Prior linguistic knowledge influences implicit language learning

Paper no. 0514Theme: Cooperative Minds: Social Interaction and Group DynamicsWe report three experiments that explore the effect of prior linguistic knowledge on implicit language learning. Native speakers of English and native speakers of Cantonese participated in implicit learning (IL) experiments that involved different learning materials. In Experiment 1, both participant groups showed evidence of learning a mapping between articles and noun animacy. In Experiment 2, neither group showed learning of the mapping between articles and a linguistically anomalous concept (the number of capital letters in an English word or the number of strokes in a Chinese character). In Experiment 3, the Chinese group, but not the English group, showed evidence of learning a mapping between articles and a concept derived from the Chinese classifier system. It was concluded that first language knowledge affected implicit language learning, and that IL, at least when natural language learning is concerned, is not a completely unconstrained domain-general mechanism.postprin

The Implicit Learning of Mappings between Forms and Contextually-Derived Meanings

The traditional implicit learning literature has focused primarily on the abstraction of statistical regularities in form-form connections. More attention has been recently directed toward the implicit learning of form-meaning connections, which might be crucial in the acquisition of natural languages. The current article reports evidence for implicit learning of a mapping between a novel set of determiners and thematic roles, obtained using a newly developed reaction time methodology. The results conclude that contextually derived form-meaning connections might be implicitly learned.published_or_final_versio

Predictive processes during simultaneous interpreting from German into English

We report a study on prediction in shadowing and simultaneous interpreting (SI), both considered as forms of real-time, ‘online’ spoken language processing. The study comprised two experiments, focusing on: (i) shadowing of German head-final sentences by 20 advanced students of German, all native speakers of English; (ii) SI of the same sentences into English head-initial sentences by 22 advanced students of German, again native English speakers, and also by 11 trainee and practising interpreters. Latency times for input and production of the target verbs were measured. Drawing on studies of prediction in English-language reading production, we examined two cues to prediction in both experiments: contextual constraints (semantic cues in the context) and transitional probability (the statistical likelihood of words occurring together in the language concerned). While context affected prediction during both shadowing and SI, transitional probability appeared to favour prediction during shadowing but not during SI. This suggests that the two cues operate on different levels of language processing in SI

Pseudorehearsal in value function approximation

Catastrophic forgetting is of special importance in reinforcement learning, as the data distribution is generally non-stationary over time. We study and compare several pseudorehearsal approaches for Q-learning with function approximation in a pole balancing task. We have found that pseudorehearsal seems to assist learning even in such very simple problems, given proper initialization of the rehearsal parameters

Phase-Diverse Coherent Diffractive Imaging: High Sensitivity with Low Dose

This Letter demonstrates that coherent diffractive imaging (CDI), in combination with phase-diversity methods, provides reliable and artefact free high-resolution images. Here, using x rays, experimental results show a threefold improvement in the available image contrast. Furthermore, in conditions requiring low imaging dose, it is demonstrated that phase-diverse CDI provides a factor of 2 improvement in comparison to previous CDI techniques

Hyporheic Zone Microbiome Assembly Is Linked to Dynamic Water Mixing Patterns in Snowmelt-Dominated Headwater Catchments

Terrestrial and aquatic elemental cycles are tightly linked in upland fluvial networks. Biotic and abiotic mineral weathering, microbially mediated degradation of organic matter, and anthropogenic influences all result in the movement of solutes (e.g., carbon, metals, and nutrients) through these catchments, with implications for downstream water quality. Within the river channel, the region of hyporheic mixing represents a hot spot of microbial activity, exerting significant control over solute cycling. To investigate how snowmelt-driven seasonal changes in river discharge affect microbial community assembly and carbon biogeochemistry, depth-resolved pore water samples were recovered from multiple locations around a representative meander on the East River near Crested Butte, CO, USA. Vertical temperature sensor arrays were also installed in the streambed to enable seepage flux estimates. Snowmelt-driven high river discharge led to an expanding zone of vertical hyporheic mixing and introduced dissolved oxygen into the streambed that stimulated aerobic microbial respiration. These physicochemical processes contributed to microbial communities undergoing homogenizing selection, in contrast to other ecosystems where lower permeability may limit the extent of mixing. Conversely, lower river discharge conditions led to a greater influence of upwelling groundwater within the streambed and a decrease in microbial respiration rates. Associated with these processes, microbial communities throughout the streambed exhibited increasing dissimilarity between each other, suggesting that the earlier onset of snowmelt and longer periods of base flow may lead to changes in the composition (and associated function) of streambed microbiomes, with consequent implications for the processing and export of solutes from upland catchments

