19 research outputs found
Towards building a conceptual framework on intermarriage
Increasing migration worldwide and the cultural diversity generated as a consequence of international migration has facilitated the unions of people from different countries, religions, races, and ethnicities. Such unions are often celebrated as a sign of integration; however, at the same time as they challenge people's idea of us and them, intermarriages in fact still remain controversial, and even to some extent, taboo in many societies. Research and theorizing on intermarriage is conducted predominantly in the English-speaking North American and British contexts. This special issue includes empirical studies from not only the English-speaking countries such as the U.S., Canada, and the UK, but also from Japan, Sweden, Belgium, France, and Spain and demonstrate the increasingly diverse directions taken in the study of intermarriage in regards to the patterns, experiences, and social implications of intermarriages. Moreover, the articles address the assumed link between intermarriage and “integration.
Automatic allocation of safety integrity levels
In this paper, we describe a concept for the automatic allocationof general Safety Integrity Levels (SILs) to subsystems andcomponents of complex hierarchical networked architectures thatdeliver sets of safety critical functions. The concept is generic andcan be adapted to facilitate the safety engineering approachdefined in several standards that employ the concept of integrityor assurance levels including ISO 26262, the emergingautomotive safety standard. SIL allocation is facilitated by HiPHOPS,an automated safety analysis tool, and can be performed inthe context of development using EAST-ADL2, an automotivearchitecture description language. The process rationalizescomplex risk allocation and leads to optimal/economic allocationof SILs
Genetic Testing and Clinical Management Practices for Variants in Non-BRCA1/2 Breast (and Breast/Ovarian) Cancer Susceptibility Genes: An International Survey by the Evidence-Based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Clinical Working Group.
Purpose To describe a snapshot of international genetic testing practices, specifically regarding the use of multigene panels, for hereditary breast/ovarian cancers. We conducted a survey through the Evidence-Based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium, covering questions about 16 non- BRCA1 / 2 genes.Methods Data were collected via in-person and paper/electronic surveys. ENIGMA members from around the world were invited to participate. Additional information was collected via country networks in the United Kingdom and in Italy.Results Responses from 61 cancer genetics practices across 20 countries showed that 16 genes were tested by > 50% of the centers, but only six ( PALB2 , TP53 , PTEN , CHEK2 , ATM , and BRIP1 ) were tested regularly. US centers tested the genes most often, whereas United Kingdom and Italian centers with no direct ENIGMA affiliation at the time of the survey were the least likely to regularly test them. Most centers tested the 16 genes through multigene panels; some centers tested TP53 , PTEN , and other cancer syndrome-associated genes individually. Most centers reported (likely) pathogenic variants to patients and would test family members for such variants. Gene-specific guidelines for breast and ovarian cancer risk management were limited and differed among countries, especially with regard to starting age and type of imaging and risk-reducing surgery recommendations.Conclusion Currently, a small number of genes beyond BRCA1 / 2 are routinely analyzed worldwide, and management guidelines are limited and largely based on expert opinion. To attain clinical implementation of multigene panel testing through evidence-based management practices, it is paramount that clinicians (and patients) participate in international initiatives that share panel testing data, interpret sequence variants, and collect prospective data to underpin risk estimates and evaluate the outcome of risk intervention strategies