Miracle-dz/UniFAR-FTUs huggingface dataset:
Biology of marine birds

Seabirds in the Marine Environment, E.A. Schreiber and J. Burger The Fossil Seabird Fossil Record and the Role of Paleontology in Understanding Seabird Community Structure, K.I. Warheit Seabird Systematics and Distribution: A Review of Current Knowledge, M. de L. Brooke Colonial Breeding in Seabirds, J.C. Coulson Seabird Demography and Its Relationship with the Marine Environment, H. Weimerskirch Foraging Behavior and Food of Seabirds, D.A. Shealer Climate and Weather Effects on Seabirds, E.A. Schreiber Breeding Biology, Life Histories and Life History-Environment Interactions in Seabirds, K.C. Hamer, E.A. Schreiber, and J. Burger Site and Mate Choice in Seabirds: An Evolutionary Approach, J. Bried and P. Jouventin Seabird Communication and Displays, J.B. Nelson and P.H. Baird Energetics of Free-Ranging Seabirds, H.I. Ellis and G.W. Gabrielson Seabird Reproductive Physiology and Energetics, G.C. Whittow Chick Growth and Development in Seabirds, G.H. Visser Water and Salt Balance in Seabirds, D.L. Goldstein Effects of Chemicals and Pollution on Seabirds, J. Burger and M. Gochfeld Interactions Between Fisheries and Seabirds, W.A. Montevecchi Seabird Conservation, P.D. Boersma, J.A. Clark, and N. Hilgarth Shorebirds in the Marine Environment, N. Warnock, M.A. Rubega, and C. Elphick Wading Birds in the Marine Environment, P.C. Frederick Appendix 1: List of Seabird Species Appendix 2: Table of Seabird Species and Life History Characteristics Index
VALES VI: ISM enrichment in star-forming galaxies up to z ∼ 0.2 using 12CO(1–0), 13CO(1–0), and C18O(1–0) line luminosity ratios

We present Atacama Large Millimeter/sub-millimeter Array (ALMA) observations towards 27 low-redshift (0.02 < z < 0.2) star-forming galaxies taken from the Valparaíso ALMA/APEX Line Emission Survey. We perform stacking analyses of the 12CO(1–0), 13CO(1–0), and C18O(1–0) emission lines to explore the L′ [12CO(1–0)]/L′ [13CO(1–0)] [hereafter L′ (12CO)/L′ (13CO)] and L′ [13CO(1–0)]/L′ [C18O(1–0)] [hereafter L′ (13CO)/L′ (C18O)] line luminosity ratio dependence as a function of different global galaxy parameters related to the star formation activity. The sample has far-IR luminosities of $10^{10.1\! -\! 11.9}\,$ L⊙ and stellar masses of 109.8–10.9 M⊙ corresponding to typical star-forming and starburst galaxies at these redshifts. On average, we find an L′ (12CO)/L′ (13CO) line luminosity ratio value of 16.1 ± 2.5. Galaxies with pieces of evidence of possible merging activity tend to show higher L′ (12CO)/L′ (13CO) ratios by a factor of 2, while variations of this order are also found in galaxy samples with higher star formation rates (SFRs) or star formation efficiencies (SFEs). We also find an average L′ (13CO)/L′ (C18O) line luminosity ratio of 2.5 ± 0.6, which is in good agreement with those previously reported for starburst galaxies. We find that galaxy samples with high LIR, SFR, and SFE show low L′ (13CO)/L′ (C18O) line luminosity ratios with high L′ (12CO)/L′ (13CO) line luminosity ratios, suggesting that these trends are produced by selective enrichment of massive stars in young starbursts.
Adversarial Example Games

