Curvature-dimension inequalities and Li-Yau inequalities in sub-Riemannian spaces

In this paper we present a survey of the joint program with Fabrice Baudoin originated with the paper \cite{BG1}, and continued with the works \cite{BG2}, \cite{BBG}, \cite{BG3} and \cite{BBGM}, joint with Baudoin, Michel Bonnefont and Isidro Munive.Comment: arXiv admin note: substantial text overlap with arXiv:1101.359

The promoter polymorphism -232C/G of the PCK1 gene is associated with type 2 diabetes in a UK-resident South Asian population

Background: The PCK1 gene, encoding cytosolic phosphoenolpyruvate carboxykinase (PEPCK-C), has previously been implicated as a candidate gene for type 2 diabetes (T2D) susceptibility. Rodent models demonstrate that over-expression of Pck1 can result in T2D development and a single nucleotide polymorphism (SNP) in the promoter region of human PCK1 (-232C/G) has exhibited significant association with the disease in several cohorts. Within the UK-resident South Asian population, T2D is 4 to 6 times more common than in indigenous white Caucasians. Despite this, few studies have reported on the genetic susceptibility to T2D in this ethnic group and none of these has investigated the possible effect of PCK1 variants. We therefore aimed to investigate the association between common variants of the PCK1 gene and T2D in a UK-resident South Asian population of Punjabi ancestry, originating predominantly from the Mirpur area of Azad Kashmir, Pakistan. \ud \ud Methods: We used TaqMan assays to genotype five tagSNPs covering the PCK1 gene, including the -232C/G variant, in 903 subjects with T2D and 471 normoglycaemic controls. \ud \ud Results: Of the variants studied, only the minor allele (G) of the -232C/G SNP demonstrated a significant association with T2D, displaying an OR of 1.21 (95% CI: 1.03 - 1.42, p = 0.019). \ud \ud Conclusion: This study is the first to investigate the association between variants of the PCK1 gene and T2D in South Asians. Our results suggest that the -232C/G promoter polymorphism confers susceptibility to T2D in this ethnic group. \ud \ud Trial registration: UKADS Trial Registration: ISRCTN38297969

The Dirichlet and the weighted metrics for the space of Kahler metrics

In this work we study the intrinsic geometry of the space of Kahler metrics under various Riemannian metrics. The first part is on the Dirichlet metric. We motivate its study, we compute its curvature, and we make links with the Calabi metric, the K-energy, the degenerate complex Hessian equation. The second part is on the weighted metrics, for which we investigate as well their geometric properties.Comment: 33 pages, new sections on the weighted metric

On the spectrum of the Page and the Chen-LeBrun-Weber metrics

We give bounds on the first non-zero eigenvalue of the scalar Laplacian for both the Page and the Chen-LeBrun-Weber Einstein metrics. One notable feature is that these bounds are obtained without explicit knowledge of the metrics or numerical approximation to them. Our method also allows the calculation of the invariant part of the spectrum for both metrics. We go on to discuss an application of these bounds to the linear stability of the metrics. We also give numerical evidence to suggest that the bounds for both metrics are extremely close to the actual eigenvalue.Comment: 15 pages, v2 substantially rewritten, section on linear stability added; v3 updated to reflect referee's comments, v4 final version to appear in Ann. Glob. Anal. Geo

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

On the Importance of Countergradients for the Development of Retinotopy: Insights from a Generalised Gierer Model

