Final Research Report on Auto-Tagging of Music

The deliverable D4.7 concerns the work achieved by IRCAM until M36 for the “auto-tagging of music”. The deliverable is a research report. The software libraries resulting from the research have been integrated into Fincons/HearDis! Music Library Manager or are used by TU Berlin. The final software libraries are described in D4.5. The research work on auto-tagging has concentrated on four aspects: 1) Further improving IRCAM’s machine-learning system ircamclass. This has been done by developing the new MASSS audio features, including audio augmentation and audio segmentation into ircamclass. The system has then been applied to train HearDis! “soft” features (Vocals-1, Vocals-2, Pop-Appeal, Intensity, Instrumentation, Timbre, Genre, Style). This is described in Part 3. 2) Developing two sets of “hard” features (i.e. related to musical or musicological concepts) as specified by HearDis! (for integration into Fincons/HearDis! Music Library Manager) and TU Berlin (as input for the prediction model of the GMBI attributes). Such features are either derived from previously estimated higher-level concepts (such as structure, key or succession of chords) or by developing new signal processing algorithm (such as HPSS) or main melody estimation. This is described in Part 4. 3) Developing audio features to characterize the audio quality of a music track. The goal is to describe the quality of the audio independently of its apparent encoding. This is then used to estimate audio degradation or music decade. This is to be used to ensure that playlists contain tracks with similar audio quality. This is described in Part 5. 4) Developing innovative algorithms to extract specific audio features to improve music mixes. So far, innovative techniques (based on various Blind Audio Source Separation algorithms and Convolutional Neural Network) have been developed for singing voice separation, singing voice segmentation, music structure boundaries estimation, and DJ cue-region estimation. This is described in Part 6.EC/H2020/688122/EU/Artist-to-Business-to-Business-to-Consumer Audio Branding System/ABC D

Le numérique à l’école : évolution ou révolution pédagogique ?

Ce débat entre experts et praticiens fait apparaître des lignes de fracture et de force : fracture entre le temps long de l’école et l’immédiateté numérique de la jeunesse, tensions sur les mésusages technologiques, mais aussi travail d’équipe, développement de projets, enrichissement de la culture humaniste. Le numérique bouscule l’école, ses certitudes, son organisation, ses instruments. Son enseignement ne saurait, selon les participants, se réduire à celui d’une discipline, et requiert une approche transversale de la littératie numérique, associant usage responsable des instruments, connaissance des grand concepts du numérique, et développement d’une réflexion scientifique, éthique et philosophique.This debate between experts and practitioners reveals the main areas of discussion and divergence: the gap between the long timeframe of school and the digital immediacy of youth, tensions surrounding the misuse of technologies, but also teamwork, project development and an enriched culture of humanism. Digital technologies are disrupting school’s certainties, organisation and -equipment. According to the speakers, the teaching of digital technologies cannot be reduced to a single discipline and requires a multisectoral approach to digital literacy – one that combines the responsible use of equipment, knowledge of major digital concepts and the development of scientific, ethical and philosophical reflections.Este debate entre expertos y practicantes hace aparecer unas líneas de fractura : fractura entre el tiempo largo de la escuela y la inmediatez digital de la juventud, tensiones entre los malos usos tecnológicos, pero también trabajo colectivo, desarrollo de proyectos, enriquecimiento de la cultura humanista. Lo digital empuja a la escuela, sus certidumbres, su organización, sus instrumentos. Según los participantes, su enseñanza no podría reducirse al de una asignatura, y requiere una aproximación transversal de la alfabetización digital, que asocie uso responsable de los instrumentos, conocimiento de los grandes conceptos de lo digital y desarrollo de una reflexión científica, ética y filosófica

Positive regulation of plasmacytoid dendritic cell function via Ly49Q recognition of class I MHC

Plasmacytoid dendritic cells (pDCs) are an important source of type I interferon (IFN) during initial immune responses to viral infections. In mice, pDCs are uniquely characterized by high-level expression of Ly49Q, a C-type lectin-like receptor specific for class I major histocompatibility complex (MHC) molecules. Despite having a cytoplasmic immunoreceptor tyrosine-based inhibitory motif, Ly49Q was found to enhance pDC function in vitro, as pDC cytokine production in response to the Toll-like receptor (TLR) 9 agonist CpG-oligonucleotide (ODN) could be blocked using soluble monoclonal antibody (mAb) to Ly49Q or H-2Kb. Conversely, CpG-ODN–dependent IFN-α production by pDCs was greatly augmented upon receptor cross-linking using immobilized anti-Ly49Q mAb or recombinant H-2Kb ligand. Accordingly, Ly49Q-deficient pDCs displayed a severely reduced capacity to produce cytokines in response to TLR7 and TLR9 stimulation both in vitro and in vivo. Finally, TLR9-dependent antiviral responses were compromised in Ly49Q-null mice infected with mouse cytomegalovirus. Thus, class I MHC recognition by Ly49Q on pDCs is necessary for optimal activation of innate immune responses in vivo

