A Simple Multiple pulsewidth Modulated AC Multiple Chopper

A simple multiple pulsewidth modulated (MPWM) ac chopper using power transistors for 3-¿ power control is discussed. 120° chopping period is used for main transistors so that the circuit can accommodate resistive and lagging or leading power factor loads. Only 1-¿ sensing is used for 3-¿ control. An alternate economical power and control schemes for 3-¿ MPWM ac choppers suitable only for resistive loads is also suggested. The experimental results for 12 choppings per cycle are given.

Damage assessment of structures with uncertainty by using mode-shape curvatures and fuzzy logic

Uncertainties associated with the structural model and measured vibration data may lead to unreliable damage detection. In this paper, we show that geometric and measurement uncertainty cause considerable problem in damage assessment which can be alleviated by using a fuzzy logic-based approach for damage detection. Curvature damage factor (CDF) of a tapered cantilever beam are used as damage indicators. Monte Carlo simulation (MCS) is used to study the changes in the damage indicator due to uncertainty in the geometric properties of the beam. Variation in these CDF measures due to randomness in structural parameter, further contaminated with measurement noise, are used for developing and testing a fuzzy logic system (FLS). Results show that the method correctly identifies both single and multiple damages in the structure. For example, the FLS detects damage with an average accuracy of about 95 percent in a beam having geometric uncertainty of 1 percent COV and measurement noise of 10 percent in single damage scenario. For multiple damage case, the FLS identifies damages in the beam with an average accuracy of about 94 percent in the presence of above mentioned uncertainties. The paper brings together the disparate areas of probabilistic analysis and fuzzy logic to address uncertainty in structural damage detection.

Cross Talk between Receptor Guanylyl Cyclase C and c-src Tyrosine Kinase Regulates Colon Cancer Cell Cytostasis

Increased activation of c-src seen in colorectal cancer is an indicator of a poor clinical prognosis, suggesting that identification of downstream effectors of c-src may lead to new avenues of therapy. Guanylyl cyclase C (GC-C) is a receptor for the gastrointestinal hormones guanylin and uroguanylin and the bacterial heat-stable enterotoxin. Though activation of GC-C by its ligands elevates intracellular cyclic GMP (cGMP) levels and inhibits cell proliferation, its persistent expression in colorectal carcinomas and occult metastases makes it a marker for malignancy. We show here that GC-C is a substrate for inhibitory phosphorylation by c-src, resulting in reduced ligand-mediated cGMP production. Consequently, active c-src in colonic cells can overcome GC-C-mediated control of the cell cycle. Furthermore, docking of the c-src SH2 domain to phosphorylated GC-C results in colocalization and further activation of c-src. We therefore propose a novel feed-forward mechanism of activation of c-src that is induced by cross talk between a receptor GC and a tyrosine kinase. Our findings have important implications in understanding the molecular mechanisms involved in the progression and treatment of colorectal cancer.

Sustainable bioenergy for India: Technical, economic and policy analysis

India's energy challenges are multi-pronged. They are manifested through growing demand for modern energy carriers, a fossil fuel dominated energy system facing a severe resource crunch, the need for creating access to quality energy for the large section of deprived population, vulnerable energy security, local and global pollution regimes and the need for sustaining economic development. Renewable energy is considered as one of the most promising alternatives. Recognizing this potential, India has been implementing one of the largest renewable energy programmes in the world. Among the renewable energy technologies. bioenergy has a large diverse portfolio including efficient biomass stoves, biogas, biomass combustion and gasification and process heat and liquid fuels. India has also formulated and implemented a number of innovative policies and programmes to promote bioenergy technologies. However, according to some preliminary studies, the success rate is marginal compared to the potential available. This limited success is a clear indicator of the need for a serious reassessment of the bioenergy programme. Further, a realization of the need for adopting a sustainable energy path to address the above challenges will be the guiding force in this reassessment. In this paper an attempt is made to consider the potential of bioenergy to meet the rural energy needs: (I) biomass combustion and gasification for electricity; (2) biomethanation for cooking energy (gas) and electricity; and (3) efficient wood-burning devices for cooking. The paper focuses on analysing the effectiveness of bioenergy in creating this rural energy access and its sustainability in the long run through assessing: the demand for bioenergy and potential that could be created; technologies, status of commercialization and technology transfer and dissemination in India; economic and environmental performance and impacts: bioenergy policies, regulatory measures and barrier analysis. The whole assessment aims at presenting bioenergy as an integral part of a sustainable energy strategy for India. The results show that bioenergy technology (BET) alternatives compare favourably with the conventional ones. The cost comparisons show that the unit costs of BET alternatives are in the range of 15-187% of the conventional alternatives. The climate change benefits in terms of carbon emission reductions are to the tune of 110 T C per year provided the available potential of BETs are utilized.

