A quantitative imaging-based screen reveals the exocyst as a network hub connecting endocytosis and exocytosis

The coupling of endocytosis and exocytosis underlies fundamental biological processes ranging from fertilization to neuronal activity and cellular polarity. However, the mechanisms governing the spatial organization of endocytosis and exocytosis require clarification. Using a quantitative imaging-based screen in budding yeast, we identified 89 mutants displaying defects in the localization of either one or both pathways. High-resolution single-vesicle tracking revealed that the endocytic and exocytic mutants she4 Delta and bud6 Delta alter post-Golgi vesicle dynamics in opposite ways. The endocytic and exocytic pathways display strong interdependence during polarity establishment while being more independent during polarity maintenance. Systems analysis identified the exocyst complex as a key network hub, rich in genetic interactions with endocytic and exocytic components. Exocyst mutants displayed altered endocytic and post-Golgi vesicle dynamics and interspersed endocytic and exocytic domains compared with control cells. These data are consistent with an important role for the exocyst in coordinating endocytosis and exocytosis.

QoS Performance Analysis of Routing Protocols in Vehicular Ad-hoc Networks

Vehicular Ad-hoc Networks (VANET), is a type of wireless ad-hoc network that aims to provide communication among vehicles. A key characteristic of VANETs is the very high mobility of nodes that result in a frequently changing topology along with the frequent breakage and linkage of the paths among the nodes involved. These characteristics make the Quality of Service (QoS) requirements in VANET a challenging issue. In this paper we characterize the performance available to applications in infrastructureless VANETs in terms of path holding time, path breakage probability and per session throughput as a function of various vehicle densities on road, data traffic rate and number of connections formed among vehicles by making use of table-driven and on-demand routing algorithms. Several QoS constraints in the applications of infrastructureless VANETs are observed in the results obtained.

Influence of fuel hydrogen fraction on syngas fueled SI engine: Fuel thermo-physical property analysis and in-cylinder experimental investigations

Hydrogen, either in pure form or as a gaseous fuel mixture specie enhances the fuel conversion efficiency and reduce emissions in an internal combustion engine. This is due to the reduction in combustion duration attributed to higher laminar flame speeds. Hydrogen is also expected to increase the engine convective heat flux, attributed (directly or indirectly) to parameters like higher adiabatic flame temperature, laminar flame speed, thermal conductivity and diffusivity and lower flame quenching distance. These factors (adversely) affect the thermo-kinematic response and offset some of the benefits. The current work addresses the influence of mixture hydrogen fraction in syngas on the engine energy balance and the thermo-kinematic response for close to stoichiometric operating conditions. Four different bio-derived syngas compositions with fuel calorific value varying from 3.14 MJ/kg to 7.55 MJ/kg and air fuel mixture hydrogen fraction varying from 7.1% to 14.2% by volume are used. The analysis comprises of (a) use of chemical kinetics simulation package CHEMKIN for quantifying the thermo-physical properties (b) 0-D model for engine in-cylinder analysis and (c) in-cylinder investigations on a two-cylinder engine in open loop cooling mode for quantifying the thermo-kinematic response and engine energy balance. With lower adiabatic flame temperature for Syngas, the in-cylinder heat transfer analysis suggests that temperature has little effect in terms of increasing the heat flux. For typical engine like conditions (700 K and 25 bar at CR of 10), the laminar flame speed for syngas exceeds that of methane (55.5 cm/s) beyond mixture hydrogen fraction of 11% and is attributed to the increase in H based radicals. This leads to a reduction in the effective Lewis number and laminar flame thickness, potentially inducing flame instability and cellularity. Use of a thermodynamic model to assess the isolated influence of thermal conductivity and diffusivity on heat flux suggests an increase in the peak heat flux between 2% and 15% for the lowest (0.420 MW/m(2)) and highest (0.480 MW/m(2)) hydrogen containing syngas over methane (0.415 MW/m(2)) fueled operation. Experimental investigations indicate the engine cooling load for syngas fueled engine is higher by about 7% and 12% as compared to methane fueled operation; the losses are seen to increase with increasing mixture hydrogen fraction. Increase in the gas to electricity efficiency is observed from 18% to 24% as the mixture hydrogen fraction increases from 7.1% to 9.5%. Further increase in mixture hydrogen fraction to 14.2% results in the reduction of efficiency to 23%; argued due to the changes in the initial and terminal stages of combustion. On doubling of mixture hydrogen fraction, the flame kernel development and fast burn phase duration decrease by about 7% and 10% respectively and the terminal combustion duration, corresponding to 90%-98% mass burn, increases by about 23%. This increase in combustion duration arises from the cooling of the near wall mixture in the boundary layer attributed to the presence of hydrogen. The enhancement in engine cooling load and subsequent reduction in the brake thermal efficiency with increasing hydrogen fraction is evident from the engine energy balance along with the cumulative heat release profiles. Copyright (C) 2015, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Risk-Sensitive Ergodic Control of Continuous Time Markov Processes With Denumerable State Space

In this article, we study risk-sensitive control problem with controlled continuous time Markov chain state dynamics. Using multiplicative dynamic programming principle along with the atomic structure of the state dynamics, we prove the existence and a characterization of optimal risk-sensitive control under geometric ergodicity of the state dynamics along with a smallness condition on the running cost.

