Miracle-dz/UniFAR-FTUs huggingface dataset:
Light-induced ferromagnetism in III-V-based diluted magnetic semiconductor heterostructures

We report for the first time the occurrence of light-induced ferromagnetic order in the III-V-based diluted magnetic semiconductor heterostructures (In,Mn)As/GaSb. We believe that the phenomenon is based on the generation of excess carriers (holes) in the (In,Mn)As layer by the irradiation of light, which enhances a carrier-mediated ferromagnetic interaction between Mn ions.
Photoacoustic image reconstruction based on Bayesian compressive sensing algorithm

The photoacoustic tomography (PAT) method, based on compressive sensing (CS) theory, requires that, for the CS reconstruction, the desired image should have a sparse representation in a known transform domain. However, the sparsity of photoacoustic signals is destroyed because noises always exist. Therefore, the original sparse signal cannot be effectively recovered using the general reconstruction algorithm. In this study, Bayesian compressive sensing (BCS) is employed to obtain highly sparse representations of photoacoustic images based on a set of noisy CS measurements. Results of simulation demonstrate that the BCS-reconstructed image can achieve superior performance than other state-of-the-art CS-reconstruction algorithms.
Matrix Variate Distributions

PRELIMINARIES Matrix Algebra Jacobians of Transformations Integration Zonal Polynomials Hypergeometric Functions of Matrix Argument LaGuerre Polynomials Generalized Hermite Polynomials Notion of Random Matrix Problems MATRIX VARIATE NORMAL DISTRIBUTION Density Function Properties Singular Matrix Variate Normal distribution Symmetic Matrix Variate Normal Distribution Restricted Matrix Variate Normal Distribution Matrix Variate Q-Generalized Normal Distribution WISHART DISTRIBUTION Introduction Density Function Properties Inverted Wishart Distribution Noncentral Wishart Distribution Matrix Variate Gamma Distribution Approximations MATRIX VARIATE t-DISTRIBUTION Density Function Properties Inverted Matrix Variate t-Distribution Disguised Matrix Variate t-Distribution Restricted Matrix Variate t-Distribution Noncentral Matrix Variate t-Distribution Distribution of Quadratic Forms MATRIX VARIATE BETA DISTRIBUTIONS Density Functions Properties Related Distributions Noncentral Matrix Variate Beta Distribution MATRIX VARIATE DIRICHLET DISTRIBUTIONS Density Functions Properties Related Distributions Noncentral Matrix Variate Dirichlet Distributions DISTRIBUTION OF MATRIX QUADRATIC FORMS Density Function Properties Functions of Quadratic Forms Series Representation of the Density Noncentral Density Function Expected Values Wishartness and Independence of Quadratic Forms of the Type XAX' Wishartness and Independence of Quadratic Forms of the Type XAX'+1/2(LX'+XL')+C Wishartness and Independence of Quadratic Forms of the Type XAX'+L1X'+XL'2+C MISCELLANEOUS DISTRIBUTIONS Uniform Distribution on Stiefel Manifold Von Mises-Fisher Distribution Bingham Matrix Distribution Generalized Bingham-Von Mises Matrix Distribution Manifold Normal Distribution Matrix Angular Central Gaussian Distribution Bimatix Wishart Distribution Beta-Wishart Distribution Confluent Hypergeometric Function Kind 1 Distribution Confluent Hypergeometric Function Kind 2 Distribution Hypergeometric Function Distributions Generalized Hypergeometric Function Distributions Complex Matrix Variate Distributions GENERAL FAMILIES OF MATRIX VARIATE DISTRIBUTIONS Matrix Variate Liouville Distributions Matrix Variate Spherical Distributions Matrix Variate Elliptically Contoured Distributions Orthogonally Invariant and Residual Independent Matrix Distributions GLOSSARY REFERENCES SUBJECT INDEX Each chapter also includes an Introduction and Problems @
Growth of tin oxide nanorods induced by nanocube-oriented coalescence mechanism

