Functional connectivity of reward processing in the brain

Controversial results have been reported concerning the neural mechanisms involved in the processing of rewards and punishments. On the one hand, there is evidence suggesting that monetary gains and losses activate a similar fronto-subcortical network. On the other hand, results of recent studies imply that reward and punishment may engage distinct neural mechanisms. Using functional magnetic resonance imaging (fMRI) we investigated both regional and interregional functional connectivity patterns while participants performed a gambling task featuring unexpectedly high monetary gains and losses. Classical univariate statistical analysis showed that monetary gains and losses activated a similar fronto-striatallimbic network, in which main activation peaks were observed bilaterally in the ventral striatum. Functional connectivity analysis showed similar responses for gain and loss conditions in the insular cortex, the amygdala, and the hippocampus that correlated with the activity observed in the seed region ventral striatum, with the connectivity to the amygdala appearing more pronounced after losses. Larger functional connectivity was found to the medial orbitofrontal cortex for negative outcomes. The fact that different functional patterns were obtained with both analyses suggests that the brain activations observed in the classical univariate approach identifi es the involvement of different functional networks in the current task. These results stress the importance of studying functional connectivity in addition to standard fMRI analysis in reward-related studies.

Kaivoslastauskoneen hybridisointianalyysi virtuaali- ja in-loop -simuloinnin avulla

Työssä tutkitaan raskaiden työkoneiden hybridisointimitoitusta simuloimalla. Työssä esitetään simulation-in-the-loop-simulointiin perustuva järjestelmä, jolla esimerkkitapauksena oleva kaivoslastauskone työympäristöineen voidaan mallintaa mekaaniselta osaltaan monikappaledynamiikkaan perustuvalla ohjelmistolla ja hybridijärjestelmän osalta Simulinkissa. Yhdistetty simulointi mahdollistaa hybridityökoneen virtuaalimallin ohjaamisen käyttäjän toimesta reaaliajassa. Simuloinnista saadaan tuloksena mm. työsykli, jota voidaan käyttää hybridisointimitoitukseen. Hybridisointi toteutetaan kahdella erilaisella kokoonpanolla, joista analysoidaan suorituskykyä sekä polttoaineen kulutusta. Tuloksia verrataan pelkästään dieselmoottoria voimanlähteenä käyttävään lastauskoneeseen. Työssä tehty tutkimus osoittaa, että (sarja-) hybridisoinnilla voidaan saavuttaa merkittäviä etuja raskaiden työkoneiden polttoainetehokkuudessa. Dieselmoottoria voidaan ajaa sellaisessa staattisessa toimintapisteessä, jonka hyötysuhde on korkea riippumatta työkoneen kuormituksesta. Saavutettu hyöty on toteutetussa tutkimuksessa parhaimmillaan jopa 56 % vähennys polttoaineenkulutuksessa. Lisäksi tarvittava dieselin nimellisteho pienenee huomattavasti. Tutkimuksen osana esitellään myös Hardware-in-the-Loop -laitteisto, jonka avulla voidaan liittää oikea sähkömoottori ja taajuudenmuuttaja osaksi virtuaalisesti simuloitua työkonetta.

Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

Plasmodium falciparum Rosetting Epitopes Converge in the SD3-Loop of PfEMP1-DBL1α

