Attitudes of Primary School Teachers Toward Inclusive Education

Background: The aims of our study are related to examining the relevance of teachers' attitudes toward the implementation of inclusive education. In addition, its subject is related to the implications on inclusive education policies, limitations of the existing study along with the recommendations for our future research endeavors. Methods: The research is a cross-sectional study type. The sample included 64 primary school teachers in the lower grades of primary school (grades 1–4), selected by using simple random sampling, in three primary schools on the territory of Belgrade, Serbia in 2021 (26, 17, and 21 primary school teachers). The Questionnaire for Teachers, which was used as a research instrument, was taken from the Master's Thesis Studen Rajke, which was part of the project “Education for the Knowledge Society” at the Institute for Educational Research in Belgrade. Dependent variables measured in the study referred to the attitudes of primary school teachers toward inclusive education. Categorical variables are represented as frequencies and the Chi-square test was used to determine if a distribution of observed frequencies differed from the expected frequencies. Results: One in three teachers (32.8%) thought that inclusion was useful for children with disabilities (29.7%), of them thought that schools did not have the conditions for inclusive education, whereas one in four teachers (25.0%) believed that inclusion was not good. No statistically significant differences were found in the attitudes of professors, when observed in terms of their gender, age and length of service. Conclusion: Investing more resources and time in developing and implementing special education policies can promote successful inclusive education

Closed-loop separation control over a sharp edge ramp using Genetic Programming

We experimentally perform open and closed-loop control of a separating turbulent boundary layer downstream from a sharp edge ramp. The turbulent boundary layer just above the separation point has a Reynolds number $Re_{\theta}\approx 3\,500$ based on momentum thickness. The goal of the control is to mitigate separation and early re-attachment. The forcing employs a spanwise array of active vortex generators. The flow state is monitored with skin-friction sensors downstream of the actuators. The feedback control law is obtained using model-free genetic programming control (GPC) (Gautier et al. 2015). The resulting flow is assessed using the momentum coefficient, pressure distribution and skin friction over the ramp and stereo PIV. The PIV yields vector field statistics, e.g. shear layer growth, the backflow area and vortex region. GPC is benchmarked against the best periodic forcing. While open-loop control achieves separation reduction by locking-on the shedding mode, GPC gives rise to similar benefits by accelerating the shear layer growth. Moreover, GPC uses less actuation energy.Comment: 24 pages, 24 figures, submitted to Experiments in Fluid

Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach

The final publication is available at Springer via http://dx.doi.org/10.1007/s00348-015-2107-3The potential benefits of active flow control are no more debated. Among many others applications, flow control provides an effective mean for manipulating turbulent separated flows. Here, a nonthermal surface plasma discharge (dielectric barrier discharge) is installed at the step corner of a backward-facing step (U0 = 15 m/s, Reh = 30,000, Re¿ = 1650). Wall pressure sensors are used to estimate the reattaching location downstream of the step (objective function #1) and also to measure the wall pressure fluctuation coefficients (objective function #2). An autonomous multi-variable optimization by genetic algorithm is implemented in an experiment for optimizing simultaneously the voltage amplitude, the burst frequency and the duty cycle of the high-voltage signal producing the surface plasma discharge. The single-objective optimization problems concern alternatively the minimization of the objective function #1 and the maximization of the objective function #2. The present paper demonstrates that when coupled with the plasma actuator and the wall pressure sensors, the genetic algorithm can find the optimum forcing conditions in only a few generations. At the end of the iterative search process, the minimum reattaching position is achieved by forcing the flow at the shear layer mode where a large spreading rate is obtained by increasing the periodicity of the vortex street and by enhancing the vortex pairing process. The objective function #2 is maximized for an actuation at half the shear layer mode. In this specific forcing mode, time-resolved PIV shows that the vortex pairing is reduced and that the strong fluctuations of the wall pressure coefficients result from the periodic passages of flow structures whose size corresponds to the height of the step model.Peer ReviewedPostprint (author's final draft

Frequency selection by feedback control of a turbulent shear-flow

International audienceMany previous studies have shown that the turbulent mixing layer under periodic forcing tends to adopt a lock-on state, where the major portion of the fluctuations in the flow are synchronized at the forcing frequency. The goal of this experimental study is to apply closed-loop control in order to provoke the lock-on state, using information from the flow itself. We aim to determine the range of frequencies for which the closed-loop control can establish the lock-on, and what mechanisms are contributing to the selection of a feedback frequency. In order to expand the solution space for optimal closed-loop control laws, we use the genetic programming control (GPC) framework. The best closed-loop control laws obtained by GPC are analysed along with the associated physical mechanisms in the mixing layer flow. The resulting closed-loop control significantly outperforms open-loop forcing in terms of robustness to changes in the free-stream velocities. In addition, the selection of feedback frequencies is not locked to the most amplified local mode, but rather a range of frequencies around it

Evaluation of quality of life in patients with schizophrenia: An inpatient social welfare institution-based cross-sectional study

Schizophrenia is a chronic mental illness with a poor quality of life (QoL). The main aim of this study was to measure the QoL and factors that affect the QoL of patients with schizophrenia placed in a social welfare institution. This cross-sectional study included 287 patients with schizophrenia who were treated in a long-stay social care institution in which QoL was assessed using five different instruments: the World Health Organization Quality of Life scale, the EuroQoL Five-Dimension-Five-Level scale (including the visual analog scale), the Quality of Life Enjoyment and Satisfaction Questionnaire – Short Form, and the Brief Psychiatric Rating Scale. To determine the impact of patients’ characteristics on score values, multiple linear regression using backward elimination was employed. Due to non-normality in the distribution of the dependent variables, a Box–Cox power transformation was applied to each dependent variable prior to conducting multiple linear regression analysis. Results revealed that patients with schizophrenia have lower QoL. Our study revealed that age, level of education, type of accommodation, type of pavilion, age of onset of the disease, number of prescribed antipsychotics, number of psychiatric comorbidities, duration of therapy, and the number of daily doses of antipsychotics are dominant contributors to the QoL in patients with schizophrenia who were treated in social welfare institution