Miracle-dz/UniFAR-FTUs huggingface dataset:
Swift/XRT, Chandra, and XMM–Newton observations of IGR J17091–3624 as it returns into quiescence

IGR J17091–3624 is a low-mass X-ray binary (LMXB), which received wide attention from the community thanks to its similarities with the bright black hole system GRS 1915+105. Both systems exhibit a wide range of highly structured X-ray variability during outburst, with time-scales from few seconds to tens of minutes, which make them unique in the study of mass accretion in LMXBs. In this work, we present a general overview into the long-term evolution of IGR J17091–3624, using Swift/XRT observations from the onset of the 2011–2013 outburst in 2011 February till the end of the last bright outburst in 2016 November. We found four re-flares during the decay of the 2011 outburst, but no similar re-flares appear to be present in the latter one. We studied, in detail, the period with the lowest flux observed in the last 10 yr, just at the tail end of the 2011–2013 outburst, using Chandra and XMM-Newton observations. We observed changes in flux as high as a factor of 10 during this period of relative quiescence, without strong evidence of softening in the spectra. This result suggests that the source has not been observed at its true quiescence so far. By comparing the spectral properties at low luminosities of IGR J17091–3624 and those observed for a well-studied population of LMXBs, we concluded that IGR J17091–3624 is most likely to host a black hole as a compact companion rather than a neutron star.
Flesh quality differentiation of wild and cultured Nile tilapia (Oreochromis niloticus ) populations

Variation in chemical composition and carcass traits among different wild and cultured Nile tilapia, Oreochromis niloticus populations were analyzed to study and compare the differences among different wild (Manzalah lake, Nile river and Edku lake) and cultured Nile tilapia populations. Data of body composition of different Nile tilapia ( O. niloticus ) populations showed that, the highest mean value of moisture content (80.32 ± 0.39%) was shown by cultured population and differ significantly (P≤0.05) from those of other populations studied. The highest mean value of protein content (58.14 ± 0.51%) was shown by cultured population but did not differ significantly (P≤0.05) from that of River Nile population. Lipids content showed lower mean (21.74 ± 0.06%) by River Nile population but did not differ significantly (P≤0.05) from that of cultured population. The results of carcass traits show insignificant differences (P≤0.05) in all parameters among different Nile tilapia populations studied. The evaluation of flesh quality of different wild and cultured populations of Nile tilapia studied can result in a genotype suitable for aquaculture. Key words : Flesh quality, wild, cultured, Nile tilapia, population.
Maintained physical activity and physiotherapy in the management of distal arm pain: a randomised controlled trial

Objectives The epidemiology of distal arm pain and back pain are similar. However, management differs considerably: for back pain, rest is discouraged, whereas patients with distal arm pain are commonly advised to rest and referred to physiotherapy. We hypothesised that remaining active would reduce long-term disability and that fast-track physiotherapy would be superior to physiotherapy after time on a waiting list. Methods Adults referred to community-based physiotherapy with distal arm pain were randomised to: advice to remain active while awaiting physiotherapy (typically delivered after 6–8 weeks); advice to rest while awaiting physiotherapy, or immediate treatment. Intention-to-treat analysis determined whether the probability of recovery at 26 weeks was greater among the active advice group, compared with those advised to rest and/or among those receiving immediate versus usually timed physiotherapy. Results 538 of 1663 patients invited between February 2012 and February 2014 were randomised (active=178; rest=182; immediate physiotherapy=178). 81% provided primary outcome data, and complete recovery was reported by 60 (44%), 46 (32%) and 53 (35%). Those advised to rest experienced a lower probability of recovery (OR: 0.54; 95% CI 0.32 to 0.90) versus advice to remain active. However, there was no benefit of immediate physiotherapy (0.64; 95% CI 0.39 to 1.07). Conclusions Among patients awaiting physiotherapy for distal arm pain, advice to remain active results in better 26-week functional outcome, compared with advice to rest. Also, immediate physiotherapy confers no additional benefit in terms of disability, compared with physiotherapy delivered after 6–8 weeks waiting time. These findings question current guidance for the management of distal arm pain.
Generalization and Invariances in the Presence of Unobserved Confounding