The ability of Plasmodium falciparum parasitized RBC (pRBC) to form rosettes with normal RBC is linked to the virulence of the parasite and RBC polymorphisms that weaken rosetting confer protection against severe malaria. The adhesin PfEMP1 mediates the binding and specific antibodies prevent sequestration in the micro-vasculature, as seen in animal models. Here we demonstrate that epitopes targeted by rosette disrupting antibodies converge in the loop of subdomain 3 (SD3) which connects the h6 and h7 α-helices of PfEMP1-DBL1α. Both monoclonal antibodies and polyclonal IgG, that bound to epitopes in the SD3-loop, stained the surface of pRBC, disrupted rosettes and blocked direct binding of recombinant NTS-DBL1α to RBC. Depletion of polyclonal IgG raised to NTS-DBL1α on a SD3 loop-peptide removed the anti-rosetting activity. Immunizations with recombinant subdomain 1 (SD1), subdomain 2 (SD2) or SD3 all generated antibodies reacting with the pRBC-surface but only the sera of animals immunized with SD3 disrupted rosettes. SD3-sequences were found to segregate phylogenetically into two groups (A/B). Group A included rosetting sequences that were associated with two cysteine-residues present in the SD2-domain while group B included those with three or more cysteines. Our results suggest that the SD3 loop of PfEMP1-DBL1α is an important target of anti-rosetting activity, clarifying the molecular basis of the development of variant-specific rosette disrupting antibodies.

Global exponential periodicity of a class of neural networks with recent-history distributed delays

In this paper, we propose to study a class of neural networks with recent-history distributed delays. A sufficient condition is derived for the global exponential periodicity of the proposed neural networks, which has the advantage that it assumes neither the differentiability nor monotonicity of the activation function of each neuron nor the symmetry of the feedback matrix or delayed feedback matrix. Our criterion is shown to be valid by applying it to an illustrative system. (c) 2005 Elsevier Ltd. All rights reserved.

Age-related changes in the functional neuroanatomy of overt speech production

Alterations of existing neural networks during healthy aging, resulting in behavioral deficits and changes in brain activity, have been described for cognitive, motor, and sensory functions. To investigate age-related changes in the neural circuitry underlying overt non-lexical speech production, functional MRI was performed in 14 healthy younger (21–32 years) and 14 healthy older individuals (62–84 years). The experimental task involved the acoustically cued overt production of the vowel /a/ and the polysyllabic utterance /pataka/. In younger and older individuals, overt speech production was associated with the activation of a widespread articulo-phonological network, including the primary motor cortex, the supplementary motor area, the cingulate motor areas, and the posterior superior temporal cortex, similar in the /a/ and /pataka/ condition. An analysis of variance with the factors age and condition revealed a significant main effect of age. Irrespective of the experimental condition, significantly greater activation was found in the bilateral posterior superior temporal cortex, the posterior temporal plane, and the transverse temporal gyri in younger compared to older individuals. Significantly greater activation was found in the bilateral middle temporal gyri, medial frontal gyri, middle frontal gyri, and inferior frontal gyri in older vs. younger individuals. The analysis of variance did not reveal a significant main effect of condition and no significant interaction of age and condition. These results suggest a complex reorganization of neural networks dedicated to the production of speech during healthy aging.

An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology

This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.

The influence of the loop between residues 223-235 in beetle luciferase bioluminescence spectra: A solvent gate for the active site of pH-sensitive luciferases

Beetle luciferases emit a wide range of bioluminescence colors, ranging from green to red. Firefly luciferases can shift the spectrum to red in response to pH and temperature changes, whereas click beetle and railroadworm luciferases do not. Despite many studies on firefly luciferases, the origin of pH-sensitivity is far from being understood. Through comparative site-directed mutagenesis and modeling studies, using the pH-sensitive luciferases (Macrolampis and Cratomorphus distinctus fireflies) and the pH-insensitive luciferases (Pyrearinus termitilluminans, Phrixotrix viviani and Phrixotrix hirtus) cloned by our group, here we show that substitutions dramatically affecting bioluminescence colors in both groups of luciferases are clustered in the loop between residues 223-235 (Photinus pyralis sequence). The substitutions at positions 227, 228 and 229 (P. pyralis sequence) cause dramatic redshift and temporal shift in both groups of luciferases, indicating their involvement in labile interactions. Modeling studies showed that the residues Y227 and N229 are buried in the protein core, fixing the loop to other structural elements participating at the bottom of the luciferin binding site. Changes in pH and temperature (in firefly luciferases), as well as point mutations in this loop, may disrupt the interactions of these structural elements exposing the active site and modulating bioluminescence colors. © 2007 The Authors.

