Miracle-dz/UniFAR-FTUs huggingface dataset:
Reverse order laws for generalized inverses of products of two or three matrices with applications

One of the fundamental research problems in the theory of generalized inverses of matrices is to establish reverse order laws for generalized inverses of matrix products. Under the assumption that $A$, $B$, and $C$ are three nonsingular matrices of the same size, the products $AB$ and $ABC$ are nonsingular as well, and the inverses of $AB$ and $ABC$ admit the reverse order laws $(AB)^{-1} = B^{-1} A^{-1}$ and $(ABC)^{-1} = C^{-1}B^{-1}A^{-1}$, respectively. If some or all of $A$, $B$, and $C$ are singular, two extensions of the above reverse order laws to generalized inverses can be written as $(AB)^{(i,\ldots,j)} = B^{(i_2,\ldots,j_2)} A^{(i_1,\ldots,j_1)}$ and $(ABC)^{(i,\ldots,j)} = C^{(i_3,\ldots,j_3)} B^{(i_2,\ldots,j_2)}A^{(i_1,\ldots,j_1)}$, or other mixed reverse order laws. These equalities do not necessarily hold for different choices of generalized inverses of the matrices. Thus it is a tremendous work to classify and derive necessary and sufficient conditions for the reverse order law to hold because there are all 15 types of $\{i,\ldots, j\}$-generalized inverse for a given matrix according to combinatoric choices of the four Penrose equations. In this paper, we first establish several decades of mixed reverse order laws for $\{1\}$- and $\{1,2\}$-generalized inverses of $AB$ and $ABC$. We then give a classified investigation to a special family of reverse order laws $(ABC)^{(i,\ldots,j)} = C^{-1}B^{(k,\ldots,l)}A^{-1}$ for the eight commonly-used types of generalized inverses using definitions, formulas for ranges and ranks of matrices, as well as conventional operations of matrices. Furthermore, the special cases $(ABA^{-1})^{(i,\ldots,j)} = AB^{(k,\ldots,l)}A^{-1}$ are addressed and some applications are presented.
The Million Quasars (Milliquas) Catalogue, v6.4.

Announcing the release v6.4 of the Milliquas (Million Quasars) quasar catalogue which presents all published quasars to 11 December 2019, including SDSS-DR16. Its totals are 757,991 type-I QSOs/AGN and approx 1.1M high-confidence (80%+ likelihood) quasar candidates from SDSS-based & AllWISE photometric quasar catalogs, plus all-sky radio/X-ray associated candidates available only here. Type-II and Bl Lac objects are also included, plus candidates/galaxies with double radio lobes (so calculated), bringing the total count to 1,968,377. Gaia-DR2 astrometry is given for most objects. The catalogue is available on its home page and on NASA HEASARC.
Fundamental Entropic Laws and Lp Limitations of Feedback Systems: Implications for Machine-Learning-in-the-Loop Control

In this paper, we study the fundamental performance limitations for generic feedback systems in which both the controller and the plant may be arbitrarily causal while the disturbance can be with any distributions. In particular, we obtain fundamental $\mathcal{L}_p$ bounds based on the entropic laws that are inherent in any feedback systems. We also examine the implications of the generic bounds for machine-learning-in-the-loop control; in other words, fundamental limits in general exist to what machine learning elements in feedback loops can achieve.
IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks

Retinal vessel segmentation is of great interest for diagnosis of retinal vascular diseases. To further improve the performance of vessel segmentation, we propose IterNet, a new model based on UNet [1], with the ability to find obscured details of the vessel from the segmented vessel image itself, rather than the raw input image. IterNet consists of multiple iterations of a mini-UNet, which can be 4× deeper than the common UNet. IterNet also adopts the weight-sharing and skip-connection features to facilitate training; therefore, even with such a large architecture, IterNet can still learn from merely 10~20 labeled images, without pre-training or any prior knowledge. IterNet achieves AUCs of 0.9816, 0.9851, and 0.9881 on three mainstream datasets, namely DRIVE, CHASE-DB1, and STARE, respectively, which currently are the best scores in the literature. The source code is available1.
Estimating viral bottleneck sizes for FMDV transmission within and between hosts and implications for the rate of viral evolution

