Maximum Entropy Bootstrap for Time Series: The meboot R Package

The maximum entropy bootstrap is an algorithm that creates an ensemble for time series inference. Stationarity is not required and the ensemble satisfies the ergodic theorem and the central limit theorem. The meboot R package implements such algorithm. This document introduces the procedure and illustrates its scope by means of several guided applications.

Maximum Entropy Bootstrap for Time Series: The meboot R Package

The maximum entropy bootstrap is an algorithm that creates an ensemble for time series inference. Stationarity is not required and the ensemble satisfies the ergodic theorem and the central limit theorem. The meboot R package implements such algorithm. This document introduces the procedure and illustrates its scope by means of several guided applications

Molecular Model of the Contractile Ring

We present a model for the actin contractile ring of adherent animal cells. The model suggests that the actin concentration within the ring and consequently the power that the ring exerts both increase during contraction. We demonstrate the crucial role of actin polymerization and depolymerization throughout cytokinesis, and the dominance of viscous dissipation in the dynamics. The physical origin of two phases in cytokinesis dynamics ("biphasic cytokinesis") follows from a limitation on the actin density. The model is consistent with a wide range of measurements of the midzone of dividing animal cells.Comment: PACS numbers: 87.16.Ka, 87.16.Ac http://www.ncbi.nlm.nih.gov/pubmed/16197254 http://www.weizmann.ac.il/complex/tlusty/papers/PhysRevLett2005.pd

Self-identity disclosure in TV Fandom : Analysing the comments posted by Spanish female fans and community managers

Digital age brings to television fiction viewers a variety of spaces where they can disclose their self-identity and emotions generated by the texts consumed. Methodology. This article analyses 7,849 comments posted by female fans and community managers on 122 sites (forums and social networks) dedicated to the Spanish TV fiction. The 22,301 items generated from the comments analysed explore the emotions aroused by television fiction, such as joy, enthusiasm

BODIPY-based conjugated polymers for broadband light sensing and harvesting applications

The synthesis of novel low band-gap polymers has significantly improved light sensing and harvesting in polymer-fullerene devices. Here the synthesis of two low band-gap polymers based on the 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene core (BODIPY), and either bis(3,4-ethylenedioxythiophene) (bis-EDOT) or its all-sulfur analogue bis(3,4-ethylenedithiathiophene) (bis-EDTT) are described. The polymers demonstrate ambipolar charge transport and are shown to be suitable for broadband light sensing and solar energy harvesting in solution-processable polymer-fullerene devices

Short-Cut Method to Assess a Gross Available Energy in a Medium-Load Screw Friction Press

The present study proposed a rapid method, based on a previous universal compression tests, to estimate the required load capacity to cold forge different specimen quantity in a screw press. Accordingly, experimental and theoretical approach are performed to check new adjustable drive motor of the modified forging machine to achieve a gross available energy to deform the specimens preventing damage of the forging machine. During the forging experiments, two screw friction presses (as-received and modified) are used to validate the theoretical approach. The modified press exhibits an increase of 51% of gross energy and 11% of maximum load capacity compare to the as-received press. This method is used to improve the effective of the forging process avoiding excessive loads that could promote machine failure. Therefore, a low-cost and easy to implement methodology is proposed to determine the energy and load capacity of a screw friction press to forge different specimen quantities with symmetry pattern configurations.This work is supported by the Ministry of Economy and Competitiveness of Spain (reference project: FJCI-2016-29297), Instituto Nacional de Tecnologia Industrial (INTI) of Argentina and the Aeronautics Advanced Manufacturing Center (CFAA) of Bilbao

An air-stable DPP-thieno-TTF copolymer for single-material solar cell devices and field effect transistors

Following an approach developed in our group to incorporate tetrathiafulvalene (TTF) units into conjugated polymeric systems, we have studied a low band gap polymer incorporating TTF as a donor component. This polymer is based on a fused thieno-TTF unit that enables the direct incorporation of the TTF unit into the polymer, and a second comonomer based on the diketopyrrolopyrrole (DPP) molecule. These units represent a donor–acceptor copolymer system, p(DPP-TTF), showing strong absorption in the UV–visible region of the spectrum. An optimized p(DPP-TTF) polymer organic field effect transistor and a single material organic solar cell device showed excellent performance with a hole mobility of up to 5.3 × 10–2 cm2/(V s) and a power conversion efficiency (PCE) of 0.3%, respectively. Bulk heterojunction organic photovoltaic devices of p(DPP-TTF) blended with phenyl-C71-butyric acid methyl ester (PC71BM) exhibited a PCE of 1.8%

