Miracle-dz/UniFAR-FTUs huggingface dataset:
A NOTE ON NAVIER–STOKES EQUATIONS WITH NONORTHOGONAL COORDINATES

There are many fluid flow problems involving geometries for which a nonorthogonal curvilinear coordinate system may be the most suitable. To the authorsâ€™ knowledge, the Navierâ€“Stokes equations for an incompressible fluid formulated in terms of an arbitrary nonorthogonal curvilinear coordinate system have not been given explicitly in the literature in the simplified form obtained herein. The specific novelty in the equations derived here is the use of the general Laplacian in arbitrary nonorthogonal curvilinear coordinates and the simplification arising from a Ricci identity for Christoel symbols of the second kind for flat space. Evidently, however, the derived equations must be consistent with the various general forms given previously by others. The general equations derived here admit the well-known formulae for cylindrical and spherical polars, and for the purposes of illustration, the procedure is presented for spherical polar coordinates. Further, the procedure is illustrated for a nonorthogonal helical coordinate system. For a slow flow for which the inertial terms may be neglected, we give the harmonic equation for the pressure function, and the corresponding equation if the inertial effects are included. We also note the general stress boundary conditions for a free surface with surface tension. For completeness, the equations for a compressible flow are derived in an appendix. doi:10.1017/S144618111700058X
Recent results on quarkonium spectroscopy and exotic quarkonium-like resonances at Belle

In 2012, using a 121.4 fb−1 sample of data taken at the Υ(5S) resonance, Belle reported the observation of two new charged bottomonium-like resonances (Z± b (10610) and Z ± b (10650)) in the M(Υ(nS)π±) (n=1,2,3) and M(hbπ) (m=1,2) distributions of Υ(5S) → Υ(nS)π+π− and Υ(5S) → hb(mP) decays. We report the results of the search for neutral partners, “Z0 b ,” in Υ(5S)→ Υ(nS)π0π0, with evidence for the Z0 b(10610) at 4. 9σ with systematic errors. We also report the observation of the similar charged charmonium-like state Z±(3895) in the M(J/ψπ±) distribution in Y (4260)→ J/ψπ+π− decays.
Roads to objectivity: Quantum Darwinism, Spectrum Broadcast Structures, and Strong quantum Darwinism

The problem of objectivity, i.e. how to explain on quantum grounds the objective character of the macroscopic world, is one of the aspects of the celebrated quantum-to-classical transition. Initiated by W. H. Zurek and collaborators, this problem gained some attention recently with several approaches being developed. The aim of this paper is to compare three of them: quantum Darwinism, Spectrum Broadcast Structures, and strong quantum Darwinism. I will concentrate solely on foundations, analyzing how the three approaches realize the idea of objectivity and how they are related to each other. I will also briefly comment on the recent quantum Darwinism experiments.
Multiframe Maximum-Likelihood Tag Estimation for RFID Anticollision Protocols

Automatic identification based on radio frequency identification (RFID) is progressively being introduced into industrial environments, enabling new applications and processes. In the context of communications, RFID rely mostly on Frame Slotted Aloha (FSA) anticollision protocols. Their goal is to reduce the time required to detect all the tags within range (identification time). Using FSA, the maximum identification rate is achieved when the number of contending tags equals the number of contention slots available in the frame. Therefore, the reader must estimate the number of contenders and allocate that number of slots for the next frame. This paper introduces the new MFML-DFSA anticollision protocol. It estimates the number of contenders by means of a maximum-likelihood estimator, which uses the statistical information from several frames (multiframe estimation) to improve the accuracy of the estimate. Based on this expected number of tags, the algorithm determines the best frame length for the next reading frame, taking into account the constraints of the EPCglobal Class-1 Gen-2 standard. The MFML-DFSA algorithm is compared with previous proposals and found to outperform these in terms of (lower) average identification time and computational cost, which makes it suitable for implementation in commercial RFID readers.
PROPERTIES OF THE OLD OPEN CLUSTER CZERNIK 30

