Retirement Investors' Club Plan Document; Fund Fees Comparison, 2005

The Retirement Investors’ Club (RIC) (also referred to as 457/401(a) deferred compensation) is a voluntary retirement savings program designed to help you meet your need for income at retirement and lower your current income taxes. Your contributions to RIC are automatically withdrawn from your paycheck and you are credited with an employer match. You may enroll*and make changes at any time. Other advantages are explained below…keep reading about this excellent employee benefit!

Employee referrals and efficiency wages

Many workers believe that personal contacts are crucial for obtainingjobs in high-wage sectors. On the other hand, firms in high-wage sectorsreport using employee referrals because they help provide screening andmonitoring of new employees. This paper develops a matching model thatcan explain the link between inter-industry wage differentials and useof employee referrals. Referrals lower monitoring costs because high-effortreferees can exert peer pressure on co-workers, allowing firms to pay lowerefficiency wages. On the other hand, informal search provides fewer job andapplicant contacts than formal methods (e.g., newspaper ads). In equilibrium,the matching process generates segmentation in the labor market becauseof heterogeneity in the size of referral networks. Referrals match good high-paying jobs to well-connected workers, while formal methods matchless attractive jobs to less-connected workers. Industry-level data show apositive correlation between industry wage premia and use of employeereferrals. Moreover, evidence using the NLSY shows similar positive andsignificant OLS and fixed-effects estimates of the returns to employeereferrals, but insignificant effects once sector of employment is controlledfor. This evidence suggests referred workers earn higher wages not becauseof higher unobserved ability or better matches but rather because theyare hired in high-wage sectors.

Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using MP2RAGE.

PURPOSE: To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w) images obtained with the magnetization prepared 2 rapid gradient echoes sequence (MP2RAGE) and to compare the clinical utility of these robust T1w images against the uniform T1w images. MATERIALS AND METHODS: 8 healthy subjects (29.0±4.1 years; 6 Male), who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test. RESULTS: The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004). In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004) from an average volumetric difference across structures of ≈6.6% to ≈2.4% for the uniform image and robust T1w image respectively. CONCLUSIONS: The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages.

Liver segmentation: Practical tips.

The liver segmentation system, described by Couinaud, is based on the identification of the three hepatic veins and the plane passing by the portal vein bifurcation. Nowadays, Couinaud's description is the most widely used classification since it is better suited for surgery and more accurate for the localisation and monitoring of intra-parenchymal lesions. Knowledge of the anatomy of the portal and venous system is therefore essential, as is knowledge of the variants resulting from changes occurring during the embryological development of the vitelline and umbilical veins. In this paper, the authors propose a straightforward systematisation of the liver in six steps using several additional anatomical points of reference. These points of reference are simple and quickly identifiable in any radiological examination with section imaging, in order to avoid any mistakes in daily practice. In fact, accurate description impacts on many diagnostic and therapeutic applications in interventional radiology and surgery. This description will allow better preparation for biopsy, portal vein embolisation, transjugular intrahepatic portosystemic shunt, tumour resection or partial hepatectomy for transplantation. Such advance planning will reduce intra- and postoperative difficulties and complications.

Patentes, regulación de precios e innovación en la industria farmacéutica

The trade-off between property rights/price regulation and innovation depends on countrycharacteristics and drug industry specificities. Access to drugs and innovation can bereconciled by seven ways that, among others, include: public health strengthening in thecountries with the largest access problems (those among the poor with the weakestinstitutions); public and private aid to make attractive R&D on neglected diseases; pricediscrimination with market segmentation; to require patent owners to choose eitherprotection in the rich countries or protection in the poor countries (but not both).Regarding price regulation, after a review of theoretical arguments and empirical evidence,seven strategies to reconcile health and industrial considerations are outlined, including:mitigation of the medical profession dependence on the pharmaceutical industry; considerationof a drug as an input of a production process; split drug authorization from public fundingdecisions; establish an efficiency minimum for all health production inputs; and stop theEuropean R&D hemorrhagia.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

Impacte d'un programa d'informació sobre l'elaboració del document de voluntats anticipades

