Miracle-dz/UniFAR-FTUs huggingface dataset:
Older Physical Education Teachers’ Wellbeing at Work and Its Challenges

This article examines older physical education (PE) teachers’ wellbeing over the course of their career in Finland. The study highlights challenges to physical and mental functioning as well as how teachers respond to these challenges. The six interviewees were over 55-year-old PE teachers, whose career had lasted for more than 30 years. Qualitative methods were used in the collection, transcription and analysis of the research data. The qualitative analysis consisted of a series of interpretations that visualised the world described by the interviewees. All the research participants had physical problems that affected their teaching and make teachers consider a potential career change. To be able to teach, teachers adapted their ways of working according to the challenges brought by age and injuries. The research participants found that the challenges caused by musculoskeletal problems and ageing were an inevitable part of the profession. They emphasised the positive sides of the work: the profession permits varied workdays. In addition, the teachers noted that their work provides them with opportunities to remain physically fit. Teaching health education is a means to lighten the workload of older teachers. PE teachers enjoy their profession and are dedicated to it, despite all the challenges. The interviewed participants clearly experienced work engagement. Our development proposal for teacher education is that future PE teachers be informed about the risks involved in the profession. Such activity helps young teachers reflect proactively on the measures taken to maintain their functioning during their career and on perspectives related to the ways of working.
Currents in a many-particle parabolic quantum dot under a strong magnetic field

Currents in a few-electron parabolic quantum dot placed into a perpendicular magnetic field are considered. We show that traditional ways of investigating the Wigner crystallization by studying the charge density correlation function can be supplemented by the examination of the densitycurrent correlator. However, care must be exercised when constructing the correct projection of the multi-dimensional wave function space. The interplay between the magnetic field and Euler-liquidlike behavior of the electron liquid gives rise to persistent and local currents in quantum dots. We demonstrate these phenomena by collating a quasi-classical theory valid in high magnetic fields and an exact numerical solution of the many-body problem.
Gilbert damping in magnetic multilayers

We study the enhancement of the ferromagnetic relaxation rate in thin films due to the adjacent normal-metal layers. Using linear-response theory, we derive the dissipative torque produced by the $s\ensuremath{-}d$ exchange interaction at the ferromagnet--normal-metal interface. For a slow precession, the enhancement of the Gilbert damping constant is proportional to the square of the $s\ensuremath{-}d$ exchange constant times the zero-frequency limit of the frequency derivative of the local dynamic spin susceptibility of the normal metal at the interface. Electron-electron interactions increase the relaxation rate by the Stoner factor squared. We attribute the large anisotropic enhancements of the relaxation rate observed recently in multilayers containing palladium to this mechanism. For free electrons, the present theory compares favorably with recent spin-pumping results of Tserkovnyak et al. [Phys. Rev. Lett. $88,$ 117601 (2002)].
Constraints on Nonlinear Tides due to p–g Mode Coupling from the Neutron Star Merger GW170817

It has been suggested by Weinberg et al. that an instability due to the nonlinear coupling of a neutron star’s tide to its p- and g-modes could affect the gravitational-wave phase evolution of a neutron star binary. Weinberg suggests that this instability can turn on as the gravitational waves pass through the sensitive band of ground-based detectors, although the size of the effect is not known. The discovery of the binary neutron star merger GW170817 provides an opportunity to look for evidence of nonlinear tides from p–g mode coupling. We compute Bayesian evidences that compare waveform models that include the p–g mode coupling with models that do not. We find that the consistency between GW170817 signal and the p–g mode model reported by Abbott et al. is due to a degeneracy between the phenomenological waveform used to model the effect of nonlinear tides and the standard post-Newtonian waveform. We investigate the consistency of the GW170817 signal with regions of the parameter space where the effect of nonlinear tides is not degenerate with the standard model. Regions of the nonlinear tide parameter space that have a fitting factor of less than 99% (98.5%) are disfavored by a Bayes factor of 15 (25). We conclude that regions of the parameter space where nonlinear tides produce a measurable effect are strongly disfavored and improved theoretical modeling will be needed if future observations are to constrain nonlinear tides from p–g mode coupling in neutron stars.
Superdirectional beam of surface spin wave

