Miracle-dz/UniFAR-FTUs huggingface dataset:
How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks

This paper studies the novel concept of weight correlation in deep neural networks and discusses its impact on the networks' generalisation ability. For fully-connected layers, the weight correlation is defined as the average cosine similarity between weight vectors of neurons, and for convolutional layers, the weight correlation is defined as the cosine similarity between filter matrices. Theoretically, we show that, weight correlation can, and should, be incorporated into the PAC Bayesian framework for the generalisation of neural networks, and the resulting generalisation bound is monotonic with respect to the weight correlation. We formulate a new complexity measure, which lifts the PAC Bayes measure with weight correlation, and experimentally confirm that it is able to rank the generalisation errors of a set of networks more precisely than existing measures. More importantly, we develop a new regulariser for training, and provide extensive experiments that show that the generalisation error can be greatly reduced with our novel approach.
Perceptimatic: A human speech perception benchmark for unsupervised subword modelling

In this paper, we present a data set and methods to compare speech processing models and human behaviour on a phone discrimination task. We provide Perceptimatic, an open data set which consists of French and English speech stimuli, as well as the results of 91 English- and 93 French-speaking listeners. The stimuli test a wide range of French and English contrasts, and are extracted directly from corpora of natural running read speech, used for the 2017 Zero Resource Speech Challenge. We provide a method to compare humans' perceptual space with models' representational space, and we apply it to models previously submitted to the Challenge. We show that, unlike unsupervised models and supervised multilingual models, a standard supervised monolingual HMM-GMM phone recognition system, while good at discriminating phones, yields a representational space very different from that of human native listeners.
Hierarchical Formation Of An Intermediate Mass Black Hole Via Seven Mergers: Implications For GW190521

The gravitational wave event GW190521 involves the merger of two black holes of $\sim 85\text{M}_\odot$ and $\sim 66\text{M}_\odot$ forming an intermediate-mass black hole (IMBH) of mass $\sim 142\text{M}_\odot$. Both progenitors are challenging to explain within standard stellar evolution as they belong to the upper black-hole mass gap. We propose a dynamical formation pathway for this IMBH based on multiple hierarchical mergers of progenitors in the core of a dense star cluster. We identified such scenarios from analysis of a set of 58 direct N-body simulations using NBODY6-gpu. In one of our canonical runs aimed at describing the evolution of a star cluster with $N=10^5$ stars and typical globular cluster properties, we observe a stellar black hole undergoing a chain of seven binary mergers in 6 Gyr, attaining a final mass of $97.8\text{M}_\odot$. We discuss the dynamical interactions that lead to the final IMBH product, as well as the evolution of the black hole population in that simulation. From the analysis of all simulations in our dataset we observe additional smaller chains, tentatively inferring that an IMBH formation through chain mergers is expected in the lifetime of a typical (i.e. median mass) globular cluster with probability $0.01 \lesssim p \lesssim 0.1$. Using this order-of-magnitude estimate and comoving star formation rates we show our results are broadly consistent with the mean rate implied by GW190521, and we discuss implications for future gravitational wave detections of IMBHs.
The LSST DESC DC2 Simulated Sky Survey

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin’s LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep area of approximately 300 deg2, as well as a deep drilling field of approximately 1 deg2. We simulate 5 yr of the planned 10 yr survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the data set to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic test bed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time domain cosmology.
Measuring and Reducing Gendered Correlations in Pre-trained Models

Pre-trained models have revolutionized natural language understanding. However, researchers have found they can encode artifacts undesired in many applications, such as professions correlating with one gender more than another. We explore such gendered correlations as a case study for how to address unintended correlations in pre-trained models. We define metrics and reveal that it is possible for models with similar accuracy to encode correlations at very different rates. We show how measured correlations can be reduced with general-purpose techniques, and highlight the trade offs different strategies have. With these results, we make recommendations for training robust models: (1) carefully evaluate unintended correlations, (2) be mindful of seemingly innocuous configuration differences, and (3) focus on general mitigations.
Observables of spheroidal magnetized strange stars

