Ivana Carla Strapazzon, Marco Tulio Aniceto França, Gustavo Saraiva Frio
Uma das formas de um estudante receber dinheiro é por meio da mesada. Esse mecanismo representa uma forma de os pais premiarem os(as) filhos(as) por bom comportamento, permitindo que os jovens possam fazer a gestão do dinheiro para cobrir despesas extraordinárias ou, ainda, um presente livre de condições. Nesse contexto, o artigo estuda o efeito dessa ação por meio de diferentes modelos de pareamento: escore de propensão (Propensity Score Matching), Ponderação pelo Inverso da Probabilidade do Tratamento (IPTW), Balanceamento por Entropia e Distância de Mahalanobis associado à Regressão Ajustada (RA), chamada de duplamente robusta, sobre o letramento financeiro de jovens usando a base de dados do PISA (Programme for International Student Assessment) 2018. Os resultados mostram que o ganho de mesada é benéfico para todos os jovens, quando ela é não condicionada, caracterizando-se como um presente, contribuindo para o aumento das notas no PISA, em especial para os meninos, e aumentando a diferença entre os gêneros em educação financeira. Além disso, a pesquisa demonstrou que, quando a mesada é condicionada, seu efeito se torna negativo, reduzindo as notas de finanças das meninas. Uma possível explicação é a menor disponibilidade de tempo para estudar, decorrente das atividades domésticas, o que contribui para a redução do desempenho em alfabetização financeira.
Economic theory. Demography, Economic history and conditions
Najeeb Manhanpally, Praveen Nagarajan, Suman Saha
et al.
Abstract In search of sustainable construction material as an alternative to existing ordinary cement concrete, the use of recycled aggregates in geopolymer concrete has garnered significant attention. Using industrial by-products such as dolomite and ground granulated blast furnace slag (GGBS), combined with alkali activators like sodium silicate and sodium hydroxide to prepare geopolymer concrete, offers a promising substitute to traditional Portland cement concrete. This study explores the potential of incorporating recycled aggregates, specifically focusing on the benefits of treated recycled-aggregates (TRCA) into the concrete for improving sustainability of geopolymer concrete. Mechanical grinding treatment is found to be effective in removing adhered mortar from recycled-aggregates, and thus improving aggregate quality and reducing porosity and micro-cracks. By systematically analyzing the effects of untreated and treated recycled aggregates on concrete properties, this research provides a comprehensive understanding of how treatment processes can mitigate the limitations of RCA and optimize the material’s performance. Incorporating treated recycled aggregates enables the construction industry to adopt more sustainable building practices, thus helping global efforts to minimise damages to the environment. The experimental results demonstrated that treating recycled aggregates showed key engineering properties of geopolymer concrete similar to normal geopolymer concrete with reduction less than 5% at 100% replacement level. Geopolymer concrete, made from GGBS and dolomite with treated recycled aggregates, provides a sustainable substitute for conventional concrete, offering environmental and structural advantages. This paper promotes the use of treated recycled aggregates to decrease the dependency on natural resources, therefore promoting the circular economy within the building industry. The findings of this study are expected to advance the knowledge of recycled aggregate utilization in geopolymer concrete, offering practical insights for construction professionals and researchers. The research seeks to develop novel, sustainable, and high-performance construction materials that meet environmental and structural requirements.
Maja Rajković, Ivana Jelić, Marija Janković
et al.
The increasing importance of waste materials utilization with the necessary modification to remove various pollutants from industrial wastewater has been a research focus over the past few decades. Using waste material from one industry to solve pollution problems in another ultimately leads toward sustainable and circular approaches in environmental engineering, solving waste management and wastewater treatment issues simultaneously. In contemporary research and industry, there is a notable trend toward utilizing industrial wastes as precursors for adsorbent formation with a wide application range. In line with this trend, red mud, a byproduct generated during alumina production, is increasingly viewed as a material with the potential for beneficial reuse rather than strictly a waste. One of the potential uses of red mud, due to its specific composition, is in the removal of heavy metal and radionuclide ions. This study summarizes red mud’s potential as an adsorbent for wastewater treatment, emphasizing techno-economic analysis and sorption capacities. An overview of the existing research includes a critical evaluation of the adsorption performance, factors influencing efficiency rather than efficacy, and the potential for specific pollutant adsorption from aqueous solutions. This review provides a new approach to a circular economy implementation in wastewater treatment while guiding future research directions for sustainable and cost-effective solutions.
