Stratified Learning: a general-purpose statistical method for improved learning under Covariate Shift

Covariate shift arises when the labelled training (source) data is not representative of the unlabelled (target) data due to systematic differences in the covariate distributions. A supervised model trained on the source data subject to covariate shift may suffer from poor generalization on the target data. We propose a novel, statistically principled and theoretically justified method to improve learning under covariate shift conditions, based on propensity score stratification, a well-established methodology in causal inference. We show that the effects of covariate shift can be reduced or altogether eliminated by conditioning on propensity scores. In practice, this is achieved by fitting learners on subgroups ("strata") constructed by partitioning the data based on the estimated propensity scores, leading to balanced covariates and much-improved target prediction. We demonstrate the effectiveness of our general-purpose method on contemporary research questions in observational cosmology, and on additional benchmark examples, matching or outperforming state-of-the-art importance weighting methods, widely studied in the covariate shift literature. We obtain the best reported AUC (0.958) on the updated "Supernovae photometric classification challenge" and improve upon existing conditional density estimation of galaxy redshift from Sloan Data Sky Survey (SDSS) data

Creating Teaching Opportunities for STEM Future Faculty Development

Graduate school is an important time for future faculty to develop teaching skills, but teaching opportunities are limited. Discipline-related course work and research do not provide the pedagogy, strategies, and skills to effectively teach and compete for higher education jobs. As future faculty, graduate students will influence the future of science, technology, engineering, and mathematics (STEM) education through their teaching. The purpose of this case study was to examine future faculty’s (graduate students’) perceived teaching development during a semester-long STEM teaching development course. Findings included STEM future faculty’s teaching confidence and skill development in instructional design, preparation, and facilitation; greater development in skill awareness than student awareness and self-awareness; and a focus on knowledge-centered learning environments for future classroom teaching experiences

Live Migration Downtime Analysis of a VNF Guest for a Proposed Optical FMC Network Architecture

Fixed Mobile Convergence (FMC) implies use of a shared optical fronthaul network infrastructure able to carry transparently both fixed and mobile traffic including Wi-Fi, Mobile and fixed Ethernet. Network Function Virtualization (NFV) is a main enabler for FMC using a shared infrastructure for fixed and mobile gateways. Live migration, a virtualization key-feature, offers load-balancing, increased energy efficiency, application elasticity and other worthy advantages. This paper presents the evaluation of migrating a VNF over an FMC infrastructure. Our results show that, performing a livemigration over a dedicated connection yielded zero downtime and met a benchmark delay. The following scenario, where the ongoing connection is re-routed on a different optical path, shows the successful completion of the migration with an increase in delay of 2.4 seconds (22% higher than the benchmark) and only 2.1 seconds downtime Fixed Mobile Convergence (FMC) implies use of a shared optical fronthaul network infrastructure able to carry transparently both fixed and mobile traffic including Wi-Fi, Mobile and fixed Ethernet. Network Function Virtualization (NFV) is a main enabler for FMC using a shared infrastructure for fixed and mobile gateways. Live migration, a virtualization key-feature, offers load-balancing, increased energy efficiency, application elasticity and other worthy advantages. This paper presents the evaluation of migrating a VNF over an FMC infrastructure. Our results show that, performing a live migration over a dedicated connection yielded zero downtime and met a benchmark delay. The following scenario, where the ongoing connection is re-routed on a different optical path, shows the successful completion of the migration with an increase in delay of 2.4 seconds (22% higher than the benchmark) and only 2.1 seconds downtime

Improved Weak Lensing Photometric Redshift Calibration via StratLearn and Hierarchical Modeling

