Miracle-dz/UniFAR-FTUs huggingface dataset:
A Quartz Crystal Microbalance (QCM) Study on the Formation of Aqueous κ-Carrageenan-Chitosan Composite Bilayers with NaCl and Graphene Oxide

Abstract Biomaterials and thin biofilms play a fundamental role in the medical, food and pharmaceutical industries. The Quartz crystal microbalance (QCM) measurement technique is one of the attractive techniques which have been used for monitoring the thin-film formation process. In the current work described here, κ-carrageenan and chitosan solutions were used for the layer-by-layer (LBL) deposition of polyelectrolyte multilayers (PEMs) on the gold surface of a 5 MHz AT-cut (thickness-shear mode) quartz crystal in a flow module. A sensitive QCM system was designed to detect 0.1 Hz differences in the resonance frequency (Δf) and 10−7 changes in the energy dissipation (ΔD) values, which are the measures of the deposited mass and the film rigidity, respectively. Negatively charged carrageenan and positively charged chitosan biomolecules in the solutions were used to build up sequential and very thin bilayers on the modified gold surface. The effects of NaCl and graphene oxide (GO) addition on the mass of the deposited films were also investigated. Intermolecular interactions between the biopolymer chains, Na+ cations and GO sheets were explained by interactions between molecules, such as electrostatic forces and hydrogen bondings.
Monte Carlo and experimental assessment of CT-based attenuation correction in PET

The general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C) was used for the simulation of x-ray spectra in diagnostic radiology and mammography. The electrons were transported until they slow down and stop in the target. Both bremsstrahlung and characteristic x-ray production were considered in this work. We focus on the simulation of various target/filter combinations to investigate the effect of tube voltage, target material and filter thickness on x-ray spectra in the diagnostic radiology and mammography energy ranges. The simulated x-ray spectra were compared with experimental measurements and spectra calculated by IPEM report number 78. In addition, the anode heel effect and off-axis x-ray spectra were assessed for different anode angles and target materials and the results were compared with EGS4based Monte Carlo simulations and measured data. Quantitative evaluation of the differences between our Monte Carlo simulated and comparison spectra was performed using student’s t-test statistical analysis. Generally, there is a good agreement between the simulated x-ray and comparison spectra, although there are systematic differences between the simulated and reference spectra especially in the K-characteristic x-rays intensity. Nevertheless, no statistically significant differences have been observed between IPEM spectra and the simulated spectra. It has been shown that the difference between MCNP simulated spectra and IPEM spectra in the low energy range is the result of the overestimation of characteristic photons following the normalization procedure. The transmission curves produced by MCNP4C have good agreement with the IPEM report especially for tube voltages of 50 kV and 80 kV. The systematic discrepancy for higher tube voltages is the result of systematic differences between the corresponding spectra. (Some figures in this article are in colour only in the electronic version) 0031-9155/04/214897+21$30.00 © 2004 IOP Publishing Ltd Printed in the UK 4897 51
Novel state-of-health estimation of lithium-ion battery based on the incremental capacity analysis method and extreme learning machine

Accurate estimation of the State-of-Health (SOH) can provide reliable guidance information for Battery Management System (BMS) to ensure safe and efficient operation of Li-ion batteries. In this paper, we proposed a novel lithium-ion battery SOH estimation method. Firstly, we used the incremental capacity analysis method to analyze battery aging characteristics and extract the health interest, and an important smoothing step was also introduced in this process. Then a battery SOH estimation model was built based on the extreme learning machine theory. Finally, the performance of the ELM model was validated using four Li-ion batteries cyclic aging data sets. The results show that the SOH estimation error was not exceed 0.1, which indicates that our proposed method has a high estimation accuracy.
MCM-GPU Voltage Noise Characterization and Architecture-Level Mitigation

Due to manufacturing process and yield constraints, scaling GPU performance via increasing chip area becomes difficult. In the meanwhile, the demand for high computational throughput is increasing for high performance computing applications. As an alternative, multichip module GPU (MCM-GPU) achieves performance scalability via integrating multiple GPU chip modules (GPMs) on the same package. However, large MCM-GPU systems are susceptible to voltage noise effects, which cause voltage instability during program execution and result in energy inefficiency. In this work, we first model and analyze the voltage noise of MCM-GPUs at architecture level in detail. We characterize the voltage noise distributions of MCM-GPUs at different levels and under various design parameters. We further propose two architecture level voltage noise mitigation approaches, including GPM aware mitigation (GAM) and droop magnitude aware smoothing (DMAS), that leverage the voltage noise characteristics of MCM-GPUs. Evaluation shows both techniques are effective in reducing the voltage droop magnitudes and achieve good energy savings with negligible performance degradation.
Application of Wavelet Neural Networks to Forecast Deformation Monitoring

