title
stringlengths
7
239
abstract
stringlengths
7
2.76k
cs
int64
0
1
phy
int64
0
1
math
int64
0
1
stat
int64
0
1
quantitative biology
int64
0
1
quantitative finance
int64
0
1
"I can assure you [$\ldots$] that it's going to be all right" -- A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships
As technology become more advanced, those who design, use and are otherwise affected by it want to know that it will perform correctly, and understand why it does what it does, and how to use it appropriately. In essence they want to be able to trust the systems that are being designed. In this survey we present assu...
1
0
0
1
0
0
Study of Electro-Caloric Effect in Ca and Sn co-Doped BaTiO3 Ceramics
The present work deals with the study of structural, ferroelectric, dielectric and electro-caloric effects in lead free ferroelectric polycrystalline Ba1-xCaxTi0.95Sn0.05O3 (x= 2, 5 and 10 %) i.e., Ca, Sn co-doped BaTiO3 (BTO). Phase purity of the samples is confirmed from X-ray data by using Rietveld refinement. 119...
0
1
0
0
0
0
Motivic Measures through Waldhausen K-Theories
In this paper we introduce the notion of a $cdp$-functor to a Waldhausen category. We show that such functors admit extensions that satisfy the excision property, to which we associate Euler-Poincaré characteristics that send the class of a proper scheme to the class of its image. As an application, we show that the ...
0
0
1
0
0
0
A Brief Introduction to Machine Learning for Engineers
This monograph aims at providing an introduction to key concepts, algorithms, and theoretical results in machine learning. The treatment concentrates on probabilistic models for supervised and unsupervised learning problems. It introduces fundamental concepts and algorithms by building on first principles, while also...
1
0
0
1
0
0
The Development of Microfluidic Systems within the Harrison Research Team
D. Jed Harrison is a full professor at the Department of Chemistry at the University of Alberta. Here he describes the development of microfluidic techniques in his lab from the initial demonstration of an integrated separation system for samples in liquids to the recent development of methods to fabricate crystallin...
0
0
0
0
1
0
Landau phonon-roton theory revisited for superfluid helium 4 and Fermi gases
Liquid helium and spin-1/2 cold-atom Fermi gases both exhibit in their superfluid phase two distinct types of excitations, gapless phonons and gapped rotons or fermionic pair-breaking excitations. In the long wavelength limit, revising and extending Landau and Khalatnikov's theory initially developed for helium [ZhET...
0
1
0
0
0
0
Counting points on hyperelliptic curves with explicit real multiplication in arbitrary genus
We present a probabilistic Las Vegas algorithm for computing the local zeta function of a genus-$g$ hyperelliptic curve defined over $\mathbb F_q$ with explicit real multiplication (RM) by an order $\Z[\eta]$ in a degree-$g$ totally real number field. It is based on the approaches by Schoof and Pila in a more favorab...
1
0
0
0
0
0
Minimal surfaces and Schwarz lemma
We prove a sharp Schwarz type inequality for the Weierstrass-Enneper representation of the minimal surfaces.
0
0
1
0
0
0
Estimating activity cycles with probabilistic methods I. Bayesian Generalised Lomb-Scargle Periodogram with Trend
Period estimation is one of the central topics in astronomical time series analysis, where data is often unevenly sampled. Especially challenging are studies of stellar magnetic cycles, as there the periods looked for are of the order of the same length than the datasets themselves. The datasets often contain trends,...
0
1
0
1
0
0
Mean Actor Critic
We propose a new algorithm, Mean Actor-Critic (MAC), for discrete-action continuous-state reinforcement learning. MAC is a policy gradient algorithm that uses the agent's explicit representation of all action values to estimate the gradient of the policy, rather than using only the actions that were actually executed...
1
0
0
1
0
0
HAWC Observations Strongly Favor Pulsar Interpretations of the Cosmic-Ray Positron Excess
Recent measurements of the Geminga and B0656+14 pulsars by the gamma-ray telescope HAWC (along with earlier measurements by Milagro) indicate that these objects generate significant fluxes of very high-energy electrons. In this paper, we use the very high-energy gamma-ray intensity and spectrum of these pulsars to ca...
0
1
0
0
0
0
Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning
Deep neural networks require a large amount of labeled training data during supervised learning. However, collecting and labeling so much data might be infeasible in many cases. In this paper, we introduce a source-target selective joint fine-tuning scheme for improving the performance of deep learning tasks with ins...