The existence of adversarial examples capable of fooling trained neural network classifiers calls for a much better understanding of possible attacks to guide the development of safeguards against them. This includes attack methods in the challenging non-interactive blackbox setting, where adversarial attacks are generated without any access, including queries, to the target model. Prior attacks in this setting have relied mainly on algorithmic innovations derived from empirical observations (e.g., that momentum helps), lacking principled transferability guarantees. In this work, we provide a theoretical foundation for crafting transferable adversarial examples to entire hypothesis classes. We introduce Adversarial Example Games (AEG), a framework that models the crafting of adversarial examples as a min-max game between a generator of attacks and a classifier. AEG provides a new way to design adversarial examples by adversarially training a generator and a classifier from a given hypothesis class (e.g., architecture). We prove that this game has an equilibrium, and that the optimal generator is able to craft adversarial examples that can attack any classifier from the corresponding hypothesis class. We demonstrate the efficacy of AEG on the MNIST and CIFAR-10 datasets, outperforming prior state-of-the-art approaches with an average relative improvement of $29.9\%$ and $47.2\%$ against undefended and robust models (Table 2 & 3) respectively.
A Complex C Region Genotype [? R] that with G B vlae Produces Dark Seal-brown Seedcoat Color in Common Bean

Common bean (Phaseolus vulgaris L.) plant introduction 527829 (formerly Lamprecht M0048) has dark seal- brown (DSB) seedcoats and pink flowers. An investigation was conducted to determine the genotype of DSB seedcoat color. M0048 was crossed with Florida breeding line 5-593, which has genotype P (C r) D J G B V Rk. A series of crosses involving M0048, 5-593, and three genetic tester stocks ( v BC 2 5-593, c u BC 2 5-593, and b v BC 2 5-593) led to determination of the genotype. Data analysis indicated that M0048 has the genotype P (? R) J G B vlae , where DSB color is produced by the interaction of R with B. Crosses between (? R ) and testers with (C r) always produced seedcoat mottling in F 1 , except where V masks the effect. The cross ( ? R) B v (DSB) x cu BC 2 5-593 (cartridge buff seedcoat) produced marbled seedcoats (black/ cartridge buff) with genotype (? R)/(cu ? ) B V. No way was found to determine whether the mottled or marbled seedcoat patterns were controlled at C or R; hence, the allelic ambiguity is indicated with a question mark. Illustrations are provided showing the difference between seedcoat mottling (a highly variable low-contrast patterning) and seedcoat marbling (a less variable high-contrast patterning, usually with cartridge buff as the background color). The development of a new genetic tester stock, ( ? R) b v BC 3 5-593, was described, where (? R) b v gives unpatterned dominant red seedcoat color.
Efficient Hybrid Beamforming With Anti-Blockage Design for High-Speed Railway Communications

Future railway is expected to accommodate both train operation services and passenger broadband services. The millimeter wave (mmWave) communication is a promising technology in providing multi-gigabit data rates to onboard users. However, mmWave communications suffer from severe propagation attenuation and vulnerability to blockage, which can be very challenging in high-speed railway (HSR) scenarios. In this paper, we investigate efficient hybrid beamforming (HBF) design for train-to-ground communications. First, we develop a two-stage HBF algorithm in blockage-free scenarios. In the first stage, the minimum mean square error method is adopted for optimal hybrid beamformer design with low complexity and fast convergence; in the second stage, the orthogonal matching pursuit method is utilized to approximately recover the analog and digital beamformers. Second, in blocked scenarios, we design an anti-blockage scheme by adaptively invoking the proposed HBF algorithm, which can efficiently deal with random blockages. Extensive simulation results are presented to show the sum rate performance of the proposed algorithms under various configurations, including transmission power, velocity of the train, blockage probability, etc. It is demonstrated that the proposed anti-blockage algorithm can improve the effective rate by 20$\%$ in severely-blocked scenarios while maintaining low outage probability.
Deep Learning Methods for Universal MISO Beamforming

This letter studies deep learning (DL) approaches to optimize beamforming vectors in downlink multi-user multi-antenna systems that can be universally applied to arbitrarily given transmit power limitation at a base station. We exploit the sum power budget as side information so that deep neural networks (DNNs) can effectively learn the impact of the power constraint in the beamforming optimization. Consequently, a single training process is sufficient for the proposed universal DL approach, whereas conventional methods need to train multiple DNNs for all possible power budget levels. Numerical results demonstrate the effectiveness of the proposed DL methods over existing schemes.
Studies on Genetic Characteristics of Pigeon Pea Germplasm at Otobi, Benue State of Nigeria