Wavelet neural network has good localization characteristics both in time-domain and frequency-domain,and also has the self-learning function of neural network.The wavelet series,which are got by wavelet resolution in shift and scale transform,have the characteristics of the average approximating functions by wavelet resolution.So it can be used to forecast deformation monitoring.There are two new parameters added into wavelet neural network,which are scale factor and shift factor.Therefore,it has more degree of freedom than wavelet resolution to make its approximating function more flexible and effective and make its fault tolerance better.
The Protective Effect of Mangiferin on Formaldehyde-Induced HT22 Cell Damage and Cognitive Impairment

Formaldehyde (FA) has been found to induce major Alzheimer’s disease (AD)-like features including cognitive impairment, Aβ deposition, and Tau hyperphosphorylation, suggesting that it may play a significant role in the initiation and progression of AD. Therefore, elucidating the mechanism underlying FA-induced neurotoxicity is crucial for exploring more comprehensive approaches to delay or prevent the development of AD. Mangiferin (MGF) is a natural C-glucosyl-xanthone with promising neuroprotective effects, and is considered to have potential in the treatment of AD. The present study was designed to characterize the effects and mechanisms by which MGF protects against FA-induced neurotoxicity. The results in murine hippocampal cells (HT22) revealed that co-treatment with MGF significantly decreased FA-induced cytotoxicity and inhibited Tau hyperphosphorylation in a dose-dependent manner. It was further found that these protective effects were achieved by attenuating FA-induced endoplasmic reticulum stress (ERS), as indicated by the inhibition of the ERS markers, GRP78 and CHOP, and downstream Tau-associated kinases (GSK-3β and CaMKII) expression. In addition, MGF markedly inhibited FA-induced oxidative damage, including Ca2+ overload, ROS generation, and mitochondrial dysfunction, all of which are associated with ERS. Further studies showed that the intragastric administration of 40 mg/kg/day MGF for 6 weeks significantly improved spatial learning ability and long-term memory in C57/BL6 mice with FA-induced cognitive impairment by reducing Tau hyperphosphorylation and the expression of GRP78, GSK-3β, and CaMKII in the brains. Taken together, these findings provide the first evidence that MGF exerts a significant neuroprotective effect against FA-induced damage and ameliorates mice cognitive impairment, the possible underlying mechanisms of which are expected to provide a novel basis for the treatment of AD and diseases caused by FA pollution.
Undergraduate Students’ Knowledge, Attitudes and Willingness to Receive COVID-19 Vaccines: A Survey of Convenience Sample in Namibia

Introduction The global consequences of the COVID-19 pandemic cannot be overstated. Vaccinations are one of the leading strategies to protect against the virus, and it is likely that students’ understanding and desire to be vaccinated can be major factors in helping contain the pandemic. Nonetheless, no studies looked into the vaccine attitude, knowledge and willingness in Namibia. Objectives To assess and describe the association between knowledge, attitudes, and willingness of undergraduate students to receive COVID-19 vaccines in the school of education, nursing and economics and management science at the university campus in Namibia. Methods The study employed a cross-sectional descriptive study from 200 undergraduate university students using a convenience sampling. Data analysis was done using SPSSv28 and descriptive statistics were used to depict trends in data while a Pearson's correlation determined the relationship between the study variables. Results The data showed that 54.2% (1.54 ± 0.49) of the participants had adequate knowledge concerning the vaccine, while 57.1% and 58.6% had a negative outlook and were unwilling to get vaccinated. A moderate positive correlation was observed between attitudes and willingness to take COVID-19 vaccines (r = .546, P =<.001), while a negative relation existed between knowledge and attitudes (r = −.017, P =>.001). Conclusions This study has provided valuable insight into the knowledge, attitudes, and willingness of undergraduate students to receive COVID-19 vaccines. Despite more than half of the participants having appropriate knowledge, they had an unfavourable outlook toward COVID-19 vaccination. It is recommended that further studies focus on how factors such as incentives, religion and cultural values affect their desires to be vaccinated.
Robust Adaptive Rescaled Lncosh Neural Network Regression Toward Time-Series Forecasting

In time series forecasting with outliers and random noise, parameter estimation in a neural network via minimizing the <inline-formula> <tex-math notation="LaTeX">$l_{2}$ </tex-math></inline-formula> loss is unreliable. Therefore, an adaptive rescaled lncosh loss function is proposed in this article to handle time series modeling with outliers and random noise. It overcomes the limitation of the single distribution of traditional loss functions and can switch among <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$l_{2}$ </tex-math></inline-formula>, and the Huber losses. A tuning parameter in the loss function is estimated by using a “working” likelihood approach according to estimated residuals. From the proposed loss function, a robust adaptive rescaled lncosh neural network (RARLNN) regression model is developed for highly accurate predictions. In the training phase of the model, an iterative learning procedure is presented to estimate the tuning parameter and train the neural network in iterations. A new prediction interval construction method is also developed based on quantile theory. The proposed RARLNN model is applied to two groups of wind speed forecasting tasks. The results show that the proposed RARLNN model is more conducive to enhancing forecasting accuracy and stability from the perspectives of noise distribution and outliers.
A Satisficing Game Theory Approach for Efficiency Evaluation with Interval Data

