Miracle-dz/UniFAR-FTUs huggingface dataset:
The effectiveness of persuasive health communication techniques

Objective: This study tests the effectiveness of Framing and Fear conditions to change attitudes towards elective single embryo transfer (eSET) in a large, non-clinical population. Method:A repeated measures randomised control trial design was used with 632 male and female participants allocated to one of two intervention groups (Framing or Fear condition) or a control group. There were two conditions in the Framing group (gain or loss frame), three conditions in the Fear group (high, medium or low fear) and two control conditions (education and non-education). Questionnaires were completed before exposure to the message (time 1) and immediately afterwards (time 2). Results: High fear (β = .637, P<0.008) and gain frame (β = .718, P<0.005) were the only significant conditions predicting hypothetical intentions towards eSET at Time 2 for the total sample. No other conditions were predictive of hypothetical intentions. Education only improved knowledge and non-education showed no changes in scores. Conclusion: These results highlight the benefits of multidisciplinary expertise in designing health promotion to reduce multiple pregnancies. Practice Implications: Findings suggest that educational material needs to be presented along- side persuasive communication techniques incorporating high fear and gain frames to help promote eSET in clinical practice.
Money Growth and Inflation: A Wavelet Analysis for a Monetization Approach to COVID 19

Abstract COVID 19 pandemic will cause a global economic contraction. The magnitude of shocks will impact the fiscal deficit and the public debt in all Countries. This paper provides an insight into the dynamic relationship between money growth and inflation for several Countries. The Morlet wavelet coherence model is employed since it allows the simultaneous examination of lead-lag effects and co-movements between the couple of variables in the different Countries. The overall results do not evidence a clear impact of the money growth on inflation. This outcome has relevant economic policy consequences considering that the monetization of the public debt can sustain the economic recovery. Thus, the pure monetary nature of the inflationary phenomenon can hardly be considered as a constraint in designing the measures to counteract the issue.
On Lipschitz continuity of the solution map for two-dimensional wave maps

with initial data u(0, x) = u0(x), ut(0, x) = u1(x), in the case when x ∈ R and the target is the unit sphere S (embedded in R), n ≥ 2. Thus u : Rt ×Rx → S and we have the additional constraint |u| = 1. For this problem several results of global well-posedness are available under suitable smallness assumptions on the initial data (see [4], [12], [13], [7]). Moreover, the existence of a global weak solution in H is known ([6], [14], [1]) and the existence and uniqueness
Wide-field imaging spectrometer for the Hyperspectral Infrared Imager (HyspIRI) mission

We report on the design, tolerancing, and laboratory breadboard of an imaging spectrometer for the Earth Science Decadal Survey Hyperspectral and Infrared Imager (HyspIRI) mission. The spectrometer is of the Offner type but with a much longer slit than typical designs, with 1600 resolvable spatial elements along the slit for a length of 48 mm. Two such spectrometers cover more than the required swath while maintaining high throughput and signal-to-noise thanks to the large pixel size (30 μm), relatively high speed (F/2.8) and small number of reflections. We also demonstrate a method for measuring smile using a linear array, and use the method to prove the achievement of negligible smile of less than 2% of a pixel over the entire 48 mm slit. Thus we show that this high-heritage, all-spherical mirror design can serve the requirements of the HyspIRI mission.
On the inverses of some patterned matrices arising in the theory of stationary time series

Expressions are obtained for the determinant and inverse of the covariance matrix of a set of n consecutive observations on a mixed autoregressive moving average process. Explicit formulae for the inverse of this matrix are given for the general autoregressive process of order p (n ≧ p), and for the first order mixed autoregressive moving average process.
Guided Time-Optimal Model Predictive Control of a Multi-Rotor