Weight vector estimation of circular arrays of antennas using Artificial Neural Networks

This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to attenuate interference. The control of the array is based on Artificial Neural Networks (ANN) of the type RBF (Radial Basis Functions), trained from samples generated by the Wiener equation. The obtained results suggest that the objective was reached.

An assessment of the economic impact of climate change on the water sector in the Turks and Caicos Islands

The best description of water resources for Grand Turk was offered by Pérez Monteagudo (2000) who suggested that rain water was insufficient to ensure a regular water supply although water catchment was being practised and water catchment possibilities had been analysed. Limestone islands, mostly flat and low lying, have few possibilities for large scale surface storage, and groundwater lenses exist in very delicate equilibrium with saline seawater, and are highly likely to collapse due to sea level rise, improper extraction, drought, tidal waves or other extreme event. A study on the impact of climate change on water resources in the Turks and Caicos Islands is a challenging task, due to the fact that the territory of the Islands covers different environmental resources and conditions, and accurate data are lacking. The present report is based on collected data wherever possible, including grey data from several sources such as the Intergovernmental Panel on Climate Change (IPCC) and Cuban meteorological service data sets. Other data were also used, including the author’s own estimates and modelling results. Although challenging, this was perhaps the best approach towards analysing the situation. Furthermore, IPCC A2 and B2 scenarios were used in the present study in an effort to reduce uncertainty. The main conclusion from the scenario approach is that the trend observed in precipitation during the period 1961 - 1990 is decreasing. Similar behaviour was observed in the Caribbean region. This trend is associated with meteorological causes, particularly with the influence of the North Atlantic Anticyclone. The annual decrease in precipitation is estimated to be between 30-40% with uncertain impacts on marine resources. After an assessment of fresh water resources in Turks and Caicos Islands, the next step was to estimate residential water demand based on a high fertility rate scenario for the Islands (one selected from four scenarios and compared to countries having similar characteristics). The selected scenario presents higher projections on consumption growth, enabling better preparation for growing water demand. Water demand by tourists (stopover and excursionists, mainly cruise passengers) was also obtained, based on international daily consumption estimates. Tourism demand forecasts for Turks and Caicos Islands encompass the forty years between 2011 and 2050 and were obtained by means of an Artificial Neural Networks approach. for the A2 and B2 scenarios, resulting in the relation BAU>B2>A2 in terms of tourist arrivals and water demand levels from tourism. Adaptation options and policies were analysed. Resolving the issue of the best technology to be used for Turks and Caicos Islands is not directly related to climate change. Total estimated water storage capacity is about 1, 270, 800 m3/ year with 80% capacity load for three plants. However, almost 11 desalination plants have been detected on Turks and Caicos Islands. Without more data, it is not possible to estimate long term investment to match possible water demand and more complex adaptation options. One climate change adaptation option would be the construction of elevated (30 metres or higher) storm resistant water reservoirs. The unit cost of the storage capacity is the sum of capital costs and operational and maintenance costs. Electricity costs to pump water are optional as water should, and could, be stored for several months. The costs arising for water storage are in the range of US$ 0.22 cents/m3 without electricity costs. Pérez Monteagudo (2000) estimated water prices at around US$ 2.64/m3 in stand points, US$ 7.92 /m3 for government offices, and US$ 13.2 /m3for cistern truck vehicles. These data need to be updated. As Turks and Caicos Islands continues to depend on tourism and Reverse Osmosis (RO) for obtaining fresh water, an unavoidable condition to maintaining and increasing gross domestic product(GDP) and population welfare, dependence on fossil fuels and vulnerability to increasingly volatile prices will constitute an important restriction. In this sense, mitigation supposes a synergy with adaptation. Energy demand and emissions of carbon dioxide (CO2) were also estimated using an emissions factor of 2. 6 tCO2/ tonne of oil equivalent (toe). Assuming a population of 33,000 inhabitants, primary energy demand was estimated for Turks and Caicos Islands at 110,000 toe with electricity demand of around 110 GWh. The business as usual (BAU), as well as the mitigation scenarios were estimated. The BAU scenario suggests that energy use should be supported by imported fossil fuels with important improvements in energy efficiency. The mitigation scenario explores the use of photovoltaic and concentrating solar power, and wind energy. As this is a preliminary study, the local potential and locations need to be identified to provide more relevant estimates. Macroeconomic assumptions are the same for both scenarios. By 2050, Turks and Caicos Islands could demand 60 m toe less than for the BAU scenario.