A three-year study was conducted during the growing season of 2002, 2003 and 2004 at the National Root Crops Research Institute Sub-station, Otobi (07° 10 N, 08° 39 E, 105.1m elevation) located in Southern 11 Guinea Savanna agro-ecological zone of Nigeria. The study was conducted to evaluate 29 new pigeon pea genotypes and a local variety for genetic variability, character association and path coefficients among the yield and yield component traits. The experiment was laid out in a Randomized Complete Block Design with three replications. The results indicated that the genotypes showed significant variability for all the traits studied. The phenotypic coefficient of variability and genotypic coefficient of variability were relatively high for number of pods per plant, dry pod weight, dry grain yield and number of primary branches. Phenotypic coefficient of variability and genotypic coefficient of variability were generally moderate for days to 50% flowering, days to maturity and plant height. Heritability (broad sense) was generally high for all the traits with exception of number of seeds per pod (0.58). Relatively high expected genetic advance was obtained for number of branches per plant (58.26%), number of pods per plants (161.84%), dry pod weight (68.48%) and dry grain yield (82.65%). High heritability and expected genetic advance in these traits indicated the presence of additive gene effects. Dry grain yield (t ) showed significant positive association with dry pod weight (0.87) and number of primary ha branches (r = 0.14). The results also revealed the presence of significant negative relationship between dry grain yield and days to 50% flowering (r =-0.14) and days to maturity (r =-0.25). The path coefficient revealed that dry pod weight gave the highest direct effect on dry grain yield (0.84171), followed by pod length (0.05440) and number of pods per plant (0.04605). In this study dry pod weight, pod lengthand number of pods have been identified as selection criteria for obtaining good parental lines in a pigeon pea breeding program.
Effect of uniaxial stress on the electronic band structure of NbP

The Weyl semimetal NbP exhibits a very small Fermi surface consisting of two electron and two hole pockets, whose fourfold degeneracy in $k$ space is tied to the rotational symmetry of the underlying tetragonal crystal lattice. By applying uniaxial stress, the crystal symmetry can be reduced, which successively leads to a degeneracy lifting of the Fermi-surface pockets. This is reflected by a splitting of the Shubnikov--de Haas frequencies when the magnetic field is aligned along the $c$ axis of the tetragonal lattice. In this study, we present the measurement of Shubnikov--de Haas oscillations of single-crystalline NbP samples under uniaxial tension, combined with state-of-the-art calculations of the electronic band structure. Our results show qualitative agreement between calculated and experimentally determined Shubnikov--de Haas frequencies, demonstrating the robustness of the band-structure calculations upon introducing strain. Furthermore, we predict a significant shift of the Weyl points with increasing uniaxial tension, allowing for an effective tuning to the Fermi level at only 0.8% of strain along the $a$ axis.
Natural variation and QTL analysis for cationic mineral content in seeds of Arabidopsis thaliana

Naturally occurring genetic variation for contents of cationic minerals in seeds of Arabidopsis thaliana was studied by screening a series of accessions (ecotypes) for Ca, Fe, K, Mg, Mn, Na, Zn, and for total contents of P. Variation was observed for all minerals and correlations between contents of various minerals were present, most noticeably between Ca and Mg, P and Mg, and P and Mn. The genetic basis of this variation was further studied by QTL analysis, using the Landsberg erecta (L er ) ¥ Cape Verde Islands (Cvi) recombinant inbred population. For all minerals, except Na, one or more QTL were detected, explaining up to 78% of the variation. The map positions of several QTL were confirmed by analysis of near isogenic lines, carrying small Cvi introgressions in L er background. Interesting co-locations of QTL suggest pleiotropic effects, due to physiological coupling of the accumulation of certain minerals or to linkage of different genes. By comparing the map positions of QTL with the positions of genes expected to play a role in cation translocation, several candidate genes are suggested.
On Beltrami states near black hole event horizon

