May 2023 arXiv papers — page 91

Hitoshi Furusawa, Walter Guttmann, Georg Struth

We formalise the modal operators from the concurrent dynamic logics of Peleg, Nerode and Wijesekera in a multirelational algebraic language based on relation algebra and power allegories, using relational approximation operators on multirelations developed in a companion article. We relate Nerode and Wijesekera's box operator with a relational approximation

M. L. Glasser

An $n$-dimensional generalization of the Onsager Ising partition function integral is reduced to a single integral and applied to evaluate the partition function and residual entropy of an eight vertex model.

Niharika Veeravalli

This study investigates the capability blessings of the use of eye-monitoring technology to beautify the usability of web sites. With the upward thrust of on-line interactions, website usability has turn out to be increasingly important for making sure person pleasure and engagement. Eye-tracking technology offers a non-invasive way to measure how users inte

Hitoshi Furusawa, Walter Guttmann, Georg Struth

Binary multirelations can model alternating nondeterminism, for instance, in games or nondeterministically evolving systems interacting with an environment. Such systems can show partial or total functional behaviour at both levels of alternation, so that nondeterministic behaviour may occur only at one level or both levels, or not at all. We study classes o

Senlei Li, Mengqi Huang, Hanyi Lu, Nathan J. McLaughlin

Noncollinear antiferromagnets with novel magnetic orders, vanishingly small net magnetization and exotic spin related properties hold enormous promise for developing next-generation, transformative spintronic applications. A major ongoing research focus of this community is to explore, control, and harness unconventional magnetic phases of this emergent mate

Hitoshi Furusawa, Walter Guttmann, Georg Struth

Binary multirelations form a model of alternating nondeterminism useful for analysing games, interactions of computing systems with their environments or abstract interpretations of probabilistic programs. We investigate this alternating structure with inner or demonic and outer or angelic choices in a relation-algebraic language extended with specific opera

Romain Branchereau

A general conjecture of Harder relates the denominator of the Eisenstein cohomology of certain locally symmetric spaces to special values of $L$-functions. In this paper we consider the locally symmetric space $\operatorname{SL}_2(\mathcal{O}) \backslash \mathbb{H}_3$ where $\mathcal{O}$ is the ring of integers of an imaginary quadratic field $K$ and $\mathb

Wenhao Ding, Tong Che, Ding Zhao, Marco Pavone

Recently, reward-conditioned reinforcement learning (RCRL) has gained popularity due to its simplicity, flexibility, and off-policy nature. However, we will show that current RCRL approaches are fundamentally limited and fail to address two critical challenges of RCRL -- improving generalization on high reward-to-go (RTG) inputs, and avoiding out-of-distribu

Eduardo Orozco, Petr Tsygankov, Fredy Parada, Alejandro Hernández

An electron autoresonant acceleration by the rotating TM110 mode microwave field in an inhomogeneous magnetostatic field is studied. A set of differential equations describing the evolution of the phase shift between the electron angular position and the angle for which the transferred power is maximum, the total electron energy, and the longitudinal electro

Qikui Zhu, Yihui Bi, Danxin Wang, Xiangpeng Chu

Heatmap-based anatomical landmark detection is still facing two unresolved challenges: 1) inability to accurately evaluate the distribution of heatmap; 2) inability to effectively exploit global spatial structure information. To address the computational inability challenge, we propose a novel position-aware and sample-aware central loss. Specifically, our c

Liangchen Song, Liangliang Cao, Hongyu Xu, Kai Kang

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different style. Unlike existing image synthesis methods, our work addresses the challenge of synthesizing both geometry and texture

Hans Baehr

Circumstellar discs likely have a short window when they are self-gravitating and prone to the effects of disc instability, but during this time the seeds of planet formation can be sown. It has long been argued that disc fragmentation can form large gas giant planets at wide orbital separations, but its place in the planet formation paradigm is hindered by

Yihao Huang, Shangdi Yu, Julian Shun

Clustering multidimensional points is a fundamental data mining task, with applications in many fields, such as astronomy, neuroscience, bioinformatics, and computer vision. The goal of clustering algorithms is to group similar objects together. Density-based clustering is a clustering approach that defines clusters as dense regions of points. It has the adv