The ability to extrapolate, or generalize, from observed to new related environments is central to any form of reliable machine learning, yet most methods fail when moving beyond $i.i. d$ data. In some cases, the reason lies in a misappreciation of the causal structure that governs the observed data. But, in others, it is unobserved data, such as hidden confounders, that drive changes in observed distributions and distort observed correlations. In this paper, we argue that generalization must be defined with respect to a broader class of distribution shifts, irrespective of their origin (arising from changes in observed, unobserved or target variables). We propose a new learning principle from which we may expect an explicit notion of generalization to certain new environments, even in the presence of hidden confounding. This principle leads us to formulate a general objective that may be paired with any gradient-based learning algorithm; algorithms that have a causal interpretation in some cases and enjoy notions of predictive stability in others. We demonstrate the empirical performance of our approach on healthcare data from different modalities, including image and speech data.
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review

This work provides the community with a timely comprehensive review of backdoor attacks and countermeasures on deep learning. According to the attacker's capability and affected stage of the machine learning pipeline, the attack surfaces are recognized to be wide and then formalized into six categorizations: code poisoning, outsourcing, pretrained, data collection, collaborative learning and post-deployment. Accordingly, attacks under each categorization are combed. The countermeasures are categorized into four general classes: blind backdoor removal, offline backdoor inspection, online backdoor inspection, and post backdoor removal. Accordingly, we review countermeasures, and compare and analyze their advantages and disadvantages. We have also reviewed the flip side of backdoor attacks, which are explored for i) protecting intellectual property of deep learning models, ii) acting as a honeypot to catch adversarial example attacks, and iii) verifying data deletion requested by the data contributor.Overall, the research on defense is far behind the attack, and there is no single defense that can prevent all types of backdoor attacks. In some cases, an attacker can intelligently bypass existing defenses with an adaptive attack. Drawing the insights from the systematic review, we also present key areas for future research on the backdoor, such as empirical security evaluations from physical trigger attacks, and in particular, more efficient and practical countermeasures are solicited.
Sorted Pooling in Convolutional Networks for One-shot Learning

We present generalized versions of the commonly used maximum pooling operation: $k$th maximum and sorted pooling operations which selects the $k$th largest response in each pooling region, selecting locally consistent features of the input images. This method is able to increase the generalization power of a network and can be used to decrease training time and error rate of networks and it can significantly improve accuracy in case of training scenarios where the amount of available data is limited, like one-shot learning scenarios
Central limit theorems for stationary random fields under weak dependence with application to ambit and mixed moving average fields

We obtain central limit theorems for stationary random fields which are based on the use of a novel measure of dependence called $\theta$-lex weak dependence. We discuss hereditary properties for $\theta$-lex and $\eta$-weak dependence and illustrate the possible applications of the weak dependence notions to the study of the asymptotic properties of stationary random fields. Our general results are applied to mixed moving average fields (MMAF in short) and ambit fields. We show general conditions such that MMAF and ambit fields, with the volatility field being an MMAF or a $p$-dependent random field, are weakly dependent. For all the aforementioned models, we give a complete characterization of their weak dependence coefficients and sufficient conditions to obtain asymptotic normality of their sample moments. Finally, we give explicit computations of the weak dependence coefficients in the case of MSTOU and CARMA fields.
On an interior Calder\'{o}n operator and a related Steklov eigenproblem for Maxwell's equations

We discuss a Steklov-type problem for Maxwell's equations which is related to an interior Calder\'{o}n operator and an appropriate Dirichlet-to-Neumann type map. The corresponding Neumann-to-Dirichlet map turns out to be compact and this provides a Fourier basis of Steklov eigenfunctions for the associated energy spaces. With an approach similar to that developed by Auchmuty for the Laplace operator, we provide natural spectral representations for the appropriate trace spaces, for the Calder\'{o}n operator itself and for the solutions of the corresponding boundary value problems subject to electric or magnetic boundary conditions on a cavity.
Understanding Polarized Dust Emission from ρ Ophiuchi A in Light of Grain Alignment and Disruption by Radiative Torques

