Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise

Abstract While there are a plethora of algorithms for detecting changes in mean in univariate time-series, almost all struggle in real applications where there is autocorrelated noise or where the mean fluctuates locally between the abrupt changes that one wishes to detect. In these cases, default implementations, which are often based on assumptions of a constant mean between changes and independent noise, can lead to substantial over-estimation of the number of changes. We propose a principled approach to detect such abrupt changes that models local fluctuations as a random walk process and autocorrelated noise via an AR(1) process. We then estimate the number and location of changepoints by minimizing a penalized cost based on this model. We develop a novel and efficient dynamic programming algorithm, DeCAFS, that can solve this minimization problem; despite the additional challenge of dependence across segments, due to the autocorrelated noise, which makes existing algorithms inapplicable. Theory and empirical results show that our approach has greater power at detecting abrupt changes than existing approaches. We apply our method to measuring gene expression levels in bacteria. Supplementary materials for this article are available online.
On Identifying and Mitigating Bias in the Estimation of the COVID-19 Case Fatality Rate

The relative case fatality rates (CFRs) between groups and countries are key measures of relative risk that guide policy decisions regarding scarce medical resource allocation during the ongoing COVID-19 pandemic. In the middle of an active outbreak when surveillance data is the primary source of information, estimating these quantities involves compensating for competing biases in time series of deaths, cases, and recoveries. These include time- and severity- dependent reporting of cases as well as time lags in observed patient outcomes. In the context of COVID-19 CFR estimation, we survey such biases and their potential significance. Further, we analyze theoretically the effect of certain biases, like preferential reporting of fatal cases, on naive estimators of CFR. We provide a partially corrected estimator of these naive estimates that accounts for time lag and imperfect reporting of deaths and recoveries. We show that collection of randomized data by testing the contacts of infectious individuals regardless of the presence of symptoms would mitigate bias by limiting the covariance between diagnosis and death. Our analysis is supplemented by theoretical and numerical results and a simple and fast open-source codebase at https://github.com/aangelopoulos/cfr-covid-19 .
Can BERT Reason? Logically Equivalent Probes for Evaluating the Inference Capabilities of Language Models

Pre-trained language models (PTLM) have greatly improved performance on commonsense inference benchmarks, however, it remains unclear whether they share a human's ability to consistently make correct inferences under perturbations. Prior studies of PTLMs have found inference deficits, but have failed to provide a systematic means of understanding whether these deficits are due to low inference abilities or poor inference robustness. In this work, we address this gap by developing a procedure that allows for the systematized probing of both PTLMs' inference abilities and robustness. Our procedure centers around the methodical creation of logically-equivalent, but syntactically-different sets of probes, of which we create a corpus of 14,400 probes coming from 60 logically-equivalent sets that can be used to probe PTLMs in three task settings. We find that despite the recent success of large PTLMs on commonsense benchmarks, their performances on our probes are no better than random guessing (even with fine-tuning) and are heavily dependent on biases--the poor overall performance, unfortunately, inhibits us from studying robustness. We hope our approach and initial probe set will assist future work in improving PTLMs' inference abilities, while also providing a probing set to test robustness under several linguistic variations--code and data will be released.
A MUTANT GENOTYPE OF FLAX (Linum usitatissimum L.) CONTAINING VERY LOW LEVELS OF LINOLENIC ACID IN ITS SEED OIL

Two flax (Linum usitatissimum L.) mutants having reduced linolenic acid content in their seed oil (M1589 = 19.1% linolenic; M1722 = 23.4% linolenic) were crossed to determine whether further reductions could be achieved by recombination of the mutant genes. Extensive transgressive segregation was evident in the F2 for both linolenic acid (1.2–36.6%) and linoleic acid (14.7–55.2%), which were strongly negatively correlated (r = −0.97). F2 plants homozygous for both the M1589 and M1722 mutations had very low levels of linolenic acid ( 46%). Key words: Flax, linseed, Linum usitatissimum, linoleic acid, linolenic acid, seed oil
Integrated Time Series Summarization and Prediction Algorithm and its Application to COVID-19 Data Mining

