Miracle-dz/UniFAR-FTUs huggingface dataset:
Band gap dependent thermophotovoltaic device performance using the InGaAs and InGaAsP material system

Thermophotovoltaic cells with a range of band gaps are modeled under a variety of illumination conditions, including a range of source temperatures and a variable degree of spectral control. Thus, the balance between the requirements of high power densities and high efficiencies can be investigated. The influence of elevated cell temperatures, cell cooling, Auger recombination, and series resistances have been included, and all weight the optimum band gap thermophotovoltaic cell toward higher band gaps than the ∼0.5–0.6 eV conventional optimum. The cells have been modeled using fundamental physical parameters from the InGaAs and InGaAsP material system which accurately reproduce reported device performance and allow a comparison to theoretical limits.
Spectral Efficiency of Time-Variant Massive MIMO Using Wiener Prediction

Massive multiple-input multiple-output (MIMO) serves as technological pillar in current 5G deployments. The spectral efficiency (SE) reduction due to time-variance of the wireless channel, and respective mitigation strategies, are still not sufficiently understood. In this letter, we propose a multi-step Wiener predictor with a general temporal covariance function to quantify the impact of time-variance on the SE for different numbers of consecutive pilot symbols and prediction horizons. We provide asymptotic expressions of the SE for maximum ratio combining (MRC) beam-forming that show excellent agreement to numerical simulations. We investigate the channel hardening capability of massive MIMO systems in time-variant propagation channels and show that it is largely independent of the prediction horizon. The numerical evaluations show that channel prediction allows to double SE utilizing four instead of one uplink pilot symbol for a prediction horizon of $0.3\,\lambda $ for both MRC and regularized zero-forcing (RZF) beam-forming.
Generative Building Feature Estimation From Satellite Images

Urban and environmental researchers seek to obtain building features (e.g., building shapes, counts, and areas) at large scales. However, blurriness, occlusions, and noise from prevailing satellite images severely hinder the performance of image segmentation, super-resolution, or deep-learning-based translation networks. In this article, we combine globally available satellite images and spatial geometric feature datasets to create a generative modeling framework that enables obtaining significantly improved accuracy in per-building feature estimation and the generation of visually plausible building footprints. Our approach is a novel design that compensates for the degradation present in satellite images by using a novel deep network setup that includes segmentation, generative modeling, and adversarial learning for instance-level building features. Our method has proven its robustness through large-scale prototypical experiments covering heterogeneous scenarios from dense urban to sparse rural. Results show better quality over advanced segmentation networks for urban and environmental planning, and show promise for future continental-scale urban applications.
Measurement of the Tensor Polarization in Electron-Deuteron Elastic Scattering

This paper reports the first measurement of the tensor polarization t/sub 20/ in e-d elastic scattering. The polarization of the recoil deuterons was measured for two values of momentum transfer, q = 1.74 and 2.03 fm/sup -1/, with a high-efficiency polarimeter. The results are in good agreement with reasonable models for the deuteron.
Solid Ink Laser Patterning for High‐Resolution Information Labels with Supervised Learning Readout

Tagging, tracking, or validation of products are often facilitated by inkjet‐printed optical information labels. However, this requires thorough substrate pretreatment, ink optimization, and often lacks in printing precision/resolution. Herein, a printing method based on laser‐driven deposition of solid polymer ink that allows for printing on various substrates without pretreatment is demonstrated. Since the deposition process has a precision of <1 µm, it can introduce the concept of sub‐positions with overlapping spots. This enables high‐resolution fluorescent labels with comparable spot‐to‐spot distance of down to 15 µm (444,444 spots cm−2) and rapid machine learning‐supported readout based on low‐resolution fluorescence imaging. Furthermore, the defined thickness of the printed polymer ink spots can be used to fabricate multi‐channel information labels. Additional information can be stored in different fluorescence channels or in a hidden topography channel of the label that is independent of the fluorescence.
Flow between time-periodically co-rotating cylinders

