Normative requirements for business process compliance

Norms regulate the behaviour of their subjects and define what is legal and what is illegal. Norms typically describe the conditions under which they are applicable and the normative effects as a results of their applications. On the other hand, process models specify how a business operation or service is to be carried out to achieve a desired outcome. Norms can have significant impact on how business operations are conducted and they can apply to the whole or part of a business process. For example, they may impose conditions on the different aspects of a process (e.g., perform tasks in a specific sequence (control-flow), at a specific time or within a certain time frame (temporal aspect), by specific people (resources)). We propose a framework that provides the formal semantics of the normative requirements for determining whether a business process complies with a normative document (where a normative document can be understood in a very broad sense, ranging from internal policies to best practice policies, to statutory acts). We also present a classification of normal requirements based on the notion of different types of obligations and the effects of violating these obligations.

Which dissimilarity is to be used when extracting typologies in sequence analysis? A comparative study

Originally developed in bioinformatics, sequence analysis is being increasingly used in social sciences for the study of life-course processes. The methodology generally employed consists in computing dissimilarities between the trajectories and, if typologies are sought, in clustering the trajectories according to their similarities or dissemblances. The choice of an appropriate dissimilarity measure is a major issue when dealing with sequence analysis for life sequences. Several dissimilarities are available in the literature, but neither of them succeeds to become indisputable. In this paper, instead of deciding upon one dissimilarity measure, we propose to use an optimal convex combination of different dissimilarities. The optimality is automatically determined by the clustering procedure and is defined with respect to the within-class variance.

A flexible Bayesian model for describing temporal variability of N2O emissions from an Australian pasture

Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

Mining temporal and spatial travel regularities for transit planning

Smart Card data from Automated Fare Collection system has been considered as a promising source of information for transit planning. However, literature has been limited to mining travel patterns from transit users and suggesting the potential of using this information. This paper proposes a method for mining spatial regular origins-destinations and temporal habitual travelling time from transit users. These travel regularity are discussed as being useful for transit planning. After reconstructing the travel itineraries, three levels of Density-Based Spatial Clustering of Application with Noise (DBSCAN) have been utilised to retrieve travel regularity of each of each frequent transit users. Analyses of passenger classifications and personal travel time variability estimation are performed as the examples of using travel regularity in transit planning. The methodology introduced in this paper is of interest for transit authorities in planning and managements

Spatio-temporal modelling of ultrafine particle number concentration

This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.

Towards an appropriate fatigue loading sequence for roof claddings in cyclone prone areas

Currently two different fatigue tests are being used to investigate the fatigue susceptibility of roof claddings in the cyclone prone areas of Australia. In order to resolve this issue a detailed investigation was conducted to study the nature of cyclonic wind forces using wind tunnel testing and computer modelling and the fatigue behaviour of metal roof claddings using structural testing. This led to the development of an accurate, but complicated loading matrix for a design cyclone. Based on this matrix, a simplified low-high-low loading sequence has been developed for the testing of roofing systems in cyclone prone areas. This paper first reviews the currently used fatigue loading sequences, then presents details of the cyclonic wind loading matrix and finally the development of the new simplified loading sequence. This simplified sequence should become the only suitable test for most of the cyclone prone areas of Australia covered by Region C which suffers from Category 4 cyclones. For Region D which suffers from Category 5 cyclones, the same loading sequence with 20% increased cycles has been recommended. An experimental programme to validate the new simplified loading sequence has been proposed.

A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

Agreement between temporal and spatial gait parameters from an instrumented walkway and treadmill system at matched walking speed

Background Commercially available instrumented treadmill systems that provide continuous measures of temporospatial gait parameters have recently become available for clinical gait analysis. This study evaluated the level of agreement between temporospatial gait parameters derived from a new instrumented treadmill, which incorporated a capacitance-based pressure array, with those measured by a conventional instrumented walkway (criterion standard). Methods Temporospatial gait parameters were estimated from 39 healthy adults while walking over an instrumented walkway (GAITRite®) and instrumented treadmill system (Zebris) at matched speed. Differences in temporospatial parameters derived from the two systems were evaluated using repeated measures ANOVA models. Pearson-product-moment correlations were used to investigate relationships between variables measured by each system. Agreement was assessed by calculating the bias and 95% limits of agreement. Results All temporospatial parameters measured via the instrumented walkway were significantly different from those obtained from the instrumented treadmill (P < .01). Temporospatial parameters derived from the two systems were highly correlated (r, 0.79–0.95). The 95% limits of agreement for temporal parameters were typically less than ±2% of gait cycle duration. However, 95% limits of agreement for spatial measures were as much as ±5 cm. Conclusions Differences in temporospatial parameters between systems were small but statistically significant and of similar magnitude to changes reported between shod and unshod gait in healthy young adults. Temporospatial parameters derived from an instrumented treadmill, therefore, are not representative of those obtained from an instrumented walkway and should not be interpreted with reference to literature on overground walking.

