Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.This work is funded by National Funds through the FCT, Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within projects PEstOE/EEI/UI0752/2014 and PEst-OE/QUI/UI0619/2012

Modulating spin transfer torque switching dynamics with two orthogonal spin-polarizers by varying the cell aspect ratio

We study in-plane magnetic tunnel junctions with additional perpendicular polarizer for subnanosecond-current-induced switching memories. The spin-transfer-torque switching dynamics was studied as a function of the cell aspect ratio both experimentally and by numerical simulations using the macrospin model. We show that the anisotropy field plays a significant role in the dynamics, along with the relative amplitude of the two spin-torque contributions. This was confirmed by micromagnetic simulations. Real-time measurements of the reversal were performed with samples of low and high aspect ratio. For low aspect ratios, a precessional motion of the magnetization was observed and the effect of temperature on the precession coherence was studied. For high aspect ratios, we observed magnetization reversals in less than 1 ns for high enough current densities, the final state being controlled by the current direction in the magnetic tunnel junction cell.Comment: 6 pages, 7 figure

One session of fMRI-Neurofeedback training on motor imagery modulates whole-brain effective connectivity and dynamical complexity

In the past decade, several studies have shown that Neurofeedback (NFB) by functional magnetic resonance imaging can alter the functional coupling of targeted and non-targeted areas. However, the causal mechanisms underlying these changes remain uncertain. Here, we applied a whole-brain dynamical model to estimate Effective Connectivity (EC) profiles of resting-state data acquired before and immediately after a single-session NFB training for 17 participants who underwent motor imagery NFB training and 16 healthy controls who received sham feedback. Within-group and between-group classification analyses revealed that only for the NFB group it was possible to accurately discriminate between the 2 resting-state sessions. NFB training-related signatures were reflected in a support network of direct connections between areas involved in reward processing and implicit learning, together with regions belonging to the somatomotor, control, attention, and default mode networks, identified through a recursive-feature elimination procedure. By applying a data-driven approach to explore NFB-induced changes in spatiotemporal dynamics, we demonstrated that these regions also showed decreased switching between different brain states (i.e. metastability) only following real NFB training. Overall, our findings contribute to the understanding of NFB impact on the whole brain's structure and function by shedding light on the direct connections between brain areas affected by NFB training

Deposition of silicon nitride thin films by hot-wire CVD at 100ºC and 250ºC

Silicon nitride thin films for use as passivation layers in solar cells and organic electronics or as gate dielectrics in thin-film transistors were deposited by the Hot-wire chemical vapor deposition technique at a high deposition rate (1-3 Ǻ/s) and at low substrate temperature. Films were deposited using NH3/SiH4 flow rate ratios between 1 and 70 and substrate temperatures of 100º C and 250ºC. For NH3/SiH4 ratios between 40 and 70, highly transparent (T ~ 90%), dense films (2.56 - 2.74 g/cm3) with good dielectric properties and refractive index between 1.93 and 2.08 were deposited on glass substrates. Etch rates in BHF of 2.7 Ǻ/s and 10 MV cm−1.Fundação para a Ciência e Tecnologia (FCT) - FCT/CNRS programa com o contracto no. 20798, bolsa de investigaçao e projecto PTDC-CTM-66558-200

Meditation-induced effects on whole-brain structural and effective connectivity

In the past decades, there has been a growing scientific interest in characterizing neural correlates of meditation training. Nonetheless, the mechanisms underlying meditation remain elusive. In the present work, we investigated meditation-related changes in functional dynamics and structural connectivity (SC). For this purpose, we scanned experienced meditators and control (naive) subjects using magnetic resonance imaging (MRI) to acquire structural and functional data during two conditions, resting-state and meditation (focused attention on breathing). In this way, we aimed to characterize and distinguish both short-term and long-term modifications in the brain's structure and function. First, to analyze the fMRI data, we calculated whole-brain effective connectivity (EC) estimates, relying on a dynamical network model to replicate BOLD signals' spatio-temporal structure, akin to functional connectivity (FC) with lagged correlations. We compared the estimated EC, FC, and SC links as features to train classifiers to predict behavioral conditions and group identity. Then, we performed a network-based analysis of anatomical connectivity. We demonstrated through a machine-learning approach that EC features were more informative than FC and SC solely. We showed that the most informative EC links that discriminated between meditators and controls involved several large-scale networks mainly within the left hemisphere. Moreover, we found that differences in the functional domain were reflected to a smaller extent in changes at the anatomical level as well. The network-based analysis of anatomical pathways revealed strengthened connectivity for meditators compared to controls between four areas in the left hemisphere belonging to the somatomotor, dorsal attention, subcortical and visual networks. Overall, the results of our whole-brain model-based approach revealed a mechanism underlying meditation by providing causal relationships at the structure-function level

