305,370 research outputs found
GEmo-CLAP: Gender-Attribute-Enhanced Contrastive Language-Audio Pretraining for Accurate Speech Emotion Recognition
No full textContrastive cross-modality pretraining has recently exhibited impressive
success in diverse fields, whereas there is limited research on their merits in
speech emotion recognition (SER). In this paper, we propose GEmo-CLAP, a kind
of gender-attribute-enhanced contrastive language-audio pretraining (CLAP)
method for SER. Specifically, we first construct an effective emotion CLAP
(Emo-CLAP) for SER, using pre-trained text and audio encoders. Second, given
the significance of gender information in SER, two novel multi-task learning
based GEmo-CLAP (ML-GEmo-CLAP) and soft label based GEmo-CLAP (SL-GEmo-CLAP)
models are further proposed to incorporate gender information of speech
signals, forming more reasonable objectives. Experiments on IEMOCAP indicate
that our proposed two GEmo-CLAPs consistently outperform Emo-CLAP with
different pre-trained models. Remarkably, the proposed WavLM-based SL-GEmo-CLAP
obtains the best WAR of 83.16\%, which performs better than state-of-the-art
SER methods.Comment: 5 page
Modelling phase-change integrated photonic devices
No full textAvailable from E\PCOS via the link in this recordWe report the progress made on the development of a self-consistent 3-dimensional simulation framework, yielding the time and spatially resolved electric field, temperature and material phase, for integrated phase-change photonic devices. We illustrate the analysis made for a prototypical integrated phase-change photonic memory, and report the results of SET and RESET operations.Engineering and Physical Sciences Research Council (EPSRC
SHIP: a computational framework for simulating and validating novel technologies in hardware spiking neural networks
No full textInvestigations in the field of spiking neural networks (SNNs) encompass diverse, yet overlapping, scientific disciplines. Examples range from purely neuroscientific investigations, researches on computational aspects of neuroscience, or applicative-oriented studies aiming to improve SNNs performance or to develop artificial hardware counterparts. However, the simulation of SNNs is a complex task that can not be adequately addressed with a single platform applicable to all scenarios. The optimization of a simulation environment to meet specific metrics often entails compromises in other aspects. This computational challenge has led to an apparent dichotomy of approaches, with model-driven algorithms dedicated to the detailed simulation of biological networks, and data-driven algorithms designed for efficient processing of large input datasets. Nevertheless, material scientists, device physicists, and neuromorphic engineers who develop new technologies for spiking neuromorphic hardware solutions would find benefit in a simulation environment that borrows aspects from both approaches, thus facilitating modeling, analysis, and training of prospective SNN systems. This manuscript explores the numerical challenges deriving from the simulation of spiking neural networks, and introduces SHIP, Spiking (neural network) Hardware In PyTorch, a numerical tool that supports the investigation and/or validation of materials, devices, small circuit blocks within SNN architectures. SHIP facilitates the algorithmic definition of the models for the components of a network, the monitoring of states and output of the modeled systems, and the training of the synaptic weights of the network, by way of user-defined unsupervised learning rules or supervised training techniques derived from conventional machine learning. SHIP offers a valuable tool for researchers and developers in the field of hardware-based spiking neural networks, enabling efficient simulation and validation of novel technologies
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
On the interaction of replication and transcriptional regulation
No full textDNA replication introduces a gradient of gene copy numbers, and in Bacteria it affects gene expression accordingly. In E. coli and other species, the slope of the gradient averaged over the population can be predicted on the basis of its relationship with growth rate. In this work we integrated this growth- and position-dependent gradient into a classical transcriptional regulation model, to highlight their interaction. The theoretical treatment of our model highlights that the sensitivity to transcription factor-mediated regulations acquires an additional dimension related to the position of a locus on the oriter axis and to division time. This reinforces the idea of replication as an additional layer in gene regulation. We highlight here that replication- and transcription factor-mediated regulations can in theory work in concert or counteract each other, and we discuss why this is important from an evolutionary point of view with respect to both steady state transcript abundance and its variance across conditions. Finally, we note that this treatment may improve the estimation of kinetic parameters for transcription factor activity using RNA-seq data, and the estimation of the dispersion factor in differential gene expression analysis when division time across conditions changes significantly
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
The GEMO project: Analysis and comparison of genomes of the fungal pathogen Magnaporthe oryzae
No full textGEMO is a project of comparative fungal genomics focusing on related species and sub-species from the Magnaporthe grisea/oryzae species complex. The dataset gathered by the GEMO project encompasses 10 Magnaporthe genomes: 9 M. oryzae genomes from isolates specifically pathogenic on Oryza sativa, Triticum sp, Setaria sp or Eleusine sp, and 1 from a M. grisea isolate specifically pathogenic on Digitaria sp. In this project, the MIG in collaboration with the URGI-Bioger platform are realizing a comparative analysis of these genomes which consists of automatic annotation of genes, structural comparison of these genomes and detection of positive selection in orthologs across this taxonomic sampling [1]. In addition, a detailed evolutionary and syntenic analysis will be performed on two particular groups of genes encoding putative effectors known to be involved in pathogenicity: small secreted proteins (SSPs) and genes involved in the biosynthesis of secondary metabolites. The first step will be to establish the repertory of genes belonging to these families in the 10 available genomes. Different sources of information will be used, such as a set of lists of secondary metabolism genes already established [1], a list of SSP to be compiled fromdifferent sources (transcriptomes, proteomes, effectomes), the automatic annotations of the 10available genomes, and RNAseq data from in planta early infection. We will then address three questions: 1) Are SSP and secondary metabolism genes more subject to birth/death/duplication processes and to horizontal gene transfers, than the rest of the coding genome? 2) Are transposable elements more frequently associated with SSP and secondarymetabolism genes than in the rest of the coding genome? 3) Are SSP and secondary metabolism genes more targeted by positive selection than the rest of the coding genome? All this information will allow depicting the evolutionary history of some pathogenicity and host-specificity related genes in Magnaporthe. [1] Collemare 2007. Communication entre les plantes et leurs agents pathogènes : rôle des métabolites secondaires dans la reconnaissance du champignon Magnaporthe grisea par le riz. PhD Thesis
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