Pruning methods to MLP neural networks considering proportional apparent error rate for classification problems with unbalanced data

This article deals with classification problems involving unequal probabilities in each class and discusses metrics to systems that use multilayer perceptrons neural networks (MLP) for the task of classifying new patterns. In addition we propose three new pruning methods that were compared to other seven existing methods in the literature for MLP networks. All pruning algorithms presented in this paper have been modified by the authors to do pruning of neurons, in order to produce fully connected MLP networks but being small in its intermediary layer. Experiments were carried out involving the E. coli unbalanced classification problem and ten pruning methods. The proposed methods had obtained good results, actually, better results than another pruning methods previously defined at the MLP neural network area. (C) 2014 Elsevier Ltd. All rights reserved.

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

Specificities of Caenorhabditis elegans and human hairpin binding proteins for the first nucleotide in the histone mRNA hairpin loop.

The 3' ends of animal replication-dependent histone mRNAs are formed by endonucleolytic cleavage of the primary transcripts downstream of a highly conserved RNA hairpin. The hairpin-binding protein (HBP) binds to this RNA element and is involved in histone RNA 3' processing. A minimal RNA-binding domain (RBD) of approximately 73 amino acids that has no similarity with other known RNA-binding motifs was identified in human HBP [Wang Z-F et al., Genes & Dev, 1996, 10:3028-3040]. The primary sequence identity between human and Caenorhabditis elegans RBDs is 55% compared to 38% for the full-length proteins. We analyzed whether differences between C. elegans and human HBP and hairpins are reflected in the specificity of RNA binding. The C. elegans HBP and its RBD recognize only their cognate RNA hairpins, whereas the human HBP or RBD can bind both the mammalian and the C. elegans hairpins. This selectivity of C. elegans HBP is mostly mediated by the first nucleotide in the loop, which is C in C. elegans and U in all other metazoans. By converting amino acids in the human RBD to the corresponding C. elegans residues at places where the latter deviates from the consensus, we could identify two amino acid segments that contribute to selectivity for the first nucleotide of the hairpin loop.

Identification of specific Rp-phosphate oxygens in the tRNA anticodon loop required for ribosomal P-site binding

tRNA binding to the ribosomal P site is dependent not only on correct codon–anticodon interaction but also involves identification of structural elements of tRNA by the ribosome. By using a phosphorothioate substitution–interference approach, we identified specific nonbridging Rp-phosphate oxygens in the anticodon loop of tRNAPhe from Escherichia coli which are required for P-site binding. Stereo-specific involvement of phosphate oxygens at these positions was confirmed by using synthetic anticodon arm analogues at which single Rp- or Sp-phosphorothioates were incorporated. Identical interference results with yeast tRNAPhe and E. coli tRNAfMet indicate a common backbone conformation or common recognition elements in the anticodon loop of tRNAs. N-ethyl-N-nitrosourea modification–interference experiments with natural tRNAs point to the importance of the same phosphates in the loop. Guided by the crystal structure of tRNAPhe, we propose that specific Rp-phosphate oxygens are required for anticodon loop (“U-turn”) stabilization or are involved in interactions with the ribosome on correct tRNA–mRNA complex formation.