Miracle-dz/UniFAR-FTUs huggingface dataset:
The Boulder Population of Asteroid 4 Vesta: Size‐Frequency Distribution and Survival Time

Dawn's framing camera observed boulders on the surface of Vesta when the spacecraftwas in its lowest orbit (Low Altitude Mapping Orbit, LAMO). We identified, measured, and mapped boulders in LAMO images, which have a scale of 20 m per pixel. We estimate that our sample is virtually complete down to a boulder size of 4 pixels (80 m). The largest boulder is a 400 m‐sized block on the Marcia crater floor. Relatively few boulders reside in a large area of relatively low albedo, surmised to be the carbon‐rich ejecta of the Veneneia basin, either because boulders form less easily here or live shorter. By comparing the density of boulders around craters with a known age, we find that the maximum boulder lifetime is about 300 Ma. The boulder size‐frequency distribution (SFD) is generally assumed to follow a power law. We fit power laws to the Vesta SFD by means of the maximum likelihood method, but they do not fit well. Our analysis of power law exponents for boulders on other small Solar System bodies suggests that the derived exponent is primarily a function of boulder size range. The Weibull distribution mimics this behavior and fits the Vesta boulder SFD well. The Weibull distribution is often encountered in rock grinding experiments and may result from the fractal nature of cracks propagating in the rock interior. We propose that, in general, the SFD of particles (including boulders) on the surface of small bodies follows a Weibull distribution rather than a power law.
Effect of Constant Temperature Treatments Followed by Fluctuating Temperatures on the Softening of Hard Seeds of Trifolium subterraneum L

Three experiments are described in which the effects of constant temperatures ranging from 15 to 80°C, followed by diurnally fluctuating temperatures of 60/15°C were compared on seed softening in three cultivars of T. subterraneum. Constant temperature treatments alone produced relatively few soft seeds, but rapid seed softening ensued within a few days of subsequent fluctuating temperature treatment. The higher and the longer the constant temperature pretreatment, the more soft seeds were obtained. The rate at which this preconditioning of the seed took place was highest in the early stages of exposure to constant temperatures. Differences between cultivars and between temperature treatments were established mainly during this early period of constant temperature treatment. Rates of change of temperature in the 60/15°C fluctuation treatment were important in the final seed softening process: the slower the rate of temperature change the more soft seeds were produced. It is suggested that two distinct temperature dependent processes are involved in seed softening. The first appears to be a thermal degradation process which probably results in weakening of the strophiolar region. Fluctuating temperatures bring about the second stage of softening in which the strophiole is rendered permeable to water.
The Mexican and Central American Species of Fuchsia (Onagraceae) Except for Sect. Encliandra

Six native and one naturalized species of Fuchsia (Onagraceae) from Mexico and Central America are recognized, not including the recently revised sect. Encliandra. One species, Fuchsia jimenezii, and one section, Jimenezia, are newly described, and Ellobium is also recognized as a section. The recognition of subdioecy in Fuchsia paniculata (sect. Schufia) now strengthens evidence of a trend toward male sterility and eventual dioecy in the small, peripheral sections of the genus. The distinctions between that species and the closely related but entirely hermaphroditic F. arborescens are established. Fuchsia jimenezii (sect. Jimenezia) is a phylogenetically key species because it has the antipetalous stamens reflexed into the tube like sect. Encliandra, yet it has the more generalized many-seeded berry and hermaphroditic flowers of most other sections. The new sect. Ellobium joins F. splendens, F. fulgens, and F. decidua into a morphologically and geographically coherent unit, with links to the Andean sects. Fuchsia and Hemsleyella. Fuchsia cordifolia is reduced to the synonymy of F. splendens on the basis of a study of populations from throughout its range. Fuchsia is a predominantly South American group comprising some 100 species of shrubs and trees. In the only comprehensive revision of the genus, Munz (1943) recognized seven sections, Quelusia, Fuchsia, Hemsleyella, Kiershlegeria, Schufia, Encliandra, and Skinnera, of which the last three, a small part of sect. Fuchsia, and one species of Hemsleyella were found outside of South America. Recently, Breedlove (1969) revised the Mexican and Central American sect. Encliandra, reducing the number of species recognized from 16 to 6 through the study of populations in the field. Later, experimental work by Arroyo & Raven (1975) revealed that the three morphologically gynodioecious species in this section are functionally subdioecious and that the remaining morphologically dioecious species probably evolved from gynodioecious ancestors via subdioecy. As
A reinforcement learning approach to hybrid control design

