Economic laws of division and changing the labor in the system of contemporary vocational education determination

The topical character of the problem in question is stipulated by the demand of highly skilled competitive personnel in the vocational education sphere of modern society, which is determined by the totality of objective and subjective factors of its development. The goal of the present research consists in the verification of the economic laws of division and change of the labor, that produce an immediate impact on the vocational education development strategy and a mediated impact on the requirements made to the personality of a student within this system. The primary method of investigation in the given area is the modelling method that allows to identify specific features of these laws’ operation depending on the historical period of social development and extrapolate their functioning on the present-day reality as well as make scientifically-based forecasts of its future development. Research outcomes: the article presents a structural functional model of the interaction of the economic laws of division and changing the labor during the industrial and post-industrial periods of social development; an algorithm of competently mature personality’s character formation in the modern system of vocational education. Materials of the research may prove useful to the rule-making specialists and practitioners in the educational sphere – in elaborating and upgrading educational and professional standards, in developing a model for the preparation of future competitive workers in the system of vocational education based on the objective factors of its development, such as the economic laws of division and change of the labor. © 2016 Ronzhina et al

Optimization of a company’s property structure aiming at maximization of its profit using neural networks with the example of a set of construction companies

This contribution tries to find an efficient way of a company´s property optimization. It searches for such a property structure that would ensure adequate benefit, respectively, the appreciation of own capital provided for remuneration. To carry out the calculation balance sheets, respectively their parts informing about the company´s property are used, as well as income statements – the total taxed profit of all companies running their business in the CZ from 2006 to 2015. To find the model artificial neural networks are used – specifically a multi-layer perceptron network and a neural network of a radial basic function. The result is a neural structure that will help the building company find a suitable property structure, so that the company reaches the required ROE of 10% (a company is considered successful, if it reaches 10% and more on Return on Equity). The model is useful not only in company management but also in evaluating its performance and health by competitors, creditors or suppliers.Стаття присвячена аналізу одного з варіантів можливої оптимізації власного капіталу компанії. Наведено підхід до пошуку оптимальної структури капіталу, який дозволить забезпечити адекватну вигоду і зробити оцінку власного капіталу. Підхід базується на традиційному аналізі балансів, деталізації майна компанії, звітах про прибутки та збитки – загальних звітах для всіх компаній Чеської Республіки з 2006 по 2015 р. Для побудови моделі на основі нейронної мережі використовуються багатошарові мережі персептрона і нейронні мережі з радіально-базисною функцією. У результаті отримана нейронна структура для оптимізації капіталу будівельної компанії з необхідною рентабельністю власного капіталу в 10% (компанія вважається успішною, якщо вона досягає 10% і більше рентабельності власного капіталу). Модель призначена не тільки для управління компаніями, але й для оцінки їх продуктивності та працездатності конкурентами, кредиторами або постачальниками.Данная работа посвящена анализу одного из вариантов возможной оптимизации собственного капитала компании. Представлен подход к поиску оптимальной структуры капитала, которая позволит обеспечить адекватную выгоду и произвести оценку собственного капитала. Подход базируется на традиционном анализе балансов, детализации имущества компании, отчетах о прибылях и убытках – общих отчетах для всех компаний Чешской Республики с 2006 по 2015 г. Для построения модели на основе нейронной сети используются многослойные сети персептрона и нейронные сети с радиально-базисной функцией. В результате получена нейронная структура для оптимизации капитала строительной компании с необходимой рентабельностью собственного капитала в 10% (компания считается успешной, если она достигает 10% и более по рентабельности собственного капитала). Модель предназначена не только для управления компаниями, но и для оценки их производительности и работоспособности конкурентами, кредиторами или поставщиками

Evaluation of Solvency of potential customers of a company

The manufacturing sector is one of the main pillars of an advanced economy. It is the first sector to indicate potential national economic problems. In a similar way it is the first sector to show signs of recovery when an economy is coming out of recession or crisis. The aim of this article is to apply a neural network to be able to predict potential financial problems in manufacturing companies in the Czech Republic.Строительная отрасль является одной из ключевых отраслей всех развитых экономик мира. Раньше других отраслей она указывает на потенциальные проблемы национальной экономики. Раньше других отраслей она указывает и на потенциальное улучшение экономики, которая выходит из рецессии или даже из кризиса. Целью этой статьи является использование нейронных сетей для прогнозирования возможных финансовых трудностей строительных компаний в Чешской Республике.Будівельна галузь є однією з ключових галузей всіх розвинених економік світу. Раніше інших галузей вона вказує на потенційні проблеми національної економіки. Раніше інших галузей вона вказує і на потенційне поліпшення економіки, яка виходить з рецесії або навіть з кризи. Метою цієї статті є використання нейронних мереж для прогнозування можливих фінансових труднощів будівельних компаній в Чеській Республіці

Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives

[EN] Digital transformation provide supply chains (SCs) with extensive accurate data that should be combined with analytical techniques to improve their management. Among these techniques Artificial Intelligence (AI) has proved their suitability, memory and ability to manage uncertain and constantly changing information. Despite the fact that a number of AI literature reviews exist, no comprehensive review of reviews for the SC operations planning has yet been conducted. This paper aims to provide a comprehensive review of AI literature reviews in a structured manner to gain insights into their evolution in incorporating new ICTs and collaboration. Results show that hybrization man-machine and collaboration and ethical aspects are understudied.This research has been funded by the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE). 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Molecular dynamics simulation studies of the interactions between ionic liquids and amino acids in aqueous solution

