Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain

AbstractThe assumption of subgrid-scale (SGS) horizontal homogeneity within a model grid cell, which forms the basis of SGS turbulence closures used by mesoscale models, becomes increasingly tenuous as grid spacing is reduced to a few kilometers or less, such as in many emerging high-resolution applications. Herein, the turbulence kinetic energy (TKE) budget equation is used to study the spatiotemporal variability in two types of terrain—complex [Columbia Basin Wind Energy Study (CBWES) site, northeastern Oregon] and flat [Scaled Wind Farm Technology (SWiFT) site, west Texas]—using the Weather Research and Forecasting (WRF) Model. In each case, six nested domains [three domains each for mesoscale and large-eddy simulation (LES)] are used to downscale the horizontal grid spacing from ~10 km to ~10 m using the WRF Model framework. The model output was used to calculate the values of the TKE budget terms in vertical and horizontal planes as well as the averages of grid cells contained in the four quadrants o.
LETTER TO THE EDITOR Condence limits for the ratio of two rates based on likelihood scores: non-iterative method

Graham, Mengersen and Morton present a simple closed-form method to calculate condence limits for the ratio of two rates based on Poisson likelihood scores, and demonstrate that this method has excellent coverage properties. The purpose of this letter is to point out that this method (which I shall refer to as the GMM method) is closely analogous to a method I proposed (1) for the ratio of two binomial probabilities, and has certain closely similar properties. The Wilson score interval (2) for the binomial proportion, like the logit Wald or logit scale delta method interval (3; 4), is symmetrical on the logit scale (5). In reference (1), these two intervals are shown to be closely related: their quarter-widths on the logit scale are related by a simple sinh function. This led to the suggestion that the delta method intervals for the ratio of independent binomial proportions and the corresponding odds ratio may be shortened by inverse sinh transformation. In each case the resulting modied interval is symmetrical about the empirical estimate on the log scale. It can be calculated even when one of the cells contains a zero. It then takes a very simple form in which the appropriate centile of the chi-square distribution on one degree of freedom is substituted for the zero. Similarly, with the notation of the above paper, let ˆ � denote the empirical estimate of the
Targeting the Optimal Design in Randomized Clinical Trials with Binary Outcomes and No Covariate: Theoretical Study

This article is devoted to the asymptotic study of adaptive group sequential designs in the case of randomized clinical trials (RCTs) with binary treatment, binary outcome and no covariate. By adaptive design, we mean in this setting a RCT design that allows the investigator to dynamically modify its course through data-driven adjustment of the randomization probability based on data accrued so far, without negatively impacting on the statistical integrity of the trial. By adaptive group sequential design, we refer to the fact that group sequential testing methods can be equally well applied on top of adaptive designs. We obtain that, theoretically, the adaptive design converges almost surely to the targeted unknown randomization scheme. In the estimation framework, we obtain that our maximum likelihood estimator of the parameter of interest is a strongly consistent estimator, and it satisfies a central limit theorem. We can estimate its asymptotic variance, which is the same as that it would feature had we known in advance the targeted randomization scheme and independently sampled from it. Consequently, inference can be carried out as if we had resorted to independent and identically distributed (iid) sampling. In the testing framework, we obtain that the multidimensional t-statistic that we would use under iid sampling still converges to the same canonical distribution under adaptive sampling. Consequently, the same group sequential testing can be carried out as if we had resorted to iid sampling. Furthermore, a comprehensive simulation study that we undertake in a companion article validates the theory. A three-sentence take-home message is “Adaptive designs do learn the targeted optimal design and inference, and testing can be carried out under adaptive sampling as they would under the targeted optimal randomization probability iid sampling. In particular, adaptive designs achieve the same efficiency as the fixed oracle design. This is confirmed by a simulation study, at least for moderate or large sample sizes, across a large collection of targeted randomization probabilities. '”
Mixed Galerkin and Least-Squares formulations for Isogeometric analysis

