Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Analysis of Multi-Substrate Materials in Microstrip Antenna Models for Broadband Wireless Communications

Multi-substrate antenna material is a combination of more than one primary antenna base material where this substrate material can determine the quality of antenna performance. A quantitative empirical approach is carried out to achieve maximum performance by processing the dielectric constant of the substrate to obtain other antenna parameters. This aims to increase the stability of the antenna gain and produce a large bandwidth. The results show that diamond has a bandwidth of 75 MHz with a maximum gain of 4.228 dBi and a VSWR of 18.017. While epoxy FR-4 produces a bandwidth of 57 MHz with a maximum gain of 3.444 dBi and a VSWR of 2.011, the quartz material produces a bandwidth of 80 MHz with a maximum gain of 4.426 dBi and a VSWR of 10.884. The conclusion is that FR-4 epoxy substrate performs better than diamond and quartz. It is hoped that the results of this research will impact the development of a smart antenna system.
Power absorption and ferromagnetic resonance in Co-rich metallic glasses

The power absorption of Co-rich metallic glasses in the shape of ribbons and microwires has been measured in the microwave frequency range. The technique employed consists of replacing the dielectric of a coaxial transmission line by the amorphous sample to be measured. The ferromagnetic resonance frequency of the microwires has been obtained by analyzing the absorbed power as a function of an external magnetic field. From the evolution of this resonance frequency, the anisotropy field has been deduced and successfully compared to that obtained from low-frequency hysteresis loops.
Estimating building dimensions from synthetic aperture radar image sequences

The problem of automatically extracting building dimensions from synthetic aperture radar (SAR) image sequences of urban scenes is considered. An algorithm based on the delineation of shadows using active contours constrained by a simple wire-frame building model has been developed and demonstrated using SAR imagery of a village on Salisbury plain. The core of the algorithm is a novel technique for target delineation involving multiple active contours evolving simultaneously. In particular, a technique referred to as multiple hypothesis delineation, in which contours can be in several states simultaneously, is developed and shown to lead to considerable improvement in convergence time and delineation accuracy when used to delineate multiple targets in close proximity. The technique is applied to the automatic estimation of building dimensions by delineation of shadows in a sequence of SAR images of an urban scene. The estimation of building dimensions is automatic; user interaction is limited identifying a building of interest and a region of background clutter close to the building. Results are presented for six different buildings, in each case two SAR images were used in the estimation process separated in illumination angle by either 28° or 90°. The estimates of building dimensions are compared with the actual building dimensions obtained from architectural drawings. The algorithm was found to perform robustly and provide reasonably accurate estimates of the building dimensions, typically within ∼10% of the true values.
The torsion of the group of homeomorphisms of powers of the long line

Abstract By blending techniques from set theory and algebraic topology we investigate the order of any homeomorphism of the nth power of the long ray or long line L having finite order, finding all possible orders when n = 1, 2, 3 or 4 in the first case and when n = 1 or 2 in the second. We also show that all finite powers of L are acyclic with respect to Alexander-Spanier cohomology.
THE INFLUENCE OF NORMAL FLOW BOUNDARY CONDITIONS ON SPURIOUS MODES IN FINITE ELEMENT SOLUTIONS TO THE SHALLOW WATER EQUATIONS

