The effect of curvature and topology on membrane hydrodynamics

We study the mobility of extended objects (rods) on a spherical liquid-liquid interface to show how this quantity is modified in a striking manner by both the curvature and the topology of the interface. We present theoretical calculations and experimental measurements of the interfacial fluid velocity field around a moving rod bound to the crowded interface of a water-in-oil droplet. By using different droplet sizes, membrane viscosities, and rod lengths, we show that the viscosity mismatch between the interior and exterior fluids leads to a suppression of the fluid flow on small droplets that cannot be captured by the flat interface predictions.Comment: 4 pages, 3 figure

From LTL and Limit-Deterministic B\"uchi Automata to Deterministic Parity Automata

Controller synthesis for general linear temporal logic (LTL) objectives is a challenging task. The standard approach involves translating the LTL objective into a deterministic parity automaton (DPA) by means of the Safra-Piterman construction. One of the challenges is the size of the DPA, which often grows very fast in practice, and can reach double exponential size in the length of the LTL formula. In this paper we describe a single exponential translation from limit-deterministic B\"uchi automata (LDBA) to DPA, and show that it can be concatenated with a recent efficient translation from LTL to LDBA to yield a double exponential, \enquote{Safraless} LTL-to-DPA construction. We also report on an implementation, a comparison with the SPOT library, and performance on several sets of formulas, including instances from the 2016 SyntComp competition

Dissociation of ssDNA - Single-Walled Carbon Nanotube Hybrids by Watson-Crick Base Pairing

The unwrapping event of ssDNA from the SWNT during the Watson-Crick base paring is investigated through electrical and optical methods, and binding energy calculations. While the ssDNA-metallic SWNT hybrid shows the p-type semiconducting property, the hybridization product recovered metallic properties. The gel electrophoresis directly verifies the result of wrapping and unwrapping events which was also reflected to the Raman shifts. Our molecular dynamics simulations and binding energy calculations provide atomistic description for the pathway to this phenomenon. This nano-physical phenomenon will open up a new approach for nano-bio sensing of specific sequences with the advantages of efficient particle-based recognition, no labeling, and direct electrical detection which can be easily realized into a microfluidic chip format.Comment: 4 pages, 4 figure

Reversible Metal-Semiconductor Transition of ssDNA-Decorated Single-Walled Carbon Nanotubes

A field effect transistor (FET) measurement of a SWNT shows a transition from a metallic one to a p-type semiconductor after helical wrapping of DNA. Water is found to be critical to activate this metal-semiconductor transition in the SWNT-ssDNA hybrid. Raman spectroscopy confirms the same change in electrical behavior. According to our ab initio calculations, a band gap can open up in a metallic SWNT with wrapped ssDNA in the presence of water molecules due to charge transfer.Comment: 13 pages, 6 figure

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

Gianluca Tramontana was supported by the GEOCARBON EU FP7 project (GA 283080). Dario Papale, Martin Jung and Markus Reichstein acknowledge funding from the EU FP7 project GEOCARBON (grant agreement no. 283080) and the EU H2020 BACI project (grant agreement no. 640176). Gustau Camps-Valls wants to acknowledge the support by an ERC Consolidator Grant with grant agreement 647423 (SEDAL). Kazuhito Ichii was supported by Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan and the JAXA Global Change Observation Mission (GCOM) project (no. 115). Christopher R. Schwalm was supported by National Aeronautics and Space Administration (NASA) grants nos. NNX12AP74G, NNX10AG01A, and NNX11AO08A. M. Altaf Arain thanks the support of Natural Sciences and Engineering Research Council (NSREC) of Canada. Penelope Serrano Ortiz was partially supported by the GEISpain project (CGL2014-52838-C2-1-R) funded by the Spanish Ministry of Economy and Competitiveness and the European Union ERDF funds. Sebastian Wolf acknowledges support from a Marie Curie International Outgoing Fellowship (European Commission, grant 300083). The FLUXCOM initiative is coordinated by Martin Jung, Max Planck Institute for Biogeochemistry (Jena, Germany). This work used eddy-covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (US Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, FluxnetCanada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy-covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, the Max Planck Institute for Biogeochemistry, the National Science Foundation, the University of Tuscia and the US Department of Energy, and the databasing and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, the University of California - Berkeley, and the University of Virginia.Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2  0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.European Union (EU) GA 283080 283080 640176European Research Council (ERC) 647423Ministry of the Environment, Japan 2-1401JAXA Global Change Observation Mission (GCOM) project 115National Aeronautics & Space Administration (NASA) NNX12AP74G NNX10AG01A NNX11AO08ANatural Sciences and Engineering Research Council of CanadaGEISpain project - Spanish Ministry of Economy and Competitiveness CGL2014-52838-C2-1-REuropean Commission Joint Research Centre 300083United States Department of Energy (DOE) DE-FG02-04ER63917 DE-FG02-04ER63911FAO-GTOS-TCOiLEAPSMax Planck Institute for BiogeochemistryNational Science Foundation (NSF)University of Tusci

