A direct adaptive neural command controller design for an unstable helicopter

This paper presents an off-line (finite time interval) and on-line learning direct adaptive neural controller for an unstable helicopter. The neural controller is designed to track pitch rate command signal generated using the reference model. A helicopter having a soft inplane four-bladed hingeless main rotor and a four-bladed tail rotor with conventional mechanical controls is used for the simulation studies. For the simulation study, a linearized helicopter model at different straight and level flight conditions is considered. A neural network with a linear filter architecture trained using backpropagation through time is used to approximate the control law. The controller network parameters are adapted using updated rules Lyapunov synthesis. The off-line trained (for finite time interval) network provides the necessary stability and tracking performance. The on-line learning is used to adapt the network under varying flight conditions. The on-line learning ability is demonstrated through parameter uncertainties. The performance of the proposed direct adaptive neural controller (DANC) is compared with feedback error learning neural controller (FENC).

A new intelligent algorithm for online voltage stability assessment and monitoring

This paper presents a new approach for assessing power system voltage stability based on artificial feed forward neural network (FFNN). The approach uses real and reactive power, as well as voltage vectors for generators and load buses to train the neural net (NN). The input properties of the NN are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The performance of the trained NN is investigated on two systems under various voltage stability assessment conditions. Main advantage is that the proposed approach is fast, robust, accurate and can be used online for predicting the L-indices of all the power system buses simultaneously. The method can also be effectively used to determining local and global stability margin for further improvement measures.

Stability of Dimeric Interface in Banana Lectin: Insight from Molecular Dynamics Simulations

Banana lectin (Banlec) is a homodimeric non-glycosylated protein. It exhibits the b-prism I structure. High-temperature molecular dynamics simulations have been utilized to monitor and understand early stages of thermally induced unfolding of Banlec. The present study elucidates the behavior of the dimeric protein at four different temperatures and compares the structural and conformational changes to that of the minimized crystal structure. The process of unfolding was monitored by following the radius of gyration, the rms deviation of each residue, change in relative solvent accessibility and the pattern of inter- and intra-subunit interactions. The overall study demonstrates that the Banlec dimer is a highly stable structure, and the stability is mostly contributed by interfacial interactions. It maintains its overall conformation during high-temperature (400–500 K) simulations, with only the unstructured loop regions acquiring greater momentum under such condition. Nevertheless, at still higher temperatures (600 K) the tertiary structure is gradually lost which later extends to loss of secondary structural elements. The pattern of hydrogen bonding within the subunit and at the interface across different stages has been analyzed and has provided rationale for its intrinsic high stability.

Response And Stability Of A Stochastic Beam-Column Using Stochastic Fem

A beam-column resting on continuous Winkler foundation and discrete elastic supports is considered. The beam-column is of variable cross-section and the variation of sectional properties along the axis of the beam-column is deterministic. Young's modulus, mass per unit length and distributed axial loadings of the beam-column have a stochastic distribution. The foundation stiffness coefficient of the Winkler model, the stiffnesses of discrete elastic supports, stiffnesses of end springs and the end thrust, are all considered as random parameters. The material property fluctuations and distributed axial loadings are considered to constitute independent, one-dimension uni-variate homogeneous real stochastic fields in space. The foundation stiffness coefficient, stiffnesses of the discrete elastic supports, stiffnesses of end springs and the end thrust are considered to constitute independent random variables. Static response, free vibration and stability behaviour of the beam-column are studied. Hamilton's principle is used to formulate the problem using stochastic FEM. Sensitivity vectors of the response and stability parameters are evaluated. Using these statistics of free vibration frequencies, mode shapes, buckling parameters, etc., are evaluated. A numerical example is given.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

The Linear Tripeptide L-Alanylglyeyl-L- alanine

L-Alanylglycyl-L-alanine, C8H15N3O4, exists as zwitter-ion in the crystal with the N terminus protonated and the C terminus in an ionized form, Both the peptide units are in trans configurations and deviate significantly from planarity. Backbone torsion angles are psi(1)=172.7(2), omega(1)=-178.2(2), phi(2)=91.7(2), phi(2)=-151.9(2), omega(2)=-176.9(2), phi(3)=-71.3(2), phi(31)=-7.0(3) and psi(32) 172.4(2)degrees. The protonated NH3+ group forms three hydrogen bonds with atoms of symmetry-related molecules.

