Minimisation of event structures

Event structures are fundamental models in concurrency theory, providing a representation of events in computation and of their relations, notably concurrency, conflict and causality. In this paper we present a theory of minimisation for event structures. Working in a class of event structures that generalises many stable event structure models in the literature, (e.g., prime, asymmetric, flow and bundle event structures) we study a notion of behaviour-preserving quotient, taking hereditary history preserving bisimilarity as a reference behavioural equivalence. We show that for any event structure a uniquely determined minimal quotient always exists. We observe that each event structure can be seen as the quotient of a prime event structure, and that quotients of general event structures arise from quotients of (suitably defined) corresponding prime event structures. This gives a special relevance to quotients in the class of prime event structures, which are then studied in detail, providing a characterisation and showing that also prime event structures always admit a unique minimal quotient

Knowledge Representation with Multiple Logical Theories and Time

We present a knowledge representation framework where a collection of logic programs can be combined together by means of meta-level program composition operations. Each object-level program is composed of a collection of extended clauses, equipped with a time interval representing the time period in which they hold. The interaction between program composition operations and time yields a powerful knowledge representation language in which many applications can be naturally developed. The language is given a meta-level semantics which also provides an executable specification. Moreover, we define an abstract semantics by extending the immediate consequence operator from a single logic program to compositions of logic programs and taking into account time intervals. The operational, meta-level semantics is proven sound and complete with respect to the abstract bottom-up semantics. The approach is further extended in order to cope with the problem of reasoning over joined intervals of time. Three applications in the field of business regulations are shown

A Logical Approach to Cooperative Information Systems

``Cooperative information system management'' refers to the capacity of several computing systems to communicate and cooperate in order to acquire, store, manage, query data and knowledge. Current solutions to the problem of cooperative information management are still far from being satisfactory. In particular, they lack the ability to fully model cooperation among heterogeneous systems according to a declarative style. The use of a logical approach to model all aspects of cooperation seems very promising. In this paper, we de®ne a logical language able to support cooperative queries, updates and update propagation. We model the sources of information as deductive databases, sharing the same logical language to ex- press queries and updates, but containing independent, even if possibly related, data. We use the Obj-U-Datalog (E. Bertino, G. Guerrini, D. Montesi, Toward deductive object data- bases, Theory and Practice of Object Systems 1 (1) (1995) 19±39) language to model queries and transactions in each source of data. Such language is then extended to deal with active rules in the style of Active-U-Datalog (E. Bertino, B. Catania, V. Gervasi, A. Ra aet a, Ac- tive-U-Datalog: Integrating active rules in a logical update language, in: B. Freitag, H. Decker, M. Kifer, A. Voronkov (Eds.), LBCS 1472: Transactions and Change in Login Databases, 1998, pp. 106±132), interpreted according to the PARK semantics proposed in G. Gottlob, G. Moerkotte, V.S. Subrahmanian (The PARK semantics for active rules, in: P.M.G. Apers, M. Bouzeghoub, G. Gardarin (Eds.), LNCS 1057: Proceedings of the Fifth International Con- ference on Extending Database Technology, 1996, pp. 35±55). By using active rules, a system can e ciently perform update propagation among di erent databases. The result is a logical environment, integrating active and deductive rules, to perform update propagation in a cooperative framework

A rule-based method for discovering trajectory profiles

The discovery of people profiles such as workers, students, families with kids, etc, is of interest for several application domains. For decades, such information has been extracted using census data, and more recently, from social networks, where people’s profile is clearly defined. A new type of data that has not been explored for discovering profiles, but which stores the real movement of people, are trajectories of moving objects. In this paper we propose a rule-based method to represent socio-demographic profiles, a moving object history model to summarize the daily movement of individuals, and define similarity functions for matching the profile model and the history model. We evaluate the method for single and multiple profile discovery.The discovery of people profiles such as workers, students, families with kids, etc, is of interest for several application domains. For decades, such information has been extracted using census data, and more recently, from social networks, where people's profile is clearly defined. A new type of data that has not been explored for discovering profiles, but which stores the real movement of people, are trajectories of moving objects. In this paper we propose a rule-based method to represent socio-demographic profiles, a moving object history model to summarize the daily movement of individuals, and define similarity functions for matching the profile model and the history model. We evaluate the method for single and multiple profile discovery