This work is concerned with the use of isogeometric analysis based on NonUniform Rational B-Splines (NURBS) to develop efficient and robust numerical techniques to deal with the problems of incompressibility in the fields of solid and fluid mechanics. Towards this, two types of formulations, mixed Galerkin and least-squares, are studied. During the first phase of this work, mixed Galerkin formulations, in the context of isogeometric analysis, are presented. Two-field and three-field mixed variational formulations — in both small and large strains — are presented to obtain accurate numerical solutions for the problems modelled with nearly incompressible and elasto-plastic materials. The equivalence of the two mixed formulations, for the considered material models, is derived; and the computational advantages of using two-field formulations are illustrated. Performance of these formulations is assessed by studying several benchmark examples. The ability of the mixed methods, to accurately compute limit loads for problems involving elasto-plastic material models; and to deal with volumetric locking, shear locking and severe mesh distortions in finite strains, is illustrated. Later, finite element formulations are developed by combining least-squares and isogeometric analysis in order to extract the best of both. Least-squares finite element methods (LSFEMs) based on the use of governing differential equations directly — without the need to reduce them to equivalent lower-order systems — are developed for compressible and nearly incompressible elasticity in both the small and finite strain regimes; and incompressible Navier-Stokes. The merits of using Gauss-Newton scheme instead of Newton-Raphson method to solve the underlying nonlinear equations are presented. The performance of the proposed LSFEMs is demonstrated with several benchmark examples from the literature. Advantages of using higher-order NURBS in obtaining optimal convergence rates for non-norm-equivalent LSFEMs; and the robustness of LSFEMs, for Navier-Stokes, in obtaining accurate numerical solutions without the need to incorporate any artificial stabilisation techniques, are demonstrated.
Parsing Early Modern English for Linguistic Search

We investigate the question of whether advances in NLP over the last few years make it possible to vastly increase the size of data usable for research in historical syntax. This brings together many of the usual tools in NLP - word embeddings, tagging, and parsing - in the service of linguistic queries over automatically annotated corpora. We train a part-of-speech (POS) tagger and parser on a corpus of historical English, using ELMo embeddings trained over a billion words of similar text. The evaluation is based on the standard metrics, as well as on the accuracy of the query searches using the parsed data.
How to apply for financial aid: Exploring perplexity and jargon in texts for non-expert audiences

This extended abstract presents a preliminary study of a new dataset from a genre of research that has little prior work in NLP: United States Title IV federal student aid application instructions (in English) gathered from official websites of postsecondary institutions. Financial aid communications for such colleges and universities have been highly criticized for their complexity (Dynarski and Scott-Clayton, 2008; Rosinger, 2019; Feeney and Heroff, 2013). In particular, the context-specific jargon1 is found intimidating for applicants (Ardoin, 2013); this consequently exacerbates issues in post-secondary education accessibility between L1 and L2 speakers of English in the US (Taylor, 2020). The identification and interpretation of genrespecific terminology have been recognized as a crucial step in the understanding of technical texts aimed at expert audiences, including in domains such as biomedical (Lee et al., 2020), engineering (Jin et al., 2018), legal (Moreno-Schneider et al., 2020), and finance (Maarouf et al., 2020). However, there is noticeably less research done on the use of such terminology in texts meant for a broad audience. This data sets includes texts which are a prime example of a genre which needs both precision and a low barrier of entry. The language used in the instructions must be specific and precise enough for consistency because of the direct financial consequences, but the texts clear enough for students to be willing to apply for aid. We introduce 1,014 federal financial aid application instructional texts and identify jargon phrases using a glossary defined by the U.S. Department of Education. We find the text to be jargon-rich, with 40% of sentences including at least one jargon phrase and many sentences with multiple jargon phrases (see Figure 1). We show the results
Enabling continuous blood pressure estimation on artifact contaminated recordings applying a novel pulse wave signal quality detector

The universe of home-monitoring and unobtrusive longtime measurements has experienced a remarkable development in the past years. Smart and cheap recording devices interconnected to body sensor networks have emerged in a great variety, promoting features such as on-line signal processing, low power consumption and high data rates. These hardware systems provide a novel platform for ambitious medical applications, thereby broadening the possibilities of related treatments and diagnostics. One field of operation that significantly profits from this technological process involves multimodal pulse wave analysis, which is exploited in innovative procedures such as continuous blood pressure estimation. These methods can yield invaluable insights into the cardiovascular state, especially in unsupervised settings. On the other hand, ambulatory records incorporating electrocardiography and pulse wave signals have to cope with external influences, including motion artifacts, and pathophysiological incidents, such as ectopic beats. If left unattended, automatic signal processing routines can be severely hampered, resulting in infeasible outputs that impede further evaluations. To tackle those issues in an attempt to support pulse wave analysis procedures in difficult environments, this thesis deals with different aspects of signal quality, ranging from hardware considerations to algorithmic implementations concentrating on the detection and suppression of different kinds of signal distortions. In the scope of the conducted efforts, an improved wireless body sensor network was developed, which features competitive properties including an accurate synchronization mechanism based on Bluetooth, capable and rich frontends equipped with additional acceleration sensors and a well balanced trade-off regarding processing power and overall power consumption. Further, a novel signal quality estimator for photoplethysmographic signals is realized, which outperforms existing methods and is executable on battery driven devices with reduced computational capabilities. Thanks to its convincing detection qualities, pulse wave related recordings were shown to remain applicable in noisy measurement environments, as periods of decreased signal quality are reliably discarded. Especially artifact prone methods such as blood pressure estimation routines profit from the presented achievements, becoming more robust in ambulatory measurement settings again. The proposed signal quality discrimination stage is further complemented by a multimodal ectopic beat detector, which accounts for physiological abnormalites that are known to have a serious impact on pulse wave processing as well. Finally, preliminary results of a novel hand movement recognition and an improved pulse wave artifact suppression approach are presented, providing powerful tools to further increase the robustness of ubiquitous pulse wave monitoring.
Theses and Dissertations 2014 Statistical inference in high dimensional linear and AFT models

