Miracle-dz/UniFAR-FTUs huggingface dataset:
A test of local adaptation to drought in germination and seedling traits in populations of two alpine forbs across a 2000 mm/year precipitation gradient

Abstract Seed regeneration is a critical stage in the life histories of plants, affecting species' abilities to maintain local populations, evolve, and disperse to new sites. In this study, we test for local adaptations to drought in germination and seedling growth of two alpine forbs with contrasting habitat preferences: the alpine generalist Veronica alpina and the snowbed specialist Sibbaldia procumbens. We sampled seeds of each species from four populations spanning a precipitation gradient from 1200 to 3400 mm/year in western Norway. In a growth chamber experiment, we germinated seeds from each population at 10 different water potentials under controlled light and temperature conditions. Drought led to lower germination percentage in both species, and additionally, slower germination, and more investment in roots for V. alpina. These responses varied along the precipitation gradient. Seeds from the driest populations had higher germination percentage, shorter time to germination, and higher investments in the roots under drought conditions than the seeds from the wettest populations – suggesting local adaption to drought. The snowbed specialist, S. procumbens, had lower germination percentages under drought, but otherwise did not respond to drought in ways that indicate physiological or morphological adaptions to drought. S. procumbens germination also did not vary systematically with precipitation of the source site, but heavier‐seeded populations germinated to higher rates and tolerated drought better. Our study is the first to test drought effects on seed regeneration in alpine plants populations from high‐precipitation regions. We found evidence that germination and seedling traits may show adaptation to drought even in populations from wet habitats. Our results also indicate that alpine generalists might be more adapted to drought and show more local adaptations in drought responses than snowbed specialists.
Enhancing study recruitment through implementation of an opt-out, cold contact process with consideration for autonomy, beneficence and justice

Abstract The potential utilization of a cold-contact approach to research recruitment, where members of the research team are unknown to the patient, has grown with the expanded use of electronic health records (EHRs) and affiliated patient portals. Institutions that permit this strategy vary in their implementation and management of it but tend to lean towards more conservative approaches. This process paper describes the Medical University of South Carolina’s transition to an opt-out model of “cold-contact” recruitment (known as patient outreach recruitment or POR), wherein patients can be contacted so long as they do not express an unwillingness to receive such communication. The work highlights the benefits of this model by explaining how it, in many ways, supports and protects autonomy, beneficence, and justice for patients. The paper then describes the process of standing up the recruitment strategy, communicating the change to patients and the community, and documenting study team contact and patient research preference. Data supporting increased access to potentially eligible patients of greater diversity as well as initial researcher feedback on perceived success of POR is also shared. The paper ends with a discussion of next steps to enhance the POR process via more detailed data collection and reengagement with community stakeholders.
Foreign Language Speaking Anxiety among Chinese English Majors: Causes, Effects and Strategies

Language anxiety is becoming an important issue of research in our profession, especially speaking anxiety. The study aims to explore the affective factors, effects and coping strategies of speaking anxiety among Chinese English majors. A mixed approach was used: survey, and interview. In total, 123 English majors answered the Foreign Language Classroom Anxiety Scale (FLCAS), other basic questionnaires, they participated oral English test hold by school teachers. Two teachers and three students with varying degrees of anxiety were interviewed. The results were: (1) According to the survey, half of the students have oral anxiety, though most of them are moderately nervous; (2)Speaking anxiety negatively impacted how well students’ oral performance, which was further confirmed by the statistical analysis; (3) A variety of factors was revealed to cause the students’ speaking anxiety; (4) When faced with speaking anxiety, there are some effective solutions from the perspective of both students and teachers. This paper contributes to making teachers realize the existence of oral anxiety in students English learning, its impact on English learning, and to better adjusting teaching strategies.
Investigating Epidemiologic and Molecular Links Between Patients With Community- and Hospital-Acquired Influenza A: 2017–2018 and 2019–2020, Michigan

