The Grow-Shrink strategy for learning Markov network structures constrained by context-specific independences

Markov networks are models for compactly representing complex probability distributions. They are composed by a structure and a set of numerical weights. The structure qualitatively describes independences in the distribution, which can be exploited to factorize the distribution into a set of compact functions. A key application for learning structures from data is to automatically discover knowledge. In practice, structure learning algorithms focused on "knowledge discovery" present a limitation: they use a coarse-grained representation of the structure. As a result, this representation cannot describe context-specific independences. Very recently, an algorithm called CSPC was designed to overcome this limitation, but it has a high computational complexity. This work tries to mitigate this downside presenting CSGS, an algorithm that uses the Grow-Shrink strategy for reducing unnecessary computations. On an empirical evaluation, the structures learned by CSGS achieve competitive accuracies and lower computational complexity with respect to those obtained by CSPC.Comment: 12 pages, and 8 figures. This works was presented in IBERAMIA 201

Stock Assessment of Norwegian Atlantic Halibut North of 62°N Latitude Using a Data-Limited Approach

Landings of Atlantic halibut (Hippoglossus hippoglossus) have increased significantly in later years. More fishing boats are joining the open-access fishery, with an ever-increasing number of fishing gear. The Atlantic halibut is also a popular tourist and recreational fishery target species. Atlantic halibut is a large, late-maturing flatfish with life history traits that make the stock sensitive to overfishing. The stock has a long history of exploitation, and historical fisheries show that increased landings over time have been followed by significant reductions in landings. The current regulations of the Norwegian Atlantic halibut fishery north of 62°N consist of input regulations (minimum catch size, no-catch periods, and fishing gear restrictions). Management authorities suggest new management actions to ensure a sustainable fishery of the Atlantic halibut stock in a long-term perspective. The aim of this study was to perform a stock assessment of the Norwegian Atlantic halibut stock north of 62°N using a data-limited approach. The purpose was to use the Stochastic Surplus Production Model in Continuous Time (SPiCT) and empirical approaches (with Data Limited Methods Toolkit (DLMtool)) on the limited data to assess the stock status and propose a management advice. The potential effects of tourist- and recreational fisheries were also examined through alternative landings (+20% and +40%) scenarios. Landings in Norway north of 62°N and Norwegian coastal scientific survey data were used. Four survey indices were developed from the scientific survey, of which one was used in the full assessment. The SPiCT assessment fulfilled the technical criteria, and the halibut stock was given ICES (International Council for the Exploration of the Sea) category 2 MSY (maximum sustainable yield) advice. The DLMtool gave similar results and provided estimates of a new minimum catch size. The assessment showed that the stock is close to optimal levels and utilized around MSY. The stock is probably declining due to overfishing in recent years. The management advice for the Norwegian halibut stock north of 62°N is to reduce fishing by implementing a TAC at 2000-2424 tons. An increased minimum catch size of around 90-106 cm should be implemented (together with or independently of other measures) to fit the species' life-history traits better. Tourist- and recreational fisheries might have a negative effect on the halibut stock, especially locally. The findings in this thesis can contribute to better management of the Norwegian halibut stock north of 62°N.Landingene av atlantisk kveite (Hippoglossus hippoglossus) har økt signifikant de siste årene. Flere båter har blitt med i det åpne fiskeriet, og et stadig større antall fiskeredskaper er i bruk. Atlantisk kveite er også en populær målart for turist- og fritidsfiskerier. Arten atlantisk kveite er en stor flatfisk som blir sent kjønnsmoden, og som har livshistorietrekk som gjør at den er sensitiv for overfiske. Kveitefiske har en lang historie, og statistikk viser at økte landinger over tid følges av store reduksjoner i landinger. Dagens forvaltning av norsk atlantisk kveite nord for 62°N består av innsatsreguleringer (minstemål, fredningsperioder og restriksjoner av fiskeredskap). Nye forvaltningstiltak er blitt foreslått av fiskerimyndighetene for å sikre et bærekraftig fiske av kveitebestanden i et langtidsperspektiv. Formålet med denne studien var å gjennomføre en bestandsvurdering av den norske atlantiske kveitebestanden nord for 62°N ved bruk av en databegrenset tilnærming. Målet var å teste og tilpasse en anerkjent stokastisk produksjonsmodell (Stochastic Surplus Production Model in Continuous Time - SPiCT) samt en empirisk tilnærming (med Data-Limited Methods Toolkit - DLMtool) for å vurdere bestandsstatus og foreslå et forvaltningsråd. De mulige effektene av turist- og fritidsfiske ble også undersøkt gjennom alternative scenarioer for landinger (+20% and +40%). Landingene for at atlantisk kveite i Norge nord for 62°N og data fra kysttoktet ble brukt. Fire indekser ble utviklet fra toktdataene, hvorav en ble brukt i hele bestandsvurderingen. Bestandsvurderingen med SPiCT oppfylte de tekniske kriteriene, og kveitebestanden ble gitt MSY-råd (maksimal bærekraftig fangst) etter det internasjonale havforskningsrådets (ICES) bestandskategori 2. DLMtool ga tilsvarende resultater og forslag til nytt økt minstemål. Bestandsvurderingen viste at bestanden er i tilnærmet optimal tilstand og utnyttet rundt MSY. Bestanden minsker trolig på grunn av overfiske de siste årene. Forvaltningsrådet for den norske atlantiske kveitebestanden nord for 62°N er å redusere fiske ved å innføre en kvote på mellom 2000-2424 tonn i fiskeriet. I tillegg foreslås det å øke minstemålet til mellom 90-106 cm (i tillegg til, eller uavhengig av andre forvaltningstiltak) som er bedre tilpasset arten. Turist- og fritidsfiske kan ha en negativ effekt på kveitebestanden, særlig lokalt. Funnene i denne oppgaven kan bidra til en bedre forvaltning av dem norske atlantiske kveitebestanden nord for 62°N

