Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of a Flat Polyimide Inlay on the Propagation of Guided Ultrasonic Waves in a Narrow GFRP-Specimen

Structural health monitoring systems for composite laminates using guided ultrasonic waves become more versatile with the structural integration of sensors. However, the data generated within these sensors have to be transmitted from the laminate to the outside, where polyimide-based printed circuit boards play a major role. This study investigates, to what extent integrated polyimide inlays with applied sensor bodies influence the guided ultrasonic wave propagation in glass fiber-reinforced polymer specimens. For reasons of resource efficiency, narrow specimens are used. Numerical simulations of a damping-free specimen indicate reflections of the S0-mode at the integrated inlay. This is validated experimentally with an air-coupled ultrasonic technique and a 3D laser Doppler vibrometry measurement. The experimental data are evaluated with a method including temporal and spatial continuous wavelet transformations to clearly identify periodically occurring wave packages as edge reflections and distinguish them from possible inlay reflections. However, even when separating in-plane and out-of-plane movements using the 3D measurement, no reflections at the inlays are detected. This leads to the conclusion that polyimide inlays are well suited as substrates for printed circuit boards integrated into fiber-reinforced polymer structures for structural health monitoring, since they do not significantly influence the wave propagation.
Concise review: gamma-glutamyl transferase - evolution from an indiscriminate liver test to a biomarker of cardiometabolic risk

This concise review article critically examines the recent medical literature regarding gamma glutamyl transferase (GGT) with a special emphasis on newly proposed indications for GGT use, including cardiovascular risk assessment. GGT is a ubiquitous glycosylated protein embedded in the outer surface of cell membranes, which catalyzes the transfer of glutamyl groups from various substrates and plays a key role in the antioxidant/pro-oxidant balance. In the past, the enzyme was considered a non-specific liver test. Current evidence supports the role of GGT in the assessment of portal hypertension in cystic fibrosis, porto-sinusoidal vascular disease, malignant mesothelioma, and incident type 2 diabetes and as a biomarker of cardiometabolic risk and cardiovascular disease. Several specific points including the use of GGT in hepatology as a sensitive but poorly specific test and the association of GGT with metabolic syndrome, nonalcoholic fatty liver disease and its fibrotic stages, cardiometabolic risk, chronic kidney disease, neurodegenerative disorders and dementia, idiopathic pulmonary arterial hypertension, and Corona Virus Disease 2019 (COVID-19) are addressed based on the most recent research in these fields. Putative mechanisms linking GGT with increased metabolic stress and the effects of various therapeutic interventions on GGT values are also discussed. We conclude that GGT has evolved from an indiscriminate liver test and an index of alcohol consumption to a biomarker of cardiometabolic health. The proper interpretation of GGT values (i.e., of hepatic vs. extrahepatic origin) is deeply affected by the clinical and epidemiological context. We propose that GGT may be utilized in public health campaigns, in the research arena, and in clinical practice to identify those individuals who can benefit most from the proactive preventive and therapeutic approaches, given that they are at high cardiometabolic risk.
Introduction to Nonequilibrium Quantum Field Theory

There has been substantial progress in recent years in the quantitative understanding of the nonequilibrium time evolution of quantum fields. Important topical applications, in particular in high energy particle physics and cosmology, involve dynamics of quantum fields far away from the ground state or thermal equilibrium. In these cases, standard approaches based on small deviations from equilibrium, or on a sufficient homogeneity in time underlying kinetic descriptions, are not applicable. A particular challenge is to connect the far‐from‐equilibrium dynamics at early times with the approach to thermal equilibrium at late times. Understanding the “link” between the early‐ and the late‐time behavior of quantum fields is crucial for a wide range of phenomena. For the first time questions such as the explosive particle production at the end of the inflationary universe, including the subsequent process of thermalization, can be addressed in quantum field theory from first principles. The progress in this f.
Spin-orbit torque magnetization switching of a three-terminal perpendicular magnetic tunnel junction

