U.S. Teenage Pregnancies, Births, and Abortions, 2010: National and State Trends by Age, Race, and Ethnicity

This report contains the most recent and comprehensive statistics available -- for 2010 -- on the incidence of teenage pregnancy, birth and abortion for the United States as a whole and for individual states. At the national level, we show trends since 1972. For states, we present trends since 1988. The report concludes with a discussion of the methodology and sources used to obtain the estimates. Our previously published statistics for national- and state-level estimates through 2008 were published in two separate reports.Counts of pregnancies include births, abortions, miscarriage and stillbirths. The National Center for Health Statistics (NCHS) provides annual counts of teen births in the United States, as reported in the National Vital Statistics System (via birth certificates).The estimates we present for 2010 are part of the Guttmacher Institute's ongoing surveillance of teen pregnancy in the United States. Our national- and state-level teen pregnancy report is generally updated every two years and contains the only available estimates of teen pregnancy for all 50 states using counts of abortions from the Guttmacher Institute's periodic national census of abortion providers. This census is widely recognized as the most accurate count of abortions performed annually in the United States. Through a collaborative agreement with NCHS, we also provide abortion data for the calculation of teen pregnancy rates at the national level for use in NCHS vital statistics reports. A demographic rate is defined as the number of events (in this case, pregnancies, births or abortions) divided by the number of individuals who could experience the event -- the "population." The pregnancy rate is composed of the rates of pregnancy outcomes (births, abortions and miscarriages) and is not synonymous with the birthrate. Trends in rates of births, abortions and pregnancies can move in different directions and may be affected by different social and economic factors. Unless otherwise indicated, in this report, the words "teenagers" and "teens" refer to women aged 15 -- 19. The report also includes numbers, and in some cases rates, shown separately for women aged 14 and younger, 15 -- 17-year-olds, 18 -- 19-year-olds and all women younger than 20. We also present statistics by race and ethnicity when the data are sufficient to provide these estimates

"A man without a job is a dead man": The meaning of work and welfare in the lives of young men

Little is known about the use of welfare by young men; most research and debate have concentrated on the use of welfare by families headed by single women. The present research includes young men in the debate by examining the personal characteristics, backgrounds, and reasons for use of young men who participated in a General Assistance (GA) program. It explores the events that precipated their use, why they exited, and the barriers they faced in obtaining employment. Data are from qualitative interviews of 20 young men who resided in Madison, Wisconsin. A majority of respondents came from disadvantaged backgrounds, and more than half had been raised in a single-parent family. Fourteen of the 20 respondents had some involvement in the criminal justice system while they were adolescents; thirteen were fathers, only one of whom was married to the mother; eleven had been homeless, nine had a parent who had received AFDC; and six had neither a high school diploma nor a GED. Findings suggest that these young men use GA as a type of unemployment insurance between jobs. The average length of use for men in this sample was 7.5 months, and about half the men used GA more than once. This research makes clear the importance of assistance in improving the level of human capital and locating and retaining employment for poor men and suggests areas for future research.

Resolving single molecule structures with Nitrogen-vacancy centers in diamond.

We present theoretical proposals for two-dimensional nuclear magnetic resonance spectroscopy protocols based on Nitrogen-vacancy (NV) centers in diamond that are strongly coupled to the target nuclei. Continuous microwave and radio-frequency driving fields together with magnetic field gradients achieve Hartmann-Hahn resonances between NV spin sensor and selected nuclei for control of nuclear spins and subsequent measurement of their polarization dynamics. The strong coupling between the NV sensor and the nuclei facilitates coherence control of nuclear spins and relaxes the requirement of nuclear spin polarization to achieve strong signals and therefore reduced measurement times. Additionally, we employ a singular value thresholding matrix completion algorithm to further reduce the amount of data required to permit the identification of key features in the spectra of strongly sub-sampled data. We illustrate the potential of this combined approach by applying the protocol to a shallowly implanted NV center addressing a small amino acid, alanine, to target specific hydrogen nuclei and to identify the corresponding peaks in their spectra

Point-of-care testing for disasters: needs assessment, strategic planning, and future design.