Accurate dynamic assessment of water resource carrying capacity (WRCC) plays a pivotal role in urban sustainability governance. This study developed a comprehensive evaluation framework for regional WRCC, comprising an indicator system with standardized assessment criteria. We proposed an innovative methodology for computing dynamic difference coefficients by integrating semi-partial subtraction set pair potential with triangular fuzzy numbers, subsequently constructing a coupled dynamic evaluation model. Using Hefei City(Anhui Province, China) as a demonstrative case, our analysis reveals:(1) Compared with the level characteristic value method based on set pair analysis, the proposed method reduces the evaluation error of sample evaluation grade values by 1.6 %. Moreover, it is confirmed that the difference coefficient exhibits significant dynamic variation characteristics with both samples and time, which significantly enhances the dynamics, inclusiveness, and rationality of sample evaluation results. (2) From the temporal dimension, the overall WRCC of Hefei is in a state of equi-potential and partial anti-potential. The potential value decreased from −0.148(2012) to −0.196(2023), with an average annual decline rate of 2.95 %, indicating that the WRCC tends to deteriorate.(3) From the spatial distribution perspective, the WRCC of the Shixiaqu is the worst (moderate overload status), followed by Changfeng County, Feixi County, Feidong County, and Lujiang County (slight overloaded status), and then Chaohu City (critical status).This systematic approach provides multidimensional insights into Hefei's WRCC evolution, establishing a scientific foundation for adaptive water resource management strategies and water security enhancement in rapidly urbanizing regions.
Syed Ijaz Ul Haq, Guobin Wang, Shahid Nawaz Khan
et al.
Early and accurate detection of crop stress is essential for sustainable agriculture and food security, particularly as climate change and environmental degradation intensify agricultural challenges. This comprehensive review examines advanced crop stress monitoring strategies that leverage multi-dimensional optical remote sensing approaches, specifically integrating spectral, angular, and spatial perspectives across diverse observation scales. We systematically analyze how biotic stresses (diseases, pests) and abiotic stresses (drought, nutrient deficiency, temperature extremes) manifest through detectable changes in plant spectral signatures, from chlorophyll degradation in the visible spectrum to water content variations in shortwave infrared regions. Our review encompasses sensing technologies spanning RGB, multispectral, hyperspectral, thermal infrared, and chlorophyll fluorescence sensors deployed across three complementary scales: proximal ground-based systems for detailed physiological assessment, unmanned aerial vehicles (UAVs) for field-scale monitoring, and satellites for regional surveillance. A key innovation of this work is the emphasis on multi-angle remote sensing, which captures bidirectional reflectance distribution function (BRDF) effects that reveal stress-induced changes in canopy structure and leaf orientation invisible to conventional nadir-only observations. We demonstrate how viewing geometry significantly affects vegetation indices (NDVI, PRI) and sun-induced fluorescence (SIF) measurements, requiring sophisticated angular correction methods for accurate stress assessment. Through synthesis of 138 recent studies spanning 12 major crop types, we identify critical research gaps including: (1) inconsistent angular reflectance modeling across stress types, (2) inadequate sensor calibration protocols for variable field conditions, and (3) lack of standardized frameworks for integrating multi-source, multi-scale data streams. Our analysis reveals that advanced machine learning approaches particularly deep learning and transformer networks show exceptional promise for extracting meaningful stress signatures from complex, high-dimensional datasets while maintaining interpretability for agricultural decision-making. We propose a hierarchical monitoring architecture supported by physics-aware artificial intelligence models that address three fundamental challenges: temporal optimization for capturing stress progression dynamics, spatial integration across observation scales, and angular standardization for consistent stress quantification. This framework aims to transform crop stress monitoring from reactive management to predictive intervention, enabling real-time diagnostics suitable for diverse agricultural systems ranging from high-value specialty crops to extensive grain production. The review concludes with a strategic roadmap for operational implementation, addressing economic constraints, technological limitations, and knowledge transfer requirements necessary for widespread adoption. Our findings indicate that successful deployment requires service-based delivery models, simplified decision support interfaces, and staged implementation approaches that demonstrate incremental value while building organizational capacity. The literature selection was conducted using Scopus, Web of Science, and IEEE Xplore databases, covering publications from 2018 to 2024. Search terms included “crop stress monitoring,” “spectral remote sensing,” “multi-angle sensing,” and “UAV agriculture.” A total of 138 peer-reviewed studies meeting relevance and methodological rigor criteria were included. These studies span 12 major crop types: wheat, maize, rice, soybean, cotton, sugarcane, potato, grapevine, tomato, barley, sorghum, and rapeseed, ensuring broad coverage across cereal, legume, fiber, tuber, and horticultural crops.
