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Ah, alright, okay! : communicating understanding in conversational product search

When talking about products, people often express their needs in vague terms with vocabulary that does not necessarily overlap with product descriptions written by retailers. This poses a problem for chatbots in online shops, as the vagueness and vocabulary mismatch can lead to misunderstandings. In human-human communication, people intuitively build a common understanding throughout a conversatio

A multi-program analysis of cleft lip with cleft palate prevalence and mortality using data from 22 International Clearinghouse for Birth Defects Surveillance and Research programs, 1974–2014

Background: Cleft lip with cleft palate (CLP) is a congenital condition that affects both the oral cavity and the lips. This study estimated the prevalence and mortality of CLP using surveillance data collected from birth defect registries around the world. Methods: Data from 22 population- and hospital-based surveillance programs affiliated with the International Clearinghouse for Birth Defects S

Circuit analysis using monotone+skew splitting

It is shown that the behavior of an m-port circuit of maximal monotone elements can be expressed as a zero of the sum of a maximal monotone operator containing the circuit elements, and a structured skew-symmetric linear operator representing the interconnection structure, together with a linear output transformation. The Condat–Vũ algorithm solves inclusion problems of this form, and may be used

CyberROAD : a cybersecurity risk assessment ontology for automotive domain aligned with ISO/SAE 21434:2021

The automotive domain is becoming increasingly complex through the integration of new technologies. As a result, cybersecurity is recognized as a pressing issue. This study focuses on the ISO/SAE 21434:2021 standard for road vehicles cybersecurity engineering, evaluating the effectiveness of the standard’s risk assessment approach. The standard suggests a set of assessment steps, and previous rese

Atmospheric new particle formation identifier using longitudinal global particle number size distribution data

Atmospheric new particle formation (NPF) is a naturally occurring phenomenon, during which high concentrations of sub-10 nm particles are created through gas to particle conversion. The NPF is observed in multiple environments around the world. Although it has observable influence onto annual total and ultrafine particle number concentrations (PNC and UFP, respectively), only limited epidemiologic

Language exposure and use in study abroad versus migration contexts: Modelling activity and learner profiles with ESM data

Language exposure and use (LEU) are widely viewed as key factors in multilingual development, and research highlights the importance of considering not just the frequency and quantity of LEU, but also contextual factors such as when and where a language is used, with whom and why. In this study, we illustrate the complexity of LEU in two contexts (study abroad and migration) by applying sequential

Duality-based Dynamical Optimal Transport of Discrete Time Systems

We study dynamical optimal transport of discrete time systems (dDOT) with Lagrangian cost. The problem is approached by combining optimal control and Kantorovich duality theory. Based on the derived solution, a first order splitting algorithm is proposed for numerical implementation. While solving partial differential equations is often required in the continuous time case, a salient feature of ou

Optimal Mass Transport of Nonlinear Systems under Input and Density Constraints

We investigate optimal mass transport problem of affine-nonlinear dynamical systems with input and density constraints. Three algorithms are proposed to tackle this problem, including two Uzawa-type methods and a splitting algorithm based on the Douglas-Rachford algorithm. Some preliminary simulation results are presented to demonstrate the effectiveness of our approaches.

Exploiting Heterogeneity in the Decentralised Control of Platoons

This paper investigates the use of decentralised control architectures with heterogeneous dynamics for improving performance in large-scale systems. Our focus is on two well-known decentralised approaches; the 'predecessor following' and 'bidirectional' architectures for vehicle platooning. The former, utilising homogeneous control dynamics, is known to face exponential growth in disturbance ampli

On PI-control in Capacity-Limited Networks

This paper concerns control of a class of systems where multiple dynamically stable agents share a nonlinear and bounded control-interconnection. The agents are subject to a disturbance which is too large to reject with the available control action, making it impossible to stabilize all agents in their desired states. In this nonlinear setting, we consider two different anti-windup equipped propor

Data-Driven Adaptive Dispatching Policies for Processing Networks

This letter presents and analyzes an adaptive data-driven controller that learns the optimal processing rate in a multi-unit processing network in the presence of disturbances. We formulate an optimization problem of linear cost, linear dynamics for the processing network model and an affine constraint on the dispatcher policy. A data-driven linear equation is constructed, based on which the onlin

Characteristic Modes of Nonreciprocal Systems

The scattering formulation of characteristic mode decomposition is utilized to extend modal analysis to lossless scatterers breaking time-reversal symmetry. This enables characteristic modes analysis on devices containing gyrotropic or moving media. The resulting nonreciprocity introduces features not observed in reciprocal scenarios, such as asymmetric phase progression in characteristic far fiel

Optimal control of linear cost networks

We present a method for optimal control with respect to a linear cost function for positive linear systems with coupled input constraints. We show that the Bellman equation giving the optimal cost function and resulting sparse state feedback for these systems can be stated explicitly, with the solution given by a linear program. Our framework admits a range of network routing problems with underly

A Minimax Optimal Controller for Positive Systems

We present an explicit solution to the discrete-time Bellman equation for minimax optimal control of positive systems under unconstrained disturbances. The primary contribution of our result relies on deducing a bound for the disturbance penalty, which characterizes the existence of a finite solution to the problem class. Moreover, this constraint on the disturbance penalty reveals that, in scenar

A frequency domain analysis of slow coherency in networked systems

Network coherence generally refers to the emergence of simple aggregated dynamical behaviors, despite heterogeneity in the dynamics of the subsystems that constitute the network. In this paper, we develop a general frequency domain framework to analyze and quantify the level of network coherence that a system exhibits by relating coherence with a low-rank property of the system's input–output resp

Gamifying user feedback collection on static program analysis tools

Use of static program analysis tools can be highly beneficial in software development, but usage is hindered by usability issues. One method to better understand these issues is to gather user feedback, but it is challenging to get developers to invest effort in giving user feedback.In this paper, we investigate whether gamification can increase user engagement in feedback collection on static ana

Time-resolved representational similarity analysis reveals integrated and separated neural patterns of overlapping events

Episodic memory allows the flexible retrieval of commonalities and idiosyncrasies of overlapping life events. For example, seeing a woman in the city with your colleague's daughter may form an integrated memory representation involving the woman and your colleague. However, you may also keep a specific representation of the city event to talk with your colleague about the circumstances of having m

Longitudinal enumeration and cluster evaluation of circulating tumor cells improve prognostication for patients with newly diagnosed metastatic breast cancer in a prospective observational trial

Background: Circulating tumor cells (CTCs) carry independent prognostic information in patients with metastatic breast cancer (MBC) on different lines of therapy. Moreover, CTC clusters are suggested to add prognostic information to CTC enumeration alone but their significance is unknown in patients with newly diagnosed MBC. We aimed to evaluate whether longitudinal enumeration of circulating tumo

Using machine learning hardware to solve linear partial differential equations with finite difference methods

This study explores the potential of utilizing hardware built for Machine Learning (ML) tasks as a platform for solving linear Partial Differential Equations via numerical methods. We examine the feasibility, benefits, and obstacles associated with this approach. Given an Initial Boundary Value Problem (IBVP) and a finite difference method, we directly compute stencil coefficients and assign them

Theory and Computation of Substructure Characteristic Modes

The problem of substructure characteristic modes is developed using a scattering matrix-based formulation, generalizing subregion characteristic mode decomposition to arbitrary computational tools. It is shown that the modes of the scattering formulation are identical to the modes of the classical formulation based on the background Green’s function for lossless systems under conditions where both