Debate over Fair Value Accounting: Should we allow Politics to take an active role in setting accounting standards or should we trust that the SEC knows best?

In light of the recent economic downfall, there has been significant media coverage on the topic of fair value accounting. There are many critics of the accounting rule, who place blame on it for the destruction of billions of dollars in capital between financial institutions. Other commentators, however, see the rule as necessary and applaud its ability to bring the turmoil in the economy into the spotlight promptly so that it could be addressed effectively. This paper will begin by conducting a study of fair-value accounting from its inception in previous standards and then follow it through to Statement No. 157. I will then discuss the SEC’s most recent study of FAS157 and their decision as a result of the study.

Consumer satisfaction with primary care provider choice and associated trust

Trust is important in medical relationships and for the achievement of better health outcomes. Developments in managed care in the recent years are believed to affect the quality of healthcare services delivery and to undermine trust in the healthcare provider. Physician choice has been identified as a strong predictor of provider trust but has not been studied in detail. Consumer satisfaction with primary care provider (PCP) choice includes having or not having physician choice. This dissertation developed a conceptual framework that guided the study of consumer satisfaction with PCP choice as a predictor of provider trust, and conducted secondary data analyses examining the association between PCP choice and trust, by identifying factors related to PCP choice satisfaction, and their relative importance in predicting provider trust. The study specific aims were: (1) to determine variables related to the factors: consumer characteristics and health status, information and consumer decision-making, consumer trust in providers in general and trust in the insurer, health plan financing and plan characteristics, and provider characteristics that may relate to PCP choice satisfaction; (2) to determine if the factors in aim one are related to PCP choice satisfaction; and (3) to analyze the association between PCP choice satisfaction and provider trust, controlling for potential confounders. Analyses were based on secondary data from a random national telephone survey in 1999, of residential households in the United States which included respondents aged over 20 and who had at least two visits with a health professional in the past two years. Among 1,117 eligible households interviewed (response rate 51.4%), 564 randomly selected to respond to insurer related questions made up the study sample. Analyses using descriptive statistics, and linear and logistic regressions found continual effective care and interaction with the PCP beyond the medical setting most predictive of PCP choice satisfaction. Four PCP choice satisfaction factors were also predictive of provider trust. Findings highlighted the importance of the PCP's professional and interpersonal competencies for the development of sustainable provider trust. Future research on the access, utilization, cognition, and helpfulness of provider specific information will further our understanding of consumer choice and trust. ^

Influence of trust on HIV diagnosis and care practices

Many factors have been studied as potential correlates in delayed HIV diagnosis and delayed linkage to HIV healthcare. Few studies have analyzed the association of trust as a correlate in HIV diagnosis and HIV medical treatment delays. This study sought to assess the effect of patient trust in physicians and trust in the healthcare system, and whether diminished levels of trust affect delays in HIV diagnosis and/or linking to HIV healthcare, among a cohort of newly diagnosed HIV-infected persons, in Harris County, Texas.^ This study is a secondary data analysis from the Attitude and Beliefs and the Steps of HIV Care Study, also known as the Steps Study, a prospective observational cohort study. From January 2006 to October 2007 patients newly diagnosed with HIV infection and not yet in HIV primary care were recruited from publically funded HIV testing sites in Houston, Texas.^ Two outcomes were assessed in this study. The first outcome sought to determine the influence of trust and whether decreased levels of trust predicted delays in HIV diagnosis. Trust in physicians and trust in the healthcare system were measured via 2 validated trust scales. Trust scores of those with late diagnosis (CD4 counts <200 cells/mm3) were compared statistically with those with early diagnosis (CD4 counts ≥ 200 cells/mm3) in a cross sectional study design. Trust was not found to be predictive of delays in HIV diagnosis. ^ The second outcome utilized the same trust scales and a prospective cohort study design to assess whether there were differences in trust scores between those who successfully linked to HIV healthcare, compared to those who failed to link to HIV healthcare, within 6 months of diagnosis. Patients with higher trust in physicians and trust in the healthcare system were significantly more likely to be linked to HIV healthcare than those with lower trust.^ Overall, this study showed that among low-income persons with undiagnosed HIV infection, low trust is not a barrier to timely diagnosis of HIV infection. Trust may be a factor in promoting a prompt linkage to HIV healthcare among those who are newly diagnosed.^

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.

