Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Tunable Coupling Scheme of Kerr Parametric Oscillators Based on Shortcuts to Adiabaticity

Kerr parametric oscillators (KPOs), which can be implemented with superconducting parametrons possessing large Kerr nonlinearity, have been attracting much attention in terms of their applications to quantum annealing, universal quantum computation and studies of quantum many-body systems. It is of practical importance for these studies to realize fast and accurate tunable coupling between KPOs in a simple manner. We develop a simple scheme of fast tunable coupling of KPOs with high tunability in speed and amplitude using the fast transitionless rotation of a KPO in the phase space based on the shortcuts to adiabaticity. Our scheme enables rapid switching of the effective coupling between KPOs, and can be implemented with always-on linear coupling between KPOs, by controlling the phase of the pump field and the resonance frequency of the KPO without controlling the amplitude of the pump field nor using additional drive fields and couplers. We apply the coupling scheme to a two-qubit gate, and show that our scheme realizes high gate fidelity compared to a purely adiabatic one, by mitigating undesired nonadiabatic transitions.
Arakelov class groups of random number fields

The main purpose of the paper is to formulate a probabilistic model for Arakelov class groups in families of number fields, offering a correction to the Cohen--Lenstra--Martinet heuristic on ideal class groups. To that end, we show that Chinburg's Omega(3) conjecture implies tight restrictions on the Galois module structure of oriented Arakelov class groups. As a consequence, we construct a new infinite series of counterexamples to the Cohen--Lenstra--Martinet heuristic, which have the novel feature that their Galois groups are non-abelian.
Local Decoding in Distributed Compression

A recent result says that the lossless compression of a single source <inline-formula> <tex-math notation="LaTeX">$X^{n}$ </tex-math></inline-formula> is achievable with a strong locality property; any <inline-formula> <tex-math notation="LaTeX">$X_{i}$ </tex-math></inline-formula> can be decoded from a <italic>constant</italic> number of compressed bits, with a vanishing in <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> probability of error. By contrast, we show that for two separately encoded sources <inline-formula> <tex-math notation="LaTeX">$(X^{n},Y^{n})$ </tex-math></inline-formula>, lossless compression and strong locality is generally not possible. Specifically, we show that for the class of “confusable” sources, strong locality cannot be achieved whenever one of the sources is compressed below its entropy. Irrespective of <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>, there always exists at least one index <inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula> for which the probability of incorrectly decoding <inline-formula> <tex-math notation="LaTeX">$(X_{i},Y_{i})$ </tex-math></inline-formula> is lower bounded by <inline-formula> <tex-math notation="LaTeX">$2^{-O( \mathtt {d})}$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$ \mathtt {d}$ </tex-math></inline-formula> denotes the worst-case (over indices) number of compressed bits accessed by the local decoder. Conversely, if the source is not confusable, strong locality is possible even if one of the sources is compressed below its entropy. Results extend to an arbitrary number of sources.
Analysis of Relaxation Methods for Feature Selection in Mixed Effects Models

Linear Mixed-Effects (LME) models are a fundamental tool for modeling clustered data, including cohort studies, longitudinal data analysis, and meta-analysis. The design and analysis of variable selection methods for LMEs is considerably more difficult than for linear regression because LME models are nonlinear. The approach considered here is motivated by a recent method for sparse relaxed regularized regression (SR3) for variable selection in the context of linear regression. The theoretical underpinnings for the proposed extension to LMEs are developed, including consistency results, variational properties, implementability of optimization methods, and convergence results. In particular we provide convergence analyses for a basic implementation of SR3 for LME (called MSR3) and an accelerated hybrid algorithm (called MSR3-fast). Numerical results show the utility and speed of these algorithms on realistic simulated datasets. The numerical implementations are available in an open source python package pysr3.
MIRA: Stata module to compute Rubin's measure for multiple imputation regression analysis

mira computes Rubin's (1987) measures for Multiple Imputation (MI) regression analysis using numbered datasets. For example, pretend that you have the following datasets generated by some MI procedure: imp1.dta, imp2.dta, etc. Then mira runs the regression command in each dataset up to dataset m (default is 5) and analyzes the results using Rubin's formulas.
NMR investigation of contextuality in a quantum harmonic oscillator via pseudospin mapping

