Features in visual search combine linearly

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features ( intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and coactivation models ( based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features-in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search.

Object attributes combine additively in visual search

We perceive objects as containing a variety of attributes: local features, relations between features, internal details, and global properties. But we know little about how they combine. Here, we report a remarkably simple additive rule that governs how these diverse object attributes combine in vision. The perceived dissimilarity between two objects was accurately explained as a sum of (a) spatially tuned local contour-matching processes modulated by part decomposition; (b) differences in internal details, such as texture; (c) differences in emergent attributes, such as symmetry; and (d) differences in global properties, such as orientation or overall configuration of parts. Our results elucidate an enduring question in object vision by showing that the whole object is not a sum of its parts but a sum of its many attributes.

Quest for new materials: Inorganic chemistry plays a crucial role

There is an endless quest for new materials to meet the demands of advancing technology. Thus, we need new magnetic and metallic/semiconducting materials for spintronics, new low-loss dielectrics for telecommunication, new multi-ferroic materials that combine both ferroelectricity and ferromagnetism for memory devices, new piezoelectrics that do not contain lead, new lithium containing solids for application as cathode/anode/electrolyte in lithium batteries, hydrogen storage materials for mobile/transport applications and catalyst materials that can convert, for example, methane to higher hydrocarbons, and the list is endless! Fortunately for us, chemistry - inorganic chemistry in particular - plays a crucial role in this quest. Most of the functional materials mentioned above are inorganic non-molecular solids, while much of the conventional inorganic chemistry deals with isolated molecules or molecular solids. Even so, the basic concepts that we learn in inorganic chemistry, for example, acidity/basicity, oxidation/reduction (potentials), crystal field theory, low spin-high spin/inner sphere-outer sphere complexes, role of d-electrons in transition metal chemistry, electron-transfer reactions, coordination geometries around metal atoms, Jahn-Teller distortion, metal-metal bonds, cation-anion (metal-nonmetal) redox competition in the stabilization of oxidation states - all find crucial application in the design and synthesis of inorganic solids possessing technologically important properties. An attempt has been made here to illustrate the role of inorganic chemistry in this endeavour, drawing examples from the literature its well as from the research work of my group.

Purification and partial characterization of microsomal cytochrome b555 from the higher plant Catharanthus-Roseus

Microsomal b-type hemoprotein designated, cytochrome b555 of C-Roseus seedlings was solubilized using detergents and purified by a combination of ion exchange chromatography and gel filtration to a specific content of 18.5 nmol per mg of protein. The purified cytochrome b555 was homogeneous and estimated to have an apparent molecular weight of 16500 on SDS-PAGE. The absorption spectrum of the reduced form has major peaks at 424, 525 and 555 nm. The α-band of the reduced form is asymmetric with a pronounced shoulder at 559 nm. The spectrum of the pyridine ferrohemochrome shows absorption peaks at 557, 524 and 418 nm indicating that the cytochrome has protoheme prosthetic group. The purified cytochrome is autoxidizable and does not combine with carbon monoxide, azide or cyanide. It is reducible by NADH in the presence of NADH-cytochrome b555 reductase partially purified from C-Roseus microsomes.

Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling

The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.

Recognition of Interaction Interface Residues in Low-Resolution Structures of Protein Assemblies Solely from the Positions of C alpha Atoms

Background: The number of available structures of large multi-protein assemblies is quite small. Such structures provide phenomenal insights on the organization, mechanism of formation and functional properties of the assembly. Hence detailed analysis of such structures is highly rewarding. However, the common problem in such analyses is the low resolution of these structures. In the recent times a number of attempts that combine low resolution cryo-EM data with higher resolution structures determined using X-ray analysis or NMR or generated using comparative modeling have been reported. Even in such attempts the best result one arrives at is the very course idea about the assembly structure in terms of trace of the C alpha atoms which are modeled with modest accuracy. Methodology/Principal Findings: In this paper first we present an objective approach to identify potentially solvent exposed and buried residues solely from the position of C alpha atoms and amino acid sequence using residue type-dependent thresholds for accessible surface areas of C alpha. We extend the method further to recognize potential protein-protein interface residues. Conclusion/Significance: Our approach to identify buried and exposed residues solely from the positions of C alpha atoms resulted in an accuracy of 84%, sensitivity of 83-89% and specificity of 67-94% while recognition of interfacial residues corresponded to an accuracy of 94%, sensitivity of 70-96% and specificity of 58-94%. Interestingly, detailed analysis of cases of mismatch between recognition of interface residues from C alpha positions and all-atom models suggested that, recognition of interfacial residues using C alpha atoms only correspond better with intuitive notion of what is an interfacial residue. Our method should be useful in the objective analysis of structures of protein assemblies when positions of only C alpha positions are available as, for example, in the cases of integration of cryo-EM data and high resolution structures of the components of the assembly.

