Constituents of the Essential Oil of Suregada zanzibariensis Leaves are Repellent to the Mosquito, Anopheles gambiae s.s.

In traditional African communities, repellent volatiles from certain plants generated by direct burning or by thermal expulsion have played an important role in protecting households against vectors of malaria and other diseases. Previous research on volatile constituents of plants has shown that some are good sources of potent mosquito repellents. In this bioprospecting initiative, the essential oil of leaves of the tree, Suregada zanzibariensis Verdc. (Angiospermae: Euphobiaceae) was tested against the mosquito, Anopheles gambiae s.s. Giles (Diptera: Culicidae) and found to be repellent. Gas chromatography (GC), GC-linked mass spectrometry (GC-MS) and, where possible, GC-co-injections with authentic compounds, led to the identification of about 34 compounds in the essential oil. About 56% of the constituents were terpenoid ketones, mostly methyl ketones. Phenylacetaldehyde (14.4%), artemisia ketone (10.1%), (1S)-(-)-verbenone (12.1%) and geranyl acetone (9.4%) were the main constituents. Apart from phenylacetaldehyde, repellent activities of the other main constituents were higher than that of the essential oil. The blends of the main constituents in proportions found in the essential oil were more repellent to An. gambiae s.s. than was the parent oil (p < 0.05), and the presence of artemisia ketone in the blend caused a significant increase in the repellency of the resulting blend. These results suggested that blends of some terpenoid ketones can serve as effective An. gambiae s.s. mosquito repellents

A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies

A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works20th Argentinean Bioengineering Society Congress, SABI 2015 (XX Congreso Argentino de Bioingeniería y IX Jornadas de Ingeniería Clínica)28–30 October 2015, San Nicolás de los Arroyos, Argentin

Detection of Bulbar Dysfunction in ALS Patients Based on Running Speech Test

This paper deals with detection of speech changes due to amyotrophic lateral sclerosis (ALS) – fatal neurological disease with no cure. The detection process is based on analysis of running speech test. However, in contrast to conventional frame-based classification (in which whole signal is analyzed) we proposed to use selected vowels extracted from the test signal. It is shown that similarity of spectral envelopes of different vowels and formant frequencies are crucial features for bulbar ALS detection. Applying the proposed features to classifier base on linear discriminant analysis (LDA) the detection accuracy of 84.8% is achieved

Intuitive control of rolling sound synthesis

International audienceThis paper presents a rolling sound synthesis model which can be intuitively controlled. To propose this model, different aspects of the rolling phenomenon are explored : physical modeling, perceptual attributes and signal morphology. A source-filter model for rolling sounds synthesis is presented with associated intuitive controls

A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain–computer interface

Objective: Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain–computer interface (BCI) applications. Approach: Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that often occur during data recording can deteriorate the recognition performance. Therefore, it is meaningful to extract a few frequency sub-bands of interest to avoid or reduce the influence of unrelated brain activity and artifacts. This paper presents an improved method to detect the frequency component associated with SSVEP using multivariate empirical mode decomposition (MEMD) and CCA (MEMD-CCA). EEG signals from nine healthy volunteers were recorded to evaluate the performance of the proposed method for SSVEP recognition. Main results: We compared our method with CCA and temporally local multivariate synchronization index (TMSI). The results suggest that the MEMD-CCA achieved significantly higher accuracy in contrast to standard CCA and TMSI. It gave the improvements of 1.34%, 3.11%, 3.33%, 10.45%, 15.78%, 18.45%, 15.00% and 14.22% on average over CCA at time windows from 0.5 s to 5 s and 0.55%, 1.56%, 7.78%, 14.67%, 13.67%, 7.33% and 7.78% over TMSI from 0.75 s to 5 s. The method outperformed the filter-based decomposition (FB), empirical mode decomposition (EMD) and wavelet decomposition (WT) based CCA for SSVEP recognition. Significance: The results demonstrate the ability of our proposed MEMD-CCA to improve the performance of SSVEP-based BCI

Edible bio-based nanostructures: delivery, absorption and potential toxicity

The development of bio-based nanostructures as nanocarriers of bioactive compounds to specific body sites has been presented as a hot topic in food, pharmaceutical and nanotechnology fields. Food and pharmaceutical industries seek to explore the huge potential of these nanostructures, once they can be entirely composed of biocompatible and non-toxic materials. At the same time, they allow the incorporation of lipophilic and hydrophilic bioactive compounds protecting them against degradation, maintaining its active and functional performance. Nevertheless, the physicochemical properties of such structures (e.g., size and charge) could change significantly their behavior in the gastrointestinal (GI) tract. The main challenges in the development of these nanostructures are the proper characterization and understanding of the processes occurring at their surface, when in contact with living systems. This is crucial to understand their delivery and absorption behavior as well as to recognize potential toxicological effects. This review will provide an insight into the recent innovations and challenges in the field of delivery via GI tract using bio-based nanostructures. Also, an overview of the approaches followed to ensure an effective deliver (e.g., avoiding physiological barriers) and to enhance stability and absorptive intestinal uptake of bioactive compounds will be provided. Information about nanostructures potential toxicity and a concise description of the in vitro and in vivo toxicity studies will also be given.Joana T. Martins, Oscar L. Ramos, Ana C. Pinheiro, Ana I. Bourbon, Helder D. Silva and Miguel A. Cerqueira (SFRH/BPD/89992/2012, SFRH/BPD/80766/2011, SFRH/BPD/101181/2014, SFRH/BD/73178/2010, SFRH/BD/81288/2011, and SFRH/BPD/72753/2010, respectively) are the recipients of a fellowship from the Fundacao para a Ciencia e Tecnologia (FCT, POPH-QREN and FSE, Portugal). The authors thank the FCT Strategic Project PEst-OE/EQB/LA0023/2013 and the project "BioInd-Biotechnology and Bioengineering for improved Industrial and Agro-Food processes," REF.NORTE-07-0124-FEDER-000028, co-funded by the Programa Operacional Regional do Norte (ON.2-O Novo Norte), QREN, FEDER. We also thank to the European Commission: BIOCAPS (316265, FP7/REGPOT-2012-2013.1) and Xunta de Galicia: Agrupamento INBIOMED (2012/273) and Grupo con potencial de crecimiento. The support of EU Cost Action FA1001 is gratefully acknowledged