The purpose of this research is to analyze the Synergy of Green Economy, Blue Economy and Brown Economy as a Prerequisite for the Success of SDG’s. or literature study. By comparing hypotheses found in literature books or previous research findings found in scientific journals, this strategy investigates a hypothesis according to the discipline of Green Economy, Blue Economy and Brown Economy Synergy and SDG’s Success. Based on the analysis that has been done, the synergy of green economy synergy is: such as reducing carbon emissions. The findings of this study include the term ""green economy"" refers to a way of thinking about economic activities that emphasizes economic growth and the idea of preventing environmental degradation and damage that has an impact on improving the welfare of society and humanity. synergy of the blue economy is 1) This idea gives priority to the improvement of marine manufacturing. 2) In terms of contribution to national income, marine productivity will be a major sector. 3) Most of the fishing waste can be exported as commodities and earn foreign exchange. And the synergy of the brown economy is: increasing the competitiveness of a nation. Even if some mitigation measures, such as transition or adjustment costs, still entail net costs, the potential future damage from ongoing climate change may be much higher.
The work is devoted to the study of the problems of forming a full-fledged set of competencies of engineers, contributing to their professional implementation and ensuring the personnel sovereignty of domestic enterprises. The necessity of participation in the training of engineering personnel of enterprises of the real sector of the economy, especially the high-tech sector, is substantiated. The role of integration of technical universities and enterprises in the process of personnel training to ensure technological and personnel sovereignty of the Russian industry is shown. The personnel sovereignty of the Russian economy is impossible without attracting a sufficient number of highly qualified specialists who have received education in relevant, practice-oriented programs that include not only basic knowledge, skills and training skills, but also "soft" skills that allow you to choose and apply successful behavioral and communication strategies in various production situations. The main factors that need to be guided by when building an effective system for training engineers are identified. Underestimation of these factors, leading to the exclusion of disciplines such as business planning, resource management, and business communications from the educational programs of technical universities, reduces the effectiveness of training graduates who replenish the personnel corps of enterprises, therefore, special attention is paid in the article to the problem of forming a set of competencies of engineers that contribute to their professional implementation and, ultimately, ensuring human resources the sovereignty of the high-tech sector of the economy.
Education (General), Theory and practice of education
Предметом дослідження в статті є вплив глобальних катастроф, зокрема пандемії COVID-19 та російської збройної агресії проти України, на споживчу поведінку українців у інтернет-магазинах, зокрема на зміни в потребах споживачів і адаптація маркетингових стратегій підприємств. Мета роботи – аналіз змін споживчої поведінки в умовах глобальних катастроф і розроблення рекомендацій для бізнесу щодо ефективного реагування на нові виклики ринку. У статті виконуються такі завдання: досліджується вплив пандемії COVID-19 та російської збройної агресії проти України на споживчу поведінку в інтернет-магазинах; визначаються ключові чинники, що позначаються на рішеннях споживачів під час кризових ситуацій; аналізуються актуальні маркетингові стратегії та інструменти, що застосовуються компаніями в умовах кризи. Упроваджуються такі методи: математичне оброблення даних для аналізу результатів опитувань і статистичних досліджень; компаративний аналіз для порівняння поведінки споживачів до та під час пандемії; експертне оцінювання для визначення ефективності маркетингових стратегій; контент-аналіз для дослідження трендів у соціальних мережах та інших онлайн-платформах. Досягнуті результати. Сформульовано принципи адаптації маркетингових стратегій в умовах пандемії COVID-19 та воєнного стану. Визначено, що пріоритетами для споживачів стають здоров’я, доступність основних товарів і безпека, зокрема й кібербезпека. Виявлено зміни в споживчій поведінці: люди стали більш уважними до ціни, якості товарів та віддають перевагу продуктам місцевих виробників. Проведено маркетингове дослідження серед клієнтів компанії "Горгани", яке показало, що попит на товари для активного відпочинку залишається високим, навіть у період війни, і споживачі віддають перевагу якісним і доступним товарам вітчизняного виробництва. Висновки: застосування методу аналізу змін споживчої поведінки дало змогу визначити ключові фактори, що впливають на рішення про покупку в умовах глобальних криз, знання сприяє тому, що підприємства вчасно адаптують свої маркетингові стратегії та зберігають конкурентні переваги; оптимізація асортименту товарів та вдосконалення цифрової присутності є ключовими факторами успіху на сучасному ринку; підприємства, які швидко реагують на зміни споживчих пріоритетів і використовують новітні технології для комунікації з клієнтами, мають більше шансів на успіх.