We report on the current-induced magnetization switching of a three-terminal perpendicular magnetic tunnel junction by spin-orbit torque and its read-out using the tunnelling magnetoresistance (TMR) effect. The device is composed of a perpendicular Ta/FeCoB/MgO/FeCoB stack on top of a Ta current line. The magnetization of the bottom FeCoB layer can be switched reproducibly by the injection of current pulses with density 5 × 1011 A/m2 in the Ta layer in the presence of an in-plane bias magnetic field, leading to the full-scale change of the TMR signal. Our work demonstrates the proof of concept of a perpendicular spin-orbit torque magnetic memory cell.
Bidirectional Denoising Autoencoders-Based Robust Representation Learning for Underwater Acoustic Target Signal Denoising

The marine environmental noise formed by wind noise, rain noise, biological noise, sea surface waves, seismic disturbances, and so on is a kind of interference background field in underwater acoustic channels, which brings adverse effects to underwater acoustic target recognition. To improve the recognition accuracy of underwater targets under background noise interference, a bidirectional denoising autoencoder (BDAE) is proposed in this article for underwater acoustic target signal denoising robust representation learning. The proposed BDAE is an extension of the regular denoising autoencoder, which uses the original underwater acoustic target signals and their corresponding denoised signals to learn robust representations. We then measure the usefulness of the learned representations using a support vector machine (SVM) classifier. Our proposed approach is verified on the ShipsEar database. Experimental results indicate that the proposed BDAE can effectively learn the robust representations of underwater acoustic target signal denoising and is superior to the traditional methods.
A Review on Thermal Imaging-Based Breast Cancer Detection Using Deep Learning

Breast cancer is the most common form of cancer in women. Its aggressive nature has made it one of the chief factors of high female mortality. Therefore, this has motivated research to achieve early diagnosis since it is the best strategy for patient survival. Currently, mammography is the gold standard for detecting breast cancer. However, it is expensive, unsuitable for dense breasts, and an invasive process that exposes the patient to radiation. Infrared thermography is gaining popularity as a screening modality for the early detection of breast cancer. It is a noninvasive and cost-effective modality that allows health practitioners to observe the temperature profile of the breast region for signs of cancerous tumors. Deep learning has emerged as a powerful computational tool for the early detection of breast cancer in radiology. As such, this study presents a review that shows existing work on deep learning-based Computer-aided Diagnosis (CADx) systems for breast cancer detection. In the same context, it reflects on classification utilizing breast thermograms. It first provides an overview of infrared thermography, details on available breast thermogram datasets, and then segmentation techniques applied to these thermograms. We also provide a brief overview of deep neural networks. Finally, it reviews works adopting Deep Neural Networks (DNNs) for breast thermogram classification.
Calibration, modeling, parameterization, and verification of the instrument transfer function of an interferometric microscope

Interferometric microscopes are used to measure surface roughness, from which the computed power spectral density function can be used to extract bandwidth-limited values of the various surface properties, such as root-mean-square (rms) height and slope errors. Measurements with a microscope equipped with different objectives that have an overlapping spatial frequency range usually give different rms results over the common frequency bandwidth. This is a result of different instrument transfer functions (ITFs) that attenuate spatial frequencies by different amounts over the overlapping range. We report on the use of binary pseudo-random array (BPRA) standards to characterize the ITF of an interferometric microscope with the various objectives. We use a simple model of a 1D binary Results show that the spectrum for an undersampled array is a cosine function, rather than a straight line, constant white noise spectrum. We have an analytical model of the ITF that includes the effects of an obscured aperture and defocus, in addition to the usual parameters of numerical aperture, wavelength, and sampling period. In addition, the model includes the effect of aliasing of spatial frequency components beyond the Nyquist back into the sub-Nyquist region. We compare the model PSD predictions to the measurements performed with different objectives. Departures of the measured PSDs from the model predictions indicate that there are higher-order ITF corrections yet to be identified and included in the model.
Food selection and processing: Can we blend science with engineering to address Chronic Kidney Disease (CKD)?

