Analytical solution of the generalized discrete Poisson equation

We present an analytical solution to the generalized discrete Poisson equation, a matrix equation which has a tridiagonal matrix with fringes having an arbitrary value for the diagonal elements. The results are of relevance to a variety of physical problems, which require the numerical solution of the Poisson equation. As examples, the formula has been applied to the solution of the electrostatic problem of tunnelling junction arrays with two and three rows

Action biases perceptual decisions towards expected outcomes

We predict how our actions will influence the world around us. Prevailing models in the action control literature propose that we use these predictions to suppress or ‘cancel’ perception of expected action outcomes, to highlight more informative surprising events. However, contrasting normative Bayesian models in sensory cognition suggest that we are more, not less, likely to perceive what we expect–given that what we expect is more likely to occur. Here we adjudicated between these models by investigating how expectations influence perceptual decisions about action outcomes in a signal detection paradigm. Across three experiments, participants performed one of two manual actions that were sometimes accompanied by brief presentation of expected or unexpected visual outcomes.Contrary to dominant cancellation models but consistent with Bayesian accounts, we found that observers were biased to report the presence of expected action outcomes. There were no effects of expectation on sensitivity. Computational modelling revealed that the action-induced bias reflected a sensory bias in how evidence was accumulated rather than a baseline shift in decision circuits. Expectation effects remained in Experiments 2 and 3 when orthogonal cues indicated which finger was more likely to be probed (i.e.,task-relevant). These biases towards perceiving expected action outcomes are suggestive of a mechanism that would enable generation of largely veridical representations of our actions and their consequences in an inherently uncertain sensory world

Variation in Manduca sexta pollination-related floral traits and reproduction in a wild tobacco plant

Most flowering plants depend on animal pollination for successful sexual reproduction. Floral signals such as color, shape, and odor are crucial in establishing this (often mutualistic) interaction. Plant and pollinator phenotypes can vary temporally but also spatially, thus creating mosaic-like patterns of local adaptations. Here, we investigated natural variation in floral morphology, flower volatile emission, and phenology in four accessions of a self-compatible wild tobacco, Nicotiana attenuata, to assess how these traits match the sensory perception of a known pollinator, the hawkmoth Manduca sexta. These accessions differ in floral traits and also in their habitat altitudes. Based on habitat temperatures, the accession occurring at the highest altitude (California) is less likely to be visited by M. sexta, while the others (Arizona, Utah 1, and Utah 2) are known to receive M. sexta pollinations. The accessions varied significantly in flower morphologies, volatile emissions, flower opening, and phenology, traits likely important for M. sexta perception and floral handling. In wind tunnel assays, we assessed the seed set of emasculated flowers after M. sexta visitation and of natural selfed and hand-pollinated selfed flowers. After moth visitations, plants of two accessions (Arizona and Utah 2) produced more capsules than the other two, consistent with predictions that accessions co-occurring with M. sexta would benefit more from the pollination services of this moth. We quantified flower and capsule production in four accessions in a glasshouse assay without pollinators to assess the potential for self-pollination. The two Utah accessions set significantly more seeds after pollen supplementation compared with those of autonomous selfing flowers, suggesting a greater opportunistic benefit from efficient pollinators than the other two. Moreover, emasculated flowers of the accession with the most exposed stigma (Utah 2) produced the greatest seed set after M. sexta visitation. This study reveals intraspecific variation in pollination syndromes that illuminate the potential of a plant species to adapt to local pollinator communities, changing environments, and altered pollination networks

True density of soot particles: A comparison of results highlighting the influence of the organic contents

International audienc

The predictive brain as a stubborn scientist

Bayesian theories of perception have traditionally cast the brain as an idealised scientist, refining predictions about the outside world based on evidence sampled by the senses. However, recent predictive coding models include predictions that are resistant to change, and these stubborn predictions can be usefully incorporated into cognitive models

Natural variation of HIV-1 group M integrase: Implications for a new class of antiretroviral inhibitors