Time-optimal control of a multi-rotor remains an open problem due to the under-actuation and nonlinearity of its dynamics, which make it difficult to solve this problem directly. In this letter, the time-optimal control problem of the multi-rotor is studied. Firstly, a thrust limit optimal decomposition method is proposed, which can reasonably decompose the limited thrust into three directions according to the current state and the target state. As a result, the thrust limit constraint is decomposed as a linear constraint. With the linear constraint and decoupled dynamics, a time-optimal guidance trajectory can be obtained. Then, a cost function is defined based on the time-optimal guidance trajectory, which has a quadratic form and can be used to evaluate the time-optimal performance of the system outputs. Finally, based on the cost function, the time-optimal control problem is reformulated as an MPC (Model Predictive Control) problem. The experimental results demonstrate the feasibility and validity of the proposed methods.
A simulation comparison of two methods for controlling the experiment-wise Type I error rate of correlated tests for contrasts in one-way completely randomized designs

A Bonferroni and an ordered P-value solution to the problem of controlling the experiment-wise Type I error rate are studied and compared in terms of actual size and power when carrying out correlated tests. Although both of these solutions can be used in a wide variety of settings, here they are only investigated in the context of multiple testing that specified pairwise comparisons of means, selected before data are collected, are all equal to zero in a completely randomized, balanced, one factor design where the data are independent random samples from normal distributions all having the same variance. Simulations indicate that both methods are very similar and effective in controlling experiment wise type error at a nominal rate of 0.05. Because the ordered Pvalue method has, almost uniformly, slightly greater power, it is my recommendation for use in the setting of this report.
THE AVERAGE NUMBER OF REAL ROOTS OF A RANDOM ALGEBRAIC EQUATION

The average number of real roots of the random algebraic equation F_n(ω, t)=a_0(ω)+a_1(ω)t+…+a_(n-1)(ω)t~(n-1)=0 has been estimated by Kac, M. for the case where the a_i(ω)(i=0,1,…, n-1)are indenpendent Gaussian random variables with mean 0 and standard deviation 1. Let EN_F(ω) be the average number of real roots of F_n(ω,t), Kac's main result is Later in (8), Stevens obtained The purpose of this paper is to prove the following theorem.Theorem. Let be a random algebraic epuation where a_i(ω)(i=0, 1,…, n-l) are indenpendent Gaussian random variables with mean 0 and standard deviation 1, Then for all n≥1
Suppressed Phase Separation of Mixed-Halide Perovskite Quantum Dots Confined in Mesoporous Metal Organic Frameworks

Mixed-halide perovskite quantum dots (PeQDs) are the most competitive candidates in designing solar cells and light-emitting devices (LEDs) due to their tunable bandgap and high-efficiency quantum yield. However, phase separation in mixed-halide perovskites under illumination can form rich iodine and bromine regions, which change its optical responses. Herein, we synthesize PeQDs combined with mesoporous zinc-based metal organic framework (MOF) crystals, which can greatly improve the stability of anti-anion exchange, including photo-, thermal, and long-term stabilities under illumination. This unique structure provides a solution for improving the performance of perovskite optoelectronic devices and stabilizing mixed-halide perovskite devices.
Deep learning–based detection of diabetic macular edema using optical coherence tomography and fundus images: A meta-analysis

Diabetic macular edema (DME) is an important cause of visual impairment in the working-age group. Deep learning methods have been developed to detect DME from two-dimensional retinal images and also from optical coherence tomography (OCT) images. The performances of these algorithms vary and often create doubt regarding their clinical utility. In resource-constrained health-care systems, these algorithms may play an important role in determining referral and treatment. The survey provides a diversified overview of macular edema detection methods, including cutting-edge research, with the objective of providing pertinent information to research groups, health-care professionals, and diabetic patients about the applications of deep learning in retinal image detection and classification process. Electronic databases such as PubMed, IEEE Explore, BioMed, and Google Scholar were searched from inception to March 31, 2022, and the reference lists of published papers were also searched. The study followed the preferred reporting items for systematic review and meta-analysis (PRISMA) reporting guidelines. Examination of various deep learning models and their exhibition regarding precision, epochs, their capacity to detect anomalies for less training data, concepts, and challenges that go deep into the applications were analyzed. A total of 53 studies were included that evaluated the performance of deep learning models in a total of 1,414,169°CT volumes, B-scans, patients, and 472,328 fundus images. The overall area under the receiver operating characteristic curve (AUROC) was 0.9727. The overall sensitivity for detecting DME using OCT images was 96% (95% confidence interval [CI]: 0.94–0.98). The overall sensitivity for detecting DME using fundus images was 94% (95% CI: 0.90–0.96).
Optimization of Phytochemical-Rich Citrus maxima Albedo Extract Using Response Surface Methodology