Chronic kidney disease (CKD) alters the function and structure of the kidney irreversibly, over months or years. The rising incidence of CKD has become a leading global health problem and therefore a number of multi-field investigations are being carried on. In general, diabetes and high blood pressure (hypertension) are the most common causes of CKD. However, the importance of functional food selection and less consumption of ultra-processed food is at the forefront of the current research domain to manage CKD. To address this threat, experts suggest and recommend adopting a science-based dietary pattern, for instance, the Dietary Approaches to Stop Hypertension (DASH). Moreover, food bioactive compounds are non-nutrients that typically occur in small quantities in foods, and hence, the selection of proper food (source) and subsequent processing is of paramount importance to attenuate the magnitude of CKD. The role of food science in managing chronic diseases could be coupled with the advancement of food engineering to minimize the detrimental effect of food processing along with the delivery of target bioactive molecules. This potentially indicates bold ambitions to innovate holistic solutions to address CKD through a proper selection of food and processing parameters.
Multiresolution signal decomposition schemes

[PNA-R9810] Interest in multiresolution techniques for signal processing and analysis is increasing steadily. An important instance of such a technique is the so-called pyramid decomposition scheme. This report proposes a general axiomatic pyramid decomposition scheme for signal analysis and synthesis. This scheme comprises the following ingredients: (i) the pyramid consists of a (finite or infinite) number of levels such that the information content decreases towards higher levels; (ii) each step towards a higher level is constituted by an (information-reducing) analysis operator, whereas each step towards a lower level is modeled by an (information-preserving) synthesis operator. One basic assumption is necessary: synthesis followed by analysis yields the identity operator, meaning that no information is lost by these two consecutive steps. In this report, several examples are described of linear as well as nonlinear (e.g., morphological) pyramid decomposition schemes. Some of these examples are known from the literature (Laplacian pyramid, morphological granulometries, skeleton decomposition) and some of them are new (morphological Haar pyramid, median pyramid). Furthermore, the report makes a distinction between single-scale and multiscale decomposition schemes (i.e. without or with sample reduction). #[PNA-R9905] In its original form, the wavelet transform is a linear tool. However, it has been increasingly recognized that nonlinear extensions are possible. A major impulse to the development of nonlinear wavelet transforms has been given by the introduction of the lifting scheme by Sweldens. The aim of this report, which is a sequel to a previous report devoted exclusively to the pyramid transform, is to present an axiomatic framework encompassing most existing linear and nonlinear wavelet decompositions. Furthermore, it introduces some, thus far unknown, wavelets based on mathematical morphology, such as the morphological Haar wavelet, both in one and two dimensions. A general and flexible approach for the construction of nonlinear (morphological) wavelets is provided by the lifting scheme. This paper discusses one example in considerable detail, the max-lifting scheme, which has the intriguing property that it preserves local maxima in a signal over a range of scales, depending on how local or global these maxima are.
The filling factor of intergalactic metals at redshift z= 3

Observations of quasar absorption-line systems reveal that the z= 3 intergalactic medium (IGM) is polluted by heavy elements down to H i optical depths τH I≪ 10. What is not yet clear, however, is what fraction of the volume needs to be enriched by metals and whether it suffices to enrich only regions close to galaxies in order to reproduce the observations. We use gas density fields derived from large cosmological simulations, together with synthetic quasar spectra and imposed model metal distributions, to investigate what enrichment patterns can reproduce the observed median optical depth of C iv as a function of τH I. Our models can only satisfy the observational constraints if the z= 3 IGM was primarily enriched by galaxies that reside in low-mass (mtot rsim 102 kpc. Galaxies in more massive haloes cannot possibly account for the observations as they are too rare for their outflows to cover a sufficiently large fraction of the volume. Galaxies need to enrich gas out to distances that are much greater than the virial radii of their host haloes. Assuming the metals to be well mixed on small scales, our modelling requires that the fractions of the simulated volume and baryonic mass that are polluted with metals are, respectively, >10 per cent and >50 per cent in order to match observations.
A CORRELATION BETWEEN SURFACE DENSITIES OF YOUNG STELLAR OBJECTS AND GAS IN EIGHT NEARBY MOLECULAR CLOUDS

