Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithm for the solution of elastoplastic half-space impact: Force-indentation linearisation method

The governing equation of a half-space impact is generally nonlinear and it is normally solved using numerical techniques that are mostly conditionally stable and require many iteration steps for convergence of the solution. In this paper, we present the force-indentation linearisation method (FILM), an approximate technique that produces closed-form solutions of piecewise linearisation of the governing nonlinear differential equation and is capable of producing accurate impact response for an elastoplastic half-space impact. In contrast to the existing numerical techniques, which discretise the impact force or variable of interest in the time-domain, the present technique discretises the impact force with respect to the indentation using successive piecewise linear approximations. Generalised closed-form solutions were derived for each piecewise approximation, and this was used to develop an iterative algorithm for updating the solutions from one piecewise approximation to the next. The results of the present technique matched with results obtained by direct numerical integration of the governing nonlinear differential equation for a half-space impact, and the FILM was found to converge to the results of the numerical solution after a few iterations, typically between five and 10 iterations. The FILM is simple, is inherently stable, converges quickly, gives accurate results and can be implemented manually; these features make it potentially more attractive than the comparable numerical methods.
Neurociência da música e ações da musicoterapia nos transtornos mentais: uma revisão sistemática

Investigar o potencial musical no encéfalo humano como ferramenta terapêutica nos transtornos mentais. Realizou-se uma revisão sistemática com busca e seleção de estudos via Scielo, PubMed, Capes e BVS, relacionando a musicoterapia aos transtornos mentais. Para a busca, considerou-se publicações no período 2015 a 2020 em português ou inglês. Foram avaliados 11 artigos. A musicoterapia tem crescente destaque no manejo psicopatológico, possuindo diferentes aplicações terapêuticas, elevando a autopercepção e autorrealização, reduzindo ansiedade, depressão e afeto negativo. Evidenciou-se modificações encefálicas com aumento na conectividade funcional insular em esquizofrênicos e aumento da massa cinzenta no Tinnitus. Ademais, a musicoterapia aprimorou a resposta comportamental e relações interpessoais de idosos institucionalizados com demência e pacientes com Transtorno do Espectro do Autismo. A musicoterapia mostra forte potencial terapêutico nos transtornos mentais, induzindo alterações psicofisiológicas e cognitivo-comportamentais, sendo uma terapia eficaz, não invasiva e de baixo custo.
The partial-equilibrium approximation in reacting flows

Complex reaction systems that are subject to the partial‐equilibrium approximation are analyzed. In order to take proper account of equilibrium and finite rate reactions, a distinction is made between linearly independent and dependent species and reactions, respectively. The assumption of partial equilibrium removes short time scales from the problem and leads to a reduction in the number of independent thermodynamic variables. Making use of a fundamental property of equilibrium reactions, a general formulation for partial chemical equilibrium in complex reaction systems is obtained. Furthermore, a partially frozen sound speed is defined and an analytical expression for this sound speed is given. The concept of partial chemical equilibrium is applied to high‐speed reacting flows. A characteristic formulation of the conservation and rate equations is presented. Finally, a high‐enthalpy flow, namely the expansion of high‐temperature air through the axisymmetric nozzle of a shock tunnel, is calculated using the method of lines.
ON MEROMORPHIC VECTOR FIELDS ON PROJECTIVE SPACES

Fix integers n and r with n > 2 and r > 0. A section s E HO(Pn, TPn(r)) was called [GK] a meromorphic vector field of degree r (on pn); let Z := (s)0 be its zero locus; s was called nondegenerate if dim (Z) = 0 and Z is reduced, i.e. if s has only isolated zeroes and each zero has multiplicity one. It was proved in [GK] that a nondegenerate meromorphic vector field is uniquely determined by its zero locus and that its zero locus is stable in the sense of [Mu]. Set x(n, r) := cn(TPn(r)) = ((r + 1)n+l 1)/r (the last equality following from the Euler's sequence). It is a natural problem to know if, for a given integer y < x(n, r) and a given set Z of y points of pn, there is a nondegenerate meromorphic vector field of degree n vanishing on Z; we can ask also for the dimension of such vector fields. We work over an algebraically closed field K (but of course the interesting case is when K is the complex number field). For a real number u, let [u] be its integral part; set w(n, r) := [(h0(Pn, TPn(r)) 1)/n]; note that by the Euler's sequence we have ho(Pn, TPn(r)) = (n+ 1)((n+r+ 1)! /(n! (r+ 1)! ))((n+r)! /(n! r! ). Here are the main results of this paper.
Magnetically-actuated hydrogel-based achiral planar microswimmers for SERS detection: In situ coprecipitation for continuous loading of iron oxide nanoparticles

