5,270 research outputs found

    A replica free evaluation of the neuronal population information with mixed continuous and discrete stimuli: from the linear to the asymptotic regime

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    Recent studies have explored theoretically the ability of populations of neurons to carry information about a set of stimuli, both in the case of purely discrete or purely continuous stimuli, and in the case of multidimensional continuous angular and discrete correlates, in presence of additional quenched disorder in the distribution. An analytical expression for the mutual information has been obtained in the limit of large noise by means of the replica trick. Here we show that the same results can actually be obtained in most cases without the use of replicas, by means of a much simpler expansion of the logarithm. Fitting the theoretical model to real neuronal data, we show that the introduction of correlations in the quenched disorder improves the fit, suggesting a possible role of signal correlations-actually detected in real data- in a redundant code. We show that even in the more difficult analysis of the asymptotic regime, an explicit expression for the mutual information can be obtained without resorting to the replica trick despite the presence of quenched disorder, both with a gaussian and with a more realistic thresholded-gaussian model. When the stimuli are mixed continuous and discrete, we find that with both models the information seem to grow logarithmically to infinity with the number of neurons and with the inverse of the noise, even though the exact general dependence cannot be derived explicitly for the thresholded gaussian model. In the large noise limit lower values of information were obtained with the thresholded-gaussian model, for a fixed value of the noise and of the population size. On the contrary, in the asymptotic regime, with very low values of the noise, a lower information value is obtained with the gaussian model.Comment: 34 pages, 5 figure

    Estimating causal effects with matching methods in the presence and absence of bias cancellation

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    This paper explores the implications of possible bias cancellation using Rubin-style matching methods with complete and incomplete data. After reviewing the naïve causal estimator and the approaches of Heckman and Rubin to the causal estimation problem, we show how missing data can complicate the estimation of average causal effects in different ways, depending upon the nature of the missing mechanism. While - contrary to published assertions in the literature - bias cancellation does not generally occur when the multivariate distribution of the errors is symmetric, bias cancellation has been observed to occur for the case where selection into training is the treatment variable, and earnings is the outcome variable. A substantive rationale for bias cancellation is offered, which conceptualizes bias cancellation as the result of a mixture process based on two distinct individual-level decision-making models. While the general properties are unknown, the existence of bias cancellation appears to reduce the average bias in both OLS and matching methods relative to the symmetric distribution case. Analysis of simulated data under a set of difference scenarios suggests that matching methods do better than OLS in reducing that portion of bias that comes purely from the error distribution (i.e., from “selection on unobservables”). This advantage is often found also for the incomplete data case. Matching appears to offer no advantage over OLS in reducing the impact of bias due purely to selection on unobservable variables when the error variables are generated by standard multivariate normal distributions, which lack the bias-cancellation property. (AUTHORS)

    Replica symmetric evaluation of the information transfer in a two-layer network in presence of continuous+discrete stimuli

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    In a previous report we have evaluated analytically the mutual information between the firing rates of N independent units and a set of multi-dimensional continuous+discrete stimuli, for a finite population size and in the limit of large noise. Here, we extend the analysis to the case of two interconnected populations, where input units activate output ones via gaussian weights and a threshold linear transfer function. We evaluate the information carried by a population of M output units, again about continuous+discrete correlates. The mutual information is evaluated solving saddle point equations under the assumption of replica symmetry, a method which, by taking into account only the term linear in N of the input information, is equivalent to assuming the noise to be large. Within this limitation, we analyze the dependence of the information on the ratio M/N, on the selectivity of the input units and on the level of the output noise. We show analytically, and confirm numerically, that in the limit of a linear transfer function and of a small ratio between output and input noise, the output information approaches asymptotically the information carried in input. Finally, we show that the information loss in output does not depend much on the structure of the stimulus, whether purely continuous, purely discrete or mixed, but only on the position of the threshold nonlinearity, and on the ratio between input and output noise.Comment: 19 pages, 4 figure

    Perspective on saffron spice separation based on controlled fluid dynamic system and computer vision

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    To correctly develop, validate and mass-produce a saffron spice separation machine it is mandatory to particularly know physical and aerodynamics characteristics of the flower. To achieve this goal a wind tunnel is developed by the authors. The data obtained with the wind tunnel are used to get a rough calibration of a fluid dynamic separation device based on the differences of the terminal velocities of the parts that must be separated. To fine-tuning of the machine, a computer-vision system and a controller are developed to automatically adapt the machine parameter following the variability of the saffron spice

