Evaluating a formal KBS specification language

In recent years, the knowledge engineering community has begun to explore formal specification languages as a tool in the development of knowledge-based systems. These formal knowledge modelling languages have a number of advantages over informal languages, such as their precise meaning and the possibility to derive properties through formal proofs. However, these formal languages also suffer from problems which limit their practical usefulness: they are often not expressive enough to deal with real world applications, formal models are complex and hard to read, and constructing a formal model is a difficult, error prone and expensive process. The goal of the study presented in this paper is to investigate the usability of one such formal {KBS} modelling language, called (ML)^2. (ML)^2 is strongly based on the structure of the knowledge-models used in the KADS KBS development method. We first designed a set of evaluation criteria. We then applied (ML)^2 in two case-studies and scored the language on our evaluation criteria. (ML)^2 scored well on most of our criteria. This leads us to conjecture that the close correspondence between the informal KADS models and the formal (ML)^2 models avoids some of the problems that traditionally plague formal specification languages

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

, Joke van de Plassche ¡

Abstract. Formal knowledge modelling languages have a number of advantages over informal languages, such as their precise meaning and the possibility to derive properties through formal proofs. However, these formal languagesalso suffer from problems which limit their practical usefulness: they are often not expressive enough to deal with real world applications, formal models are complex and hard to read, and constructing a formal model is a difficult, error prone and expensive process. The goal of the study presented in this paper is to investigate the usability of one such formal KBS modelling language, called (ML) ¤. In order to analyse the properties of (ML) ¤ that influence its usability, we designed a set of evaluation criteria. We then applied (ML) ¤ in two case-studies and scored the language on our evaluation criteria. A separate case-study was devoted to analysing the possibilities for reusing formal model fragment. (ML) ¤ scored well on most of our criteria. This leads us to conjecture that the close correspondence between the informal KADS models and the formal (ML) ¤ models avoids some of the problems that traditionally plague formal specification languages. The case-studiesrevealed problems with the reuse of formal model fragments. These problems were caused by the (inevitable) ambiguous interpretations of the informal model fragments. Finally, extensive software-support is required when constructing formal specifications. Our case-studies showed that the close correspondence between formal and informal models makes it possible to provide more support (and particularly: different kinds of support) than have traditionally been considered.

Chapter 10: SCIAMACHY's View of the Changing Earth's Atmosphere

Since August 2002 SCIAMACHY delivers a wealth of high-quality data permitting to study the status of the Earth’s atmosphere. Enhanced concentrations of greenhouse gases are identified as the major source of global warming and their atmospheric concentrations are increasing. SCIAMACHY monitors the most prominent species such as CO2, CH4 and water vapour, the latter including isotope variants. Further anthropogenic impacts on the troposphere occur by emission of reactive trace gases contributing to pollution and affecting air quality. With SCIAMACHY their global, regional and even local signatures can be detected. Long-term analyses document how the emissions of NO2, SO2, HCHO, CHOCHO and CO evolve with time. In addition, the halogen cycle of polar BrO and IO, both of natural origin, is studied. The stratosphere is the layer where public interest in the Earth’s atmosphere has begun to grow with the detection of the ozone hole in the mid-1980’s. Until the mid-1990s a steady decrease has been observed in the ozone abundance. The most striking feature is the massive loss of stratospheric ozone over Antarctica during each southern spring. In order to detect possible signs of recovery, SCIAMACHY contributes to the continuous monitoring of the ozone layer, the ozone hole, Polar Stratospheric Clouds (PSC) and species impacting the ozone chemistry such as NO2, OClO and BrO. A much more poorly explored region is the mesosphere and lower thermosphere, which forms the transition between interplanetary space and the terrestrial atmosphere. This region is dominated by extraterrestrial impacts as well as couplings to the lower atmosphere. With SCIAMACHY’s limb viewing capabilities Noctilucent Clouds (NLC) are studied providing insight into generation and depletion mechanisms. At times of strong solar activity, SCIAMACHY measurements reveal how the chemistry of the upper atmosphere is disturbed. By analysis of emission lines in SCIAMACHY spectra the composition of the thermosphere above 100 km can be studied. SCIAMACHY is the first instrument to globally observe the metal layers in the upper mesosphere / lower thermosphere (MLT) region. When applying appropriate retrieval techniques it is meanwhile possible to derive vegetation information over land and phytoplankton characteristics in the oceans from SCIAMACHY data. Finally SCIAMACHY even has proven useful in planetary science by measuring spectra of our solar system neighbour Venu