Giorgi Kokaia, Pratyush Sinha, Yutong Jiang, Nozha Boujemaa

We introduce two novel methods, Tree-Search and Self-contextualizing QA, designed to enhance the performance of large language models (LLMs) in question-answering tasks. Tree-Search is a sampling technique specifically created to extract diverse information from an LLM for a given prompt. Self-contextualizing QA leverages Tree-Search to enable the model to c

Łukasz Mazurkiewicz, Szymon Żeberski

We study analytic and Borel subsets defined similarily to the old example of analytic complete set given by Luzin. Luzin's example, which is essentially a subset of the Baire space, is based on the natural partial order on naturals, i.e. division. It consists of sequences which contain increasing subsequence in given order. We consider a variety of sets defi

Shintaro Kuroki

The purpose of this paper is to determine the ring structure of the graph equivariant cohomology of the GKM graph induced from the even-dimensional complex quadrics. We show that the graph equivariant cohomology is generated by two types of subgraphs in the GKM graph, which are subject to four different types of relations. By utilizing this ring structure, w

Omaira González-Martín, Cristina Ramos Almeida, Jacopo Fritz, Almudena Alonso-Herrero

Fits the infrared spectra from the nuclear regions of AGN can place constraints on the dust properties, distribution, and geometry by comparison with models. However, none of the currently available models fully describe the observations of AGN currently available. Among the aspects least explored, here we focus on the role of dust grain size. We offer the c

Yong-Chull Jang, Rajan Gupta, Tanmoy Bhattacharya, Boram Yoon

We present results for the isovector axial vector form factors obtained using thirteen 2+1+1-flavor highly improved staggered quark (HISQ) ensembles generated by the MILC collaboration. The calculation of nucleon two- and three-point correlation functions has been done using Wilson-clover fermions. In the analysis of these data, we quantify the sensitivity o

Wladimir Silva

This work describes a series of experiments in IBM's 16-qubit Guadalupe quantum processor to find the ground state of various lattice systems implemented in the Qiskit library. We aim to design a Variational Quantum Eigensolver (QVE) resistant to noise and independent of the number of vertices in the lattice. Furthermore, we test our solution against two Isi

Sanchita Ghosh, Nutan Saha, Tanushree Roy

Under a changing driving environment, a Connected Autonomous Vehicle (CAV) platoon relies strongly on the acquisition of accurate traffic information from neighboring vehicles as well as reliable commands from a centralized supervisory controller through the communication network. Even though such modalities are imperative to ensure the safe and efficient dr

Bhanu Prakash Voutharoja, Peng Wang, Lei Wang, Vivienne Guan

Image-to-recipe retrieval is a challenging vision-to-language task of significant practical value. The main challenge of the task lies in the ultra-high redundancy in the long recipe and the large variation reflected in both food item combination and food item appearance. A de-facto idea to address this task is to learn a shared feature embedding space in wh

Marcos Gomez-Vazquez, Jordi Cabot, Robert Clarisó

Tabular data is the most common format to publish and exchange structured data online. A clear example is the growing number of open data portals published by public administrations. However, exploitation of these data sources is currently limited to technical people able to programmatically manipulate and digest such data. As an alternative, we propose the

Hsiu-Chung Yeh, Gabriel Cardoso, Leonid Korneev, Dries Sels

The transverse field Ising model (TFIM) on the half-infinite chain possesses an edge zero mode. This work considers an impurity model -- TFIM perturbed by a boundary integrability breaking interaction. For sufficiently large transverse field, but in the ordered phase of the TFIM, the zero mode is observed to decay. The decay is qualitatively different from z

D. Yates, R. Kruecken, I. Dillmann, P. E. Garrett

\noindent \textbf{Background:} Detailed spectroscopy of neutron-rich, heavy, deformed nuclei is of broad interest for nuclear astrophysics and nuclear structure. Nuclei in the r-process path and following freeze-out region impact the resulting r-process abundance distribution, and the structure of nuclei midshell in both proton and neutron number helps to un

Isabel Kloumann, Hannah Korevaar, Chris McConnell, Mark Tygert

The simplest, most common paired samples consist of observations from two populations, with each observed response from one population corresponding to an observed response from the other population at the same value of an ordinal covariate. The pair of observed responses (one from each population) at the same value of the covariate is known as a "matched pa

Jiechen Chen, Sangwoo Park, Osvaldo Simeone

Spiking neural networks (SNNs) process time-series data via internal event-driven neural dynamics. The energy consumption of an SNN depends on the number of spikes exchanged between neurons over the course of the input presentation. Typically, decisions are produced after the entire input sequence has been processed. This results in latency and energy consum

