Miracle-dz/UniFAR-FTUs huggingface dataset:
The extended Baryon Oscillation Spectroscopic Survey: a cosmological forecast

We present a science forecast for the extended Baryon Oscillation Spectroscopic Survey (eBOSS) survey. Focusing on discrete tracers, we forecast the expected accuracy of the baryonic acoustic oscillation (BAO), the redshift-space distortion (RSD) measurements, the fNL parameter quantifying the primordial non-Gaussianity, the dark energy and modified gravity parameters. We also use the line-of-sight clustering in the Lyman a forest to constrain the total neutrino mass. We find that eBOSS luminous red galaxies, emission line galaxies and clustering quasars can achieve a precision of 1, 2.2 and 1.6 per cent, respectively, for spherically averaged BAO distance measurements. Using the same samples, the constraint on fob is expected to be 2.5, 3.3 and 2.8 per cent, respectively. For primordial non-Gaussianity, eBOSS alone can reach an accuracy of a (f(NL)) similar to 10-15. eBOSS can at most improve the dark energy figure of merit by a factor of 3 for the Chevallier-Polarski-Linder parametrization, and can well constrain three eigenmodes for the general equation-of-state parameter. eBOSS can also significantly improve constraints on modified gravity parameters by providing the RSD information, which is highly complementary to constraints obtained from weak lensing measurements. A principal component analysis shows that eBOSS can measure the eigenmodes of the effective Newton's constant to 2 per cent precision; this is a factor of 10 improvement over that achievable without eBOSS. Finally, we derive the eBOSS constraint (combined with Planck, Dark Energy Survey and BOSS) on the total neutrino mass, sigma (Em(upsilon)) = 0.03 eV (68 per cent CL), which in principle makes it possible to distinguish between the two scenarios of neutrino mass hierarchies.
From Text Representation to Financial Market Prediction: A Literature Review

News dissemination in social media causes fluctuations in financial markets. (Scope) Recent advanced methods in deep learning-based natural language processing have shown promising results in financial market analysis. However, understanding how to leverage large amounts of textual data alongside financial market information is important for the investors’ behavior analysis. In this study, we review over 150 publications in the field of behavioral finance that jointly investigated natural language processing (NLP) approaches and a market data analysis for financial decision support. This work differs from other reviews by focusing on applied publications in computer science and artificial intelligence that contributed to a heterogeneous information fusion for the investors’ behavior analysis. (Goal) We study various text representation methods, sentiment analysis, and information retrieval methods from heterogeneous data sources. (Findings) We present current and future research directions in text mining and deep learning for correlation analysis, forecasting, and recommendation systems in financial markets, such as stocks, cryptocurrencies, and Forex (Foreign Exchange Market).
Expert Systems With Applications

Stock price prediction and modeling demonstrate high economic value in the financial market. Due to the non-linearity and volatility of stock prices and the unique nature of financial transactions, it is essential for the prediction method to ensure high prediction performance and interpretability. However, existing methods fail to achieve both the two goals simultaneously. To fill this gap, this paper presents an interpretable intuitionistic fuzzy inference model, dubbed as IIFI. While retaining the prediction accuracy, the interpretable module in IIFI can automatically calculate the feature contribution based on the intuitionistic fuzzy set, which provides high interpretability of the model. Also, most of the existing training algorithms, such as LightGBM, XGBoost, DNN, Stacking, etc, can be embedded in the inference module of our proposed model and achieve better prediction results. The back-test experiment on China’s A-share market shows that IIFI achieves superior performance — the stock profitability can be increased by more than 20% over the baseline methods. Meanwhile, interpretable results show that IIFI can effectively distinguish between important and redundant features via rating corresponding scores to each feature. As a byproduct of our interpretable methods, the scores over features can be used to further optimize the investment strategy.
Low distortion embeddings into Asplund Banach spaces