1
0
0
1
0
0
The Convex Feasible Set Algorithm for Real Time Optimization in Motion Planning
With the development of robotics, there are growing needs for real time motion planning. However, due to obstacles in the environment, the planning problem is highly non-convex, which makes it difficult to achieve real time computation using existing non-convex optimization algorithms. This paper introduces the conve...
1
0
0
0
0
0
Continuous-Time Visual-Inertial Odometry for Event Cameras
Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. However, due to the fundamentally differ...
1
0
0
0
0
0
Reconstructing a $f(R)$ theory from the $α$-Attractors
We show an analogy at high curvature between a $f(R) = R + aR^{n - 1} + bR^2$ theory and the $\alpha$-Attractors. We calculate the expressions of the parameters $a$, $b$ and $n$ as functions of $\alpha$ and the predictions of the model $f(R) = R + aR^{n - 1} + bR^2$ on the scalar spectral index $n_{\rm s}$ and the te...
0
1
0
0
0
0
Systems of ergodic BSDE arising in regime switching forward performance processes
We introduce and solve a new type of quadratic backward stochastic differential equation systems defined in an infinite time horizon, called \emph{ergodic BSDE systems}. Such systems arise naturally as candidate solutions to characterize forward performance processes and their associated optimal trading strategies in...
0
0
0
0
0
1
Extraction and Classification of Diving Clips from Continuous Video Footage
Due to recent advances in technology, the recording and analysis of video data has become an increasingly common component of athlete training programmes. Today it is incredibly easy and affordable to set up a fixed camera and record athletes in a wide range of sports, such as diving, gymnastics, golf, tennis, etc. H...
1
0
0
0
0
0
The inertial Jacquet-Langlands correspondence
We give a parametrization of the simple Bernstein components of inner forms of a general linear group over a local field by invariants constructed from type theory, and explicitly describe its behaviour under the Jacquet-Langlands correspondence. Along the way, we prove a conjecture of Broussous, Sécherre and Stevens...
0
0
1
0
0
0
Universal geometric constraints during epithelial jamming
As an injury heals, an embryo develops, or a carcinoma spreads, epithelial cells systematically change their shape. In each of these processes cell shape is studied extensively, whereas variation of shape from cell-to-cell is dismissed most often as biological noise. But where do cell shape and variation of cell shap...
0
1
0
0
0
0
Semi-independent resampling for particle filtering
Among Sequential Monte Carlo (SMC) methods,Sampling Importance Resampling (SIR) algorithms are based on Importance Sampling (IS) and on some resampling-based)rejuvenation algorithm which aims at fighting against weight degeneracy. However %whichever the resampling technique used this mechanism tends to be insufficien...
0
0
0
1
0
0
Free Information Flow Benefits Truth Seeking
How can we approach the truth in a society? It may depend on various factors. In this paper, using a well-established truth seeking model, we show that the persistent free information flow will bring us to the truth. Here the free information flow is modeled as the environmental random noise that could alter one's co...
1
1
1
0
0
0
Towards a Holistic Approach to Designing Theory-based Mobile Health Interventions
Increasing evidence has shown that theory-based health behavior change interventions are more effective than non-theory-based ones. However, only a few segments of relevant studies were theory-based, especially the studies conducted by non-psychology researchers. On the other hand, many mobile health interventions, e...
1
0
0
0
0
0
Connections between transport of intensity equation and two-dimensional phase unwrapping
In a recent publication [Appl. Opt. 55, 2418 (2016)], a method for two-dimensional phase unwrapping based on the transport of intensity equation (TIE) was studied. We wish to show that this approach is associated with the standard least squares phase unwrapping algorithm, but with additional numerical errors.
0
1
0
0
0
0
On approximations of Value at Risk and Expected Shortfall involving kurtosis
We derive new approximations for the Value at Risk and the Expected Shortfall at high levels of loss distributions with positive skewness and excess kurtosis, and we describe their precisions for notable ones such as for exponential, Pareto type I, lognormal and compound (Poisson) distributions. Our approximations ar...
0
0
0
0
0
1
DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications
Computational methods that predict differential gene expression from histone modification signals are highly desirable for understanding how histone modifications control the functional heterogeneity of cells through influencing differential gene regulation. Recent studies either failed to capture combinatorial effec...
