Miracle-dz/UniFAR-FTUs huggingface dataset:
The Sherrington–Kirkpatrick model near T = Tc: expanding around the replica symmetric solution

An expansion for the free energy functional of the Sherrington–Kirkpatrick (SK) model, around the replica symmetric (RS) SK solution Q(RS)ab = δab + q(1 − δab) is investigated. In particular, when the expansion is truncated to the fourth order in Qab − Q(RS)ab the full replica symmetry broken (FRSB) solution is explicitly found but it turns out to exist only in the range of temperature 0.549… ⩽ T ⩽ Tc = 1, not including T = 0. On the other hand, an expansion around the paramagnetic solution Q(PM)ab = δab, up to the fourth order, yields a FRSB solution that exists in a limited temperature range 0.915… ⩽ T ⩽ Tc = 1.
Experimental limits on the free parameters of higher-derivative gravity

Fourth-derivative gravity has two free parameters, $\alpha$ and $\beta$, which couple the curvature-squared terms $R^2$ and $R_{\mu\nu}^2$. Relativistic effects and short-range laboratory experiments can be used to provide upper limits to these constants. In this work we briefly review both types of experimental results in the context of higher-derivative gravity. The strictest limit follows from the second kind of test. Interestingly enough, the bound on $\beta$ due to semiclassical light deflection at the solar limb is only one order of magnitude larger.
Germline RUNX1 variants in paediatric patients in a French specialised centre

Familial platelet disorder with associated myeloid malignancy (FPD‐MM; OMIM 601399) is related to germline RUNX1 mutation. The pathogenicity of RUNX1 variants was initially linked to FPD‐MM phenotype, but the discovery of new variants through the expansion of genetic explorations in leukaemia is questioning this assertion. In this study, we add 10 families with germline RUNX1 variant explored at Armand Trousseau Hospital for leukaemia diagnosis or thrombocytopenia, to the 259 described so far. Detailed description of their personal and family history of haematological pathologies allows identifying three phenotypes related to germline RUNX1 variants: thrombocytopenia and/or malignant haematological disease with family history of haematological diseases, thrombocytopenia with no family history of haematological diseases and acute lymphoblastic leukaemia (ALL) with no family history of haematological diseases. In the latter phenotype, ALL characteristics involving RUNX1 suggest the implication of germline variants in the onset of the malignancy.
Analysis and Qualitative Observability of Two Vapor Compression Cycle Models

In this paper, a physically-oriented vapor compression cycle model is analyzed regarding different measures of the degree of observability. The high-dimensional nonlinear model employs pressures and enthalpies as state variables and involves two control inputs. A set of equilibrium points is determined over a grid of both input variables, and corresponding Taylor linearizations are performed. After an analysis of the eigenvalue locations, the observability properties are investigated using two alternative approaches: the first is based on the observability Gramians, the second on a stationary Kalman Filter. The analysis of the Gramians provides a deeper insight into the interconnections of states and individual measured outputs, whereas the Kalman Filter indicates the achievable estimation quality which is related to the variances. Moreover, a direct way to include equality constraints related to the overall mass conservation and its impact on the observability is discussed in detail.
Interaction quantum quenches in the one-dimensional Fermi-Hubbard model with spin imbalance

Using the time-dependent density matrix renormalization group method and exact diagonalization, we study the non-equilibrium dynamics of the one-dimensional Fermi-Hubbard model following a quantum quench or a ramp of the onsite interaction strength. For quenches from the non-interacting to the attractive regime, we investigate the dynamical emergence of Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) correlations, which at finite spin polarizations are the dominant two-body correlations in the ground state, and their signatures in the pair quasi-momentum distribution function. We observe that the post-quench double occupancy exhibits a maximum as the interaction strength becomes of the order of the bandwidth. Finally, we study quenches and ramps from attractive to repulsive interactions, which imprint FFLO correlations onto repulsively bound pairs. We show that a quite short ramp time is sufficient to wipe out the characteristic FFLO features in the post-quench pair momentum distribution functions.
Discovery and progenitor constraints on the Type Ia supernova 2013gy

