Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of the Kentville Stock Clone Apple Rootstocks. II. Precocity and Productivity

The precocity and productivity of 30 Kentville Stock Clone (KSC) apple (Malus domestica Borkh.) rootstocks, with 'McIntosh' and 'Delicious' as scion cultivars, were assessed independently of each other using a procedure involving computer-aided fitting of curves to yearly production data. A good fit to the data was obtained after biennial fluctuations in yield were removed by using a weighted, 3-year running average. For all 30 rootstocks combined, 'McIntosh' was more precocious and reached a higher level of productivity compared to 'Delicious'. There was poor correlation between precocity and productivity. Precocity and productivity are extensively studied characteris- tics of candidate apple rootstocks (Cummins and Aldwinckle, 1983). Before the selection of superior individuals, these traits, which are time dependent, often require years of evaluation to determine the degree of precocity and the level of productivity. Preston (1967) concluded that a 15-year field trial was required before rootstock performance could be defined fully, but preliminary selection could be made after 6 or 7 years. Crowe (1975) noted that the relative cropping advantage of MM.106 declined relative to other stocks after the early years, and he became concerned that selection based on precocity alone could be biased. Schmidt (1988) confirmed this concern, noting that the shorter the period of cumulative yields the greater the advantage of the precocity- inducing M.9. Cummins and Aldwinkle (1983) also noted that clear distinctions are needed among aspects of precocity and productivity. The most common method of assessing productivity has been to measure fruit yield over a particular time span and adjust it for trunk circumference (Waring, 1920), tree weight (Pearce, 1952), or trunk cross-sectional area (TCA) (Westwood and Roberts, 1970). The latter is relatively easy to measure and is now the characteristic most widely used to describe efficiency. Unfortunately, when this method is used for numerous rootstocks for many years, it is very difficult to identify the most efficient because they could change positions each year. Efficiency in our view should reflect both the speed at which a tree comes into production (precocity) and the level of production it achieves and maintains when mature (productivity). Precocity is important, especially in high density orchards, but it may not signal superior productivity. When evaluating cultivars or rootstocks that vary in the rate at which they come into production, the selection of an appropriate time period on which to base the final conclusion becomes somewhat arbitrary. Dwarf rootstocks that have been selected for precocity will tend to be more efficient when a relatively short time span is chosen. More vigorous rootstocks likely will show higher levels of efficiency if a longer period is selected. It would be useful, therefore, to have a less time depen- dent method of assessing rootstock productivity. The purpose of this study was to compare the precocity and productivity of the 30
Supernormal delay in hatching, embryo cold tolerance and egg fostering in the Black Guillemot Cepphus grylle

The avian embryo can experience a period of suspended growth after egg deposition and before the onset of incubation (Feast et al. 1998). This suspension of embryonic growth requires temperatures too low to allow development and high enough to avoid embryo death (White & Kinney 1974). It also requires humidity sufficient to limit evaporative water loss but low enough to minimize microbial growth on eggshells (Cook et al. 2005). For species with a multi-egg clutch, this postponement of development allows an increase in hatching synchrony when incubation is withheld until clutch completion (Hébert 2002). In avian husbandry and poultry science, the storage of viable eggs prior to incubation has practical applications, where Chicken Gallus gallus (Funk & Forward 1960), Turkey Melagris gallopavo (Bakst & Gupta 1997) and Ostrich Struthio camelus (Hassan et al. 2005) eggs can be stored ≤14 d before the onset of incubation.
Fucols and Phlorethols from the Brown Alga Scytothamnus australis Hook. et Harv. (Chnoosporaceae)

