Intermarriage and immigrant employment: the role of networks

The social integration of immigrants is believed to be an important determinant of immigrants’ labor market outcomes. Using 2000 U.S. Census data, we examine how and why marriage to a native, one measure of social assimilation, affects immigrant employment rates. We show that even when controlling for a variety of human capital and assimilation measures, marriage to a native increases the probability that an immigrant is employed. An instrumental variables approach which exploits variation in marriage market conditions suggests that the relationship between marriage decisions and employment rates is not likely to arise from positive selection into marrying a native. We then present several pieces of evidence suggesting that networks obtained through marriage play an important part in explaining this effect

I’ll marry you if you get me a job: cross-nativity marriages and immigrant employment rates

This paper tests whether marriage to a native affects the probability that an immigrant is employed. We provide a theoretical background which explains how marriage to a native may positively or negatively affect an immigrant’s employment probability. Utilizing the 2000 U.S. Census, we first look at the effect of cross-nativity marriages on employment using a linear probability model. Then, we estimate a two stage least squares model instrumenting for cross-nativity marriages using local marriage market conditions. Results from a linear probability model controlling for the usual measures of human capital and immigrant assimilation suggest that marriage to a native increases the employment probability of an immigrant by approximately 5 percentage points. When controlling for the endogeneity of the intermarriage decision, marriage to a native increases the employment probability by about 11 percentage points. We provide alternative explanations and suggest policy implications

Interethnic marriage decisions: a choice between ethnic and educational similarities

This paper examines the effect of education on intermarriage and specifically, whether the mechanisms through which education affects intermarriage differ by immigrant generation and race. We consider three main paths through which education affects marriage choice. First, educated people may be better able to adapt to different customs and cultures making them more likely to marry outside of their ethnicity. Second, because the educated are less likely to reside in ethnic enclaves, meeting potential spouses of the same ethnicity may involve higher search costs. Lastly, if spouse-searchers value similarities in education as well as ethnicity, then they may be willing to substitute similarities in education for ethnicity when evaluating spouses. Thus, the effect of education will depend on the availability of same-ethnicity potential spouses with a similar level of education. Using U.S. Census data, we find evidence for all three effects for the population in general. However, assortative matching on education seems to be relatively more important for the native born, for the foreign born that arrived at a fairly young age, and for Asians. We conclude by providing additional pieces of evidence suggestive of our hypotheses

Custom architecture for multicore audio Beamforming systems

The audio Beamforming (BF) technique utilizes microphone arrays to extract acoustic sources recorded in a noisy environment. In this article, we propose a new approach for rapid development of multicore BF systems. Research on literature reveals that the majority of such experimental and commercial audio systems are based on desktop PCs, due to their high-level programming support and potential of rapid system development. However, these approaches introduce performance bottlenecks, excessive power consumption, and increased overall cost. Systems based on DSPs require very low power, but their performance is still limited. Custom hardware solutions alleviate the aforementioned drawbacks, however, designers primarily focus on performance optimization without providing a high-level interface for system control and test. In order to address the aforementioned problems, we propose a custom platform-independent architecture for reconfigurable audio BF systems. To evaluate our proposal, we implement our architecture as a heterogeneous multicore reconfigurable processor and map it onto FPGAs. Our approach combines the software flexibility of General-Purpose Processors (GPPs) with the computational power of multicore platforms. In order to evaluate our system we compare it against a BF software application implemented to a low-power Atom 330, amiddle-ranged Core2 Duo, and a high-end Core i3. Experimental results suggest that our proposed solution can extract up to 16 audio sources in real time under a 16-microphone setup. In contrast, under the same setup, the Atom 330 cannot extract any audio sources in real time, while the Core2 Duo and the Core i3 can process in real time only up to 4 and 6 sources respectively. Furthermore, a Virtex4-based BF system consumes more than an order less energy compared to the aforementioned GPP-based approaches. © 2013 ACM

Multiscale analysis of re-entrant production lines: An equation-free approach

The computer-assisted modeling of re-entrant production lines, and, in particular, simulation scalability, is attracting a lot of attention due to the importance of such lines in semiconductor manufacturing. Re-entrant flows lead to competition for processing capacity among the items produced, which significantly impacts their throughput time (TPT). Such production models naturally exhibit two time scales: a short one, characteristic of single items processed through individual machines, and a longer one, characteristic of the response time of the entire factory. Coarse-grained partial differential equations for the spatio-temporal evolution of a "phase density" were obtained through a kinetic theory approach in Armbruster et al. [2]. We take advantage of the time scale separation to directly solve such coarse-grained equations, even when we cannot derive them explicitly, through an equation-free computational approach. Short bursts of appropriately initialized stochastic fine-scale simulation are used to perform coarse projective integration on the phase density. The key step in this process is lifting: the construction of fine-scale, discrete realizations consistent with a given coarse-grained phase density field. We achieve this through computational evaluation of conditional distributions of a "phase velocity" at the limit of large item influxes.Comment: 14 pages, 17 figure

dReDBox: Materializing a full-stack rack-scale system prototype of a next-generation disaggregated datacenter

