Project Governance in an Embedded State : Possibilities and Challenges

Peer reviewe

Evaluation of environmental policy instruments : a case study of the Finnish pulp & paper and chemical industries

This research-based evaluation of environmental policy Instruments in Finland is focussed on regulatory instruments based on the Water Act, the Air Pollution Control Act and the Chemicals Act, on electricity taxation and on voluntary environmental management systems. The examined policy instruments have had several positive effects. They have directed major industrial point source polluters towards solving environmental problems. The transparency has been an important factor ensuring the success of the policy instruments and in avoiding the regulatory capture that could have thrived in a system largely based on negotiations between operators and authorities. The transparency has made it easy for Finnish firms to adopt environmental management systems and an open attitude to environmental reporting. The permit conditions have not directly resulted in innovations, but they have contributed to the diffusion of end-of-pipe technology and have contributed to innovations by expanding the market for environmentally better technical solutions. The permit systems have also indirectly contributed to innovations by creating a demand for environmental experts and environmental education.Networks have clearly developed as a consequence of and in response to regulatory instruments. These networks appear to have had their greatest significance prior to the permit procedures. The trend has been towards a greater emphasis of the communication in the networks prior to the presentation of an application in order to ensure a smoothly functioning permit process. In the networks contributing to innovations and the diffusion of innovations authorities have largely been outsiders, except when an innovation has become a de facto standard for permit conditions.The different kind of effects, the complexity of consequences and the uncertainties with respect to causes and effects mean that studies aiming at evaluating the overall worth and merit of an environmental policy instrument should never be structured from a single point of view using only one method. Multiple criteria should be used. The drawback of the multiple approach principle in evaluation is that the evaluations will run into data problems and all the difficulties of multi- and transdisciplinary research, but the multidisciplinarity is a necessary condition for developing an informed view of the functioning and effects of environmental policy instruments.This publication is the result of a project financed by the environmental cluster research programme

Governance Mechanisms as Promoters of Governability: A Political Science Perspective on Institutional Complexity

Peer reviewe

Administrative Agencies and the Collaborative Game : An Analysis of the Influence of Government Agencies in Collaborative Policy Implementation

Over the past decades, most countries have witnessed an increase in collaborative arrangements for engaging stakeholders in collective decision‐making processes. Despite the fact that the role of the state in the collaborative structures has been one of the highly debated issues, there is still a need for a more comprehensive understanding of how governmental agencies affect the performance of collaborative actions. This article develops a framework for systematic analyses of collaborative effects on policy performance. Using PROCESS OLS regression, the authors apply the framework to project‐level Cohesion Policy implementation in Finland – that is, to collaborative arrangements embedded in a rather fragmented and complex administrative context. The typical state characteristics of a Nordic country make Finland an interesting case for studying the interaction in collaborative arrangements between the administration and external agencies in a modern welfare state. The results presented in this article show that government agencies have a considerable moderating impact on the relationships between collaborative qualities and performance. The impact is, however, dependent on the responsiveness of the external agent to the bureaucratic rationale. The results underline the importance of more holistic approaches for analyzing complex collaborative constellations, focusing particularly on interaction effects between potential explanatory factors.Peer reviewe

A comparative study of different failure modeling strategies on a laboratory scale test component

Ultra-high strength steel (UHSS) has become a common material in the automotive industry during the last decades. The technique of press hardening allows modifying and tailoring the material properties of the blank in accordance with desired performance. In the present work, a laboratory scale test component is developed. On basis of tests on the component it is intended to investigate the deformation and fracture behavior of a boron alloyed steel after different heat treatments. The tooling is developed to allow the production of single phase microstructures like martensite and bainite as well as mixed microstructures containing ferrite. Testing of the component is performed in a standard tensile testing machine with additional digital speckle measurements to determine the strain to fracture in the critical cross section. The initial geometry shape introduces bending in the critical cross-section during tensile loading of the specimen. The aim of this work is to compare different material models on a component like level, including the prediction of failure. A finite element model of a laboratory scale component is analyzed using LS-Dyna. To compare different failure modeling approaches a set of damage models is calibrated to full hardened, martensitic steel. The deformation and fracture behavior of the component is presented in terms of load-displacement, plastic strain-stress triaxiality as well as in principal strain space

Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer.

BACKGROUND: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. METHODS: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). RESULTS: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. CONCLUSIONS: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer