National Foreclosure Mitigation Counseling Program Evaluation: Final Report, Rounds 1 and 2

The National Foreclosure Mitigation Counseling (NFMC) program is a special federal appropriation, administered by NeighborWorks (NW) America, to support a rapid expansion of foreclosure intervention counseling in response to the nationwide foreclosure crisis. As this is a federal appropriation, NW America must inform Congress and other entities of the NFMC program's progress. The Urban Institute (UI) was selected by NW America to evaluate the NFMC program. This report presents the final results from UI's evaluation of the first two rounds of the NFMC program (people receiving counseling in 2008 and 2009), including a detailed analysis of program outcomes first described in preliminary reports of November 2009 (Mayer et al.) and December 2010 (Mayer et al.). According to those reports, homeowners receiving NFMC counseling avoided entering foreclosure, successfully cured existing foreclosures, and obtained more favorable loan modifications. This report updates previous analyses and also includes revised models of several homeowner outcomes for NFMC clients counseled in 2008 and 2009. These new models use an improved comparison sample selection design, which addressed potential issues raised by reviewers of earlier analyses, and a better method for controlling for possible selection bias in the NFMC sample. The additional analyses in this report include models of non-modification cures, non-modification redefaults, and foreclosures avoided

Mind over chatter: plastic up-regulation of the fMRI alertness network by EEG neurofeedback

EEG neurofeedback (NFB) is a brain-computer interface (BCI) approach used to shape brain oscillations by means of real-time feedback from the electroencephalogram (EEG), which is known to reflect neural activity across cortical networks. Although NFB is being evaluated as a novel tool for treating brain disorders, evidence is scarce on the mechanism of its impact on brain function. In this study with 34 healthy participants, we examined whether, during the performance of an attentional auditory oddball task, the functional connectivity strength of distinct fMRI networks would be plastically altered after a 30-min NFB session of alpha-band reduction (n=17) versus a sham-feedback condition (n=17). Our results reveal that compared to sham, NFB induced a specific increase of functional connectivity within the alertness/salience network (dorsal anterior and mid cingulate), which was detectable 30 minutes after termination of training. Crucially, these effects were significantly correlated with reduced mind-wandering 'on-task' and were coupled to NFB-mediated resting state reductions in the alpha-band (8-12 Hz). No such relationships were evident for the sham condition. Although group default-mode network (DMN) connectivity was not significantly altered following NFB, we observed a positive association between modulations of resting alpha amplitude and precuneal connectivity, both correlating positively with frequency of mind-wandering. Our findings demonstrate a temporally direct, plastic impact of NFB on large-scale brain functional networks, and provide promising neurobehavioral evidence supporting its use as a noninvasive tool to modulate brain function in health and disease

National Foreclosure Mitigation Counseling Program Evaluation: Final Report, Rounds 3 Through 5

The Urban Institute completed a four-year evaluation of Rounds 3 through 5 of the National Foreclosure Mitigation Counseling (NFMC) program. Using a representative NFMC sample of 137,000 loans and a comparison non-NFMC sample of 103,000 loans, the Urban Institute was able to employ robust statistical techniques to isolate the impact of NFMC counseling on loan performance through June 2013.The final evaluation of Rounds 3 through 5 conducted by Urban Institute indicates that the NFMC program continues to have positive effects for homeowners participating in the program Counseled homeowners were more likely to cure a serious delinquency or foreclosure with a modification or other type cure, stay current after obtaining a cure, and for NFMC clients who cured a serious delinquency, avoid foreclosure altogether

Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis

Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for disease diagnosis, where discriminating subjects with mild cognitive impairment (MCI) from normal controls (NC) is still one of the most challenging problems. Dynamic functional connectivity (dFC), consisting of time-varying spatiotemporal dynamics, may characterize "chronnectome" diagnostic information for improving MCI classification. However, most of the current dFC studies are based on detecting discrete major brain status via spatial clustering, which ignores rich spatiotemporal dynamics contained in such chronnectome. We propose Deep Chronnectome Learning for exhaustively mining the comprehensive information, especially the hidden higher-level features, i.e., the dFC time series that may add critical diagnostic power for MCI classification. To this end, we devise a new Fully-connected Bidirectional Long Short-Term Memory Network (Full-BiLSTM) to effectively learn the periodic brain status changes using both past and future information for each brief time segment and then fuse them to form the final output. We have applied our method to a rigorously built large-scale multi-site database (i.e., with 164 data from NCs and 330 from MCIs, which can be further augmented by 25 folds). Our method outperforms other state-of-the-art approaches with an accuracy of 73.6% under solid cross-validations. We also made extensive comparisons among multiple variants of LSTM models. The results suggest high feasibility of our method with promising value also for other brain disorder diagnoses.Comment: The paper has been accepted by MICCAI201

Disambiguating the role of blood flow and global signal with partial information decomposition

Global signal (GS) is an ubiquitous construct in resting state functional magnetic resonance imaging (rs-fMRI), associated to nuisance, but containing by definition most of the neuronal signal. Global signal regression (GSR) effectively removes the impact of physiological noise and other artifacts, but at the same time it alters correlational patterns in unpredicted ways. Performing GSR taking into account the underlying physiology (mainly the blood arrival time) has been proven to be beneficial. From these observations we aimed to: 1) characterize the effect of GSR on network-level functional connectivity in a large dataset; 2) assess the complementary role of global signal and vessels; and 3) use the framework of partial information decomposition to further look into the joint dynamics of the global signal and vessels, and their respective influence on the dynamics of cortical areas. We observe that GSR affects intrinsic connectivity networks in the connectome in a non-uniform way. Furthermore, by estimating the predictive information of blood flow and the global signal using partial information decomposition, we observe that both signals are present in different amounts across intrinsic connectivity networks. Simulations showed that differences in blood arrival time can largely explain this phenomenon, while using hemodynamic and calcium mouse recordings we were able to confirm the presence of vascular effects, as calcium recordings lack hemodynamic information. With these results we confirm network-specific effects of GSR and the importance of taking blood flow into account for improving de-noising methods. Additionally, and beyond the mere issue of data denoising, we quantify the diverse and complementary effect of global and vessel BOLD signals on the dynamics of cortical areas

