Learning processes and the neural analysis of conditioning

Classical and operant conditioning principles, such as the behavioral discrepancy-derived assumption that reinforcement always selects antecedent stimulus and response relations, have been studied at the neural level, mainly by observing the strengthening of neuronal responses or synaptic connections. A review of the literature on the neural basis of behavior provided extensive scientific data that indicate a synthesis between the two conditioning processes based mainly on stimulus control in learning tasks. The resulting analysis revealed the following aspects. Dopamine acts as a behavioral discrepancy signal in the midbrain pathway of positive reinforcement, leading toward the nucleus accumbens. Dopamine modulates both types of conditioning in the Aplysia mollusk and in mammals. In vivo and in vitro mollusk preparations show convergence of both types of conditioning in the same motor neuron. Frontal cortical neurons are involved in behavioral discrimination in reversal and extinction procedures, and these neurons preferentially deliver glutamate through conditioned stimulus or discriminative stimulus pathways. Discriminative neural responses can reliably precede operant movements and can also be common to stimuli that share complex symbolic relations. The present article discusses convergent and divergent points between conditioning paradigms at the neural level of analysis to advance our knowledge on reinforcement.

Polar organic marker compounds in atmospheric aerosols during the LBA-SMOCC 2002 biomass burning experiment in Rondonia, Brazil: sources and source processes, time series, diel variations and size distributions

Measurements of polar organic marker compounds were performed on aerosols that were collected at a pasture site in the Amazon basin (Rondonia, Brazil) using a high-volume dichotomous sampler (HVDS) and a Micro-Orifice Uniform Deposit Impactor (MOUDI) within the framework of the 2002 LBA-SMOCC (Large-Scale Biosphere Atmosphere Experiment in Amazonia - Smoke Aerosols, Clouds, Rainfall, and Climate: Aerosols From Biomass Burning Perturb Global and Regional Climate) campaign. The campaign spanned the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). In the present study a more detailed discussion is presented compared to previous reports on the behavior of selected polar marker compounds, including levoglucosan, malic acid, isoprene secondary organic aerosol (SOA) tracers and tracers for fungal spores. The tracer data are discussed taking into account new insights that recently became available into their stability and/or aerosol formation processes. During all three periods, levoglucosan was the most dominant identified organic species in the PM(2.5) size fraction of the HVDS samples. In the dry period levoglucosan reached concentrations of up to 7.5 mu g m(-3) and exhibited diel variations with a nighttime prevalence. It was closely associated with the PM mass in the size-segregated samples and was mainly present in the fine mode, except during the wet period where it peaked in the coarse mode. Isoprene SOA tracers showed an average concentration of 250 ng m(-3) during the dry period versus 157 ng m(-3) during the transition period and 52 ng m(-3) during the wet period. Malic acid and the 2-methyltetrols exhibited a different size distribution pattern, which is consistent with different aerosol formation processes (i.e., gas-to-particle partitioning in the case of malic acid and heterogeneous formation from gas-phase precursors in the case of the 2-methyltetrols). The 2-methyltetrols were mainly associated with the fine mode during all periods, while malic acid was prevalent in the fine mode only during the dry and transition periods, and dominant in the coarse mode during the wet period. The sum of the fungal spore tracers arabitol, mannitol, and erythritol in the PM(2.5) fraction of the HVDS samples during the dry, transition, and wet periods was, on average, 54 ng m(-3), 34 ng m(-3), and 27 ng m(-3), respectively, and revealed minor day/night variation. The mass size distributions of arabitol and mannitol during all periods showed similar patterns and an association with the coarse mode, consistent with their primary origin. The results show that even under the heavy smoke conditions of the dry period a natural background with contributions from bioaerosols and isoprene SOA can be revealed. The enhancement in isoprene SOA in the dry season is mainly attributed to an increased acidity of the aerosols, increased NO(x) concentrations and a decreased wet deposition.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

Shared information in stationary states of stochastic processes

We present four estimators of the shared information (or interdepency) in ground states given that the coefficients appearing in the wave function are all real non-negative numbers and therefore can be interpreted as probabilities of configurations. Such ground states of Hermitian and non-Hermitian Hamiltonians can be given, for example, by superpositions of valence bond states which can describe equilibrium but also stationary states of stochastic models. We consider in detail the last case, the system being a classical not a quantum one. Using analytical and numerical methods we compare the values of the estimators in the directed polymer and the raise and peel models which have massive, conformal invariant and nonconformal invariant massless phases. We show that like in the case of the quantum problem, the estimators verify the area law with logarithmic corrections when phase transitions take place.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

