Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Approximate Simulation for Hierarchical Control of Linear Systems under Disturbances

Approximate simulation, an extension of simulation relations from formal methods to continuous systems, is a powerful tool for hierarchical control of complex systems. Finding an approximate simulation relation between the full "concrete" system and a simplified "abstract" system establishes a bound on the output error between the two systems, allowing one to design a controller for the abstract system while formally certifying performance on the concrete system. However, many real-world control systems are subject to external disturbances, which are not accounted for in the standard approximate simulation framework. We present a notion of robust approximate simulation, which considers external disturbances to the concrete system. We derive output error bounds for the case of linear systems subject to two types of additive disturbances: bounded disturbances and a sequence of (unbounded) impulse disturbances. We demonstrate the need for robust approximate simulation and the effectiveness of our proposed approach with a simulated robot motion planning example.
Improving Noise Robust Automatic Speech Recognition with Single-Channel Time-Domain Enhancement Network

With the advent of deep learning, research on noise-robust automatic speech recognition (ASR) has progressed rapidly. However, ASR performance in noisy conditions of single-channel systems remains unsatisfactory. Indeed, most single-channel speech enhancement (SE) methods (denoising) have brought only limited performance gains over state-of-the-art ASR back-end trained on multi-condition training data. Recently, there has been much research on neural network-based SE methods working in the time-domain showing levels of performance never attained before. However, it has not been established whether the high enhancement performance achieved by such time-domain approaches could be translated into ASR. In this paper, we show that a single-channel time-domain denoising approach can significantly improve ASR performance, providing more than 30 % relative word error reduction over a strong ASR back-end on the real evaluation data of the single-channel track of the CHiME-4 dataset. These positive results demonstrate that single-channel noise reduction can still improve ASR performance, which should open the door to more research in that direction.
Upper and lower bounds on the rate of decay of the Favard curve length for the four-corner Cantor set

The Favard length of a subset of the plane is defined as the average of its orthogonal projections. This quantity is related to the probabilistic Buffon needle problem; that is, the Favard length of a set is proportional to the probability that a needle or a line that is dropped at random onto the set will intersect the set. If instead of dropping lines onto a set, we drop fixed curves, then the associated Buffon curve probability is proportional to the so-called Favard curve length. As we show in our companion paper, a Besicovitch generalized projection theorem still holds in the setting where lines are replaced by curves. Consequently, the Favard curve length of any purely unrectifiable set is zero. Since the four-corner Cantor set is a compact, purely unrectifiable $1$-set with bounded, non-zero Hausdorff measure, then its Favard curve length equals zero. In this article, we estimate upper and lower bounds for the rate of decay of the Favard curve length of the four-corner Cantor set. Our techniques build on the ideas that have been previously used for the classical Favard length.
How to Train Your Super-Net: An Analysis of Training Heuristics in Weight-Sharing NAS

Weight sharing promises to make neural architecture search (NAS) tractable even on commodity hardware. Existing methods in this space rely on a diverse set of heuristics to design and train the shared-weight backbone network, a.k. a. the super-net. Since heuristics and hyperparameters substantially vary across different methods, a fair comparison between them can only be achieved by systematically analyzing the influence of these factors. In this paper, we therefore provide a systematic evaluation of the heuristics and hyperparameters that are frequently employed by weight-sharing NAS algorithms. Our analysis uncovers that some commonly-used heuristics for super-net training negatively impact the correlation between super-net and stand-alone performance, and evidences the strong influence of certain hyperparameters and architectural choices. Our code and experiments set a strong and reproducible baseline that future works can build on.
The HOSTS Survey for Exozodiacal Dust: Observational Results from the Complete Survey

The Large Binocular Telescope Interferometer (LBTI) enables nulling interferometric observations across the N band (8 to 13 μm) to suppress a star’s bright light and probe for faint circumstellar emission. We present and statistically analyze the results from the LBTI/Hunt for Observable Signatures of Terrestrial Systems survey for exozodiacal dust. By comparing our measurements to model predictions based on the solar zodiacal dust in the N band, we estimate a 1σ median sensitivity of 23 zodis times the solar system dust surface density in its habitable zone (HZ; 23 zodis) for early-type stars and 48 zodis for Sun-like stars, where 1 zodi is the surface density of HZ dust in the solar system. Of the 38 stars observed, 10 show significant excess. A clear correlation of our detections with the presence of cold dust in the systems was found, but none with the stellar spectral type or age. The majority of Sun-like stars have relatively low HZ dust levels (best-fit median: 3 zodis, 1σ upper limit: 9 zodis, 95% confidence: 27 zodis based on our N band measurements), while ∼20% are significantly more dusty. The solar system’s HZ dust content is consistent with being typical. Our median HZ dust level would not be a major limitation to the direct imaging search for Earth-like exoplanets, but more precise constraints are still required, in particular to evaluate the impact of exozodiacal dust for the spectroscopic characterization of imaged exo-Earth candidates.
Long time error analysis of the fourth‐order compact finite difference methods for the nonlinear Klein–Gordon equation with weak nonlinearity