In this article, we study Beltrami equilibria for plasmas in near the horizon of a spinning black hole, and develop a framework for constructing the magnetic field profile in the near horizon limit for Clebsch flows in the single-fluid approximation. We find that the horizon profile for the magnetic field is shown to satisfy a system of first-order coupled ODEs dependent on a boundary condition for the magnetic field. For states in which the generalized vorticity vanishes (the generalized `superconducting' plasma state), the horizon profile becomes independent of the boundary condition, and depend only on the thermal properties of the plasma. Our analysis makes use of the full form for the time-independent Ampere's law in the 3+1 formalism, generalizing earlier conclusions for the case of vanishing vorticity, namely the complete magnetic field expulsion near the equator of an axisymmetric black horizon assuming that the thermal properties of the plasma are symmetric about the equatorial plane. For the general case, we find and discuss additional conditions required for the expulsion of magnetic fields at given points on the black hole horizon. We perform a length scale analysis which indicates the emergence of two distinct length scales characterizing the magnetic field variation and strength of the Beltrami term, respectively.
The Fyodorov-Hiary-Keating Conjecture. I

By analogy with conjectures for random matrices, Fyodorov-Hiary-Keating and Fyodorov-Keating proposed precise asymptotics for the maximum of the Riemann zeta function in a typical short interval on the critical line. In this paper, we settle the upper bound part of their conjecture in a strong form. More precisely, we show that the measure of those $T \leq t \leq 2T$ for which $$ \max_{|h| \leq 1} |\zeta(1/2 + i t + i h)| > e^y \frac{\log T }{(\log\log T)^{3/4}}$$ is bounded by $Cy e^{-2y}$ uniformly in $y \geq 1$. This is expected to be optimal for $y= O(\sqrt{\log\log T})$. This upper bound is sharper than what is known in the context of random matrices, since it gives (uniform) decay rates in $y$. In a subsequent paper we will obtain matching lower bounds.
Attention-Oriented Action Recognition for Real- Time Human-Robot Interaction

Despite the notable progress made in action recognition tasks, not much work has been done in action recognition specifically for human-robot interaction. In this paper, we deeply explore the characteristics of the action recognition task in interaction scenes and propose an attention-oriented multi-level network framework to meet the need for real-time interaction. Specifically, a Pre-Attention network is employed to roughly focus on the interactor in the scene at low resolution firstly and then perform fine-grained pose estimation at high resolution. The other compact CNN receives the extracted skeleton sequence as input for action recognition, utilizing attention-like mechanisms to capture local spatial-temporal patterns and global semantic information effectively. To evaluate our approach, we construct a new action dataset specially for the recognition task in interaction scenes. Experimental results on our dataset and high efficiency (112 fps at 640 x 480 RGBD) on the mobile computing platform (Nvidia Jetson AGX Xavier) demonstrate excellent applicability of our method on action recognition in real-time human-robot interaction.
Unsupervised Landmark Learning from Unpaired Data

Recent attempts for unsupervised landmark learning leverage synthesized image pairs that are similar in appearance but different in poses. These methods learn landmarks by encouraging the consistency between the original images and the images reconstructed from swapped appearances and poses. While synthesized image pairs are created by applying pre-defined transformations, they can not fully reflect the real variances in both appearances and poses. In this paper, we aim to open the possibility of learning landmarks on unpaired data (i.e. unaligned image pairs) sampled from a natural image collection, so that they can be different in both appearances and poses. To this end, we propose a cross-image cycle consistency framework ($C^3$) which applies the swapping-reconstruction strategy twice to obtain the final supervision. Moreover, a cross-image flow module is further introduced to impose the equivariance between estimated landmarks across images. Through comprehensive experiments, our proposed framework is shown to outperform strong baselines by a large margin. Besides quantitative results, we also provide visualization and interpretation on our learned models, which not only verifies the effectiveness of the learned landmarks, but also leads to important insights that are beneficial for future research.
Inverse stellar population age gradients of post-starburst galaxies at z = 0.8 with LEGA-C

