julilili42/papers huggingface dataset:
Cyclotron resonant scattering feature simulations. I. Thermally averaged cyclotron scattering cross sections, mean free photon-path tables, and electron momentum sampling
2022-03-05

Electron cyclotron resonant scattering features (CRSFs) are observed as absorption-like lines in the spectra of X-ray pulsars. A significant fraction of the computing time for Monte Carlo simulations of these quantum mechanical features is spent on the calculation of the mean free path for each individual photon before scattering, since it involves a complex numerical integration over the scattering cross section and the (thermal) velocity distribution of the scattering electrons. We aim to numerically calculate interpolation tables which can be used in CRSF simulations to sample the mean free path of the scattering photon and the momentum of the scattering electron. The tables also contain all the information required for sampling the scattering electron's final spin. The tables were calculated using an adaptive Simpson integration scheme. The energy and angle grids were refined until a prescribed accuracy is reached. The tables are used by our simulation code to produce artificial CRSF spectra. The electron momenta sampled during these simulations were analyzed and justified using theoretically determined boundaries. We present a complete set of tables suited for mean free path calculations of Monte Carlo simulations of the cyclotron scattering process for conditions expected in typical X-ray pulsar accretion columns (0.01<b></b>
Digitizing Non-Invasive Neuromodulation Trials: Scoping Review, Process Mapping, and Recommendations from a Delphi Panel
2022-03-05

Abstract Although relatively costly and non-scalable, non-invasive neuromodulation interventions are treatment alternatives for neuropsychiatric disorders. The recent developments of highly-deployable transcranial electric stimulation (tES) systems, combined with mobile-Health technologies, could be incorporated in digital trials to overcome methodological barriers and increase equity of access. We convened 61 highly-productive specialists and contacted 8 tES companies to assess 71 issues related to tES digitalization readiness, and processes, barriers, advantages, and opportunities for implementing tES digital trials. Delphi-based recommendations (&gt;60% agreement) were provided. Device appraisal showed moderate digitalization readiness, with high safety and the possibility of trial implementation, but low connectivity. Panelists recognized the potential of tES for scalability, generalizability, and leverage of digital trials processes; although they reached no consensus about aspects regarding methodological biases. We further propose and discuss a conceptual framework for exploiting shared aspects between mobile-Health tES technologies with digital trials methodology to drive future efforts for digitizing tES trials. Graphical Abstract. Consensus Roadmap (A) Recruitment process . The study procedure started with defining the components of the research problem by the core research team. After defining the problems, two different sets of participants (the steering committee (SC) including key leaders of the field identified by the core team and the expert panel (EP) as a more diverse group of experts identified based on the number of publications based on a systematic review) were identified and were invited to participate in a Delphi study. The study facilitators (first and last authors) led the communications with the SC to design the initial questionnaire through an iterative approach. (B) Evidence synthesis: To collect the available evidence, companies producing portable tES (ptES) devices were contacted, based on the companies suggested by the SC and EP to provide details about the available devices. For mapping methodological processes of digitizing tES trials, two distinct strategies were performed and embedded into the questionnaire, namely SIPOC (Suppliers, Inputs, Process, Outputs, and Customer) and SWOT (Strengths, Weaknesses, Opportunities, and Threats) assessment were performed and embedded into the questionnaire. (C) Consensus development: In the next phase, the questionnaire was validated and finalized via collecting and summarizing opinions. Afterward, the SC and EP responded to the final questionnaire, and results were analyzed providing a list of recommendations for running tES digital trials based on a pre-registered consensus threshold.
The well-preserved Late Neolithic dolmen burial of Oberbipp, Switzerland. Construction, use, and post-depositional processes
2022-03-05

Excavation of the Late Neolithic dolmen of Oberbipp BE, Steingasse in the Swiss Central Plateau provided a unique opportunity for a comprehensive study of the archaeological and anthropological evidence. In multidisciplinary studies, we investigated the processes at work during construction, use, and abandonment of the megalithic structure, as well as the dietary habits, subsistence strategy, and possible mobility of the Neolithic population. Archaeological methods included micromorphology, archaeobiology, typology, use-wear analysis, and geology. The anthropological investigation was complemented by an analysis of stable isotope ratios and palaeogenetics. Local topography and the cover of alluvial sediments ensured an extraordinary conservation of the monument. It allowed the preservation of the human remains of at least 42 individuals of both sexes and all ages. The observation of the sedimentary and post-depositional processes, supplemented by an extensive series of radiocarbon dates, allowed us to reconstruct the history of the dolmen in its environment and the definition of at least two deposition phases. We found genetic evidence of lactase intolerance, a local population with a mixed ancestry of early Anatolian farmers and Western hunter-gatherers, and a crop-based diet. Sparse remains of a nearby Late Neolithic settlement sustain the interpretation that this is the burial site of a local farming community. Evidence of higher mobility of females and kinship over three generations solely in the paternal line suggests a virilocal community. Bone-altering pathologies support the assumption of a caring society.
End-to-End Learning for Image Burst Deblurring
2022-03-05