We present new photometric and spectroscopic data of the old open cluster Czernik 30. Wide field BVI photometry allows us to correct for the high field contamination by statistical subtraction to produce a color–magnitude diagram (CMD) that clearly reveals the cluster sequence. From spectra of stars in the cluster field obtained with the Hydra spectrograph on the Wisconsin-Indiana-Yale-NOAO 3.5 m telescope we determine a mean cluster velocity of +79.9 ± 1.5 km s−1 and provide membership information that helps further define the cluster giant branch and red clump. Stellar abundances for the brighter giants in the cluster indicate a mean metallicity of [Fe/H] = −0.2 ± 0.15. Fitting theoretical isochrones to the CMD we determine the following properties of Czernik 30: age = 2.8 ± 0.3 Gyr, (m − M)v = 14.8 ± 0.1, E(B − V) = 0.24 ± 0.06, and E(V − I) = 0.36 ± 0.04. Czernik 30 is an old, sub-solar metallicity cluster located at a Galactocentric radius of Rgc ∼ 13.3 kpc. Given its age and position just beyond the transition to a flat abundance gradient seen in the open cluster population, Czernik 30 provides an interesting target for future observations.
Order Matters: Sequence to sequence for sets

Sequences have become first class citizens in supervised learning thanks to the resurgence of recurrent neural networks. Many complex tasks that require mapping from or to a sequence of observations can now be formulated with the sequence-to-sequence (seq2seq) framework which employs the chain rule to efficiently represent the joint probability of sequences. In many cases, however, variable sized inputs and/or outputs might not be naturally expressed as sequences. For instance, it is not clear how to input a set of numbers into a model where the task is to sort them; similarly, we do not know how to organize outputs when they correspond to random variables and the task is to model their unknown joint probability. In this paper, we first show using various examples that the order in which we organize input and/or output data matters significantly when learning an underlying model. We then discuss an extension of the seq2seq framework that goes beyond sequences and handles input sets in a principled way. In addition, we propose a loss which, by searching over possible orders during training, deals with the lack of structure of output sets. We show empirical evidence of our claims regarding ordering, and on the modifications to the seq2seq framework on benchmark language modeling and parsing tasks, as well as two artificial tasks -- sorting numbers and estimating the joint probability of unknown graphical models.
The hidden dynamics of relativistic electrons (0.7–1.5 MeV) in the inner zone and slot region

We present measurements of relativistic electrons (0.7–1.5 MeV) in the inner zone and slot region obtained by the Magnetic Electron and Ion Spectrometer (MagEIS) instrument on Van Allen Probes. The data presented are corrected for background contamination, which is primarily due to inner‐belt protons in these low‐L regions. We find that ∼1 MeV electrons were transported into the inner zone following the two largest geomagnetic storms of the Van Allen Probes era to date, the March and June 2015 events. As ∼1 MeV electrons were not observed in Van Allen Probes data in the inner zone prior to these two events, the injections created a new inner belt that persisted for at least 1.5 years. In contrast, we find that electrons injected into the slot region decay on much faster timescales, approximately tens of days. Furthermore, we find no evidence of >1.5 MeV electrons in the inner zone during the entire time interval considered (April 2013 through September 2016). The energies we examine thus span a transition range in the steeply falling inner zone electron spectrum, where modest intensities are observed at 0.7 MeV, and no electrons are observed at 1.5 MeV. To validate the results obtained from the background corrected flux measurements, we also present detailed pulse‐height spectra from individual MagEIS detectors. These measurements confirm our results and also reveal low‐intensity inner zone and slot region electrons that are not captured in the standard background corrected data product. Finally, we briefly discuss efforts to refine the upper limit of inner zone MeV electron flux obtained in earlier work.
Approximation Theory of Tree Tensor Networks: Tensorized Multivariate Functions

