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Internationalisation has gained prominence in debates on higher education and can be analysed from different perspectives, including cross-border higher education. Cross-border higher education entails relevant challenges, namely regarding its quality. This paper intends to discuss, based on a literature review, the link between cross-border higher education and quality assurance, namely the role quality assurance may have in contributing to a quality cross-border educational offer. 79 documents (indexed in Scopus or Web of Science) published between 1998 and 2019 were content analysed. The results show that both internal and external quality assurance are relevant topics when discussing cross-border higher education and a means to stimulate the overall quality of this educational offer. Moreover, to be effective, quality assurance must rely on cooperation and mutual trust between importing and exporting countries, including their quality assurance agencies. [ABSTRACT FROM AUTHOR]

Drawn from the SQELT Erasmus+ project, this article explores how learning analytics is implemented at a set of six European universities in the context of their performance data management models, including its multiple functions and ethical issues. It further identifies possible good practice and policy recommendations at decision-making level. Results show that learning analytics is present to a certain extent in all six institutions, although mostly based on traditional data and still lacking predictive capacity concerning students' performance. Learning analytics is viewed as useful in providing more accurate personal data on students' learning, contributing to the establishment of more sophisticated quality management systems. The European General Data Protection Regulation and national privacy laws sufficiently cover the majority of data ethics risks posed by learning analytics. Overall, learning analytics entails both opportunities and threats. The possibilities of a learning analytics approach deserve further attention within universities and quality assurance agencies. [ABSTRACT FROM AUTHOR]

This paper analyses teaching and non-teaching staff perceptions on the implementation of internal quality assurance (QA) practices at their higher education institutions. The aim is to understand how far different perspectives on quality - as culture, as compliance or as consistency - are reflected in the views of these two groups on such practices. Data from a survey sent to all Portuguese institutions show that, to some extent, the perspectives of quality as culture and quality as compliance seem to permeate both groups' views. This is evident in regard to the factors identified as supporting the development of internal QA, the main features underlying the implementation of such practices and their main effects. As the study allows for a better understanding on how these practices are perceived by teaching and non-teaching staff, it can contribute to promoting the critical reflection of institutions about QA and the way it can be both more effective and aligned with academia's needs and expectations, contributing to influencing institutional practices. [ABSTRACT FROM AUTHOR]

Academics’ support for quality assurance (QA) depends on several factors, including their sense of ownership, which seems to be influenced by academics’ participation in QA’s implementation. This paper aims to understand whether this participation is indeed contributing to academics’ ownership of QA. Findings from a survey of Portuguese academics’ on their participation in study programmes accreditation suggests that this may not be the case. Academics present a partial withdrawal towards effective participation in study programmes’ accreditation, especially regarding external assessment. Furthermore, they do not seem willing to enhance this participation nor are they very critical about it. Since academics’ sense of ownership is essential for the successful implementation of QA, these results may represent a challenge for both institutions and QA agencies. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to look at the characteristics of internal quality assurance (IQA) systems of higher education institutions to understand whether these systems tend to reproduce a given model, externally defined and suggested to institutions, or rather to be shaped by institutions’ features and interests.Design/methodology/approach The study is supported in the analysis of the content of self-assessment reports of 12 internal QA systems certified, in Portugal, between 2012 and 2015. An analysis grid was used based on three categories: IQA systems’ historical framework, structural/managerial component and monitoring, assessment and continuous improvement.Findings Institutions tended to follow a “one size fits all” approach, meaning that external (European and national) quality assurance (QA) references were used in an identical way, giving origin to rather similar IQA systems. Institutional characteristics do not seem to have played a relevant role, eventually due to institutions’ will to obtain their systems’ certification and, thus, achieve a light-touch external QA.Research limitations/implications The study was based on the analysis of only certified IQA systems and relies on document analysis. It would be interesting to also include non-certified systems, in a comparative perspective, complemented with data deriving from interviews and/or questionnaires with some of the actors involved in the certification process.Practical implications The study provides an understanding of how IQA systems are being implemented in Portugal. Thus, it can be of interest to other institutions as well as to QA agencies.Originality/value The study addresses a topic still relatively absent from research on QA in higher education, being of interest for researchers in the field. [ABSTRACT FROM AUTHOR]

