization, and computation placement. The data movement code generated minimizes the volume of communication for a particular configuration of these. We use a combination of powerful static analyses relying on the polyhedral compiler framework and lightweight runtime routines they generate, to build a source-to-source transformation tool that automatically generates communication code. We demonstrate that the tool is scalable and leads to substantial gains in efficiency. On a heterogeneous system, the communication volume is reduced by a factor of 11X to 83X over state-of-the-art, translating into a mean execution time speedup of 1.53X. On a distributed-memory cluster, our scheme reduces the communication volume by a factor of 1.4X to 63.5X over state-of-the-art, resulting in a mean speedup of 1.55X. In addition, our scheme yields a mean speedup of 2.19X over hand-optimized UPC codes.