Binary Ones Research Articles

APPLYING THE INTEGRATIVE APPROACH IN THE PROCESS OF FORMING FUTURE PRIMARY SCHOOL TEACHERS’ FOREIGN LANGUAGE COMMUNICATIVE COMPETENCE


 
 
 The article deals with proving the advantages of multi-subject integrated training. It was defined the importance of taking into account the theoretical and methodological foundations of using an integrative approach in the process of forming future primary education teachers’ foreign language communicative competence. It was determined the specifics of conducting integrated courses, practical classes, including binary ones, in order to implement the professional training of future primary school teachers according to time requirements. The integration principle corresponds to the mental and physiological nature of the individual, through integration of a person-centered approach to training, as the student is able to choose basic knowledge and skills in different subjects and to apply them in practice.
 
 

Employing a Narrow-Band-Gap Mediator in Ternary Solar Cells for Enhanced Photovoltaic Performance.

Ternary organic solar cells (OSCs) provide a convenient and effective means to further improve the power conversion efficiency (PCE) of binary ones via composition control. However, the role of the third component remains to be explored in specific binary systems. Herein, we report ternary blend solar cells by adding the narrow-band-gap donor PCE10 as the mediator into the PBDB-T:IDTT-T binary blend system. The extended absorption, efficient fluorescence resonance energy transfer, enhanced charge dissociation, and induced tighter molecular packing of the ternary blend films enhance the photovoltaic properties of devices and deliver a champion PCE of 10.73% with an impressively high open-circuit voltage (VOC) of 1.03 V. Good miscibility and similar molecular packing behavior of the components guarantee the desired morphology in the ternary blend films, leading to solar cell devices with over 10% PCEs at a range of compositions. Our results suggest that ternary systems with properly aligned energy levels and overlapping absorption among the components hold great promises to further enhance the performance of corresponding binary ones.

Thermodynamic and corrosion study of Sm1-xMgxNiy (y = 3.5 or 3.8) compounds forming reversible hydrides

AB5 compounds (A = rare earth, B = transition metal) have been widely studied as anodes for Ni-MH applications. However, they have reached their technical limitations and the search for new promising materials with high capacity is foreseen. ABy compounds (2 < y < 5) are good candidates. They are made by stacking [AB5] and [A2B4] units along the c crystallographic axis. The latter unit allows a large increase in capacity, while the [AB5] unit provides good cycling stability. Consequently, the AB3.8 composition (i.e. A5B19 with three [AB5] for one [A2B4]) is expected to exhibit better cycling stability than the AB3.5 (i.e. A2B7 with two [AB5] for one [A2B4]). Furthermore, substitution of rare earth by light magnesium improves both the capacity and cycling stability. In this paper, we compare the hydrogenation and corrosion properties of two binary compounds, SmNi3.5 and SmNi3.8, and two pseudo-binary ones, (Sm, Mg)Ni3.5 and (Sm, Mg)Ni3.8. A better solid-gas cycling stability is highlighted for the binary SmNi3.8. The pseudo-binary compounds also exhibit higher cycling stability than the binary ones. Furthermore, their resistance to corrosion was investigated.

Fluctuation of photon-releasing with ligand coordination in polyacrylonitrile-based electrospun nanofibers

Multivariate terbium-complexes were incorporated into polyacrylonitrile (PAN) and electrospun into flexible multifunctional nanofibers with a uniform diameter of ~200 nm. Fluorescence comparison in multi-ligand-binding nanofibers under ultraviolet (UV) radiation verifies that the differentiated β-diketone ligands with dual functions are the primary cause of the spectral fluctuation, adequately illustrating the available methods for the quantification of intermolecular reciprocities between organic ligands and central Tb3+ ions. Especially under 308 nm UVB-LED pumping, the total emission spectral power of supramolecular Tb-complexes/PAN nanofibers are identified to be 2.88 µW and the total emission photon number reaches to 7.94 × 1012 cps which are nearly six times higher than those of the binary complex ones in the visible region, respectively. By modifying the sorts of organic ligands, the luminous flux and luminous efficacy of multi-ligand Tb-complexes/PAN nanofibers are up to 1553.42 μlm and 13.72 mlm/W, respectively. Efficient photon-releasing and intense green-emission demonstrate that the polymer-capped multi-component terbium-complexes fibers have potential prospects for making designable flexible optoelectronic devices.

