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We study the effect of educational attainment on family formation using regression discontinuity designs generated by centralized admissions processes to both secondary and tertiary education in Finland. Admission to further education at either margin does not increase the likelihood that men form families. In contrast, women admitted to further education are more likely to both live with a partner and have children. We then pre-register and test two hypotheses which could explain each set of results using survey data. These suggest that the positive association between men's education and family formation observed in the data is driven by selection. For women, our estimates are consistent with the idea that, as increased returns to social skills shift the burden of child development from schools to parents and particularly mothers, education can make women more attractive as potential partners. [Funding for this report was provided by The Strategic Research Council, the Research Council of Finland, and Palkansaajasäätiö.]

This paper introduces briefly the history and growth of the Detection and Classification of Acoustic Scenes and Events (DCASE) challenge, workshop, research area and research community. Created in 2013 as a data evaluation challenge, DCASE has become a major research topic in the Audio and Acoustic Signal Processing area. Its success comes from a combination of factors: the challenge offers a large variety of tasks that are renewed each year; and the workshop offers a channel for dissemination of related work, engaging a young and dynamic community. At the same time, DCASE faces its own challenges, growing and expanding to different areas. One of the core principles of DCASE is open science and reproducibility: publicly available datasets, baseline systems, technical reports and workshop publications. While the DCASE challenge and workshop are independent of IEEE SPS, the challenge receives annual endorsement from the AASP TC, and the DCASE community contributes significantly to the ICASSP flagship conference and the success of SPS in many of its activities., Comment: Submitted to ICASSP 2025

Recent advancements in music source separation have significantly progressed, particularly in isolating vocals, drums, and bass elements from mixed tracks. These developments owe much to the creation and use of large-scale, multitrack datasets dedicated to these specific components. However, the challenge of extracting similarly sounding sources from orchestra recordings has not been extensively explored, largely due to a scarcity of comprehensive and clean (i.e bleed-free) multitrack datasets. In this paper, we introduce a novel multitrack dataset called SynthSOD, developed using a set of simulation techniques to create a realistic (i.e. using high-quality soundfonts), musically motivated, and heterogeneous training set comprising different dynamics, natural tempo changes, styles, and conditions. Moreover, we demonstrate the application of a widely used baseline music separation model trained on our synthesized dataset w.r.t to the well-known EnsembleSet, and evaluate its performance under both synthetic and real-world conditions., Comment: Submitted to the OJSP - ICASSP 2025

Zero-shot learning models are capable of classifying new classes by transferring knowledge from the seen classes using auxiliary information. While most of the existing zero-shot learning methods focused on single-label classification tasks, the present study introduces a method to perform multi-label zero-shot audio classification. To address the challenge of classifying multi-label sounds while generalizing to unseen classes, we adapt temporal attention. The temporal attention mechanism assigns importance weights to different audio segments based on their acoustic and semantic compatibility, thus enabling the model to capture the varying dominance of different sound classes within an audio sample by focusing on the segments most relevant for each class. This leads to more accurate multi-label zero-shot classification than methods employing temporally aggregated acoustic features without weighting, which treat all audio segments equally. We evaluate our approach on a subset of AudioSet against a zero-shot model using uniformly aggregated acoustic features, a zero-rule baseline, and the proposed method in the supervised scenario. Our results show that temporal attention enhances the zero-shot audio classification performance in multi-label scenario., Comment: Accepted to International Workshop on Acoustic Signal Enhancement (IWAENC) 2024

Digital audio watermarking consists in inserting a message into audio signals in a transparent way and can be used to allow automatic recognition of audio material and management of the copyrights. We propose a perceptual loss function to be used in deep neural network based audio watermarking systems. The loss is based on the noise-to-mask ratio (NMR), which is a model of the psychoacoustic masking effect characteristic of the human ear. We use the NMR loss between marked and host signals to train the deep neural models and we evaluate the objective quality with PEAQ and the subjective quality with a MUSHRA test. Both objective and subjective tests show that models trained with NMR loss generate more transparent watermarks than models trained with the conventionally used MSE loss, Comment: 6 pages, 7 figures