    Evaporation Channel as a Tool to Study Fission Dynamics

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    The dynamics of the fission process is expected to affect the evaporation residue cross section because of the fission hindrance due to the nuclear viscosity. Systems of intermediate fissility constitute a suitable environment for testing such hypothesis, since they are characterized by evaporation residue cross sections comparable or larger than the fission ones. Observables related to emitted charged particle, due to their relatively high emission probability, can be used to put stringent constraints on models describing the excited nucleus decay and to recognize the effects of fission dynamics. In this work model simulations are compared with the experimental data collected via the ^{32}S + ^{100}Mo reaction at E_{lab}= 200 MeV. By comparing an extended set of evaporation channel observables the limits of the statistical model and the large improvement coming by using a dynamical model are evidenced. The importance of using a large angular covering apparatus to extract the observable is stressed. The opportunity to measure more sensitive observables by a new detection device in operation at LNL are also discussed.Comment: v1: 7 pages, 6 figure

    Nanometer-scale Tomographic Reconstruction of 3D Electrostatic Potentials in GaAs/AlGaAs Core-Shell Nanowires

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    We report on the development of Electron Holographic Tomography towards a versatile potential measurement technique, overcoming several limitations, such as a limited tilt range, previously hampering a reproducible and accurate electrostatic potential reconstruction in three dimensions. Most notably, tomographic reconstruction is performed on optimally sampled polar grids taking into account symmetry and other spatial constraints of the nanostructure. Furthermore, holographic tilt series acquisition and alignment have been automated and adapted to three dimensions. We demonstrate 6 nm spatial and 0.2 V signal resolution by reconstructing various, previously hidden, potential details of a GaAs/AlGaAs core-shell nanowire. The improved tomographic reconstruction opens pathways towards the detection of minute potentials in nanostructures and an increase in speed and accuracy in related techniques such as X-ray tomography

    Does fairness matter? Consumers' perception of fairness in the agro-food chain

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    IntroductionDefining 'fairness' in the agro-food sector is a challenging task. There is no single definition of fairness and the literature does not provide a complete conceptualization from the consumer's point of view. The current research seeks to explore the consumers' interest in fairness and ethics in the agro-food chain by exploring (i) a comprehensive theoretical framework to conceptualize fairness from a consumer perspective, and (ii) the consumers' perceived importance of different food attributes as fairness-related aspects. MethodLiterature review and focus groups allowed for the creation of the final survey to be submitted to consumers. 529 valid responses from a predominantly Italian female sample were collected. Data were elaborated with Exploratory Factor Analysis and ANOVA test. ResultsThe research identified five dimensions of fairness: Fair price, environment, networking, short chain, and working condition. Also, it emerged that age influences consumers' perceived importance of products with fair attributes. DiscussionThis research contributes to the development of a fairer and more sustainable food system by identifying perceptions of agro-food chain fairness and establishing a link with food shopping intentions. The research provides companies with suggestions on how to expand sales by reaching a greater number of consumers

    Chocolate consumption and purchasing behaviour review: Research issues and insights for future research

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    Chocolate is consumed all over the world. Since its origin, it has undergone many transformations to meet changing market demand. A better understanding of consumer behaviour is a key objective of any business, and so it is for chocolate businesses. In order to fulfil this aim, the current study presents a systematic literature review of consumers' consumption and purchasing behaviour towards cocoa and chocolate. Two databases have been used to collect the literature: Scopus andWeb of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram was used to identify the articles through the process of data screening and extractions. A total of sixty-four scientific articles have been selected. Research topics, methodological approach and data collection method were identified for each article selected. Then, the identified topics were grouped into four categories in order to obtain a model of major determinants in chocolate consumption: personal preferences, product attributes, socio-demographic factors and economic attributes. Results show that there is a strong focus on Fair Trade in chocolate. Moreover, the current literature review supports the fact that the price and promotion are under-investigated issues. This research represents a valuable tool, especially from a marketing point of view, by creating new channels and new sales opportunities for chocolate products

    Sheet metal forming optimization methodology for servo press process control improvement

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    In sheet metal forming manufacturing operations the use of servo presses is gaining more interest due to the opportunity to improve process performance (quality, productivity, cost reduction, etc.). It is not yet clear how to proceed in the engineering process when this type of operating machine is used to achieve the maximum possible potential of this technology. Recently, several press builders have developed gap‐ and straight‐sided metal forming presses adopting the mechanical servo‐drive technology. The mechanical servo‐drive press offers the flexibility of a hydraulic press with the speed, accuracy and reliability of a mechanical press. Servo drive presses give the opportunity to improve the productivity of process conditions and improve the quality of stamped parts. Forming simulation and numerical optimization can be useful tools to define beforehand the optimal process parameter set‐up in terms of servo press downward curve properties. This is done by carrying out a sensitivity analysis of the forming parameters having influence on said curve. The authors have developed a numerical methodology able to analyze the influence factors, for comparison with the degrees of freedom made available by the usage of a servo press, in terms of stroke profile management, to obtain an optimized process parameters combination
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