Circuit layout through an analogy with neural networks

Standard-cell design methodology is an important technique in semicustom-VLSI design. It lends itself to the easy automation of the crucial layout part, and many algorithms have been proposed in recent literature for the efficient placement of standard cells. While many studies have identified the Kerninghan-Lin bipartitioning method as being superior to most others, it must be admitted that the behaviour of the method is erratic, and that it is strongly dependent on the initial partition. This paper proposes a novel algorithm for overcoming some of the deficiencies of the Kernighan-Lin method. The approach is based on an analogy of the placement problem with neural networks, and, by the use of some of the organizing principles of these nets, an attempt is made to improve the behavior of the bipartitioning scheme. The results have been encouraging, and the approach seems to be promising for other NP-complete problems in circuit layout.

Molecular Modeling Studies on Amphotericin B and its Complex with Phospholipid,

Molecular dynamics simulation studies on polyene antifungal antibiotic amphotericin B, its head-to-tail dimeric structure and lipid - amphotericin B complex demonstrate interesting features of the flexibilities within the molecule and define the optimal interactions for the formation of a stable dimeric structure and complex with phospholipid.

Computer modeling studies on the binding of 2',5'-linked dinucleoside phosphates to ribonuclease T1-influence of subsite interactions on the substrate specificity

The modes of binding of Gp(2',5')A, Gp(2',5')C, Gp(2',5')G and Gp(2',5')U to RNase T1 have been determined by computer modelling studies. All these dinucleoside phosphates assume extended conformations in the active site leading to better interactions with the enzyme. The 5'-terminal guanine of all these ligands is placed in the primary base binding site of the enzyme in an orientation similar to that of 2'-GMP in the RNase T1-2'-GMP complex. The 2'-terminal purines are placed close to the hydrophobic pocket formed by the residues Gly71, Ser72, Pro73 and Gly74 which occur in a loop region. However, the orientation of the 2'-terminal pyrimidines is different from that of 2'-terminal purines. This perhaps explains the higher binding affinity of the 2',5'-linked guanine dinucleoside phosphates with 2'-terminal purines than those with 2'-terminal pyrimidines. A comparison of the binding of the guanine dinucleoside phosphates with 2',5'- and 3',5'-linkages suggests significant differences in the ribose pucker and hydrogen bonding interactions between the catalytic residues and the bound nucleoside phosphate implying that 2',5'-linked dinucleoside phosphates may not be the ideal ligands to probe the role of the catalytic amino acid residues. A change in the amino acid sequence in the surface loop region formed by the residues Gly71 to Gly74 drastically affects the conformation of the base binding subsite, and this may account for the inactivity of the enzyme with altered sequence i.e., with Pro, Gly and Ser at positions 71 to 73 respectively. These results thus suggest that in addition to recognition and catalytic sites, interactions at the loop regions which constitute the subsite for base binding are also crucial in determining the substrate specificity.

Some experiments on human memory and a new neural model

An associative memory with parallel architecture is presented. The neurons are modelled by perceptrons having only binary, rather than continuous valued input. To store m elements each having n features, m neurons each with n connections are needed. The n features are coded as an n-bit binary vector. The weights of the n connections that store the n features of an element has only two values -1 and 1 corresponding to the absence or presence of a feature. This makes the learning very simple and straightforward. For an input corrupted by binary noise, the associative memory indicates the element that is closest (in terms of Hamming distance) to the noisy input. In the case where the noisy input is equidistant from two or more stored vectors, the associative memory indicates two or more elements simultaneously. From some simple experiments performed on the human memory and also on the associative memory, it can be concluded that the associative memory presented in this paper is in some respect more akin to a human memory than a Hopfield model.

Impact of climate change on Indian forests: a dynamic vegetation modeling approach

We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.

Modeling and Field Oriented Control of Salient Pole Wound Field Synchronous Machine in Stator Flux Coordinates

This paper describes the field oriented control of a salient pole wound field synchronous machine in stator flux coordinates. The procedure for derivation of flux linkage equations along any general rotating axes including stator flux axes is given. The stator flux equations are used to identify the cross-coupling occurring between the axes due to saliency in the machine. The coupling terms are canceled as feedforward terms in the generation of references for current controllers to achieve good decoupling during transients. The design of current controller for stator-flux-oriented control is presented. This paper proposes the method of extending rotor flux closed loop observer for sensorless control of wound field synchronous machine. This paper also proposes a new sensorless control by using stator flux closed loop observer and estimation of torque angle using stator current components in stator flux coordinates. Detailed experimental results from a sensorless 15.8 hp salient pole wound field synchronous machine drive are presented to demonstrate the performance of the proposed control strategy from a low speed of 0.8 Hz to 50 Hz.

Constitutive modeling of ice in the high strain rate regime

The objective of the present work is to propose a constitutive model for ice by considering the influence of important parameters such as strain rate dependence and pressure sensitivity on the response of the material. In this regard, the constitutive model proposed by Carney et al. (2006) is considered as a starting basis and subsequently modified to incorporate the effect of brittle cracking within a continuum damage mechanics framework. The damage is taken to occur in the form of distributed cracking within the material during impact which is consistent with experimental observations. At the point of failure, the material is assumed to be fluid-like with deviatoric stress almost dropping down to zero. The constitutive model is implemented in a general purpose finite element code using an explicit formulation. Several single element tests under uniaxial tension and compression, as well as biaxial loading are conducted in order to understand the performance of the model. Few large size simulations are also performed to understand the capability of the model to predict brittle damage evolution in un-notched and notched three point bend specimens. The proposed model predicts lower strength under tensile loading as compared to compressive loading which is in tune with experimental observations. Further the model also asserts the strain rate dependency of the strength behavior under both compressive as well as tensile loading, which also corroborates well with experimental results. (C) 2010 Elsevier Ltd. All rights reserved.