Abstract Eight fucols and two phlorethols were isolated by HPLC from the ethanolic extract of the brown alga Scytothamnus australis,. Because of their instability the substances were peracetylated before isolation. The phlorotannins trifucolnonaacetate, tetrafucol-A-dodecaacetate, tetrafucol-B-dodecaacetate, cis-pentafucol-A-pentadecaacetate, diphlorethol-A-pentaacetate and triphlorethol-A-heptaacetate have been characterized previously. In addition to these substances we found hydroxytetrafucol-B-tridecaacetate, pentafucol-B-pentadecaacetate, cis, trans-pentafucol-A-pentadecaacetate and hexafucol-B-octadecaacetate all of which are described for the first time. The elucidation of their structure was achieved by 1H NMR, 13C NMR, 1H 1H ROESY NMR and mass spectral data.
Distance effect from cloud forest fragments on plant community structure in abandoned pastures in Veracruz, Mexico

Secondary succession was studied in a Mexican cloud forest region along a chronosequence of 15 abandoned pastures (0.25–80 y). Our objective was to determine the effects of distance from the forest border on successional vegetation structure and woody species richness along the chronosequence. Vegetation structure similar to that of mature forests recovered over 40–50 y, both close to (0–10 m) and away from (40–50 m) the border. Total woody species richness was similar for both distances but species composition differed significantly. When primary forest species were analysed separately, basal area, height, abundance and richness were all significantly higher close to the forest border. Primary species such as Quercus spp. (barochorous-synzoochorous) and Carpinus caroliniana (anemochorous) had lower basal area, density and height away from the border than close to it. Secondary species such as Lippia myriocephala (anemochorous) and Myrsine coriacea (endozoochorous) did not differ in their rate of colonization between distances. The limitation of seed dispersal and establishment for primary woody species away from forest borders suggests that propagules need to be introduced to accelerate forest restoration.
Ultra-fast Deep Mixtures of Gaussian Process Experts

Mixtures of experts have become an indispensable tool for flexible modelling in a supervised learning context, and sparse Gaussian processes (GP) have shown promise as a leading candidate for the experts in such models. In the present article, we propose to design the gating network for selecting the experts from such mixtures of sparse GPs using a deep neural network (DNN). This combination provides a flexible, robust, and efficient model which is able to significantly outperform competing models. We furthermore consider efficient approaches to computing maximum a posteriori (MAP) estimators of these models by iteratively maximizing the distribution of experts given allocations and allocations given experts. We also show that a recently introduced method called Cluster-Classify-Regress (CCR) is capable of providing a good approximation of the optimal solution extremely quickly. This approximation can then be further refined with the iterative algorithm.
Online Competitive Influence Maximization

Online influence maximization has attracted much attention as a way to maximize influence spread through a social network while learning the values of unknown network parameters. Most previous works focus on single-item diffusion. In this paper, we introduce a new Online Competitive Influence Maximization (OCIM) problem, where two competing items (e.g., products, news stories) propagate in the same network and influence probabilities on edges are unknown. We adapt the combinatorial multi-armed bandit (CMAB) framework for the OCIM problem, but unlike the non-competitive setting, the important monotonicity property (influence spread increases when influence probabilities on edges increase) no longer holds due to the competitive nature of propagation, which brings a significant new challenge to the problem. We prove that the Triggering Probability Modulated (TPM) condition for CMAB still holds, and then utilize the property of competitive diffusion to introduce a new offline oracle, and discuss how to implement this new oracle in various cases. We propose an OCIM-OIFU algorithm with such an oracle that achieves logarithmic regret. We also design an OCIM-ETC algorithm that has worse regret bound but requires less feedback and easier offline computation. Our experimental evaluations demonstrate the effectiveness of our algorithms.
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds

We study differentially private (DP) algorithms for stochastic non-convex optimization. In this problem, the goal is to minimize the population loss over a $p$-dimensional space given $n$ i.i. d. samples drawn from a distribution. We improve upon the population gradient bound of ${\sqrt{p}}/{\sqrt{n}}$ from prior work and obtain a sharper rate of $\sqrt[4]{p}/\sqrt{n}$. We obtain this rate by providing the first analyses on a collection of private gradient-based methods, including adaptive algorithms DP RMSProp and DP Adam. Our proof technique leverages the connection between differential privacy and adaptive data analysis to bound gradient estimation error at every iterate, which circumvents the worse generalization bound from the standard uniform convergence argument. Finally, we evaluate the proposed algorithms on two popular deep learning tasks and demonstrate the empirical advantages of DP adaptive gradient methods over standard DP SGD.
Gender and Emotion Recognition from Implicit User Behavior Signals