RNA viruses exist as populations of closely related genomes, characterized by a high diversity of low-frequency variants. As viral genomes from one population disperse to establish new sites of replication, the fate of these low-frequency variants depends to a large extent on the size of the founding population. Focusing on foot-and-mouth disease virus (FMDV) we conjecture that variants are more likely to be transmitted through wide bottlenecks, but more likely to approach fixation in new populations following narrow bottlenecks; therefore, the longer-term rate of accumulation of ‘nearly neutral’ variants at high frequencies is likely to be inversely related to the bottleneck size. We examine this conjecture in vivo by estimating bottleneck sizes relating ‘parent’ and ‘daughter’ populations observed at different scales ranging from within host to between host (within the same herd, and in different herds) using a previously established method. Within hosts, we find bottleneck sizes to range from 5 to 20 viral genomes between populations transmitted from the pharynx to the serum, and from 4 to 54 between serum and lesion populations. Between hosts, we find bottleneck sizes to range from 2 to 39, suggesting inter-host bottlenecks are of a similar size to intra-host bottlenecks. We establish a statistically significant negative relationship between the probability of genomic consensus level change and bottleneck size, and present a simple sampling model that captures this empirical relationship. We also present a novel in vitro experiment to investigate the impact of bottleneck size on the frequency of mutations within FMDV populations, demonstrate that variant frequency in a population increases more rapidly during small population passages, and provide evidence for positive selection during the passage of large populations.
The PlayStation Reinforcement Learning Environment (PSXLE)

We propose a new benchmark environment for evaluating Reinforcement Learning (RL) algorithms: the PlayStation Learning Environment (PSXLE), a PlayStation emulator modified to expose a simple control API that enables rich game-state representations. We argue that the PlayStation serves as a suitable progression for agent evaluation and propose a framework for such an evaluation. We build an action-driven abstraction for a PlayStation game with support for the OpenAI Gym interface and demonstrate its use by running OpenAI Baselines.
Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax

Deep learning models are full of hyperparameters, which are set manually before the learning process can start. To find the best configuration for these hyperparameters in such a high dimensional space, with time-consuming and expensive model training / validation, is not a trivial challenge. Bayesian optimization is a powerful tool for the joint optimization of hyperparameters, efficiently trading off exploration and exploitation of the hyperparameter space. In this paper, we discuss Bayesian hyperparameter optimization, including hyperparameter optimization, Bayesian optimization, and Gaussian processes. We also review BoTorch, GPyTorch and Ax, the new open-source frameworks that we use for Bayesian optimization, Gaussian process inference and adaptive experimentation, respectively. For experimentation, we apply Bayesian hyperparameter optimization, for optimizing group weights, to weighted group pooling, which couples unsupervised tiered graph autoencoders learning and supervised graph classification learning for molecular graphs. We find that Ax, BoTorch and GPyTorch together provide a simple-to-use but powerful framework for Bayesian hyperparameter optimization, using Ax's high-level API that constructs and runs a full optimization loop and returns the best hyperparameter configuration.
Finite models and the theory of concatenation

We propose FC, a logic on words that combines the previous approaches of finite-model theory and the theory of concatenation, and that has immediate applications in information extraction and database theory in the form of document spanners. Like the theory of concatenation, FC is built around word equations; in contrast to it, its semantics are defined to only allow finite models, by limiting the universe to a word and all its subwords. As a consequence of this, FC has many of the desirable properties of FO[<], while being far more expressive. Most noteworthy among these desirable properties are sufficient criteria for efficient model checking and capturing various complexity classes by extending the logic with appropriate closure or iteration operators. These results allows us to obtain new insights into and techniques for the expressive power and efficient evaluation of document spanners. In fact, FC provides us with a general framework for reasoning about words that has potential applications far beyond document spanners.
Long-Term Ibrutinib Therapy Reverses CD8+ T Cell Exhaustion in B Cell Chronic Lymphocytic Leukaemia