We present an early-phase g-band light curve and visual-wavelength spectra of the normal Type Ia supernova (SN) 2013gy. The light curve is constructed by determining the appropriate S-corrections to transform KAIT natural-system B- and V-band photometry and Carnegie Supernova Project natural-system g-band photometry to the Pan-STARRS1 g-band natural photometric system. A Markov chain Monte Carlo calculation provides a best-fit single power-law function to the first ten epochs of photometry described by an exponent of 2.16+0.06−0.06 and a time of first light of MJD 56629.4+0.1−0.1, which is 1.93+0.12−0.13 days (i.e., < 48 h) before the discovery date (2013 December 4.84 UT) and −19.10+0.12−0.13 days before the time of B-band maximum (MJD 56648.5 ± 0.1). The estimate of the time of first light is consistent with the explosion time inferred from the evolution of the Si IIλ6355 Doppler velocity. Furthermore, discovery photometry and previous nondetection limits enable us to constrain the companion radius down to Rc ≤ 4 R⊙. In addition to our early-time constraints, we used a deep +235 day nebular-phase spectrum from Magellan/IMACS to place a stripped H-mass limit of < 0.018 M⊙. Combined, these limits effectively rule out H-rich nondegenerate companions.
Low mass WIMP search with EDELWEISS-III: First reults

We present the first search for low mass WIMPs using the Germanium bolometers of the EDELWEISS-III experiment. Upgrades to the detectors and the electronics enhance the background discrimination and the low energy sensitivity with respect to EDELWEISS-II. A multivariate analysis is implemented to fully exploit the detector's potential, reaching a sensitivity of 1.6 $\times 10^{-5}$ pb for a WIMP mass of 7 GeV/c$^2$ with a fraction of the data set, unblinded for background modeling and analysis tuning.
State-of-Health Prediction Using Transfer Learning and a Multi-Feature Fusion Model

Existing data-driven technology for prediction of state of health (SOH) has insufficient feature extraction capability and limited application scope. To deal with this challenge, this paper proposes a battery SOH prediction model based on multi-feature fusion. The model is based on a convolutional neural network (CNN) and a long short-term memory network (LSTM). The CNN can learn the cycle features in the battery data, the LSTM can learn the aging features of the battery over time, and regression prediction can be made through the full-connection layer (FC). In addition, for the aging differences caused by different battery operating conditions, this paper introduces transfer learning (TL) to improve the prediction effect. Across cycle data of the same battery under 12 different charging conditions, the fusion model in this paper shows higher prediction accuracy than with either LSTM and CNN in isolation, reducing RMSPE by 0.21% and 0.19%, respectively.
Supernova Driving. IV. The Star-formation Rate of Molecular Clouds

We compute the star-formation rate (SFR) in molecular clouds (MCs) that originate ab initio in a new, higher-resolution simulation of supernova-driven turbulence. Because of the large number of well-resolved clouds with self-consistent boundary and initial conditions, we obtain a large range of cloud physical parameters with realistic statistical distributions, which is an unprecedented sample of star-forming regions to test SFR models and to interpret observational surveys. We confirm the dependence of the SFR per free-fall time, SFRff, on the virial parameter, αvir, found in previous simulations, and compare a revised version of our turbulent fragmentation model with the numerical results. The dependences on Mach number, , gas to magnetic pressure ratio, β, and compressive to solenoidal power ratio, χ at fixed αvir are not well constrained, because of random scatter due to time and cloud-to-cloud variations in SFRff. We find that SFRff in MCs can take any value in the range of 0 ≤ SFRff ≲ 0.2, and its probability distribution peaks at a value of SFRff ≈ 0.025, consistent with observations. The values of SFRff and the scatter in the SFRff–αvir relation are consistent with recent measurements in nearby MCs and in clouds near the Galactic center. Although not explicitly modeled by the theory, the scatter is consistent with the physical assumptions of our revised model and may also result in part from a lack of statistical equilibrium of the turbulence, due to the transient nature of MCs.
Comparative evaluation of the bonding of glass-ionomer cement modification to dental composite established by dental adhesives.

