Miracle-dz/UniFAR-FTUs huggingface dataset:
A Frequency-Reconfigurable Dielectric Resonator Antenna With a Water Layer

This letter introduces a frequency-reconfigurable dielectric resonator antenna (DRA) with water layer integration. The proposed method is based on the strategy combination of mode reconfiguration and dielectric loading. First, the frequency band of the DRA is reconfigured between the resonant frequencies of the fundamental <inline-formula><tex-math notation="LaTeX">$TE_{111}^y$</tex-math></inline-formula> and quasi-<inline-formula><tex-math notation="LaTeX">$TE_{113}^y$</tex-math></inline-formula> modes by flowing liquid control of water pumping in and out of the microfluidic cavity. Then, the frequency response of quasi-<inline-formula><tex-math notation="LaTeX">$TE_{113}^y$</tex-math></inline-formula> mode is continuously swept by altering the thickness of water layer. For demonstration, the DRA is designed with a solid dielectric material of K9 glass with the permittivity of 6.25 and loaded with a layer of fresh water with the permittivity of 77. Finally, the proposed antenna is fabricated and measured, which performs with a wideband reconfigurability and stable far-field performance corresponding to the different frequency responses.
Improving robustness in multiscale methods

An important constraint on our ability to simulate physical processes numerically is our ability to solve the resulting linear systems. Multiscale methods, such as multigrid, provide optimal or near-optimal order solution techniques for a wide range of problems. Current multigrid methods (both geometric and algebraic) rely on the use of effective coarse-scale operators to achieve this efficiency. Classical geometric multigrid methods construct these operators based on the geometry of a given problem and are, thus, most effective when this geometry is known and simple. Algebraic multigrid methods are free from most geometric constraints, instead relying on assumptions about the character of the matrix that limit the applicability of such methods to a relatively small class of problems. In this thesis, we first study the applicability of multigrid methods to the problem of flow through porous media, particularly motivated by the size of the linear systems resulting from discretization. For such problems, it is well known how to construct effective coarse-scale models for a correction-based multigrid method. For these robust multigrid solvers, we consider whether sufficient information is contained in the multigrid hierarchy to allow for efficient approximation of solutions of these linear systems. In particular, we examine important properties of the coarse-scale operators and the solutions to these coarse-scale equations and demonstrate their relevance to both the fine-scale and continuum-scale models. Additionally, we consider the question of improvements to multigrid algorithms in the form of adaptivity or self-correction. By utilizing the multigrid method itself to expose slow-to-converge components, we may adapt the multigrid hierarchy in order to improve performance, resulting in improved efficiency for a new class of problems. We present results for both the classical algebraic multigrid and smoothed aggregation frameworks illustrating typical multigrid efficiency with fewer assumptions on the given matrix systems. We consider theoretical issues of this adaptive procedure in the reduction-based algebraic multigrid setting.
Second Order Efficiency of the MLE with Respect to any Bounded Bowl-Shape Loss Function

Let X 1 , X 2 , . be a sequence of i.i. d. random variables, each having density f(x, θ 0 ) where {f(x, θ)} is a family of densities with respect to a dominating measure µ. Suppose n ½ (θˆ - θ) and n ½ (T - θ), where θˆ is the mle and T is any other efficient estimate, have Edgeworth expansions up to o(n -1 ) uniformly in a compact neighbourhood of θ 0 . Then (under certain regularity conditions) one can choose a function c(θ) such that θˆ = θˆ + c(θˆ)/n satisfies Pθ 0 {-x 1 < n ½ (θˆ' - θ 0 )(I(θ 0 )) ½ < x 2 } > Pθ 0 {-x 1 ½ (T - θ 0 )(I(θ 0 )) ½ 2 } + o(n -1 ), for all x 1 , x 2 > 0. This result implies the second order efficiency of the mle with respect to any bounded loss function Ln(θ, a) = h(n ½ (a - θ)), which is bowl-shaped i.e., whose minimum value is zero at a - θ = 0 and which increases as |a - θ| increases. This answers a question raised by C. R. Rao (Discussion on Professor Efron's paper).
Transnational migration and dual citizenship: The conundrum of social and economic rights of dual citizens in Pakistan