This work explores the utility of implicit behavioral cues, namely, Electroencephalogram (EEG) signals and eye movements for gender recognition (GR) and emotion recognition (ER) from psychophysical behavior. Specifically, the examined cues are acquired via low-cost, off-the-shelf sensors. 28 users (14 male) recognized emotions from unoccluded (no mask) and partially occluded (eye or mouth masked) emotive faces; their EEG responses contained gender-specific differences, while their eye movements were characteristic of the perceived facial emotions. Experimental results reveal that (a) reliable GR and ER is achievable with EEG and eye features, (b) differential cognitive processing of negative emotions is observed for females and (c) eye gaze-based gender differences manifest under partial face occlusion, as typified by the eye and mouth mask conditions.
Multi-modal Trajectory Optimization for Impact-aware Manipulation

The transition from free motion to contact is a challenging problem in robotics, in part due to its hybrid nature. Additionally, disregarding the effects of impacts at the motion planning level often results in intractable impulsive contact forces. In this paper, we introduce an impact-aware multi-mode trajectory optimization (TO) method that combines hybrid dynamics and hybrid control in a coherent fashion. A key concept is the incorporation of an explicit contact force transmission model in the TO method. This allows the simultaneous optimization of the contact forces, contact timings, continuous motion trajectories and compliance, while satisfying task constraints. We compare our method against standard compliance control and an impact-agnostic TO method in physical simulations. Further, we experimentally validate the proposed method with a robot manipulator on the task of halting a large-momentum object.
Embedding Differentiable Sparsity into Deep Neural Network

In this paper, we propose embedding sparsity into the structure of deep neural networks, where model parameters can be exactly zero during training with the stochastic gradient descent. Thus, it can learn the sparsified structure and the weights of networks simultaneously. The proposed approach can learn structured as well as unstructured sparsity.
Seasonal and Geographic Eurythermy in a Coastal Peruvian Lizard

Abstract We contrasted the summer and winter field body temperatures of the tropidurid lizard Microlophus peruvianus at the Paracas Peninsula in southern Peru. We also compared our winter data to those gathered by >Huey (1974) at the Illescas Peninsula in northern Peru to test the hypothesis that southern lizards would tolerate lower temperatures than northern lizards. Cloud cover is more persistent in Paracas than it is in Illescas. During the austral winter, lizards at Paracas reduced surface activity to midday hours and had body temperatures below the mean set-point temperature (as measured in a photo-thermal gradient). Lizards from southern Peru were active over a wider range of temperatures than were lizards from Illescas. Mean body temperature of field-active lizards in the cloudy Paracas site was 33.0 ± 0.44 C, significantly lower than the mean field body temperature at the sunnier Illescas site (36.3 ± 0.26 C, t = −6.19, P < 0.001). Although thermal preferences tend to be conserved among related lizard species, we found considerable variation in body temperatures and activity patterns of two populations of this species.
DeepTracking-Net: 3D Tracking with Unsupervised Learning of Continuous Flow

This paper deals with the problem of 3D tracking, i.e., to find dense correspondences in a sequence of time-varying 3D shapes. Despite deep learning approaches have achieved promising performance for pairwise dense 3D shapes matching, it is a great challenge to generalize those approaches for the tracking of 3D time-varying geometries. In this paper, we aim at handling the problem of 3D tracking, which provides the tracking of the consecutive frames of 3D shapes. We propose a novel unsupervised 3D shape registration framework named DeepTracking-Net, which uses the deep neural networks (DNNs) as auxiliary functions to produce spatially and temporally continuous displacement fields for 3D tracking of objects in a temporal order. Our key novelty is that we present a novel temporal-aware correspondence descriptor (TCD) that captures spatio-temporal essence from consecutive 3D point cloud frames. Specifically, our DeepTracking-Net starts with optimizing a randomly initialized latent TCD. The TCD is then decoded to regress a continuous flow (i.e. a displacement vector field) which assigns a motion vector to every point of time-varying 3D shapes. Our DeepTracking-Net jointly optimizes TCDs and DNNs' weights towards the minimization of an unsupervised alignment loss. Experiments on both simulated and real data sets demonstrate that our unsupervised DeepTracking-Net outperforms the current supervised state-of-the-art method. In addition, we prepare a new synthetic 3D data, named SynMotions, to the 3D tracking and recognition community.
NuSTAR observations of four nearby X-ray faint AGNs: low luminosity or heavy obscuration?