Hydrochemistry and trophic state change in a large reservoir in the Brazilian northeast region under intense drought conditions

The study shows changes on physical and chemical water parameters and of trophic state in a large reservoir in the Brazilian semiarid region following decreasing reservoir volume due to rainfall shortage during four consecutive years. The monitoring period, between November 2011 and May 2014, assessed approximately 50% water volume reduction and 10 meters’ decrease of reservoir water level that degraded water quality. Decrease in reservoir volume, strong evaporation and the permanent influence of anthropogenic activities, favored the concentration of salts and accumulation of nutrients and of increasing pH. Thermal stratification of the water column occurred when volume was maximum and lead to a significant reduction in dissolved oxygen in the hypolimnion (0.07 to 2.62 mg L–1). Diminishing volume resulted in mixing of the hypolimnion nutrient-rich and oxygen-poor waters in the entre water column and changed the initial oligotrophic condition to eutrophic. However, the temporal scale of the response of the reservoir’s trophic state differs in the different areas of the reservoir. Whereas deeper areas accumulating nutrients from aquaculture and agriculture progressively became mesotrophic and eventually eutrophic; shallower regions far from direct anthropogenic influences, changed their trophic sate much later, but rapidly turned into super-eutrophic conditions, probably due to more intense sediment resuspension and water mixing. Trophic State Index followed nutrient increase during most of the period. However, it also responded to an increase in chlorophyll a concentrations when the reservoir achieved its minimum volume, in particular in the shallower areas. The results suggest that this type of reservoir systems are vulnerable to eutrophication during extended drought periods and that a better assessment of the maximum support capacity for reservoir activities, particularly aquaculture, must be re-assessed taking into consideration worst case scenarios forecasted by global climate change

RESÍDUOS ALIMENTARES NO EXAME ANTIDOPING EQUINO

O doping é descrito no turfe como aplicação ilegal de medicamentos, substâncias ou qualquer agente físico capaz de alterar, efetiva ou potencialmente, o desempenho do cavalo, com a finalidade de favorecer transações desonestas e fraudulentas. Esta revisão tem como objetivo discutir sobre as principais substâncias contaminantes de origem alimentar, bem como se a presença ou não de alguma substância ilícita ou seu metabólito interfere na performance do animal atleta. PALAVRAS-CHAVE: Cavalo, doping, droga, nutrição

Higher Order Statistics in a mmWave Propagation Environment

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] A thorough measurement campaign in an indoor environment at the millimeter-wave band is carried out with an aim at characterizing the short-term fading channel in terms of its higher-order statistics. The measurements are conducted in a variety of scenarios, with frequencies ranging from 55 to 65 GHz, in line-of-sight and non-line-of-sight conditions, and combinations of horizontal and vertical polarizations at both the transmitter and the receiver. A number of fading models are tested, namely Rayleigh, Rice, Nakagami-m, alpha-mu, kappa-mu, eta-mu, and alpha-eta-kappa-mu. The main second-order statistics under analysis are the level crossing rate (LCR) and average fade duration (AFD) both given per distance unit. From the experimental data, the parameters of these statistics are estimated, and the corresponding curves of the theoretical models are compared with the empirical ones and the best model is selected. Additionally, the study of the very general distribution, namely alpha-eta-kappa-mu, is advanced, in which new expressions for time-/distance-domain LCR and Al-ll are derived using an envelope-based approach. Such an approach leads to integral-form formulations with much less computational complexity and computes rapidly compared with the already existing ones presented elsewhere, also given in the integral form. Furthermore, a series of expansion expression for the alpha-eta-kappa-mu time-/distance-domain LCR is then derived that improves even further the computational time.This work was supported in part by the Conselho Nacional de Desenvolvimento Cientico e Tecnologico (CNPq) under Grant 304248/2014-2 and Grant 308365/2017-8, in part by the Rede Nacional de Ensino e Pesquisa (RNP), with resources from Ministerio da Ciencia, Tecnologia, Inovacoes e Comunicacoes (MCTIC), through the Radiocommunication Reference Center [Centro de Referencia em Radiocomunicacoes (CRR)] Project of the National Institute of Telecommunications [Instituto Nacional de Telecomunicacoes (INATEL)], Brazil, under Grant 01250.075413/2018-04, and in part by the Ministerio de Economia, Industria y Competitividad of the Spanish Government through the Agencia Estatal de Investigacion (AEI) and the Fondo Europeo de Desarrollo Regional (FEDER) under Project TEC2017-86779-C2-2-R.Dos Anjos, AA.; Rufino-Marins, TR.; Nogueira Da Silva, CR.; Rodrigo Peñarrocha, VM.; Rubio Arjona, L.; Reig, J.; Amaral De Souza, RA.... (2019). Higher Order Statistics in a mmWave Propagation Environment. IEEE Access. 7:103876-103892. https://doi.org/10.1109/ACCESS.2019.2930931S103876103892

