Miracle-dz/UniFAR-FTUs huggingface dataset:
Burden, depression and fatigue in caregivers of lung transplantation candidates

Objective: A great deal of social support is often provided by the caregiver of the patient. The purpose of this study is to evaluate the burden, fatigue and depression of the primary caregiver of patients with pulmonary transplantation candidates. Patients and Method: The primary caregivers of patients who were admitted to our hospital’s pulmonary transplant outpatient clinic with end-stage pulmonary disease and no definite contraindications for transplantation, were included in the study. Zarit Burden Scale, Beck Depression Inventory and Short-Form (SF)-36 – Vitality questionnaires were applied to participants. Results: Thirty-nine patients and their caregivers were evaluated. Caregivers experienced low levels of depression. Mean score for Beck Depression Inventory was 12.7±10.1. Caregivers generally experienced medium levels of burden. Mean score for Zarit Burden Scale was 26.9±14.2. Majority of caregivers experienced clinically significant fatigue. Mean score for SF-36 – Vitality was 61±16.7. Zarit Burden Scale scores and Beck Depression Inventory scores showed a statistically significant positive correlation (r:0.962 p
Geon Type Solutions of the Nonlinear {Heisenberg-Klein-Gordon} Equation

As a model for a "unitary" field theory of extended particles we consider the nonlinear Klein-Gordon equation\char22{}associated with a "squared" Heisenberg-Pauli-Weyl nonlinear spinor equation\char22{}coupled to strong gravity. Using a stationary spherical ansatz for the complex scalar field as well as for the background metric generated via Einstein's field equation, we are able to study the effects of the scalar self-interaction as well as of the classical tensor forces. By numerical integration we obtain a continuous spectrum of localized, gravitational solitons resembling the geons previously constructed for the Einstein-Maxwell system by Wheeler. A self-generated curvature potential originating from the curved background partially confines the Schr\"odinger-type wave functions within the "scalar geon. " For zero-angular-momentum states and normalized scalar charge the spectrum for the total gravitational energy of these solitons exhibits a branching with respect to the number of nodes appearing in the radial part of the scalar field. Preliminary studies for higher values of the corresponding "principal quantum number" reveal that a kind of fine splitting of the energy levels occurs, which may indicate a rich, particlelike structure of these "quantized geons. "
Aero-Acoustic Modelling using Large Eddy Simulation

The splitting technique for aero-acoustic computations is extended to simulate three-dimensional flow and acoustic waves from airfoils. The aero-acoustic model is coupled to a sub-grid-scale turbulence model for Large-Eddy Simulations. In the first test case, the model is applied to compute laminar flow past a NACA 0015 airfoil at a Reynolds number of 800, a Mach number of 0.2 and an angle of attack of 20°. The model is then applied to compute turbulent flow past a NACA 0015 airfoil at a Reynolds number of 100 000, a Mach number of 0.2 and an angle of attack of 20°. The predicted noise spectrum is compared to experimental data.
Miniaturized Aperture Dual-Polarized Folded-dipole Antenna

This article presents a miniaturized aperture dual-polarized folded-dipole antenna. The aperture is reduced by loading vertical metal columns (VMCs) in the four corners of the horizonal square radiator. At the same time, the impedance matching of the antenna with VMCs (VMC-ant) can be improved. Simulated results show that the proposed antenna can operate from 1.7 to 2.3 GHz with VSWRs $< \mathbf{1}. \mathbf{5}$. Stable antenna gain (about 7.8 dBi) is also achieved over the entire operating frequency band. Furthermore, the size of the proposed antenna is $\mathbf{0}. \mathbf{253}\boldsymbol{\lambda}_{\mathbf{0}}\times \mathbf{0}. \mathbf{253}\boldsymbol{\lambda}_{\mathbf{0}}\times \mathbf{0}. \mathbf{253}\boldsymbol{\lambda}_{\mathbf{0}}$ ($\boldsymbol{\lambda}_{\mathbf{0}}$ is the free-space wavelength at 2GHz). This design approach may provide a feasible solution to realize miniaturized aperture of antenna.
Indoor Localization Using Reflection Paths Under Non-Line-of-Sight Environments

At present, most mature localization technologies are based on the line-of-sight (LoS) environment. However, many human activities occur in the indoor non-line-of-sight (NLoS) environment, and thus localization in this challenging environment is also indispensable. In addition, the localization using a single access point (AP) is more suitable for limited space, such as shopping malls and teaching buildings. Therefore, it is of great significance to study the localization technology of single AP in indoor NLoS environments. This paper proposes a localization algorithm to solve this difficult problem based on the natural reflection path, which can associate the locations of the target, scatterer, and AP. Firstly, the localization model is constructed based on the angle-of-departure ($A$oD), angle-of-arrival (AoA), and relative-time-of-flight (rToF) of the natural reflection path. Unlike absolute time-of-flight (ToF), rToF can eliminate synchronization errors. Then, we derive the closed form solution of the target location, and the least square (LS) algorithm is used to solve the target location. Finally, we use the commercial-grade ray-tracing simulation software to conduct the experiments. Simulation results show that the algorithm can achieve high localization accuracy with only a few natural reflection paths.
Listeria monocytogenes, Escherichia coli and Coagulase Positive Staphylococci in Cured Raw Milk Cheese from Alentejo Region, Portugal

Traditional cheeses are part of the Portuguese gastronomic identity, and raw milk of autochthonous species is a common primary ingredient. Here, we investigated the presence of Listeria monocytogenes, Coagulase Positive Staphylococci (CPS) and pathogenic Escherichia coli, as well as of indicator microorganisms (E. coli and other Listeria spp.) in 96 cured raw milk cheeses from the Alentejo region. Whole genome sequencing (WGS) of pathogenic E. coli and Listeria spp. as well as antimicrobial resistance (AMR) screening of E. coli isolates was also performed. L. monocytogenes, CPS > 104 cfu/g and Extraintestinal E. coli were detected in 15.6%, 16.9% and 10.1% of the samples, respectively. Moreover, L. monocytogenes > 102 cfu/g and Staphylococcal enterotoxins were detected in 4.2% and 2.2% of the samples, respectively. AMR was observed in 27.3% of the E. coli isolates, six of which were multidrug resistant. WGS analysis unveiled clusters of high closely related isolates for both L. monocytogenes and L. innocua (often correlating with the cheese producer). This study can indicate poor hygiene practices during milk collection/preservation or during cheese-making procedures and handling, and highlights the need of more effective prevention and control measures and of multi-sectoral WGS data integration, in order to prevent and detect foodborne bacterial outbreaks.
MXene-Based Nanomaterials for Multifunctional Applications

MXene is becoming a “rising star” material due to its versatility for a wide portfolio of applications, including electrochemical energy storage devices, electrocatalysis, sensors, biomedical applications, membranes, flexible and wearable devices, etc. As these applications promote increased interest in MXene research, summarizing the latest findings on this family of materials will help inform the scientific community. In this review, we first discuss the rapid evolutionary change in MXenes from the first reported M2XTx structure to the last reported M5X4Tx structure. The use of systematically modified synthesis routes, such as foreign atom intercalation, tuning precursor chemistry, etc., will be further discussed in the next section. Then, we review the applications of MXenes and their composites/hybrids for rapidly growing applications such as batteries, supercapacitors, electrocatalysts, sensors, biomedical, electromagnetic interference shielding, membranes, and flexible and wearable devices. More importantly, we notice that its excellent metallic conductivity with its hydrophilic nature distinguishes MXene from other materials, and its properties and applications can be further modified by surface functionalization. MXene composites/hybrids outperform pristine MXenes in many applications. In addition, a summary of the latest findings using MXene-based materials to overcome application-specific drawbacks is provided in the last few sections. We hope that the information provided in this review will help integrate lab-scale findings into commercially viable products.
Accuracy of atmospheric trends inferred from the Halogen Occultation Experiment data

