Learning to suspend implicated contrast:The acquisition of <em>ook</em> in Dutch

Children acquire the meaning of ook ‘also’ in Dutch relatively late ( Bergsma 2006 ), although this focus particle is highly frequent. We argue that this late acquisition is caused by a pragmatic rule: contrastive implicature. We follow Sæbø (2004) , who argues that additives are used because without them, the sentences they appear in would be interpreted as contrastive in relation to the context. Data from a sentence completion task administered to Dutch L1 learners (N = 62, ages 4;0–5;11) show that, on average, four-year-olds do not distinguish sentences with ook from sentences without ook. Five-year-olds do better on sentences with ook but worse on sentences without it. We argue that they have generally acquired contrastive implicature: they apply the correct contrastive interpretation to sentences without ook, but overgeneralize this implicature to sentences with ook, before completely acquiring the meaning of ook

Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape

COOD: Combined out-of-distribution detection using multiple measures for anomaly & novel class detection in large-scale hierarchical classification

High-performing out-of-distribution (OOD) detection, both anomaly and novel class, is an important prerequisite for the practical use of classification models. In this paper, we focus on the species recognition task in images concerned with large databases, a large number of fine-grained hierarchical classes, severe class imbalance, and varying image quality. We propose a framework for combining individual OOD measures into one combined OOD (COOD) measure using a supervised model. The individual measures are several existing state-of-the-art measures and several novel OOD measures developed with novel class detection and hierarchical class structure in mind. COOD was extensively evaluated on three large-scale (500k+ images) biodiversity datasets in the context of anomaly and novel class detection. We show that COOD outperforms individual, including state-of-the-art, OOD measures by a large margin in terms of TPR@1% FPR in the majority of experiments, e.g., improving detecting ImageNet images (OOD) from 54.3% to 85.4% for the iNaturalist 2018 dataset. SHAP (feature contribution) analysis shows that different individual OOD measures are essential for various tasks, indicating that multiple OOD measures and combinations are needed to generalize. Additionally, we show that explicitly considering ID images that are incorrectly classified for the original (species) recognition task is important for constructing high-performing OOD detection methods and for practical applicability. The framework can easily be extended or adapted to other tasks and media modalities

The Roots of Bioinformatics in Theoretical Biology

From the late 1980s onward, the term “bioinformatics” mostly has been used to refer to computational methods for comparative analysis of genome data. However, the term was originally more widely defined as the study of informatic processes in biotic systems. In this essay, I will trace this early history (from a personal point of view) and I will argue that the original meaning of the term is re-emerging

Cyanotoxin profiling in the subalpine district lakes

Contains fulltext : 193062.pdf (Publisher’s version ) (Open Access

Sympatric speciation and extinction driven by environment dependent sexual selection

A theoretical model is studied to investigate the possibility of sympatric speciation driven by sexual selection and ecological diversi¢cation. In particular, we focus on the rock-dwelling haplochromine cichlid species in Lake Victoria. The high speciation rate in these cichlids has been explained by their apparent ability to specialize rapidly to a large diversity of feeding niches. Seehausen and colleagues, however, demonstrated the importance of sexual selection in maintaining reproductive barriers between species. Our individual-orientated model integrates both niche di¡erentiation and a Fisherian runaway process, which is limited by visibility constraints. The model shows rapid sympatric speciation or extinction of species, depending on the strength of sexual selection

Resource distributions affect social learning on multiple timescales

We study how learning is shaped by foraging opportunities and self-organizing processes and how this impacts on the effects of “copying what neighbors eat” on multiple timescales. We use an individual-based model with a rich environment, where group foragers learn what to eat. We vary foraging opportunities by changing local variation in resources, studying copying in environments with pure patches, varied patches, and uniform distributed resources. We find that copying can help individuals explore the environment by sharing information, but this depends on how foraging opportunities shape the learning process. Copying has the greatest impact in varied patches, where local resource variation makes learning difficult, but local resource abundance makes copying easy. In contrast, copying is redundant or excessive in pure patches where learning is easy, and mostly ineffective in uniform environments where learning is difficult. Our results reveal that the mediation of copying behavior by individual experience is crucial for the impact of copying. Moreover, we find that the dynamics of social learning at short timescales shapes cultural phenomena. In fact, the integration of learning on short and long timescales generates cumulative cultural improvement in diet. Our results therefore provide insight into how and when such processes can arise. These insights need to be taken into account when considering behavioral patterns in nature