Viraj Shah, Svetlana Lazebnik, Julien Philip

Intrinsic Image Decomposition (IID) is a challenging inverse problem that seeks to decompose a natural image into its underlying intrinsic components such as albedo and shading. While recent image decomposition methods rely on learning-based priors on these components, they often suffer from component cross-contamination owing to joint training of priors; or

Li-Jen Yang, Chao-Han Huck Yang, Jen-Tzung Chien

This paper presents a parameter-efficient learning (PEL) to develop a low-resource accent adaptation for text-to-speech (TTS). A resource-efficient adaptation from a frozen pre-trained TTS model is developed by using only 1.2\% to 0.8\% of original trainable parameters to achieve competitive performance in voice synthesis. Motivated by a theoretical foundati

Silvana M. Pesenti, Sebastian Jaimungal, Yuri F. Saporito, Rodrigo S. Targino

We define and develop an approach for risk budgeting allocation - a risk diversification portfolio strategy - where risk is measured using a dynamic time-consistent risk measure. For this, we introduce a notion of dynamic risk contributions that generalise the classical Euler contributions and which allow us to obtain dynamic risk contributions in a recursiv

Bithika Karmakar, Dusan Zigic, Igor Salom, Jussi Auvinen

We study whether it is possible to use high-$p_\perp$ data/theory to constrain the temperature dependence of the shear viscosity over entropy density ratio $\eta/s$ of the matter formed in ultrarelativistic heavy-ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). We use two approaches: i) We calculate h

Wanrong Zhu, Xinyi Wang, Yujie Lu, Tsu-Jui Fu

The field of text-to-image (T2I) generation has garnered significant attention both within the research community and among everyday users. Despite the advancements of T2I models, a common issue encountered by users is the need for repetitive editing of input prompts in order to receive a satisfactory image, which is time-consuming and labor-intensive. Given

Kristina Lerman, Aryan Karnati, Shuchan Zhou, Siyi Chen

The rise in eating disorders, a condition with serious health complications, has been linked to the proliferation of idealized body images on social media platforms. However, the relationship between social media and eating disorders is more complex, with online platforms potentially enabling harmful behaviors by linking people to ``pro-ana'' communities tha

Zeyu Zhang, Steven Bethard

Geocoding is the task of converting location mentions in text into structured data that encodes the geospatial semantics. We propose a new architecture for geocoding, GeoNorm. GeoNorm first uses information retrieval techniques to generate a list of candidate entries from the geospatial ontology. Then it reranks the candidate entries using a transformer-base

Yeuk Hay Joshua Lam, Daniel Litt

Let $J(m)$ be an $m\times m$ Jordan block with eigenvalue $1$. For $\lambda\in \mathbb{C}\setminus\{0,1\}$, we explicitly construct all rank $2$ local systems of geometric origin on $\mathbb{P}^1\setminus\{0,1,\lambda, \infty\}$, with local monodromy conjugate to $J(2)$ at $0,1,\lambda$ and conjugate to $-J(2)$ at $\infty$. The construction relies on Katz's

J. Galen Wang, Daniel R. Ladiges, Ishan Srivastava, Sean P. Carney

We study the role of steric effects on the induced-charge electro-osmosis (ICEO) phenomenon using a recently developed mesoscale fluid model. A hybrid Eulerian-Lagrangian method is used to simulate the dynamics of discrete immersed ions in a thermally fluctuating solvent near a metallic plate embedded in the dielectric interface. We observe that the characte

FNU Shariful, Justin Weathers, Anirban Ghosh, Giri Narasimhan

We design and engineer Fast-Sparse-Spanner, a simple and practical (fast and memory-efficient) algorithm for constructing sparse low stretch-factor geometric graphs on large pointsets in the plane. To our knowledge, this is the first practical algorithm to construct fast low stretch-factor graphs on large pointsets with average-degrees (hence, the number of

Nedeljko Radulovic, Albert Bifet, Fabian Suchanek

Understanding the decision-making process of black-box models has become not just a legal requirement, but also an additional way to assess their performance. However, the state of the art post-hoc explanation approaches for regression models rely on synthetic data generation, which introduces uncertainty and can hurt the reliability of the explanations. Fur

