Leiden University

Recently Hahn et al. [1] published the “Joint recommendations of the project group “Biostatistical DNA Calculations” and the Stain Commission on the Biostatistical Evaluation of Forensic DNA Analytical Findings with Fully Continuous Models (FCM).” While the work of the project group and commission to encourage the adoption of FCMs in Germany is to be commended, some of their recommendations are problematic, in our opinion. In this reaction we will point out a number of issues with their analysis of FCM results, and with their recommendations based on that analysis.

Triangle count is a frequently used network statistic, possessing high computational cost. Moreover, this task gets even more complex in the case of signed networks which consist of unbalanced and balanced triangles. In this work, we propose a fast I ncremental T riangle C ounting (ITC) algorithm for counting all types of triangles, including balanced and unbalanced. The proposed algorithm updates the count of different types of triangles for newly added nodes and edges only instead of recalculating the same triangle multiple times for the entire network repeatedly. Thus, the proposed ITC algorithm also works for dynamic networks. The experimental results show that the proposed method is practically efficient having run time complexity of $O(m k_{\text{max}})$ , where $m$ represents the number of edges and $k_{\text{max}}$ represents the maximum degree of the given signed network.

Species’ natural regeneration capacity is an ecological property of plant communities that is key to restoring diversity after disturbances and to conserving the delivery of related ecosystem services within agroecosystems. Reduced diversity of trees and shrubs promoted by conventional and intensive livestock pastureland management can reduce capacity for natural regeneration of woody vegetation, negatively affecting current and future ecological processes. We evaluate the relationships between the cover of woody species with different plant traits and the abundance of naturally regenerated seedlings and saplings within conventional pastureland management. Four main dimensions of plant traits (leaf, stem density, canopy height and reproductive variability spectra) were measured for the 76 woody species most commonly found within conventionally managed pastureland in the Mesoamerican region. All these plant traits were correlated with species’ abundance and natural regeneration capacity. Under current practices, there is a risk of decrease in functional diversity of woody components and their capacity to deliver ecosystem services due to loss of species with a low regeneration capacity. The development of livestock management strategies, like agroforestry and specifically silvopastoral systems that take into account woody plant traits and natural regeneration management, are important to conserve current and future agro-biodiversity and potential delivery of ecosystem services in agricultural landscapes.

Machine learning methods have shown large potential for the automatic early diagnosis of Alzheimer’s Disease (AD). However, some machine learning methods based on imaging data have poor interpretability because it is usually unclear how they make their decisions. Explainable Boosting Machines (EBMs) are interpretable machine learning models based on the statistical framework of generalized additive modeling, but have so far only been used for tabular data. Therefore, we propose a framework that combines the strength of EBM with high-dimensional imaging data using deep learning-based feature extraction. The proposed framework is interpretable because it provides the importance of each feature. We validated the proposed framework on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, achieving accuracy of 0.883 and area-under-the-curve (AUC) of 0.970 on AD and control classification. Furthermore, we validated the proposed framework on an external testing set, achieving accuracy of 0.778 and AUC of 0.887 on AD and subjective cognitive decline (SCD) classification. The proposed framework significantly outperformed an EBM model using volume biomarkers instead of deep learning-based features, as well as an end-to-end convolutional neural network (CNN) with optimized architecture.

Aim Understanding the various factors that contribute to the distribution and geographical ranges of plant and animal species has been a central issue in ecology, evolution and biogeography for more than two centuries. In this study, we investigated whether (i) niche breadth is phylogenetically conserved, (ii) niche overlap is negatively correlated with orchid evolutionary distance, and (iii) more recently diverged sister species show more niche overlap compared to older sister species. Location Europe. Taxon Orchids (Orchidaceae). Methods Ecological niche models were created for 107 European orchid species distributed across 17 genera using occurrence and environmental data. A time‐calibrated phylogeny was reconstructed and the phylogenetic signal for range size and niche breadth was estimated. Phylogenetic distances among species were calculated to test the hypothesis that niche overlap is explained by evolutionary history. Finally, we investigated whether the divergence age of sister taxa was negatively related to niche overlap. Results Range size and niche breadth in both geographical and environmental space varied by more than three orders of magnitude and were strongly correlated with each other. We did not find strong evidence for phylogenetic conservatism in range size, niche breadth and niche overlap. However, sister taxa pairs with older divergence age showed less overlap in their environmental niche compared to more recently diverged sister taxa. Main Conclusions We conclude that orchid species that have broader ecological niches tend to display larger range sizes. Our results further show that the current distribution of orchid species across the European continent is best explained by recent speciation events and relative rapid adaptation to local environmental conditions, while deep‐level phylogenetic relationships are not correlated with ecological niche breadth.

Theories of planet formation predict that low-mass stars should rarely host exoplanets with masses exceeding that of Neptune. We used radial velocity observations to detect a Neptune-mass exoplanet orbiting LHS 3154, a star that is nine times less massive than the Sun. The exoplanet’s orbital period is 3.7 days, and its minimum mass is 13.2 Earth masses. We used simulations to show that the high planet-to-star mass ratio (>3.5 × 10 ⁻³ ) is not an expected outcome of either the core accretion or gravitational instability theories of planet formation. In the core-accretion simulations, we show that close-in Neptune-mass planets are only formed if the dust mass of the protoplanetary disk is an order of magnitude greater than typically observed around very low-mass stars.