Ultraviolet lithography is a very promising technology used for the batch fabrication of biomedical microswimmers. However, creating microswimmers that can swim at low Reynolds number using biocompatible materials while retaining strong magnetic properties and excellent biomedical functionality is a great challenge. Most of the previously reported biomedical microswimmers possess either strong magnetic properties by using non-biocompatible nickel coating or good biocompatibility by using iron oxide particle-embedded hydrogel with weak magnetism, but not both. Alternatively, iron oxide nanoparticles can be coated on the surface of microswimmers to improve magnetic properties; however, this method limited the usability of the microswimmers’ surfaces. To address these shortcomings, this work utilized an in situ synthesis technique to generate high magnetic content inside hydrogel-based achiral planar microswimmers while leaving their surfaces free to be functionalized for SERS detection. The hydrogel matrices of the magnetically actuated hydrogel-based microswimmers were first prepared by ultraviolet lithography. Then, the high concentration of iron oxide was achieved through multiple continuous in situ coprecipitation cycles. Finally, the SERS detection capability of magnetically actuated hydrogel-based microswimmers was enabled by uniformly growing silver nanoparticles on the surface of the microswimmers. In the motion control tests, the microswimmers showed a high swimming efficiency, high step-out frequency, and consistent synchronized motion. Furthermore, the magnetically actuated hydrogel-based microswimmers were able to improve the detection efficiency of analytes under magnetic guidance.
An Ensemble-Based Machine Learning Model for Forecasting Network Traffic in VANET

Vehicular Ad-hoc Networks (VANETs), as the most significant element of the Intelligent Transportation Systems (ITS), have the potential to enhance traffic efficiency and road safety by making the transportation system smarter and are still at the initial point of development. In this paper, we propose an ensemble-based machine learning model for network traffic prediction in VANET. We take advantage of Ensemble Learning (EL), which combines different Machine Learning (ML) models to achieve better performance and improve accuracy. We consider the most informative attributes of the VANET dataset using Boruta and LightGBM as ensemble feature selection methods. Our proposed model is based on Stacking Ensemble Learning with Booster Model (STK–EBM) designed with a stacking ensemble of heterogeneous ML models. The framework of the proposed model consists of two layers, including a base layer and a meta layer. The first layer integrates Random Forest (RF), K-Nearest Neighbor (KNN) and XGBoost as a booster of the base learners. An optimized Logistic Regression (LR) employs as our meta learner in the second layer. We evaluate the performance of our model considering classification metrics and then compare it with the most popular traffic predictive models. Simulation results show that the STK–EBM model gives a more stable prediction than the single algorithm, as well as better overall performance in terms of prediction accuracy and execution time.
Initial misfit dislocations in a graded heteroepitaxial layer

We show that for a mismatched heteroepitaxial layer with linear compositional grading, the first misfit dislocations will be introduced at a finite distance yC from the substrate interface. This is of practical as well as fundamental importance; it alters the value of the critical layer thickness for lattice relaxation and it moves the misfit dislocations away from the interface, where contaminants and defects may cause dislocation pinning or mobility reduction. We have calculated the position of the initial misfit dislocations yC for linearly graded Si1−xGex/Si(001) heteroepitaxial layers with lattice mismatch given by f=Cfy, where Cf is the grading coefficient and y is the distance from the interface. The distance of the first misfit dislocations from the interface yC decreases with increasing grading coefficient but can exceed 40 nm in layers with shallow grading (|Cf|<12 cm−1). For the range of grading coefficients investigated, yC varies from 6% to 11% of the critical layer thickness. Based on the mo.
Peningkatan Berpikir Kritis Siswa Smp Dalam Pembelajaran IPA Melalui Model Pembelajaran Problem Based Learning

