Miracle-dz/UniFAR-FTUs huggingface dataset:
Subspace Locally Competitive Algorithms

We introduce subspace locally competitive algorithms (SLCAs), a family of novel network architectures for modeling latent representations of natural signals with group sparse structure. SLCA first layer neurons are derived from locally competitive algorithms, which produce responses and learn representations that are well matched to both the linear and non-linear properties observed in simple cells in layer 4 of primary visual cortex (area V1). SLCA incorporates a second layer of neurons which produce approximately invariant responses to signal variations that are linear in their corresponding subspaces, such as phase shifts, resembling a hallmark characteristic of complex cells in V1. We provide a practical analysis of training parameter settings, explore the features and invariances learned, and finally compare the model to single-layer sparse coding and to independent subspace analysis.
TWO MOUNTAINS, TWO SPECIES: NEW TAXA OF THE CICADETTA MONTANA SPECIES COMPLEX IN GREECE (HEMIPTERA: CICADIDAE)

On two mountains of Greece (Mt. Olymbos, Mt. Kissavos) in the eastern part of Thessalia, two new species of Cicadettini have been discovered. On Mt. Olymbos Cicadetta olympica sp. n. and on Mt. Kissavos C. kissavi sp. n. – both belonging to the Cicadetta montana species complex. On Mt. Kissavos we acoustically detected also C. montana s. stricto. Both new species have characteristic, species specific song patterns, which differ from all other species of the C. montana species complex. Morphologically however, both new species are very similar to other species of the C. montana species complex and to each other.
Real-time Facial Expression Recognition “In The Wild” by Disentangling 3D Expression from Identity

Human emotions analysis has been the focus of many studies, especially in the field of Affective Computing, and is important for many applications, e.g. human-computer intelligent interaction, stress analysis, interactive games, animations, etc. Solutions for automatic emotion analysis have also benefited from the development of deep learning approaches and the availability of vast amount of visual facial data on the internet. This paper proposes a novel method for human emotion recognition from a single RGB image. We construct a largescale dataset of facial videos (FaceVid), rich in facial dynamics, identities, expressions, appearance and 3D pose variations. We use this dataset to train a deep Convolutional Neural Network for estimating expression parameters of a 3D Morphable Model and combine it with an effective back-end emotion classifier. Our proposed framework runs at 50 frames per second and is capable of robustly estimating parameters of 3D expression variation and accurately recognizing facial expressions from in the-wild images. We present extensive experimental evaluation that shows that the proposed method outperforms the compared techniques in estimating the 3D expression parameters and achieves state-of-the-art performance in recognising the basic emotions from facial images, as well as recognising stress from facial videos.
Effects of Prosodic Focus on Voice Onset Time (VOT) in Chongming Chinese

Prosodic focus is phonetically realized by increasing intensity, extending duration, and expanding pitch rage of focused components (Xu et al., 2012). Previous studies have also found the effect of prosodic focus on enlarging two-way or three-way stop contrast by lengthening the VOT (voice onset time) of voiceless or aspirated consonants (e.g. Choi, 2003; Chen, 2011). The present study investigates the influence of prosodic focus on the realization of VOT of an under-studied language, Chongming Chinese. Twelve monosyllabic words were selected and embedded in carrier sentences with different discourse conditions: one baseline neutral focus condition and three focus conditions. Precursor questions were prepared to elicit production from native speakers of Chongming Chinese. Results showed the significant main effects of stop types and discourse conditions on VOT realization. VOTs were shortened in unaspirated and voiced stops in the on-focus condition, suggesting a different way of expanding the three-way difference in stops. VOT was also affected by other focus conditions, providing implications for the study of focus domain. The study suggests that VOT can serve as acoustic cue for stop contrasts in Chongming Chinese in different prosodic environment and contributes new data to the typology of prosodic focus study as well as stop contrast research.
Bacterial and Fungal Diversity of Quaternary Cave Sediment Deposits

The bacterial and fungal assemblages of clastic sediments collected from two caves located in north-western Romania were investigated by assessing ITS and 16S rRNA gene diversity. Bacterial members belonging to Chloroflexi, Nitrospirae, Proteobacteria, Firmicutes, Acidobacteria, Gemmatimonadetes, and fungal members of Ascomycota were identified. Except for Bacillus sp. , all bacteria were related to uncultured or unknown species and the majority (86%) of the bacterial sequences from one of the caves had no close GenBank relatives. The bacterial sequences obtained clustered with species found in extreme environments. Half of the bacterial operational taxonomic units were clustered with clones isolated from deep subsurface sediments of a radioactively contaminated site in the USA. The present study represents the first attempt to identify microorganisms in Quaternary cave sediments. Supplemental materials are available for this article. Go to the publisher's online edition of Geomicrobiology Journal to view the supplemental file.
The Importance of Selenium Biofortification in Food Crops

