Few-shot re-identification of the speaker by social robots

Nowadays advanced machine learning, computer vision, audio analysis and natural language understanding systems can be widely used for improving the perceptive and reasoning capabilities of the social robots. In particular, artificial intelligence algorithms for speaker re-identification make the robot aware of its interlocutor and able to personalize the conversation according to the information gathered in real-time and in the past interactions with the speaker. Anyway, this kind of application requires to train neural networks having available only a few samples for each speaker. Within this context, in this paper we propose a social robot equipped with a microphone sensor and a smart deep learning algorithm for few-shot speaker re-identification, able to run in real time over an embedded platform mounted on board of the robot. The proposed system has been experimentally evaluated over the VoxCeleb1 dataset, demonstrating a remarkable re-identification accuracy by varying the number of samples per speaker, the number of known speakers and the duration of the samples, and over the SpReW dataset, showing its robustness in real noisy environments. Finally, a quantitative evaluation of the processing time over the embedded platform proves that the processing pipeline is almost immediate, resulting in a pleasant user experience

Post-harvest non-conventional and traditional methods to control cadophora luteo-olivacea: Skin pitting agent of actinidia chinensis var. deliciosa (A. chev.)

Cadophora luteo-olivacea represents a critical problem for kiwifruit in the post-harvest phase, mainly for its little note epidemiology. The study presented some results about the possibility of preserving kiwifruit from skin pitting symptoms using alternative methods to fungicides. By in vitro assays, antagonist mechanisms of action against pathogen isolates were tested. Trichoderma harzianum (Th1) showed the highest inhibitory activity against C. luteo-olivacea isolates by volatile, non-volatile, and by dual culture assay, displaying an inhibition respectively by 90%, 70.6%, and 78.8%, and with respect to Aureobasidium pullulans (L1 and L8) by 23.3% and 25.8%, 50% and 34.7%, and 22.5% and 23.6%, respectively. Further, the sensitivity on CFU and mycelial growth of C. luteo-olivacea isolates to fludioxonil, and CaCl2 was tested, displaying interesting EC50 values (0.36 and 0.92 g L-1, 22.5 g L-1, respectively). The effect of Brassica nigra defatted meal was tested as biofumigation assays and through FT-IR (Fourier-Transform Infrared) spectroscopy. The above-mentioned treatments were applied in vivo to evaluate their efficacy on kiwifruits. Our data demonstrated that alternative solutions could be considered to control postharvest pathogens such as C. luteo-olivacea

Chemical and physical characterization of thermal aggregation of model proteins modulated by zinc (II) and copper (II) ions.

BACKGROUND: Metal ions are implicated in protein aggregation processes of several neurodegenerative pathologies, where the protein deposition occurs, and in the biotechnology field like the food technology where many processes in food manufacturing are based on thermal treatments. OBJECTIVE: The influence of Cu2+ or Zn2+ ions on the thermal aggregation process of Bovine beta-lactoglobulin (BLG) and Bovine Serum Albumin (BSA), two protein models, was studied with the aim of delineating the role of these ions in the protein aggregation kinetics and to clarify the related molecular mechanisms. METHODS: The protein structure changes were monitored by Raman spectroscopy, whereas the aggregate growth was followed by Dynamic Light Scattering measurements. RESULTS: Both metal ions are able to favour the BLG aggregation, whereas only Zn2+ ions have a promoter effect on the thermal aggregation of BSA. The reason of this different behaviour is that the BLG aggregation evolution is manly affected by the redistribution of charges, whereas that of BSA by the metal coordination binding which depends on metal. CONCLUSIONS: Raman spectroscopy, combined with dynamic light scattering experiments, was very useful in identifying the role played by Cu2+ and Zn2+ on the aggregation pathways of BLG and BSA. The results provide evidence for the role of histidine residues both in the redistribution of charges and in the two modes of metal binding that take place in BLG- and BSA-containing systems, respectively

A Method for Detecting Long Term Left Baggage based on Heat Map

n/

Mn-Containing Bioactive Glass-Ceramics: BMP-2-Mimetic Peptide Covalent Grafting Boosts Human-Osteoblast Proliferation and Mineral Deposition