Building Trust for Lambda-Congenial Secret Groups

Establishing trust while preserving privacy is a challenging research problem. In this paper we introduce lambda -congenial secret groups which allow users to recognize trusted partners based on common attributes while preserving their anonymity and privacy. Such protocols are different from authentication protocols, since the latter are based on identities, while the former are based on attributes. Introducing attributes in trust establishment allows a greater flexibility but also brings up several issues. In this paper, we investigate the problem of building trust with attributes by presenting motivating examples, analyzing the security requirements and giving an informal definition. We also survey one of the most related techniques, namely private matching, and finally present solutions based on it.

An investigation of the performance of a new Mechanical thrombectomy device using Bond Graph modelling: application to the extraction of blood clots in the middle cerebral artery

A number of thrombectomy devices using a variety of methods have now been developed to facilitate clot removal. We present research involving one such experimental device recently developed in the UK, called a ‘GP’ Thrombus Aspiration Device (GPTAD). This device has the potential to bring about the extraction of a thrombus. Although the device is at a relatively early stage of development, the results look encouraging. In this work, we present an analysis and modeling of the GPTAD by means of the bond graph technique; it seems to be a highly effective method of simulating the device under a variety of conditions. Such modeling is useful in optimizing the GPTAD and predicting the result of clot extraction. The aim of this simulation model is to obtain the minimum pressure necessary to extract the clot and to verify that both the pressure and the time required to complete the clot extraction are realistic for use in clinical situations, and are consistent with any experimentally obtained data. We therefore consider aspects of rheology and mechanics in our modeling.

Uniformly Reweighted Belief Propagation: A Factor Graph Approach

Tree-reweighted belief propagation is a message passing method that has certain advantages compared to traditional belief propagation (BP). However, it fails to outperform BP in a consistent manner, does not lend itself well to distributed implementation, and has not been applied to distributions with higher-order interactions. We propose a method called uniformly-reweighted belief propagation that mitigates these drawbacks. After having shown in previous works that this method can substantially outperform BP in distributed inference with pairwise interaction models, in this paper we extend it to higher-order interactions and apply it to LDPC decoding, leading performance gains over BP.

A graph-based approach for latency modeling and optimization in multiview video encoding

We present a novel framework for encoding latency analysis of arbitrary multiview video coding prediction structures. This framework avoids the need to consider an specific encoder architecture for encoding latency analysis by assuming an unlimited processing capacity on the multiview encoder. Under this assumption, only the influence of the prediction structure and the processing times have to be considered, and the encoding latency is solved systematically by means of a graph model. The results obtained with this model are valid for a multiview encoder with sufficient processing capacity and serve as a lower bound otherwise. Furthermore, with the objective of low latency encoder design with low penalty on rate-distortion performance, the graph model allows us to identify the prediction relationships that add higher encoding latency to the encoder. Experimental results for JMVM prediction structures illustrate how low latency prediction structures with a low rate-distortion penalty can be derived in a systematic manner using the new model.

Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation.

Graph based study of allergen cross-reactivity of plant lipid transfer proteins (LTPs) using microarray in a multicenter study.

The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens.

Time series irreversibility: a visibility graph approach

We propose a method to measure real-valued time series irreversibility which combines two different tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) between the in and out degree distributions of the associated graph. The method is computationally efficient and does not require any ad hoc symbolization process. We find that the method correctly distinguishes between reversible and irreversible stationary time series, including analytical and numerical studies of its performance for: (i) reversible stochastic processes (uncorrelated and Gaussian linearly correlated), (ii) irreversible stochastic processes (a discrete flashing ratchet in an asymmetric potential), (iii) reversible (conservative) and irreversible (dissipative) chaotic maps, and (iv) dissipative chaotic maps in the presence of noise. Two alternative graph functionals, the degree and the degree-degree distributions, can be used as the Kullback-Leibler divergence argument. The former is simpler and more intuitive and can be used as a benchmark, but in the case of an irreversible process with null net current, the degree-degree distribution has to be considered to identify the irreversible nature of the series

Segmentation of RV in 4D Cardiac MR Volumes using region-merging graph cuts

Non-invasive quantitative assessment of the right ventricular anatomical and functional parameters is a challenging task. We present a semi-automatic approach for right ventricle (RV) segmentation from 4D MR images in two variants, which differ in the amount of user interaction. The method consists of three main phases: First, foreground and background markers are generated from the user input. Next, an over-segmented region image is obtained applying a watershed transform. Finally, these regions are merged using 4D graph-cuts with an intensity based boundary term. For the first variant the user outlines the inside of the RV wall in a few end-diastole slices, for the second two marker pixels serve as starting point for a statistical atlas application. Results were obtained by blind evaluation on 16 testing 4D MR volumes. They prove our method to be robust against markers location and place it favourably in the ranks of existing approaches.