Physical potentials are routinely approximated to harmonic potentials. Hence it is important to know when a quantum harmonic oscillator (QHO) behaves quantum mechanically and when classically. Recently Su et al. (Phys. Rev. A, 85 (2012) 052126) have theoretically shown that QHO exhibits quantum contextuality (QC) for a certain set of pseudospin observables. Here we encode the four eigenstates of a QHO onto four Zeeman product states of a pair of spin-(1/2) nuclei. Using the techniques of NMR quantum information processing, we then demonstrate the violation of both state-dependent and state-independent inequalities arising from the noncontextual hidden variable model.
The people of the Cambridge Austin friars

ABSTRACT The Austin friars in Cambridge was an important religious institution between the late thirteenth and mid-sixteenth centuries. Excavations have revealed well-dated and contextualised burials associated with the friary, as well as a range of material culture. The burials have been subject to a wide range of analyses including osteology, palaeopathology, stable isotopes, ancient DNA and geometric morphometrics. Significantly the distinction between clothed and shrouded burials allows members of the Augustinian order and the laity to be identified. This represents the best-understood published group of burials from an Austin friars in the British Isles and emphasises the importance of nuanced interpretation, as burial at friaries was a structured and multi-local phenomenon. These burials and other material can be interpreted in terms of both mendicant ideals and anti-fraternal criticisms.
Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models

1. Introduction. - I. Optimization Techniques. - 2. Introduction to Optimization. - 3. Linear Optimization. - 4. Nonlinear Local Optimization. - 5. Nonlinear Global Optimization. - 6. Unsupervised Learning Techniques. - 7. Model Complexity Optimization. - II. Static Models. - 9. Introduction to Static Models. - 10. Linear, Polynomial, and Look-Up Table Models. - 11. Neural Networks. - 12. Fuzzy and Neuro-Fuzzy Models. - 13. Local Linear Neuro-Fuzzy Models: Fundamentals. - 14. Local Linear Neuro-Fuzzy Models: Advanced Aspects. - III. Dynamic Models. - 16. Linear Dynamic System Identification. - 17. Nonlinear Dynamic System Identification. - 18. Classical Polynomial Approaches. - 19. Dynamic Neural and Fuzzy Models. - 20. Dynamic Local Linear Neuro-Fuzzy Models. - 21. Neural Networks with Internal Dynamics. - IV. Applications. - 22. Applications of Static Models. - 23. Applications of Dynamic Models. - 24. Applications of Advanced Methods. - A. Vectors and Matrices. - A.1 Vector and Matrix Derivatives. - A.2 Gradient, Hessian, and Jacobian. - B. Statistics. - B.1 Deterministic and Random Variables. - B.2 Probability Density Function (pdf). - B.3 Stochastic Processes and Ergodicity. - B.4 Expectation. - B.5 Variance. - B.6 Correlation and Covariance. - B.7 Properties of Estimators. - References.
Error Correcting Codes that Achieve BSC Capacity Against Channels that are Poly-Size Circuits

