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.

Primary structure of sesbania mosaic virus coat protein: its implications to the assembly and architecture of the virus

Sesbania mosaic virus (SMV) is a plant virus that infects Sesbania grandiflora plants in Andhra Pradesh, India. The amino acid sequence of the coat protein of SMV was determined using purified peptides generated by cleavage with trypsin, chymotrypsin, V8 protease and clostripain. The 230 residues so far determined were compared to the corresponding residues of southern bean mosaic virus (SBMV), the type member of sobemoviruses. The overall identity between the sequences is 61.7%. The amino terminal 64 residues, which constitute an independent domain (R-domain) known to interact with RNA, are conserved to a lower extent (52.5%). Comparison of the positively charged residues in this domain suggests that the RNA-protein interactions are considerably weaker in SMV. The residues that constitute the major domain of the coat protein, the surface domain (S-domain, residues 65-260), are better conserved (66.5%). The positively charged residues of this domain that face the nucleic acid are well conserved. The longest conserved stretch of residues (131-142) corresponds to the loop involved in intersubunit interactions between subunits related by the quasi 3-fold symmetry. A unique cation binding site located on the quasi 3-fold axis contributes to the stability of SMV. These differences are reflected in the increased stability of the SMV coat protein and its ability to be reconstituted with RNA at pH 7.5. A major epitope was identified using monoclonal antibodies to SMV in the segment 201-223 which contains an exposed helix in the capsid structure. This region is highly conserved between SMV and SBMV (70%) suggesting that it could represent the site of an important function such as vector recognition.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

Mathematical model of COREX melter gasifier: Part I. Steady-state model

The COREX melter gasifier is a countercurrent reactor to produce liquid iron. Directly reduced iron (DRI), noncoking coal, and other additives are charged to the melter gasifier at their respective temperatures, and O-2 is blown through the tuyeres. Functionally, a melter gasifier is divided into three zones: a moving bed, fluidized bed, and free board. A model has been developed for the moving bed, where the tuyere region is two-dimensional (2-D) and the rest is one-dimensional (1-D). It is based on multiphase conservation of mass, momentum, and heat. The fluidized bed has been treated as 1-D. Partial equilibrium is calculated for the free board. The calculated temperature of the hot metal, the top gas, and the chemistry of the top gas agree with the reported plant data. The model has been used to study the effects of bed height, injection of impure O-2, coal chemistry, and reactivity on the process performance.

Modeling Architecture-OS interactions using Layered Queuing Network Models

The prevalent virtualization technologies provide QoS support within the software layers of the virtual machine monitor(VMM) or the operating system of the virtual machine(VM). The QoS features are mostly provided as extensions to the existing software used for accessing the I/O device because of which the applications sharing the I/O device experience loss of performance due to crosstalk effects or usable bandwidth. In this paper we examine the NIC sharing effects across VMs on a Xen virtualized server and present an alternate paradigm that improves the shared bandwidth and reduces the crosstalk effect on the VMs. We implement the proposed hardwaresoftware changes in a layered queuing network (LQN) model and use simulation techniques to evaluate the architecture. We find that simple changes in the device architecture and associated system software lead to application throughput improvement of up to 60%. The architecture also enables finer QoS controls at device level and increases the scalability of device sharing across multiple virtual machines. We find that the performance improvement derived using LQN model is comparable to that reported by similar but real implementations.

A Multi-layer Perceptron based Non-linear Mixture Model to estimate class abundance from mixed pixels

Sub-pixel classification is essential for the successful description of many land cover (LC) features with spatial resolution less than the size of the image pixels. A commonly used approach for sub-pixel classification is linear mixture models (LMM). Even though, LMM have shown acceptable results, pragmatically, linear mixtures do not exist. A non-linear mixture model, therefore, may better describe the resultant mixture spectra for endmember (pure pixel) distribution. In this paper, we propose a new methodology for inferring LC fractions by a process called automatic linear-nonlinear mixture model (AL-NLMM). AL-NLMM is a three step process where the endmembers are first derived from an automated algorithm. These endmembers are used by the LMM in the second step that provides abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual proportions are fed to multi-layer perceptron (MLP) architecture as input to train the neurons which further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. AL-NLMM is validated on computer simulated hyperspectral data of 200 bands. Validation of the output showed overall RMSE of 0.0089±0.0022 with LMM and 0.0030±0.0001 with the MLP based AL-NLMM, when compared to actual class proportions indicating that individual class abundances obtained from AL-NLMM are very close to the real observations.

