Abstract
Building from the authors’ plan to conceptualize an artificial intelligence (AI) solution that allows SME owners to make more sustainable choices in foreign-market-entry decisions, this systematic literature review (SLR) researches the state-of-the-art in SME internationalization from 1920 to 2023 (since 2014 in more depth). The authors gather all articles in Scopus, tagged with the keyword internationalization (25,303 as of January 2023), order them by citations, and download the top 2000 papers’ metadata for analysis and debate, then narrow it to reviews and SMEs, and use bibliometric visualization and qualitative data analysis software (VOSviewer and NVivo) to identify the key players and determinants of export performance/intensity, and finally draw conclusions. The results reveal key internationalization theories, top authors, reviews, and sources and expand Werner´s determinants via several tables and figures. The findings reveal the rise of relevance regarding theories related to social narratives and corporate activism, but also show that there is still much to do in SME internationalization, namely on what makes a small firm well established in their native market and have success in other countries. The contribution to science is an update on the topic and the pinpointing of several trends and gaps, such as a focus on services, theory integration, longitudinal studies between antecedents and performance, strategic fit versus opportunism, network theory on niche marketing, born-“glocal” strategies, disruptive technologies, and discourse variables, for the future of SME export success.

Abstract
Organizational dependency on Information and Communication Technology (ICT) drives the preparedness challenge to cope with business process disruptions. Business Continuity Management (BCM) encompasses effective planning to enable business functions to resume to an acceptable state of operation within a defined timeframe. This paper presents a systematic literature review that communicates the strategic guidelines to streamline the organizational processes in the BCM program, culminating in the Business Continuity Plan design, according to the organization's maturity. The systematic literature review methodology follows the Evidence-Based Software Engineering protocol assisted by the Parsifal tool, using the EbscoHost, ScienceDirect, and Scopus databases, ranging from 2000 to February 2021. International Standards and Frameworks guide the BCM program implementation, however, there is a gap in communicating metrics and what needs to be measured in the BCM program. The major paper result is the confirmation of the identified gap, through the analysis of the studies that, according to the BCM components, report strategic guidelines to streamline the BCM program. The analysis quantifies and discusses the contribution of the studies on each BCM component to design a framework supported by metrics, that allows assessing the organization's preparedness in each BCM component, focusing on Information Systems and ICT strategies.

Abstract
IntroductionPerinatal asphyxia is one of the most frequent causes of neonatal mortality, affecting approximately four million newborns worldwide each year and causing the death of one million individuals. One of the main reasons for these high incidences is the lack of consensual methods of early diagnosis for this pathology. Estimating risk-appropriate health care for mother and baby is essential for increasing the quality of the health care system. Thus, it is necessary to investigate models that improve the prediction of perinatal asphyxia. Access to the cardiotocographic signals (CTGs) in conjunction with various clinical parameters can be crucial for the development of a successful model. ObjectivesThis exploratory work aims to develop predictive models of perinatal asphyxia based on clinical parameters and fetal heart rate (fHR) indices. MethodsSingle gestations data from a retrospective unicentric study from Centro Hospitalar e Universitario do Porto de Sao Joao (CHUSJ) between 2010 and 2018 was probed. The CTGs were acquired and analyzed by Omniview-SisPorto, estimating several fHR features. The clinical variables were obtained from the electronic clinical records stored by ObsCare. Entropy and compression characterized the complexity of the fHR time series. These variables' contribution to the prediction of asphyxia perinatal was probed by binary logistic regression (BLR) and Naive-Bayes (NB) models. ResultsThe data consisted of 517 cases, with 15 pathological cases. The asphyxia prediction models showed promising results, with an area under the receiver operator characteristic curve (AUC) >70%. In NB approaches, the best models combined clinical and SisPorto features. The best model was the univariate BLR with the variable compression ratio scale 2 (CR2) and an AUC of 94.93% [94.55; 95.31%]. ConclusionBoth BLR and Bayesian models have advantages and disadvantages. The model with the best performance predicting perinatal asphyxia was the univariate BLR with the CR2 variable, demonstrating the importance of non-linear indices in perinatal asphyxia detection. Future studies should explore decision support systems to detect sepsis, including clinical and CTGs features (linear and non-linear).

Abstract
Automatic grading based on unit tests is a key feature of massive open online courses (MOOC) on programming, as it allows instant feedback to students and enables courses to scale up. This technique works well for sequential programs, by checking outputs against a sample of inputs, but unfortunately it is not adequate for detecting races and deadlocks, which precludes its use for concurrent programming, a key subject in parallel and distributed computing courses. In this paper we provide a hands-on evaluation of verification and testing tools for concurrent programs, collecting a precise set of requirements, and describing to what extent they can or can not be used for this purpose. Our conclusion is that automatic grading of concurrent programming exercises remains an open challenge.

Abstract

Abstract
We investigate the properties of time-dependent dissipative solitons for a cubic complex Ginzburg-Landau equation stabilized by nonlinear gradient terms. The separation of initially nearby trajectories in the asymptotic limit is predominantly used to distinguish qualitatively between time-periodic behavior and chaotic localized states. These results are further corroborated by Fourier transforms and time series. Quasiperiodic behavior is obtained as well, but typically over a fairly narrow range of parameter values. For illustration, two examples of nonlinear gradient terms are examined: the Raman term and combinations of the Raman term with dispersion of the nonlinear gain. For small quintic perturbations, it turns out that the chaotic localized states are showing a transition to periodic states, stationary states, or collapse already for a small magnitude of the quintic perturbations. This result indicates that the basin of attraction for chaotic localized states is rather shallow.