Miracle-dz/UniFAR-FTUs huggingface dataset:
A CONDITION IN FINITE SOLVABLE GROUPS RELATED TO CYCLIC SUBGROUPS

Abstract In this paper, we classify the finite groups belonging to the class of cyclic-transitive groups. A group G is said to be cyclic-transitive if the following condition holds: if x, y, z are nonidentity elements of G such that 〈x,y〉 and 〈y,z〉 are both cyclic, then 〈x,z〉 is also cyclic.
Prediction models of the nutritional quality of fresh and dry Brachiaria brizantha cv. Piatã grass by near infrared spectroscopy

ABSTRACT This study aimed to generate prediction models to estimate the chemical composition of fresh and dry Brachiaria brizantha cv. Piatã grass using near infrared spectroscopy (NIRS). Chemical analyses of 249 samples were performed to determine oven-dried sample (ODS), dry matter (DM), crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), cellulose (CEL) and total digestible nutrients (TDN). The samples were scanned in an NIRS spectrometer and different percentages were used to compose and develop the models (100% fresh; 100% dry; 25% fresh:75% dry; 50% fresh:50% dry and 75% fresh:25% dry). The purpose of these mixed models is to know if it is possible to obtain reliable predictions from fresh samples in a database that contains dry samples. The calibration models were developed using modified partial least squares (MPLS) and evaluated by statistical parameters, including coefficient of determination (R²) and residual predictive deviation (RPD). The model with 100% dry samples obtained the best results in R² and RPD validations, for CP (0.94; 3.98), NDF (0.92; 3,49) and TDN (0.90; 3.12). The 100% fresh samples produced the best R² results in ODS (0.83), CP (0.85), ADF (0.84) and ADL (0.83). A screening model was validated to predict the characteristics and components of the fresh samples. The model using 100% dry grass was suitable for predicting all the variables, except ODS, DM and CEL.
Characteristics of laser-induced gratings in Pr 3+ - and Eu 3+ -doped silicate glasses

Four-wave mixing techniques are used to produce laser-induced gratings in Pr3+-doped silicate glasses for the first time to our knowledge. The characteristics of the laser-induced grating are investigated and compared with those found in Eu3+-doped silicate glasses. An attempt to form a laser-induced grating in an Er3+-doped silicate glass was made. Under excitation conditions similar to those in previous experiments, no laser-induced grating could be produced. Differences between the samples are discussed in terms of high-energy phonons, which are emitted when the rare-earth ion relaxes nonradiatively. Temperature dependences of the laser-induced grating signal intensity are investigated in Eu3+-doped silicate glasses, and the results are compared with theoretical predictions.
Relaxer ferroelectric polymers for actuators and transducers

Ultra-high electrostrictive strains, both longitudinal and transverse strains, were observed in polyvinylidene fluoride-trifluoroethylene (P(VDF-TrFE)) copolymers under a proper electron irradiation treatment. In addition, in DC electric field biased states, the material also exhibits a high effective piezoelectric coefficient, comparable to those in piezoceramic PZT. The material also has a high dielectric constant and relative low dielectric loss. Moreover, these properties can be tailored in a broad range by the processing conditions. These features indicate that the material is attractive for high performance actuators and transducers. In this paper, electrostrictive strain, effective piezocoefficients, elastic, dielectric properties and polarization behavior of the material are reported. We will also show that the material exhibits typical relaxor ferroelectric behavior.
İnternet Penetrasyonu, Doğrudan Yabancı Yatırımlar, Dış Ticaret ve Ekonomik Büyüme Arasındaki Nedensellik İlişkileri: BRICS-T Ülkeleri Üzerine Bir Araştırma

