Theoretical Conditions Research Articles

Neuropedagogical Principles as a Factor of Inclusive Education in the Context of Managerial Activity: European Experience

The article analyzes the types, perspectives and trends of inclusive education management in a multifaceted manner, in particular, the experience of Western Europe today and during the last decades is analyzed. This is done with the aim of finding the most effective models or at least predicted appropriate recommendations for reforming inclusive education management. The general approach to writing the article is review-analytical with modeling elements. In this regard, the purpose of the article is to generalize the current trends in the management of inclusion in the world as a neuropedagogical principle of inclusive education in the context of management activities and to understand the theoretical conditions of reforming such management, taking into account the European experience. According to the authors, the relevance of the article is due to the contradiction between the managerial (vertical) and self-initiative (horizontal) intentions in inclusive education. As a result, it was possible to formulate a number of recommendations and find common problems and directions for the development of Ukrainian and European inclusion. The main trend that should be developed is the reduction of the management of state powers and the introduction of self-management principles based on the personal motivation of subjects of inclusion (self-directe

The race between education and technology in Chile and its impact on the skill premium

While studies using pre-2000 data for Chile implied that technological change drives the skill premium evolution, post-2000 data suggests that the supply of skilled labour expansion has reduced this premium. In contrast, literature shows a consistent link between technology and the growing demand for skilled labour, despite educational improvements, leading to skill premium increases. We examine these interactions under the race between education and technology model (RBET) for Chile between 1980 and 2018 considering the inconsistent findings (e.g., negative elasticities) reported by past studies. We also find inconsistencies using cointegration techniques. Alternatively, we apply an Unobserved Component Model using a Bayesian estimation that enforces the required economic and theoretical conditions. We find that, before the 2000s, the technological change dominated. However, in the 2000s, the demand was surpassed by educational supply increases, reducing the premium. The estimated elasticity of substitution between skilled and unskilled labour is 6.5, implying that both are more substitutable than commonly thought.

Model-based approach for analysis of contrast media regions in contrast enhanced breast model images

Contrast agents in radiology improve visualisation and iodine-based ones are applied in differ- ent radiology techniques. Energies, used in these techniques, vary in a very wide range. The energies can be as low as 26 kVp in mammography and reach up to 140 - 150 kVp in computed tomography. Dual-energy studies can also be applied. X-ray images of resin phantoms with iodine-based contrast base are taken at different energies and the image pixel values of various regions of interest were measured. Based on the performed measurements, the visual contrast between the studied different areas is calculated and analysed. The obtained data are applied for the estimation of models for the expected pixel values depending on the energies and the contrast agent quantities. These models can be used to describe the real conditions, which differ from the applicable to theoretical calculations ideal conditions.

The macroeconomics of near zero growth of GDP in a world of geopolitical risks and conflicts

This paper offers an analysis of the macroeconomic conditions for near zero economic growth based on a demand-led growth model, and their implications in terms of paid employment, government finances, and the rate of profit. The main finding of the paper is that a level of net investment compatible with near zero growth would lead to a lower level of paid employment in terms of total hours worked. The effects on the distribution of work and the unemployment level would depend on changes to working time, whether in terms of average hours worked per annum, ages of entry into, and exit from, the work force. Furthermore, changes in working time would be achieved through social actions and legislation, rather than market mechanisms. A government budget deficit may well be required to underpin full employment and capacity utilisation, though there may be long-term limits on the use of budget deficits in a near zero growth context. Finally, a near zero growth rate would also mean a substantial lower rate of profit than hitherto.The implementation of these theoretical conditions require a level of cooperation between and within countries, which is much more difficult to reach in the presence of geopolitical risks and conflicts. Yet, there is no country secure from geopolitical risks and conflicts without an ecologically sustainable use of the natural resources. The theoretical conditions discussed in this paper could serve as “condiciones sine quibus non” to ecological sustainability, while navigating the complexities and uncertainties caused by the on-going conflicts and heightened geopolitical risks.

