Modular multi-level DC-DC converter for high-power and high-voltage applications

A transformer-less DC-DC Modular Multi-level Converter (DC-DC-MMC) topology based on H-bridge cells is proposed in this paper. The suggested DC-DC-MMC can be used to either control the power flow in a HVdc grid or interconnect HVdc lines with different voltage levels. Branch energy and current control loops are presented as well as a cell capacitor voltage balancing strategy. Finally, the operation of the converter is validated by means of PSCAD simulations. Results for the operation of the DC-DC-MMC controlling the power flow between two HVdc grids with different voltage levels are presented.The present work was supported by the Spanish Ministry of Economy funds under Grant DPI2014-53245-R and by Universitat Jaume I under Grants P1·1B2013-51 and E-2014-24. The support of Fondecyt Chile under grant 1151325, CONICYT/FONDAP/15110019 is also kindly acknowledged

Spontaneous synchronization to speech reveals neural mechanisms facilitating language learning

We introduce a deceptively simple behavioral task that robustly identifies two qualitatively different groups within the general population. When presented with an isochronous train of random syllables, some listeners are compelled to align their own concurrent syllable production with the perceived rate, whereas others remain impervious to the external rhythm. Using both neurophysiological and structural imaging approaches, we show group differences with clear consequences for speech processing and language learning. When listening passively to speech, high synchronizers show increased brain-to-stimulus synchronization over frontal areas, and this localized pattern correlates with precise microstructural differences in the white matter pathways connecting frontal to auditory regions. Finally, the data expose a mechanism that underpins performance on an ecologically relevant word-learning task. We suggest that this task will help to better understand and characterize individual performance in speech processing and language learning

Power flow control using a DC-DC MMC for HVdc grid connected wind power plants

This paper proposes the use of a transformer-less DC-DC Modular Multilevel Converter (MMC) topology, based on cascaded H-bridge converters, for power flow control in High Voltage Direct Current (HVDC) grids used to connect off-shore wind power plants to on-shore grids. An energy based approach is used to regulate the DC voltage of H-bridge modules. Results for the operation of the DC-DC MMC supplying energy to a DC network and controlling the power flow in a HVDC system are presented.The support of Fondecyt grant 1151325, CONICYT/FONDAP/15110019, the Spanish Ministry of Economy Grant DPI2014-53245-R, University La Frontera grant DIUFRO09-0037 and Universitat Jaume I grants P1ā1B2013-51 and E-2014-24 is kindly acknowledged

Non-adjacent dependency learning in humans and other animals

International audienc

Specific patterns of brain alterations underlie distinct clinical profiles in Huntington's disease

Huntington's disease (HD) is a genetic neurodegenerative disease which involves a triad of motor, cognitive and psychiatric disturbances. However, there is great variability in the prominence of each type of symptom across individuals. The neurobiological basis of such variability remains poorly understood but would be crucial for better tailored treatments. Multivariate multimodal neuroimaging approaches have been successful in disentangling these profiles in other disorders. Thus we applied for the first time such approach to HD. We studied the relationship between HD symptom domains and multimodal measures sensitive to grey and white matter structural alterations. Forty-three HD gene carriers (23 manifest and 20 premanifest individuals) were scanned and underwent behavioural assessments evaluating motor, cognitive and psychiatric domains. We conducted a multimodal analysis integrating different structural neuroimaging modalities measuring grey matter volume, cortical thickness and white matter diffusion indices - fractional anisotropy and radial diffusivity. All neuroimaging measures were entered into a linked independent component analysis in order to obtain multimodal components reflecting common inter-subject variation across imaging modalities. The relationship between multimodal neuroimaging independent components and behavioural measures was analysed using multiple linear regression. We found that cognitive and motor symptoms shared a common neurobiological basis, whereas the psychiatric domain presented a differentiated neural signature. Behavioural measures of different symptom domains correlated with different neuroimaging components, both the brain regions involved and the neuroimaging modalities most prominently associated with each type of symptom showing differences. More severe cognitive and motor signs together were associated with a multimodal component consisting in a pattern of reduced grey matter, cortical thickness and white matter integrity in cognitive and motor related networks. In contrast, depressive symptoms were associated with a component mainly characterised by reduced cortical thickness pattern in limbic and paralimbic regions. In conclusion, using a multivariate multimodal approach we were able to disentangle the neurobiological substrates of two distinct symptom profiles in HD: one characterised by cognitive and motor features dissociated from a psychiatric profile. These results open a new view on a disease classically considered as a uniform entity and initiates a new avenue for further research considering these qualitative individual differences

Devolution dynamics of Spanish local government

Over the last few years, ther has been a devolutionary tendency in many developed and developing countries. In this article we propose a methodology to decompose whether the benefits in terms of effciency derived from transfers of powers from higher to municipal levels of government "the "economic dividend" of devolution) might increase over time. This methodology is based on linear programming approaches for effciency measurement. We provide anapplication to Spanish municipalities, which have had to adapt to both the European Stability and Growth Pact as well as to domestic regulation seeking local governments balanced budget. Results indicate that efficiency gains from enhaced decentralization have increased over time. However, the way through which these gains accrue differs across municipalities -in some cases technical change is the main component, whereas in others catching up dominates

On the determinants of local government debt: Does one size fit all?

