Miracle-dz/UniFAR-FTUs huggingface dataset:
Dark Matter: A Relativistic Inertial Effect in Einstein Canonical Gravity?

After consideration of non-inertial frames in special relativity with emphasis on the problem of clock synchronization (i.e. of how to define 3-space), an overview is given of Einstein canonical gravity in the York canonical basis and of its Hamiltonian Post-Minkowskian (PM) linearization in 3-orthogonal gauges. It is shown that the York time (the trace of the extrinsic curvature of 3-spaces) is the inertial gauge variable describing the general relativistic remnant of the clock synchronization gauge freedom. The dark matter implied by the rotation curves of galaxies can be explained with a choice of the York time implying a PM extension of the Newtonian International Celestial Reference System (ICRS).
A Selective Overview of Deep Learning

Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a long history, recent advances have greatly improved their performance in computer vision, natural language processing, etc. From the statistical and scientific perspective, it is natural to ask: What is deep learning? What are the new characteristics of deep learning, compared with classical methods? What are the theoretical foundations of deep learning? To answer these questions, we introduce common neural network models (e.g., convolutional neural nets, recurrent neural nets, generative adversarial nets) and training techniques (e.g., stochastic gradient descent, dropout, batch normalization) from a statistical point of view. Along the way, we highlight new characteristics of deep learning (including depth and over-parametrization) and explain their practical and theoretical benefits. We also sample recent results on theories of deep learning, many of which are only suggestive. While a complete understanding of deep learning remains elusive, we hope that our perspectives and discussions serve as a stimulus for new statistical research.
Impact of First-Line FOLFIRINOX-Induced Peripheral Neuropathy on the Efficacy of Second-Line GnP in Patients with Unresectable Advanced Pancreatic Cancer

Modified FOLFIRINOX (mFFX) and Gemcitabine plus nab-paclitaxel (GnP) are effective first-line chemotherapies for unresectable advanced pancreatic cancer (APC); however, both lead to peripheral neuropathy (PN). Aims: To evaluate the impact of first-line mFFX-induced PN on the efficacy of second-line GnP in patients with APC. Methods: A database containing patients with APC was retrospectively analyzed to evaluate patients who received second-line GnP after first-line mFFX failure between September 2014 and January 2021. The efficacy and safety of GnP were compared between patients with PN ≥ Grade 2 (PN group) and PN ≤ Grade 1 (non-PN group) at the start of second-line GnP. Cox proportional hazards analysis was also performed to examine the effect on overall survival (OS) and time-to-treatment failure (TTF). Results: Fifty-nine patients (PN group, 18 patients; non-PN group, 41 patients) were included. Median OS and TTF in the PN versus non-PN group were 7.7 versus 5.7 months (p = 0.19) and 3.8 versus 2.7 months (p = 0.18), respectively. Multivariate analysis showed that PN (≥Grade 2) was not a significant factor affecting either OS (hazard ratio (HR) 0.66, 95% confidence interval [CI] 0.33–1.31, p = 0.24) or TTF (HR 0.71, 95% CI 0.38–1.33, p = 0.28). No significant difference was observed in the relative dose intensity of GEM or nab-PTX, and incidence of adverse events. Conclusions: mFFX-induced PN has little impact on the efficacy and safety of second-line GnP in patients with APC. Second-line GnP could be a possible treatment option regardless of the presence of PN.
High-resolution optical spectroscopy of V838 Monocerotis in 2009