In the present study, response surface methodology (RSM) and Box–Behnken design (BBD) were employed to optimize the conditions for the extraction of C. maxima albedo from agricultural waste, to obtain notable phytochemicals. Ethanol concentration, extraction temperature, and extraction time were included as key factors contributing to the extraction. The results showed that the optimum extraction condition for C. maxima albedo was 50% (v/v) aqueous ethanol at 30 °C for 4 h, which provided total phenolic contents and total flavonoid contents at 15.79 mg of gallic equivalent/g dry weight (DW) and 4.50 mg of quercetin equivalent/g DW, respectively. Considerable amounts of hesperidin and naringenin at 161.03 and 3430.41 µg/g DW, respectively, were detected in the optimized extract using liquid chromatography–electrospray ionization–tandem mass spectrometry (LC–ESI–MS/MS). The extract was later subjected to a test for its enzyme-inhibitory activities against key enzymes relevant to Alzheimer’s disease (AD), obesity, and diabetes as well as for its mutagenicity potential. Among enzyme inhibitory activities, the extract showed the highest inhibitory strength against β-secretase (BACE-1), which is a drug target for AD treatment. The extract was also devoid of mutagenicity properties. Overall, this study demonstrated a simple and optimal extraction procedure for C. maxima albedo with a significant quantity of phytochemicals, health benefits, and genome safety.
An Improved Particle Swarm Optimization Algorithm for Seismic Wavelet Estimation

An improved particle swarm optimization algorithm is presented in this study. The new method proposes a linear time-varying acceleration co-efficient and brings in two mutations including differential mutation and random mutation. Also, some betterment is made over the bound constraints which keep the escaped particles diversity. At last, this new method is applied to seismic wavelet estimation. Numerical data tests demonstrate that the method is capable of extracting wavelets with relatively higher accuracy.
Icing analysis and test of a business jet engine inlet duct

A program was developed to design an inlet duct anti-icing system of a light jet passenger aircraft. The inlet system consists of two offset “S-Shaped” intakes that provide air to a single jet engine after joining together at the engine face. Experimental and analytical methods were used in a combined approach to predict the impingement limits, ice mass interception, and power required for maintaining the internal inlet surfaces free of ice. A full-scale model of an inlet duct was constructed with integral heaters and placed in the Cox Icing Wind Tunnel. The test series included icing runs to investigate the impingement limits at various cloud droplet diameters conditions. The analytical methods used a full Navier-Stokes CFD solver and the NASA LEWICE3D ice accretion code.
Free vibration of FGM Euler beam with post-buckling configuration subjected to axial force

Based on geometrically non-linear theory for axially extensible beams,an exact mathematical model of post-buckling transverse free vibration of FGM beams made of metal and ceramic subjected to axial force was derived.By using shooting method,pre-buckling and post-buckling free vibrations of one end simply supported and other end fixed Euler FGM beam were solved and characteristics curves of the lowst three orders of non-dimensional frequencies versus load parameter of FGM beams under different graded indexes were plotted.The numerical results show that all the frequencies of unbuckled beams decrease continuously with the increment of load.However,when the beams are in post-buckled state,the effect of axial force on each order of natural frequency is variant.
Studies of the Absolute Correlation Degree Image Border Detecting Method Based on Grey System Theory

The border detecting is that the gradation to the image changes magnanimity,detecting being in progress mainly. Nothing,true and false,orientation and allocation resolving image border having. The data is compared with other a little method owing to the absolute correlation degree method image to the law handling atypia in border detecting gray system theory,has clear superiority. Measure method that the main body of a book has been submitted according to absolute correlation degree analysis method that border of integration of affine alternation with minimum two multiplication principle and absolute correlation degree model is inspected up one kind,Be method’s turn to have certain effect on the norm and ordinal number effect problem overcoming absolute correlation degree analysis method.
An Improved Barycenter Method Used in Light-trap Center Acquiring