This paper proposes a simple method to extract from a set of multiple related time series a compressed representation for each time series based on statistics for the entire set of all time series. This is achieved by a hierarchical algorithm that first generates an alphabet of shapelets based on the segmentation of centroids for clustered data, before labels of these shapelets are assigned to the segmentation of each single time series via nearest neighbor search using unconstrained dynamic time warping as distance measure to deal with non-uniform time series lenghts. Thereby, a sequence of labels is assigned for each time series. Completion of the last label sequence permits prediction of individual time series. Proposed method is evaluated on two global COVID-19 datasets, first, for the number of daily net cases (daily new infections minus daily recoveries), and, second, for the number of daily deaths attributed to COVID-19 as of April 27, 2020. The first dataset involves 249 time series for different countries, each of length 96. The second dataset involves 264 time series, each of length 96. Based on detected anomalies in available data a decentralized exit strategy from lockdowns is advocated.
Recipes for bolometric corrections and Gaia luminosities of B-type stars: application to an asteroseismic sample

We provide three statistical model prescriptions for the bolometric corrections appropriate for B-type stars as a function of (i) Teff, (ii) Teff and log g, and (iii)Teff, log g and [M/H]. These statistical models have been calculated for 27 different filters, including those of the Gaia space mission, and were derived based on two different grids of bolometric corrections assuming LTE and LTE+NLTE, respectively. Previous such work has mainly been limited to a single photometric passband without taking into account non-local thermodynamic equilibrium (NLTE) effects on the bolometric corrections. Using these statistical models, we calculate the luminosities of 34 slowly pulsating B-type (SPB) stars with available spectroscopic parameters, to place them in the Hertzsprung–Russell diagram and to compare their position to the theoretical SPB instability strip. We find that excluding NLTE effects has no significant effect on the derived luminosities for the temperature range 11 500–21 000 K. We conclude that spectroscopic parameters are needed in order to achieve meaningful luminosities of B-type stars. The three prescriptions for the bolometric corrections are valid for any galactic B-type star with effective temperatures and surface gravities in the ranges 10 000–30 000 K and 2.5–4.5 dex, respectively, covering regimes below the Eddington limit.
Improving Robustness via Risk Averse Distributional Reinforcement Learning

One major obstacle that precludes the success of reinforcement learning in real-world applications is the lack of robustness, either to model uncertainties or external disturbances, of the trained policies. Robustness is critical when the policies are trained in simulations instead of real world environment. In this work, we propose a risk-aware algorithm to learn robust policies in order to bridge the gap between simulation training and real-world implementation. Our algorithm is based on recently discovered distributional RL framework. We incorporate CVaR risk measure in sample based distributional policy gradients (SDPG) for learning risk-averse policies to achieve robustness against a range of system disturbances. We validate the robustness of risk-aware SDPG on multiple environments.
ROLE OF SETTLEMENT DENSITY ON GAMETOPHYTE GROWTH AND REPRODUCTION IN THE KELPS PTERYGOPHORA CALIFORNICA AND MACROCYSTIS PYRIFERA (PHAEOPHYCEAE) 1

Laboratory studies were used to examine how variation in the density of spore settlement influences gametophyte growth, reproduction, and subsequent sporophyte production in the kelps Pterygophora californica Ruprecht and Macrocystis pyrifera (L.) C. Ag. In still (non‐aerated) cultures, egg maturation in both species was delayed when spores were seeded at densities 300 · mm−2. Although the density at which this inhibition was first observed was similar for both species, the age at which their eggs matured was not. P. californica females reached sexual maturity an average of 4 days (or ∼ 30%) sooner than did M, pyrifera. As observed previously in field experiments, per capita sporophyte production was negatively density dependent for both species when seeded at spore densities of 10 · mm−2. Total sporophyte production (i.e. number · cm−2) for both species, however, was greatest at intermediate densities of spore settlement (∼ 50 spores · mm−2). In contrast, total sporophyte production by P. californica steadily increased with increasing spore density in aerated cultures; highest sporophyte density was observed on slides seeded at a density of 1000 spores · mm−2. Preliminary experiments with P. californica involving manipulation of aeration and nutrients indicate that inhibition of gametophyte growth and reproduction at higher densities of spore settlement in non‐aerated cultures was probably caused by nutrient limitation.
Capturing heterosis in forage crop cultivar development