Abstract Background Hospital-acquired influenza virus infection (HAII) can cause severe morbidity and mortality. Identifying potential transmission routes can inform prevention strategies. Methods We identified all hospitalized patients testing positive for influenza A virus at a large, tertiary care hospital during the 2017–2018 and 2019–2020 influenza seasons. Hospital admission dates, locations of inpatient service, and clinical influenza testing information were retrieved from the electronic medical record. Time-location groups of epidemiologically linked influenza patients were defined and contained ≥1 presumed HAII case (first positive ≥48 hours after admission). Genetic relatedness within time-location groups was assessed by whole genome sequencing. Results During the 2017–2018 season, 230 patients tested positive for influenza A(H3N2) or unsubtyped influenza A including 26 HAIIs. There were 159 influenza A(H1N1)pdm09 or unsubtyped influenza A–positive patients identified during the 2019–2020 season including 33 HAIIs. Consensus sequences were obtained for 177 (77%) and 57 (36%) of influenza A cases in 2017–2018 and 2019–2020, respectively. Among all influenza A cases, there were 10 time-location groups identified in 2017–2018 and 13 in 2019–2020; 19 of 23 groups included ≤4 patients. In 2017–2018, 6 of 10 groups had ≥2 patients with sequence data, including ≥1 HAII case. Two of 13 groups met this criteria in 2019–2020. Two time-location groups from 2017–2018 each contained 3 genetically linked cases. Conclusions Our results suggest that HAIIs arise from outbreak transmission from nosocomial sources as well as single infections from unique community introductions.
Convergence analysis of the extended Kalman filter as an observer for nonlinear discrete-time systems

In the current paper, a modified version of the extended Kalman filter (EKF), when used as an observer for nonlinear discrete-time systems, is presented. The approach proposed consists in introducing time varying matrices to enhance convergence and stability of the obtained estimator. Based on a new formulation of the first order linearization technique, sufficient conditions to ensure local asymptotic convergence are established. Efficiency of this approach, compared to the classical version of the EKF, is shown through a nonlinear identification problem.
Manifold Recognition Based on Discriminative-Analysis of Canonical Correlations

Nowadays, the idea of recognition based on image sets looms so large in real world applications. From the view of manifold learning, each image set has commonly been regarded as a manifold, and we formulate the problem of set recognition as manifold recognition (MR). Since it is impossible to directly compute the distance between nonlinear manifolds, constructing local linear subspaces is brought into our focus. Among methods offering of subspace matching, canonical correlations have recently drawn intensive attention. For the task of MR, we propose a method of Manifold Recognition Based On Discriminative-analysis of Canonical Correlations (MRDCC). The proposed method is evaluated on two datasets: Honda/UCSD face video database and ETH-80 object database. Comprehensive comparisons and results demonstrate the effectiveness of our method.
Current distributions and AC transport losses for simple parallel conductor composed of Ag-sheathed (Bi, Pb)-2223 multifilamentary tapes

Alternating-current (AC) transport losses in self-fields at 77 K have been investigated for simple parallel conductors composed of several pieces of Ag-sheathed (Bi, Pb)-2223 multifilamentary tapes with different filament arrangements. The loss values of the conductors depend on the filament arrangement in the tape strand and the arrangement of tape strands in conductors, although the main contribution to the losses comes from the hysteresis loss in the superconductor. The conductors composed of tape strands with sectioned filament arrangements have lower losses than those without sectioned filament arrangements, because the field-free core in the former is sectioned into some parts in the filament group. Improvement for the tape arrangement in the conductor, together with a functional design for the filament arrangement in tape strands, is important to suppress the loss generation in cable conductors under AC current transmission.
Control of the FWER in Multiple Testing Under Dependence

Multiple testing issues have long been considered almost exclusively in the context of General Linear Model, in which usually the significance of a quite limited number of contrasts is tested simultaneously. Most of the procedures used in this context have been designed to control the so-called Family-Wise Error Rate (FWER), defined as the probability of more than one erroneous rejection of a null hypothesis. In the last two decades, large-scale significance tests encountered for example in microarray data analysis have renewed the methodology on multiple testing by introducing novel definitions of Type-I error rates, such as the False Discovery Rate (FDR), to define less conservative procedures. High dimension has also highlighted the need for improvements, to guarantee the control of the error rates in various situations of dependent data. The present article gives motivations for a factor analysis modeling of the covariance between test statistics, both in the situation of simultaneous tests of a small set of contrasts in the General Linear Model and also in high-dimensional significance tests. Impact of the dependence on the power of multiple testing is first discussed and a new procedure controlling the FWER and based on factor-adjusted test statistics is presented as a solution to improve the Type-II error rate with respect to existing methods. Finally, the beneficial impact of the new method is shown on simulated datasets.
Optimal design for the proportional odds model

The authors construct locally optimal designs for the proportional odds model for ordinal data. While they investigate the standard D‐optimal design, they also investigate optimality criteria for the simultaneous estimation of multiple quantiles, namely DA ‐optimality and the omnibus criterion. The design of experiments for the simultaneous estimation of multiple quantiles is important in both toxic and effective dose studies in medicine. As with c‐optimality in the binary response problem, the authors find that there are distinct phase changes when exploring extreme quantiles that require additional design points. The authors also investigate relative efficiencies of the criteria.
Fringing field effects on electrical resistivity of semiconductor nanowire-metal contacts