Quality assurance is currently an established activity in Europe, driven either by national quality assurance agencies or by institutions themselves. However, whether quality assurance is perceived as actually being capable of promoting quality is still a question open to discussion. Based on three different views on quality derived from the literature – quality as culture, as compliance and as consistency – the current article sheds light on this issue by identifying the main obstacles to quality as perceived by Portuguese academics. The analysis reveals that academics tend to see those obstacles as essentially related to the view of quality as culture and especially with its structural component, including the design and functioning of institutional governance and management. Although this may indeed correspond to the Portuguese higher education institutions’ reality, one must not forget that academics tend to have a poor knowledge about the structural frames that are embedded in governance and management. By highlighting obstacles related to different views on quality, this study may serve as a base to the development of more effective quality assurance mechanisms. [ABSTRACT FROM PUBLISHER]

This research seeks to explore academics’ perceptions of the importance and degree of implementation of the Standards and Guidelines for Quality Assurance in the European Higher Education Area (ESG) for internal quality assurance. It uses empirical evidence from Portugal, gathered via a questionnaire given to all university academics. Results show academics’ perceptions of the importance and implementation of the ESG in their institutions to be quite positive. Nevertheless, academics tend to find the standards more important than effectively implemented. Furthermore, significant differences in perceptions emerge between groups of academics. This study intends to contribute to a better understanding of the implementation of quality management practices in universities, and the influence of the ESG in this process. [ABSTRACT FROM AUTHOR]

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to discuss student satisfaction with Portuguese higher education institutions, and to analyse how this varies for different types of students. A survey instrument was used to collect data on students’ perceptions and expectations regarding different aspects of service provision. Based on the gap model of satisfaction, satisfaction indices were calculated for all items considered and were checked for their statistical significance. Although, generically speaking, students’ perceptions and expectations are high, the satisfaction indices are all negative and statistically different from zero. Furthermore, significant differences of satisfaction regarding some aspects of service provision were found between different groups of students. This study may contribute to institutions improving the quality of services they provide. Furthermore, this study will contribute to improving the quality of higher education institutions through correcting mistakes and designing better processes, provided that the information collected through student satisfaction surveys has been treated adequately. [ABSTRACT FROM PUBLISHER]

The accountability versus improvement debate is an old one. Although being traditionally considered dichotomous purposes of higher education quality assessment, some authors defend the need of balancing both in quality assessment systems. This article goes a step further and contends that not only they should be balanced but also that other purposes can be devised for assessing quality in higher education. Five different purposes are proposed: communication, motivation, control, improvement and innovation, derived both from the higher education and the organisational performance literatures. Then the answers given to a set of questions related to these five intended purposes are analysed. The answers were collected through a questionnaire designed to investigate Portuguese academics’ perceptions on higher education quality assessment. Overall the analysis performed reveals a certain degree of support for all the purposes, albeit higher in the case of the improvement and communication purposes and lower for control and motivation. Since an adequate implementation of quality assessment systems needs the support of academics, this article can inform the design of systems integrating academics’ views on the subject. [ABSTRACT FROM PUBLISHER]

Functional magnetic resonance imaging (fMRI), with blood oxygenation level-dependent (BOLD) contrast, is a widely used technique for studying the human brain. However, it is an indirect measure of underlying neuronal activity and the processes that link this activity to BOLD signals are still a topic of much debate. In order to relate findings from fMRI research to other measures of neuronal activity it is vital to understand the underlying neurovascular coupling mechanism. Currently, there is no consensus on the relative roles of synaptic and spiking activity in the generation of the BOLD response. Here we designed a modelling framework to investigate different neurovascular coupling mechanisms. We use Electroencephalographic (EEG) and fMRI data from a visual stimulation task together with biophysically informed mathematical models describing how neuronal activity generates the BOLD signals. These models allow us to non-invasively infer the degree of local synaptic and spiking activity in the healthy human brain. In addition, we use Bayesian model comparison to decide between neurovascular coupling mechanisms. We show that the BOLD signal is dependent upon both the synaptic and spiking activity but that the relative contributions of these two inputs are dependent upon the underlying neuronal firing rate. When the underlying neuronal firing is low then the BOLD response is best explained by synaptic activity. However, when the neuronal firing rate is high then both synaptic and spiking activity are required to explain the BOLD signal. [ABSTRACT FROM AUTHOR]