Pakistan is among the Asian countries which permits dual citizenship. However, the dual citizenship privileges availed by overseas-based Pakistanis spark intense debate making Pakistani dual citizens and their entitlements a contested subject in the country. A qualitative study was conducted in the city of Rawalpindi asking what the attitudes of Pakistani citizens on dual citizenship are, as well as their positions on the rights of dual citizens with regard to education, employment and property ownership in Pakistan. In-depth interviews were conducted with two groups of interviewees: 25 Pakistani citizens and 18 Pakistani dual citizens. The findings suggest that Pakistani citizens resist the unconditional provision of socio-economic rights to Pakistani dual citizens considering their “split loyalties. ” Most of the respondents argued against their employment in sensitive institutions such as the armed forces and judiciary, however, their right to education and property acquisition was supported in circumstances when it benefits Pakistan’s development. The perspectives of dual citizens also reflect ambivalence over how to resolve the allegiance conundrum and as a result, display divergent views on their privileges and rights in their home country.
Release of a viscous power-law fluid over an inviscid ocean

Abstract We consider the two- and three-dimensional spreading of a finite volume of viscous power-law fluid released over a denser inviscid fluid and subject to gravitational and capillary forces. In the case of gravity-driven spreading, with a power-law fluid having strain rate proportional to stress to the power $n$, there are similarity solutions with the extent of the current being proportional to ${t}^{1/ n} $ in the two-dimensional case and ${t}^{1/ 2n} $ in the three-dimensional case. Perturbations from these asymptotic states are shown to retain their initial shape but to decay relatively as ${t}^{\ensuremath{-} 1} $ in the two-dimensional case and ${t}^{\ensuremath{-} 3/ (n+ 3)} $ in the three-dimensional case. The former is independent of $n$, whereas the latter gives a slower rate of relative decay for fluids that are more shear-thinning. In cases where the layer is subject to a constraining surface tension, we determine the evolution of the layer towards a static state of uniform thickness in which the gravitational and capillary forces balance. The asymptotic form of this convergence is shown to depend strongly on $n$, with rapid finite-time algebraic decay in shear-thickening cases, large-time exponential decay in the Newtonian case and slow large-time algebraic decay in shear-thinning cases.
Identifiability and Estimation of Causal Effects by Principal Stratification With Outcomes Truncated by Death

In medical studies, there are many situations where the final outcomes are truncated by death, in which patients die before outcomes of interest are measured. In this article we consider identifiability and estimation of causal effects by principal stratification when some outcomes are truncated by death. Previous studies mostly focused on large sample bounds, Bayesian analysis, sensitivity analysis. In this article, we propose a new method for identifying the causal parameter of interest under a nonparametric and semiparametric model. We show that the causal parameter of interest is identifiable under some regularity assumptions and the assumption that there exists a pretreatment covariate whose conditional distributions among two principal strata are not the same, but our approach does not need the assumption of a mixture normal distribution for outcomes as required by Zhang, Rubin, and Mealli (2009). Hence, the proposed method is applicable not only to a continuous outcome but also to a binary outcome. When some of the assumptions are violated, we discuss biases of estimators and propose methods to reduce these biases. We conduct several simulation studies to evaluate the finite-sample performance of the proposed approach. Finally, we apply the proposed approach to a real dataset from a Southwest Oncology Group (SWOG) clinical trial.
THE FREQUENCY OF SN IA IN GALAXIES OF DIFFERING HUBBLE TYPE

found to be an order of magnitude higher in late-type spirals than it is in early-type galaxies. Presently available data also suggest, but do not yet prove, that the SN Ia rate in amorphous/I0 galaxies may be even higher than it is in normal late-type spirals. These results might be accounted for by assuming that the rate at which intermediate-age binaries containing white dwarfs evolve into SN Ia is much higher than that for old white-dwarf binaries. The implications of this result for the evolution of elliptical galaxies are briefly discussed.
High-Performance Near-Infrared Photodetector Based on PbS Colloidal Quantum Dots/ZnO-Nanowires Hybrid Nanostructures