Boris I. Bednyi, Nikolay V. Rybakov, Nadezhda A. Khodeeva
Modern Russian postgraduate school is institutionally oriented towards the reproduction of the personnel potential for science and higher education. Since the career trajectories of a significant part of PhD graduates go beyond the academic labor market, the scientific and pedagogical community is discussing the prospects for the development of the so-called professional postgraduate studies in Russia, which should provide targeted training of highly qualified personnel for knowledge-intensive sectors of the economy and the sphere of intellectual services. The discourse on professional postgraduate studies is focused on the possibility of adapting the effective practices of foreign universities, and, unfortunately, is currently not supported by quantitative data on the demand for such a format of postgraduate training in Russia. The purpose of this study is an empirical analysis of the demand for professional postgraduate studies in the field of technical sciences. Using data on PhD graduates who successfully defended dissertations in technical sciences in 2019 as an example, for the first time a quantitative assessment was made of the prevalence of practice-oriented dissertations, the authors of which are employees of organizations in the knowledge-intensive sectors of the economy. The empirical basis of the study was the publicly available data on the defense of dissertations for the degree of candidate of technical sciences in Russia in 2019 (N=1663). For a detailed analysis, dissertation materials were selected, which contained information about postgraduate studies and the place of employment of dissertators (N=715). As a result of the study, parameters were determined that characterize the degree of prevalence in Russia of practice-oriented dissertations on various disciplinary groups of technical sciences, including: the proportion of PhD graduates employed outside the academic sphere; the proportion of dissertations thematically related to the professional activities of their authors; prevalence of preparation of dissertations on the basis of enterprises of the real sector of the economy; differences in socio-demographic characteristics and publication activity of PhD graduates working on dissertations at universities and in science-intensive business organizations. On the basis of the analysis, a conclusion is made about the expediency of developing professional postgraduate programs in the field of engineering and technology aimed at staffing the innovation sphere, as well as legitimizing the special requirements for these programs and practice-oriented dissertations prepared during their implementation.
Globally, over 1.4 billion adult people remain unbanked. This worrisome phenomenon was exacerbated by the outbreak of the COVID-19 pandemic, which further created a new dimension of inequality in accessing financial services. Digital financial inclusion promises to be an effective tool for addressing this socioeconomic ill and propelling economic development. Given the limited studies on the subject in the context of developing economies, it is imperative to understand the existing policies, practices, and barriers to digital financial inclusion in developing economies so as to provide cutting-edge interventions for redress. It is against this background that this study seeks to address the following research questions: (1) What is the state of digital financial inclusion in the developing economy? (2) What are the policies and practices regarding digital financial inclusion in the developing economy? (3) What are the barriers to digital financial inclusion and innovative interventions for redress? Findings reveal that about 44% of the adult population in developing countries does not have access to financial services, with only a few countries that have made significant progress and gains through policy and practice, such as mobile financial services, mobile money interoperability, native connectivity, human capital development, and the digitalization of public services for digital financial inclusion. Our findings also identify challenges and implications with recommendations, which are discussed in detail in this paper.