We present a neural network model approach for multi-frame blind deconvolution. The discriminative approach adopts and combines two recent techniques for image deblurring into a single neural network architecture. Our proposed hybrid-architecture combines the explicit prediction of a deconvolution filter and non-trivial averaging of Fourier coefficients in the frequency domain. In order to make full use of the information contained in all images in one burst, the proposed network embeds smaller networks, which explicitly allow the model to transfer information between images in early layers. Our system is trained end-to-end using standard backpropagation on a set of artificially generated training examples, enabling competitive performance in multi-frame blind deconvolution, both with respect to quality and runtime.
On the Relationship between $k$-Planar and $k$-Quasi Planar Graphs
2022-03-05

A graph is -planar if it can be drawn in the plane such that no edge is crossed more than times. A graph is -quasi planar if it can be drawn in the plane with no pairwise crossing edges. The families of -planar and -quasi planar graphs have been widely studied in the literature, and several bounds have been proven on their edge density. Nonetheless, only trivial results are known about the relationship between these two graph families. In this paper we prove that, for , every -planar graph is -quasi planar.
The adiabatic limit of the connection Laplacian
2022-03-05

We study the behaviour of Laplace-type operators H on a complex vector bundle E M in the adiabatic limit of the base space. This space is a fibre bundle M B with compact fibres and the limit corresponds to blowing up directions perpendicular to the fibres by a factor 1/ . Under a gap condition on the fibre-wise eigenvalues we prove existence of effective operators that provide asymptotics to any order in for H (with Dirichlet boundary conditions), on an appropriate almost-invariant subspace of L (E).
Runge-Kutta time discretization of nonlinear parabolic equations studied via discrete maximal parabolic regularity
2022-03-05

For a large class of fully nonlinear parabolic equations, which include gradient flows for energy functionals that depend on the solution gradient, the semidiscretization in time by implicit Runge-Kutta methods such as the Radau IIA methods of arbitrary order is studied. Error bounds are obtained in the norm uniformly on bounded time intervals and, with an improved approximation order, in the parabolic energy norm. The proofs rely on discrete maximal parabolic regularity. This is used to obtain estimates, which are the key to the numerical analysis of these problems.
Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics
2022-03-05

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.
Log terminal singularities, platonic tuples and iteration of Cox rings
2022-03-05

Looking at the well understood case of log terminal surface singularities, one observes that each of them is the quotient of a factorial one by a finite solvable group. The derived series of this group reflects an iteration of Cox rings of surface singularities. We extend this picture to log terminal singularities in any dimension coming with a torus action of complexity one. In this setting, the previously finite groups become solvable torus extensions. As explicit examples, we investigate compound du Val threefold singularities. We give a complete classification and exhibit all the possible chains of iterated Cox rings.
Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
2022-03-05

We describe the first method to automatically estimate the 3D pose of the human body as well as its 3D shape from a single unconstrained image. We estimate a full 3D mesh and show that 2D joints alone carry a surprising amount of information about body shape. The problem is challenging because of the complexity of the human body, articulation, occlusion, clothing, lighting, and the inherent ambiguity in inferring 3D from 2D. To solve this, we first use a recently published CNN-based method, DeepCut, to predict (bottom-up) the 2D body joint locations. We then fit (top-down) a recently published statistical body shape model, called SMPL, to the 2D joints. We do so by minimizing an objective function that penalizes the error between the projected 3D model joints and detected 2D joints. Because SMPL captures correlations in human shape across the population, we are able to robustly fit it to very little data. We further leverage the 3D model to prevent solutions that cause interpenetration. We evaluate our method, SMPLify, on the Leeds Sports, HumanEva, and Human3.6M datasets, showing superior pose accuracy with respect to the state of the art.
Regularly Decomposable Tensors and Classical Spin States
2022-03-05

