Temporal correlations of the sentiment content in consecutive sentences are studied based on a large corpus of the world-famous literary texts in four major European languages (English, French, German, and Spanish). F...
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The rapidity-dependent directed flow of particles produced in a relativistic heavy-ion collision can be generated in the hydrodynamic expansion of a tilted source. The asymmetry of the pressure leads to a buildup of a...
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The rapidity-dependent directed flow of particles produced in a relativistic heavy-ion collision can be generated in the hydrodynamic expansion of a tilted source. The asymmetry of the pressure leads to a buildup of a directed flow of matter with respect to the collision axis. The experimentally observed ordering of the directed flow of baryons, pions, and antibaryons can be described as resulting from the expansion of a baryon inhomogeneous fireball. An uneven distribution of baryons in the transverse plane leads to a difference in the collective push for protons and antiprotons. Precise measurements of the collective flow of identified particles as a function of rapidity could serve as a strong constraint on mechanism of baryon stopping in the early phase of the collision.
This paper describes the results of experimental and numerical studies of airflow through the nasal cavities of human. The flow geometry obtained from the CT scan is used to produce a 3D printout for the experimental ...
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This paper is concerned with the existence and multiplicity of solutions for singular Kirchhoff-type problems involving the fractional p-Laplacian *** precisely,we study the following nonlocal problem:{M (∫∫_(R2N)|x...
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This paper is concerned with the existence and multiplicity of solutions for singular Kirchhoff-type problems involving the fractional p-Laplacian *** precisely,we study the following nonlocal problem:{M (∫∫_(R2N)|x|^(α1p)|y|^(α2p)|u(x) − u(y)|^(p)/|x − y|^(N+ps) dxdy)L_(p)^(s)u = |x| ^(β)f(u) in Ω,u = 0 in R^(N) \ Ω,where L_(p)^(s) is the generalized fractional p-Laplacian operator,N≥1,s∈(0,1),α_(1),α_(2),β∈R,Ω■R^(N) is a bounded domain with Lipschitz boundary,and M:R0^(+)→R0^(+),f:Ω→R are continuous ***,we introduce a variational framework for the above ***,the existence of least energy solutions is obtained by using variational methods,provided that the nonlinear term f has(θ_(p-1))-sublinear growth at ***,the existence of infinitely many solutions is obtained by using Krasnoselskii’s genus ***,we obtain the existence and multiplicity of solutions if f has(θ_(p-1))-superlinear growth at *** main features of our paper are that the Kirchhoff function may vanish at zero and the nonlinearity may be singular.
Deep learning has contributed greatly to many successes in artificial intelligence in recent years. Breakthroughs have been made in many applications such as natural language processing, speech processing, or computer...
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Deep learning has contributed greatly to many successes in artificial intelligence in recent years. Breakthroughs have been made in many applications such as natural language processing, speech processing, or computer vision. Recently, many techniques have been implemented to enable the training of increasingly larger and deeper neural networks. Today, it is possible to train models that have thousands of layers and hundreds of billions of parameters on powerful GPU or TPU clusters. Large-scale deep models have achieved great success, but the enormous computational complexity and gigantic storage requirements make it extremely difficult to implement them in real-time applications, especially on devices with limited resources, which is very common in the case of offline inference on edge devices. On the other hand, the size of the dataset is still a real problem in many domains. Data are often missing, too expensive, or impossible to obtain for other reasons. Ensemble learning is partially a solution to the problem of small datasets and overfitting. By training many different models on subsets of the training set, we are able to obtain more accurate and better-generalized predictions. However, ensemble learning in its basic version is associated with a linear increase in computational complexity. We check if there are methods based on Ensemble learning which, while maintaining the generalization increase characteristic of ensemble learning, will be immediately more acceptable in terms of computational complexity. As part of this work, we analyze the various aspects that influence ensemble learning: We investigate methods of quick generation of submodels for ensemble learning, where multiple checkpoints are obtained while training the model only once. We analyzed the impact of the ensemble decision-fusion mechanism and checked various methods of sharing the decisions including voting algorithms. Finally, we used the modified knowledge distillation framework as a decis
Electricity price forecasts play a crucial role in making key business decisions within the electricity markets. A focal point in this domain are probabilistic predictions, which delineate future price values in a mor...
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Obtaining information from a quantum system through a measurement typically disturbs its state. The postmeasurement states for a given measurement, however, are not unique and highly rely on the chosen measurement mod...
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Obtaining information from a quantum system through a measurement typically disturbs its state. The postmeasurement states for a given measurement, however, are not unique and highly rely on the chosen measurement model, complicating the puzzle of information disturbance. Two distinct questions are then in order. First, what is the minimum disturbance a measurement may induce? Second, when a fixed disturbance occurs, how informative is the possible measurement in the best-case scenario? Here we propose various approaches to tackle these questions and provide explicit solutions for the set of unbiased binary qubit measurements and postmeasurement state spaces that are equivalent to the image of a unital qubit channel. In particular, we show there are different tradeoff relations between the sharpness of this measurement and the average fidelity of the premeasurement and postmeasurement state spaces as well as the sharpness and quantum resources preserved in the postmeasurement states in terms of coherence and discordlike correlation once the measurement is applied locally.
Applications of the Mössbauer spectroscopy (MS) in the investigation of Fe-Cr alloys are reviewed. A high sensitivity of the hyperfine magnetic field to the presence of Cr atoms in the vicinity of the probe Fe at...
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The field of Abstract Visual Reasoning (AVR) encompasses a wide range of problems, many of which are inspired by human IQ tests. The variety of AVR tasks has resulted in state-of-the-art AVR methods being task-specifi...
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Rendering high-polygonal models from distant perspectives has certain performance issues related to high density of subpixel triangles, which can be solved by levels of detail, a classical optimization method. Since a...
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