Getting the big picture: Development of spatial scaling abilities

Spatial scaling is an integral aspect of many spatial tasks that involve symbol-to-referent correspondences (e.g., map reading, drawing). In this study, we asked 3–6-year-olds and adults to locate objects in a two-dimensional spatial layout using information from a second spatial representation (map). We examined how scaling factor and reference features, such as the shape of the layout or the presence of landmarks, affect performance. Results showed that spatial scaling on this simple task undergoes considerable development, especially between 3 and 5 years of age. Furthermore, the youngest children showed large individual variability and profited from landmark information. Accuracy differed between scaled and un-scaled items, but not between items using different scaling factors (1:2 vs. 1:4), suggesting that participants encoded relative rather than absolute distances.

Defined morphological criteria allow reliable diagnosis of colorectal serrated polyps and predict polyp genetics.

Criteria for the diagnosis of serrated colorectal lesions (hyperplastic polyp, sessile serrated adenoma without or with dysplasia--which we called mixed polyp--and traditional serrated adenoma) for which consensus has been reached should be validated for applicability in daily practice in terms of inter-observer reproducibility and their association with clinical features and (epi)genetic events. A study set was created from a consecutive series of colorectal polyps (n = 1,926) by selecting all sessile serrated adenomas, traditional serrated adenomas and mixed polyps. We added consecutive series of hyperplastic polyps, classical adenomas and normal mucosa samples for a total of 200 specimens. With this series, we conducted an inter-observer study, encompassing ten pathologists with gastrointestinal pathology experience from five European countries, in three rounds in which all cases were microscopically evaluated. An assessment of single morphological criteria was included, and these were correlated with clinical parameters and the mutation status of KRAS, BRAF and PIK3CA and the methylation status of MLH1. Gender, age and localisation were significantly associated with certain types of lesions. Kappa statistics revealed moderate to good inter-observer agreement for polyp classification (κ = 0.56 to 0.63), but for single criteria, this varied considerably (κ = 0.06 to 0.82). BRAF mutations were frequently found in hyperplastic polyps (86 %, 62/72) and sessile serrated adenomas (80 %, 41/51). KRAS mutations occurred more frequently in traditional serrated adenomas (78 %, 7/9) and less so in classical adenomas (20 %, 10/51). Single morphological criteria for sessile serrated adenomas showed significant correlation with BRAF mutation (all p ≤ 0.001), and those for classical adenomas or traditional serrated adenoma correlated significantly with KRAS mutation (all p < 0.001). Therefore, single well-defined morphological criteria are predictive for genetic alterations in colorectal polyps.

Up-Scaling Sustainable Pro-Poor Energy Solutions: Addressing Stumbling Blocks

The session aims at analyzing efforts in up-scaling cleaner and more efficient energy solutions for poor people in developing countries by addressing the following questions: What are factors along the whole value chain and in the institutional, social, but also environmental space that enable up-scaling of improved pro-poor technologies? Are there differences between energy carriers or in different contexts? What are most promising entry points for up-scaling?

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.