We give a simple example of a countable metric space $M$ that does not embed bi-Lipschitz with distortion strictly less than 2 into any Asplund space. Actually, if $M$ embeds with distortion strictly less than 2 to a Banach space $X$, then $X$ contains an isomorphic copy of $\ell_1$. We also show that the space $M$ does not embed with distortion strictly less than $2$ into $\ell_1$ itself but it does embed isometrically into a space that is isomorphic to $\ell_1$.
An Investigation on the Effect of Actuation Pattern on the Power Consumption of Legged Robots for Extraterrestrial Exploration

Legged robots have great potential to be extraterrestrial exploration rovers of extraordinary versatility. Minimizing power consumption is of vital importance in the scenarios of extraterrestrial explorations. The actuation pattern, which refers to the combination of necessary actuators that output torque, has a significant influence on the power consumption of legged robots. This article seeks to investigate the effect of actuation patterns on the power consumption of legged robots that perform motion in a quasi-static manner. The power consumption model of legged robots considering actuation patterns is deduced. Based on that, the effect of the actuation pattern on mechanical power and heat power, which are the main power-loss terms, is investigated. The lowest power consumption under various conditions achieved by different actuation patterns is investigated. Simulation results show that the power consumption can be reduced by choosing the actuation pattern properly. Furthermore, the principles of selecting the optimal actuation pattern from the perspective of power consumption are summarized, which are expected to facilitate the minimal power consumption motion planning of legged robots.
Potentially Inappropriate Medication Use among Nursing Home Residents: Medication Errors Associated with Pro re nata Medications and the Importance of Pill Burden

Background The use of potentially inappropriate medications (PIM) has become more common among nursing home residents (NHR). This study focused on drugs initially prescribed as pro re nata (PRN) medications and pill burden in association with PIM among NHR. Methods This observational cross-sectional study was conducted between March and April 2019 on 225 adult NHR aged ≥60 years. Results The prevalence of PIM was 47.6% among NHR according to the Screening Tool of Older Persons' Prescriptions (STOPP) criteria version 2. The most frequent PIM was the use of any drug prescribed without evidence-based clinical indication; most medication errors were associated with PRN medications. The prevalence rates of PRN in non-PIM and PIM users were 12% and 62.4%, respectively. PRN medications that most commonly caused PIM were non-steroidal anti-inflammatory drugs and proton pump inhibitors. The cut-off value for both medications and pills to correctly identify participants with PIM was 5.5. Pill burden had a similar sensitivity to polypharmacy in identifying individuals with PIM. Conclusion Medication errors associated with PRN medications were overlooked as factors that increased the risk of PIMs. The most common error related to PRN medications was the continued daily use despite symptom resolution.
Quantum Corrections for a Bardeen Regular Black Hole

In this paper, we study the quantum corrections to the thermodynamical quantities (temperature and entropy) for a Bardeen charged regular black hole by using a quantum tunneling approach over semiclassical approximations. Taking into account the quantum effects, the semiclassical Bekenstein-Hawking temperature and the area law are obtained, which are then used in the first law of thermodynamics to evaluate corrections to these quantities. It is interesting to mention here that these corrections reduce to the corresponding corrections for the Schwarzschild black hole when the charge $e=0$.
Geometry of principal sheaves

The book provides a detailed introduction to the theory of connections on principal sheaves in the framework of Abstract Differential Geometry (ADG). This is a new approach to differential geometry based on sheaf theoretic methods, without use of ordinary calculus. This point of view complies with the demand of contemporary physics to cope with non-smooth models of physical phenomena and spaces with singularities. Starting with a brief survey of the required sheaf theory and cohomology, the exposition then moves on to differential triads (the abstraction of smooth manifolds) and Lie sheaves of groups (the abstraction of Lie groups). Having laid the groundwork, the main part of the book is devoted to the theory of connections on principal sheaves, incorporating connections on vector and associated sheaves. Topics such as the moduli sheaf of connections, classification of principal sheaves, curvature, flat connections and flat sheaves, Chern-Weil theory, are also treated. The study brings to light fundamental notions and tools of the standard differential geometry which are susceptible of the present abstraction, and whose role remains unexploited in the classical context, because of the abundance of means therein. However, most of the latter are nonsensical in ADG.
Jellyfish Polysaccharides for Wound Healing Applications