The Halogen Occultation Experiment (HALOE) operated in orbit for over 14 years, providing high quality measurements from the upper troposphere into the lower thermosphere. Since the quality of this data set depended on the long-term stability of the instrument, a series of analysis tests were designed to routinely monitor instrument performance. These tests evaluated possible changes in the gas cells, electronic gains, optical performance, and signal temperature dependencies. The gas cell stability was determined from an analysis of the Doppler shift signature in retrieved mixing ratios. Electronic gain stability was determined by instrument scans of the solar disk, each with different balance settings. Optical and tracking performance was also determined from solar scan data. The only statistically significant changes detected were: 1. a small methane gas cell change, causing less than 0.5% per decade change in retrieved methane, and 2. a small optical alignment change in the HF channel that only affects HF results below 25 kilometers. These detailed analyses indicate that the HALOE instrument remained stable throughout the mission, adding confidence to the long-term atmospheric trends deduced from HALOE products.
Short‐Time Spectrum and “Cepstrum” Techniques for Vocal‐Pitch Detection

A spectrum analyzer based on a definition of short‐time power spectra has been designed and simulated on a digital computer. The analyzer is primarily intended for use in speech analysis. It has been designed to operate in real time, and to produce high‐resolution spectra without utilizing either heterodyning methods or bandpass filter banks. The logarithm of each consecutive amplitude spectrum thus obtained can be used as the input to a second similar spectrum analyzer. The output of this analyzer is then the “cepstrum” or power spectrum of the logarithm spectrum. The cepstrum of a speech signal has a peak corresponding to the fundamental period for voiced speech but no peak for unvoiced speech. Thus, a cepstrum analyzer can function both as a pitch and as a voiced‐unvoiced detector. Cepstral pitch detection has the important advantages that it is insensitive to phase distortion, and is also resistant to additive noise and amplitude distortion of the speech signal. The method does not require the presence of the fundamental frequency in the speech signal, and will give several separate cepstral peaks if several different pitch periods are present. Cepstral techniques appear to be even more reliable and efficient than visual methods for pitch detection. The short‐time spectrum and cepstrum analyzers described in this paper were simulated by a sampled‐data system on an IBM‐7090 digital computer. The simulation was programmed with the assistance of a special block‐diagram compiler.
Love Addiction, Adult Attachment Patterns and Self-Esteem: Testing for Mediation Using Path Analysis

Love addiction is a dysfunctional relational modality that takes on the addiction characteristics and which, for the individuals who suffer from it, can have a negative and pervasive impact on various areas of functioning. The objective of this research was the analysis the factors that can be associated with love addiction, particularly focusing on adult attachment patterns and self-esteem. A sample group of 300 individuals who declared themselves to have a romantic relationship was involved in this research (Mage = 37.83 years, SD = 12.937). They completed an online survey including the Love Addiction Inventory—Short form, Relationship Questionnaire, and Rosenberg Self-Esteem Scale. Results showed significant and positive associations between preoccupied and fearful adult attachment and love addiction. Furthermore, these relationships were totally mediated by self-esteem. Gender and age were controlled as potential covariates and showed significant effects in influencing the levels of self-esteem and love addiction. Such findings may provide useful information for orienting future research and supporting an effective clinical practice.
Metformin Directly Binds to MMP-9 to Improve Plaque Stability

Vulnerable atherosclerotic plaque rupture is the principal mechanism that accounts for myocardial infarction and stroke. High matrix metalloproteinase-9 (MMP-9) expression and activity have been proven to lead to plaque instability. Metformin, a first-line treatment for type 2 diabetes, is beneficial to plaque vulnerability. However, the mechanism underlying its anti-atherogenic effect remains unclear. Molecular docking and surface plasmon resonance experiments showed that metformin directly interacts with MMP-9, and incubated MMP-9 overexpressing HEK293A cells with metformin (1 μmol·L−1) significantly attenuates MMP-9’s activity using zymography and MMP activity assays. Moreover, metformin treatment drives MMP-9 degradation. Next, we constructed a carotid artery atherosclerotic plaque model and administered consecutive 14-day metformin (200 mg·kg−1·d−1) treatment by intragastric gavage. Immunofluorescence staining of the right carotid common artery and serum MMP activity assay results showed that metformin treatment decreased local plaque MMP-9 protein level and circulating MMP-9 activity, respectively. Histochemical staining revealed that after metformin treatment, the collagen content in plaque was significantly preserved, and the plaque vulnerability index decreased. These findings suggested that metformin improved atherosclerotic plaque stability by directly binding to MMP-9 and driving its degradation.
Roles of donor and acceptor nanodomains in 6% efficient thermally annealed polymer photovoltaics