The alignment of dust grains with the ambient magnetic field produces polarization of starlight as well as thermal dust emission. Using the archival SOFIA/HAWC+ polarimetric data observed toward the ρ Ophiuchus (Oph) A cloud hosted by a B star at 89 and 154 μm, we find that the fractional polarization of thermal dust emission first increases with the grain temperature and then decreases once the grain temperature exceeds ≃25–32 K. The latter trend differs from the prediction of the popular RAdiative Torques (RATs) alignment theory, which implies a monotonic increase of the polarization fraction with the grain temperature. We perform numerical modeling of polarized dust emission for the ρ Oph-A cloud and calculate the degree of dust polarization by simultaneously considering the dust grain alignment and rotational disruption by RATs. Our modeling results could successfully reproduce both the rising and declining trends of the observational data. Moreover, we show that the alignment of only silicate grains or a mixture of silicate–carbon grains within a composite structure can reproduce the observational trends, assuming that all dust grains follow a power-law size distribution. Although there are a number of simplifications and limitations to our modeling, our results suggest grains in the ρ Oph-A cloud have a composite structure, and the grain size distribution has a steeper slope than the standard size distribution for the interstellar medium. Combination of SOFIA/HAWC+ data with JCMT observations 450 and 850 μm would be useful to test the proposed scenario based on grain alignment and disruption by RATs.
Living under temporarily arid conditions - succulence as an adaptive strategy

Summary: Succulence is an adaptive strategy that allows plants to remain active during seasonal water shortage. The term was first used formally by Johann (Jean) Bauhin in 1619 to refer to plants with thick, juicy leaves. Its subsequent use and selected definitions are critically discussed, including concepts such as utilizable water, caudiciforms and pachycauls, and root succulence. A unified definition of succulence considers aspects of morphology and anatomy, ecology, and physiology. Stem succulence and the “cactus life form” are used to illustrate the parallel evolution of functional adaptations in morphology, and to contrast the obvious external similarities with the widely variable internal architecture, including the participation of different stem tissues in water storage.
Interpretable Neuroevolutionary Models for Learning Non-Differentiable Functions and Programs

A key factor in the modern success of deep learning is the astonishing expressive power of neural networks. However, this comes at the cost of complex, black-boxed models that are unable to extrapolate beyond the domain of the training dataset, conflicting with goals of expressing physical laws or building human-readable programs. In this paper, we introduce OccamNet, a neural network model that can find interpretable, compact and sparse solutions for fitting data, a la Occam's razor. Our model defines a probability distribution over a non-differentiable function space, and we introduce an optimization method that samples functions and updates the weights based on cross-entropy matching in an evolutionary strategy: we train by biasing the probability mass towards better fitting solutions. We demonstrate that we can fit a variety of algorithms, ranging from simple analytic functions through recursive programs to even simple image classification. Our method takes minimal memory footprint, does not require AI accelerators for efficient training, fits complicated functions in minutes of training on a single CPU, and demonstrates significant performance gains when scaled on GPU. Our implementation, demonstrations and instructions for reproducing the experiments are available at this https URL.
PROTECTIVE ROLE OF SODIUM SELENITE AND VITAMIN E AGAINST RAT ERYTHROCYTES INDUCED BY MERCURY CHLORIDE

The aim of this study was to investigate the effect of subacute mercury chloride exposure on lipid peroxidation and activities of antioxidant enzymes and the possible protective effect of sodium selenite and/or vitamin E. For this purpose, male Wistar rats were divided into eight groups. It was shown that exposure to mercury chloride caused a significant increase in MDA, while significant decrease in SOD, CAT, GPx, GST activities in erythrocytes. Sodium selenite and vitamin E administration had a beneficial effect on the mercury chloride induced oxidative stress. Our results implicate mercury chloride-induced oxidative stress in erythrocytes protected by sodium selenite and vitamin E.
Extragradient with player sampling for faster Nash equilibrium finding