Lesion Detection in Breast Ultrasound Images Using Tissue Transition Analysis

Breast cancer is one of the leading cause of cancer related deaths in women and early detection is crucial for reducing mortality rates. In this paper, we present a novel and fully automated approach based on tissue transition analysis for lesion detection in breast ultrasound images. Every candidate pixel is classified as belonging to the lesion boundary, lesion interior or normal tissue based on its descriptor value. The tissue transitions are modeled using a Markov chain to estimate the likelihood of a candidate lesion region. Experimental evaluation on a clinical dataset of 135 images show that the proposed approach can achieve high sensitivity (95 %) with modest (3) false positives per image. The approach achieves very similar results (94 % for 3 false positives) on a completely different clinical dataset of 159 images without retraining, highlighting the robustness of the approach.

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Experimental Analysis of Water Vapor Diffusion Through Porous Membranes in a Proton Exchange Membrane Fuel Cell

We report the diffusion characteristics of water vapor through two different porous media, viz., membrane electrode assembly (MEA) and gas diffusion layer (GDL) in a nonoperational fuel cell. Tunable diode laser absorption spectroscopy (TDLAS) was employed for measuring water vapor concentration in the test channel. Effects of the membrane pore size and the inlet humidity on the water vapor transport are quantified through mass flux and diffusion coefficient. Water vapor transport rate is found to be higher for GDL than for MEA. The flexibility and wide range of application of TDLAS in a fuel cell setup is demonstrated through experiments with a stagnant flow field on the dry side.

As-You-Go Deployment of a 2-Connected Wireless Relay Network for Sensor-Sink Interconnection

A person walks along a line (which could be an idealisation of a forest trail, for example), placing relays as he walks, in order to create a multihop network for connecting a sensor at a point along the line to a sink at the start of the line. The potential placement points are equally spaced along the line, and at each such location the decision to place or not to place a relay is based on link quality measurements to the previously placed relays. The location of the sensor is unknown apriori, and is discovered as the deployment agent walks. In this paper, we extend our earlier work on this class of problems to include the objective of achieving a 2-connected multihop network. We propose a network cost objective that is additive over the deployed relays, and accounts for possible alternate routing over the multiple available paths. As in our earlier work, the problem is formulated as a Markov decision process. Placement algorithms are obtained for two source location models, which yield a discounted cost MDP and an average cost MDP. In each case we obtain structural results for an optimal policy, and perform a numerical study that provides insights into the advantages and disadvantages of multi-connectivity. We validate the results obtained from numerical study experimentally in a forest-like environment.

A fast and accurate performance analysis of beaconless IEEE 802.15.4 multi-hop networks

We develop an approximate analytical technique for evaluating the performance of multi-hop networks based on beaconless IEEE 802.15.4 ( the ``ZigBee'' PHY and MAC), a popular standard for wireless sensor networks. The network comprises sensor nodes, which generate measurement packets, relay nodes which only forward packets, and a data sink (base station). We consider a detailed stochastic process at each node, and analyse this process taking into account the interaction with neighbouring nodes via certain time averaged unknown variables (e.g., channel sensing rates, collision probabilities, etc.). By coupling the analyses at various nodes, we obtain fixed point equations that can be solved numerically to obtain the unknown variables, thereby yielding approximations of time average performance measures, such as packet discard probabilities and average queueing delays. The model incorporates packet generation at the sensor nodes and queues at the sensor nodes and relay nodes. We demonstrate the accuracy of our model by an extensive comparison with simulations. As an additional assessment of the accuracy of the model, we utilize it in an algorithm for sensor network design with quality-of-service (QoS) objectives, and show that designs obtained using our model actually satisfy the QoS constraints (as validated by simulating the networks), and the predictions are accurate to well within 10% as compared to the simulation results in a regime where the packet discard probability is low. (C) 2015 Elsevier B.V. All rights reserved.