Tot i que en el nostre territori comptem des de els anys 80 amb diferents models de Document de Voluntats Anticipades (DVA), aquests continuen essent desconeguts tant per la ciutadania com pels professionals de la salut. Aquesta situació ha fet que ens plantegem com a objectiu d’aquest estudi descriure si existeix la correlació entre el fet de proporcionar informació sobre el DVA i la motivació per la seva realització. En aquest estudi hem agafat com a mostra els usuaris del servei de psicogeriatria de la Fundació Sociosanitaria de Manresa l’Hospital de Sant Andreu de Manresa, tenint en compte les recomanacions del Document Sitges del 2005 i d’altres autors que recomanen fer el DVA en situació de demència lleu o moderada. També s’ha tingut present l’elevada prevalença d’aquesta patologia. S'ha dissenyat un assaig clínic comunitari amb aleatorització de dos consultoris d'un servei de psicogeriatria. Els metges del consultori assignat al grup control feien el tractament habitual en relació al DVA, és a dir, no informar els pacients atesos sobre l'existència i característiques del DVA, i els metges del consultori assignat al grup intervenció donaven informació reglada als seus pacients sobre el DVA. En el moment de la inclusió es registrava informació sociodemogràfica i clínica per poder classificar els participants i, també a tots els subjectes inclosos en l'assaig, al cap de tres setmanes se'ls feia una enquesta telefònica per avaluar l'opinió i el coneixement sobre el DVA. De les respostes de l’enquesta podem extreure com a resultats que més del 90% dels subjectes del grup control no coneixen el DVA. També s’observa de manera significativa com les persones del grup intervenció parlen amb el metge,la infermera i/o la família sobre la dependència i la mort, tenint en compte que la mort i la dependència continuen sent un tema tabú, i que la majoria de la població de l’estudi no planifiquen com volen ser atesos. Tanmateix s’observa com un 2’3 % tenia fet el DVA i un 22’7% manifesten la seva voluntat de realitzar-lo. Amb aquest estudi es conclou que el fet de proporcionar informació sobre el DVA als usuaris del servei de psicogeriatria afavoreix que aquests estiguin motivats per la realització d’aquest document; al mateix temps també afavoreix la planificació de les cures i el parlar sobres temes com la mort i/o la dependència amb la família, el metge la infermera.

Reconeixement de gestos de la mà amb el sensor Kinect

El reconeixement dels gestos de la mà (HGR, Hand Gesture Recognition) és actualment un camp important de recerca degut a la varietat de situacions en les quals és necessari comunicar-se mitjançant signes, com pot ser la comunicació entre persones que utilitzen la llengua de signes i les que no. En aquest projecte es presenta un mètode de reconeixement de gestos de la mà a temps real utilitzant el sensor Kinect per Microsoft Xbox, implementat en un entorn Linux (Ubuntu) amb llenguatge de programació Python i utilitzant la llibreria de visió artifical OpenCV per a processar les dades sobre un ordinador portàtil convencional. Gràcies a la capacitat del sensor Kinect de capturar dades de profunditat d’una escena es poden determinar les posicions i trajectòries dels objectes en 3 dimensions, el que implica poder realitzar una anàlisi complerta a temps real d’una imatge o d’una seqüencia d’imatges. El procediment de reconeixement que es planteja es basa en la segmentació de la imatge per poder treballar únicament amb la mà, en la detecció dels contorns, per després obtenir l’envolupant convexa i els defectes convexos, que finalment han de servir per determinar el nombre de dits i concloure en la interpretació del gest; el resultat final és la transcripció del seu significat en una finestra que serveix d’interfície amb l’interlocutor. L’aplicació permet reconèixer els números del 0 al 5, ja que s’analitza únicament una mà, alguns gestos populars i algunes de les lletres de l’alfabet dactilològic de la llengua de signes catalana. El projecte és doncs, la porta d’entrada al camp del reconeixement de gestos i la base d’un futur sistema de reconeixement de la llengua de signes capaç de transcriure tant els signes dinàmics com l’alfabet dactilològic.

Labor market heterogeneity and the aggregate matching function

The matching function -a key building block in models of labor market frictions- impliesthat the job finding rate depends only on labor market tightness. We estimate such amatching function and find that the relation, although remarkably stable over 1967-2007,broke down spectacularly after 2007. We argue that labor market heterogeneities are notfully captured by the standard matching function, but that a generalized matching functionthat explicitly takes into account worker heterogeneity and market segmentation is fullyconsistent with the behavior of the job finding rate. The standard matching function canbreak down when, as in the Great Recession, the average characteristics of the unemployedchange too much, or when dispersion in labor market conditions -the extent to which somelabor markets fare worse than others- increases too much.

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.