We present NuSTAR (Nuclear Spectroscopic Telescope Array) observations of four active galactic nuclei (AGNs) located within 15 Mpc. These AGNs, namely ESO 121-G6, NGC 660, NGC 3486, and NGC 5195, have observed X-ray luminosities of L2–10 keV,obs ≲ 1039 erg s−1, classifying them as low-luminosity AGN (LLAGN). We perform broad-band X-ray spectral analysis for the AGN by combining our NuSTAR data with Chandra or XMM–Newton observations to directly measure their column densities (NH) and infer their intrinsic power. We complement our X-ray data with archival and new high-angular resolution mid-infrared (mid-IR) data for all objects, except NGC 5195. Based on our X-ray spectral analysis, we found that both ESO 121-G6 and NGC 660 are heavily obscured (NH > 1023 cm−2; L2–10 keV,int ∼ 1041 erg s−1), and NGC 660 may be Compton thick. We also note that the X-ray flux and spectral slope for ESO 121-G6 have significantly changed over the last decade, indicating significant changes in the obscuration and potentially accretion rate. On the other hand, NGC 3486 and NGC 5195 appear to be unobscured and just mildly obscured, respectively, with L2–10 keV,int < 1039 erg s−1, i.e. genuine LLAGN. Both of the heavily obscured AGNs have Lbol > 1041 erg s−1 and λEdd ≳ 10−3, and are detected in high-angular resolution mid-IR imaging, indicating the presence of obscuring dust on nuclear scale. NGC 3486, however, is undetected in high-resolution mid-IR imaging, and the current data do not provide stringent constraints on the presence or absence of obscuring nuclear dust in the AGN.
Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression

Owing to their statistical properties, non-convex sparse regularizers have attracted much interest for estimating a sparse linear model from high dimensional data. Given that the solution is sparse, for accelerating convergence, a working set strategy addresses the optimization problem through an iterative algorithm by incre-menting the number of variables to optimize until the identification of the solution support. While those methods have been well-studied and theoretically supported for convex regularizers, this paper proposes a working set algorithm for non-convex sparse regularizers with convergence guarantees. The algorithm, named FireWorks, is based on a non-convex reformulation of a recent primal-dual approach and leverages on the geometry of the residuals. Our theoretical guarantees derive from a lower bound of the objective function decrease between two inner solver iterations and shows the convergence to a stationary point of the full problem. More importantly, we also show that convergence is preserved even when the inner solver is inexact, under sufficient decay of the error across iterations. Our experimental results demonstrate high computational gain when using our working set strategy compared to the full problem solver for both block-coordinate descent or a proximal gradient solver.
Monitoring reproductive steroids in feces of Arabian oryx: toward a non-invasive method to predict reproductive status in the wild

