Performance of the generalized delta rule in structural damage detection

The paper examines the suitability of the generalized data rule in training artificial neural networks (ANN) for damage identification in structures. Several multilayer perceptron architectures are investigated for a typical bridge truss structure with simulated damage stares generated randomly. The training samples have been generated in terms of measurable structural parameters (displacements and strains) at suitable selected locations in the structure. Issues related to the performance of the network with reference to hidden layers and hidden. neurons are examined. Some heuristics are proposed for the design of neural networks for damage identification in structures. These are further supported by an investigation conducted on five other bridge truss configurations.

On the problem of spurious patterns in neural associative memory models

The problem of spurious patterns in neural associative memory models is discussed, Some suggestions to solve this problem from the literature are reviewed and their inadequacies are pointed out, A solution based on the notion of neural self-interaction with a suitably chosen magnitude is presented for the Hebb learning rule. For an optimal learning rule based on linear programming, asymmetric dilution of synaptic connections is presented as another solution to the problem of spurious patterns, With varying percentages of asymmetric dilution it is demonstrated numerically that this optimal learning rule leads to near total suppression of spurious patterns. For practical usage of neural associative memory networks a combination of the two solutions with the optimal learning rule is recommended to be the best proposition.

The Boltzmann collision integrals for a combination of Maxwellians

The gain and loss integrals in the Boltzmann equation for a rigid sphere gas are evaluated in closed form for a distribution which can be expressed as a linear combination of Maxwellians. Application to the Mott-Smith bimodal distribution shows that the gain is also bimodal, but the two modes in the gain are less pronounced than in the distribution. Implications of these results for simple collision models in non-equilibrium flow are discussed.

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

Rule-based modelling of iron homeostasis in tuberculosis

To establish itself within the host system, Mycobacterium tuberculosis (Mtb) has formulated various means of attacking the host system. One such crucial strategy is the exploitation of the iron resources of the host system. Obtaining and maintaining the required concentration of iron becomes a matter of contest between the host and the pathogen, both trying to achieve this through complex molecular networks. The extent of complexity makes it important to obtain a systems perspective of the interplay between the host and the pathogen with respect to iron homeostasis. We have reconstructed a systems model comprising 92 components and 85 protein-protein or protein-metabolite interactions, which have been captured as a set of 194 rules. Apart from the interactions, these rules also account for protein synthesis and decay, RBC circulation and bacterial production and death rates. We have used a rule-based modelling approach, Kappa, to simulate the system separately under infection and non-infection conditions. Various perturbations including knock-outs and dual perturbation were also carried out to monitor the behavioral change of important proteins and metabolites. From this, key components as well as the required controlling factors in the model that are critical for maintaining iron homeostasis were identified. The model is able to re-establish the importance of iron-dependent regulator (ideR) in Mtb and transferrin (Tf) in the host. Perturbations, where iron storage is increased, appear to enhance nutritional immunity and the analysis indicates how they can be harmful for the host. Instead, decreasing the rate of iron uptake by Tf may prove to be helpful. Simulation and perturbation studies help in identifying Tf as a possible drug target. Regulating the mycobactin (myB) concentration was also identified as a possible strategy to control bacterial growth. The simulations thus provide significant insight into iron homeostasis and also for identifying possible drug targets for tuberculosis.

Authors reply to "On uniqueness, transfer and combination of acoustic sources in one-dimensional systems"

The use of electroacoustic analogies suggests that a source of acoustical energy (such as an engine, compressor, blower, turbine, loudspeaker, etc.) can be characterized by an acoustic source pressure ps and internal source impedance Zs, analogous to the open-circuit voltage and internal impedance of an electrical source. The present paper shows analytically that the source characteristics evaluated by means of the indirect methods are independent of the loads selected; that is, the evaluated values of ps and Zs are unique, and that the results of the different methods (including the direct method) are identical. In addition, general relations have been derived here for the transfer of source characteristics from one station to another station across one or more acoustical elements, and also for combining several sources into a single equivalent source. Finally, all the conclusions are extended to the case of a uniformly moving medium, incorporating the convective as well as dissipative effects of the mean flow.