In this paper we design hybrid control policies for hybrid systems whose mathematical models are unknown. Our contributions are threefold. First, we propose a framework for modelling the hybrid control design problem as a single Markov Decision Process (MDP). This result facilitates the application of off-the-shelf algorithms from Reinforcement Learning (RL) literature towards designing optimal control policies. Second, we model a set of benchmark examples of hybrid control design problem in the proposed MDP framework. Third, we adapt the recently proposed Proximal Policy Optimisation (PPO) algorithm for the hybrid action space and apply it to the above set of problems. It is observed that in each case the algorithm converges and finds the optimal policy.
An exploratory study of L1-specific non-words

In this paper, we explore L1-specific non-words, i.e. non-words in a target language (in this case Swedish) that are re-ranked by a different-language language model. We surmise that speakers of a certain L1 will react different to L1-specific non-words than to general non-words. We present the results from two small case studies exploring whether re-ranking non-words with different language models leads to a perceived difference in `Swedishness' (pilot study 1) and whether German and English native speakers have longer reaction times in a lexical decision task when presented with their respective L1-specific non-words (pilot study 2). Tentative results seem to indicate that L1-specific non-words are processed second-slowest, after purely Swedish-looking non-words.
A meta-analysis of Boolean network models reveals design principles of gene regulatory networks

Gene regulatory networks (GRNs) play a central role in cellular decision-making. Understanding their structure and how it impacts their dynamics constitutes thus a fundamental biological question. GRNs are frequently modeled as Boolean networks, which are intuitive, simple to describe, and can yield qualitative results even when data are sparse. We assembled the largest repository of expert-curated Boolean GRN models. A meta-analysis of this diverse set of models reveals several design principles. GRNs exhibit more canalization, redundancy, and stable dynamics than expected. Moreover, they are enriched for certain recurring network motifs. This raises the important question why evolution favors these design mechanisms.
Temporal variation in recruitement and mortality for the pasture weed Hieracium floribundum: implications for a model of population dynamics

(1) Threefold differences in annual recruitment were recorded for the pasture weed Hieracium floribundum* during an 8-year study. There were also eight-fold differences in the maximum value of annual mortality during the same period. (2) Annual variation in the effects of herbivores (e.g., Microtus sp.) apparently accounted for most of the change in mortality and recruitment. Recruitment may also have been influenced by the availability of soil moisture early in the growing season. (3) Population density increased more slowly than predicted by a mathematical model, because the model did not allow for this temporal variation in recruitment and mortality. After 6 years, predicted density was an average of 60% greater than actual density. Models to predict long-term changes in weed density must therefore allow for annual variation in recruitment and mortality.
Density and growth of juvenile Amphiura filiformis (Ophiuroidea) in the Øresund

Abstract By regular, quantitative sampling during two years 13 050 specimens of Amphiura filiformis were collected at a locality in the Oresund (27 m depth, muddy sand). The material included all stages from newly settled to adults. Three settling periods were registered with maximum numbers of newly settled from 6200 to 6800 · m−2. The mean disc diameter at settling was 0.3 mm, after 1 year 0.6 mm and after 2 years 1.6 mm. The adults had disc diameters of 4–9 mm. Consequently, the juvenile life lasted at least 3 years. } During all seasons there was a remarkable paucity of individuals with disc diameters between 2 and 4 mm. No age groups were found among the adults. Altogether, there is every possibility of a long life span — maybe 25 years. The density of adults has been stable for at least 20 years and was during the study period 575 · m−2 (mean), max. 1050 · m−2. Compared with other European populations the density was high and, therefore, I conclude that conditions are favourable for Amphiura filiform.
Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee

