960 resultados para High Confidence Rules


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ACM Computing Classification System (1998): H.2.8, H.3.3.

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Essential genes are absolutely required for the survival of an organism. The identification of essential genes, besides being one of the most fundamental questions in biology, is also of interest for the emerging science of synthetic biology and for the development of novel antimicrobials. New antimicrobial therapies are desperately needed to treat multidrug-resistant pathogens, such as members of the Burkholderia cepacia complex.

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The Sznajd model is a sociophysics model that is used to model opinion propagation and consensus formation in societies. Its main feature is that its rules favor bigger groups of agreeing people. In a previous work, we generalized the bounded confidence rule in order to model biases and prejudices in discrete opinion models. In that work, we applied this modification to the Sznajd model and presented some preliminary results. The present work extends what we did in that paper. We present results linking many of the properties of the mean-field fixed points, with only a few qualitative aspects of the confidence rule (the biases and prejudices modeled), finding an interesting connection with graph theory problems. More precisely, we link the existence of fixed points with the notion of strongly connected graphs and the stability of fixed points with the problem of finding the maximal independent sets of a graph. We state these results and present comparisons between the mean field and simulations in Barabasi-Albert networks, followed by the main mathematical ideas and appendices with the rigorous proofs of our claims and some graph theory concepts, together with examples. We also show that there is no qualitative difference in the mean-field results if we require that a group of size q > 2, instead of a pair, of agreeing agents be formed before they attempt to convince other sites (for the mean field, this would coincide with the q-voter model).

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On-time completion is an important temporal QoS (Quality of Service) dimension and one of the fundamental requirements for high-confidence workflow systems. In recent years, a workflow temporal verification framework, which generally consists of temporal constraint setting, temporal checkpoint selection, temporal verification, and temporal violation handling, has been the major approach for the high temporal QoS assurance of workflow systems. Among them, effective temporal checkpoint selection, which aims to timely detect intermediate temporal violations along workflow execution plays a critical role. Therefore, temporal checkpoint selection has been a major topic and has attracted significant efforts. In this paper, we will present an overview of work-flow temporal checkpoint selection for temporal verification. Specifically, we will first introduce the throughput based and response-time based temporal consistency models for business and scientific cloud workflow systems, respectively. Then the corresponding benchmarking checkpoint selection strategies that satisfy the property of “necessity and sufficiency” are presented. We also provide experimental results to demonstrate the effectiveness of our checkpoint selection strategies, and finally points out some possible future issues in this research area.

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The problem of the relevance and the usefulness of extracted association rules is of primary importance because, in the majority of cases, real-life databases lead to several thousands association rules with high confidence and among which are many redundancies. Using the closure of the Galois connection, we define two new bases for association rules which union is a generating set for all valid association rules with support and confidence. These bases are characterized using frequent closed itemsets and their generators; they consist of the non-redundant exact and approximate association rules having minimal antecedents and maximal consequences, i.e. the most relevant association rules. Algorithms for extracting these bases are presented and results of experiments carried out on real-life databases show that the proposed bases are useful, and that their generation is not time consuming.

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The rivalry between the men's basketball teams of Duke University and the University of North Carolina-Chapel Hill (UNC) is one of the most storied traditions in college sports. A subculture of students at each university form social bonds with fellow fans, develop expertise in college basketball rules, team statistics, and individual players, and self-identify as a member of a fan group. The present study capitalized on the high personal investment of these fans and the strong affective tenor of a Duke-UNC basketball game to examine the neural correlates of emotional memory retrieval for a complex sporting event. Male fans watched a competitive, archived game in a social setting. During a subsequent functional magnetic resonance imaging session, participants viewed video clips depicting individual plays of the game that ended with the ball being released toward the basket. For each play, participants recalled whether or not the shot went into the basket. Hemodynamic signal changes time locked to correct memory decisions were analyzed as a function of emotional intensity and valence, according to the fan's perspective. Results showed intensity-modulated retrieval activity in midline cortical structures, sensorimotor cortex, the striatum, and the medial temporal lobe, including the amygdala. Positively valent memories specifically recruited processing in dorsal frontoparietal regions, and additional activity in the insula and medial temporal lobe for positively valent shots recalled with high confidence. This novel paradigm reveals how brain regions implicated in emotion, memory retrieval, visuomotor imagery, and social cognition contribute to the recollection of specific plays in the mind of a sports fan.

