Miracle-dz/UniFAR-FTUs huggingface dataset:
E-Cigarette Use among Sexual Minoritized Women and Nonbinary People Assigned Female at Birth: Assessing the Roles of Discrimination, Perceived Stress, and Social Support

Abstract Background: Young adult sexual minoritized women (SMW) are at disproportionate risk for e-cigarette use, which may in part be due to excess minority stress imposed by discrimination exposure. While discrimination exposure is associated with risk for combustible tobacco/nicotine use among SMW, similar associations have yet to be tested with e-cigarettes. Moreover, it is unknown if discrimination-related risk may be mitigated by protective factors such as social support. This study examined concurrent associations of discrimination, perceived stress, and social support with past 30-day e-cigarette use in a sample of young adult SMW during the COVID-19 pandemic. Methods: N = 501 SMW and nonbinary people assigned female at birth (AFAB) aged 18–30 completed an online survey. A series of logistic regressions examined associations of discrimination, perceived stress, and four forms of social support received during the COVID-19 pandemic with past-30-day e-cigarette use. Results: Among SMW, greater perceived stress (OR = 1.10, p = .03), but not discrimination exposure, was associated with e-cigarette use. Associations of discrimination with e-cigarette use were nonsignificant when most forms of social support (emotional, material/financial, and virtual) were accounted for. Associations of perceived stress with e-cigarette use were strongest among those who needed but did not receive material support. Conclusions: Perceived stress, but not discrimination exposure, was associated with risk for e-cigarette use among young SMW during the COVID-19 pandemic. Effects of nonspecific stress may be compounded by insufficient material/financial support.
Effective plasmonic spectroscopic amplifiers for hyper-Raman scattering process

In an asymmetric Au cubic trimer, influence of the rotation angle (θ) and side length (w) on both plasmonic coupling features and corresponding enhancement factor of hyper-Raman scattering (HRS) process have been investigated comprehensively under the illumination of a longitudinally polarized light. The finite-difference time-domain (FDTD) electrodynamic simulation tool has been employed to calculate the optical cross-section and associated nearfield intensity of the irradiated coupled resonators. As θ increases, the polarization state that dominates the coupling phenomenon is gradually switched from facing sides into facing edges which results in (1) a dramatic change in the spectral response of the trimer and (2) a significant improvement in the nearfield intensity that is directly related to the improvement of HRS signal. Breaking size symmetry of the cubic trimer provides a novel approach to reach the desired spectral response that permits such trimer to be used as an active substrate for HRS procedures. After optimizing both the orientation angle and size of the interacting plasmonic characters forming of the trimer, the enhancement factor of HRS process can reach a value never reported before as high as 1 × 1021.
Finite Element Methods with Local Projection Stabilization for Thermally Coupled Incompressible Flow

This thesis considers conforming finite element discretizations for the time-dependent Oberbeck-Boussinesq model with a pressure-correction projection scheme of second order in time. Discrete inf-sup stability of the ansatz spaces for velocity and pressure is assumed. For handling poor mass conservation, a stabilization of the incompressibility constraint, the so called grad-div stabilization, is considered. Furthermore, a local projection stabilization method in streamline direction (LPS SU) is applied for velocity and temperature for dealing with dominating convection. Numerical analysis is performed both with respect to the semi-discretization in space and for the fully discretized model: Stability and convergence results are given and a suitable design of stabilization parameters is proposed. Here, grad-div stabilization proves to be essential for robustness of this approach. These findings are validated by various numerical experiments. Analytical examples are considered to verify convergence rates in space and time. In addition, more realistic isothermal and non-isothermal flow examples are investigated and a suitable parameter choice within the bounds of the theoretical results is obtained experimentally.
A Micro-Cell Size Dependent Damage Law of Concrete

A micro-cell size dependent damage law is proposed by the multi-scale damage representation to remedy the mesh sensitivities involving in the numerical simulations. The homogenization based multi-scale damage representation is firstly introduced in obtaining the macro-damage evolution from micro-cell analysis. Then, the micro-cells with different sizes are generated and the corresponding simulations are given. Based on the simulation results, we define the micro-cell size dependent damage law. Finally, the accuracy and efficiency of the proposed damage law are verified by the notched beam simulation results.
Hydrodynamic instabilities of a dual-mode air–SF6 interface induced by a cylindrically convergent shock