Spatial patterning of the distribution of Ca-2+ in Dictyostelium discoideum

We have shown previously that the Ca2+-specific fluorescent dyes chlortetracycline (CTC) and indo-1/AM can be used to distinguish between prestalk and prespore cells in Dictyostelium discoideum at a very early stage. In the present study, pre- and post-aggregative amoebae of Dictyostelium discoideum were labelled with CTC or indo-1 and their fluorescence monitored after being drawn into a fine glass capillary. The cells rapidly form two zones of Ca2+-CTC or Ca2+-indo-1 fluorescence. Anterior (air side) cells display a high level of fluorescence; the level drops in the middle portion of the capillary and rises again to a lesser extent in the posteriormost cells (oil side). When bounded by air on both sides, the cells display high fluorescence at both ends. When oil is present at both ends of the capillary, there is little fluorescence except for small regions at the ends. These outcomes are evident within a couple of minutes of the start of the experiment and the fluorescence pattern intensifies over the course of time. By using the indicator neutral red, as well as with CTC and indo-1, we show that a band displaying strong fluorescence moves away from the anterior end before stabilizing at the anterior-posterior boundary. We discuss our findings in relation to the role of Ca2+ in cell-type differentiation in Dictyostelium discoideum.

Time and Energy Complexity of Distributed Computation of a Class of Functions in Wireless Sensor Networks

We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

Cerimetry in nonaqueous media - Oxidation of ascorbic acid

The reaction between ascorbic acid and ammonium hexa nitrato cerate was studied potentiometrically in the mixed solvent glacial acetic acid acetonitrile medium. It was found that one mole of ascorbic acid consumes four equivalents of cerate in non-aqueous medium. This reaction can be made use of to estimate potentiometrically ascorbic acid with ammonium nitrato cerate in non-aqueous media, using either glass or antimony as reference electrode and platinum as indicator electrode.

Potentiometric titrations in nonaqueous cerimetry

Potassium iodide and hydroquinone can be estimated potentiometrically in nonaqueous medium using ammonium nitrato cerate as oxidant. A platinum indicator electrode coupled with either a glass electrode or an antimony electrode as reference electrode, can be used in nonaqueous medium satisfactorily, for following the potentiometric titration. Direct potentiometric titration of xanthate with ammonium nitrato cerate in nonaqueous medium yields slightly lower values than the actual values in presence of platinum indicator electrode.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Impedance parameters and the state-of-charge. III. Zinc-manganese dioxide and magnesium-manganese dioxide dry batteries

The problem of non-destructive determination of the state-of-charge of zinc- and magnesium-manganese dioxide dry batteries is examined experimentally from the viewpoint of internal impedance and open-circuit voltage at equilibrium. It is shown that the impedance is mainly charge-transfer controlled at relatively high states-of-charge and progressively changes over to diffusion control as the state-of-charge decreases in the case of zinc-manganese dioxide dry batteries. On the other hand, the impedance is mainly diffusion controlled for undischarged batteries but becomes charge-transfer controlled as soon as there is some discharge in the case of magnesium-manganese dioxide batteries. It is concluded that the determination of state-of-charge is not possible for both types of batteries by the measurement of impedance parameters due to film-induced fluctuations of these parameters. The measurement of open-circuit voltage at equilibrium can be used as a state-of-charge indicator for Zn-MnO2 batteries but not for Mg-MnO2 batteries.