Quantum dots have found significant applications in photoelectric detectors due to their unique electronic and optical properties, such as tunable bandgap. Recently, colloidal quantum dots (CQDs) have attracted much interest because of the ease of controlling the dot size and low production cost. In this paper, a high-performance ZnO/PbS heterojunction photodetector was fabricated by spin-coating PbS CQDs onto the surface of a hydrothermally grown vertical array of ZnO nanowires (NWs) on an indium tin oxide (ITO) substrate. Under 940 nm near-infrared light illumination, the device demonstrated a responsivity and detectivity of ~3.9 × 104 A/W and ~9.4 × 1013 Jones, respectively. The excellent performances and low cost of this nanocomposite-based photodetector show that it has the potential for widespread applications ranging from medical diagnosis to environmental monitoring.
Strengthened fixed point property and products in ordered sets

Strengthened fixed point property for ordered sets is formulated. It is weaker than the strong fixed point property due to Duffus and Sauer and stronger than the product property meaning that A × Y has the fixed point property whenever A has the former and Y has the latter. In particular, doubly chain complete ordered sets with no infinite antichain have the strengthened fixed point property whenever they have the fixed point property, which yields a transparent proof of the well-known theorem saying that doubly chain complete ordered sets with no infinite antichain have the product property whenever they have the fixed point property. The new proof does not require the axiom of choice.
Scaling the Inference of Digital Pathology Deep Learning Models Using CPU-Based High-Performance Computing

Digital pathology whole-slide images (WSIs) are large-size gigapixel images, and image analysis based on deep learning artificial intelligence technology often involves pixelwise testing of a trained deep learning neural network (DLNN) on hundreds of WSI images, which is time-consuming. We take advantage of high-performance computing (HPC) facilities to parallelize this procedure into multiple independent (and hence delightfully parallel) tasks. However, traditional software parallelization techniques and regular file formats can have significant scaling problems on HPC clusters. In this work, a useful computational strategy is designed to localize and extract relevant patches in WSI files and group them in Hierarchical Data Format version 5 files well suited for parallel I/O. HPC's array job facilities are adapted for hierarchical scaling and parallelization of WSI preprocessing and testing of trained algorithms. Applying these techniques to testing a trained DLNN on the CAMELYON datasets with 399 WSIs reduced the theoretical processing time of 18 years on a single central processing unit (CPU) or 30 days on a single graphics processing unit to less than 45 h on an HPC cluster of 4000 CPU cores. The efficiency–accuracy tradeoff we demonstrated on this dataset further reinforced the importance of efficient computation techniques, without which accuracy may be sacrificed. The framework developed here for testing DLNNs does not rely on any specific neural network architecture and HPC cluster setup and can be utilized for any large-scale image processing and big-data analysis.
Pressure Drop Distribution in Smooth and Rib Roughened Square Channel with Sharp 180° Bend in the Presence of Guide Vanes

An experimental investigation is carried out to study the effect of several turn treatments like single guide vane (short and long) and multiple guide vanes on the pressure drop distribution in smooth and rib roughened square channels with a sharp 180 ◦ bend. The sharp 180 ◦ turn is obtained by dividing a rectangular passage into two square channels using a divider wall with a rounded tip at the location where the flow negotiates the turn. In rib roughened channels, ribs are configured on the top and bottom surfaces in a symmetric arrangement with an angle of 90 ◦ to the mainstream flow. Rib height-to-hydraulic diameter ratio (e/D) is maintained constant at 0.14 with a constant pitch-to-rib height ratio (P/e) of 10. The pressure drop distribution normalized with the mainstream fluid dynamic pressure head is presented for the outer surfaces. Results suggest that 90 ◦ multiple guide vanes result in the decrease of overall pressure drop by around 40% in smooth square channels. However, a reduction in overall pressure drop by only 15% is achievable through guide vanes in rib roughened square channels.
FULL-RANGE SOLUTION FOR THE MEASUREMENT OF THIN-FILM SURFACE DENSITIES WITH PROTON-EXCITED X RAYS.