İnternet kullanımının yaygınlaşmasıyla birlikte internet penetrasyonu ile makroekonomik göstergeler arasındaki ilişkilerin incelenmesi önemli hale gelmiştir. Bu çalışmanın amacı, 1993-2019 dönemi için BRICS-T (Brezilya, Rusya, Hindistan, Çin, Güney Afrika ve Türkiye) ülkelerinde internet penetrasyonu, doğrudan yabancı yatırımlar, dış ticaret ve ekonomik büyüme arasındaki nedensellik ilişkilerini incelemektir. Bu kapsamda çalışmada panel veri analiz tekniklerinden yararlanılmıştır. Değişkenler arasındaki nedensellik ilişkisi, Dumitrescu ve Hurlin (2012) tarafından geliştirilen nedensellik testi kullanılarak araştırılmıştır. Bulgular, değişkenler arasında güçlü nedensellik ilişkilerinin varlığını destekleyen niteliktedir.
The Effect of Exercise on Serum Resistin and Leptin Values in Rats Fed with a High Fat Diet

Aim: This study was performed to investigate the effect of exercise on serum resistin and leptin values in rats fed with a high-fat diet. Material and Method: 24 Wistar albino male rats were used in the study. They were randomly divided into 4 groups, with 6 rats in each group. The groups were determined as the control group (C), exercise group (E), high-fat diet (HFD) group, and high-fat diet + exercise (HFDE) Group. Results: When the findings obtained in this study were evaluated statistically, it was determined that the resistin values were similar in the C, E and HFDE groups, and higher in the HFD group compared to the other groups. It was observed that resistin value increased with high-fat diet and decreased with exercise. When evaluated in terms of leptin levels, the C and E groups showed similarity, while the HFD and HFDE groups showed similarity with each other. Although exercise decreased the leptin level, which was highly increased with a high-fat diet, it was not statistically significant. Conclusion: It has been determined that feeding with a high-fat diet causes an increase in serum resistin and leptin levels, and exercise provides a significant decrease in resistin values, but is not effective in leptin levels.
Extremely low excess noise avalanche photodiode with GaAsSb absorption region and AlGaAsSb avalanche region

An extremely low noise Separate Absorption and Multiplication Avalanche Photodiode (SAM-APD), consisting of a GaAs0.52Sb0. 48 absorption region and an Al0.85Ga0. 15As0.56Sb0. 44 avalanche region, is reported. The device incorporated an appropriate doping profile to suppress tunneling current from the absorption region, achieving a large avalanche gain, ∼130 at room temperature. It exhibits extremely low excess noise factors of 1.52 and 2.48 at the gain of 10 and 20, respectively. At the gain of 20, our measured excess noise factor of 2.48 is more than three times lower than that in the commercial InGaAs/InP SAM-APD. These results are corroborated by a Simple Monte Carlo simulation. Our results demonstrate the potential of low excess noise performance from GaAs0.52Sb0. 48/Al0.85Ga0. 15As0.56Sb0. 44 avalanche photodiodes.
Clinical Significance of Liver MR Imaging

MRI is widely used in clinical practice for detecting liver diseases. Since the introduction of gadoxetic acid, MRI has become the most effective modality for the detection and characterization of focal liver lesions. According to previous meta-analyses, the area under the receiver operating characteristic curve (AUROC) was 0.97–0.99 for the diagnosis of small hepatocellular carcinoma (≥ 2 cm) by gadoxetic-acid-enhanced MRI. Moreover, the AUROC for the diagnosis of colorectal liver metastases was significantly high (0.98). Despite gadoxetic acid’s drawbacks, its clinical utility outweighs them, making it the contrast agent of choice in routine liver MRIs. Moreover, clinically, liver MRI has become more prevalent for a quantitative assessment. Liver fibrosis can be evaluated using MR elastography; whereas, hepatic steatosis and iron overload can be evaluated using proton density fat fraction, with high accuracy and reproducibility. This article reviewed the usefulness of liver MRI, which can be a comprehensive imaging modality in clinical practice.
Infant‐directed vowels are easier to learn for a computer model