Although the understanding of the influence of ionic liquids (ILs) on the solubility behavior of biomolecules in aqueous solutions is relevant for the design and optimization of novel biotechnological processes, the underlying molecular-level mechanisms are not yet consensual or clearly elucidated. In order to contribute to the understanding of the molecular interactions established between amino acids and ILs in aqueous media, classical molecular dynamics (MD) simulations were performed for aqueous solutions of five amino acids with different structural characteristics (glycine, alanine, valine, isoleucine, and glutamic acid) in the presence of 1-butyl-3-methylimidazolium bis(trifluoromethyl)sulfonyl imide. The results from MD simulations enable to relate the properties of the amino acids, namely their hydrophobicity, to the type and strength of their interactions with ILs in aqueous solutions and provide an explanation for the direction and magnitude of the solubility phenomena observed in [IL + amino acid + water] systems by a mechanism governed by a balance between competitive interactions of the IL cation, IL anion, and water with the amino acids

Solvation free energy profile of the SCN- ion across the water-1,2-dichloroethane liquid/liquid interface. A computer simulation study

The solvation free energy profile of a single SCN- ion is calculated across the water-1,2-dichloroethane liquid/liquid interface at 298 K by the constraint force method. The obtained results show that the free energy cost of transferring the ion from the aqueous to the organic phase is about 70 kJ/mol, The free energy profile shows a small but clear well at the aqueous side of the interface, in the subsurface region of the water phase, indicating the ability of the SCN- ion to be adsorbed in the close vicinity of the interface. Upon entrance of the SCN- ion to the organic phase a coextraction of the water molecules of its first hydration shell occurs. Accordingly, when it is located at the boundary of the two phases the SCN- ion prefers orientations in which its bulky S atom is located at the aqueous side, and the small N atom, together with its first hydration shell, at the organic side of the interface

The phase diagram of water at high pressures as obtained by computer simulations of the TIP4P/2005 model: the appearance of a plastic crystal phase

In this work the high pressure region of the phase diagram of water has been studied by computer simulation by using the TIP4P/2005 model of water. Free energy calculations were performed for ices VII and VIII and for the fluid phase to determine the melting curve of these ices. In addition molecular dynamics simulations were performed at high temperatures (440K) observing the spontaneous freezing of the liquid into a solid phase at pressures of about 80000 bar. The analysis of the structure obtained lead to the conclusion that a plastic crystal phase was formed. In the plastic crystal phase the oxygen atoms were arranged forming a body center cubic structure, as in ice VII, but the water molecules were able to rotate almost freely. Free energy calculations were performed for this new phase, and it was found that for TIP4P/2005 this plastic crystal phase is thermodynamically stable with respect to ices VII and VIII for temperatures higher than about 400K, although the precise value depends on the pressure. By using Gibbs Duhem simulations, all coexistence lines were determined, and the phase diagram of the TIP4P/2005 model was obtained, including ices VIII and VII and the new plastic crystal phase. The TIP4P/2005 model is able to describe qualitatively the phase diagram of water. It would be of interest to study if such a plastic crystal phase does indeed exist for real water. The nearly spherical shape of water makes possible the formation of a plastic crystal phase at high temperatures. The formation of a plastic crystal phase at high temperatures (with a bcc arrangements of oxygen atoms) is fast from a kinetic point of view occurring in about 2ns. This is in contrast to the nucleation of ice Ih which requires simulations of the order of hundreds of ns

Determination of Alkali and Halide Monovalent Ion Parameters for Use in Explicitly Solvated Biomolecular Simulations

Alkali (Li+, Na+, K+, Rb+, and Cs+) and halide (F−, Cl−, Br−, and I−) ions play an important role in many biological phenomena, roles that range from stabilization of biomolecular structure, to influence on biomolecular dynamics, to key physiological influence on homeostasis and signaling. To properly model ionic interaction and stability in atomistic simulations of biomolecular structure, dynamics, folding, catalysis, and function, an accurate model or representation of the monovalent ions is critically necessary. A good model needs to simultaneously reproduce many properties of ions, including their structure, dynamics, solvation, and moreover both the interactions of these ions with each other in the crystal and in solution and the interactions of ions with other molecules. At present, the best force fields for biomolecules employ a simple additive, nonpolarizable, and pairwise potential for atomic interaction. In this work, we describe our efforts to build better models of the monovalent ions within the pairwise Coulombic and 6-12 Lennard-Jones framework, where the models are tuned to balance crystal and solution properties in Ewald simulations with specific choices of well-known water models. Although it has been clearly demonstrated that truly accurate treatments of ions will require inclusion of nonadditivity and polarizability (particularly with the anions) and ultimately even a quantum mechanical treatment, our goal was to simply push the limits of the additive treatments to see if a balanced model could be created. The applied methodology is general and can be extended to other ions and to polarizable force-field models. Our starting point centered on observations from long simulations of biomolecules in salt solution with the AMBER force fields where salt crystals formed well below their solubility limit. The likely cause of the artifact in the AMBER parameters relates to the naive mixing of the Smith and Dang chloride parameters with AMBER-adapted Åqvist cation parameters. To provide a more appropriate balance, we reoptimized the parameters of the Lennard-Jones potential for the ions and specific choices of water models. To validate and optimize the parameters, we calculated hydration free energies of the solvated ions and also lattice energies (LE) and lattice constants (LC) of alkali halide salt crystals. This is the first effort that systematically scans across the Lennard-Jones space (well depth and radius) while balancing ion properties like LE and LC across all pair combinations of the alkali ions and halide ions. The optimization across the entire monovalent series avoids systematic deviations. The ion parameters developed, optimized, and characterized were targeted for use with some of the most commonly used rigid and nonpolarizable water models, specifically TIP3P, TIP4PEW, and SPC/E. In addition to well reproducing the solution and crystal properties, the new ion parameters well reproduce binding energies of the ions to water and the radii of the first hydration shells