A Fredholm‐integral expression for characteristic x‐ray production by proton bombardment is developed relating multicomponent elemental thin‐film concentration profiles to proton‐stopping power, x‐ray‐production cross section, and x‐ray attenuation. The thickness of Al2O3 and Ta2O5 films on their respective metallic substrates were measured with 20‐ to 80‐keV protons with an accuracy of 5% for thick films (1200 A) and 25% for thinner films (30 A). Nonlinear regression analysis of the data indicated that all parameters of interest, including the zero‐voltage anodization potential, can be determined from the raw data. With exception to the oxygen K‐shell x‐ray attenuation coefficient, the parameters were determined with good to reasonable accuracy. A general concentration profile could not be determined by numerical methods as a result of insufficient variation in the kernel of the integral equation.
On the IMC-based synthesis of the feedback block of ISA PID regulators

This paper presents and analyses a method for synthesizing the feedback block of a 2-d.o. f. real PID regulator, referring to the widely used ISA structure and particularly well suited for auto-tuning. A rigorous stability, performance, robustness and consistency analysis is provided, extending some results of the previous literature. An objective criterion is devised for selecting the method’s (single) design parameter based on the process model employed and an overestimate of the corresponding process/model mismatch. Both simulation and practical application examples are reported.
Assessment of Pulmonary Functions and Dysfunctions in Type II Diabetes Mellitus: A Comparative Cross-Sectional Study

Background Diabetes mellitus causes microvascular complications in the eyes and kidneys as well as the nervous system, among other parts of the body. Lungs are a potential target organ for diabetic microvascular complications and remain the least researched among diabetic patients. The aim of this study was to explore whether there is any difference in pulmonary functions in patients with diabetes mellitus compared to those without. Methodology A comparative cross-sectional study was conducted on 50 participants each with and without type II diabetes mellitus. Pulmonary function parameters, including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), FEV1 as a percentage of FVC in percentage (FEV1%), peak expiratory flow rate in L/second (PEFR), forced expiratory flow rate in L/second in 25% of FVC (FEF25%), forced expiratory flow rate in L/second in 50% of FVC (FEF50%), forced expiratory flow rate in L/second in 75% of FVC (FEF75%), forced expiratory flow rate during 25-75% of expiration (FEF25-75%), and maximal voluntary ventilation (MVV), of both groups were analyzed using the NDD Large True Flow (Easy One) spirometer (NDD Meditechnik AG., Switzerland). A fully automated chemistry analyzer and linear chromatography were used for glycemic control measurements. Results All pulmonary function test parameter values were lower in participants with diabetes mellitus compared to those without, except FEV1% and PEFR, which indicates a mixed pattern of lung dysfunction. FVC had a significant negative correlation with the duration of diabetes (r = -0.299, p = 0.034). Conclusions Type II diabetes mellitus patients had significant dysfunction in pulmonary functions with early involvement of restrictive parameters which can be monitored/diagnosed by regularly following up patients by measuring pulmonary functions, and, hence, can be taken care of.
A Comparison of Variance Components Estimators Using Balanced Versus Unbalanced Data

1. The authors of the problem require a(xx) to be measurable in the statement of their problem, but in their solution, which uses arguments similar to those given by Potzelberger, show that a(jr,) degenerate is, in fact, a necessary and sufficient condition. A proof, which did not completely pick up the error, but is otherwise interesting, has been submitted by M. Rahaman and S.K. Samanta (Trenton State College, USA).
Terahertz pulsed spectroscopic imaging using optimized binary masks

We report the development of a terahertz pulsed spectroscopic imaging system based on the concept of compressive sensing. A single-point terahertz detector, together with a set of 40 optimized two-dimensional binary masks, was used to measure the terahertz waveforms transmitted through a sample. Terahertz time- and frequency-domain images of the sample comprising 20×20 pixels were subsequently reconstructed. We demonstrate that both the spatial distribution and the spectral characteristics of a sample can be obtained by this means. Compared with conventional terahertz pulsed imaging, no raster scanning of the object is required, and ten times fewer terahertz spectra need be taken. It is therefore ideal for real-time imaging applications.
Analyzing Out-of-Domain Generalization Performance of Pre-Trained Segmentation Models