We consider oscillatory flows between concentric co-rotating cylinders at angular velocity Ω(t) = Ωm + Ωo cos ωt as a prototype to investigate the competing effects of centrifugal and Coriolis forces on the flow stability. We first study by flow visualization the effect of the mean rotation Ωm on the centrifugal destabilization due to the temporal modulation. We show that increasing the mean rotation first destabilizes and then restabilizes the flow. The instability of the purely azimuthal basic flow is then analysed by investigating the dynamics of the axial velocity component of the vortex structures. Velocity measurements performed in the rotating frame of the cylinders using ultrasound Doppler velocimetry show that secondary flow appears and disappears several times during a flow period. Based on a finite-gap expression for the basic flow, linear stability analysis is performed with a quasi-steady approach, providing the times of appearance and disappearance of secondary flow in a cycle as well as the effect on the instability threshold of the mean rotation. The theoretical and numerical results are in agreement with experimental results up to intermediate values of the frequency. Notably, the flow periodically undergoes restabilization at particular time intervals.
Formation of self‐assembled metal/silicon nanocomposites

The fabrication of nanoscopic silicon based membranes has been carried out by using a non‐expensive electrochemical preparation technique. For these purposes an n+‐silicon wafer is anodized to create oriented pores with typical diameters around 50 nm. The length of the channels is up to 50 μm which yields to an aspect ratio of 1000. The channels of these templates are partially filled with a metal, especially a ferromagnetic one to obtain an array of nanostructures. Metal‐deposition within such high aspect ratio pores is a great challenge but could be realized in some extent. The introduced silicon based nanocomposite offers the opportunity to change between different nano‐architectures by accurate adjustment of the electrochemical fabrication parameters. Also the size and spatial distribution of the precipitated metal‐structures within the pores can be varied by altering the galvanic deposition process. Different morphologies and varying metal fillings modify the physical properties (e.g. magnetic behaviour) of the nanocomposite system. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Effect of teach-back education on exercise compliance and quality of life in elderly patients with hemiplegia after stroke

： Objective To explore the effect of teach - back method on exercise compliance and quality of life in elderly patients with hemiplegia after stroke. Method Using the convenient sampling method ， a total of 80 elderly patients with hemiplegia after stroke were randomly divid⁃ ed into control group （ n = 40 ） and intervention group （ n = 40 ） . The control group adopted the routine health education method ， and the intervention group adopted the teach - back method on the basis of routine care. After a 3 - month follow - up ， the rehabilitation exercise compliance scale ， Na⁃ tional Institutes of Health Stroke Scale （ NIHSS ） score ， Fugl - Meyer Assessment （ FMA ）， Modi⁃ fied Barthel Index scale （ MBI ） and Stroke Specific Quality of Life Scale （ SS - QOL ） were used to compare the effects of exercise compliance ， neurological function ， limb motor function ， self - care ability and quality of life between the two groups. Results The compliance rate was 85 . 00 % （ 34 / 40 ） in the intervention group ， which was significant higher than 72 . 50 % （ 29 / 40 ） in the control group （ P ＜ 0 . 01 ） . The NIHSS score decreased in both two groups after intervention ， and NIHSS
Velocity retrieval for coherent Doppler lidar

Coherent Doppler light detection and ranging (lidar) measures a component of atmospheric wind motion in the direction of the lidar beam. However, velocity vectors are needed in order to obtain more complete knowledge of flow fields in the atmospheric boundary layer (ABL). Several methods such as the velocity azimuthal display (VAD) and dual-Doppler approaches exist to retrieve two-dimensional vector fields, but these methods tend to lose local information about the flow field due to the averaging involved. A two-dimensional vector retrieval method has been adapted from radar data assimilation techniques. The retrievals are performed on data from the Joint Urban 2003 (JU2003) experiment and are shown to retain the local velocity information which is lost in a method like the VAD. A comparison with dual-Doppler retrievals shows reasonable agreement. Furthermore, radial velocities computed using the projections of the retrieved vectors from one lidar and the look direction from the other lidar compare well w.
Comments on six papers published by S.P. Anjali Devi and R. Kandasamy

