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The Comprehensive Development Framework (CDF) is an important tool for long-term development of any country. It attempts to balance state, public, private and donor interests into a single 10-year planning framework. Attempts to learn from experience of using the model have been gathered by the World Bank in almost 50 low-income pilot countries. These identify some of the benefits and constraints. This article takes the example of Kyrgyz Republic in Central Asia where the CDF approach was introduced in 2001. The research is based on interim findings from a donor-funded project to assist the strengthening of the CDF. This assessment notes the way in which the CDF has been used to promote national identity and only latterly been more closely integrated with the National Poverty Reduction Strategy, which has a three-year plan. The range of stakeholders remains wide, putting pressure on the coordinating authority within the President’s Office. Important implications for monitoring and evaluation methodologies are drawn through pilot research in two districts. The need for local participation and bottom-up approaches is critical in order to balance the over-centralized approach of the past. Issues of capacity, including skills and systems for the coordinating body and other stakeholders, are crucial when considering what will work.

This article considers some of the key issues in reforming the public sector in Central and Eastern Europe (CEE). Drawing on the experience of donor funded projects, some conclusions are drawn about the process of public sector reform with particular reference to Latvia. In particular, it is argued that the process will take time but strategic choices need to be made in the absence of obvious demands from within the country. Several constraints are noted which together constitute formidable barriers to progress. However, the results of work to date provide some optimism for pilot approaches to strategic budgeting in reformist ministries. A simple checklist is used as a yardstick for progress in the main areas of public administration reform. Copyright © 2004 John Wiley & Sons, Ltd.

Silica dust-exposed individuals are at high risk of developing silicosis, a fatal and incurable lung disease. The presence of disseminated micronodules on thoracic CT is the radiological hallmark of silicosis but locating micronodules, to identify subjects at risk, is tedious for human observers. We present a computer-aided detection scheme to automatically find micronodules and quantify micronodule load. The system used lung segmentation, template matching, and a supervised classification scheme. The system achieved a promising sensitivity of 84% at an average of 8.4 false positive marks per scan. In an independent data set of 54 CT scans in which we defined four risk categories, the CAD system automatically classified 83% of subjects correctly, and obtained a weighted kappa of 0.76.

Contains fulltext : 136826.pdf (Publisher’s version ) (Open Access) Subsolid pulmonary nodules occur less often than solid pulmonary nodules, but show a much higher malignancy rate. Therefore, accurate detection of this type of pulmonary nodules is crucial. In this work, a computer-aided detection (CAD) system for subsolid nodules in computed tomography images is presented and evaluated on a large data set from a multi-center lung cancer screening trial. The paper describes the different components of the CAD system and presents experiments to optimize the performance of the proposed CAD system. A rich set of 128 features is defined for subsolid nodule candidates. In addition to previously used intensity, shape and texture features, a novel set of context features is introduced. Experiments show that these features significantly improve the classification performance. Optimization and training of the CAD system is performed on a large training set from one site of a lung cancer screening trial. Performance analysis on an independent test from another site of the trial shows that the proposed system reaches a sensitivity of 80% at an average of only 1.0 false positive detections per scan. A retrospective analysis of the output of the CAD system by an experienced thoracic radiologist shows that the CAD system is able to find subsolid nodules which were not contained in the screening database.

An institution's performance is closely linked to the ways in which a donor attempts to build capacity as well as the environment in which it functions. Much has been made of the importance of a stable environment and in the last decade aid agencies have increasingly moved toward the influencing of sector policy as a critical means of technical co-operation. However, at the project level the relationship between donor and recipient is fundamental to the success of any intervention. In this article a best practice model is developed. Case studies of institutional development projects in South East Nigeria provide examples with which to evaluate the model. © 1998 John Wiley & Sons, Ltd.