Jieyeon Woo, Mireille Fares, Catherine Pelachaud, Catherine Achard

Socially Interactive Agents (SIAs) are physical or virtual embodied agents that display similar behavior as human multimodal behavior. Modeling SIAs' non-verbal behavior, such as speech and facial gestures, has always been a challenging task, given that a SIA can take the role of a speaker or a listener. A SIA must emit appropriate behavior adapted to its ow

Kohei Hayashi, Laszlo Dobos, Carrie Filion, Evan Kirby

The Galactic dwarf spheroidal galaxies (dSphs) provide valuable insight into dark matter (DM) properties and its role in galaxy formation. Their close proximity enables the measurement of line-of-sight velocities for resolved stars, which allows us to study DM halo structure. However, uncertainties in DM mass profile determination persist due to the degenera

Poupak Azad, Baris Coskunuzer, Murat Kantarcioglu, Cuneyt Gurcan Akcora

The rise of cryptocurrencies like Bitcoin, which enable transactions with a degree of pseudonymity, has led to a surge in various illicit activities, including ransomware payments and transactions on darknet markets. These illegal activities often utilize Bitcoin as the preferred payment method. However, current tools for detecting illicit behavior either re

Lyle Regenwetter, Yazan Abu Obaideh, Faez Ahmed

Designers may often ask themselves how to adjust their design concepts to achieve demanding functional goals. To answer such questions, designers must often consider counterfactuals, weighing design alternatives and their projected performance. This paper introduces Multi-objective Counterfactuals for Design (MCD), a computational tool that automates and str

Amine Elhafsi, Rohan Sinha, Christopher Agia, Edward Schmerling

As robots acquire increasingly sophisticated skills and see increasingly complex and varied environments, the threat of an edge case or anomalous failure is ever present. For example, Tesla cars have seen interesting failure modes ranging from autopilot disengagements due to inactive traffic lights carried by trucks to phantom braking caused by images of sto

Janik Karoly, Derek Ward-Thompson, Kate Pattle, David Berry

We present observations of polarized dust emission at 850 $\mu$m from the L43 molecular cloud which sits in the Ophiuchus cloud complex. The data were taken using SCUBA-2/POL-2 on the James Clerk Maxwell Telescope as a part of the BISTRO large program. L43 is a dense ($N_{\rm H_2}\sim 10^{22}$-10$^{23}$ cm$^{-2}$) complex molecular cloud with a submillimetre

Matthew Amy, Andrew N. Glaudell, Sarah Meng Li, Neil J. Ross

The matrices that can be exactly represented by a circuit over the Toffoli-Hadamard gate set are the orthogonal matrices of the form $M/ \sqrt{2}{}^k$, where $M$ is an integer matrix and $k$ is a nonnegative integer. The exact synthesis problem for this gate set is the problem of constructing a circuit for a given such matrix. Existing methods produce circui

Arnaud Mayeux

Dilatations modify categories by imposing that some morphisms factorize through some others. This is formalized by a universal property. This text is devoted to introduce and study this construction. Examples of dilatations of categories include localizations of categories and dilatations of rings.

Bridget C. Andersen, Chitrang Patel, Charanjot Brar, P. J. Boyle

Fast radio bursts (FRBs) are bright radio transients of micro-to-millisecond duration and unknown extragalactic origin. Central to the mystery of FRBs are their extremely high characteristic energies, which surpass the typical energies of other radio transients of similar duration, like Galactic pulsar and magnetar bursts, by orders of magnitude. Calibration

Yuhao Wang, Enlu Zhou

We consider a robust reinforcement learning problem, where a learning agent learns from a simulated training environment. To account for the model mis-specification between this training environment and the real environment due to lack of data, we adopt a formulation of Bayesian risk MDP (BRMDP) with infinite horizon, which uses Bayesian posterior to estimat

Giovanni Bellettini, Simone Carano, Riccardo Scala

We compute the relaxed Cartesian area in the strict $BV$-convergence on a class of piecewise Lipschitz maps from the plane to the plane, having jump made of several curves allowed to meet at a finite number of junction points. We show that the domain of this relaxed area is strictly contained in the domain of the classical $L^1$-relaxed area.