Berfikir kritis adalah salah satu proses yang berjalan searah mencakup interaksi dari suatu rangkaina perkiran dan presepsi. Tujuan penelitian ini adalah untuk menguji pengaruh paradigma pembelajaran berbasis masalah terhadap kemampuan berpikir kritis siswa SMP dalam pembelajaran IPA. Penelitian ini menggunakan tata cara analisis. Model penelitian Tindakan kelas untuk mendorong pemikiran kritis dalam pembelajaran IPA dengan pembelajaran pemecahan masalah melalui perbandingan antara pre-test dan post test dari 15 artikel yang serupa sebagai perbandingan melaui uji pair sample test dan untuk mengetahui seberaba besar pengaruhnya menggunakan effect size. Berdasarkan hasil kajian meta analisis didapatkan bahwa sebesar 1,87 yang menunjukan nilai pengaruh yang besar pada perhitungan effect size. Berdasarkan temuan tersebut, disimpulkan penerapan pembelajaran berbasis masalah pada pembelajaran IPA memiliki dampak yang cukup besar terhadap ketrampilan berpikir kritis pada siswa SMP.
Exploring the referential range of etymologically-related lexical pairs in the language of the Qur’an: A cognitive-semantic approach

Abstract The present study conducts a cognitive-semantic analysis of etymologically-related lexical pairs in the language of the Qur’an. Based on objective selection criteria, the lexical pair rīĥ (a singular form literally meaning wind) and riyāĥ (a plural form literally meaning winds) has been claimed to be representative of the final data set, which includes 20 lexical pairs. Building on the theoretical underpinnings of descriptive semantics and frame semantics, the analysis sought to fulfill three main objectives: (a) identifying the referential range of the pair rīĥ and riyāĥ and its central reference point; (b) explaining the way the historical and theological context helps to mark the connotations associated with each sense in the referential range; and (c) sorting the discourse functions communicated through the cognitive frame(s) evoked by such a lexical pair. Findings showed that the central cognitive frame of both lexical items is that of moving air. However, rīĥ has developed, through metaphorical extension, two other senses that are not applicable to riyāĥ: power/predominance and smell. Finally, both lexical items have been proven to have positive, negative, and neutral connotations that have been divinely manipulated to perform various discourse functions.
A new approach for flux and speed estimation in induction motor

A structure of the induction machine flux and speed observer is proposed. The observer is designed in the stationary frame of references to avoid errors affiliated with the coordinate transformations. In order to ensure the convergence in any operational conditions a nonlinear additional term is added to the observer structure. Full stability analysis based on the Lyapunov stability method is derived. The results are confirmed by the simulation results.
RF-BiLSTM Neural Network Incorporating Attention Mechanism for Online Ride-Hailing Demand Forecasting

Accurately predicting online ride-hailing demand can help operators allocate vehicle resources on demand, avoid idle time, and improve traffic conditions. However, due to the randomness and complexity of online ride-hailing demand data, which are affected by many factors and mostly time-series in nature, it is difficult to forecast accurately and effectively based on traditional forecasting models. Therefore, this study proposes an online ride-hailing demand forecasting model based on the attention mechanism of a random forest (RF) combined with a symmetric bidirectional long short-term memory (BiLSTM) neural network (Att-RF-BiLSTM). The model optimizes the inputs and can use past and future data to forecast, improving the forecasting precision of online ride-hailing demand. The model utilizes a random forest to filter and optimize the input variables to reduce the neural network complexity, and then an attention mechanism was incorporated into the BiLSTM neural network to construct a demand forecasting model and validate it using actual Uber pickup data from New York City. Compared with other forecasting models (Att-XGBoost-BiLSTM, Att-BiLSTM, and pure LSTM), the results show that the proposed symmetrical Att-RF-BiLSTM online ride-hailing demand forecasting model has a higher forecasting precision and fitting degree, which indicates that the proposed model can be satisfactorily applied to the area of online ride-hailing demand.
Effects of void size and gas content on electrical breakdown in lightweight, mechanically compliant, void-filled dielectrics