Jellyfishes are considered a new potential resource in food, pharmaceutical and biomedical industries. In these latter cases, they are studied as source of active principles but are also exploited to produce marine collagen. In the present work, jellyfish skin polysaccharides (JSP) with glycosaminoglycan (GAG) features were extracted from Rhizostoma pulmo, a main blooming species of Mediterranean Sea, massively augmented by climate leaded “jellyfishication” of the sea. Two main fractions of R. pulmo JSP (RP-JSPs) were isolated and characterized, namely a neutral fraction (RP-JSP1) and a sulphate rich, negatively charged fraction (RP-JSP2). The two fractions have average molecular weights of 121 kDa and 590 kDa, respectively. Their sugar composition was evaluated through LC-MS analysis and the result confirmed the presence of typical GAG saccharides, such as glucose, galactose, glucosamine and galactosamine. Their use as promoters of wound healing was evaluated through in vitro scratch assay on murine fibroblast cell line (BALB/3T3 clone A31) and human keratinocytes (HaCaT). Both RP-JSPs demonstrated an effective confluency rate activity leading to 80% of scratch repair in two days, promoting both cell migration and proliferation. Additionally, RP-JSPs exerted a substantial protection from oxidative stress, resulting in improved viability of treated fibroblasts exposed to H2O2. The isolated GAG-like polysaccharides appear promising as functional component for biomedical skin treatments, as well as for future exploitation as pharmaceutical excipients.
Chern pump: a bridge between integer quantum Hall effect and quantum spin Hall effect

We propose a electron-pumping mechanism called Chern pump to explain the integer quantum Hall effect(IQHE) in the Chern insulator. By using the parallel transport gauge in the hybrid Wannier representation we establish the bulk and edge states correspondence in the Chern insulator. The same correspondence can also be established in two dimensional(2D) topological insulator(TI). So we can consider 2D TI as two time reversal(TR) related CIs put together. The quantum spin Hall effect(QSHE) can be viewed as two TR related Chern pumps pumping electrons to opposite directions. Compared with the Z2 spin pump, the two Chern pumps explanation of QSHE is inherently 2D and predict that the QSHE can be detected in isolated device, thus make the QSHE directly measurable.
G 10.472+0.027: AN EXTREME WATER MASER OUTFLOW ASSOCIATED WITH A MASSIVE PROTOSTELLAR CLUSTER

An Australia Telescope Compact Array search for 22 GHz water masers toward 6.7 GHz class II methanol masers detected in the Methanol Multibeam survey has resulted in the detection of extremely high-velocity emission from one of the sources. The water maser emission associated with this young stellar object covers a velocity span of nearly 300 km s−1. The highest velocity water maser emission is redshifted from the systemic velocity by 250 km s−1, which is a new record for high-mass star formation regions. The maser is associated with a very young late O, or early B star, which may still be actively accreting matter (and driving the extreme outflow). If that is the case, future observations of the kinematics of this water maser will provide a unique probe of accretion processes in the highest mass young stellar objects and test models of water maser formation.
Evidence for Bolgiano-Obukhov scaling in rotating stratified turbulence using high-resolution direct numerical simulations

We report results on rotating stratified turbulence in the absence of forcing and with large-scale isotropic initial conditions using direct numerical simulations computed on grids of up to 40963 points. The Reynolds and Froude numbers are, respectively, equal to Re = 5.4 × 104 and Fr = 0.0242. The ratio of the Brunt-Vaisala to the inertial wave frequency, N/f, is taken to be equal to 4.95, a choice appropriate to model the dynamics of the southern abyssal ocean at mid latitudes. This gives a global buoyancy Reynolds number RB = ReFr2 ≈ 32, a value sufficient for some isotropy to be recovered in the small scales beyond the Ozmidov scale, but still moderate enough that the intermediate scales where waves are prevalent are well resolved. We concentrate on the large-scale dynamics, for which we find a spectrum compatible with the Bolgiano-Obukhov scaling. This scaling is also found for geostrophically balanced initial conditions on a run at a lower resolution and hence lower RB ≈ 4. Furthermore, we confirm t.
A Review of the Biological Mechanisms of Dexmedetomidine for Postoperative Neurocognitive Disorders

