Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa

Recurrence quantification analysis is a widely used method for characterizing patterns in time series. This article presents a comprehensive survey for conducting a wide range of recurrence based analyses to quantify the dynamical structure of single and multivariate time series and capture coupling properties underlying leader-follower relationships. The basics of recurrence quantification analysis (RQA) and all its variants are formally introduced step-by-step from the simplest auto recurrence to the most advanced multivariate case. Importantly, we show how such RQA methods can be deployed under a single computational framework in R using a substantially renewed version of our crqa 2.0 package. This package includes implementations of several recent advances in recurrence based analysis, among them applications to multivariate data and improved entropy calculations for categorical data. We show concrete applications of our package to example data, together with a detailed description of its functions and some guidelines on their usage

Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa

Recurrence quantification analysis is a widely used method for characterizing patterns in time series. This article presents a comprehensive survey for conducting a wide range of recurrence-based analyses to quantify the dynamical structure of single and multivariate time series, and to capture coupling properties underlying leader-follower relationships. The basics of recurrence quantification analysis (RQA) and all its variants are formally introduced step-by-step from the simplest autorecurrence to the most advanced multivariate case. Importantly, we show how such RQA methods can be deployed under a single computational framework in R using a substantially renewed version our crqa 2.0 package. This package includes implementations of several recent advances in recurrence-based analysis, among them applications to multivariate data, and improved entropy calculations for categorical data. We show concrete applications of our package to example data, together with a detailed description of its functions and some guidelines on their usage

Single-Batch Production of Recombinant Human Polyclonal Antibodies

We have previously described the development and implementation of a strategy for production of recombinant polyclonal antibodies (rpAb) in single batches employing CHO cells generated by site-specific integration, the SympressTM I technology. The SympressTM I technology is implemented at industrial scale, supporting a phase II clinical development program. Production of recombinant proteins by site-specific integration, which is based on incorporation of a single copy of the gene of interest, makes the SympressTM I technology best suited to support niche indications. To improve titers while maintaining a cost-efficient, highly reproducible single-batch manufacturing mode, we have evaluated a number of different approaches. The most successful results were obtained using random integration in a new producer cell termed ECHO, a CHO DG44 cell derivative engineered for improved productivity at Symphogen. This new expression process is termed the SympressTM II technology. Here we describe proof-of-principle data demonstrating the feasibility of the SympressTM II technology for single-batch rpAb manufacturing using two model systems each composed of six target-specific antibodies. The compositional stability and the batch-to-batch reproducibility of rpAb produced by the ECHO cells were at least as good as observed previously using site-specific integration technology. Furthermore, the new process had a significant titer increase

The first view of δ Scuti and γ Doradus stars with the TESS mission

We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilize the 2-min cadence TESS data for a sample of 117 stars to classify their behaviour regarding variability and place them in the Hertzsprung-Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74 per cent for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system. Furthermore, our sample contains many high-frequency pulsators, allowing us to probe the frequency variability of hot young δ Scuti stars, which were lacking in the Kepler mission data set, and identify promising targets for future asteroseismic modelling. The TESS data also allow us to refine the stellar parameters of SX Phoenicis, which is believed to be a blue straggler.Fil: Antoci, Victoria. Stellar Astrophysics Centre; DinamarcaFil: Cunha, M. S.. Universidad de Porto; PortugalFil: Bowman, D. M.. Institute of Astronomy; BélgicaFil: Murphy, S. J.. Stellar Astrophysics Centre; Dinamarca. University of Sydney; AustraliaFil: Kurtz, D. W.. University of Central Lancashire; Reino UnidoFil: Bedding, T. R.. Stellar Astrophysics Centre; Dinamarca. University of Sydney; AustraliaFil: Borre, C. C.. Stellar Astrophysics Centre; DinamarcaFil: Christophe, S.. Universite de Paris I Pantheon - Sorbonne; Francia. Centre National de la Recherche Scientifique. Observatoire de Paris; FranciaFil: Daszynska Daszkiewicz, J.. Instytut Astronomiczny; PoloniaFil: Fox Machado, L.. Universidad Nacional Autónoma de México; MéxicoFil: García Hernández, A.. Universidad de Granada; EspañaFil: Ghasemi, Hamed. Institute For Advanced Studies In Basic Sciences; IránFil: Handberg, R.. Stellar Astrophysics Centre; DinamarcaFil: Hansen, Ted H.. Stellar Astrophysics Centre; DinamarcaFil: Hasanzadeh, A.. University Of Zanjan; IránFil: Houdek, G.. Stellar Astrophysics Centre; DinamarcaFil: Johnston, C.. Katholikie Universiteit Leuven; BélgicaFil: Justesen, A. B.. Stellar Astrophysics Centre; DinamarcaFil: Kahraman Alicavus, F.. Nicolaus Copernicus Astronomical Center Of The Polish Academy Of Sciences; PoloniaFil: Kotysz, K.. Instytut Astronomiczny, Uniwersytet Wrocławski; PoloniaFil: Latham, D.. Harvard-Smithsonian Center for Astrophysics; Estados UnidosFil: Matthews, J. M.. University of British Columbia; CanadáFil: Mønster, J.. Stellar Astrophysics Centre; DinamarcaFil: Niemczura, E.. Uniwersytet Wrocławski; PoloniaFil: Paunzen, E.. Masaryk University; República ChecaFil: Sánchez Arias, Julieta Paz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Pigulski, A.. Uniwersytet Wrocławski; PoloniaFil: Pepper, J.. Lehigh University; Estados UnidosFil: Richey Yowell, T.. Lehigh University; Estados UnidosFil: Safari, H.. University of Zanjan; Irá

Biosignals reflect pair-dynamics in collaborative work : EDA and ECG study of pair-programming in a classroom environment

Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.Peer reviewe

The first view of δ Scuti and γ Doradus stars with the TESS mission

Abstract We present the first asteroseismic results for δ Scuti and γ Doradus stars observed in Sectors 1 and 2 of the TESS mission. We utilise the 2-min cadence TESS data for a sample of 117 stars to classify their behaviour regarding variability and place them in the Hertzsprung-Russell diagram using Gaia DR2 data. Included within our sample are the eponymous members of two pulsator classes, γ Doradus and SX Phoenicis. Our sample of pulsating intermediate-mass stars observed by TESS also allows us to confront theoretical models of pulsation driving in the classical instability strip for the first time and show that mixing processes in the outer envelope play an important role. We derive an empirical estimate of 74% for the relative amplitude suppression factor as a result of the redder TESS passband compared to the Kepler mission using a pulsating eclipsing binary system. Furthermore, our sample contains many high-frequency pulsators, allowing us to probe the frequency variability of hot young δ Scuti stars, which were lacking in the Kepler mission data set, and identify promising targets for future asteroseismic modelling. The TESS data also allow us to refine the stellar parameters of SX Phoenicis, which is believed to be a blue straggler

MdRQA

We introduce Multidimensional Recurrence Quantification Analysis (MdRQA) as a tool to analyze multidimensional time-series data. We show how MdRQA can be used to capture the dynamics of high-dimensional signals, and how MdRQA can be used to assess coupling between two or more variables. In particular, we describe applications of the method in research on joint and collective action, as it provides a coherent analysis framework to systematically investigate dynamics at different group levels – from individual dynamics, to dyadic dynamics, up to global group-level of arbitrary size. The appendix contains a software implementation in MATLAB to calculate MdRQA measures