SUMMARY Finite element solutions of the primitive equation (PE) form of the shallow water equations are notorious for the severe spurious 2Ax modes which appear. Wave equation (WE) solutions do not exhibit these numerical modes. In this paper we show that the severe spurious modes in PE solutions are strongly influenced by essential normal flow boundary conditions in the coupled continuity-momentum system of equations. This is demonstrated through numerical examples that avoid the use of essential normal flow boundary conditions either by specifying elevation values over the entire boundary or by implementing natural flow boundary conditions in the weak weighted residual form of the continuity equation. Results from a series of convergence tests show that PE solutions are of nearly the same quality as WE solutions when spurious modes are suppressed by alternative specification of the boundary conditions. Network intercomparisons indicate that varying nodal support does not excite spurious modes in a solution, although it does enhance the spurious modes introduced when an essential normal flow boundary condition is used. Dispersion analysis of discrete equations for interior and boundary nodes offers an explanation of the observed solution behaviour. For certain PE algorithms a mixed situation can arise where the boundary nodes exhibit a monotonic (noise-free) dispersion relationship and the interior nodes exhibit a folded (noisy) dispersion relationship. We have found that the mixed situation occurs when all boundary nodes are specified elevation nodes (which are enforced as essential conditions in the continuity equation) or when specified flow boundary nodes are treated as natural boundary conditions in the continuity equation. In either case the effect is to generate a solution that is essentially free of noise. Apparently, the monotonic dispersion behaviour at the boundaries suppresses the otherwise noisy behaviour caused by the folded dispersion relation on the interior.
PACOSYT: A Passive Component Synthesis Tool Based on Machine Learning and Tailored Modeling Strategies Towards Optimal RF and mm-Wave Circuit Designs

In this paper, the application of regression-based supervised machine learning (ML) methods to the modeling of integrated inductors and transformers is examined. Different ML techniques are used and compared to improve accuracy. However, it is demonstrated that none of the ML techniques considered provided good results unless a smart modeling strategy, tailored to the specific design problem, is used. Taking advantage of these modeling strategies, high accuracy can be obtained when compared to full-wave electromagnetic (EM) simulations (less than 2% error) and experimental measurements (less than 5% error). The most accurate model, obtained by the appropriate combination of an ML technique and modeling strategy, has been integrated into a tool called PACOSYT. The tool uses optimization algorithms to allow the designer to obtain an inductor/transformer with optimal performances in just seconds while keeping the accuracy of EM simulations. Furthermore, the tool provides the passive component S parameter description file for seamless use in circuit simulations. The tool can be used standalone or integrated with design frameworks, like Cadence Virtuoso or AIDASoft, a framework for circuit optimization. To illustrate the different usages of the tool, several passive devices are synthesized, and hundreds of millimeter-wave power amplifiers are synthesized using AIDASoft together with PACOSYT. The tool has been developed using open-source Python frameworks and does not use any closed-source licenses. PACOSYT, which also allows other designers to create their models for different technologies, is made publicly available.
Association between Decreased Estimated Glomerular Filtration Rates and Long-term Mortality in Korean Patients with Acute Myocardial Infarction

A reduced estimated glomerular filtration rate (eGFR) is a predictor for mortality in patients with acute myocardial infarction (AMI). This study aimed to compare mortality according to the GFR and eGFR calculation methods during long-term clinical follow-ups. Using the Korean Acute Myocardial Infarction Registry-National Institutes of Health Data, 13,021 patients with AMI were included in this study. Patients were divided into the surviving (n=11,503, 88.3%) and deceased (n=1,518, 11.7%) groups. Clinical characteristics, cardiovascular risk factors, and 3-year mortality-related factors were analyzed. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations. The surviving group was younger than the deceased group (62.6±12.4 vs. 73.6±10.5 years, p<0.001), whereas the deceased group had higher hypertension and diabetes prevalences than the surviving group. A high Killip class was more frequently observed in the deceased group. eGFR was significantly lower in the deceased group (82.2±24.1 vs. 55.2±28.6 ml/min/1.73 m2, p<0.001). Multivariate analysis revealed that low eGFR was an independent risk factor for mortality during the 3-year follow-up. The CKD-EPI equation was more useful for predicting mortality than the MDRD equation (0.766; 95% confidence interval [CI], 0.753-0.779 vs. 0.738; 95% CI, 0.724-0.753; p=0.001). Decreased renal function was a significant predictor of mortality after 3 years in patients with AMI. The CKD-EPI equation was more useful for predicting mortality than the MDRD equation.
Lightweight vehicle object detection network for unmanned aerial vehicles aerial images