A large amount of previous literature proposed and studied variable selection procedures for high dimensional data, and most of the researchers focused on the selection properties as well as the point estimation properties. However, there have been limited studies considering the construction of confidence intervals for the highdimensional variable selection problems. In this thesis, we propose two approaches to address this problem for high-dimensional linear and accelerated failure time models. This work is motivated by recent cancer research, in which researchers would like to analyze the clinical and genomic information simultaneously, so as to find out the potential risk factors for different types of cancers. Moreover, they wish to account for the effect of the clinical information while selecting the potential genes and pathways that are associated with the disease. In order to do so, we consider a model with two sets of dependent variables. One set consists of low-dimensional yet practically more interpretable variables, such as clinical and treatment variables. The other set consists of a large number of variables that can be correlated with the response variable in complicated ways, an example being gene expression levels. Two approaches are established to select crucial variables from the highdimensional variable set and estimate the confidence intervals for the parameters in the low-dimensional set. The first approach is called the partially penalized method. This method first selects variables from the high-dimensional set and then fits a traditional regression model using the selected variables along with the variables in the
An H1-conforming virtual element for Darcy and Brinkman equations

The focus of this paper is on developing a virtual element method (VEM) for Darcy and Brinkman equations. In [L. Beirao da Veiga, C. Lovadina and G. Vacca, ESAIM Math. Model. Numer. Anal. 51 (2017)], we presented a family of virtual elements for Stokes equations and we defined a new virtual element space of velocities such that the associated discrete kernel is pointwise divergence-free. We use a slightly different virtual element space having two fundamental properties: the L2-projection onto ℙk is exactly computable on the basis of the degrees of freedom, and the associated discrete kernel is still pointwise divergence-free. The resulting numerical scheme for the Darcy equation has optimal order of convergence and H1-conforming velocity solution. We can apply the same approach to develop a robust virtual element method for the Brinkman equation that is stable for both the Stokes and Darcy limit case. We provide a rigorous error analysis of the method and several numerical tests.
A Regional Thermohaline Inverse Method for Estimating Circulation and Mixing in the Arctic and Subpolar North Atlantic

A regional thermohaline inverse method (RTHIM) is presented that estimates velocities through the section bounding an enclosed domain and transformation rates resulting from interior mixing within the domain, given inputs of surface boundary fluxes of heat and salt and interior distributions of salinity and temperature. The method works by invoking a volumetric balance in thermohaline coordinates between the transformation resulting from mixing, surface fluxes, and advection, and constraining the mixing to be down tracer gradients. The method is validated using a 20-yr mean of outputs from the NEMO model in an Arctic and subpolar North Atlantic domain, bound to the south by a section with a mean latitude of 66°N. RTHIM solutions agree well with the NEMO model “truth” and are robust to a range of parameters; the meridional overturning circulation (MOC), heat, and freshwater transports calculated from an ensemble of RTHIM solutions are within 12%, 10%, and 19%, respectively, of the NEMO values. There is also bulk agreement between RTHIM solution transformation rates resulting from mixing and those diagnosed from NEMO. Localized differences in diagnosed mixing may be used to guide the development of mixing parameterizations in models such as NEMO, whose downgradient diffusive closures with prescribed diffusivity may be considered oversimplified and too restrictive.
Twitter Corpus of the #BlackLivesMatter Movement And Counter Protests: 2013 to 2020

Black Lives Matter (BLM) is a grassroots movement protesting violence towards Black individuals and communities with a focus on police brutality. The movement has gained significant media and political attention following the killings of Ahmaud Arbery, Breonna Taylor, and George Floyd and the shooting of Jacob Blake in 2020. Due to its decentralized nature, the #BlackLivesMatter social media hashtag has come to both represent the movement and been used as a call to action. Similar hashtags have appeared to counter the BLM movement, such as #AllLivesMatter and #BlueLivesMatter. We introduce a data set of 41.8 million tweets from 10 million users which contain one of the following keywords: BlackLivesMatter, AllLivesMatter and BlueLivesMatter. This data set contains all currently available tweets from the beginning of the BLM movement in 2013 to June 2020. We summarize the data set and show temporal trends in use of both the BlackLivesMatter keyword and keywords associated with counter movements. In the past, similarly themed, though much smaller in scope, BLM data sets have been used for studying discourse in protest and counter protest movements, predicting retweets, examining the role of social media in protest movements and exploring narrative agency. This paper open-sources a large-scale data set to facilitate research in the areas of computational social science, communications, political science, natural language processing, and machine learning.
Automatic Local Remeshing of Unstructured Quadrilateral Meshes in Problems with Large Deformations