Context. V838 Mon erupted at the beginning of 2002. In the course of the outburst the object evolved to low effective temperatures and declined as a very late M-type supergiant. Among various scenarios proposed to explain the nature of the outburst, the most promising is a stellar merger event. Aims. We aim at studying the structure and evolution of the object in the decline from the 2002 eruption. Methods. We obtained spectroscopic observations of V838 Mon in January−March 2009 with UVES/VLT. The results are analysed and compared with similar observations obtained in October 2005 with HIRES/Keck. Results. The most striking difference between 2009 and 2005 is a complete absence of the B3 V component and of the [FeII] emission lines in 2009. The present spectrum displays only the spectrum of the 2002 eruption remnant. It resembles that of an ∼M6 giant, although the molecular bands in V838 Mon are deeper than those in standard stellar spectra of a similar spectral class. Several atomic lines, which displayed P-Cyg profiles in 2005, are now dominated by pure absorptions. Some of these lines, however, show a narrow emission component, which, as we argue, measures the radial velocity of V838 Mon. The resulting heliocentric velocity is 71 km s −1 , which very well agrees with the velocity obtained from SiO maser observations. The atomic lines and the molecular bands show very complex kinematics. In some atomic lines and high-excitation molecular bands we observe matter infalling in the object atmosphere. The infall components were already observed in 2005, but were less pronounced and present in fewer lines than in 2009. We argue that the most negative radial velocity components seen in the resonance atomic lines and in the low-excitation molecular bands were formed in the ejecta of the 2002 eruption. The B3 V companion most probably became engulfed in an opaque dusty matter of the 2002 V838 Mon ejecta.
THREE-DIMENSIONAL STRUCTURE OF THE CENTRAL REGION OF NGC 7027: A QUEST FOR TRAILS OF HIGH-VELOCITY JETS

We report on the results of a radio interferometric observation of NGC 7027 in the CO J = 2–1 and 13CO J = 2–1 lines. The results are analyzed with morpho-kinematic models developed from the software tool Shape. Our goal is to reveal the morpho-kinematic properties of the central region of the nebula, and to explore the nature of unseen high-velocity jets that may have created the characteristic structure of the central region consisting of molecular and ionized components. A simple ellipsoidal shell model explains the intensity distribution around the systemic velocity, but the high-velocity features deviate from the ellipsoidal model. Through the Shape automatic reconstruction model, we found a possible trail of a jet only in one direction, but no other possible holes were created by the passage of a jet.
Long-range interactions between substitutional nitrogen dopants in graphene: electronic properties calculations

Being a true two-dimensional crystal, graphene has special properties. In particular, a point-like defect in graphene may have effects in the long range. This peculiarity questions the validity of using a supercell geometry in an attempt to explore the properties of an isolated defect. Still, this approach is often used in ab-initio electronic structure calculations, for instance. How does this approach converge with the size of the supercell is generally not tackled for the obvious reason of keeping the computational load to an affordable level. The present paper addresses the problem of substitutional nitrogen doping of graphene. DFT calculations have been performed for 9x9 and 10x10 supercells. Although these calculations correspond to N concentrations that differ by about 10%, the local densities of states on and around the defects are found to depend significantly on the supercell size. Fitting the DFT results by a tight-binding Hamiltonian makes it possible to explore the effects of a random distribution of the substitutional N atoms, in the case of finite concentrations, and to approach the case of an isolated impurity when the concentration vanishes. The tight-binding Hamiltonian is used to calculate the STM image of graphene around an isolated N atom. STM images are also calculated for graphene doped with 0.5 % concentration of nitrogen. The results are discussed in the light of recent experimental data and the conclusions of the calculations are extended to other point defects in graphene.
Elementary processes in hydrogen-helium plasmas : cross sections and reaction rate coefficients