Objective: To evaluate the influence of the application of various adhesives on the strength of the bonding established amongst resin-modified glass-ionomer cement (RMGIC) and resin composite restoration (RBC). Materials and method: Twenty discs were made-up with (RMGIC) and divided into four groups (n = 5) based on the adhesive resin system applied. Cylinders of resin composite were bonded to the RMGI discs utilizing different adhesive resin systems in the first three groups. While the fourth group was used as a control receiving no adhesive resin treatment. Microshear bond strength was measured and the data was registered with computer software in MPa. Results: The results revealed that applying different adhesive resin systems statistically significantly increased the bond strength between the tested materials. Conclusion: Microshear bond strength of (RMGIC) to resin composite improved considerably using different adhesive resin systems. The outcomes vary depending upon the type of adhesive resin system utilized.
Improving financial literacy of village community by using a saving program: A social enterprise strategy

A social enterprise is an organization that has a social mission and uses innovative revenue-generating techniques to fulfill their mission. Social mission in social enterprises is to improve the well-being of the community through good business practices. Nagari's Owned Enterprise (BUMNag) is an organization run with a social enterprise business model. Therefore, the establishment of BUMNag aims to gain profits through empowerment to the community. The purpose of this study is to explore how BUMNag role in improving financial literacy of village community. This research uses a qualitative approach. Data collected through observation, interviews, documentation, then analyzed data is using a modified Theory of Planned Behavior (TPB) to investigate BUMNag innovative idea of a "bajapuik saving system" in improving financial literacy. Informants numbered 10 people, 5 BUMNag managers and 5 people who opened bajapuik deposit contracts. The results of this study show that the strategy with the bajapuik deposit program implemented by BUMNag Pakandangan Emas can provide people with an understanding of the urgency of making deposits from now on to anticipate risks that will occur in the future.
THERMAL PROPERTIES OF THE MIDDLE-AGED PULSAR J1741−2054

We present results of the spectral analysis of the X-ray emission from the middle-aged Fermi pulsar J1741−2054 using all Chandra archival data collected in 2010 and 2013. We confirm early findings by Romani et al. in 2010 that the pulsar spectrum contains a thermal emission component. The component is best described by the blackbody model with temperature ≈60 eV and emitting area radius ≈17 Dkpc km. The thermal emission likely originates from the entire surface of the cooling neutron star if the distance to the pulsar is ≈0.8 kpc. The latter is supported by a large absorbing column density inferred from the X-ray fit and empirical optical extinction–distance relations along the pulsar line of sight. The neutron star surface temperature and characteristic age make it similar to the well studied middle-aged pulsar B1055−52. Like this pulsar, PSR J1741−2054 is hotter than predicted by the standard cooling scenario.
Evaluation of Machine Learning Algorithms for Emotions Recognition using Electrocardiogram

In recent studies, researchers have focused on using various modalities to recognize emotions for different applications. A major challenge is identifying emotions correctly with only electrocardiograms (ECG) as the modality. The main objective is to reduce costs by using single-modality ECG signals to predict human emotional states. This paper presents an emotion recognition approach utilizing the heart rate variability features obtained from ECG with feature selection techniques (exhaustive feature selection (EFS) and Pearson’s correlation) to train the classification models. Seven machine learning (ML) models: multi-layer perceptrons (MLP), Support Vector Machine (SVM), Decision Tree (DT), Gradient Boosting Decision Tree (GBDT), Logistic Regression, Adaboost and Extra Tree classifier are used to classify emotional state. Two public datasets, DREAMER and SWELL are used for evaluation. The results show that no particular ML works best for all data. For DREAMER with EFS, the best models to predict valence, arousal, and dominance are Extra Tree (74.6%), MLP and DT (74.6%), and GBDT and DT (69.8%), respectively. Extra tree with Pearson’s correlation are the best method for the ECG SWELL dataset and provide 100% accuracy. The usage of Extra tree classifier and feature selection technique contributes to the improvement of the model accuracy. Moreover, the Friedman test proved that ET is as good as other classification models for predicting human emotional state and ranks highest. Doi: 10.28991/ESJ-2023-07-01-011 Full Text: PDF
Cosmological Collider Physics