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Predictive distribution modeling for rare Himalayan medicinal plant Berberis aristata DC

Predictive distribution modelling of Berberis aristata DC, a rare threatened plant with high medicinal values has been done with an aim to understand its potential distribution zones in Indian Himalayan region. Bioclimatic and topographic variables were used to develop the distribution model with the help of three different algorithms viz. GeneticAlgorithm for Rule-set Production (GARP), Bioclim and Maximum entroys(MaxEnt). Maximum entropy has predicted wider potential distribution (10.36%) compared to GARP (4.63%) and Bioclim (2.44%). Validation confirms that these outputs are comparable to the present distribution pattern of the B. atistata. This exercise highlights that this species favours Western Himalaya. However, GARP and MaxEnt's prediction of Eastern Himalayan states (i.e. Arunachal Pradesh, Nagaland and Manipur) are also identified as potential occurrence places require further exploration.

Operational experience on a grid connected 100 kWe biomass gasification power plant in Karnataka, India

The paper reports the operational experience from a 100 kWe gasification power plant connected to the grid in Karnataka. Biomass Energy for Rural India (BERI) is a program that implemented gasification based power generation with an installed capacity of 0.88 MWe distributed over three locations to meet the electrical energy needs in the district of Tumkur. The operation of one 100 kWe power plant was found unsatisfactory and not meeting the designed performance. The Indian Institute of Science, Bangalore, the technology developer, took the initiative to ensure the system operation, capacity building and prove the designed performance. The power plant connected to the grid consists of the IISc gasification system which includes reactor, cooling, cleaning system, fuel drier and water treatment system to meet the producer gas quality for an engine. The producer gas is used as a fuel in Cummins India Limited, GTA 855 G model, turbo charged engine and the power output is connected to the grid. The system has operated for over 1000 continuous hours, with only about 70 h of grid outages. The total biomass consumption for 1035 h of operation was 111 t at an average of 107 kg/h. Total energy generated was 80.6 MWh reducing over loot of CO(2) emissions. The overall specific fuel consumption was about 1.36 kg/kWh, amounting to an overall efficiency from biomass to electricity of about 18%. The present operations indicate that a maintenance schedule for the plant can be at the end of 1000 h. The results for another 1000 h of operation by the local team are also presented. (C) 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Robust Observer Design with Application to Fault Detection

A new scheme for robust estimation of the partial state of linear time-invariant multivariable systems is presented, and it is shown how this may be used for the detection of sensor faults in such systems. We consider an observer to be robust if it generates a faithful estimate of the plant state in the face of modelling uncertainty or plant perturbations. Using the Stable Factorization approach we formulate the problem of optimal robust observer design by minimizing an appropriate norm on the estimation error. A logical candidate is the 2-norm, corresponding to an H�¿ optimization problem, for which solutions are readily available. In the special case of a stable plant, the optimal fault diagnosis scheme reduces to an internal model control architecture.

Sensitivity of terrestrial water and energy budgets to CO(2)-physiological forcing: an investigation using an offline land model

Increasing concentrations of atmospheric carbon dioxide (CO(2)) influence climate by suppressing canopy transpiration in addition to its well- known greenhouse gas effect. The decrease in plant transpiration is due to changes in plant physiology (reduced opening of plant stomata). Here, we quantify such changes in water flux for various levels of CO(2) concentrations using the National Center for Atmospheric Research's (NCAR) Community Land Model. We find that photosynthesis saturates after 800 ppmv (parts per million, by volume) in this model. However, unlike photosynthesis, canopy transpiration continues to decline at about 5.1% per 100 ppmv increase in CO(2) levels. We also find that the associated reduction in latent heat flux is primarily compensated by increased sensible heat flux. The continued decline in canopy transpiration and subsequent increase in sensible heat flux at elevated CO(2) levels implies that incremental warming associated with the physiological effect of CO(2) will not abate at higher CO(2) concentrations, indicating important consequences for the global water and carbon cycles from anthropogenic CO(2) emissions.

Performance modeling and architecture exploration of network processors

This paper proposes a Petri net model for a commercial network processor (Intel iXP architecture) which is a multithreaded multiprocessor architecture. We consider and model three different applications viz., IPv4 forwarding, network address translation, and IP security running on IXP 2400/2850. A salient feature of the Petri net model is its ability to model the application, architecture and their interaction in great detail. The model is validated using the Intel proprietary tool (SDK 3.51 for IXP architecture) over a range of configurations. We conduct a detailed performance evaluation, identify the bottleneck resource, and propose a few architectural extensions and evaluate them in detail.