Metal contacts play an important role in nanowire devices and are expected to exhibit qualitatively different properties from those of planar contacts due to small contact cross sections. We numerically investigate certain unique properties of nanowire-metal contacts and demonstrate that contact resistivity increases as nanowire radius shrinks. This increase is more significant for nanowire-three-dimensional metal contacts than for nanowire-one-dimensional metal contacts. The underlying cause for this size effect is identified as the strong fringing field effects, which become more significant as temperature decreases. Our simulation provides a more complete understanding of the size effects on nanowire-metal contacts.
Detection of Oceanic Quasi-Zonal Jets from Altimetry Observations

AbstractRecent analyses of observations and ocean model outputs have revealed coherent low-frequency quasi-zonal jets in observed sea surface height (SSH) anomaly and model velocity fields. The jets were latent, that is, they were not detectable by eye, but revealed and selected by time-averaging procedures. Time-averaging procedures, when applied to fields that contain propagating features (eddies and waves), can create jetlike structures of nonphysical nature (artifacts). This paper suggests the application of three criteria to distinguish real jets from these artifacts, and demonstrates that quasi-zonal jets extracted from satellite altimetry observations off California were not artifacts. First, quasi-zonal jets off California were stronger than artifacts: the observed SSH for the jets reached 4–5 cm, which is considerably larger than SSH artifacts, which did not exceed 0.9–1.2 cm. Second, axes of the observed jets were not always oriented along the paths of propagating mesoscale features (waves and e.
Euclidean Shortest Paths in Simple Polygons

Let p and q be two points in a simple polygon Π. This chapter provides two rubberband algorithms for computing a shortest path between p and q that is contained in Π. The two algorithms are based on previously known results on triangular or trapezoidal decompositions of simple polygons, and have either κ(e)· O(n) or κ(e) · O(n log n) time complexity, where κ(e) = (L0 − L)/e, for the true length L of the shortest path and length L0 of a used initial polygonal path. Rubberband algorithms follow a straightforward design strategy, and the proposed algorithms are easy to implement (after having the decompositions at hand).
The carbon abundance in the Magellanic Clouds from IUE observations of H II regions

Observations of C II), C III), and C IV lines in the ultraviolet spectra of three H II regions in the Small Magellanic Cloud (SMC) and of four H II regions in the Large Magellanic Cloud (LMC) were obtained with the International Ultraviolet Explorer satellite and used to derive the carbon abundance in the Megellanic Clouds by nebular model analyses. Based on absolute emission line fluxes between the IUE and ground-based observations for the individual H II regions, it is found that 12+log C/H = 7.16 +- 0.04 for the SMC and 7.90 +- 0.15 for the LMC (where the errors quoted are statistical; systematic errors due to aperture geometry and positioning differences between the IUE and ground-based observations may be several times larger). The corresponding values for the average C/O ratios are log C/O = -0.89 +- 0.02 for the SMC and -0.48 +- 0.04 for the LMC (statistical errors). For one SMC H II region, N81, the O III) lambda1663 lines were observed in the IUE spectra and permitted direct calculation of the C/O ratio independent of absolute fluxes. The result (log C/O = -0.94) is in excellent agreement with ratio based on absolute fluxes.
Dynamics of Correlated Double-Ionization of Two-Electron Quantum Dots in Laser Fields

Using an ab initio, time-dependent calculational method, we study the non-linear dynamics of a two-electron quantum dot in the presence of ultrashort Thz laser pulses. The analysis of the contribution of the various partial waves to two-electron joint radial and energy distribution patterns revealed strongly correlated electron ejection channels. In the double-ionization process, regardless of the photon energy, the two-electron wave packets are born and remain concentrated until the pulse’s peak; at later times, and depending on the photon energy of the field, distinctly different patterns emerge. Our calculations also showed the gradual transition of the radial and energy patterns from a single-peak to a doubly peaked structure, associated with the direct and the sequential double-ionization mechanisms, respectively.
The role of respiratory flow asynchrony on convective mixing in the pulmonary acinus

Fine aerosol transport in the alveolated regions of the lungs is intrinsically coupled to alveolar flow patterns driven by lung breathing motions. Hence, understanding acinar flow characteristics is critical in determining local aerosol deposition sites. To date, inhaled aerosol dynamics have been mainly investigated using self-similar expanding lung models, although it is known that anisotropic lung motions exist and thus, potentially alter flow characteristics and enhance convective mixing. Using both experimental and numerical approaches, we assess here the influence of respiratory flow asynchrony on convective mixing by investigating alveolar flow patterns and massless particle transport for increasing phase lags between local wall motion and acinar ductal flows. Experimental results using a microfluidic platform, as well as numerical simulations, suggest that alveolar flow patterns are time-dependent in contrast to quasi-steady phenomena that pertain under synchronous conditions. To capture statistics of convective mixing, we numerically track massless tracers over multiple breathing cycles using anatomically inspired models of alveolated airways. By systemically probing various degrees of phase lag, our results underline the strong correlation between the magnitude of particle dispersion and flow asynchrony. In particular, we find that the dispersion of massless particles in acinar ducts is dramatically increased under flow asynchrony, relative to local, isolated alveolar cavity mixing. Despite the simplicity of the present models, our work highlights the critical role of respiratory flow asynchrony in governing the fate of fine inhaled particles in the pulmonary acinus.
Balancing the scales: archaeological approaches to social inequality

