Miracle-dz/UniFAR-FTUs huggingface dataset:
The vanishing surface tension limit for the Hele-Shaw problem

In this paper, we show the existence of solutions of the Hele-Shaw problem in two dimensions in the presence of surface tension and for a general class of initial data. The limit problem from nonzero to zero surface tension will also be investigated. In the case of injection and when volume conservation holds, for a sufficiently small surface tension, we prove the existence and uniqueness of perturbed solutions with nonzero surface tension near solutions with zero surface tension. We also show that solutions with nonzero surface tension exist up to a finite time before a possible singularity occurs in which solutions with zero surface tension are well defined. In addition, in the finite time interval, we prove that the solutions with nonzero surface tension approach the solutions with zero surface tension as the surface tension coefficient goes to zero. In the case of suction, for sufficiently small surface tension, we prove the existence of perturbed solutions near solutions with zero surface tension in any initially smooth domains. In this case, the local existence time depends on the surface tension coefficient.
Permanent Magnet Synchronous Motor (PMSM) Speed Response Correction Using Fuzzy-PID Self-Tuning Controller Under Sudden and Gradual Load Variation

: The development and improvement of the control of electric motors has drawn the researchers' attention to the implementation of all types of controllers in motors, especially the permanent magnets, because of advantages such as high-power density in lower volumes, lower losses, higher efficiency, high speed performance range and etc. in comparison with other motors, as well as extensive use in the industries including robotics, military, medical
Time-Reduced Model for Multilayer Spiking Neural Networks

: Spiking neural networks (SNNs) is a type of biological neural network model, which is more biologically plausible and computationally powerful than traditional artificial neural networks (ANNs). SNNs can achieve the same goals as ANNs, and can build a large-scale network structure (i.e. deep spiking neural network) to accomplish complex tasks. However, training deep spiking neural network is difficult due to the non-differentiable nature of spike events, and it requires much computation time during the training period. In this paper, a time-reduced model adopting two methods is presented for reducing the computation time of a deep spiking neural network (i.e. approximating the spike response function by the piecewise linear method, and choosing the suitable number of sub-synapses). The experimental results show that the methods of piecewise linear approximation and choosing the suitable number of sub-synapses is effective. This method can not only reduce the training time but also simplify the network structure. With the piecewise linear approximation method, the half of computation time of the original model can be reduced by at least. With the rule of choosing the number of sub-synapses, the computation time of less than one-tenth of the original model can be reduced for XOR and Iris tasks.
Long short-term memory network based deep transfer learning approach for sales forecasting

Üretim ve hizmet sektörlerinde faaliyet gösteren firmalar, artan rekabet koşulları ile mücadele edebilmek için belirsizlik altında geleceğe yönelik çeşitli kararlar alırlar. Bu kritik kararlardan biri satış tahminidir. Dijital teknolojilerin yaygınlaşması ile derin öğrenme yaklaşımlarının satış tahmininde kullanımı artmaktadır. Derin öğrenme, başarılı sonuçlar vermesine rağmen büyük miktarda veri ile uzun eğitim sürelerine ihtiyaç duymaktadır. Bu duruma çözüm olarak problemler arası bilgi aktarımını sağlayan transfer öğrenme (TL) kullanılmaktadır. Transfer öğrenme, kaynak veriler ile modelin eğitimini ve hedef veriye aktarımını sağlamaktadır. Bu çalışmada, farklı ürünlerin satış tahmini modellerinden elde edilen bilginin gelecekteki tahmin modellerine aktarımını sağlamak üzere derin transfer öğrenme yaklaşımı önerilmiştir. Satış verisi tek değişkenli zaman serisi olarak ele alınmıştır. Kaynak veri seçiminde aktarılabilirlik ölçütü olarak hedef ve kaynak veri arasındaki gerçek cezalı düzenleme uzaklığı (ERP) kullanılmıştır. Seçilen kaynak veri ile zamansal bağımlılıkların modellenmesini sağlayan uzun kısa vadeli hafıza (LSTM) ağı eğitilmiştir. Ön eğitilen LSTM ağında parametre transferi yapılarak hedef veri için ERP-LSTM-TL tahmin modeli oluşturulmuştur. Çeşitli sektörlere ait satış veri kümelerinde yapılan deneysel çalışmalarda ERP-LSTM-TL, hedef veri ile eğitilen LSTM’e göre tahmin doğruluğunda ve eğitim süresinde iyileşme sağlamıştır. Önerilen yaklaşımın performansı klasik tahmin ve makine öğrenmesi yöntemlerinin performansları ile karşılaştırılmıştır. ERP-LSTM-TL karşılaştırılan yöntemlere göre istatistiksel olarak daha iyi sonuç vermiştir.
A signal conditioning module for denoising Electrocardiogram signals