Contains fulltext : 125893.pdf (Publisher’s version ) (Open Access) Accurate measurement of subsolid pulmonary nodules (SSN) is becoming increasingly important in the management of these nodules. SSNs were previously quantified with time-consuming manual measurements. The aim of the present study is to test the feasibility of semi-automatic SSNs measurements and to compare the results to the manual measurements.In 33 lung cancer screening participants with 33 SSNs, the nodules were previously quantified by two observers manually. In the present study two observers quantified these nodules by using semi-automated nodule volumetry software. Nodules were quantified for effective diameter, volume and mass. The manual and semi-automatic measurements were compared using Bland-Altman plots and paired T tests. Observer agreement was calculated as an intraclass correlation coefficient. Data are presented as mean (SD).Semi-automated measurements were feasible in all 33 nodules. Nodule diameter, volume and mass were 11.2 (3.3) mm, 935 (691) ml and 379 (311) milligrams for observer 1 and 11.1 (3.7) mm, 986 (797) ml and 399 (344) milligrams for observer 2, respectively. Agreement between observers and within observer 1 for the semi-automatic measurements was good with an intraclass correlation coefficient >0.89. For observer 1 and observer 2, measured diameter was 8.8\% and 10.3\% larger (p

International audience; Polygonal faulting is a widespread phenomenon in sedimentary basins worldwide. It changes basin-scale fluid flow patterns and alters the physical properties of the sediments making it important for hydrocarbon exploration and geohazard analysis. It is generally accepted that polygonal fault patterns derive from dewatering and compaction of the host sediments, but there is debate regarding the processes that control polygonal faulting. New multibeam-bathymetry data from the Hatton Basin, NE Atlantic, show up to 10 m deep and 200-600 m wide troughs at the seabed. They connect to each other forming polygons that are several hundred metres across, i.e. of similar size as buried polygonal fault systems observed in 3D seismic data. The troughs are symmetrical and resemble elongated pockmarks. Previously unpublished high-resolution 2D seismic data from the same area show seismic disturbance zones similar to pipes observed under pockmarks elsewhere as well as faults that have all the characteristics of polygonal fault systems. The observation of the wide disturbance zones is enigmatic, as they appear to follow the polygonal seafloor pattern. The observed extent of the polygonal sediment contraction system is substantial covering almost 37,000 km2. We calculate that some 2600 km3 of possibly carbon-bearing fluids have been expelled from this system and we expect that this will affect the benthic ecosystems, although so far there is only limited evidence for chemosynthetic habitats.

Contains fulltext : 108857.pdf (Publisher’s version ) (Open Access) The purpose of our study was to assess the normal range of CT measures of emphysema and air trapping in young men with normal lung function.A cohort of 70 young men with high-normal spirometry and body plethysmography underwent paired inspiratory and expiratory CT. Visual and quantitative scores of emphysema and air trapping were obtained. On CT, emphysema was defined as the 15th percentile of the attenuation curve (Perc(15)), and as the percentage of inspiratory voxels below -950 (IN(-950)) and below -960 (IN(-960)) HU. On CT, air trapping was defined as the expiratory-to-inspiratory ratio of mean lung density (EI-ratio(MLD)), and the percentage of voxels below -856 HU in expiration (EXP(-856)). Means, medians, and upper limits of normal (ULN) are presented for the total population and for smokers and nonsmokers separately.The mean age (� SD) of the subjects was 36.1 � 9.3 years. Smoking history was limited (range, 0-11 pack-years). Spirometry was high normal, ranging from 113\% to 160\% of predicted for vital capacity (VC), and from 104\% to 140\% of predicted for forced expiratory volume in 1 second (FEV(1)). The ULN was 2.73\% for IN(-950), 0.87\% for IN(-960), -936 HU for Perc(15), 89.0\% for EI-ratio(MLD), and 17.2\% for EXP(-856).Visual CT scores showed minimal emphysema in eight (11\%), > 5 lobules of air trapping in five (7\%), and segmental air trapping in three (4\%) subjects. CT measures were similar for never- and ever-smokers.We report the normal range of CT values for young male subjects with normal lung function, which is important to define pulmonary disease.

