From specific examples to general knowledge in language learning

AbstractThe extraction of general knowledge from individual episodes is critical if we are to learn new knowledge or abilities. Here we uncover some of the key cognitive mechanisms that characterise this process in the domain of language learning. In five experiments adult participants learned new morphological units embedded in fictitious words created by attaching new affixes (e.g., -afe) to familiar word stems (e.g., “sleepafe is a participant in a study about the effects of sleep”). Participants’ ability to generalise semantic knowledge about the affixes was tested using tasks requiring the comprehension and production of novel words containing a trained affix (e.g., sailafe). We manipulated the delay between training and test (Experiment 1), the number of unique exemplars provided for each affix during training (Experiment 2), and the consistency of the form-to-meaning mapping of the affixes (Experiments 3–5). In a task where speeded online language processing is required (semantic priming), generalisation was achieved only after a memory consolidation opportunity following training, and only if the training included a sufficient number of unique exemplars. Semantic inconsistency disrupted speeded generalisation unless consolidation was allowed to operate on one of the two affix-meanings before introducing inconsistencies. In contrast, in tasks that required slow, deliberate reasoning, generalisation could be achieved largely irrespective of the above constraints. These findings point to two different mechanisms of generalisation that have different cognitive demands and rely on different types of memory representations

Simulation and data processing of GOMOS measurements

In this paper the data simulation and data inversion studies for stellar occultation measurements are discussed. The specific application is the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument which has been proposed for the first European Platform, Polar Orbiting Earth Mission (POEM-1)

Archaea are prominent members of the prokaryotic communities colonizing common forest mushrooms

In this study, the abundance and composition of prokaryotic communities associated with the inner tissue of fruiting bodies of Suillus bovinus, Boletus pinophilus, Cantharellus cibarius, Agaricus arvensis, Lycoperdon perlatum, and Piptoporus betulinus were analyzed using culture-independent methods. Our findings indicate that archaea and bacteria colonize the internal tissues of all investigated specimens and that archaea are prominent members of the prokaryotic community. The ratio of archaeal 16S rRNA gene copy numbers to those of bacteria was >1 in the fruiting bodies of four out of six fungal species included in the study. The largest proportion of archaeal 16S rRNA gene sequences belonged to thaumarchaeotal classes Terrestrial group, Miscellaneous Crenar-chaeotic Group (MCG), and Thermoplasmata. Bacterial communities showed characteristic compositions in each fungal species. Bacterial classes Gammaproteobacteria, Actinobacteria, Bacilli, and Clostridia were prominent among communities in fruiting body tissues. Bacterial populations in each fungal species had different characteristics. The results of this study imply that fruiting body tissues are an important habitat for abundant and diverse populations of archaea and bacteria.Peer reviewe

Subjective mental well-being among higher education students in Finland during the first wave of COVID-19

Aims: Increased mental health problems during the COVID-19 pandemic have become a major concern among young adults. Our aim was to understand which COVID-19-related questions predicted mental well-being during the outbreak. Methods: Two cross-sectional datasets were used. The primary dataset was collected in May 2020 (n = 1001), during the initial COVID-19 outbreak, and the secondary in April 2019 (n = 10866), before the pandemic. Mental well-being was assessed with the Short Warwick-Edinburgh Mental Well-Being Scale. Relationships between mental well-being and COVID-19-related questions were investigated with lasso regression. As an exploratory analysis, two-way ANOVAs were used to compare mental well-being before and during the outbreak. Results: Higher levels of mental well-being were associated with lower levels of academic stress and COVID-19-related worry, along with a higher satisfaction with the procedures and information provided by the higher education institutions and the government. COVID-19-related symptoms and infections did not have an impact on students' mental well-being during the outbreak. Small to moderate effect sizes across the time points were detected, indicating an overall decrease in mental well-being across age and gender during the outbreak. Conclusions: COVID-19 had an impact on higher education students' mental well-being. Higher education institutes may play a crucial role in protecting their students' well-being during uncertain times.Peer reviewe