Guruswami and Smith (J. ACM 2016) considered codes for channels that are poly-size circuits which modify at most a p-fraction of the bits of the codeword. This class of channels is significantly stronger than Shannon’s binary symmetric channel (BSC), but weaker than Hamming’s channels which are computationally unbounded. Guruswami and Smith gave an explicit Monte-Carlo construction of codes with optimal rate of R(p) = 1 − H(p) that achieve list-decoding in this scenario. Here, “explicit Monte-Carlo” means that both encoding and decoding algorithms run in polynomial time. However, the encoding and decoding algorithms also receive a uniformly chosen string of polynomial length (which is chosen and published, once and for all, in a pre-processing stage) and their correctness is guaranteed w.h. p. over this random choice. Guruswami and Smith asked whether it is possible to obtain uniquely decodable codes for poly-size channels with rate that beats the Gilbert-Varshamov bound $R^{GV}(p)=1-H(2p)$. We give an affirmative answer, Specifically:•For every $0\leq p\lt\frac{1}{4}$, we give an explicit Monte-Carlo construction of uniquely-decodable codes with optimal rate R(p) = 1 − H(p). This matches the rate achieved by Guruswami and Smith for the easier task of list-decoding, and also matches the capacity of binary symmetric channels. Moreover, this rate is strictly larger than that of codes for the standard coding scenario (namely, uniquely-decodable codes for Hamming channels). •Even ignoring explicitness, our result implies a characterization of the capacity of poly-size channels, which was not previously understood.Our technique builds on the earlier list-decodable codes of Guruswami and Smith, achieving unique-decoding by extending and modifying the construction so that we can identify the correct message in the list. For this purpose we use ideas from coding theory and pseudorandomness, specifically:•We construct codes for binary symmetric channels that beat the Gilbert-Varshamov bound, and are “evasive” in the sense that a poly-size circuit that receives a random (or actually pseudorandom) string, cannot find a codeword within relative distance 2p. This notion of evasiveness is inspired by the recent work of Shaltiel and Silbak (STOC 2021) on codes for space bounded channels. •We develop a methodology (that is inspired by proofs of t-wise independent tail inequalities, and may be of independent interest) to analyze random codes, in scenarios where the success of the channel is measured in an additional random experiment (as in the evasiveness experiment above). •We introduce a new notion of “small-set non-malleable codes” that is tailored for our application, and may be of independent interest.
Fooling polynomials using invariant theory*

We revisit the problem of constructing explicit pseudorandom generators that fool with error ϵ degree-d polynomials in n variables over the field Fq, in the case of large q. Previous constructions either have seed length $\geq 2^{d}\log q$, and thus are only non-trivial when $d\lt \log n$, or else rely on a seminal reduction by Bogdanov (STOC 2005). This reduction yields seed length not less than $d^{4}\log n+\log q$ and requires fields of size $q\geq d^{6}/\epsilon^{2}$; and explicit generators meeting such bounds are known.Departing from Bogdanov’s reduction, we develop an algebraic analogue of the Bogdanov-Viola paradigm (FOCS 2007, SICOMP 2010) of summing generators for degree-one polynomials. Whereas previous analyses of the paradigm are restricted to degree $d\lt \log n$, we give a new analysis which handles large degrees. A main new idea is to show that the construction preserves indecomposability of polynomials. Apparently for the first time in the area, the proof uses invariant theory.Our approach in particular yields several new pseudorandom generators. In particular, for large enough fields we obtain seed length $O(d\log n+\log q)$ which is optimal up to constant factors. We also construct generators for fields of size as small as $O(d^{4})$. Further reducing the field size requires a significant change in techniques: Most or all generators for large-degree polynomials rely on Weil bounds; but such bounds are only applicable when $q\gt d^{4}$
Single Image Super-Resolution - A Quantitative Comparison

— Super-resolution (SR) techniques generates high resolution (HR) image from low resolution (LR) images. Since HR image contains more information than LR image, it is severely demanding for all applications of image analysis. High resolution images improves the pictorial information for both human and automatic machine perception. This paper presents a comparison on well-known techniques of super resolution. Performance of the algorithms are evaluated by means of objective image quality criteria like Peak Signal to Ratio (PSNR), Structural Similarity Index (SSIM) and Maximum Difference (MD). From the analysis we have found that learning based algorithm using sparse dictionary performs better.
Multiple populations in globular clusters: the distinct kinematic imprints of different formation scenarios