We study the approximation of multivariate functions with tensor networks (TNs). The main conclusion of this work is an answer to the following two questions:"What are the approximation capabilities of TNs? "and"What is an appropriate model class of functions that can be approximated with TNs? "To answer the former: we show that TNs can (near to) optimally replicate $h$-uniform and $h$-adaptive approximation, for any smoothness order of the target function. Tensor networks thus exhibit universal expressivity w.r. t. isotropic, anisotropic and mixed smoothness spaces that is comparable with more general neural networks families such as deep rectified linear unit (ReLU) networks. Put differently, TNs have the capacity to (near to) optimally approximate many function classes -- without being adapted to the particular class in question. To answer the latter: as a candidate model class we consider approximation classes of TNs and show that these are (quasi-)Banach spaces, that many types of classical smoothness spaces are continuously embedded into said approximation classes and that TN approximation classes are themselves not embedded in any classical smoothness space.
Epidemiology of Celiac Disease in Iran: A Review

Celiac disease (CD) was traditionally believed to be a chronic enteropathy, almost exclusively affecting people of European origin. Celiac disease is the permanent intolerance to dietary gluten, the major protein component of wheat. The availability of new, simple, very sensitive and specific serological tests has shown that CD is as common in Middle Eastern countries as in Europe, Australia and New Zealand where the major dietary staple is wheat. A high prevalence of CD has been found in Iran, in both the general population and the at-risk groups, i.e. patients with type 1 diabetes or irritable bowel syndrome (IBS). In developing countries, serological testing in at risk groups is necessary for early identification of celiac patients. Clinical studies show that presentation with non-specific symptoms or a lack of symptoms is as common in the Middle East as in Europe. Wheat is a major component of the Iranian diet and exposure to wheat proteins induces some degree of immune tolerance, leading to milder symptoms that may be mistaken with other GI disorders. The implementation of gluten free diet (GFD) is a major challenge for both patients and clinicians in Iran, especially since commercial gluten-free products are not available in this area.
Approximation of Solutions to the Mixed Dirichlet-Neumann Boundary Value Problem on Lipschitz Domains

OF DISSERTATION APPROXIMATION OF SOLUTIONS TO THE MIXED DIRICHLET-NEUMANN BOUNDARY VALUE PROBLEM ON LIPSCHITZ DOMAINS We show that solutions to the mixed problem on a Lipschitz domain Ω can be approximated in the Sobolev space H(Ω) by solutions to a family of related mixed Dirichlet-Robin boundary value problems which converge in H(Ω), and we give a rate of convergence. Further, we propose a method of solving the related problem using layer potentials.
The truth about the effective dimension

The effective dimension of a model is a useful measure of its complexity. In linear models, the trace of the so‐called hat matrix is a convenient choice. It has strong links to variance estimation in mixed models, and it suggests straightforward partial effective dimensions for additive model components. Efron (2004) casts doubt on the trace of the hat matrix and advocates an alternative definition of the effective dimension, based on a covariance formula. Unfortunately, he uses the robust lowess smoother, which is strongly nonlinear. This blurs the issue and invalidates his conclusions. I show that the problems disappear if a linear smoother is being used. The computation of the trace of the hat matrix is much more efficient than using the covariance formula, which needs bootstrapping.
On n-quasi-(m,C)-isometric operators

ABSTRACT In this paper, we introduce the class of n-quasi- -isometric operator on a Hilbert space which is a variation of -isometric operators Chō M, Ko E, Lee JE. [On -isometric operators. Complex Anal Oper Theory. 2016;10:1679–1694]. An operator is said to be n-quasi- -isometric if for some positive integers n and m. We study this class of such operators and give some of their basic properties.
External approximation of bifurcation problems

— This paper deals with an external approximation of bifurcation problems. It is a continuation of the articles Descloux, Rappaz [5], [6]. Résumé. — Le sujet est Vapproximation extérieure du problème de la bifurcation. Cet article peut être regardé comme la continuation des articles Descloux, Rappaz [5], [6].
Time-lapse and slow-motion tracking of temperature changes: response time of a thermometer