Data-driven modeling increasingly requires to find a Nash equilibrium in multi-player games, e.g. when training GANs. In this paper, we analyse a new extra-gradient method for Nash equilibrium finding, that performs gradient extrapolations and updates on a random subset of players at each iteration. This approach provably exhibits a better rate of convergence than full extra-gradient for non-smooth convex games with noisy gradient oracle. We propose an additional variance reduction mechanism to obtain speed-ups in smooth convex games. Our approach makes extrapolation amenable to massive multiplayer settings, and brings empirical speed-ups, in particular when using a heuristic cyclic sampling scheme. Most importantly, it allows to train faster and better GANs and mixtures of GANs.
Castor canadensis (Beaver) Impoundment Associated with Geomorphology of Southeastern Streams

Abstract We used a geographic information system (GIS) and logistic regression to investigate relationships between geomorphology and Castor canadensis (North American beaver) impoundment of lower-order, blackwater streams of a southeastern landscape. Using GIS, we divided streams into 632 500-m reaches and measured a set of geomorphic variables for each reach. Beavers were most likely to impound stream reaches crossed by roads with a gradient of ≈ 0.6 to 1.2% and watershed sizes of ≈ 2500 ha; reaches with watershed sizes < ≈ 500 ha or > 5000 ha were almost completely avoided. Gradient and road crossings contributed little to discrimination among impounded and unimpounded reaches, suggesting these variables had relatively small influences on beaver impoundment when compared to stream size. Our results indicate that GIS and geomorphic variables can be used to model the impoundment of streams over larger areas (e.g., the proportion of third-order watersheds impounded), but are less accurate at predicting the impoundment of individual reaches. However, the temporal dynamics of impoundment creation and abandonment will need to be incorporated into region-specific models before they can be used in ecosystem integrity assessment.
The Effects of Approximate Multiplication on Convolutional Neural Networks

This article analyzes the effects of approximate multiplication when performing inferences on deep convolutional neural networks (CNNs). The approximate multiplication can reduce the cost of the underlying circuits so that CNN inferences can be performed more efficiently in hardware accelerators. The study identifies the critical factors in the convolution, fully-connected, and batch normalization layers that allow more accurate CNN predictions despite the errors from approximate multiplication. The same factors also provide an arithmetic explanation of why bfloat16 multiplication performs well on CNNs. The experiments are performed with recognized network architectures to show that the approximate multipliers can produce predictions that are nearly as accurate as the FP32 references, without additional training. For example, the ResNet and Inception-v4 models with Mitch-<inline-formula><tex-math notation="LaTeX">$w$</tex-math><alternatives><mml:math><mml:mi>w</mml:mi></mml:math><inline-graphic xlink:href="kim-ieq1-3050989.gif"/></alternatives></inline-formula>6 multiplication produces Top-5 errors that are within 0.2 percent compared to the FP32 references. A brief cost comparison of Mitch-<inline-formula><tex-math notation="LaTeX">$w$</tex-math><alternatives><mml:math><mml:mi>w</mml:mi></mml:math><inline-graphic xlink:href="kim-ieq2-3050989.gif"/></alternatives></inline-formula>6 against bfloat16 is presented where a MAC operation saves up to 80 percent of energy compared to the bfloat16 arithmetic. The most far-reaching contribution of this article is the analytical justification that multiplications can be approximated while additions need to be exact in CNN MAC operations.
Chlamydomonas reinhardtii cDNAs upregulated in low-CO2 conditions: expression and analyses

Unicellular algae acquire the ability to raise their internal CO2 concentrations under low-CO2 conditions because of the presence of a CO2 concentrating mechanism (CCM). In Chlamydomonas reinhardtii, this mechanism is induced when cells grown in high-CO2 conditions are switched to low-CO2 conditions. To elucidate the genes and proteins involved in this mechanism, we constructed a cDNA library from low CO2 adapted cells and differentially screened the library for cDNAs upregulated under low-CO2 conditions. Earlier studies identified six classes of clones specific to low CO2 adapting cells. To identify other genes and proteins playing a role in this mechanism, we have systematically characterized the cDNA clones that appear to be upregulated by low-CO2 adaptation but do not cross-hybridize with the six previously identified classes. We identified seven new classes of clones that are distinctly upregulated in low-CO2 conditions. These clones were checked by Northern analyses, sequencing, and homology studies.
Consequences of acclimation to Microcystis on the selective feeding behavior of the calanoid copepod Eudiaptomus gracilis