We report the discovery and characterization of a power-law correlation between the local surface densities of Spitzer-identified, dusty young stellar objects (YSOs) and the column density of gas (as traced by near-IR extinction) in eight molecular clouds within 1 kpc and with 100 or more known YSOs. This correlation, which appears in data smoothed over size scales of ∼1 pc, varies in quality from cloud to cloud; those clouds with tight correlations, MonR2 and Ophiuchus, are fit with power laws of slope 2.67 and 1.87, respectively. The spread in the correlation is attributed primarily to local gas disruption by stars that formed there or to the presence of very young subregions at the onset of star formation. We explore the ratio of the number of Class II to Class I sources, a proxy for the star formation age of a region, as a function of gas column density; this analysis reveals a declining Class II to Class I ratio with increasing column density. We show that the observed star–gas correlation is consistent with a star formation law where the star formation rate per area varies with the gas column density squared. We also propose a simple picture of thermal fragmentation of dense gas in an isothermal, self-gravitating layer as an explanation for the power law. Finally, we briefly compare the star–gas correlation and its implied star formation law with other recent proposed of star formation laws at similar and larger size scales from nearby star-forming regions.
1λ Spaced Dual Radiating Modes Based Phased Array Antenna Using Silicon RFICs With Grating Lobe Cancellation

A dual radiating modes (TM11 and TM21)-based phased array antenna with $1\lambda $ interelement spacing at Ku-band is demonstrated using silicon beamforming RFICs, which offers grating lobe cancellation. The radiating element consists of concentric microstrip circular patch antennas supporting TM11 and TM21 modes. Excitation of both modes (TM11 and TM21), with the proper amplitude and phase values, allows for the suppression of grating lobe present in the array radiation pattern. The array utilizes Anokiwave RFICs (AWMF-0117), which provides flat panel integration of the beamforming network with the antenna aperture. A suitable beamforming network consisting of wideband Wilkinson power dividers was used to feed the RFICs from a single input. We demonstrate a grating lobe suppression ability of up to 30.8 dB with a first sidelobe level (SLL) of 15.2 dB. We also confirm the grating lobe mitigation technique through the demonstration of an over-the-air (OTA) link using digitally modulated signals and observing the error vector magnitude (EVM) of the received signal.
Stereo-Based Region-Growing using String Matching

We present a novel stereo algorithm based on a coarse texture segmentation preprocessing phase. Matching is performed using a string comparison. Matching sub-strings correspond to matching sequences of textures. Inter-scanline clustering of matching sub-strings yields regions of matching texture. The shape of these regions yield information concerning object's height, width and azimuthal position relative to the camera pair. Hence, rather than the standard dense depth map, the output of this algorithm is a segmentation of objects in the scene. Such a format is useful for the integration of stereo with other sensor modalities on a mobile robotic platform. It is also useful for localization; the height and width of a detected object may be used for landmark recognition, while depth and relative azimuthal location determine pose. The algorithm does not rely on the monotonicity of order of image primitives. Occlusions, exposures, and foreshortening effects are not problematic. The algorithm can deal with certain types of transparencies. It is computationally efficient, and very amenable to parallel implementation. Further, the epipolar constraints may be relaxed to some small but significant degree. A version of the algorithm has been implemented and tested on various types of images. It performs best on random dot stereograms, on images with easily filtered backgrounds (as in synthetic images), and on real scenes with uncontrived backgrounds.
The graph isomorphism problem is polynomial