Gasification of wood particles in a co-current packed bed: Experiments and model analysis

This study focuses on addressing the propagation front movement in a co-current downdraft gasification system. A detailed single particle modeling analysis extended to the packed bed reactor is used to compare with the experimental measurement as well those available in the literature. This model for biomass gasification systems considered pyrolysis process, gas phase volatile combustion, and heterogeneous char reactions along with gas phase reactions in the packed bed. The pyrolysis kinetics has a critical influence on the gasification process. The propagation front has been shown to increase with air mass flux, attains a peak and then decreases with further increase in air mass flux and finally approaches negative propagation rate. This indicates that front is receding, or no upward movement() bra her it is moving downward towards the char bed. The propagation rate correlates with mass flux as (m) over dot `'(0.883) during the increasing regimes of the front movement The study clearly identifies that bed movement is an important parameter for consideration in a co-current configuration towards establishing the effective bed movement. The study also highlights the importance of surface area to volume ratio of the particles in the packed bed and its influence on the volatile generation. Finally, the gas composition for air gasification under various air mass fluxes is compared with the experimental results. (C) 2016 Elsevier B.V. All rights reserved.

Structural analysis of dihydrofolate reductases enables rationalization of antifolate binding affinities and suggests repurposing possibilities

Antifolates are competitive inhibitors of dihydrofolate reductase ( DHFR), a conserved enzyme that is central to metabolism and widely targeted in pathogenic diseases, cancer and autoimmune disorders. Although most clinically used antifolates are known to be target specific, some display a fair degree of cross-reactivity with DHFRs from other species. A method that enables identification of determinants of affinity and specificity in target DHFRs from different species and provides guidelines for the design of antifolates is currently lacking. To address this, we first captured the potential druggable space of a DHFR in a substructure called the `supersite' and classified supersites of DHFRs from 56 species into 16 `site-types' based on pairwise structural similarity. Analysis of supersites across these site-types revealed that DHFRs exhibit varying extents of dissimilarity at structurally equivalent positions in and around the binding site. We were able to explain the pattern of affinities towards chemically diverse antifolates exhibited by DHFRs of different site-types based on these structural differences. We then generated an antifolate-DHFR network by mapping known high-affinity antifolates to their respective supersites and used this to identify antifolates that can be repurposed based on similarity between supersites or antifolates. Thus, we identified 177 human-specific and 458 pathogen-specific antifolates, a large number of which are supported by available experimental data. Thus, in the light of the clinical importance of DHFR, we present a novel approach to identifying differences in the druggable space of DHFRs that can be utilized for rational design of antifolates.

Mass spectrometric analysis of dimer-disrupting mutations in Plasmodium triosephosphate isomerase

Electrospray ionization mass spectrometry (ESI MS) under nanospray conditions has been used to examine the effects of mutation at two key dimer interface residues, Gln (Q) 64 and Thr (T) 75, in Plasmodium falciparum triosephosphate isomerase. Both residues participate in an intricate network of intra- and intersubunit hydrogen bonds. The gas phase distributions of dimeric and monomeric protein species have been examined for the wild type enzyme (TWT) and three mutants, Q64N, Q64E, and 175S, under a wide range of collision energies (40-160 eV). The results established the order of dimer stability as TWT > T75S > Q64E similar to Q64N. The mutational effects on dimer stability are in good agreement with the previously reported estimates, based on the concentration dependence of enzyme activity. Additional experiments in solution, using inhibition of activity by a synthetic dimer interface peptide, further support the broad agreement between gas phase and solution studies. (C) 2016 Elsevier Inc. All rights reserved.

Wave Propagation Analysis in a Pressure-Wave-Refrigerator

Pressure wave refrigerators (PWR) refrigerate the gas through periodical expansion waves. Due to its simple structure and robustness, PWR may have many potential applications if the efficiency becomes competitive with existing alternative devices. In order to improve the efficiency, the characteristics of wave propagation in a PWR are studied by experiment, numerical simulation and theoretical analysis. Based on the experimental results and numerical simulation, a simplified model is suggested, which includes the assumptions of flux-equilibrium and conservation of the free energy. This allows the independent analysis of the operation parameters and design specifics. Furthermore, the optimum operation condition can be deduced. Some considerations to improve the PWR efficiency are also given.

A general design method for electric machines using magnetic circuit model considering the flux saturation problem

This paper proposes an analytical approach that is generalized for the design of various types of electric machines based on a physical magnetic circuit model. Conventional approaches have been used to predict the behavior of electric machines but have limitations in accurate flux saturation analysis and hence machine dimensioning at the initial design stage. In particular, magnetic saturation is generally ignored or compensated by correction factors in simplified models since it is difficult to determine the flux in each stator tooth for machines with any slot-pole combinations. In this paper, the flux produced by stator winding currents can be calculated accurately and rapidly for each stator tooth using the developed model, taking saturation into account. This aids machine dimensioning without the need for a computationally expensive finite element analysis (FEA). A 48-slot machine operated in induction and doubly-fed modes is used to demonstrate the proposed model. FEA is employed for verification.