We study stable spheroidal configurations of magnetized strange stars using an axially symmetric metric in spherical coordinates that uses a gamma parameter to link the anisotropy in the equation of state due to the magnetic field with the deformation of the star. The stars are composed by magnetized strange quark matter described within the framework of the MIT bag model. Their masses, radii, eccentricity, redshift and mass quadrupole moment are computed. Results are compared with spherical strange star solutions obtained with Tolman-Oppenheimer-Volkoff equations and observational data of strange star candidates. In the spheroidal model the observables depend directly on the deformation of the star, and, even though it is small, the observables strongly deviate from the corresponding spherical configurations. Thus, the highest values of the mass quadrupole moment correspond to the intermediate mass regime. These differences might allow us to discriminate between models with and without magnetic field when compared with observations.
Automation of Hemocompatibility Analysis Using Image Segmentation and a Random Forest

The hemocompatibility of blood-contacting medical devices remains one of the major challenges in biomedical engineering and makes research in the field of new and improved materials inevitable. However, current in-vitro test and analysis methods are still lacking standardization and comparability, which impedes advances in material design. For example, the optical platelet analysis of material in-vitro hemocompatibility tests is carried out manually or semi-manually by each research group individually. As a step towards standardization, this paper proposes an automation approach for the optical platelet count and analysis. To this end, fluorescence images are segmented using Zach's convexification of the multiphase-phase piecewise constant Mumford--Shah model. The resulting connected components of the non-background segments then need to be classified as platelet or no platelet. Therefore, a supervised random forest is applied to feature vectors derived from the components using features like area, perimeter and circularity. With an overall high accuracy and low error rates, the random forest achieves reliable results. This is supported by high areas under the receiver-operator and the prediction-recall curve, respectively. We developed a new method for a fast, user-independent and reproducible analysis of material hemocompatibility tests, which is therefore a unique and powerful tool for advances in biomaterial research.
Separation between RR Lyrae and type II Cepheids and their importance for a distance determination: the case of omega Cen

The separation between RR Lyrae (RRLs) and type II Cepheid (T2Cs) variables based on their period is debated. Both types of variable stars are distance indicators, and we aim to promote the use of T2Cs as distance indicators in synergy with RRLs. We adopted new and existing optical and near-infrared (NIR) photometry ofωCen to investigate several diagnostics (color-magnitude diagram, Bailey diagram, Fourier decomposition of the light curve, and amplitude ratios) for their empirical separation. We found that the classical period threshold at one day is not universal and does not dictate the evolutionary stage: V92 has a period of 1.3 days but is likely to be still in its core helium-burning phase, which is typical of RRLs. We also derived NIR period-luminosity relations and found a distance modulus of 13.65 ± 0.07 (err.) ± 0.01 (σ) mag, in agreement with the recent literature. We also found that RRLs and T2Cs obey the same period-luminosity relations in the NIR. This equivalence provides the opportunity of adopting RRLs+T2Cs as an alternative to classical Cepheids to calibrate the extragalactic distance scale.
Collaborative Video Object Segmentation by Multi-Scale Foreground-Background Integration

This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation. Unlike previous practices that focus on exploring the embedding learning of foreground object (s), we consider background should be equally treated. Thus, we propose a Collaborative video object segmentation by Foreground-Background Integration (CFBI) approach. CFBI separates the feature embedding into the foreground object region and its corresponding background region, implicitly promoting them to be more contrastive and improving the segmentation results accordingly. Moreover, CFBI performs both pixel-level matching processes and instance-level attention mechanisms between the reference and the predicted sequence, making CFBI robust to various object scales. Based on CFBI, we introduce a multi-scale matching structure and propose an Atrous Matching strategy, resulting in a more robust and efficient framework, CFBI+. We conduct extensive experiments on two popular benchmarks, i.e., DAVIS and YouTube-VOS. Without applying any simulated data for pre-training, our CFBI+ achieves the performance (<inline-formula><tex-math notation="LaTeX">$\mathcal {J}$</tex-math><alternatives><mml:math><mml:mi mathvariant="script">J</mml:mi></mml:math><inline-graphic xlink:href="yang-ieq1-3081597.gif"/></alternatives></inline-formula>&<inline-formula><tex-math notation="LaTeX">$\mathcal {F}$</tex-math><alternatives><mml:math><mml:mi mathvariant="script">F</mml:mi></mml:math><inline-graphic xlink:href="yang-ieq2-3081597.gif"/></alternatives></inline-formula>) of 82.9 and 82.8 percent, outperforming all the other state-of-the-art methods. Code: <uri>https://github.com/z-x-yang/CFBI</uri>.
Spike-and-Slab Meets LASSO: A Review of the Spike-and-Slab LASSO