Intellectualization of a method for solving a logistics problem to optimize costs within the framework of Lean Production technology

In the article, within the framework of intellectualization of the Lean Production technology, it is proposed to optimize the costs arising from the insufficient efficiency of placing goods in the warehouse by creating an optimization method based on the immune metaheuristics of the T-cell model, which allows solving the knapsack constrained optimization problem. The proposed metaheuristic method does not require specifying the probability of mutation, the number of mutations, the number of selected new cells and allows using only binary potential solutions, which makes discrete optimization possible and reduces computational complexity by preventing permanent transformations of real potential solutions into intermediate binary ones and vice versa. An immune metaheuristic algorithm based on the T-cell model has been created, intended for implementation on the GPU using the CUDA parallel information processing technology. The proposed optimization method based on immune metaheuristics can be used to intellectualize the Lean Production technology. The prospects for further researches are to test the proposed methods on a wider set of test databases.

Improved regularity assumptions for partial outer convexification of mixed-integer PDE-constrained optimization problems

Partial outer convexification is a relaxation technique for MIOCPs being constrained by time-dependent differential equations. Sum-Up-Rounding algorithms allow to approximate feasible points of the relaxed, convexified continuous problem with binary ones that are feasible up to an arbitrarily smallδ&gt; 0. We show that this approximation property holds for ODEs and semilinear PDEs under mild regularity assumptions on the nonlinearity and the solution trajectory of the PDE. In particular, requirements of differentiability and uniformly bounded derivatives on the involved functions from previous work are not necessary to show convergence of the method.

Modeling Unified Language Templates for Designing Information Systems

Abstract—The most popular tools for developing object-oriented information systems are CASE-tools. More often, they do not support n-ary association relationships between classes. It is shown how, when describing a domain model, one can go from n-ary associations to binary ones, how to reduce the number of information system objects, and how to take into account the restrictions placed on objects. Situations that allow this kind of transformation are presented in the form of design patterns.

Sequential binary decay of light nuclear systems: An assessment of statistical model codes

The sequential decay of excited nuclei is described as a succession of binary processes involving fragments in their ground, excited-bound and unbound states. Primary together with secondary decays lead to the final mass and charge distributions. Asymmetric mass splittings involving nucleon emission up to symmetric binary ones are treated within the Weisskopf evaporation formalism, in a unified manner. This procedure was imple- mented in the Monte-Carlo multi-step statistical model code MECO (Multisequential Evaporation COde). We study the evolution of the calculated final mass and charge distributions from 40Ar* as a function of the excitation energy, up to complete dissociation. Our results are compared with the predictions of statistical evaporation codes based on different assumptions for the compound nucleus decay.

Monoidal characterisation of groupoids and connectors

We study internal structures in regular categories using monoidal methods. Groupoids in a regular Goursat category can equivalently be described as special dagger Frobenius monoids in its monoidal category of relations. Similarly, connectors can equivalently be described as Frobenius structures with a ternary multiplication. We study such ternary Frobenius structures and the relationship to binary ones, generalising that between connectors and groupoids.

An Improved, Negatively Correlated Search for Solving the Unit Commitment Problem’s Integration with Electric Vehicles

With the rapid development of plug-in electric vehicles (PEVs), the charging of a number of PEVs has already brought huge impact and burden to the power grid, particularly at the medium and low voltage distribution networks. This presents a big challenge for further mass roll-out of electric vehicles. To assess the impact of charging of substantial number of electric vehicles on the grid, a model of 30000 PEVs integrated with unit commitment (UCEV) was investigated in this study. The unit commitment was a large-scale, mixed-integer, nonlinear, NP-Hard (non-deterministic polynomial) optimization problem, while the integration of PEVs further increased the complexity of the model. In this paper, a global best inspired negatively correlated search (GBNCS) method which extends the evolutionary logic of negatively correlated search is proposed to tackle the UCEV problem. In the proposed algorithm, a rounding transfer function in GBNCS, is deployed to convert real-valued variables into binary ones; further, the global best information is combined in the population to improve the efficiency of the algorithm. Numerical results confirmed that the proposed GBNCS can achieve good performance in both a basic IEEE 10 unit commitment problem and the UCEV problem. It was also shown that, among four charging modes, the off-peak charging mode and EPRI (Electric Power Research Institute) charging mode are more economical in PEV charging.

Sequential binary decay of highly excited 40Ar*

The sequential statistical binary decay of the highly excited compound nucleus 40Ar* is described with an extended evaporation formalism implemented in a Monte-Carlo multi-step statistical model code. Asymmetric mass splittings involving nucleon emission up to symmetric binary ones are treated within the evaporation formalism, in a unified manner. Emission of heavy fragments in their ground and excited (particle-bound or unbound) states is considered. The evolution of the final mass distributions from 40Ar* is studied as a function of the initial excitation energy, in the range from 45 up to 405 MeV. The population of final states originating from the decay of intermediate mass fragments in particle-bound and particle-unbound states (side-feeding) is discussed. Results are compared with an alternative description in which the time-dependent decay process is described by rate equations for the generation of different fragment species.