We study the imprint of new particles on the primordial cosmological fluctuations. New particles with masses comparable to the Hubble scale produce a distinctive signature on the non-gaussianities. This feature arises in the squeezed limit of the correlation functions of primordial fluctuations. It consists of particular power law, or oscillatory, behavior that contains information about the masses of new particles. There is an angular dependence that gives information about the spin. We also have a relative phase that crucially depends on the quantum mechanical nature of the fluctuations and can be viewed as arising from the interference between two processes. While some of these features were noted before in the context of specific inflationary scenarios, here we give a general description emphasizing the role of symmetries in determining the final result.
Phase separation and critical percolation in bidimensional spin-exchange models

Binary mixtures prepared in a homogeneous phase and quenched into a two-phase region phase-separate via a coarsening process whereby domains of the two phases grow in time. With a numerical study of a spin-exchange model we show that this dynamics first take a system with equal density of the two species to a critical percolation state. We prove this claim and we determine the time dependence of the growing length associated to this process with the scaling analysis of the statistical and morphological properties of the clusters of the two phases.
Magnetic fluctuations and spin freezing in nonsuperconducting LiFeAs derivatives.

We present detailed magnetometry and muon-spin rotation data on polycrystalline samples of overdoped, nonsuperconducting LiFe1−xNixAs (x = 0.1,0.2) and Li1−yFe1+yAs (0 y 0.04) as well as superconducting LiFeAs.While LiFe1−xNixAs exhibits weak antiferromagnetic fluctuations down to 1.5 K,Li1−yFe1+yAs samples, which have a much smaller deviation from the 1 : 1 : 1 stoichiometry, show a crossover from ferromagnetic to antiferromagnetic fluctuations on cooling and a freezing of dynamically fluctuating moments at low temperatures. We do not find any signatures of time-reversal symmetry breaking in stoichiometric LiFeAs that would support recent predictions of triplet pairing.
Hamiltonian Simulation by Uniform Spectral Amplification

The exponential speedups promised by Hamiltonian simulation on a quantum computer depends crucially on structure in both the Hamiltonian $\hat{H}$, and the quantum circuit $\hat{U}$ that encodes its description. In the quest to better approximate time-evolution $e^{-i\hat{H}t}$ with error $\epsilon$, we motivate a systematic approach to understanding and exploiting structure, in a setting where Hamiltonians are encoded as measurement operators of unitary circuits $\hat{U}$ for generalized measurement. This allows us to define a \emph{uniform spectral amplification} problem on this framework for expanding the spectrum of encoded Hamiltonian with exponentially small distortion. We present general solutions to uniform spectral amplification in a hierarchy where factoring $\hat{U}$ into $n=1,2,3$ unitary oracles represents increasing structural knowledge of the encoding. Combined with structural knowledge of the Hamiltonian, specializing these results allow us simulate time-evolution by $d$-sparse Hamiltonians using $\mathcal{O}\left(t(d \|\hat H\|_{\text{max}}\|\hat H\|_{1})^{1/2}\log{(t\|\hat{H}\|/\epsilon)}\right)$ queries, where $\|\hat H\|\le \|\hat H\|_1\le d\|\hat H\|_{\text{max}}$. Up to logarithmic factors, this is a polynomial improvement upon prior art using $\mathcal{O}\left(td\|\hat H\|_{\text{max}}+\frac{\log{(1/\epsilon)}}{\log\log{(1/\epsilon)}}\right)$ or $\mathcal{O}(t^{3/2}(d \|\hat H\|_{\text{max}}\|\hat H\|_{1}\|\hat H\|/\epsilon)^{1/2})$ queries. In the process, we also prove a matching lower bound of $\Omega(t(d\|\hat H\|_{\text{max}}\|\hat H\|_{1})^{1/2})$ queries, present a distortion-free generalization of spectral gap amplification, and an amplitude amplification algorithm that performs multiplication on unknown state amplitudes.
A Waitlist Randomized Implementation Trial of Classroom Pivotal Response Teaching for Students With Autism