We use deep, spatially resolved spectroscopy from the Large Early Galaxy Astrophysics Census Survey to study radial variations in the stellar population of 17 spectroscopically selected post-starburst (PSB) galaxies. We use spectral fitting to measure two Lick indices, H δA and Fe 4383 , and find that, on average, PSB galaxies have radially decreasing H δA and increasing Fe 4383 profiles. In contrast, a control sample of quiescent, non-PSB galaxies in the same mass range shows outwardly increasing H δA and decreasing Fe 4383 . The observed gradients are weak (≈−0.2 Å/Re), mainly due to seeing convolution. A two-SSP (simple stellar population) model suggests that intrinsic gradients are as strong as observed in local PSB galaxies (≈−0.8 Å/Re). We interpret these results in terms of inside-out growth (for the bulk of the quiescent population) versus star formation occurring last in the centre (for PSB galaxies). At z ≈ 0.8, central starbursts are often the result of gas-rich mergers, as evidenced by the high fraction of PSB galaxies with disturbed morphologies and tidal features (40 per cent). Our results provide additional evidence for multiple paths to quiescence: a standard path, associated with inside-out disc formation and with gradually decreasing star formation activity, without fundamental structural transformation, and a fast path, associated with centrally concentrated starbursts, leaving an inverse age gradient and smaller half-light radius.
Viability and activity of bifidobacteria in yoghurt containing fructooligosaccharide during refrigerated storage

Summary The viability of yoghurt bacteria and two commercial strains of bifidobacteria was assessed in either yoghurt containing chicory fructooligosaccharide (FOS) or without any prebiotic, during 28 days storage at 4 °C. All the products showed a decrease in the viable count of yoghurt bacteria and bifidobacteria during storage. Numbers of Lactobacillus delbrueckii ssp. bulgaricus decreased faster than those for Streptococcus thermophilus. The viability of bifidobacteria in yoghurt was affected by the strain type and the presence of FOS. Bifidobacterium animalis exhibited better stability in the yoghurt than B. longum. The recommended level of 1 million cells was exceeded for B. animalis throughout storage. The highest viable number of bifidobacteria (3.59–2.25 × 107 CFU g−1) was obtained in the product containing B. animalis and FOS. Viability of B. longum in yoghurt containing FOS remained above 106 CFU g−1 for up to 21 days, whereas this level was maintained for only 7 days for that organism in yoghurt without any prebiotic.
Robust Learning against Logical Adversaries

Test-time adversarial attacks have posed serious challenges to the robustness of machine learning models, and in many settings the adversarial manipulation needs not be bounded by small $\ell_p$-norms. Motivated by semantic-preserving attacks in security domain, we investigate logical adversaries, a broad class of attackers who create adversarial examples within a reflexive-transitive closure of a logical relation. We analyze the conditions for robustness and propose normalize-and-predict -- a learning framework with provable robustness guarantee. We compare our approach with adversarial training and derive a unified framework that provides the benefits of both approaches.Driven by the theoretical findings, we apply our framework to malware detection. We use our framework to learn new detectors and propose two generic logical attacks to validate model robustness. Experiment results on real-world data set show that attacks using logical relations can evade existing detectors, and our unified framework can significantly enhance model robustness.
STNN: A Spatio-Temporal Neural Network for Traffic Predictions

Traffic is very important to route planning and people’s daily lives. Traffic prediction is still very challenging as it is affected by many complex factors including dynamic spatio-temporal dependencies and external factors (e.g., road types and nearby points of interest) in the road network. Dynamic spatio-temporal dependencies simultaneously contain spatial and temporal dependencies. Existing models for predicting traffic of links only consider the spatial dependencies from the perspective of links or the whole road network by ignoring the spatial dependencies among regions. To this end, this paper proposes a new Spatio-Temporal Neural Network (STNN) with the encoder-decoder architecture to improve the accuracy of traffic predictions by additionally taking into account the region-based spatial dependencies and external factors. Specifically, STNN learns dynamic spatio-temporal dependencies from historical traffic time series via an encoder in the perspective of the road network, with two spatial models, i.e., region-based spatial model and link-based spatial attention model in the perspectives of regions and links, respectively. Further, STNN decodes the output from the encoder via a decoder with a temporal attention model for recording long-term dependencies and fuses external factors in the road network, to improve network-wide traffic predictions. We conduct extensive experiments to evaluate the performance of STNN on three real-world traffic datasets, which shows that STNN is significantly better than the state-of-the-art models.