Abstract Shock-tube experiments are performed on the convergent Richtmyer–Meshkov (RM) instability of a multimode interface. The temporal growth of each Fourier mode perturbation is measured. The hydrodynamic instabilities, including the RM instability and the additional Rayleigh–Taylor (RT) effect, imposed by the convergent shock wave on the dual-mode interface, are investigated. The mode-coupling effect on the convergent RM instability coupled with the RT effect is quantified. It is evident that the amplitude growths of all first-order modes and second-order harmonics and their couplings depend on the variance of the interface radius, and are influenced by the mode-coupling from the very beginning. It is confirmed that the mode-coupling mechanism is closely related to the initial spectrum, including azimuthal wavenumbers, relative phases and initial amplitudes of the constituent modes. Different from the conclusion in previous studies on the convergent single-mode RM instability that the additional RT effect always suppresses the perturbation growth, the mode-coupling might result in the additional RT effect promoting the instability of the constituent Fourier mode. By considering the geometry convergence, the mode-coupling effect and other physical mechanisms, second-order nonlinear solutions are established to predict the RM instability and the additional RT effect in the cylindrical geometry, reasonably quantifying the amplitude growths of each mode, harmonic and coupling. The nonlinear solutions are further validated by simulations considering various initial spectra. Last, the temporal evolutions of the mixed mass and normalized mixed mass of a shocked multimode interface are calculated numerically to quantify the mixing of two fluids in the cylindrical geometry.
Generation of Replacement Options in Text Sanitization

The purpose of text sanitization is to edit text documents to mask text spans that may directly or indirectly reveal personal information. An important problem in text sanitization is to find less specific, yet still informative replacements for each text span to mask. We present an approach to generate possible replacements using a combination of heuristic rules and an ontology derived from Wikidata. Those replacement options are hierarchically structured and cover various types of personal identifiers. Using this approach, we extend a recently released text sanitization dataset with manually selected replacements. The outcome of this data collection shows that the approach is able to suggest appropriate replacement options for most text spans.
GiellaLT — a stable infrastructure for Nordic minority languages and beyond

Long term language technology infrastructures are critical for continued maintenance of language technology based software that is used to support the use of languages in digital world. In Nordic area we have languages ranging from well-resourced national majority languages like Norwegian, Swedish and Finnish as well as minoritised, unresourced and indigenous languages like Sámi languages. We present an infrastructure that has been build in over 20 years time that supports building language technology and tools for most of the Nordic languages as well as many of the languages all over the world, with focus on Sámi and other indigenous, minoritised and unresourced languages. We show that one common infrastructure can be used to build tools from keyboards and spell-checkers to machine translators, grammar checkers and text-to-speech as well as automatic speech recognition.
MeDa-BERT: A medical Danish pretrained transformer model

This paper introduces a medical Danish BERT-based language model (MeDa-BERT) and medical Danish word embeddings. The word embeddings and MeDa-BERT were pretrained on a new medical Danish corpus consisting of 133M tokens from medical Danish books and text from the internet. The models showed improved performance over general-domain models on medical Danish classification tasks. The medical word embeddings and MeDa-BERT are publicly available.
Machine Translation for Low-resource Finno-Ugric Languages

This paper focuses on neural machine translation (NMT) for low-resource Finno-Ugric languages. Our contributions are three-fold: (1) we extend existing and collect new parallel and monolingual corpora for 20 languages, (2) we expand the 200-language translation benchmark FLORES-200 with manual translations into nine new languages, and (3) we present experiments using the collected data to create NMT systems for the included languages and investigate the impact of back-translation data on the NMT performance for low-resource languages. Experimental results show that carefully selected limited amounts of back-translation directions yield the best results in terms of translation scores, for both high-resource and low-resource output languages.
Parser Evaluation for Analyzing Swedish 19th-20th Century Literature

In this study, we aim to find a parser for accurately identifying different types of subordinate clauses, and related phenomena, in 19th–20th-century Swedish literature. Since no test set is available for parsing from this time period, we propose a lightweight annotation scheme for annotating a single relation of interest per sentence. We train a variety of parsers for Swedish and compare evaluations on standard modern test sets and our targeted test set. We find clear trends in which parser types perform best on the standard test sets, but that performance is considerably more varied on the targeted test set. We believe that our proposed annotation scheme can be useful for complementing standard evaluations, with a low annotation effort.
Predicting the presence of inline citations in academic text using binary classification