Legacy ExtraGalactic UV Survey with The Hubble Space Telescope: Stellar Cluster Catalogs and First Insights Into Cluster Formation and Evolution in NGC 628

We report the large effort that is producing comprehensive high-level young star cluster (YSC) catalogs for a significant fraction of galaxies observed with the Legacy ExtraGalactic UV Survey (LEGUS) Hubble treasury program. We present the methodology developed to extract cluster positions, verify their genuine nature, produce multiband photometry (from NUV to NIR), and derive their physical properties via spectral energy distribution fitting analyses. We use the nearby spiral galaxy NGC 628 as a test case for demonstrating the impact that LEGUS will have on our understanding of the formation and evolution of YSCs and compact stellar associations within their host galaxy. Our analysis of the cluster luminosity function from the UV to the NIR finds a steepening at the bright end and at all wavelengths suggesting a dearth of luminous clusters. The cluster mass function of NGC 628 is consistent with a power-law distribution of slopes ~-2 and a truncation of a few times 10^5 M⊙. After their formation, YSCs and compact associations follow different evolutionary paths. YSCs survive for a longer time frame, confirming their being potentially bound systems. Associations disappear on timescales comparable to hierarchically organized star-forming regions, suggesting that they are expanding systems. We find mass-independent cluster disruption in the inner region of NGC 628, while in the outer part of the galaxy there is little or no disruption. We observe faster disruption rates for low mass (≤10^4 M⊙) clusters, suggesting that a mass-dependent component is necessary to fully describe the YSC disruption process in NGC 628

Semi-automated Ontology Generation for Biocuration and Semantic Search

Background: In the life sciences, the amount of literature and experimental data grows at a tremendous rate. In order to effectively access and integrate these data, biomedical ontologies – controlled, hierarchical vocabularies – are being developed. Creating and maintaining such ontologies is a difficult, labour-intensive, manual process. Many computational methods which can support ontology construction have been proposed in the past. However, good, validated systems are largely missing. Motivation: The biocuration community plays a central role in the development of ontologies. Any method that can support their efforts has the potential to have a huge impact in the life sciences. Recently, a number of semantic search engines were created that make use of biomedical ontologies for document retrieval. To transfer the technology to other knowledge domains, suitable ontologies need to be created. One area where ontologies may prove particularly useful is the search for alternative methods to animal testing, an area where comprehensive search is of special interest to determine the availability or unavailability of alternative methods. Results: The Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG) developed in this thesis is a system which supports the creation and extension of ontologies by semi-automatically generating terms, definitions, and parent-child relations from text in PubMed, the web, and PDF repositories. The system is seamlessly integrated into OBO-Edit and Protégé, two widely used ontology editors in the life sciences. DOG4DAG generates terms by identifying statistically significant noun-phrases in text. For definitions and parent-child relations it employs pattern-based web searches. Each generation step has been systematically evaluated using manually validated benchmarks. The term generation leads to high quality terms also found in manually created ontologies. Definitions can be retrieved for up to 78% of terms, child ancestor relations for up to 54%. No other validated system exists that achieves comparable results. To improve the search for information on alternative methods to animal testing an ontology has been developed that contains 17,151 terms of which 10% were newly created and 90% were re-used from existing resources. This ontology is the core of Go3R, the first semantic search engine in this field. When a user performs a search query with Go3R, the search engine expands this request using the structure and terminology of the ontology. The machine classification employed in Go3R is capable of distinguishing documents related to alternative methods from those which are not with an F-measure of 90% on a manual benchmark. Approximately 200,000 of the 19 million documents listed in PubMed were identified as relevant, either because a specific term was contained or due to the automatic classification. The Go3R search engine is available on-line under www.Go3R.org