The impact of music on learning and consolidation of novel words

Music can be a powerful mnemonic device, as shown by a body of literature demonstrating that listening to text sung to a familiar melody results in better memory for the words compared to conditions where they are spoken. Furthermore, patients with a range of memory impairments appear to be able to form new declarative memories when they are encoded in the form of lyrics in a song, while unable to remember similar materials after hearing them in the spoken modality. Whether music facilitates the acquisition of completely new information, such as new vocabulary, remains unknown. Here we report three experiments in which adult participants learned novel words in the spoken or sung modality. While we found no benefit of musical presentation on free recall or recognition memory of novel words, novel words learned in the sung modality were more strongly integrated in the mental lexicon compared to words learned in the spoken modality. This advantage for the sung words was only present when the training melody was familiar. The impact of musical presentation on learning therefore appears to extend beyond episodic memory and can be reflected in the emergence and properties of new lexical representations

Short communication : Lameness impairs feeding behavior of dairy cows

Peer reviewe

Estimation of ECHAM5 climate model closure parameters with adaptive MCMC

Climate models contain closure parameters to which the model climate is sensitive. These parameters appear in physical parameterization schemes where some unresolved variables are expressed by predefined parameters rather than being explicitly modeled. Currently, best expert knowledge is used to define the optimal closure parameter values, based on observations, process studies, large eddy simulations, etc. Here, parameter estimation, based on the adaptive Markov chain Monte Carlo (MCMC) method, is applied for estimation of joint posterior probability density of a small number (<i>n</i>=4) of closure parameters appearing in the ECHAM5 climate model. The parameters considered are related to clouds and precipitation and they are sampled by an adaptive random walk process of the MCMC. The parameter probability densities are estimated simultaneously for all parameters, subject to an objective function. Five alternative formulations of the objective function are tested, all related to the net radiative flux at the top of the atmosphere. Conclusions of the closure parameter estimation tests with a low-resolution ECHAM5 climate model indicate that (i) adaptive MCMC is a viable option for parameter estimation in large-scale computational models, and (ii) choice of the objective function is crucial for the identifiability of the parameter distributions

Residual Energy Dispersal Fracturing: A newly proposed term for fractures propagating from sharp-force trauma

Objectives: The identification and interpretation of skeletal trauma is an important topic in osteoarchaeology, forensic anthropology and palaeosciences. Trauma analysis is a fast-moving sub-discipline with constantly evolving methodological approaches. This paper describes the process of a particular form of fracturing that propagates specifically from the floor of cut marks and proposes new terminology for this subset of fractures. Materials and Methods: This terminological gap was identified during the reexamination of remains from a minimum of 52 decapitated individuals (52 postcranial and 47 cranial remains) found in a mass grave from the 10th–11th century CE on Ridgeway Hill near Weymouth in Dorset (UK) in 2009. Originally analyzed by Oxford Archaeology Ltd., all individuals in this collection were re-appraised using digital technology to test new techniques for this study. Results: During this investigation, it has become apparent that the length of chop marks can be overestimated during some conventional analysis because the chop transitions into a fracture propagating from the floor of the chop mark. Discussion: To increase awareness of these fractures, the term residual energy dispersal (RED) fractures is proposed as these are distinct from other radiating fractures arising from sharp-blunt-force trauma. The ability to distinguish RED fractures from others has the potential to contribute to the identification of previously unidentified chop marks and to the interpretation of events surrounding an injury

Digital multiplex ligation assay for highly multiplexed screening of beta-lactamase-encoding genes in bacterial isolates

Increasing incidence of antibiotic resistance in clinical and environmental settings calls for increased scalability in their surveillance. Current screening technologies are limited by the number of samples and genes that can easily be screened. We demonstrate here digital multiplex ligation assay (dMLA) as a low-cost targeted genomic detection workflow capable of highly-parallel screening of bacterial isolates for multiple target gene regions simultaneously. Here, dMLA is used for simultaneous detection of 1187 beta-lactamase-encoding genes, including extended spectrum beta-lactamase (ESBL) genes, in 74 bacterial isolates. We demonstrate dMLA as a light-weight and cost-efficient workflow which provides a highly scalable tool for antimicrobial resistance surveillance and is also adaptable to genetic screening applications beyond antibiotic resistance.Tamminen et al. develop a digital multiplex ligation assay (dMLA) that enables the detection of bacterial isolates using probe hybridization and ligation-based assays with next-generation sequencing. Their method can be applied in high-throughput and affordable screening for antibiotic resistance