Properly citing sources is a crucial component of any good-quality academic paper. The goal of this study was to determine what kind of accuracy we could reach in predicting whether or not a sentence should contain an inline citation using a simple binary classification model. To that end, we fine-tuned SciBERT on both an imbalanced and a balanced dataset containing sentences with and without inline citations. We achieved an overall accuracy of over 0.92, suggesting that language patterns alone could be used to predict where inline citations should appear with some degree of accuracy.
Borrowing Information Across Genes and Experiments for Improved Error Variance Estimation in Microarray Data Analysis

Statistical inference for microarray experiments usually involves the estimation of error variance for each gene. Because the sample size available for each gene is often low, the usual unbiased estimator of the error variance can be unreliable. Shrinkage methods, including empirical Bayes approaches that borrow information across genes to produce more stable estimates, have been developed in recent years. Because the same microarray platform is often used for at least several experiments to study similar biological systems, there is an opportunity to improve variance estimation further by borrowing information not only across genes but also across experiments. We propose a lognormal model for error variances that involves random gene effects and random experiment effects. Based on the model, we develop an empirical Bayes estimator of the error variance for each combination of gene and experiment and call this estimator BAGE because information is Borrowed Across Genes and Experiments. A permutation strategy is used to make inference about the differential expression status of each gene. Simulation studies with data generated from different probability models and real microarray data show that our method outperforms existing approaches.
Les algorithmes génétiques

Genetic algorithms are considered as a heuristic method for optimisation problems with (very) large solution spaces. They are characterized by working directly on the values of the function to be optimized. They do not require any other auxiliary information. They proceed by a blind search in the space of potential solutions. Genetic algorithms use the metaphor of the natural selection mechanism of the species evolution theory. The general behaviour of a simple genetic algorithm is to consider an initial population which is a random subset of the space of potential solutions. It evaluates this population relatively to an objective function. The best individuals of the population are then selected to be reproduced with greater number of copies in the next generation. The reproduced individuals are then combined to produce better individuals. In this article we give a general description of a simple genetic algorithm and describe its behaviour on a small example. We then describe the use of genetic algorithms in automated learning systems where they are used to select and discover a set of production rules, describing a more adapted behaviour to solve the problem at hand.
A Simple Jerk System with Piecewise Exponential Nonlinearity

Third-order explicit autonomous differential equations in one scalar variable, sometimes called jerky dynamics, constitute an interesting subclass of dynamical systems that can exhibit chaotic behavior. In this paper, we investigated a simple jerk system with a piecewise exponential nonlinearity by numerical examination as well as dynamic simulation. Using the largest Lyapunov exponent as the signature of chaos, the region of parameter space exhibiting chaos is identified. The results show that this system has a perioddoubling route to chaos and a narrow chaotic region in parameter space. The rescaled system is approximately described by a one-dimensional quadratic map. The parameters are fitted to a simple function to predict the values for which chaos occurs in the case of high nonlinearity where the region in parameter space that admits chaos is relatively small.
Putting Ducks in a Row: Methods for Empirical Alignment of Performance Standards

There is much focus at the state and national levels in graduating students that are prepared for college and careers. In order for students to be prepared at the end of their K-12 education, indicators are also needed along the way about whether students are on track. Using historical state data, nine different methods were used to align performance standards in mathematics grades 3-8 (i.e., OLS regression – forward, OLS regression – backward, logistic regression, quantile regression with 40, 50, and 60 percentile growth, equal percent impact data, vertical scale – equal intervals, and vertical scale – based on changes in test difficulty). The methods were evaluated for classification or prediction accuracy, number of correct classifications, pass rates, and types of errors. The effect of selecting different methods on standards alignment are discussed as well as potential implications for interpretations of student progress and school success.
The Number of Graphs with a given Automorphism Group

In this paper, the graphs under consideration may have multiple edges but they do not have loops. We enumerate the number N[H: n, p] of topologically distinct graphs with n vertices and p edges whose automorphism group is the permutation group H. As in (5), this enumeration is considered in the context of the theory of permutation representations of finite groups. We begin with some definitions and notation.
Ordering Trees Having Small General Sum-Connectivity Index 1