Due to the hierarchical structure of many machine learning problems, bilevel programming is becoming more and more important recently, however, the complicated correlation between the inner and outer problem makes it extremely challenging to solve. Although several intuitive algorithms based on the automatic differentiation have been proposed and obtained success in some applications, not much attention has been paid to finding the optimal formulation of the bilevel model. Whether there exists a better formulation is still an open problem. In this paper, we propose an improved bilevel model which converges faster and better compared to the current formulation. We provide theoretical guarantee and evaluation results over two tasks: Data Hyper-Cleaning and Hyper Representation Learning. The empirical results show that our model outperforms the current bilevel model with a great margin. \emph{This is a concurrent work with \citet{liu2020generic} and we submitted to ICML 2020. Now we put it on the arxiv for record. }
WaveGrad: Estimating Gradients for Waveform Generation

This paper introduces WaveGrad, a conditional model for waveform generation which estimates gradients of the data density. The model is built on prior work on score matching and diffusion probabilistic models. It starts from a Gaussian white noise signal and iteratively refines the signal via a gradient-based sampler conditioned on the mel-spectrogram. WaveGrad offers a natural way to trade inference speed for sample quality by adjusting the number of refinement steps, and bridges the gap between non-autoregressive and autoregressive models in terms of audio quality. We find that it can generate high fidelity audio samples using as few as six iterations. Experiments reveal WaveGrad to generate high fidelity audio, outperforming adversarial non-autoregressive baselines and matching a strong likelihood-based autoregressive baseline using fewer sequential operations. Audio samples are available at this https URL.
Strange quark mass turns magnetic domain walls into multi-winding flux tubes

Dense quark matter is expected to behave as a type-II superconductor at strong coupling. It was previously shown that if the strange quark mass $m_s$ is neglected, magnetic domain walls in the so-called 2SC phase are the energetically preferred magnetic defects in a certain parameter region. Computing the flux tube profiles and associated free energies within a Ginzburg-Landau approach, we find a cascade of multi-winding flux tubes as "remnants" of the domain wall when $m_s$ is increased. These flux tubes exhibit an unconventional ring-like structure of the magnetic field. We show that flux tubes with winding numbers larger than one survive for values of $m_s$ up to about 20% of the quark chemical potential. This makes them unlikely to play a significant role in compact stars, but they may appear in the QCD phase diagram in the presence of an external magnetic field.
Urgent data for COVID-19 are needed for a scientific design of social distancing

The COVID-19 pandemic is largely caused by airborne transmission, a phenomenon that rapidly gained the attention of the scientific community. Social distancing is of paramount importance to limit the spread of the disease, but to design social distancing rules on a scientific basis the process of dispersal of virus containing respiratory droplets must be understood. Here, we demonstrate that available knowledge is largely inadequate to make predictions on the reach of infectious droplets emitted during a cough and on their infectious potential. We follow the position and evaporation of thousands of respiratory droplets by massive state-of-the-art numerical simulations of the airflow caused by a typical cough. We find that different initial distributions of droplet size taken from literature and different ambient relative humidity lead to opposite conclusions: (1) most vs none of the viral content settles in the first 1-2 m; (2) viruses are carried entirely on dry nuclei vs on liquid droplets; (3) small droplets travel less than 2.5 m vs more than 7.5 m. We point to two key issues that need to be addressed urgently in order to provide a scientific foundation to social distancing rules: (I1) a careful characterisation of the initial distribution of droplet sizes; (I2) the infectious potential of viruses carried on dry nuclei vs liquid droplets.
Curves with sharp Chabauty-Coleman bound