Comments on six papers published by S.P. Anjali Devi and R. Kandasamy in Heat and Mass Transfer, ZAMM, Mechanics Research Communications, International Communications in Heat and Mass Transfer, Communications in Numerical Methods in Engineering, Journal of Computational and Applied Mechanics In conclusion all the above papers are of very low quality, written without care and are partly or completely wrong.
Cascaded Fins for Heat Transfer Enhancement

Recent developments in electronics cooling imposed fin structures constructed from two materials (e.g., copper and aluminum) as a thermo-economical solution for heat transfer enhancement. Such fins facilitate savings of expensive materials and reduce operating and investment costs by increasing efficiency. This paper stresses the importance of constraints on the geometrical optimization of “cascaded” fins made from two materials. Two types of constraints are analyzed in a unitary way: fixed weight (relevant to aerospace and transportation applications) and fixed investment cost. The cascaded fin geometry springs from the thermal performance maximization under constraints (constructal principle). To illustrate the design principle and derive its fundamental features, it is sufficient to consider the most basic case of one-dimensional heat conduction through rectangular-rectangular, rectangular-triangular, and rectangular-parabolic cascaded fins. The study reveals that the ideal/theoretical limit of heat transfer enhancement obtained with a cascaded fin, with respect to an optimal-profile rectangular fin made in one single material, is about 15%. Additional effects like contact resistance at the interface between the two materials and the variation of heat transfer coefficient along the fins degrade the performance of the cascaded fin. However, even for relatively high contact resistances, cascaded fins can remain slightly superior to single material fins.
High-resolution studies of cubic perovskites by elastic neutron diffraction. II. SrTiO3, KMnF3, RbCaF3 and CsPbCl3

For pt.I see ibid., vol.12, p.5393 (1979). A programme of elastic neutron-diffraction experiments has been undertaken to derive (and compare) atomic distribution functions, with high spatial resolution, for the ABX3 antiferroelectric perovskites SrTiO3, KMnF3, RbCaF3 and CsPbCl3 in their cubic phase. The background and motivation of the work, and some first results for CsPbCl3, have been published in paper I. Data collected 5-10K above the cubic to tetragonal transition temperature, Tc, have been used in least-squares refinements of parameters describing anharmonic distributions for the metal and X ions. For KMnF3 and RbCaF3 the same parameters have been refined from data collected approximately 100K above Tc-at room temperature. The metal ions are found to have relatively small anharmonicity, which decreases on cooling. By contrast the X ions have an anharmonicity which becomes anomalously enhanced near Tc. This effect increases strongly through the series SrTiO3 to KMnF3 to RbCaF3 to CsPbCl3: for the O-ion distribution in SrTiO3 no anharmonic parameter (i.e. above second order) is significantly non-zero, even at Tc+5K, whilst the Cl-ion distribution in CsPbCl3 at Tc+5K has some significant sixth-order parameters. The form and temperature dependence of the X-ion anharmonicity are examined in relation to current attempts to understand some structural phase transitions in terms of 'precursor' order (clusters), already present in the high-temperature phase.
Utility of repeat colonoscopy within 1 year: a patient-level analysis

Abstract Patients undergo colonoscopies for colorectal cancer screening and for the evaluation of gastrointestinal symptoms. Analysis of large administrative databases has demonstrated that some patients undergo repeat colonoscopies at intervals inconsistent with current recommendations, but these studies do not provide patient-level details. The medical records of 110 patients undergoing repeat colonoscopies within 1 year of their index colonoscopies at a tertiary care hospital-based endoscopy center were retrospectively reviewed to determine patient demographics, gastrointestinal symptoms, and endoscopic findings. Thirty-five patients had poor bowel preparations, and 11 patients had a history of colorectal cancer. Thirty-four patients had polyps identified during their index colonoscopies, and 28 patients had no polyps identified during their index colonoscopies. Eleven patients in the nonpolyp group had new endoscopic findings identified during the repeat colonoscopies. Twenty patients who had polyps identified on their index colonoscopies had 44 polyps identified on repeat colonoscopies. Repeat colonoscopies within 1 year occurred relatively infrequently in this endoscopy center. Indications included poor bowel preparation with incomplete studies, colonic polyps with incomplete resection, multiple polyps resulting in the possibility of missed polyps, and new gastrointestinal symptoms.
GDF15 Promotes Cell Growth, Migration, and Invasion in Gastric Cancer by Inducing STAT3 Activation