Abstract. Due to the limited computing power of unmanned aerial vehicles (UAVs) and the problems of missed detection and wrong detection of small objects, the current object detection algorithm cannot achieve real-time and high-precision detection. To solve these problems, we propose a vehicle detection network Shuffle CarNet for UAVs aerial images, which is composed of a feature extraction network, a feature fusion network, and a three-scale prediction network. First, according to the limited hardware resources of embedded devices, a lightweight feature extraction network Light CarNet is proposed by fusing the attention mechanism. Second, a four-scale feature bidirectional weighted fusion module is designed. According to the characteristics of the object scale, multilevel feature map bidirectional weighted fusion is selected for target classification and bounding box regression on three scales. Finally, Car-non-maximum suppression is used to reduce false detection and missed detection. Experiments show that compared with other algorithms on the VisDrone-2019 dataset, the proposed method improves the mean average precision by 1.14%, achieves a precision of 82.96%, and can meet the needs of real-time vehicle detection. The superiority of this method is proved by many comparative experiments.
Study of the structural evolutions of crystalline tungsten oxide films prepared using hot-filament CVD

Structural evolutions of tungsten oxide(WO3) samples on different substrates are studied using Raman spectroscopy, scanning electron microscopy, energy dispersive spectroscopy, x-ray diffraction and x-ray photoelectron spectroscopy. The WO3 samples are prepared using hot-filament CVD techniques. The focus of the study is on the evolutions of nano structures at different stages following deposition time. The experimental measurements reveal evolutions of the surface structures from uniform film to fractal-like structures, and eventually to nano particles, and crystalline structures from mono (0 1 0) crystalline thin film to polycrystalline thick film developments. The effect of high temperature on the nanostructured WO3 is also investigated. Well-aligned nanoscale WO3 rod arrays are obtained at a substrate temperature of up to 1400 °C. Further increasing the substrate temperature yields microscale crystalline WO3 particles.
STA1600LN: low-noise 10560 x 10560 pixel high-resolution CCD for astronomy

The demand from the astronomical community for high resolution low noise CCDs has led to the development of the STA1600LN, a 10560 × 10560 pixel, 95mm × 95mm, full-frame CCD imager with 9×9 μ2 pixels. The device improvements include noise reduction to below 3ē at 100kHz, improved quantum efficiency, as well as packaging developments for improved fill factor in mosaic systems. We provide test results from production devices, along with updates on scientific systems utilizing the STA1600 for astronomy.
On-Chip Fast Signal Generation and Low-Power SAR ADC for SiPM Readout

This article presents an ON-chip fast signal generator and a successive-approximation-register (SAR) analog-to-digital data converter (ADC) for silicon photomultiplier (SiPM) readout applications. The high-pass filter (HPF)-based fast-signal generator sharpens the rising edge of the standard SiPM output signal reducing time jitter due to the dark counts of the detector. It is implemented by leveraging the equivalent resistance of the current mirror transistor and the ac-coupling capacitor between the current mirror and the current discriminator to avoid hardware and power consumption overhead. Compared with OFF-chip solutions, the ON-chip approach eliminates the packaging pins and high-speed buffers needed for carrying the fast signals reducing packaging complexity and power consumption of the readout system. The energy quantizer utilizes the SiPM charge integrator as the ADC track-and-hold (T/H) circuit to improve the front-end power efficiency. The fast signal generator and the SAR ADC are implemented in a current-mode application-specific integrated circuit (ASIC) designed in a 0.18- $\mu \text{m}$ CMOS technology. Measurement results show that the ON-chip fast signal generator is effective in improving the timing performance of the readout system. The timing resolutions are measured using SensL’s $3\times $ 3 mm2 SiPM device with a terminal capacitance of 850 pF using an ultrashort laser pulser. Measurement results show that the fast signal generator improves the timing resolution by 23.4% compared with timing measurement using the standard output signal when the output charge is 300 pC. The ASIC achieved a measured ADC signal-to-noise-distortion ratio (SNDR) of 53.08 dB and a spurious-free dynamic range (SFDR) of 62.74 dB at 1 MS/s and a maximum front-end gain nonlinearity of 3.3% over 20–800-pC input charge range while dissipating 4.1 mW of power from a 1.8-V supply.
Type I error in multiple comparison tests in analysis of variance