Vladimir A. Bychenkov Irina I. KuznetsovaAbstractAutomatic local remeshing is used to maintain meshquality in 2D problems which are modeled on themoving meshes. The mesh is ﬂrst smoothed in localregions selected for remeshing. If smoothing does nothelp improve the mesh, we construct a new one usingthe advancing front method of unstructured quadri-lateral meshing.1 IntroductionWhen problems with large deformations are mod-eled with Lagrangian meshes, quality of cells degradesand may become unacceptable for further calcula-tion. This problem can be resolved by using remesh-ing/rezoning techniques. Triangles can be remeshedusing topological operations such as splitting andelimination of cells and edges and merging of cells.However, for many modeling problems, it is prefer-able to use quadrilaterals. Direct topological opera-tions with quadrilateral elements are not usually suit-able for remeshing (but can be used for adaptive re-ﬂnement). \Topological" remeshing may be based onsplitting quads into triangles; optimization of triangu-lar mesh and further transformation of triangles intoquads. But this approach usually generates mesh withnonuniformly oriented cells and poor topological qual-ity (if it is not the advancing front method based ontriangle transformations). Another technique widelyused for remeshing (especially in 3D) is a grid-basedapproach proposed by Schneiders [1]. This method isrobust but it generates poor quality elements near theboundary and mesh orientation depends on the inte-rior grid only. The grid-based approach is suitable forremeshing of the entire domain but its use for localremeshing tends mesh to be not uniform in topologyand element sizes. Local remeshing is more eﬁectivebecause only small region of domain often needs tobe remeshed. Remeshing of regions with good ele-ments causes diﬁusion of state variables in the pro-cess of rezoning which leads to unjustiﬂed losses inaccuracy. It is especially undesirable in numericalanalysis of shock waves propagation. In this paperwe suggest automatic local remeshing based on the
Changing the internal health and safety organization through organizational learning and change management

Research from several countries indicates that the internal health and safety organization is marginalized in most companies, and it is difficult for the professionals to secure a proper role in health and safety on the companies' present agenda. The goal of a Danish project involving a network of 11 companies was to search for a solution to this problem. The health and safety managers and safety representatives played the role of “change agents” for local projects aiming to develop the health and safety organization. The study showed that 3 of the 11 companies proved to be able to implement successful changes; 5 were partially successful; 3 were nonperformers. The more successful outcomes seem to depend on the abilities of change agents to handle a complex and unpredictable project. Based on these case studies, it has been possible to deduce some strategies change agents must follow to fulfill such a process. Such strategies require the ability to be able to identify opportunities for change, establish a sustainable problem definition, and build coalitions. An amoeba model is suggested as a metaphor for this type of development project. © 2006 Wiley Periodicals, Inc. Hum Factors Man 16: 269–284, 2006.
Textlinguistic Analysis of Events: A Paradox

The aim of this paper is to present and analyze a paradox which arises through the use of complex events as the denotation of causative verbs within texts. According to the majority of event-based theories, complex events consist of at least two parts of the same ontological status, namely events. The paradox appears as soon as a single complex event can be identified with arbitrarily many parts within the text. A way out of the paradoxical situation comes when one recognizes the fact that the verb denotes an event, but that its parts are not of the same status. For this analysis I use the discourse-sensitive strategy of Asher and Lascarides (2003) in order to demonstrate the advantages of using discourse entities implied by a verb, which are available for textual inference.
A Corpus Processing and Analysis Pipeline for Quickref

Quicklisp is a library manager working with your existing Common Lisp implementation to download and install around 2000 libraries, from a central archive. Quickref, an application itself written in Common Lisp, generates, automatically and by introspection, a technical documentation for every library in Quicklisp, and produces a website for this documentation. In this paper, we present a corpus processing and analysis pipeline for Quickref. This pipeline consists of a set of natural language processing blocks allowing us to analyze Quicklisp libraries, based on natural language contents sources such as README files, docstrings, or symbol names. The ultimate purpose of this pipeline is the generation of a keyword index for Quickref, although other applications such as word clouds or topic analysis are also envisioned.