Analysis of grid connected induction generators driven by hydro/wind turbines under realistic system constraints

Results of an investigation dealing with the behaviour of grid-connected induction generators (GCIGs) driven by typical prime movers such as mini-hydro/wind turbines are presented. Certain practical operational problems of such systems are identified. Analytical techniques are developed to study the behavior of such systems. The system consists of the induction generator (IG) feeding a 11 kV grid through a step-up transformer and a transmission line. Terminal capacitors to compensate for the lagging VAr are included in the study. Computer simulation was carried out to predict the system performance at the given input power from the turbine. Effects of variations in grid voltage, frequency, input power, and terminal capacitance on the machine and system performance are studied. An analysis of self-excitation conditions on disconnection of supply was carried out. The behavior of a 220 kW hydel system and 55/11 kW and 22 kW wind driven system corresponding to actual field conditions is discussed

Effect of microstructure and hardness on the grinding abrasive wear resistance of a ball bearing steel

Grinding media wear appears to be non-linear with the time of grinding in a laboratory-scale ball mill. The kinetics of wear can be expressed as a power law of the type w=atb, where the numerical constant a represents wear of a particular microstructure at time t = 1 min and b is the wear exponent which is independent of the particle size prevailing inside a ball mill at any instant of time of grinding. The wear exponent appears to be an indicator of the cutting wear mechanism in dry grinding: a plot of the inverse of the normalised wear exponent (Image ) versusHs (where Hs is the worn surface hardness of the media) yields a curve similar to that of a wear resistance plot obtained in the case of two-body sliding abrasive wear. This method of evaluating the cutting wear resistance of media is demonstrated by employing 15 different microstructures of AISI-SAE 52100 steel balls in dry grinding of quartz in a laboratory-scale ball mill.

A new Fuzzy-LOGIC based Model for Chlorophyll-a in Pulicat Lagoon, India

Coastal lagoons are complex ecosystems exhibiting a high degree of non-linearity in the distribution and exchange of nutrients dissolved in the water column due to their spatio-temporal characteristics. This factor has a direct influence on the concentrations of chlorophyll-a, an indicator of the primary productivity in the water bodies as lakes and lagoons. Moreover the seasonal variability in the characteristics of large-scale basins further contributes to the uncertainties in the data on the physico-chemical and biological characteristics of the lagoons. Considering the above, modelling the distributions of the nutrients with respect to the chlorophyll-concentrations, hence requires an effective approach which will appropriately account for the non-linearity of the ecosystem as well as the uncertainties in the available data. In the present investigation, fuzzy logic was used to develop a new model of the primary production for Pulicat lagoon, Southeast coast of India. Multiple regression analysis revealed that the concentrations of chlorophyll-a in the lagoon was highly influenced by the dissolved concentrations of nitrate, nitrites and phosphorous to different extents over different seasons and years. A high degree of agreement was obtained between the actual field values and those predicted by the new fuzzy model (d = 0.881 to 0.788) for the years 2005 and 2006, illustrating the efficiency of the model in predicting the values of chlorophyll-a in the lagoon.

Study of voltage collapse at converter bus in asynchronous MTDC-AC systems

This paper presents the analysis and study of voltage collapse at any converter bus in an AC system interconnected by multiterminal DC (MTDC) links. The analysis is based on the use of the voltage sensitivity factor (VSF) as a voltage collapse proximity indicator (VCPI). In this paper the VSF is defined as a matrix which is applicable to MTDC systems. The VSF matrix is derived from the basic steady state equations of the converter, control, DC and AC networks. The structure of the matrix enables the derivation of some of the basic properties which are generally applicable. A detailed case study of a four-terminal MTDC system is presented to illustrate the effects of control strategies at the voltage setting terminal (VST) and other terminals. The controls considered are either constant angle, DC voltage, AC voltage, reactive current and reactive power at the VST and constant power or current at the other terminals. The effect of the strength of the AC system (measured by short circuit ratio) on the VSF is investigated. Several interesting and new results are presented. An analytical expression for the self VSF at VST is also derived for some specific cases which help to explain the number of transitions in VSF around the critical values of SCR.