In a hypothesis test, a researcher initially fixes a type I error rate, that is, the probability of rejecting the null hypothesis given that it is true. In the case of means tests, it is important to present a type I error that is equal to the nominal pre-fixed level, such that this error remains unchanged across various scenarios, including the number of treatments, number of repetitions, and coefficient of variation. The purpose of this study is to analyse and compare the following multiple comparison tests for the control of both conditional and unconditional type I error rates, depending on a significant F-test in the analysis of variance: Tukey, Duncan, Fisher’s least significant difference, Student–Newman–Keuls (SNK), and Scheffé. As an application, we present a motivation study and develop a simulation study using the Monte Carlo method for a total of 64 scenarios. In each simulated scenario, we estimate the comparison-wise and experiment-wise error rates, conditional and unconditional on a significant result of the overall F-test of analysis of variance for each of the five multiple comparison tests evaluated. The results indicate that the application of the means tests based only on the significance of the F-test should be considered when determining the error rates, as this can change them. In addition, we find that Fisher’s test controls for the comparison-wise error rate, the Tukey and SNK tests control for the experiment-wise error rate, and the Duncan and Fisher tests control for the conditional experiment-wise error rate. Scheffé’s test does not control for any of the error rates considered.
Faraday rotation effects of Mn/sup 2+/-modified Tb/sub 2/O/sub 3/-B/sub 2/O/sub 3/ glass in pulsed magnetic field

We present the dynamical Faraday rotation of a terbium metaborate glass (25Tb/sub 2/O/sub 3/-75B/sub 2/O/sub 3/) modified with Mn/sup 2+/ ions using pulsed magnetic fields, which reached up to /spl sim/16 T. The superexchange couplings of Tb/sup 3+/-O/sup 2-/-Tb/sup 3+/ or Tb/sup 3+/-O/sup 2-/-Mn/sup 2+/ were magnetooptically observed at lower temperature. In particular, the enhancement of the Faraday rotation effect was obtained at 15 K with repetitional operation of the 16-T pulsed magnetic fields, resulting in the destruction of the dimer couplings. When the operated glasses were heated back to 300 K, only the Tb/sub 2/O/sub 3/-B/sub 2/O/sub 3/:Mn/sup 2+/ exhibited a significant change in the Faraday rotation.
Coping as a Mediator and Moderator between Psychological Distress and Disordered Eating Behaviors and Weight Changes during the COVID-19 Pandemic

Previous research has already shown the negative impact of the COVID-19 pandemic on college students’ well-being and mental health. Eating problems and weight gain due to changes in eating habits and physical activity experienced during this period have also been noticed. However, few studies have explored the role of students’ resources as used during the COVID-19 pandemic, such as coping strategies. This study aimed to (1) explore the associations among psychological distress, disordered eating, coping strategies, and weight changes; (2) examine the moderating role of coping strategies in the process of weight gain and weight loss; and (3) study the mediating role of coping strategies in the process of weight gain and weight loss. The participants in this study were 772 students at a Portuguese university. The data collected included sociodemographic data and three self-reported questionnaires (Depression, Anxiety, and Stress Scale; Eating Disorder Examination Questionnaire; Brief COPE) during the first few months of the pandemic, which included a 72-day full national lockdown. The results showed that depression, anxiety, stress, and disordered eating were related to increased weight. Guilt, denial, self-distraction, use of substances, and behavior disinvestment were also related to increased weight. Behavioral disinvestment had a strong mediating effect on weight gain. Additionally, planning, positive reframing, and acceptance all showed a moderating effect between psychological distress and weight changes. In conclusion, coping strategies allow for a better understanding of the mechanisms by which psychological distress and disordered eating were related to weight changes during the pandemic.
Boundary conditions for direct computation of aerodynamic sound generation