This paper introduces laser ambulator simply,on the basis of analysis the principle and classes of grating sensor,in view of the problem that ambulator requires high precision when surveying the high voltage cable,a scheme of using grating sensor in laser ambulator is proposed.Two diffraction gratings sensors in the laser ambulator platform design are installed,which separately output elevation angle and the agimuth angle,and the subdivision circuit of grating sensor is designed using subdivision algorithm,increasing the measurement precision greatly.
DA-CBGRU-Seq2Seq Based Soft Sensor for Mechanical Properties of Hot Rolling Process

High-precision prediction of material properties is an advanced direction of hot rolled product technology in manufacturing processes. However, complex disturbance usually produces wrong or missing data in the acquisition and entry stages. The long process and the diverse operating conditions bring great challenges to constructing soft sensors for the hot rolling process. To address this problem, a new time-series soft sensor model framework is proposed for mechanical properties prediction. First, in order to process the raw dataset, the isolation forest algorithm is used to remove the outliers, and the random forest algorithm is used to fill in missing values. Second, the auxiliary variables are extracted by the combination of the XGBoost algorithm and prior mechanistic knowledge. Then, a dual-stage attention-convolutional neural network and bidirectional gated recurrent unit (DA-CBGRU)-sequence-to-sequence (Seq2Seq) time-series model based on a two-stage attention mechanism is designed for soft sensor modeling. In the encoder stage, external factors are introduced by an entity embedding layer. A combination structure of bidirectional gated recurrent units (GRUs) and convolutional layers is designed for extracting and learning the input features adaptively with the input attention mechanism. In the decoder stage, the long-term time dependence of the time series is learned by the temporal attention mechanism. Finally, the reliability of the proposed sensor model is compared and verified by the hot rolling process. The results indicate that the proposed method has an accuracy of over 95% in predicting the mechanical properties of a real hot-rolling process dataset, and has a better performance compared to other comparative soft sensor prediction methods.
Pressurized Liquid Extraction: A Powerful Tool to Implement Extraction and Purification of Food Contaminants

Pressurized liquid extraction (PLE) is considered an advanced extraction technique developed in the mid-1990s with the aim of saving time and reducing solvent with respect to traditional extraction processes. It is commonly used with solid and semi-solid samples and employs solvent extraction at elevated temperatures and pressures, always below the respective critical points, to maintain the solvent in a liquid state throughout the extraction procedure. The use of these particular pressure and temperature conditions changes the physicochemical properties of the extraction solvent, allowing easier and deeper penetration into the matrix to be extracted. Furthermore, the possibility to combine the extraction and clean-up steps by including a layer of an adsorbent retaining interfering compounds directly in the PLE extraction cells makes this technique extremely versatile and selective. After providing a background on the PLE technique and parameters to be optimized, the present review focuses on recent applications (published in the past 10 years) in the field of food contaminants. In particular, applications related to the extraction of environmental and processing contaminants, pesticides, residues of veterinary drugs, mycotoxins, parabens, ethyl carbamate, and fatty acid esters of 3-monochloro-1,2-propanediol and 2-monochloro-1,3-propanediol from different food matrices were considered.
Robust output feedback control for linear stochastic systems in continuous time with time-varying parameters

In the present work we consider a multidimensional linear system with additive inputs (controls) and noise governed by a Brownian motion. We allow the parameters of the system to change in time. In addition we assume that the exact form of the coefficients is not known, rather the intervals within which these coefficients fluctuate are given. In addition, we do not know the exact state of the system, rather we observe the output process correlated with this state. The set of allowable controls are feedback controls based on the observation of the output process and "an ideal model dynamics". With each control we associate a performance functional characterizing "the quality of tracking process" and the objective is to construct a robust feedback control which minimizes the maximal performance functional within the class of systems with nonstochastic coefficients fluctuating in the same intervals as those of our problem.
Thermal Conductivity and Phase-Change Properties of Boron Nitride–Lead Oxide Nanoparticle-Doped Polymer Nanocomposites