Josef Rucska, James Wadsley

Kilometre-sized planetesimals form from pebbles of a range of sizes. We present the first simulations of the streaming instability that begin with a realistic, peaked size distribution, as expected from grain growth predictions. Our 3D numerical simulations directly form planetesimals via the gravitational collapse of pebble clouds. Models with multiple grai

Mohak Goyal, Sahasrajit Sarmasarkar, Ashish Goel

Participatory budgeting (PB) has been widely adopted and has attracted significant research efforts; however, there is a lack of mechanisms for PB which elicit project interactions, such as substitution and complementarity, from voters. Also, the outcomes of PB in practice are subject to various minimum/maximum funding constraints on 'types' of projects. We

Selma Saidi

Collaboration in multi-agent autonomous systems is critical to increase performance while ensuring safety. However, due to heterogeneity of their features in, e.g., perception qualities, some autonomous systems have to be considered more trustworthy than others when contributing to collaboratively build a common environmental model, especially under uncertai

Adrian Groza

The proposed approach is to formalise the probabilistic puzzle in equational FOL. Two formalisations are needed: one theory for all models of the given puzzle, and a second theory for the favorable models. Then Mace4 - that computes all the interpretation models of a FOL theory - is called twice. First, it is asked to compute all the possible models M p .Sec

Kalvin Eng, Abram Hindle, Eleni Stroulia

Software design patterns present general code solutions to common software design problems. Modern software systems rely heavily on containers for running their constituent service components. Yet, despite the prevalence of ready-to-use Docker service images ready to participate in multi-container service compositions of applications, developers do not have

Vivin Vinod, Sayan Maity, Peter Zaspel, Ulrich Kleinekathöfer

The accurate but fast calculation of molecular excited states is still a very challenging topic. For many applications, detailed knowledge of the energy funnel in larger molecular aggregates is of key importance requiring highly accurate excited state energies. To this end, machine learning techniques can be an extremely useful tool though the cost of genera

Aditya Deshmukh, Zifei Wang, Aaron Gunn, Huizhong Guo

Automated vehicles (AVs) are of great potential in reducing crashes on the road. However, it is still complicated to eliminate all the possible accidents, especially those with vulnerable road users (VRUs), who are among the greater risk than vehicle occupants in traffic accidents. Thus, in this paper, we conducted a systematic review of safety-critical scen

Junwei Kuang, Jiaheng Xie, Zhijun Yan

The early identification and intervention of latent depression are of significant societal importance for mental health governance. While current automated detection methods based on social media have shown progress, their decision-making processes often lack a clinically interpretable framework, particularly in capturing the duration and dynamic evolution o

Matt Barnes, Matthew Abueg, Oliver F. Lange, Matt Deeds

Inverse reinforcement learning (IRL) offers a powerful and general framework for learning humans' latent preferences in route recommendation, yet no approach has successfully addressed planetary-scale problems with hundreds of millions of states and demonstration trajectories. In this paper, we introduce scaling techniques based on graph compression, spatial

Carl Lian

We compare two formulas for the class of a generic torus orbit closure on the Grassmannian, due to Klyachko and Berget-Fink. The naturally emerging combinatorial objects are semi-standard fillings we call 1-strip-less tableaux.

Ziheng Chen, Yue Song, Gaowen Liu, Ramana Rao Kompella

Deep neural networks for learning Symmetric Positive Definite (SPD) matrices are gaining increasing attention in machine learning. Despite the significant progress, most existing SPD networks use traditional Euclidean classifiers on an approximated space rather than intrinsic classifiers that accurately capture the geometry of SPD manifolds. Inspired by Hype

Matthew P. Leighton, David A. Sivak

Bounding and estimating entropy production has long been an important goal of nonequilibrium thermodynamics. We recently derived a lower bound on the total and subsystem entropy production rates of continuous stochastic systems. This `Jensen bound' has led to fundamental limits on the performance of collective transport systems and permitted thermodynamic in

Anh Tran, Edward Talmage

A multiplicity queue is a concurrently-defined data type which relaxes the conditions of a linearizable FIFO queue to allow concurrent Dequeue instances to return the same value. It would seem that this should allow faster implementations, as processes should not need to wait as long to learn about concurrent operations at remote processes and previous work

Yotam Shomroni

Every word $w$ in the free group $F_r$ of rank $r$ induces a probability measure (the $w$-measure) on every compact group $G$, by substitution of Haar-random $G$-elements in the letters. This measure is determined by its Fourier coefficients: the $w$-expectations $\mathbb{E}_w[\chi]$ of the irreducible characters of $G$. For every compact group $G$, the wrea