ABSTRACT Archaeology lends a critical perspective to research on social inequality due to the field’s unique access to deep history, emphasis on materiality, and explicit incorporation of multiple lines of evidence. This paper offers a concise overview of archaeological approaches aimed at students and scholars in other fields. We develop a categorization of disciplinary strategies, arguing that archaeologists address institutionalized inequality through examining inequalities in the accumulation of goods or resources (economic differentiation); access to resources or knowledge (social differentiation), and inequalities in action, the ability to make decisions for oneself or others (political differentiation). We illustrate these categories with reference to the distinctions between material, relational, and embodied wealth. We draw upon a broad range of geographic, chronological, and cultural case studies to illustrate the flexibility and utility of archaeological methods for answering questions about inequality in human societies.
A NLP-learning Powered Customizable Approach Towards Auto-blocking Distracting Websites

Over the past few decades, the problem of distraction and its accompanying side effects has taken its root deeply in all parts of our daily life and extended its ever-increasing influences among young generations [2]. In addition to its alarming prevalence, another characteristic of distraction that raises most concerns is how easily we can get distracted from our tasks at hand while using the electronic devices as a means of solving problems [3]. This paper attempts to address this society-wide problem thoroughly and universally through a technical approach of detecting, analyzing, and blocking the websites intelligently. Our design highlights the applications of machine learning and natural language processing, and is implemented purely in Python, Javascript, and several other web development languages. After retrieving the web content from the target websites through the web scraping process, summarizing the data to a number of short paragraphs via the use of NLP, we were able to perform data analysis on the result and finally block the websites accordingly [4]. With the help of this extension, students and those who wish to improve their concentration in work will be able to put more focus on the tasks at hand and thus boost their work efficiency under any working conditions.
TIME RESPONSE ANALYSIS OF A PYROELECTRIC DETECTOR

Abstract The pyroelectric time response of a pyroelectric detector is calculated as a function of film thickness, the volume specific heat and thermal conductivity. It is found that the thinner the pyroelectric layer is, the faster the time response is and the larger the response amplitude is, and that the thinner the absorbing layer is, the faster the time response is and the larger the response amplitude; however, the effect of the absorbing layer thickness is lower than that of the pyroelectric layer thickness. Though the thinner the pyroelectric layer is, the better the pyroelectric response is, in reality, the tunneling current (i.e., leakage current) increases with decreasing the pyroelectric layer thickness and this is forbidden in some applications. In this paper, we propose two models to analyze the thermal conduction. The fit is, quite well compared with the experimental result.
Multimodal Sensing and Computational Intelligence for Situation Awareness Classification in Autonomous Driving

Maintaining situation awareness (SA) is essential for drivers to deal with the situations that Society of Automotive Engineers (SAE) Level 3 automated vehicle systems are not designed to handle. Although advanced physiological sensors can enable continuous SA assessments, previous single-modality approaches may not be sufficient to capture SA. To address this limitation, the current study demonstrates a multimodal sensing approach for objective SA monitoring. Physiological sensor data from electroencephalogram and eye-tracking were recorded for 30 participants as they performed three secondary tasks during automated driving scenarios that consisted of a pre-takeover (pre-TOR) request segment and a post-TOR segment. The tasks varied in terms of how visual attention was allocated in the pre-TOR segment. In the post-TOR segment, drivers were expected to gather information from the driving environment in preparation for a vehicle-to-driver transition. Participants' ground-truth SA level was measured using the Situation Awareness Global Assessment Techniques (SAGAT) after the post-TOR segment. A total of 23 physiological features were extracted from the post-TOR segment to train computational intelligence models. Results compared the performance of five different classifiers, the ground-truth labeling strategies, and the features included in the model. Overall, the proposed neural network model outperformed other machine learning models and achieved the best classification accuracy (90.6%). A model with 11 features was optimal. In addition, the multi-physiological sensor-model outperformed the single sensing model by comparing prediction performance. Our results suggest that multimodal sensing model can objectively predict SA. The results of this study provide new insight into how physiological features contribute to the SA assessment.