403 research outputs found

    Active particle dynamics beyond the jamming density

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    Many biological systems form colonies at high density. Passive granular systems will be jammed at such densities, yet for the survival of biological systems it is crucial that they are dynamic. We construct a phase diagram for a system of active particles interacting via Vicsek alignment, and vary the density, self-propulsion force, and orientational noise. We find that the system exhibits four different phases, characterized by transitions in the effective diffusion constant and in the orientational order parameter. Our simulations show that there exists an optimal noise such that particles require a minimal force to unjam, allowing for rearrangements.Comment: 7 pages, 8 figure

    Obesidad infantil y parámetros de composición corporal en niños de extremadura (españa).

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    Introducción En las sociedades desarrolladas la obesidad es uno de los trastornos nutricionales más frecuente en la infancia y la adolescencia (Serra Majem, 2003) y el quinto factor principal de riesgo de defunción en el mundo (Fernández-Bergés, 2012. Estudios previos establecen que 2 de cada 10 niños/as extremeños padecen obesidad o sobrepeso (Torres, 2008). El objetivo del estudio es describir la prevalencia de la obesidad en escolares extremeños y conocer la influencia de la obesidad sobre factores de parámetros de composición corporal. Métodos 242 niños/as (9 a 12 años) de centros de primaria de la Comunidad Autónoma de Extremadura fueron evaluados. Tras informar y recibir el consentimiento informado de los tutores legales de los sujetos, se llevaron a cabo mediciones individuales de parámetros antropométricos : peso, talla, IMC, masa grasa, masa libre de grasa, % grasa y peso óseo, índice cintura-cadera. Se llevó a cabo un análisis descriptivo para conocer el porcentaje de obesidad entre los escolares y un ANOVA de un factor con un test post hoc para comparar los resultados con los tres niveles del factor de estudio (normopeso, sobrepeso y obesidad). Resultados El 9,9% de los niños/as extremeños evaluados eran obesos, siendo este porcentaje mayor en el caso de los niños (11,2% frente a 8,54% de las niñas). Existen diferencias significativas (p> 0.05) en cuanto al nivel de composición corporal en las variables IMC, ICC, masa grasa y % masa grasa. Conclusiones 18% escolares extremeños presenta sobrepeso u obesidad, valor que se ha mantenido constante en los últimos años. Los niños/as con sobrepeso y obesidad presentan mayores niveles de IMC, ICC y niveles de grasa corporal

    Scheduling deliveries under uncertainty

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    Quite often transportation companies face two types of jobs, ones which they can plan themselves and ones which have to be done on call. In this paper we study the scheduling of these jobs, while we assume that job durations are known beforehand as well as windows in which the jobs need to be done. We develop several heuristics to solve the problem at hand. The most successful are based on defining an appropriate buffer. The methods are assessed in extensive experiments on two aspects, viz. efficiency, in the sense that they carry out many jobs and certainty, in the sense that they provide information beforehand about which jobs they will execute

    On T-Duality in Brane Gas Cosmology

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    In the context of homogeneous and isotropic superstring cosmology, the T-duality symmetry of string theory has been used to argue that for a background space-time described by dilaton gravity with strings as matter sources, the cosmological evolution of the Universe will be nonsingular. In this Letter we discuss how T-duality extends to brane gas cosmology, an approximation in which the background space-time is again described by dilaton gravity with a gas of branes as a matter source. We conclude that the arguments for nonsingular cosmological evolution remain valid.Comment: 8 pages, Appendix adde

    Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation

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    Sensing enabled implantable devices and next-generation neurotechnology allow real-time adjustments of invasive neuromodulation. The identification of symptom and disease-specific biomarkers in invasive brain signal recordings has inspired the idea of demand dependent adaptive deep brain stimulation (aDBS). Expanding the clinical utility of aDBS with machine learning may hold the potential for the next breakthrough in the therapeutic success of clinical brain computer interfaces. To this end, sophisticated machine learning algorithms optimized for decoding of brain states from neural time-series must be developed. To support this venture, this review summarizes the current state of machine learning studies for invasive neurophysiology. After a brief introduction to the machine learning terminology, the transformation of brain recordings into meaningful features for decoding of symptoms and behavior is described. Commonly used machine learning models are explained and analyzed from the perspective of utility for aDBS. This is followed by a critical review on good practices for training and testing to ensure conceptual and practical generalizability for real-time adaptation in clinical settings. Finally, first studies combining machine learning with aDBS are highlighted. This review takes a glimpse into the promising future of intelligent adaptive DBS (iDBS) and concludes by identifying four key ingredients on the road for successful clinical adoption: i) multidisciplinary research teams, ii) publicly available datasets, iii) open-source algorithmic solutions and iv) strong world-wide research collaborations.Fil: Merk, Timon. Charité – Universitätsmedizin Berlin; AlemaniaFil: Peterson, Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina. Harvard Medical School; Estados UnidosFil: Köhler, Richard. Charité – Universitätsmedizin Berlin; AlemaniaFil: Haufe, Stefan. Charité – Universitätsmedizin Berlin; AlemaniaFil: Richardson, R. Mark. Harvard Medical School; Estados UnidosFil: Neumann, Wolf Julian. Charité – Universitätsmedizin Berlin; Alemani