Self-sensed, self-adapted and self-powered piezoelectric generator architecture by synchronous circuits of autonomous parameter tuning

Synchronous circuits are effective to enhance the performance of piezoelectric generators and further show the capability of extending the generator’s bandwidth by tuning the switching parameters due to the electromechanical coupling effect. However, many studies are limited to theoretical investigations or restricted experimental conditions with externally powered controllers. Besides, a critical and unsolved challenge for the circuit controller is the sensing of the generator’s dynamics for the tuning of the operation parameters of the synchronous circuits since the switching timing cannot be ensured for varied generator dynamics due to the electromechanical effect of the tunable circuit. This paper presents a new self-powered autonomous piezoelectric energy harvesting system with an integrated structural and electrical design, including a dedicated self-sensed generator and a self-adaptive synchronous interface circuit. The system can automatically tune the extraction parameters (the switching phase and the voltage flip ratio) according to the self-sensed information by utilization of a precise maximum power tracking strategy for optimized power and bandwidth. Compared to the system with the classical synchronous circuit, the proposed design demonstrates superior power harvesting capabilities (0.7125mW@0.05 g), extended bandwidth (2.5 Hz, 471 % of the conventional approach) and excellent adaptability (a tunable and self-sufficient frequency range of 10.6 Hz at 0.1 g acceleration).

Saamische Schatzsagen

This article deals with the Sámi treasure legends, which are part of the corresponding Nordic tradition. The corpus of the present study consists of approximately one hundred written sources, both published and unpublished, collected at different times, as well as about the same amount of taped interviews. The latter mostly date from the late 1960s and were collected as part of the Talvadas project, archived at the University of Turku. A great part of the material deals with the more theoretical conditions of how to lay hands on the treasure buried in the ground. Narratives about concrete efforts to dig up the silver, often old coins or other valuables the person burying them in the ground wanted to secure, are in the minority.
 The place where a treasure has been buried may reveal itself by optical or even acoustical signs, above all by a light. This light is visible especially on Midsummer Eve. For different reasons, success in the endeavour to dig up a treasure is very rare: Challenges were constituted by facing the frightening apparitions, breaking the silence during digging up a buried treasure, forgetting to give an offering, etc. One prerequisite for success mentioned is to throw a knife or some other metal object over the fire, which is one of the bonds with the earth spirits. Especially in more recent sources, they are mentioned as owners of buried treasures. The legends also cite other guardians.

Happy Times: Measuring Happiness Using Response Times

Surveys measuring happiness or preferences generate discrete ordinal data. Ordered response models, which are used to analyze such data, suffer from an identification problem. Their conclusions depend on distributional assumptions about a latent variable. We propose using response times to solve that problem. Response times contain information about the distribution of the latent variable through a chronometric effect. Using an online survey experiment, we verify the chronometric effect. We then provide theoretical conditions for testing conventional distributional assumptions. These assumptions are rejected in some cases, but overall our evidence is consistent with the qualitative validity of the conventional models. (JEL C14, D60, D91, I31)

Optimasi Mix Design Beton Melalui Teknologi Machine Learning

The concrete mix design is a crucial step in ensuring the quality of concrete used in construction projects. Traditional mix design methods rely on trial and error, which can be time-consuming and escalate construction costs. In recent years, machine learning technology has been developed to predict concrete properties and optimize mix designs for high-quality concrete. This study aims to explore the application of machine learning in high-quality concrete mix design, considering theoretical conditions, methods, and related research. The focus of this research is to test the use of machine learning techniques in predicting concrete properties and optimizing mix designs for high-quality concrete. The theory and concepts of machine learning will be applied to concrete mix design datasets and relevant properties. The methods employed will include data pre-processing, feature selection, and model training and evaluation. The performance of the machine learning model will be compared with traditional mix design methods to determine its effectiveness. Furthermore, the results and benefits of this study will demonstrate the potential advantages of using machine learning in determining high-performance concrete mix designs. By accurately predicting concrete properties and optimizing mix designs, construction projects can be completed more efficiently and with higher quality. This technology also has the potential to reduce costs associated with trial and error methods and minimize the environmental impact of concrete production. The success of this study will pave the way for further research and development in the field of machine learning for high-performance concrete mix designs.

