The different time course of phonotactic constraint learning in children and adults : evidence from speech errors

Speech errors typically respect the speaker’s implicit knowledge of language-wide phonotactics (e.g., /ŋ/ cannot be a syllable onset in the English language). Previous work demonstrated that adults can learn novel experimentally-induced phonotactic constraints by producing syllable strings in which the allowable position of a phoneme depends on another phoneme within the sequence (e.g., /t/ can only be an onset if the medial vowel is /i/), but not earlier than the second day of training. Thus far, no work has been done with children. In the current 4-day experiment, a group of Dutch-speaking adults and nine-year-old children were asked to rapidly recite sequences of novel word-forms (e.g., kieng nief siet hiem) that were consistent with phonotactics of the spoken Dutch language. Within the procedure of the experiment, some consonants (i.e., /t/ and /k/) were restricted to onset or coda position depending on the medial vowel (i.e., /i/ or “ie” versus /øː/ or “eu”). Speech errors in adults revealed a learning effect for the novel constraints on the second day of learning, consistent with earlier findings. A post-hoc analysis at trial-level showed that learning was statistically reliable after an exposure of 120 sequence-trials (including a consolidation period). In contrast, cChildren, however, started learning the constraints already on the first day. More precisely, the effect appeared significantly after an exposure of 24 sequences. These findings indicate that children are rapid implicit learners of novel phonotactics, which bears important implications for theorizing about developmental sensitivities in language learning

Population genomic structure of the gelatinous zooplankton species Mnemiopsis leidyi in its nonindigenous range in the North Sea

Nonindigenous species pose a major threat for coastal and estuarine ecosystems. Risk management requires genetic information to establish appropriate management units and infer introduction and dispersal routes. We investigated one of the most successful marine invaders, the ctenophore Mnemiopsis leidyi, and used genotyping-by-sequencing (GBS) to explore the spatial population structure in its nonindigenous range in the North Sea. We analyzed 140 specimens collected in different environments, including coastal and estuarine areas, and ports along the coast. Single nucleotide polymorphisms (SNPs) were called in approximately 40 k GBS loci. Population structure based on the neutral SNP panel was significant (F-ST .02; p < .01), and a distinct genetic cluster was identified in a port along the Belgian coast (Ostend port; pairwise F-ST .02-.04; p < .01). Remarkably, no population structure was detected between geographically distant regions in the North Sea (the Southern part of the North Sea vs. the Kattegat/Skagerrak region), which indicates substantial gene flow at this geographical scale and recent population expansion of nonindigenous M. leidyi. Additionally, seven specimens collected at one location in the indigenous range (Chesapeake Bay, USA) were highly differentiated from the North Sea populations (pairwise F-ST .36-.39; p < .01). This study demonstrates the utility of GBS to investigate fine-scale population structure of gelatinous zooplankton species and shows high population connectivity among nonindigenous populations of this recently introduced species in the North Sea. OPEN RESEARCH BADGES This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at: The DNA sequences generated for this study are deposited in the NCBI sequence read archive under SRA accession numbers -, and will be made publically available upon publication of this manuscript

The use of procedural fairness in electronic reverse auctions to enhance relationship quality

In this study, the use of procedural fairness by a buying organization in an electronic reverse auction (ERA) is examined. Drawing on the literature, a conceptual model is developed that relates procedural fairness to two key ERA outcomes: relationship quality and quality of the offering. The hypothesized relationships between procedural fairness and quality outcomes are empirically tested through a global field study with 179 procurement professionals in multinational companies, and explored through a supporting field study with 31 sales professionals from supplier firms. The results show that the use of procedural fairness by a buying organization is positively related to relationship quality and quality of the offering, without jeopardizing price savings. In addition, the positive association between procedural fairness and relationship quality is found to increase in the case of a repeat auction. This study contributes to the relationship marketing literature by examining how procedural fairness can mitigate relationship quality concerns in ERA use by buying organizations. (C) 2016 Wiley Periodicals, Inc

Overexpression of GA20-OXIDASE1 impacts plant height, biomass allocation and saccharification efficiency in maize

Increased biomass yield and quality are of great importance for the improvement of feedstock for the biorefinery. For the production of bioethanol, both stem biomass yield and the conversion efficiency of the polysaccharides in the cell wall to fermentable sugars are of relevance. Increasing the endogenous levels of gibberellic acid (GA) by ectopic expression of GA20-OXIDASE1 (GA20-OX1), the rate-limiting step in GA biosynthesis, is known to affect cell division and cell expansion, resulting in larger plants and organs in several plant species. In this study, we examined biomass yield and quality traits of maize plants overexpressing GA20-OX1 (GA20-OX1). GA20-OX1 plants accumulated more vegetative biomass than control plants in greenhouse experiments, but not consistently over two years of field trials. The stems of these plants were longer but also more slender. Investigation of GA20-OX1 biomass quality using biochemical analyses showed the presence of more cellulose, lignin and cell wall residue. Cell wall analysis as well as expression analysis of lignin biosynthetic genes in developing stems revealed that cellulose and lignin were deposited earlier in development. Pretreatment of GA20-OX1 biomass with NaOH resulted in a higher saccharification efficiency per unit of dry weight, in agreement with the higher cellulose content. On the other hand, the cellulose-to-glucose conversion was slower upon HCl or hot-water pretreatment, presumably due to the higher lignin content. This study showed that biomass yield and quality traits can be interconnected, which is important for the development of future breeding strategies to improve lignocellulosic feedstock for bioethanol production

LEAF-E: a tool to analyze grass leaf growth using function fitting

In grasses, leaf growth is often monitored to gain insights in growth processes, biomass accumulation, regrowth after cutting, etc. To study the growth dynamics of the grass leaf, its length is measured at regular time intervals to derive the leaf elongation rate (LER) profile over time. From the LER profile, parameters such as maximal LER and leaf elongation duration (LED), which are essential for detecting inter-genotype growth differences and/or quantifying plant growth responses to changing environmental conditions, can be determined. As growth is influenced by the circadian clock and, especially in grasses, changes in environmental conditions such as temperature and evaporative demand, the LER profiles show considerable experimental variation and thus often do not follow a smooth curve. Hence it is difficult to quantify the duration and timing of growth. For these reasons, the measured data points should be fitted using a suitable mathematical function, such as the beta sigmoid function for leaf elongation. In the context of high-throughput phenotyping, we implemented the fitting of leaf growth measurements into a user-friendly Microsoft Excel-based macro, a tool called LEAF-E. LEAF-E allows to perform non-linear regression modeling of leaf length measurements suitable for robust and automated extraction of leaf growth parameters such as LER and LED from large datasets. LEAF-E is particularly useful to quantify the timing of leaf growth, which forms an important added value for detecting differences in leaf growth development. We illustrate the broad application range of LEAF-E using published and unpublished data sets of maize, Miscanthus spp. and Brachypodium distachyon, generated in independent experiments and for different purposes. In addition, we show that LEAF-E could also be used to fit datasets of other growth-related processes that follow the sigmoidal profile, such as cell length measurements along the leaf axis. Given its user-friendliness, ability to quantify duration and timing of leaf growth and broad application range, LEAF-E is a tool that could be routinely used to study growth processes following the sigmoidal profile