The visualized diffraction patterns of a surface spin wave excited by an arbitrarily oriented linear transducer are investigated experimentally in the plane of a tangentially magnetized ferrite film for the case in which the transducer length D is much larger than the wavelength . It is shown experimentally and theoretically that the angular width of a diffracted surface spin wave beam in an anisotropic ferrite film can take values greater or less than and can also be zero. For the last case a superdirectional (non-expanding) beam of the surface spin wave is observed experimentally: the smearing of the beam energy along the film plane is absent and the length of the beam trajectory is maximal . It is found that the well-known Rayleigh criterion used in isotropic media cannot be used to estimate the angular width of spin wave beams. The experimental results are in good agreement with theoretical investigations, predictions, calculations and formulas obtained recently.
Introduction to Feynman Integrals

In these lectures I will give an introduction to Feynman integrals. In the first part of the course I review the basics of the perturbative expansion in quantum field theories. In the second part of the course I will discuss more advanced topics: Mathematical aspects of loop integrals related to periods, shuffle algebras and multiple polylogarithms are covered as well as practical algorithms for evaluating Feynman integrals.
Regulation of Cyclooxygenase-2 Expression in Human T Cells by Glucocorticoid Receptor-Mediated Transrepression of Nuclear Factor of Activated T Cells

Cyclooxygenase (COX) is the key enzyme in prostanoid synthesis from arachidonic acid (AA). Two isoforms, named COX-1 and COX-2, are expressed in mammalian tissues. The expression of COX-2 isoform is induced by several stimuli including cytokines and mitogens, and this induction is inhibited by glucocorticoids (GCs). We have previously shown that the transcriptional induction of COX-2 occurs early after T cell receptor (TCR) triggering, suggesting functional implications of this enzyme in T cell activation. Here, we show that dexamethasone (Dex) inhibits nuclear factor of activated T cells (NFAT)-mediated COX-2 transcriptional induction upon T cell activation. This effect is dependent on the presence of the GC receptor (GR), but independent of a functional DNA binding domain, as the activation-deficient GRLS7 mutant was as effective as the wild-type GR in the repression of NFAT-dependent transcription. Dex treatment did not disturb NFAT dephosphorylation, but interfered with activation mediated by the N-terminal transactivation domain (TAD) of NFAT, thus pointing to a negative cross-talk between GR and NFAT at the nuclear level. These results unveil the ability of GCs to interfere with NFAT activation and the induction of pro-inflammatory genes such as COX-2, and explain some of their immunomodulatory properties in activated human T cells.
Highly localized Brillouin scattering response in a photonic integrated circuit

The interaction of optical and acoustic waves via stimulated Brillouin scattering (SBS) has recently reached on-chip platforms, which has opened new fields of applications ranging from integrated microwave photonics and on-chip narrow-linewidth lasers, to phonon-based optical delay and signal processing schemes. Since SBS is an effect that scales exponentially with interaction length, on-chip implementation on a short length scale is challenging, requiring carefully designed waveguides with optimized opto-acoustic overlap. In this work, we use the principle of Brillouin optical correlation domain analysis (BOCDA) to locally measure the SBS spectrum with high spatial resolution of 800 {\mu}m and perform a distributed measurement of the Brillouin spectrum along a spiral waveguide in a photonic integrated circuit (PIC). This approach gives access to local opto-acoustic properties of the waveguides, including the Brillouin frequency shift (BFS) and linewidth, essential information for the further development of high quality photonic-phononic waveguides for SBS applications.
Generalization bounds for the regression of real-valued functions

The paper suggests a new bound of estimating the confidence interval defined by the absolute value of difference between the true (or general) and empirical risks for the regression of real-valued functions. The theoretical bounds of confidence intervals can be derived in the sense of probably approximately correct (PAC) learning. However, these theoretical bounds are too overestimated and not well fitted to the empirical data. In this sense, a new bound of the confidence interval which can explain the behavior of learning machines more faithfully to the given samples, is suggested.
A machine learning approach to statistical shape models with applications to medical image analysis