Growth differentiation factor 15 (GDF15) has been reported to play an important role in cancer and is secreted and involved in the progression of various cancers, including ovarian cancer, prostate cancer, and thyroid cancer. Nevertheless, the functional mechanism of GDF15 in gastric cancer is still unclear. Immunohistochemical staining was performed to estimate the expression of GDF15 in 178 gastric cancer tissues. The biological role and action mechanism of GDF15 were investigated by examining the effect of GDF15 knockdown in AGS and SNU216 gastric cancer cells. Here, we report that the high expression of GDF15 was associated with invasion depth (p = 0.002), nodal involvement (p = 0.003), stage III/IV (p = 0.01), lymphatic invasion (p = 0.05), and tumor size (p = 0.049), which are related to poor survival in gastric cancer patients. GDF15 knockdown induced G0/G1 cell cycle arrest and remarkably inhibited cell proliferation and reduced cell motility, migration, and invasion compared to the control. GDF15 knockdown inhibited the epithelial–mesenchymal transition by regulating the STAT3 phosphorylation signaling pathways. Taken together, our results indicate that GDF15 expression is associated with aggressive gastric cancer by promoting STAT3 phosphorylation, suggesting that the GDF15-STAT3 signaling axis is a potential therapeutic target against gastric cancer progression.
A morphological filter for removing cirrus-like' emission from far-infrared extragalactic IRAS fields

The presence of diffuse extended IR emission from the Galaxy in the form of the so called 'Galactic Cirrus' emission has hampered the exploration of the extragalactic sky at long IR wavelengths. We describe the development of a filter based on mathematical morphology which appears to be a promising approach to the problem of cirrus removal. The method of Greyscale Morphology was applied to a 100 micron IRAS image of the M81 group of galaxies. This is an extragalactic field which suffers from serious contamination from foreground Galactic 'cirrus'. Using a technique called 'sieving', it was found that the cirrus emission has a characteristic behavior which can be quantified in terms of an average spatial structure spectrum or growth function. This function was then used to attempt to remove 'cirrus' from the entire image. The result was a significant reduction of cirrus emission by an intensity factor of 15 compared with the original input image. The method appears to preserve extended emission in the spatially extended IR disks of M81 and M82 as well as distinguishing fainter galaxies within bright regions of galactic cirrus. The techniques may also be applicable to IR databases obtained with the Cosmic Background Explorer.
Nonlinear Finite Element Calculations of Layered SAW Resonators

In this work the nonlinear behavior of layered surface acoustic wave (SAW) resonators is studied with the help of finite element (FE) computations. The full calculations depend strongly on the availability of accurate tensor data. While there are accurate material data for linear computations, the complete sets of higher-order material constants, needed for nonlinear simulations, are still not available for relevant materials. To overcome this problem, scaling factors were used for each available nonlinear tensor. The approach here considers piezoelectricity, dielectricity, electrostriction, and elasticity constants up to the fourth order. These factors act as a phenomenological estimate for incomplete tensor data. Since no set of fourth-order material constants for LiTaO3 is available, an isotropic approximation for the fourth-order elastic constants was applied. As a result, it was found that the fourth-order elastic tensor is dominated by one-fourth order Lamé constant. With the help of the FE model, derived in two different, but equivalent ways, we investigate the nonlinear behavior of a SAW resonator with a layered material stack. The focus was set to third-order nonlinearity. Accordingly, the modeling approach is validated using measurements of third-order effects in test resonators. In addition, the acoustic field distribution is analyzed.
A Convergent Iteration Method for 3-D AOA Localization

