Present simple and continuous: emergence of self-regulation and contextual sophistication in adolescent decision-making

Sophisticated, intentional decision-making is a hallmark of mature, self-aware behaviour. Although neural, psychological, interpersonal, and socioeconomic elements that contribute to such adaptive, foresighted behaviour mature and/or change throughout the life-span, here we concentrate on relevant maturational processes that take place during adolescence, a period of disproportionate developmental opportunity and risk. A brief, eclectic overview is presented of recent evidence, new challenges, and current thinking on the fundamental mechanisms that mature throughout adolescence to support adaptive, self-controlled decision-making. This is followed by a proposal for the putative contribution of frontostriatal mechanisms to the moment-to-moment assembly of evaluative heuristics that mediate increased decision-making sophistication, promoting the maturation of self-regulated behaviour through adolescence and young adulthood.

Computationally efficient rule-based classification for continuous streaming data

Advances in hardware and software technologies allow to capture streaming data. The area of Data Stream Mining (DSM) is concerned with the analysis of these vast amounts of data as it is generated in real-time. Data stream classification is one of the most important DSM techniques allowing to classify previously unseen data instances. Different to traditional classifiers for static data, data stream classifiers need to adapt to concept changes (concept drift) in the stream in real-time in order to reflect the most recent concept in the data as accurately as possible. A recent addition to the data stream classifier toolbox is eRules which induces and updates a set of expressive rules that can easily be interpreted by humans. However, like most rule-based data stream classifiers, eRules exhibits a poor computational performance when confronted with continuous attributes. In this work, we propose an approach to deal with continuous data effectively and accurately in rule-based classifiers by using the Gaussian distribution as heuristic for building rule terms on continuous attributes. We show on the example of eRules that incorporating our method for continuous attributes indeed speeds up the real-time rule induction process while maintaining a similar level of accuracy compared with the original eRules classifier. We termed this new version of eRules with our approach G-eRules.

Automated identification of neural correlates of continuous variables

Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.

First-principles study of the inversion thermodynamics and electronic structure of FeM2X4 (thio)spinels (M = Cr, Mn, Co, Ni; X = O, S)

FeM2X4 spinels, where M is a transition metal and X is oxygen or sulfur, are candidate materials for spin filters, one of the key devices in spintronics. We present here a computational study of the inversion thermodynamics and the electronic structure of these (thio)spinels for M = Cr, Mn, Co, Ni, using calculations based on the density functional theory with on-site Hubbard corrections (DFT+U). The analysis of the configurational free energies shows that different behaviour is expected for the equilibrium cation distributions in these structures: FeCr2X4 and FeMn2S4 are fully normal, FeNi2X4 and FeCo2S4 are intermediate, and FeCo2O4 and FeMn2O4 are fully inverted. We have analyzed the role played by the size of the ions and by the crystal field stabilization effects in determining the equilibrium inversion degree. We also discuss how the electronic and magnetic structure of these spinels is modified by the degree of inversion, assuming that this could be varied from the equilibrium value. We have obtained electronic densities of states for the completely normal and completely inverse cation distribution of each compound. FeCr2X4, FeMn2X4, FeCo2O4 and FeNi2O4 are half-metals in the ferrimagnetic state when Fe is in tetrahedral positions. When M is filling the tetrahedral positions, the Cr-containing compounds and FeMn2O4 are half-metallic systems, while the Co and Ni spinels are insulators. The Co and Ni sulfide counterparts are metallic for any inversion degree together with the inverse FeMn2S4. Our calculations suggest that the spin filtering properties of the FeM2X4 (thio)spinels could be modified via the control of the cation distribution through variations in the synthesis conditions.

Brain-computer music interfacing for continuous control of musical tempo

A Brain-computer music interface (BCMI) is developed to allow for continuous modification of the tempo of dynamically generated music. Six out of seven participants are able to control the BCMI at significant accuracies and their performance is observed to increase over time.