Block Coordinate Descent for Sparse NMF

Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms, such as L$_1$/L$_2$ measure, have been shown to model sparsity robustly, based on intuitive attributes that such measures need to satisfy. This is in contrast to computationally cheaper alternatives such as the plain L$_1$ norm. However, present algorithms designed for optimizing the mixed norm L$_1$/L$_2$ are slow and other formulations for sparse NMF have been proposed such as those based on L$_1$ and L$_0$ norms. Our proposed algorithm allows us to solve the mixed norm sparsity constraints while not sacrificing computation time. We present experimental evidence on real-world datasets that shows our new algorithm performs an order of magnitude faster compared to the current state-of-the-art solvers optimizing the mixed norm and is suitable for large-scale datasets

Joint and individual analysis of breast cancer histologic images and genomic covariates

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genetics. While histopathology is the gold standard for diagnostics and there have been many recent breakthroughs in genetics, there is little overlap between these two fields. We aim to bridge this gap by developing methods based on Angle-based Joint and Individual Variation Explained (AJIVE) to directly explore similarities and differences between these two modalities. Our approach exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction to address some of the challenges presented by statistical analysis of histopathology image data. CNNs raise issues of interpretability that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features. Our results provide many interpretable connections and contrasts between histopathology and genetics

Shale oil : potential economies of large-scale production, preliminary phase

Producing shale oil on a large scale is one of the possible alternatives for reducing dependence of the United States on imported petroleum. Industry is not producing shale oil on a commercial scale now because costs are too high even though industry dissatisfaction is most frequently expressed about "non-economic" barriers: innumerable permits, changing environmental regulations, lease limitations, water rights conflicts, legal challenges, and so on. The overall purpose of this study is to estimate whether improved technology might significantly reduce unit costs for production of shale oil in a planned large-scale industry as contrasted to the case usually contemplated: a small industry evolving slowly on a project-by-project basis. In this preliminary phase of the study, we collected published data on the costs of present shale oil technology and adjusted them to common conditions; these data were assembled to help identify the best targets for cost reduction through improved large-scale technology They show that the total cost of producing upgraded shale oil (i.e. shale oil accpetable as a feed to a petroleum refinery) by surface retorting ranges from about $18 to$28/barrel in late '78 dollars with a 20% chance that the costs would be lower than and 20% higher than that range. The probability distribution reflects our assumptions about ranges of shale richness, process performance, rate of return, and other factors that seem likely in a total industry portfolio of projects. About 40% of the total median cost is attributable to retorting, 20% to upgrading, and the remaining 40% to resource acquisition, mining, crushing, and spent shale disposal and revegetation. Capital charges account for about 70% of the median total cost and operating costs for the other 30%. There is a reasonable chance that modified in-situ processes (like Occidental's) may be able to produce shale oil more cheaply than surface retorting, but no reliable cost data have been published; in 1978, DOE estimated a saving of roughly $5/B for in-situ. Because the total costs of shale oil are spread over many steps in the production process, improvements in most or all of those steps are required if we seek a significant reduction in total cost. A June 1979 workshop of industry experts was held to help us identify possible cost-reduction technologies. Examples of the improved large-scale technologies proposed (for further evaluation) to the workshop were: - Instead of hydrotreating raw shale oil to make syncrude capable of being refined conventionally, rebalance all of a refinery's processes (or develop new catalysts/processes less sensitive to feed nitrogen) to accommodate shale oil feed -- a change analogous to a shift from sweet crude to sour crude. - Instead of refining at or near the retort site, use heated pipelines to move raw shale oil to existing major refining areas. - Instead of operating individual mines, open-pit mine all or much of the Piceance Creek Basin. - Instead of building individual retorts, develop new methods for mass production of hundreds of retorts

Parents, children and the porous boundaries of the sexual family in law and popular culture

This article focuses on a perceived ideological overlap between popular cultural and judicial treatments of sex and conjugality that contributes to a discursive construction of parenthood and parenting. The author perceives that in both legal and popular cultural texts, there is a sense in which notions of ‘natural’ childhood are discursively constituted as being put at risk by those who reproduce outside of dominant sexual norms, and that signs of normative sexuality (typically in the form of heterosexual coupling) may be treated as a sign of safety. These ideas are rooted in ancient associations between fertility, sexuality and femininity that can also be traced in the historical development of the English language. With the help of commentators such as Martha Fineman, the article situates parents and children within a discourse of family which prioritises conjugality, with consequences for the ways in which the internal and external boundaries of families are delineated

Scholar-activists in an expanding European food sovereignty movement

This article analyzes the roles, relations, and positions of scholar-activists in the European food sovereignty movement. In doing so, we document, make visible and question the political dimensions of researchers' participation in the movement. We argue that scholar-activists are part of the movement, but are distinct from the affected constituencies, put in place to ensure adequate representation of key movement actors. This is because scholar-activists lack a collective identity, have no processes to formulate collective demands, and no mechanisms for inter-researcher and researchers-movement communication. We reflect on whether and how scholar-activists could organize, and discuss possible pathways for a more cohesive and stronger researcher engagement in the movement.</p