We present the fourth‐order compact finite difference (4cFD) discretizations for the long time dynamics of the nonlinear Klein–Gordon equation (NKGE), while the nonlinearity strength is characterized by ϵp with a constant p ∈ ℕ+ and a dimensionless parameter ϵ ∈ (0, 1]. Based on analytical results of the life‐span of the solution, rigorous error bounds of the 4cFD methods are carried out up to the time at O(ϵ−p). We pay particular attention to how error bounds depend explicitly on the mesh size h and time step τ as well as the small parameter ϵ ∈ (0, 1], which indicate that, in order to obtain ‘correct’ numerical solutions up to the time at O(ϵ−p), the ϵ‐scalability (or meshing strategy requirement) of the 4cFD methods should be taken as: h = O(ϵp/4) and τ = O(ϵp/2). It has better spatial resolution capacity than the classical second order central difference methods. By a rescaling in time, it is equivalent to an oscillatory NKGE whose solution propagates waves with wavelength at O(1) in space and O(ϵp) in time. It is straightforward to get the error bounds of the oscillatory NKGE in the fixed time. Finally, numerical results are provided to confirm our theoretical analysis.
Collaborative care for individuals with bipolar disorder or schizophrenia and co-occurring physical health conditions: A systematic review

ABSTRACT While rates of chronic physical health conditions are increasing for the general population, individuals with severe mental illness are at greater risk. Co-occurring mental and physical health conditions are associated with poor health care utilization, socioeconomic, and patient-reported health status outcomes. This study used systematic review procedures to investigate the effectiveness of collaborative care models for improving the health of adults with bipolar disorder or schizophrenia and co-occurring chronic physical health conditions. Six studies met inclusion criteria, and included outcomes related to quality of life, physical health, and mental health. Collective and study-level results are reported and discussed, including implications for social work practice and research.
Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule

While the generalization properties of neural networks are not yet well understood, several papers argue that wide minima generalize better than narrow minima. In this paper, through detailed experiments that not only corroborate the generalization properties of wide minima, we also provide empirical evidence for a new hypothesis that the density of wide minima is likely lower than the density of narrow minima. Further, motivated by this hypothesis, we design a novel explore-exploit learning rate schedule. On a variety of image and natural language datasets, compared to their original hand-tuned learning rate baselines, we show that our explore-exploit schedule can result in either up to 0.5\% higher absolute accuracy using the original training budget or up to 44\% reduced training time while achieving the original reported accuracy.
Spectrum of singly heavy baryons from a chiral effective theory of diquarks

The mass spectra of singly charmed and bottom baryons, ${\mathrm{\ensuremath{\Lambda}}}_{c/b}(1/{2}^{\ifmmode\pm\else\textpm\fi{}},3/{2}^{\ensuremath{-}})$ and ${\mathrm{\ensuremath{\Xi}}}_{c/b}(1/{2}^{\ifmmode\pm\else\textpm\fi{}},3/{2}^{\ensuremath{-}})$, are investigated using a nonrelativistic potential model with a heavy quark and a light diquark. The masses of the scalar and pseudoscalar diquarks are taken from a chiral effective theory. The effect of ${U}_{A}(1)$ anomaly induces an inverse hierarchy between the masses of strange and nonstrange pseudoscalar diquarks, which leads to a similar inverse mass ordering in $\ensuremath{\rho}$-mode excitations of singly heavy baryons.
Variational Inference for Deep Probabilistic Canonical Correlation Analysis

In this paper, we propose a deep probabilistic multi-view model that is composed of a linear multi-view layer based on probabilistic canonical correlation analysis (CCA) description in the latent space together with deep generative networks as observation models. The network is designed to decompose the variations of all views into a shared latent representation and a set of view-specific components where the shared latent representation is intended to describe the common underlying sources of variation among the views. An efficient variational inference procedure is developed that approximates the posterior distributions of the latent probabilistic multi-view layer while taking into account the solution of probabilistic CCA. A generalization to models with arbitrary number of views is also proposed. The empirical studies confirm that the proposed deep generative multi-view model can successfully extend deep variational inference to multi-view learning while it efficiently integrates the relationship between multiple views to alleviate the difficulty of learning.
Searching Central Difference Convolutional Networks for Face Anti-Spoofing