Thermally conductive phase-change materials (PCMs) were produced using the crosslinked Poly (Styrene-block-Ethylene Glycol Di Methyl Methacrylate) (PS-PEG DM) copolymer by employing boron nitride (BN)/lead oxide (PbO) nanoparticles. Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA) methods were used to research the phase transition temperatures, the phase-change enthalpies (melting enthalpy (ΔHm), and crystallization enthalpies (ΔHc)). The thermal conductivities (λ) of the PS-PEG/BN/PbO PCM nanocomposites were investigated. The λ value of PS-PEG/BN/PbO PCM nanocomposite containing BN 13 wt%, PbO 60.90 wt%, and PS-PEG 26.10 wt% was determined to be 18.874 W/(mK). The crystallization fraction (Fc) values of PS-PEG (1000), PS-PEG (1500), and PS-PEG (10,000) copolymers were 0.032, 0.034, and 0.063, respectively. XRD results of the PCM nanocomposites showed that the sharp diffraction peaks at 17.00 and 25.28 °C of the PS-PEG copolymer belonged to the PEG part. Since the PS-PEG/PbO and the PS-PEG/PbO/BN nanocomposites show remarkable thermal conductivity performance, they can be used as conductive polymer nanocomposites for effective heat dissipation in heat exchangers, power electronics, electric motors, generators, communication, and lighting equipment. At the same time, according to our results, PCM nanocomposites can be considered as heat storage materials in energy storage systems.
Networks in Healthcare: A Systematic Review

Networks form the backbone of any healthcare system. Various databases were searched with relevant keywords, data were abstracted, and numerous papers were appraised for this synthesis. This compiled systematic review gives a comprehensive overview of various networks that are found in healthcare, with a special reference to the treatment, referral, and best-practice care of patients. Special support networks, such as Clinical decision support systems, Physician collaboration networks, Telemedicine networks, and Shared healthcare record access, are also described, as these support networks play a pivotal role in improving the quality of healthcare for patients.
Immobility beyond borders: Differential inclusion and the impact of the COVID-19 border closures

This article discusses differential inclusion as it relates to mobility in Europe through migrants’ experiences of the closure of the European Union (EU) Schengen borders during the COVID-19 pandemic. Based on 36 comparative online interviews with three groups of migrants – Erasmus students, asylum seekers and seasonal workers – the article empirically investigates how differential inclusion is reflected in migrants’ perceptions of border closures and the impact of border closures on international mobility. Drawing on the concept of differential inclusion, I examine the divergent border mobilities in a moment of crisis. In the interviews, migrants’ reflections on borders are informed either by their own perception of borders, their surprise at the lack of awareness of borders for other migrants, or the realisation that closed borders are crossed for capitalist economic demands under high health risks. Taking this as its basis, the article makes two arguments. First, that preexisting differential inclusion exacerbated during border closures in a global health emergency. Second, that borders are not concrete but flexible in (im)mobilising people according to capitalist economic demands. In this way, the article contributes to an understanding of the process of rebordering that took place during COVID-19 and in which borders remained spaces of differentiation.
Hall MHD Stability and Turbulence in Magnetically Accelerated Plasmas

The object of the research was to develop theory and carry out simulations of the Z pinch and plasma opening switch (POS), and compare with experimental results. In the case of the Z pinch, there was experimental evidence of ion kinetic energy greatly in excess of the ion thermal energy. It was thought that this was perhaps due to fine scale turbulence. The simulations showed that the ion energy was predominantly laminar, not turbulent. Preliminary studies of a new Z pinch experiment with an axial magnetic field were carried out. The axial magnetic is relevant to magneto - inertial fusion. These studies indicate the axial magnetic field makes the Z pinch more turbulent. Results were also obtained on Hall magnetohydrodynamic instability of the POS.