All Articles

Summary: The aim of this study is to examine the relationship between teachers’ job crafting, job satisfaction, and life satisfaction. This study is significant for understanding how the relationship between job crafting, job satisfaction, and life satisfaction contributes to enhancing the overall quality of life of teachers, who are key stakeholders in the education system. The literature highlights a strong relationship between job satisfaction and life satisfaction, emphasizing that the satisfaction individuals derive from their jobs positively influences their overall well-being. Aligned with the purpose of the study, Job Crafting Scale, Job Satisfaction Scale and Satisfaction with Life Scale were used. The results indicate that teachers’ job satisfaction and cognitive job crafting have a significant and positive impact on their life satisfaction. However, the dimensions of task crafting and relational crafting were found to have no significant effect on life satisfaction. Also, the study revealed that female teachers exhibit higher levels of cognitive, relational, and task crafting compared to male teachers. Finally, the article, provide some suggestions and directions for future research.

Summary: The Net Promoter Score (NPS) has emerged as a well-known measure for assessing customer satisfaction and loyalty across different sectors, including higher education. This study examines how NPS is applied in higher education institutions to assess student satisfaction, loyalty, and overall institutional effectiveness. This study explores how adapting NPS, typically used in business environment, to the specific dynamics of higher education can function as an essential instrument for evaluating student experiences, pinpointing areas needing enhancements, and promoting greater student involvement. This research seeks to offer higher education leaders practical insights to improve student satisfaction, loyalty, and institutional results via NPS. The net promoter score's importance for higher education was investigated using systematic and phenomenological approaches.

Summary: Unemployment is an important phenomenon affecting all economies, especially during crises such as the recent COVID-19 pandemic. Besides, the government size is significant for all the formerly planned and centralized economies, like the Central and Eastern European countries. This study aims to investigate the impact of government size, income tax, economic growth, inflation, trade openness, and urbanization process on the unemployment level in Romania from 1991 to 2021. After testing the nonlinearity property, the findings of the nonlinear autoregressive distributive lag (NARDL), estimations show a positive influence of urbanization on unemployment. Conversely, government size significantly reduces the unemployment rate in Romania. Inflation and trade are negatively associated with unemployment, while taxation has a positive impact. In this regard, the Romanian authorities should adopt appropriate measures to support governmental expenditure, they need to collect budgetary tax that can reduce the unemployment rate, unless some efficiency measures are adopted such as defeating tax evasion which is high in Romania.

Summary: A mathematical model of a queuing-inventory system (QIS) with catastrophes is built. Incoming customers form a Poisson flow with rate λ. The customer servicing time in the considered QIS is zero. The (S,Q) replenishment policy is used to increase the inventory level in the system. Here, S is the maximum storage size of the QIS, and Q=S-s indicates the fixed size of the proposed order.

Summary: Pneumonia is a prevalent illness that has a global impact, primarily affecting children and older individuals. Timely identification is essential for immediate intervention, particularly in regions with restricted healthcare availability. The purpose of this paper is to compare how well two methods work for finding pneumonia on chest X-rays creating a custom Convolutional Neural Network (CNN) and using a model that has been pre-trained, such as ResNet-50. The results indicated that although the customized CNN had difficulties achieving satisfactory performance, the ResNet-50 model demonstrated encouraging outcomes following the process of fine-tuning. This paper seeks to improve the detection of pneumonia, especially in disadvantaged places with limited medical resources, by utilizing modern technologies such as deep learning and pre-trained models. Considering the results gained to enhance patient outcomes and decrease mortality rates associated with pneumonia by enabling more precise and prompt detection, this has a beneficial effect on global public health

Summary: This work is dedicated to the impulsive Sturm - Liouville operator on the whole axis with complex almost periodic potentials and the discontinuous coefficient on the right – hand side. We investigated the main characteristics of the fundamental solutions of the Sturm – Liouville equation. From the impulsive condition we found the transfer matrix. Using the impulsive condition and transfer matrix, we constructed Green’s function and obtained the resolvent of the impulsive Sturm – Liouville operator. In future works, eigenvalues of the impulsive Sturm - Liouville operator will be investigated. The inverse problem will be formulated, a constructive procedure for the solution of the inverse problem will be provided.

Summary: Artificial intelligence driven drone systems offer promising solutions for early detection and response to environmental hazards like wildfires and oil leaks. However, their widespread adoption raises significant ethical and environmental implications, including privacy infringements, algorithmic bias, data security, noise pollution, and greenhouse gas emissions. This study addresses these issues through literature reviews, surveys of affected populations, and prototype testing of AI models for disaster identification, in order to mitigate ethical issues. A specific metric was developed to rate drone components and identify the most sustainable options, minimizing the environmental impact. By promoting these solutions, this research aims to ensure the sustainable and responsible integration of artificial intelligence systems in environmental monitoring, protecting ecosystems and communities effectively.

Summary: The paper considers a boundary value problem generated by a differential diffusion equation and nonseparated boundary conditions. One of the boundary conditions contains a quadratic function of the spectral parameter. The multiplicity of eigenvalues of the boundary value problem under consideration is investigated. A criterion for the multiplicity of eigenvalues and zeros of the characteristic function of a boundary value problem is obtained.The found necessary and sufficient conditions are expressed through the values of the fundamental solutions of the diffusion equation and the coefficients of the boundary conditions. Note that the results obtained can be used in the study of direct and inverse problems of spectral analysis for various differential operators. These results also play an important role in studying the structure of the spectrum, in establishing the order of arrangement of eigenvalues of boundary value problems, and in finding sufficient conditions for the reconstruction of the corresponding problems.

Summary: In this article, the issue of controlling the movement of a hexacopter-type unman-ned aerial vehicle (UAV) along a route is investigated. The movement of the hexacopter is modeled as the movement of a rigid body, and in this process, the forces of gravity and aerodynamic resistance are taken into account. The spatial orientation of the hexacopter is expressed using quaternions. The movement route is considered as a broken line consisting of straight segments, and the parameters controlling its flight are determined when one of the hexacopter's motors is not working. Mathematical justification is provided for how the operational motors are controlled to continue the hexacopter's movement in its previous manner when one motor fails.

Summary: The paper examines different types of hypersingular integrals with the Cauchy kernel on a segment and a unit circle and defines them using specific methods. It presents more general definitions for one-dimensional hypersingular integrals with the Cauchy kernel based on Hadamard's integral in the sense of a finite part. The paper also establishes the existence theorems of these hypersingular integrals and formulas, which demonstrates the accuracy of the resulting integrals that are applied in various applications and engineering problem-solving. The proposed formulas are straightforward to calculate, making the new approximate method reliable and easy to apply and the obtained numerical results demonstrate the stability and efficiency of the approach.