On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

1-42 beta-Amyloid peptide requires PDK1/nPKC/Rac 1 pathway to induce neuronal death

1-42 beta-Amyloid (A beta(1-42)) peptide is a key molecule involved in the development of Alzheimer's disease. Some of its effects are manifested at the neuronal morphological level. These morphological changes involve loss of neurites due to cytoskeleton alterations. However, the mechanism of A beta(1-42) peptide activation of the neurodegenerative program is still poorly understood. Here, A beta(1-42) peptide-induced transduction of cellular death signals through the phosphatidylinositol 3-kinase (PI3K)/phosphoinositol- dependent kinase (PDK)/novel protein kinase C (nPKC)/Rac 1 axis is described. Furthermore, pharmacological inhibition of PDK1 and nPKC activities blocks Rac 1 activation and neuronal cell death. Our results provide insights into an unsuspected connection between PDK1, nPKCs and Rac 1 in the same signal-transduction pathway and points out nPKCs and Rac 1 as potential therapeutic targets to block the toxic effects of A beta(1-42) peptide in neurons.

Use of generalised additive models to categorise continuous variables in clinical prediction

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Synthetic scope and DFT analysis of the chiral binap-gold(I) complex-catalyzed 1,3-dipolar cycloaddition of azlactones with alkenes

he 1,3-dipolar cycloaddition between glycine-derived azlactones with maleimides is efficiently catalyzed by the dimeric chiral complex [(S-a)-Binap.AuTFA](2). The alanine-derived oxazolone only reacts with tert-butyl acrylate giving anomalous regiochemistry, which is explained and supported by Natural Resonance Theory and Nucleus Independent Chemical Shifts calculations. The origin of the high enantiodiscrimination observed with maleimides and tert-butyl acrylate is analyzed using DFT computed at M06/Lanl2dz//ONIOM(b3lyp/Lanl2dz:UFF) level. Several applications of these cycloadducts in the synthesis of new proline derivatives with a 2,5-trans-arrangement and in the preparation of complex fused polycyclic molecules are described.

FTT-MA: A Flexible Time-Triggered Middleware Architecture for Time Sensitive, Resource-Aware AmI Systems

There is an increasing number of Ambient Intelligence (AmI) systems that are time-sensitive and resource-aware. From healthcare to building and even home/office automation, it is now common to find systems combining interactive and sensing multimedia traffic with relatively simple sensors and actuators (door locks, presence detectors, RFIDs, HVAC, information panels, etc.). Many of these are today known as Cyber-Physical Systems (CPS). Quite frequently, these systems must be capable of (1) prioritizing different traffic flows (process data, alarms, non-critical data, etc.), (2) synchronizing actions in several distributed devices and, to certain degree, (3) easing resource management (e.g., detecting faulty nodes, managing battery levels, handling overloads, etc.). This work presents FTT-MA, a high-level middleware architecture aimed at easing the design, deployment and operation of such AmI systems. FTT-MA ensures that both functional and non-functional aspects of the applications are met even during reconfiguration stages. The paper also proposes a methodology, together with a design tool, to create this kind of systems. Finally, a sample case study is presented that illustrates the use of the middleware and the methodology proposed in the paper.

Inoculation of Triatoma Virus (Dicistroviridae: Cripavirus) elicits a non-infective immune response in mice

Background: Dicistroviridae is a new family of small, non-enveloped, +ssRNA viruses pathogenic to both beneficial arthropods and insect pests. Little is known about the dicistrovirus replication mechanism or gene function, and any knowledge on these subjects comes mainly from comparisons with mammalian viruses from the Picornaviridae family. Due to its peculiar genome organization and characteristics of the per os viral transmission route, dicistroviruses make good candidates for use as biopesticides. Triatoma virus (TrV) is a pathogen of Triatoma infestans (Hemiptera: Reduviidae), one of the main vectors of the human trypanosomiasis disease called Chagas disease. TrV was postulated as a potential control agent against Chagas' vectors. Although there is no evidence that TrV nor other dicistroviruses replicate in species outside the Insecta class, the innocuousness of these viruses in humans and animals needs to be ascertained. Methods: In this study, RT-PCR and ELISA were used to detect the infectivity of this virus in Mus musculus BALB/c mice. Results: In this study we have observed that there is no significant difference in the ratio IgG2a/IgG1 in sera from animals inoculated with TrV when compared with non-inoculated animals or mice inoculated only with non-infective TrV protein capsids. Conclusions: We conclude that, under our experimental conditions, TrV is unable to replicate inmice. This study constitutes the first test to evaluate the infectivity of a dicistrovirus in a vertebrate animal model.

Advances in Click Chemistry for Single-Chain Nanoparticle Construction

Single-chain polymeric nanoparticles are artificial folded soft nano-objects of ultra-small size which have recently gained prominence in nanoscience and nanotechnology due to their exceptional and sometimes unique properties. This review focuses on the current state of the investigations of click chemistry techniques for highly-efficient single-chain nanoparticle construction. Additionally, recent progress achieved for the use of well-defined single-chain nanoparticles in some promising fields, such as nanomedicine and catalysis, is highlighted.