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DNaseI footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High-throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. Multiple computational approaches have been developed to identify DNase-seq footprints as predictors of TF binding. However, recent studies have pointed to a substantial cleavage bias of DNase and its negative impact on predictive performance of footprinting. To assess the potential for using DNase-seq to identify individual binding sites, we performed DNase-seq on deproteinized genomic DNA and determined sequence cleavage bias. This allowed us to build bias corrected and TF-specific footprint models. The predictive performance of these models demonstrated that predicted footprints corresponded to high-confidence TF-DNA interactions. DNase-seq footprints were absent under a fraction of ChIP-seq peaks, which we show to be indicative of weaker binding, indirect TF-DNA interactions or possible ChIP artifacts. The modeling approach was also able to detect variation in the consensus motifs that TFs bind to. Finally, cell type specific footprints were detected within DNase hypersensitive sites that are present in multiple cell types, further supporting that footprints can identify changes in TF binding that are not detectable using other strategies.

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Invasive rodent species have established on 80% of the world's islands causing significant damage to island environments. Insular ecosystems support proportionally more biodiversity than comparative mainland areas, highlighting them as critical for global biodiversity conservation. Few techniques currently exist to adequately detect, with high confidence, species that are trap-adverse such as the black rat, Rattus rattus, in high conservation priority areas where multiple non-target species persist. This study investigates the effectiveness of camera trapping for monitoring invasive rodents in high conservation areas, and the influence of habitat features and density of colonial-nesting seabirds on rodent relative activity levels to provide insights into their potential impacts. A total of 276 camera sites were established and left in situ for 8 days. Identified species were recorded in discrete 15 min intervals, referred to as 'events'. In total, 19 804 events were recorded. From these, 31 species were identified comprising 25 native species and six introduced. Two introduced rodent species were detected: the black rat (90% of sites), and house mouse Mus musculus (56% of sites). Rodent activity of both black rats and house mice were positively associated with the structural density of habitats. Density of seabird burrows was not strongly associated with relative activity levels of rodents, yet rodents were still present in these areas. Camera trapping enabled a large number of rodents to be detected with confidence in site-specific absences and high resolution to quantify relative activity levels. This method enables detection of multiple species simultaneously with low impact (for both target and non-target individuals); an ideal strategy for monitoring trap-adverse invasive rodents in high conservation areas.

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This paper examines a trend in European and American High Courts to endorse majority religion by transforming it into “culture”, and thus by secularizing it. To dissociate religion and state is the hallmark of the liberal state. However, no state has ever managed a perfect separation, not even the American. Under conditions of mounting religious pluralism and ongoing secularization, there is pressure on the state to live up to its “neutrality”. A main strategy to square the circle of neutrality and incomplete dissociation from religion is to declare it “culture”, which gives the state the license to associate or even identify with it (as guardian of nationhood). The paper compares recent American and European High Court rules on religious symbols (especially crucifixes) that exhibits this strategy, addressing similarities and differences as well as the limits and pitfalls of “culturalizing” religion.

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INTRODUCTION: Household food gatekeepers have the potential to influence the food attitudes and behaviours of family members, as they are mainly responsible for food-related tasks in the home. The aim of this study was to determine the role of gatekeepers' confidence in food-related skills and nutrition knowledge on food practices in the home.

METHODS: An online survey was completed by 1059 Australian dietary gatekeepers selected from the Global Market Insite (GMI) research database. Participants responded to questions about food acquisition and preparation behaviours, the home eating environment, perceptions and attitudes towards food, and demographics. Two-step cluster analysis was used to identify groups based on confidence regarding food skills and nutrition knowledge. Chi-square tests and one-way ANOVAs were used to compare the groups on the dependent variables.

RESULTS: Three groups were identified: low confidence, moderate confidence and high confidence. Gatekeepers in the highest confidence group were significantly more likely to report lower body mass index (BMI), and indicate higher importance of fresh food products, vegetable prominence in meals, product information use, meal planning, perceived behavioural control and overall diet satisfaction. Gatekeepers in the lowest confidence group were significantly more likely to indicate more perceived barriers to healthy eating, report more time constraints and more impulse purchasing practices, and higher convenience ingredient use. Other smaller associations were also found.

CONCLUSION: Household food gatekeepers with high food skills confidence were more likely to engage in several healthy food practices, while those with low food skills confidence were more likely to engage in unhealthy food practices. Food education strategies aimed at building food-skills and nutrition knowledge will enable current and future gatekeepers to make healthier food decisions for themselves and for their families.