Aspects of tautomerism. Part IV. A kinetic study of the dimerization reaction of pseudo-acid chlorides

The kinetics of dimerization of 4-substituted- and unsubstituted o-benzoylbenzoyl chlorides, with iodide ion can be described by the expression, rate =k2[acid chloride][iodide]. The value for the reaction in dimethylformamide solution is –0·38. The entropy of activation for the reaction is –34·2 cal mol–1 K–1 and the activation energy is 10·7 kcal mol–1. These results have been interpreted as evidence for the formation of pseudo-iodide in the rate-determining step and its fast decomposition to radicals which combine to give a mixture of stereoisomeric dilactones.

Reliability models for existing structures based on dynamic state estimation and data based asymptotic extreme value analysis

The problem of time variant reliability analysis of existing structures subjected to stationary random dynamic excitations is considered. The study assumes that samples of dynamic response of the structure, under the action of external excitations, have been measured at a set of sparse points on the structure. The utilization of these measurements m in updating reliability models, postulated prior to making any measurements, is considered. This is achieved by using dynamic state estimation methods which combine results from Markov process theory and Bayes' theorem. The uncertainties present in measurements as well as in the postulated model for the structural behaviour are accounted for. The samples of external excitations are taken to emanate from known stochastic models and allowance is made for ability (or lack of it) to measure the applied excitations. The future reliability of the structure is modeled using expected structural response conditioned on all the measurements made. This expected response is shown to have a time varying mean and a random component that can be treated as being weakly stationary. For linear systems, an approximate analytical solution for the problem of reliability model updating is obtained by combining theories of discrete Kalman filter and level crossing statistics. For the case of nonlinear systems, the problem is tackled by combining particle filtering strategies with data based extreme value analysis. In all these studies, the governing stochastic differential equations are discretized using the strong forms of Ito-Taylor's discretization schemes. The possibility of using conditional simulation strategies, when applied external actions are measured, is also considered. The proposed procedures are exemplifiedmby considering the reliability analysis of a few low-dimensional dynamical systems based on synthetically generated measurement data. The performance of the procedures developed is also assessed based on a limited amount of pertinent Monte Carlo simulations. (C) 2010 Elsevier Ltd. All rights reserved.

Nature of hydrogen atom trapped inside palladium lattice

Colloid of palladium nanoparticles has been prepared by the Solvated Metal Atom Dispersion (SMAD) method. Reaction of Pd(0) nanopowder obtained upon precipitation from the colloid, with ammonia borane (H3N center dot BH3, AB) in aqueous solutions at room temperature results in the generation of active hydrogen atoms. The active hydrogen atoms either combine with one another resulting in H-2 evolution or diffuse into the Pd lattice to afford PdHx. Diffusion of hydrogen atoms leads to an expansion of the Pd lattice. The diffused hydrogen atoms are distributed uniformly over the entire particle. These features were established using powder XRD and electron microscopy studies. The H-1 NMR spectral studies of PdHx before and after desorption of H-2 revealed that the hydrogen atoms trapped inside Pd lattice are hydridic in nature. Desorption of hydrogen from PdHx did not result in complete reversibility suggesting that some hydrogen atoms are strongly trapped inside the Pd lattice. (C) 2010 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved.

Reducibility of Ce1-xZrxO2: origin of enhanced oxygen storage capacity

We combine first-principles calculations with EXAFS studies to investigate the origin of high oxygen storage capacity in ceria-zirconia solid solution, prepared by solution combustion method. We find that nanocrystalline Ce0.5Zr0.5O2 can be reduced to Ce0.5Zr0.5O1.57 by H-2 upto 850 degrees C with an OSC of 65 cc/gm which is extremely high. Calculated local atomic-scale structure reveals the presence of long and short bonds resulting in four-fold coordination of the cations, confirmed by the EXAFS studies. Bond valence analysis of the microscopic structure and energetics is used to evaluate the strength of binding of different oxide ions and vacancies. We find the presence of strongly and weakly bound oxygens, of which the latter are responsible for the higher oxygen storage capacity in the mixed oxides than in the pure CeO2.