During the development of the topographic map from vertebrate retina to superior colliculus (SC), EphA receptors are expressed in a gradient along the nasotemporal retinal axis. Their ligands, ephrin-As, are expressed in a gradient along the rostrocaudal axis of the SC. Countergradients of ephrin-As in the retina and EphAs in the SC are also expressed. Disruption of any of these gradients leads to mapping errors. Gierer's (1981) model, which uses well-matched pairs of gradients and countergradients to establish the mapping, can account for the formation of wild type maps, but not the double maps found in EphA knock-in experiments. I show that these maps can be explained by models, such as Gierer's (1983), which have gradients and no countergradients, together with a powerful compensatory mechanism that helps to distribute connections evenly over the target region. However, this type of model cannot explain mapping errors found when the countergradients are knocked out partially. I examine the relative importance of countergradients as against compensatory mechanisms by generalising Gierer's (1983) model so that the strength of compensation is adjustable. Either matching gradients and countergradients alone or poorly matching gradients and countergradients together with a strong compensatory mechanism are sufficient to establish an ordered mapping. With a weaker compensatory mechanism, gradients without countergradients lead to a poorer map, but the addition of countergradients improves the mapping. This model produces the double maps in simulated EphA knock-in experiments and a map consistent with the Math5 knock-out phenotype. Simulations of a set of phenotypes from the literature substantiate the finding that countergradients and compensation can be traded off against each other to give similar maps. I conclude that a successful model of retinotopy should contain countergradients and some form of compensation mechanism, but not in the strong form put forward by Gierer

General Gauge Mediation at the Weak Scale

We completely characterize General Gauge Mediation (GGM) at the weak scale by solving all IR constraints over the full parameter space. This is made possible through a combination of numerical and analytical methods, based on a set of algebraic relations among the IR soft masses derived from the GGM boundary conditions in the UV. We show how tensions between just a few constraints determine the boundaries of the parameter space: electroweak symmetry breaking (EWSB), the Higgs mass, slepton tachyons, and left-handed stop/sbottom tachyons. While these constraints allow the left-handed squarks to be arbitrarily light, they place strong lower bounds on all of the right-handed squarks. Meanwhile, light EW superpartners are generic throughout much of the parameter space. This is especially the case at lower messenger scales, where a positive threshold correction to $m_h$ coming from light Higgsinos and winos is essential in order to satisfy the Higgs mass constraint.Comment: 43 pages, 20 figures, mathematica package included in the sourc

Medoid-based clustering using ant colony optimization

The application of ACO-based algorithms in data mining has been growing over the last few years, and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works about unsupervised learning have focused on clustering, showing the potential of ACO-based techniques. However, there are still clustering areas that are almost unexplored using these techniques, such as medoid-based clustering. Medoid-based clustering methods are helpful—compared to classical centroid-based techniques—when centroids cannot be easily defined. This paper proposes two medoid-based ACO clustering algorithms, where the only information needed is the distance between data: one algorithm that uses an ACO procedure to determine an optimal medoid set (METACOC algorithm) and another algorithm that uses an automatic selection of the number of clusters (METACOC-K algorithm). The proposed algorithms are compared against classical clustering approaches using synthetic and real-world datasets

Intelligent Insect–Computer Hybrid Robot: Installing Innate Obstacle Negotiation and Onboard Human Detection onto Cyborg Insect

Developing small mobile robots for Urban Search and Rescue (USAR) is a major challenge due to constraints in size and power required to perform vital functions such as obstacle navigation, victim detection, and wireless communication. Drawing upon the idea that insects’ locomotion can be controlled, what if we further utilize the insects’ intrinsic ability to avoid obstacles? Herein, a cockroach hybrid robot (≈ 1.5 cm height, 5.7 cm length) that implements the abovementioned functions is developed. It is tested in an arena with randomly placed obstacles, and a motion capture system is used to track the insect's position among the untracked obstacles. A navigation algorithm that uses an inertial measurement unit (IMU) is developed to heuristically predict the insect's situation and stimulate the insect to escape nearby obstacles. The utilization of insect's intrinsic locomotor ability and low-powered IMU reduces the onboard power load, allowing the addition of a human-detecting function. An image classification model enables the use of an onboard low-resolution infrared camera for human detection. Consequently, a single hybrid robot is established that includes locomotion control, autonomous navigation in obstructed areas, onboard human detection, and wireless communication, representing a significant step toward real USAR application