Artists illustrate objects to various degrees of complexity. As the amount of detail or the similarity to reality of a depiction decreases, the object tends to be reduced to its simplest, most relevant higher-level features (Harrison, 1981). One of the reasons Deep Neural Networks (DNN) may fail to identify objects in an image is that models are unable to recognize the order of importance of features such as shape, depth, or color within an image, which means even the most minute distortions of pixels within an image that would be imperceptible to humans would greatly impact the performance of the object detection models (Eykholt et al., 2018). However, by training DNN on artworks where the most prominent features defining specific objects are emphasized, perhaps a model can be made to be more resilient against small-scale changes in an image. In this paper, the correlation between the level of similarity to reality of images and artworks of an object and the accuracy of object detection models is investigated to test the ability of object detection models in identifying the most salient features of a particular object. The results of this report can help outline the efficacy of models only trained on real images in identifying increasingly abstract artworks that have simplified an object to its most prominent features. The experiment shows that the accuracies of models decrease as the images or illustrations provided become more abstract or simplified, which suggests the higher level features that identify a particular object are different in object detection models and humans.
Multi-omics analysis reveals genomic, clinical and immunological features of SARS-CoV-2 virus target genes in pan-cancer

The SARS-CoV-2 virus, also known as the severe acute respiratory syndrome coronavirus 2, has raised great threats to humans. The connection between the SARS-CoV-2 virus and cancer is currently unclear. In this study, we thus evaluated the multi-omics data from the Cancer Genome Atlas (TCGA) database utilizing genomic and transcriptomic techniques to fully identify the SARS-CoV-2 target genes (STGs) in tumor samples from 33 types of cancers. The expression of STGs was substantially linked with the immune infiltration and may be used to predict survival in cancer patients. STGs were also substantially associated with immunological infiltration, immune cells, and associated immune pathways. At the molecular level, the genomic changes of STGs were frequently related with carcinogenesis and patient survival. In addition, pathway analysis revealed that STGs were involved in the control of signaling pathways associated with cancer. The prognostic features and nomogram of clinical factors of STGs in cancers have been developed. Lastly, by mining the cancer drug sensitivity genomics database, a list of potential STG-targeting medicines was compiled. Collectively, this work demonstrated comprehensively the genomic alterations and clinical characteristics of STGs, which may offer new clues to explore the mechanisms on a molecular level between SARS-CoV-2 virus and cancers as well as provide new clinical guidance for cancer patients who are threatened by the COVID-19 epidemic.
Eight Weeks of High-Intensity Interval Training Using Elevation Mask May Improve Cardiorespiratory Fitness, Pulmonary Functions, and Hematological Variables in University Athletes

Background: In the last two decades, high-altitude training (HAT) and elevation training masks (ETMs) have been widely used among athletes to enhance physical performance. However, few studies have examined the effect of wearing ETMs on physiological and hematological parameters in different sports. Aims: The present study aimed to investigate the impact of ETM use in athletes on several hematological and physiological indicators among cyclists, runners, and swimmers. Methods: The impact of wearing an ETM on lung function (LF), aerobic capacity (AC), and hematological levels in male university-level athletes (cyclists, runners, and swimmers) was investigated using an experimental approach. The participants (N = 44) were divided into (i) an experimental group wearing ETMs (n = 22; aged 21.24 ± 0.14 years old) and (ii) a control group not wearing ETMs (n = 22; aged 21.35 ± 0.19 years old). Both groups underwent 8 weeks of high-intensity cycle ergometer interval training. Pre- and post-training tests included the above-mentioned physiological and hematological parameters. Results: Except for FEV₁, FEV₁/FVC, VT1, and MHR in the control group and FEV₁/FVC and HRM in the experimental group, all variables were significantly improved after the 8-week cycle ergometer HIIT program. Significant benefits in favor of the experimental group were noted in terms of changes in FVC, FEV₁, VO₂max, VT1, PO to VT, VT2, and PO to VT2. Conclusions: The eight-week ETM-assisted HIIT program improved cardiorespiratory fitness and hematological variables in all participants. Future research would be useful to further investigate the physiological changes resulting from ETM-assisted HIIT programs.