Omega-Regular Objectives in Model-Free Reinforcement Learning

We provide the first solution for model-free reinforcement learning of ω-regular objectives for Markov decision processes (MDPs). We present a constructive reduction from the almost-sure satisfaction of ω-regular bjectives to an almost-sure reachability problem, and extend this technique to learning how to control an unknown model so that the chance of satisfying the objective is maximized. We compile ω-regular properties into limit-deterministic B¨uchi automata instead of the traditional Rabin automata; this choice sidesteps difficulties that have marred previous proposals. Our approach allows us to apply model-free, off-the-shelf reinforcement learning algorithms to compute optimal strategies from the observations of the MDP. We present an experimental evaluation of our technique on benchmark learning problems

The Male Warrior Hypothesis: Testosterone-related Cooperation and Aggression in the Context of Intergroup Conflict

Indexación ScopusThe Male Warrior Hypothesis (MWH) establishes that men’s psychology has been shaped by inter-group competition to acquire and protect reproductive resources. In this context, sex-specific selective pressures would have favored cooperation with the members of one’s group in combination with hostility towards outsiders. We investigate the role of developmental testosterone, as measured indirectly through static markers of prenatal testosterone (2D:4D digit ratio) and pubertal testosterone (body musculature and facial masculinity), on both cooperation and aggressive behavior in the context of intergroup conflict among men. Supporting the MWH, our results show that the intergroup conflict scenario promotes cooperation within group members and aggression toward outgroup members. Regarding the hormonal underpinnings of this phenomenon, we find that body musculature is positively associated with aggression and cooperation, but only for cooperation when context (inter-group competition) is taken into account. Finally, we did not find evidence that the formidability of the group affected individual rates of aggression or cooperation, controlling for individual characteristics. © 2020, The Author(s).https://www-nature-com.recursosbiblioteca.unab.cl/articles/s41598-019-57259-

The effect of social interactions in the primary life cycle of motion pictures

We model the consumption life cycle of theater attendance for single movies by taking into account the size of the targeted group and the effect of social interactions. We provide an analytical solution of such model, which we contrast with empirical data from the film industry obtaining good agreement with the diverse types of behaviors empirically found. The model grants a quantitative measure of the valorization of this cul- tural good based on the relative values of the coupling between agents who have watched the movie and those who have not. This represents a measurement of the observed quality of the good that is extracted solely from its dynamics, independently of critics reviews.Comment: 9 Pages, 3 figure

Tumor-infiltrating macrophages and dendritic cells in human colorectal cancer: relation to local regulatory T cells, systemic T-cell response against tumor-associated antigens and survival

<p>Abstract</p> <p>Introduction</p> <p>Although systemic T-cell responses against tumor antigens and tumor infiltration by T cells have been investigated in colorectal cancer (CRC), the initiation of spontaneous immune responses <it>in situ </it>is not well understood. Macrophages and dendritic cells (DC) play an important role as a link between innate and adaptive immune response. The aim of the present study was to analyze macrophage and DC infiltration in CRC and to investigate whether there is a correlation to systemic T-cell response, regulatory T cell (Treg) infiltration, and survival.</p> <p>Methods</p> <p>Immunohistological staining was performed with nine markers for macrophages and DC (CD68, CD163, S100, CD11c, CD208, CD209, CD123, CD1a, Langerin) in 40 colorectal cancer samples from patients, in whom the state of systemic T-cell responses against tumor-associated antigens (TAA) and Treg infiltration had previously been determined.</p> <p>Results</p> <p>All specimens contained cells positive for CD68, CD163, S100 and CD1a in epithelial tumor tissue and tumor stroma. Only a very few (less than median 3/HPF) CD123+, CD1a+, CD11c+, CD 208+, CD209+, or Langerin+ cells were detected in the specimens. Overall, we found a trend towards increased infiltration by S100-positive DC and a significantly increased number of stromal S100-positive DC in patients without T-cell response. There was an increase of stromal S100 DC and CD163 macrophages in limited disease (S100: 11.1/HPF vs. 7.3/HPF, p = 0.046; CD163: 11.0/HPF vs. 8.1/HPF, p = 0.06). We found a significant, positive correlation between S100-positive DC and FOXP3-positive Tregs. Survival in patients with high DC infiltration was significantly better than that in those with low DC infiltration (p < 0.05). Furthermore, we found a trend towards better survival for increased infiltration with CD163-positive macrophages (p = 0.07).</p> <p>Conclusion</p> <p>The present <it>in situ </it>study adds new data to the discussion on the interaction between the innate and adoptive immune system. Our data strongly support the hypothesis that tumor-infiltrating DC are a key factor at the interface between innate and adaptive immune response in malignant disease. Tumor infiltrating S100-positive DC show an inverse relationship with the systemic antigen-specific T-cell response, a positive correlation with regulatory T cells, and a positive association with survival in CRC. These data put tumor-infiltrating DC at the center of the relevant immune response in CRC.</p