E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, Iowa Department of Corrections, July 2003

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, January 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

Cognitive features in euthymic bipolar patients in old age.

OBJECTIVES: Studies of cognition in bipolar disorder (BD) have reported impairments in processing speed, working memory, episodic memory, and executive function, but they have primarily focused on young and middle-aged adults. In such studies, the severity of cognitive deficits increases with the duration of illness. Therefore, one would expect more pronounced deficits in patients with longstanding BD. The first aim of the present study was to determine the pattern and the magnitude of cognitive impairment in older euthymic BD patients. The second aim was to explore the interrelationship between these cognitive deficits and determine whether they reflect a single core impairment or the co-occurrence of independent cognitive deficits. METHODS: Twenty-two euthymic elderly BD patients and 22 controls, matched for gender, age, and education, underwent a comprehensive neuropsychological assessment. RESULTS: Compared to controls, BD patients had significantly reduced performance in processing speed, working memory, verbal fluency, and episodic memory, but not in executive function. Hierarchical regression analyses showed that verbal fluency and working memory impairments were fully mediated by changes in processing speed. This was not the case for the episodic memory dysfunction. CONCLUSION: The cognitive profile in older euthymic BD cases is similar to the one described in younger BD cohorts. Our results further suggest that impaired processing speed plays a major role in the cognitive changes observed in BD patients except for deficits in episodic memory, thus providing strong evidence that processing speed and episodic memory are two core deficits in elderly BD patients.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, January 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-7 Statistical Report On FIP Applications And Cases Discontinued, January 2004

Monthly statistical report on FIP by the Iowa Department of Human Services

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, February 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, February 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-7 Statistical Report On FIP Applications And Cases Discontinued, February 2004

Monthly statistical report on FIP by Iowa Department of Human Services

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, March 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

A-1 Monthly Public Assistance Statistical Report Family Investment Program, March 2004

Monthly Public Assistance Statistical Report Family Investment Program

A-7 Statistical Report On FIP Applications And Cases Discontinued, March 2004

Monthly statistical report on FIP by Iowa Department of Human Services

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, April 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

A-7 Statistical Report On FIP Applications And Cases Discontinued, May 2004

Monthly statistical report on FIP by the Iowa Department of Human Services