Soroosh Tayebi Arasteh, Cristian David Rios-Urrego, Elmar Noeth, Andreas Maier

Parkinson's disease (PD) is a neurological disorder impacting a person's speech. Among automatic PD assessment methods, deep learning models have gained particular interest. Recently, the community has explored cross-pathology and cross-language models which can improve diagnostic accuracy even further. However, strict patient data privacy regulations largel

Jiawei Huang, Batuhan Yardim, Niao He

In this paper, we study the fundamental statistical efficiency of Reinforcement Learning in Mean-Field Control (MFC) and Mean-Field Game (MFG) with general model-based function approximation. We introduce a new concept called Mean-Field Model-Based Eluder Dimension (MF-MBED), which characterizes the inherent complexity of mean-field model classes. We show th

Christis Katsouris

This paper considers the specification of covariance structures with tail estimates. We focus on two aspects: (i) the estimation of the VaR-CoVaR risk matrix in the case of larger number of time series observations than assets in a portfolio using quantile predictive regression models without assuming the presence of nonstationary regressors and; (ii) the co

Ziyi Wu, Jingyu Hu, Wuyue Lu, Igor Gilitschenski

Object-centric learning aims to represent visual data with a set of object entities (a.k.a. slots), providing structured representations that enable systematic generalization. Leveraging advanced architectures like Transformers, recent approaches have made significant progress in unsupervised object discovery. In addition, slot-based representations hold gre

Sergio E. Aguilar-Gutierrez, Michal P. Heller, Silke Van der Schueren

Recent developments in anti-de Sitter holography point towards the association of an infinite class of covariant objects, the simplest one being codimension-one extremal volumes, with quantum computational complexity in the microscopic description. One of the defining features of these gravitational complexity proposals is describing the persistent growth of

Siavash Farzan

Control theory is an important cornerstone of the robotics field and is considered a fundamental subject in an undergraduate and postgraduate robotics curriculum. Furthermore, project-based learning has shown significant benefits in engineering domains, specifically in interdisciplinary fields such as robotics which require hands-on experience to master the

Matthew Dowling, Yuan Zhao, Il Memming Park

Latent variable models have become instrumental in computational neuroscience for reasoning about neural computation. This has fostered the development of powerful offline algorithms for extracting latent neural trajectories from neural recordings. However, despite the potential of real time alternatives to give immediate feedback to experimentalists, and en

Abraham del Valle Rodríguez

In 2002, it was conjectured that a free divisor satisfying the so-called Logarithmic Comparison Theorem must be strongly Euler-homogeneous and it was proved for the two-dimensional case. Later, in 2006, it was shown that the conjecture is also true in dimension three, but, today, the answer for the general case remains unknown. In this paper, we use the deco

Yaqiao Li, Pierre McKenzie

A model of computation for which reasonable yet still incomplete lower bounds are known is the read-once branching program. Here variants of complexity measures successful in the study of read-once branching programs are defined and studied. Some new or simpler proofs of known bounds are uncovered. Branching program resources and the new measures are compare

Galen Pogoncheff, Jacob Granley, Michael Beyeler

Convolutional neural networks (CNNs) have recently emerged as promising models of the ventral visual stream, despite their lack of biological specificity. While current state-of-the-art models of the primary visual cortex (V1) have surfaced from training with adversarial examples and extensively augmented data, these models are still unable to explain key ne

François Dahmani, Nicholas Touikan

Motivated by the study of the conjugacy problem for outer automorphism of free groups, we develop the algorithmic theory of the free-by-cyclic group produced by unipotent linearly growing automorphisms of f.g. free groups. We compute canonical splittings of these suspensions as well as their subgroups. We compute their automorphism groups. We show that this

Frederick Butler

Two well-known distributions in the study of permutation statistics are the Mahonian and Eulerian distributions. Mahonian statistics include the major index MAJ and the number of inversions INV, while examples of Eulerian statistics are the number of descents des and excedances exc. Also of interest are pairs of permutation statistics that have the same join

David Angeli, Lars Grüne

In this paper we extend dynamic programming techniques to the study of discrete-time infinite horizon optimal control problems on compact control invariant sets with state-independent best asymptotic average cost. To this end we analyse the interplay of dissipativity and optimal control, and propose novel recursive approaches for the solution of so called sh

Cristian-Paul Bara, Ziqiao Ma, Yingzhuo Yu, Julie Shah

Collaborative tasks often begin with partial task knowledge and incomplete initial plans from each partner. To complete these tasks, agents need to engage in situated communication with their partners and coordinate their partial plans towards a complete plan to achieve a joint task goal. While such collaboration seems effortless in a human-human team, it is