When addressing infants, caretakers use a special register, called ‘‘motherese’’ or ‘‘parentese. ’’ Kuhl et al. (Science, 1997) demonstrated that the formant patterns of the centers of vowels in this register are farther apart than those in adult‐directed speech, and postulated that this helps children learn the categories of speech in their language. In this study, this hypothesis was tested with a computer model. Three words were used: sock, shoe, and sheep. Recordings of these words were available from ten mothers in both infant‐directed and adult‐directed registers. The first two formants were automatically extracted from the voiced parts of each word. Automatic formant extraction often results in formant patterns with errors, but no corrections were made. After formant extraction, their distributions were compared and a mixture of three Gaussians was fitted to the data points. The results demonstrated that infant‐directed tokens not only used a larger part of the acoustic space, but also resulted in a.
Boundary Integral Equation Method in the Steady State Oscillation Problems for Anisotropic Bodies

The three-dimensional steady state oscillation problems of the elasticity theory for homogeneous anisotropic bodies are studied. By means of the limiting absortion principle the fundamental matrices maximally decaying at infinity are constructed and the generalized Sommerfeld-Kupradze type radiation conditions are formulated. Special functional spaces are introduced in which the basic and mixed exterior boundary value problems of the steady state oscillation theory have unique solutions for arbitrary values of the oscillation parameter. Existence theorems are proved by reduction of the original boundary value problems to equivalent boundary integral (pseudodifferential) equations.
Silk fibroin fibers-based shape memory membrane with Janus wettability for multitiered wearable protection

Realizing breathable shape memory fiber-based material with antibacterial and waterproof performances is important for multitiered wearable protection to address the increasing concerns of air pollution. Herein, using an alternating electrospinning-electrospraying technology, we develop a fiber-based membrane with Janus wettability based on a silk fibroin nanofibers-substrate (SFNFs), a polyurethane nanospheres-top layer (PUNSs), and a middle layer of PU nanofibers-mat with in-situ grown silver nanoparticles (PUNFs-AgNPs), which serves separately for skin contact, a self-cleaning physical barrier to resist external aerosol/bacteria (PM2.5 filtration efficiency ~ 98.1%), and a bio-barrier that can sterilize harmful particles and inhibit bacteria proliferation (> 95%). This breathable Janus film (SFNFs/PUNFs-AgNPs/PUNSs, SPAP) with an antibacterial filter shows shape memory stretchability enabled by the thermoplastic PU component, which is mechanically adaptive to human body for wearable protection. This work presents a breathable wearable material for air-filtration and anti-bacteria, promising for applications such as wound dressings, medical masks, protection suits, and multifunctional filters. Graphical abstract An alternating electrospinning-electrospraying technology was proposed to achieve a silk fibroin-based antibacterial membrane with Janus wettability, as well as good skin affinity and breathability, which serves well as physical and bio-barriers for water resistance, PM2.5 filtration (~98.1%) and bacteria inhibition (efficiency of 95%). This shape memory Janus membrane can adapt mechanically to human body curvatures for functional wearable protections.
Multiparameter Radar And Microwave Radiative Transfer Modeling Of Nonspherical Atmospheric Ice Particles

Multiparameter radar and polarized microwave radiative transfer models for arbitrarily shaped particles are developed. These models are used concurrently to study the radar/radiometry properties of atmospheric ice crystals with regard to particle shape and bulk den- sity. The ice crystals modeled are horizontally oriented hexagonal plates, columns, and needles. The ice water content is fixed at 0.1 g/m3 and a realistic size distribution is used. The radar modeling is done for S through K-band, and the passive microwave calculations are at 37, 85, and 157 GHz. The electromagnetic scattering properties of the ice crystals is computed using the discrete dipole approximation. The modeling results show that particle shape is important for both mul- tiparameter radar and passive microwave radiometry. Radar reflectiv- ity and upwelling microwave brightness temperatures depend strongly on the individual particle volume, which in turn depends on the ice crystal shape. Radar differential reflectivity is high for the plates and lower for needles and columns. Linear depolarization calculations in- dicate that oblate ice crystals such as plates can be distinguished from prolate crystals such as columns. At 85 and 157 GHz, significant po- larization brightness temperature differences are calculated for plates and columns. The particle bulk density strongly affects the radar and radiometer observables. Recent measurements taken of ice crystals using the C-band polarimetric DLR (German Aerospace Research Es- tablishment) radar and the National Center for Atmospheric Re- search's CP-2 radar are discussed to show that the model results have practical applicability. Modeling with equivalent volume spheres is shown to approximate poorly the ice crystal results. The implications of the results for future observations and instruments and for combin- ing radar and radiometer measurements are outlined.
Polyetherketoneketone Mesh for Alveolar Bone Augmentation: Geometric Parameter Design and Finite Element Analysis