SpheroidJ: An Open-Source Set of Tools for Spheroid Segmentation

Background and objectives: Spheroids are the most widely used 3D models for studying the effects of different micro-environmental characteristics on tumour behaviour, and for testing different preclinical and clinical treatments. In order to speed up the study of spheroids, imaging methods that automatically segment and measure spheroids are instrumental; and, several approaches for automatic segmentation of spheroid images exist in the literature. However, those methods fail to generalise to a diversity of experimental conditions. The aim of this work is the development of a set of tools for spheroid segmentation that works in a diversity of settings. Methods: In this work, we have tackled the spheroid segmentation task by first developing a generic segmentation algorithm that can be easily adapted to different scenarios. This generic algorithm has been employed to reduce the burden of annotating a dataset of images that, in turn, has been employed to train several deep learning architectures for semantic segmentation. Both our generic algorithm and the constructed deep learning models have been tested with several datasets of spheroid images where the spheroids were grown under several experimental conditions, and the images acquired using different equipment. Results: The developed generic algorithm can be particularised to different scenarios; however, those particular algorithms fail to generalise to different conditions. By contrast, the best deep learning model, constructed using the HRNet-Seg architecture, generalises properly to a diversity of scenarios. In order to facilitate the dissemination and use of our algorithms and models, we present SpheroidJ, a set of open-source tools for spheroid segmentation. Conclusions: In this work, we have developed an algorithm and trained several models for spheroid segmentation that can be employed with images acquired under different conditions. Thanks to this work, the analysis of spheroids acquired under different conditions will be more reliable and comparable; and, the developed tools will help to advance our understanding of tumour behaviour

IAA : Información y actualidad astronómica (26)

Sumario : Estrellas de neutrones: furioso magnetismo.-- La astronomía en el arte.-- DECONSTRUCCIÓN Y otros ENSAYOS : Lo más frío del Universo.-- CIENCIA: PILARES E INCERTIDUMBRES : Los meteoritos “ordinarios”.-- ACTUALIDAD.-- ENTRE BASTIDORES : Las generaciones perdidas.-- HISTORIAS DE ASTRONOMÍA : El organista que descubrió Urano.-- ACTIVIDADES IAA.Esta revista se publica con la ayuda FCT-08-0130 del Programa Nacional de Fomento de la Cultura Científica y Tecnológica 2008.N

Multi-Response Optimization of WEDM Process Parameters for Machining of Superelastic Nitinol Shape-Memory Alloy Using a Heat-Transfer Search Algorithm

Nitinol, a shape-memory alloy (SMA), is gaining popularity for use in various applications. Machining of these SMAs poses a challenge during conventional machining. Henceforth, in the current study, the wire-electric discharge process has been attempted to machine nickel-titanium (Ni55.8Ti) super-elastic SMA. Furthermore, to render the process viable for industry, a systematic approach comprising response surface methodology (RSM) and a heat-transfer search (HTS) algorithm has been strategized for optimization of process parameters. Pulse-on time, pulse-off time and current were considered as input process parameters, whereas material removal rate (MRR), surface roughness, and micro-hardness were considered as output responses. Residual plots were generated to check the robustness of analysis of variance (ANOVA) results and generated mathematical models. A multi-objective HTS algorithm was executed for generating 2-D and 3-D Pareto optimal points indicating the non-dominant feasible solutions. The proposed combined approach proved to be highly effective in predicting and optimizing the wire electrical discharge machining (WEDM) process parameters. Validation trials were carried out and the error between measured and predicted values was negligible. To ensure the existence of a shape-memory effect even after machining, a differential scanning calorimetry (DSC) test was carried out. The optimized parameters were found to machine the alloy appropriately with the intact shape memory effect