In this work, we propose to use an optimal multiband filter with least mean square algorithm to design a signal conditioning module for denoising Electrocardiogram (ECG) signals contaminated with predominant noises. The module is implemented on a Field Programmable Gate Array (FPGA) hardware. The experimental results of the proposed module are investigated and compared using an ECGID database available on Physionet. Quantitative and qualitative analysis is performed using Signal to Noise Ratio (SNR), Mean Square Error (MSE), and quality indexes to assess the effectiveness of the module. The average values of SNR are 10.90124, and MSE is 0.001761, indicating the successful elimination of noises in the filtered ECG signal using the proposed module. The signal quality indexes also demonstrate that the relevant information for diagnosing cardiac functionality is preserved. Furthermore, the performance of the designed module is tested on ECG signals obtained from electrodes placed on the human body. The Spartan 3s500efg320-5 FPGA device is employed to implement the filter design module using the partial serial architecture.
Detection of False Data Injection Attack in Power System Based on Hellinger Distance

The deep integration of sensor, computer, and communication networks has dramatically improved the efficiency and operational performance of the electric grid. However, it also exposes the grid to rising threats of cyber-physical attacks. False data injection attack (FDIA) is one of the most representative attacks. To improve the security of grid operation, we propose a Hellinger-distance-based FDIA detection method by tracking the dynamic characteristics of measurement variations at adjacent moments. First, the irrelevant components of measured data are sieved out by empirical modal decomposition. Second, the image transform algorithms are used to deal with the mapping of measurement variations to refine the distribution characteristics. Last, the discrepancies between the probability distributions are derived based on Hellinger distance to determine whether FDIA exists. Concerning state-variable attacks on different nodes, the method is tested using the IEEE 14-bus system. The results indicate that the proposed scheme has high-level detection precision for false data injection attacks.
Numerical Comparisons of Expected Log-Utility Maximization Problem with a Factor Model under Several Situations

In this paper, we consider effects of information, estimations and constraints on a portfolio optimization problem in mathematical finance. In particular, a portfolio optimization problem of investors who want to maximize their expected utility of their terminal wealth is considered. As our risky security model we adopt a factor model in which the growth rate depends on an exogenous factor. We assume several strategies whose differences come from information of markets, estimations of the factor and constraints of strategies, and we numerically investigate their effects on the expected utility. The logarithmic utility function as the utility function showing risk aversion investors is used in their paper.
Application of central differencing and low‐dissipation weights in a weighted compact nonlinear scheme

This paper proposes WCNS‐CU‐Z, a weighted compact nonlinear scheme, that incorporates adapted central difference and low‐dissipative weights together with concepts of the adaptive central‐upwind sixth‐order weighted essentially non‐oscillatory scheme (WENO‐CU) and WENO‐Z schemes. The newly developed WCNS‐CU‐Z is a high‐resolution scheme, because interpolation of this scheme employs a central stencil constructed by upwind and downwind stencils. The smoothness indicator of the downwind stencil is calculated using the entire central stencil, and the downwind stencil is stopped around the discontinuity for stability. Moreover, interpolation of the sixth‐order WCNS‐CU‐Z exhibits sufficient accuracy in the smooth region through use of low‐dissipative weights. The sixth‐order WCNS‐CU‐Zs are implemented with a robust linear difference formulation (R‐WCNS‐CU6‐Z), and the resolution and robustness of this scheme were evaluated. These evaluations showed that R‐WCNS‐CU6‐Z is capable of achieving a higher resolution than the seventh‐order classical robust weighted compact nonlinear scheme and can provide a crisp result in terms of discontinuity. Among the schemes tested, R‐WCNS‐CU6‐Z has been shown to be robust, and variable interpolation type R‐WCNS‐CU6‐Z (R‐WCNS‐CU6‐Z‐V) provides a stable computation by modifying the first‐order interpolation when negative density or negative pressure arises after nonlinear interpolation. Copyright © 2016 John Wiley & Sons, Ltd.
On Non-homogeneity of Takagi functions

