Specification and Verification of Media Constraints using UPPAAL

We present the formal specification and verification of a multimedia stream. The stream is described in a timed automata notation. We verify that the stream satisfies certain quality of service properties, in particular, throughput and end-to-end latency. The verification tool used is the real-time model checker UPPAAL

Clustering daily patterns of human activities in the city

Data mining and statistical learning techniques are powerful analysis tools yet to be incorporated in the domain of urban studies and transportation research. In this work, we analyze an activity-based travel survey conducted in the Chicago metropolitan area over a demographic representative sample of its population. Detailed data on activities by time of day were collected from more than 30,000 individuals (and 10,552 households) who participated in a 1-day or 2-day survey implemented from January 2007 to February 2008. We examine this large-scale data in order to explore three critical issues: (1) the inherent daily activity structure of individuals in a metropolitan area, (2) the variation of individual daily activities—how they grow and fade over time, and (3) clusters of individual behaviors and the revelation of their related socio-demographic information. We find that the population can be clustered into 8 and 7 representative groups according to their activities during weekdays and weekends, respectively. Our results enrich the traditional divisions consisting of only three groups (workers, students and non-workers) and provide clusters based on activities of different time of day. The generated clusters combined with social demographic information provide a new perspective for urban and transportation planning as well as for emergency response and spreading dynamics, by addressing when, where, and how individuals interact with places in metropolitan areas.Massachusetts Institute of Technology. Dept. of Urban Studies and PlanningUnited States. Dept. of Transportation (Region One University Transportation Center)Singapore-MIT Alliance for Research and Technolog

Classifying nursing organization in wards in Norwegian hospitals: self-identification versus observation

<p>Abstract</p> <p>Background</p> <p>The organization of nursing services could be important to the quality of patient care and staff satisfaction. However, there is no universally accepted nomenclature for this organization. The objective of the current study was to classify general hospital wards based on data describing organizational practice reported by the ward nurse managers, and then to compare this classification with the name used in the wards to identify the organizational model (self-identification).</p> <p>Methods</p> <p>In a cross-sectional postal survey, 93 ward nurse managers in Norwegian hospitals responded to questions about nursing organization in their wards, and what they called their organizational models. K-means cluster analysis was used to classify the wards according to the pattern of activities attributed to the different nursing roles and discriminant analysis was used to interpret the solutions. Cross-tabulation was used to validate the solutions and to compare the classification obtained from the cluster analysis with that obtained by self-identification. The bootstrapping technique was used to assess the generalizability of the cluster solution.</p> <p>Results</p> <p>The cluster analyses produced two alternative solutions using two and three clusters, respectively. The three-cluster solution was considered to be the best representation of the organizational models: 32 team leader-dominated wards, 23 primary nurse-dominated wards and 38 wards with a hybrid or mixed organization. There was moderate correspondence between the three-cluster solution and the models obtained by self-identification. Cross-tabulation supported the empirical classification as being representative for variations in nursing service organization. Ninety-four per cent of the bootstrap replications showed the same pattern as the cluster solution in the study sample.</p> <p>Conclusions</p> <p>A meaningful classification of wards was achieved through an empirical cluster solution; this was, however, only moderately consistent with the self-identification. This empirical classification is an objective approach to variable construction and can be generally applied across Norwegian hospitals. The classification procedure used in the study could be developed into a standardized method for classifying hospital wards across health systems and over time.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Statistical disclosure control when publishing on thematic maps

The spatial distribution of a variable, such as the energy consumption per company, is usually plotted by colouring regions of the study area according to an underlying table which is already protected from disclosing sensitive information. The result is often heavily influenced by the shape and size of the regions. In this paper, we are interested in producing a continuous plot of the variable directly from microdata and we protect it by adding random noise. We consider a simple attacker scenario and develop an appropriate sensitivity rule that can be used to determine the amount of noise needed to protect the plot from disclosing private information