Chronic Lymphocytic Leukaemia (CLL) is associated with immune suppression and susceptibility to infection. CD8+ T cell numbers are increased and demonstrate elevated expression of PD-1 and impaired function. The mechanisms driving these features of exhaustion are uncertain but are likely to include chronic immune recognition of tumor and/or infectious agents. We investigated the number, phenotype and function of total and virus-specific CD8+ T cells in 65 patients with CLL and 14 patients undergoing long-term ibrutinib therapy (median 21 months). Ibrutinib substantially reduced the number of both CD3+ T cells and CD8+ T cells. Importantly, this was associated with a reduction in PD-1 expression on CD8+ T cells (median 28 vs. 24%; p = 0.042) and 3.5 fold increase in cytokine production following mitogen stimulation. The influence of ibrutinib on antigen-specific CD8+ T cell function was assessed by HLA-peptide tetramers and revealed increased IFNγ and TNFα cytokine responses following stimulation with CMV or EBV peptides together with a 55% reduction in the frequency of “inflated” virus-specific CD8+ T cells. These findings reveal that long-term ibrutinib therapy is associated with substantial reversal of T cell exhaustion in B-CLL and is likely to contribute to the reduced infection risk seen in association with this agent.
Cosmological constraints on ultra-light axion fields

Ultra-light axions (ULAs) with mass less than 10−20 eV have interesting behaviors that may contribute to either dark energy or dark matter at different epochs of the Universe. Their properties can be explored by cosmological observations, such as expansion history of the Universe, cosmic large-scale structure, cosmic microwave background, etc. In this work, we study the ULAs with mass around 10−33 eV, which means that the ULA field still rolls slowly at present with the equation of state w = −1 as dark energy. To investigate the mass and other properties of this kind of ULA field, we adopt the measurements of Type Ia supernova (SN Ia), baryon acoustic oscillation (BAO), and Hubble parameter H(z). The Markov Chain Monte Carlo (MCMC) technique is employed to perform the constraints on the parameters. Finally, by exploring four cases of the model, we find that the mass of this ULA field is about 3 × 10−33 eV if assuming the initial axion field ϕi = Mpl. We also investigate a general case by assuming ϕi ≤ Mpl, and find that the fitting results of ϕi/Mpl are consistent with or close to 1 for the datasets that we use.
Stem-Cell-Derived Circulating Progenitors Dysfunction in Behçet's Syndrome Patients Correlates With Oxidative Stress

Behçet's syndrome (BS) is a systemic vasculitis considered as the prototype of a systemic inflammation-induced thrombotic condition whose pathogenesis cannot be explained just by coagulation abnormalities. Circulating hematopoietic progenitor cells (CPC), a population of rare, pre-differentiated adult stem cells originating in the bone marrow and capable of both self-renewal and multi-lineage differentiation, are mobilized in response to vascular injury and play a key role in tissue repair. In cardiovascular and thrombotic diseases, low circulating CPC number and reduced CPC function have been observed. Oxidative stress may be one of the relevant culprits that account for the dysfunctional and numerically reduced CPC in these conditions. However, the detailed mechanisms underlying CPC number reduction are unknown. On this background, the present study was designed to evaluate for the first time the possible relationship between CPC dysfunction and oxidative stress in BS patients. In BS patients, we found signs of plasma oxidative stress and significantly lower CD34+/CD45−/dim and CD34+/CD45−/dim/CD133+ CPC levels. Importantly, in all the considered CPC subsets, significantly higher ROS levels with respect to controls were observed. Higher levels of caspase-3 activity in all the considered CPC population and a strong reduction in GSH content in CPC subpopulation from BS patients with respect to controls were also observed. Interestingly, in BS patients, ROS significantly correlated with CPC number and CPC caspase-3 activity and CPC GSH content significantly correlated with CPC number, in all CPC subsets. Collectively, these data demonstrate for the first time that CPC from BS patients show signs of oxidative stress and apoptosis and that a reduced CPC number is present in BS patients with respect to controls. Interestingly, we observed an inverse correlation between circulating CPC number and CPC ROS production, suggesting a possible toxic ROS effect on CPC in BS patients. The significant correlations between ROS production/GSH content and caspase-3 activity point out that oxidative stress can represent a determinant in the onset of apoptosis in CPC. These data support the hypothesis that oxidative-stress-mediated CPC dysfunctioning may counteract their vascular repair actions, thereby contributing to the pathogenesis and the progression of vascular disease in BS.
Imaging the Visual Network in the Migraine Spectrum

