julilili42/papers huggingface dataset:
Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
2022-02-27

In recent years, Generative Adversarial Networks have achieved impressive results in photorealistic image synthesis. This progress nurtures hopes that one day the classical rendering pipeline can be replaced by efficient models that are learned directly from images. However, current image synthesis models operate in the 2D domain where disentangling 3D properties such as camera viewpoint or object pose is challenging. Furthermore, they lack an interpretable and controllable representation. Our key hypothesis is that the image generation process should be modeled in 3D space as the physical world surrounding us is intrinsically three-dimensional. We define the new task of 3D controllable image synthesis and propose an approach for solving it by reasoning both in 3D space and in the 2D image domain. We demonstrate that our model is able to disentangle latent 3D factors of simple multi-object scenes in an unsupervised fashion from raw images. Compared to pure 2D baselines, it allows for synthesizing scenes that are consistent wrt. changes in viewpoint or object pose. We further evaluate various 3D representations in terms of their usefulness for this challenging task.
On realizability of lines on tropical cubic surfaces and the Brundu-Logar normal form
2022-02-27

We present results on the relative realizability of infinite families of lines on general smooth tropical cubic surfaces. Inspired by the problem of relative realizability of lines on surfaces, we investigate the information we can derive tropically from the Brundu-Logar normal form of smooth cubic surfaces. In particular, we prove that for a residue field of characteristic the tropicalization of the Brundu-Logar normal form is not smooth. We also take first steps in investigating the behavior of the tropicalized lines.
Attacking Optical Flow
2022-02-27

Deep neural nets achieve state-of-the-art performance on the problem of optical flow estimation. Since optical flow is used in several safety-critical applications like self-driving cars, it is important to gain insights into the robustness of those techniques. Recently, it has been shown that adversarial attacks easily fool deep neural networks to misclassify objects. The robustness of optical flow networks to adversarial attacks, however, has not been studied so far. In this paper, we extend adversarial patch attacks to optical flow networks and show that such attacks can compromise their performance. We show that corrupting a small patch of less than 1% of the image size can significantly affect optical flow estimates. Our attacks lead to noisy flow estimates that extend significantly beyond the region of the attack, in many cases even completely erasing the motion of objects in the scene. While networks using an encoder-decoder architecture are very sensitive to these attacks, we found that networks using a spatial pyramid architecture are less affected. We analyse the success and failure of attacking both architectures by visualizing their feature maps and comparing them to classical optical flow techniques which are robust to these attacks. We also demonstrate that such attacks are practical by placing a printed pattern into real scenes.
P4-Protect: 1+1 Path Protection for P4
2022-02-27

1+1 protection is a method to secure traffic between two nodes against failures in between. The sending node duplicates the traffic and forwards it over two disjoint paths. The receiving node assures that only a single copy of the traffic is further forwarded to its destination. In contrast to other protection schemes, this method prevents almost any packet loss in case of failures. 1+1 protection is usually applied on the optical layer, on Ethernet, or on MPLS. In this work we propose the application of 1+1 for P4-based IP networks. We define an 1+1 protection header for that purpose. We describe the behavior of sending and receiving nodes and provide a P4-based implementation for the BMv2 software switch and the hardware switch Tofino Edgecore Wedge 100BF-32X. We illustrate how to secure traffic, e.g. individual TCP flows, on the Internet with this approach. Finally, we present performance results showing that the P4-based implementation efficiently works on the Tofino Edgecore Wedge 100BF-32X.
Compiling PL/SQL Away
2022-02-27

"PL/SQL functions are slow," is common developer wisdom that derives from the tension between set-oriented SQL evaluation and statement-by-statement PL/SQL interpretation. We pursue the radical approach of compiling PL/SQL away, turning interpreted functions into regular subqueries that can then be efficiently evaluated together with their embracing SQL query, avoiding any PL/SQL to SQL context switches. Input PL/SQL functions may exhibit arbitrary control flow. Iteration, in particular, is compiled into SQL-level recursion. RDBMSs across the board reward this compilation effort with significant run time savings that render established developer lore questionable.
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation
2022-02-27