We propose the use of a smartphone based time-lapse and slow-motion video techniques together with tracking analysis as valuable tools for investigating thermal processes such as the response time of a thermometer. The two simple experimental activities presented here, suitable also for high school and undergraduate students, allow one to measure in a simple yet rigorous way the response time of an alcohol thermometer and show its critical dependence on the properties of the surrounding environment giving insight into instrument characteristics, heat transfer and thermal equilibrium concepts.
The Application of Theory of Action in the Formulation of Opportunity to Learn Strategies

This paper focuses on the application of theory of action in the formulation of opportunity to learn strategies. The strategies are explicitly outlined based on three domains of opportunity to learn, that are content coverage, teaching practices and teaching quality. The explicit strategies for each opportunity to learn domain are believed to help teachers visualize specific actions that can be implemented in order to maximize students’ opportunity to learn, and hence improve students’ achievement. Furthermore, the visible, clear and systematic delineated strategies can be used as guidelines to uncover any undesirable results that require prompt refinement.
PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration

The existence of a lot of redundant information in convolutional neural networks leads to the slow deployment of its equipment on the edge. To solve this issue, we proposed a novel deep learning model compression acceleration method based on data distribution characteristics, namely Pruning Filter via Gaussian Distribution Feature(PFGDF) which was to found the smaller interval of the convolution layer of a certain layer to describe the original on the grounds of distribution characteristics . Compared with revious advanced methods, PFGDF compressed the model by filters with insignificance in distribution regardless of the contribution and sensitivity information of the convolution filter. The pruning process of the model was automated, and always ensured that the compressed model could restore the performance of original model. Notably, on CIFAR-10, PFGDF compressed the convolution filter on VGG-16 by 66:62%, the parameter reducing more than 90%, and FLOPs achieved 70:27%. On ResNet-32, PFGDF reduced the convolution filter by 21:92%. The parameter was reduced to 54:64%, and the FLOPs exceeded 42%
Energy condition of isothermal magnetoelectric switching of perpendicular exchange bias in Pt/Co/Au/Cr2O3/Pt stacked film

Energy condition for isothermal reversible magnetoelectric switching of exchange bias was investigated using Pt/Co/Au/Cr2O3/Pt stacked films with different thicknesses of the antiferromagnetic layer (tAFM). We discussed the effective magnetic anisotropy energy of the antiferromagnetic layer ( K AFM eff ), the interface exchange coupling energy (JINT), and the offset electric field (E0). The dependence of K AFM eff on tAFM suggested that the magnetic domain wall motion significantly influenced the switching of the electric-field-induced magnetization similar to an ordinal ferromagnet. Below 0.025 mJ/m2, JINT was equal to the exchange anisotropy energy (JK), and above 0.025 mJ/m2, JINT exceeded JK, suggesting that JK is restricted by the magnetic domain wall energy. The dependence of E0 on tAFM revealed that E0 mainly arose from the interfacial uncompensated antiferromagnetic moment. The obtained results suggest that the energetic interpretation of static switching of electric-field-induced magnetization in Cr2O3 was similar to that of the ordinary ferromagnetic materials.Energy condition for isothermal reversible magnetoelectric switching of exchange bias was investigated using Pt/Co/Au/Cr2O3/Pt stacked films with different thicknesses of the antiferromagnetic layer (tAFM). We discussed the effective magnetic anisotropy energy of the antiferromagnetic layer ( K AFM eff ), the interface exchange coupling energy (JINT), and the offset electric field (E0). The dependence of K AFM eff on tAFM suggested that the magnetic domain wall motion significantly influenced the switching of the electric-field-induced magnetization similar to an ordinal ferromagnet. Below 0.025 mJ/m2, JINT was equal to the exchange anisotropy energy (JK), and above 0.025 mJ/m2, JINT exceeded JK, suggesting that JK is restricted by the magnetic domain wall energy. The dependence of E0 on tAFM revealed that E0 mainly arose from the interfacial.
HUBUNGAN MINAT BELAJAR DAN HASIL BELAJAR PADA MATA PELAJARAN MATEMATIKA DI SMK YADIKA BANDAR LAMPUNG