Here we study the non-homogeneity via the Assouad dimension of graphs of Takagi functions $T_{a,b}(x):[0,1]\to\mathbb{R}$ with parameters $a,b$ such that the product $ab$ is a root of a Littlewood polynomial. Such algebraic integers can be proved to be dense in interval $[\frac{1}{2},2]$. We prove here that for those special parameters with $ab\geq 1$ there exist level sets of Takagi functions with Hausdorff dimension larger than $B-1$, where $B=2+\frac{\ln a}{\ln b}$ denotes the box dimension of such a Takagi function. Then followed by a certain box counting method we show that the Assouad dimension of graphs of such Takagi functions with special parameter $ab>1$ can be bounded from below and for large parameter $b$ the bound is non trivial, namely larger than $B$.
Full Immunization Coverage and Related Socio-Demographics Factors in Children Aged 12-23 Months Received in Albert Royer Hospital in Dakar, Senegal

: Introduction : Vaccination is one of the most effective and least costly public health interventions in the world. Methods : This is a cross-sectional, descriptive and analytical study of children aged 12-23 months received in consultation at the Albert Royer Children’s Hospital during the period from November 20, 2019 to January 20
Flat structure, phrasal variability and VSO

Contra the prevailing Chomskyan view of Modern Irish VSO, where the order is derived via verb movement, this paper proposes that Lexical-Functional Grammar provides a more explanatory account using a flat, VP-less structure. Using evidence from complex copular predicates, we show that the variability in category of the initial predicate is due to a categorial underspecification in the S phrase structure rule. Further, in order to account for the fact that both phrasal and head material can appear in this position, we propose a new kind of variable that holds over bar level. Finally, we account for the outward appearance of VP-like constituents by appealing to the fact that the language uses verbal nouns, and it has an NP rule, but no VP rule.
Irradiance Modeling Variance on Vertical Plane of Array Surfaces

Significant radiative transfer occurs outside of buildings, yet energy control systems are typically signaled by internal air temperature thermostats. As façades essentially behave as flat plate solar thermal collectors, while windows permit rooms to behave as cavity collectors, we propose that buildings may perform at higher economic efficiency with external signals. An analysis of measured irradiation for plane of array (POA) vertical surfaces was compared to modeled irradiance data (TRNSYS) to evaluate differences in error. The measured POA irradiation data integrates all irradiation components for a given orientation, collected on minute intervals for half of the year between the months of July and December. The data were available for the East, West, and North surfaces of the Energy Efficient Buildings Hub’s Building 101 in the Philadelphia Navy Yard. Modeled data was generated from global horizontal irradiation from a meteorological station in Avondale, Pennsylvania, located thirty three miles from the Philadelphia Navy Yard. Comparative analyses between irradiation data averaged over each hour and irradiance collected from Avondale, PA resulted in a weighted mean error of 36 W/m or 26%. Results align with findings of Gueymard (2010), particularly at minute interval time steps that are necessary for building controls.
Computational study of the aerodynamics of the gliding snake Chrysopelea Paradisi

Flying snakes exhibit an exceptional gliding mechanism without any added appendages that can aid gliding. Several studies on the mechanism have shown that the snake performs a ballistic dive from a height and glides through the air at high angles of attack of 35 degrees and above. Research has shown the morphing of their body structure from a cylindrical to a flattened shape with a rounder dorsal surface makes it possible for these creatures to not only perform glide but also various turning maneuvers. In this study, the variations of the lift, drag and normal force coefficients (CL, CD and CN) with glide angle are predicted by solving the three dimensional, steady, viscous, incompressible flow over the snake during its glide using CFD study. The three dimensional CFD analysis shows that the lift and normal force coefficients keep increasing increases with the glide angle even up to a high glide angle of 35 degrees which helps the snake to counteract the gravitational force. Further, the aerodynamic efficiency of the snake is still less than its maximum value at this glide angle, which is not predicted by twodimensional analysis. This study can aid in applications for security and defense.
Non-Monotonic Temperature Dependence of Coulomb Drag Peaks in Graphene

