Miracle-dz/UniFAR-FTUs huggingface dataset:
Planetesimal-driven migration as an explanation for observations of high levels of warm, exozodiacal dust

High levels of exozodiacal dust have been observed in the inner regions of a large fraction of main sequence stars. Given the short lifetime of the observed small dust grains, these 'exozodis' are difficult to explain, especially for old (>100 Myr) stars. The exozodiacal dust may be observed as excess emission in the mid-infrared, or using interferometry. We hypothesise that exozodi are sustained by planetesimals scattered by planets inwards from an outer planetesimal belt, where collision timescales are long. In this work, we use N-body simulations to show that the outwards migration of a planet into a belt, driven by the scattering of planetesimals, can increase, or sustain, the rate at which planetesimals are scattered from the outer belt to the exozodi region. We hypothesise that this increase is sufficient to sustain the observed exozodi on Gyr timescales. No correlation between observations of an outer belt and an exozodi is required for this scenario to work, as the outer belt may be too faint to detect. If planetesimal driven migration does explain the observed exozodi, this work suggests that the presence of an exozodi indicates the presence of outer planets and a planetesimal belt.
Structure and correlation effects in semiconducting SrTiO

We have investigated the effects of structure change and electron correlation on ${\text{SrTiO}}_{3}$ single crystals using angle-resolved photoemission spectroscopy. We show that the cubic to tetragonal phase transition at 105 K is manifested by a charge transfer from in-plane (${d}_{yz}$ and ${d}_{zx}$) bands to out-of-plane $({d}_{xy})$ band, which is opposite to the theoretical predictions. Along this second-order phase transition, we find a smooth evolution of the quasiparticle strength and effective masses. The in-plane band exhibits a peak-dip-hump lineshape, indicating a high degree of correlation on a relatively large (170 meV) energy scale, which is attributed to the polaron formation.
A Review of Probiotic Applications in Poultry: Improving Immunity and Having Beneficial Effects on Production and Health

Abstract A new class of feed additives and nutritional supplements, known as probiotics, include bacterial, fungal, and yeast cultures from various sources. Overall, probiotics are believed to promote the health and well-being of animals, birds, and humans in a variety of settings. Incorporating probiotics into the diets of cattle and poultry has been demonstrated to improve growth, feed conversion efficiency, immunological responses, and the animal's ability to manage enteric infections. The use of probiotic-enriched chicken feed has been shown to enhance egg production by as much as 30% among laying chickens. Probiotics may be used to fight off harmful microorganisms, create antibacterial compounds (such as bacteriocins or colicins), and alter the immunological response of the host, according to the National Institutes of Health. Pathogenic microbial strains such as Lactobacillus, Streptococcus, Bacillus, Enterococcus, Pediococcus, Aspergillus, and Saccharomyces are employed in the making of chicken products. The use of subtherapeutic doses of antimicrobial agents, including antibiotics, to combat or remove harmful bacteria and promote animal growth and feed efficiency has resulted in the accumulation of antibiotic residues in animal feed as well as the emergence of drug-resistant microbes in the feed supply chain. As a result of public health concerns, there has been a renewed emphasis on the use of probiotics in chicken production rather than antibiotics in recent years. This research examines the effects of probiotics and direct-fed microorganisms (DFM) on chicken health and performance, with a particular emphasis on the favourable effects they have on poultry health and performance.
A faster, high precision algorithm for calculating symmetric and asymmetric $M_{T2}$

A new algorithm for calculating the stransverse mass, $M_{T2}$, in either symmetric or asymmetric situations has been developed which exhibits good stability, high precision and quadratic convergence for the majority of the $M_{T2}$ parameter space, leading to up to a factor of ten increase in speed compared to other $M_{T2}$ calculators of comparable precision. This document describes and validates the methodology used by the algorithm, and provides comparisons both in terms of accuracy and speed with other existing implementations.
Numerical simulation of the Tayler instability in liquid metals