SeedGerm: a cost‐effective phenotyping platform for automated seed imaging and machine‐learning based phenotypic analysis of crop seed germination

Efficient seed germination and establishment are important traits for field and glasshouse crops. Large-scale germination experiments are laborious and prone to observer errors, leading to the necessity for automated methods. We experimented with five crop species, including tomato, pepper, Brassica, barley, and maize, and concluded an approach for large-scale germination scoring. Here, we present the SeedGerm system, which combines cost-effective hardware and open-source software for seed germination experiments, automated seed imaging, and machine-learning based phenotypic analysis. The software can process multiple image series simultaneously and produce reliable analysis of germination- and establishment-related traits, in both comma-separated values (CSV) and processed images (PNG) formats. In this article, we describe the hardware and software design in detail. We also demonstrate that SeedGerm could match specialists’ scoring of radicle emergence. Germination curves were produced based on seed-level germination timing and rates rather than a fitted curve. In particular, by scoring germination across a diverse panel of Brassica napus varieties, SeedGerm implicates a gene important in abscisic acid (ABA) signalling in seeds. We compared SeedGerm with existing methods and concluded that it could have wide utilities in large-scale seed phenotyping and testing, for both research and routine seed technology applications

Caecal metastasis from breast cancer presenting as intestinal obstruction

<p>Abstract</p> <p>Background</p> <p>Gastrointestinal metastsasis from the breast cancer are rare. We report a patient who presented with intestinal obstruction due to solitary caecal metastasis from infiltrating ductal carcinoma of breast. We also review the available literature briefly.</p> <p>Case presentation</p> <p>A 72 year old lady with past history of breast cancer presented with intestinal obstruction due to a caecal mass. She underwent an emergency right hemicolectomy. The histological examination of the right hemicolectomy specimen revealed an adenocarcinoma in caecum staining positive for Cytokeratin 7 and Carcinoembryonic antigen and negative for Cytokeratin 20, CDX2 and Estrogen receptor. Eight out of 11 mesenteric nodes showed tumour deposits. A histological diagnosis of metastatic breast carcinoma was given.</p> <p>Conclusion</p> <p>To the best of our knowledge, this is the first case report of solitary metastasis to caecum from infiltrating ductal carcinoma of breast. Awareness of this possibility will aid in appropriate management of such patients.</p

An affinity-based scoring scheme for predicting DNA-binding activities of modularly assembled zinc-finger proteins

Zinc-finger proteins (ZFPs) have long been recognized for their potential to manipulate genetic information because they can be engineered to bind novel DNA targets. Individual zinc-finger domains (ZFDs) bind specific DNA triplet sequences; their apparent modularity has led some groups to propose methods that allow virtually any desired DNA motif to be targeted in vitro. In practice, however, ZFPs engineered using this ‘modular assembly’ approach do not always function well in vivo. Here we report a modular assembly scoring strategy that both identifies combinations of modules least likely to function efficiently in vivo and provides accurate estimates of their relative binding affinities in vitro. Predicted binding affinities for 53 ‘three-finger’ ZFPs, computed based on energy contributions of the constituent modules, were highly correlated (r = 0.80) with activity levels measured in bacterial two-hybrid assays. Moreover, Kd values for seven modularly assembled ZFPs and their intended targets, measured using fluorescence anisotropy, were also highly correlated with predictions (r = 0.91). We propose that success rates for ZFP modular assembly can be significantly improved by exploiting the score-based strategy described here

A quinolin-8-ol sub-millimolar inhibitor of UGGT, the ER glycoprotein folding quality control checkpoint

Misfolded glycoprotein recognition and endoplasmic reticulum (ER) retention are mediated by the ER glycoprotein folding quality control (ERQC) checkpoint enzyme, UDP-glucose glycoprotein glucosyltransferase (UGGT). UGGT modulation is a promising strategy for broad-spectrum antivirals, rescue-of-secretion therapy in rare disease caused by responsive mutations in glycoprotein genes, and many cancers, but to date no selective UGGT inhibitors are known. The small molecule 5-[(morpholin-4-yl)methyl]quinolin-8-ol (5M-8OH-Q) binds a CtUGGTGT24 “WY” conserved surface motif conserved across UGGTs but not present in other GT24 family glycosyltransferases. 5M-8OH-Q has a 47 μM binding affinity for CtUGGTGT24 in vitro as measured by ligand-enhanced fluorescence. In cellula, 5M-8OH-Q inhibits both human UGGT isoforms at concentrations higher than 750 μM. 5M-8OH-Q binding to CtUGGTGT24 appears to be mutually exclusive to M5-9 glycan binding in an in vitro competition experiment. A medicinal program based on 5M-8OH-Q will yield the next generation of UGGT inhibitors