0
0
0
1
0
0
t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data
Modern datasets and models are notoriously difficult to explore and analyze due to their inherent high dimensionality and massive numbers of samples. Existing visualization methods which employ dimensionality reduction to two or three dimensions are often inefficient and/or ineffective for these datasets. This paper ...
1
0
0
1
0
0
Coma Cluster Ultra-Diffuse Galaxies Are Not Standard Radio Galaxies
Matching members in the Coma cluster catalogue of ultra-diffuse galaxies (UDGs, Yagi et al. 2016) from SUBARU imaging with a very deep radio continuum survey source catalogue of the cluster (Miller et al. 2009) using the Karl G. Jansky Very Large Array (VLA) within a rectangular region of ~ 1.19 square degrees centre...
0
1
0
0
0
0
LD-SDS: Towards an Expressive Spoken Dialogue System based on Linked-Data
In this work we discuss the related challenges and describe an approach towards the fusion of state-of-the-art technologies from the Spoken Dialogue Systems (SDS) and the Semantic Web and Information Retrieval domains. We envision a dialogue system named LD-SDS that will support advanced, expressive, and engaging use...
1
0
0
0
0
0
On a spiked model for large volatility matrix estimation from noisy high-frequency data
Recently, inference about high-dimensional integrated covariance matrices (ICVs) based on noisy high-frequency data has emerged as a challenging problem. In the literature, a pre-averaging estimator (PA-RCov) is proposed to deal with the microstructure noise. Using the large-dimensional random matrix theory, it has b...
0
0
0
1
0
0
Graph-based Features for Automatic Online Abuse Detection
While online communities have become increasingly important over the years, the moderation of user-generated content is still performed mostly manually. Automating this task is an important step in reducing the financial cost associated with moderation, but the majority of automated approaches strictly based on messa...
1
0
0
0
0
0
All Classical Adversary Methods are Equivalent for Total Functions
We show that all known classical adversary lower bounds on randomized query complexity are equivalent for total functions, and are equal to the fractional block sensitivity $\text{fbs}(f)$. That includes the Kolmogorov complexity bound of Laplante and Magniez and the earlier relational adversary bound of Aaronson. Th...
1
0
0
0
0
0
A new approach for short-spacing correction of radio interferometric data sets
The short-spacing problem describes the inherent inability of radio-interferometric arrays to measure the integrated flux and structure of diffuse emission associated with extended sources. New interferometric arrays, such as SKA, require solutions to efficiently combine interferometer and single-dish data. We presen...
0
1
0
0
0
0
Data and uncertainty in extreme risks - a nonlinear expectations approach
Estimation of tail quantities, such as expected shortfall or Value at Risk, is a difficult problem. We show how the theory of nonlinear expectations, in particular the Data-robust expectation introduced in [5], can assist in the quantification of statistical uncertainty for these problems. However, when we are in a h...
0
0
1
1
0
0
Flow equations for cold Bose gases
We derive flow equations for cold atomic gases with one macroscopically populated energy level. The generator is chosen such that the ground state decouples from all other states in the system as the renormalization group flow progresses. We propose a self-consistent truncation scheme for the flow equations at the le...
0
1
0
0
0
0
Fluid flows shaping organism morphology
A dynamic self-organized morphology is the hallmark of network-shaped organisms like slime moulds and fungi. Organisms continuously re-organize their flexible, undifferentiated body plans to forage for food. Among these organisms the slime mould Physarum polycephalum has emerged as a model to investigate how organism...
0
0
0
0
1
0
Frames of exponentials and sub-multitiles in LCA groups
In this note we investigate the existence of frames of exponentials for $L^2(\Omega)$ in the setting of LCA groups. Our main result shows that sub-multitiling properties of $\Omega \subset \widehat{G}$ with respect to a uniform lattice $\Gamma$ of $\widehat{G}$ guarantee the existence of a frame of exponentials with ...
0
0
1
0
0
0
Exponential Random Graph Models with Big Networks: Maximum Pseudolikelihood Estimation and the Parametric Bootstrap
With the growth of interest in network data across fields, the Exponential Random Graph Model (ERGM) has emerged as the leading approach to the statistical analysis of network data. ERGM parameter estimation requires the approximation of an intractable normalizing constant. Simulation methods represent the state-of-t...