Linear filtering in DCT IV/DST IV and MDCT/MDST domain

In this paper, expressions for convolution multiplication properties of DCT IV and DST IV are derived starting from equivalent DFT representations. Using these expressions methods for implementing linear filtering through block convolution in the DCT IV and DST IV domain are proposed. Techniques developed for DCT IV and DST IV are further extended to MDCT and MDST where the filter implementation is near exact for symmetric filters and approximate for non-symmetric filters. No additional overlapping is required for implementing the symmetric filtering in the MDCT domain and hence the proposed algorithm is computationally competitive with DFT based systems. Moreover, inherent 50% overlap between the adjacent frames used for MDCT/MDST domain reduces the blocking artifacts due to block processing or quantization. The techniques are computationally efficient for symmetric filters and provides a new alternative to DFT based convolution.

Stability of pargasite during ultrahigh-temperature metamorphism:A consequence of titanium and REE partitioning

Orthopyroxene-clinopyroxene-plagioclase needles and symplectite along the cleavage planes and grain boundaries of fluorine-bearing titanian-ferroan pargasite from the Highland Complex, Sri Lanka, are interpreted as evidence for dehydration melting at ultrahigh-temperature conditions. High Ti (up to 0.4 pfu) and F (XF up to 0.56) content in pargasite extends its stability to higher temperatures, and the composition indicates the dehydration melting reaction may take place at ultrahigh-temperatures (~950 °C) at a pressure around 10 kbar, close to peak metamorphic conditions. The increase of Ti content close to the grain boundaries and cleavage planes in pargasite indicates titanium partitioning from the melt during dehydration melting enhanced the stability of the mineral toward ultrahigh-temperature conditions. The REE content in the pargasite shows a similar behavior to that of titanium. The cores with no breakdown assemblage consist of low and flat REE concentrations with respect to the high and Eu-depleted rim. Clinopyroxene in symplectite and needle-shaped lamellae within the pargasite porphyroblasts have similar REE patterns with slightly low-concentrations relative to that of pargasite. In the breakdown assemblage, LREEs are partitioned mainly into plagioclase while the HREEs are partitioned into orthopyroxene. The REE enrichment in the pargasite rims signals their relative partitioning between pargasite rims and melt. Modeling of the partitioning of Ti and REEs associated with pargasite breakdown demonstrates that its stability is greatly enhanced at UHT conditions. This investigation implies that the stability of hydrous minerals such as amphibole can be extended to UHT conditions, and expands our knowledge of metamorphism in the lower crust.

Nonlinear mechanical property of tracheal cartilage: A theoretical and experimental study

Background: Despite being the stiffest airway of the bronchial tree, the trachea undergoes significant deformation due to intrathoracic pressure during breathing. The mechanical properties of the trachea affect the flow in the airway and may contribute to the biological function of the lung. Method: A Fung-type strain energy density function was used to investigate the nonlinear mechanical behavior of tracheal cartilage. A bending test on pig tracheal cartilage was performed and a mathematical model for analyzing the deformation of tracheal cartilage was developed. The constants included in the strain energy density function were determined by fitting the experimental data. Result: The experimental data show that tracheal cartilage is a nonlinear material displaying higher strength in compression than in tension. When the compression forces varied from -0.02 to -0.03 N and from -0.03 to -0.04 N, the deformation ratios were 11.03±2.18% and 7.27±1.59%, respectively. Both were much smaller than the deformation ratios (20.01±4.49%) under tension forces of 0.02 to 0.01 N. The Fung-type strain energy density function can capture this nonlinear behavior very well, whilst the linear stress-strain relation cannot. It underestimates the stability of trachea by exaggerating the displacement in compression. This study may improve our understanding of the nonlinear behavior of tracheal cartilage and it may be useful for the future study on tracheal collapse behavior under physiological and pathological conditions.