Face anti-spoofing (FAS) plays a vital role in face recognition systems. Most state-of-the-art FAS methods 1) rely on stacked convolutions and expert-designed network, which is weak in describing detailed fine-grained information and easily being ineffective when the environment varies (e.g., different illumination), and 2) prefer to use long sequence as input to extract dynamic features, making them difficult to deploy into scenarios which need quick response. Here we propose a novel frame level FAS method based on Central Difference Convolution (CDC), which is able to capture intrinsic detailed patterns via aggregating both intensity and gradient information. A network built with CDC, called the Central Difference Convolutional Network (CDCN), is able to provide more robust modeling capacity than its counterpart built with vanilla convolution. Furthermore, over a specifically designed CDC search space, Neural Architecture Search (NAS) is utilized to discover a more powerful network structure (CDCN++), which can be assembled with Multiscale Attention Fusion Module (MAFM) for further boosting performance. Comprehensive experiments are performed on six benchmark datasets to show that 1) the proposed method not only achieves superior performance on intra-dataset testing (especially 0.2% ACER in Protocol-1 of OULU-NPU dataset), 2) it also generalizes well on cross-dataset testing (particularly 6.5% HTER from CASIA-MFSD to Replay-Attack datasets). The codes are available at https://github.com/ZitongYu/CDCN.
Dirac–Coulomb operators with general charge distribution II. The lowest eigenvalue

Consider the Coulomb potential −μ*|x|−1 generated by a non‐negative finite measure μ . It is well known that the lowest eigenvalue of the corresponding Schrödinger operator −Δ/2−μ*|x|−1 is minimized, at fixed mass μ(R3)=ν , when μ is proportional to a delta. In this paper, we investigate the conjecture that the same holds for the Dirac operator −iα·∇+β−μ*|x|−1 . In a previous work on the subject, we proved that this operator is self‐adjoint when μ has no atom of mass larger than or equal to 1, and that its eigenvalues are given by min–max formulas. Here we consider the critical mass ν1 , below which the lowest eigenvalue does not dive into the lower continuous spectrum for any μ⩾0 with μ(R3)
The Validity of the Mini International Neuropsychiatric Interview (M.I.N.I)-Thai version

The objective of the study was to translate and validate the Thai-version of the Mini International Neuropsychiatric Interview: M.I. N.I. :5.0. 0, which was the structured diagnostic interview instrument for psychiatric disorders. After translation, the M.I. N.I. was validated for face and content validity. The criterion- related validity was compared the diagnosis by trained psychiatric nurses using the M.I. N.I. -Thai version with that by psychiatrist as a gold
An Empirical Investigation of Pre-Trained Transformer Language Models for Open-Domain Dialogue Generation

We present an empirical investigation of pre-trained Transformer-based auto-regressive language models for the task of open-domain dialogue generation. Training paradigm of pre-training and fine-tuning is employed to conduct the parameter learning. Corpora of News and Wikipedia in Chinese and English are collected for the pre-training stage respectively. Dialogue context and response are concatenated into a single sequence utilized as the input of the models during the fine-tuning stage. A weighted joint prediction paradigm for both context and response is designed to evaluate the performance of models with or without the loss term for context prediction. Various of decoding strategies such as greedy search, beam search, top-k sampling, etc. are employed to conduct the response text generation. Extensive experiments are conducted on the typical single-turn and multi-turn dialogue corpora such as Weibo, Douban, Reddit, DailyDialog, and Persona-Chat. Detailed numbers of automatic evaluation metrics on relevance and diversity of the generated results for the languages models as well as the baseline approaches are reported.
Calculating with Ramsey degrees

In this paper we thoroughly investigate the relationship between the small Ramsey degrees and the big Ramsey degrees in arbitrary categories satisfying some mild conditions. As the first nontrivial consequence of the generalization we advocate in this paper we prove that small Ramsey degrees are the minima of the corresponding big ones. We show how to derive a monotonicity property for small Ramsey degrees from the analogous fact for the big Ramsey degrees. We prove that small Ramsey degrees are subadditive and show that equality is enforced by the expansion property. We also prove that big Ramsey degrees are subadditive and show that equality is enforced by an abstract property of objects we refer to as self-similarity. We also prove that the small Ramsey degrees enjoy a submultiplicative property. We do not know whether the analogous property holds for big Ramsey degrees. At the end of the paper we apply the abstract machinery developed in the paper to show that if a countable relational structure has finite big Ramsey degrees, then so do its quantifier-free reducts. In particular, it follows that the reducts of the rationals (Q, <), the random graph, the random tournament and (Q, <, 0) all have finite big Ramsey degrees.
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets

We consider causal discovery from time series using conditional independence (CI) based network learning algorithms such as the PC algorithm. The PC algorithm is divided into a skeleton phase where adjacencies are determined based on efficiently selected CI tests and subsequent phases where links are oriented utilizing the Markov and Faithfulness assumptions. Here we show that autocorrelation makes the PC algorithm much less reliable with very low adjacency and orientation detection rates and inflated false positives. We propose a new algorithm, called PCMCI$^+$ that extends the PCMCI method from [Runge et al., 2019b] to also include discovery of contemporaneous links. It separates the skeleton phase for lagged and contemporaneous conditioning sets and modifies the conditioning sets for the individual CI tests. We show that this algorithm now benefits from increasing autocorrelation and yields much more adjacency detection power and especially more orientation recall for contemporaneous links while controlling false positives and having much shorter runtimes. Numerical experiments indicate that the algorithm can be of considerable use in many application scenarios for dozens of variables and large time delays.
Paraoxonase Activity in Cirrhotic and Non Alcoholic Steatohepatitis Patients

Paraoxonase-1 (PON1) is an esterase and lactonase synthesized by the liver and found in the circulation associated with high-density lipoproteins (HDL). The physiological function of PON1 seems to degrade specific oxidized cholesteryl esters and oxidized phospholipids in lipoproteins and cell membranes. Alterations in circulating PON1 levels have been reported in a variety of diseases involving oxidative stress including chronic liver diseases. The aim of this work has been planned to demonstrate: the PON1 activity in cirrhosis and non alcoholic steatohepatitis (NASH). This study was carried out on 40 Patients from Internal Medicine clinic, Suez Canal University Hospital, divided in two groups; 20 patients suffering from cirrhosis (Cirrhosis group) and 20 patients suffering from NASH (NASH group) in addition to 20 healthy subjects free from any disease as control group. Fasting blood sugar, lipid profile and liver function tests were performed in all groups using colorimetric methods, PON1 activity was measured colorimetri-cally using paraoxon as a substrate and apolipoprotein A1(ApoA1) using nephlometric method. PON1 activity and ApoA1 levels were significantly decreased in cirrhosis and NASH patients compared to controls. Cirrhotic patients demonstrated normal lipid profile compared to their controls except HDL which demonstrated low levels while dyslipidemia was demonstrated in NASH patients. High levels of ALT and AST were demonstrated in the two patients groups with low levels of albumin and high levels of total and direct bilirubin in cirrhotic patients only compared to the controls. PON1 activity was found positively correlated with ApoA1 in the two patients groups while it was found positively correlated with HDL and negatively correlated with LDL in NASH group only. PON1activity and ApoA1were significantly reduced in cirrhosis and NASH patients compared to their controls. Dyslipidemia is associated with patients of NASH. A positive correlation was seen between PON1 activity and Apo A1 in the two discussed diseases. Key wards: ApoA1, Cirrhosis, Dyslipidemia, Oxidative stress, NASH, PON1.
New Constructions of Complementary Sequence Pairs Over 4q-QAM

The researches of Golay complementary sequences (GCSs) over 16 and 64 quadrature amplitude modulation (QAM) from 2001 to 2008 were generalized to <inline-formula> <tex-math notation="LaTeX">$4^{q} $ </tex-math></inline-formula>-QAM GCSs of length <inline-formula> <tex-math notation="LaTeX">$2^{m}$ </tex-math></inline-formula> by Li (the generalized cases I-III for <inline-formula> <tex-math notation="LaTeX">$q\ge 2$ </tex-math></inline-formula>) in 2010 and Liu et al. (the generalized cases IV-V for <inline-formula> <tex-math notation="LaTeX">$q\ge 3$ </tex-math></inline-formula>) in 2013. Those sequences are presented by the combination of the quaternary standard GCSs and compatible offsets. By providing new compatible offsets based on the factorization of the integer <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula>, we propose two new constructions of <inline-formula> <tex-math notation="LaTeX">$4^{q} $ </tex-math></inline-formula>-QAM GCSs, which have the generalized cases I-V as special cases. The numbers of the proposed GCSs are equal to the product of the number of the quaternary standard GCSs and the number of the compatible offsets. Denote the number of prime factors of <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> counted with multiplicity by <inline-formula> <tex-math notation="LaTeX">$\Omega (q)$ </tex-math></inline-formula>. The number of new offsets in our first construction is lower bounded by a polynomial of <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> with degree <inline-formula> <tex-math notation="LaTeX">$\Omega (q)$ </tex-math></inline-formula>, while the numbers of offsets in the generalized cases I-III and IV-V are a linear polynomial and a quadratic polynomial of <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>, respectively. If <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula> has a prime factor larger than 2, the number of new offsets in our second construction is lower bounded by a polynomial of <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> with degree <inline-formula> <tex-math notation="LaTeX">$\Omega (q)+1$ </tex-math></inline-formula>. As an example, the new offsets in our two constructions for <inline-formula> <tex-math notation="LaTeX">$q=6$ </tex-math></inline-formula>, whose number is bounded by a cubic polynomial, is also given. The proof in this paper implies that all the mentioned GCSs over QAM can be regarded as projections of Golay complementary arrays of size <inline-formula> <tex-math notation="LaTeX">$2\times 2\times \cdots \times 2$ </tex-math></inline-formula>.