Statistical shape models have become an indispensable tool for image analysis. The use of shape models is especially popular in computer vision and medical image analysis, where they were incorporated as a prior into a wide range of different algorithms. In spite of their big success, the study of statistical shape models has not received much attention in recent years. Shape models are often seen as an isolated technique, which merely consists of applying Principal Component Analysis to a set of example data sets. In this thesis we revisit statistical shape models and discuss their construction and applications from the perspective of machine learning and kernel methods. The shapes that belong to an object class are modeled as a Gaussian Process whose parameters are estimated from example data. This formulation puts statistical shape models in a much wider context and makes the powerful inference tools from learning theory applicable to shape modeling. Furthermore, the formulation is continuous and thus helps to avoid discretization issues, which often arise with discrete models. An important step in building statistical shape models is to establish surface correspondence. We discuss an approach which is based on kernel methods. This formulation allows us to integrate the statistical shape model as an additional prior. It thus unifies the methods of registration and shape model fitting. Using Gaussian Process regression we can integrate shape constraints in our model. These constraints can be used to enforce landmark matching in the fitting or correspondence problem. The same technique also leads directly to a new solution for shape reconstruction from partial data. In addition to experiments on synthetic 2D data sets, we show the applicability of our methods on real 3D medical data of the human head. In particular, we build a 3D model of the human skull, and present its applications for the planning of cranio-facial surgeries.
A Phenomenological Model for the Light Curve of Three Quiescent Low-inclination Dwarf Novae and One Pre-cataclysmic Variable

We used the light curve code XRBinary to model the quiescent K2 light curves of three low-inclination cataclysmic variables (CVs): 1RXS J0632+2536 (J0632+2536), RZ Leo, TW Vir and the pre-CV WD 1144+011. Optimized light curve models were obtained using a nonlinear fitting code NMfit and visualized by Phoebe 2.0. The disk model of J0632+2536 shows that one hotspot at the edge of the disk is enough to describe its light curve, while the other two dwarf nova (DN): RZ Leo and TW Vir require two hotspots. A typical pre-CV model with a weak irradiation effect for WD 1144+011 can explain its single-hump modulation and the newly observed spectrum confirms its previous classification. The synthetic analyses for the DN clearly indicate that phase zero of the double-hump modulations occurs around the secondary minimum and the primary hump is mainly caused by the hotspot at the edge of the disk. The quiescent disk has a flat temperature distribution with a power index of ∼0.11. The disk model of RZ Leo implies a truncated disk, supporting its previously speculated classification as an intermediate polar (IP). Except for the IP model of RZ Leo, which lacks a component related to the inferred accretion curtain, the models of J0632+2536, TW Vir and WD 1144+011 are consistent with results from the Gaia mission. The derived masses and radii of the secondaries of the three DN are consistent with the semi-empirical relations for CV donor stars, while their effective temperatures are higher than the predictions. Irradiation of the donor stars is investigated to explain this discrepancy.
Bi-EB: Empirical Bayesian Biclustering for Multi-Omics Data Integration Pattern Identification among Species