High-dimensional data sets have become ubiquitous in the past few decades, often with many more covariates than observations. In the frequentist setting, penalized likelihood methods are the most popular approach for variable election and estimation in high-dimensional data. In the Bayesian framework, spike-and-slab methods are commonly used as probabilistic constructs for high-dimensional modeling. Within the context of univariate linear regression, Rockova and George (2018) introduced the spike-and-slab LASSO (SSL), an approach based on a prior which forms a continuum between the penalized likelihood LASSO and the Bayesian point-mass spike-and-slab formulations. Since its inception, the spike-and-slab LASSO has been extended to a variety of contexts, including generalized linear models, factor analysis, graphical models, and nonparametric regression. The goal of this paper is to survey the landscape surrounding spike-and-slab LASSO methodology. First we elucidate the attractive properties and the computational tractability of SSL priors in high dimensions. We then review methodological developments of the SSL and outline several theoretical developments. We illustrate the methodology on both simulated and real datasets.
Trace Reconstruction Problems in Computational Biology

The problem of reconstructing a string from its error-prone copies, the trace reconstruction problem, was introduced by Vladimir Levenshtein two decades ago. While there has been considerable theoretical work on trace reconstruction, practical solutions have only recently started to emerge in the context of two rapidly developing research areas: immunogenomics and DNA data storage. In immunogenomics, traces correspond to mutated copies of genes, with mutations generated naturally by the adaptive immune system. In DNA data storage, traces correspond to noisy copies of DNA molecules that encode digital data, with errors being artifacts of the data retrieval process. In this paper, we introduce several new trace generation models and open questions relevant to trace reconstruction for immunogenomics and DNA data storage, survey theoretical results on trace reconstruction, and highlight their connections to computational biology. Throughout, we discuss the applicability and shortcomings of known solutions and suggest future research directions.
Power spectrum of density fluctuations, halo abundances, and clustering with primordial black holes

We study the effect of dark matter (DM) being encapsulated in primordial black holes (PBHs) on the power spectrum of density fluctuations $P(k)$; we also look at its effect on the abundance of haloes and their clustering. We allow the growth of Poisson fluctuations since matter and radiation equality and study both monochromatic and extended PBH mass distributions. We present updated monochromatic black hole mass constraints by demanding $ 10^4$h$^{-1}M_\odot$ are excluded from conforming all of the dark matter in the Universe. We also apply this condition to our extended Press-Schechter (PS) mass functions, and find that the Poisson power is scale dependent even before applying evolution, due to the change of the mass density in PBHs with redshift, and therefore with scale, as they start affecting the gravitational potential at different times. We find that characteristic masses $M^*\leq10^2 $h$^{-1}M_\odot$ are allowed, {leaving only two characteristic PBH mass windows of PS mass functions when combining with previous constraints, at $M^*\sim10^2$h$^{-1}M_\odot$ and $\sim10^{-8}$h$^{-1}M_\odot$ where all of the DM can be in PBHs. The resulting dark matter halo mass functions within these windows are similar} to those resulting from cold dark matter made of fundamental particles, but as soon as the parameters produce unrealistic $P(k)$, the resulting halo mass functions and their bias as a function of halo mass deviate strongly from the behaviour measured in the real Universe.
First sample of N2H+ nitrogen isotopic ratio measurements in low-mass protostars

Context. The nitrogen isotopic ratio is considered an important diagnostic tool of the star formation process, and N2H+ is particularly important because it is directly linked to molecular nitrogen N2. However, theoretical models still do not provide an exhaustive explanation for the observed 14N/15N values. Aims. Recent theoretical works suggest that the 14N/15N behaviour is dominated by two competing reactions that destroy N2H+: dissociative recombination and reaction with CO. When CO is depleted from the gas phase, if the N2H+ recombination rate is lower with respect to that for N15NH+, the rarer isotopologue is destroyed more quickly. In prestellar cores, due to a combination of low temperatures and high densities, most CO is frozen in ices onto the dust grains, leading to high levels of depletion. On the contrary, in protostellar cores, where temperature are higher, CO ices evaporate back to the gas phase. This implies that the N2H+ isotopic ratio in protostellar cores should be lower than that in prestellar cores, and consistent with the elemental value of ≈440. We aim to test this hypothesis, producing the first sample of N2H+∕N15NH+ measurements in low-mass protostars. Methods. We observe the N2H+ and N15NH+ lowest rotational transition towards six young stellar objects in the Perseus and Taurus molecular clouds. We model the spectra with a custom python code using a constant Tex approach to fit the observations. We discuss in the Appendix the validity of this hypothesis. The derived column densities are used to compute the nitrogen isotopic ratios. Results. Our analysis yields an average of 14N/15N|pro = 420 ± 15 in the protostellar sample. This is consistent with the protosolar value of 440, and significantly lower than the average value previously obtained in a sample of prestellar objects. Conclusions. Our results are in agreement with the hypothesis that, when CO is depleted from the gas-phase, dissociative recombinations with free electrons destroy N15NH+ faster than N2H+, leading to high isotopic ratios in prestellar cores where carbon monoxide is frozen onto dust grains.
Structure of old-growth and managed stands and growth of old trees in a Mediterranean Pinus nigra forest in southern Spain