Two Multi-Setting Causal Inequalities and Their Violations

In this paper, two simple causal inequalities with 4 inputs and 2 outputs are derived. To this end, we have introduced two causal games, and the corresponding inequality can be derived as an upper bound of the success probability under the causal order. Those inequalities can be violated by choosing proper process matrices and instruments. Moreover, the violation for one of them is maximal when the instruments are restricted to be binary ones.

Integrating Dense LiDAR-Camera Road Detection Maps by a Multi-Modal CRF Model

Road detection is an important task in autonomous navigation systems. In this paper, we propose a road detection method via a LiDAR-camera fusion strategy to exploit both the range and color information. The whole system consists of three parts. In the LiDAR based part, we transform the discrete 3D LiDAR point clouds to continuous 2D LiDAR range images and propose a distance-aware height-difference based scanning approach to get the road estimations quickly. In the camera based part, we apply a light-weight transfer learning based road segmentation network. In the LiDAR-camera fusion part, we transform the detection results from LiDAR and camera to dense and binary ones to solve the data imbalance problem and fuse them in a multi-modal conditional random field (MM-CRF) framework. Experiments show that the proposed MM-CRF fusion method can operate in real-time and achieve competitive performance compared with the state-of-the-art road detection algorithms on the KITTI-Road benchmark.

Multi‐dimensional Sum‐Up Rounding using Hilbert curve iterates

AbstractMixed‐integer optimal control problems can be reformulated by means of partial outer convexification, which introduces binary‐valued switching functions for the different realizations of a discrete‐valued control variable. They can be relaxed naturally by allowing them to take values in [0, 1]. Sum‐Up Rounding (SUR) algorithms approximate feasible switching functions of the relaxation with binary ones. If the controls are distributed in one dimension, the approximants are known to converge in the weak∗ topology of L∞. We show that this still holds true for controls that are distributed in more than one dimension if an appropriate grid refinement strategy that is coupled with a deliberate ordering of the grid cells is chosen. This condition is satisfied by the iterates of space‐filling curves, e.g. the Hilbert curve.

Chemical effect on the structural and dynamical properties in Zr-Ni-Al liquids

We develop an embedded-atom method (EAM) model to perform classical molecular-dynamics computer simulations of a model of Zr-Ni-Al ternary melts, based on the existing binary ones. The EAM potential is validated against a broad range of experimental data for the liquid melt, including both static-structure factors and dynamical data on the mass-transport coefficients. We use our simulation model to address the structural and dynamical changes induced by a systematic replacement of Zr by Al in ${\mathrm{Zr}}_{75\ensuremath{-}x}{\mathrm{Ni}}_{25}{\mathrm{Al}}_{x}\phantom{\rule{4pt}{0ex}}(x=0--30)$ ternary alloys. We find strong chemical-ordering effects exhibited as the locally preferred structure when the Al-concentration ${c}_{\text{Al}}$ is increased. Along with the chemical effects, effective-power-law relations are found between the self-diffusion coefficients in the melts, with an exponent that monotonically decreases with increasing Al concentration. The associated Stokes-Einstein relation between diffusivity and viscosity breaks down at higher temperature upon Al addition. We also address the influence of Al admixture on the vibrational spectrum of the melt. With increasing ${c}_{\text{Al}}$, sound waves move faster, and an optical vibrational mode is found.

A sparse structure for fast circle detection

In the paper, we present a circle detector that achieves the state-of-art performance in almost every type of image. The detector represents each circle instance by a set of equally distributed arcs and searches for the same number of edge points to cover these arcs. The new formulation leads to the voting in minimizing/maximizing way which is different from the typical accumulative way adopted by Hough transform. From the formulation, circle detection is then decomposed into radius-dependent and -independent part. The calculation of independent part is computationally expensive but shared by different radii. This decomposition gets rid of the redundant computation in handling multiple radii and therefore speeds up the detection process. Originated from the sparse nature of independent part, we design a sparse structure for its batch computation which is fulfilled in just one sweep of the edge points. Circle detector based on this sparse structure is then proposed which achieves the comparable time complexity as the algorithm based on Hough transform using 2D accumulator array. For testing, we created an information-rich dataset with images coming from multiple sources. It contains five categories and covers a wide spectrum of images, ranging from true color images to the binary ones. The experimental results demonstrate that the proposed approach outperforms the solutions based on accumulative voting.