In this study we consider the problem of analyzing the performance of a decision making unit in to two directions: at first stage, we consider resource utilization versus output performance and at second stage, we investigate inter-unit comparison or group evaluation when the data are interval. A famous method that deals with the second stage of the forgoing proposed method is data envelopment analysis (DEA). Although comparing DMUs only with each other in DEA have some shortcomings that we are interested to overcome these shortcomings in the case when the data are interval. Some parts of game theory and optimization are considered to propose a solution.
Domain transferring self-supervised pretraining based wind power plant safety helmet detection

To train high-accuracy wind power plant safety helmet detection models with limited labelled data, a domain transferring self-supervised pretraining based wind power plant safety helmet detection method is proposed. Self-supervised pre-training with local unlabeled data is adopted to train a wind power plant domain specific pretrained model from public data set domain. Only a small amount of labelled data is required to fine tune the safety helmet detection task to achieve high accuracy. Comprehensive experiments demonstrate that the proposed method significantly improves the accuracy of wind power plant safety helmet detection with limited labelled data.
A note on wadleys problem with overdispersion

Wadley's problem results from quantal dose-response experiments when the basic distribution is Poisson, rather than binomial. We review approaches to the problem, with particular reference to using GLIM and incorporating overdispersion. Two examples are provided, and the importance of estimating overdispersion from the fit of a saturated model is emphasized.
Attitude Calibration on Three-line Array CCD Camera of Space Stereo Mapping

One method for calibrating the transformation matrix of cubic prism coordinate system between stereo mapping camera and star sensor was adopted.Auto-collimation on two cubic prisms was finished using 4 theodolites.After that,the cubic prism coordinate system was set up.And the detailed equations of rotation matrix were deduced too.The attitude between two cubic prisms was calibrated by azimuth transmission.Tests indicate that the calibration error of angle between two cubic prism coordinate system axes is less than 1.5″(1δ). The error of final attitude calibration of the stereo mapping camera is less than 5″(1δ).
FUSION OF INFRARED AND VISIBLE LIGHT IMAGES BASED ON NONSUBSAMPLED CONTOURLET TRANSFORM

Focusing on the fusion problem of infrared and visible light images with the same scene,a novel multi-sensor image fusion algorithm based on the nonsubsampled contourlet transform(NSCT)was proposed.Firstly,the NSCT was performed on the source images at different scales and directions,thus the low frequency subband coefficients and varieties of directional bandpass subband coefficients were obtained.Secondly,for the low frequency subband coefficients,a 'weighted averaging' scheme based on the physical features of infrared images and visible light images was presented;while for the bandpass directional subband coefficients,a selection principle based on the local energy matching was developed,which was also consistent with the characteristics of the human vision system.Finally,the fused image was obtained by performing the inverse NSCT on the combined coefficients.Quantitative and qualitative analysis of the experimental results demonstrate that the proposed approach performs significantly better than the traditional methods based on the discrete wavelet transform and the discrete wavelet frame transform.
Politicization of Immigration and Language Use in Political Elites: A Study of Spanish Parliamentary Speeches

This study uses natural language processing (NLP) tools to analyze how politicians recreate the stereotype of immigrants in the Spanish Parliament. An interdisciplinary approach from computational linguistics and social psychology has been used to construct a variety of indices about content and linguistic styles. The analysis of 2,516 parliamentary interventions about immigration delivered between 1996 and 2016 by representatives of the two political parties that alternated in power during that period (conservative Popular Party and Spanish Socialist Party) shows that both the rhetorical strategy to present immigrants as “victims” or as a “threat” and the language style that politicians use reveal an interaction between the ideology of the party and the party's political position in government or in the opposition. Results also suggest some changes over time in the polarization and politicization of the debate about immigration.
Regional Differences in Self-Reported Health, Physical Activity and Physical Fitness of Urban Senior Citizens in Austria

The aim of this study is to compare data on the health status, self-reported exercise and non-exercise physical activity as well as fitness parameters, such as grip strength, of people in retirement in two cities that are both considered urban centres according to the statistical office of the European Union (EUROSTAT), but differ by geographic location. Self-reported physical activity questionnaires and objective assessments of physical fitness indicators collected by sports scientists were used and examined for differences. A total of 210 people (66.3 years ± 2.3) in Salzburg (n = 90) and Vienna (n = 120) was analysed. While no differences were found in self-reported health, there were differences in self-reported exposure to self-reported exercise and non-exercise physical activity, with the Viennese population being more inactive than their more western comparison group. In addition, the objective indicators for muscle strength, balance and flexibility of the lower extremities differed significantly in favour of the more western Austrian population. We recommend assessing the situation of older people in Austria regarding their physical activity and fitness on a regional basis, even if they live in cities of the same category. Future projects should therefore aim to consider specific regional needs during development and incorporate both subjective and objective indicators when monitoring the success of such programs.
Exponential convergence of spectral approximations and time-domain computation of scattering problems.