0
0
0
1
0
0
Critical behavior of a stochastic anisotropic Bak-Sneppen model
In this paper we present our study on the critical behavior of a stochastic anisotropic Bak-Sneppen (saBS) model, in which a parameter $\alpha$ is introduced to describe the interaction strength among nearest species. We estimate the threshold fitness $f_c$ and the critical exponent $\tau_r$ by numerically integratin...
0
1
0
0
0
0
Probability, Statistics and Planet Earth, I: Geotemporal covariances
The study of covariances (or positive definite functions) on the sphere (the Earth, in our motivation) goes back to Bochner and Schoenberg (1940--42) and to the first author (1969, 1973), among others. Extending to the geotemporal case (sphere cross line, for position and time) was for a long time an obstacle to geos...
0
1
0
1
0
0
Gang-GC: Locality-aware Parallel Data Placement Optimizations for Key-Value Storages
Many cloud applications rely on fast and non-relational storage to aid in the processing of large amounts of data. Managed runtimes are now widely used to support the execution of several storage solutions of the NoSQL movement, particularly when dealing with big data key-value store-driven applications. The benefits...
1
0
0
0
0
0
Good cyclic codes and the uncertainty principle
A long standing problem in the area of error correcting codes asks whether there exist good cyclic codes. Most of the known results point in the direction of a negative answer. The uncertainty principle is a classical result of harmonic analysis asserting that given a non-zero function $f$ on some abelian group, eith...
1
0
1
0
0
0
An Amateur Drone Surveillance System Based on Cognitive Internet of Things
Drones, also known as mini-unmanned aerial vehicles, have attracted increasing attention due to their boundless applications in communications, photography, agriculture, surveillance and numerous public services. However, the deployment of amateur drones poses various safety, security and privacy threats. To cope wit...
1
0
0
0
0
0
Two-species boson mixture on a ring: A group theoretic approach to the quantum dynamics of low-energy excitations
We investigate the weak excitations of a system made up of two condensates trapped in a Bose-Hubbard ring and coupled by an interspecies repulsive interaction. Our approach, based on the Bogoliubov approximation scheme, shows that one can reduce the problem Hamiltonian to the sum of sub-Hamiltonians $\hat{H}_k$, each...
0
1
0
0
0
0
On a simple model of X_0(N)
We find plane models for all $X_0(N)$, $N\geq 2$. We observe a map from the modular curve $X_0(N)$ to the projective plane constructed using modular forms of weight $12$ for the group $\Gamma_0(N)$; the Ramanujan function $\Delta$, $\Delta(N\cdot)$ and the third power of Eisestein series of weight $4$, $E_4^3$, and p...
0
0
1
0
0
0
A Supervised STDP-based Training Algorithm for Living Neural Networks
Neural networks have shown great potential in many applications like speech recognition, drug discovery, image classification, and object detection. Neural network models are inspired by biological neural networks, but they are optimized to perform machine learning tasks on digital computers. The proposed work explor...
1
0
0
1
0
0
Optimal Topology Design for Disturbance Minimization in Power Grids
The transient response of power grids to external disturbances influences their stable operation. This paper studies the effect of topology in linear time-invariant dynamics of different power grids. For a variety of objective functions, a unified framework based on $H_2$ norm is presented to analyze the robustness t...
1
0
1
0
0
0
Asymptotic behaviour of the Christoffel functions on the Unit Ball in the presence of a Mass on the Sphere
We present a family of mutually orthogonal polynomials on the unit ball with respect to an inner product which includes a mass uniformly distributed on the sphere. First, connection formulas relating these multivariate orthogonal polynomials and the classical ball polynomials are obtained. Then, using the representat...
0
0
1
0
0
0
Tangent: Automatic Differentiation Using Source Code Transformation in Python
Automatic differentiation (AD) is an essential primitive for machine learning programming systems. Tangent is a new library that performs AD using source code transformation (SCT) in Python. It takes numeric functions written in a syntactic subset of Python and NumPy as input, and generates new Python functions which...
1
0
0
1
0
0
Ca II K 1-A Emission Index Composites
We describe here a procedure to combine measurements in the 393.37 nm Ca II K spectral line taken at different observatories. Measurements from the National Solar Observatory (NSO) Integrated Sunlight Spectrometer (ISS) on the Synoptic Optical Long-term Investigations of the Sun (SOLIS) telescope, the NSO/Sac Peak Ca...
