Time Series Clustering with Deep Reservoir Computing

This paper proposes a method for clustering of time series, based upon the ability of deep Reservoir Computing networks to grasp the dynamical structure of the series that is presented as input. A standard clustering algorithm, such as k-means, is applied to the network states, rather than the input series themselves. Clustering is thus embedded into the network dynamical evolution, since a clustering result is obtained at every time step, which in turn serves as initialisation at the next step. We empirically assess the performance of deep reservoir systems in time series clustering on benchmark datasets, considering the influence of crucial hyperparameters. Experimentation with the proposed model shows enhanced clustering quality, measured by the silhouette coefficient, when compared to both static clustering of data, and dynamic clustering with a shallow network

Approximating Euclidean by Imprecise Markov Decision Processes

Euclidean Markov decision processes are a powerful tool for modeling control problems under uncertainty over continuous domains. Finite state imprecise, Markov decision processes can be used to approximate the behavior of these infinite models. In this paper we address two questions: first, we investigate what kind of approximation guarantees are obtained when the Euclidean process is approximated by finite state approximations induced by increasingly fine partitions of the continuous state space. We show that for cost functions over finite time horizons the approximations become arbitrarily precise. Second, we use imprecise Markov decision process approximations as a tool to analyse and validate cost functions and strategies obtained by reinforcement learning. We find that, on the one hand, our new theoretical results validate basic design choices of a previously proposed reinforcement learning approach. On the other hand, the imprecise Markov decision process approximations reveal some inaccuracies in the learned cost functions

The co-evolution of technological promises, modelling, policies and climate change targets

The nature and framing of climate targets in international politics has changed substantially since their early expressions in the 1980s. Here, we describe their evolution in five phases-from 'climate stabilization' to specific 'temperature outcomes'-co-evolving with wider climate politics and policy, modelling methods and scenarios, and technological promises (from nuclear power to carbon removal). We argue that this co-evolution has enabled policy prevarication, leaving mitigation poorly delivered, yet the technological promises often remain buried in the models used to inform policy. We conclude with a call to recognise and break this pattern to unleash more effective and just climate policy. This Perspective maps the history of climate targets and shows how the international goal of avoiding dangerous climate change has been reinterpreted in the light of new modelling methods and technological promises, ultimately enabling policy prevarication and limiting mitigation

Automatic Tumor-Stroma Separation in Fluorescence TMAs Enables the Quantitative High-Throughput Analysis of Multiple Cancer Biomarkers

The upcoming quantification and automation in biomarker based histological tumor evaluation will require computational methods capable of automatically identifying tumor areas and differentiating them from the stroma. As no single generally applicable tumor biomarker is available, pathology routinely uses morphological criteria as a spatial reference system. We here present and evaluate a method capable of performing the classification in immunofluorescence histological slides solely using a DAPI background stain. Due to the restriction to a single color channel this is inherently challenging. We formed cell graphs based on the topological distribution of the tissue cell nuclei and extracted the corresponding graph features. By using topological, morphological and intensity based features we could systematically quantify and compare the discrimination capability individual features contribute to the overall algorithm. We here show that when classifying fluorescence tissue slides in the DAPI channel, morphological and intensity based features clearly outpace topological ones which have been used exclusively in related previous approaches. We assembled the 15 best features to train a support vector machine based on Keratin stained tumor areas. On a test set of TMAs with 210 cores of triple negative breast cancers our classifier was able to distinguish between tumor and stroma tissue with a total overall accuracy of 88%. Our method yields first results on the discrimination capability of features groups which is essential for an automated tumor diagnostics. Also, it provides an objective spatial reference system for the multiplex analysis of biomarkers in fluorescence immunohistochemistry

Repression of FLOWERING LOCUS C and FLOWERING LOCUS T by the Arabidopsis Polycomb Repressive Complex 2 Components

Polycomb group (PcG) proteins are evolutionarily conserved in animals and plants, and play critical roles in the regulation of developmental gene expression. Here we show that the Arabidopsis Polycomb repressive complex 2 (PRC2) subunits CURLY LEAF (CLF), EMBRYONIC FLOWER 2 (EMF2) and FERTILIZATION INDEPENDENT ENDOSPERM (FIE) repress the expression of FLOWERING LOCUS C (FLC), a central repressor of the floral transition in Arabidopsis and FLC relatives. In addition, CLF directly interacts with and mediates the deposition of repressive histone H3 lysine 27 trimethylation (H3K27me3) into FLC and FLC relatives, which suppresses active histone H3 lysine 4 trimethylation (H3K4me3) in these loci. Furthermore, we show that during vegetative development CLF and FIE strongly repress the expression of FLOWERING LOCUS T (FT), a key flowering-time integrator, and that CLF also directly interacts with and mediates the deposition of H3K27me3 into FT chromatin. Our results suggest that PRC2-like complexes containing CLF, EMF2 and FIE, directly interact with and deposit into FT, FLC and FLC relatives repressive trimethyl H3K27 leading to the suppression of active H3K4me3 in these loci, and thus repress the expression of these flowering genes. Given the central roles of FLC and FT in flowering-time regulation in Arabidopsis, these findings suggest that the CLF-containing PRC2-like complexes play a significant role in control of flowering in Arabidopsis