This paper analyzes the factors that directly influence levels of debt in Spanish local governments. Specifically, the main objective is to find out the extent to which indebtedness is originated by controllable factors that public managers can influence, or whether it hinges on other variables beyond managers’ control. The importance of this issue has intensified since the start of the crisis in 2007, due to the abrupt decline of revenues and, simultaneously, to the stagnation (or even increase) in the levels of costs facing these institutions face. Results can be explored from multiple perspectives, given that the set of explanatory factors is also multiple. However, the most interesting result relates to the varying effect of each covariate depending on each municipality’s specific debt level, which suggests that economic policy recommendations should not be homogeneous across local governments

BLISS: an artificial language for learnability studies

To explore neurocognitive mechanisms underlying the human language faculty, cognitive scientists use artificial languages to control more precisely the language learning environment and to study selected aspects of natural languages. Artificial languages applied in cognitive studies are usually designed ad hoc, to only probe a specific hypothesis, and they include a miniature grammar and a very small vocabulary. The aim of the present study is the construction of an artificial language incorporating both syntax and semantics, BLISS. Of intermediate complexity, BLISS mimics natural languages by having a vocabulary, syntax, and some semantics, as defined by a degree of non-syntactic statistical dependence between words. We quantify, using information theoretical measures, dependencies between words in BLISS sentences as well as differences between the distinct models we introduce for semantics. While modeling English syntax in its basic version, BLISS can be easily varied in its internal parametric structure, thus allowing studies of the relative learnability of different parameter sets

Heterogeneous patterns of tissue injury in NARP syndrome

Point mutations at m.8993T>C and m.8993T>G of the mtDNA ATPase 6 gene cause the neurogenic weakness, ataxia and retinitis pigmentosa (NARP) syndrome, a mitochondrial disorder characterized by retinal, central and peripheral neurodegeneration. We performed detailed neurological, neuropsychological and ophthalmological phenotyping of a mother and four daughters with NARP syndrome from the mtDNA m.8993T>C ATPase 6 mutation, including 3-T brain MRI, spectral domain optical coherence tomography (SD-OCT), adaptive optics scanning laser ophthalmoscopy (AOSLO), electromyography and nerve conduction studies (EMG-NCS) and formal neuropsychological testing. The degree of mutant heteroplasmy for the m.8993T>C mutation was evaluated by real-time allele refractory mutation system quantitative PCR of mtDNA from hair bulbs (ectoderm) and blood leukocytes (mesoderm). There were marked phenotypic differences between family members, even between individuals with the greatest degrees of ectodermal and mesodermal heteroplasmy. 3-T MRI revealed cerebellar atrophy and cystic and cavitary T2 hyperintensities in the basal ganglia. SD-OCT demonstrated similarly heterogeneous areas of neuronal and axonal loss in inner and outer retinal layers. AOSLO showed increased cone spacing due to photoreceptor loss. EMG-NCS revealed varying degrees of length-dependent sensorimotor axonal polyneuropathy. On formal neuropsychological testing, there were varying deficits in processing speed, visual–spatial functioning and verbal fluency and high rates of severe depression. Many of these cognitive deficits likely localize to cerebellar and/or basal ganglia dysfunction. High-resolution retinal and brain imaging in NARP syndrome revealed analogous patterns of tissue injury characterized by heterogeneous areas of neuronal loss

Syntactic learning by mere exposure - An ERP study in adult learners

<p>Abstract</p> <p>Background</p> <p>Artificial language studies have revealed the remarkable ability of humans to extract syntactic structures from a continuous sound stream by mere exposure. However, it remains unclear whether the processes acquired in such tasks are comparable to those applied during normal language processing. The present study compares the ERPs to auditory processing of simple Italian sentences in native and non-native speakers after brief exposure to Italian sentences of a similar structure. The sentences contained a non-adjacent dependency between an auxiliary and the morphologically marked suffix of the verb. Participants were presented four alternating learning and testing phases. During learning phases only correct sentences were presented while during testing phases 50 percent of the sentences contained a grammatical violation.</p> <p>Results</p> <p>The non-native speakers successfully learned the dependency and displayed an N400-like negativity and a subsequent anteriorily distributed positivity in response to rule violations. The native Italian group showed an N400 followed by a P600 effect.</p> <p>Conclusion</p> <p>The presence of the P600 suggests that native speakers applied a grammatical rule. In contrast, non-native speakers appeared to use a lexical form-based processing strategy. Thus, the processing mechanisms acquired in the language learning task were only partly comparable to those applied by competent native speakers.</p