Developing ideation cards for mixed reality game design

Mixed reality games (MRGs) pose new challenges but also opportunities to designers. In order to make the design space of MRGs easily accessible and enable collaborative design in a playful manner we have developed Mixed Reality Game Cards. These ideation cards synthesize design knowledge about MRGs and are inspired by a variety of other successful ideation cards. We describe six studies, illustrate the iterative development of our cards, and reflect how the structure of our cards might influence future ideation cards

El desarrollo sostenible de las microrregiones de Paraná en los años 2000 y 2012

This article studies the sustainable development profile of 39 microregions in the state of Paraná,Brazil. For each microregion, we analyzed the environmental, economic, social and institutional dimensions.In order to verify the indicators evolution and improvement, we used data from 2000 and2012 in the Sustainability Panel to generate the Sustainable Development Index. The results showthat the microregion of Curitiba had the best performance in sustainable development. However,the most developed microregions from 2000 to 2012 were Pato Branco, Londrina and Ponta Grossa,whereas the least developed ones were Jaguariaíva, São Mateus do Sul, Prudentópolis and Lapa.Este estudio analiza el perfil de desarrollo sostenible de las 39 microrregiones del departamento de Paraná, Brasil. Para cada microrregión, se analizaron las dimensiones ambientales, económica, social e institucional. Para verificar la evolución y mejora de los indicadores se utilizaron datos de 2000 y 2012 en el Panel de Sostenibilidad para generar el Índice de Desarrollo Sostenible. Los resultados indicaron que la microrregión de Curitiba obtuvo el mejor desempeño en el desarrollo sostenible. Sin embargo, las microrregiones que más se desarrollaron de 2000 a 2012 fueron Pato Branco, Londrina y Ponta Grossa, mientras las que menos presentaron desarrollo fueron las de Jaguariaíva, São Mateus do Sul, Prudentópolis y Lapa.Este estudio analisa o perfil do desenvolvimento sustentável das 39 microrregiões do estado do Paraná, Brasil. Para cada microrregião, analisaram-se as dimensões ambiental, econômica, social e institucional. Para verificar a evolução e melhoria dos indicadores, foram utilizados dados de 2000 e 2012 no Painel de Sustentabilidade para gerar o Índice de Desenvolvimento Sustentável. Os resultados apontaram que a microrregião de Curitiba teve o melhor desempenho no desenvolvimento sustentável. No entanto, as microrregiões que mais se desenvolveram de 2000 a 2012 foram Pato Branco, Londrina e Ponta Grossa. Aquelas que menos se desenvolveram nesse período foram as de Jaguariaíva, São Mateus do Sul, Prudentópolis e Lapa

Metagenomic insights into the abundance and composition of resistance genes in aquatic environments:Influence of stratification and geography

A global survey was performed with 122 aquatic metagenomic DNA datasets (92 lake water and 30 seawater) obtained from the Sequence Read Archive (SRA). Antibiotic resistance genes (ARGs) and metal resistance genes (MRGs) were derived from the dataset sequences via bioinformatic analysis. The relative abundances of ARGs and MRGs in lake samples were in the ranges ND (not detected)-1.34x10(0) and 1.22x10(-3) -1.98x10(-1) copies per 16S rRNA, which were higher than those in seawater samples. Among ARGs, multidrug resistance genes and bacitracin resistance genes had high relative abundances in both lake and sea water samples. Multimetal resistance genes, mercury resistance genes and copper resistance genes had the greatest relative abundance for MRGs. No significant difference was found between epilimnion and hypolimnion in abundance or the Shannon diversity index for ARGs and MRGs. Principal coordinates analysis and permutational multivariate analysis of variance (PERMANOVA) test showed that stratification and geography had significant influence on the composition of ARGs and MRGs in lakes (p < 0.05, PERMANOVA). Coastal seawater samples had significantly greater relative abundance and a higher Shannon index for both ARGs and MRGs than deep ocean and Antarctic seawater samples (p < 0.05, Kruskal-Wallis one-way ANOVA), suggesting that human activity may exert more selective pressure on ARGs and MRGs in coastal areas than those in deep ocean and Antarctic seawater