Gunamantha I. Made, Oviantari Made Vivi, Yuningrat Ni Wayan
The existence of waste in the environment, which is not managed well, could contribute to global warming and cause climate change on the earth. This research aimed to determine the suitable management preference for organic waste treatment produced in small cities. The methods used are based on pair comparison in hierarchy decisions developed through the analytical hierarchy process. The hierarchy consisted of goals, criteria, sub-criteria and alternatives applied to waste treatment engineering. The expert suggestion was used in a pair comparison matrix to determine the level of technology. The comparison was used to get the significance level of decision criteria and the relative performance of the options. The city’s waste managed by the Buleleng government was used to demonstrate the application of the analytical hierarchy process in that region. The result showed that the important factor in deciding on waste treatment for the small city is environment and engineering, with each eigenvector priority (0.28), sociocultural (0.24) and economy (0.20). According to the recruitment preference for Singaraja waste treatment, the analytical hierarchy process showed that controlled landfill and composting are the most suitable treatment, followed by incineration, anaerobic digestion, and mechanical and biological treatment.
The subject of the article is feature selection techniques that are used on data preprocessing step before building machine learning models. In this paper the focus is put on a Filter technique when it uses Correlation-based Feature Selection (further CFS) with symmetrical uncertainty method (further CFS-SU) or CFS with Pearson Correlation (further CFS-PearCorr). The goal of the work is to increase the efficiency of feature selection by Filter with CFS by proposing a new organization process of feature selection. The tasks which are solved in the article: review and analysis of the existing organization process of feature selections
by Filter with CFS; identify the routs cause the performance degradation; propose a new approach; evaluate the proposed approach. To implement the specified tasks, the following methods were used: information theory, process theory, algorithm theory, statistics theory, sampling techniques, data modeling theory, science experiments. Results. Based on the received results are proved: 1) the chosen features subset’s evaluation function couldn’t be based only on CFS merit as it causes a learning algorithm’s results degradation; 2) the accuracies of the classification learning algorithms had improved and the values of determination coefficient of the regression leaning algorithms had increased when features are selected according to the proposed new organization process. Conclusions. A new organization process for feature selection which is proposed in current work combines filter and learning algorithm properties in evaluation strategy which helps to choose the optimal feature subset for predefined learning algorithm. The computation complexity of the proposed approach to feature selection doesn’t depend on dataset’s dimensions which makes it robust to different data varieties; it eliminates the time needed for feature subsets’ search as subsets are selected randomly. The conducted experiments proved that the performance of the classification and regression learning algorithms with features selected according to the new flow had outperformed the performance of the same learning algorithms built with without applied new process on data preprocessing step.
Francesca Patrignani, Gabriella Siesto, Davide Gottardi
et al.
The present research is aimed at investigating the potential of two commercial <i>Saccharomyces cerevisiae</i> strains (EC1118 and AWRI796) to generate wine-specific volatile molecule fingerprinting in relation to the initial must applied. To eliminate the effects of all the process variables and obtain more reliable results, comparative fermentations on interlaboratory scale of five different regional red grape musts were carried out by five different research units (RUs). For this purpose, the two <i>S. cerevisiae</i> strains were inoculated separately at the same level and under the same operating conditions. The wines were analyzed by means of SPME-GC/MS. Quali-quantitative multivariate approaches (two-way joining, MANOVA and PCA) were used to explain the contribution of strain, must, and their interaction to the final wine volatile fingerprinting. Our results showed that the five wines analyzed for volatile compounds, although characterized by a specific aromatic profile, were mainly affected by the grape used, in interaction with the inoculated <i>Saccharomyces</i> strain. In particular, the AWRI796 strain generally exerted a greater influence on the aromatic component resulting in a higher level of alcohols and esters. This study highlighted that the variable strain could have a different weight, with some musts experiencing a different trend depending on the strain (i.e., Negroamaro or Magliocco musts).
Nutrition. Foods and food supply, Nutritional diseases. Deficiency diseases
In order to study the suspender layout parameters and design parameters of the tied arch bridge with mesh suspenders under the action of vehicle load, the structure stress is more reasonable and meets the higher economy and aesthetics. Taking a 96m span reticulated tied arch bridge as the engineering background, the finite element model is established by using Midas/Civil 2019 program. The variation law of internal force and Suspender Force of the structure is calculated and analysed under the change of rise span ratio and suspender number parameters, and the relatively optimal value range of corresponding parameters is given. The results show that the rise span ratio should be 0.2-0.24; The number of Suspenders for one side arch rib should be 34-38; The relatively optimal range of the above parameters is discussed for reference.