Using angle-of-arrival (AOA) measurements from several sensors to locate a target in 3-D space is one of the commonly used wireless localization techniques. A challenge of this technique is that the weighted least-squares (WLS) needed for it tend to incur the threshold effect when the noise level is high or when the localization geometry is poor, because its implementation requires the inversion of a matrix whose condition number will be large under such conditions. This paper presents an iterative method that does not require any matrix operation and is proved to be convergent with any initial value. Additionally, it outperforms the WLS-based methods as validated by comprehensive simulation results. Index Term-Angle-of-arrival (AOA), target localization, weighted least-squares (WLS).
Homotopic solution of the chemically reactive magnetohydrodynamic flow of a hybrid nanofluid over a rotating disk with Brownian motion and thermophoresis effects

Due to the synergetic effects of several types of nanomaterials, the primary goal of the hybrid nanofluid is to enhance the energy transport capabilities over a base fluid. Hybrid nanofluids have a wide range of applications in the industrial, technical, and medical industries, including solar heating systems, food processing, microchannel heat sinks (MCHS), and medicines. In this article, the researchers have investigated the water‐based hybrid nanofluid flow comprising silver and alumina nanoparticles past a spinning disk. The effect of Brownian motion, activation energy, magnetic field, and thermophoresis are taken into account. The PDEs are transformed into ODEs by means of suitable correspondence transformations. The modeled equations are solved by using a semi‐analytical method known as HAM. Graphical representations of the nanofluid and hybrid nanofluid profiles are used. The current findings are contrasted with those that have already been published and are confirmed to be remarkably comparable. The outcomes showed that the radial and tangential velocities of the nanofluids and hybrid nanofluid reduced as the magnetic factor augmented. Nanofluids and hybrid nanofluid surface drag is increased by magnetic factor. Hybrid nanofluid exhibits higher growth due to the magnetic factor than nanofluids do. The heat transmission rates of nanofluids and hybrid nanoliquid have grown as a result of the thermophoresis factor and nanoparticle volume fractions. In comparison to nanofluids, the hybrid nanofluid also possesses a better thermal conductivity.
Computational Solution of Linear Two-Point Boundary Value Problems via Orthonormalization

We discuss algorithmic matters of a computer code for solving linear two-point boundary-value problems. The method of solution uses superposition coupled with an orthonormalization procedure and a variable-step Runge–Kutta–Fehlberg integration scheme. Each time the linearly independent solutions start to lose their numerical independence, the vectors are reorthonormalized before integration proceeds. The underlying principle of the algorithm is then to piece together the intermediate (orthogonalized) solutions, defined on the various subintervals, to obtain the desired solution.
Machine Learning Techniques for Sentiment Analysis of COVID-19-Related Twitter Data

On Twitter, COVID-19 is a highly discussed topic. People worldwide have used Twitter to express their viewpoints and feelings during the pandemic. Previous research has focused on particular topics such as the public’s sentiment during the lockdown, their opinion on governmental measures, or their stance towards COVID-19 vaccines. However, until today, there is no comprehensive overview that presents possible areas of application for sentiment analysis of COVID-19 Twitter data. Therefore, this study reveals how sentiment analysis can provide relevant insights for managing the pandemic by applying a behavioral and social science lens. In this context, our systematic literature review focuses on machine learning-based sentiment analysis techniques and compares the best-performing classification algorithms for COVID-19-related Twitter data. We performed a search in five databases, which are: IEEE Xplore DL, ScienceDirect, SpringerLink, ACM DL, and AIS Electronic Library. This search resulted in 40 papers published between October 2019 and January 2022 that used sentiment analysis to evaluate the public opinion on COVID-19-related topics, which we further investigated. Our research indicates that the best performing models in terms of accuracy are ensemble models that comprise various machine learning classifiers. Especially BERT and RoBERTa models provide the most promising results when fine-tuned on Twitter data. Our study aims to combine machine learning-based sentiment analysis and insights from social and behavioral science to provide decision-makers and public health experts with guidance on the application of sentiment analysis in the fight against the spread of COVID-19.