0
1
0
0
0
0
Application of the Bead Perturbation Technique to a Study of a Tunable 5 GHz Annular Cavity
Microwave cavities for a Sikivie-type axion search are subject to several constraints. In the fabrication and operation of such cavities, often used at frequencies where the resonator is highly overmoded, it is important to be able to reliably identify several properties of the cavity. Those include identifying the s...
0
1
0
0
0
0
Homogeneous Kobayashi-hyperbolic manifolds with high-dimensional group of holomorphic automorphisms
We determine all connected homogeneous Kobayashi-hyperbolic manifolds of dimension $n\ge 2$ whose holomorphic automorphism group has dimension $n^2-2$. This result complements an existing classification for automorphism group dimension $n^2-1$ and greater obtained without the homogeneity assumption.
0
0
1
0
0
0
New estimates for some functions defined over primes
In this paper we first establish new explicit estimates for Chebyshev's $\vartheta$-function. Applying these new estimates, we derive new upper and lower bounds for some functions defined over the prime numbers, for instance the prime counting function $\pi(x)$, which improve the currently best ones. Furthermore, we ...
0
0
1
0
0
0
Transferrable End-to-End Learning for Protein Interface Prediction
While there has been an explosion in the number of experimentally determined, atomically detailed structures of proteins, how to represent these structures in a machine learning context remains an open research question. In this work we demonstrate that representations learned from raw atomic coordinates can outperfo...
0
0
0
1
1
0
A new astrophysical solution to the Too Big To Fail problem - Insights from the MoRIA simulations
We test whether advanced galaxy models and analysis techniques of simulations can alleviate the Too Big To Fail problem (TBTF) for late-type galaxies, which states that isolated dwarf galaxy kinematics imply that dwarfs live in lower-mass halos than is expected in a {\Lambda}CDM universe. Furthermore, we want to expl...
0
1
0
0
0
0
Friction Variability in Planar Pushing Data: Anisotropic Friction and Data-collection Bias
Friction plays a key role in manipulating objects. Most of what we do with our hands, and most of what robots do with their grippers, is based on the ability to control frictional forces. This paper aims to better understand the variability and predictability of planar friction. In particular, we focus on the analysi...
1
0
0
0
0
0
Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers
Turkish Wikipedia Named-Entity Recognition and Text Categorization (TWNERTC) dataset is a collection of automatically categorized and annotated sentences obtained from Wikipedia. We constructed large-scale gazetteers by using a graph crawler algorithm to extract relevant entity and domain information from a semantic ...
1
0
0
0
0
0
Strong Completeness and the Finite Model Property for Bi-Intuitionistic Stable Tense Logics
Bi-Intuitionistic Stable Tense Logics (BIST Logics) are tense logics with a Kripke semantics where worlds in a frame are equipped with a pre-order as well as with an accessibility relation which is 'stable' with respect to this pre-order. BIST logics are extensions of a logic, BiSKt, which arose in the semantic conte...
1
0
1
0
0
0
Using lab notebooks to examine students' engagement in modeling in an upper-division electronics lab course
We demonstrate how students' use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process of constructing, testing, and refining these models is much less com...
0
1
0
0
0
0
An accurate finite element method for the numerical solution of isothermal and incompressible flow of viscous fluid
Despite its numerical challenges, finite element method is used to compute viscous fluid flow. A consensus on the cause of numerical problems has been reached; however, general algorithms---allowing a robust and accurate simulation for any process---are still missing. Either a very high computational cost is necessar...
1
1
0
0
0
0
Re-evaluating Evaluation
Progress in machine learning is measured by careful evaluation on problems of outstanding common interest. However, the proliferation of benchmark suites and environments, adversarial attacks, and other complications has diluted the basic evaluation model by overwhelming researchers with choices. Deliberate or accide...
0
0
0
1
0
0
Ranking and Selection as Stochastic Control
Under a Bayesian framework, we formulate the fully sequential sampling and selection decision in statistical ranking and selection as a stochastic control problem, and derive the associated Bellman equation. Using value function approximation, we derive an approximately optimal allocation policy. We show that this po...
1
0
0
1
0
0
An application of $Γ$-semigroups techniques to the Green's Theorem
The concept of a $\Gamma$-semigroup has been introduced by Mridul Kanti Sen in the Int. Symp., New Delhi, 1981. It is well known that the Green's relations play an essential role in studying the structure of semigroups. In the present paper we deal with an application of $\Gamma$-semigroups techniques to the Green's ...