Crosslinking of a CD4 Mimetic Miniprotein with HIV-1 Env gp140 Alters Kinetics and Specificities of Antibody Responses against HIV-1 Env in Macaques

Evaluation of the epitope specificities, location (systemic, mucosal) and effector function of antibodies elicited by novel HIV-1 immunogens engineered to improve exposure of specific epitopes is critical for HIV-1 vaccine development. Utilizing an array of humoral assays, we evaluated the magnitude, epitope specificity, avidity and function of systemic and mucosal immune responses elicited by a vaccine regimen containing Env cross-linked to a CD4 mimetic miniprotein (gp140-M64U1) in rhesus macaques. Crosslinking of gp140 Env with M64U1 resulted in an earlier increase in both the magnitude and avidity of the IgG binding response compared to Env protein alone. Notably, binding IgG responses at an early time point correlated with Antibody Dependent Cellular Cytotoxicity (ADCC) function at the peak immunity time point, which was higher for the crosslinked Env group compared to the Env group alone. In addition, the crosslinked Env group developed higher IgG responses against a linear epitope in the C1 gp120 region of the HIV-1 envelope glycoprotein. These data demonstrate that structural modification of the HIV-1 envelope immunogen by crosslinking gp140 with the CD4 mimetic M64U1 elicited an earlier increase of binding antibody responses and altered the specificity of the IgG responses that correlated with the rise of subsequent antibody-mediated antiviral functions.IMPORTANCE The development of an efficacious HIV-1 vaccine remains a global priority to prevent new cases of HIV-1 infection. Of the six HIV-1 efficacy trials to date, only one has demonstrated partial efficacy, and the immune correlates analysis of this trial revealed a role for binding antibodies and antibody Fc mediated effector functions. New HIV-1 envelope immunogens are being engineered to selectively expose the most vulnerable and conserved sites on the HIV-1 envelope with the goal of eliciting antiviral antibodies. Evaluation of the humoral responses elicited by these novel immunogen designs in nonhuman primates is critical for understanding how to improve upon immunogen design to inform further testing in human clinical trials. Our results demonstrate that Env structural modifications that aim to mimic the CD4 bound conformation can result in earlier antibody elicitation, altered epitope specificity and increased antiviral function post immunization.This work was supported by the National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID) grants, Center for HIV/AIDS Vaccine Immunology (CHAVI)/ HIV Vaccine Trials Network (HVTN) Early Stage Investigator (ESI) Award (U19AI067854, UM1AI068618), (HHSN27201100016C), 1P01AI120756 and the NIH NIAID Duke Center for AIDS Research Immunology Core P30 AI 64518. The NHP study was funded by NIH PO1 AI066287-02

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

A Conserved Developmental Patterning Network Produces Quantitatively Different Output in Multiple Species of Drosophila

Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3–4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of equivalent cells

Nothing a Hot Bath Won't Cure: Infection Rates of Amphibian Chytrid Fungus Correlate Negatively with Water Temperature under Natural Field Settings

Dramatic declines and extinctions of amphibian populations throughout the world have been associated with chytridiomycosis, an infectious disease caused by the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Previous studies indicated that Bd prevalence correlates with cooler temperatures in the field, and laboratory experiments have demonstrated that Bd ceases growth at temperatures above 28°C. Here we investigate how small-scale variations in water temperature correlate with Bd prevalence in the wild. We sampled 221 amphibians, including 201 lowland leopard frogs (Rana [Lithobates] yavapaiensis), from 12 sites in Arizona, USA, and tested them for Bd. Amphibians were encountered in microhabitats that exhibited a wide range of water temperatures (10–50°C), including several geothermal water sources. There was a strong inverse correlation between the water temperature in which lowland leopard frogs were captured and Bd prevalence, even after taking into account the influence of year, season, and host size. In locations where Bd was known to be present, the prevalence of Bd infections dropped from 75–100% in water <15°C, to less than 10% in water >30°C. A strong inverse correlation between Bd infection status and water temperature was also observed within sites. Our findings suggest that microhabitats where water temperatures exceed 30°C provide lowland leopard frogs with significant protection from Bd, which could have important implications for disease dynamics, as well as management applications