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Deep Learning methods achieve state-of-the-art in many tasks, including vocal pitch extraction. However, these methods rely on the availability of pitch track annotations without errors, which are scarce and expensive to obtain for Carnatic Music. Here we identify the tradition-related challenges and propose tailored solutions to generate a novel, large, and open dataset, the Saraga-Carnatic-Melody-Synth (SCMS), comprising audio mixtures and time-aligned vocal pitch annotations. Through a cross-cultural evaluation leveraging this novel dataset, we show improvements in the performance of Deep Learning vocal pitch extraction methods on Indian Art Music recordings. Additional experiments show that the trained models outperform the currently used heuristic-based pitch extraction solutions for the computational melodic analysis of Carnatic Music and that this improvement leads to better results in the musicologically relevant task of repeated melodic pattern discovery when evaluated using expert annotations. The code and annotations are made available for reproducibility. The novel dataset and trained models are also integrated into the Python package compIAM1 which allows them to be used out-of-the-box.

Abstract Background Mechanisms driving the progression of chronic lymphocytic leukemia (CLL) from its early stages are not fully understood. The acquisition of molecular changes at the time of progression has been observed in a small fraction of patients, suggesting that CLL progression is not mainly driven by dynamic clonal evolution. In order to shed light on mechanisms that lead to CLL progression, we investigated longitudinal changes in both the genetic and immunological scenarios. Methods We performed genetic and immunological longitudinal analysis using paired primary samples from untreated CLL patients that underwent clinical progression (sampling at diagnosis and progression) and from patients with stable disease (sampling at diagnosis and at long-term asymptomatic follow-up). Results Molecular analysis showed limited and non-recurrent molecular changes at progression, indicating that clonal evolution is not the main driver of clinical progression. Our analysis of the immune kinetics found an increasingly dysfunctional CD8+ T cell compartment in progressing patients that was not observed in those patients that remained asymptomatic. Specifically, terminally exhausted effector CD8+ T cells (T-betdim/−EomeshiPD1hi) accumulated, while the the co-expression of inhibitory receptors (PD1, CD244 and CD160) increased, along with an altered gene expression profile in T cells only in those patients that progressed. In addition, malignant cells from patients at clinical progression showed enhanced capacity to induce exhaustion-related markers in CD8+ T cells ex vivo mainly through a mechanism dependent on soluble factors including IL-10. Conclusions Altogether, we demonstrate that the interaction with the immune microenvironment plays a key role in clinical progression in CLL, thereby providing a rationale for the use of early immunotherapeutic intervention.

The use of CSF for diagnosis of metastatic brain tumors could be of clinical and patient benefit. Here the authors undertake a single-cell RNA analysis of CSF and brain to determine whether the phenotype in the CSF is reflective of the phenotype in the tumor.

Attractor networks and drift diffusion models are two approaches to model the perceptual decision making process. Here, the authors identify an intermediate regime only for the attractor model that allows flexible categorization of two choice decisions for long duration and noisy stimuli and validate these model predictions with psychophysical experiments.

This text presents an investigation of social interaction taking place in the public space of Plaça del Sol (Barcelona), conducted in terms of the conceptual framework offered by the thought of Jürgen Habermas regarding "public opinion" and "communicative rationality". After giving an account of the theoretical and methodological aspects which have informed the study, the article focuses on presenting the findings in concordance with the Frankfurtian philosopher’s conception of ‘communicative action’. Lastly, the studied human activity of the public sphere constitutes a foundation from which a discussion of ideal of a civic and politically active citizenship defended by Jürgen Harbermas and Hannah Arendt.

Cis-regulatory elements are important factors for morphological changes. Here, the authors show widespread divergence of limb and eye regulatory elements in limb loss in snakes and eye degeneration in subterranean mammals respectively.

Review of: FERNÁNDEZ LIRIA, Carlos (2016). En defensa del populismo. Madrid: Los Libros de la Catarata. 240 pp.

