Efficient Dynamic Approximate Distance Oracles for Vertex-Labeled Planar Graphs

Let $G$ be a graph where each vertex is associated with a label. A Vertex-Labeled Approximate Distance Oracle is a data structure that, given a vertex $v$ and a label $\lambda$, returns a $(1+\varepsilon)$-approximation of the distance from $v$ to the closest vertex with label $\lambda$ in $G$. Such an oracle is dynamic if it also supports label changes. In this paper we present three different dynamic approximate vertex-labeled distance oracles for planar graphs, all with polylogarithmic query and update times, and nearly linear space requirements

GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction

In voxel-based neuroimage analysis, lesion features have been the main focus in disease prediction due to their interpretability with respect to the related diseases. However, we observe that there exists another type of features introduced during the preprocessing steps and we call them "\textbf{Procedural Bias}". Besides, such bias can be leveraged to improve classification accuracy. Nevertheless, most existing models suffer from either under-fit without considering procedural bias or poor interpretability without differentiating such bias from lesion ones. In this paper, a novel dual-task algorithm namely \emph{GSplit LBI} is proposed to resolve this problem. By introducing an augmented variable enforced to be structural sparsity with a variable splitting term, the estimators for prediction and selecting lesion features can be optimized separately and mutually monitored by each other following an iterative scheme. Empirical experiments have been evaluated on the Alzheimer's Disease Neuroimaging Initiative\thinspace(ADNI) database. The advantage of proposed model is verified by improved stability of selected lesion features and better classification results.Comment: Conditional Accepted by Miccai,201

Enabling internal electronic circuitry within additively manufactured metal structures - The effect and importance of inter-laminar topography

Purpose: This paper aims to explore the potential of ultrasonic additive manufacturing (UAM) to incorporate the direct printing of electrical materials and arrangements (conductors and insulators) at the interlaminar interface of parts during manufacture to allow the integration of functional and optimal electrical circuitries inside dense metallic objects without detrimental effect on the overall mechanical integrity. This holds promise to release transformative device functionality and applications of smart metallic devices and products. Design/methodology/approach: To ensure the proper electrical insulation between the printed conductors and metal matrices, an insulation layer with sufficient thickness is required to accommodate the rough interlaminar surface which is inherent to the UAM process. This in turn increases the total thickness of printed circuitries and thereby adversely affects the integrity of the UAM part. A specific solution is proposed to optimise the rough interlaminar surface through deforming the UAM substrates via sonotrode rolling or UAM processing. Findings: The surface roughness (Sa) could be reduced from 4.5 to 4.1 µm by sonotrode rolling and from 4.5 to 0.8 µm by ultrasonic deformation. Peel testing demonstrated that sonotrode-rolled substrates could maintain their mechanical strength, while the performance of UAM-deformed substrates degraded under same welding conditions ( approximately 12 per cent reduction compared with undeformed substrates). This was attributed to the work hardening of deformation process which was identified via dual-beam focussed ion beam–scanning electron microscope investigation. Originality/value: The sonotrode rolling was identified as a viable methodology in allowing printed electrical circuitries in UAM. It enabled a decrease in the thickness of printed electrical circuitries by ca. 25 per cent

Samlande och visualiserande av verksamhetsstyrande data för en digital marknadsföringsbyrå

I dagens läge, med stor konkurrens mellan företag i samma bransch är det ytterst viktigt för företag att veta hur de når sina målgrupper. I detta examensarbete diskuteras vikten av verksamhetsstyrande data, hur det samlats och visualiserats tidigare jämfört med idag, och hur företag använder sig av den för att göra beslut och ändringar i sina strategier. Arbetet hänvisar till flera artiklar och intervjuer med experter inom visualisering av data, samt datadriven beslutsfattning inom företag. Målet med arbetet är att ha en fungerande nätverksapplikation, skriven i Node.js, som automatiskt sköter samlande av data från olika molntjänster ett företag använder. Utöver samlandet skall applikationen kunna utföra räkningar på data och skicka den vidare till en tjänst som visualiserar den i olika widgets på en dashboard.With increasing competition between companies within the same area, it is becoming more important than ever for companies to know how to reach their target groups. This thesis focus on the importance of performance related data, how it has been gathered and visualized earlier compared to today, and how companies use it to make data-based decisions for their strategies. Articles and interviews with experts in the fields of data visualization and data driven management are reviewed in the thesis. The goal is to have a working network application that gathers data from several online services in use by the company. In addition to gathering, the application will also perform calculations and format the data in such a way that it is easy to visualize using widgets on dashboards

A simple, cost-effective but highly efficient system for deriving ventricular cardiomyocytes from human pluripotent stem cells

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Generalized Ricci Curvature Bounds for Three Dimensional Contact Subriemannian manifolds

Measure contraction property is one of the possible generalizations of Ricci curvature bound to more general metric measure spaces. In this paper, we discover sufficient conditions for a three dimensional contact subriemannian manifold to satisfy this property.Comment: 49 page

Survivin as a therapeutic target in Sonic hedgehog-driven medulloblastoma.

Medulloblastoma (MB) is a highly malignant brain tumor that occurs primarily in children. Although surgery, radiation and high-dose chemotherapy have led to increased survival, many MB patients still die from their disease, and patients who survive suffer severe long-term side effects as a consequence of treatment. Thus, more effective and less toxic therapies for MB are critically important. Development of such therapies depends in part on identification of genes that are necessary for growth and survival of tumor cells. Survivin is an inhibitor of apoptosis protein that regulates cell cycle progression and resistance to apoptosis, is frequently expressed in human MB and when expressed at high levels predicts poor clinical outcome. Therefore, we hypothesized that Survivin may have a critical role in growth and survival of MB cells and that targeting it may enhance MB therapy. Here we show that Survivin is overexpressed in tumors from patched (Ptch) mutant mice, a model of Sonic hedgehog (SHH)-driven MB. Genetic deletion of survivin in Ptch mutant tumor cells significantly inhibits proliferation and causes cell cycle arrest. Treatment with small-molecule antagonists of Survivin impairs proliferation and survival of both murine and human MB cells. Finally, Survivin antagonists impede growth of MB cells in vivo. These studies highlight the importance of Survivin in SHH-driven MB, and suggest that it may represent a novel therapeutic target in patients with this disease

Polynomial Growth Harmonic Functions on Finitely Generated Abelian Groups

In the present paper, we develop geometric analytic techniques on Cayley graphs of finitely generated abelian groups to study the polynomial growth harmonic functions. We develop a geometric analytic proof of the classical Heilbronn theorem and the recent Nayar theorem on polynomial growth harmonic functions on lattices \mathds{Z}^n that does not use a representation formula for harmonic functions. We also calculate the precise dimension of the space of polynomial growth harmonic functions on finitely generated abelian groups. While the Cayley graph not only depends on the abelian group, but also on the choice of a generating set, we find that this dimension depends only on the group itself.Comment: 15 pages, to appear in Ann. Global Anal. Geo