The electrical current through an incompressible, viscous and resistive liquid conductor produces an azimuthal magnetic field that becomes unstable when the corresponding Hartmann number exceeds a critical value of the order of 20. This Tayler instability (TI), which is not only discussed as a key ingredient of a nonlinear stellar dynamo model (Tayler–Spruit dynamo), but also as a limiting factor for the maximum size of large liquid metal batteries, was recently observed experimentally in a column of a liquid metal (Seilmayer et al 2012 Phys. Rev. Lett. 108 244501). On the basis of an integro-differential equation approach, we have developed a fully three-dimensional numerical code, and have utilized it for the simulation of the Tayler instability at typical viscosities and resistivities of liquid metals. The resulting growth rates are in good agreement with the experimental data. We illustrate the capabilities of the code for the detailed simulation of liquid metal battery problems in realistic geometries.
A Survey of Physical Principles Attempting to Define Quantum Mechanics

Quantum mechanics, one of the most successful theories in the history of science, was created to account for physical systems not describable by classical physics. Though it is consistent with all experiments conducted thus far, many of its core concepts (amplitudes, global phases, etc.) can not be directly accessed and its interpretation is still the subject of intense debate, more than 100 years since it was introduced. So, a fundamental question is why this particular mathematical model is the one that nature chooses, if indeed it is the correct model. In the past two decades there has been a renewed effort to determine what physical or informational principles define quantum mechanics. In this paper, recent attempts at establishing reasonable physical principles are reviewed and their degree of success is tabulated. An alternative approach using joint quasi-probability distributions is shown to provide a common basis of representing most of the proposed principles. It is argued that having a common representation of the principles can provide intuition and guidance to relate current principles or advance new principles. The current state of affairs, along with some alternative views are discussed.
Exact bound–bound Gaunt factor values for quantum levels up to n = 2000

Comparison of observations of radio recombination lines in the interstellar medium with theoretical models can be used to constrain electron temperature and density of the gas. An important component of the models is spontaneous transition rates between bound levels. Calculating these rates relies on accurate bound-bound oscillator strengths, which can be cast in terms of the Gaunt factor. The Gaunt factor contains terminating hypergeometric functions that cannot be calculated with sufficient accuracy for high quantum levels ($n \gtrsim 50$) by standard machine-precision methods. Methods to overcome the accuracy problem have been developed, which include asymptotic expansions and recursion relations. These methods, used in astrophysical models to calculate oscillator strengths, can introduce errors, sometimes up to as much as $\sim 8$ per cent. Detections of radio recombination lines with the new Low Frequency Array (LOFAR) has prompted an examination of theoretical models of the interstellar medium. We revisit the calculation of the Gaunt factor, employing modern arbitrary-precision computational methods to tabulate the Gaunt factor for transitions up to quantum level $n=2000$, sufficient to model low frequency Carbon radio recombination lines. The calculations provide a relative error of $\sim3\times 10^{-4}$ when compared to more detailed calculations including relativistic corrections. Our values for the Gaunt factor are provided for download in a tabular format to be used for a wide range of applications.
Learning from Imbalanced Crowdsourced Labeled Data

Crowdsourcing has proven to be a cost-eﬀective way to meet the demands for labeled training data in supervised deep learning models. However, crowdsourced labels are often inconsistent and noisy due to cognitive and expertise diﬀerences among crowd workers. Existing approaches either infer latent true labels from noisy crowdsourced labels or learn a discriminative model directly from the crowdsourced labeled data, assuming the latent true label distribution is class-balanced. Unfortunately, in many real-world applications, the true label distribution typically is imbalanced across classes. Therefore, in this paper, we address the problem of learning from crowdsourced labeled data with an imbalanced true label distribution. We propose a new framework, named “Learning from Imbalanced Crowdsourced Labeled Data” (ICED), which simultaneously infers true labels from imbalanced crowdsourced labeled data and achieves high accuracy on downstream tasks such as classiﬁcation. The ICED framework consists of two modules, i.e., a true label inference module and a synthetic data generation module, that augment each other iteratively. Extensive experiments conducted on both synthetic and real-world datasets demonstrate the eﬀectiveness of the ICED framework. Our code is available at https://github.com/wentao-repo/ICED .
Do the Tropics Rule? Assessing the State of Tropical Climate Science