Background: In the past years, there has been a growing concern in designing physical activity (PA) programmes for elderly people, because evidence suggests that such health promotion interventions may reduce the deleterious effects of the ageing process. Quality is an important issue when designing a PA programme for older people. Some studies support the Excellence Model of the European Foundation for Quality Management (EFQM) as an operational framework for evaluating the quality of an organization. Within this context, the aim of this study was to characterize the quality management models of the PA programmes developed by Portuguese Local Administration to enhance quality of life for elderly people, according to the criteria of the EFQM Excellence Model. Methods: A methodological triangulation was conducted in 26 PA programmes using questionnaire surveys, semistructured interviews and document analysis. We used standard approaches to the statistical analysis of data including frequencies and percentages for the categorical data. Results: Results showed that Processes (65,38%), Leadership (61,03%), Customer results (58,46) and People (51,28%) had high percentage occurrences of quality practices. In contrast, Partnerships and resources (45,77%), People results (41,03%), Policy and strategy (37,91%), Key performance results (19,23%) and Society results (19,23%) had lower percentage occurrences. Conclusions: Our findings suggest that although there are some good practices in PA programmes, there are still relevant areas that require improvement. [ABSTRACT FROM AUTHOR]

Tetracyclines have been extensively used as adjunctives to conventional periodontal therapy. Emergence of resistant strains, however, has been reported. This study evaluated longitudinally the tetracycline resistance patterns of the subgingival microbiota of periodontitis subjects treated with systemic or local tetracycline therapy+scaling and root planing (SRP). Thirty chronic periodontitis patients were randomly assigned to three groups: SRP+500 mg of systemic tetracycline twice/day for 14 days; SRP alone and SRP+tetracycline fibers (Actsite®) at four selected sites for 10 days. Subgingival plaque samples were obtained from four sites with probing pocket depths (PPD)⩾6 mm in each patient at baseline, 1 week, 3, 6 and 12 months post-therapy. Samples were dispersed and diluted in pre-reduced anaerobically sterilized Ringer's solution, plated on Trypticase Soy Agar (TSA)+5% blood with or without 4 μg/ml of tetracycline and incubated anaerobically for 10 days. The percentage of resistant microorganisms were determined and the isolates identified by DNA probes and the checkerboard method. Significance of differences among and within groups over time was sought using the Kruskal–Wallis and Friedman tests, respectively. The percentage of resistant microorganisms increased significantly at 1 week in the tetracycline groups, but dropped to baseline levels over time. The SRP+Actsite® group presented the lowest proportions of resistant species at 6 and 12 months. No significant changes were observed in the SRP group. The predominant tetracycline-resistant species included Streptococcus spp., Veillonela parvula, Peptostreptococcus micros, Prevotella intermedia, Gemella morbillorum and Actinobacillus actinomycetemcomitans (Aa). A high percentage of sites with resistant Aa, Porphyromonas gingivalis and Tanerella forsythensis was observed in all groups at baseline. However, T. forsythensis was not detected in any group and P. gingivalis was not present in the SRP+Actsite® group at 1 year post-therapy. Aa was still frequently detected in all groups after therapy. However, the greatest reduction was observed in the SRP+Actsite® group. Local or systemically administered tetracycline results in transitory selection of subgingival species intrinsically resistant to this drug. Although the percentage of sites harboring periodontal pathogens resistant to tetracycline were quite elevated in this population, both therapies were effective in reducing their prevalence over time. [ABSTRACT FROM AUTHOR]