The objective of ordinal embedding is to find a Euclidean representation of a set of abstract items, using only answers to triplet comparisons of the form "Is item closer to the item or item ?". In recent years, numerous algorithms have been proposed to solve this problem. However, there does not exist a fair and thorough assessment of these embedding methods and therefore several key questions remain unanswered: Which algorithms perform better when the embedding dimension is constrained or few triplet comparisons are available? Which ones scale better with increasing sample size or dimension? In our paper, we address these questions and provide the first comprehensive and systematic empirical evaluation of existing algorithms as well as a new neural network approach. We find that simple, relatively unknown, non-convex methods consistently outperform all other algorithms, including elaborate approaches based on neural networks or landmark approaches. This finding can be explained by our insight that many of the non-convex optimization approaches do not suffer from local optima. Our comprehensive assessment is enabled by our unified library of popular embedding algorithms that leverages GPU resources and allows for fast and accurate embeddings of millions of data points.
Simultaneous observation of high order multiple quantum coherences at ultralow magnetic fields
2022-02-27

We present a method for the simultaneous observation of heteronuclear multi-quantum coherences (up to the 3rd order), which give an additional degree of freedom for ultralow magnetic field (ULF) MR experiments, where the chemical shift is negligible. The nonequilibrium spin state is generated by Signal Amplification By Reversible Exchange (SABRE) and detected at ULF with SQUID-based NMR. We compare the results obtained by the heteronuclei Correlated SpectroscopY (COSY) with a Flip Angle FOurier Series (FAFOS) method. COSY allows a quantitative analysis of homo- and heteronuclei quantum coherences.
A filtered Boris algorithm for charged-particle dynamics in a strong magnetic field
2022-02-27

A modification of the standard Boris algorithm, called filtered Boris algorithm, is proposed for the numerical integration of the equations of motion of charged particles in a strong non-uniform magnetic field in the asymptotic scaling known as maximal ordering. With an appropriate choice of filters, second-order error bounds in the position and in the parallel velocity, and first-order error bounds in the normal velocity are obtained with respect to the scaling parameter. The proof compares the modulated Fourier expansions of the exact and the numerical solutions. Numerical experiments illustrate the error behaviour of the filtered Boris algorithm.
Thompson-like characterization of solubility for products of finite groups
2022-02-27

A remarkable result of Thompson states that a finite group is soluble if and only if its two-generated subgroups are soluble. This result has been generalized in numerous ways, and it is in the core of a wide area of research in the theory of groups, aiming for global properties of groups from local properties of two-generated (or more generally, -generated) subgroups. We contribute an extension of Thompson's theorem from the perspective of factorized groups. More precisely, we study finite groups with subgroups such that is soluble for all and . In this case, the group is said to be an -connected product of the subgroups and for the class of all finite soluble groups. Our main theorem states that is -connected if and only if is soluble. In the course of the proof we derive a result of own interest about independent primes regarding the soluble graph of almost simple groups.
A short observational view of black hole X-ray binaries with INTEGRAL
2022-02-27

Accreting black holes are unique tools to understand the physics under extreme gravity. While black hole X-ray binaries differ vastly in mass from AGN, their accretion and ejection flows are assumed to be essentially similar. Black hole X-ray binaries or microquasars are, however, quasars for the impatient as variability timescales scale directly with mass. State changes, i.e., strong variations in emission properties, in black hole X-ray binaries can happen within hours and whole outburst cycles within months to years. But our understanding of the drivers of such changes and the contributions of individual accretion and ejection components to the overall emission is still lacking. Here, I highlight some of the INTEGRAL's unique contributions to the understanding of black hole X-ray binaries through its coverage of the energies above the spectral cutoff, its long uninterrupted monitoring observations and the measurements of hard X-ray / soft -ray polarization.
On a Conjecture of Lovász on Circle-Representations of Simple 4-Regular Planar Graphs
2022-02-27