Dielectric potting materials (encapsulants) are used to prevent air breakdown in high-voltage electrical devices. We report breakdown strengths in void-filled encapsulants, stressed with unipolar voltage pulses of the order of 10 μs duration. High strengths, on the order of 100 kV mm−1, are measured under these test conditions. The materials studied include low-density open celled gel-derived foams with cell sizes of 4 μm or less, closed celled CO2-blown polystyrene and urethane foams, and epoxies containing 48 vol % of hollow glass microballoon (GMB) fillers. These last specimens varied the void gas (N2 or SO2) and also the void diameters (tens to hundreds of μm). Our measurements are thought to be directly sensitive to the rate of field-induced ionization events in the void gas; however, the breakdown strengths of the materials tested appeared to vary in direct proportion with the conventional Paschen-law gas-discharge inception threshold, the electric stress at which gas-ionization avalanches become po.
Die digitale Hashtag-Kampagne rund um #CoronaEltern und #CoronaElternRechnenAb: Twitter-Positionierungspraktiken in der Pandemie

As kindergartens and schools closed down during the first wave of the COVID-19 pandemic in Germany, two hashtags emerged on Twitter: #CoronaEltern (#CoronaParents) and #CoronaEltern­Rech­nenAb (#CoronaParentsDocumentTheCosts). In this paper, we examine the positioning practices around both hashtags as expres­sions of “digital activism” (Joyce 2010: VIII). One characteristic of the hashtag campaign is that political demands are hardly ever made di­rectly. Rather, the participants resort to five main linguistic patterns: (1) they address different target groups; (2) they refer to different protagonists; (3) in the subcorpus #CoronaEltern specifically, they constitute themselves as a collective through (4) the recurring use of first-person narratives; (5) and generalization and typification. Our findings show that #CoronaParents are not just parents in times of a pandemic: #CoronaParents are only those who see themselves as such, participating in an evolving, at times misunderstood commu­nity.
ERR-Net: Facial Expression Removal and Recognition Network With Residual Image

Facial expression recognition is an important part of computer vision and has attracted great attention. Although deep learning pushes forward the development of facial expression recognition, it still faces huge challenges due to unrelated factors such as identity, gender, and race. Inspired by decomposing an expression into two parts: neutral component and expression component, we define residual features and propose an end-to-end network framework named Expression Removal and Recognition Network (ERR-Net), which can simultaneously perform expression removal and recognition tasks. The residual features are represented in two ways: pixel level and facial landmark level. Our network focuses on interpreting the encoder’s output and corresponding its segments to expressions to maximize the inter-class distances. We explore the improved generative adversarial network to convert different expressions into neutral expressions (i.e., expression removal), take the residual images as the output, learn the expression components in the process, and realize the classification of expressions. Through sufficient ablation experiments, we have proved that various improvements added on the network have obvious effects. Experimental comparisons on two benchmarks CK+ and MMI demonstrate that our proposed ERR-Net surpasses the state-of-the-art methods in terms of accuracy.
Defect modes caused by twinning in one-dimensional photonic crystals

Propagation of electromagnetic waves in a one-dimensional photonic crystal with a twin-defect—a periodicity break where one half of the photonic structure is a mirror image of the other one—is studied using a transfer-matrix method. This work is done in the general framework of photonic structures composed of isotropic materials exhibiting both dielectric and magnetic properties. Both polarizations of electromagnetic waves impinging at oblique incidence on the structure are considered. We derive analytical expressions for the frequency of defect modes and for the enhancement of the electromagnetic field inside the defect. In particular, we discuss possibilities of tuning of defect levels for a photonic crystal structure with a two-layer elementary cell.
Fertilization and Global Warming Impact on Paddy CH4 Emissions