Despite the widespread use of hybrid cultivars in many crop species, most forage crop cultivars are synthetic populations that do not express maximum heterosis for important agronomic traits such as yield. Several aspects of these crops, including severe inbreeding depression, perfect flowers, and polyploidy, limit the ability to produce conventional single- or double-cross hybrids, but the viable alternative of developing semihybrid populations has been relatively unexplored. Both theoretical and empirical evidence support the notion that hybrids, developed by crossing divergent populations, can outyield the better performing parental population. A method to produce semihybrids is discussed, necessitating the development and maintenance of heterotic groups within a species. Progeny formed by crossing populations are semihybrids because in a cross of two populations, 1/2 of the progeny result from interpopulation crosses and 112 from intrapopulation crosses. Expected genotype proportions are presented for several scenarios to show the feasibility of using semihybrids to capture partial heterotic gains. Development of pure hybrids is more problematic but could be realized by using transgenic selectable markers, such as herbicide resistances, to rogue nonhybrid plants in production fields. Molecular markers may aid in the development of the heterotic groups and in choosing parents to be crossed. Potential heterotic groups in several forage species are suggested. By requiring attention to germplasm resources, this method will also be useful for broadening and improving the genetic bases of most cultivated forage crops.
Learning an Unreferenced Metric for Online Dialogue Evaluation

Evaluating the quality of a dialogue interaction between two agents is a difficult task, especially in open-domain chit-chat style dialogue. There have been recent efforts to develop automatic dialogue evaluation metrics, but most of them do not generalize to unseen datasets and/or need a human-generated reference response during inference, making it infeasible for online evaluation. Here, we propose an unreferenced automated evaluation metric that uses large pre-trained language models to extract latent representations of utterances, and leverages the temporal transitions that exist between them. We show that our model achieves higher correlation with human annotations in an online setting, while not requiring true responses for comparison during inference.
The Second Plateau in X-Ray Afterglow Providing Additional Evidence for Rapidly Spinning Magnetars as the GRB Central Engine

Evidence for the central engine of gamma-ray bursts (GRBs) has been collected in the Neil Gehrels Swift data. For instance, some GRBs show an internal X-ray plateau followed by very steep decay, which is difficult interpret within the framework of a black hole (BH) central engine, but is consistent within a rapidly spinning magnetar engine picture. The very steep decay at the end of the plateau suggests a sudden cessation of the central engine, which is explained as the collapse of a supramassive magnetar into a BH when it spins down. Here we propose that some additional evidence, such as a second X-ray plateau feature, would show up if the fallback accretion could activate the newborn BH and sufficient energy could be transferred from the newborn BH to the GRB blast wave. With a systematic data analysis for all long GRBs, we find three candidates in the Swift sample, i.e., GRBs 070802, 090111, and 120213A, whose X-ray afterglow lightcurves contain two plateaus, with the first one being an internal plateau. We find that in a fairly loose and reasonable parameter space, the second X-ray plateau data for all 3 GRBs could be interpreted with our proposed model. Future observations are likely to discover similar events, which could offer more information on the properties of the magnetar, as well as the newborn BH.
Phytogenic and microbial phytases in human nutrition

