Is there a right time to know? The right not to know and genetic testing in children

The increasing implementation of next-generation sequencing technologies in the clinical context and the expanding commercial offer of genetic tests directly-toconsumers has increased the availability of previously inaccessible genetic information. A particular concern in both situations is how the volume of novel information will affect the processing of genetic and genomic information from minors. For minors, it is argued that in the provision of genetic testing, their "right not to know" should be respected as much as possible. Testing a minor early in life eliminates the possibility for the minor to make use of his or her "right not to know." The article discusses the theoretical underpinnings of the right not know, analyzes reasons why various direct-to-consumer companies process samples from minors, and discusses the right not to know in relation to common complex disorders in a pediatric population

Geological Controls on Water Resource Variability in Minnesota, USA

Sustainable management of water resources requires quantitative description of spatio-temporal variability, and the map is a universal medium to reflect the spatio-temporal distribution of water resources. The long history of cartography and the recent digital revolution have culminated in the Google Earth web portal with unprecedented frequency of daily use. System analysis with combination of a cyber model of landscapes, multidimensional methods of data analysis, and GIS cartography of water resources in Minnesota started in 1996 with support from faculty of Department of Geology University of Minnesota-Duluth and has continued ever since. The “Water Resource Sustainability” project, funded by the Legislative Citizens Commission on Minnesota Resources (2007-2009) was the most resent phase of the research. 

Research using river flow monitoring data available from USGS for Minnesota and bordering areas of North Dakota, South Dakota, Iowa and Wisconsin was completed for the territory. Analysis of landscapes properties for watersheds taken from maps - Bailey’s Ecological Provinces, Soil Taxonomy Order, topographic characteristics (average altitude, average watershed slope, total, intermittent, and perennial drainage density), thickness of quaternary sediments, and Hydrogeological Hierarchical Regionalization - revealed control of geological conditions on water resource variability. The trends of interannual patterns and seasonality of river runoff depend on bedrock type and presence or absence of thick depositions of quaternary sediments in NE and SE of research territory and also on thickness of quaternary sediments in NW. The same parts of territory have main differences in annual and February monthly yields for interval of observations 1955-1978. The numbers of river discharge yield reach difference from 5 to 20 times. 

The control over water resource distribution and variability belongs to geological boundaries for types of bedrocks, lithology, and thickness of quaternary sediments. Groups of watersheds recognized by mutual landscape properties (geological conditions) with statistically proven influence on hydrologic characteristics provide a basis for regionalization and creation of a water resource map. The regionalization on the water resource map opens the way to study and climate change for regional level

Effects of Long-term Professional Development Training in Technology Integration on Teacher and Student Performance

The four primary questions addressed by the evaluation were: 1) Does the AZCOTT program influence the frequency of digital technology activities that teachers use with their students and that students perform in the classroom? 2) Does the program influence student performance of computer skills? 3) Does the program influence student self-reports of their technology skills? and 4) Does the program influence student self-reports of their use of technology for classroom activities? Also, investigated were the students’ ability to select appropriate software tools for given tasks and teacher attitudes toward the AZCOTT program

Towards an institutional PLE

PLEs in their broader sense (the ad-hoc, serendipitous and potentially chaotic set of tools that learners bring to their learning) are increasingly important for learners in the context of formal study. In this paper we outline the approach that we are taking at the University of Southampton in redesigning our teaching and learning infrastructure into an Institutional PLE. We do not see this term as an oxymoron. We define an Institutional PLE as an environment that provides a personalised interface to University data and services and at the same time exposes that data and services to a student’s personal tools. Our goal is to provide a digital platform that can cope with an evolving learning and teaching environment, as well as support the social and community aspects of the institution

Distributed consensus revised

We depend upon distributed systems in every aspect of life. Distributed consensus, the ability to reach agreement in the face of failures and asynchrony, is a fundamental and powerful primitive for constructing reliable distributed systems from unreliable components. For over two decades, the Paxos algorithm has been synonymous with distributed consensus. Paxos is widely deployed in production systems, yet it is poorly understood and it proves to be heavyweight, unscalable and unreliable in practice. As such, Paxos has been the subject of extensive research to better understand the algorithm, to optimise its performance and to mitigate its limitations. In this thesis, we re-examine the foundations of how Paxos solves distributed consensus. Our hypothesis is that these limitations are not inherent to the problem of consensus but instead specific to the approach of Paxos. The surprising result of our analysis is a substantial weakening to the requirements of this widely studied algorithm. Building on this insight, we are able to prove an extensive generalisation over the Paxos algorithm. Our revised understanding of distributed consensus enables us to construct a diverse family of algorithms for solving consensus; covering classical as well as novel algorithms to reach consensus where it was previously thought impossible. We will explore the wide reaching implications of this new understanding, ranging from pragmatic optimisations to production systems to fundamentally novel approaches to consensus, which achieve new tradeoffs in performance, scalability and reliability