Purpose To examine the factors that affect inter- and intraobserver agreement for pulmonary nodule type classification on low-radiation-dose computed tomographic (CT) images, and their potential effect on patient management. Materials and Methods Nodules (n = 160) were randomly selected from the Dutch-Belgian Lung Cancer Screening Trial cohort, with equal numbers of nodule types and similar sizes. Nodules were scored by eight radiologists by using morphologic categories proposed by the Fleischner Society guidelines for management of pulmonary nodules as solid, part solid with a solid component smaller than 5 mm, part solid with a solid component 5 mm or larger, or pure ground glass. Inter- and intraobserver agreement was analyzed by using Cohen κ statistics. Multivariate analysis of variance was performed to assess the effect of nodule characteristics and image quality on observer disagreement. Effect on nodule management was estimated by differentiating CT follow-up for ground-glass nodules, solid nodules 8 mm or smaller, and part-solid nodules smaller than 5 mm from immediate diagnostic work-up for solid nodules larger than 8 mm and part-solid nodules 5 mm or greater. Results Pair-wise inter- and intraobserver agreement was moderate (mean κ, 0.51 [95% confidence interval, 0.30, 0.68] and 0.57 [95% confidence interval, 0.47, 0.71]). Categorization as part-solid nodules and location in the upper lobe significantly reduced observer agreement (P = .012 and P < .001, respectively). By considering all possible reading pairs (28 possible combinations of observer pairs × 160 nodules = 4480 possible agreements or disagreements), a discordant nodule classification was found in 36.4% (1630 of 4480), related to presence or size of a solid component in 88.7% (1446 of 1630). Two-thirds of these discrepant readings (1061 of 1630) would have potentially resulted in different nodule management. Conclusion There is moderate inter- and intraobserver agreement for nodule classification by using current recommendations for low-radiation-dose CT examinations of the chest. Discrepancies in nodule categorization were mainly caused by disagreement on the size and presence of a solid component, which may lead to different management in the majority of cases with such discrepancies. (©) RSNA, 2015.

Ground glass nodules (GGNs) occur less frequent in computed tomography (CT) scans than solid nodules but have a much higher chance of being malignant. Accurate detection of these nodules is therefore highly important. A complete system for computer-aided detection of GGNs is presented consisting of initial segmentation steps, candidate detection, feature extraction and a two-stage classification process. A rich set of intensity, shape and context features is constructed to describe the appearance of GGN candidates. We apply a two-stage classification approach using a linear discriminant classifier and a GentleBoost classifier to efficiently classify candidate regions. The system is trained and independently tested on 140 scans that contained one or more GGNs from around 10,000 scans obtained in a lung cancer screening trial. The system shows a high sensitivity of 73% at only one false positive per scan.

Ground glass nodules (GGNs) occur less frequent in computed tomography (CT) scans than solid nodules but have a much higher chance of being malignant. Accurate detection of these nodules is therefore highly important. A complete system for computer-aided detection of GGNs is presented consisting of initial segmentation steps, candidate detection, feature extraction and a two-stage classification process. A rich set of intensity, shape and context features is constructed to describe the appearance of GGN candidates. We apply a two-stage classification approach using a linear discriminant classifier and a GentleBoost classifier to efficiently classify candidate regions. The system is trained and independently tested on 140 scans that contained one or more GGNs from around 10,000 scans obtained in a lung cancer screening trial. The system shows a high sensitivity of 73% at only one false positive per scan.