Objective evidence-based national surveys serve as a first step in identifying suitable point-of-care device designs, effective test clusters, and environmental operating conditions. Preliminary survey results show the need for point-of-care testing (POCT) devices using test clusters that specifically detect pathogens found in disaster scenarios. Hurricane Katrina, the tsunami in southeast Asia, and the current influenza pandemic (H1N1, "swine flu") vividly illustrate lack of national and global preparedness. Gap analysis of current POCT devices versus survey results reveals how POCT needs can be fulfilled. Future thinking will help avoid the worst consequences of disasters on the horizon, such as extensively drug-resistant tuberculosis and pandemic influenzas. A global effort must be made to improve POC technologies to rapidly diagnose and treat patients to improve triaging, on-site decision making, and, ultimately, economic and medical outcomes

Kaluza-Klein Towers in the Early Universe: Phase Transitions, Relic Abundances, and Applications to Axion Cosmology

We study the early-universe cosmology of a Kaluza-Klein (KK) tower of scalar fields in the presence of a mass-generating phase transition, focusing on the time-development of the total tower energy density (or relic abundance) as well as its distribution across the different KK modes. We find that both of these features are extremely sensitive to the details of the phase transition and can behave in a variety of ways significant for late-time cosmology. In particular, we find that the interplay between the temporal properties of the phase transition and the mixing it generates are responsible for both enhancements and suppressions in the late-time abundances, sometimes by many orders of magnitude. We map out the complete model parameter space and determine where traditional analytical approximations are valid and where they fail. In the latter cases we also provide new analytical approximations which successfully model our results. Finally, we apply this machinery to the example of an axion-like field in the bulk, mapping these phenomena over an enlarged axion parameter space that extends beyond those accessible to standard treatments. An important by-product of our analysis is the development of an alternate "UV-based" effective truncation of KK theories which has a number of interesting theoretical properties that distinguish it from the more traditional "IR-based" truncation typically used in the extra-dimension literature.Comment: 30 pages, LaTeX, 18 figures. Replaced to match published versio

Applying Neural Networks for Tire Pressure Monitoring Systems

A proof-of-concept indirect tire-pressure monitoring system is developed using neural net- works to identify the tire pressure of a vehicle tire. A quarter-car model was developed with Matlab and Simulink to generate simulated accelerometer output data. Simulation data are used to train and evaluate a recurrent neural network with long short-term memory blocks (RNN-LSTM) and a convolutional neural network (CNN) developed in Python with Tensorflow. Bayesian Optimization via SigOpt was used to optimize training and model parameters. The predictive accuracy and training speed of the two models with various parameters are compared. Finally, future work and improvements are discussed

Dynamically generated multi-modal application interfaces

This work introduces a new UIMS (User Interface Management System), which aims to solve numerous problems in the field of user-interface development arising from hard-coded use of user interface toolkits. The presented solution is a concrete system architecture based on the abstract ARCH model consisting of an interface abstraction-layer, a dialog definition language called GIML (Generalized Interface Markup Language) and pluggable interface rendering modules. These components form an interface toolkit called GITK (Generalized Interface ToolKit). With the aid of GITK (Generalized Interface ToolKit) one can build an application, without explicitly creating a concrete end-user interface. At runtime GITK can create these interfaces as needed from the abstract specification and run them. Thereby GITK is equipping one application with many interfaces, even kinds of interfaces that did not exist when the application was written. It should be noted that this work will concentrate on providing the base infrastructure for adaptive/adaptable system, and does not aim to deliver a complete solution. This work shows that the proposed solution is a fundamental concept needed to create interfaces for everyone, which can be used everywhere and at any time. This text further discusses the impact of such technology for users and on the various aspects of software systems and their development. The targeted main audience of this work are software developers or people with strong interest in software development