999 resultados para Cyclic generalized polynomial codes


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Diastereoselective conjugate addition of lithium (S)-N-allyl-N-alpha-methylbenzylamide to a range of alpha,beta-unsaturated esters followed by ring closing metathesis is used to afford efficiently a range of substituted cyclic beta-amino esters in high d.e. Alternatively, conjugate addition to alpha,beta-unsaturated Weinreb amides, functional group conversion and ring closing metathesis affords cyclic amines in high d.e. The further application of this methodology to the synthesis of a range of carbocyclic beta-amino esters via conjugate addition, enolate alkylation and ring closing metathesis is also described. Application of this methodology affords, after deprotection, (S)-homoproline, (S)-homopipecolic acid, (S)-coniine and (1S,2S)-trans-pentacin.

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OBJECTIVE: The anticipation of adverse outcomes, or worry, is a cardinal symptom of generalized anxiety disorder. Prior work with healthy subjects has shown that anticipating aversive events recruits a network of brain regions, including the amygdala and anterior cingulate cortex. This study tested whether patients with generalized anxiety disorder have alterations in anticipatory amygdala function and whether anticipatory activity in the anterior cingulate cortex predicts treatment response. METHOD: Functional magnetic resonance imaging (fMRI) was employed with 14 generalized anxiety disorder patients and 12 healthy comparison subjects matched for age, sex, and education. The event-related fMRI paradigm was composed of one warning cue that preceded aversive pictures and a second cue that preceded neutral pictures. Following the fMRI session, patients received 8 weeks of treatment with extended-release venlafaxine. RESULTS: Patients with generalized anxiety disorder showed greater anticipatory activity than healthy comparison subjects in the bilateral dorsal amygdala preceding both aversive and neutral pictures. Building on prior reports of pretreatment anterior cingulate cortex activity predicting treatment response, anticipatory activity in that area was associated with clinical outcome 8 weeks later following treatment with venlafaxine. Higher levels of pretreatment anterior cingulate cortex activity in anticipation of both aversive and neutral pictures were associated with greater reductions in anxiety and worry symptoms. CONCLUSIONS: These findings of heightened and indiscriminate amygdala responses to anticipatory signals in generalized anxiety disorder and of anterior cingulate cortex associations with treatment response provide neurobiological support for the role of anticipatory processes in the pathophysiology of generalized anxiety disorder.

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Time-resolved kinetic studies of silylene, SiH2, generated by laser flash photolysis of phenylsilane, have been carried out to obtain rate constants for its bimolecular reactions with oxirane, oxetane, and tetrahydrofuran (THF). The reactions were studied in the gas phase over the pressure range 1-100 Torr in SF6 bath gas, at four or five temperatures in the range 294-605 K. All three reactions showed pressure dependences characteristic of third-body-assisted association reactions with, surprisingly, SiH2 + oxirane showing the least and SiH2 + THF showing the most pressure dependence. The second-order rate constants obtained by extrapolation to the high-pressure limits at each temperature fitted the Arrhenius equations where the error limits are single standard deviations: log(k(oxirane)(infinity)/cm(3) molecule(-1) s(-1)) = (-11.03 +/- 0.07) + (5.70 +/- 0.51) kJ mol(-1)/RT In 10 log(k(oxetane)(infinity)/cm(3) molecule(-1) s(-1)) = (-11.17 +/- 0.11) + (9.04 +/- 0.78) kJ mol(-1)/RT In 10 log(k(THF)(infinity)/cm(3) molecule(-1) s(-1)) = (-10.59 +/- 0.10) + (5.76 +/- 0.65) kJ mol(-1)/RT In 10 Binding-energy values of 77, 97, and 92 kJ mol(-1) have been obtained for the donor-acceptor complexes of SiH2 with oxirane, oxetane, and THF, respectively, by means of quantum chemical (ab initio) calculations carried Out at the G3 level. The use of these values to model the pressure dependences of these reactions, via RRKM theory, provided a good fit only in the case of SiH2 + THF. The lack of fit in the other two cases is attributed to further reaction pathways for the association complexes of SiH2 with oxirane and oxetane. The finding of ethene as a product of the SiH2 + oxirane reaction supports a pathway leading to H2Si=O + C2H4 predicted by the theoretical calculations of Apeloig and Sklenak.

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We consider the Stokes conjecture concerning the shape of extreme two-dimensional water waves. By new geometric methods including a nonlinear frequency formula, we prove the Stokes conjecture in the original variables. Our results do not rely on structural assumptions needed in previous results such as isolated singularities, symmetry and monotonicity. Part of our results extends to the mathematical problem in higher dimensions.

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A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

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The problem of identification of a nonlinear dynamic system is considered. A two-layer neural network is used for the solution of the problem. Systems disturbed with unmeasurable noise are considered, although it is known that the disturbance is a random piecewise polynomial process. Absorption polynomials and nonquadratic loss functions are used to reduce the effect of this disturbance on the estimates of the optimal memory of the neural-network model.

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The paper proposes a method of performing system identification of a linear system in the presence of bounded disturbances. The disturbances may be piecewise parabolic or periodic functions. The method is demonstrated effectively on two example systems with a range of disturbances.

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Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

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Use of orthogonal space-time block codes (STBCs) with multiple transmitters and receivers can improve signal quality. However, in optical intensity modulated signals, output of the transmitter is non-negative and hence standard orthogonal STBC schemes need to be modified. A generalised framework for applying orthogonal STBCs for free-space IM/DD optical links is presented.

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Little has so far been reported on the robustness of non-orthogonal space-time block codes (NO-STBCs) over highly correlated channels (HCC). Some of the existing NO-STBCs are indeed weak in robustness against HCC. With a view to overcoming such a limitation, a generalisation of the existing robust NO-STBCs based on a 'matrix Alamouti (MA)' structure is presented.

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1,1′-Diacetylferrocene reacts with neat hydrate over a period of 72 h at 20°C to give the dihydrazone [H2NN(Me)CC5H4FeC5H4C(Me)NNH2] (6) in almost quantitative yield. Either prolonging the reaction time or reacting 6 with fresh hydrazine causes the iron to be stripped from the metallocene and bis(hydrazine)bis(hydrazinecarboxylato-N′,O) iron(II), [Fe(N2H4)2(OOCNHNH2)2] (11), crystallizes. In the presence of Ba2+ or Mo2+ ions two molecules of complex 6 react to give the cyclic diazine [N(Me)CC5H4FeC5H4C (Me)N]2 (7) in high yield. Hydrazine is liberated in this reaction. Complexes 6 and 11 have been characterized crystallographically. The cyclic voltammograms of complexes 6 and 7 contain essentially non-reversible oxidation peaks.