Design, Search and Implementation of Improved Large Order Multiple Recursive Generators and Matrix Congruential Generators

Large order, maximum period multiple recursive generators (MRGs) with few nonzero terms (e.g., DX-k-s generators) have become popular in the area of computer simulation. They are efficient, portable, have a long period, and have the nice property of high-dimensional equi-distribution. The latter two properties become more advantageous as k increases. The performance on the spectral test, a theoretical test that provides some measure of uniformity in dimensions beyond the MRG\u27s order k, could be improved by choosing multipliers that yield a better spectral test value. We propose a new method to compute the spectral test which is simple, intuitive, and efficient for some special classes of large order MRGs. Using this procedure, we list \u27\u27better\u27\u27 FMRG-k and DX-k-s generators with respect to performance on the spectral test. Even so, MRGs with few nonzero terms do not perform as well with respect to the spectral test as MRGs with many nonzero terms. However, MRGs with many nonzero terms can be inefficient or lack a feasible parallelization method, i.e., a method of producing substreams of (pseudo) random numbers that appear independent. To implement these MRGs efficiently and in parallel, we can use an equivalent recursion from another type of generator, the matrix congruential generator (MCG), a k-dimensional generalization of a first order linear recursion where the multipliers are embedded in a k by k matrix. When MRGs are used to construct MCGs and the recursion of the MCG is implemented k at a time for a k-dimensional vector sequence, then the MCG mimics k copies of a MRG in parallel with different starting seeds. Therefore, we propose a method for efficiently finding MRGs with many nonzero terms from an MRG with few nonzero terms and then give an efficient and parallel MCG implementation of these MRGs with many nonzero terms. This method works best for moderate order k. For large order MRGs with many nonzero terms, we propose a special class called DW-k. This special class has a characteristic polynomial that yields many nonzero terms and corresponds to an efficient and parallel MCG implementation

Cast Iron Drinking Water Pipe Biofilms Support Diverse Microbial Communities Containing Antibiotic Resistance Genes, Metal Resistance Genes, and Class 1 Integrons

Antimicrobial resistance is a well-documented public health concern. The role that drinking water distribution pipes have as sources of antibiotic resistance genes (ARGs) is not well known. Metals are a known stressor for antibiotic resistance development, implying that aging metal-pipe infrastructure could be a source of ARGs. The objective of this study was to determine if ARGs, metal resistance genes (MRGs), and intI1 were pervasive across various pipe biofilm sample types (biomass surfaces, pipe surfaces, corrosion tubercles, and under corrosion tubercles) and if the resistance genes associated with particular microbial taxa. Eight sample types in triplicate (n = 24) were taken from inside a \u3e100 year-old, six ft. section of a full-scale chloraminated cast iron drinking water main. Droplet digital PCR (ddPCR) was employed as a novel approach to quantify ARGs in pipes from full-scale drinking water distribution systems (DWDS) because it yielded higher detection frequencies than quantitative PCR (qPCR). Illumina sequencing was employed to characterize the microbial community based on 16S rRNA genes. ARGs and MRGs were detected in all 24 pipe samples. Every sample contained targeted genes. Interestingly, the mean absolute abundances of ARGs and MRGs only varied by approximately one log value across sample types, but the mean relative abundances (copy numbers normalized to 16S rRNA genes) varied by over two log values. The ARG and MRGs concentrations were not significantly different between sample types, despite significant changes in dominant microbial taxa. The most abundant genera observed in the biofilm communities were Mycobacterium (0.2–70%), and β-lactam resistance genes blaTEM, blaSHV, and the integrase gene of class 1 integrons (intI1) were positively correlated with Mycobacterium. The detection of ARGs, MRGs, and class 1 integrons across all sample types within the pipe indicates that pipes themselves can serve as sources for ARGs in DWDS. Consequently, future work should investigate the role of pipe materials as well as corrosion inhibitors to determine how engineering decisions can mitigate ARGs in drinking water that stem from pipe materials