Summary Phytate (inositol hexa phosphate) hydrolysis can occur during food preparation and production and in the intestine, either by phytase from plants, yeasts or other micro-organisms. This degradation is of nutritional importance, because removal of phosphate groups from the inositol ring results in an increased bioavailability of essential dietary minerals. To substantially improve iron absorption the degradation has to be virtually complete. Food processing techniques increasing the activity of the naturally occurring plant phytases are soaking, malting, hydrothermal treatment and fermentation. An alternative is addition of phytases or micro-organisms producing phytase. Phytate degradation in the stomach and small intestine occurs as a result of activity of dietary phytase of plant or microbial origin. The plant phytase is less stable than fungal phytase in the physiological conditions of the intestine. Biotechnologically produced phytases may be possible for use tomorrow in food processing as well as plant raw material and starter cultures with inserted phytase genes.
Multivariate Analyses of the Influences of Water Chemistry and Habitat Parameters on the Abundances of Pond-Breeding Amphibians

ABSTRACT We surveyed 104 potential amphibian-breeding sites in northwest Indiana for the presence and abundance of amphibians, habitat parameters, and water chemistry. Linear regression was used as an exploratory analysis, and stepwise multiple regression and ANOVA were used to model factors that best explained amphibian species richness, abundance, and number of years with breeding populations. The most important breeding site factors among those studied were wetlands with semi-permanent hydrology, levels of dissolved chloride, silica, hardness and alkalinity, standing waters that were not ditches, wetlands without agriculture within 200 m, the number of hydrology types within one kilometer, the number of wetlands within 400 m, and biotic interactions within the amphibian community. Minor factors included the presence of ammonia, turbidity, low phosphates, low detergents and pH level; wetlands with wooded upland habitats <200 m, palustrine wetland habitats, surface area of the wetland, and percentage of the wetland covered by emergent vegetation.
Morse potential in relativistic contexts from generalized momentum operator and non-minimal coupling

In this work we explore a generalization of the Dirac and Klein-Gordon oscillators, where the linear momentum is replaced by a deformed version inspired in nonextensive statistics, that gives place to the Morse potential in both relativistic contexts by first principles. We employ a canonical transformation that maps the harmonic oscillator with a generalized momentum operator into the Morse potential. We study the 1D and the 3D cases, using the Pekeris approximation in the later case. In the non-relativistic limit we reproduce the S-wave states of the H2 molecule while in the null deformation limit we recover spinless (KG) and spin-orbit (Dirac) oscillators.
The Breeding Biology of Epacris impressa. Is This Species Heterostylous

The suggestion that Epacris impressa is heterostylous is discussed in relation to an examination of the morphological characteristics and the incompatibility system of the species. The conclusion is reached that, although the style length is variable, the species does not exhibit either the full morphological or incompatibility syndromes associated with heterostylic systems. An interpretation is given suggesting E. impressa may represent the early stages of the evolution of heterostyly. The results of self- and crosspollination experiments are presented which confirm the view that E. impressa is a species which is essentially self-infertile, but a significant minority of individuals within each population demonstrate self-fertility.
Bioresistance of thermally modified Populus tremuloides (North American Aspen) wood against four decay fungi

A study was carried out to investigate the effect of thermal treatment on biological resistance of Populus tremuloides wood against four decay fungi, including T. versicolor, P. placenta, G. trabeum and C. puteana. The weight loss data showed that degradation of untreated wood by the white rot fungus T. versicolor resulted in higher weight loss (57·1%) compared to those by brown rot fungi G. trabeum (21·9%), P. placenta (36·7%) and C. puteana (7·1%). When this species was heat treated at 220°C, the weight loss was reduced to <10%. Increasing temperature and the holding time appeared to affect the resistance against T. versicolor, P. placenta and G. trabeum attacks, but the effect on the resistance against C. puteana was not significant. The humidity during thermal modification affected the degradation of wood against T. versicolor attack, but it did not have a significant effect on the other fungi.
Photospheric Polarization Signatures from Long Gamma-Ray Burst Simulations