Shape-controlled continuous synthesis of metal nanostructures

A segmented flow-based microreactor is used for the continuous production of faceted nanocrystals. Flow segmentation is proposed as a versatile tool to manipulate the reduction kinetics and control the growth of faceted nanostructures; tuning the size and shape. Switching the gas from oxygen to carbon monoxide permits the adjustment in nanostructure growth from 1D (nanorods) to 2D (nanosheets). CO is a key factor in the formation of Pd nanosheets and Pt nanocubes; operating as a second phase, a reductant, and a capping agent. This combination confines the growth to specific structures. In addition, the segmented flow microfluidic reactor inherently has the ability to operate in a reproducible manner at elevated temperatures and pressures whilst confining potentially toxic reactants, such as CO, in nanoliter slugs. This continuous system successfully synthesised Pd nanorods with an aspect ratio of 6; thin palladium nanosheets with a thickness of 1.5 nm; and Pt nanocubes with a 5.6 nm edge length, all in a synthesis time as low as 150 s.

An accelerating cosmology without dark energy

The negative pressure accompanying gravitationally-induced particle creation can lead to a cold dark matter (CDM) dominated, accelerating Universe (Lima et al. 1996 [1]) without requiring the presence of dark energy or a cosmological constant. In a recent study, Lima et al. 2008 [2] (LSS) demonstrated that particle creation driven cosmological models are capable of accounting for the SNIa observations [3] of the recent transition from a decelerating to an accelerating Universe, without the need for Dark Energy. Here we consider a class of such models where the particle creation rate is assumed to be of the form Gamma = beta H + gamma H(0), where H is the Hubble parameter and H(0) is its present value. The evolution of such models is tested at low redshift by the latest SNe Ia data provided by the Union compilation [4] and at high redshift using the value of z(eq), the redshift of the epoch of matter - radiation equality, inferred from the WMAP constraints on the early Integrated Sachs-Wolfe (ISW) effect [5]. Since the contributions of baryons and radiation were ignored in the work of LSS, we include them in our study of this class of models. The parameters of these more realistic models with continuous creation of CDM are constrained at widely-separated epochs (z(eq) approximate to 3000 and z approximate to 0) in the evolution of the Universe. The comparison of the parameter values, {beta, gamma}, determined at these different epochs reveals a tension between the values favored by the high redshift CMB constraint on z(eq) from the ISW and those which follow from the low redshift SNIa data, posing a potential challenge to this class of models. While for beta = 0 this conflict is only at less than or similar to 2 sigma, it worsens as beta increases from zero.

On phantom thermodynamics

The thermodynamic properties of dark energy fluids described by an equation of state parameter omega = p/rho are rediscussed in the context of FRW type geometries. Contrarily to previous claims, it is argued here that the phantom regime omega < -1 is not physically possible since that both the temperature and the entropy of every physical fluids must be always positive definite. This means that one cannot appeal to negative temperature in order to save the phantom dark energy hypothesis as has been recently done in the literature. Such a result remains true as long as the chemical potential is zero. However, if the phantom fluid is endowed with a non-null chemical potential, the phantom field hypothesis becomes thermodynamically consistent, that is, there are macroscopic equilibrium states with T > 0 and S > 0 in the course of the Universe expansion. (C) 2008 Elsevier B.V. All rights reserved.

Cladistic analysis of continuous modularized traits provides phylogenetic signals in Homo evolution