SnO2 nanocrystals (NCs) with spherical, cubic, and cuboid nanorod morphologies are obtained at different stages in hydrothermal synthesis using a SnCl4⋅5H2O to CO(NH2)2 ratio of 1 to 10. Microstructural examination and theoretical derivation reveal that small spherical NCs are formed initially and some of them morph into cylindrical NCs because of the low surface free energy. These NCs transform into bigger cubic NCs with time finally evolving into cuboid nanorods due to Brownian motion. The cuboid nanorods have a lower surface free energy than the cubic NCs and constitute a stable nanostructure.
A REVIEW ON DENOISING

This paper aims to give a quick view on denoising without comprehensive details. Denoising can be understood as removing unwanted parts in signals and images. Noise incorporates intrinsic random fluctuations in the data. Since noise is ubiquitous, denoising methods and models are diverse. Starting from what noise means, we briefly discuss a denoising model as maximum a posteriori estimation and relate it with a variational form or energy model. After that we present a few major branches in image and signal processing; filtering, shrinkage or thresholding, regularization and data adapted methods, although it may not be a general way of classifying denoising methods.
Advantages of top-gate, high-k dielectric carbon nanotube field-effect transistors

The subthreshold slope, transconductance, threshold voltage, and hysteresis of a carbon nanotube field-effect transistor (CNT FET) were examined as its configuration was changed from bottom-gate exposed channel, bottom-gate covered channel to top-gate FET. An individual single wall CNT was grown by chemical vapor deposition and its gate configuration was changed while determining its transistor characteristics to ensure that the measurements were not a function of different chirality or diameter CNTs. The bottom-gate exposed CNT FET utilized 900nm SiO2 as the gate insulator. This CNT FET was then covered with TiO2 to form the bottom-gate covered channel CNT FET. Finally, the top-gate CNT FET was fabricated and the device utilized TiO2 (κ∼80, equivalent oxide thickness=0.25nm) as the gate insulator. Of the three configurations investigated, the top-gate device exhibited best subthreshold slope (67–70mV∕dec), highest transconductance (1.3μS), and negligible hysteresis in terms of threshold voltage shift.
The Role of Alexithymia and Dysfunctional Reactions in Predicting Marital Intimacy

Objective: This study aims to investigate the relationship between alexithymia and dysfunctional reactions with marital intimacy among married men and women in Mashhad City, Iran. Methods: The data collection tools in this study included the Persian version of the Toronto alexithymia scale-20, the dysfunctional attitude scale (Weissman and Beck), and the intimacy scale (Walker and Thompson). The statistical population included all married men and women who lived in Mashhad City in the second half of 2019. The sample of this study consisted of 171 married individuals (100 women and 71 men) who were selected via the convenience sampling method. Results: he results indicated a negative and significant relationship between marital intimacy and alexithymia (P<0.05, β=-25.258) and dysfunctional reactions (P<0.01, β=-0.0318). Alexithymia accounted for about 6% and dysfunctional reactions for about 10% of the dispersion of marital intimacy. Also, a positive and significant correlation existed between alexithymia and dysfunctional reactions (P<0.01, r=0.553) among married couples. In addition, alexithymia and dysfunctional reactions could be a predictor of marital intimacy. Conclusion: Paying attention to variables, such as alexithymia and dysfunctional reactions can ensure marital intimacy. The results of this study have implications for improving marital intimacy and its positive outcomes in families.
Prevalence of iron deficiency and iron deficiency anaemia among children with congenital heart defects at tertiary hospitals in Dar es Salaam, Tanzania: a cross-sectional study