1. Introduction. - 1.1 Previous Surveys. - 1.2 Scope of Present Survey. - 1.3 Organization of Information. - 1.4 Sources and Criteria for Selection and Evaluation of Data. - 1.5 Accuracy. - 1.6 References. - 1.7 Digitization of the Cross Sections. - 1.8 Calculation of Reaction Rate Coefficients. - 1.9 Numerical Fits to a and ? - 1.10Example of Use of Fits. - 2. Electron Impact Collision Processes. - 2.1 Electron Collisions with H and H+. - 2.2 Electron Collisions with H2, H2+, and H3+. - 2.3 Electron Collisions with He, He+, and He2+. - 3. Proton Impact Collision Processes. - 3.1 Proton Collisions with H. - 3.2 Proton Collisions with H2 and H2+. - 3.3 Proton Collisions with He and He*. - 4. Collision Processes and Reactions of H2+ Ions. - 4.1 General Remarks. - 4.2 Collisions of H2+ with H. - 4.3 Collisions of H2+ with H2. - 4.4 Collisions of H2+ with He. - 5. Collision Processes of He+. - 5.1 General Remarks. - 5.2 Collisions of He+ with H2. - 5.3 Collisions of He+ with He. - 6. Collision Processes of He2+. - 6.1 Collisions of He2+ with H. - 6.2 Collision of He2+ with H2. - 6.3 Collisions of He2+ with He. - 7. Collision Processes of H-. - 7.1 Electron Collisions with H-. - 7.2 Proton Collisions with H-. - 7.3 Collisions of H with H-. - 8. Analytic Fits. - 8.1 Fits for ? - 8.2 Polynomial Fits for ? for Fixed E : Electron Reactions. - 8.3 Double Polynomial Fits for ? - A. Oscillator Strengths, Radiative Rates, and Excitation Energies for Hydrogen and Helium. - References.
Variational Information Distillation for Knowledge Transfer

Transferring knowledge from a teacher neural network pretrained on the same or a similar task to a student neural network can significantly improve the performance of the student neural network. Existing knowledge transfer approaches match the activations or the corresponding hand-crafted features of the teacher and the student networks. We propose an information-theoretic framework for knowledge transfer which formulates knowledge transfer as maximizing the mutual information between the teacher and the student networks. We compare our method with existing knowledge transfer methods on both knowledge distillation and transfer learning tasks and show that our method consistently outperforms existing methods. We further demonstrate the strength of our method on knowledge transfer across heterogeneous network architectures by transferring knowledge from a convolutional neural network (CNN) to a multi-layer perceptron (MLP) on CIFAR-10. The resulting MLP significantly outperforms the-state-of-the-art methods and it achieves similar performance to the CNN with a single convolutional layer.
Intraguild Competition between Endangered Kit Foxes and a Novel Predator in a Novel Environment

Simple Summary A population of endangered San Joaquin kit foxes inhabits the urban environment in the city of Bakersfield, California, United States. Non-native red foxes, a larger competitor, also occur in Bakersfield and are a potential threat to kit foxes. Based on scat analysis, dietary overlap between the two species is high and red foxes have usurped kit fox dens. Based on logistic regression, habitat attributes generally were similar between grid cells used by each species. However, kit foxes tended to use areas with smaller open spaces and more human activity. We also found that the two species almost never overlapped temporally when using the same grid cells. Because of this temporal separation in addition to an abundance of food and dens in the urban environment, competition from red foxes does not currently appear to be a significant threat to kit foxes. Abstract A population of endangered San Joaquin kit foxes inhabits the urban environment in the city of Bakersfield, California, United States. This population is considered important for the conservation and recovery of this species. In this novel environment, kit foxes encounter a novel competitor, that being non-native red foxes. We examined exploitative and interference competition between these two species. Based on scat analysis, both species consumed similar foods and dietary overlap was high. Red foxes also were found to usurp kit fox dens. Direct mortality to kit foxes from red foxes appears to be rare. Kit foxes and red foxes also appear to overlap spatially, although we found evidence of temporal partitioning of shared space. Based on binary logistic regression modeling, habitat attributes in grid cells used by the two species generally were similar, consistent with the spatial overlap. However, differences in specific attributes indicated that kit foxes are more likely to use areas with smaller open spaces and more human activity compared to red foxes. Competition from red foxes may be mitigated by several factors. Critical resources such as food and dens may be sufficiently abundant such that they are not a limiting factor. Some degree of spatial segregation and temporal partitioning of shared space may reduce interference competition. These factors may facilitate coexistence, and consequently, red foxes do not currently appear to constitute a significant competitive risk to this important population of endangered San Joaquin kit foxes.
CARBON-RICH PLANET FORMATION IN A SOLAR COMPOSITION DISK