Objective To evaluate the mechanical properties of porous polyetherketoneketone (PEKK) meshes with different thicknesses, pore sizes, and porosities through finite element analysis to provide an optimal PEKK design for alveolar bone augmentation in the posterior mandibular region. Methods A three-dimensional evaluation model of severe alveolar bone defects in the mandibular posterior was constructed based on cone beam computerized tomography (CBCT) data. Then, PEKK meshes with different structural designs were obtained. Two key parameters were set with different values: five levels of thickness (0.2 mm, 0.3 mm, 0.4 mm, 0.5 mm, and 0.6 mm) and three levels of pore size (1 mm, 2 mm, and 3 mm) with a corresponding porosity of 19.18%–42.67%. A 100 N physiological force was simultaneously loaded by finite element analysis (FEA), and the deformation and stress data were outputted for further analysis. Results The deformation and stress of the PEKK meshes are negatively correlated with the changes in thickness and positively correlated with the changes in pore size. The FEA results show that the maximum deformation, equivalent stress, and maximum principal stress of the PEKK meshes are 0.168 mm–0.478 mm, 49.243 MPa–124.890 MPa, and 31.549 MPa–104.200 MPa, respectively. The PEKK mesh group with a thickness of 0.2 mm, pore size of 3 mm, and porosity of 42.67% is in danger of plastic deformation or even fracture during use. Conclusion According to the FEA results, the PEKK meshes with larger thicknesses and smaller pore sizes and porosities behave better. In consideration of reducing soft tissue stimulation and promoting bone regeneration, an ultrathin porous PEKK mesh with a pore size of no more than 3 mm, porosity of no more than 42.67%, and thickness of 0.2 mm can be used clinically to meet the mechanical performance requirements of the guided bone regeneration (GBR) structure.
SCADA data-driven blade icing detection for wind turbines: an enhanced spatio-temporal feature learning approach

Blade icing is one of the common issues of large-scale wind turbines located in cold regions, which will affect the safety and efficiency of the whole turbine system. Currently, data-driven fault detection has gained increasing interest due to the availability of a large volume of supervisory control and data acquisition (SCADA) data. However, SCADA data has complex time-varying characteristics and strong spatio-temporal correlations among different sensor variables, thus it is still challenging to extract effective fault features for accurate detection. To this end, this paper proposes an enhanced spatio-temporal feature learning approach, called multi-task temporal spatial attention network (MT-STAN). It contains two core modules: a feature extraction module and a multi-task learning module. For better spatio-temporal feature extraction, a spatio-temporal attention block is first developed to extract important variables in the spatial dimension and temporal segments in the temporal dimension via the attention mechanism. Then, we design a multitask learning module, consisting of both deep metric learning and classification learning tasks, to further enhance the discriminative ability of the learned representations and improve the performance of fault detection. The proposed approach is evaluated on a real SCADA dataset, and the results show that our proposed MT-STAN model achieved better detection performance compared with several baseline models.
Stochastic Stability Analysis for Switched Genetic Regulatory Networks with Interval Time-Varying Delays Based on Average Dwell Time Approach

In this article, the problem of stochastic stability analysis for switched stochastic genetic regulatory networks with interval time-varying delays based on average dwell time approach is investigated. By constructing the piecewise Lyapunov-Krasovskii functional, delay-dependent stability conditions are derived by using free-weighting matrix and convex combination approach. The derived stability conditions are expressed in terms of linear matrix inequalities which can be easily solved by using the MATLAB LMI control toolbox. Finally, numerical examples are provided to demonstrate the effectiveness and less conservativeness of the proposed theoretical results.
A Generalized Markov-Chain Modelling Approach to $(1,\lambda )$-ES Linear Optimization: Technical Report