We construct curves of each genus $g\geq 2$ for which Coleman's effective Chabauty bound is sharp and Coleman's theorem can be applied to determine rational points if the rank condition is satisfied. We give numerous examples of genus two and rank one curves for which Coleman's bound is sharp. Based on one of those curves, we construct an example of a curve of genus five whose rational points are determined using the descent method together with Coleman's theorem.
Equivariant Cerf theory and perturbative $SU(n)$ Casson invariants

We develop an equivariant Cerf theory for Morse functions on finite-dimensional manifolds with group actions, and adapt the technique to the infinite-dimensional setting to study the moduli space of perturbed flat $SU(n)$-connections. As a consequence, we prove the existence of perturbative $SU(n)$ Casson invariants on integer homology spheres for all $n\ge 3$, and write down an explicit formula when $n=4$. This generalizes the previous works of Boden and Herald.
Semantically Adaptive Image-to-image Translation for Domain Adaptation of Semantic Segmentation

Domain shift is a very challenging problem for semantic segmentation. Any model can be easily trained on synthetic data, where images and labels are artificially generated, but it will perform poorly when deployed on real environments. In this paper, we address the problem of domain adaptation for semantic segmentation of street scenes. Many state-of-the-art approaches focus on translating the source image while imposing that the result should be semantically consistent with the input. However, we advocate that the image semantics can also be exploited to guide the translation algorithm. To this end, we rethink the generative model to enforce this assumption and strengthen the connection between pixel-level and feature-level domain alignment. We conduct extensive experiments by training common semantic segmentation models with our method and show that the results we obtain on the synthetic-to-real benchmarks surpass the state-of-the-art.
Accelerated reactive transport simulations in heterogeneous porous medium using Reaktoro and Firedrake

Geochemical reaction calculations in reactive transport modeling are costly in general. They become more expensive the more complex is the chemical system and the activity models used to describe the non-ideal thermodynamic behavior of its phases. Accounting for many aqueous species, gases, and minerals also contributes to more expensive computations. This work investigates the performance of the on-demand machine learning (ODML) algorithm presented in Allan etal. (2020) when applied to different reactive transport problems in heterogeneous porous media. We demonstrate that the ODML algorithm enables faster chemical equilibrium calculations by one to three orders of magnitude. This, in turn, significantly accelerates the entire reactive transport simulations. The numerical experiments are carried out using the coupling of two open-source software packages: Firedrake (Rathgeber, 2016) and Reaktoro (Leal, 2015).
Seeing wake words: Audio-visual Keyword Spotting

The goal of this work is to automatically determine whether and when a word of interest is spoken by a talking face, with or without the audio. We propose a zero-shot method suitable for in the wild videos. Our key contributions are: (1) a novel convolutional architecture, KWS-Net, that uses a similarity map intermediate representation to separate the task into (i) sequence matching, and (ii) pattern detection, to decide whether the word is there and when; (2) we demonstrate that if audio is available, visual keyword spotting improves the performance both for a clean and noisy audio signal. Finally, (3) we show that our method generalises to other languages, specifically French and German, and achieves a comparable performance to English with less language specific data, by fine-tuning the network pre-trained on English. The method exceeds the performance of the previous state-of-the-art visual keyword spotting architecture when trained and tested on the same benchmark, and also that of a state-of-the-art lip reading method.
Scaling attributed network embedding to massive graphs