Author(s): Seager, R; Chiang, JCH; Shaman, J | Abstract: A symposium honoring Mark Cane and his role in the advancement of climate science was held at the Lamont-Doherty Earth Observatory of Columbia University in October 2014. Over 150 climate scientists from the United States and abroad participated in the program. First day of the symposium began with a retrospective session on the development of tropical ocean? atmosphere interactions, equatorial wave dynamics, and a theory for ENSO. Steve Zebiak, David Halpern and Ed Sarachik, each provided historical context on the advances during the 1960s to 1980s that led to ENSO prediction. The first session of the second day was devoted to outstanding issues in paleoclimate dynamics. David Battisti. He revisited the question of why the ocean overturning circulation was situated in the Atlantic and not the Pacific, reviewing various hypotheses for why the Atlantic is the saltier ocean. The final session of the symposium highlighted the perspectives of climate dynamics from some key contributors to the field. Tim Palmer discussed nonlinear dynamics and regime shifts as a paradigm for understanding climate changes.
THE UV–MID-IR SPECTRAL ENERGY DISTRIBUTION OF A z = 1.7 QUASAR HOST GALAXY

We have measured the spectral energy distribution (SED) of the host galaxy of the zs = 1.7 gravitationally lensed quasar SDSS J1004+4112 from 0.44–8.0 μm (0.16–3.0 μm in the rest frame). The large angular extent of the lensed images and their separation from the central galaxy of this cluster lens allows the images to be resolved even with the Spitzer Space Telescope. Based on the SED, the host galaxy is a mixture of relatively old and intermediate age stars with an inferred stellar mass of log(M⋆/M☉) = 11.09 ± 0.28 and a star-formation rate of yr−1) = 1.21 ± 0.26. Given the estimated black hole mass of MBH ≃ 108.6 M☉ from locally calibrated correlations of black hole masses with line widths and luminosities, the black hole represents a fraction log(MBH/M⋆) = −2.49 ± 0.28 of the stellar mass and it is radiating at 0.24 ± 0.05 of the Eddington limit. The ratio of the host stellar mass to the black hole mass is only marginally consistent with the locally observed ratio.
Molecular basis of stepwise cyclic tetra-adenylate cleavage by the type III CRISPR ring nuclease Crn1/Sso2081

The cyclic oligoadenylates (cOAs) act as second messengers of type III CRISPR immunity system through activating the auxiliary nucleases for indiscriminate RNA degradation. The cOA-degrading nucleases (ring nucleases) provide an ‘off-switch’ regulation of the signaling, thereby preventing cell dormancy or cell death. Here, we describe the crystal structures of the CRISPR-associated ring nuclease 1 (Crn1) from Saccharolobus solfataricus (Sso) 2081 in its apo or bound to cA4 in both pre-cleavage and transient intermediate states. Sso2081 harbors a unique helical insert that encloses cA4 in the central cavity. Two free phosphates symmetrically bind the catalytic site of apo Sso2081 and overlap with the two scissile phosphates of cA4, supporting a bilaterally symmetrical cleavage. The structure of transient intermediate state captured by Ser11Ala mutation immediately illustrates a stepwise cleavage of cA4 by Sso2081. Our study establishes atomic mechanisms of cA4 recognition and degradation by the type III CRISPR ring nuclease Crn1/Sso2081.
Correlation analysis between drug resistance and virulence genes of carbapenem-resistant Acinetobacter baumannii In Western Guilin

