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This study investigates the causal effects of open-water swim drafting by leveraging a natural experiment induced by staggered race starts during the COVID-19 pandemic. Before 2020, athletes started in groups, enabling drafting benefits, while pandemic-related restrictions significantly reduced these opportunities. Using agglomerative hierarchical clustering of swim-out times, I analyze optimal drafting positions and estimate their impact on Swim-Out performance. Our empirical findings reveal that swim drafting benefits were statistically insignificant in 2020 but persisted post-pandemic at slightly reduced levels. I find that drafting becomes advantageous only from the third trailing position onward, with earlier positions primarily serving to minimize fatigue. To mitigate endogeneity, I employ athlete and event fixed effects. The seemingly inverse decaying nature of drafting benefits partially addresses some concerns of simultaneous reverse causality and omitted variable bias. This study provides the first largescale causal estimate of drafting effects in real-world triathlon race settings., Comment: 16 pages

Increasingly frequent publications in the literature report voice quality differences between depressed patients and controls. Here, we examine the possibility of using voice analysis as an early warning signal for the development of emotion disturbances in young adults. As part of a major interdisciplinary European research project in four countries (ECoWeB), examining the effects of web-based prevention programs to reduce the risk for depression in young adults, we analyzed a large number of acoustic voice characteristics in vocal reports of emotions experienced by the participants on a specific day. We were able to identify a number of significant differences in acoustic cues, particularly with respect to the energy distribution in the voice spectrum, encouraging further research efforts to develop promising non-obtrusive risk indicators in the normal speaking voice. This is particularly important in the case of young adults who are less likely to exhibit standard risk factors for depression such as negative life experiences., Comment: Submitted to ToaC

According zu Kadir et al. (2023) online marketplaces are used to buy and sell products and services, as well as to exchange money and data between users or the platform. Due to the large product selection, low costs and the ease of shopping without physical restrictions as well as the technical possibilities, online marketplaces have grown rapidly Kadir et al. (2023). Online marketplaces are also used in the consumer-to-consumer (C2C) sector and thus offer a broad user group a marketplace, for example for used products. This article focuses on Willhaben.at (2024), a leading C2C marketplace in Austria, as stated by Obersteiner, Schmied, and Pamperl (2023). The empirical analysis in this course essay centers around the offer ads of Woom Bikes, a standardised product which is sold on Willhaben. Through web scraping, a dataset of approximately 826 observations was created, focusing on mid-to-high price segment bicycles, which are characterized by price stability and uniformity as we claim. This analysis aims to create analyse ad listing prices through predictive models using willhaben product listing attributes and using the spatial distribution of one of the product attributes., Comment: 12 pages, 7 tables, 5 figures

Complex networks are made up of vertices and edges. The edges, which may be directed or undirected, are equipped with positive weights. Modeling complex systems that consist of different types of objects leads to multilayer networks, in which vertices in distinct layers represent different kinds of objects. Multiplex networks are special vertex-aligned multilayer networks, in which vertices in distinct layers are identified with each other and inter-layer edges connect each vertex with its copy in other layers and have a fixed weight $\gamma>0$ associated with the ease of communication between layers. This paper discusses two different approaches to analyze communication in a multiplex. One approach focuses on the multiplex global efficiency by using the multiplex path length matrix, the other approach considers the multiplex total communicability. The sensitivity of both the multiplex global efficiency and the multiplex total communicability to structural perturbations in the network is investigated to help to identify intra-layer edges that should be strengthened to enhance communicability., Comment: 16 pages, 4 tables

We consider the full set of Maxwell equations in a slab or cylindrical waveguide with a cubically nonlinear material law for the polarization of the electric field. The nonlinear polarization may be instantaneous or retarded, and we assume it to be confined inside the core of the waveguide. We prove existence of infinitely many spatially localized, real-valued and time-periodic solutions (breathers) propagating inside the waveguide by applying a variational minimization method to the resulting scalar quasilinear elliptic-hyperbolic equation for the profile of the breathers. The temporal period of the breathers has to be carefully chosen depending on the linear properties of the waveguide. As an example, our results apply if a two-layered linear axisymmetric waveguide is enhanced by a third core region with low refractive index where also the nonlinearity is located. In this case we can also connect our existence result with a bifurcation result. We illustrate our results with numerical simulations. Our solutions are polychromatic functions in general, but for some special models of retarded nonlinear material laws, also monochromatic solutions can exist. In this case the numerical simulations raise an interesting open question: are the breather solutions with minimal energy monochromatic or polychromatic?