Market turbulence, temporal orientation and firm performance

This study investigates the role of environmental dynamics (i.e., market turbulence) as a factor influencing an organisation’s top management temporal orientation, and the impact of temporal orientation on innovative and financial performance. Results show that firm’s operating in highly turbulent markets exhibit higher degrees of future orientation, as opposed to present orientation. Future-oriented (rather than present-oriented) firms also experience higher levels of both incremental and radical innovations, which in turn generate financial performance. The study highlights the important role of shared strategic mindset (which is contextually influenced) as a driving factor behind the firm innovative and financial performance.

De Novo Transcriptome Sequence Assembly and Analysis of RNA Silencing Genes of Nicotiana benthamiana

Background: Nicotiana benthamiana has been widely used for transient gene expression assays and as a model plant in the study of plant-microbe interactions, lipid engineering and RNA silencing pathways. Assembling the sequence of its transcriptome provides information that, in conjunction with the genome sequence, will facilitate gaining insight into the plant's capacity for high-level transient transgene expression, generation of mobile gene silencing signals, and hyper-susceptibility to viral infection. Methodology/Results: RNA-seq libraries from 9 different tissues were deep sequenced and assembled, de novo, into a representation of the transcriptome. The assembly, of16GB of sequence, yielded 237,340 contigs, clustering into 119,014 transcripts (unigenes). Between 80 and 85% of reads from all tissues could be mapped back to the full transcriptome. Approximately 63% of the unigenes exhibited a match to the Solgenomics tomato predicted proteins database. Approximately 94% of the Solgenomics N. benthamiana unigene set (16,024 sequences) matched our unigene set (119,014 sequences). Using homology searches we identified 31 homologues that are involved in RNAi-associated pathways in Arabidopsis thaliana, and show that they possess the domains characteristic of these proteins. Of these genes, the RNA dependent RNA polymerase gene, Rdr1, is transcribed but has a 72 nt insertion in exon1 that would cause premature termination of translation. Dicer-like 3 (DCL3) appears to lack both the DEAD helicase motif and second dsRNA binding motif, and DCL2 and AGO4b have unexpectedly high levels of transcription. Conclusions: The assembled and annotated representation of the transcriptome and list of RNAi-associated sequences are accessible at www.benthgenome.com alongside a draft genome assembly. These genomic resources will be very useful for further study of the developmental, metabolic and defense pathways of N. benthamiana and in understanding the mechanisms behind the features which have made it such a well-used model plant. © 2013 Nakasugi et al.

Replicating satellite RNA induces sequence-specific DNA methylation and truncated transcripts in plants

Tobacco plants were transformed with a chimeric transgene comprising sequences encoding β-glucuronidase (GUS) and the satellite RNA (satRNA) of cereal yellow dwarf luteovirus. When transgenic plants were infected with potato leafroll luteovirus (PLRV), which replicated the transgene-derived satRNA to a high level, the satellite sequence of the GUS:Sat transgene became densely methylated. Within the satellite region, all 86 cytosines in the upper strand and 73 of the 75 cytosines in the lower strand were either partially or fully methylated. In contrast, very low levels of DNA methylation were detected in the satellite sequence of the transgene in uninfected plants and in the flanking nonsatellite sequences in both infected and uninfected plants. Substantial amounts of truncated GUS:Sat RNA accumulated in the satRNA-replicating plants, and most of the molecules terminated at nucleotides within the first 60 bp of the satellite sequence. Whereas this RNA truncation was associated with high levels of satRNA replication, it appeared to be independent of the levels of DNA methylation in the satellite sequence, suggesting that it is not caused by methylation. All the sequenced GUS:Sat DNA molecules were hypermethylated in plants with replicating satRNA despite the phloem restriction of the helper PLRV. Also, small, sense and antisense ∼22 nt RNAs, derived from the satRNA, were associated with the replicating satellite. These results suggest that the sequence-specific DNA methylation spread into cells in which no satRNA replication occurred and that this was mediated by the spread of unamplified satRNA and/or its associated 22 nt RNA molecules.