The general sum-connectivity index of a graph G is defined as χα(G )= � uv∈E(G) (d(u)+d(v)) α , where d(u) denotes the degree of vertex u in G ,a ndα is a real number. The aim of this paper is twofold. We determine the minimum value of the general sum-connectivity index: (i) for trees of order n ≥ 3 and diameter d ,2 ≤ d ≤ n − 1 and of trees of order n ≥ 5 having p pendant vertices, 3 ≤ p ≤ n − 2 and the corresponding extremal trees for −1 ≤ α< 0a nd (ii) for connected multigraphs of order n ≥ 3 and size m, m ≥ n − 1 and the corresponding extremal multigraphs for −3 ≤ α< 0. Further, for n sufficiently large and −1 ≤ α< 0, we characterize five n-vertex trees having smallest values of χα.
Diffusion kinetics and boronizing of high entropy alloy produced by TIG melting reverse suction method

ABSTRACT In this study, CrMnFeCoNi high entropy alloy was produced using TIG melting reverse vacuum method using a shielding gas atmosphere. Produced samples were boronized with pack boriding method at 1173, 1223, 1273 K temperatures and for 2, 4 and 6 h. As a result of the experiments, the morphology of the boride layers formed on the high entropy alloy surfaces was investigated by SEM microscope. The hardness values were measured with a microhardness device and the phases formed on the boride layer were determined by the XRD method. In addition, the thickness and growth kinetics of the boride layer on the high entropy alloy were investigated. The boride coating thickness ranges from 38 µm to 268 µm. FCC crystal structure is present in the HEAs produced in XRD examinations and the hardness value was determined as 242 HV0,05 (± 15). B-dependent phases of Cr, Mn, Fe, Co, Ni were obtained in the coating layer and the hardness value was measured as 2250 HV0,05 maximum. The boride layer activation energy value of the coated HEA was calculated as 376,465 kJ/mol.
To tell or not to tell – disclosure of autism in the workplace

Autism, sometimes called an ‘invisible disability’, can lead to different difficulties for young adults entering the workplace as well as maintaining the job. One of the questions young adults with autism face: should he/she/they disclose the information about their autism to the employer? This current study aims to fill a gap in research on the young adult population with autism in the workplace, particularly within the Latvian context. Four young adults (aged 18–26) living and working in Latvia, who have identified themselves as having autism, job seekers and employees with strong language and intellectual abilities, and their mothers participated in this study. Qualitative semi-structured interviews were conducted to gather in-depth data from participants; after that, an inductive content analysis was made. The results reveal that young adults do not disclose that they have autism to neither co-workers nor employers, yet at the same time, they are ready to disclose it to close friends outside of the workplace. Four main reasons for not disclosing their status on the autism spectrum emerged. To begin with, young adults did not want to be treated differently; they wanted to be perceived as ‘normal’. Second, they feared social stigma. Third, they did not feel there could be any benefits by disclosing their autism to their employer. Finally, it is much more important to explain to their employer what the often-unique limitations of each specific young person with autism are and how to overcome them than to just inform only of their autistic status.
A Multi-Objective Evolutionary Approach to Discover Explainability Trade-Offs when Using Linear Regression to Effectively Model the Dynamic Thermal Behaviour of Electrical Machines

Modelling and controlling heat transfer in rotating electrical machines is very important as it enables the design of assemblies (e.g., motors) that are efficient and durable under multiple operational scenarios. To address the challenge of deriving accurate data-driven estimators of key motor temperatures, we propose a multi-objective strategy for creating Linear Regression (LR) models that integrate optimised synthetic features. The main strength of our approach is that it provides decision makers with a clear overview of the optimal trade-offs between data collection costs, the expected modelling errors and the overall explainability of the generated thermal models. Moreover, as parsimonious models are required for both microcontroller deployment and domain expert interpretation, our modelling strategy contains a simple but effective step-wise regularisation technique that can be applied to outline domain-relevant mappings between LR variables and thermal profiling capabilities. Results indicate that our approach can generate accurate LR-based dynamic thermal models when training on data associated with a limited set of load points within the safe operating area of the electrical machine under study.