Complex networks are made up of vertices and edges. The latter connect the vertices. There are several ways to measure the importance of the vertices, e.g., by counting the number of edges that start or end at each vertex, or by using the subgraph centrality of the vertices. It is more difficult to assess the importance of the edges. One approach is to consider the line graph associated with the given network and determine the importance of the vertices of the line graph, but this is fairly complicated except for small networks. This paper compares two approaches to estimate the importance of edges of medium-sized to large networks. One approach computes partial derivatives of the total communicability of the weights of the edges, where a partial derivative of large magnitude indicates that the corresponding edge may be important. Our second approach computes the Perron sensitivity of the edges. A high sensitivity signals that the edge may be important. The performance of these methods and some computational aspects are discussed. Applications of interest include to determine whether a network can be replaced by a network with fewer edges with about the same communicability., Comment: 25 pages, 8 tables, 2 figures

Early results on the plasma deposition of dielectric thin films on acoustic wave (AW) activated substrates revealed a densification pattern arisen from the focusing of plasma ions and their impact on specific areas of the piezoelectric substrate. Herein, we extend this methodology to tailor the plasma deposition of metals onto AW-activated LiNbO3 piezoelectric substrates. Our investigation reveals the tracking of the initial stages of nanoparticle (NP) formation and growth during the submonolayer deposition of silver. We elucidate the specific role of AW activation in reducing particle size, enhancing particle circularity, and retarding NP agglomeration and account for the physical phenomena making these processes differ from those occurring on non-activated substrates. We provide a comparative analysis of the results obtained under two representative plasma conditions: diode DC sputtering and magnetron sputtering. In the latter case, the AW activation gives rise to a 2D pattern of domains with different amounts of silver and a distinct size and circularity for the silver NPs. This difference was attributed to the specific characteristics of the plasma sheath formed onto the substrate in each case. The possibilities of tuning the plasmon resonance absorption of silver NPs by AW activation of the sputtering deposition process are discussed., Comment: 26 pages, 8 figures

The Arnoldi-Tikhonov method is a well-established regularization technique for solving large-scale ill-posed linear inverse problems. This method leverages the Arnoldi decomposition to reduce computational complexity by projecting the discretized problem into a lower-dimensional Krylov subspace, in which it is solved. This paper explores the iterated Arnoldi-Tikhonov method, conducting a comprehensive analysis that addresses all approximation errors. Additionally, it introduces a novel strategy for choosing the regularization parameter, leading to more accurate approximate solutions compared to the standard Arnoldi-Tikhonov method. Moreover, the proposed method demonstrates robustness with respect to the regularization parameter, as confirmed by the numerical results.

Continuous-variable bosonic systems stand as prominent candidates for implementing quantum computational tasks. While various necessary criteria have been established to assess their resourcefulness, sufficient conditions have remained elusive. We address this gap by focusing on promoting circuits that are otherwise simulatable to computational universality. The class of simulatable, albeit non-Gaussian, circuits that we consider is composed of Gottesman-Kitaev-Preskill (GKP) states, Gaussian operations, and homodyne measurements. Based on these circuits, we first introduce a general framework for mapping a continuous-variable state into a qubit state. Subsequently, we cast existing maps into this framework, including the modular and stabilizer subsystem decompositions. By combining these findings with established results for discrete-variable systems, we formulate a sufficient condition for achieving universal quantum computation. Leveraging this, we evaluate the computational resourcefulness of a variety of states, including Gaussian states, finite-squeezing GKP states, and cat states. Furthermore, our framework reveals that both the stabilizer subsystem decomposition and the modular subsystem decomposition (of position-symmetric states) can be constructed in terms of simulatable operations. This establishes a robust resource-theoretical foundation for employing these techniques to evaluate the logical content of a generic continuous-variable state, which can be of independent interest., Comment: 31 pages, 14 figures

Modeling complex systems that consist of different types of objects leads to multilayer networks, in which vertices are connected by both inter-layer and intra-layer edges. In this paper, we investigate multiplex networks, in which vertices in different layers are identified with each other, and the only inter-layer edges are those that connect a vertex with its copy in other layers. Let the third-order adjacency tensor $\mathcal{A}\in\R^{N\times N\times L}$ and the parameter $\gamma\geq 0$, which is associated with the ease of communication between layers, represent a multiplex network with $N$ vertices and $L$ layers. To measure the ease of communication in a multiplex network, we focus on the average inverse geodesic length, which we refer to as the multiplex global efficiency $e_\mathcal{A}(\gamma)$ by means of the multiplex path length matrix $P\in\R^{N\times N}$. This paper generalizes the approach proposed in \cite{NR23} for single-layer networks. We describe an algorithm based on min-plus matrix multiplication to construct $P$, as well as variants $P^K$ that only take into account multiplex paths made up of at most $K$ intra-layer edges. These matrices are applied to detect redundant edges and to determine non-decreasing lower bounds $e_\mathcal{A}^K(\gamma)$ for $e_\mathcal{A}(\gamma)$, for $K=1,2,\dots,N-2$. Finally, the sensitivity of $e_\mathcal{A}^K(\gamma)$ to changes of the entries of the adjacency tensor $\mathcal{A}$ is investigated to determine edges that should be strengthened to enhance the multiplex global efficiency the most., Comment: 18 pages, 1 figure, 5 tables

