A Multi-Task Learning Approach for Meal Assessment

Key role in the prevention of diet-related chronic diseases plays the balanced nutrition together with a proper diet. The conventional dietary assessment methods are time-consuming, expensive and prone to errors. New technology-based methods that provide reliable and convenient dietary assessment, have emerged during the last decade. The advances in the field of computer vision permitted the use of meal image to assess the nutrient content usually through three steps: food segmentation, recognition and volume estimation. In this paper, we propose a use one RGB meal image as input to a multi-task learning based Convolutional Neural Network (CNN). The proposed approach achieved outstanding performance, while a comparison with state-of-the-art methods indicated that the proposed approach exhibits clear advantage in accuracy, along with a massive reduction of processing time

Traces of Fallback Breccia on the Rim of Barringer Meteorite Crater (a.k.a. Meteor Crater), Arizona

Barringer Meteorite Crater (a.k.a. Meteor Crater), Arizona, is one of the youngest and best preserved impact craters on Earth. For that rea-son, it provides a baseline for similar craters formed in the geologic past, formed elsewhere in the Solar Sys-tem, and illuminates the astronomical and geological processes that produce them. The crater has not, how-ever, escaped erosion completely. While Shoemaker [1] mapped a breccia with fallback components inside the crater, he did not locate it beyond the crater rim. He only found remnants of that type of debris in re-worked alluvium [1; see also 2]. Fallback breccia and any base-surge deposits have, thus, been missing components in studies of material ejected beyond the transient crater rim

Predicting video game players’ fun from physiological and behavioural data : one algorithm does not fit all

Finding a physiological signature of a player’s fun is a goal yet to be achieved in the field of adaptive gaming. The research presented in this paper tackles this issue by gathering physiological, behavioural and self-report data from over 200 participants who played off-the-shelf video games from the Assassin’s Creed series within a minimally invasive laboratory environment. By leveraging machine learning techniques the prediction of the player’s fun from its physiological and behavioural markers becomes a possibility. They provide clues as to which signals are the most relevant in establishing a physiological signature of the fun factor by providing an important score based on the predictive power of each signal. Identifying those markers and their impact will prove crucial in the development of adaptive video games. Adaptive games tailor their gameplay to the affective state of a player in order to deliver the optimal gaming experience. Indeed, an adaptive video game needs a continuous reading of the fun level to be able to respond to these changing fun levels in real time. While the predictive power of the presented classifier remains limited with a gain in the F1 score of 15% against random chance, it brings insight as to which physiological features might be the most informative for further analysis and discuss means by which low accuracy classification could still improve gaming experience

Can dissonance engineering improve risk analysis of human–machine systems?

The paper discusses dissonance engineering and its application to risk analysis of human–machine systems. Dissonance engineering relates to sciences and technologies relevant to dissonances, defined as conflicts between knowledge. The richness of the concept of dissonance is illustrated by a taxonomy that covers a variety of cognitive and organisational dissonances based on different conflict modes and baselines of their analysis. Knowledge control is discussed and related to strategies for accepting or rejecting dissonances. This acceptability process can be justified by a risk analysis of dissonances which takes into account their positive and negative impacts and several assessment criteria. A risk analysis method is presented and discussed along with practical examples of application. The paper then provides key points to motivate the development of risk analysis methods dedicated to dissonances in order to identify the balance between the positive and negative impacts and to improve the design and use of future human–machine system by reinforcing knowledge

Identification of differential gene expression in in vitro FSH treated pig granulosa cells using suppression subtractive hybridization

FSH, which binds to specific receptors on granulosa cells in mammals, plays a key role in folliculogenesis. Its biological activity involves stimulation of intercellular communication and upregulation of steroidogenesis, but the entire spectrum of the genes regulated by FSH has yet to be fully characterized. In order to find new regulated transcripts, however rare, we have used a Suppression Subtractive Hybridization approach (SSH) on pig granulosa cells in primary culture treated or not with FSH. Two SSH libraries were generated and 76 clones were sequenced after selection by differential screening. Sixty four different sequences were identified, including 3 novel sequences. Experiments demonstrated the presence of 25 regulated transcripts. A gene ontology analysis of these 25 genes revealed (1) catalytic; (2) transport; (3) signal transducer; (4) binding; (5) anti-oxidant and (6) structural activities. These findings may deepen our understanding of FSH's effects. Particularly, they suggest that FSH is involved in the modulation of peroxidase activity and remodelling of chromatin