A comprehensive understanding of gamma-ray bursts (GRBs) has been elusive due to the variety of questions surrounding the radiation mechanism at play in these events. Polarization measurements of GRBs can heavily constrain the relevant radiation mechanisms and the structure of the GRB jet; however, there is a limited number of theoretical predictions that observed GRB polarizations can be compared against. Here, we conduct radiative transfer calculations of a set of two-dimensional relativistic hydrodynamic long GRB (LGRB) jet simulations, of a constant and a variable jet, using the Monte Carlo Radiation Transport (MCRaT) code. MCRaT has been enhanced by the inclusion of polarization; it has been first verified by reproducing a variety of results in the literature and then used to obtain the time-integrated and time-resolved polarization degrees and angles of the synthetic LGRBs. While the obtained time-integrated polarization degrees (≲1%) are consistent with the constraints from the POLAR experiment, they are lower than other theoretical studies due to the lack of strong gradients in the model jet profiles that we use. The time-resolved results suggests that GRBs with wide jets observed on axis will have small polarization degrees (≲2%) and constant polarization angles, during the brightest portion of the light curve. GRBs observed off-axis will have larger polarization degrees and polarization angles that change with the temporal structure of radiating shells in the outflow. We then place our results in the context of GRB prompt emission models and future LEAP and POLAR-2 GRB polarimetry detections.
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation

Evaluation of cross-lingual encoders is usually performed either via zero-shot cross-lingual transfer in supervised downstream tasks or via unsupervised cross-lingual textual similarity. In this paper, we concern ourselves with reference-free machine translation (MT) evaluation where we directly compare source texts to (sometimes low-quality) system translations, which represents a natural adversarial setup for multilingual encoders. Reference-free evaluation holds the promise of web-scale comparison of MT systems. We systematically investigate a range of metrics based on state-of-the-art cross-lingual semantic representations obtained with pretrained M-BERT and LASER. We find that they perform poorly as semantic encoders for reference-free MT evaluation and identify their two key limitations, namely, (a) a semantic mismatch between representations of mutual translations and, more prominently, (b) the inability to punish “translationese”, i.e., low-quality literal translations. We propose two partial remedies: (1) post-hoc re-alignment of the vector spaces and (2) coupling of semantic-similarity based metrics with target-side language modeling. In segment-level MT evaluation, our best metric surpasses reference-based BLEU by 5.7 correlation points.
On leucophores and the chromatic unit of Octopus vulgaris

The leucophores of Octopus vulgaris are much branched cells bearing, all over the surface, small clubs that contain electron-dense material of an unknown nature. Some tens of leucophores are organized to form a “sponge” in the centre of the chromatic unit, which can be elevated above the peripheral region. This central region reflects light over a broad band and may be important in camouflage. The chromatic unit also contains iridophores and chromatophores. The latter may be yellow, orange, red or black, and the different types are interspersed among one another in a regular manner. The chromatophores are disposed in a precise way with respect to the leucophores, the black ones lying above holes in the sponge. The possible significance of this arrangement for camouflage is discussed.
The effect of thermal environment on the digestion of broilers

Summary Two experiments were conducted to determine the effect of thermal environment on the digestion of broilers. In both experiments the birds were exposed to three temperatures: 5, 21, and 32° C, and relative humidity was maintained at 60%. In experiment one, the amount of chyme in the whole digestive tract was decreased by the cold environment (5° C, 60% relative humidity) and increased by hot environment (32° C, 60% relative humidity), compared with control environment (20° C, 60% relative humidity). The expelling of digesta from the crop or small intestine was suppressed by high temperature (32° C) (p < 0.01). In experiment two, the activities of trypsin, chymotrypsin, and amylase were affected significantly by different environmental temperatures (p < 0.01). Compared to normal environment, the activities of the three kinds of enzymes in intestinal juice were decreased by the hot environment: trypsin (p < 0.01), chymotrypsin (p < 0.05), and amylase (p < 0.01), respectively. The activities of the three kinds of digestive enzyme were not influenced by the cold environment.