    Comparison of a web-based 24-h dietary recall tool (Foodbook24) to an interviewer-led 24-h dietary recall

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    Web-based tools have the potential to reduce the cost of dietary assessment; however, it is necessary to establish their performance compared to traditional dietary assessment methods. This study aims to compare nutrient and food intakes derived from Foodbook24 to those obtained from an interview-led 24-h dietary recall (24HDR). Seventy-nine adult participants completed one self-administered 24HDR using Foodbook24 and one interviewer-led 24HDR on the same day. Following a 10 days wash-out period the same process was completed again in opposite order to the previous study visit. Statistical analysis including Spearman’s rank order correlation, Mann-Whitney U tests, cross-classification analysis, and “Match”, “Omission”, and “Intrusion” rates were used to investigate the relationship between both methods. Strong, positive correlations of nutrient intake estimated using both methods was observed (rs = 0.6–1.0; p < 0.001). The percentage of participants classified into the same tertile of nutrient intake distribution using both methods ranged from 58% (energy) to 82% (vitamin D). The overall match rate for food intake between both methods was 85%, while rates for omissions and intrusions were 11.5% and 3.5%, respectively. These results, alongside the reduced cost and participant burden associated with Foodbook24, highlight the tool’s potential as a viable alternative to the interviewer-led 24HDR

    Root colonization by arbuscular mycorrhizal fungi is reduced in tomato plants sprayed with fungicides

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    Arbuscular mycorrhizal fungi (AMF) form symbioses with many agricultural crops and can improve plant biomass and health. The performance of the AM symbiosis is context dependent, for example, usually the inoculation of the AMF Rhizophagus irregularis benefits plant biomass, but benefits can be suppressed by high soil fertility levels. Nevertheless, the importance of many other agricultural management practices on AMF, such as fungicides application, is poorly understood. Also, pesticide regulations usually neglect a comprehensive safety testing of fungicides on AMF and lawmakers require empirical support to improve such laws. The objective of this study was to evaluate the effects of spraying fungicides on tomato plants and the subsequent root colonization of plants grown in natural soil containing AMF and inoculated with R. irregularis. We detected that the inoculation of R. irregularis increased the total root colonization of the control plants that did not receive fungicides and that spraying the plants with the fungicides Signum® and Topas® reduced total root colonization. The effect on specific AM fungal structures was variable according to the product. Signum® reduced the occurrence of arbuscules, while Topas® reduced the occurrence of AM hyphae in the colonized roots. Cuprozin® did not reduce total root colonization but reduced the occurrence of AM vesicles. Sampling time was also relevant. Effects were detected at 90 days, but not at 35 days. Our results show that fungicides safety should be evaluated for their effects on root colonization of crops in non-sterilized soils and at adequate sampling time

    Energy- and Cost-Efficient Pumping Station Control

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    With renewable energy becoming more common, energy prices fluctuate more depending on environmental factors such as the weather. Consuming energy without taking volatile prices into consideration can not only become expensive, but may also increase the peak load, which requires energy providers to generate additional energy using less environment-friendly methods. In the Netherlands, pumping stations that maintain the water levels of polder canals are large energy consumers, but the controller software currently used in the industry does not take real-time energy availability into account. We investigate if existing AI planning techniques have the potential to improve upon the current solutions. In particular, we propose a light weight but realistic simulator and investigate if an online planning method (UCT) can utilise this simulator to improve the cost-efficiency of pumping station control policies. An empirical comparison with the current control algorithms indicates that substantial cost, and thus peak load, reduction can be attained
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