Kernel bandwidth optimization in spike rate estimation

Kernel smoother and a time-histogram are classical tools for estimating an instantaneous rate of spike occurrences. We recently established a method for selecting the bin width of the time-histogram, based on the principle of minimizing the mean integrated square error (MISE) between the estimated rate and unknown underlying rate. Here we apply the same optimization principle to the kernel density estimation in selecting the width or “bandwidth” of the kernel, and further extend the algorithm to allow a variable bandwidth, in conformity with data. The variable kernel has the potential to accurately grasp non-stationary phenomena, such as abrupt changes in the firing rate, which we often encounter in neuroscience. In order to avoid possible overfitting that may take place due to excessive freedom, we introduced a stiffness constant for bandwidth variability. Our method automatically adjusts the stiffness constant, thereby adapting to the entire set of spike data. It is revealed that the classical kernel smoother may exhibit goodness-of-fit comparable to, or even better than, that of modern sophisticated rate estimation methods, provided that the bandwidth is selected properly for a given set of spike data, according to the optimization methods presented here

ARGONAUTE10 and ARGONAUTE1 Regulate the Termination of Floral Stem Cells through Two MicroRNAs in Arabidopsis

Stem cells are crucial in morphogenesis in plants and animals. Much is known about the mechanisms that maintain stem cell fates or trigger their terminal differentiation. However, little is known about how developmental time impacts stem cell fates. Using Arabidopsis floral stem cells as a model, we show that stem cells can undergo precise temporal regulation governed by mechanisms that are distinct from, but integrated with, those that specify cell fates. We show that two microRNAs, miR172 and miR165/166, through targeting APETALA2 and type III homeodomain-leucine zipper (HD-Zip) genes, respectively, regulate the temporal program of floral stem cells. In particular, we reveal a role of the type III HD-Zip genes, previously known to specify lateral organ polarity, in stem cell termination. Both reduction in HD-Zip expression by over-expression of miR165/166 and mis-expression of HD-Zip genes by rendering them resistant to miR165/166 lead to prolonged floral stem cell activity, indicating that the expression of HD-Zip genes needs to be precisely controlled to achieve floral stem cell termination. We also show that both the ubiquitously expressed ARGONAUTE1 (AGO1) gene and its homolog AGO10, which exhibits highly restricted spatial expression patterns, are required to maintain the correct temporal program of floral stem cells. We provide evidence that AGO10, like AGO1, associates with miR172 and miR165/166 in vivo and exhibits “slicer” activity in vitro. Despite the common biological functions and similar biochemical activities, AGO1 and AGO10 exert different effects on miR165/166 in vivo. This work establishes a network of microRNAs and transcription factors governing the temporal program of floral stem cells and sheds light on the relationships among different AGO genes, which tend to exist in gene families in multicellular organisms

What we stand for: Reputation platforms in Scandinavian higher education

acceptedVersio

Widespread Occurrence of Secondary Lipid Biosynthesis Potential in Microbial Lineages

Bacterial production of long-chain omega-3 polyunsaturated fatty acids (PUFAs), such as eicosapentaenoic acid (EPA, 20:5n-3) and docosahexaenoic acid (DHA, 22:6n-3), is constrained to a narrow subset of marine γ-proteobacteria. The genes responsible for de novo bacterial PUFA biosynthesis, designated pfaEABCD, encode large, multi-domain protein complexes akin to type I iterative fatty acid and polyketide synthases, herein referred to as “Pfa synthases”. In addition to the archetypal Pfa synthase gene products from marine bacteria, we have identified homologous type I FAS/PKS gene clusters in diverse microbial lineages spanning 45 genera representing 10 phyla, presumed to be involved in long-chain fatty acid biosynthesis. In total, 20 distinct types of gene clusters were identified. Collectively, we propose the designation of “secondary lipids” to describe these biosynthetic pathways and products, a proposition consistent with the “secondary metabolite” vernacular. Phylogenomic analysis reveals a high degree of functional conservation within distinct biosynthetic pathways. Incongruence between secondary lipid synthase functional clades and taxonomic group membership combined with the lack of orthologous gene clusters in closely related strains suggests horizontal gene transfer has contributed to the dissemination of specialized lipid biosynthetic activities across disparate microbial lineages