A role-based conceptual framework for teaching robotic construction technologies to architects

In the last 30 years, there has been increasing interest in the adoption of robotics in the construction industry and more recently in architecture. Cutting edge technologies are often pioneered in industries such as automotive, aeronautical and ship building, and take decades to filter into the hands of architects. If this is to change, architects need to be better educated in the field of robotic construction technology. This research catalogues robotic construction technology currently being used by architects and discusses the motivations that drive architects to use this technology. This catalogue includes an interview with architect Dr Simon Weir and investigates his motivation for using robotic construction technologies on a project for an Aboriginal community in central Australia. Existing frameworks for classifying robotic construction technologies are reviewed and assessed for their suitability for use teaching architecture students about these technologies. This leads to the development of a new conceptual framework for teaching architecture students about robotic construction technology. This conceptual framework classifies the technology according to the role it plays in the construction process, which makes the information more accessible to architects. The developed conceptual framework is implemented by teaching a class of students from the Master of Architecture course at the University of Sydney. Results from this class reveal outcomes for further development of the implementation of the framework into the classroom. A revised course structure is presented along with an appropriate hybrid robotic system for teaching architecture students about robotic construction technology

Hydraulic structures: Useful water harvesting systems or relics?

Throughout the ages, the construction of hydraulic structures has supported the development of human civilisation. Around 3000 BC, masonry dams on the Nile provided irrigation water in Egypt, while in Mesopotamia canals were built for irrigation, draining swamps and transportation [2, 3, 5]. The 18th and 19th centuries saw the rapid development of water supply systems in response to the industrial development and the needs for reliable water supply [4, 7, 8] (Fig. 1 & 2). More recently, the 1940s to 1970s saw a worldwide boom in large water projects, mainly for consumption, irrigation, transport, hydropower and flood protection [3]. For example, the California Central Valley Project, built between 1933 and 1970, provides irrigation water to over 1.2 million hectares and generates over 1 million kW of power [3]. The rate of construction of new water projects in Europe and North America has dropped during the last few decades, and many of the original water harvesting system mega projects are now near, or even past, their original intended design lives. The question therefore arises whether the existing systems are redundant relics from the past that have reached their sell-by date, or do they still have an important role to play in modern society

Shape based indexing for faster search of RNA family databases

Janssen S, Reeder J, Giegerich R. Shape based indexing for faster search of RNA family databases. BMC Bioinformatics. 2008;9(1):131.Background: Most non-coding RNA families exert their function by means of a conserved, common secondary structure. The Rfam data base contains more than five hundred structurally annotated RNA families. Unfortunately, searching for new family members using covariance models (CMs) is very time consuming. Filtering approaches that use the sequence conservation to reduce the number of CM searches, are fast, but it is unknown to which sacrifice. Results: We present a new filtering approach, which exploits the family specific secondary structure and significantly reduces the number of CM searches. The filter eliminates approximately 85% of the queries and discards only 2.6% true positives when evaluating Rfam against itself. First results also capture previously undetected non-coding RNAs in a recent human RNAz screen. Conclusion: The RNA shape index filter (RNAsifter) is based on the following rationale: An RNA family is characterised by structure, much more succinctly than by sequence content. Structures of individual family members, which naturally have different length and sequence composition, may exhibit structural variation in detail, but overall, they have a common shape in a more abstract sense. Given a fixed release of the Rfam data base, we can compute these abstract shapes for all families. This is called a shape index. If a query sequence belongs to a certain family, it must be able to fold into the family shape with reasonable free energy. Therefore, rather than matching the query against all families in the data base, we can first (and quickly) compute its feasible shape(s), and use the shape index to access only those families where a good match is possible due to a common shape with the query

Cross-Presentation of Cell-Associated Antigens by Mouse Splenic Dendritic Cell Populations

Cross-presentation of cell-associated antigens (Ag) plays an important role in the induction of anti-tumor responses, autoimmune diseases, and transplant rejection. While several dendritic cell (DC) populations can induce pro-inflammatory CD8+ T cell responses to cell-associated Ag during infection, in the absence of infection, cross-priming of naïve CD8+ T cells is highly restricted. Comparison of the main splenic DC populations in mice – including the classic, cross-presenting CD8α DC and the recently described merocytic DC (mcDC) – reveals that cross-priming DCs display a distinct phenotype in cell-associated Ag uptake, endosomal/lysosomal trafficking, lysosomal acidification, and Ag persistence compared to non-cross-priming DC populations. Although the CD8α DC and mcDC subsets utilize similar processing pathways to cross-present cell-associated Ag, cross-priming by CD8α DCs is associated with IL-12 production, while the superior priming of the mcDC is critically dependent on type I IFN production. This discussion illustrates how subtle differences in internal processing pathways and their signaling sequelae significantly affect the duration of Ag cross-presentation and cytokine production by DCs, thereby shaping the ensuing CD8+ T cell response

An introductory study of house spiders (Araneae) in Belgium

More than 800 spiders were collected in 43 houses heated in winter, distributed mainly in the northern part of Belgium. Information required for the collections to be eligible for the project was: address, construction year, type of house, and surroundings. The spiders were qualified as ‘house spiders’ or ‘garden spiders’. Of the 93 species collected, 19 could be defined as house spiders. Pholcus phalangioides was the most common, followed by Eratigena atrica and Steatoda triangulosa. Garden spiders enter the house much more often in houses in a rural environment than in those situated in clusters, and mainly in spring. The spiders are most common in autumn when many of them are breeding. The common house spiders colonize houses shortly after their construction

Lost in folding space? Comparing four variants of the thermodynamic model for RNA secondary structure prediction

Janssen S, Schudoma C, Steger G, Giegerich R. Lost in folding space? Comparing four variants of the thermodynamic model for RNA secondary structure prediction. BMC Bioinformatics. 2011;12(1): 429.BACKGROUND:Many bioinformatics tools for RNA secondary structure analysis are based on a thermodynamic model of RNA folding. They predict a single, "optimal" structure by free energy minimization, they enumerate near-optimal structures, they compute base pair probabilities and dot plots, representative structures of different abstract shapes, or Boltzmann probabilities of structures and shapes. Although all programs refer to the same physical model, they implement it with considerable variation for different tasks, and little is known about the effects of heuristic assumptions and model simplifications used by the programs on the outcome of the analysis.RESULTS:We extract four different models of the thermodynamic folding space which underlie the programs RNAfold, RNAshapes, and RNAsubopt. Their differences lie within the details of the energy model and the granularity of the folding space. We implement probabilistic shape analysis for all models, and introduce the shape probability shift as a robust measure of model similarity. Using four data sets derived from experimentally solved structures, we provide a quantitative evaluation of the model differences.CONCLUSIONS:We find that search space granularity affects the computed shape probabilities less than the over- or underapproximation of free energy by a simplified energy model. Still, the approximations perform similar enough to implementations of the full model to justify their continued use in settings where computational constraints call for simpler algorithms. On the side, we observe that the rarely used level 2 shapes, which predict the complete arrangement of helices, multiloops, internal loops and bulges, include the "true" shape in a rather small number of predicted high probability shapes. This calls for an investigation of new strategies to extract high probability members from the (very large) level 2 shape space of an RNA sequence. We provide implementations of all four models, written in a declarative style that makes them easy to be modified. Based on our study, future work on thermodynamic RNA folding may make a choice of model based on our empirical data. It can take our implementations as a starting point for further program development