Jay Benesch

Circular accelerators typically have one injection and one extraction septum magnet. CEBAF is a recircuating electron linac which has a total of 27 DC current septa and one Lambertson. Current densities range from 28-48 A/mm 2 . Current sheet widths are 5-24 mm, turns count 5-24 and lengths 1000-3000 mm. A design exercise to increase the beam energy to 22 Ge

Luofu Liu, Chao Duan, Rui Wang

Despite the wide existence of vesicles in living cells as well as their important applications like drug-delivery, the underlying mechanism of vesicle fusion/fission remains under debate. Here, we develop a constrained self-consistent field theory (SCFT) which allows tracking the shape evolution and free energy as a function of center-of-mass separation dist

Manish Kumar Mandal, Saikat Roy

In this work, we thoroughly investigate the impact process on the granular media in the limit when the ratio of the impact velocity to the acoustic speed becomes of the order of 0.01-1, which is far greater than the existing literature (0.0001-0.001). We show that the energy dissipation is largely due to the energy cost associated with the exploration betwee

Christopher W. Davis, Shelly Harvey, JungHwan Park

A geometric interpretation of the vanishing of Milnor's higher order linking numbers remains an important open problem in the study of link concordance. In the 1990's, works of Cochran-Orr and Livingston exhibit a potential resolution to this problem in the form of homology boundary links. They exhibit the first known links with vanishing Milnor's invariants

Srdjan Sobot, Milan Lukic, Dusan Bortnik, Vladimir Nikic

In this paper, we propose, design, deploy and demonstrate a two-tier Low Power Wide Area Network (LP WAN) system based on Unmanned Aerial Vehicle (UAV) base stations suitable for dynamic deployment in deep rural environments. The proposed UAV-based LP WAN network augments the existing macro-cellular LP WAN network (Tier 1) with an additional layer of mobile

Sahabub Jahedi

We investigate the measurement of non-standard ZZV (V = {\gamma}, Z) couplings through Z-boson pair production at the $e^+ e^-$ colliders. We adopt Standard Model Effective Field Theory (SMEFT) approach to study these anomalous neutral triple gauge couplings. There are one CP-conserving and three CP-violating dim-8 SMEFT operators that contribute to ZZV coup

Krishnendu K. S.

Multi-focus is a technique of focusing on different aspects of a particular object or scene. Wireless Visual Sensor Networks (WVSN) use multi-focus image fusion, which combines two or more images to create a more accurate output image that describes the scene better than any individual input image. WVSN has various applications, including video surveillance,

Beata Zjawin, Marcin Bober, Roman Ciuryło, Daniel Lisak

Experiments aimed at searching for variations in the fine-structure constant $\alpha$ are based on spectroscopy of transitions in microscopic bound systems, such as atoms and ions, or resonances in optical cavities. The sensitivities of these systems to variations in $\alpha$ are typically on the order of unity and are fixed for a given system. For heavy ato

Sara Buson, Andrea Tramacere, Lenz Oswald, Eleonora Barbano

Identifying the astrophysical sources responsible for the high-energy cosmic neutrinos has been a longstanding challenge. In a previous work, we report evidence for a spatial correlation between blazars from the 5th Roma-BZCat catalog and neutrino data of the highest detectable energies, i.e. >0.1 PeV, collected by the IceCube Observatory in the southern cel

Jiaxu Zhao, Meng Fang, Zijing Shi, Yitong Li

\textit{\textbf{\textcolor{red}{Warning}:} This paper contains content that may be offensive or upsetting.} Pretrained conversational agents have been exposed to safety issues, exhibiting a range of stereotypical human biases such as gender bias. However, there are still limited bias categories in current research, and most of them only focus on English. In

Vojtech Kovarik, Caspar Oesterheld, Vincent Conitzer

Game-theoretic interactions with AI agents could differ from traditional human-human interactions in various ways. One such difference is that it may be possible to simulate an AI agent (for example because its source code is known), which allows others to accurately predict the agent's actions. This could lower the bar for trust and cooperation. In this pap

Zhan Gao, Amanda Prorok

Traditional approaches to the design of multi-agent navigation algorithms consider the environment as a fixed constraint, despite the influence of spatial constraints on agents' performance. Yet hand-designing conducive environment layouts is inefficient and potentially expensive. The goal of this paper is to consider the environment as a decision variable i