We tested the hypothesis that calanoid copepods would adapt to extended periods of Microcystis exposure by increasing selective feeding on alternative food. Copepod (Eudiaptomus gracilis) clearance rates were compared before and after a 5‐d acclimation to Microcystis aeruginosa using paired food mixtures containing a microcystin‐producing (MC+) or ‐lacking (MC‐) strain and the green alga Chlamydomonas reinhardtii. Acclimation reduced the ingestion of Microcystis, increased ingestion of Chlamydomonas, and subsequently increased feeding selectivity. The effect of acclimation was more pronounced for food mixtures with MC+ Microcystis, suggesting that E. gracilis uses a strain‐specific cue related to microcystin or microcystin itself to avoid harmful food. The results indicate that exposure to sublethal abundances of Microcystis may increase copepod tolerance to blooms, given sufficient alternative food. Zooplankton grazing behavior should, therefore, be viewed as flexible and adaptive to extended periods of cyanobacteria blooms.
Learning to Match Distributions for Domain Adaptation

When the training and test data are from different distributions, domain adaptation is needed to reduce dataset bias to improve the model's generalization ability. Since it is difficult to directly match the cross-domain joint distributions, existing methods tend to reduce the marginal or conditional distribution divergence using predefined distances such as MMD and adversarial-based discrepancies. However, it remains challenging to determine which method is suitable for a given application since they are built with certain priors or bias. Thus they may fail to uncover the underlying relationship between transferable features and joint distributions. This paper proposes Learning to Match (L2M) to automatically learn the cross-domain distribution matching without relying on hand-crafted priors on the matching loss. Instead, L2M reduces the inductive bias by using a meta-network to learn the distribution matching loss in a data-driven way. L2M is a general framework that unifies task-independent and human-designed matching features. We design a novel optimization algorithm for this challenging objective with self-supervised label propagation. Experiments on public datasets substantiate the superiority of L2M over SOTA methods. Moreover, we apply L2M to transfer from pneumonia to COVID-19 chest X-ray images with remarkable performance. L2M can also be extended in other distribution matching applications where we show in a trial experiment that L2M generates more realistic and sharper MNIST samples.
LATERALIZED TEMPORAL‐LIMBIC DYSFUNCTION AND PSYCHOPATHOLOGY *

Impressed by the fact that rabies, with its predilection for hippocampal structures, presents with prominent mental symptoms: fear, terror, rage, insomnia, struck by the psychological changes accompanying tumors of the corpus callosum which encroached on the mesial aspect of the hemisphere and by the dysphoric states occurring with ischaemic lesions of the anterior cingulum, Papez, in 1937, stated his celebrated hypothesis. The hippocampus, fornix, mamilloanterior thalamic tract, and its projections to the cingulate gyri formed the anatomical substrate for emotion. MacLean in 1949 expanded the Papez circuit, showing that the septal nuclei, their brain stem connections via the medial forebrain bundle, the amygdaloid nuclei, and the insula were all, anatomically and functionally, part of the same complex neurophysiological system. This system he labeled ‘‘the limbic system’’ in 1952, emphasizing that the anterior cingulate and orbital-frontal components had important inhibitory functions as well as being crucial to autonomic regulation. MacLean also separated the amygdaloid subdivision of the limbic system, related to aggression and defense, from the septal subdivision, related to sexuality. Importantly, he stressed that the frontotemporal region, (posteroorbital-insulartemporopolar-pyriform-amygdaloid-rostral-hippocampal) was essentially a closed physiological system where discharges induced by electrical or strychnine stimulation tended to be confined to these limbic circuits. MacLean in 1970, because of the common symptomatology often seen in ‘‘smouldering limbic epilepsy’’