Experimental investigation of the freely cooling granular gas

Using diamagnetically levitated particles we investigate the dynamics of the freely cooling granular gas. At early times we find good agreement with Haff's law, where the time scale for particle collisions can be determined from independent measurements. At late times, clustering of particles occurs. This can be included in a Haff-like description taking into account the decreasing number of free particles. With this a good description of the data is possible over the whole time range.Comment: 4 pages, 5 figure

1-s Productions: A Validation of an Efficient Measure of Clock Variability

Objective: Clock variance is an important statistic in many clinical and developmental studies. Existing methods require a large number of trials for accurate clock variability assessment, which is problematic in studies using clinical or either young or aged participants. Furthermore, these existing methods often implicitly convolute clock and memory processes, making it difficult to disentangle whether the clock or memory system are driving the observed deviations. Here we assessed whether 20 repeated productions of a well-engrained interval (1 s), a task that does not incorporate memory updating nor the processing of feedback, could provide an accurate assessment of clock variability.Method: Sixty-eight undergraduate students completed two tasks: a 1-s production task in which they were asked to produce a 1-s duration by ending a tone by a keypress, and a multi-duration reproduction task. Durations presented in the reproduction task were tones lasting 1.17, 1.4 and 1.68 s. No feedback was presented in either task, and the order of presentation was counterbalanced between participants.Results: The observed central tendency in the reproduction task was better explained by models including the measures of clock variability derived from the 1-s production task than by models without it. Three clock variability measures were calculated for each participant [standard deviation, root mean squared residuals (RMSRs) from an estimated linear slope, and RMSR scaled by mean production duration]. The model including the scaled RMSR was preferred over the alternative models, and no notable effects of the order of task presentation were observed. These results suggest that: (1) measures of variability should account for drift; (2) the presentation of another timing task before a 1-s production task did not influence the assessment of the clock variability; and (3) the observed variability adheres to the scalar property and predicts temporal performance, and is thus a usable index of clock variability.Conclusion: This study shows that just 20 repeated productions of 1 s provide a reliable index of clock variability. As administering this task is fast and easy, it could prove to be useful in a large variety of developmental and clinical populations

Timing deficiencies in amnestic Mild Cognitive Impairment:Disentangling clock and memory processes

Interval timing performance in cognitive decline is typically characterized by decreased accuracy, precision, or both. One explanation for this decreased performance is a larger clock time variability. However, memory deficiencies associated with cognitive decline might also affect temporal performance in two alternative ways: First, memory deficiencies could lead to reduced encoding of just perceived durations, and thus a stronger reliance on the memory traces of previous experiences (the “prior”), yielding less precise reproductions of the most current experiences. Second, memory deficiencies could hamper the storage of perceived intervals, thus resulting in less influence of the prior. Here, we present data of 15 patients with amnestic Mild Cognitive Impairment (aMCI) and 44 healthy, aged controls, the latter split in two groups based on memory performance. All participants were tested on a temporal production task to assess clock time variability and a multi-duration reproduction task to assess the influence of memory traces reflecting current and previous experiences. Patients with aMCI showed the strongest regression towards the mean in a multi-duration reproduction task, followed by low-performing healthy controls and high-performing healthy controls, respectively. As no difference was observed between the groups in terms of clock time variability, and clock variability did not statistically contribute to the observed regression, this increased central tendency effect was not attributable to clock noise. We therefore, in line with the first explanation, conclude that memory deficiencies result in a stronger (relative) reliance on the prior

How Soil Invertebrates Deal With Microplastic Contamination

Small animals living in soils, called soil invertebrates, represent a very diverse group of soil inhabitants. They include earthworms, woodlice, spiders, springtails, mites, and some insects. Soil invertebrates feed on dead plants, on fungi and bacteria, or on other soil invertebrates. The many ways soil invertebrates interact with each other, and the large number of different species, make life in soils complex and difficult to understand. Unfortunately, soil invertebrates have been dealing with soil pollution, including contamination with tiny particles of plastic called microplastics for decades now. But are microplastics harmful to these organisms? Can microplastics be passed between soil invertebrates when one feeds on another? Most questions about microplastics and soil invertebrates have been investigated using earthworms, but a few studies on others, like springtails, mites, and nematodes, also exist. In this article, we summarize the effects of microplastics on soil invertebrates

Prediction of temperature induced shape deviations in dry milling

In this paper a model for a simulation based prediction of temperature induced shape deviations in dry milling is presented. A closed loop between Boolean material removal, process forces, heat flux and thermoelastic deformation is established. Therefore, an efficient dexel based machining simulation is extended by a contact zone analysis to model the local workpiece load. Based on the computed contact zone the cutting forces and heat flux are calculated using a semi-empirical process model. For a detailed consideration of the loads they are discretized and localized on the dexel-represented workpiece surface. A projection of the localized workpiece loads on the boundary of the finite element domain, taking into account the Boolean material removal during the process, allows the calculation of the current temperature and deformation of the workpiece. By transforming these thermomechanical characteristics back to the dexel-model a consideration in the machining simulation is possible. An extended contact zone analysis is developed for the prediction of the localized shape deviations. Finally, the results of the simulation are compared with measured data. The comparison shows that workpiece temperatures, workpiece deformation and shape deviations in different workpiece areas are predicted accurately.DFG/DE 447/90-2DFG/MA 1657/21-