Introduction iron deficiency (ID) is the most prevalent nutritional problem worldwide with children being the most vulnerable. In children with congenital heart defect (CHD), ID may lead to iron deficiency anaemia (IDA) which carries a poor prognosis due to exacerbation of left ventricular dysfunction and heart failure. This study assessed the prevalence and factors associated with ID and IDA among children with CHD at Muhimbili National Hospital (MNH) and Jakaya Kikwete Cardiac Institute (JKCI) in Tanzania. Methods a descriptive hospital-based cross-sectional study was conducted among 238 participants with echocardiography confirmed CHD presenting at MNH and JKCI. A structured questionnaire was used to collect demographic data and medical history. Anthropometric measurements were done and blood samples for evaluation of complete blood count, serum ferritin and C-reactive protein were collected. Descriptive statistics such as frequencies, percentages, median with interquartile range, were used to describe study participants. Comparison of continuous variables was performed using Student's t-test or Mann-Whitney U-test as appropriate and Chi-square (x2) test or Fisher's exact test for categorical variables to determine associations. Odds ratio (OR) with 95% confidence intervals (CI) were estimated to determine risk factors for iron deficiency and iron deficiency anaemia. All analyses were conducted using SPSS version 20 and p-value ≤0.05 was considered statistically significant. Results characteristic of study participant majority 66.4% (n 158) were less than 60 month of age with nearly equal number of male 51.3%(122) to female 48.7% (n 116). The overall prevalence of anaemia among study participants was 47.5% (n 238) with mild, moderate and severe anaemia being 21.4%, 21.4% and 4.6% respectively. The prevalence of iron deficiency was 26.9% (n 64) and that of iron deficiency anaemia was 20.2% (n 48). Age below 5 years, cyanotic CHD, history of recent illness and less consumption of red meat were significantly associated with iron deficiency (ID) and iron deficiency anaemia (IDA). After controlling for independent variables, history of recent illness aOR 0.46, 95% CI 0.22-0.98 P 0.045 less frequent consumption of red meat aOR 0.11 95% CI 0.04-0.32 P <0.001 and cyanotic CHD aOR: 0.40, 95% CI 0.18-0.87; p 0.021, were associated with of iron deficiency similarly age below 5 years aOR 0.33 0, 95% CI 14-0.89 P 0.02 early weaning practices aOR 0.50 95% CI 0.23-0.97 P 0.050 less frequent consumption of red meat aOR 0.07 CI (0.02-0.24 p <0.01 were significantly associated with iron deficiency anaemia. Conclusion nearly half of the children with CHD in this study had anaemia, more than a quarter had ID and one-fifth had IDA. Routine screening and management of both ID and IDA in children with CHD should be practised during weaning and throughout the childhood to prevent ventricular dysfunction further heart failure.
Pneumonia Detection in Chest X-ray Images using Convolutional Neural Networks

Pneumonia is an infectious and deadly disease which strikes over millions of people. Usually, chest X-rays are used by radiotherapist to diagnose pneumonia. In this paper, a Computer-Aided Diagnosis (CAD) system for pneumonia detection in chest X-ray images is proposed. This system is based on Convolutional Neural Networks (CNNs) which are able to classify the image into two classes (pneumonia or normal). Experimental results show that the proposed system obtained an accuracy rate of 98.59%.
INSTABILITY IN A TREE APPROACH TO REGRESSION

One of the major problems that a tree-approach to data analysis often encounters is instability of tree-structures. Thus if one wishes to interprete the data structure by the tree-approach, the instability issue must be dealt with. Examining instability at a node of a tree provides insight into the instability of the whole tree, since the same theory of instability applies to all the nodes. Thus, this paper deals with the instability issue at a single node of a tree. We assume that data are from a regression model, and examine what factors in that model affect the instability. Squared-error loss is considered as a criterion for tree-construction (“ls” criterion in CART program). The selection rate of a regressor variable at a node of a tree is used as a measure of instability. The selection rate mainly depends on (i) regression coefficients, (ii) (conditional) variance-covariance structure of the regressor variables (given a subset of the regressor variables), (iii) the sample size, and (iv) noise in the response variable. We report simulation results that show patterns of instability for several different settings of regression models.
Assessment of Genetic Diversity and Conservation in South African Indigenous Goat Ecotypes: A Review