Backgound In order to detect the resistance of Acinetobacter baumannii to β-lactam antibiotics in western Guilin, analyze the reasons for its resistance, and provide laboratory basis for clinical treatment; method for the β-lactamase gene of Acinetobacter baumannii, and to explore the relationship between the presence of the β-lactamase gene of Acinetobacter baumannii and multidrug resistance. Methods From November 2020 to June 2022, 78 non-repeated Acinetobacter baumannii strains from the Second Affiliated Hospital of Guilin Medical University were collected, and their resistance to carbapenem antibiotics was analyzed. PCR was used to detect resistance-related genes (blaOXA-23, blaOXA-51, blaOXA-58, blaOXA-24, blaIMP and blaSIM) and virulence genes (cusE, abaI and bfmS). To analyze the relationship between drug resistance and virulence genes of Acinetobacter baumannii. Results Most of the 165 non-enterobacteriaceae bacteria we collected from the hospital were Acinetobacter baumannii and Pseudomonas aeruginosa, and most of the specimen types were from sputum and secretions, and most of them were from respiratory and critical care diseases area and intensive care unit, among them, there are 78 strains of Acinetobacter baumannii studied this time. After screening, 78 Acinetobacter baumannii strains were resistant to Cefazolin, Ampicillin, Amoxicillin/Clavulanate, Aztreonam, Chloramphenicol, Tetracycline, Cefotaxime, Ampicillin/Sulbactam, Piperacillin, Gentamicin, Ciprofloxacin, Levofloxacin, Moxifloxacin, Cefepime, Ceftazidime, Piperacillin/Tazobactam, Compound Sulfonamide, Meropenem, Imipenem, Amikacin, Polymyxin, resistance rates were 98.72%, 98.72%, 96.16%, 96.15%, 96.15%, 66.67%, 60.26%, 58.98%, 58.97%, 57.69%, 57.69%, 57.69%, 57.69%, 57.69%, 56.41%, 55.13%, 53.85%, 52.56%, 52.56%, 50%, 0%. Among them, 17 strains with drug resistance gene blaOXA-51 were detected,accounting for 21.79%; drug gene blaOXA-23, blaOXA-24, blaIMP, blaOXA-58, blaSIM gene were not detected; 17 strains with virulence gene bfmS was detected, accounting for 21.79%; abaI, csuE virulence gene was not detected. Conclusion Acinetobacter baumannii in the hospital is highly resistant to carbapenems, mainly carrying blaOXA-51 resistance genes. Drug resistance is closely related to the virulence gene bfmS.
RNA structural probing of guanine and uracil nucleotides in yeast

RNA structure can be essential for its cellular function. Therefore, methods to investigate the structure of RNA in vivo are of great importance for understanding the role of cellular RNAs. RNA structure probing is an indirect method to asess the three-dimensional structure of RNA by analyzing the reactivity of different nucleotides to chemical modifications. Dimethyl sulfate (DMS) is a well-established compound that reports on base pairing context of adenine (A) and cytidine (C) in-vitro and in-vivo, but is not reactive to guanine (G) or uracil (U). Recently, new compounds were used to modify Gs and Us in plant, bacteria, and human cells. To complement the scope of RNA structural probing by chemical modifications in the model organism yeast, we analyze the effectiveness of guanine modification by the glyoxal family in Saccharomyces cerevisiae and Candida albicans. We show that within glyoxal family of compounds, phenylglyoxal (PGO) is the best guanine probe for structural probing in S. cerevisiae and C. albicans. Further, we show that PGO treatment does not affect the processing of different RNA species in the cell and is not toxic for the cells under the conditions we have established for RNA structural probing. We also explore the effectiveness of uracil modification by Cyclohexyl-3-(2-Morpholinoethyl) Carbodiimide metho-p-Toluenesulfonate (CMCT) in vivo and demonstrate that uracils can be modified by CMCT in S. cerevisiae in vivo. Our results provide the conditions for in vivo probing the reactivity of guanine and uracil nucleotides in RNA structures in yeast and offer a valuable tool for studying RNA structure and function in two widely used yeast model systems.
Fast and Automated Protein-DNA/RNA Macromolecular Complex Modeling from Cryo-EM Maps

Cryo-electron microscopy (cryo-EM) allows a macromolecular structure such as protein-DNA/RNA complexes to be reconstructed in a three-dimensional coulomb potential map. The structural information of these macromolecular complexes forms the foundation for understanding the molecular mechanism including many human diseases. However, the model building of large macromolecular complexes is often difficult and time-consuming. We recently developed DeepTracer-2.0, an artificial intelligence-based pipeline that can build amino acid and nucleic acid backbones from a single cryo-EM map, and even predict the best-fit residues according to the density of side chains. The experiments showed improved accuracy and efficiency when benchmarking the performance on independent experimental maps of protein-DNA/RNA complexes and demonstrated the promising future of macromolecular modeling from cryo-EM maps. Our method and pipeline could benefit researchers worldwide who work in molecular biomedicine and drug discovery, and substantially increase the throughput of the cryo-EM model building. The pipeline has been integrated into the web portal https://deeptracer.uw. edu/.
Convergence Analysis and Adaptively Weighted Regularization for Multiple Kernel Learning