Reseña de Prieto (2018) Clase, pueblo y naciónGenís Plana Joya

The Cucurbita pepo genome comprises 263 Mb and 34,240 gene models organized in 20 different chromosomes. To improve our understanding of gene function we have generated an EMS mutant platform, consisting of 3,751 independent M2 families. The quality of the collection has been evaluated based on phenotyping and whole-genome re-sequencing (WGS) results. The phenotypic evaluation of the whole platform at seedling stage has demonstrated that the rate of variation for easily observable traits is more than 10%. The percentage of families with albino or chlorotic seedlings exceeded 3%, similar or higher to that found in other EMS collections of cucurbit crops. A rapid screening of the library for triple ethylene response in etiolated seedlings allowed the identification of four ethylene-insensitive mutants, that were found to be semidominant (ein1, ein2, and ein3) or dominant (EIN4). By evaluating 4 adult plants from 300 independent families more than 28% of apparent mutations were found for vegetative and reproductive traits, including plant vigor, leaf size and shape, sex expression and sex determination, and fruit set and development. Two pools of genomic DNA derived from 20 plants of two mutant families were subjected to WGS by using NGS methodology, estimating the density, spectrum, distribution and impact of EMS induced mutation. The number of EMS mutations in the genomes of families L1 and L2 was 1,704 and 859, respectively, which represents a density of 11.8 and 6 mutations per Mb, respectively. As expected, the predominant EMS induced mutations were C > T and G > A transitions (80.3% in L1, and 61% L2), that were found to be randomly distributed along the 20 chromosomes of C. pepo. The mutations were mostly affecting intergenic regions, but 7.9 and 6% of the identified EMS mutations in L1 and L2, respectively, were located in the exome, and 0.4 and 0.2% had a moderate and high putative impact on gene functions. These results provide information regarding the potential use of the obtained mutant platform in the discovery of novel alleles for both functional genomics and Cucurbita breeding by using direct- or reverse-genetic approaches.

Crítica de libro: Francisco Javier Ullán de la Rosa. Teorías sociológicas de los movimientos sociales. Madrid: La Catarata, 2016, 96 páginas, ISBN: 9788490972557.

The brain is able to interpret streams of high-dimensional ambiguous information and yield coherent percepts. The mechanisms governing sensory integration have been extensively characterized using time-varying visual stimuli (Britten et al. 1996; Roitman and Shadlen 2002), but some of the basic principles regarding the network dynamics underlying this process remain largely unknown. We captured the basic features of a neural integrator using three canonical one-dimensional models: (1) the Drift Diffusion Model (DDM), (2) the Perfect Integrator (PI) which is a particular case of the DDM where the bounds are set to infinity and (3) the double-well potential (DW) which captures the dynamics of the attractor networks (Wang 2002; Roxin and Ledberg 2008). Although these models has been widely studied (Bogacz et al. 2006; Roxin and Ledberg 2008; Gold and Shadlen 2002), it has been difficult to experimentally discriminate among them because most of the observables measured are only quantitatively different among these models (e.g. psychometric curves). Here we aim to find experimentally measurable quantities that can yield qualitatively different behaviors depending on the nature of the underlying network dynamics. We examined the categorization dynamics of these models in response to fluctuating stimuli of different duration (T). On each time step, stimuli are drawn from a Gaussian distribution N(μ, σ) and the two stimulus categories are defined by μ > 0 and μ < 0. Psychometric curves can therefore be obtained by quantifying the probability of the integrator to yield one category versus μ . We find however that varying σ can reveal more clearly the differences among the different integrators. In the small σ regime, both the DW and the DDM perform transient integration and exhibit a decaying stimulus reverse correlation kernel revealing a primacy effect (Nienborg and Cumming 2009; Wimmer et al. 2015) . In the large σ regime, the integration in the DDM becomes even more transient (i.e. the bound is reached earlier during the stimulus) but in the DW the rate of reversed classifications increases and the kernel changes from monotonically decreasing to monotonically increasing revealing a recency effect. In contrast the PI performs uniform integration and shows a constant kernel for all σ's. The discrimination sensitivity in the PI decreases monotonically as 1/σ just because the two stimulus categories become less separable in the stimulus space. In the DDM the decrease with σ is even more pronounced due to the reduction of the effective integration time (the average time to reach the bound). Unexpectedly however, the sensitivity in the DW shows a non-monotonic behavior with a local maximum for Ts beyond a critical value. This is because, provided there is enough time to reverse the initial classification, the increase in the rate of correcting reversals compensates for the decrease in stimulus separability. Finally, we also found that the three models behave differently with σ when the initial condition of the integrator is offset (e.g. representing that the prior probabilities of the two stimulus categories are uneven): increasing σ decreases the choice bias caused by the offset in the DW model, increases the bias for the DDM model and leaves it unchanged in the PI model. We propose specific ways to test these predictions in a random duration two alternative forced-choice (2AFC) task which could help us pinning down the basic principles of sensory integration dynamics.