Classroom Pivotal Response Teaching (CPRT) is a community-partnered adaptation of a naturalistic developmental behavioral intervention identified as an evidence-based practice for autistic children. The current study evaluated student outcomes in a randomized, wait-list controlled implementation trial across classrooms. Participants included teachers (n = 126) and students with autism (n = 308). Teachers participated in 12 hours of didactic, interactive training and additional in-classroom coaching. Generalized Estimating Equations accounted for clustering. Adjusted models evaluated the relative effects of training group, CPRT fidelity, and classroom quality on student outcomes. Results indicate higher CPRT fidelity was associated with greater increases in student learning. Having received CPRT training predicted increased student engagement and greater decreases in reported approach/withdrawal problems. These differences may be linked to the theoretical foundations of CPRT of increasing student motivation and engagement and collaborative adaptation to increase feasibility in schools. Overall, results suggest CPRT may be a beneficial approach for supporting autistic students.
Sampled-Data Model-Free Adaptive Control of Piezoelectric Actuators with Input Rate Constraint Using Extended State Observer

This paper investigates the motion tracking problem for piezoelectric actuators (PEAs) using a sampled-data control method known as sampled-data model-free adaptive control (SMFAC). The fundamental architecture of the proposed scheme is based on input-output data, and the sampling period is an integral part of the design. PEA with the Bouc-Wen hysteresis model is first considered to obtain a sampled-data nonlinear model using the integral mean value theorem and the discrete-time Euler approximation. Then, a sampled-data control rule subject to input rate constraint is constructed by applying a sampled-data extended state observer (SESO) and a sampled-data parameter estimation technique. The SESO is used to estimate the unknown residual nonlinearity and external disturbances. The convergence of the tracking error is proven through theoretical analysis. Experimental results confirm the adequate performance of the proposed scheme.
Light-Sound Interaction in Nanoscale Silicon Waveguides

This thesis studies the interaction between near-infrared light and gigahertz sound in nanoscale silicon waveguides. Chapter 2 introduces photon-phonon coupling and its theoretical description, describing basic mechanisms and developing a quantum field theory of the process. Chapter 3 explores the dynamical effects in both waveguides and cavities. It also proves a connection between the Brillouin gain coefficient and the vacuum coupling rate. Chapter 4 deals with the observation of Brillouin scattering in nanoscale silicon waveguides. The waveguides tightly confine $193 \, \text{THz}$ light and $10 \, \text{GHz}$ acoustic vibrations. The acoustic quality factor remains limited to about $300$ because of leakage into silica substrate. These waveguides are optically transparent in a narrow band of frequencies at a pump power of $25 \, \text{mW}$. Besides this amplification, we translate a $10 \, \text{GHz}$ microwave signal across $1 \, \text{THz}$. Chapter 5 extends the experimental work of chapter 4 by fabricating a cascade of fully suspended nanowires held by silica anchors. This enhances the mechanical quality factor from $300$ to $1000$, enabling the observation of Brillouin amplification exceeding the propagation losses in silicon. The amount of amplification is mostly limited by a rapid drop in acoustic quality as the number of suspensions increases. We propose a mechanism to cancel this inhomogeneous broadening. Chapter 6 looks at the potential of narrow silicon slot waveguides to enhance the optomechanical coupling. For certain dimensions, these waveguides support opto-acoustic modes with an interaction efficiency simulated an order of magnitude above those of single-nanobeam systems.
Magnetic Influences on the Solar Wind (Ph.D. Dissertation)

The steady, supersonic outflow from the Sun we call the solar wind was first posited in the 1950s and initial theories rightly linked the acceleration of the wind to the existence of the million-degree solar corona. Still today, the wind acceleration mechanisms and the coronal heating processes remain unsolved challenges in solar physics. In this work, I seek to answer a portion of the mystery by focusing on a particular acceleration process: Alfven waves launched by the motion of magnetic field footpoints in the photosphere. The entire corona is threaded with magnetic loops and flux tubes that open up into the heliosphere. I have sought a better understanding of the role these magnetic fields play in determining solar wind properties in open flux tubes. After an introduction of relevant material, I discuss my parameter study of magnetic field profiles and the statistical understanding we can draw from the resulting steady-state wind. In the chapter following, I describe how I extended this work to consider time dependence in the turbulent heating by Alfven waves in three dimensional simulations. The bursty nature of this heating led to a natural next step that expands my work to include not only the theoretical, but also a project to analyze observations of small network jets in the chromosphere and transition region, and the underlying photospheric magnetic field that forms thresholds in jet production. In summary, this work takes a broad look at the extent to which Alfven-wave-driven turbulent heating can explain measured solar wind properties and other observed phenomena.