Lovász conjectured that every connected 4-regular planar graph G admits a realization as a system of circles, i.e., it can be drawn on the plane utilizing a set of circles, such that the vertices of G correspond to the intersection and touching points of the circles and the edges of G are the arc segments among pairs of intersection and touching points of the circles. In this paper, we settle this conjecture. In particular, (a) we first provide tight upper and lower bounds on the number of circles needed in a realization of any simple 4-regular planar graph, (b) we affirmatively answer Lovász's conjecture, if G is 3-connected, and (c) we demonstrate an infinite class of simple connected 4-regular planar graphs which are not 3-connected (i.e., either simply connected or biconnected) and do not admit realizations as a system of circles.
Magnetic ordering in metal-free radical thin films
2022-02-27

Molecular systems are materials that intersect with many different promising fields such as organic/molecular electronics and spintronics, organic magnetism and quantum computing1-7. Particularly, magnetism in organic materials is very intriguing: the possibility to realize long-range magnetic order in completely metal-free systems means that magnetic moments are coupled to useful properties of organic materials, such as optical transparency, low-cost fabrication, and flexible chemical design. Magnetic ordering in light elements, such as nitrogen and carbon, has been studied in magnetic-edged graphene nanoribbons8 and bilayers9, and polymers10 while in organic thin films most of the investigations show this effect as due to the proximity of light atoms to heavy metals, impurities, or vacancies11. Purely organic radicals are molecules that carry one unpaired electron giving rise to a permanent magnetic moment, in the complete absence of metal ions.12-14 Inspired by their tremendous potential, here we investigate thin films of an exceptionally chemically stable Blatter radical derivative15 by using X-ray magnetic circular dichroism (XMCD)16-18. Here we observe XMCD at the nitrogen K-edge. Our results show a magnetic ordering different than in the single crystals and calculations indicate, although weak, a long-range intermolecular coupling. We anticipate our work to be a starting point for investigating and modelling magnetic behaviour in purely organic thin films. The tuning of the magnetic properties by the molecular arrangement in organic films is an exciting perspective towards revealing new properties and applications.
Coloring outerplanar graphs and planar 3-trees with small monochromatic components
2022-02-27

In this work, we continue the study of vertex colorings of graphs, in which adjacent vertices are allowed to be of the same color as long as each monochromatic connected component is of relatively small cardinality. We focus on colorings with two and three available colors and present improved bounds on the size of the monochromatic connected components for two meaningful subclasses of planar graphs, namely maximal outerplanar graphs and complete planar 3-trees.
Theia: An advanced optical neutrino detector
2022-02-27

New developments in liquid scintillators, high-efficiency, fast photon detectors, and chromatic photon sorting have opened up the possibility for building a large-scale detector that can discriminate between Cherenkov and scintillation signals. Such a detector could exploit these two distinct signals to observe particle direction and species using Cherenkov light while also having the excellent energy resolution and low threshold of a scintillator detector. Situated in a deep underground laboratory, and utilizing new techniques in computing and reconstruction techniques, such a detector could achieve unprecedented levels of background rejection, thus enabling a rich physics program that would span topics in nuclear, high-energy, and astrophysics, and across a dynamic range from hundreds of keV to many GeV. The scientific program would include observations of low- and high-energy solar neutrinos, determination of neutrino mass ordering and measurement of the neutrino CP violating phase, observations of diffuse supernova neutrinos and neutrinos from a supernova burst, sensitive searches for nucleon decay and, ultimately, a search for NeutrinoLess Double Beta Decay (NLDBD) with sensitivity reaching the normal ordering regime of neutrino mass phase space. This paper describes Theia, a detector design that incorporates these new technologies in a practical and affordable way to accomplish the science goals described above. We consider two scenarios, one in which Theia would reside in a cavern the size and shape of the caverns intended to be excavated for the Deep Underground Neutrino Experiment (DUNE) which we call Theia 25, and a larger 100 ktonne version (Theia 100) that could achieve an even broader and more sensitive scientific program.
Dynamics of neural fields with exponential temporal kernel
2022-02-27