Personality traits are essential parts of human behavior analysis and may be applied in scientific domains like job screening. Nowadays, organizations utilize self-assessment methodologies to evaluate people or groups to establish productive teams. Even though study has been done on questionnaires and other self-assessment techniques to profile a candidate or an employee, they are frequently mundane and repetitive. In this study, we present a serious 3D Escape Room game with the goal of analyzing behaviors based on the OCEAN Five Personality Traits model. This model encompasses an individual’s behavior on five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. We created corresponding rooms to monitor the player’s gameplay style to develop customized models that assess personalities. These models use gameplay data generated by deep reinforcement learning agents that emulate human behavior, as a ground truth for each trait. Undergraduate and postgraduate students from Greece and Italy took part in our preliminary study and the game results are correlated with the baseline established by weighted questionnaires. The results show that there is indeed a correlation between the profiles from the questionnaires and the game.

Interest is key to learning. Video is a promising tool for interest development in education, but professionals in education are in need of more theory-grounded guidance for production, selection, and use of videos. In previous studies, we developed and validated a model on film’s interest raising mechanisms in educational contexts, called the FIRM model. In the qualitative study reported here, we used the model to explain how pupils’ appraisals of video characteristics relate to their interest in the video. We evaluated the use of five videos in seven 12th-grade science and mathematics classrooms (177 pupils). We measured interest at scene level and grouped pupils on general interest. We performed video analyses, case studies (N = 5), and a cross-case analysis. Our findings resulted in three relationships between appraisals and interest, regarding the video’s complexity level and the pupils’ knowledge level, pupils’ recognition of video categories, and pupils’ expectations of videos.

Eye Movement Desensitization and Reprocessing (EMDR), while recognized as evidence-based, continues to be viewed as a novel and controversial treatment. At the same time, numerous alternative eye movement therapies have been introduced, each of which requires its own set of randomized controlled trials (RCTs) to assess remarkable claims of cure. The present situation is untenable in our opinion because any clever entrepreneur can claim a new method and trademark a new acronym. Recommendations are made for more stringent criteria to establish science-based methods that guide clinical practice.

The expansion of people speaking Bantu languages is the most dramatic demographic event in Late Holocene Africa and fundamentally reshaped the linguistic, cultural and biological landscape of the continent1–7. With a comprehensive genomic dataset, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we contribute insights into this expansion that started 6,000–4,000 years ago in western Africa. We genotyped 1,763 participants, including 1,526 Bantu speakers from 147 populations across 14 African countries, and generated whole-genome sequences from 12 Late Iron Age individuals⁸. We show that genetic diversity amongst Bantu-speaking populations declines with distance from western Africa, with current-day Zambia and the Democratic Republic of Congo as possible crossroads of interaction. Using spatially explicit methods⁹ and correlating genetic, linguistic and geographical data, we provide cross-disciplinary support for a serial-founder migration model. We further show that Bantu speakers received significant gene flow from local groups in regions they expanded into. Our genetic dataset provides an exhaustive modern-day African comparative dataset for ancient DNA studies¹⁰ and will be important to a wide range of disciplines from science and humanities, as well as to the medical sector studying human genetic variation and health in African and African-descendant populations.

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.

In this study, we investigate how the accumulation of stressful life events and chronic stressors experienced in adolescence predict young adults’ future self-identification (i.e., connectedness, vividness, and valence of the future self) in a sample of 1482 Swiss youth. Furthermore, we investigate future self-identification as a source of resilience mediating the association between accumulated stressful life events on the one hand, and increased delinquency and less educational attainment on the other. In line with our hypothesis, we found that experiencing more stressful life events predicted reduced future self-connectedness. This was not the case for vividness and valence of the future self. Furthermore, we found that future self-connectedness partially mediated the association between stressful life events and low educational attainment. Lastly, latent class trajectories revealed that there was no association between the timing of stressful life events – whether in early or late adolescence – and future self-identification.

Introduction Ignited by the persistent health inequalities many cities and neighbourhoods, the ‘Healthy and Happy The Hague’ network in the Netherlands wanted to gain insight in how prevention and health promotion could become successful in one deprived neighbourhood, Moerwijk. Methods The cycle of Look-Think-Act of Participatory Action Research was used in which both citizens and professionals got involved from the start. Besides interviews, field notes were analysed, visualised and discussed in several rounds of focus groups. Results Thematic analysis yielded seven themes: Healthy Eating and Exercise, Healthy Money, Healthy Mind, Healthy Relationships, Growing up healthy, Healthy Environment and Healthy Collaboration. During sessions around combination of themes, eight initiatives were co-created by citizens and professionals together, improving the feeling of ownership and interconnectedness. Discussion and conclusion This PAR sheds a light on the mismatch between the system world’s solutions for individuals and the living world’s needs for solutions for the collective. Findings provides a better insight into the social, political, and cultural mechanisms and processes that influence clustering and interaction of health conditions. PAR is a promising process of citizens and professionals working together is an excellent way to learn about the conditions under which people experience health inequalities, and how to combat these inequalities.

Progressive constructions in Germanic are usually studied as progressive constructions—that is, exclusively so. I characterize this as a top-down approach to aspect, which, I argue, harbors the risk of overlooking relevant language-specific structures that are similar in form and meaning. This paper, therefore, advocates taking a bottom-up approach. Based on a case study of the prepositional progressive in Dutch ( aan het -progressive), I claim that this approach is of added empirical and theoretical value. Drawing on construction-based theories, the relevant patterns—dubbed situational constructions —are analyzed in terms of horizontal constructional links.*