Although several biclustering algorithms have been studied, few are used for cross-pattern identification across species using multi-omics data mining. A fast empirical Bayesian biclustering (Bi-EB) algorithm is developed to detect the patterns shared from both integrated omics data and between species. The Bi-EB algorithm addresses the clinical critical translational question using the bioinformatics strategy, which addresses how modules of genotype variation associated with phenotype from cancer cell screening data can be identified and how these findings can be directly translated to a cancer patient subpopulation. Empirical Bayesian probabilistic interpretation and ratio strategy are proposed in Bi-EB for the first time to detect the pairwise regulation patterns among species and variations in multiple omics on a gene level, such as proteins and mRNA. An expectation–maximization (EM) optimal algorithm is used to extract the foreground co-current variations out of its background noise data by adjusting parameters with bicluster membership probability threshold Ac; and the bicluster average probability p. Three simulation experiments and two real biology mRNA and protein data analyses conducted on the well-known Cancer Genomics Atlas (TCGA) and The Cancer Cell Line Encyclopedia (CCLE) verify that the proposed Bi-EB algorithm can significantly improve the clustering recovery and relevance accuracy, outperforming the other seven biclustering methods—Cheng and Church (CC), xMOTIFs, BiMax, Plaid, Spectral, FABIA, and QUBIC—with a recovery score of 0.98 and a relevance score of 0.99. At the same time, the Bi-EB algorithm is used to determine shared the causality patterns of mRNA to the protein between patients and cancer cells in TCGA and CCLE breast cancer. The clinically well-known treatment target protein module estrogen receptor (ER), ER (p118), AR, BCL2, cyclin E1, and IGFBP2 are identified in accordance with their mRNA expression variations in the luminal-like subtype. Ten genes, including CCNB1, CDH1, KDR, RAB25, PRKCA, etc., found which can maintain the high accordance of mRNA–protein for both breast cancer patients and cell lines in basal-like subtypes for the first time. Bi-EB provides a useful biclustering analysis tool to discover the cross patterns hidden both in multiple data matrixes (omics) and species. The implementation of the Bi-EB method in the clinical setting will have a direct impact on administrating translational research based on the cancer cell screening guidance.
Antimicrobial Resistance and Molecular Characterization of Methicillin-Resistant Staphylococcus aureus from Two Pig Farms: Longitudinal Study of LA-MRSA

Pigs were identified as the most important reservoir of livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA), mostly belonging to the emergent zoonotic clonal complex (CC) 398. Here, we investigated the presence of MRSA in sows and piglets over a period of several months in two pig farms (intensive farm A and family-run farm B). Isolates underwent antimicrobial susceptibility testing, PCR characterization and spa typing. We collected 280 samples, namely 206 nasal swabs from pigs and 74 environmental samples from pig housings at 12 consecutive time points. A total of 120/161 (74.5%) and 75/119 (63.0%) samples were MRSA-positive in farms A and B, respectively. All isolates harbored mecA but lacked mecC and PVL-encoding genes. The identified spa types (t571, t034, t1250 and t898 in farm A, t1451 and t011 in farm B) were indicative of CC398. Antimicrobial resistance patterns (all multidrug resistant in farm A, 57.2% in farm B) depended on the farm, suggesting the impact of farm size and management practices on the prevalence and characteristics of MRSA. Due to the intermittent colonization of pigs and the high contamination of their immediate environment, MRSA status should be determined at the farm level when considering preventive measures or animal trade between farms.
Testing scalar versus vector dark matter

We investigate and compare two simple models of dark matter (DM): a vector and a scalar DM model. Both models require the presence of two physical Higgs bosons $h_1$ and $h_2$ which come from mixed components of the standard Higgs doublet $H$ and a complex singlet $S$. In the Vector model, the extra $U(1)$ symmetry is spontaneously broken by the vacuum of the complex field $S$. This leads to a massive gauge boson $X^\mu$ that is a DM candidate stabilized by the dark charge conjugation symmetry $S \to S^*$, $X^\mu\to -X^\mu$. On the other hand, in the Scalar model the gauge group remains the standard one. The DM field $A$ is the imaginary component of $S$ and the stabilizing symmetry is also the dark charge conjugation $S \to S^*$ ($A \to - A$). In this case, in order to avoid spontaneous breaking, the $U(1)$ symmetry is broken explicitly, but softly, in the scalar potential. The possibility to disentangle the two models has been investigated. We have analyzed collider, cosmological, DM direct and indirect detection constraints and shown that there are regions in the space spanned by the mass of the non-standard Higgs boson and the mass of the DM particle where the experimental bounds exclude one of the models. We have also considered possibility to disentangle the models at $e^+e^-$ collider and concluded that the process $e^+e^-\to Z + \text{DM}$ provides a useful tool to distinguish the models.
Analysis of density matrix reconstruction in NMR quantum computing