Association rule mining activity : A general formalism

Mining association rules from a large collection of databases is based on two main tasks. One is generation of large itemsets; and the other is finding associations between the discovered large itemsets. Existing formalism for association rules are based on a single transaction database which is not sufficient to describe the association rules based on multiple database environment. In this paper, we give a general characterization of association rules and also give a framework for knowledge-based mining of multiple databases for association rules.

Curcumin-Arteether Combination Therapy of Plasmodium berghei-Infected Mice Prevents Recrudescence Through Immunomodulation

Earlier studies in this laboratory have shown the potential of artemisinin-curcumin combination therapy in experimental malaria. In a parasite recrudescence model in mice infected with Plasmodium berghei (ANKA), a single dose of alpha, beta-arteether (ART) with three oral doses of curcumin prevented recrudescence, providing almost 95% protection. The parasites were completely cleared in blood with ART-alone (AE) or ART+curcumin (AC) treatments in the short-term, although the clearance was faster in the latter case involving increased ROS generation. But, parasites in liver and spleen were not cleared in AE or AC treatments, perhaps, serving as a reservoir for recrudescence. Parasitemia in blood reached up to 60% in AE-treated mice during the recrudescence phase, leading to death of animals. A transient increase of up to 2-3% parasitemia was observed in AC-treatment, leading to protection and reversal of splenomegaly. A striking increase in spleen mRNA levels for TLR2, IL-10 and IgG-subclass antibodies but a decrease in those for INF gamma and IL-12 was observed in AC-treatment. There was a striking increase in IL-10 and IgG subclass antibody levels but a decrease in INF gamma levels in sera leading to protection against recrudescence. AC-treatment failed to protect against recrudescence in TLR2(-/-) and IL-10(-/-) animals. IL-10 injection to AE-treated wild type mice and AC-treated TLR22/2 mice was able to prolong survival. Blood from the recrudescence phase in AE-treatment, but not from AC-treatment, was able to reinfect and kill naive animals. Sera from the recrudescence phase of AC-treated animals reacted with several parasite proteins compared to that from AE-treated animals. It is proposed that activation of TLR2-mediated innate immune response leading to enhanced IL-10 production and generation of anti-parasite antibodies contribute to protective immunity in AC-treated mice. These results indicate a potential for curcumin-based combination therapy to be tested for prevention of recrudescence in falciparum and relapse in vivax malaria.

Artemisinin-based combination with curcumin adds a new dimension to malaria therapy

Malaria afflicts 300 million people worldwide, with over a million deaths every year. With no immediate prospect of a vaccine against the disease, drugs are the only choice to treat it. Unfortunately, the parasite has become resistant to most antimalarials, restricting the option to use artemisinins (ARTs) for effective cure. With the use of ARTs as the front-line antimalarials, reports are already available on the possible resistance development to these drugs as well. Therefore, it has become necessary to use ART-based combination therapies to delay emergence of resistance. It is also necessary to discover new pharmacophores to eventually replace ART. Studies in our laboratory have shown that curcumin not only synergizes with ART as an antimalarial to kill the parasite, but is also uniquely able to prime the immune system to protect against parasite recrudescence in the animal model. The results indicate a potential for the use of ART curcumin combination against recrudescence/relapse in falciparum and vivax malaria. In addition, studies have also suggested the use of curcumin as an adjunct therapy against cerebral malaria. In this review we have attempted to highlight these aspects as well as the studies directed to discover new pharmacophores as potential replacements for ART.

Structure and mechanical properties of Ti-C films deposited using combination of pulsed DC and normal DC magnetron co-sputtering

