Comparison of Localized Radial Basis Functions’ (LRBF) Solution of the Two-dimensional Advection–Diffusion Equation to the Finite Difference Methods’ (FDM)

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

An assistive tabletop keyboard for stroke rehabilitation

We propose a tabletop keyboard that assists stroke patients in using computers. Using computers for purposes such as paying bills, managing bank accounts, sending emails, etc., which all include typing, is part of Activities of Daily Living (ADL) that stroke patients wish to recover. To date, stroke rehabilitation research has greatly focused on using computer-assisted technology for rehabilitation. However, working with computers as a skill that patients need to recover has been neglected. The conventional human computer interfaces are mouse and keyboard. Using keyboard stays the main challenge for hemiplegic stroke patients because typing is usually a bimanual task. Therefore, we propose an assistive tabletop keyboard which is not only a novel computer interface that is specially designed to facilitate patient-computer interaction but also a rehab medium through which patients practice the desired arm/hand functions. © 2013 Authors

Evaluation of pre-clinical safety and toxicology of Althaea officinalis extracts as naturopathic medicine for common carp (Cyprinus carpio)

The current study was done to investigate the preclinical safety and toxicology of Althaea officinalis extract as naturopathic medicine in common carp (Cyprinus carpio). Specimens were treated with 0 (control), 2.5, 5 and 10 g of marshmallow extract for 45 days. Plasma biochemical parameters were measured after 15 and 45 days. Total protein, albumin and globulin levels (p0.05). During the experimental period, triglyceride levels noticeably decreased in fish fed with 2.5 g of A. officinalis extract (p<0.05). Although, administration of marshmallow extract up to 5 g per kg of feed did not show any side effect on fishes, the use of the A. officinalis extract (10 g) led to cytotoxicity and modifications in blood biochemical parameters of fish. Therefore, we recommend the use of the lower concentrations than 10 g A. officinalis extract in prospective clinical studies

Short communication: Jellyfish of Khuzestan coastal waters and their impact on fish larvae populations

One of the most valuable groups in the food chain of aquatic ecosystems is zooplankton. A large portion of them are invertebrate organisms with great variety of forms and structure, size, habitat and food value. The term ‘jellyfish’ is used in reference to medusa of the phylum Cnidaria (hydromedusae, siphonophores and scyphomedusae) and planktonic members of the phylum Ctenophora (Mills, 2001). Jellyfish medusa is a zooplankton which is frequently present in coastal ocean waters and all marine habitats. They are also primary predators of other zooplanktons which have significant impact on abundance and diversity of zooplankton communities that are one of the key parts of the marine food web. Most jellyfish include Hydromedusae, Siphonophora and Scyphomedusae and planktonic Ctenophora, especially in the productive warm months (Brodeur et al., 1999). In recent years, the frequency of the jellyfish in many ecosystems has increased (Xian et al., 2005; Lynam et al., 2006)

A surrogate modelling approach based on nonlinear dimension reduction for uncertainty quantification in groundwater flow models

In this paper, we develop a surrogate modelling approach for capturing the output field (e.g., the pressure head) from groundwater flow models involving a stochastic input field (e.g., the hy- draulic conductivity). We use a Karhunen-Lo`eve expansion for a log-normally distributed input field, and apply manifold learning (local tangent space alignment) to perform Gaussian process Bayesian inference using Hamiltonian Monte Carlo in an abstract feature space, yielding outputs for arbitrary unseen inputs. We also develop a framework for forward uncertainty quantification in such problems, including analytical approximations of the mean of the marginalized distri- bution (with respect to the inputs). To sample from the distribution we present Monte Carlo approach. Two examples are presented to demonstrate the accuracy of our approach: a Darcy flow model with contaminant transport in 2-d and a Richards equation model in 3-d

Navigation of micro-swimmers in steady flow: the importance of symmetries

Marine microorganisms must cope with complex flow patterns and even turbulence as they navigate the ocean. To survive they must avoid predation and find efficient energy sources. A major difficulty in analysing possible survival strategies is that the time series of environmental cues in non-linear flow is complex, and that it depends on the decisions taken by the organism. One way of determining and evaluating optimal strategies is reinforcement learning. In a proof-of-principle study, Colabrese et al. [Phys. Rev. Lett. (2017)] used this method to find out how a micro-swimmer in a vortex flow can navigate towards the surface as quickly as possible, given a fixed swimming speed. The swimmer measured its instantaneous swimming direction and the local flow vorticity in the laboratory frame, and reacted to these cues by swimming either left, right, up, or down. However, usually a motile microorganism measures the local flow rather than global information, and it can only react in relation to the local flow, because in general it cannot access global information (such as up or down in the laboratory frame). Here we analyse optimal strategies with local signals and actions that do not refer to the laboratory frame. We demonstrate that symmetry-breaking is required in order to learn vertical migration in a meaningful way. Using reinforcement learning we analyse the emerging strategies for different sets of environmental cues that microorganisms are known to measure.Comment: 20 pages, 5 figure