In this article, we survey recent developments of generalization error analysis of Multiple Kernel Learning (MKL) and a reﬁned method based on the theoretical developments. The main target in this article is dense type regularizations including $P _{p}$ -MKL that imposes $ \ell_{p}$ -mixed-norm regularization instead of $ \ell_{1}$ -mixed-norm regularization. According to the recent numerical experiments, the sparse regularization does not necessarily show a good performance compared with dense type regulariza-tions. Motivated by this fact, a general theoretical tool was recently established to derive fast learning rates that is applicable to arbitrary mixed-norm-type regulariza-tions in a unifying manner. As a by-product, the general result gives a fast leaming rate of $ \ell_{p}$ -MKL that is tightest among existing bounds. The leaming rate achieves the minimax lower bound. As a consequence, when the complexities of candidate reproducing kemel Hilbert spaces are inhomogeneous, it is shown that dense type regularization shows better learning rate compared with sparse $ \ell_{1}$ regularization. Moreover, on the basis of the theoretical analysis, a new method of MKL that utilizes an adaptively weighted regularization has been proposed. The method controls strength of penalty for each kernel depending on its importance so that important components are ampliﬁed and unimportant components are shrinked.
Height-dependence of spatio-temporal spectra of wall-bounded turbulence – LES results and model predictions

Wavenumber–frequency spectra of the streamwise velocity component obtained from large-eddy simulations (LES) are presented. Following recent work we show that the main features, a Doppler shift and a Doppler broadening of frequencies, are captured by an advection model based on the Tennekes–Kraichnan random-sweeping hypothesis with additional mean flow. In this paper, we focus on the height-dependence of the spectra within the logarithmic layer of the flow. We furthermore benchmark an analytical model spectrum that takes the predictions of the random-sweeping model as a starting point and find good agreement with the LES data. We also quantify the influence of the LES grid resolution on the wavenumber–frequency spectra.
Endogenous GFP tagging in the diatom Thalassiosira pseudonana

The regulated abundance and spatial distribution of proteins determines cellular structure and function. The discovery of green fluorescent protein (GFP) and fusing it to a target protein to determine subcellular localization revolutionized cell biology. Most localization studies involve introducing additional copies of a target gene genetically fused to GFP and under the control of a constitutive promoter, resulting in the expression of the GFP-fusion protein at non-native levels. Here we have developed a single vector CRISPR/Cas9 guided GFP knock-in strategy in the diatom Thalassiosira pseudonana. This enables precise and scarless knock-in of GFP at the endogenous genomic location to create GFP fusion proteins under their native cis and trans regulatory elements with knock-in efficiencies of over 50%. We show that a previously uncharacterized bestrophin-like protein localizes to the CO2-fixing pyrenoid and demonstrate that by measuring GFP fluorescence we can track relative protein abundance in response to environmental change. To enable endogenous tagging, we developed a Golden Gate Molecular Cloning system for the rapid assembly of episomes for transformation into Thalassiosira pseudonana via bacterial conjugation. In addition, this versatile toolbox enables CRISPR/Cas9 gene editing, provides a broad range of validated fluorophores and enables future large-scale functional studies in diatoms. Significance statement Fluorescent protein (FP) tagging is a widely utilized technique for understanding the spatial distribution of proteins. However, introducing extra gene copies under constitutive promoters that randomly integrate into the genome can result in non-biologically relevant expression levels, unwanted genomic mutations and localization artefacts. To overcome this, we developed a novel single vector system capable of CRISPR/Cas9-guided endogenous GFP tagging in a globally important model diatom. This allows scarless GFP knock-in at precise genomic locations resulting in GFP fusions regulated by native promoters/terminators, which facilitates accurate localization and determination of relative protein abundance. Moreover, the developed modular cloning framework is user-friendly and opens the door for high throughput large-scale studies, including FP tagging, knock-out, and knock-in.