Selenium (Se) is an essential element for maintenance of human health. Although it has not been confirmed an essential nutrient in higher plants, there is increasing evidence that Se is a beneficial element for plants, as an antioxidant and a promoter of plant growth. Today, the investigation is directed to elucidate the specific biochemical mechanisms that underlie this positive effect in plants. This ability of some plants to accumulate and transform Se into bioactive compounds has important implications for human nutrition and health. Because Se deficiency is a common problem worldwide, plants are an excellent source of dietary Se than can help to alleviate this problem. It is considered that the beneficial role of Se in human nutrition and health is attributed both to Se compounds and to its presence within selenoproteins; however, it is important to know which Se species are beneficial or detrimental to human nutrition. This review presents the roles of Se in plant and human nutrition; particular attention is paid to the importance of plant Se biochemistry, the strategies to increase Se density in crops by biofortification, the necessity of reaching the correct Se levels through diet and the importance of increased Se to a whole population.
STUDIES ON YEAST ESTERASE

An esterase (carboxylic acid hydrolase EC 3 1.1.1.) has been prepared from Saccharomyces cerevisiae. This esterase is active at pH 4.4 and, though it is unstable in solution, it can be maintained in an active form either by lyophilization or by coupling to an affinity gel. At pH 4.4, yeast esterase can hydrolyse between 20 and 40% of the esters commonly present in beer, and it is capable of synthesizing ethyl acetate from ethanol and acetic acid in a simple buffered solution without the provision of a co-factor. Different yeast strains yield different amounts of esterase, and there appears to be a positive correlation between the ability of the yeast to form esterase and the level of esters present in fermentations accomplished by that yeast.
Radio Observations of Two Intermittent Pulsars: PSRs J1832+0029 and J1841−0500

We present long-term observations of two intermittent pulsars, PSRs J1832+0029 and J1841−0500, using the Parkes 64 m radio telescope. The radio emission for these pulsars switches off for year-long durations. Our new observations have enabled us to improve the determination of the on–off timescales and the spin-down rates during those emission states. In general our results agree with previous studies of these pulsars, but we now have significantly longer data spans. We have identified two unexpected signatures in the data. Weak emission was detected in a single observation of PSR J1832+0029 during an off emission state. For PSR J1841−0500, we identified a quasi-periodic fluctuation in the intensities of the detectable single pulses, with a modulation period between 21 and 36 pulse periods.
A simple superconductor quantum interference device to test gravity

A simple tabletop setup based on a superconductor quantum interference device is proposed to test the gravitational interaction. A D-shaped superconducting loop has the straight segment immersed inside a massive sphere while the half-circle segment is wrapped around the sphere. The superconducting condensate within the straight arm of the loop thus bathes inside a gravitational simple harmonic oscillator potential while the condensate in the half-circle arm bathes in the constant gravitational potential around the sphere. The resulting phase difference at the Josephson junctions on both sides of the straight arm induces a sinusoidal electric current that has a frequency determined by the precise gravitational potential due to the massive sphere.
Comparison of Randomized Solutions for Constrained Vehicle Routing Problem

In this short paper, we study capacity constrained vehicle routing problem (CVRP) and its solution by randomized Monte Carlo methods. For solving CVRP we use some pseudorandom number generators commonly used in practice. We use linear, multiple-recursive, inversive and explicit inversive congruential generators and obtain random numbers from each to provide a route for CVRP. Then we compare the performance of pseudorandom number generators with respect to the total time the random route takes. We also constructed an open-source library github.com/iedmrc/binary-cws-mcs on solving CVRP by Monte-Carlo based heuristic methods.
Upper Bounds on the Generalization Error of Private Algorithms for Discrete Data

In this work, we study the generalization capability of algorithms from an information-theoretic perspective. It has been shown that the expected generalization error of an algorithm is bounded from above by a function of the relative entropy between the conditional probability distribution of the algorithm’s output hypothesis, given the dataset with which it was trained, and its marginal probability distribution. We build upon this fact and introduce a mathematical formulation to obtain upper bounds on this relative entropy. Assuming that the data is discrete, we then develop a strategy using this formulation, based on the method of types and typicality, to find explicit upper bounds on the generalization error of stable algorithms, i.e., algorithms that produce similar output hypotheses given similar input datasets. In particular, we show the bounds obtained with this strategy for the case of <inline-formula> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula>-DP and <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-GDP algorithms.
DiscreTalk: Text-to-Speech as a Machine Translation Problem

