Coding of relative size in monkey inferotemporal cortex

We seldom mistake a closer object as being larger, even though its retinal image is bigger. One underlying mechanism could be to calculate the size of the retinal image relative to that of another nearby object. Here we set out to investigate whether single neurons in the monkey inferotemporal cortex (IT) are sensitive to the relative size of parts in a display. Each neuron was tested on shapes containing two parts that could be conjoined or spatially separated. Each shape was presented in four versions created by combining the two parts at each of two possible sizes. In this design, neurons sensitive to the absolute size of parts would show the greatest response modulation when both parts are scaled up, whereas neurons encoding relative size would show similar responses. Our main findings are that 1) IT neurons responded similarly to all four versions of a shape, but tuning tended to be more consistent between versions with proportionately scaled parts; 2) in a subpopulation of cells, we observed interactions that resulted in similar responses to proportionately scaled parts; 3) these interactions developed together with sensitivity to absolute size for objects with conjoined parts but developed slightly later for objects with spatially separate parts. Taken together, our results demonstrate for the first time that there is a subpopulation of neurons in IT that encodes the relative size of parts in a display, forming a potential neural substrate for size constancy.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations

The Lattice-Boltzmann method (LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a state-of-the-art LBM solver such as Palabos, a user has to still manually write the program using library-supplied primitives. We propose an automated code generator for a class of LBM computations with the objective to achieve high performance on modern architectures. Few studies have looked at time tiling for LBM codes. We exploit a key similarity between stencils and LBM to enable polyhedral optimizations and in turn time tiling for LBM. We also characterize the performance of LBM with the Roofline performance model. Experimental results for standard LBM simulations like Lid Driven Cavity, Flow Past Cylinder, and Poiseuille Flow show that our scheme consistently outperforms Palabos-on average by up to 3x while running on 16 cores of an Intel Xeon (Sandybridge). We also obtain an improvement of 2.47x on the SPEC LBM benchmark.

Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-Offs and Optimal Design

Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.

A new class of high strength high temperature Cobalt based gamma-gamma ` Co-Mo-Al alloys stabilized with Ta addition

The present paper reports a new class of Co based superalloys that has gamma-gamma' microstructure and exhibits much lower density compared to other commercially available Co superalloys including Co-Al-W based alloys. The basic composition is Co-10Al-5Mo (at%) with addition of 2 at% Ta for stabilization of gamma' phase. The gamma-gamma' microstructure evolves through solutionising and aging treatment. Using first principles calculations, we observe that Ta plays a crucial role in stabilizing gamma' phase. By addition of Ta in the basic stoichiometric composition Co-3(Al, Mo), the enthalpy of formation (Delta H-f) of L1(2) structure (gamma' phase) becomes more negative in comparison to DO19 structure. The All of the L12 structure becomes further more negative by the occupancy of Ni and Ti atoms in the lattice suggesting an increase in the stability of the gamma' precipitates. Among large number of alloys studied experimentally, the paper presents results of detailed investigations on Co-10Al-5Mo-2Ta, Co-30Ni-10Al-5Mo-2Ta and Co-30Ni-10Al-5Mo-2Ta-2Ti. To evaluate the role alloying elements, atom probe tomography investigations were carried out to obtain partition coefficients for the constituent elements. The results show strong partitioning of Ni, Al, Ta and Ti in ordered gamma' precipitates. 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Effect of Size Reduction on Magnetic Ordering in Sm1-x Ca (x) MnO3 (x=0.35, 0.65 and 0.92) Manganites: Magnetic and EMR Studies

We have employed the highly sensitive electron magnetic resonance technique complimented by magnetization measurements to study the impact of size reduction on the magnetic ordering in nanosized Sm1-x Ca (x) MnO3 (x = 0.35, 0.65 and 0.92). In the bulk form, x = 0.35 sample shows a charge ordering transition at 235 K followed by a mixed magnetic phase, the sample with x = 0.65 exhibits charge order below 275 K and shows an antiferromagnetic insulator phase below 135 K while that with x = 0.92 has a ferromagnetic-cluster glass ground state. Thus, a comparative study of magnetic ground states of bulk and nanoparticles (diameter similar to 25 nm) enables us to investigate size-induced effects on different types of magnetic ordering. It is seen that in the bulk samples the temperature dependences of the EPR parameters are quite different from each other. This difference diminishes for the nanosamples where all the three samples show qualitatively similar behavior. The magnetization measurements corroborate this conclusion.