Doctoral education has grown substantially, resulting in a larger and diverse pool of graduates for research. Simultaneously, gender balance in research has become a growing concern, particularly in Europe. Based on the Portuguese case, this paper discusses whether the increase in the pool of graduate talent, considered to be comprised of doctoral graduates, has resulted in a gender balance across different disciplines. The analysis of the evolution of doctoral theses completed by men and women from 1970 to 2016 suggests that, while gender balance has been achieved in terms of participation in doctoral education, horizontal segregation in disciplines persists. A more gender-balanced pool of graduate talent for research across disciplines seems to require more action from Portuguese policymakers and universities, particularly in terms of the implementation of gender equality measures. This is also true for countries where gender equality in doctoral education is a challenge. [ABSTRACT FROM AUTHOR]

Abstract Background The programming of sleep architecture begins in pregnancy and depends upon optimal in utero formation and maturation of the neural connectivity of the brain. Particulate air pollution exposure can disrupt fetal brain development but associations between fine particulate matter (PM 2.5) exposure during pregnancy and child sleep outcomes have not been previously explored. Methods Analyses included 397 mother-child pairs enrolled in a pregnancy cohort in Mexico City. Daily ambient prenatal PM 2.5 exposure was estimated using a validated satellite-based spatio-temporally resolved prediction model. Child sleep periods were estimated objectively using wrist-worn, continuous actigraphy over a 1-week period at age 4–5 years. Data-driven advanced statistical methods (distributed lag models (DLMs)) were employed to identify sensitive windows whereby PM 2.5 exposure during gestation was significantly associated with changes in sleep duration or efficiency. Models were adjusted for maternal education, season, child's age, sex, and BMI z-score. Results Mother's average age was 27.7 years, with 59% having at least a high school education. Children slept an average of 7.7 h at night, with mean 80.1% efficiency. The adjusted DLM identified windows of PM 2.5 exposure between 31 and 35 weeks gestation that were significantly associated with decreased sleep duration in children. In addition, increased PM 2.5 during weeks 1–8 was associated with decreased sleep efficiency. In other exposure windows (weeks 39–40), PM 2.5 was associated with increased sleep duration. Conclusion Prenatal PM 2.5 exposure is associated with altered sleep in preschool-aged children in Mexico City. Pollutant exposure during sensitive windows of pregnancy may have critical influence upon sleep programming. Highlights • Prenatal PM 2.5 exposure was associated with sleep disruption in preschoolers. • Higher PM 2.5 was linked to decreased sleep efficiency and altered sleep duration. • Significant associations were identified during sensitive windows of gestation. [ABSTRACT FROM AUTHOR]

The paper enquires into the institutional impact of European policies, as embodied by the Standards and Guidelines for Quality Assurance in the European Higher Education Area (ESG). Theoretically, the work departs from the ‘worlds of compliance’ framework in relation to EU law implementation to study EU initiatives under the Open Method of Coordination. Empirically, it presents how ESG are taken up by higher education institutions in Portugal and the Czech Republic. The study finds a substantial misfit between the modes of governance traditionally ascribed to Portugal and the Czech Republic and the identified patterns of ESG translations in those countries. [ABSTRACT FROM AUTHOR]

The emergence and development of quality assurance schemes in European countries over the last 15-20 years has inspired many national case studies of the systems and procedures adopted. The methods, contexts, and procedures associated with this policy change are diverse. But although individual countries have set about changing policy in different ways there appear to be some common developmental patterns within the Europe of the Bologna Process. How can these developments be conceptualised? In a first step this paper advances a typology based on the quality assurance literature. In a second step, the paper applies the typology to quality assurance developments in three countries. The third part of the paper discusses the strengths and weaknesses of the modelling approach in the light of the empirical evidence and a political science analysis of policy change. The paper concludes with a discussion on future directions for the comparative study of policy change within the European Higher Education Area on the basis of this conceptualisation of developments in quality assurance policy. [ABSTRACT FROM AUTHOR]

In the following pages, we share a collection of photos, drawings, and mixed-media creations, most of them especially made for this JoN issue, manifesting C. elegans researchers' affection for their model organism and the founders of the field. This is a celebration of our community's growth, flourish, spread, and bright future. Descriptions provided by the contributors, edited for space.1 [ABSTRACT FROM AUTHOR]