A hybrid technique of modeling of cracks using displacement discontinuity and direct boundary element method

A hybrid technique to model two dimensional fracture problems which makes use of displacement discontinuity and direct boundary element method is presented. Direct boundary element method is used to model the finite domain of the body, while displacement discontinuity elements are utilized to represent the cracks. Thus the advantages of the component methods are effectively combined. This method has been implemented in a computer program and numerical results which show the accuracy of the present method are presented. The cases of bodies containing edge cracks as well as multiple cracks are considered. A direct method and an iterative technique are described. The present hybrid method is most suitable for modeling problems invoking crack propagation.

Quantum Threshold Voltage Modeling of Short Channel Quad Gate Silicon Nanowire Transistor

In this paper, a physically based analytical quantum linear threshold voltage model for short channel quad gate MOSFETs is developed. The proposed model, which is suitable for circuit simulation, is based on the analytical solution of 3-D Poisson and 2-D Schrodinger equation. Proposed model is fully validated against the professional numerical device simulator for a wide range of device geometries and also used to analyze the effect of geometry variation on the threshold voltage.

Calcium ionophore, A23187 and its amino acid complexes: spectroscopic and molecular modeling studies.

The circular dichroism, fluorescence, Nuclear Magnetic Resonance and BLM conductance studies indicate that A23187 forms a stable complex with amino acids at low ionophore concentrations (<10(-4)M). However, A23187 prefers to be in a dimeric structure with no significant binding to amino acids, at concentrations higher than 10(-4)M. It was also observed that at lower concentrations, at which the amino acids bind to the ionophore, the affinity for calcium ions was several orders of magnitude lower than that at higher ionophore concentrations. We have also conducted molecular modeling studies to examine the structure of the A23187 dimer and its amino acid complexes. The results of these modeling studies strongly support our experimental results and validate the formation of a hydrogen bonded and energetically stable A23187 dimer and its amino acid complexes.

Multiscale Modeling Approach to Acoustic Emission during Plastic Deformation

We address the long-standing problem of the origin of acoustic emission commonly observed during plastic deformation. We propose a framework to deal with the widely separated time scales of collective dislocation dynamics and elastic degrees of freedom to explain the nature of acoustic emission observed during the Portevin-Le Chatelier effect. The Ananthakrishna model is used as it explains most generic features of the phenomenon. Our results show that while acoustic emission bursts correlated with stress drops are well separated for the type C serrations, these bursts merge to form nearly continuous acoustic signals with overriding bursts for the propagating type A bands.

Diacylglycerol Kinase Is Stimulated by Arachidonic Acid in Neural Membranes.

The effect of arachidonic acid (AA) on the activity of diacylglycerol (DG) kinase in neural membranes was investigated. When rat brain cortical membranes were incubated with 0.5 mM dipalmitin and [gamma-P-32]ATP, formation of phosphatidic acid (PA) was observed. It was linear up to 5 min, and the initial rate was similar to 1.0 nmol/min/mg of protein. The DG kinase activity was stimulated twofold by 0.25 mM AA. The stimulation was apparent at the earliest time point measured (1 min) and with the lowest concentration of AA tested (62.5 mu M). The stimulation was proportional to the concentration of AA up to 250 mu M. AA was the most potent stimulator of DG kinase, and linolenic acid showed similar to 40% stimulation. Oleic acid showed no effect, whereas linoleic and the saturated fatty acids tested were inhibitory. AA stimulation of DG kinase was observed only with membranes of cerebrum, cerebellum, and myelin and not with brain cytosol or liver membranes. AA also stimulated the formation of PA in the absence of added dipalmitin (endogenous activity) with membranes prepared from whole brain. DG kinase of neural membranes was extracted with 2 M NaCl, which on dialysis yielded a precipitate. Both the precipitate and the supernatant showed DG kinase activity, but only the enzyme in the precipitate was stimulated by AA at concentrations as low as 25 mu M. It is suggested that AA, through its effect on DG kinase, regulates the level of DG in neural membranes, which in turn regulates protein kinase C activity.

Modeling and design of a solar thermal system for hybrid cooking application

This paper proposes a hybrid solar cooking system where the solar energy is brought to the kitchen. The energy source is a combination of the solar thermal energy and the Liquefied Petroleum Gas (LPG) that is in common use in kitchens. The solar thermal energy is transferred to the kitchen by means of a circulating fluid. The transfer of solar heat is a twofold process wherein the energy from the collector is transferred first to an intermediate energy storage buffer and the energy is subsequently transferred from the buffer to the cooking load. There are three parameters that are controlled in order to maximize the energy transfer from the collector to the load viz, the fluid flow rate from collector to buffer, fluid flow rate from buffer to load and the diameter of the pipes. This is a complex multi energy domain system comprising energy flow across several domains such as thermal, electrical and hydraulic. The entire system is modeled using the bond graph approach with seamless integration of the power flow in these domains. A method to estimate different parameters of the practical cooking system is also explained. Design and life cycle costing of the system is also discussed. The modeled system is simulated and the results are validated experimentally. (C) 2010 Elsevier Ltd. All rights reserved.

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Water-modeling study of the surface disturbances in continuous slab caster

The present work is based on four static molds using nozzles of different port diameter, port angle, and immersion depth. It has been observed that the meniscus is wavy. The wave amplitude shows a parabolic variation with the nozzle exit velocity. The dimensionless amplitude is found to vary linearly with the Froude number. Vortex formation and bubble entrainment by the wave occurs at the meniscus beyond a critical flow rate, depending upon the nozzle configuration, immersion depth, and the mold aspect ratio.