Several scenarios have been proposed to explain the presence of multiple stellar populations in globular clusters. Many of them invoke multiple generations of stars to explain the observed chemical abundance anomalies, but it has also been suggested that self-enrichment could occur via accretion of ejecta from massive stars on to the circumstellar disc of low-mass pre-main sequence stars. These scenarios imply different initial conditions for the kinematics of the various stellar populations. Given some net angular momentum initially, models for which a second generation forms from gas that collects in a cooling flow into the core of the cluster predict an initially larger rotational amplitude for the polluted stars compared to the pristine stars. This is opposite to what is expected from the accretion model, where the polluted stars are the ones crossing the core and are on preferentially radial (low-angular momentum) orbits, such that their rotational amplitude is lower. Here we present the results of a suite of N-body simulations with initial conditions chosen to capture the distinct kinematic properties of these pollution scenarios. We show that initial differences in the kinematics of polluted and pristine stars can survive to the present epoch in the outer parts of a large fraction of Galactic globular clusters. The differential rotation of pristine and polluted stars is identified as a unique kinematic signature that could allow us to distinguish between various scenarios, while other kinematic imprints are generally very similar from one scenario to the other. (Less)
Evolution of competitive traits changes species diversity in a natural field

Studying the interaction between evolutionary and ecological processes (i.e. eco-evolutionary dynamics) has great potential to improve our understanding of biological processes such as species interactions, community assembly and ecosystem functions. However, most experimental studies have been conducted under controlled laboratory or mesocosm conditions, and the importance of these interactions in natural field communities has not been evaluated. In this study, we focused on the contemporary divergence of a competitive trait (the height–width ratio) of an annual grass Eleusine indica between urban and farmland populations and investigated how trait evolution affects ecological processes by transplanting E. indica individuals from lineages with different trait values into semi-natural grassland. The competitive trait of the transplanted individuals not only affected their own growth and fitness, but also affected the vegetative growth of the competing species and the species diversity. These results indicate that the evolution of competitive traits, even in a single species, can influence the community species diversity through changes in interspecific interactions. Eco-evolutionary interactions therefore play a crucial role in natural field environments. Our results suggest that understanding intraspecific variation in competitive traits driven by rapid evolution is essential for understanding interspecific competitive interactions, community assembly and species diversity.
Native species exhibit physiological habituation to invaders: a reason for hope

Animals cope with environmental perturbations through the stress response, a set of behavioural and physiological responses aimed to maintain and/or return to homeostasis and enhance fitness. Vertebrate neuroendocrine axis activation in response to environmental stressors can result in the secretion of glucocorticoids (GCs), whose acute increases may be adaptive, while chronic elevation may be detrimental. Invasive grey squirrels (Sciurus carolinensis) act as a stressor eliciting elevation of GCs in native red squirrels (Sciurus vulgaris). Here we used 6-year data of variation in faecal glucocorticoid metabolite (FGM) concentrations following invasion by grey squirrels in three red squirrel populations, to identify if red squirrels showed physiological habituation to this stressor. The decrease in FGMs over time was more pronounced shortly after invasion and at high densities of grey squirrels while it decreased less strongly and was no longer influenced by the invader density as time since invasion elapsed. At the individual level, FGMs also decreased more markedly as each red squirrel experienced prolonged contact with the invader. Our study provides compelling new data suggesting that native species in the wild can habituate to prolonged contact with invasive species, showing that they may avoid the potentially harmful effects of chronic elevations in GCs.
Deconvolution of Hubble Space Telescope images using simulated point spread functions

Presented is a study of the use of simulated point spread functions (PSF's) to deconvolve Hubble Space Telescope images. We concentrate on images from the Wide Field and Planetary Camera (WFPC) and examine the affect of position dependence of the PSF and the telescope focus position on deconvolutions. Comparisons will be made to what will be expected from WFPC 2, which will include corrective optics. Since PSF's can be simulated for any specific observation, with the added advantage of being noise free and the ability to subsample them, they may be more suitable for deconvolution than observed ones in some cases. And since finding a suitable observed PSF may be difficult, simulated ones may be easier to use.
Identification of promising anti-EBOV inhibitors: de novo drug design, molecular docking and molecular dynamics studies