The authors have fabricated thin film polymer photovoltaics using 1-(3-methoxycarbonyl)propyl-1-phenyl-(6,6)C61 within regioregular poly(3-hexylthiophene) bulk heterojunction absorbing layers. Using thermal annealing at temperatures approaching the glass transition temperature, they have examined the formation of nanodomains within the matrix. These domains modify charge transport pathways in such a way as to allow for the efficient use of thicker absorbing layers. This results in a nearly 20% gain in overall performance for this polymer system with external power efficiencies exceeding 6%.
A Frequency-Tunable Rat-Race Coupler With Improved Performance

Based on the design method of port equivalent impedance, a reconfigurable rat-race coupler with better performance is designed in this paper. First of all, on the premise of selecting the four-port network, the port equivalent impedance is obtained according to matching and isolation conditions. In addition, design a frequency reconfigurable matching network (MN) to match the port equivalent impedance to the port impedance across the entire frequency range. Last, by connecting the MN to the four ports, the adjustable operating frequency of the rat-race coupler is realized. This design method can simplify the coupler design. In order to verify the above proposed design method of reconfigurable coupler based on port equivalent impedance, we designed and measured a frequency reconfigurable rat-race coupler. The measured results show that the working frequency of the proposed coupler is continuously adjustable from 0.82 GHz to 2.26 GHz. In addition, the return loss and isolation are always better than 21 dB in the working frequency range of the coupler. Compared with similar couplers, the main advantage of this coupler is its superior performance over a comparable frequency adjustment range.
An Automated Short-Period Surface-Wave Detection Algorithm

We describe an automated short-period Rayleigh wave ( Rg ) detector designed to work on local (<2.5° epicentral distance) events recorded at three- component stations. The detector was modeled after an automatic 17- to 22-sec Rayleigh-wave detection method; however, we have modified the algorithms for local distance and short-period applications. We have tested the detector on a well-located cluster of mining events from central India and on a set of ground-truth events in the area. The Rg detector was also integrated into a semiautomatic event detection and location algorithm and applied on continuous data. Fourier and wavelet-based methods are evaluated for prefiltering. We observe that sample standard deviations of backazimuth estimates using the Rg detector, after wavelet prefiltering, are comparable to fk 3C P backazimuth estimates from event clusters. Our results indicate that using the Rg -phase backazimuths for event location is a promising alternative to using small signal-to-noise ratio first-arrival backazimuths. We recommend wavelet prefiltering versus Fourier prefiltering because it is more consistent for the detection of low signal-to-noise ratio events at local distances.
Various design techniques to reduce cogging torque by controlling energy variation in permanent magnet motors

Using energy method, this paper analytically reveals that the cogging torque can be reduced by controlling N/sub L/th harmonic components of the square of airgap permeance function and flux density function, where N/sub L/ denotes the least common multiple of number of poles and number of slots. As for design tools, it introduces various design techniques to reduce cogging torque with analytical formulation and FEM examples.
SD-HRNet: Slimming and Distilling High-Resolution Network for Efficient Face Alignment