Angular non-critical phase-matching second harmonic generation with the Ba3(ZnB5O10)PO4 crystal

The angular non-critical phase-matching (A-NCPM) second-harmonic-generation (SHG) properties of Ba3(ZnB5O10)PO4 (BZBP) crystal were investigated. Based on the small signal solution formula of SHG, the effective nonlinear coefficient deff along z-axis was corrected to 1.43 p.m./V. Combining the theoretical SHG PM conditions, BZBP crystal can be achieved type-I A-NCPM with the fundamental wavelength of 750 nm on y-axis, and 1012 nm on z-axis. Using an OPO laser as pump source, the BZBP crystal could realize the 506 nm and 375 nm SHG lasers with the conversion efficiencies of 35 % and 45.5 % respectively. The acquired results demonstrated that BZBP is a promising NLO crystal for A-NCPM frequency conversion applications in the output spectral regions of Ti:sapphire laser and near-infrared lasers.

Exact solution of the Langmuir rate equation: New Insights into pseudo-first-order and pseudo-second-order kinetics models for adsorption

The Langmuir adsorption rate equation was obtained in its exact, linear, and simple form. Using Stochastic Numerical Simulation, it was demonstrated that this equation can accurately calculate the adsorption rate constant (ka), which is more precise than the values obtained using pseudo-first-order (PFO) and pseudo-second-order (PSO) models. The derivation conditions of the PFO and PSO kinetics models from Langmuir kinetics were also investigated. The results showed that the PFO model can be obtained at two limit states: at Ce≅C0 and at Ce≪C0 with a very low fractional coverage. Also, the PSO model is derived under the condition Ce→0 and θe→1. The accuracy of the exact Langmuir model, both linear and nonlinear, and the theoretical derivation conditions of the PFO and PSO models were examined using several sets of kinetics data generated by the Stochastic Numerical Simulation method. The simulation results supported the theoretical approaches of this study.

Cooperative online schedule of interconnected data center microgrids with shared energy storage

The rapid increasing of data centers calls for an efficient method to reduce high operation costs and carbon emissions. This paper proposes a cooperative online schedule framework for local interconnected data centers considering shared energy storage. A time-average optimization problem is built to reduce the overall operation cost with essential operational constraints. Multiple randomness and the temporal coupling constraints of energy system levels make it challenging to solve the stochastic problem. Adapting the Lyapunov optimization theory with relaxation and perturbation technique, an online algorithm is proposed to find an acceptable solution to the problem to achieve both good service coordination and efficient energy coordination. The algorithm does not require prediction of random parameters, and has a fast convergence rate. Especially, the theoretical conditions for convergence and the distance between the acceptable and real optimal solution are derived in a closed form. Simulation studies show that the algorithm can effectively reduce operation cost of data centers, carbon emissions, and dependence on the main grid.

Reconstruction of Land Surface Temperature Derived from FY-4A AGRI Data Based on Two-Point Machine Learning Method

Land surface temperature (LST) is one of the most important parameters of the interface between the earth surface and the atmosphere, and it plays a significant role in many research fields, such as agriculture, climate, hydrology, and the environment. However, the thermal infrared band of remote sensors is easily affected by clouds and aerosols, leading to many data gaps in LST products, which restricts the subsequent application of these products. In this paper, Beijing, China, is selected as the study area, and the LST data retrieved from Fengyun 4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) are reconstructed based on the two-point machine learning method. Firstly, the two-point machine learning model is built to reconstruct the theoretical clear-sky LST from simulated and actual images, and the accuracy of the reconstruction results is evaluated compared with the random forest algorithm and the inverse distance weighted method. Secondly, the actual LST under the influence of clouds is reconstructed by using the ERA5 reanalysis LST data as the auxiliary data, and the reconstruction accuracy is then evaluated by the field measurement LST data. The experimental results show that (1) the prediction accuracy of the two-point machine learning method is higher than that of the random forest method in both simulated data and actual data experiments; (2) the R2 of reconstructed LST under theoretical clear-sky conditions is 0.6860 and the root mean square error (RMSE) is 2.9 K, while the R2 of the reconstructed accuracy of actual LST under clouds is 0.7275 and the RMSE is 2.6 K, i.e., the RMSE decreases by 10.34%; (3) the two-point machine method combined with the auxiliary ERA5 LST data can well reconstruct LST under cloudy conditions and present a reasonable LST distribution.