The Ebola virus (EBOV) outbreak was recorded as the largest in history and caused many fatalities. As seen in previous studies, drug repurposing and database filtration were the two major pathways to searching for potent compounds against EBOV. In this study, a deep learning (DL) approach via the LigDream tool was employed to obtain novel and effective anti-EBOV inhibitors. Based on the galidesivir (BCX4430) chemical structure, 100 compounds were collected and inspected using various in silico approaches. Results from the molecular docking study indicated that mol1_069 and mol1_092 were the best two potent compounds with a docking score of −7.1 kcal mol−1 and −7.0 kcal mol−1, respectively. Molecular dynamics simulations, in addition to binding energy calculations, were conducted over 100 ns. Both compounds exhibited lower binding energies than BCX4430. Furthermore, compared with BCX4430 (%Absorption = 60.6%), mol1_069 and mol1_092 scored higher values of % Absorption equal to 68.1% and 63.7%, respectively. The current data point to the importance of using DL in the drug design process instead of conventional methods such as drug repurposing or database filtration. In conclusion, mol1_069 and mol1_092 are promising anti-EBOV drug candidates that require further in vitro and in vivo investigations.
Panel Discussion: Emerging Topics on Video Summarization

With video capture devices becoming widely popular, the amount of video data generated per day has seen a rapid increase over the past few years. Browsing through hours of video data to retrieve useful information is a tedious and boring task. Video Summarization technology has played a crucial role in addressing this issue and is a well-researched topic in the multimedia community. This panel aims to bring together researchers working on relevant backgrounds to discuss emerging topics on video summarization, including recent developments, future directions, challenges, solutions, potential applications and other open problems.
Discovery of exercise-related genes and pathway analysis based on comparative genomes of Mongolian originated Abaga and Wushen horse

Abstract The Mongolian horses have excellent endurance and stress resistance to adapt to the cold and harsh plateau conditions. Intraspecific genetic diversity is mainly embodied in various genetic advantages of different branches of the Mongolian horse. Since people pay progressive attention to the athletic performance of horse, we expect to guide the exercise-oriented breeding of horses through genomics research. We obtained the clean data of 630,535,376,400 bp through the entire genome second-generation sequencing for the whole blood of four Abaga horses and ten Wushen horses. Based on the data analysis of single nucleotide polymorphism, we severally detected that 479 and 943 positively selected genes, particularly exercise related, were mainly enriched on equine chromosome 4 in Abaga horses and Wushen horses, which implied that chromosome 4 may be associated with the evolution of the Mongolian horse and athletic performance. Four hundred and forty genes of positive selection were enriched in 12 exercise-related pathways and narrowed in 21 exercise-related genes in Abaga horse, which were distinguished from Wushen horse. So, we speculated that the Abaga horse may have oriented genes for the motorial mechanism and 21 exercise-related genes also provided a molecular genetic basis for exercise-directed breeding of the Mongolian horse.
Brain atrophy pattern in patients with mild cognitive impairment: MRI study

Abstract We evaluated the accuracy of the quantitative and semiquantitative analysis in detecting regional atrophy patterns and differentiating mild cognitive impairment patients who remain stable (aMCI-S) from patients who develop Alzheimer’s disease (aMCI-AD) at clinical follow-up. Baseline magnetic resonance imaging was used for quantitative and semiquantitative analysis using visual rating scales. Visual rating scores were related to gray matter thicknesses or volume measures of some structures belonging to the same brain regions. Receiver operating characteristic (ROC) analysis was performed to assess measures’ accuracy in differentiating aMCI-S from aMCI-AD. Comparing aMCI-S and aMCI-AD patients, significant differences were found for specific rating scales, for cortical thickness belonging to the middle temporal lobe (MTL), anterior temporal (AT), and fronto-insular (FI) regions, for gray matter volumes belonging to MTL and AT regions. ROC curve analysis showed that middle temporal atrophy, AT, and FI visual scales showed better diagnostic accuracy than quantitative measures also when thickness measures were combined with hippocampal volumes. Semiquantitative evaluation, performed by trained observers, is a fast and reliable tool in differentiating, at the early stage of disease, aMCI patients that remain stable from those patients that may progress to AD since visual rating scales may be informative both about early hippocampal volume loss and cortical thickness reduction.