Simple Summary This review seeks to understand the scientific research on the genetic diversity of the indigenous goat ecotypes of South Africa and to provide an understanding of the relationships among the ecotypes and their structure. It is essential for their utilization and for the establishment of conservation priorities. The conservation of genetically diverse ecotypes is significant for sustainable production and relevant breeding objectives. It is, therefore, important to review the knowledge that has been gathered on the genetic diversity and conservation of indigenous goat ecotypes to be able to identify the gaps that remain and the niches for future research. The review focuses on the status of indigenous goat ecotypes in South Africa, the genetic diversity that exists, and the production potential and adaptation by highlighting the importance of prioritization for conservation and sustainable utilization. Abstract Goats were amongst the first livestock to be domesticated more than 10,000 years ago for their meat, milk, skin, and fiber. They were introduced to Southern Africa by migrating nations from Central Africa to the south. Due to local adaptation to the different agro-ecological zones and selection, indigenous goats are identified as ecotypes within the indigenous veld goat breed. Their ability to thrive in a resource-limited production system and in challenging environmental conditions makes them valuable animal resources for small-scale and emerging farmers. They play important roles in household agriculture and cultural activities as well as in poverty alleviation. Studies have described the phenotypic and genetic variations in indigenous goats, targeting the major goat-producing regions and the breeds of South Africa. In turn, information is restricted to certain breeds and regions, and the experimental design is often not adequate to inform the conservation status and priorities in changing environments. Advances in genomics technologies have availed more opportunities for the assessment of the biodiversity, demographic histories, and detection regions associated with local adaptation. These technologies are essential for breeding and conservation strategies for sustainable production for food security. This review focuses on the status of indigenous goats in South Africa and the application of genomics technologies for characterization, with emphasis on prioritization for conservation and sustainable utilization.
Dependency of hydrogel membrane pores on membrane pressure and concentration: Numerical and experimental investigations

Abstract Control of pore opening is a valuable contribution to ensure filtration and separation of particles and cells of different sizes. These can be, e.g. blood cells with their cell distribution width, which is typically measured in the Complete Blood Count. In the current work, we investigate hydrogel pores made of pNIPAAm with swelling and de-swelling capabilities. They react to variations in ethanol concentration. Additionally, we analyze the effect of microfluidic pressure on membrane pores. Furthermore, the influence of the gel volume for cross-shaped pores is shown. For this purpose, experimental and numerical investigations are performed. An analogy model for the swelling behavior based on the Temperature-Expansion-Model from our previous work and a neo-Hookean material description is applied to describe swelling and mechanical deformation of the pores. Simulation results show a negligible influence to the pore bending in the specified pressure range. In the experiments, only a slight change in the pore area is observed under pressure variation. Nonetheless, there is a very good agreement between numerical and experimental results. The current investigations show the potential for the mechanical description of hydrogel pores for their further geometric optimization.
Propagation of Seismic Wavelets

This is a survey paper covering the development of the Wavelet Theory of Seismogram Structure over the past fifteen years. The paper discusses the failure of the classical wave equation in accounting for the nature of seismograms, shows that the absorption of the earth must be taken into consideration, and sketches the development of the theory based on Stokes' wave equation ∇2[Φ + 1ω0 ∂Φ∂t] = 1c2 ∂2Φ∂t2. The results of an extensive series of experimental researches are reviewed, and it is shown that the form and laws of propagation of the seismic disturbance, predicted by the theory, are supported by the experimental evidence. Applications of the theory to practical improvements in seismic prospecting are discussed briefly.
Particle Impact Phenomena