Resonance mechanism of hydroelastic response of multi-patch floating photovoltaic structure in water waves over stepped seabed

This paper investigates the hydroelastic response of a multi-patch floating photovoltaic (FPV) structure in water waves over a stepped seabed. The resonance conditions and underlying mathematical mechanism of FPV patches are explored based on the linear potential-flow theory and the thin-plate model. An implicit function of the open-water wavelength and the FPV patch's structural wavelength is derived. Resonance conditions occur in the FPV patch when the patch length and structural wavelength (rather than the water wavelength, as commonly believed) satisfy certain proportions. Mathematical derivations are conducted to interpret the value of each proportion. Two resonance conditions are recognized based on the mathematical structure of the solution. The effects of a stepped seabed and adjacent patches on the resonance conditions and hydroelastic behavior of FPV structures are also investigated. For a given stiffness parameter, the resonance conditions of FPV patches are solely determined by the water depth. The distance between adjacent patches does not alter the resonance conditions of each patch. Resonance occurs in the water body between two patches when the ratio of patch distance to water wavelength takes certain proportional values. A resonant water body tends to amplify the oscillation amplitude of both patches. However, when two FPV patches and a constrained water body reach their theoretical resonance conditions at the same time, the oscillation amplitudes of both the seaward patch and the constrained free surface are evidently suppressed. The transmitted waves of an FPV structure are largely determined by the dynamics of the leeward patch.

Ultra-high-sensitivity micro-accelerometer achieved by pure axial deformation of piezoresistive beams

Microfabricated piezoresistive accelerometers with purely axially deformed piezoresistive beams have demonstrated high performance. However, the conventional design of such accelerometers requires complex theoretical calculations and specific dimensional conditions to achieve purely axial deformation, which inevitably increases the difficulty and cost of the design and manufacturing. We propose an innovative structure that can simply realize pure axial deformation of piezoresistive beams by eliminating the transverse displacement at both ends without tedious calculations. An accelerometer based on the structure was fabricated; both static and dynamic performances were tested. The results showed that the accelerometer had high sensitivity (2.44 mV g−1 with 5 V bias, without circuit amplification), low cross-axis sensitivity (1.56% and 0.49 %, respectively), and high natural frequency (11.4 kHz), with a measurement range of 0–100 g. This design method provides an easy approach for designing high-performance piezoresistive sensors.

Dynamical Transmission and Mathematical Analysis of Ebola Virus Using a Constant Proportional Operator with a Power Law Kernel

The Ebola virus continues to be the world’s biggest cause of mortality, especially in developing countries, despite the availability of safe and effective immunization. In this paper, we construct a fractional-order Ebola virus model to check the dynamical transmission of the disease as it is impacted by immunization, learning, prompt identification, sanitation regulations, isolation, and mobility limitations with a constant proportional Caputo (CPC) operator. The existence and uniqueness of the proposed model’s solutions are discussed using the results of fixed-point theory. The stability results for the fractional model are presented using Ulam–Hyers stability principles. This paper assesses the hybrid fractional operator by applying methods to invert proportional Caputo operators, calculate CPC eigenfunctions, and simulate fractional differential equations computationally. The Laplace–Adomian decomposition method is used to simulate a set of fractional differential equations. A sustainable and unique approach is applied to build numerical and analytic solutions to the model that closely satisfy the theoretical approach to the problem. The tools in this model appear to be fairly powerful, capable of generating the theoretical conditions predicted by the Ebola virus model. The analysis-based research given here will aid future analysis and the development of a control strategy to counteract the impact of the Ebola virus in a community.

A War Gaming in the Context of a Computer Simulation of Combat

The war game is a respected tool for commanders' decision-making. Its preparation, execution, and evaluation of results require precise organization and a considerable time commitment. However, the time aspect is a limiting factor in the current dynamic era to a rather objectified evaluation of the variants of operation execution. The article does not describe the process of wargame preparation, it focuses on the execution phase, where it presents the use of a particular simulation system in wargames and under which theoretical conditions the results of combat simulation can be considered valid. It also evaluates the time efficiency of its use in a wargame. It has been experimentally verified that the tested simulation system can be used for a wargame especially in the accelerated simulation mode. The configuration of the computing system was also verified, which allowed a substantial acceleration of the simulation run of the wargame scenario.