Ordering near the percolation threshold in models of two-dimensional interacting bosons with quenched dilution

Randomly diluted quantum boson and spin models in two dimensions combine the physics of classical percolation with the well-known dimensionality dependence of ordering in quantum lattice models. This combination is rather subtle for models that order in two dimensions but have no true order in one dimension, as the percolation cluster near threshold is a fractal of dimension between 1 and 2: two experimentally relevant examples are the O(2) quantum rotor and the Heisenberg antiferromagnet. We study two analytic descriptions of the O(2) quantum rotor near the percolation threshold. First a spin-wave expansion is shown to predict long-ranged order, but there are statistically rare points on the cluster that violate the standard assumptions of spin-wave theory. A real-space renormalization group (RSRG) approach is then used to understand how these rare points modify ordering of the O(2) rotor. A new class of fixed points of the RSRG equations for disordered one-dimensional bosons is identified and shown to support the existence of long-range order on the percolation backbone in two dimensions. These results are relevant to experiments on bosons in optical lattices and superconducting arrays, and also (qualitatively) for the diluted Heisenberg antiferromagnet La-2(Zn,Mg)(x)Cu1-xO4.

Structure of bovine prothrombin fragment 1 refined at 2.25 Å resolution

The structure of bovine prothrombin fragment 1 has been refined at 2.25 Å resolution using high resolution measurements made with the synchrotron beam at CHESS. The synchrotron data were collected photographically by oscillation methods (R-merge = 0.08). These were combined with lower order diffractometer data for refinement purposes. The structure was refined using restrained least-squares methods with the program PROLSQ to a crystallographic R-value of 0.175. The structure includes 105 water molecules with occupancies of >0·6. The first 35 residues (Ala1-Leu35) of the N-terminal ?-carboxy glutamic acid-domain (Ala1-Cys48) of fragment 1 are disordered as are two carbohydrate chains of Mr ? 5000; the latter two combine to render 40% of the structure disordered. The folding of the kringle of fragment 1 is related to the close intramolecular contact between the inner loop disulfide groups. Half of the conserved sequence of the kringle forms an inner core surrounding these disulfide groups. The remainder of the sequence conservation is associated with the many turns of the main chain. The Pro95 residue of the kringle has a cis conformation and Tyr74 is ordered in fragment 1, although nuclear magnetic resonance studies indicate that the comparable residue of plasminogen kringle 4 has two positions. Surface accessibility calculations indicate that none of the disulfide groups of fragment 1 is accessible to solvent.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Amplitude Frequency Response Measurement: A Simple Technique

A simple method is described to combine a modern function generator and a digital oscilloscope to configure a setup that can directly measure the amplitude frequency response of a system. This is achieved by synchronously triggering both instruments, with the function generator operated in the ``Linear-Sweep'' frequency mode, while the oscilloscope is operated in the ``Envelope'' acquisition mode. Under these conditions, the acquired envelopes directly correspond to the (input and output signal) spectra, whose ratio yields the amplitude frequency response. The method is easy to configure, automatic, time-efficient, and does not require any external control or interface or programming. This method is ideally suited to impart hands-on experience in sweep frequency response measurements, demonstrate resonance phenomenon in transformer windings, explain the working principle of an impedance analyzer, practically exhibit properties of network functions, and so on. The proposed method is an inexpensive alternative to existing commercial equipment meant for this job and is also an effective teaching aid. Details of its implementation, along with some practical measurements on an actual transformer, are presented.

Thermodynamic and structural consequences of changing a sulfur atom to a methylene group in the M13Nle mutation in ribonuclease-S

Two fragments of pancreatic ribonuclease A, a truncated version of S-peptide (residues 1-15) and S-protein (residues 21-124), combine to give a catalytically active complex. We have substituted the wild-type residue at position 13, methionine (Met), with norleucine (Nle), where the only covalent change is the replacement of the sulfur atom with a methylene group. The thermodynamic parameters associated with the binding of this variant to S-protein, determined by titration calorimetry in the temperature range 10-40 degrees C, are reported and compared to values previously reported [Varadarajan, R., Connelly, P. R., Sturtevant, J. M., & Richards, F. M. (1992) Biochemistry 31, 1421-1426] for other position 13 analogs. The differences in the free energy and enthalpy of binding between the Met and Nle peptides are 0.6 and 7.9 kcal/mol at 25 degrees C, respectively. These differences are slightly larger than, but comparable to, the differences in the values for the Met/Ile and Met/Leu pairs. The structure of the mutant complex was determined to 1.85 Angstrom resolution and refined to an R-factor of 17.4% The structures of mutant and wild-type complexes are practically identical although the Nle side chain has a significantly higher average B-factor than the corresponding Met side chain. In contrast, the B-factors of the atoms of the cage of residues surrounding position 13 are all somewhat lower in the Nle variant than in the Met wild-type. Thus, the large differences in the binding enthalpy appear to reside entirely in the difference in chemical properties or dynamic behavior of the -S- and -CH2- groups and not in differences in the geometry of the side chains or the internal cavity surface. In addition, a novel method of obtaining protein stability data by means of isothermal titration calorimetry is introduced.