Coulomb drag is a direct measurement of the electron-electron interactions between two electronic layers. Graphene is a versatile electronic material with a high-degree of tunability opening up regimes that were not previously accessible. All previous theoretical studies of graphene Coulomb drag away from charge neutrality assume a spatially homogeneous carrier density which gives a peak in the Coulomb drag that decreases with temperature in contradiction to available experimental results. In this work, we develop an effective medium theory for Coulomb drag and show that including spatial inhomogeneity in the carrier density gives rise to a non-monotonic temperature dependence of the drag peaks that is in quantitative agreement with experimental data. Our results also show that at double-charge neutrality, there is a large negative momentum drag for correlated density fluctuations that competes with energy drag and is also non-monotonic with temperature. In addition, we show that when the density fluctuations in the two layers are correlated, the disordered theory has less symmetry than the homogeneous case, giving rise to a violation of Onsager reciprocity between the active and passive layers.
Validation of the toolkit for fake news awareness in social media

Fake news has gained attention in recent years, particularly among social media users. The quick spread of fake news has been made possible by the increased usage of social media as a platform to get the most recent news and information. As a consequence, it is getting harder to distinguish between real news and fake news. This essay will outline a study that evaluated the usefulness of a toolset for identifying false news. The first hypothesis is that an increase in media literacy will result in a rise in awareness of fake news. The second theory is that fake news toolkits significantly increase students’ and working adults’ awareness of false news. On the staff of a manufacturing company and an institution, a survey was undertaken. The organization’s employees were given approximately 150 questionnaires, and 110 responses were received. The project includes the creation of a web application-a false news awareness toolkit-that will raise user awareness of fake news in terms of knowledge, behaviour, and attitude among students and workers.
Composite Bite Blocks—An Indigenous, Simple, Fixed Class II Corrector

Fixed functional appliances are used at either the fag end of the growth spurt or after the completion of the same. We orthodontists are yet to come across an appliance which satisfies all the ideal requirements for a fixed functional appliance. Most disadvantages of the fixed functional appliances such as increase in lower anterior facial height, proclination of lower anteriors, constant breakages, and huge expenses were taken into consideration in the basic designing of this ingenious appliance. In this article, a simple fixed functional appliance was designed to function along with fixed appliance therapy to stimulate mandibular growth. After the initial leveling and aligning, 0.019 × 0.025 stainless steel posted arch wires were placed. The bite jumping blocks were fabricated in the upper and lower arches with light cure blue composite. Using indirect bonding trays they were bonded in position. The case finished in an ideal overjet and overbite with a balanced face. Cephalometric values demonstrate an advancement of the mandible.
Maximum genus orientable embeddings from circuit decompositions of dense eulerian graphs and digraphs

Suppose we have an eulerian (di)graph with a (directed) circuit decomposition. We show that if the (di)graph is sufficiently dense, then it has an orientable embedding in which the given circuits are facial walks and there are exactly one or two other faces. This embedding has maximum genus subject to the given circuits being facial walks. When there is only one other face, it is necessarily bounded by an euler circuit. Thus, if the numbers of vertices and edges have the same parity, a sufficiently dense (di)graph $D$ with a given (directed) euler circuit $C$ has an orientable embedding with exactly two faces, each bounded by an euler circuit, one of which is $C$. The main theorem encompasses several special cases in the literature, for example, when the digraph is a tournament.
Efficient 2D FD-K Modeling in Heterogeneous VTI Media