Introduction: This study aimed to assess the influence of experimental warming and fertilization on rice yield and paddy methane emissions. Methods: A free-air temperature increase system was used for the experimental warming treatment (ET), while the control treatment used ambient temperature (AC). Each treatment contained two fertilization strategies, (i) normal fertilization with N, P and K fertilizers (CN) and (ii) without N fertilizer input (CK). Results: The yield was remarkably dictated by fertilization (p < 0.01), but not warming. Its value with CN treatment increased by 76.24% compared to CK. Also, the interactive effect of warming and fertilization on CH4 emissions was insignificant. The seasonal emissions from warming increased by 36.93% compared to AC, while the values under CN treatment increased by 79.92% compared to CK. Accordingly, the ET-CN treatment obtained the highest CH4 emissions (178.08 kg ha−1), notably higher than the other treatments. Also, the results showed that soil fertility is the main driver affecting CH4 emissions rather than soil microorganisms. Conclusions: Fertilization aggravates the increasing effect of warming on paddy methane emissions. It is a daunting task to optimize fertilization to ensure yield and reduce methane emissions amid global warming.
A generalized approximation for the meshfree analysis of solids

This paper presents a new approach in the construction of meshfree approximations as well as the weak Kronecker‐delta property at the boundary, referred to as a generalized meshfree (GMF) approximation. The GMF approximation introduces an enriched basis function in the original Shepard's method. This enriched basis function is introduced to meet the linear or higher order reproducing conditions and at the same time to offer great flexibility on the control of the smoothness and convexity of the approximation. The construction of the GMF approximation can be viewed as a special root‐finding scheme of constraint equations that enforces that the basis functions are corrected and the reproducing conditions with certain orders are satisfied within a set of nodes. By choosing different basis functions, various convex and non‐convex approximations including moving least‐squares (MLS), reproducing kernel (RK), and maximum entropy (ME) approximations can be obtained. Furthermore, the basis function can also be translated or blended with other functions to generate a particular approximation for a special purpose. One application in this paper is to incorporate a blending function at the boundary based on the concept of local convexity for the non‐convex approximation, such as MLS, to acquire the weak Kronecker‐delta property. To achieve the higher order GMF approximation, two possible methods are also introduced. Several examples are presented to examine the effectiveness of various GMF approximations. Copyright © 2010 John Wiley & Sons, Ltd.
Localizing gauge theories

We study N = 2 supersymmetric gauge theories on toric four dimensional manifolds. We recall the notion of Ω-background and calculate the partition function of gauge theory in this background. As a result, we get generalizations of the formulae of the author for the theories on R4 and Nakajima-Yoshioka for the theories on R4 blown up at one point. In the case of compact toric space our results give an alternative derivation of Donaldson invariants, and generalize the results of Gottche-Zagier.
Statistical mechanical theory of cooperative phenomena. I: General theory of fluctuations, coherent anomalies and scaling exponents with simple applications to critical phenomena

A general method is proposed to study non-classical scaling behaviors of cooperative systems. This is based on the appearance of a “coherent anomaly” in mean-field-type or classical approximations of cooperative systems. The degree of approximation is analytically continued to construct a parameterized expression of a whole set of approximations, using Kubo's linear response theory. General relations between scaling (or critical) exponents and “coherent-anomaly exponents” are derived using the theory of envelope and are also obtained from a finite-degree-of-approximation scaling, which is inspired by Fisher's finite-size scaling. The present coherent-anomaly method (CAM) is promising for calculating analytically non-classical scaling exponents in cooperative phenomena. A general scheme of CAM in critical phenomena is presented. It is shown that even the combination of the Weiss and Bethe approximations gives rather good estimates of static and dynamic critical exponents.
Stabilization of input delayed systems via static state-feedback

This paper considers the problem of stabilization for input delayed systems. Using the descriptor representation, we derive a sufficient condition for stability of input delayed systems via static state-feedback. Furthermore, we give a robust stabilization condition for input delayed system whose coefficient matrices depend rationally on uncertainty parameters. Finally, an illustrative numerical example is given.