Generation of Formal Model Metrics for MOF based Domain Specific Languages

The assessment of quality in a software development process is vital for the quality of the final system. A number of approaches exist, which can be used to determine such quality properties. In a model-driven development process models are the primary artifacts. Novel technologies are needed in order to assess the quality of those artifacts. Often, the Object Constraint Language is used to formulate model metrics and to compute them automatically afterwards. This paper describes an approach for the generation of model metrics expressed as OCL statements based on a set of generic rules. These rules can be applied on any domain specific modeling languages for creating a basic set of metrics which can be tailored for the specific needs of a development process. The paper also briefly describes a prototype of a tool for the generation, computation, and management of these model metrics by using the Software Metrics Meta-model - SMM

Generation of Formal Model Metrics for MOF based Domain Specific Languages

The assessment of quality in a software development process is vital for the quality of the final system. A number of approaches exist, which can be used to determine such quality properties. In a model-driven development process models are the primary artifacts. Novel technologies are needed in order to assess the quality of those artifacts. Often, the Object Constraint Language is used to formulate model metrics and to compute them automatically afterwards. This paper describes an approach for the generation of model metrics expressed as OCL statements based on a set of generic rules. These rules can be applied on any domain specific modeling languages for creating a basic set of metrics which can be tailored for the specific needs of a development process. The paper also briefly describes a prototype of a tool for the generation, computation, and management of these model metrics by using the Software Metrics Meta-model - SMM

Methane output of rabbits (Oryctolagus cuniculus) and guinea pigs (Cavia porcellus) fed a hay-only diet: Implications for the scaling of methane production with body mass in non-ruminant mammalian herbivores

It is assumed that small herbivores produce negligible amounts of methane, but it is unclear whether this is a physiological peculiarity, or simply a scaling effect. A respiratory chamber experiment was conducted with six rabbits (Oryctolagus cuniculus, 1.57 ± 0.31 kg body mass) and six guinea pigs (Cavia porcellus, 0.79 ± 0.07 kg) offered grass hay ad libitum. Daily dry matter (DM) intake and DM digestibility were 50 ± 6 g kg–0.75 d–1 and 55 ± 6 % in rabbits and 59 ± 11 g kg–0.75 d–1 and 61 ± 3 % in guinea pigs, respectively. Methane production was similar for both species (0.20 ± 0.10 L d–1 and 0.22 ± 0.08 L d–1) and represented 0.69 ± 0.32 and 1.03 ± 0.29 % of gross energy intake in rabbits and guinea pigs, respectively. In relation to body mass (BM) guinea pigs produced significantly more methane. The data on methane per unit of BM obtained in this study and from literature on methane output of elephant, wallabies and hyraxes all lay close to a regression line derived from roughage-fed horses, showing an increase in methane output with BM. The regression including all data was nearly identical to that based on the horse data only (methane production in horses [L d–1] = 0.18 body mass [kg]0.97 (95%CI 0.92–1.02)) and indicates linear scaling. Because feed intake typically scales to BM0.75, linear scaling of methane output translates into increasing energetic losses at increasing BM. Accordingly, the data collection indicates that an increasing proportion of ingested gross energy is lost because relative methane production increases with BM. Different from ruminants, such losses (1-2% of gross energy) appear too small in non-ruminant herbivores to represent a physiologic constraint on body size. Nevertheless, this relationship may represent a physiological disadvantage with increasing herbivore body size

Detector Systems Engineering for Extremely Large Instruments

The scientific detector systems for the ESO ELT first-light instruments, HARMONI, MICADO, and METIS, together will require 27 science detectors: seventeen 2.5 $\mu$m cutoff H4RG-15 detectors, four 4K x 4K 231-84 CCDs, five 5.3 $\mu$m cutoff H2RG detectors, and one 13.5 $\mu$m cutoff GEOSNAP detector. This challenging program of scientific detector system development covers everything from designing and producing state-of-the-art detector control and readout electronics, to developing new detector characterization techniques in the lab, to performance modeling and final system verification. We report briefly on the current design of these detector systems and developments underway to meet the challenging scientific performance goals of the ELT instruments.Comment: Proceedings of the SPIE Astronomical Telescopes and Instrumentation Conference 202

Methane emission by Camelids

Methane emissions from ruminant livestock have been intensively studied in order to reduce contribution to the greenhouse effect. Ruminants were found to produce more enteric methane than other mammalian herbivores. As camelids share some features of their digestive anatomy and physiology with ruminants, it has been proposed that they produce similar amounts of methane per unit of body mass. This is of special relevance for countrywide greenhouse gas budgets of countries that harbor large populations of camelids like Australia. However, hardly any quantitative methane emission measurements have been performed in camelids. In order to fill this gap, we carried out respiration chamber measurements with three camelid species (Vicugna pacos, Lama glama, Camelus bactrianus; n = 16 in total), all kept on a diet consisting of food produced from alfalfa only. The camelids produced less methane expressed on the basis of body mass (0.3260.11 L kg21 d21) when compared to literature data on domestic ruminants fed on roughage diets (0.5860.16 L kg21 d21). However, there was no significant difference between the two suborders when methane emission was expressed on the basis of digestible neutral detergent fiber intake (92.7633.9 L kg21 in camelids vs. 86.2612.1 L kg21 in ruminants). This implies that the pathways of methanogenesis forming part of the microbial digestion of fiber in the foregut are similar between the groups, and that the lower methane emission of camelids can be explained by their generally lower relative food intake. Our results suggest that the methane emission of Australia’s feral camels corresponds only to 1 to 2% of the methane amount produced by the countries’ domestic ruminants and that calculations of greenhouse gas budgets of countries with large camelid populations based on equations developed for ruminants are generally overestimating the actual levels

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock