Visual ecology of Indian carpenter bees II: adaptations of eyes and ocelli to nocturnal and diurnal lifestyles

Most bees are diurnal, with behaviour that is largely visually mediated, but several groups have made evolutionary shifts to nocturnality, despite having apposition compound eyes unsuited to vision in dim light. We compared the anatomy and optics of the apposition eyes and the ocelli of the nocturnal carpenter bee, Xylocopa tranquebarica, with two sympatric species, the strictly diurnal X. leucothorax and the occasionally crepuscular X. tenuiscapa. The ocelli of the nocturnal X. tranquebarica are unusually large (diameter ca. 1 mm) and poorly focussed. Moreover, their apposition eyes show specific visual adaptations for vision in dim light, including large size, large facets and very wide rhabdoms, which together make these eyes 9 times more sensitive than those of X. tenuiscapa and 27 times more sensitive than those of X. leucothorax. These differences in optical sensitivity are surprisingly small considering that X. tranquebarica can fly on moonless nights when background luminance is as low as 10(-5) cd m(-2), implying that this bee must employ additional visual strategies to forage and find its way back to the nest. These strategies may include photoreceptors with longer integration times and higher contrast gains as well as higher neural summation mechanisms for increasing visual reliability in dim light.

A model for visual recognition of alphanumerics

In this paper we propose a hypothetical scheme for recognizing the alphanumerics. The scheme is based on the known physiological structure of the visual cortex and the concept of a short Lino extractor nouron (SLEN). We assumo four basic typca of such units for extracting vertical, horizontal, right and left inclined straight line segments. The patterns reconstructed from the scheme show perfect agreement with the test patterns. The model indicates that the recognition of letters T and H requires extraction of the largest number of features.

Visual Analysis of Biomolecular Surfaces

Surface models of biomolecules have become crucially important for the study and understanding of interaction between biomolecules and their environment. We argue for the need for a detailed understanding of biomolecular surfaces by describing several applications in computational and structural biology. We review methods used to model, represent, characterize, and visualize biomolecular surfaces focusing on the role that geometry and topology play in identifying features on the surface. These methods enable the development of efficient computational and visualization tools for studying the function of biomolecules.

Non-segmented negative sense RNA viruses as vectors for vaccine development

This article intends to cover two aspects of non-segmented negative sense RNA viruses. In the initial section, the strategy employed by these viruses to replicate their genomes is discussed. This would help in understanding the later section in which the use of these viruses as vaccine vectors has been discussed. For the description of the replication strategy which encompasses virus genome transcription and genome replication carried out by the same RNA dependent RNA polymerase complex, a member of the prototype rhabdovirus family - Chandipura virus has been chosen as an example to illustrate the complex nature of the two processes and their regulation. In the discussion on these viruses serving as vectors for carrying vaccine antigen genes, emphasis has been laid on describing the progress made in using the attenuated viruses as vectors and a description of the systems in which the efficiency of immune responses has been tested.

On Using Projective Relations for Calibration and Estimation in a Structured-Light Scanner

For structured-light scanners, the projective geometry between a projector-camera pair is identical to that of a camera-camera pair. Consequently, in conjunction with calibration, a variety of geometric relations are available for three-dimensional Euclidean reconstruction. In this paper, we use projector-camera epipolar properties and the projective invariance of the cross-ratio to solve for 3D geometry. A key contribution of our approach is the use of homographies induced by reference planes, along with a calibrated camera, resulting in a simple parametric representation for projector and system calibration. Compared to existing solutions that require an elaborate calibration process, our method is simple while ensuring geometric consistency. Our formulation using the invariance of the cross-ratio is also extensible to multiple estimates of 3D geometry that can be analysed in a statistical sense. The performance of our system is demonstrated on some cultural artifacts and geometric surfaces.

COMMON-Sense net:Improved water management for resource-poor farmers via sensor networks

We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology.

Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

Fluorescence and visual sensing of nitroaromatic explosives using electron rich discrete fluorophores

Several pi-electron rich fluorescent aromatic compounds containing trimethylsilylethynyl functionality have been synthesized by employing Sonogashira coupling reaction and they were characterized fully by NMR (H-1, C-13)/IR spectroscopy. Incorporation of bulky trimethylsilylethynyl groups on the peripheral of the fluorophores prevents self-quenching of the initial intensity through pi-pi interaction and thereby maintains the spectroscopic stability in solution. These compounds showed fluorescence behavior in chloroform solution and were used as selective fluorescence sensors for the detection of electron deficient nitroaromatics. All these fluorophores showed the largest quenching response with high selectivity for nitroaromatics among the various electron deficient aromatic compounds tested. Quantitative analysis of the fluorescence titration profile of 9,10-bis(trimethylsilylethynyl) anthracene with picric acid provided evidence that this particular fluorophore detects picric acid even at ppb level. A sharp visual detection of 2,4,6-trinitrotoluene was observed upon subjecting 1,3,6,8-tetrakis (trimethylsilylethynyl) pyrene fluorophore to increasing quantities of 2,4,6-trinitrotoluene in chloroform. Furthermore, thin film of the fluorophores was made by spin coating of a solution of 1.0 x 10(-3) M in chloroform or dichloromethane on a quartz plate and was used for the detection of vapors of nitroaromatics at room temperature. The vapor-phase sensing experiments suggested that the sensing process is reproducible and quite selective for nitroaromatic compounds. Selective fluorescence quenching response including a sharp visual color change for nitroaromatics makes these fluorophores as promising fluorescence sensory materials for nitroaromatic compounds (NAC) with a detection limit of even ppb level as judged with picric acid.