A spin- state can be represented by a symmetric tensor of order and dimension . Here, can be a positive integer, which corresponds to a boson; can also be a positive half-integer, which corresponds to a fermion. In this paper, we introduce regularly decomposable tensors and show that a spin- state is classical if and only if its representing tensor is a regularly decomposable tensor. In the even-order case, a regularly decomposable tensor is a completely decomposable tensor but not vice versa; a completely decomposable tensors is a sum-of-squares (SOS) tensor but not vice versa; an SOS tensor is a positive semi-definite (PSD) tensor but not vice versa. In the odd-order case, the first row tensor of a regularly decomposable tensor is regularly decomposable and its other row tensors are induced by the regular decomposition of its first row tensor. We also show that complete decomposability and regular decomposability are invariant under orthogonal transformations, and that the completely decomposable tensor cone and the regularly decomposable tensor cone are closed convex cones. Furthermore, in the even-order case, the completely decomposable tensor cone and the PSD tensor cone are dual to each other. The Hadamard product of two completely decomposable tensors is still a completely decomposable tensor. Since one may apply the positive semi-definite programming algorithm to detect whether a symmetric tensor is an SOS tensor or not, this gives a checkable necessary condition for classicality of a spin- state. Further research issues on regularly decomposable tensors are also raised.
How to morph planar graph drawings
2022-03-05

Given an -vertex graph and two straight-line planar drawings of the graph that have the same faces and the same outer face, we show that there is a morph (i.e., a continuous transformation) between the two drawings that preserves straight-line planarity and consists of steps, which we prove is optimal in the worst case. Each step is a unidirectional linear morph, which means that every vertex moves at constant speed along a straight line, and the lines are parallel although the vertex speeds may differ. Thus we provide an efficient version of Cairns' 1944 proof of the existence of straight-line planarity-preserving morphs for triangulated graphs, which required an exponential number of steps.
Bezafibrate Reduces Elevated Hepatic Fumarate in Insulin-Deficient Mice
2022-03-06

Glucotoxic metabolites and pathways play a crucial role in diabetic complications, and new treatment options which improve glucotoxicity are highly warranted. In this study, we analyzed bezafibrate (BEZ) treated, streptozotocin (STZ) injected mice, which showed an improved glucose metabolism compared to untreated STZ animals. In order to identify key molecules and pathways which participate in the beneficial effects of BEZ, we studied plasma, skeletal muscle, white adipose tissue (WAT) and liver samples using non-targeted metabolomics (NMR spectroscopy), targeted metabolomics (mass spectrometry), microarrays and mitochondrial enzyme activity measurements, with a particular focus on the liver. The analysis of muscle and WAT demonstrated that STZ treatment elevated inflammatory pathways and reduced insulin signaling and lipid pathways, whereas BEZ decreased inflammatory pathways and increased insulin signaling and lipid pathways, which can partly explain the beneficial effects of BEZ on glucose metabolism. Furthermore, lysophosphatidylcholine levels were lower in the liver and skeletal muscle of STZ mice, which were reverted in BEZ-treated animals. BEZ also improved circulating and hepatic glucose levels as well as lipid profiles. In the liver, BEZ treatment reduced elevated fumarate levels in STZ mice, which was probably due to a decreased expression of urea cycle genes. Since fumarate has been shown to participate in glucotoxic pathways, our data suggests that BEZ treatment attenuates the urea cycle in the liver, decreases fumarate levels and, in turn, ameliorates glucotoxicity and reduces insulin resistance in STZ mice.
Amortised MAP Inference for Image Super-resolution
2022-03-06

Image super-resolution (SR) is an underdetermined inverse problem, where a large number of plausible high-resolution images can explain the same downsampled image. Most current single image SR methods use empirical risk minimisation, often with a pixel-wise mean squared error (MSE) loss. However, the outputs from such methods tend to be blurry, over-smoothed and generally appear implausible. A more desirable approach would employ Maximum a Posteriori (MAP) inference, preferring solutions that always have a high probability under the image prior, and thus appear more plausible. Direct MAP estimation for SR is non-trivial, as it requires us to build a model for the image prior from samples. Furthermore, MAP inference is often performed via optimisation-based iterative algorithms which don't compare well with the efficiency of neural-network-based alternatives. Here we introduce new methods for amortised MAP inference whereby we calculate the MAP estimate directly using a convolutional neural network. We first introduce a novel neural network architecture that performs a projection to the affine subspace of valid SR solutions ensuring that the high resolution output of the network is always consistent with the low resolution input. We show that, using this architecture, the amortised MAP inference problem reduces to minimising the cross-entropy between two distributions, similar to training generative models. We propose three methods to solve this optimisation problem: (1) Generative Adversarial Networks (GAN) (2) denoiser-guided SR which backpropagates gradient-estimates from denoising to train the network, and (3) a baseline method using a maximum-likelihood-trained image prior. Our experiments show that the GAN based approach performs best on real image data. Lastly, we establish a connection between GANs and amortised variational inference as in e.g. variational autoencoders.
The RHIC Cold QCD Plan for 2017 to 2023: A Portal to the EIC
2022-03-06

