Policy change and learning: Implementing EU environmental policies affecting agriculture

This thesis aims to show whether and how the implementation of the EU environmental policy could be improved through policy learning. The results are based on two case studies: the development of agri-environmental policy in Finland and the implementation of the Water Framework Directive(WFD)in Ireland. The institutional analysis shows that the institutional structures changed due to the membership: the formal structures changed almost overnight and, as a result of increased cross-sectoral cooperation and policy learning, the informal structures also changed. The implementation of agri-environmental policy was studied in one administrative region, namely Uusimaa, located in southern Finland. The adaptation of EU environmental policies is an interesting research topic, not only because of the policy process itself but also because of the actors and context involved

Silicon Pixel R&D for the CLIC Tracking Detector

The physics aims at the proposed high-energy $e^+e^-$ collider CLIC pose challenging demands on the performance of the detector system. Precise hit-time tagging, an excellent spatial resolutions, and a low mass are required for the vertex and tracking detectors. To meet these requirements, an all-silicon vertex and tracking detector system is foreseen, for which a broad R&D programme on a variety of novel silicon detector technologies is being pursued. For the ultra-low mass vertex detector, different hybrid technologies with innovative sensor concepts and interconnection techniques are explored. For the large-scale tracking detector, the focus of the R&D lies on monolithic HV-MAPS and HR-CMOS technologies. This contribution gives an overview of the ongoing activities with a focus on monolithic technologies for the CLIC tracking detector. Recent results from laboratory and test-beam measurement campaigns of the ATLASpix_Simple and the CLICTD sensor prototypes are presented.Comment: Proceedings for INSTR20, 10 pages, 9 figure

Spectrum and wave functions of excited states in lattice gauge theory

We suggest a new method to compute the spectrum and wave functions of excited states. We construct a stochastic basis of Bargmann link states, drawn from a physical probability density distribution and compute transition amplitudes between stochastic basis states. From such transition matrix we extract wave functions and the energy spectrum. We apply this method toU(1)2+1 lattice gauge theory. As a test we compute the energy spectrum, wave functions and thermodynamical functions of the electric Hamiltonian and compare it with analytical results. We find excellent agreement. We observe scaling of energies and wave functions in the variable of time. We also present first results on a small lattice for the full Hamiltonian including the magnetic term

The Massive Schwinger Model in a Fast Moving Frame

We present a non-perturbative study of the massive Schwinger model. We use a Hamiltonian approach, based on a momentum lattice corresponding to a fast moving reference frame, and equal time quantization.Comment: contribution to Lattice'98 including: 2 style files (espcrc2.sty,psfig.sty) + text file (LaTeX) + 3 figures (ps) + complete paper(ps

Generalized Aharonov-Bohm effect, homotopy classes and Hausdorff dimension

We suggest as gedanken experiment a generalization of the Aharonov-Bohm experiment, based on an array of solenoids. This experiment allows in principle to measure the decomposition into homotopy classes of the quantum mechanical propagator. This yields information on the geometry of the average path of propagation and allows to determine its Hausdorff dimension.Comment: 14 pages, LaTeX + 3 figures, P

Bioinformatics Databases: State of the Art and Research Perspectives

Bioinformatics or computational biology, i.e. the application of mathematical and computer science methods to solving problems in molecular biology that require large scale data, computation, and analysis, is a research area currently receiving a considerable attention. Databases play an essential role in molecular biology and consequently in bioinformatics. molecular biology data are often relatively cheap to produce, leading to a proliferation of databases: the number of bioinformatics databases accessible worldwide probably lies between 500 and 1.000. Not only molecular biology data, but also molecular biology literature and literature references are stored in databases. Bioinformatics databases are often very large (e.g. the sequence database GenBank contains more than 4 × 10 6 nucleotide sequences) and in general grows rapidly (e.g. about 8000 abstracts are added every month to the literature database PubMed). Bioinformatics databases are heterogeneous in their data, in their data modeling paradigms, in their management systems, and in the data analysis tools they supports. Furthermore, bioinformatics databases are often implemented, queried, updated, and managed using methods rarely applied for other databases. This presentation aims at introducing in current bioinformatics databases, stressing their aspects departing from conventional databases. A more detailed survey can be found in [1] upon which thi

A Molecular Biology Database Digest

Computational Biology or Bioinformatics has been defined as the application of mathematical and Computer Science methods to solving problems in Molecular Biology that require large scale data, computation, and analysis [18]. As expected, Molecular Biology databases play an essential role in Computational Biology research and development. This paper introduces into current Molecular Biology databases, stressing data modeling, data acquisition, data retrieval, and the integration of Molecular Biology data from different sources. This paper is primarily intended for an audience of computer scientists with a limited background in Biology

Topological analysis of polymeric melts: Chain length effects and fast-converging estimators for entanglement length

Primitive path analyses of entanglements are performed over a wide range of chain lengths for both bead spring and atomistic polyethylene polymer melts. Estimators for the entanglement length N_e which operate on results for a single chain length N are shown to produce systematic O(1/N) errors. The mathematical roots of these errors are identified as (a) treating chain ends as entanglements and (b) neglecting non-Gaussian corrections to chain and primitive path dimensions. The prefactors for the O(1/N) errors may be large; in general their magnitude depends both on the polymer model and the method used to obtain primitive paths. We propose, derive and test new estimators which eliminate these systematic errors using information obtainable from the variation of entanglement characteristics with chain length. The new estimators produce accurate results for N_e from marginally entangled systems. Formulas based on direct enumeration of entanglements appear to converge faster and are simpler to apply.Comment: Major revisions. Developed near-ideal estimators which operate on multiple chain lengths. Now test these on two very different model polymers