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  1. Abstract

    To fulfill the demands of more bandwidth in 5G and 6G communication technology, new dielectric substrates that can be co‐fired into packages and devices that have low dielectric loss and improved thermal conductivity are desired. The motivation for this study is to design composites with low dielectric loss (tan δ) and high thermal conductivity (κ), while still limiting the electrical conductivity, for microwave applications involving high power and high frequency. This work describes the fabrication of high‐density electroceramic composites with a model dielectric material for cold sintering, namely sodium molybdate (Na2Mo2O7), and fillers with higher thermal conductivity such as hexagonal boron nitride. The physical properties of the composites were characterized as a function of filler vol.%, temperature, and frequency. Understanding the variation in measured properties is achieved through analyzing the respective transport mechanisms.

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    Free, publicly-accessible full text available October 1, 2024
  2. Magnetic induction localization is an inverse problem that determines the relative position and orientation (pose) between transmitting and receiving coils by analyzing the received signals. Related work has established methods to resolve the localization into two candidate poses. However, these methods require having signed signals, or periodic signals whose starting point is unambiguously determined with respect to an absolute reference (the transmitted signal). For distributed systems, the signal signs are difficult to resolve. This paper presents a method to extract partial information about the signs from unsigned signals. The method is tested in a hardware experiment. 
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  3. Background: Multivariate pattern analysis (MVPA or pattern decoding) has attracted considerable attention as a sensitive analytic tool for investigations using functional magnetic resonance imaging (fMRI) data. With the introduction of MVPA, however, has come a proliferation of methodological choices confronting the researcher, with few studies to date offering guidance from the vantage point of controlled datasets detached from specific experimental hypotheses. New method: We investigated the impact of four data processing steps on support vector machine (SVM) classification performance aimed at maximizing information capture in the presence of common noise sources. The four techniques included: trial averaging (classifying on separate trial estimates versus condition-based averages), within-run mean centering (centering the data or not), method of cost selection (using a fixed or tuned cost value), and motion-related denoising approach (comparing no denoising versus a variety of nuisance regressions capturing motion-related reference signals). The impact of these approaches was evaluated on real fMRI data from two control ROIs, as well as on simulated pattern data constructed with carefully controlled voxel- and trial-level noise components. Results: We find significant improvements in classification performance across both real and simulated datasets with run-wise trial averaging and mean centering. When averaging trials within conditions of each run, we note a simultaneous increase in the between-subject variability of SVM classification accuracies which we attribute to the reduced size of the test set used to assess the classifier's prediction error. Therefore, we propose a hybrid technique whereby randomly sampled subsets of trials are averaged per run and demonstrate that it helps mitigate the tradeoff between improving signal-to-noise ratio by averaging and losing exemplars in the test set. Comparison with existing methods: Though a handful of empirical studies have employed run-based trial averaging, mean centering, or their combination, such studies have done so without theoretical justification or rigorous testing using control ROIs. Conclusions: Therefore, we intend this study to serve as a practical guide for researchers wishing to optimize pattern decoding without risk of introducing spurious results. 
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  4. This paper investigates using a sampling-based approach, the RRT*, to reconfigure a 2D set of connected tiles in complex environments, where multiple obstacles might be present. Since the target application is automated building of discrete, cellular structures using mobile robots, there are constraints that determine what tiles can be picked up and where they can be dropped off during reconfiguration. We compare our approach to two algorithms as global and local planners, and show that we are able to find more efficient build sequences using a reasonable amount of samples, in environments with varying degrees of obstacle space. 
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    Localization is a key ability for robot navigation and collision avoidance. The advent of technologies such as GPS have led to many improvements in terrestrial navigation. Unfortunately traditional electromagnetic (EM) communications propagate poorly through lossy media such as underwater and underground. Therefore, localization remains a challenging problem in such environments, necessitating other approaches such as acoustics and magnetic induction (MI). This paper investigates estimating the relative location of a pair of MI triaxial coil antennas in air, as a preliminary step to underwater applications. By measuring the voltages induced in the receiving antenna when the transmitting antenna's coils are turned on sequentially, the distance between the antennas can be computed. Then, with knowledge of the current velocities of the antennas, we can apply a particle filter to generate an estimate of the location of the transmitting antenna with respect to the receiving one. The theory is supported by simulations and later verified through a series of experiments. 
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  8. Abstract

    Observations of linear polarization in the 2–8 keV energy range with the Imaging X-ray Polarimetry Explorer (IXPE) explore the magnetic field geometry and dynamics of the regions generating nonthermal radiation in relativistic jets of blazars. These jets, particularly in blazars whose spectral energy distribution peaks at X-ray energies, emit X-rays via synchrotron radiation from high-energy particles within the jet. IXPE observations of the X-ray-selected BL Lac–type blazar 1ES 1959+650 on 2022 May 3–4 showed a significant linear polarization degree of Πx= 8.0% ± 2.3% at an electric-vector position angleψx= 123° ± 8°. However, on 2022 June 9–12, only an upper limit of Πx≤ 5.1% could be derived (at the 99% confidence level). The degree of optical polarization at that time, ΠO∼ 5%, is comparable to the X-ray measurement. We investigate possible scenarios for these findings, including temporal and geometrical depolarization effects. Unlike some other X-ray-selected BL Lac objects, there is no significant chromatic dependence of the measured polarization in 1ES 1959+650, and its low X-ray polarization may be attributed to turbulence in the jet flow with dynamical timescales shorter than 1 day.

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    Free, publicly-accessible full text available February 21, 2025