Evolutionary novelties in the skeleton are usually expressed as changes in the timing of growth of features intrinsically integrated at different hierarchical levels of development(1). As a consequence, most of the shape- traits observed across species do vary quantitatively rather than qualitatively(2), in a multivariate space(3) and in a modularized way(4,5). Because most phylogenetic analyses normally use discrete, hypothetically independent characters(6), previous attempts have disregarded the phylogenetic signals potentially enclosed in the shape of morphological structures. When analysing low taxonomic levels, where most variation is quantitative in nature, solving basic requirements like the choice of characters and the capacity of using continuous, integrated traits is of crucial importance in recovering wider phylogenetic information. This is particularly relevant when analysing extinct lineages, where available data are limited to fossilized structures. Here we show that when continuous, multivariant and modularized characters are treated as such, cladistic analysis successfully solves relationships among main Homo taxa. Our attempt is based on a combination of cladistics, evolutionary- development- derived selection of characters, and geometric morphometrics methods. In contrast with previous cladistic analyses of hominid phylogeny, our method accounts for the quantitative nature of the traits, and respects their morphological integration patterns. Because complex phenotypes are observable across different taxonomic groups and are potentially informative about phylogenetic relationships, future analyses should point strongly to the incorporation of these types of trait.

Continuous and High-Level In Vivo Delivery of Endostatin From Recombinant Cells Encapsulated in TheraCyte (R) Immunoisolation Devices

Endostatin (ES) is a potent inhibitor of angiogenesis and tumor growth. Continuous ES delivery of ES improves the efficacy and potency of the antitumoral therapy. The TheraCyte (R) system is a polytetrafluoroethylene (PTFE) semipermeable membrane macroencapsulation system for implantation of genetically engineered cells specially designed for the in vivo delivery of therapeutic proteins, such as ES, which circumvents the problem of limited half-life and variation in circulating levels. In order to enable neovascularization at the tissues adjacent to the devices prior to ES secretion by the cells inside them, we designed a scheme in which empty TheraCyte (R) devices were preimplanted SC into immunodeficient mice. Only after healing (17 days later) were Chinese hamster ovary cells expressing ES injected into the preimplanted devices. In another model for device implantation, the cells expressing ES where loaded into the immunoisolation devices prior to implantation into the animals, and the TheraCyte (R) were then immediately implanted SC into the mice. Throughout the 2-month study, constant high ES levels of up to 3.7 mu g/ml were detected in the plasma of the mice preimplanted with the devices, while lower but also constant levels of ES (up to 2.1 mu g/ml plasma) were detected in the mice that had received devices preloaded with the ES-expressing cells. Immunohistochemistry using anti-ES antibody showed reaction within the device and outside it, demonstrating that ES, secreted by the confined recombinant cells, permeated through the membrane and reached the surrounding tissues.

THE POINCARE-BENDIXSON THEOREM ON THE KLEIN BOTTLE FOR CONTINUOUS VECTOR FIELDS

We present a version of the Poincare-Bendixson Theorem on the Klein bottle K(2) for continuous vector fields. As a consequence, we obtain the fact that K(2) does not admit continuous vector fields having a omega-recurrent injective trajectory.

THE IMPLICIT FUNCTION THEOREM FOR CONTINUOUS FUNCTIONS

In the present paper we obtain a new homological version of the implicit function theorem and some versions of the Darboux theorem. Such results are proved for continuous maps on topological manifolds. As a consequence. some versions of these classic theorems are proved when we consider differenciable (not necessarily C-1) maps.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Aerosol inorganic composition at a tropical site: Discrepancies between filter-based sampling and a semi-continuous method

The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.

New mechanical samples positioning system for irradiations on a radial channel at nuclear research reactor in a full-power continuous operation

This paper describes a new mechanical samples positioning system that allows the safe placement and removal of biological samples for prolonged irradiation, in a nuclear reactor during full-power continuous operation. Also presented herein the materials of construction and operating principles. Additionally, this sample positioning system is compared with an existing pneumatic and automated transfer system, already available at the research reactors. The system consists of a mechanical arm with a claw, which can deliver the samples for irradiations without reactor shutdown. It was installed in the lEA-R1 research reactor at Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, Brazil, and for the past 5 years, the system has successfully operated and allowed the conducting of important experiments. As a result of its introduction, the facility has been in a position to positively respond to the increased demand in studies of biology, medicine, physics, engineering, detector/dosimeter calibrations, etc. It is one example of the appropriated technologies that save energy and resources. (C) 2010 Elsevier Ltd. All rights reserved.