Reconstruction of density matrices is important in NMR quantum computing. An analysis is made for a 2-qubit system using the error matrix method. It is found that the state tomography method determines well the parameters that are necessary for reconstructing the density matrix in NMR quantum computations. Analysis is also made for a simplified state tomography procedure that uses fewer read-outs. The result of this analysis with the error matrix method demonstrates that a satisfactory accuracy in the density matrix reconstruction can be achieved even in a measurement with the number of read-outs being largely reduced.
Bianchi type-V Dark Energy Modified f(R,T) Gravity Model in the Presence of Massive Scalar Field in Lyra Geometry

Here, we investigate Bianchi type-V modified f(R,T) gravity cosmological models in Lyra geometry. To acquire the deterministic solution of the field equations with f(R,T) gravity based on Lyra geometry, we consider f(R,T)= f_1 (R)+f_2 (T), R indicates Ricci Scalar, T indicates trace of the energy momentum tensor in Lagrangian matter. Presence of Massive scalar field and Displacement vector of Lyra played an important role. The physical as well as the geometrical nature of the f(R,T) model is also discussed. HIGHLIGHTS In this present model of universe, we obtained that the universe starts with zero volume As in present observational data like CMB, BAO, La Supernona, our model is accelerating It is observed that the scalar field and kinetic energy both are non singular CDM is not satisfied in this model of universe GRAPHICAL ABSTRACT
Going beyond modelling and inversion of first-order reflection data - Generalization of Kirchhoff reflectivity and consequences

We emphasize in a novel way the connections and differences between Kirchhoff and Born modelling. We show how they lead to similar expressions, and derive a general expression for the conversion of a velocity model perturbation into a reflectivity through the "generalized reflectivity" concept. This allows the modelling of first-order effects within the Kirchhoff scheme that go beyond first-order reflections (for example first-order diffractions). Also, we clarify some aspects related to Kirchhoff modelling, in the context of possibly non-smooth propagating media (introducing travel-time branches or multipathing) and the linearity approximation on reflectors. The scheme we develop offers opportunities within the framework of Kirchhoff inversion, i.e. for the interpretation of seismic-migrated images: generalized reflectivity gives a basis to interpret more information than only that associated with first-order reflections (for instance the amplitudes of first-order diffractors). Also the scheme offers opportunities for full-waveform inversion (FWI) approaches that include a reflectivity, showing how to rigorously convert the reflectivity into a velocity perturbation.
Denumerable Markov chains

This textbook provides a systematic treatment of denumerable Markov chains, covering both the foundations of the subject and topics in potential theory and boundary theory. It is a discussion of relations among what might be called the descriptive quantities associated with Markov chains - probabilities of events and means of random variables that give insight into the behaviour of the chains. The approach, by means of infinite matrices, simplifies the notation, shortens statements and proofs of theorems, and often suggests new results. This second edition includes a new chapter, "Introduction to Random Fields", written by David Giffeath.
Temperature Programmed Desorption of Water Ice from the Surface of Amorphous Carbon and Silicate Grains as Related to Planet-forming Disks

Understanding the history and evolution of small bodies, such as dust grains and comets, in planet-forming disks is very important to reveal the architectural laws responsible for the creation of planetary systems. These small bodies in cold regions of the disks are typically considered to be mixtures of dust particles with molecular ices, where ices cover the surface of a dust core or are actually physically mixed with dust. While the first case, ice-on-dust, has been intensively studied in the laboratory in recent decades, the second case, ice-mixed-with-dust, presents uncharted territory. This work is the first laboratory study of the temperature-programmed desorption of water ice mixed with amorphous carbon and silicate grains. We show that the kinetics of desorption of H2O ice depends strongly on the dust/ice mass ratio, probably due to the desorption of water molecules from a large surface of fractal clusters composed of carbon or silicate grains. In addition, it is shown that water ice molecules are differently bound to silicate grains in contrast to carbon. The results provide a link between the structure and morphology of small cosmic bodies and the kinetics of desorption of water ice included in them.