Does size matter? Comparative population genetics of two butterflies with different wingspans

The dispersal ability of a species is central to its biology, affecting other processes like local adaptation, population and community dynamics, and genetic structure. Among the intrinsic, species-specific factors that affect dispersal ability in butterflies, wingspan was recently shown to explain a high amount of variance in dispersal ability. In this study, a comparative approach was adopted to test whether a difference in wingspan translates into a difference in population genetic structure. Two closely related butterfly species from subfamily Satyrinae, family Nymphalidae, which are similar with respect to all traits that affect dispersal ability except for wingspan, were studied. Melanitis leda (wingspan 60-80 mm) and Ypthima baldus (wingspan 30-40 mm) were collected from the same areas along the Western Ghats of southern India. Amplified fragment length polymorphisms were used to test whether the species with a higher wingspan (M. leda) exhibited a more homogenous population genetic structure, as compared to a species with a shorter wingspan (Y. baldus). In all analyses, Y. baldus exhibited greater degree of population genetic structuring. This study is one of the few adopting a comparative approach to establish the relationship between traits that affect dispersal ability and population genetic structure.

Vegetation structure and composition of tropical evergreen and deciduous forests in Uttara Kannada District, Western Ghats under different disturbance regimes

In the present paper, we present the structure and composition of tropical evergreen and deciduous forests in the Western Ghats monitored under a long-term programme involving Indian Institute of Science, Earthwatch and volunteer investigators from HSBC. Currently, there is limited evidence on the status and dynamics of tropical forests in the context of human disturbance and climate change. Observations made in this study show that the `more disturbed' evergreen and one of the deciduous plots have low species diversity compared to the less-disturbed forests. There are also variations in the size class structure in the more and `less disturbed' forests of all the locations. The variation is particularly noticeable in the DBH size class 10 - 15 cm category. When biomass stock estimates are considered, there was no significant difference between evergreen and deciduous forests. The difference in biomass stocks between `less disturbed' and `more disturbed' forests within a forest type is also low. Thus, the biomass and carbon stock has not been impacted despite the dependence of communities on the forests. Periodic and long-term monitoring of the status and dynamics of the forests is necessary in the context of potential increased human pressure and climate change. There is, therefore, a need to inform the communities of the impact of extraction and its effect on regeneration so as to motivate them to adopt what may be termed as ``adaptive resource management'', so as to sustain the flow of forest products.

Strategy for Obtaining Bimodal Bubble Size Distribution in Water Blown Polyurethane Foams

Polyurethane foams with multimodal cell distribution exhibit superior mechanical and thermal properties. A technique for generating bimodal bubble size distribution exists in the literature, but it uses supercritical conditions. In the present work, an alternative based on milder operating conditions is proposed. It is a modification of reaction injection molding (RIM), using reactants already seeded with bubbles. The number density of the seeds determines if two nucleating events can occur. A bimodal bubble size distribution is obtained when this happens A mathematical model is used to test this hypothesis by simulating water blown free rise polyurethane foams. The effects of initial concentration of bubbles, temperature of the reactants, and the weight fraction of water are studied. The study reveals that for certain concentrations of initial number of bubbles, when initial temperature and weight fraction of water are high, it is possible to obtain a second nucleation event, leading to bimodal bubble size distribution.

Hybrid Working Set Algorithm for SVM Learning With a Kernel Coprocessor on FPGA

Support vector machines (SVM) are a popular class of supervised models in machine learning. The associated compute intensive learning algorithm limits their use in real-time applications. This paper presents a fully scalable architecture of a coprocessor, which can compute multiple rows of the kernel matrix in parallel. Further, we propose an extended variant of the popular decomposition technique, sequential minimal optimization, which we call hybrid working set (HWS) algorithm, to effectively utilize the benefits of cached kernel columns and the parallel computational power of the coprocessor. The coprocessor is implemented on Xilinx Virtex 7 field-programmable gate array-based VC707 board and achieves a speedup of upto 25x for kernel computation over single threaded computation on Intel Core i5. An application speedup of upto 15x over software implementation of LIBSVM and speedup of upto 23x over SVMLight is achieved using the HWS algorithm in unison with the coprocessor. The reduction in the number of iterations and sensitivity of the optimization time to variation in cache size using the HWS algorithm are also shown.