Development and properties evaluation of sustainable ultra-high performance pastes with quaternary blends

This study aims to investigate the synergistic effect of quaternary blends applying supplementary cementitious materials on sustainable Ultra-high Performance Concrete (UHPC) pastes. The hydration kinetics, pore structures, fresh behaviour, strength, fibre-to-matrix bond, shrinkage and environmental sustainability of 14 UHPC pastes are determined and analysed. The results show that limestone powder contributes to better environmental sustainability and fresh behaviour, but enlarged shrinkage and diminished strength, and application of silica powder is an effective measure to overcome those disadvantages. Slag cement possessing a relatively lower Ca/Si ratio (2.45) is preferred to a lower amount but finer silica (3% nano silica) in the presence of limestone powder, compared to the Portland cement with a higher Ca/Si (3.22) that needs more silica even with coarser particle size (5% micro silica). Quaternary blends with cement-slag-limestone-silica in UHPC pastes have considerable advantage of reducing embedded CO2 emission and and improving sustainability efficiency. Furthermore, positive synergies in term of strength, fibre-to-matrix bond and total free shrinkage are observed in UHPC pastes with quaternary binders compared to binary and ternary ones.

Limiting diffusion coefficients of glufosinate ammonium, cymoxanil and imidacloprid in aqueous solutions

We have measured the limiting diffusion coefficients of three different pesticides in aqueous solutions: glufosinate ammonium, cymoxanil and imidacloprid, highly used for tomato production. The experiments were carried in aqueous solutions, at 25 °C, at concentrations below 3 mmol dm−3 (depending on the solubility of pesticides). Mutual diffusion coefficients (D) obtained by using the Taylor dispersion technique, and by using pure water and different solutions of concentration c, as carrier stream and injection solutions, respectively, show that the systems can be analyzed as binary ones. The hydrodynamic radii and the respective limiting diffusion coefficients of the glufosinate anion, cymoxanil and imidacloprid have also been estimated. For the electrolyte glufosinate ammonium, by using the Nernst equation, it is also possible to estimate the limiting molar conductivity of the glufosinate anion.In order to mimic field conditions, we have measured the tracer diffusion coefficients of glufosinate ammonium in aqueous solutions of ammonium nitrate at different concentrations, permitting us to analysis the salting-in effects on the diffusion of this pesticide.From these measurements useful information on the thermodynamic, transport and structural parameters can be obtained, allowing a better understanding of the behaviour of these compounds in aqueous solution.These studies have been complemented with 1H and 31P NMR spectroscopy in order to obtain more additional structural information on the interaction of ammonium nitrate with glufosinate-ammonium in aqueous solution. The results obtained support the hypothesis of salting-in effects on the diffusion of this pesticide in aqueous solution.

Near-Lossless Binarization of Word Embeddings

Word embeddings are commonly used as a starting point in many NLP models to achieve state-of-the-art performances. However, with a large vocabulary and many dimensions, these floating-point representations are expensive both in terms of memory and calculations which makes them unsuitable for use on low-resource devices. The method proposed in this paper transforms real-valued embeddings into binary embeddings while preserving semantic information, requiring only 128 or 256 bits for each vector. This leads to a small memory footprint and fast vector operations. The model is based on an autoencoder architecture, which also allows to reconstruct original vectors from the binary ones. Experimental results on semantic similarity, text classification and sentiment analysis tasks show that the binarization of word embeddings only leads to a loss of ∼2% in accuracy while vector size is reduced by 97%. Furthermore, a top-k benchmark demonstrates that using these binary vectors is 30 times faster than using real-valued vectors.

Retracted: The fabrication of magnetic recyclable nitrogen‐doped titanium dioxide/calcium ferrite/diatomite heterojunction nanocomposite for improved visible‐light‐driven degradation of tetracycline

AbstractBACKGROUNDPowdery photocatalysts have long been studied in various aspects, yet their low recovery in suspension systems remains the bottleneck hindering their practical application. An alternative method to overcome this shortcoming is to develop magnetic recyclable ferrite‐based hybrid photocatalysts. In this work, we prepared a nitrogen (N)‐doped titania (TiO2)/calcium ferrite (CaFe2O4)/diatomite (Dt) (N‐TCD) ternary hybrid via the sol–gel method. The physicochemical properties of various hybrid catalysts were characterized and studied, and their photocatalytic properties were evaluated via the degradation of the antibiotic tetracycline (TC) under visible light.RESULTSThe photodegradation rate of TC was accelerated by the high adsorption ability of Dt, due to the adsorption and degradation synergistic effect between catalysts and substrate Dt. The ternary composite indicated higher degradation rate than binary ones, implying the interaction between three components. Based on the degradation results, the optimal N dopant amount and catalyst dosage were determined.CONCLUSIONSThe formation of heterojunction between N‐doped TiO2 and CaFe2O4 hindered the recombination of photo‐induced charge carriers and improved the photocatalytic activity. The ternary N‐TCD composite could simply be recovered from TC solution via an external magnet, and repetition tests indicated no obvious decrease of photoactivity, even after five runs. This nanocomposite was considered appropriate for application in wastewater remediation processes, thanks to its high photocatalytic efficiency under visible light irradiation, as well as its good reusability and stability. © 2019 Society of Chemical Industry