Miracle-dz/UniFAR-FTUs huggingface dataset:
Regularized particle filter with Langevin resampling step

The solution of an inverse problem involves the estimation of variables and parameters values given by the state‐space system. While a general (infinite‐dimensional) optimal filter theory [1, 2] exists for nonlinear systems with Gaussian or non‐Gaussian noise, applications rely on (finite‐dimensional) suboptimal approximations to the optimal filter for practical implementations. The most widely‐studied filters of this kind include the Regularized Particle Filter (RPF) [3, 4] and the Ensemble Square Root Filter (EnSRF) [5]. The latter is an ad‐hoc approximation to the Bayes Filter, while the former is rigorously formulated, based upon the Glivenko‐Cantelli theorem. By introducing a new global resampling step to the RPF, the EnSRF is proved to approximate the RPF in a special case.
Frequency shift attack on ‘plug-and-play’ quantum key distribution systems

Many imperfections in a practical quantum key distribution (QKD) system have been exploited by an eavesdropper (Eve) to attack the system. However, most of these attacks will introduce perturbations to the system while collecting information about the key. For example, the phase-remapping attack [Phys. Rev. A2007,75, 032314], in which Eve performs time shift on the signal pulse from the constant acting range of the phase modulation voltage to its rising edge to introduce an imperfection, results in an quantum bit error rate (QBER) of 14.6%, which is too high and will be discovered by careful users. In this paper, a frequency shift (FS) attack on ‘plug-and-play’ QKD systems with phase-coding BB84 protocol is proposed, in which Eve introduces an imperfection by the same method as she used in the phase-remapping attack. The most novel advantage of our FS attack is that Eve can get full information without introducing detectable QBER, which is more deceptive than the phase-remapping attack.
Geopolitical Influences and Language Contacts of the Ukrainian Speech Community of the Chelm and Podlachia Regions in the Kingdom of Poland (1815–1912)

Geopolitical Influences and Language Contacts of the Ukrainian Speech Community of the Chelm and Podlachia Regions in the Kingdom of Poland (1815–1912)This paper explores language contacts, unrecorded in Ukrainian-language texts, which occurred during a period of history when Ukrainian was a minority language. In order to reconstruct language contacts, I applied the theoretical framework of the social history of language. The database was constructed using metalinguistic evidence from secondary sources. The characterization of the macro-level of language contacts from the standpoint of the sociology of language was provided through the inductive method and the method of metalinguistic evidence interpretation. The findings of the article on the variable transition of native speakers from Ukrainian as a colloquial code to oral and written forms of Polish, Russian and (occasionally) to the written form of Ukrainian are relevant for studying language contacts in subsequent periods of the social history of Ukrainian, using the linguistic evidence available from the Ukrainian-language sources. Wpływy geopolityczne i kontakty językowe ukraińskiej społeczności językowej Chełmszczyzny i Podlasia w Królestwie Polskim (w latach 1815–1912)Przedmiotem artykułu są kontakty językowe w nieudokumentowanym tekstami ukraińskojęzycznymi okresie historii języka ukraińskiego jako języka mniejszości. W celu rekonstrukcji kontaktów językowych wykorzystano teoretyczne ramy społecznej historii języka. Bazę danych stanowią dowody metalingwistyczne pochodzące ze źródeł wtórnych. Opis makropoziomu kontaktów językowych z punktu widzenia socjologii języka został dokonany z zastosowaniem metody indukcyjnej oraz metody interpretacji dowodów metalingwistycznych. Wyniki przeprowadzonych badań, dotyczące zmiennego przechodzenia rodzimych użytkowników języka z języka ukraińskiego jako kodu gwarowego na formę ustną i pisemną języka polskiego i rosyjskiego oraz (okazjonalnie) na formę pisemną języka ukraińskiego, są ważne z punktu widzenia dalszych studiów nad kontaktami językowymi w kolejnych okresach historii społecznej języka ukraińskiego, opartych na dowodach językowych, pochodzących z pierwotnych źródeł ukraińskojęzycznych.
Ambiguities and Pragmatic Factors in the Units of Selection Controversy