This paper proposes a new end-to-end text-to-speech (E2E-TTS) model based on neural machine translation (NMT). The proposed model consists of two components; a non-autoregressive vector quantized variational autoencoder (VQ-VAE) model and an autoregressive Transformer-NMT model. The VQ-VAE model learns a mapping function from a speech waveform into a sequence of discrete symbols, and then the Transformer-NMT model is trained to estimate this discrete symbol sequence from a given input text. Since the VQ-VAE model can learn such a mapping in a fully-data-driven manner, we do not need to consider hyperparameters of the feature extraction required in the conventional E2E-TTS models. Thanks to the use of discrete symbols, we can use various techniques developed in NMT and automatic speech recognition (ASR) such as beam search, subword units, and fusions with a language model. Furthermore, we can avoid an over smoothing problem of predicted features, which is one of the common issues in TTS. The experimental evaluation with the JSUT corpus shows that the proposed method outperforms the conventional Transformer-TTS model with a non-autoregressive neural vocoder in naturalness, achieving the performance comparable to the reconstruction of the VQ-VAE model.
Introduction to a small cancellation theorem

This note is intended as an introduction to two previous works respectively by Dahmani, Guirardel, Osin, and by Cantat, Lamy. We give two proofs of a Small Cancellation Theorem for groups acting on a simplicial tree. We discuss the application to the group of plane polynomial automorphisms over any ground field.
Restricted Chase Termination for Existential Rules: A Hierarchical Approach and Experimentation

Abstract The chase procedure for existential rules is an indispensable tool for several database applications, where its termination guarantees the decidability of these tasks. Most previous studies have focused on the skolem chase variant and its termination analysis. It is known that the restricted chase variant is a more powerful tool in termination analysis provided a database is given. But all-instance termination presents a challenge since the critical database and similar techniques do not work. In this paper, we develop a novel technique to characterize the activeness of all possible cycles of a certain length for the restricted chase, which leads to the formulation of a framework of parameterized classes of the finite restricted chase, called $k$-$\mathsf{safe}(\Phi)$ rule sets. This approach applies to any class of finite skolem chase identified with a condition of acyclicity. More generally, we show that the approach can be applied to the hierarchy of bounded rule sets previously only defined for the skolem chase. Experiments on a collection of ontologies from the web show the applicability of the proposed methods on real-world ontologies.
Gradient-Free Methods for Saddle-Point Problem

In the paper, we generalize the approach Gasnikov et. al, 2017, which allows to solve (stochastic) convex optimization problems with an inexact gradient-free oracle, to the convex-concave saddle-point problem. The proposed approach works, at least, like the best existing approaches. But for a special set-up (simplex type constraints and closeness of Lipschitz constants in 1 and 2 norms) our approach reduces $\frac{n}{\log n}$ times the required number of oracle calls (function calculations). Our method uses a stochastic approximation of the gradient via finite differences. In this case, the function must be specified not only on the optimization set itself, but in a certain neighbourhood of it. In the second part of the paper, we analyze the case when such an assumption cannot be made, we propose a general approach on how to modernize the method to solve this problem, and also we apply this approach to particular cases of some classical sets.
The effect of salivary amylase on the viscosity behaviour of gelatinised starch suspensions and the mechanical properties of gelatinised starch granules

The digestion of gelatinised starch suspensions by salivary amylase was studied using a viscometric assay and also by measuring the mechanical properties of individual granules. Viscosity decay as a function of time was approximately exponential. A comparison with a reducing group assay showed that a 50% fall in viscosity corresponded to the scission of about 0.05% of the glycosidic bonds. The half-time for the reduction of viscosity by the enzyme was found to be proportional to enzyme concentration but independent of starch concentration over a wide concentration range. This result suggests that the starch concentrations used were well below the saturating point for the enzyme, which was thus largely in the free state, and that the enzyme attacked the gelatinised granules throughout their structure rather than just at the surface. Measurements of the forces required to deform individual granules supported this hypothesis by showing that the gelatinised granules lost nearly all their mechanical strength during initial contact with salivary amylase, without any apparent change in diameter.
End-to-End Automatic Sleep Stage Classification Using Spectral-Temporal Sleep Features

Sleep disorder is one of many neurological diseases that can affect greatly the quality of daily life. It is very burdensome to manually classify the sleep stages to detect sleep disorders. Therefore, the automatic sleep stage classification techniques are needed. However, the previous automatic sleep scoring methods using raw signals are still low classification performance. In this study, we proposed an end-to-end automatic sleep staging framework based on optimal spectral-temporal sleep features using a sleep-edf dataset. The input data were modified using a bandpass filter and then applied to a convolutional neural network model. For five sleep stage classification, the classification performance 85.6% and 91.1% using the raw input data and the proposed input, respectively. This result also shows the highest performance compared to conventional studies using the same dataset. The proposed framework has shown high performance by using optimal features associated with each sleep stage, which may help to find new features in the automatic sleep stage method.Clinical Relevance— The proposed framework would help to diagnose sleep disorders such as insomnia by improving sleep stage classification performance
Nutritional Compounds in Figs from the Southern Mediterranean Region