lected in 74 forest inventory plots. Significant differences were tested by means of the Mann‐Whitney U-test. A partialredundancyanalysiswasconductedtoassesstherelativecontributionofbothenvironmentalandmanagement variables in explaining differences in thecurrent structure of old-growth and managed stands.Additionally, 25 trees of different size (range 25.4‐98 cm) and age (67‐803 years) were cored and dendrochronological methods and bootstrap linear regression were used to study the effects of size and age on tree growth. The oldgrowth stand exhibited a higher density of large trees (diameter at breast height .50 cm) and greater variability intreesizethanmanagedstands,butlowertreedensityand,consequently,similarvaluesofstandbasalareaand volume.Environmentalvariablesaccountedfor5. 7percentofthetotalvarianceobservedinstructuralattributes, while the contrasting silvicultural condition (old-growth vs managed) accounted for 10.2 per cent. Growth, measured in units of stand basal area, increased continuously with tree size.
Role of atmospheric stability over the Arabian Sea and the unprecedented failure of monsoon 2002

The anomalous behaviour of the monsoon 2002 has been studied. We have made an attempt to combine satellite and other data sources to characterize the thermal stratification over the Arabian Sea during different phases of monsoon 2002. Using NOAA-ATOVSderived atmospheric temperature and moisture profiles, we have calculated a daily stability index (SI) over the entire Indian region and surrounding oceans. The time series of SI clearly brings out the three major significant epochs of monsoon 2002. The relatively dry atmosphere west of 65° E, signifying lack of convection and an unstable atmosphere over the southeast Arabian Sea with west-to-east gradients in water vapour, SI and cloud liquid water content are noted. The unfavourable stratification during July over the entire Arabian Sea has been investigated in detail. The dominant modes of instability oscillations have been seen to be ~ 30 days both over the western and eastern Arabian Sea, while for the high-frequency modes preference was seen over the eastern part. Using the analysed fields of the National Centre for Medium Range Weather Forecasts, the relative contributions of advective and subsidence components in the maintenance of stratification have been investigated. The latter has been found to have played a more dominant role in the deficit monsoon 2002.
Assigning a Value to Dried Distillers' Grains as a Protein Supplement in Cattle Consuming Low-Quality Forage

Assigning a Value to Dried Distillers’ Grains as a Protein Supplement in Cattle Consuming Low-Quality Forage. (May 2010) Zachary Joseph Rambo, B.S., Texas A&M University Chair of Advisory Committee: Dr. Tryon A. Wickersham Cattle consuming low-quality forage may have decreased forage organic matter intake as a result of decreased nitrogen (N) intake. To date, a value has not been assigned to dried distillers’ grains as a protein supplement to cattle consuming lowquality Bermudagrass forage. To address this shortcoming in the data, 13 duodenally and ruminally fistulated steers were arranged in an incomplete 13 × 4 Latin square with 13 treatments and 4 periods. Treatments were arranged as a 4 × 3 factorial plus a negative control (NC), which received no supplement. The first factor consisted of 4 levels of supplemental protein provided at 52, 104, 156, and 208 mg N/kg BW. The second factor consisted of one of three supplemental protein sources, cottonseed meal (CSM), dried distillers’ grains (DDG), and dried distillers’ grains plus urea (DDGU). Total digestible organic matter (TDOMI), and total organic matter intake (TOMI) increased in response to the increasing level of supplemental protein (P <0.01). Similarly, digestible neutral detergent fiber intake (DNDFI) increased as a result of supplementation (P = 0.06). Forage organic matter intake did not increase as a result of protein supplementation (P =