Computation of the sound field of a free shear flow requires that the Navier Stokes equations be solved using accurate numerical differentiation and time-marching schemes, with nonreflecting boundary conditions. These conditions are modified for use with nonlinear Navier Stokes computations of open flow problems. At an outflow, vortical structures are found to produce large reflections due to non linear effects. An exit zone just upstream of an outflow where disturbances are significantly attenuated through grid stretching and filtering is developed for use with the nonreflecting boundary conditions; Reflections from vortical structures are decreased by 3 orders of magnitude
Toward Memory-Efficient and Interpretable Factorization Machines via Data and Model Binarization

Factorization Machines (FM) is a general predictor that can efficiently model feature interactions in linear time, and thus has been broadly used for regression, classification and ranking tasks. Subspace Encoding Factorization Machine (SEFM) is one of the recent approaches which is proposed to enhance FM’s effectiveness by explicit nonlinear feature mapping for both individual features and feature interactions through equal-width binning per input feature. SEFM, despite its effectiveness, has a major drawback of increasing the memory cost of FM by $b$ times where $b$ is the number of bins adopted for the binning. To reduce the memory cost of SEFM, we propose Binarized FM (BiFM) in which each model parameter takes only a binary value (i.e., 1 or −1) and thus can be efficiently stored using one bit. We derive an algorithm which can learn the proposed FM with binary constraints using Straight Through Estimator (STE) with Adaptive Gradient Descent (Adagrad). For performance evaluation, we compare our proposed methods with a number of baselines based on eight different classification datasets. Our experimental results demonstrated that BiFM can achieve higher accuracy than SEFM at much less memory cost. BiFM also inherits the interpretability property from SEFM, and together with adaptive data binning methods can result in a more compact and interpretable set of classification rules.
Survival and comorbidities in lung cancer patients: Evidence from administrative claims data in Germany

Lung cancer is the most common cancer type worldwide and has the highest and second highest mortality rate for men and women respectively in Germany. Yet, the role of comorbid illnesses in lung cancer patient prognosis is still debated. We analyzed administrative claims data from one of the largest statutory health insurance (SHI) funds in Germany, covering close to 9 million people (11% of the national population); observation period was from 2005 to 2019. Lung cancer patients and their concomitant diseases were identified by ICD-10-GM codes. Comorbidities were classified according to the Charlson Comorbidity Index (CCI). Incidence, comorbidity prevalence and survival are estimated considering sex, age at diagnosis, and place of residence. Kaplan Meier curves with 95% confidence intervals were built in relation to common comorbidities. We identified 70,698 lung cancer incident cases in the sample. Incidence and survival figures are comparable to official statistics in Germany. Most prevalent comorbidities are chronic obstructive pulmonary disease (COPD) (36.7%), followed by peripheral vascular disease (PVD) (18.7%), diabetes without chronic complications (17.4%), congestive heart failure (CHF) (16.5%) and renal disease (14.7%). Relative to overall survival, lung cancer patients with CHF, cerebrovascular disease (CEVD) and renal disease are associated with largest drops in survival probabilities (9% or higher), while those with PVD and diabetes without chronic complications with moderate drops (7% or lower). The study showed a negative association between survival and most common comorbidities among lung cancer patients, based on a large sample for Germany. Further research needs to explore the individual effect of comorbidities disentangled from that of other patient characteristics such as cancer stage and histology.
The origin of non-Drude terahertz conductivity in nanomaterials

The Drude-Smith (DS) model hitherto has been a well accepted model for the terahertz conductivity of nanomaterials, even though its physical basis is not clear. It is shown that a series sequence of transport involving grains and grain boundaries produces a Lorentzian-type energy loss and dominates the THz conductivity in nanomaterials, which is able to explain both the real and imaginary parts of the conductivity. The present model represents a completely different point of view than the standard Drude-Smith model.
Hyperspectral image acquisition and analysis of skin

Hyperspectral imaging of skin combines the spectral information of diffuse reflectance spectroscopy with the spatial information of 2D imaging. Skin chromophore maps can be reconstructed in which features such as pigmented lesions, diffuse and localized erythema, areas of increased blood stasis, etc. could be identified and the relative parameters quantified. Hyperspectral imaging is the only reliable method to produce a quantitative distribution map of chromophores contributing to the color appearance of the skin.