Sequence and organization of barley yellow dwarf virus genomic RNA

The nucleotide sequence of the genomic RNA of barley yellow dwarf virus, PAV serotype was determined except for the 5′-terminal base, and its genome organization deduced. The 5,677 nucleotide genome contains five large open reading frames (ORFs). The genes for the coat protein (1) and the putative viral RNA-dependent RNA polymerase were identified. The latter shows a striking degree of similarity to that of carnation mottle virus (CarMV). By comparison with corona- and retrovirus RNAs, it is proposed that a translational frameshift is involved in expression of the polymerase. An ORF encoding an Mr 49,797 protein (50K ORF) may be translated by in-frame readthrough of the coat protein stop codon. The coat protein, an overlapping 17K ORF, and a 3′ 6.7K ORF are likely to be expressed via subgenomic mRNAs. © 1988 IRL Press Limited.

Complete genomic sequence of a Rubus yellow net virus isolate and detection of genome-wide pararetrovirus-derived small RNAs

Rubus yellow net virus (RYNV) was cloned and sequenced from a red raspberry (Rubus idaeus L.) plant exhibiting symptoms of mosaic and mottling in the leaves. Its genomic sequence indicates that it is a distinct member of the genus Badnavirus, with 7932. bp and seven ORFs, the first three corresponding in size and location to the ORFs found in the type member Commelina yellow mottle virus. Bioinformatic analysis of the genomic sequence detected several features including nucleic acid binding motifs, multiple zinc finger-like sequences and domains associated with cellular signaling. Subsequent sequencing of the small RNAs (sRNAs) from RYNV-infected R. idaeus leaf tissue was used to determine any RYNV sequences targeted by RNA silencing and identified abundant virus-derived small RNAs (vsRNAs). The majority of the vsRNAs were 22-nt in length. We observed a highly uneven genome-wide distribution of vsRNAs with strong clustering to small defined regions distributed over both strands of the RYNV genome. Together, our data show that sequences of the aphid-transmitted pararetrovirus RYNV are targeted in red raspberry by the interfering RNA pathway, a predominant antiviral defense mechanism in plants. © 2013.

Small RNA sequencing of potato leafroll virus-infected plants reveals an additional subgenomic RNA encoding a sequence-specific RNA-binding protein

Potato leafroll virus (PLRV) is a positive-strand RNA virus that generates subgenomic RNAs (sgRNA) for expression of 3' proximal genes. Small RNA (sRNA) sequencing and mapping of the PLRV-derived sRNAs revealed coverage of the entire viral genome with the exception of four distinctive gaps. Remarkably, these gaps mapped to areas of PLRV genome with extensive secondary structures, such as the internal ribosome entry site and 5' transcriptional start site of sgRNA1 and sgRNA2. The last gap mapped to ~500. nt from the 3' terminus of PLRV genome and suggested the possible presence of an additional sgRNA for PLRV. Quantitative real-time PCR and northern blot analysis confirmed the expression of sgRNA3 and subsequent analyses placed its 5' transcriptional start site at position 5347 of PLRV genome. A regulatory role is proposed for the PLRV sgRNA3 as it encodes for an RNA-binding protein with specificity to the 5' of PLRV genomic RNA. © 2013.

Posttranscriptional gene silencing is not compromised in the Arabidopsis CARPEL FACTORY (DICER-LIKE1) mutant, a homolog of dicer-1 from Drosophila

Posttranscriptional silencing (PTGS) in plants, nematodes, Drosophila, and perhaps all eukaryotes operates by sequence-specific degradation or translational inhibition of the target mRNA. These processes are mediated by duplexed RNA. In Drosophila and nematodes, double-stranded (ds)RNA or self-complementary RNA is processed into fragments of approximately 21 nt by Dicer-1 [1, 2]. These small interfering RNAs (siRNAs) serve as guides to target degradation of homologous single-stranded (ss)RNA [1, 3]. In some cases, the approximately 21 nt guide fragments derived from endogenous, imperfectly self-complementary RNAs cause translational inhibition of their target mRNAs, with which they have substantial, but not perfect sequence complementarity [4-6]. These small temporal RNAs (stRNAs) belong to a class of noncoding microRNAs (miRNAs), 20-24 nt in length, that are found in flies, plants, nematodes, and mammals [4, 6-12]. In nematodes, the Dicer-1 enzyme catalyzes the production of both siRNA and stRNA [2, 13-15]. Mutation of the Arabidopsis Dicer-1 homolog, CARPEL FACTORY (CAF), blocks miRNA production [1, 4, 16-18]. Here, we report that the same caf mutant does not block either PTGS or siRNA production induced by self-complementary hairpin RNA. This suggests either that this mutation only impairs miRNA formation or, more interestingly, that plants have two distinct dicer-like enzymes, one for miRNA and another for siRNAi production.