Positive‐social emotions mediate one's cognitive performance, mood, well‐being, and social bonds, and represent a critical variable within therapeutic settings. It has been shown that the upregulation of positive emotions in social situations is associated with increased top‐down signals that stem from the prefrontal cortices (PFC) which modulate bottom‐up emotional responses in the amygdala. However, it remains unclear if positive‐social emotion upregulation of the amygdala occurs directly through the dorsomedial PFC (dmPFC) or indirectly linking the bilateral amygdala with the dmPFC via the subgenual anterior cingulate cortex (sgACC), an area which typically serves as a gatekeeper between cognitive and emotion networks. We performed functional MRI (fMRI) experiments with and without effortful positive‐social emotion upregulation to demonstrate the functional architecture of a network involving the amygdala, the dmPFC, and the sgACC. We found that effortful positive‐social emotion upregulation was associated with an increase in top‐down connectivity from the dmPFC on the amygdala via both direct and indirect connections with the sgACC. Conversely, we found that emotion processes without effortful regulation increased network modulation by the sgACC and amygdala. We also found that more anxious individuals with a greater tendency to suppress emotions and intrusive thoughts, were likely to display decreased amygdala, dmPFC, and sgACC activity and stronger connectivity strength from the sgACC onto the left amygdala during effortful emotion upregulation. Analyzed brain network suggests a more general role of the sgACC in cognitive control and sheds light on neurobiological informed treatment interventions. [ABSTRACT FROM AUTHOR]

In 2009, the National Institute of Mental Health launched the Research Domain Criteria, an attempt to move beyond diagnostic categories and ground psychiatry within neurobiological constructs that combine different levels of measures (e.g., brain imaging and behavior). Statistical methods that can integrate such multimodal data, however, are often vulnerable to overfitting, poor generalization, and difficulties in interpreting the results. We propose an innovative machine learning framework combining multiple holdouts and a stability criterion with regularized multivariate techniques, such as sparse partial least squares and kernel canonical correlation analysis, for identifying hidden dimensions of cross-modality relationships. To illustrate the approach, we investigated structural brain–behavior associations in an extensively phenotyped developmental sample of 345 participants (312 healthy and 33 with clinical depression). The brain data consisted of whole-brain voxel-based gray matter volumes, and the behavioral data included item-level self-report questionnaires and IQ and demographic measures. Both sparse partial least squares and kernel canonical correlation analysis captured two hidden dimensions of brain–behavior relationships: one related to age and drinking and the other one related to depression. The applied machine learning framework indicates that these results are stable and generalize well to new data. Indeed, the identified brain–behavior associations are in agreement with previous findings in the literature concerning age, alcohol use, and depression-related changes in brain volume. Multivariate techniques (such as sparse partial least squares and kernel canonical correlation analysis) embedded in our novel framework are promising tools to link behavior and/or symptoms to neurobiology and thus have great potential to contribute to a biologically grounded definition of psychiatric disorders. [ABSTRACT FROM AUTHOR]

Understanding how variations in dimensions of psychometrics, IQ and demographics relate to changes in brain connectivity during the critical developmental period of adolescence and early adulthood is a major challenge. This has particular relevance for mental health disorders where a failure to understand these links might hinder the development of better diagnostic approaches and therapeutics. Here, we investigated this question in 306 adolescents and young adults (14–24 y, 25 clinically depressed) using a multivariate statistical framework, based on canonical correlation analysis (CCA). By linking individual functional brain connectivity profiles to self-report questionnaires, IQ and demographic data we identified two distinct modes of covariation. The first mode mapped onto an externalization/internalization axis and showed a strong association with sex. The second mode mapped onto a well-being/distress axis independent of sex. Interestingly, both modes showed an association with age. Crucially, the changes in functional brain connectivity associated with changes in these phenotypes showed marked developmental effects. The findings point to a role for the default mode, frontoparietal and limbic networks in psychopathology and depression. [ABSTRACT FROM AUTHOR]

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This ''best model'' approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data. [ABSTRACT FROM AUTHOR]