Multiple aspect trajectories: A case study on fishing vessels in the northern adriatic sea

In this paper we build, implement and analyze a spatio-temporal database describing the fishing activities in the Northern Adriatic Sea over four years. The database results from the fusion of two complementary data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed) and the corresponding fish catch reports (i.e., the quantity and type of fish caught). We present all the phases of the dataset creation, starting from the raw data and proceeding through data exploration, data cleaning, trajectory reconstruction and semantic enrichment. Moreover, we formalise and compare different techniques to distribute the fish caught by the fishing vessels along their trajectories. We implement the database with MobilityDB, an open source geospatial trajectory data management and analysis platform. Subsequently, guided by our ecological experts, we perform some analyses on the resulting spatio-temporal database, with the goal of mapping the fishing activities on some key species, highlighting all the interesting information and inferring new knowledge that will be useful for fishery management

From multiple aspect trajectories to predictive analysis: a case study on fishing vessels in the Northern Adriatic sea

In this paper we model spatio-temporal data describing the fishing activities in the Northern Adriatic Sea over four years. We build, implement and analyze a database based on the fusion of two complementary data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed) and fish catch reports (i.e., the quantity and type of fish caught) of the main fishing market of the area. We present all the phases of the database creation, starting from the raw data and proceeding through data exploration, data cleaning, trajectory reconstruction and semantic enrichment. We implement the database by using MobilityDB, an open source geospatial trajectory data management and analysis platform. Subsequently, we perform various analyses on the resulting spatio-temporal database, with the goal of mapping the fishing activities on some key species, highlighting all the interesting information and inferring new knowledge that will be useful for fishery management. Furthermore, we investigate the use of machine learning methods for predicting the Catch Per Unit Effort (CPUE), an indicator of the fishing resources exploitation in order to drive specific policy design. A variety of prediction methods, taking as input the data in the database and environmental factors such as sea temperature, waves height and Clorophill-a, are put at work in order to assess their prediction ability in this field. To the best of our knowledge, our work represents the first attempt to integrate fishing ships trajectories derived from AIS data, environmental data and catch data for spatio-temporal prediction of CPUE – a challenging task

Analysis of 1321 Eubacterium rectale genomes from metagenomes uncovers complex phylogeographic population structure and subspecies functional adaptations

Funding This work was supported by NIH NHGRI grant R01HG005220, NIDDK grant R24DK110499, NIDDK grant U54DE023798, and CMIT grant 6935956 to C.H., and by the European Research Council (ERC-STG project MetaPG-716575), MIUR “Futuro in Ricerca” RBFR13EWWI_001, the European Union (H2020-SFS-2018-1 project MASTER-818368 and H2020-SC1-BHC project ONCOBIOME-825410), and the National Cancer Institute of the National Institutes of Health (1U01CA230551) to N.S. Further support was provided by the Programma Ricerca Budget prestazioni Eurac 2017 of the Province of Bolzano, Italy to F.M., and by the EU-H2020 (DiMeTrack-707345) to E.P. and N.S. D.B., S.H.D., P.L., A.W.W. and The Rowett Institute received core funding support from the Scottish Government Rural and Environmental Sciences and Analytical Services (SG-RESAS). Availability of data and materials All datasets used in this study are publicly available and matched with their respective PMID (Additional file 5). The high-quality E. rectale MAGs in fasta format and a metadata file are available at http://segatalab.cibio.unitn.it/data/Erectale_Karcher_et_al.html and in the following Zenodo repository: https://doi.org/10.5281/zenodo.3763191 [80]. The two new isolate genomes L2–21 and T3BWe13 have been uploaded to NCBI and can be found in RefSeq under the accession numbers GCF_008122485.1 [81] and GCF_008123415.1 [82], respectively.Peer reviewedPublisher PD

Spatio-temporal knowledge bases in a constraint logic programming framework with multiple theories

Technical Report Dipartimento di Informatica Universita` di Pisa