Collision probabilities in the rarefaction fan of asymmetric exclusion processes

We consider the one-dimensional asymmetric simple exclusion process (ASEP) in which particles jump to the right at rate p is an element of (1/2, 1.] and to the left at rate 1 - p, interacting by exclusion. In the initial state there is a finite region such that to the left of this region all sites are occupied and to the right of it all sites are empty. Under this initial state, the hydrodynamical limit of the process converges to the rarefaction fan of the associated Burgers equation. In particular suppose that the initial state has first-class particles to the left of the origin, second-class particles at sites 0 and I, and holes to the right of site I. We show that the probability that the two second-class particles eventually collide is (1 + p)/(3p), where a collision occurs when one of the particles attempts to jump over the other. This also corresponds to the probability that two ASEP processes. started from appropriate initial states and coupled using the so-called ""basic coupling,"" eventually reach the same state. We give various other results about the behaviour of second-class particles in the ASEP. In the totally asymmetric case (p = 1) we explain a further representation in terms of a multi-type particle system, and also use the collision result to derive the probability of coexistence of both clusters in a two-type version of the corner growth model.

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Hitting and returning to rare events for all alpha-mixing processes

We prove that for any a-mixing stationary process the hitting time of any n-string A(n) converges, when suitably normalized, to an exponential law. We identify the normalization constant lambda(A(n)). A similar statement holds also for the return time. To establish this result we prove two other results of independent interest. First, we show a relation between the rescaled hitting time and the rescaled return time, generalizing a theorem of Haydn, Lacroix and Vaienti. Second, we show that for positive entropy systems, the probability of observing any n-string in n consecutive observations goes to zero as n goes to infinity. (c) 2010 Elsevier B.V. All rights reserved.

Gibbs random graphs on point processes

Consider a discrete locally finite subset Gamma of R(d) and the cornplete graph (Gamma, E), with vertices Gamma and edges E. We consider Gibbs measures on the set of sub-graphs with vertices Gamma and edges E` subset of E. The Gibbs interaction acts between open edges having a vertex in common. We study percolation properties of the Gibbs distribution of the graph ensemble. The main results concern percolation properties of the open edges in two cases: (a) when Gamma is sampled from a homogeneous Poisson process; and (b) for a fixed Gamma with sufficiently sparse points. (c) 2010 American Institute of Physics. [doi:10.1063/1.3514605]

Influence of land-use change on near-surface hydrological processes: Undisturbed forest to pasture

Soil compaction that follows the clearing of tropical forest for cattle pasture is associated with lower soil hydraulic conductivity and increased frequency and volume of overland flow. We investigated the frequency of perched water tables, overland flow and stormflow in an Amazon forest and in an adjacent 25-year-old pasture cleared from the same forest. We compared the results with the frequencies of these phenomena estimated from comparisons of rainfall intensity and soil hydraulic conductivity. The frequency of perched water tables based on rainfall intensity and soil hydraulic conductivity was expected to double in pasture compared with forest. This corresponded closely with an approximate doubling of the frequency of stormflow and overland flow in pasture. In contrast, the stormflow volume in pasture increased 17-fold. This disproportional increase of stormflow resulted from overland flow generation over large areas of pasture, while overland flow generation in the forest was spatially limited and was observed only very near the stream channel. In both catchments, stormflow was generated by saturation excess because of perched water tables and near-surface groundwater levels. Stormflow was occasionally generated in the forest by rapid return flow from macropores, while slow return flow from a continuous perched water table was more common in the pasture. These results suggest that deforestation for pasture alters fundamental mechanisms of stormflow generation and may increase runoff volumes over wide regions of Amazonia. (C) 2009 Elsevier B.V. All rights reserved.