Multiple Sclerosis (MS) is a common neurological disease affecting the central nervous system characterized by pathologic changes including demyelination and axonal injury. MR imaging has become the most important tool to evaluate the disease progression of MS which is characterized by the occurrence of white matter lesions. Currently, radiologists evaluate and assess the multiple sclerosis lesions manually by estimating the lesion volume and amount of lesions. This process is extremely time-consuming and sensitive to intra- and inter-observer variability. Therefore, there is a need for automatic segmentation of the MS lesions followed by lesion quantification. We have developed a fully automatic segmentation algorithm to identify the MS lesions. The segmentation algorithm is accelerated by parallel computing using Graphics Processing Units (GPU) for practical implementation into a clinical environment. Subsequently, characterized quantification of the lesions is performed. The quantification results, which include lesion volume and amount of lesions, are stored in a structured report together with the lesion location in the brain to establish a standardized representation of the disease progression of the patient. The development of this structured report in collaboration with radiologists aims to facilitate outcome analysis and treatment assessment of the disease and will be standardized based on DICOM-SR. The results can be distributed to other DICOM-compliant clinical systems that support DICOM-SR such as PACS. In addition, the implementation of a fully automatic segmentation and quantification system together with a method for storing, distributing, and visualizing key imaging and informatics data in DICOM-SR for MS lesions improves the clinical workflow of radiologists and visualizations of the lesion segmentations and will provide 3-D insight into the distribution of lesions in the brain.

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates multiple MRI studies to track disease progression. Currently, MRI assessment of multiple sclerosis requires manual lesion measurement and yields an estimate of lesion volume and change that is highly variable and user-dependent. In the setting of a longitudinal study, disease trends and changes become difficult to extrapolate from the lesions. In addition, it is difficult to establish a correlation between these imaged lesions and clinical factors such as treatment course. To address these clinical needs, an MS specific e-Folder for decision support in the evaluation and assessment of MS has been developed. An e-Folder is a disease-centric electronic medical record in contrast to a patient-centric electronic health record. Along with an MS lesion computer aided detection (CAD) package for lesion load, location, and volume, clinical parameters such as patient demographics, disease history, clinical course, and treatment history are incorporated to make the e-Folder comprehensive. With the integration of MRI studies together with related clinical data and informatics tools designed for monitoring multiple sclerosis, it provides a platform to improve the detection of treatment response in patients with MS. The design and deployment of MS e-Folder aims to standardize MS lesion data and disease progression to aid in decision making and MS-related research.

Multiple Sclerosis (MS) is a progressive neurological disease affecting myelin pathways in the brain. Multiple lesions in the white matter can cause paralysis and severe motor disabilities of the affected patient. To solve the issue of inconsistency and user-dependency in manual lesion measurement of MRI, we have proposed a 3-D automated lesion quantification algorithm to enable objective and efficient lesion volume tracking. The computer-aided detection (CAD) of MS, written in MATLAB, utilizes K-Nearest Neighbors (KNN) method to compute the probability of lesions on a per-voxel basis. Despite the highly optimized algorithm of imaging processing that is used in CAD development, MS CAD integration and evaluation in clinical workflow is technically challenging due to the requirement of high computation rates and memory bandwidth in the recursive nature of the algorithm. In this paper, we present the development and evaluation of using a computing engine in the graphical processing unit (GPU) with MATLAB for segmentation of MS lesions. The paper investigates the utilization of a high-end GPU for parallel computing of KNN in the MATLAB environment to improve algorithm performance. The integration is accomplished using NVIDIA's CUDA developmental toolkit for MATLAB. The results of this study will validate the practicality and effectiveness of the prototype MS CAD in a clinical setting. The GPU method may allow MS CAD to rapidly integrate in an electronic patient record or any disease-centric health care system.

Better state regulation is a key component of economic reform. This is the first book to comprehensively explore international experience in the use of Regulatory Impact Assessment (RIA), which involves assessing the potential benefits and costs of any regulatory change. The contributors reveal that RIA is being adopted by an increasing number of countries as a route to better regulation with varying degrees of success. The book includes contributions from leading experts on regulatory reform and introduces a range of case studies from developed, developing and transitional economies.

International audience

Better state regulation is a key component of economic reform. This is the first book to comprehensively explore international experience in the use of Regulatory Impact Assessment (RIA), which involves assessing the potential benefits and costs of any regulatory change. The contributors reveal that RIA is being adopted by an increasing number of countries as a route to better regulation with varying degrees of success. The book includes contributions from leading experts on regulatory reform and introduces a range of case studies from developed, developing and transitional economies.