Abstract We measured metabolites of progesterone (progestins) in fecal samples collected from captive Arabian oryx (Oryx leucoryx) females in postpartum (n=8), nonpregnant (n=9), and pregnant (n=8) reproductive stages between 1996 and 1998. We analyzed progestins using enzyme-immunoassays for pregnanediol and 20-oxo-pregnanes, respectively. Progestin concentrations were elevated for 3 days after parturition and then decreased to basal anestrous concentrations. Ovarian cyclicity resumed 25±2.4 days after parturition in 5 of the 8 females monitored. In nonpregnant females, excretion of fecal progestins followed a cyclic pattern increasing 6- to 12-fold from the follicular to the luteal phase. Fecal progestin concentrations allowed discrimination between pregnant and nonpregnant females after 3 months of gestation (P<0.01), mean concentration of the tested hormone metabolites being at least 3 times higher during mid and later stages of gestation (>3 months) than during early pregnancy (0–3 months). These data were subsequently used to set criteria for designation of a cow as pregnant in 55 free-ranging Arabian oryx in the reserve of Mahazat as-Sayd, Saudi Arabia sampled in 1998–1999 and 2003. The proportion of pregnant and nonpregnant oryx correctly identified by the test was 81% and 83%, respectively, when using both progestin assays. Despite a limited sample size, our results provide evidence that fecal progestin analysis is a reliable non-invasive method to determine the reproductive status of captive Arabian oryx and that it also can provide reasonably accurate physiological indices of pregnancy status in free-ranging specimens.
Black-box Adaptation of ASR for Accented Speech

We introduce the problem of adapting a black-box, cloud-based ASR system to speech from a target accent. While leading online ASR services obtain impressive performance on main-stream accents, they perform poorly on sub-populations - we observed that the word error rate (WER) achieved by Google's ASR API on Indian accents is almost twice the WER on US accents. Existing adaptation methods either require access to model parameters or overlay an error-correcting module on output transcripts. We highlight the need for correlating outputs with the original speech to fix accent errors. Accordingly, we propose a novel coupling of an open-source accent-tuned local model with the black-box service where the output from the service guides frame-level inference in the local model. Our fine-grained merging algorithm is better at fixing accent errors than existing word-level combination strategies. Experiments on Indian and Australian accents with three leading ASR models as service, show that we achieve as much as 28% relative reduction in WER over both the local and service models.
Rapid elimination of small dust grains in molecular clouds

We argue that impact velocities between dust grains with sizes of less than ∼0.1 μm in molecular cloud cores are dominated by drift arising from ambipolar diffusion. This effect is due to the size dependence of the dust coupling to the magnetic field and the neutral gas. Assuming perfect sticking in collisions up to ≈50 m s−1, we show that this effect causes rapid depletion of small grains, consistent with starlight extinction and IR and microwave emission measurements, both in the core center (n ∼ 106 cm−3) and envelope (n ∼ 104 cm−3). The upper end of the size distribution does not change significantly if only velocities arising from this effect are considered. We consider the impact of an evolved grain-size distribution on the gas temperature, and argue that if the depletion of small dust grains occurs as expected from our model, then the cosmic ray ionization rate must be well below 10−16 s−1 at a number density of 105 cm−3.
Isotopic Evolution of the Inner Solar System Inferred from Molybdenum Isotopes in Meteorites

The fundamentally different isotopic compositions of non-carbonaceous (NC) and carbonaceous (CC) meteorites reveal the presence of two distinct reservoirs in the solar protoplanetary disk that were likely separated by Jupiter. However, the extent of material exchange between these reservoirs, and how this affected the composition of the inner disk, are not known. Here we show that NC meteorites display broadly correlated isotopic variations for Mo, Ti, Cr, and Ni, indicating the addition of isotopically distinct material to the inner disk. The added material resembles bulk CC meteorites and Ca–Al-rich inclusions in terms of its enrichment in neutron-rich isotopes, but unlike the latter materials is also enriched in s-process nuclides. The comparison of the isotopic composition of NC meteorites with the accretion ages of their parent bodies reveals that the isotopic variations within the inner disk do not reflect a continuous compositional change through the addition of CC dust, indicating an efficient separation of the NC and CC reservoirs and limited exchange of material between the inner and outer disk. Instead, the isotopic variations among NC meteorites more likely record a rapidly changing composition of the disk during infall from the Sun’s parental molecular cloud, where each planetesimal locks the instant composition of the disk when it forms. A corollary of this model is that late-formed planetesimals in the inner disk predominantly accreted from secondary dust that was produced by collisions among pre-existing NC planetesimals.