We consider the standard neural field equation with an exponential temporal kernel. We analyze the time-independent (static) and time-dependent (dynamic) bifurcations of the equilibrium solution and the emerging spatiotemporal wave patterns. We show that an exponential temporal kernel does not allow static bifurcations such as saddle-node, pitchfork, and in particular, static Turing bifurcations. However, the exponential temporal kernel possesses the important property that it takes into account the finite memory of past activities of neurons, which Green's function does not. Through a dynamic bifurcation analysis, we give explicit bifurcation conditions. Hopf bifurcations lead to temporally non-constant, but spatially constant solutions, but Turing-Hopf bifurcations generate spatially and temporally non-constant solutions, in particular, traveling waves. Bifurcation parameters are the coefficient of the exponential temporal kernel, the transmission speed of neural signals, the time delay rate of synapses, and the ratio of excitatory to inhibitory synaptic weights.
The Phenotypic Course of Age-Related Macular Degeneration for ARMS2/HTRA1
2022-02-28

Carriers of the risk haplotype at ARMS2/HTRA1 have a particularly high risk of late AMD at a relatively early age. Data suggest that risk variants at ARMS2/HTRA1 act as a strong catalyst of progression once early signs are present. The phenotypic spectrum resembles that of complement genes, only with higher risks of CNV.
Minerals and Cancer: Overview of the Possible Diagnostic Value
2022-02-28

Cancer is the second leading cause of death worldwide and is expected to increase by one-third over the next two decades, in parallel with the growing proportion of the elderly population. Treatment and control of cancer incidence is a global issue. Since there is no clear way to prevent or cure this deadly malignancy, diagnostic, predictive, and prognostic markers for oncological diseases are of great therapeutic value. Minerals and trace elements are important micronutrients for normal physiological function of the body. They are abundant in natural food sources and are regularly included in dietary supplements whereas highly processed industrial food often contains reduced or altered amounts of them. In modern society, the daily intake, storage pools, and homeostasis of these micronutrients are dependent on certain dietary habits and can be thrown out of balance by malignancies. The current work summarizes the data on minerals and trace elements associated with abnormal accumulation or depletion states in tumor patients and discusses their value as potential tumor-associated biomarkers that could be introduced into cancer therapy.
Triple Targeting of HER Receptors Overcomes Heregulin-mediated Resistance to EGFR Blockade in Colorectal Cancer
2022-02-28

Abstract Current treatment options for patients with advanced colorectal cancers include anti-EGFR/HER1 therapy with the blocking antibody cetuximab. Although a subset of patients with KRAS WT disease initially respond to the treatment, resistance develops in almost all cases. Relapse has been associated with the production of the ligand heregulin (HRG) and/or compensatory signaling involving the receptor tyrosine kinases HER2 and HER3. Here, we provide evidence that triple-HER receptor blockade based on a newly developed bispecific EGFR×HER3-targeting antibody (scDb-Fc) together with the HER2-blocking antibody trastuzumab effectively inhibited HRG-induced HER receptor phosphorylation, downstream signaling, proliferation, and stem cell expansion of DiFi and LIM1215 colorectal cancer cells. Comparative analyses revealed that the biological activity of scDb-Fc plus trastuzumab was sometimes even superior to that of the combination of the parental antibodies, with PI3K/Akt pathway inhibition correlating with improved therapeutic response and apoptosis induction as seen by single-cell analysis. Importantly, growth suppression by triple-HER targeting was recapitulated in primary KRAS WT patient-derived organoid cultures exposed to HRG. Collectively, our results provide strong support for a pan-HER receptor blocking approach to combat anti-EGFR therapy resistance of KRAS WT colorectal cancer tumors mediated by the upregulation of HRG and/or HER2/HER3 signaling.
Rosacea and Dry Eye Disease
2022-02-28