Chunyin Siu, Gennady Samorodnitsky, Christina Lee Yu, Rongyi He

The preferential attachment model is a natural and popular random graph model for a growing network that contains very well-connected ``hubs''. We study the higher-order connectivity of such a network by investigating the topological properties of its clique complex. We concentrate on the expected Betti numbers, a sequence of topological invariants of the co

Antonio De Rosa, Reinaldo Resende

We prove that $m$-dimensional Lipschitz graphs in any codimension with $C^{1,\alpha}$ boundary and anisotropic mean curvature bounded in $L^p$, $p > m$, are regular at every boundary point with density bounded above by $1/2 +\sigma$, provided the anisotropic energy satisfies the uniform scalar atomic condition.

Lucas S. Flores, Mendeli H. Vainstein, Heitor C. M. Fernandes, Marco A. Amaral

When studying social dilemma games, a crucial question arises regarding the impact of general heterogeneity on cooperation, which has been shown to have positive effects in numerous studies. Here, we demonstrate that heterogeneity in the contribution value for the focal Public Goods Game can jeopardize cooperation. We show that there is an optimal contributi

Eloy Geenjaar, Donghyun Kim, Riyasat Ohib, Marlena Duda

The neural dynamics underlying brain activity are critical to understanding cognitive processes and mental disorders. However, current voxel-based whole-brain dimensionality reduction techniques fall short of capturing these dynamics, producing latent timeseries that inadequately relate to behavioral tasks. To address this issue, we introduce a novel approac

Amrit Sedain, Nikolay Kacharov

Prolate rotation is characterized by a significant stellar rotation around a galaxy's major axis, which contrasts with the more common oblate rotation. Prolate rotation is thought to be due to major mergers and thus studies of prolate-rotating systems can help us better understand the hierarchical process of galaxy evolution. Dynamical studies of such galaxi

Hao Fei, Bobo Li, Qian Liu, Lidong Bing

While sentiment analysis systems try to determine the sentiment polarities of given targets based on the key opinion expressions in input texts, in implicit sentiment analysis (ISA) the opinion cues come in an implicit and obscure manner. Thus detecting implicit sentiment requires the common-sense and multi-hop reasoning ability to infer the latent intent of

Sergey V. Ulyanov, Viktor S. Ulyanov, Takakhide Hagiwara

A generalized strategy for the design of intelligent robust control systems based on quantum / soft computing technologies is described. The reliability of hybrid intelligent controllers increase by providing the ability to self-organize of imperfect knowledge bases. The main attention is paid to increasing the level of robustness of intelligent control syst

Chandana Mondal, Michael Moshe, Itamar Procaccia, Saikat Roy

When amorphous solids are subjected to simple or pure strain, they exhibit elastic increase in stress, punctuated by plastic events that become denser (in strain) upon increasing the system size. It is customary to assume in theoretical models that the stress released in each plastic event is redistributed according to the linear Eshelby kernel, causing aval

Samuel Schmidgall, Jascha Achterberg, Thomas Miconi, Louis Kirsch

Artificial neural networks (ANNs) have emerged as an essential tool in machine learning, achieving remarkable success across diverse domains, including image and speech generation, game playing, and robotics. However, there exist fundamental differences between ANNs' operating mechanisms and those of the biological brain, particularly concerning learning pro

Wanyong Feng, Aritra Ghosh, Stephen Sireci, Andrew S. Lan

Computerized adaptive testing (CAT) is a form of personalized testing that accurately measures students' knowledge levels while reducing test length. Bilevel optimization-based CAT (BOBCAT) is a recent framework that learns a data-driven question selection algorithm to effectively reduce test length and improve test accuracy. However, it suffers from high qu

Oleg Sobchuk, Artjoms Šeļa

What are the best methods of capturing thematic similarity between literary texts? Knowing the answer to this question would be useful for automatic clustering of book genres, or any other thematic grouping. This paper compares a variety of algorithms for unsupervised learning of thematic similarities between texts, which we call "computational thematics". T

Sarah A. Gilbert

Shortcomings of current models of moderation have driven policy makers, scholars, and technologists to speculate about alternative models of content moderation. While alternative models provide hope for the future of online spaces, they can fail without proper scaffolding. Community moderators are routinely confronted with similar issues and have therefore f