Titanium-carbon (Ti-C) thin films of different compositions were prepared by a combination of pulsed DC (for Ti target) and normal DC (for graphite target) magnetron co-sputtering on oxidized silicon and fused quartz substrates. At 33.7 at.% of C content, pure hcp Ti transforms into fcc-TiC with a preferential orientation of (2 2 0) along with (1 1 1) and (2 0 0). A clear transformation in the preferential orientation from (2 2 0) to (1 1 1) has been observed when the C content was increased to 56 at.%. At 62.5 at.% of C, TiC precipitates in an amorphous carbon matrix whereas further increase in C leads to X-ray amorphous films. The cross-sectional scanning electron microscope images reveal that the films with low carbon content consists of columnar grains, whereas, randomly oriented grains are in an amorphous carbon matrix at higher carbon content. A dramatic variation was observed in the mechanical properties such as hardness, H, from 30 to 1 GPa and in modulus, E, from 255 to 25 GPa with varying carbon content in the films. Resistance to plastic deformation parameter was observed as 0.417 for films containing 62.5 at.% of C. Nanoscratch test reveals that the films are highly scratch resistant with a coefficient of friction ranging from 0.15 to 0.04. (C) 2012 Elsevier B.V. All rights reserved.

Silicon surface texturing with a combination of potassium hydroxide and tetra-methyl ammonium hydroxide etching

A two step silicon surface texturing, consisting of potassium hydroxide (KOH) etching followed by tetra-methyl ammonium hydroxide etching is presented. This combined texturing results in 13.8% reflectivity at 600 nm compared to 16.1% reflectivity for KOH etching due to the modification of microstructure of etched pyramids. This combined etching also results in significantly lower flat-band voltage (V-FB) (-0.19V compared to -1.3 V) and interface trap density (D-it) (2.13 x 10(12) cm(-2) eV(-1) compared to 3.2 x 10(12) cm(-2) eV(-1)). (C) 2013 American Institute of Physics. http://dx.doi.org/10.1063/1.4776733]

Combination of similarity measures for time series classification using genetic algorithms

Time series classification deals with the problem of classification of data that is multivariate in nature. This means that one or more of the attributes is in the form of a sequence. The notion of similarity or distance, used in time series data, is significant and affects the accuracy, time, and space complexity of the classification algorithm. There exist numerous similarity measures for time series data, but each of them has its own disadvantages. Instead of relying upon a single similarity measure, our aim is to find the near optimal solution to the classification problem by combining different similarity measures. In this work, we use genetic algorithms to combine the similarity measures so as to get the best performance. The weightage given to different similarity measures evolves over a number of generations so as to get the best combination. We test our approach on a number of benchmark time series datasets and present promising results.

A Calcium-Dependent Plasticity Rule for HCN Channels Maintains Activity Homeostasis and Stable Synaptic Learning

Theoretical and computational frameworks for synaptic plasticity and learning have a long and cherished history, with few parallels within the well-established literature for plasticity of voltage-gated ion channels. In this study, we derive rules for plasticity in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and assess the synergy between synaptic and HCN channel plasticity in establishing stability during synaptic learning. To do this, we employ a conductance-based model for the hippocampal pyramidal neuron, and incorporate synaptic plasticity through the well-established Bienenstock-Cooper-Munro (BCM)-like rule for synaptic plasticity, wherein the direction and strength of the plasticity is dependent on the concentration of calcium influx. Under this framework, we derive a rule for HCN channel plasticity to establish homeostasis in synaptically-driven firing rate, and incorporate such plasticity into our model. In demonstrating that this rule for HCN channel plasticity helps maintain firing rate homeostasis after bidirectional synaptic plasticity, we observe a linear relationship between synaptic plasticity and HCN channel plasticity for maintaining firing rate homeostasis. Motivated by this linear relationship, we derive a calcium-dependent rule for HCN-channel plasticity, and demonstrate that firing rate homeostasis is maintained in the face of synaptic plasticity when moderate and high levels of cytosolic calcium influx induced depression and potentiation of the HCN-channel conductance, respectively. Additionally, we show that such synergy between synaptic and HCN-channel plasticity enhances the stability of synaptic learning through metaplasticity in the BCM-like synaptic plasticity profile. Finally, we demonstrate that the synergistic interaction between synaptic and HCN-channel plasticity preserves robustness of information transfer across the neuron under a rate-coding schema. Our results establish specific physiological roles for experimentally observed plasticity in HCN channels accompanying synaptic plasticity in hippocampal neurons, and uncover potential links between HCN-channel plasticity and calcium influx, dynamic gain control and stable synaptic learning.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.