The article contains sections titled: 1 Introduction 2 Scattering from a Coulomb Potential 3 Electron Impact 3.1 Interaction Mechanisms 3.1. 1 Collisions with Electrons in the Solid 3.1. 2 Scattering from the Lattice 3.1. 3 Bremsstrahlung 3.2 Phenomena 3.2. 1 Plasmons 3.2. 2 Radiative Transitions 3.2. 3 Auger Processes 3.2. 4 Desorption Induced by Electronic Transitions (DIET) 3.2. 5 Secondary Electron Emission 3.3 Applications 3.3.1 Scattered-Beam Electrons 3.3.2 Electrons from the Target 3.3.3 Fluorescence Measurements 4 Ion Impact 4.1 Interaction Mechanisms 4.1. 1 Elastic Collisions with Target Atoms 4.1. 2 Collisions with Electrons in the Solid 4.2 Phenomena 4.2. 1 Depth Dependence of Backscattering 4.2. 2 Sputtering 4.2. 3 Channeling 4.2. 4 Damage and amorphization 4.2. 5 Electronic Excitations 4.3 Applications 4.3.1 Measuring Beam Particles 4.3.2 Recoil Target Atoms 4.3.3 Fluorescence Measurements 5 Photon Impact 5.1 Interaction Mechanisms 5.1. 1 Electronic Absorption 5.1. 2 Nuclear Scattering 5.1. 3 Coupling to Vibrational and Rotational Modes 5.2 Phenomena 5.2. 1 Photoelectric Effect 5.2. 2 Compton Scattering 5.2. 3 Raman Scattering 5.2. 4 Two-Phonon Absorption 5.2. 5 Resonant Bond Breaking 5.2. 6 Laser Ablation 5.2. 7 Exciton Creation 5.2. 8 Pockels and Kerr Effects 5.2. 9 Coherent Phonon Generation 5.2. 10 Sum Frequency Generation 5.3 Applications 5.3.1 Scattered or Absorbed Incident Light 5.3.2 Electrons from the Target 5.3.3 Measuring Scattered Light 5.3. 4 Mode Locking Lasers 6 Neutron Impact 6.1 Interaction Mechanisms 6.1. 1 Scattering from Target Nuclei 6.1. 2 Elastic Scattering from a Lattice 6.1. 3 Neutron Activation 6.2 Neutron-Bombardment Phenomena 6.2. 1 Phonon Emission and Absorption 6.2. 2 Decay-Product Energy Loss 6.3 Applications 6.3.1 Elastic Scattering 6.3.2 Inelastic Scattering 6.3.3 Reaction Products 6.3. 4 Spallation 7 Conclusion Keywords: Rutherford backscattering; particle beams; Coulomb potential; dipole matrix; photon irradiation; plasmons; lattice vectors
Energy management approach in electric vehicle with optimizing electricity consumption cost using hybrid method

This paper proposes a hybrid approach for the optimal design of electric vehicle (EV) home energy management. The proposed hybrid system combines the execution of the Lichtenberg optimization algorithm and the heap-based optimizer; hence, it is named as LAHBO method. The main purpose of the proposed system is the reduction of costs and improvement of the power factor. Thus, two phases of optimization, such as Lichtenberg optimization algorithm–based cost minimization and heap-based optimizer–based power factor improvement. At initial phase, power conversation, and operating time of the smart home components are decided using the Lichtenberg optimization algorithm method. It is categorized into four groups, such as interruptible, uninterruptible, thermostatically controlled, and non-programmable loads. In second phase, the residential power factor at grid connection point is improved using the heap-based optimizer approach. Finally, the proposed system is carried out on MATLAB platform related to several existing approaches. The proposed method enhances the power factor and diminishes the cost than the existing method. The cost of proposed method is 0.16$ and existing approaches such as CGO, SMO, and SOA cost become 0.2, 0.3, and 0.35$, respectively.
p-adic local Langlands correspondence and geometry

This thesis concerns the geometry behind the p-adic local Langlands correspondence. We give a formalism of methods of Emerton, which would permit to establish the Fontaine-Mazur conjecture in the general case for unitary groups. Then, we verify that our formalism works well in the case of U(3) where we use the construction of Breuil-Herzig as the input for the p-adic correspondence.From the local viewpoint, we start a study of the modulo p and p-adic cohomology of the Lubin-Tate tower for GL_2(Q_p). In particular, we show that we can find the local p-adic Langlands correspondence in the completed cohomology of the Lubin-Tate tower.
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers

Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum error rate, and the test maximum accuracy for K_value selection with an accuracy of 86.24%. Where the distance metric has been assigned using the Euclidean approach. From previous models, it seems that Breast Cancer Grade2 is the most prevalent type. For the future perspective, a comparative study could be performed to compare the supervised and unsupervised data mining algorithms.
Numerical simulation of cavitating flow in 2D and 3D inducer geometries

A computational method is proposed to simulate 3D unsteady cavitating flows in spatial turbopump inducers. It is based on the code FineTurbo, adapted to take into account two‐phase flow phenomena. The initial model is a time‐marching algorithm devoted to compressible flow, associated with a low‐speed preconditioner to treat low Mach number flows. The presented work covers the 3D implementation of a physical model developed in LEGI for several years to simulate 2D unsteady cavitating flows. It is based on a barotropic state law that relates the fluid density to the pressure variations. A modification of the preconditioner is proposed to treat efficiently as well highly compressible two‐phase flow areas as weakly compressible single‐phase flow conditions.