Hybrid and Rogue Kinases Encoded in the Genomes of Model Eukaryotes

The highly modular nature of protein kinases generates diverse functional roles mediated by evolutionary events such as domain recombination, insertion and deletion of domains. Usually domain architecture of a kinase is related to the subfamily to which the kinase catalytic domain belongs. However outlier kinases with unusual domain architectures serve in the expansion of the functional space of the protein kinase family. For example, Src kinases are made-up of SH2 and SH3 domains in addition to the kinase catalytic domain. A kinase which lacks these two domains but retains sequence characteristics within the kinase catalytic domain is an outlier that is likely to have modes of regulation different from classical src kinases. This study defines two types of outlier kinases: hybrids and rogues depending on the nature of domain recombination. Hybrid kinases are those where the catalytic kinase domain belongs to a kinase subfamily but the domain architecture is typical of another kinase subfamily. Rogue kinases are those with kinase catalytic domain characteristic of a kinase subfamily but the domain architecture is typical of neither that subfamily nor any other kinase subfamily. This report provides a consolidated set of such hybrid and rogue kinases gleaned from six eukaryotic genomes-S. cerevisiae, D. melanogaster, C. elegans, M. musculus, T. rubripes and H. sapiens-and discusses their functions. The presence of such kinases necessitates a revisiting of the classification scheme of the protein kinase family using full length sequences apart from classical classification using solely the sequences of kinase catalytic domains. The study of these kinases provides a good insight in engineering signalling pathways for a desired output. Lastly, identification of hybrids and rogues in pathogenic protozoa such as P. falciparum sheds light on possible strategies in host-pathogen interactions.

Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm

The recently developed reference-command tracking version of model predictive static programming (MPSP) is successfully applied to a single-stage closed grinding mill circuit. MPSP is an innovative optimal control technique that combines the philosophies of model predictive control (MPC) and approximate dynamic programming. The performance of the proposed MPSP control technique, which can be viewed as a `new paradigm' under the nonlinear MPC philosophy, is compared to the performance of a standard nonlinear MPC technique applied to the same plant for the same conditions. Results show that the MPSP control technique is more than capable of tracking the desired set-point in the presence of model-plant mismatch, disturbances and measurement noise. The performance of MPSP and nonlinear MPC compare very well, with definite advantages offered by MPSP. The computational speed of MPSP is increased through a sequence of innovations such as the conversion of the dynamic optimization problem to a low-dimensional static optimization problem, the recursive computation of sensitivity matrices and using a closed form expression to update the control. To alleviate the burden on the optimization procedure in standard MPC, the control horizon is normally restricted. However, in the MPSP technique the control horizon is extended to the prediction horizon with a minor increase in the computational time. Furthermore, the MPSP technique generally takes only a couple of iterations to converge, even when input constraints are applied. Therefore, MPSP can be regarded as a potential candidate for online applications of the nonlinear MPC philosophy to real-world industrial process plants. (C) 2014 Elsevier Ltd. All rights reserved.

Evaluation of developmental toxicity and apoptotic induction of the aqueous extract of Millettia pachycarpa using zebrafish as model organism

Extensive and indiscriminate use of synthetic compounds and natural compounds obtained from plant sources have resulted in serious threats to the aquatic ecosystem and human health. Aqueous extract of the root of the plant, Milletia pachycarpa Benth, is currently used for killing fish in the state of Manipur, India. Moreover, this plant is also used as traditional medicine in this region. Although it is widely used in traditional medicine, there is limited information available regarding the adverse effects and mechanism underlying its toxicity. This study examined the effects of exposure to aqueous extract of M. pachycarpa (AEMP) on early embryonic development of zebrafish embryos and mechanisms underlying toxicity. Zebrafish embryos treated with different concentrations of the AEMP produced embryonic lethality and developmental defects. The 96-hr-LC50 of AEMP was found to be 4.276 mu g/mL. Further, multiple developmental abnormalities such as pericardial edema, yolk sac edema, spinal curvature, swim bladder deflation, decreased heart rate, and delayed hatching were also observed in a dose-dependent manner. Zebrafish embryo showing moderate-to-severe developmental defects following AEMP exposure cannot swim properly. Further, this study examined oxidative stress and apoptosis in embryos exposed to AEMP. Enhanced production of ROS and apoptosis was found in brain, trunk, and tail of zebrafish embryos treated with AEMP. Data suggest that oxidative stress and apoptosis are associated with AEMP-induced embryonic lethality and developmental toxicity in zebrafish embryos.