Discrepancies between cosmological parameter estimates from cosmic shear surveys and from recent Planck cosmic microwave background measurements challenge the ability of the highly successful $\Lambda$CDM model to describe the nature of the Universe. To rule out systematic biases in cosmic shear survey analyses, accurate redshift calibration within tomographic bins is key. In this paper, we improve photo-$z$ calibration via Bayesian hierarchical modeling of full galaxy photo-$z$ conditional densities, by employing $\textit{StratLearn}$, a recently developed statistical methodology, which accounts for systematic differences in the distribution of the spectroscopic training/source set and the photometric target set. Using realistic simulations that were designed to resemble the KiDS+VIKING-450 dataset, we show that $\textit{StratLearn}$-estimated conditional densities improve the galaxy tomographic bin assignment, and that our $\textit{StratLearn}$-Bayesian framework leads to nearly unbiased estimates of the target population means. This leads to a factor of $\sim 2$ improvement upon the previously best photo-$z$ calibration method. Our approach delivers a maximum bias per tomographic bin of $\Delta \langle z \rangle = 0.0095 \pm 0.0089$, with an average absolute bias of $0.0052 \pm 0.0067$ across the five tomographic bins.Comment: 24 pages, 20 figures, 3 appendice

Dynamic Virtual Network Reconfiguration Over SDN Orchestrated Multitechnology Optical Transport Domains

Network virtualization is an emerging technique that enables multiple tenants to share an underlying physical infrastructure, isolating the traffic running over different virtual infrastructures/tenants. This technique aims to improve network utilization, while reducing the complexities in terms of network management for operators. Applied to this context, software defined networking (SDN) paradigm can ease network configurations by enabling network programmability and automation, which reduces the amount of operations required from both service and infrastructure providers. SDN techniques are decreasing vendor lock-in issues due to specific configuration methods or protocols. Application-based Network Operations (ABNO) is a toolbox of key network functional components with the goal of offering application-driven network management. Service provisioning using ABNO may involve direct configuration of data plane elements or delegate it to several control plane modules. We validate the applicability of ABNO to multi-tenant virtual networks in multi-technology optical domains based on two scenarios, in which multiple control plane instances are orchestrated by the architecture. Congestion Detection and Failure Recovery, are chosen to demonstrate fast recalculation and reconfiguration, while hiding the configurations in the physical layer from the upper layer.Grant numbers : supported by the Spanish Ministry of Economy and Competitiveness through the project FARO (TEC2012-38119)

Design and implementation of the OFELIA FP7 facility: The European OpenFlow testbed

The growth of the Internet in terms of number of devices, the number of networks associated to each device and the mobility of devices and users makes the operation and management of the Internet network infrastructure a very complex challenge. In order to address this challenge, innovative solutions and ideas must be tested and evaluated in real network environments and not only based on simulations or laboratory setups. OFELIA is an European FP7 project and its main objective is to address the aforementioned challenge by building and operating a multi-layer, multi-technology and geographically distributed Future Internet testbed facility, where the network itself is precisely controlled and programmed by the experimenter using the emerging OpenFlow technology. This paper reports on the work done during the first half of the project, the lessons learned as well as the key advantages of the OFELIA facility for developing and testing new networking ideas. An overview on the challenges that have been faced on the design and implementation of the testbed facility is described, including the OFELIA Control Framework testbed management software. In addition, early operational experience of the facility since it was opened to the general public, providing five different testbeds or islands, is described

Yersinia enterocolitica Targets Cells of the Innate and Adaptive Immune System by Injection of Yops in a Mouse Infection Model