0
0
1
0
0
0
Reflection from a multi-species material and its transmitted effective wavenumber
We formally deduce closed-form expressions for the transmitted effective wavenumber of a material comprising multiple types of inclusions or particles (multi-species), dispersed in a uniform background medium. The expressions, derived here for the first time, are valid for moderate volume fractions and without restri...
0
1
0
0
0
0
Colouring perfect graphs with bounded clique number
A graph is perfect if the chromatic number of every induced subgraph equals the size of its largest clique, and an algorithm of Grötschel, Lovász, and Schrijver from 1988 finds an optimal colouring of a perfect graph in polynomial time. But this algorithm uses the ellipsoid method, and it is a well-known open questio...
1
0
0
0
0
0
Resilient Learning-Based Control for Synchronization of Passive Multi-Agent Systems under Attack
In this paper, we show synchronization for a group of output passive agents that communicate with each other according to an underlying communication graph to achieve a common goal. We propose a distributed event-triggered control framework that will guarantee synchronization and considerably decrease the required co...
1
0
0
1
0
0
EMG-Controlled Hand Teleoperation Using a Continuous Teleoperation Subspace
We present a method for EMG-driven teleoperation of non-anthropomorphic robot hands. EMG sensors are appealing as a wearable, inexpensive and unobtrusive way to gather information about the teleoperator's hand pose. However, mapping from EMG signals to the pose space of a non-anthropomorphic hand presents multiple ch...
1
0
0
0
0
0
Numerical solutions of Hamiltonian PDEs: a multi-symplectic integrator in light-cone coordinates
We introduce a novel numerical method to integrate partial differential equations representing the Hamiltonian dynamics of field theories. It is a multi-symplectic integrator that locally conserves the stress-energy tensor with an excellent precision over very long periods. Its major advantage is that it is extremely...
0
1
1
0
0
0
Magnetite nano-islands on silicon-carbide with graphene
X-ray magnetic circular dichroism (XMCD) measurements of iron nano-islands grown on graphene and covered with a Au film for passivation reveal that the oxidation through defects in the Au film spontaneously leads to the formation of magnetite nano-particles (i.e, $Fe_3$$O_4$). The Fe nano-islands (20 and 75 monolayer...
0
1
0
0
0
0
Activation Ensembles for Deep Neural Networks
Many activation functions have been proposed in the past, but selecting an adequate one requires trial and error. We propose a new methodology of designing activation functions within a neural network at each layer. We call this technique an "activation ensemble" because it allows the use of multiple activation funct...
0
0
0
1
0
0
Formation of coalition structures as a non-cooperative game
Traditionally social sciences are interested in structuring people in multiple groups based on their individual preferences. This pa- per suggests an approach to this problem in the framework of a non- cooperative game theory. Definition of a suggested finite game includes a family of nested simultaneous non-cooperat...
1
0
1
0
0
0
Smooth and Sparse Optimal Transport
Entropic regularization is quickly emerging as a new standard in optimal transport (OT). It enables to cast the OT computation as a differentiable and unconstrained convex optimization problem, which can be efficiently solved using the Sinkhorn algorithm. However, entropy keeps the transportation plan strictly positi...
1
0
0
1
0
0
The stability and energy exchange mechanism of divergent states with real energy
The eigenvalue of the hermitic Hamiltonian is real undoubtedly. Actually, The reality can also be guaranteed by the $PT$-symmetry. The hermiticity and the $PT$-symmetric quantum theory both have requirements regarding the boundary condition. There exists a reverse strategy to investigate the quantum problem. Namely, ...
0
1
0
0
0
0
A bound on partitioning clusters
Let $X$ be a finite collection of sets (or "clusters"). We consider the problem of counting the number of ways a cluster $A \in X$ can be partitioned into two disjoint clusters $A_1, A_2 \in X$, thus $A = A_1 \uplus A_2$ is the disjoint union of $A_1$ and $A_2$; this problem arises in the run time analysis of the AST...
0
0
1
0
0
0
X-ray emission from thin plasmas. Collisional ionization for atoms and ions of H to Zn
Every observation of astrophysical objects involving a spectrum requires atomic data for the interpretation of line fluxes, line ratios and ionization state of the emitting plasma. One of the processes which determines it is collisional ionization. In this study an update of the direct ionization (DI) and excitation-...