Penelitian ini bertujuan untuk mengetahui adanya pengaruh minat belajar terhadap hasil belajar matematika pada kelas XII di SMK Yadika Bandar Lampung. Metode penelitian yang digunakan adalah metode survey dengan analisis korelasional, dengan jumlah sampel sebanyak 30 orang, yang diambil menggunakan teknik simple random sampling. Instrumen yang digunakan adalah instrumen pengisian angket yang terdiri dari 32 soal. Dari hasil penelitian perhitungan analisis regresi minat belajar dengan prestasi belajar matematika diperoleh persamaan Y’ = 66,598 + 0,096X dengan Nilai t-hitung = t-tabel = 2,447 hal ini menunjukkan bahwa regresi X atas Y berpola linear. Sedangkan untuk pengujian hipotesis, diperoleh koefisien korelasi X terhadap Y koefisien determinasi sebesar 1,75% sehingga Ho diterima pada taraf 0,05. Maka kesimpulannya tidak terdapat hubungan yang signifikan antara minat belajar terhadap hasil belajar matematika.
Virtual Assessment of air Pollution Dispersion from Anthropogenic Sudden Explosion

The control of air pollutants from anthropogenic sources seems almost impossible due to numerous influencing factors present in the atmosphere. In this study, we carried out a virtual mathematical experimentation using Math CAD, Mat lab and analytical approximation to estimate the dimensional impact of initial pollutant plume cloud from a sudden volcanic blast and the dynamics of its wind field. The high point of the experimentation is the period of the first one-tenth of a second (1 decisecond) to 1 min (60 s) of the blast at the point source. We also assessed the long range air pollution dispersion within the first 1 to 10 min of plume cloud released under practical assumptions. The model revealed a plume cloud impact of 6.8×107 μgm−3 in the first 1 millisecond (0.01 s) which decayed suddenly to a value of 1.7×107 μgm−3 in the first 1 deci-second (0.1 s). The impact concentration at the point source by the end of the first second (1.0 s) was 3.2×105 μgm−3 which implied a 99.5% sudden decay when compared with 0.01 s concentration value at the emission point source. It is observed that air pollutants released from explosives/blasts get transported into the atmosphere in the first few seconds by forceful injection instead of by gradual dispersion as is the case with normal air pollutants plume releases. A mathematical control process was propounded (which is still subject to further research) to reduce the quick flow of air pollutants
Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems

This article presents an approach to integrate a Pareto dominance concept into a comprehensive learning particle swarm optimizer (CLPSO) to handle multiple objective optimization problems. The multiobjective comprehensive learning particle swarm optimizer (MOCLPSO) also integrates an external archive technique. Simulation results (obtained using the codes made available on the Web at http://www.ntu.edu.sg/home/EPNSugan) on six test problems show that the proposed MOCLPSO, for most problems, is able to find a much better spread of solutions and faster convergence to the true Pareto‐optimal front compared to two other multiobjective optimization evolutionary algorithms. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 209–226, 2006.
COMMON FIXED POINT THEOREMS FOR PAIRS OF COMPATIBLE MAPPINGS OF TYPE (A)

I n this paper, we prove some common fixed point theorems for pairs of compatible mappings of type (A), A-compatible mappings and S-compatible mappings satisfying contractive condition of integral type in a complete metric space. The result of this paper extends and generalized the results of Aage and Salunke [1], Branciari[2], Murthy[5], Pathak and Khan[6], Shahidur Rahman et al. [9],Sharma and Sahu [10], for generalized contraction of integral type.