Designing High Performance Factory Automation Applications on Top of DDS

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Optimization of solution-processed oligothiophene:fullerene based organic solar cells by using solvent additives

The optimization of solution-processed organic bulk-heterojunction solar cells with the acceptor-substituted quinquethiophene DCV5T-Bu-4 as donor in conjunction with PC61BM as acceptor is described. Power conversion efficiencies up to 3.0% and external quantum efficiencies up to 40% were obtained through the use of 1-chloronaphthalene as solvent additive in the fabrication of the photovoltaic devices. Furthermore, atomic force microscopy investigations of the photoactive layer gave insight into the distribution of donor and acceptor within the blend. The unique combination of solubility and thermal stability of DCV5T-Bu-4 also allows for fabrication of organic solar cells by vacuum deposition. Thus, we were able to perform a rare comparison of the device characteristics of the solution-processed DCV5T-Bu-4:PC61BM solar cell with its vacuum-processed DCV5T-Bu-4:C-60 counterpart. Interestingly in this case, the efficiencies of the small-molecule organic solar cells prepared by using solution techniques are approaching those fabricated by using vacuum technology. This result is significant as vacuum-processed devices typically display much better performances in photovoltaic cells. Keywords

Enhanced Operation of Electricity Distribution Grids Through Smart Metering PLC Network Monitoring, Analysis and Grid Conditioning

Low Voltage (LV) electricity distribution grid operations can be improved through a combination of new smart metering systems' capabilities based on real time Power Line Communications (PLC) and LV grid topology mapping. This paper presents two novel contributions. The first one is a new methodology developed for smart metering PLC network monitoring and analysis. It can be used to obtain relevant information from the grid, thus adding value to existing smart metering deployments and facilitating utility operational activities. A second contribution describes grid conditioning used to obtain LV feeder and phase identification of all connected smart electric meters. Real time availability of such information may help utilities with grid planning, fault location and a more accurate point of supply management.

A Temperature Sensor Based on a Polymer Optical Fiber Macro-Bend

The design and development of a plastic optical fiber (POF) macrobend temperature sensor is presented. The sensor has a linear response versus temperature at a fixed bend radius, with a sensitivity of 1.92.10(-3) (degrees C)(-1). The sensor system used a dummy fiber-optic sensor for reference purposes having a resolution below 0.3 degrees C. A comprehensive experimental analysis was carried out to provide insight into the effect of different surrounding media on practical macro-bend POF sensor implementation. Experimental results are successfully compared with bend loss calculations.

Query-by-Example Spoken Term Detection ALBAYZIN 2012 evaluation: overview, systems, results, and discussion

Query-by-Example Spoken Term Detection (QbE STD) aims at retrieving data from a speech data repository given an acoustic query containing the term of interest as input. Nowadays, it has been receiving much interest due to the high volume of information stored in audio or audiovisual format. QbE STD differs from automatic speech recognition (ASR) and keyword spotting (KWS)/spoken term detection (STD) since ASR is interested in all the terms/words that appear in the speech signal and KWS/STD relies on a textual transcription of the search term to retrieve the speech data. This paper presents the systems submitted to the ALBAYZIN 2012 QbE STD evaluation held as a part of ALBAYZIN 2012 evaluation campaign within the context of the IberSPEECH 2012 Conference(a). The evaluation consists of retrieving the speech files that contain the input queries, indicating their start and end timestamps within the appropriate speech file. Evaluation is conducted on a Spanish spontaneous speech database containing a set of talks from MAVIR workshops(b), which amount at about 7 h of speech in total. We present the database metric systems submitted along with all results and some discussion. Four different research groups took part in the evaluation. Evaluation results show the difficulty of this task and the limited performance indicates there is still a lot of room for improvement. The best result is achieved by a dynamic time warping-based search over Gaussian posteriorgrams/posterior phoneme probabilities. This paper also compares the systems aiming at establishing the best technique dealing with that difficult task and looking for defining promising directions for this relatively novel task.

Behavioral, neurochemical and morphological changes induced by the overexpression of munc18-1a in brain of mice: relevance to schizophrenia

Overexpression of the mammalian homolog of the unc-18 gene (munc18-1) has been described in the brain of subjects with schizophrenia. Munc18-1 protein is involved in membrane fusion processes, exocytosis and neurotransmitter release. A transgenic mouse strain that overexpresses the protein isoform munc18-1a in the brain was characterized. This animal displays several schizophrenia-related behaviors, supersensitivity to hallucinogenic drugs and deficits in prepulse inhibition that reverse after antipsychotic treatment. Relevant brain areas (that is, cortex and striatum) exhibit reduced expression of dopamine D-1 receptors and dopamine transporters together with enhanced amphetamine-induced in vivo dopamine release. Magnetic resonance imaging demonstrates decreased gray matter volume in the transgenic animal. In conclusion, the mouse overexpressing brain munc18-1a represents a new valid animal model that resembles functional and structural abnormalities in patients with schizophrenia.