Analysis of BAC-end sequences in rainbow trout: Content characterization and assessment of synteny between trout and other fish genomes

<p>Abstract</p> <p>Background</p> <p>Rainbow trout (<it>Oncorhynchus mykiss</it>) are cultivated worldwide for aquaculture production and are widely used as a model species to gain knowledge of many aspects of fish biology. The common ancestor of the salmonids experienced a whole genome duplication event, making extant salmonids such as the rainbow trout an excellent model for studying the evolution of tetraploidization and re-diploidization in vertebrates. However, the lack of a reference genome sequence hampers research progress for both academic and applied purposes. In order to enrich the genomic tools already available in this species and provide further insight on the complexity of its genome, we sequenced a large number of rainbow trout BAC-end sequences (BES) and characterized their contents.</p> <p>Results</p> <p>A total of 176,485 high quality BES, were generated, representing approximately 4% of the trout genome. BES analyses identified 6,848 simple sequence repeats (SSRs), of which 3,854 had high quality flanking sequences for PCR primers design. The first rainbow trout repeat elements database (INRA RT rep1.0) containing 735 putative repeat elements was developed, and identified almost 59.5% of the BES database in base-pairs as repetitive sequence. Approximately 55% of the BES reads (97,846) had more than 100 base pairs of contiguous non-repetitive sequences. The fractions of the 97,846 non-repetitive trout BES reads that had significant BLASTN hits against the zebrafish, medaka and stickleback genome databases were 15%, 16.2% and 17.9%, respectively, while the fractions of the non-repetitive BES reads that had significant BLASTX hits against the zebrafish, medaka, and stickleback protein databases were 10.7%, 9.5% and 9.5%, respectively. Comparative genomics using paired BAC-ends revealed several regions of conserved synteny across all the fish species analyzed in this study.</p> <p>Conclusions</p> <p>The characterization of BES provided insights on the rainbow trout genome. The discovery of specific repeat elements will facilitate analyses of sequence content (e.g. for SNPs discovery and for transcriptome characterization) and future genome sequence assemblies. The numerous microsatellites will facilitate integration of the linkage and physical maps and serve as valuable resource for fine mapping QTL and positional cloning of genes affecting aquaculture production traits. Furthermore, comparative genomics through BES can be used for identifying positional candidate genes from QTL mapping studies, aid in future assembly of a reference genome sequence and elucidating sequence content and complexity in the rainbow trout genome.</p

Molecular Blocking of CD23 Supports Its Role in the Pathogenesis of Arthritis

BACKGROUND: CD23 is a differentiation/activation antigen expressed by a variety of hematopoietic and epithelial cells. It can also be detected in soluble forms in biological fluids. Initially known as the low-affinity receptor for immunoglobulin E (Fc epsilonRII), CD23 displays various other physiologic ligands such as CD21, CD11b/c, CD47-vitronectin, and mannose-containing proteins. CD23 mediates numerous immune responses by enhancing IgE-specific antigen presentation, regulating IgE synthesis, influencing cell differentiation and growth of both B- and T-cells. CD23-crosslinking promotes the secretion of pro-inflammatory mediators from human monocytes/macrophages, eosinophils and epithelial cells. Increased CD23 expression is found in patients during allergic reactions and rheumatoid arthritis while its physiopathologic role in these diseases remains to be clarified. METHODOLOGY/PRINCIPAL FINDINGS: We previously generated heptapeptidic countrestructures of human CD23. Based on in vitro studies on healthy and arthritic patients' cells, we showed that CD23-specific peptide addition to human macrophages greatly diminished the transcription of genes encoding inflammatory cytokines. This was also confirmed by significant reduction of mediator levels in cell supernatants. We also show that CD23 peptide decreased IgE-mediated activation of both human and rat CD23(+) macrophages. In vivo studies in rat model of arthritis showed that CD23-blocking peptide ameliorates clinical scores and prevent bone destruction in a dose dependent manner. Ex-vivo analysis of rat macrophages further confirmed the inhibitory effect of peptides on their activation. Taken together our results support the role of CD23 activation and subsequent inflammatory response in arthritis. CONCLUSION: CD23-blocking peptide (p30A) prevents the activation of monocytes/macrophages without cell toxicity. Thus, targeting CD23 by antagonistic peptide decreases inflammatory markers and may have clinical value in the treatment of human arthritis and allergic reactions involving CD23