Semantic wikis as flexible database interfaces for biomedical applications

Several challenges prevent extracting knowledge from biomedical resources, including data heterogeneity and the difficulty to obtain and collaborate on data and annotations by medical doctors. Therefore, flexibility in their representation and interconnection is required; it is also essential to be able to interact easily with such data. In recent years, semantic tools have been developed: semantic wikis are collections of wiki pages that can be annotated with properties and so combine flexibility and expressiveness, two desirable aspects when modeling databases, especially in the dynamic biomedical domain. However, semantics and collaborative analysis of biomedical data is still an unsolved challenge. The aim of this work is to create a tool for easing the design and the setup of semantic databases and to give the possibility to enrich them with biostatistical applications. As a side effect, this will also make them reproducible, fostering their application by other research groups. A command-line software has been developed for creating all structures required by Semantic MediaWiki. Besides, a way to expose statistical analyses as R Shiny applications in the interface is provided, along with a facility to export Prolog predicates for reasoning with external tools. The developed software allowed to create a set of biomedical databases for the Neuroscience Department of the University of Padova in a more automated way. They can be extended with additional qualitative and statistical analyses of data, including for instance regressions, geographical distribution of diseases, and clustering. The software is released as open source-code and published under the GPL-3 license at https://github.com/mfalda/tsv2swm

Assignment of sensing tasks to IoT devices: Exploitation of a Social Network of Objects

The Social Internet of Things (SIoT) is a novel communication paradigm according to which the objects connected to the Internet create a dynamic social network that is mostly used to implement the following processes: route information and service requests, disseminate data, and evaluate the trust level of each member of the network. In this paper, the SIoT paradigm is applied to a scenario where geolocated sensing tasks are assigned to fixed and mobile devices, providing the following major contributions. The SIoT model is adopted to find the objects that can contribute to the application by crawling the social network through the nodes profile and trust level. A new algorithm to address the resource management issue is proposed so that sensing tasks are fairly assigned to the objects in the SIoT. To this, an energy consumption profile is created per device and task, and shared among nodes of the same category through the SIoT. The resulting solution is also implemented in the SIoT-based Lysis platform. Emulations have been performed, which showed an extension of the time needed to completely deplete the battery of the first device of more than 40% with respect to alternative approaches

Drag Assessment for Boundary Layer Control Schemes with Mass Injection

The present study considers uniform blowing in turbulent boundary layers as active flow control scheme for drag reduction on airfoils. The focus lies on the important question of how to quantify the drag reduction potential of this control scheme correctly. It is demonstrated that mass injection causes the body drag (the drag resulting from the stresses on the body) to differ from the wake survey drag (the momentum deficit in the wake of an airfoil), which is classically used in experiments as a surrogate for the former. This difference is related to the boundary layer control (BLC) penalty, an unavoidable drag portion which reflects the effort of a mass-injecting boundary layer control scheme. This is independent of how the control is implemented. With an integral momentum budget, we show that for the present control scheme, the wake survey drag contains the BLC penalty and is thus a measure for the inclusive drag of the airfoil, i.e. the one required to determine net drag reduction. The concept of the inclusive drag is extended also to boundary layers using the von Kàrmàn equation. This means that with mass injection the friction drag only is not sufficient to assess drag reduction also in canonical flows. Large Eddy Simulations and Reynolds-averaged Navier–Stokes simulations of the flow around airfoils are utilized to demonstrate the significance of this distinction for the scheme of uniform blowing. When the inclusive drag is properly accounted for, control scenarios previously considered to yield drag reduction actually show drag increase

Uniform blowing and suction applied to nonuniform adverse-pressure-gradient wing boundary layers

A detailed analysis of the effects of uniform blowing, uniform suction, and body-force damping on the turbulent boundary layer developing around a NACA4412 airfoil at moderate Reynolds number is presented. The flow over the suction and the pressure sides of the airfoil is subjected to a nonuniform adverse pressure gradient and a moderate favorable pressure gradient, respectively. We find that the changes in total skin friction due to blowing and suction are not very sensitive to different pressure-gradient conditions or the Reynolds number. However, when blowing and suction are applied to an adverse-pressure-gradient (APG) boundary layer, their impact on properties such as the boundary-layer thickness, the intensity of the wall-normal convection, and turbulent fluctuations are more pronounced. We employ the Fukagata-Iwamoto-Kasagi decomposition [K. Fukagata et al., Phys. Fluids 14, 73 (2002)] and spectral analysis to study the interaction between intense adverse pressure gradient and these control strategies. We find that the control modifies skin-friction contributions differently in adverse-pressure-gradient and zero-pressure-gradient boundary layers. In particular, the control strategies modify considerably both the streamwise-development and the pressure-gradient contributions, which have high magnitude when a strong adverse pressure gradient is present. Blowing and suction also impact the convection of structures in the wall-normal direction. Overall, our results suggest that it is not possible to simply separate pressure-gradient and control effects, a fact to take into account in future studies on control design in practical applications

High-resolution large-eddy simulations of simplified urban flows

High-fidelity large-eddy simulations of the flow around two rectangular obstacles are carried out at a Reynolds number of 10,000 based on the free-stream velocity and the obstacle height. The incoming flow is a developed turbulent boundary layer. Mean-velocity components, turbulence fluctuations, and the terms of the turbulent-kinetic-energy budget are analyzed for three flow regimes: skimming flow, wake interference, and isolated roughness. Three regions are identified where the flow undergoes the most significant changes: the first obstacle's wake, the region in front of the second obstacle, and that around the second obstacle. In the skimming-flow case, turbulence activity in the cavity between the obstacles is limited and mainly occurs in a small region in front of the second obstacle. In the wake-interference case, there is a strong interaction between the free-stream flow that penetrates the cavity and the wake of the first obstacle. This interaction results in more intense turbulent fluctuations between the obstacles. In the isolated-roughness case, the wake of the first obstacle is in good agreement with that of an isolated obstacle. Separation bubbles with strong turbulent fluctuations appear around the second obstacle

High-resolution simulations of a turbulent boundary layer impacting two obstacles in tandem

High-fidelity large-eddy simulations of the flow around two rectangular obstacles are carried out at a Reynolds number of 10 000 based on the freestream velocity and the obstacle height. The incoming flow is a developed turbulent boundary layer. Mean-velocity components, turbulence fluctuations, and the terms of the turbulent-kinetic-energy budget are analyzed for three flow regimes: skimming flow, wake interference, and isolated roughness. Three regions are identified where the flow undergoes the most significant changes: the first obstacle's wake, the region in front of the second obstacle, and the region around the second obstacle. In the skimming-flow case, turbulence activity in the cavity between the obstacles is limited and mainly occurs in a small region in front of the second obstacle. In the wake-interference case, there is a strong interaction between the freestream flow that penetrates the cavity and the wake of the first obstacle. This interaction results in more intense turbulent fluctuations between the obstacles. In the isolated-roughness case, the wake of the first obstacle is in good agreement with that of an isolated obstacle. Separation bubbles with strong turbulent fluctuations appear around the second obstacle