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Abstract
Enhancing the reproducibility and comprehension of adaptive immune receptor repertoire sequencing (AIRR-seq) data analysis is critical for scientific progress. This study presents guidelines for reproducible AIRR-seq data analysis, and a collection of ready-to-use pipelines with comprehensive documentation. To this end, ten common pipelines were implemented using ViaFoundry, a user-friendly interface for pipeline management and automation. This is accompanied by versioned containers, documentation and archiving capabilities. The automation of pre-processing analysis steps and the ability to modify pipeline parameters according to specific research needs are emphasized. AIRR-seq data analysis is highly sensitive to varying parameters and setups; using the guidelines presented here, the ability to reproduce previously published results is demonstrated. This work promotes transparency, reproducibility, and collaboration in AIRR-seq data analysis, serving as a model for handling and documenting bioinformatics pipelines in other research domains.

Abstract
Small enterprises (SEs) represent the majority of the businesses worldwide, playing a leading role in job creation and economic development. The success of these firms substantially depends on the financial knowledge of their owners/managers. Previous literature in the field of household finances has indicated that financial literacy declines as individual ages. However, the scarce literature on entrepreneurs' financial literacy has not addressed this issue. Using a sample of 896 SE owners/managers, drawn from the survey of small enterprises' financial literacy in Spain, the authors observe a decline in objective financial knowledge with age through multivariate analyses using probit and ordered probit models. The lack of financial knowledge may put at risk the economic feasibility of an SE. Therefore, it is essential to design financial education mechanisms that are sensitive to the needs of SE owners/managers at different stages of their working lives. © 2024 by IGI Global. All rights reserved.

Abstract
This article presents a solution for a work related to the curricular unit Energy Markets and Regulation within the scope of PDEEC-Doctoral Program in Electrical and Computer Engineering. The task consists of evaluating optimal dispatch and market pool results (symmetric and asymmetric) for different periods. To check the technical feasibility of implementing the dispatch recommended by the pool market, a DC power flow is analyzed, by accounting for a network with six busbars. Results show that in some periods of higher demand, there could be an overload in some transmission lines of the considered network for certain results of market dispatch. © 2024, Universidade do Porto - Faculdade de Engenharia. All rights reserved.

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Abstract
The Eurasian grapevine (Vitis vinifera L.) is one of the most extensively cultivated horticultural crop worldwide, with significant economic relevance, particularly in wine production. Accurate grapevine variety identification is essential for ensuring product authenticity, quality control, and regulatory compliance. Traditional identification methods have inherent limitations limitations; ampelography is subjective and dependent on skilled experts, while molecular analysis is costly and time-consuming. To address these challenges, recent research has focused on applying deep learning (DL) and machine learning (ML) techniques for grapevine variety identification. This study systematically analyses 37 recent studies that employed DL and ML models for this purpose. The objective is to provide a detailed analysis of classification pipelines, highlighting the strengths and limitations of each approach. Most studies use DL models trained on leaf images captured in controlled environments at distances of up to 1.2 m. However, these studies often fail to address practical challenges, such as the inclusion of a broader range of grapevine varieties, using data directly acquired in the vineyards, and the evaluation of models under adverse conditions. This review also suggests potential directions for advancing research in this field.