The exploration of the fundamental structure of strongly interacting matter has always thrived on the complementarity of lepton scattering and purely hadronic probes. As the community eagerly anticipates a future electron ion collider (EIC) in the U.S., an outstanding scientific opportunity remains to complete "must-do" measurements in p+p and p+A physics in the years preceding the EIC. As we describe in this document, these measurements will be essential to fully realize the scientific promise of the EIC by provid-ing a comprehensive set of measurements in hadronic collisions that, when combined with data from the EIC, will establish the validity and limits of factorization and universality. The outlined program will on the one hand lay the groundwork for the EIC, both scientifically and in terms of refining the experimental requirements for the physics program at the EIC, and thus be the natural next step on the path towards an electron-ion collider. On the other hand, while much of the physics in this program is unique to proton-proton and proton-nucleus collisions and offers discovery potential on its own, when combined with data from the EIC it will provide a broad foundation to a deeper understanding of fundamental QCD.
Controlling Perceptual Factors in Neural Style Transfer
2022-03-06

Neural Style Transfer has shown very exciting results enabling new forms of image manipulation. Here we extend the existing method to introduce control over spatial location, colour information and across spatial scale. We demonstrate how this enhances the method by allowing high-resolution controlled stylisation and helps to alleviate common failure cases such as applying ground textures to sky regions. Furthermore, by decomposing style into these perceptual factors we enable the combination of style information from multiple sources to generate new, perceptually appealing styles from existing ones. We also describe how these methods can be used to more efficiently produce large size, high-quality stylisation. Finally we show how the introduced control measures can be applied in recent methods for Fast Neural Style Transfer.
Non-complete rational T-varieties of complexity one
2022-03-06

We consider rational varieties with a torus action of complexity one and extend the combinatorial approach via the Cox ring developed for the complete case in earlier work to the non-complete, e.g. affine, case. This includes in particular a description of all factorially graded affine algebras of complexity one with only constant homogeneous invertible elements in terms of canonical generators and relations.
The Planar Tree Packing Theorem
2022-03-06

Packing graphs is a combinatorial problem where several given graphs are being mapped into a common host graph such that every edge is used at most once. In the planar tree packing problem we are given two trees T1 and T2 on n vertices and have to find a planar graph on n vertices that is the edge-disjoint union of T1 and T2. A clear exception that must be made is the star which cannot be packed together with any other tree. But according to a conjecture of García et al. from 1997 this is the only exception, and all other pairs of trees admit a planar packing. Previous results addressed various special cases, such as a tree and a spider tree, a tree and a caterpillar, two trees of diameter four, two isomorphic trees, and trees of maximum degree three. Here we settle the conjecture in the affirmative and prove its general form, thus making it the planar tree packing theorem. The proof is constructive and provides a polynomial time algorithm to obtain a packing for two given nonstar trees.
On the Complexity of Bounded Context Switching
2022-03-06

Bounded context switching (BCS) is an under-approximate method for finding violations to safety properties in shared memory concurrent programs. Technically, BCS is a reachability problem that is known to be NP-complete. Our contribution is a parameterized analysis of BCS. The first result is an algorithm that solves BCS when parameterized by the number of context switches (cs) and the size of the memory (m) in O*(m^(cs)2^(cs)). This is achieved by creating instances of the easier problem Shuff which we solve via fast subset convolution. We also present a lower bound for BCS of the form m^o(cs / log(cs)), based on the exponential time hypothesis. Interestingly, closing the gap means settling a conjecture that has been open since FOCS'07. Further, we prove that BCS admits no polynomial kernel. Next, we introduce a measure, called scheduling dimension, that captures the complexity of schedules. We study BCS parameterized by the scheduling dimension (sdim) and show that it can be solved in O*((2m)^(4sdim)4^t)$, where t is the number of threads. We consider variants of the problem for which we obtain (matching) upper and lower bounds.