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The classification of bird species is of significant importance in the field of ornithology, as it plays an important role in assessing and monitoring environmental dynamics, including habitat modifications, migratory behaviors, levels of pollution, and disease occurrences. Traditional methods of bird classification, such as visual identification, were time-intensive and required a high level of expertise. However, audio-based bird species classification is a promising approach that can be used to automate bird species identification. This study aims to establish an audio-based bird species classification system for 264 Eastern African bird species employing modified deep transfer learning. In particular, the pre-trained EfficientNet technique was utilized for the investigation. The study adapts the fine-tune model to learn the pertinent patterns from mel spectrogram images specific to this bird species classification task. The fine-tuned EfficientNet model combined with a type of Recurrent Neural Networks (RNNs) namely Gated Recurrent Unit (GRU) and Long short-term memory (LSTM). RNNs are employed to capture the temporal dependencies in audio signals, thereby enhancing bird species classification accuracy. The dataset utilized in this work contains nearly 17,000 bird sound recordings across a diverse range of species. The experiment was conducted with several combinations of EfficientNet and RNNs, and EfficientNet-B7 with GRU surpasses other experimental models with an accuracy of 84.03% and a macro-average precision score of 0.8342. [ABSTRACT FROM AUTHOR]

International migration in border territories converges in multilevel territorial dynamics that are linked to diff erent forms of vulnerability, risks, and violence. These forms of vulnerability, risks, and violence tend to be concentrated in specific segments of the migrant population, particularly women, children, and adolescents. This article presents as a research product a situated analytical description of migratory processes of unaccompanied international children and their state of exposure to vulnerability in migratory transit circuits in Nariño Colombia. The problem was typified in two categories: to characterize the population segment of unaccompanied international migrant children and adolescents in a migratory transit situation (in terms of socio-demographics, migratory movements, and transit routes) and to determine their state of exposure to vulnerability factors. The research had a qualitative-quantitative approach with an exploratory-descriptive scope. The type of sampling applied was non-probabilistic with a multiple case study sample and triangulation analysis method considering the criteria of pertinence and relevance. The analysis was based on the following axes: territories, subjects, and transits versus dimensions and factors of vulnerability. The results showed individual and collective migration processes of unaccompanied international adolescents between 16 and 18 years of age. Exposure factors in the geographic physical dimensions showed a greater proclivity to suffer gender-based violence and other forms of violence that emerge from trans-territorial dynamics in areas influence sensitive to armed conflicts, which converge with their transit circuits. addition, it was found that this segment faces systems of multidimensional violence at the levels of communities, territories, and institutions that reproduce an eff of expulsion, marginalization, and segregation as a result of the geopolitics of territories in Nariño, border migration management, but also of the traditional protection model based on family reunification and humanitarian aid. [ABSTRACT FROM AUTHOR]

Mixed integer nonlinear programming (MINLP) addresses optimization problems that involve continuous and discrete/integer decision variables, as well as nonlinear functions. These problems often exhibit multiple discontinuous feasible parts due to the presence of integer variables. Discontinuous feasible parts can be analyzed as subproblems, some of which may be highly constrained. This significantly impacts the performance of evolutionary algorithms (EAs), whose operators are generally insensitive to constraints, leading to the generation of numerous infeasible solutions. In this article, a variant of the differential evolution algorithm (DE) with a gradient-based repair method for MINLP problems (G-DEmi) is proposed. The aim of the repair method is to fix promising infeasible solutions in different subproblems using the gradient information of the constraint set. Extensive experiments were conducted to evaluate the performance of G-DEmi on a set of MINLP benchmark problems and a real-world case. The results demonstrated that G-DEmi outperformed several state-of-the-art algorithms. Notably, G-DEmi did not require novel improvement strategies in the variation operators to promote diversity; instead, an effective exploration within each subproblem is under consideration. Furthermore, the gradient-based repair method was successfully extended to other DE variants, emphasizing its capacity in a more general context. [ABSTRACT FROM AUTHOR]

In the last two decades, there is an increasingly broad line of studies that warn about the emotional health of journalists and the challenges that it poses for communication professionals to be able to separate work issues from their personal lives. The coverage of COVID-19 exposed many journalists to situations of frustration, discomfort and stress for various reasons: long working hours, not having the appropriate technological material, added to an environment of uncertainty caused by the pandemic. This study aims to examine the possible scope of technostress -in some cases associated to digital divide-in journalists and analyze if they are aware of the uses of care of the self as a way to deal with stressful situations. For this, our research is based on documentary analysis, a survey answered by (50) fifty Argentinean journalists, and twelve (12) in-depth interviews to experienced journalists. Our findings suggest that constant exposure to computers and smartphones during the lockdown together with difficulties to connect to Internet or to have the adequate materials and the lack of coping strategies -as the care of the self-confirms the presence of technostress. Another result that emerges from this research, it should be addressed in future studies, is that some journalists' reactions about care of the self could respond to the third person effect theory to maintain high self-esteem and not demonstrate vulnerability. [ABSTRACT FROM AUTHOR]