Face alignment is widely used in high-level face analysis applications, such as human activity recognition and human–computer interaction. However, most existing models involve a large number of parameters and are computationally inefficient in practical applications. In this paper, we aim to build a lightweight facial landmark detector by proposing a network-level architecture-slimming method. Concretely, we introduce a selective feature fusion mechanism to quantify and prune redundant transformation and aggregation operations in a high-resolution supernetwork. Moreover, we develop a triple knowledge distillation scheme to further refine a slimmed network, where two peer student networks could learn the implicit landmark distributions from each other while absorbing the knowledge from a teacher network. Extensive experiments on challenging benchmarks, including 300W, COFW, and WFLW, demonstrate that our approach achieves competitive performance with a better trade-off between the number of parameters (0.98 M–1.32 M) and the number of floating-point operations (0.59 G–0.6 G) when compared to recent state-of-the-art methods.
S³MPL:Semi-supervised Semantic Segmentation with Mixed Pseudo Label

The introduction of semi-supervised methods reduces the cost of labeling training data. In this regard, semi-supervised semantic segmentation methods have received great attention. In this paper, a consistent regularization method called Semi-supervised Semantic Segmentation with Mixed Pseudo Label (S3 MPL) is proposed. In this approach, consistency is applied by feeding the same input image into two segmented networks that are initialized differently and encouraging both networks to make the same predictions. The one with higher confidence in the pseudo one-hot label maps generated by the two segmentation networks is selected as the mixed pseudo label map to supervise the above segmentation networks simultaneously. There are two advantages to this: 1) the quality of pseudo labels is improved; and 2) the segmentation network can not only use divergence between networks to locate its own errors, but also continuously consolidate what it has learned; In addition, our approach also incorporates ClassMix augmentation to mix input images to obtain more diverse data. The experimental results show that our method has achieved competitive performance on Cityscapes and PASCAL VOC 2012.
A Pell–Lucas Collocation Approach for an SIR Model on the Spread of the Novel Coronavirus (SARS CoV-2) Pandemic: The Case of Turkey

In this article, we present a study about the evolution of the COVID-19 pandemic in Turkey. The modelling of a new virus named SARS-CoV-2 is considered by an SIR model consisting of a nonlinear system of differential equations. A collocation approach based on the Pell–Lucas polynomials is studied to get the approximate solutions of this model. First, the approximate solution in forms of the truncated Pell–Lucas polynomials are written in matrix forms. By utilizing the collocation points and the matrix relations, the considered model is converted to a system of the nonlinear algebraic equations. By solving this system, the unknown coefficients of the assumed Pell–Lucas polynomial solutions are determined, and so the approximate solutions are obtained. Secondly, two theorems about the error analysis are given and proved. The applications of the methods are made by using a code written in MATLAB. The parameters and the initial conditions of the model are determined according to the reported data from the Turkey Ministry of Health. Finally, the approximate solutions and the absolute error functions are visualized. To demonstrate the effectiveness of the method, our approximate solutions are compared with the approximate solutions obtained by the Runge–Kutta method. The reliable results are obtained from numerical results and comparisons. Thanks to this study, the tendencies of the pandemic can be estimated. In addition, the method can be applied to other countries after some necessary arrangements.
Approaching an Optimal Bitcoin Mining Overlay

Bitcoin builds upon an unstructured peer-to-peer overlay network to disseminate transactions and blocks. Broadcast in such a network is slow and brings inconsistencies, i. e. , peers have different views of the system state. Due to the delayed block propagation and the competition of mining, forking, i. e. , the blockchain temporarily diverges into two or more branches, occurs, which wastes computation power and causes security issues. This paper proposes an autonomous and distributed topology optimization mechanism to reduce block propagation delay and hence reduce the occurrence of blockchain forks. In the proposed mechanism, a node can autonomously update his neighbor set using the information provided by his current neighbors, since each neighbor will recommend a peer from his own neighbor set, i. e. , a neighbor’s neighbor, to this node. Each recommendation is based on a peer’s propagation ability, which is characterized as a criteria function obtained through a combination of empirical analysis and machine learning. We further propose some metrics to evaluate a Bitcoin network topology. Experiment results reflect the effectiveness of the proposed mechanism and indicate the correlation between block propagation time and fork rate. Thus, we analyze the relation between block propagation time and fork rate by applying an epidemic model to capture the block propagation process. We prove that a Bitcoin network topology with a relatively small network delay variance among all nodes produces a lower fork rate than another topology if its average block propagation time to 84% of the entire network is shorter.