Given a graph G where each node is associated with a set of attributes, attributed network embedding (ANE) maps each node v ∈ G to a compact vector Xv, which can be used in downstream machine learning tasks. Ideally, Xv should capture node v's affinity to each attribute, which considers not only v's own attribute associations, but also those of its connected nodes along edges in G. It is challenging to obtain high-utility embeddings that enable accurate predictions; scaling effective ANE computation to massive graphs with millions of nodes pushes the difficulty of the problem to a whole new level. Existing solutions largely fail on such graphs, leading to prohibitive costs, low-quality embeddings, or both. This paper proposes PANE, an effective and scalable approach to ANE computation for massive graphs that achieves state-of-the-art result quality on multiple benchmark datasets, measured by the accuracy of three common prediction tasks: attribute inference, link prediction, and node classification. In particular, for the large MAG data with over 59 million nodes, 0.98 billion edges, and 2000 attributes, PANE is the only known viable solution that obtains effective embeddings on a single server, within 12 hours. PANE obtains high scalability and effectiveness through three main algorithmic designs. First, it formulates the learning objective based on a novel random walk model for attributed networks. The resulting optimization task is still challenging on large graphs. Second, PANE includes a highly efficient solver for the above optimization problem, whose key module is a carefully designed initialization of the embeddings, which drastically reduces the number of iterations required to converge. Finally, PANE utilizes multi-core CPUs through non-trivial parallelization of the above solver, which achieves scalability while retaining the high quality of the resulting embeddings. Extensive experiments, comparing 10 existing approaches on 8 real datasets, demonstrate that PANE consistently outperforms all existing methods in terms of result quality, while being orders of magnitude faster.
Towards Non-Contact Glucose Sensing in Aqueous Turbid Medium at ∼1.1 Meters Distance

This work demonstrates a non-contact diffuse reflectance approach with a working distance of ∼1.1 meters for the potential of glucose sensing. Non-contact diffuse reflectance over 1.1–1.3 µm was developed according to a center-illumination-area-detection (CIAD) geometry. The modeled response of diffuse reflectance in the CIAD geometry was examined with phantoms by altering independently the size of the collection geometry and the reduced scattering and absorption properties of the medium. When applied to aqueous turbid medium containing glucose control solutions with the cumulative volume varying over three orders of magnitude, a linear relationship expected for the diffuse reflectance as a function of the medium absorption/reduced-scattering property was observed for four conditions of the glucose-medium composition that differed either in the effective glucose concentration or the host medium scattering property. The cumulation of glucose up to 17.8 mg/dL and 8.9 mg/dL in the host medium having the same optical properties resulted in linear regression slopes of 0.0032 and 0.0030, respectively. The cumulation of the glucose up to 17.8 mg/dL in an aqueous host medium that differed two folds in the reduced scattering property caused the linear regression slope to differ between 0.0032 and 0.0019. The R2 values of all cases were all greater than 0.987.
EFFECT OF ADDITIONAL FOOD ON REPRODUCTIVE SUCCESS IN THE MAGPIE (PICA PICA)

SUMMARY (1) Magpie Pica pica pairs were given extra food (fish) before and during the breeding season. Reproductive success was compared with that of the same pairs in other seasons, when no food was offered, and with that of a control group, without extra food. Food was also offered in empty territories, occupied in earlier seasons, in the hope of inducing reoccupation. (2) Experimental pairs started egg-laying earlier, had larger clutches, heavier eggs, and greater hatching success, and produced more fledglings than control pairs. This was found also when comparing the same females under experimental and control conditions. Food did not, however, attract new settlers to empty territories. (3) Experimental pairs not only laid earlier, but they also started their laying within a significantly shorter period of time than did controls. The relatively small-scale effects of extra food on timing of breeding suggest that food alone does not determine start of laying, but that it is also stimulated by some other factors. Shortly after the additional factors were perceived by the birds, laying started. As experimental birds were in a better nutritional state than controls, they responded faster, laid larger clutches and heavier eggs. (4) The difference in reproductive success between the two groups was established during the nestling phase. Predation, mainly by hooded crows Corvus cornix L. , and starvation, especially during adverse weather, caused the mortality. As invertebrate activity decreases in such periods, food scarcity is suggested to be the ultimate mortality factor. Extra food buffers adverse periods, giving a more stable temporal distribution of food as compared with natural conditions.