On what a distinctively political normativity is

Realists in normative political theory aim to defend the importance of “distinctively political thought” as opposed to the applied ethics they believe characterizes much contemporary political theory and causes it to misunderstand and make mistakes about its subject matter. More conventional political theorists have attempted to respond to realism, including Jonathan Leader Maynard and Alex Worsnip, who have recently criticized five supposedly realist arguments for a distinctive political normativity. However, while Leader Maynard and Worsnip's arguments are themselves less decisive than they suppose, the problem with their response may lay elsewhere. Their response supposes that more conventional political theory could, in principle, be defended at an abstract general level. This may not be possible though, given the difficulty of arriving at agreed interpretations of the concepts involved and the desiderata for a successful normative political theory. It also risks missing the point of realism, which is to use different forms of normative inquiry to explore questions which have not always been central to conventional normative political theory. Judith Shklar's excellent work on vices and the liberalism of fear nicely illustrates this problem

Automating pitted red blood cell counts using deep neural network analysis: a new method for measuring splenic function in sickle cell anaemia

The spleen plays an important role in the body's defence against bacterial infections. Measuring splenic function is of interest in multiple conditions, including sickle cell anaemia (SCA), where spleen injury occurs early in life. Unfortunately, there is no direct and simple way of measuring splenic function, and it is rarely assessed in clinical or research settings. Manual counts of pitted red blood cells (RBCs) observed with differential interference contrast (DIC) microscopy is a well-validated surrogate biomarker of splenic function. The method, however, is both user-dependent and laborious. In this study, we propose a new automated workflow for counting pitted RBCs using deep neural network analysis. Secondly, we assess the durability of fixed RBCs for pitted RBC counts over time. We included samples from 48 children with SCA and 10 healthy controls. Cells were fixed in paraformaldehyde and examined using an oil-immersion objective, and microscopy images were recorded with a DIC setup. Manual pitted RBC counts were performed by examining a minimum of 500 RBCs for pits, expressing the proportion of pitted RBCs as a percentage (%PIT). Automated pitted RBC counts were generated by first segmenting DIC images using a Zeiss Intellesis deep learning model, recognising and segmenting cells and pits from background. Subsequently, segmented images were analysed using a small ImageJ macro language script. Selected samples were stored for 24 months, and manual pitted RBC counts performed at various time points. When comparing manual and automated pitted RBC counts, we found the two methods to yield comparable results. Although variability between the measurements increased with higher %PIT, this did not change the diagnosis of asplenia. Furthermore, we found no significant changes in %PIT after storing samples for up to 24 months and under varying temperatures and light exposures. We have shown that automated pitted RBC counts, produced using deep neural network analysis, are comparable to manual counts, and that fixed samples can be stored for long periods of time without affecting the %PIT. Automating pitted RBC counts makes the method less time consuming and results comparable across laboratories

The virtual haptic back: A simulation for training in palpatory diagnosis

<p>Abstract</p> <p>Background</p> <p>Models and simulations are finding increased roles in medical education. The Virtual Haptic Back (VHB) is a virtual reality simulation of the mechanical properties of the human back designed as an aid to teaching clinical palpatory diagnosis.</p> <p>Methods</p> <p>Eighty-nine first year medical students of the Ohio University College of Osteopathic Medicine carried out six, 15-minute practice sessions with the VHB, plus tests before and after the sessions in order to monitor progress in identifying regions of simulated abnormal tissue compliance. Students palpated with two digits, fingers or thumbs, by placing them in gimbaled thimbles at the ends of PHANToM 3.0^®haptic interface arms. The interface simulated the contours and compliance of the back surface by the action of electric motors. The motors limited the compression of the virtual tissues induced by the palpating fingers, by generating counterforces. Users could see the position of their fingers with respect to the back on a video monitor just behind the plane of the haptic back. The abnormal region varied randomly among 12 locations between trials. During the practice sessions student users received immediate feedback following each trial, indicating either a correct choice or the actual location of the abnormality if an incorrect choice had been made. This allowed the user to feel the actual abnormality before going on to the next trial. Changes in accuracy, speed and Weber fraction across practice sessions were analyzed using a repeated measures analysis of variance.</p> <p>Results</p> <p>Students improved in accuracy and speed of diagnosis with practice. The smallest difference in simulated tissue compliance users were able to detect improved from 28% (SD = 9.5%) to 14% (SD = 4.4%) during the practice sessions while average detection time decreased from 39 (SD = 19.8) to 17 (SD = 11.7) seconds. When asked in anonymous evaluation questionnaires if they judged the VHB practice to be helpful to them in the clinical palpation and manual medicine laboratory, 41% said yes, 51% said maybe, and 8% said no.</p> <p>Conclusion</p> <p>The VHB has potential value as a teaching aid for students in the initial phases of learning palpatory diagnosis.</p