Governance: public governance to social innovation?

ArticleThis paper reviews governance and public governance related to an emerging area of policy interest – social innovation. The European Commission’s White Paper on European Governance (2001) focused on openness, participation, accountability, effectiveness and coherence in public policy as characteristics of good governance. The EC has prioritised social innovation to address policy problems. Yet, the extant literature and research on social innovation is sparse. The paper questions whether it is a new mode of governance which contributes to good governance or a continuum of neoliberal reforms of the state which alters the relationship between the state, market and civil society

Book Review: growing the productivity of government services by Patrick Dunleavy and Leandro Carrera

In this book Patrick Dunleavy and Leandro Carrera ask why government productivity has been so neglected in the study of economics and public management. Chapters cover customs regulation, tax services, and the need to embrace digital change, and the book concludes with some clear and practical advice. Andrew Massey feels that the authors have delivered an original and innovative study, useful for public sector practitioners and academic observers of public administration and public sector management

A robust lesion boundary segmentation algorithm using level set methods

This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object. We compare the proposed method against five other segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician demarcated boundaries as ground truth

Using shape entropy as a feature to lesion boundary segmentation with level sets

Accurate lesion segmentation in retinal imagery is an area of vast research. Of the many segmentation methods available very few are insensitive to topological changes on noisy surfaces. This paper presents an extension to earlier work on a novel stopping mechanism for level sets. The elementary features scheme (ELS) in [5] is extended to include shape entropy as a feature used to ’look back in time’ and find the point at which the curve best fits the real object. We compare the proposed extension against the original algorithm for timing and accuracy using 50 randomly selected images of exudates with a database of clinician demarcated boundaries as ground truth. While this work is presented applied to medical imagery, it can be used for any application involving the segmentation of bright or dark blobs on noisy images

Lesion boundary segmentation using level set methods

This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object. We implement the level set using a fast upwind scheme and compare the proposed method against five other segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician marked-up boundaries as ground truth

Policy, performance and management in governance and intergovernmental relations: transatlantic perspectives

By examining both analytical and empirical differences and similarities between the European Union and the United States, this comprehensive book provides a better understanding of (inter) governmental systems, settings and actors operating in the post New Public Management Era. The expert contributors consider processes of policy formulation and implementation from an intergovernmental point of view, examine issues of performance and accountability that rise in IGR settings and zoom in on the importance and implications of IGR for welfare. Taken together, these insights provide an important next step into the world of transatlantic research and comparison

MUC13 Modulated Nanomechanical and Biophysical Responses in Pancreatic Cancer Cells

Pancreatic adenocarcinoma is one of the deadliest forms of cancer. Even with recent advances in diagnostic tools, chemotherapeutic regimens, and biomarkers for earlier detection, it still has dismal survival rates. Part of the reason for this is the inherent difficulty in detecting and treating this disease. Recent findings suggest that the altered expression of mucins, including MUC13, may be useful molecular signatures for early disease diagnosis, chemotherapy response and predicting patient survival. MUC13, a recently identified transmembrane glycoprotein, is normally associated with forming a protective barrier on epithelial tissues. However, its overexpression/aberrant subcellular localization has been associated with cancer, disease aggressiveness, poorer patient prognosis and drug resistance via alterations of multiple oncogenic signaling pathways. The main objective of this study is to investigate if MUC13 expression influences nanomechanical and biophysical characteristics of pancreatic cancer cells that might contribute to aggressive nature of this disease. To achieve this goal, we performed innovative nanoindentation analyses using atomic force microscopy in conjunction with standard biochemical assays. To combat this malignant disease, multiple approaches have been considered over the years. Recently, a unique biophysical method of cancer detection has been explored in other cancers, whereby an atomic force microscope (AFM) is used to measure the differences in rigidity and adhesion between normal and cancerous cells. AFMs work by using a thin metallic cantilever with a sharp probe which is brought into contact with a sample. Due to the interactions between the probe and the sample, various data can be extracted. AFMs have been used for decades to acquire high resolution, three-dimensional images of a sample, however it is also possible to acquire other types of data. For cancer research, biophysical data can help to differentiate between cancerous cells and their healthy counterparts. Current evidence suggests that normal cells have a greater rigidity than their cancerous counterparts in most malignancies, however literature dealing with pancreatic cancer is limited. In this report, a comprehensive overview of various pancreatic cell lines (both cancerous and non-cancerous) was physically investigated. We noted that there was a significant trend in the reduction of biophysical characteristics associated with differentiation status - namely, poorly differentiated pancreatic cancer cells (MIA PaCa-2, AsPC-1 and Panc-1) have significantly lower rigidity values as compared to moderately differentiated (BxPC-3), well differentiated (HPAF-II) and normal pancreatic epithelia (HPNE). A positive correlation was seen between the adhesion data and aggregation assays - notably, less aggregation was seen in cancer cells as compared to HPNE cells, an

Developing a Taxonomy of Coaching Behavior

In the field of applied behavior analysis, there is currently a lack of technicality pertaining to the term behavioral coaching. Previous research has investigated the use of behavioral principles applied to training coaches to shape behaviors. However, there is currently no behavioral literature available that has investigated how coaches allocate their behavior throughout practice. The purpose of the current study was to develop a taxonomy of coaching behavior that may aid behavior analysts to better analyze coaching behaviors by investigating what behaviors coaches engage in. A descriptive assessment identified 16 coaching behaviors that will be used throughout the study. A descriptive field assessment illustrated the type of behavior, when the behavior occurs, and how often coaches engage in these behaviors throughout multiple basketball practices