Stratigraphy of near-valley head quaternary deposits and evidence of climate-driven slope-channel processes in southern Brazilian highlands

During the past 40 years colluvial and alluvial deposits have been used in Brazil as good indicators of regional landscape sensitivity to Quaternary environmental changes. In spite of the low resolution of most of the continental sedimentary record, geomorphology and sedimentology may favor palaeoenvironmental interpretation when supported by independent proxy data. This paper presents results obtained from pedostratigraphic sequences, in near-valley head sites of southern Brazilian highlands, based on geomorphologic. sedimentologic, micromorphologic, isotopic and palynologic data. Results point to environmental changes, with ages that coincide with Marine Isotopic Stages (MIS) 5b; 3; 2 and 1. During the late Pleistocene, although under temperatures and precipitation lower than today, the local record points to relatively wet local environments, where shallow soil-water saturated zones contributed to erosion and sedimentation during periods of climatic change, as during the transition between MIS 2 and MIS 1. Late Pleistocene events with ages that coincide with the Northern Hemisphere Younger Dryas are also depicted. During the mid Holocene, slope-wash deposits suggest a climate drier than today, probably under the influence of seasonally contrasted precipitation regimes. The predominance of overland flow-related sedimentary deposits suggests an excess of precipitation over evaporation that influenced local palaeohydrology. This environmental condition seems to be recurrent and explains how slope morphology had influenced pedogenesis and sedimentation in the study area. Due to relative sensitiveness, resilience and short source-to-sink sedimentary pathways, near-valley head sites deserve further attention in Quaternary studies in the humid tropics. (c) 2008 Elsevier B.A. All rights reserved.

Combined photocatalytic and fungal processes for the treatment of nitrocellulose industry wastewater

The objective of this work was to characterize the delignification effluent originating from the delignification industry and evaluate the combination of the fungus and photocatalytic process (TiO(2)/UV system) for the treatment of this effluent. The delignification effluent has proven harmful to the environment because it presents high color (3516 CU), total phenol (876 mg/L and TOC (1599 mg/L) and is also highly toxic even in a low concentration. The results of photocatalysis were 11%, 25% and 13% higher for reductions in color, total phenol and TOC, respectively. The combined treatments presented benefits when compared to the non-combined treatments. Fungus and photocatalysis in combination proved to be the best treatment, reducing the color, total phenol, toxicity (inhibition of Escherichia coli growth) and TOC by 94.2%, 92.6%, 4.9% and 62%, respectively. (C) 2008 Elsevier B.V. All rights reserved.

High gravity batch and continuous processes for beer production: Evaluation of fermentation performance and beer quality

This study deals with two innovative brewing processes, high gravity batch and complete continuous beer fermentation systems. The results show a significant influence of the variables such as concentration and temperature on the yield factor of the substrate into ethanol and consequently on the productivity of the high gravity batch process. The technological feasibility of continuous production of beer based on yeast immobilization on cheap alternative carriers was also demonstrated. The influence of process parameters on fermentation performance and quality of the obtained beers was studied by sensorial analysis. No significant difference in the degree of acceptance between the obtained products and some traditional market brands was found. (c) 2008 Institute of Chemistry, Slovak Academy of Sciences.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

Microbial processes and bacterial populations associated to anaerobic treatment of sulfate-rich wastewater

A pilot-scale (1.2 m(3)) anaerobic sequencing batch biofilm reactor (ASBBR) containing mineral coal for biomass attachment was fed with sulfate-rich wastewater at increasing sulfate concentrations. Ethanol was used as the main organic source. Tested COD/sulfate ratios were of 1.8 and 1.5 for sulfate loading rates of 0.65-1.90 kgSO(4)(2-)/cycle (48 h-cycle) or of 1.0 in the trial with 3.0 gSO(4)(2-) l(-1). Sulfate removal efficiencies observed in all trials were as high as 99%. Molecular inventories indicated a shift on the microbial composition and a decrease on species diversity with the increase of sulfate concentration. Beta-proteobacteria species affiliated with Aminomonas spp. and Thermanaerovibrio spp. predominated at 1.0 gSO(4)(2-) l(-1). At higher sulfate concentrations the predominant bacterial group was Delta-proteobacteria mainly Desulfovibrio spp. and Desulfomicrobium spp. at 2.0 gSO(4)(2-) l(-1), whereas Desulfurella spp. and Coprothermobacter spp. predominated at 3.0 gSO(4)(2-) l(-1). These organisms have been commonly associated with sulfate reduction producing acetate, sulfide and sulfur. Methanogenic archaea(Methanosaeta spp.)was found at 1.0 and 2.0 gSO(4)(2-) l(-1). Additionally, a simplified mathematical model was used to infer on metabolic pathways of the biomass involved in sulfate reduction. (C) 2009 Elsevier Ltd. All rights reserved.