This thesis consists of two parts. The first part is on rigorous error analysis of exponential convergence of orthogonal polynomial approximations under analytic assumption. The second part is on time-domain computation of scattering problems governed by wave equations and time-dependent Maxwell’s equations. The spectral method employs global orthogonal polynomials or Fourier complex exponentials as basis functions, so it enjoys high-order accuracy (with only a few basis functions), if the underlying function is smooth (and periodic in the Fourier case). The typical algebraic order of convergence (i.e., O(n−r), where n is the number of polynomial basis functions, and r is related to the Sobolevregularity of the underlying function), is well documented in various monographs on spectral methods. It is widely accepted that if the function under consideration is sufficiently smooth or analytic, the convergence rate is of exponential order O(q) (for constant 0 < q < 1). However, there appear significantly less investigation and very limited discussions of such error bounds (mostly mentioned, but not proved e.g., in [41, 113, 17]). In the first part of the thesis, we provide error estimates for Jacobi polynomial expansions and Jacobi-Gauss-type interpolation of analytic functions (characterized by Bernstein ellipse Eρ with ρ > 1). More precisely, we derive error bounds of the type: C(n)Mρ−n with ρ > 1, where M is the maximum value of the analytic function on the Bernstein ellipse, and where we specify the explicit dependence of C(n) on n and involved parameters. Moreover, the bounds are valid for small n, and are significantly tighter than existing ones. We also discuss superconvergence
Comparative antimicrobial analysis of green synthesized silver nanoparticles using Berberis lycium root extracts and berberine

Due to their significant biological potential, nanoparticles have been a focus of recent research. For the synthesis of the silver nanoparticles, pure berberine and aqueous root extracts of Berberis lycium were employed. Analytical methods like UV-Visible spectroscopy, FT-IR, SEM, and XRD were used to characterize the nanoparticles' structural and functional properties. The particles were spherical in shape with an average crystal size of Berberine AgNPs 47nm and of B. lycium root extract AgNPs was 16nm. MIC of B. lycium root extract AgNps was 1. 5µg/ml with IC 50 of 2.463 and MIC of berberine AgNps was 2. 5µg/ml and IC50 of 2.599 against E. coli . MIC of B. lycium root extract AgNps was 1. 5µg/ml and IC50 of 2. 514 and MIC of berberine AgNps was 1. 5µg/ml and IC50 of 2.922 against S. aureus . The nanoparticles synthesized with root extracts were found to be more potent as antibacterial agents.
Surface-plasmon-based wavefront sensing

The reduction of wavefront aberrations is essential in a number of fields, including astronomy, microscopy, photography, vision science, lithography, and lasers. Aberrations may be determined either directly with wavefront sensors or indirectly with signal- or image-based optimization algorithms. Here, we introduce a novel wavefront-sensing methodology that employs intensity differences across a beam of light to encode local wavefront slopes via attenuated total internal reflection following surface-plasmon excitation at the surface of a thin gold film. This method excels due to the dense spatial sampling of the wavefront and the fact that the wavefront itself can be determined by straightforward integration of two sets of images captured in orthogonal directions without time-consuming optimization, deconvolution, or spot centroiding.
Tomography of human trabecular bone with a laser-wakefield driven x-ray source

A laser-wakefield driven x-ray source is used for the radiography of human bone. The betatron motion of accelerated electrons generates x-rays which are hard (critical energy 30$ ? >Ecrit>30 ? > keV), have small source size (<3 μm) and high average brightness. The x-rays are generated from a helium gas cell which is near-instantly replenishable, and thus the average photon flux is limited by the repetition rate of the driving laser rather than the breakdown of the x-ray source. A tomograph of a human bone sample was recorded with a resolution down to 50 μm. The photon flux was sufficiently high that a radiograph could be taken with each laser shot, and the fact that x-ray beams were produced on 97% of shots minimised failed shots and facilitated full micro-computed tomography in a reasonable time scale of several hours, limited only by the laser repetition rate. The x-ray imaging beamline length (not including the laser) is shorter than that of a synchrotron source due to the high accelerating fields and small source size. Hence this interesting laboratory-based source may one day bridge the gap between small microfocus x-ray tubes and large synchrotron facilities.