Opportunity Road: The Promise and Challenge of America's Forgotten Youth

There are millions of youth ages 16 to 24 who are out of school and out of work. They cost the nation billions of dollars every year and over their lifetimes in lost productivity and increased social services. They also represent an opportunity for the nation to tap the talents of millions of potential leaders and productive workers at a time when America's skills gap is significant. The central message of this report is that while these youth face significant life challenges, most start out with big dreams and remain confident or hopeful that they can achieve their goals; most accept responsibility for their futures; and most are looking to reconnect to school, work and service. They point the way to how they can effectively reconnect to education, productive work and civic life. On behalf of Civic Enterprises and the America's Promise Alliance, Peter D. Hart Research Associates undertook a national cross-section of opportunity youth in 23 diverse locations across the United States in August 2011 to learn about common elements in their personal histories and their lives today, and to explore opportunities to reconnect them to work and school. At the time of the survey, respondents were ages 16 to 24, neither enrolled in school nor planning to enroll in the coming year, were not working, and had not completed a college degree. In addition, they were not disabled such as to prevent long-term employment, were not incarcerated, and were not a stay-at-home parent with a working spouse. What the authors found was both heartbreaking and uplifting, frustrating and hopeful. Despite many growing up in trying circumstances of little economic means and weak family and social supports, the youth they surveyed were optimistic about their futures. More than half believed they would graduate college when they were growing up and their hopes remain high that they will achieve the American Dream with a strong family life of their own and a good job one day. For this reason, the authors believe they are truly "opportunity youth"--both for their belief in themselves that must be nurtured and for the opportunity they hold for America

Hybrid Neural Networks for Frequency Estimation of Unevenly Sampled Data

In this paper we present a hybrid system composed by a neural network based estimator system and genetic algorithms. It uses an unsupervised Hebbian nonlinear neural algorithm to extract the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. We generalize this method to avoid an interpolation preprocessing step and to improve the performance by using a new stop criterion to avoid overfitting. Furthermore, genetic algorithms are used to optimize the neural net weight initialization. The experimental results are obtained comparing our methodology with the others known in literature on a Cepheid star light curve.Comment: 5 pages, to appear in the proceedings of IJCNN 99, IEEE Press, 199

Modeling Dynamical Dark Energy

Cosmological models with different types of Dark Energy are becoming viable alternatives for standard models with the cosmological constant. Yet, such models are more difficult to analyze and to simulate. We present analytical approximations and discuss ways of making simulations for two families of models, which cover a wide range of possibilities and include models with both slow and fast changing ratio w=p\rho. More specifically, we give analytical expressions for the evolution of the matter density parameter Omega_m(z) and the virial density contrast Delta_c at any redshift z. The latter is used to identify halos and to find their virial masses. We also provide an approximation for the linear growth factor of linear fluctuations between redshift z=40 and z=0. This is needed to set the normalization of the spectrum of fluctuations. Finally, we discuss the expected behavior of the halo mass function and its time evolution.Comment: 10 pages, 10 figures ApJ submitte

Electrochemical Studies Involving CO2 Reduction with Rhenium-based Catalysts and for Guanosine Monophosphate Oxidation

The following chapter of this thesis will cover the oxidation of guanine monophosphate (GMP). GMP has been linked to numerous conditions when it is oxidized or damaged. There have been two oxidation pathways suggested in association to the oxidation of GMP: EPT and MS-EPT. The ideal conditions for GMP’s oxidation is still be studied and collected. The study focuses on the acetate versus phosphate buffer, varying base concentration in phosphate buffer, and the varying concentration of ruthenium complex, a redox mediator

Anisotropy-based mechanism for zigzag striped patterns in magnetic thin films

In this work we studied a two dimensional ferromagnetic system using Monte Carlo simulations. Our model includes exchange and dipolar interactions, a cubic anisotropy term, and uniaxial out-of-plane and in-plane ones. According to the set of parameters chosen, the model including uniaxial out-of-plane anisotropy has a ground-state which consists of a canted state with stripes of opposite out-of-plane magnetization. When the cubic anisotropy is introduced zigzag patterns appear in the stripes at fields close to the remanence. An analysis of the anisotropy terms of the model shows that this configuration is related to specific values of the ratio between the cubic and the effective uniaxial anisotropy. The mechanism behind this effect is related to particular features of the anisotropy's energy landscape, since a global minima transition as a function of the applied field is required in the anisotropy terms. This new mechanism for zigzags formation could be present in monocrystal ferromagnetic thin films in a given range of thicknesses.Comment: 910 pages, 10 figure

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IIR Adaptive Filters for Detection of Gravitational Waves from Coalescing Binaries

In this paper we propose a new strategy for gravitational waves detection from coalescing binaries, using IIR Adaptive Line Enhancer (ALE) filters. This strategy is a classical hierarchical strategy in which the ALE filters have the role of triggers, used to select data chunks which may contain gravitational events, to be further analyzed with more refined optimal techniques, like the the classical Matched Filter Technique. After a direct comparison of the performances of ALE filters with the Wiener-Komolgoroff optimum filters (matched filters), necessary to discuss their performance and to evaluate the statistical limitation in their use as triggers, we performed a series of tests, demonstrating that these filters are quite promising both for the relatively small computational power needed and for the robustness of the algorithms used. The performed tests have shown a weak point of ALE filters, that we fixed by introducing a further strategy, based on a dynamic bank of ALE filters, running simultaneously, but started after fixed delay times. The results of this global trigger strategy seems to be very promising, and can be already used in the present interferometers, since it has the great advantage of requiring a quite small computational power and can easily run in real-time, in parallel with other data analysis algorithms.Comment: Accepted at SPIE: "Astronomical Telescopes and Instrumentation". 9 pages, 3 figure