Experimental validation of thermochemical water-sorption materials for thermal energy storage: Building application

Salt hydrates for seasonal heat storage have emerged as an important research topic due to their potential to fulfil the heat demand in the residential and commercial building sector. However, the research undertaken has not yet covered key aspects of their fundamental thermal behaviour understanding e.g. experimentally validation, characterisation methodologies or material screening. The present investigation is aimed to identify promising thermochemical materials in the temperature range of 25–150°C, which are suitable for building applications and waste heat recovery. A list of ten salt hydrates has been screened through an experimental validation, which was developed and optimized for the specific working conditions. The salt hydrates were tested under operational conditions and key properties are assessed (thermal conductivity, specific heat, volume change, etc). Different case studies were used to narrow down to a list of final salts candidates under three theoretical working conditions scenarios for both open and closed systems. The cases of study prioritised high energy density (after one hydration/dehydration cycle), acceptable volume expansion and stability, which led to the final candidates. Magnesium sulphate was selected in the case of high energy density (>2 MJ/m3) and low cost (1 €/MJ), when lowering the energy density to 1 MJ/m3 calcium sulphate and copper sulphate were revealed as promising candidates for open and closed systems. While calcium nitrate was identified as a candidate along with magnesium sulphate when considering closed systems.

Event-triggered neural network control using quadratic constraints for perturbed systems

This paper investigates the event-triggered control problem for perturbed systems under neural network controllers. We propose a novel event-triggering mechanism, based on local sector conditions related to the activation functions, to reduce the computational cost associated with the neural network evaluation. It avoids redundant computations by updating only a portion of the layers instead of evaluating periodically the whole neural network. Sufficient conditions in terms of matrix inequalities are established to design the parameters of the event-triggering mechanism and compute an inner-approximation of the region of attraction for the perturbed feedback system. The theoretical conditions are obtained by using a quadratic Lyapunov function and an abstraction of the activation functions via quadratic constraints to decide whether the outputs of the layers should be transmitted through the network or not. Such conditions allow us to reduce the computational activity on the neural network while preserving the stability and performance level of the perturbed feedback system. To illustrate the efficacy of our approach, we consider the nonlinear inverted pendulum system stabilized by a trained neural network.

Extraction of the cefluosil from rare earth slag by pressurized filtration

Bayan Obo blast furnace slag (i.e., rare earth slag) is rich in rare earth elements. However, current methods for the separation and extraction of rare earth elements often suffer from lengthy production processes, high energy consumption, and significant environmental pollution, making large-scale applications difficult. Therefore, the separation, purification, and comprehensive utilization of rare earth elements from rare earth slag have become urgent priorities. In this study, gas pressure filtration technology was employed to purify and separate cerium fluorosilicate crystals from a quaternary system of CaO-SiO2-CaF2-Ce2O3 rare earth slag. The pressure filtration mechanism was investigated, and both constant rate filtration and constant pressure filtration cake models were established. Additionally, the nucleation behavior of the cefluosil crystals was studied, and the optimal nucleation temperature under theoretical conditions was estimated to be 1145 °C. Furthermore, the effects of different separation conditions on the separation efficiency were examined, and it was concluded that successful separation of the cefluosil crystals was achieved under the optimal separation conditions (i.e., filtration temperature of 1150 °C, filtration pressure of 0.35 MPa, and filtration times of 4). After the pressure filtration separation, the recovery rate of Ce, a rare earth element, in the upper crucible reached 88.83%. This study confirms the effectiveness of pressure filtration for solid-liquid separation of rare earth slag and provides new insights for the separation and purification of high-value rare earth elements in rare earth slag.

Mathematical analysis of pulse vaccination in controlling the dynamics of measles transmission

Although the incidence of measles has been significantly reduced through vaccination, it remains an important public health problem. In this paper, a measles model with pulse vaccination is formulated to investigate the influential pulse vaccination on the period of time for the extinction of the disease. The threshold value of the formulated model, called the control reproduction number and denoted by R∗, is derived. It is found that the disease-free periodic solution of the model exists and is globally attractivity whenever R∗<1 in the sense that measles is eliminated. If R∗>1, the positive solution of the model exists and is permanent which indicates the disease persists in the community. Theoretical conditions for disease eradication under various constraints are given. The effect of pulse vaccination is explored using data from Thailand. The results obtained can guide policymakers in deciding on the optimal scheduling in order to achieve the strategic plan of measles elimination by vaccination.