Crowd Textures:From Sensing Proximity to Understanding Crowd Behavior

Steen, M.R. van [Promotor]Bal, H.E. [Promotor

Adaptive Partitioning for Large-Scale Dynamic Graphs

Abstract—In the last years, large-scale graph processing has gained increasing attention, with most recent systems placing particular emphasis on latency. One possible technique to improve runtime performance in a distributed graph processing system is to reduce network communication. The most notable way to achieve this goal is to partition the graph by minimizing the num-ber of edges that connect vertices assigned to different machines, while keeping the load balanced. However, real-world graphs are highly dynamic, with vertices and edges being constantly added and removed. Carefully updating the partitioning of the graph to reflect these changes is necessary to avoid the introduction of an extensive number of cut edges, which would gradually worsen computation performance. In this paper we show that performance degradation in dynamic graph processing systems can be avoided by adapting continuously the graph partitions as the graph changes. We present a novel highly scalable adaptive partitioning strategy, and show a number of refinements that make it work under the constraints of a large-scale distributed system. The partitioning strategy is based on iterative vertex migrations, relying only on local information. We have implemented the technique in a graph processing system, and we show through three real-world scenarios how adapting graph partitioning reduces execution time by over 50 % when compared to commonly used hash-partitioning. I

Planetary landing: modelling and control of the propulsion descent

In the propulsive phase, after parachute release, of planetary landing like Mars or Moon, horizontal motion is obtained by tilting the axial thrust, so that it aligns either to the negative velocity vector (gravity turn) or to the requested acceleration vector. The latter strategy is assumed here, as it allows pinpoint landing. As such, tilt angles (pitch and yaw) become proportional to the horizontal acceleration. Instead of designing a hierarchical guidance and control in which horizontal acceleration becomes the attitude control target, a unique control system can be designed based on the fourth order dynamics from angular acceleration to position. The paper shows that the combined dynamics can be (quasi) input-state linearized except the nonlinear factor of the tilt angles (the axial thrust imposed by vertical braking). The paper shows that control design around the reference trajectory (tilt and position) given by the guidance can exploit the quasi linearization, but tracking error stability must be proved in presence of a not stabilizable external disturbance. The paper is restricted to closed-loop control strategies, and their effectiveness is proved through Monte Carlo simulations

xDGP: A Dynamic Graph Processing System with Adaptive Partitioning

13 pagesMany real-world systems, such as social networks, rely on mining efficiently large graphs, with hundreds of millions of vertices and edges. This volume of information requires partitioning the graph across multiple nodes in a distributed system. This has a deep effect on performance, as traversing edges cut between partitions incurs a significant performance penalty due to the cost of communication. Thus, several systems in the literature have attempted to improve computational performance by enhancing graph partitioning, but they do not support another characteristic of real-world graphs: graphs are inherently dynamic, their topology evolves continuously, and subsequently the optimum partitioning also changes over time. In this work, we present the first system that dynamically repartitions massive graphs to adapt to structural changes. The system optimises graph partitioning to prevent performance degradation without using data replication. The system adopts an iterative vertex migration algorithm that relies on local information only, making complex coordination unnecessary. We show how the improvement in graph partitioning reduces execution time by over 50%, while adapting the partitioning to a large number of changes to the graph in three real-world scenarios

Emerging parvoviruses in domestic cats

Parvovirus infections in cats have been well known for around 100 years. Recently, the use of molecular assays and metagenomic approaches for virus discovery and characterization has led to the detection of novel parvovirus lineages and/or species infecting the feline host. However, the involvement of emerging parvoviruses in the onset of gastroenteritis or other feline diseases is still uncertain

Photonic artificial muscles: From micro robots to tissue engineering

Light responsive shape-changing polymers are able to mimic the function of biological muscles accomplishing mechanical work in response to selected stimuli. A variety of manufacturing techniques and chemical processes can be employed to shape these materials to different length scales, from centimeter fibers and films to 3D printed micrometric objects trying to replicate biological functions and operations. Controlled deformations shown to mimick basic animal operations such as walking, swimming or grabbing objects, while also controlling the refractive index and the geometry of devices, opens up the potential to implement tunable optical properties. Another possibility is that of combining artificial polymers with cells or biological tissue (such as intact cardiac trabeculae) with the aim to improve tissue formation in vitro or to support the mechanical function of damaged biological muscles. Such versatility is afforded by chemistry. New customized liquid crystalline monomers are presented here that modulate material properties for different applications. The role of synthetic material composition is highlighted as we demonstrate how using apparently similar molecular formulations, that liquid crystalline polymers can be adapted to different technological and medical challenges

Free-form Light Actuators - Fabrication and Control of Actuation in Microscopic Scale

Liquid crystalline elastomers (LCEs) are smart materials capable of reversible shape-change in response to external stimuli, and have attracted researchers' attention in many fields. Most of the studies focused on macroscopic LCE structures (films, fibers) and their miniaturization is still in its infancy. Recently developed lithography techniques, e.g., mask exposure and replica molding, only allow for creating 2D structures on LCE thin films. Direct laser writing (DLW) opens access to truly 3D fabrication in the microscopic scale. However, controlling the actuation topology and dynamics at the same length scale remains a challenge. In this paper we report on a method to control the liquid crystal (LC) molecular alignment in the LCE microstructures of arbitrary three-dimensional shape. This was made possible by a combination of direct laser writing for both the LCE structures as well as for micrograting patterns inducing local LC alignment. Several types of grating patterns were used to introduce different LC alignments, which can be subsequently patterned into the LCE structures. This protocol allows one to obtain LCE microstructures with engineered alignments able to perform multiple opto-mechanical actuation, thus being capable of multiple functionalities. Applications can be foreseen in the fields of tunable photonics, micro-robotics, lab-on-chip technology and others

Emerging hepatotropic viruses in cats: A brief review

The possible role of viruses in feline liver disease has long remained neglected. However, in 2018, an analogue of human hepatitis B virus was identified in cats. Moreover, antibodies for human hepatitis E have been detected consistently at various prevalence rates in cats. Although the correlation between these viruses and the liver injury in cats must be clarified, hepatotropic viruses might represent an increasing risk for feline and public health

The knotty biology of canine coronavirus: a worrying model of coronaviruses’ danger.

Severe clinical diseases associated to αCoronavirus (αCoV) infections were recently demonstrated for the first time in humans and a closely related but distinct canine CoV (CCoV) variant was identified in the nasopharyngeal swabs of children with pneumonia hospitalized in Malaysia, in 2017–2018. The complete genome sequence analysis demonstrated that the isolated strain, CCoV-HuPn-2018, was a novel canine-feline-like recombinant virus with a unique nucleoprotein. The occurrence of three human epidemics/pandemic caused by CoVs in the recent years and the detection of CCoV-HuPn-2018, raises questions about the ability of these viruses to overcome species barriers from their reservoirs jumping to humans. Interestingly, in this perspective, it is interesting to consider the report concerning new CCoV strains with a potential dual recombinant origin through partial S-gene exchange with porcine transmissible gastroenteritis virus (TGEV) identified in pups died with acute gastroenteritis in 2009. The significance of the ability of CCoVs to evolve is still unclear, but several questions arisen on the biology of these viruses, focusing important epidemiological outcomes in the field, in terms of both virus evolution and prophylaxis. The new CCoV-Hupn-2018 should lead researchers to pay more attention to the mechanisms of recombination among CoVs, rather than to the onset of variants as a result of mutations, suggesting a continuous monitoring of these viruses and in particular of SARS-CoV-