The BINGO project: VII. Cosmological forecasts from 21 cm intensity mapping

Context. The 21 cm line of neutral hydrogen (HI) opens a new avenue in our exploration of the structure and evolution of the Universe. It provides complementary data to the current large-scale structure (LSS) observations with different systematics, and thus it will be used to improve our understanding of the Icold dark matter (ICDM) model. This will ultimately constrain our cosmological models, attack unresolved tensions, and test our cosmological paradigm. Among several radio cosmological surveys designed to measure this line, BINGO is a single-dish telescope mainly designed to detect baryon acoustic oscillations (BAOs) at low redshifts (0.127 < z < 0.449). Aims. Our goal is to assess the fiducial BINGO setup and its capabilities of constraining the cosmological parameters, and to analyze the effect of different instrument configurations. Methods. We used the 21 cm angular power spectra to extract cosmological information about the HI signal and the Fisher matrix formalism to study BINGO's projected constraining power. Results. We used the Phase 1 fiducial configuration of the BINGO telescope to perform our cosmological forecasts. In addition, we investigated the impact of several instrumental setups, taking into account some instrumental systematics, and different cosmological models. Combining BINGO with Planck temperature and polarization data, the projected constraint improves from a 13% and 25% precision measurement at the 68% confidence level with Planck only to 1% and 3% for the Hubble constant and the dark energy (DE) equation of state (EoS), respectively, within the wCDM model. Assuming a Chevallier- Polarski- Linder (CPL) parameterization, the EoS parameters have standard deviations given by w0 = 0.30 and wa = 1.2, which are improvements on the order of 30% with respect to Planck alone. We also compared BINGO's fiducial forecast with future SKA measurements and found that, although it will not provide competitive constraints on the DE EoS, significant information about HI distribution can be acquired. We can access information about the HI density and bias, obtaining 8.5% and 6% precision, respectively, assuming they vary with redshift at three independent bins. BINGO can also help constrain alternative models, such as interacting dark energy and modified gravity models, improving the cosmological constraints significantly. Conclusions. The fiducial BINGO configuration will be able to extract significant cosmological information from the HI distribution and provide constraints competitive with current and future cosmological surveys. It will also help in understanding the HI physics and systematic effects

The BINGO project: V. Further steps in component separation and bispectrum analysis

Context. Observing the neutral hydrogen distribution across the Universe via redshifted 21 cm line intensity mapping constitutes a powerful probe for cosmology. However, the redshifted 21 cm signal is obscured by the foreground emission from our Galaxy and other extragalactic foregrounds. This paper addresses the capabilities of the BINGO survey to separate such signals. Aims. We show that the BINGO instrumental, optical, and simulations setup is suitable for component separation, and that we have the appropriate tools to understand and control foreground residuals. Specifically, this paper looks in detail at the different residuals left over by foreground components, shows that a noise-corrected spectrum is unbiased, and shows that we understand the remaining systematic residuals by analyzing nonzero contributions to the three-point function. Methods. We use the generalized needlet internal linear combination, which we apply to sky simulations of the BINGO experiment for each redshift bin of the survey. We use binned estimates of the bispectrum of the maps to assess foreground residuals left over after component separation in the final map. Results. We present our recovery of the redshifted 21 cm signal from sky simulations of the BINGO experiment, including foreground components. We test the recovery of the 21 cm signal through the angular power spectrum at different redshifts, as well as the recovery of its non-Gaussian distribution through a bispectrum analysis. We find that non-Gaussianities from the original foreground maps can be removed down to, at least, the noise limit of the BINGO survey with such techniques. Conclusions. Our component separation methodology allows us to subtract the foreground contamination in the BINGO channels down to levels below the cosmological signal and the noise, and to reconstruct the 21 cm power spectrum for different redshift bins without significant loss at multipoles 20≲ l ≲ 500. Our bispectrum analysis yields strong tests of the level of the residual foreground contamination in the recovered 21 cm signal, thereby allowing us to both optimize and validate our component separation analysis