Postoperative neurocognitive disorders are common neurological complications following surgery that are generally characterized by varying degrees of cognitive impairment. Postoperative neurocognitive disorders can exhibit as short-term postoperative delirium and/or long-term postoperative cognitive dysfunction. In addition, postoperative neurocognitive disorders may result in poor outcomes in patients, and are a leading cause of postoperative morbidity and mortality, particularly in elderly patients. Recently, there has been a heightened interest in mechanisms and clinical treatments for postoperative neurocognitive disorders. Though some influencing factors and mechanisms of postoperative neurocognitive disorders have been revealed, they remain troublesome problems in clinical departments. Dexmedetomidine is a commonly used anesthetic adjuvant that may help improve postoperative cognitive impairment, especially the conditions of a postoperative acute event (postoperative delirium, within 1 week after operation) and delayed neurocognitive recovery (postoperative cognitive dysfunction, up to 30 days). In the recent literature, dexmedetomidine has been shown to exert positive effects on cognitive impairment in clinical and animal studies, especially for postoperative neurocognitive disorders. However, not all clinical findings support this efficacy. Though some mechanisms of dexmedetomidine on postoperative neurocognitive disorders have been proposed, such as signaling pathways associated with inflammation and apoptosis, this evidence is fragmentary and disputed in the literature. Therefore, this article aims to review the potential biological mechanisms underlying dexmedetomidine’s effects on postoperative neurocognitive disorders, providing a reference for future studies.
A Few Binary Star Puzzles for Roberto on the Occasion of His Birthday

Abstract Radial-velocity observations accumulated during the past 16 years are used to derive a preliminary orbit for the CEMP star CS 22881–036. The velocity amplitude is very small. No velocity variation is found for three additional CEMP stars observed over roughly the same time interval. Searches for companions of two CEMP double-lined spectroscopic binaries and of the RR Lyrae star TY Gru are reviewed. A disparity between the period distribution of disk carbon-star binaries and that of their parent population of normal binaries can be attributed qualitatively to a decline in accreted mass with increasing binary separation. Finally, possible reasons for failure to find expected companions of CEMP stars are discussed.
Search for associations containing young stars (SACY). VI. Is multiplicity universal? Stellar multiplicity in the range 3-1000 au from adaptive-optics observations

Context. Young loose nearby associations are unique samples of close (<150 pc), young (approx 5-100 Myr) pre-main sequence (PMS) stars. A significant number of members of these associations have been identified in the SACY collaboration. We can use the proximity and youth of these members to investigate key ingredients in star formation processes, such as multiplicity. Aims. We present the statistics of identified multiple systems from 113 confirmed SACY members. We derive multiplicity frequencies, mass-ratio, and physical separation distributions in a consistent parameter space, and compare our results to other PMS populations and the field. Methods. We have obtained adaptive-optics assisted near-infrared observations with NACO (ESO/VLT) and IRCAL (Lick Observatory) for at least one epoch of all 113 SACY members. We have identified multiple systems using co-moving proper-motion analysis and using contamination estimates. We have explored ranges in projected separation and mass-ratio of a [3-1000 au], and q [0.1-1], respectively. Results. We have identified 31 multiple systems (28 binaries and 3 triples). We derive a multiplicity frequency (MF) of MF_(3-1000au)=28.4 +4.7, -3.9% and a triple frequency (TF) of TF_(3-1000au)=2.8 +2.5, -0.8% in the separation range of 3-1000 au. We do not find any evidence for an increase in the MF with primary mass. The estimated mass-ratio of our statistical sample (with power-law index gamma=-0.04 +/- 0.14) is consistent with a flat distribution (gamma = 0). Conclusions. We show further similarities (but also hints of discrepancies) between SACY and the Taurus region: flat mass-ratio distributions and statistically similar MF and TF values. We also compared the SACY sample to the field (in the separation range of 19-100 au), finding that the two distributions are indistinguishable, suggesting a similar formation mechanism.
Viscous Kelvin–Helmholtz instabilities in highly ionized plasmas