Spectral Estimation of Conditional Random Graph Models for Large-Scale Network Data

Generative models for graphs have been typically committed to strong prior assumptions concerning the form of the modeled distributions. Moreover, the vast majority of currently available models are either only suitable for characterizing some particular network properties (such as degree distribution or clustering coefficient), or they are aimed at estimating joint probability distributions, which is often intractable in large-scale networks. In this paper, we first propose a novel network statistic, based on the Laplacian spectrum of graphs, which allows to dispense with any parametric assumption concerning the modeled network properties. Second, we use the defined statistic to develop the Fiedler random graph model, switching the focus from the estimation of joint probability distributions to a more tractable conditional estimation setting. After analyzing the dependence structure characterizing Fiedler random graphs, we evaluate them experimentally in edge prediction over several real-world networks, showing that they allow to reach a much higher prediction accuracy than various alternative statistical models.Comment: Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012

Plastics in the marine environment are reservoirs for antibiotic and metal resistance genes

Plastics have been accumulated offshore and in the deep oceans at an unprecedented scale. Microbial communities have colonized the plastisphere, which has become a reservoir for both antibiotic and metal resistance genes (ARGs and MRGs). This is the first analysis of the diversity, abundance, and co-occurrence of ARGs and MRGs, and their relationships within the microbial community, using metagenomic data of plastic particles observed in the North Pacific Gyre obtained from the National Centre for Biotechnology Information Sequence Read Archive database. The abundance of ARGs and MRGs in microbial communities on the plastics were in the ranges 7.07 x 10(-4)-1.21 x 10(-2) and 5.51 x 10(-3)-4.82 x 10(-2) copies per 16S rRNA, respectively. Both the Shannon-Wiener indices and richness of ARGs and MRGs in plastics microbiota were significantly greater than those of ARGs and MRGs in seawater microbiota in the North Pacific Gyre via one-way analysis of variance. Multidrug resistance genes and multi-metal resistance genes were the main classes of genes detected in plastic microbiota. There were no significant differences in the abundance or diversity of ARGs and MRGs between macroplastics biota and microplastics biota, indicating that particle size had no effect on resistance genes. Procrustes analysis suggested that microbial community composition was the determining factor of the ARG profile but not for MRG. Some ARGs and MRGs had a higher incidence of non-random co-occurrence, suggesting that the co-effects of selection for antibiotic or metal resistance are important factors influencing the resistome of the microbiota on the plastic particles

Defining early steps in mRNA transport: mutant mRNA in myotonic dystrophy type I is blocked at entry into SC-35 domains

In myotonic dystrophy type 1 (DM1), triplet repeat expansion in the 3′ untranslated region of dystrophia myotonica protein kinase (DMPK) causes the nuclear retention of mutant messenger RNA (mRNA). Although the DMPK gene locus positions precisely at the outer edge of a factor-rich SC-35 domain, the normal mRNA consistently accumulates within the domain, and this RNA is depleted upon transcriptional inhibition. In DM1, mutant transcripts detach from the gene but accumulate in granules that abut but do not enter SC-35 domains, suggesting that RNA entry into the domain is blocked. Despite their exclusion from these compartments, mutant transcripts are spliced. MBNL1 (muscleblind-like protein 1) is an alternative splicing factor that becomes highly concentrated with mutant RNA foci. Small interfering RNA–mediated knockdown of MBNL1 promotes the accumulation or entry of newly synthesized mutant transcripts in the SC-35 domain. Collectively, these data suggest that an initial step in the intranuclear path of some mRNAs is passage from the gene into an SC-35 domain and implicate these structures in postsplicing steps before export