Current datacenters are based on server machines, whose mainboard and hardware components form the baseline, monolithic building block that the rest of the system software, middleware and application stack are built upon. This leads to the following limitations: (a) resource proportionality of a multi-tray system is bounded by the basic building block (mainboard), (b) resource allocation to processes or virtual machines (VMs) is bounded by the available resources within the boundary of the mainboard, leading to spare resource fragmentation and inefficiencies, and (c) upgrades must be applied to each and every server even when only a specific component needs to be upgraded. The dRedBox project (Disaggregated Recursive Datacentre-in-a-Box) addresses the above limitations, and proposes the next generation, low-power, across form-factor datacenters, departing from the paradigm of the mainboard-as-a-unit and enabling the creation of function-block-as-a-unit. Hardware-level disaggregation and software-defined wiring of resources is supported by a full-fledged Type-1 hypervisor that can execute commodity virtual machines, which communicate over a low-latency and high-throughput software-defined optical network. To evaluate its novel approach, dRedBox will demonstrate application execution in the domains of network functions virtualization, infrastructure analytics, and real-time video surveillance.This work has been supported in part by EU H2020 ICTproject dRedBox, contract #687632.Peer ReviewedPostprint (author's final draft

Data Quality Assessment and Anomaly Detection Via Map / Reduce and Linked Data: A Case Study in the Medical Domain

Recent technological advances in modern healthcare have lead to the ability to collect a vast wealth of patient monitoring data. This data can be utilised for patient diagnosis but it also holds the potential for use within medical research. However, these datasets often contain errors which limit their value to medical research, with one study finding error rates ranging from 2.3%???26.9% in a selection of medical databases. Previous methods for automatically assessing data quality normally rely on threshold rules, which are often unable to correctly identify errors, as further complex domain knowledge is required. To combat this, a semantic web based framework has previously been developed to assess the quality of medical data. However, early work, based solely on traditional semantic web technologies, revealed they are either unable or inefficient at scaling to the vast volumes of medical data. In this paper we present a new method for storing and querying medical RDF datasets using Hadoop Map / Reduce. This approach exploits the inherent parallelism found within RDF datasets and queries, allowing us to scale with both dataset and system size. Unlike previous solutions, this framework uses highly optimised (SPARQL) joining strategies, intelligent data caching and the use of a super-query to enable the completion of eight distinct SPARQL lookups, comprising over eighty distinct joins, in only two Map / Reduce iterations. Results are presented comparing both the Jena and a previous Hadoop implementation demonstrating the superior performance of the new methodology. The new method is shown to be five times faster than Jena and twice as fast as the previous approach

On interconnecting and orchestrating components in disaggregated data centers:The dReDBox project vision

Computing systems servers-low-or high-end ones have been traditionally designed and built using a main-board and its hardware components as a 'hard' monolithic building block; this formed the base unit on which the system hardware and software stack design build upon. This hard deployment and management border on compute, memory, network and storage resources is either fixed or quite limited in expandability during design time and in practice remains so throughout machine lifetime as subsystem upgrades are seldomely employed. The impact of this rigidity has well known ramifications in terms of lower system resource utilization, costly upgrade cycles and degraded energy proportionality. In the dReDBox project we take on the challenge of breaking the server boundaries through materialization of the concept of disaggregation. The basic idea of the dReDBox architecture is to use a core of high-speed, low-latency opto-electronic fabric that will bring physically distant components more closely in terms of latency and bandwidth. We envision a powerful software-defined control plane that will match the flexibility of the system to the resource needs of the applications (or VMs) running in the system. Together the hardware, interconnect, and software architectures will enable the creation of a modular, vertically-integrated system that will form a datacenter-in-a-box

A Method for Prostate and Breast Cancer Cell Spheroid Cultures Using Gelatin Methacryloyl-Based Hydrogels.

Modern tissue engineering technologies have delivered tools to recreate a cell's naturally occurring niche in vitro and to investigate normal and pathological cell-cell and cell-niche interactions. Hydrogel biomaterials mimic crucial properties of native extracellular matrices, including mechanical support, cell adhesion sites and proteolytic degradability. As such, they are applied as 3D cell culture platforms to replicate tissue-like architectures observed in vivo, allowing physiologically relevant cell behaviors. Here we review bioengineered 3D approaches used for prostate and breast cancer. Furthermore, we describe the synthesis and use of gelatin methacryloyl-based hydrogels as in vitro 3D cancer model. This platform is used to engineer the microenvironments for prostate and breast cancer cells to study processes regulating spheroid formation, cell functions and responses to therapeutic compounds. Collectively, these bioengineered 3D approaches provide cell biologists with innovative pre-clinical tools that integrate the complexity of the disease seen in patients to advance our knowledge of cancer cell physiology and the contribution of a tumor's surrounding milieu