Transport coefficients in highly ionized plasmas like the intracluster medium (ICM) are still ill-constrained. They influence various processes, among them the mixing at shear flow interfaces due to the Kelvin–Helmholtz instability (KHI). The observed structure of potential mixing layers can be used to infer the transport coefficients, but the data interpretation requires a detailed knowledge of the long-term evolution of the KHI under different conditions. Here we present the first systematic numerical study of the effect of constant and temperature-dependent isotropic viscosity over the full range of possible values. We show that moderate viscosities slow down the growth of the KHI and reduce the height of the KHI rolls and their rolling-up. Viscosities above a critical value suppress the KHI. The effect can be quantified in terms of the Reynolds number Re=Uλν, where U is the shear velocity, λ the perturbation length and ν the kinematic viscosity. We derive the critical Re for constant and temperature-dependent Spitzer-like viscosities, an empirical relation for the viscous KHI growth time as a function of Re and density contrast, and describe special behaviours for Spitzer-like viscosities and high density contrasts. Finally, we briefly discuss several astrophysical situations where the viscous KHI could play a role, i.e. sloshing cold fronts, gas stripping from galaxies, buoyant cavities, ICM turbulence and high-velocity clouds.
Caenorhabditis elegans as a Model to Study Manganese-Induced Neurotoxicity

Caenorhabditis elegans (C. elegans) is a nematode present worldwide. The worm shows homology to mammalian systems and expresses approximately 40% of human disease-related genes. Since Dr. Sydney Brenner first proposed C. elegans as an advantageous experimental worm-model system for genetic approaches, increasing numbers of studies using C. elegans as a tool to investigate topics in several fields of biochemistry, neuroscience, pharmacology, and toxicology have been performed. In this regard, C. elegans has been used to characterize the molecular mechanisms and affected pathways caused by metals that lead to neurotoxicity, as well as the pathophysiological interrelationship between metal exposure and ongoing neurodegenerative disorders. Several toxic metals, such as lead, cadmium, and mercury, are recognized as important environmental contaminants, and their exposure is associated with toxic effects on the human body. Essential elements that are required to maintain cellular homeostasis and normal physiological functions may also be toxic when accumulated at higher concentrations. For instance, manganese (Mn) is a trace essential element that participates in numerous biological processes, such as enzymatic activities, energy metabolism, and maintenance of cell functions. However, Mn overexposure is associated with behavioral changes in C. elegans, which are consistent with the dopaminergic system being the primary target of Mn neurotoxicity. Caenorhabditis elegans has been shown to be an important tool that allows for studies on neuron morphology using fluorescent transgenic worms. Moreover, behavioral tests may be conducted using worms, and neurotransmitter determination and related gene expression are likely to change after Mn exposure. Likewise, mutant worms may be used to study molecular mechanisms in Mn toxicity, as well as the expression of proteins responsible for the biosynthesis, transport, storage, and uptake of dopamine. Furthermore, this review highlights some advantages and limitations of using the experimental model of C. elegans and provides guidance for potential future applications of this model in studies directed toward assessing for Mn neurotoxicity and related mechanisms.
Agricultural System Modelling with Ant Colony Optimization

Cereals contribute significantly to humanity’s livelihood. They are a source of more food energy worldwide than any other group of crops. Their production contributes considerably to the total global anthropogenic greenhouse gas (GHGs) emissions. In this study we propose a basic bio-economic farm model (BEFM) solved with the help of Ant Colony Optimization (ACO) methodology. We aim to assess farm profits and risks considering various types of policy incentives and adverse weather events. The proposed model can be applied to any annual crop.