The involvement of the visual network in migraine pathophysiology has been well-known for more than a century. Not only is the aura phenomenon linked to cortical alterations primarily localized in the visual cortex; but also migraine without aura has shown distinct dysfunction of visual processing in several studies in the past. Further, the study of photophobia, a hallmark migraine symptom, has allowed unraveling of distinct connections that link retinal pathways to the trigeminovascular system. Finally, visual snow, a recently recognized neurological disorder characterized by a continuous visual disturbance, is highly comorbid with migraine and possibly shares with it some common pathophysiological mechanisms. Here, we review the most relevant neuroimaging literature to date, considering studies that have either attempted to investigate the visual network or have indirectly shown visual processing dysfunctions in migraine. We do this by taking into account the broader spectrum of migrainous biology, thus analyzing migraine both with and without aura, focusing on light sensitivity as the most relevant visual symptom in migraine, and finally analyzing the visual snow syndrome. We also present possible hypotheses on the underlying pathophysiology of visual snow, for which very little is currently known.
Photodegradation Pathways of Typical Phthalic Acid Esters Under UV, UV/TiO2, and UV-Vis/Bi2WO6 Systems

Photolysis and photocatalysis of typical phthalic acid esters (dimethyl phthalate, DMP; diethyl phthalate, DEP; dibutyl phthalate, DBP) were carried out in UV, UV/TiO2, and UV-Vis/Bi2WO6 systems. All of the selected phthalic acid esters and their decomposition byproducts were subjected to qualitative and quantitative analysis through HPLC and GC-MS. The results of 300 min of photolysis and photodegradation reaction were that each system demonstrated different abilities to remove DMP, DEP, and DBP. The UV/TiO2 system showed the strongest degradation ability on selected PAEs, with removal efficiencies of up to 93.03, 92.64, and 92.50% for DMP, DEP, and DBP in 90 min, respectively. UV-Vis/Bi2WO6 had almost no ability to remove DMP and DEP. However, all of the systems had strong ability to degrade DBP. On the other hand, the different systems resulted in various byproducts and PAE degradation pathways. The UV system mainly attacked the carbon branch and produced o-hydroxybenzoates. No ring-opening byproducts were detected in the UV system. In the photocatalytic process, the hydroxyl radicals produced not only attacked the carbon branch but also the benzene ring. Therefore, hydroxylated compounds and ring-opening byproducts were detected by GC-MS in both the UV/TiO2 and UV-Vis/Bi2WO6 photocatalytic systems. However, there were fewer products due to direct hole oxidation in the UV-Vis/Bi2WO6 system compared with the UV/TiO2 system, which mainly reacted with the pollutants via hydroxyl radicals.
Managing Toe Walking, a Treatment Side Effect, in a Child With T-Cell Non-Hodgkin's Lymphoma: A Case Report