The question "what is (are) the unit(s) of selection" can be interpreted in three different ways. These interpretations are discussed and it is shown that they prompt different answers; such units are shown to be individuals in the context of the given interpretation. One of these interpretations is argued, by examples, not always to have an unambiguously correct answer. An alternative approach to this question is sketched.
The evolution of single pulsars on a p–p˙ diagram

The evolution of single galactic field pulsars on a P–˙P diagram is considered. An unavoidable increase in the mean value of braking indices n averaged over many years, for pulsars with characteristic times τ in the range 4.5 107 years is established. The problem is solved by assuming that the birth of pulsars can be happen at the mentioned values, too. Such births occur, probably, as a result of disruption of binary systems after the second supernova explosion in high-mass X-ray binary systems. In these binaries, mass accretion on the surface of X-ray pulsars leads to a decrease in the magnetic field from its initial value B ≈ 1012–1013 G to B < 3.
Global optimization analysis of slope stability by simulated annealing with dynamic bounds and Dirac function

In slope stability analysis, the search for the minimum factor of safety is a difficult NP-hard global minimization problem as the objective function is non-smooth and non-convex and there are multiple local minima. The use of a simulated annealing method where the control variables are controlled within dynamic domains instead of the conventional static domains is proposed. A simple transformation technique for slopes with a soft band domain (equivalent to a Dirac function) is also proposed. With these improvements, the minimum factor of safety for complicated problems can be determined with high accuracy and reasonable computer time. The proposed algorithm is demonstrated to be efficient and effective for various difficult problems.
On solving two higher-order nonlinear PDEs describing the propagation of optical pulses in optic ﬁbers using the

The propagation of the optical solitons is usually governed by the nonlinear Schrödinger equations. In this article, the two variable ( G (cid:2) G , 1 G ) -expansion method is employed to construct the exact traveling wave solutions with parameters of two nonlinear PDEs namely, the (2 + 1)-dimensional nonlinear cubic–quintic Ginzburg– Landau equation and the (1 + 1)-dimensional resonant nonlinear Schrödinger’s equation with dual-power law nonlinearity which describe the propagation of optical pulses in optic ﬁbers. When the parameters are replaced by special values, the well-known solitary wave solutions of these equations rediscovered from the traveling waves. This method can be thought of as the generalization of well-known original ( G (cid:2) G ) -expansion method proposed by M. Wang et al. It is shown that the two variable ( G (cid:2) G , 1 G ) -expansion method provides a more powerful mathematical tool for solving many other nonlinear PDEs in mathematical physics.
Characterization of flow units in metallic glass through density variation

The evolution of flow units associated with the flow “defects” in metallic glass is characterized by monitoring the metallic glassy density change upon isothermal annealing far below their glass transition temperature. A meaningful function for the density variation with the concentration of flow units is obtained for the metallic glasses. We show that the correlation between the density variation and the flow unit have implications for understanding the fragility, structural heterogeneous, and structural relaxation behaviors in metallic glasses.
First report of Plagiorhynchus spp. in the Mallard Duck (Anas platyrhynchos) in Van, Turkey

A dead mallard duck (Anas platyrhynchos) was found in the Ercek district of Van province and was brought into Parasitology Department of Yuzuncu Yıl University. After the necropsy, some acanthocephalans were found in the intestinal wall of the mallard duck. Acanthocephalans were identified as Plagiorhynchus spp. according to their morphological pe-cularities. It is important because this case is the first report of this infection in a mallard duck in Turkey
A Numerical Technique for Computing Effective Thermal Conductivity of Fluid–Particle Mixtures

