THE IMPORTANCE OF FLORA ADMINISTRATION IN THE MUNICIPALITY OF GUARUJÁ (SP), BRAZIL

Objective – The study aimed to map, identify and catalog the tree species present in the municipality of Guarujá, Metropolitan Region of Baixada Santista, State of São Paulo, used in the afforestation of the municipality. The criteria for the choice of species by the city were evaluated, aiming through this survey, future proposals for better management in the administration of inclusion of urban flora; inclusion of native species, prioritizing species that are attractive to the region's fauna. Methods - During the study, samples were taken in 5 (five) points of the city of Guarujá, with materials that present an equivalent representation of populations. The studies were carried out following seasonality, in order to observe the environmental influence on the distribution of plants. Results - Twelve families, 28 genera and 29 species were identified in the samples carried out in 117 streets in 5 districts, being 57 streets in the Vila Áurea district, 24 streets in the Jardim Progresso district, 10 streets in the Santa Rosa district, 12 streets in the Pitangueiras district and 10 streets in the Virginia Garden District. Conclusion - The interest in paying attention to plant species used in afforestation in the municipality of Guarujá is due to the fact that inappropriate afforestation is observed, sometimes planted by residents, without guidance and thus without technical criteria, thus creating a future problem, for example, causing problems urban areas such as pavement destruction, changes in the landscape and species that are not always attractive to fauna. Another fact that is also observed is the low diversity of species present, many of them exotic and not native to the region.

RESEARCH CENTERS OF DOMESTIC MAKARENKO STUDIES

The article for the first time in domestic science systematizes the history of formation and development of Ukrainian centers for the study of the creativity heritage of the outstanding teacher and writer A. Makarenko. It is emphasized that Ukraine is an integral and important part of the world Makarenko studies process, it has been at the origins of this area of research and has remained one of its driving forces for many years.The first independent Makarenko center of Ukraine was a research center formed at the Ivan Franko Lviv State University. Its initiator and long-term leader was F. Naumenko, who in the difficult socio-political conditions of the Western Ukrainian community managed to actualize in the first postwar years this promising scientific direction, unite around him young scientists and create a powerful Makarenko school. Authoritative and one of the oldest Ukrainian centers for the study of the heritage of A. Makarenko is the Kharkiv Makarenko School, personified by scientists of the Kharkiv National Hryhoriy Skovoroda Pedagogical University. A characteristic feature of this scientific center is the almost equivalent representation in it of both pedagogical and literary directions of A. Makarenko’s heritage development. The proximity of Poltava V. Korolenko Pedagogical University with the name of an outstanding teacher-reformer inspires bright traditions of research activity of student and teaching staff, including the activities of Makarenko’s student group, Research Laboratory of A. Makarenko and International and All-Ukrainian Makarenko Center, the creation of the State Museum-Reserve A. Makarenko in the village of Kovalivka near Poltava and the Internet resource “Makarenkiana”, holding annual international scientific conferences, unique editions of archival documents and more. Sumy State A. Makarenko Pedagogical University is also a powerful Makarenko center, which has a deep tradition of development of this area of historical and pedagogical science.

Affinity Derivation for Accurate Instance Segmentation

Affinity, which represents whether two pixels belong to a same instance, is an equivalent representation to the instance segmentation labels. Conventional works do not make an explicit exploration on the affinity. In this article, we present two instance segmentation schemes based on pixel affinity information and show the effectiveness of affinity in both aspects. For proposal-free method, we predict pixel affinity for each image and then propose a simple yet effective graph merge algorithm to cluster pixels into instances. It shows that the affinity is powerful as an instance-relevant information to guide the clustering procedure in proposal-free instance segmentation. For proposal-based methods, we extend conventional framework with affinity head and introduce affinity as attached supervision in training phase. Without any additional inference cost, we can improve the performance of existing proposal-based instance segmentation methods, which shows that the affinity can also be applied as an auxiliary loss and training with such extra loss is beneficial to the training progress. Experimental results show that our schemes achieve comparable performance to other state-of-the-art instance segmentation methods. With Cityscapes training data, the proposed proposal-free method achieves 28.8 AP and the proposal-based method gets 27.2 AP both on test sets.

Solving Higher-Order Boundary and Initial Value Problems via Chebyshev–Spectral Method: Application in Elastic Foundation

In this work, we introduce an efficient scheme for the numerical solution of some Boundary and Initial Value Problems (BVPs-IVPs). By using an operational matrix, which was obtained from the first kind of Chebyshev polynomials, we construct the algebraic equivalent representation of the problem. We will show that this representation of BVPs and IVPs can be represented by a sparse matrix with sufficient precision. Sparse matrices that store data containing a large number of zero-valued elements have several advantages, such as saving a significant amount of memory and speeding up the processing of that data. In addition, we provide the convergence analysis and the error estimation of the suggested scheme. Finally, some numerical results are utilized to demonstrate the validity and applicability of the proposed technique, and also the presented algorithm is applied to solve an engineering problem which is used in a beam on elastic foundation.

Robust Stability of Complex-Valued Stochastic Neural Networks with Time-Varying Delays and Parameter Uncertainties

In practical applications, stochastic effects are normally viewed as the major sources that lead to the system’s unwilling behaviours when modelling real neural systems. As such, the research on network models with stochastic effects is significant. In view of this, in this paper, we analyse the issue of robust stability for a class of uncertain complex-valued stochastic neural networks (UCVSNNs) with time-varying delays. Based on the real-imaginary separate-type activation function, the original UCVSNN model is analysed using an equivalent representation consisting of two real-valued neural networks. By constructing the proper Lyapunov–Krasovskii functional and applying Jensen’s inequality, a number of sufficient conditions can be derived by utilizing It o ^ ’s formula, the homeomorphism principle, the linear matrix inequality, and other analytic techniques. As a result, new sufficient conditions to ensure robust, globally asymptotic stability in the mean square for the considered UCVSNN models are derived. Numerical simulations are presented to illustrate the merit of the obtained results.

Multivariate Collective Risk Model: Dependent Claim Numbers and Panjer’s Recursion

In this paper, we discuss a generalization of the collective risk model and of Panjer’s recursion. The model we consider consists of several business lines with dependent claim numbers. The distributions of the claim numbers are assumed to be Poisson mixture distributions. We let the claim causes have certain dependence structures and prove that Panjer’s recursion is also applicable by finding an appropriate equivalent representation of the claim numbers. These dependence structures are of a stochastic non-negative linear nature and may also produce negative correlations between the claim causes. The consideration of risk groups also includes dependence between claim sizes. Compounding the claim causes by common distributions also keeps Panjer’s recursion applicable.

The observational equivalence of natural and unnatural rates of interest

The results of the study presented in this paper demonstrate that a structural model of the natural interest rate, which is consistent with the standard assumptions of the natural rate theory, admits an interpretable, observationally equivalent representation in which a redefined, ’unnatural’ equilibrium rate is different from the natural rate in the original model. The alternative representation was obtained by an invertible transformation implemented in the minimal state-space form of the natural-rate model. The identification theory for state-space models is used in the paper to prove the observational equivalence of these two representations. In the alternative representation, the equilibrium interest rate fails to meet the assumption of the natural rate theory, because it depends on past demand shocks. The alternative model, being observationally equivalent, has different implications for the conduct of monetary policy. The problem of observational equivalence arises in relation to natural-rate models because of the inherent unobservability of the natural interest rate; a potential solution to this problem could be the augmentation of the information set which is used to identify and estimate the natural rate.

Mathematical Connection Ability : Impact of Contextual Teaching And Learning Approaches in Flat Side Space Lesson

The purpose of this research is to analyze the students' mathematical connection ability before and after getting Contextual Teaching and Learning. The subjects were the 26 students of class VIII-A at SMI 1 MANIIS, Purwakarta Regency. The research used the descriptive method with the qualitative approach. The data for the analysis were from the test to student consist of 5 questions with 4 different indicators. The results shows that all students have moderate in mathematical connection ability with the overall results of 65.83%. For the results of each indicator, there is one indicator that has not been met, understanding the equivalent representation from one procedure to another one, or from one concept to another concept. So it can be concluded that the mathematical connection ability in terms of the Contextual Teaching and Learning approach has a significant effect.