The impact of wall shear stress and pressure drop on the stability of the atherosclerotic plaque

Rupture of vulnerable atheromatous plaque in the carotid and coronary arteries often leads to stroke and heart attack respectively. The mechanism of blood flow and plaque rupture in stenotic arteries is still not fully understood. A three dimensional rigid wall model was solved under steady state conditions and unsteady conditions by assuming a time-varying inlet velocity profile to investigate the relative importance of axial forces and pressure drops in arteries with asymmetric stenosis. Flow-structure interactions were investigated for the same geometry and the results were compared with those retrieved with the corresponding 2D cross-section structural models. The Navier-Stokes equations were used as the governing equations for the fluid. The tube wall was assumed hyperelastic, homogeneous, isotropic and incompressible. The analysis showed that the three dimensional behavior of velocity, pressure and wall shear stress is in general very different from that predicted by cross-section models. Pressure drop across the stenosis was found to be much higher than shear stress. Therefore, pressure may be the more important mechanical trigger for plaque rupture other than shear stress, although shear stress is closely related to plaque formation and progression.

Does calcium deposition play a role in the stability of atheroma? Location may be the key

Background: Rupture of vulnerable atheromatous plaque in the carotid and coronary arteries often leads to stroke and heart attack respectively. The role of calcium deposition and its contribution to plaque stability is controversial. This study uses both an idealized and a patient-specific model to evaluate the effect of a calcium deposit on the stress distribution within an atheromatous plaque. Methods: Using a finite-element method, structural analysis was performed on an idealized plaque model and the location of a calcium deposit within it was varied. In addition to the idealized model, in vivo high-resolution MR imaging was performed on 3 patients with carotid atheroma and stress distributions were generated. The individual plaques were chosen as they had calcium at varying locations with respect to the lumen and the fibrous cap. Results: The predicted maximum stress was increased by 47.5% when the calcium deposit was located in the thin fibrous cap in the model when compared with that in a model without a deposit. The result of adding a calcium deposit either to the lipid core or remote from the lumen resulted in almost no increase in maximal stress. Conclusion: Calcification at the thin fibrous cap may result in high stress concentrations, ultimately increasing the risk of plaque rupture. Assessing the location of calcification may, in the future, aid in the risk stratification of patients with carotid stenosis.

How critical is fibrous cap thickness to carotid plaque stability? A flow-plaque interaction model

Background and Purpose Acute cerebral ischemic events are associated with rupture of vulnerable carotid atheroma and subsequent thrombosis. Factors such as luminal stenosis and fibrous cap thickness have been thought to be important risk factors for plaque rupture. We used a flow-structure interaction model to simulate the interaction between blood flow and atheromatous plaque to evaluate the effect of the degree of luminal stenosis and fibrous cap thickness on plaque vulnerability. Methods A coupled nonlinear time-dependent model with a flow-plaque interaction simulation was used to perform flow and stress/strain analysis in a stenotic carotid artery model. The stress distribution within the plaque and the flow conditions within the vessel were calculated for every case when varying the fibrous cap thickness from 0.1 to 2 mm and the degree of luminal stenosis from 10% to 95%. A rupture stress of 300 kPa was chosen to indicate a high risk of plaque rupture. A 1-sample t test was used to compare plaque stresses with the rupture stress. Results High stress concentrations were found in the plaques in arteries with >70% degree of stenosis. Plaque stresses in arteries with 30% to 70% stenosis increased exponentially as fibrous cap thickness decreased. A decrease of fibrous cap thickness from 0.4 to 0.2 mm resulted in an increase of plaque stress from 141 to 409 kPa in a 40% degree stenotic artery. Conclusions There is an increase in plaque stress in arteries with a thin fibrous cap. The presence of a moderate carotid stenosis (30% to 70%) with a thin fibrous cap indicates a high risk for plaque rupture. Patients in the future may be risk stratified by measuring both fibrous cap thickness and luminal stenosis.