Conceptually plausible Bayesian inference in interval timing

In a world that is uncertain and noisy, perception makes use of optimization procedures that rely on the statistical properties of previous experiences. A well-known example of this phenomenon is the central tendency effect observed in many psychophysical modalities. For example, in interval timing tasks, previous experiences influence the current percept, pulling behavioural responses towards the mean. In Bayesian observer models, these previous experiences are typically modelled by unimodal statistical distributions, referred to as the prior. Here, we critically assess the validity of the assumptions underlying these models and propose a model that allows for more flexible, yet conceptually more plausible, modelling of empirical distributions. By representing previous experiences as a mixture of lognormal distributions, this model can be parametrized to mimic different unimodal distributions and thus extends previous instantiations of Bayesian observer models. We fit the mixture lognormal model to published interval timing data of healthy young adults and a clinical population of aged mild cognitive impairment patients and age-matched controls, and demonstrate that this model better explains behavioural data and provides new insights into the mechanisms that underlie the behaviour of a memory-affected clinical population

Version 1 of a sea ice module for the physics-based, detailed, multi-layer SNOWPACK model

Sea ice is an important component of the global climate system. The presence of a snowpack covering sea ice can strongly modify the thermodynamic behavior of the sea ice, due to the low thermal conductivity and high albedo of snow. The snowpack can be stratified and change properties (density, water content, grain size and shape) throughout the seasons. Melting snow provides freshwater which can form melt ponds or cause flushing of salt out of the underlying sea ice, while flooding of the snow layer by saline ocean water can strongly impact both the ice mass balance and the freezing point of the snow. To capture the complex dynamics from the snowpack, we introduce modifications to the physics-based, multi-layer SNOWPACK model to simulate the snow-sea-ice system. Adaptations to the model thermodynamics and a description of water and salt transport through the snow-sea-ice system by coupling the transport equation to the Richards equation were added. These modifications allow the snow microstructure descriptions developed in the SNOWPACK model to be applied to sea ice conditions as well. Here, we drive the model with data from snow and ice mass-balance buoys installed in the Weddell Sea in Antarctica. The model is able to simulate the temporal evolution of snow density, grain size and shape, and snow wetness. The model simulations show abundant depth hoar layers and melt layers, as well as superimposed ice formation due to flooding and percolation. Gravity drainage of dense brine is underestimated as convective processes are so far neglected. Furthermore, with increasing model complexity, detailed forcing data for the simulations are required, which are difficult to acquire due to limited observations in polar regions

Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning

Memorising vocabulary is an important aspect of formal foreign-language learning. Advances in cognitive psychology have led to the development of adaptive learning systems that make vocabulary learning more efficient. One way these computer-based systems optimize learning is by measuring learning performance in real time to create optimal repetition schedules for individual learners. While such adaptive learning systems have been successfully applied to word learning using keyboard-based input, they have thus far seen little application in word learning where spoken instead of typed input is used. Here we present a framework for speech-based word learning using an adaptive model that was developed for and tested with typing-based word learning. We show that typing- and speech-based learning result in similar behavioral patterns that can be used to reliably estimate individual memory processes. We extend earlier findings demonstrating that a response-time based adaptive learning approach outperforms an accuracy-based, Leitner flashcard approach in learning efficiency (demonstrated by higher average accuracy and lower response times after a learning session). In short, we show that adaptive learning benefits transfer from typing-based learning, to speech based learning. Our work provides a basis for the development of language learning applications that use real-time pronunciation assessment software to score the accuracy of the learner’s pronunciations. We discuss the implications for our approach for the development of educationally relevant, adaptive speech-based learning applications

Wissenschaftliche Weiterbildung und Öffnung für nicht-traditionelle Zielgruppen als Herausforderungen für Hochschulen: eine empirische Untersuchung zu den Sichtweisen von Hochschullehrern und Verwaltungsmitarbeitern an der Universität Rostock

Im Rahmen der Studienstrukturreformen von Bologna wurde Lebenslanges Lernen (LLL) als künftiges Betätigungsfeld der Hochschulen deklariert. Durch sinkende Studierendenzahlen und eine stetig steigende Nachfrage nach wissenschaftlichen Weiterbildungsangeboten gewinnt die Thematik für Hochschulen überdies an Bedeutung. Die Implementierung von LLL stellt auch die Universität Rostock für die nächsten Jahre vor besondere Herausforderungen. Im Rahmen des Projektes KOSMOS wird dieser notwendige Veränderungsprozess erstmals mit Maßnahmen der Organisationsentwicklung (OE) unterstützt. OE ist dabei als Veränderungsstrategie zu verstehen, die unter aktiver Mitwirkung der Betroffenen vollzogen wird (von Rosenstiel & Nerdinger, 2011). Hierzu zählt neben den Hochschullehrern als Verantwortliche für die universitäre Forschung und Lehre auch die Verwaltung als zentrales Organ bei der Gestaltung universitärer Strukturen