0
1
0
0
0
0
Support Spinor Machine
We generalize a support vector machine to a support spinor machine by using the mathematical structure of wedge product over vector machine in order to extend field from vector field to spinor field. The separated hyperplane is extended to Kolmogorov space in time series data which allow us to extend a structure of s...
1
0
0
1
0
0
Various generalizations and deformations of $PSL(2,\mathbb{R})$ surface group representations and their Higgs bundles
Recall that the group $PSL(2,\mathbb R)$ is isomorphic to $PSp(2,\mathbb R),\ SO_0(1,2)$ and $PU(1,1).$ The goal of this paper is to examine the various ways in which Fuchsian representations of the fundamental group of a closed surface of genus $g$ into $PSL(2,\mathbb R)$ and their associated Higgs bundles generaliz...
0
0
1
0
0
0
Redundancy schemes for engineering coherent systems via a signature-based approach
This paper proposes a signature-based approach for solving redundancy allocation problems when component lifetimes are not only heterogeneous but also dependent. The two common schemes for allocations, that is active and standby redundancies, are considered. If the component lifetimes are independent, the proposed ap...
0
0
0
1
0
0
Anisotropy effects on Baryogenesis in $f(R)$-Theories of Gravity
We study the $f(R)$ theory of gravity in an anisotropic metric and its effect on the baryon number to entropy ratio. The mechanism of gravitational baryogenesis based on the CPT-violating gravitational interaction between derivative of the Ricci scalar curvature and the baryon-number current is investigated in the co...
0
1
0
0
0
0
Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation
Visual tracking is a fundamental problem in computer vision. Recently, some deep-learning-based tracking algorithms have been achieving record-breaking performances. However, due to the high complexity of deep learning, most deep trackers suffer from low tracking speed, and thus are impractical in many real-world app...
1
0
0
0
0
0
Simply Exponential Approximation of the Permanent of Positive Semidefinite Matrices
We design a deterministic polynomial time $c^n$ approximation algorithm for the permanent of positive semidefinite matrices where $c=e^{\gamma+1}\simeq 4.84$. We write a natural convex relaxation and show that its optimum solution gives a $c^n$ approximation of the permanent. We further show that this factor is asymp...
1
0
0
0
0
0
Stochastic Variance Reduction for Policy Gradient Estimation
Recent advances in policy gradient methods and deep learning have demonstrated their applicability for complex reinforcement learning problems. However, the variance of the performance gradient estimates obtained from the simulation is often excessive, leading to poor sample efficiency. In this paper, we apply the st...
1
0
0
1
0
0
Weighted Low-Rank Approximation of Matrices and Background Modeling
We primarily study a special a weighted low-rank approximation of matrices and then apply it to solve the background modeling problem. We propose two algorithms for this purpose: one operates in the batch mode on the entire data and the other one operates in the batch-incremental mode on the data and naturally captur...
1
0
0
0
0
0
Master equation for She-Leveque scaling and its classification in terms of other Markov models of developed turbulence
We derive the Markov process equivalent to She-Leveque scaling in homogeneous and isotropic turbulence. The Markov process is a jump process for velocity increments $u(r)$ in scale $r$ in which the jumps occur randomly but with deterministic width in $u$. From its master equation we establish a prescription to simula...
0
1
0
0
0
0
Scaling Universality at the Dynamic Vortex Mott Transition
The dynamic Mott insulator-to-metal transition (DMT) is key to many intriguing phenomena in condensed matter physics yet it remains nearly unexplored. The cleanest way to observe DMT, without the interference from disorder and other effects inherent to electronic and atomic systems, is to employ the vortex Mott state...
0
1
0
0
0
0
Assessment Formats and Student Learning Performance: What is the Relation?
Although compelling assessments have been examined in recent years, more studies are required to yield a better understanding of the several methods where assessment techniques significantly affect student learning process. Most of the educational research in this area does not consider demographics data, differing m...
1
0
0
1
0
0
Sharing deep generative representation for perceived image reconstruction from human brain activity
Decoding human brain activities via functional magnetic resonance imaging (fMRI) has gained increasing attention in recent years. While encouraging results have been reported in brain states classification tasks, reconstructing the details of human visual experience still remains difficult. Two main challenges that h...
1
0
0
0
0
0
Two types of criticality in the brain
Neural networks with equal excitatory and inhibitory feedback show high computational performance. They operate close to a critical point characterized by the joint activation of large populations of neurons. Yet, in macaque motor cortex we observe very different dynamics with weak fluctuations on the population leve...