The C to O ratio is a crucial determinant of the chemical properties of planets. The recent observation of WASP 12b, a giant planet with a C/O value larger than that estimated for its host star, poses a conundrum for understanding the origin of this elemental ratio in any given planetary system. In this paper, we propose a mechanism for enhancing the value of C/O in the disk through the transport and distribution of volatiles. We construct a model that computes the abundances of major C- and O-bearing volatiles under the influence of gas drag, sublimation, vapor diffusion, condensation, and coagulation in a multi-iceline 1+1D protoplanetary disk. We find a gradual depletion in water and carbon monoxide vapors inside the water's iceline, with carbon monoxide depleting slower than water. This effect increases the gaseous C/O and decreases the C/H ratio in this region to values similar to those found in WASP 12b's day side atmosphere. Giant planets whose envelopes were accreted inside the water's iceline should then display C/O values larger than those of their parent stars, making them members of the class of so-called carbon-rich planets.
Wireless Network Multimedia Communication and Multi-Objective Evolutionary Algorithm and Its Female Athlete's Nutritional Diet Model

: With the improvement of people's living standards and quality of life, health and health care as an emerging industry has begun to flourish, and people have begun to pay attention to dietary nutrition issues to improve their physical fitness and quality of life. This article aims to study wireless network multimedia communication and multi-objective evolutionary algorithm and its female athletes' nutritional diet model. This article first introduces the multimedia organization model in wireless networks, and studies the transformation of the planning problem of the multi-objective evolutionary algorithm, and proposes the preferred multi-objective evolutionary algorithm. A flow chart of the realization process of the dietary nutrition model of the multi-objective evolutionary algorithm is given, and then the nutritional diet of athletes is investigated based on wireless network multimedia communication, and the dietary nutritional status of the athletes is studied based on the multi-objective evolutionary algorithm. The experimental research results show that based on wireless network multimedia communication and multi-objective evolutionary algorithm, the research findings of its female athletes' nutritional diet model, basically, only 50% of the athletes’ diets meet the needs of athletes’ sports, which indicates that it is necessary to strengthen the propaganda of athletes’ dietary rules and health, so as to ensure that athletes can compete on the field with sufficient energy.
Clustering of Time-Course Gene Expression Data

Microarray experiments have been used to measure genes’ expression levels under different cellular conditions or along certain time course. Initial attempts to interpret these data begin with grouping genes according to similarity in their expression profiles. The widely adopted clustering techniques for gene expression data include hierarchical clustering, self-organizing maps, and K-means clustering. Bayesian networks and neural networks have also been applied to gene clustering. Sharan & Shamir [3] provided a survey on this topic. Clustering techniques typically discover the inherent structure of the genes expression profiles based on some similarity measures. The clustering results largely depend on how the similarity measure corresponds to the biological correlation between genes. Before reliable conclusion about biological functions can be drawn from the data, the gene clusters obtained from microarray analysis must be investigated with respect to known biological roles of those clusters. The current analysis of whole-genome expression focuses on relationships based on global correlation over a whole time-course, identifying clusters of genes whose expression levels simultaneously rise and fall. However, genes may be regulated by different regulators in a long time course. Co-regulating in part of the long time course does not guarantee a global similarity in gene profiles. Biclustering of microarray gene expression data has recently been introduced by Chen & Church [1] as a means to discover sets of genes that co-expressed in only part of the experiment conditions under study. Essentially, overlapping in gene clusters is allowed, and many subtle gene clusters are revealed. Since then, several other algorithms have been developed to bicluster gene expression data [4]. However, existing biclustering algorithms do not consider the differences between time-series gene expression data and multi-condition gene expression data. The relations between time points are ignored, and the time points are clustered independently. It is marginally biologically meaningful if two genes show similar expression pattern in non-consecutive time points. It is therefore necessary to preserve the time locality in time-course gene expression data.
Nicandra physalodes Extract Exerts Antiaging Effects in Multiple Models and Extends the Lifespan of Caenorhabditis elegans via DAF-16 and HSF-1