Audio-text relevance learning refers to learning the shared semantic properties of audio samples and textual descriptions. The standard approach uses binary relevances derived from pairs of audio samples and their human-provided captions, categorizing each pair as either positive or negative. This may result in suboptimal systems due to varying levels of relevance between audio samples and captions. In contrast, a recent study used human-assigned relevance ratings, i.e., continuous relevances, for these pairs but did not obtain performance gains in audio-text relevance learning. This work introduces a relevance learning method that utilizes both human-assigned continuous relevance ratings and binary relevances using a combination of a listwise ranking objective and a contrastive learning objective. Experimental results demonstrate the effectiveness of the proposed method, showing improvements in language-based audio retrieval, a downstream task in audio-text relevance learning. In addition, we analyze how properties of the captions or audio clips contribute to the continuous audio-text relevances provided by humans or learned by the machine., Comment: Accepted at DCASE 2024 Workshop

The masses of the ground and isomeric states in $^{124,125}$Ag have been measured using the phase-imaging ion-cyclotron-resonance technique at the JYFLTRAP double Penning trap mass spectrometer. The ground states of $^{124}$Ag and $^{125}$Ag were found to be 30(250) keV and 250(430) keV less bound but 36 and 110 times more precise than in the Atomic Mass Evaluation 2020, respectively. The excitation energy of $^{124}$Ag$^{m}$, ${E_x = 188.2(25)}$ keV, was determined for the first time. The new precise mass values have been utilised to study the evolution of nuclear structure via two-neutron separation energies. The impact on the astrophysical rapid neutron capture process has been investigated via neutron-capture reaction rate calculations. The precision measurements indicate a more linear trend in two-neutron separation energies and reduce the mass-related uncertainties for the neutron-capture rate of $^{124}$Ag$(n,\gamma)^{125}$Ag by a factor of around 100. The new mass values also improve the mass of $^{123}$Pd, previously measured using $^{124}$Ag as a reference., Comment: 9 pages, 4 figures

We report on high-precision atomic mass measurements of $^{148\text{-}153}$La and $^{151}$Ce performed with the JYFLTRAP double Penning trap using the Phase-Imaging Ion-Cyclotron-Resonance technique. The masses of $^{152,153}$La were experimentally determined for the first time. We confirm the sharp kink in the two-neutron separation energies at the neutron number ${N=93}$ in the cerium (${Z=58}$) isotopic chain. Our precision mass measurements of the most exotic neutron-rich lanthanum (${Z=57}$) isotopes reveal a sudden increase in two-neutron separation energies from ${N=92}$ to ${N=93}$. Unlike in the cerium isotopic chain, the kink is not sharp but extends to ${N=94}$ forming a prominent bump. The gain in energy is about 0.4 MeV, making it one of the strongest changes in two-neutron separation energies over the whole chart of nuclides, away from nuclear shell closures. The results call for further studies to elucidate the structure of neutron-rich lanthanum isotopes., Comment: 9 pages, 4 figures

In this survey we show how to produce asymptotics of determinants of structured matrices using operator theory methods. We describe the asymptotics for finite Toeplitz matrices, finite Toeplitz plus Hankel matrices and generalizations of these, and also finite sections of functions of Toeplitz operators, all with smooth matrix-valued symbols. Many of these results are well-known. However, the results for certain Toeplitz plus Hankel operators with matrix-valued symbol are presented for the first time and the result for the finite sections of functions of Toeplitz operators is new.

Foundation models (FMs) are increasingly spearheading recent advances on a variety of tasks that fall under the purview of computer audition -- the use of machines to understand sounds. They feature several advantages over traditional pipelines: among others, the ability to consolidate multiple tasks in a single model, the option to leverage knowledge from other modalities, and the readily-available interaction with human users. Naturally, these promises have created substantial excitement in the audio community, and have led to a wave of early attempts to build new, general-purpose foundation models for audio. In the present contribution, we give an overview of computational audio analysis as it transitions from traditional pipelines towards auditory foundation models. Our work highlights the key operating principles that underpin those models, and showcases how they can accommodate multiple tasks that the audio community previously tackled separately.

In this article we study the generalized Hilbert matrix operator $\Gamma_\mu$ acting on the Bergman spaces $A^p$ of the unit disc for $1\leq p<\infty$. In particular, we characterize the measures $\mu$ for which the operator $\Gamma_\mu$ is bounded and we provide estimates of its operator norm. Finally, we also describe when $\Gamma_\mu$ is compact by computing its essential norm.

We describe a numerical approach to modeling magnetoelectric effects generated by spin-orbit coupling in inhomogeneous diffusive 2D superconductors. It is based on direct minimization of the free energy of diffusion modes, including their coupling to the spin-orbit field strength, described by a recently discovered $\sigma$-model action. We explain how to retain exact conservation laws in the the discretized model, and detail the numerical procedure. We apply the approach to the spin-galvanic and the inverse spin-galvanic effects in finite-size 2D superconductors, and describe short-range oscillations of circulating currents and spin densities originating from the spin-orbit coupling., Comment: 9 pages, 6 figures

We characterize the superconducting diode effect (SDE) in two-dimensional diffusive structures with Rashba spin-orbit coupling using the quasiclassical formalism. We consider both homogeneous superconductors and Josephson junctions. In the first case, the diode effect monotonically increases as the magnetic field is increased and the temperature is reduced, in contrast to the non-monotonic behavior found in clean structures. In Josephson junctions, SDE dramatically increases and changes its sign close to the $0-\pi$ transition of the junction, which occurs at specific junction lengths and strengths of the magnetic field. We show that the SDE is strongly suppressed in narrow junctions. Our results are relevant for understanding recent experiments that measure SDE in mesoscopic nanostructures, where significant disorder is unavoidable., Comment: 9 pages, 6 figures

A direct measurement of the ground-state-to-ground-state electron-capture decay $Q$ value of $^{95}$Tc has been performed utilizing the double Penning trap mass spectrometer JYFLTRAP. The $Q$ value was determined to be 1695.92(13) keV by taking advantage of the high resolving power of the phase-imaging ion-cyclotron-resonance technique to resolve the low-lying isomeric state of $^{95}$Tc (excitation energy of 38.910(40) keV) from the ground state. The mass excess of $^{95}$Tc was measured to be $-$86015.95(18) keV/c$^2$, exhibiting a precision of about 28 times higher and in agreement with the value from the newest Atomic Mass Evaluation (AME2020). Combined with the nuclear energy-level data for the decay-daughter $^{95}$Mo, two potential ultra-low $Q$-value transitions are identified for future long-term neutrino-mass determination experiments. The atomic self-consistent many-electron Dirac--Hartree--Fock--Slater method and the nuclear shell model have been used to predict the partial half-lives and energy-release distributions for the two transitions. The dominant correction terms related to those processes are considered, including the exchange and overlap corrections, and the shake-up and shake-off effects. The normalized distribution of the released energy in the electron-capture decay of $^{95}$Tc to excited states of $^{95}$Mo is compared to that of $^{163}$Ho currently being used for electron-neutrino-mass determination., Comment: 13 pages, 5 figures

In end-to-end multi-channel speech enhancement, the traditional approach of designating one microphone signal as the reference for processing may not always yield optimal results. The limitation is particularly in scenarios with large distributed microphone arrays with varying speaker-to-microphone distances or compact, highly directional microphone arrays where speaker or microphone positions change over time. Current mask-based methods often fix the reference channel during training, which makes it not possible to adaptively select the reference channel for optimal performance. To address this problem, we introduce an adaptive approach for selecting the optimal reference channel. Our method leverages a multi-channel masking-based scheme, where multiple masked signals are combined to generate a single-channel output signal. This enhanced signal is then used for loss calculation, while the reference clean speech is adjusted based on the highest scale-invariant signal-to-distortion ratio (SI-SDR). The experimental results on the Spear challenge simulated dataset D4 demonstrate the superiority of our proposed method over the conventional approach of using a fixed reference channel with single-channel masking., Comment: Accepted by EUSIPCO 2024

We have performed high-precision mass measurements of neutron-rich rare-earth Tb, Dy and Ho isotopes using the Phase-Imaging Ion-Cyclotron-Resonance technique at the JYFLTRAP double Penning trap. We report on the first experimentally determined mass values for $^{169}$Tb, $^{170}$Dy and $^{171}$Dy, as well as the first high-precision mass measurements of $^{169}$Dy and $^{169\text{-}171}$Ho. For $^{170}$Ho, the two long-lived ground and isomeric states were resolved and their mass measured, yielding an isomer excitation energy of $E_\text{exc}=150.8(54)$~keV. In addition, we have performed independent crosschecks of previous Penning-trap values obtained for $^{167\text{,} 168}$Tb and $^{167\text{,} 168}$Dy. We have extended the systematics of two-neutron separation energies to the neutron midshell at $N=104$ in all of the studied isotopic chains. Our updated and new mass measurements provide better mass-related constraints for the neutron-capture reaction rates relevant to the astrophysical rapid neutron capture (r) process. The r-process abundances calculated with the new mass values seem to produce a steeper minimum at A=170 and differ by around 15-30\% from the abundances computed with the Atomic Mass Evaluation 2020 values., Comment: 10 pages, 7 figures

Distance estimation from audio plays a crucial role in various applications, such as acoustic scene analysis, sound source localization, and room modeling. Most studies predominantly center on employing a classification approach, where distances are discretized into distinct categories, enabling smoother model training and achieving higher accuracy but imposing restrictions on the precision of the obtained sound source position. Towards this direction, in this paper we propose a novel approach for continuous distance estimation from audio signals using a convolutional recurrent neural network with an attention module. The attention mechanism enables the model to focus on relevant temporal and spectral features, enhancing its ability to capture fine-grained distance-related information. To evaluate the effectiveness of our proposed method, we conduct extensive experiments using audio recordings in controlled environments with three levels of realism (synthetic room impulse response, measured response with convolved speech, and real recordings) on four datasets (our synthetic dataset, QMULTIMIT, VoiceHome-2, and STARSS23). Experimental results show that the model achieves an absolute error of 0.11 meters in a noiseless synthetic scenario. Moreover, the results showed an absolute error of about 1.30 meters in the hybrid scenario. The algorithm's performance in the real scenario, where unpredictable environmental factors and noise are prevalent, yields an absolute error of approximately 0.50 meters. For reproducible research purposes we make model, code, and synthetic datasets available at https://github.com/michaelneri/audio-distance-estimation., Comment: Accepted for publication in IEEE/ACM Transactions on Audio, Speech, and Language Processing

We propose an adaptive change point detection method (A-CPD) for machine guided weak label annotation of audio recording segments. The goal is to maximize the amount of information gained about the temporal activations of the target sounds. For each unlabeled audio recording, we use a prediction model to derive a probability curve used to guide annotation. The prediction model is initially pre-trained on available annotated sound event data with classes that are disjoint from the classes in the unlabeled dataset. The prediction model then gradually adapts to the annotations provided by the annotator in an active learning loop. We derive query segments to guide the weak label annotator towards strong labels, using change point detection on these probabilities. We show that it is possible to derive strong labels of high quality with a limited annotation budget, and show favorable results for A-CPD when compared to two baseline query segment strategies., Comment: Accepted at EUSIPCO 2024 (nominated best student paper)

The masses of $^{84}$Br, $^{105}$Mo, $^{115,119,121}$Pd, $^{122}$Ag, $^{127,129}$In, $^{132}$Sb and their respective isomeric states have been measured with the JYFLTRAP Penning trap mass spectrometer using the phase-imaging ion-cyclotron-resonance technique. The excitation energies of the isomeric states in $^{132}$Sb and $^{119}$Pd were experimentally determined for the first time, while for $^{84}$Br, $^{115}$Pd and $^{127,129}$In, the precision of the mass values was substantially improved. In $^{105}$Mo and $^{121}$Pd there were no signs of a long-lived isomeric state. The ground-state measurements of $^{119}$Pd and $^{122}$Ag indicated that both are significantly more bound than the literature values. For $^{122}$Ag, there was no indication of a proposed third long-lived state. The results for the $N=49$ nucleus $^{84}$Br and isomers close to doubly magic $^{132}$Sn have been compared to the shell-model and the microscopic quasiparticle-phonon model calculations., Comment: 14 pages, 10 figures

Precision mass measurements of $^{104}$Y, $^{106}$Zr, $^{104,104m,109}$Nb, and $^{111,112}$Mo have been performed with the JYFLTRAP double Penning trap mass spectrometer at the Ion Guide Isotope Separator On-Line facility. The order of the long-lived states in $^{104}$Nb was unambiguously established. The trend in two-neutron separation energies around the $N=66$ neutron midshell appeared to be steeper with respect to the Atomic Mass Evaluation 2020 extrapolations for the $_{39}$Y and $_{40}$Zr isotopic chains and less steep for the $_{41}$Nb chain, indicating a possible gap opening around $Z=40$. The experimental results were compared to the BSkG2 model calculations performed with and without vibrational and rotational corrections. All of them predict two low-lying minima for $^{106}$Zr. While the unaltered BSkG2 model fails to predict the trend in two-neutron separation energies, selecting the more deformed minima in calculations and removing the vibrational correction, the calculations are more in line with experimental data. The same is also true for the $2^+_1$ excitation energies and differences in charge radii in the Zr isotopes. The results stress the importance of improved treatment of collective corrections in large-scale models and further development of beyond-mean-field techniques., Comment: 10 pages, 4 figures

The first direct determination of the ground-state-to-ground-state ${\beta^{-}}$-decay $Q$-value of $^{77}$As to $^{77}$Se was performed by measuring their atomic mass difference utilizing the double Penning trap mass spectrometer, JYFLTRAP. The resulting $Q$-value is 684.463(70) keV, representing a remarkable 24-fold improvement in precision compared to the value reported in the most recent Atomic Mass Evaluation (AME2020). With the significant reduction of the uncertainty of the ground-state-to-ground-state $Q$-value and knowledge of the excitation energies in $^{77}$Se from $\gamma$-ray spectroscopy, the ground-state-to-excited-state $Q$-value of the transition $^{77}$As (3/2$^{-}$, ground state) $\rightarrow$ $^{77}$Se$^{*}$ (5/2$^{+}$, 680.1035(17) keV) was refined to be 4.360(70) keV. We confirm that this potential low $Q$-value ${\beta^{-}}$-decay transition for neutrino mass determination is energetically allowed at a confidence level of about 60$\sigma$. Nuclear shell-model calculations with two well-established effective Hamiltonians were used to estimate the partial half-life for the low $Q$-value transition. The half-life was found to be of the order of 10$^{9}$ years for this first-forbidden non-unique transition, which rules out this candidate a potential source for rare-event experiments searching for the electron antineutrino mass., Comment: 8 pages, 4 figures

We report on new precision mass measurements of neutron-rich $^{137}$Sb and $^{136-142}$I isotopes from the JYFLTRAP double Penning trap mass spectrometer. We confirm the value from the previous Penning-trap measurement of $^{137}$Sb at the Canadian Penning Trap and therefore rule out the conflicting result from the Experimental Storage Ring. The ground state and isomer in $^{136}$I were resolved and measured directly for the first time. The isomer excitation energy, $E_x = 215.1(43)$ keV, agrees with the literature but is three times more precise. The measurements have improved the precision of the mass values and confirmed previous results in the majority of cases. However, for $^{138,140}$I the results differ by 17(6) keV and 23(12) keV, respectively. This could be explained by an unresolved contamination or different ratio of unresolved isomeric states in the case of $^{140}$I., Comment: 8 pages, 6 figures

High-precision mass measurements of exotic $^{95-97}$Ag isotopes close to the $N = Z$ line have been conducted with the JYFLTRAP double Penning trap mass spectrometer, with the silver ions produced using the recently commissioned inductively-heated hot cavity catcher laser ion source at the Ion Guide Isotope Separator On-Line facility. The atomic mass of $^{95}$Ag was directly determined for the first time. In addition, the atomic masses of $\beta$-decaying 2$^+$ and 8$^+$ states in $^{96}$Ag have been identified and measured for the first time, and the precision of the $^{97}$Ag mass has been improved. The newly measured masses, with a precision of $\approx$ 1 keV/c$^2$, have been used to investigate the $N =$ 50 neutron shell closure confirming it to be robust. Empirical shell-gap and pairing energies determined with the new ground-state mass data are compared with the state-of-the-art \textit{ab initio} calculations with various chiral effective field theory Hamiltonians. The precise determination of the excitation energy of the $^{96m}$Ag isomer in particular serves as a benchmark for \textit{ab initio} predictions of nuclear properties beyond the ground state, specifically for odd-odd nuclei situated in proximity to the proton dripline below $^{100}$Sn. In addition, density functional theory (DFT) calculations and configuration-interaction shell-model (CISM) calculations are compared with the experimental results. All theoretical approaches face challenges to reproduce the trend of nuclear ground-state properties in the silver isotopic chain across the $N =$50 neutron shell and toward the proton drip-line., Comment: 9 pages, 3 figures

The multinucleon transfer (MNT) reaction approach was successfully employed for the first time to measure the isomeric ratios (IRs) of $^{211}$Po (25/2$^+$) isomer and its (9/2$^+$) ground state at the IGISOL facility using a 945 MeV $^{136}$Xe beam impinged on $^{209}$Bi and $^{\rm nat}$Pb targets. The dominant production of isomers compared to the corresponding ground states was consistently revealed in the $\alpha$-decay spectra. Deduced IR of $^{211}$Po populated through the $^{136}$Xe+$^{\rm nat}$Pb reaction was found to enhance $\approx$1.8-times than observed for $^{136}$Xe+$^{209}$Bi. State-of-the-art Langevin-type model calculations have been utilized to estimate the spin distribution of an MNT residue. The computations qualitatively corroborate with the considerable increase in IRs of $^{211}$Po produced from $^{136}$Xe+$^{\rm nat}$Pb compared to $^{136}$Xe+$^{209}$Bi. Theoretical investigations indicate a weak influence of target spin on IRs. The enhancement of the $^{211}$Po isomer in the $^{136}$Xe+$^{\rm nat}$Pb over $^{136}$Xe+$^{209}$Bi can be attributed to the different proton ($p$)-transfer production routes. Estimations demonstrate an increment in the angular momentum transfer, favorable for isomer production, with increasing projectile energy. Comparative analysis indicates the two entrance channel parameters, projectile mass and $p$-transfer channels, strongly influencing the population of the high-spin isomer of $^{211}$Po (25/2$^+$). This is the first experimental and theoretical investigation on the IRs of nuclei produced via different channels of MNT reactions, with the latter quantitatively underestimating the former by a factor of two., Comment: 5 figures

Ambisonics encoding of microphone array signals can enable various spatial audio applications, such as virtual reality or telepresence, but it is typically designed for uniformly-spaced spherical microphone arrays. This paper proposes a method for Ambisonics encoding that uses a deep neural network (DNN) to estimate a signal transform from microphone inputs to Ambisonics signals. The approach uses a DNN consisting of a U-Net structure with a learnable preprocessing as well as a loss function consisting of mean average error, spatial correlation, and energy preservation components. The method is validated on two microphone arrays with regular and irregular shapes having four microphones, on simulated reverberant scenes with multiple sources. The results of the validation show that the proposed method can meet or exceed the performance of a conventional signal-independent Ambisonics encoder on a number of error metrics., Comment: Accepted for publication in Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing

Current multichannel speech enhancement algorithms typically assume a stationary sound source, a common mismatch with reality that limits their performance in real-world scenarios. This paper focuses on attention-driven spatial filtering techniques designed for dynamic settings. Specifically, we study the application of linear and nonlinear attention-based methods for estimating time-varying spatial covariance matrices used to design the filters. We also investigate the direct estimation of spatial filters by attention-based methods without explicitly estimating spatial statistics. The clean speech clips from WSJ0 are employed for simulating speech signals of moving speakers in a reverberant environment. The experimental dataset is built by mixing the simulated speech signals with multichannel real noise from CHiME-3. Evaluation results show that the attention-driven approaches are robust and consistently outperform conventional spatial filtering approaches in both static and dynamic sound environments.

Using the notion of integral distance to analytic functions, we give a characterization of Schatten class Hankel operators acting on doubling Fock spaces on the complex plane and use it to show that for $f\in L^{\infty}$, if $H_{f}$ is Hilbert-Schmidt, then so is $H_{\bar{f}}$. This property is known as the Berger-Coburn phenomenon. When $00$., Comment: To appear in Journal of Mathematical Analysis and Applications

We prove bosonization identities for the scaling limits of the critical Ising correlations in finitely-connected planar domains, expressing those in terms of correlations of the compactified Gaussian free field. This, in particular, yields explicit expressions for the Ising correlations in terms of domain's period matrix, Green's function, harmonic measures of boundary components and arcs, or alternatively, Abelian differentials on the Schottky double. Our proof is based on a limiting version of a classical identity due to D.~Hejhal and J.~Fay relating Szeg\H{o} kernels and Abelian differentials on Riemann surfaces, and a systematic use of operator product expansions both for the Ising and the bosonic correlations., Comment: 52 pages, 3 figures

Heat engines are key devices that convert thermal energy into usable energy. Strong thermoelectricity, at the basis of electrical heat engines, is present in superconducting spin tunnel barriers at cryogenic temperatures where conventional semiconducting or metallic technologies cease to work. Here we realize a superconducting spintronic heat engine consisting of a ferromagnetic insulator/superconductor/insulator/ferromagnet tunnel junction (EuS/Al/AlO$_x$/Co). The efficiency of the engine is quantified for bath temperatures ranging from 25 mK up to 800 mK, and at different load resistances. Moreover, we show that the sign of the generated thermoelectric voltage can be inverted according to the parallel or anti-parallel orientation of the two ferromagnetic layers, EuS and Co. This realizes a thermoelectric spin valve controlling the sign and strength of the Seebeck coefficient, thereby implementing a thermoelectric memory cell. We propose a theoretical model that allows describing the experimental data and predicts the engine efficiency for different device parameters., Comment: 12 pages, 7 figures

This paper proposes neural networks for compensating sensorineural hearing loss. The aim of the hearing loss compensation task is to transform a speech signal to increase speech intelligibility after further processing by a person with a hearing impairment, which is modeled by a hearing loss model. We propose an interpretable model called dynamic processing network, which has a structure similar to band-wise dynamic compressor. The network is differentiable, and therefore allows to learn its parameters to maximize speech intelligibility. More generic models based on convolutional layers were tested as well. The performance of the tested architectures was assessed using spectro-temporal objective index (STOI) with hearing-threshold noise and hearing aid speech intelligibility (HASPI) metrics. The dynamic processing network gave a significant improvement of STOI and HASPI in comparison to popular compressive gain prescription rule Camfit. A large enough convolutional network could outperform the interpretable model with the cost of larger computational load. Finally, a combination of the dynamic processing network with convolutional neural network gave the best results in terms of STOI and HASPI.

Collinear laser spectroscopy was performed on the isomer of the aluminium isotope $^{26m}$Al. The measured isotope shift to $^{27}$Al in the $3s^{2}3p\;^{2}\!P^\circ_{3/2} \rightarrow 3s^{2}4s\;^{2}\!S_{1/2}$ atomic transition enabled the first experimental determination of the nuclear charge radius of $^{26m}$Al, resulting in $R_c$=\qty{3.130\pm.015}{\femto\meter}. This differs by 4.5 standard deviations from the extrapolated value used to calculate the isospin-symmetry breaking corrections in the superallowed $\beta$ decay of $^{26m}$Al. Its corrected $\mathcal{F}t$ value, important for the estimation of $V_{ud}$ in the CKM matrix, is thus shifted by one standard deviation to \qty{3071.4\pm1.0}{\second}., Comment: 5 pages, 2 figures, submitted to Phys. Rev. Lett

We report on the first direct mass measurements of the $^{118,119}$Cd and $^{117-119}$In isotopes performed at the Ion Guide Isotope Separator On-Line facility using the JYFLTRAP double Penning trap mass spectrometer. The masses of $^{117}$In and $^{118}$Cd isotopes are in agreement with the literature, while $^{118,119}$In and $^{119}$Cd differ from literature by 49, 13 and 85 keV (6.1, 1.9 and 2.1 standard deviations), respectively. The excitation energy of the $^{118}$In first isomeric state, $E_x = 40.3(25)$ keV, was determined for the first time. The updated mass values removed the fluctuations observed in the two-neutron separation energies and lead to a smoother linear decrease of both isotopic chains. The $\log(ft)$ value for the $^{118}$Cd decay is also found to increase from 3.93(6) to 4.089(8). The reported results indicate an absence of significant structural changes around $N=70$., Comment: 8 pages, 3 figures

Privacy preservation has long been a concern in smart acoustic monitoring systems, where speech can be passively recorded along with a target signal in the system's operating environment. In this study, we propose the integration of two commonly used approaches in privacy preservation: source separation and adversarial representation learning. The proposed system learns the latent representation of audio recordings such that it prevents differentiating between speech and non-speech recordings. Initially, the source separation network filters out some of the privacy-sensitive data, and during the adversarial learning process, the system will learn privacy-preserving representation on the filtered signal. We demonstrate the effectiveness of our proposed method by comparing our method against systems without source separation, without adversarial learning, and without both. Overall, our results suggest that the proposed system can significantly improve speech privacy preservation compared to that of using source separation or adversarial learning solely while maintaining good performance in the acoustic monitoring task.