HIV-1 integrase is the third enzymatic target of antiretroviral (ARV) therapy. However, few data have been published on the distribution of naturally occurring amino acid variation in this enzyme. We therefore characterized the distribution of integrase variants among more than 1,800 published group M HIV-1 isolates from more than 1,500 integrase inhibitor (INI)-naïve individuals. Polymorphism rates equal or above 0.5% were found for 34% of the central core domain positions, 42% of the C-terminal domain positions, and 50% of the N-terminal domain positions. Among 727 ARV-naïve individuals in whom the complete pol gene was sequenced, integrase displayed significantly decreased inter- and intra-subtype diversity and a lower Shannon's entropy than protease or RT. All primary INI-resistance mutations with the exception of E157Q – which was present in 1.1% of sequences – were nonpolymorphic. Several accessory INI-resistance mutations including L74M, T97A, V151I, G163R, and S230N were also polymorphic with polymorphism rates ranging between 0.5% to 2.0%

AIDX: Adaptive Inference Scheme to Mitigate State-Drift in Memristive VMM Accelerators

An adaptive inference method for crossbar (AIDX) is presented based on an optimization scheme for adjusting the duration and amplitude of input voltage pulses. AIDX minimizes the long-term effects of memristance drift on artificial neural network accuracy. The sub-threshold behavior of memristor has been modeled and verified by comparing with fabricated device data. The proposed method has been evaluated by testing on different network structures and applications, e.g., image reconstruction and classification tasks. The results showed an average of 60% improvement in convolutional neural network (CNN) performance on CIFAR10 dataset after 10000 inference operations as well as 78.6% error reduction in image reconstruction.Comment: This paper is submitted to IEEE Transactions Circuits and Systems II: Express Brief

Influence of primary particle polydispersity and overlapping on soot morphological parameters derived from numerical TEM images

Experimental studies of soot morphology based on analysis of transmission electron microscopy (TEM) images usually neglect the potential effects of primary particle polydispersity and overlapping. In this study, fractal aggregates of different sizes consisting of polydisperse and overlapping primary particles were numerically generated using typical fractal dimension and prefactor relevant to soot. A total of 3600 simulated two-dimensional projections for each primary particle size distribution and level of overlapping considered was produced and analyzed using two TEM image analysis methods commonly used in the literature to evaluate the effects of primary particle polydispersity and overlapping on the recovered morphological parameters of soot. Fairly large deviations in the recovered number of primary particles in aggregates were obtained by both methods considered using the procedure commonly used in the literature. A recommendation was proposed to improve the accuracy of the retrieved number of polydisperse primary particles in an aggregate. We show that the results obtained by using both the Tian et al. (2006) and Brasil et al. (1999) methods can be significantly improved by using the recommended modification for primary particle polydispersity levels commonly encountered in flame soot. Finally, we recommend to use the modified Tian et al. 2006 method for recovering the number of primary particles of aggregates consisting of both polydisperse and overlapped primary particles. Crown Copyright (C) 2018 Published by Elsevier B.V. All rights reserved

Uncooled IRFPA developments review

Abstract Today, large number of un cooled infrared detector developments are under progress due to the availability of silicon technology that enablesJealization of low cost 2D IR arrays. Development of such a structure involves a lot of trade-offs between the different parameters which characterize these detectors: • infrared flux absorption, • measurement of the temperature increase due to the incoming infrared flux absorption, • thermal insulation between detector and readout circuit, • readout of thermometer temperature variation. These trade-offs explain the number of different approaches that are under worldwide development. We present a rapid survey of the state of the art through these developments. LETlfUR has chosen resistive amorphous silicon as thermometer for his uncooled microbolometer development. After a first phase dedicated to the acquisition of the most important detector parameters in order to help the modeling and the technological development, an IRCMOS laboratory model (256 x 64 with a pitch of 50 I-Im) was realized and characterized. It was shown that NETD of 80 mK at ff1.25 Hz and 300 K background can be obtained with high thermal insulation (1.2 10 7 K/W)