The development of safe and effective therapeutic interventions is an important issue for delaying aging and reducing the risk of aging-related diseases. Chinese herbal medicines for the treatment of aging and other complex diseases are desired due to their multiple components and targets. Through screening for effects on lifespan of 836 Chinese herbal medicine extracts, Nicandra physalodes extract (HL0285) was found to exhibit lifespan extension activity in Caenorhabditis elegans (C. elegans). In further experiments, HL0285 improved healthspan, enhanced stress resistance, and delayed the progression of neurodegenerative diseases in C. elegans. Additionally, it ameliorated senescence in human lung fibroblasts (MRC-5 cells) and reversed liver function damage and reduced senescence marker levels in doxorubicin- (Dox-) induced aging mice. In addition, the longevity effect of HL0285 in C. elegans was dependent on the DAF-16 and HSF-1 signaling pathways, as demonstrated by the results of the mutant lifespan, gene level, and GFP level assays. In summary, we discovered that HL0285 had an antiaging effect in C. elegans, MRC-5 cells, and Dox-induced aging mice and deserves to be explored in the future studies on antiaging agents.
An observational estimate for the mean secular evolution rate in spiral galaxies

We have observationally quantified the effect of gravitational torques on stars in disc galaxies due to the stellar distribution itself and explored whether these torques are efficient at transporting angular momentum within a Hubble time. We derive instantaneous torque maps for a sample of 24 spiral galaxies, based on stellar mass maps that were derived using the pixel-by-pixel mass-to-light estimator by Zibetti, Rix and Charlot. In conjunction with an estimate of the rotation velocity, the mass maps allow us to determine the torque-induced instantaneous angular momentum flow across different radii, resulting from the overall stellar distributions for each galaxy in the sample. By stacking the sample, which effectively replaces a time average by an ensemble average, we find that the torques due to the stellar disc act to transport angular momentum outwards over much of the disc (within three disc scalelengths). The strength of the ensemble-averaged gravitational torques within one disc scalelength has a time-scale of 4 Gyr for angular momentum redistribution. The individual torque profiles show that only a third of our sample exhibit torques strong enough to redistribute angular momentum within a Hubble time, mostly those with strong bars. However, advective angular momentum transport is another source of angular momentum redistribution, especially in the presence of long-lived spiral arms, but is not accessible to direct observations. The torque-driven angular momentum redistribution is thus observed to be effective, either in one-third of disc galaxies or in most disc galaxies one third of the time and should lead to either changes in the mass density profile or the orbital shapes. We use a set of self-consistent disc, bulge and halo simulated isolated disc galaxies with realistic cold gas fractions to verify that the torques exerted by the stellar distribution, such as spiral arms or a bar, exceed those of the gas and halo, as assumed in the analysis of the observations. This study is the first to observationally determine the strength of torque-driven angular momentum flow of stars for a sample of spiral galaxies, providing an important empirical constraint on secular evolution.
Bogoliubov theory of interacting bosons on a lattice in a synthetic magnetic field

We consider theoretically the problem of an artificial gauge potential applied to a cold atomic system of interacting neutral bosons in a tight-binding optical lattice. Using the Bose-Hubbard model, we show that an effective magnetic field leads to superfluid phases with simultaneous spatial order, which we analyze using Bogliubov theory. This gives a consistent expansion in terms of quantum and thermal fluctuations, in which the lowest order gives a Gross-Pitaevskii equation determining the condensate configuration. We apply an analysis based on the magnetic symmetry group to show how the spatial structure of this configuration depends on commensuration between the magnetic field and the lattice. Higher orders describe the quasiparticle excitations, whose spectrum combines the intricacy of the Hofstadter butterfly with the characteristic features of the superfluid phase. We use the depletion of the condensate to determine the range of validity of our approximations and also to find an estimate for the onset of the Mott insulator phase. Our theory provides concrete experimental predictions for both time-of-flight imagery and Bragg spectroscopy.