TY - JOUR A1 - Hannemann, Mandy A1 - Wegner, Gino A1 - Henkel, Carsten T1 - No-slip boundary conditions for electron hydrodynamics and the thermal Casimir pressure JF - Universe : open access journal N2 - We derive modified reflection coefficients for electromagnetic waves in the THz and far infrared range. The idea is based on hydrodynamic boundary conditions for metallic conduction electrons. The temperature-dependent part of the Casimir pressure between metal plates is evaluated. The results should shed light on the "thermal anomaly," where measurements deviate from the standard fluctuation electrodynamics for conducting metals. KW - dispersion force KW - metal optics KW - Drude model KW - hydrodynamic model KW - spatial KW - dispersion KW - viscosity KW - non-contact heat transfer Y1 - 2021 U6 - https://doi.org/10.3390/universe7040108 SN - 2218-1997 VL - 7 IS - 4 PB - MDPI CY - Basel ER - TY - JOUR A1 - Mooij, Wolf M. A1 - Trolle, Dennis A1 - Jeppesen, Erik A1 - Arhonditsis, George B. A1 - Belolipetsky, Pavel V. A1 - Chitamwebwa, Deonatus B. R. A1 - Degermendzhy, Andrey G. A1 - DeAngelis, Donald L. A1 - Domis, Lisette Nicole de Senerpont A1 - Downing, Andrea S. A1 - Elliott, J. Alex A1 - Fragoso Jr, Carlos Ruberto A1 - Gaedke, Ursula A1 - Genova, Svetlana N. A1 - Gulati, Ramesh D. A1 - Håkanson, Lars A1 - Hamilton, David P. A1 - Hipsey, Matthew R. A1 - ‘t Hoen, Jochem A1 - Hülsmann, Stephan A1 - Los, F. Hans A1 - Makler-Pick, Vardit A1 - Petzoldt, Thomas A1 - Prokopkin, Igor G. A1 - Rinke, Karsten A1 - Schep, Sebastiaan A. A1 - Tominaga, Koji A1 - Van Dam, Anne A. A1 - Van Nes, Egbert H. A1 - Wells, Scott A. A1 - Janse, Jan H. T1 - Challenges and opportunities for integrating lake ecosystem modelling approaches JF - Aquatic ecology N2 - A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models. KW - aquatic KW - food web dynamics KW - plankton KW - nutrients KW - spatial KW - lake KW - freshwater KW - marine KW - community KW - population KW - hydrology KW - eutrophication KW - global change KW - climate warming KW - fisheries KW - biodiversity KW - management KW - mitigation KW - adaptive processes KW - non-linear dynamics KW - analysis KW - bifurcation KW - understanding KW - prediction KW - model limitations KW - model integration Y1 - 2010 U6 - https://doi.org/10.1007/s10452-010-9339-3 SN - 1573-5125 SN - 1386-2588 VL - 44 SP - 633 EP - 667 PB - Springer Science + Business Media B.V. CY - Dordrecht ER - TY - JOUR A1 - Felisatti, Arianna A1 - Laubrock, Jochen A1 - Shaki, Samuel A1 - Fischer, Martin H. T1 - A biological foundation for spatial–numerical associations BT - the brain's asymmetric frequency tuning JF - Annals of the New York Academy of Sciences N2 - "Left" and "right" coordinates control our spatial behavior and even influence abstract thoughts. For number concepts, horizontal spatial-numerical associations (SNAs) have been widely documented: we associate few with left and many with right. Importantly, increments are universally coded on the right side even in preverbal humans and nonhuman animals, thus questioning the fundamental role of directional cultural habits, such as reading or finger counting. Here, we propose a biological, nonnumerical mechanism for the origin of SNAs on the basis of asymmetric tuning of animal brains for different spatial frequencies (SFs). The resulting selective visual processing predicts both universal SNAs and their context-dependence. We support our proposal by analyzing the stimuli used to document SNAs in newborns for their SF content. As predicted, the SFs contained in visual patterns with few versus many elements preferentially engage right versus left brain hemispheres, respectively, thus predicting left-versus rightward behavioral biases. Our "brain's asymmetric frequency tuning" hypothesis explains the perceptual origin of horizontal SNAs for nonsymbolic visual numerosities and might be extensible to the auditory domain. KW - hemispheric asymmetry KW - numerical cognition KW - SNARC effect KW - spatial KW - frequency tuning KW - spatial-numerical associations KW - spatial vision Y1 - 2020 U6 - https://doi.org/10.1111/nyas.14418 SN - 0077-8923 SN - 1749-6632 VL - 1477 IS - 1 SP - 44 EP - 53 PB - Wiley CY - Hoboken ER -