It is known that a graph isomorphism testing algorithm is polynomially equivalent to a detecting of a graph non-trivial automorphism algorithm. The polynomiality of the latter algorithm, is obtained by consideration of symmetry properties of regular k-partitions that, on one hand, generalize automorphic k-partitions (=systems of k-orbits of permutation groups), and, on other hand, schemes of relations (strongly regular 2-partitions or regular 3-partitions), that are a subject of the algebraic combinatorics. It is shown that the stabilization of a graph by quadrangles detects the triviality of the graph automorphism group. The result is obtained by lineariation of the algebraic combinatorics.
Extending H-infinity Control to Nonlinear Systems: Control of Nonlinear Systems to Achieve Performance Objectives

H-infinity control originated from an effort to codify classical control methods, where one shapes frequency response functions for linear systems to meet certain objectives. H-infinity control underwent tremendous development in the 1980s and made considerable strides toward systematizing classical control. This book addresses the next major issue of how this extends to nonlinear systems. At the core of nonlinear control theory lie two partial differential equations (PDEs). One is a first-order evolution equation called the information state equation, which constitutes the dynamics of the controller. One can view this equation as a nonlinear dynamical system. Much of this volume is concerned with basic properties of this system, such as the nature of trajectories, stability, and, most important, how it leads to a general solution of the nonlinear H-infinity control problem.
Identity Effects in Morphological Truncation

Morphologically truncated words may be phonologically irregular, constituting a class of exceptions to regular surface patterns.1 In this paper I propose that phonological irregularities in truncated words are identity effects forced by constraints demanding identity between truncated forms and their source words. These constraints, which are ranked and violable in the Optimality Theory model (Prince & Smolensky 1993), regulate the correspondence relation between the source word base and the truncated form, in the same way that faithfulness constraints require identity of base and copy in reduplicated words (McCarthy & Prince 1993a et seq.). I will show that truncated words mimic derived properties of their sources, and conclude that truncatory correspondence is a relation between two output forms. Building on proposals in McCarthy & Prince (1994b, 1995), this analysis of truncatory identity extends Correspondence Theory beyond basereduplicant and input-output relations, establishing correspondence between separate words.
CFT driven cosmology and the DGP/CFT correspondence

We present a dual 5D braneworld picture of a recently suggested model for a microcanonical description of a 4D cosmology driven by a conformal field theory with a large number of quantum fields. The 5D side of the duality relation is represented by a generalized brane induced gravity model in a Schwarzschild-de Sitter bulk. The values of the bulk cosmological and the induced 4D cosmological constants are determined by requiring the absence of conical singularity at the de Sitter horizon of the Euclidean Schwarzschild-de Sitter bulk. Those values belong to the vicinity of the upper bound of a range of admissible values for the cosmological constant. This upper bound is enforced by the 4D CFT and coincides with the natural gravitational cutoff in a theory with many quantum species. The resulting DGP/CFT duality suggests the possibility of a new type of background independent correspondence. A mechanism for inverting the sign of the effective cosmological constant is found, which might reconcile a negative value of the primordial cosmological constant compatible with supersymmetry with the one required by inflationary cosmology.
Radio structure of the Seyfert galaxy Markarian 509

Detailed radio observations of Mkn 509, a Seyfert type I galaxy, have revealed an extended radio feature at 6 and 20 cm at a position angle of −65° and pointing toward the northwest. It is remarkably well-aligned with the direction of polarized H α emission, a disk of low-ionization narrow-line region and polarized optical to IR continuum indicating that both scattering and synchrotron radiation contribute to the polarized emission. A faint linear structure at 6 cm (length ≈2 kpc), almost parallel to the minor axis of the galaxy is tentatively identified as a 'jet' and needs to be confirmed with higher resolution observations. The 'jet' extends into the narrow-line region and can easily be confined by the narrow-line gas. A plausible geometry of the emission regions is presented.