Yersinia enterocolitica (Ye) evades the immune system of the host by injection of Yersinia outer proteins (Yops) via a type three secretion system into host cells. In this study, a reporter system comprising a YopE-β-lactamase hybrid protein and a fluorescent staining sensitive to β-lactamase cleavage was used to track Yop injection in cell culture and in an experimental Ye mouse infection model. Experiments with GD25, GD25-β1A, and HeLa cells demonstrated that β1-integrins and RhoGTPases play a role for Yop injection. As demonstrated by infection of splenocyte suspensions in vitro, injection of Yops appears to occur randomly into all types of leukocytes. In contrast, upon infection of mice, Yop injection was detected in 13% of F4/80+, 11% of CD11c+, 7% of CD49b+, 5% of Gr1+ cells, 2.3% of CD19+, and 2.6% of CD3+ cells. Taking the different abundance of these cell types in the spleen into account, the highest total number of Yop-injected cells represents B cells, particularly CD19+CD21+CD23+ follicular B cells, followed by neutrophils, dendritic cells, and macrophages, suggesting a distinct cellular tropism of Ye. Yop-injected B cells displayed a significantly increased expression of CD69 compared to non-Yop-injected B cells, indicating activation of these cells by Ye. Infection of IFN-γR (receptor)- and TNFRp55-deficient mice resulted in increased numbers of Yop-injected spleen cells for yet unknown reasons. The YopE-β-lactamase hybrid protein reporter system provides new insights into the modulation of host cell and immune responses by Ye Yops

Evolutionary Toxicology: Population-Level Effects of Chronic Contaminant Exposure on the Marsh Frogs (Rana ridibunda) of Azerbaijan

We used molecular methods and population genetic analyses to study the effects of chronic contaminant exposure in marsh frogs from Sumgayit, Azerbaijan. Marsh frogs inhabiting wetlands in Sumgayit are exposed to complex mixtures of chemical contaminants, including petroleum products, pesticides, heavy metals, and many other industrial chemicals. Previous results documented elevated estimates of genetic damage in marsh frogs from the two most heavily contaminated sites. Based on mitochondrial DNA (mtDNA) control region sequence data, the Sumgayit region has reduced levels of genetic diversity, likely due to environmental degradation. The Sumgayit region also acts as an ecological sink, with levels of gene flow into the region exceeding gene flow out of the region. Additionally, localized mtDNA heteroplasmy and diversity patterns suggest that one of the most severely contaminated sites in Sumgayit is acting as a source of new mutations resulting from an increased mutation rate. This study provides an integrated method for assessing the cumulative population impacts of chronic contaminant exposure by studying both population genetic and evolutionary effects

Immune Evasion by Yersinia enterocolitica: Differential Targeting of Dendritic Cell Subpopulations In Vivo

CD4+ T cells are essential for the control of Yersinia enterocolitica (Ye) infection in mice. Ye can inhibit dendritic cell (DC) antigen uptake and degradation, maturation and subsequently T-cell activation in vitro. Here we investigated the effects of Ye infection on splenic DCs and T-cell proliferation in an experimental mouse infection model. We found that OVA-specific CD4+ T cells had a reduced potential to proliferate when stimulated with OVA after infection with Ye compared to control mice. Additionally, proliferation of OVA-specific CD4+ T cells was markedly reduced when cultured with splenic CD8α+ DCs from Ye infected mice in the presence of OVA. In contrast, T-cell proliferation was not impaired in cultures with CD4+ or CD4−CD8α− DCs isolated from Ye infected mice. However, OVA uptake and degradation as well as cytokine production were impaired in CD8α+ DCs, but not in CD4+ and CD4−CD8α− DCs after Ye infection. Pathogenicity factors (Yops) from Ye were most frequently injected into CD8α+ DCs, resulting in less MHC class II and CD86 expression than on non-injected CD8α+ DCs. Three days post infection with Ye the number of splenic CD8α+ and CD4+ DCs was reduced by 50% and 90%, respectively. The decreased number of DC subsets, which was dependent on TLR4 and TRIF signaling, was the result of a faster proliferation and suppressed de novo DC generation. Together, we show that Ye infection negatively regulates the stimulatory capacity of some but not all splenic DC subpopulations in vivo. This leads to differential antigen uptake and degradation, cytokine production, cell loss, and cell death rates in various DC subpopulations. The data suggest that these effects might be caused directly by injection of Yops into DCs and indirectly by affecting the homeostasis of CD4+ and CD8α+ DCs. These events may contribute to reduced T-cell proliferation and immune evasion of Ye