The addition of Mn in bioceramic formulation is gaining interest in the field of bone implants. Mn activates human osteoblast (h-osteoblast) integrins, enhancing cell proliferation with a dose-dependent effect, whereas Mn-enriched glasses induce inhibition of Gram-negative or Gram-positive bacteria and fungi. In an effort to further optimize Mn-containing scaffolds' beneficial interaction with h-osteoblasts, a selective and specific covalent functionalization with a bioactive peptide was carried out. The anchoring of a peptide, mapped on the BMP-2 wrist epitope, to the scaffold was performed by a reaction between an aldehyde group of the peptide and the aminic groups of silanized Mn-containing bioceramic. SEM-EDX, FT-IR, and Raman studies confirmed the presence of the peptide grafted onto the scaffold. In in vitro assays, a significant improvement in h-osteoblast proliferation, gene expression, and calcium salt deposition after 7 days was detected in the functionalized Mn-containing bioceramic compared to the controls

Subgraph spotting in graph representations of comic book images

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record Graph-based representations are the most powerful data structures for extracting, representing and preserving the structural information of underlying data. Subgraph spotting is an interesting research problem, especially for studying and investigating the structural information based content-based image retrieval (CBIR) and query by example (QBE) in image databases. In this paper we address the problem of lack of freely available ground-truthed datasets for subgraph spotting and present a new dataset for subgraph spotting in graph representations of comic book images (SSGCI) with its ground-truth and evaluation protocol. Experimental results of two state-of-the-art methods of subgraph spotting are presented on the new SSGCI dataset.University of La Rochelle (France

Impact of antiretroviral dosing and daily pill burden on viral rebound rates in naive patients receiving a tenofovir-based regimen

Methods A total of 480 ART-naive patients were selected from the GNOMO cohort. Incidence rate of viral rebound (VR = first of two consecutive VL>50 cp/ml) was calculated as number of events over PYFU and expressed at univariate and multivariate analysis as incidence rate ratio (IRR). Number of both pills and doses per day were used to define three different types of regimens: twice-a-day regimens (BID regimens); once-a-day regimens with 3 pills (high-pill QD [hp-QD]). Adjusted rates of viral rebound were estimated by Poisson regression using date of first HIV-RNA <50 c/ml as baseline. Follow-up was censored at the date of VR, death, or loss to follow-up

Graph edit distance or graph edit pseudo-distance?

Graph Edit Distance has been intensively used since its appearance in 1983. This distance is very appropriate if we want to compare a pair of attributed graphs from any domain and obtain not only a distance, but also the best correspondence between nodes of the involved graphs. In this paper, we want to analyse if the Graph Edit Distance can be really considered a distance or a pseudo-distance, since some restrictions of the distance function are not fulfilled. Distinguishing between both cases is important because the use of a distance is a restriction in some methods to return exact instead of approximate results. This occurs, for instance, in some graph retrieval techniques. Experimental validation shows that in most of the cases, it is not appropriate to denominate the Graph Edit Distance as a distance, but a pseudo-distance instead, since the triangle inequality is not fulfilled. Therefore, in these cases, the graph retrieval techniques not always return the optimal graph

Impact of antiretroviral dosing and daily pill burden on viral rebound rates in naive patients receiving a tenofovir-based regimen

Methods A total of 480 ART-naive patients were selected from the GNOMO cohort. Incidence rate of viral rebound (VR = first of two consecutive VL>50 cp/ml) was calculated as number of events over PYFU and expressed at univariate and multivariate analysis as incidence rate ratio (IRR). Number of both pills and doses per day were used to define three different types of regimens: twice-a-day regimens (BID regimens); once-a-day regimens with 3 pills (high-pill QD [hp-QD]). Adjusted rates of viral rebound were estimated by Poisson regression using date of first HIV-RNA <50 c/ml as baseline. Follow-up was censored at the date of VR, death, or loss to follow-up

Graph-based keyword spotting in historical handwritten documents

The amount of handwritten documents that is digitally available is rapidly increasing. However, we observe a certain lack of accessibility to these documents especially with respect to searching and browsing. This paper aims at closing this gap by means of a novel method for keyword spotting in ancient handwritten documents. The proposed system relies on a keypoint-based graph representation for individual words. Keypoints are characteristic points in a word image that are represented by nodes, while edges are employed to represent strokes between two keypoints. The basic task of keyword spotting is then conducted by a recent approximation algorithm for graph edit distance. The novel framework for graph-based keyword spotting is tested on the George Washington dataset on which a state-of-the-art reference system is clearly outperformed.Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR). S+SSPR 2016: Structural, Syntactic, and Statistical Pattern Recognition pp. 564-573.http://link.springer.combookseries/5582017-11-05hj2017Informatic