0
1
0
0
0
0
Topological networks for quantum communication between distant qubits
Efficient communication between qubits relies on robust networks which allow for fast and coherent transfer of quantum information. It seems natural to harvest the remarkable properties of systems characterized by topological invariants to perform this task. Here we show that a linear network of coupled bosonic degre...
0
1
0
0
0
0
How Criticality of Gene Regulatory Networks Affects the Resulting Morphogenesis under Genetic Perturbations
Whereas the relationship between criticality of gene regulatory networks (GRNs) and dynamics of GRNs at a single cell level has been vigorously studied, the relationship between the criticality of GRNs and system properties at a higher level has remained unexplored. Here we aim at revealing a potential role of critic...
0
0
0
0
1
0
Task-Driven Convolutional Recurrent Models of the Visual System
Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of neurons in the primate brain's visual system. However, biological visual systems have two ubiquitous a...
0
0
0
0
1
0
Self-organization principles of intracellular pattern formation
Dynamic patterning of specific proteins is essential for the spatiotemporal regulation of many important intracellular processes in procaryotes, eucaryotes, and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this a...
0
0
0
0
1
0
Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science
If we pick $n$ random points uniformly in $[0,1]^d$ and connect each point to its $k-$nearest neighbors, then it is well known that there exists a giant connected component with high probability. We prove that in $[0,1]^d$ it suffices to connect every point to $ c_{d,1} \log{\log{n}}$ points chosen randomly among its...
1
0
0
1
0
0
Theory of mechano-chemical patterning in biphasic biological tissues
The formation of self-organized patterns is key to the morphogenesis of multicellular organisms, although a comprehensive theory of biological pattern formation is still lacking. Here, we propose a minimal model combining tissue mechanics to morphogen turnover and transport in order to explore new routes to patternin...
0
0
0
0
1
0
Diffusion time dependence of microstructural parameters in fixed spinal cord
Biophysical modelling of diffusion MRI is necessary to provide specific microstructural tissue properties. However, estimating model parameters from data with limited diffusion gradient strength, such as clinical scanners, has proven unreliable due to a shallow optimization landscape. On the other hand, estimation of...
0
1
0
0
0
0
Optimizing Epistemic Model Checking Using Conditional Independence (Extended Abstract)
This paper shows that conditional independence reasoning can be applied to optimize epistemic model checking, in which one verifies that a model for a number of agents operating with imperfect information satisfies a formula expressed in a modal multi-agent logic of knowledge. The optimization has been implemented in...
1
0
0
0
0
0
Quickest Localization of Anomalies in Power Grids: A Stochastic Graphical Framework
Agile localization of anomalous events plays a pivotal role in enhancing the overall reliability of the grid and avoiding cascading failures. This is especially of paramount significance in the large-scale grids due to their geographical expansions and the large volume of data generated. This paper proposes a stochas...
1
0
0
1
0
0
The trouble with tensor ring decompositions
The tensor train decomposition decomposes a tensor into a "train" of 3-way tensors that are interconnected through the summation of auxiliary indices. The decomposition is stable, has a well-defined notion of rank and enables the user to perform various linear algebra operations on vectors and matrices of exponential...
1
0
0
0
0
0
Direct Measurement of Kramers Turnover with a Levitated Nanoparticle
Understanding the thermally activated escape from a metastable state is at the heart of important phenomena such as the folding dynamics of proteins, the kinetics of chemical reactions or the stability of mechanical systems. In 1940 Kramers calculated escape rates both in the high damping and the low damping regime a...
0
1
0
0
0
0
An estimator for the tail-index of graphex processes
Sparse exchangeable graphs resolve some pathologies in traditional random graph models, notably, providing models that are both projective and allow sparsity. In a recent paper, Caron and Rousseau (2017) show that for a large class of sparse exchangeable models, the sparsity behaviour is governed by a single paramete...
0
0
1
1
0
0
General tête-à-tête graphs and Seifert manifolds
Tête-à-tête graphs and relative tête-à-tête graphs were introduced by N. A'Campo in 2010 to model monodromies of isolated plane curves. By recent workof Fdez de Bobadilla, Pe Pereira and the author, they provide a way of modeling the periodic mapping classes that leave some boundary component invariant. In this work ...
0
0
1
0
0
0