Background and Purpose: Children who have survived cancer are at risk of experiencing adverse effects of the cancer or its treatments. One of the adverse effects may be the limitation of ankle dorsiflexion (DF), which may result in “toe walking. ” Although there is an increasing number of studies in pediatric oncology presenting evidences of different therapeutic interventions to improve DF function, none of these therapeutic interventions has been sufficiently documented. This case report shows the results of non-invasive neurodevelopmental treatment program combined with application of inhibiting casts in a pediatric cancer patient who presented with severe and persistent toe walking. The treatment was aimed to improve DF function and postural and gait pattern and to normalize weight distribution between forefoot and heel. Case Presentation: A 7-year-old girl with T-cell lymphoma, who presented with severe and persistent toe walking, was assessed 10 times over a course of 6 months by both clinical examination (ankle range of motion measurement) and neurophysiological measures (weight distribution between forefoot and hindfoot, postural sway, body posture, and gait). Outcomes: Neurodevelopmental treatment program combined with application of inhibiting casts for 3 months increased passive ankle DF by 10° in both lower limbs, normalized weight distribution between the forefoot and heel in both lower limbs, as well as established a heel-toe walking gait pattern. Improved ankle DF function and normalized postural and gait patterns were maintained in repeated examinations even 3 months after the removal inhibiting casts. Discussion: Early identification of toe walking in the female pediatric patient with T-cell non-Hodgkin's lymphoma and early physiotherapy intervention were beneficial in terms of her body posture and gait pattern development. Non-invasive neurodevelopmental treatment program combined with application of inhibiting casts as described in this study can be useful for managing treatment side effects in pediatric cancer patients.
Cognitive Assessment Tools for Screening Older Adults With Low Levels of Education: A Critical Review

Introduction: Cognitive assessment of older adults who are either illiterate or with low levels of education is particularly challenging because several battery tasks require a certain educational background. Early detection of mild cognitive impairment (MCI) in the elderly using validated screening tools is of great importance since this population group could benefit from new drugs that are being investigated for the treatment of dementias. Cutoff scores for psychometric properties of cognitive tests are not well established among adults with low levels of education. The present study aimed to critically review the literature on cognitive assessment tools for screening cognitive syndromes including MCI and Alzheimer’s disease (AD) in older adults with low levels of education. Methods: We conducted a systematic search of MEDLINE, LILACS, Cochrane, and SCOPUS electronic databases of cross-sectional and prospective studies with adults over 55 years of age. Results: We found a significant number of assessment tools available (n = 44), but only a few of them showed diagnostic accuracy for the diagnosis of MCI and AD in older adults with low levels of education: the Mini-Mental State Exam; the Montreal Cognitive Assessment; the Persian Test of Elderly for Assessment of Cognition and Executive Function; the Six-Item Screener; and the Memory Alteration Test. Few studies evaluated individuals with low levels of education, with a wide range of cutoff scores and cognitive test batteries. Conclusion: We found that a small number of studies evaluated adults with 4 years of formal education or less. Our findings further support the importance of developing specific tools for the assessment of older adults with low levels of education.
Solar Flare Intensity Prediction With Machine Learning Models

We develop a mixed long short‐term memory (LSTM) regression model to predict the maximum solar flare intensity within a 24‐hr time window 0–24, 6–30, 12–36, and 24–48 hr ahead of time using 6, 12, 24, and 48 hr of data (predictors) for each Helioseismic and Magnetic Imager (HMI) Active Region Patch (HARP). The model makes use of (1) the Space‐Weather HMI Active Region Patch (SHARP) parameters as predictors and (2) the exact flare intensities instead of class labels recorded in the Geostationary Operational Environmental Satellites (GOES) data set, which serves as the source of the response variables. Compared to solar flare classification, the model offers us more detailed information about the exact maximum flux level, that is, intensity, for each occurrence of a flare. We also consider classification models built on top of the regression model and obtain better results in solar flare classifications as compared to Chen et al. (2019, https://doi.org/10.1029/2019SW002214). Our results suggest that the most efficient time period for predicting the solar activity is within 24 hr before the prediction time using the SHARP parameters and the LSTM model.