Summary An efficient 2D time-domain numerical modeling algorithm based on the hybrid finite-differencewavenumber (FD-K) method has been developed for the calculation of synthetic seismograms through heterogeneous isotropic and anisotropic (VTI) elastic grid models. The FD-K method is an extension of the Alekseev-Mikhailenko semi-analytical method of separation of variables to 2D VTI models with arbitrary lateral velocity variations. It represents a combination of the wavenumber (K-) transform with respect to the horizontal in-plane coordinate and a finite-difference (FD) scheme in the remaining vertical and time coordinates. We apply the K-transform to reduce the 2D wave equation to multiple 1D wave equations. Each of these 1D wave equations is an initial-boundary-value problem that can be solved by existing FD schemes. Examples show that the computer code is sufficiently accurate in full-waveform two-component modeling and stable with model varieties.
COMPASS: A Proposal for a Common Muon and Proton Apparatus for Structure and Spectroscopy

We propose to study hadron structure and hadron spectroscopy with high-rate hadron and muon beams and a new spectrometer to be built at the CERN SPS. The experiment can start up in 1999 and a program of physics measurements for an initial period of 5 more years is planned. The COMPASS Collaboration Universität Bielefeld, Bielefeld, Germany G. Baum, J. Kyynäräinen, A. Tripet Universität Bochum, Bochum, Germany R. Gehring, S. Goertz, W. Meyer, G. Reicherz Institut für Strahlenund Kernphysik, Universität Bonn, Bonn, Germany B.M. Barnett, J. Bisplinghoff, F. Hinterberger, H. Kalinowsky, E. Klempt, R. Maschuw, Chr. Straßburger Physikalisches Institut, Universität Bonn, Bonn, Germany F. Klein H.H. Wills Laboratory, University of Bristol, Bristol, United Kingdom S.L. McKennan, V.J. Smith Université de Bruxelles, Bruxelles, Belgium F. Binon, J.M. Frère, J.P. Stroot Chiba University, Chiba, Japan H. Kawai JINR, Dubna, Russia V. Artemov, M. Finger, M. Finger Jr, O.E. Gortchakov, A. Janata, Yu.F. Kisselev, V. Kurbatov, D.V. Peshekhonov, D. Pose, A.M. Rozhdestvensky, M.G. Sapozhnikov, I.A. Savin, M. Slunecka, G.I. Smirnov, L.G. Tkatchev, S.B. Vorozhtsov Universität Erlangen, Erlangen, Germany G. Anton, W. Eyrich, F. Stinzing, S. Wirth Universität Freiburg, Freiburg, Germany H. Fischer, J. Franz, H.J. Kessler, K. Königsmann, U. Landgraf, H. Schmitt, A. Simon, A. Witzmann CERN, Genève, Switzerland U. Wiedner Max-Planck-Institut für Kernphysik, Heidelberg, Germany W. Brückner, U. Dersch, F. Dropmann, I. Konorov, S. Masciocchi, S. Paul, J. Pochodzalla, B. Povh, L. Schmitt, J. Zimmer Physikalisches Institut der Universität Heidelberg, Heidelberg, Germany E. Chudakov, H.W. Siebert Helsinki University of Technology, Helsinki, Finland P. Berglund Kernforschungsanlage Jülich, Jülich, Germany D. Gronzka, K. Kilian, W. Oelert, K. Röhrich, T. Sefzick Universität Mainz, Mainz, Germany A. Bravar, D. von Harrach, E.M. Kabuß, A. Kotzinian, G.K. Mallot, U. Müller, J. Pretz, G. Rosner, A. Steinmetz, B. Volkemer, T. Walcher Miyazaki University, Miyazaki, Japan K. Takamatsu on leave of absence from Moscow State Univ., Moscow, Russia presently at CERN, Div. PPE, Geneva
How are the Firms’ Innovative Activities and Credit Rating Signals Received in the Market?

Firm innovativeness and financing capacity are critical signals to stakeholders as they are key drivers of firm performance and competitiveness and indicate the firm’s ability to fund its operations and growth initiatives. Based on signaling theory, this study investigates the signaling effect of a firm’s innovativeness and creditworthiness and examines its signaling effectiveness. Using Korean innovation data and Korea Investors Service financial data for nine years, the findings indicate that a firm’s technological innovation has a negative impact on its credit ratings, while non-technological innovation has a positive impact. Furthermore, a firm’s credit ratings positively impact its performance. The current study contributes to the literature on signaling theory by exploring the signaling effect of a firm’s innovativeness and creditworthiness. The findings provide insights for managers on how to send and monitor signals to stakeholders.