A Gradient-Based Comparison Measure for Visual analysis of Multifield Data

We introduce a multifield comparison measure for scalar fields that helps in studying relations between them. The comparison measure is insensitive to noise in the scalar fields and to noise in their gradients. Further, it can be computed robustly and efficiently. Results from the visual analysis of various data sets from climate science and combustion applications demonstrate the effective use of the measure.

Trans-saccadic processing of visual and motor planning during sequential eye movements

How the brain maintains perceptual continuity across eye movements that yield discontinuous snapshots of the world is still poorly understood. In this study, we adapted a framework from the dual-task paradigm, well suited to reveal bottlenecks in mental processing, to study how information is processed across sequential saccades. The pattern of RTs allowed us to distinguish among three forms of trans-saccadic processing (no trans-saccadic processing, trans-saccadic visual processing and trans-saccadic visual processing and saccade planning models). Using a cued double-step saccade task, we show that even though saccade execution is a processing bottleneck, limiting access to incoming visual information, partial visual and motor processing that occur prior to saccade execution is used to guide the next eye movement. These results provide insights into how the oculomotor system is designed to process information across multiple fixations that occur during natural scanning.

A phenanthrene based highly selective fluorogenic and visual sensor for Cu2+ ion with nanomolar detection limit and its application in live cell imaging

A new phenanthrene based chemosensor has been synthesized and investigated to act as highly selective fluorescence and visual sensor for Cu2+ ion with very low detection limit of 1.58 nM: this has also been used to image Cu2+ in human cervical HeLa cancer cells. (C) 2012 Elsevier B.V. All rights reserved.

Turning visual search time on its head

Our everyday visual experience frequently involves searching for objects in clutter. Why are some searches easy and others hard? It is generally believed that the time taken to find a target increases as it becomes similar to its surrounding distractors. Here, I show that while this is qualitatively true, the exact relationship is in fact not linear. In a simple search experiment, when subjects searched for a bar differing in orientation from its distractors, search time was inversely proportional to the angular difference in orientation. Thus, rather than taking search reaction time (RT) to be a measure of target-distractor similarity, we can literally turn search time on its head (i.e. take its reciprocal 1/RT) to obtain a measure of search dissimilarity that varies linearly over a large range of target-distractor differences. I show that this dissimilarity measure has the properties of a distance metric, and report two interesting insights come from this measure: First, for a large number of searches, search asymmetries are relatively rare and when they do occur, differ by a fixed distance. Second, search distances can be used to elucidate object representations that underlie search - for example, these representations are roughly invariant to three-dimensional view. Finally, search distance has a straightforward interpretation in the context of accumulator models of search, where it is proportional to the discriminative signal that is integrated to produce a response. This is consistent with recent studies that have linked this distance to neuronal discriminability in visual cortex. Thus, while search time remains the more direct measure of visual search, its reciprocal also has the potential for interesting and novel insights. (C) 2012 Elsevier Ltd. All rights reserved.

Is saccade averaging determined by visual processing or movement planning?

Bhutani N, Ray S, Murthy A. Is saccade averaging determined by visual processing or movement planning? J Neurophysiol 108: 3161-3171, 2012. First published September 26, 2012; doi:10.1152/jn.00344.2012.-Saccadic averaging that causes subjects' gaze to land between the location of two targets when faced with simultaneously or sequentially presented stimuli has been often used as a probe to investigate the nature of computations that transform sensory representations into an oculomotor plan. Since saccadic movements involve at least two processing stages-a visual stage that selects a target and a movement stage that prepares the response-saccade averaging can either occur due to interference in visual processing or movement planning. By having human subjects perform two versions of a saccadic double-step task, in which the stimuli remained the same, but different instructions were provided (REDIRECT gaze to the later-appearing target vs. FOLLOW the sequence of targets in their order of appearance), we tested two alternative hypotheses. If saccade averaging were due to visual processing alone, the pattern of saccade averaging is expected to remain the same across task conditions. However, whereas subjects produced averaged saccades between two targets in the FOLLOW condition, they produced hypometric saccades in the direction of the initial target in the REDIRECT condition, suggesting that the interaction between competing movement plans produces saccade averaging.

Active Sequential Hypothesis Testing with Application to a Visual Search Problem

We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

Similarity relations in visual search predict rapid visual categorization

How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation.