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This study investigates the potential of using smartwatches with built-in microphone sensors for monitoring coughs and detecting various cough types. We conducted a study involving 32 participants and collected 9 hours of audio data in a controlled manner. Afterward, we processed this data using a structured approach, resulting in 223 positive cough samples. We further improved the dataset through augmentation techniques and employed a specialized 1D CNN model. This model achieved an impressive accuracy rate of 98.49% while non-walking and 98.2% while walking, showing smartwatches can detect cough. Moreover, our research successfully identified four distinct types of coughs using clustering techniques., Comment: 7 pages

In this work, we present a novel framework of relativistic non-resistive dissipative magnetohydrodynamics for spin-polarized particles. Utilizing a classical relativistic kinetic equation for the distribution function in an extended phase-space of position, momentum, and spin, we derive equations of motion for dissipative currents at first-order in spacetime gradients. Our findings reveal a coupling between fluid vorticity and magnetization via an electromagnetic field, leading to relativistic analogs of the Einstein-de Haas and Barnett effects. Our study provides a tool for a better understanding of the polarization phenomena observed in relativistic heavy-ion collisions., Comment: 10 pages, Proceedings of 25th International Spin Symposium (SPIN2023) [C23-09-24]

We contribute the first publicly available dataset of factual claims from different platforms and fake YouTube videos on the 2023 Israel-Hamas war for automatic fake YouTube video classification. The FakeClaim data is collected from 60 fact-checking organizations in 30 languages and enriched with metadata from the fact-checking organizations curated by trained journalists specialized in fact-checking. Further, we classify fake videos within the subset of YouTube videos using textual information and user comments. We used a pre-trained model to classify each video with different feature combinations. Our best-performing fine-tuned language model, Universal Sentence Encoder (USE), achieves a Macro F1 of 87\%, which shows that the trained model can be helpful for debunking fake videos using the comments from the user discussion. The dataset is available on Github\footnote{https://github.com/Gautamshahi/FakeClaim}, Comment: Accepted in the IR4Good Track at the 46th European Conference on Information Retrieval (ECIR) 2024

The present study is first to provide experimental evidence of tonal noise and acoustic feedback by a stationary airfoil with a tip-gap placed between two side plates. Tones are linked to an aero-acoustic coupling using synchronized measurements between Particle Image Velocimetry and far-field microphone probes. To aid in the correlation analysis, the wall boundary condition on the pressure side of the airfoil was modified by introducing surface roughness. For tip leakage flows without roughness elements, the far-field acoustic spectra show peaks in the acoustic autospectra. These peaks are present regardless of the flow speed studied. The findings reveal that tones associated with tip-gap extend till 16.5 kHz in a low-noise facility. Roughness alters cross-flow velocity along the airfoil chord, influencing acoustics at matched Reynolds and Mach numbers. Roughness induces cancellation of spectral peaks and changes in the velocity and acoustic pressure correlation pattern between airfoil pressure and suction side. Modal shapes confirm the presence of coherent structures in the tip-gap region, with smooth surfaces exhibiting confined flow instabilities and non-dipolar noise sources around and beyond 10 kHz. At these high frequencies, the sound radiation mechanism can be uniquely attributed to neither a jet-like noise source nor these acoustic peaks can be uniquely attributed to coherent structures in the tip-gap region. On the contrary, coherence between airfoil sides is required for noise peaks, which stresses the importance of diffraction on the airfoil pressure side and acoustic feedback., Comment: 21 pages, 10 figures

The intricate role of shear viscosity and ion-pair relaxations on ionic conductivity mechanisms and the underlying changes induced by salt concentration ($c$) in organic liquid electrolytes remain poorly understood despite their widespread technological importance. Using molecular dynamics simulations employing nonpolarizable force fields for $c$ ranging between 10$^{-3}$ to 10$^1$ M, we show that the low and high $c$ regimes of the EC-LiTFSI electrolytes are distinctly characterized by $\eta\sim\tau_c^{1/2}$ and $\eta\sim\tau_c^{1}$, where $\eta$ and $\tau_c$ are shear viscosity and cation-anion relaxation timescales, respectively. Our extensive simulations and analyses suggest a universal relationship between the ionic conductivity and $c$ as $\sigma(c)\sim c^{\alpha}e^{-c/c_{0}} (\alpha>0)$. The proposed relationship convincingly explains the ionic conductivity over a wide range of $c$, where the term $c^\alpha$ accounts for the uncorrelated motion of ions and $e^{-c/c_0}$ captures the salt-induced changes in shear viscosity. Our simulations suggest vehicular mechanism to be dominant at low $c$ regime which transitions into a structural diffusion mechanism at high $c$ regime, where structural relaxation is the dominant form of ion transport mechanism. Our findings shed light on some of the fundamental aspects of the ion conductivity mechanisms in liquid electrolytes, offering insights into optimizing the ion transport in EC-LiTFSI electrolytes., Comment: 6 pages, 5 figures

Existence, non-existence, and uniqueness of mass-conserving weak solutions to the continuous collision-induced nonlinear fragmentation equations are established for the collision kernels $\Phi$ satisfying $\Phi(x_1,x_2)={x_1}^{\lambda_1} {x_2}^{\lambda_2}+{x_2}^{\lambda_1} {x_1}^{\lambda_2}$, $(x_1,x_2)\in(0,\infty)^2$, with ${\lambda_1} \leq {\lambda_2}\leq 1$, and non-integrable fragment daughter distributions. In particular, global existence of mass-conserving weak solutions is shown when $1\le\lambda:={\lambda_1}+{\lambda_2}\le2$ with $\lambda_1\ge k_0$, the parameter $k_0\in(0,1)$ being related to the non-integrability of the fragment daughter distribution. The existence of at least one mass-conserving weak solution is also demonstrated when $2k_0 \le \lambda < 1$ with $\lambda_1\ge k_0$ but its maximal existence time is shown to be finite. Uniqueness is also established in both cases. The last result deals with the non-existence of mass-conserving weak solutions, even on a small time interval, for power law fragment daughter distribution when $\lambda_1

The recent advances in Deep Neural Networks (DNNs) stem from their exceptional performance across various domains. However, their inherent large size hinders deploying these networks on resource-constrained devices like edge, mobile, and IoT platforms. Strategies have emerged, from partial cloud computation offloading (split computing) to integrating early exits within DNN layers. Our work presents an innovative unified approach merging early exits and split computing. We determine the 'splitting layer', the optimal depth in the DNN for edge device computations, and whether to infer on edge device or be offloaded to the cloud for inference considering accuracy, computational efficiency, and communication costs. Also, Image classification faces diverse environmental distortions, influenced by factors like time of day, lighting, and weather. To adapt to these distortions, we introduce I-SplitEE, an online unsupervised algorithm ideal for scenarios lacking ground truths and with sequential data. Experimental validation using Caltech-256 and Cifar-10 datasets subjected to varied distortions showcases I-SplitEE's ability to reduce costs by a minimum of 55% with marginal performance degradation of at most 5%., Comment: To appear in proceedings of IEEE International Conference on Communications 2024

In this study, we analyze the transport properties of the Quark-Gluon Plasma, focusing on bulk ($\zeta$) and shear ($\eta$) viscosities at vanishing chemical potential. To describe the QGP, we employ a quasiparticle model for quarks along with Gribov's prescription for gluons, which effectively captures non-perturbative dynamics. The Gribov parameter $\gamma_G$ and the dynamical mass $m_g$ are obtained by solving the one-loop gap equation in the $\overline{\text{MS}}$ renormalization scheme and further using lattice QCD data for the equation of state (EoS) of pure gluonic matter. The interaction between quarks and gluons is reflected in the quark quasi-mass $m_q$, again obtained using lattice EoS data for (2+1)-flavor QCD. Our primary goal is to invertigate the influence of quasi-quarks on the transport coefficients of QGP. Interestingly, we find a substantial decrease in the scaled transport coefficients with rising temperatures within the range ($1 \le T/T_c \le 3.5$)., Comment: 16 pages; version 2, accepted for publication in PRD