Fredholm integral equations of the second kind that are defined on a finite or infinite interval arise in many applications. This paper discusses Nystr\"om methods based on Gauss quadrature rules for the solution of such integral equations. It is important to be able to estimate the error in the computed solution, because this allows the choice of an appropriate number of nodes in the Gauss quadrature rule used. This paper explores the application of averaged and weighted averaged Gauss quadrature rules for this purpose, and introduces new stability properties for them., Comment: 27 pages, 2 figures

We introduce two rule-based models to modify the prosody of speech synthesis in order to modulate the emotion to be expressed. The prosody modulation is based on speech synthesis markup language (SSML) and can be used with any commercial speech synthesizer. The models as well as the optimization result are evaluated against human emotion annotations. Results indicate that with a very simple method both dimensions arousal (.76 UAR) and valence (.43 UAR) can be simulated., Comment: accepted at 34th ESSV 2023, Munich 2023

We report on the coupling of a reconfigurable high Q fiber micro-cavity to an organic color center grafted to a carbon nanotube for telecom wavelength emission of single photons in the Purcell regime. Using three complementary approaches we assess various figures of merit of this tunable single photon source and of the cavity quantum electrodynamical effects : the brightening of the emitter is obtained by comparison of the count rates of the very same emitter in free-space and cavity coupled regimes. We demonstrate a fiber coupled single-photon output rate up to 20 MHz at 1275~nm. Using time-resolved and saturation measurements, we determine independently the radiative quantum yield and the Purcell factor of the system with values up to 30 for the smallest mode volumes. Finally, we take advantage of the tuning capability of the cavity to measure the spectral profile of the brightness of the source which gives access to the vacuum Rabi splitting $g$ with values up to $25 \; \mu$eV.

Let a network be represented by a simple graph $\mathcal{G}$ with $n$ vertices. A common approach to investigate properties of a network is to use the adjacency matrix $A=[a_{ij}]_{i,j=1}^n\in\R^{n\times n}$ associated with the graph $\mathcal{G}$, where $a_{ij}>0$ if there is an edge pointing from vertex $v_i$ to vertex $v_j$, and $a_{ij}=0$ otherwise. Both $A$ and its positive integer powers reveal important properties of the graph. This paper proposes to study properties of a graph $\mathcal{G}$ by also using the path length matrix for the graph. The $(ij)^{th}$ entry of the path length matrix is the length of the shortest path from vertex $v_i$ to vertex $v_j$; if there is no path between these vertices, then the value of the entry is $\infty$. Powers of the path length matrix are formed by using min-plus matrix multiplication and are important for exhibiting properties of $\mathcal{G}$. We show how several known measures of communication such as closeness centrality, harmonic centrality, and eccentricity are related to the path length matrix, and we introduce new measures of communication, such as the harmonic $K$-centrality and global $K$-efficiency, where only (short) paths made up of at most $K$ edges are taken into account. The sensitivity of the global $K$-efficiency to changes of the entries of the adjacency matrix also is considered., Comment: 16 pages

The tensor t-product, introduced by Kilmer and Martin [26], is a powerful tool for the analysis of and computation with third-order tensors. This paper introduces eigentubes and eigenslices of third-order tensors under the t-product. The eigentubes and eigenslices are analogues of eigenvalues and eigenvectors for matrices. Properties of eigentubes and eigenslices are investigated and numerical methods for their computation are described. The methods include the tensor power method, tensor subspace iteration, and the tensor QR algorithm. Computed examples illustrate the performance of these methods.

In this contribution we propose a data-driven surrogate model for the prediction of magnetic stray fields in two-dimensional random micro-heterogeneous materials. Since data driven models require thousands of training data sets, FEM simulations appear to be too time consuming. Hence, a stochastic model based on Brownian motion, which utilizes an efficient evaluation of stochastic transition matrices, is applied for the training data generation. For the encoding of the microstructure and the optimization of the surrogate model, two architectures are compared, i.e. the so-called UResNet model and the Fourier Convolutional neural network (FCNN). Here we analyze two FCNNs, one based on the discrete cosine transformation and one based on the complex-valued discrete Fourier transformation. Finally, we compare the magnetic stray fields for independent microstructures (not used in the training set) with results from the FE$^2$ method, a numerical homogenization scheme, to demonstrate the efficiency of the proposed surrogate model.

Here, we derive the equations to calculate the effective viscosity of solutions of methyl cellulose (MC) dissolved in phosphate buffered saline (PBS) in real-time deformability cytometry (RT-DC) experiments. The calculations are based on the rheometer measurements described by B\"uy\"ukurganci et al. (2022). We outline how to get the final equations and compare the results to the current viscosity model from Herold (2017). These viscosity functions will be used to determine the Young's moduli of biological cells and other soft materials from RT-DC experiments.