Safer Streets: Cutting Repeat Crimes by Juvenile Offenders.

FIGHT CRIME: INVEST IN KIDS is an anti-crime organization led by more than 3,500 law enforcement leaders -- chiefs, sheriffs and prosecutors -- and survivors of crime. Most of the survivors are parents of murdered children. Crime requires punishment. Punishment may be placing a young offender in custody, or, depending on the crime, imposing a range of other tough sanctions. The bottom line is that residents must be safe walking the streets. Research shows, however, that punishment alone will often not be enough; troubled teens will need help to stop their aggression, substance abuse, or other anti-social behaviors. It is usually not too late to change anti-social patterns of behavior. Sanctions that include strict and effective interventions can direct anti-social and dangerous juveniles onto a different path that will make Americans safer

Variedades de arroz para o cultivo de sequeiro no Estado do Pará.

bitstream/item/114591/1/COMUNICADO-TECNICO-15.pdfPublicado também na serie Comunicado Técnico do IPEAN, n. 15 em 1972

Manejo de gliricidia sepium para produção de forragem em sistemas silvipastoris.

O objetivo deste trabalho foi avaliar o efeito da intensidade de pastejo num banco de proteína de G. sepium sobre a produção de materia seca (MS), crescimento de plantas e proteína bruta e digestibilidade da forragem produzida

Harold Jeffreys's Theory of Probability Revisited

Published exactly seventy years ago, Jeffreys's Theory of Probability (1939) has had a unique impact on the Bayesian community and is now considered to be one of the main classics in Bayesian Statistics as well as the initiator of the objective Bayes school. In particular, its advances on the derivation of noninformative priors as well as on the scaling of Bayes factors have had a lasting impact on the field. However, the book reflects the characteristics of the time, especially in terms of mathematical rigor. In this paper we point out the fundamental aspects of this reference work, especially the thorough coverage of testing problems and the construction of both estimation and testing noninformative priors based on functional divergences. Our major aim here is to help modern readers in navigating in this difficult text and in concentrating on passages that are still relevant today.Comment: This paper commented in: [arXiv:1001.2967], [arXiv:1001.2968], [arXiv:1001.2970], [arXiv:1001.2975], [arXiv:1001.2985], [arXiv:1001.3073]. Rejoinder in [arXiv:0909.1008]. Published in at http://dx.doi.org/10.1214/09-STS284 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Cultivares de arroz irrigado capazes de produzir três safras por ano.

bitstream/item/70854/1/IPEAN-Comunicado33.pdfPublicado também na série Comunicado do IPEAN, n.33 em 1972

Resposta do arroz apura, à adubação NPK, sob regime de irrigação natural (várzea do Rio Caeté - município de Bragança-PA).

bitstream/item/114592/1/COMUNICADO-TECNICO-14.pdfPublicado também na serie Comunicado Técnico do IPEAN, n. 14

Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property

The AMP Markov property is a recently proposed alternative Markov property for chain graphs. In the case of continuous variables with a joint multivariate Gaussian distribution, it is the AMP rather than the earlier introduced LWF Markov property that is coherent with data-generation by natural block-recursive regressions. In this paper, we show that maximum likelihood estimates in Gaussian AMP chain graph models can be obtained by combining generalized least squares and iterative proportional fitting to an iterative algorithm. In an appendix, we give useful convergence results for iterative partial maximization algorithms that apply in particular to the described algorithm.Comment: 15 pages, article will appear in Scandinavian Journal of Statistic

An extended phase field higher-order active contour model for networks and its application to road network extraction from VHR satellite images.

This paper addresses the segmentation from an image of entities that have the form of a 'network', i.e. the region in the image corresponding to the entity is composed of branches joining together at junctions, e.g. road or vascular networks. We present a new phase field higher-order active contour (HOAC) prior model for network regions, and apply it to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much 'noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a severe limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly Curved, wide branches. To solve this problem, we propose a new HOAC prior energy term, and reformulate it as a nonlocal phase field energy. We analyse the stability of the new model, and find that in addition to solving the above problem by separating the interactions between points on the same and opposite sides of a network branch, the new model permits the modelling of two widths simultaneously. The analysis also fixes some of the model parameters in terms of network width(s). After adding a likelihood energy, we use the model to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The results demonstrate the superiority of the new model, the importance of strong prior knowledge in general, and of the new term in particular

Variational guidewire tracking using phase congruency

We present a novel method to track a guidewire in cardiac x-ray video. Using variational calculus, we derive differential equations that deform a spline, subject to intrinsic and extrinsic forces, so that it matches the image data, remains smooth, and preserves an a priori length. We analytically derive these equations from first principles, and show how they include tangential terms, which we include in our model. To address the poor contrast often observed in x-ray video, we propose using phase congruency as an image-based feature. Experimental results demonstrate the success of the method in tracking guidewires in low contrast x-ray video