Ocular rosacea is a chronic potentially sight-threatening inflammatory condition, which can occur in approximately 20% of patients without skin involvement. However, an accurate diagnosis of ocular rosacea has not been defined yet due to its rather nonspecific symptoms and clinical findings. Therefore, this article updates the current recommendations for diagnosis and treatment of ocular rosacea and the previously published consensus recommendations from the ROSCO expert panel on the management of rosacea.
Generation of two SPAST knockout human induced pluripotent stem cell lines to create a model for Hereditary Spastic Paraplegia type 4
2022-02-28

Spastin is a an ATPase that severs microtubules therby regulating amount and mobility of these structures. Mutations in the SPAST gene (SPG4) are the most common form of Hereditary Spastic Paraplegia (HSP). Here, we report the generation of a homozygous and a heterozygous SPAST knockout induced pluripotent stem cell (iPSC) line from a healthy control iPSC line using CRISPR/Cas9 technology.
The Electron Capture in 163 Ho Experiment - a Short Update
2022-02-28

The definition of the absolute neutrino mass scale is one of the main goals of the Particle Physics today. \\nThe study of the end-point regions of the - and electron capture (EC) spectrum offers a possibility to determine the effective electron (anti-)neutrino mass in a completely model independent way, as it only relies on the energy and momentum conservation. \\nThe ECHo (Electron Capture in Ho) experiment has been designed in the attempt to measure the effective mass of the electron neutrino by performing high statistics and high energy resolution measurements of the Ho electron capture spectrum. To achieve this goal, large arrays of low temperature metallic magnetic calorimeters (MMCs) implanted with with Ho are used. \\nHere we report on the structure and the status of the experiment.
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
2022-02-28

The ability to detect objects regardless of image distortions or weather conditions is crucial for real-world applications of deep learning like autonomous driving. We here provide an easy-to-use benchmark to assess how object detection models perform when image quality degrades. The three resulting benchmark datasets, termed Pascal-C, Coco-C and Cityscapes-C, contain a large variety of image corruptions. We show that a range of standard object detection models suffer a severe performance loss on corrupted images (down to 30--60\\% of the original performance). However, a simple data augmentation trick---stylizing the training images---leads to a substantial increase in robustness across corruption type, severity and dataset. We envision our comprehensive benchmark to track future progress towards building robust object detection models. Benchmark, code and data are publicly available.
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
2022-02-28

The evaluation of robustness against adversarial manipulation of neural networks-based classifiers is mainly tested with empirical attacks as methods for the exact computation, even when available, do not scale to large networks. We propose in this paper a new white-box adversarial attack wrt the -norms for aiming at finding the minimal perturbation necessary to change the class of a given input. It has an intuitive geometric meaning, yields quickly high quality results, minimizes the size of the perturbation (so that it returns the robust accuracy at every threshold with a single run). It performs better or similar to state-of-the-art attacks which are partially specialized to one -norm, and is robust to the phenomenon of gradient masking.
Combining Generative and Discriminative Models for Hybrid Inference
2022-02-28

A graphical model is a structured representation of the data generating process. The traditional method to reason over random variables is to perform inference in this graphical model. However, in many cases the generating process is only a poor approximation of the much more complex true data generating process, leading to suboptimal estimation. The subtleties of the generative process are however captured in the data itself and we can `learn to infer', that is, learn a direct mapping from observations to explanatory latent variables. In this work we propose a hybrid model that combines graphical inference with a learned inverse model, which we structure as in a graph neural network, while the iterative algorithm as a whole is formulated as a recurrent neural network. By using cross-validation we can automatically balance the amount of work performed by graphical inference versus learned inference. We apply our ideas to the Kalman filter, a Gaussian hidden Markov model for time sequences, and show, among other things, that our model can estimate the trajectory of a noisy chaotic Lorenz Attractor much more accurately than either the learned or graphical inference run in isolation.