Single-step, size-controlled synthesis of colloidal silver nanoparticles stabilized by octadecylamine

A single step process for the synthesis of size-controlled silver nanoparticles has been developed using a bifunctional molecule, octadecylamine (ODA). Octadecylamine complexes to Ag+ ions electrostatically, reduce them, and subsequently stabilizes the nanoparticles thus formed. Hence, octadecylamine simultaneously functions as both a reducing and a stabilizing agent. The amine-capped nanoparticles can be obtained in the form of dry powder, which is readily redispersible in aqueous and organic solvents. The particle size, and the nucleation and growth kinetics of silver nanoparticles could be tuned by varying the molar ratio of ODA to AgNO3. The UV-vis spectra of nanoparticles prepared with different concentrations of ODA displayed the well-defined plasmon band with maximum absorption around 425 nm. The formation of silver metallic nanoparticles was confirmed by their XRD pattern. The binding of ODA molecule on the surface of silver has been studied by FT-IR and NMR spectroscopy. The formation of well-dispersed spherical Ag nanoparticles has been confirmed by TEM analysis. The particle size and distribution are found to be dependent on the molar concentration of the amine molecule. Open aperture z-scans have been performed to measure the nonlinearity of Ag nanoparticles. (C) 2015 Published by Elsevier B.V.

Boron-doped carbon nanoparticles: Size-independent color tunability from red to blue and bioimaging applications

Here, we report the hydrothermal synthesis of boron-doped CNPs (B-CNPs) with different size/atomic percentage of doping and size-independent color tunability from red to blue. The variation of size/atomic percentage of B is achieved by simply varying the reaction time, while the color tunability is obtained by diluting the solution. With dilution, the luminescence spectra are not only blue-shifted, the intensity increases as well. The huge blue-shift in the emission energy (similar to 1 eV) is believed to be due to the increase in the interparticle distance. The quantum yield with optimum dilution is found to increase with boron doping though it is very low as compared to CNPs and nitrogen-doped CNPs. Finally, we show that B-CNPs with a quantum yield of 0.5% can be used for bioimaging applications. (C) 2015 Elsevier Ltd. All rights reserved.

An Exponential Lower Bound for Homogeneous Depth Four Arithmetic Formulas

We show here a 2(Omega(root d.log N)) size lower bound for homogeneous depth four arithmetic formulas. That is, we give an explicit family of polynomials of degree d on N variables (with N = d(3) in our case) with 0, 1-coefficients such that for any representation of a polynomial f in this family of the form f = Sigma(i) Pi(j) Q(ij), where the Q(ij)'s are homogeneous polynomials (recall that a polynomial is said to be homogeneous if all its monomials have the same degree), it must hold that Sigma(i,j) (Number of monomials of Q(ij)) >= 2(Omega(root d.log N)). The above mentioned family, which we refer to as the Nisan-Wigderson design-based family of polynomials, is in the complexity class VNP. Our work builds on the recent lower bound results 1], 2], 3], 4], 5] and yields an improved quantitative bound as compared to the quasi-polynomial lower bound of 6] and the N-Omega(log log (N)) lower bound in the independent work of 7].

Size Effects on Strength in the Transition from Single-to-Polycrystalline Behavior

During the transition from single crystalline to polycrystalline behavior, the available data show the strength increasing or decreasing as the number of grains in a cross section is reduced. Tensile experiments were conducted on polycrystalline Ni with grain sizes (d) between 16 and 140 mu m and varying specimen thickness (t), covering a range of lambda (-t/d) between similar to 0.5 and 20. With a decrease in lambda, the data revealed a consistent trend of strength being independent of lambda at large lambda, an increase in strength, and then a decrease in strength. Microstructural studies revealed that lower constraints enabled easier rotation of the surface grains and texture evolution, independent of the specimen thickness. In specimen interiors, there was a greater ease of rotation in thinner samples. Measurements of misorientation deviations within grains revealed important differences in the specimen interiors. A simple model is developed taking into account the additional geometrically necessary dislocations due to variations in the behavior of surface and interior grains, leading to additional strengthening. A suitable combination of this strengthening and surface weakening can give rise to wide range of possibilities with a decrease in lambda, including weakening, strengthening, and strengthening and weakening.