Periodic arrays of particles, foams, and other structures impregnated with a static fluid play an important role in heat transfer enhancement. In this article, we develop a numerical method for computing conduction heat transfer in periodic beds by exploiting the periodicity of heat flux and the resulting linear variation of mean temperature. The numerical technique is developed within the framework of an unstructured finite-volume scheme in order to enable the computation of effective thermal conductivity for complex fluid-particle arrangements. The method is applied to the computation of effective thermal conductivity of ordered as well as random beds of spheres and rods. The effects of varying surface area, aspect ratio, volume fraction, orientation, and distribution are studied for various solid-to-fluid conductivity ratios. Unlike classical theories which predict only a dependence on volume fraction, these direct simulations show that aspect ratio, distribution, and alignment of particles have an important influence on the effective thermal conductivity of the bed.
Package ‘goldilocks’

October 13, 2022 Title Goldilocks Adaptive Trial Designs for Time-to-Event Endpoints Version 0.3.0 Description Implements the Goldilocks adaptive trial design for a time to event outcome using a piecewise exponential model and conjugate Gamma prior distributions. The method closely follows the article by Broglio and colleagues <doi:10.1080/10543406.2014. 888569>, which allows users to explore the operating characteristics of different trial designs. License GPL-3 Encoding UTF-8 Depends R (>= 3.6.0), survival Imports dplyr, fastlogranktest, parallel, pbmcapply, PWEALL, rlang, stats Suggests covr, testthat (>= 3.0.0), knitr, rmarkdown Language en-US RoxygenNote 7.1. 1 Config/testthat/edition 3 VignetteBuilder knitr NeedsCompilation no Author Graeme L. Hickey [aut, cre] (<https://orcid.org/0000-0002-4989-0054>), Ying Wan [aut], Thevaa Chandereng [aut] (<https://orcid.org/0000-0003-4078-9176>, bayesDP code as a template), Becton, Dickinson and Company [cph] Maintainer Graeme L. Hickey <graemeleehickey@gmail.com> Repository CRAN Date/Publication 2021-05-10 08:20:11 UTC
Global solutions of non-Lipschitz S 2 – S p minimization over the positive semideﬁnite cone

The S 2 – S p minimization over the positive semideﬁnite cone is the semideﬁnite least squares problem with Schatten p -quasi (0 < p < 1) norm regularization term. It has wide applications in many areas including compressed sensing, control, statistics, signal and image processing, etc. In this paper, by developing the symmetric matrix p-thresholding operator representation theory, we establish the necessary condition for global optimal solutions of S 2 – S p minimization, and also provide the exact lower bound for the positive eigenvalues at global optimal solutions
Theory of relaxation oscillations in semiconductor quantum dot lasers

A microscopic approach combining rate equations for photon and electron/hole occupations with kinetic equations for Coulomb scattering rates involving quantum dot and wetting layer states in InAs∕GaAs quantum dot lasers is presented. The authors find strong damping of relaxation oscillations on a picosecond to nanosecond time scale depending on the type of the initial perturbation, similar to the damping observed in experiments by various groups. They show that the Coulomb interaction is crucial for an understanding of this characteristic strong damping.
Spectroscopic Verification of Barium Dwarf Candidates: The Analysis of HD 8270, HD 13551, and HD 22589

This work presents the abundance patterns of three barium dwarf candidates, HD 8270, HD 13551, and HD 22589, based on high-resolution optical spectra. This work also reports the spectroscopic stellar parameters, temperature, and microturbulent velocity, as well as the stellar surface gravity from a solution of excitation and ionization equilibria of Fe I and Fe II lines under the assumption of local thermodynamic equilibrium. The abundance analysis reveals that HD 8270, HD 13551, and HD 22589 have metallicities of [Fe/H] = -0.43, -0.28, and -0.12, respectively. It was found that the abundances of iron group and α-elements follow the abundance pattern of a disk population. The heavy-element abundance patterns of the three stars show enhancements by a factor of 4–8 with respect to the Sun. The abundances of the s-process elements are discussed and compared with other barium giants and dwarfs through diagrams involving the indices [hs/ls] and [s/Fe]. The metallicity distribution of barium giants and dwarfs is also discussed.
Nonlinear coloration of photochromic spiropyran solutions