Several recent publications investigated Markov-chain modelling of linear optimization by a $(1,\lambda )$-ES, considering both unconstrained and linearly constrained optimization, and both constant and varying step size. All of them assume normality of the involved random steps, and while this is consistent with a black-box scenario, information on the function to be optimized (e.g. separability) may be exploited by the use of another distribution. The objective of our contribution is to complement previous studies realized with normal steps, and to give sufficient conditions on the distribution of the random steps for the success of a constant step-size $(1,\lambda)$-ES on the simple problem of a linear function with a linear constraint. The decomposition of a multidimensional distribution into its marginals and the copula combining them is applied to the new distributional assumptions, particular attention being paid to distributions with Archimedean copulas.
Unloaded quality factor optimization of substrate integrated waveguide resonator using genetic algorithm

The main objective purpose of this paper is to study the enhancement techniques of the unloaded quality factor of substrate integrated waveguide (SIW) resonator, given that the quality of filters depends first on the quality of the resonators that compose it. Performance enhancement is achieved by employing a MATLAB-based genetic algorithm to optimize the geometrical parameters of the SIW resonator by iterative convergence to the target frequency (10 GHz frequency). On the other hand, the Ansys HFSS tool is used to model and optimize the SIW resonator with the suitable transition and plot the S-parameters for a frequency sweep range to validate its property. The results obtained allow increasing the unloaded Q-factor to be more than 1609 and reducing not only insertion and return losses but also reducing the size of the resonator. The proposed SIW resonator with its small size and low loss is directly useful for microwave and millimeter-wave applications.
A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data

Inference for cross-sectional models using longitudinal data, can be accomplished with generalized estimating equations (Zeger and Liang, 1992). We show that either a diagonal working covariance matrix should be used or a key assumption should be verified. The assumption is non-trivial when covariates vary over time. The validity of this assumption is explored for some broad classes of correlation structures. Similar considerations are shown to be relevant for the more general problem of correlated response data and marginal regression analysis with individual level covariates.
A Graphical Method of Exploring the Mean Structure in Longitudinal Data Analysis

Abstract In a longitudinal study, individuals are observed over some period of time. The investigator wishes to model the responses over this time as a function of various covariates measured on these individuals. The times of measurement may be sparse and not coincident across individuals. When the covariate values are not extensively replicated, it is very difficult to propose a parametric model linking the response to the covariates because plots of the raw data are of little help. Although the response curve may only be observed at a few points, we consider the underlying curve y(t). We fit a regression model y(t) = x Tβ(t) + e(t) and use the coefficient functions β(t) to suggest a suitable parametric form. Estimates of y(t) are constructed by simple interpolation, and appropriate weighting is used in the regression. We demonstrate the method on simulated data to show its ability to recover the true structure and illustrate its application to some longitudinal data from the Panel Study of Income Dynamics.
Zero thermal expansion in a pure-form antiperovskite manganese nitride

A zero thermal expansion material in a pure form is fabricated using an antiperovskite manganese nitride. The isotropic zero thermal expansion is achieved by optimizing the heat treatment and the chemical composition. The present study suggests that the heat treatment affects the thermal expansion mainly via the nitrogen content of the material. The obtained materials exhibit a low expansion of |α|<0.5×10−6 K−1 (α is the coefficient of linear thermal expansion) over a broad temperature range, which includes room temperature. They are desirable for many fields of industry as reliable, mechanically hard, and low-cost zero thermal expansion materials.
Association of iron deficiency anemia and eating clove in an 8-year-old girl. A rare case report

Iron-deficiency anemia is the most common nutrient disorder worldwide. It is defined pica as eating non-nutritive, non-food substances over a period of at least one month. Different types of pica have been reported in the literature. Although the exact etiology of pica is unknown, pica has been related to iron and other mineral/nutritional deficiencies. Although a relationship between iron-deficiency anemia and pica has been reported in the literature, no such association has been reported with eating clove so far. Therefore, I present the case of an 8-year-old girl diagnosed with iron-deficiency anemia with clove pica.