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In humans, more than 30,000 chimeric transcripts originating from 23,686 genes have been identified. The mechanisms and association of chimeric transcripts arising from chromosomal rearrangements with cancer are well established, but much remains unknown regarding the biogenesis and importance of other chimeric transcripts that arise from nongenomic alterations. Recently, a SLC45A3–ELK4 chimera has been shown to be androgen-regulated, and is overexpressed in metastatic or high-grade prostate tumors relative to local prostate cancers. Here, we characterize the expression of a KLK4 cis sense–antisense chimeric transcript, and show other examples in prostate cancer. Using non-protein-coding microarray analyses, we initially identified an androgen-regulated antisense transcript within the 3′ untranslated region of the KLK4 gene in LNCaP cells. The KLK4 cis-NAT was validated by strand-specific linker-mediated RT-PCR and Northern blotting. Characterization of the KLK4 cis-NAT by 5′ and 3′ rapid amplification of cDNA ends (RACE) revealed that this transcript forms multiple fusions with the KLK4 sense transcript. Lack of KLK4 antisense promoter activity using reporter assays suggests that these transcripts are unlikely to arise from a trans-splicing mechanism. 5′ RACE and analyses of deep sequencing data from LNCaP cells treated ±androgens revealed six high-confidence sense–antisense chimeras of which three were supported by the cDNA databases. In this study, we have shown complex gene expression at the KLK4 locus that might be a hallmark of cis sense–antisense chimeric transcription.

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Objective To identify predictors for initiating and maintaining active commuting (AC) to work following the 2003 Australia's Walk to Work Day (WTWD) campaign. Methods Pre- and post-campaign telephone surveys of a cohort of working age (18–65years) adults (n = 1100, 55% response rate). Two dependent campaign outcomes were assessed: initiating or maintaining AC (i.e., walk/cycle and public transport) on a single day (WTWD), and increasing or maintaining health-enhancing active commuting (HEAC) level (≥ 30min/day) in a usual week following WTWD campaign. Results A significant population-level increase in HEAC (3.9%) was observed (McNemar's χ2 = 6.53, p = 0.01) with 136 (19.0%) achieving HEAC at post campaign. High confidence in incorporating walking into commute, being active pre-campaign and younger age (< 46years) were positively associated with both outcomes. The utility of AC for avoiding parking hassles (AOR = 2.1, 95% CI: 1.2–3.6), for less expense (AOR = 1.8, 95% CI: 1.1–3.1), for increasing one's health (AOR = 2.5, 95% CI: 1.1–5.6) and for clean air (AOR = 2.2, 95% CI: 1.0–4.4) predicted HEAC outcome whereas avoiding the stress of driving (AOR = 2.6, 95% CI: 1.4–5.0) and the hassle of parking predicted the single-day AC. Conclusions Transportation interventions targeting parking and costs could be further enhanced by emphasizing health benefits of AC. AC was less likely to occur among inactive employees.

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We present an approach for detecting sensor spoofing attacks on a cyber-physical system. Our approach consists of two steps. In the first step, we construct a safety envelope of the system. Under nominal conditions (that is, when there are no attacks), the system always stays inside its safety envelope. In the second step, we build an attack detector: a monitor that executes synchronously with the system and raises an alarm whenever the system state falls outside the safety envelope. We synthesize safety envelopes using a modified machine learning procedure applied on data collected from the system when it is not under attack. We present experimental results that show effectiveness of our approach, and also validate the several novel features that we introduced in our learning procedure.

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In the present study, items pre-exposed in a familiarization series were included in a list discrimination task to manipulate memory strength. At test, participants were required to discriminate strong targets and strong lures from weak targets and new lures. This resulted in a concordant pattern of increased "old" responses to strong targets and lures. Model estimates attributed this pattern to either equivalent increases in memory strength across the two types of items (unequal variance signal detection model) or equivalent increases in both familiarity and recollection (dual process signal detection [DPSD] model). Hippocampal activity associated with strong targets and lures showed equivalent increases compared with missed items. This remained the case when analyses were restricted to high-confidence responses considered by the DPSD model to reflect predominantly recollection. A similar pattern of activity was observed in parahippocampal cortex for high-confidence responses. The present results are incompatible with "noncriterial" or "false" recollection being reflected solely in inflated DPSD familiarity estimates and support a positive correlation between hippocampal activity and memory strength irrespective of the accuracy of list discrimination, consistent with the unequal variance signal detection model account.