An investigation was made of the two-photon photochromism of spiropyran solutions subjected to ruby laser radiation. The two-photon absorption cross section of spiropyran was calculated. At high laser radiation intensities the dependence of the optical density of the photoinduced form of spiropyran on the incident radiation intensity deviated from the square law. The cause of this deviation was considered.
Optical and Structural Property Change by the Thermal Decomposition of Amorphous Platinum Oxide Film

Refractive indices of amorphous platinum oxide film (a-PtO1.1 and a-PtO1.6) at the wavelength of 400 nm and 630 nm are evaluated. A transmittance measurement obtained during heating the film demonstrated an optical property change at 550–600°C. X-ray diffraction and Raman scattering measurements confirmed that the change derives from the thermal decomposition of PtOx. Furthermore, Pt particles (diameter: 20–30 nm) are formed when thin PtOx film (thickness: about 4 nm) is thermally decomposed.
Non-negative matrix factorization with local preservation for hyperspectral image dimensionality reduction

This letter presents a non-negative matrix factorization (NMF) with local preservation framework for hyperspectral image dimensionality reduction. The proposed method combines the NMF and local manifold learning techniques. It overcomes the drawback that the NMF does not consider local spatial information of the data space. In this framework, we take the local spatial information into the low-dimensional representations. In order to do that, we introduce two local manifold learning approaches: locally linear embedding and local tangent space alignment. The local geometric structure can be effectively modelled through these approaches. This framework is a general framework which also includes the NMF with Laplacian Eigenmaps method. The gradient descent approach is used to find the solution of the proposed models. In order to evaluate the developed method, the support vector machine (SVM) and the k-nearest neighbour (k-NN) approaches are used for hyperspectral image classification. Experiments are done on a hyperspectral image and the classification accuracies are compared. The proposed methods can improve the classification accuracies (by at least for SVM and by at least for k-NN) when comparing with the other approaches.
SIRL: Similarity-based Implicit Representation Learning

When robots learn reward functions using high capacity models that take raw state directly as input, they need to both learn a representation for what matters in the task --- the task "features" --- as well as how to combine these features into a single objective. If they try to do both at once from input designed to teach the full reward function, it is easy to end up with a representation that contains spurious correlations in the data, which fails to generalize to new settings. Instead, our ultimate goal is to enable robots to identify and isolate the causal features that people actually care about and use when they represent states and behavior. Our idea is that we can tune into this representation by asking users what behaviors they consider similar: behaviors will be similar if the features that matter are similar, even if low-level behavior is different; conversely, behaviors will be different if even one of the features that matter differs. This, in turn, is what enables the robot to disambiguate between what needs to go into the representation versus what is spurious, as well as what aspects of behavior can be compressed together versus not. The notion of learning representations based on similarity has a nice parallel in contrastive learning, a self-supervised representation learning technique that maps visually similar data points to similar embeddings, where similarity is defined by a designer through data augmentation heuristics. By contrast, in order to learn the representations that people use, so we can learn their preferences and objectives, we use their definition of similarity. In simulation as well as in a user study, we show that learning through such similarity queries leads to representations that, while far from perfect, are indeed more generalizable than self-supervised and task-input alternatives.
Inertial migration in pressure-driven channel flow: beyond the Segre-Silberberg pinch

We examine theoretically the inertial migration of a neutrally buoyant rigid sphere in pressure-driven channel flow, accounting for its finite size relative to the channel width (the confinement ratio). For sufficiently large channel Reynolds numbers\,($Re_c$), a small but finite confinement ratio qualitatively alters the inertial lift velocity profiles obtained using a point-particle formulation. Finite size effects are shown to lead to new equilibria, in addition to the well known Segre-Silberberg pinch locations. Consequently, a sphere can migrate to either the near-wall Segre-Silberberg equilibria, or the new stable equilibria located closer to the channel centerline, depending on $Re_c$ and its initial position. Our findings are in accord with recent experiments and simulations, and have implications for passive sorting of particles based on size, shape and other physical characteristics, in microfluidic applications.
Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach

Reinforcement Learning (RL) is currently one of the most commonly used techniques for traffic signal control (TSC), which can adaptively adjust traffic signal phase and duration according to real-time traffic data. However, a fully centralized RL approach is beset with difficulties in a multi-network scenario because of exponential growth in state-action space with increasing intersections. Multi-agent reinforcement learning (MARL) can overcome the high-dimension problem by employing global control of each local RL agent, but it also brings new challenges, such as failures of convergence caused by the non-stationary Markov Decision Process (MDP). In this paper, we introduce an off-policy nash deep Q-Network (OPNDQN) algorithm, which mitigates the weakness of both fully centralized and MARL approaches. The OPNDQN algorithm solves the problem that traditional algorithms cannot be used in large state-action space traffic models by utilizing a fictitious game approach at each iteration to find the nash equilibrium among neighboring intersections, by which no intersection has incentive to unilaterally deviate. One of the main advantages of the OPNDQN is that it can mitigate the non-stationarity of multi agent Markov process because it considers the mutual influence among neighboring intersections by sharing their actions. On the other hand, for training a large traffic network, the convergence rate of the OPNDQN is higher than that of existing MARL approaches because it does not incorporate all state information of each agent. We conduct extensive experiments by using Simulation of Urban MObility simulator (SUMO), and show the dominant superiority of the OPNDQN over several existing MARL approaches in terms of average queue length, episode training reward and average waiting time.
New methods for analytical calculation of eliptic integrals applied in various physical problems

A short review will be made of elliptic integrals, widely applied in GPS (Global Positioning System) communications (accounting for General Relativity Theory-effects), cosmology, Black hole physics and celestial mechanics. Then a novel analytical method for calculation of zero-order elliptic integrals in the Legendre form will be presented, based on the combination of several methods from the theory of elliptic functions: 1. the recurrent system of equations for higher-order elliptic integrals in two different representations. 2. uniformization of four-dimensional algebraic equations by means of the Weierstrass elliptic function 3.a variable transformation, inversely (quadratically) proportional to a new variable. The developed method is a step forward towards constructing analytical methods, which can improve the precision of the calculation of elliptic integrals, necessary both for theoretical and experimental problems.
Mapping Knowledge Representations to Concepts: A Review and New Perspectives

The success of neural networks builds to a large extent on their ability to create internal knowledge representations from real-world high-dimensional data, such as images, sound, or text. Approaches to extract and present these representations, in order to explain the neural network's decisions, is an active and multifaceted research field. To gain a deeper understanding of a central aspect of this field, we have performed a targeted review focusing on research that aims to associate internal representations with human understandable concepts. In doing this, we added a perspective on the existing research by using primarily deductive nomological explanations as a proposed taxonomy. We find this taxonomy and theories of causality, useful for understanding what can be expected, and not expected, from neural network explanations. The analysis additionally uncovers an ambiguity in the reviewed literature related to the goal of model explainability; is it understanding the ML model or, is it actionable explanations useful in the deployment domain?
A mathematical study of note association paradigms in different folk music cultures

In order to reveal some special rules of note association paradigms in different folk music cultures, we characterized the correlations of the notes by the conditional probabilities of their joint appearances in common melodies. The complex rules of the note association paradigms being formulated by the resulting conditional probability matrices were visualized using a special kind of multidimensional scaling algorithm. We constructed a simple mathematical model of note similarity evaluation, and found that this model is able to imitate the main characteristics of the observed note association paradigms. These results pose the conjecture that certain particularities and relations of the note association paradigms might be traced back to different note perception rules in different cultures.