Nutritive value of mature figs (Ficus carica L.) was investigated in five Tunisian cultivars, ‘Bouhouli’ (BHL) and ‘Zidi’ (ZD) (dark skin figs); ‘Thgagli’ (THG), ‘Bidhi’ (BD), and ‘Khedri’ (KHD) (yellow-green skin figs). Sugars, organic acids, fibres, and polyphenols were analysed in representative fruit samples from two distinct regions known to develop fig crops. Tunisian figs were characterized by predominance of glucose (6.30 g/100 g fresh weight) and fructose (5.10 g/100 g fresh weight). Citric acid (0.35 g/100 g fresh weight) was the major organic acid in all cultivars, almost three times higher than malic acid (0.13 g/100 g fresh weight). Average content of alcohol insoluble solids was 3.3 g/100 g FW. Four main polyphenols could be identified: two anthocyanins (cyanidin-3-glucoside; cyanidin-3-rutinoside), one flavonol (rutin), and one hydroxycinnamic acid (5-cafeoylquinic acid), revealed only in ‘BD’ samples. Cyanidin-3-rutinoside was the most abundant compound among all cultivars. Compared to common fruit, figs are among high sugar leveled fruit with significant dietary fibre content. Dark skin ‘ZD’ fruit were the most interesting figs with the highest concentration of sugars, organic acids, and polyphenols, especially cyanidin-3-rutinoside. This cultivar could be better advised for fresh consumption. However, the three lighter cultivars are more suitable for drying.
Max-Consensus Over Fading Wireless Channels

This article deals with the problem of achieving finite-time max-consensus in a multiagent system that communicates over a fading wireless channel. A key feature of the wireless channel is the superposition (or broadcast) property. In traditional wireless communication systems, the superposition property is usually undesired since it might cause interference that drastically degrades system performance. In contrast, in the multiagent system considered in this article, different agents aim at achieving max-consensus. Therefore, rather than combatting interference due to the superposition property, we design a communication system that exploits this property for a more efficient usage of wireless resources. By simultaneously accessing the wireless channel, each agent obtains a weighted average of the neighboring agents’ information states, where weights (namely, channel coefficients) are unknown and fading. Given that each agent has access to this piece of information, we present a switching consensus protocol employing broadcast authorization for agents and show that max-consensus can be achieved under this protocol within a finite number of iterations.
Solar Bayesian Analysis Toolkit—A New Markov Chain Monte Carlo IDL Code for Bayesian Parameter Inference

We present the Solar Bayesian Analysis Toolkit (SoBAT), which is a new easy to use tool for Bayesian analysis of observational data, including parameter inference and model comparison. SoBAT is aimed (but not limited) to be used for the analysis of solar observational data. We describe a new IDL code designed to facilitate the comparison of a user-supplied model with data. Bayesian inference allows prior information to be taken into account. The use of Markov Chain Monte Carlo sampling allows efficient exploration of large parameter spaces and provides reliable estimation of model parameters and their uncertainties. The Bayesian evidence for different models can be used for quantitative comparison. The code is tested to demonstrate its ability to accurately recover a variety of parameter probability distributions. Its application to practical problems is demonstrated using studies of the structure and oscillation of coronal loops.
Constraints on the spin-pole orientation, jet morphology, and rotation of interstellar comet 2I/Borisov with deep HST imaging

We present high resolution, deep imaging of interstellar comet 2I/Borisov taken with the Hubble Space Telescope/Wide Field Camera 3 (HST/WFC3) on 2019 December 8 UTC and 2020 January 27 UTC (HST GO 16040, PI: Bolin) before and after its perihelion passage in combination with HST/WFC3 images taken on 2019 October 12 UTC and 2019 November 16 UTC (HST GO/DD 16009, PI: Jewitt) before its outburst and fragmentation of 2020 March, thus observing the comet in a relatively undisrupted state. We locate 1–2 arcsec long (2000–3000 km projected length) jet-like structures near the optocentre of 2I that appear to change position angles from epoch to epoch. With the assumption that the jet is located near the rotational pole supported by its stationary appearance on ∼10–100 h time frames in HST images, we determine that 2I’s pole points near α = 322 ± 10° and δ = 37 ± 10° (λ = 341° and β = 48°) and may be in a simple rotation state. Additionally, we find evidence for possible periodicity in the HST time-series light curve on the time-scale of ∼5.3 h with a small amplitude of ∼0.05 mag implying a lower limit on its b/a ratio of ∼1.5 unlike the large ∼2 mag light curve observed for 1I/‘Oumuamua. However, these small light-curve variations may not be the result of the rotation of 2I’s nucleus due to its dust-dominated light-scattering cross-section. Therefore, uniquely constraining the pre-Solar system encounter, pre-outburst rotation state of 2I may not be possible even with the resolution and sensitivity provided by HST observations.