Thermal Stability of Polystyrene Peroxide

It has been observed that poly(styrene peroxide) with a high molecular weight is thermally less stable than the same polymer with a low molecular weight. This has been explained as being due to the strain on the O-O bond due to the greater polymer chain length.

Liquid Chromatography-Mass Spectrometry in Studies of Drug Metabolism and Permeability

Poor pharmacokinetics is one of the reasons for the withdrawal of drug candidates from clinical trials. There is an urgent need for investigating in vitro ADME (absorption, distribution, metabolism and excretion) properties and recognising unsuitable drug candidates as early as possible in the drug development process. Current throughput of in vitro ADME profiling is insufficient because effective new synthesis techniques, such as drug design in silico and combinatorial synthesis, have vastly increased the number of drug candidates. Assay technologies for larger sets of compounds than are currently feasible are critically needed. The first part of this work focused on the evaluation of cocktail strategy in studies of drug permeability and metabolic stability. N-in-one liquid chromatography-tandem mass spectrometry (LC/MS/MS) methods were developed and validated for the multiple component analysis of samples in cocktail experiments. Together, cocktail dosing and LC/MS/MS were found to form an effective tool for increasing throughput. First, cocktail dosing, i.e. the use of a mixture of many test compounds, was applied in permeability experiments with Caco-2 cell culture, which is a widely used in vitro model for small intestinal absorption. A cocktail of 7-10 reference compounds was successfully evaluated for standardization and routine testing of the performance of Caco-2 cell cultures. Secondly, cocktail strategy was used in metabolic stability studies of drugs with UGT isoenzymes, which are one of the most important phase II drug metabolizing enzymes. The study confirmed that the determination of intrinsic clearance (Clint) as a cocktail of seven substrates is possible. The LC/MS/MS methods that were developed were fast and reliable for the quantitative analysis of a heterogenous set of drugs from Caco-2 permeability experiments and the set of glucuronides from in vitro stability experiments. The performance of a new ionization technique, atmospheric pressure photoionization (APPI), was evaluated through comparison with electrospray ionization (ESI), where both techniques were used for the analysis of Caco-2 samples. Like ESI, also APPI proved to be a reliable technique for the analysis of Caco-2 samples and even more flexible than ESI because of the wider dynamic linear range. The second part of the experimental study focused on metabolite profiling. Different mass spectrometric instruments and commercially available software tools were investigated for profiling metabolites in urine and hepatocyte samples. All the instruments tested (triple quadrupole, quadrupole time-of-flight, ion trap) exhibited some good and some bad features in searching for and identifying of expected and non-expected metabolites. Although, current profiling software is helpful, it is still insufficient. Thus a time-consuming largely manual approach is still required for metabolite profiling from complex biological matrices.

Stability of Fe3+ -VO defect pairs in polycrystalline Pb(Ti,Zr)O3

The intensity of the EPR signal with g = 5.985 arising from a ferric ion â oxygen vacancy defect pair (Fe3+ â VO) in PbTiO3, varies with the extent of PbO nonstoichiometry at constant Fe3+ content due to an increased oxygen vacancy concentration. In PZT solid solutions, the signal intensity decreases with an increase in Zr. A lower intensity is also noticed for Fe3+ â VO signals in PbZrO3. This behaviour is explained on the basis of PbO nonstoichiometry arising from independent Pb- and O-vacancies as well as the randomly distributed crystallographic shear (CS) plane defects. The contribution to PbO nonstoichiometry from CS planes is larger in high zirconium compositions of PZT.