Adaptive Threshold Sampling and Estimation

Sampling is a fundamental problem in both computer science and statistics. A number of issues arise when designing a method based on sampling. These include statistical considerations such as constructing a good sampling design and ensuring there are good, tractable estimators for the quantities of interest as well as computational considerations such as designing fast algorithms for streaming data and ensuring the sample fits within memory constraints. Unfortunately, existing sampling methods are only able to address all of these issues in limited scenarios. We develop a framework that can be used to address these issues in a broad range of scenarios. In particular, it addresses the problem of drawing and using samples under some memory budget constraint. This problem can be challenging since the memory budget forces samples to be drawn non-independently and consequently, makes computation of resulting estimators difficult. At the core of the framework is the notion of a data adaptive thresholding scheme where the threshold effectively allows one to treat the non-independent sample as if it were drawn independently. We provide sufficient conditions for a thresholding scheme to allow this and provide ways to build and compose such schemes. Furthermore, we provide fast algorithms to efficiently sample under these thresholding schemes

Human resource allocation to multiple projects based on members’ expertise, group heterogeneity and social cohesion

Project managers regularly allocate human resources to construction projects. This critical task is usually executed by fulfilling the minimum project staffing requirements normally based around the quantity and competence of project members. However, research has shown that team performance can increase by up to 10% and 18%, respectively, as a consequence of the group members’ heterogeneity and social cohesion. Also, there is currently no practical quantitative tool which incorporates these aspects to allow project managers to achieve this task efficiently and objectively. A new quantitative model for the effective allocation of human resources to multiple projects, which takes into account group heterogeneity and social cohesion is proposed. This model is easy to build, update and use in real project environments with the use of a spreadsheet and a basic optimization engine (e.g. Excel Solver). A case study is proposed and solved with a Genetic Algorithm to illustrate the model implementation. Finally, a validation example is provided to exemplify how group heterogeneity and social cohesion condition academic achievement in an academic setting

Minimum Energy Path to Membrane Pore Formation and Rupture

We combine dynamic self-consistent field theory with the string method to calculate the minimum energy path to membrane pore formation and rupture. In the regime where nucleation can occur on experimentally relevant time scales, the structure of the critical nucleus is between a solvophilic stalk and a locally thinned membrane. Classical nucleation theory fails to capture these molecular details and significantly overestimates the free energy barrier. Our results suggest that thermally nucleated rupture may be an important factor for the low rupture strains observed in lipid membranes

Increased risk for T cell autoreactivity to ß-cell antigens in the mice expressing the Avy obesity-associated gene.

There has been considerable debate as to whether obesity can act as an accelerator of type 1 diabetes (T1D). We assessed this possibility using transgenic mice (MIP-TF mice) whose ß-cells express enhanced green fluorescent protein (EGFP). Infecting these mice with EGFP-expressing murine herpes virus-68 (MHV68-EGFP) caused occasional transient elevation in their blood glucose, peri-insulitis, and Th1 responses to EGFP which did not spread to other ß-cell antigens. We hypothesized that obesity-related systemic inflammation and ß-cell stress could exacerbate the MHV68-EGFP-induced ß-cell autoreactivity. We crossed MIP-TF mice with Avy mice which develop obesity and provide models of metabolic disease alongside early stage T2D. Unlike their MIP-TF littermates, MHV68-EGFP-infected Avy/MIP-TF mice developed moderate intra-insulitis and transient hyperglycemia. MHV68-EGFP infection induced a more pronounced intra-insulitis in older, more obese, Avy/MIP-TF mice. Moreover, in MHV68-EGFP-infected Avy/MIP-TF mice, Th1 reactivity spread from EGFP to other ß-cell antigens. Thus, the spreading of autoreactivity among ß-cell antigens corresponded with the transition from peri-insulitis to intra-insulitis and occurred in obese Avy/MIP-TF mice but not lean MIP-TF mice. These observations are consistent with the notion that obesity-associated systemic inflammation and ß-cell stress lowers the threshold necessary for T cell autoreactivity to spread from EGFP to other ß-cell autoantigens

Interface Roughness Effects in Ultra-Thin Tunneling Oxides

Advanced MOSFET for ULSI and novel silicon-based devices require the use of ultrathin tunneling oxides where non-uniformity is often present. We report on our theoretical study of how tunneling properties of ultra-thin oxides are affected by roughness at the silicon/oxide interface. The effect of rough interfacial topography is accounted for by using the Planar Supercell Stack Method (PSSM) which can accurately and efficiently compute scattering properties of 3D supercell structures. Our results indicate that while interface roughness effects can be substantial in the direct tunneling regime, they are less important in the Fowler-Nordheim regime