Temporal synchrony is an effective cue for grouping and segmentation in the absence of form cues

The synchronous change of a feature across multiple discrete elements, i.e., temporal synchrony, has been shown to be a powerful cue for grouping and segmentation. This has been demonstrated with both static and dynamic stimuli for a range of tasks. However, in addition to temporal synchrony, stimuli in previous research have included other cues which can also facilitate grouping and segmentation, such as good continuation and coherent spatial configuration. To evaluate the effectiveness of temporal synchrony for grouping and segmentation in isolation, here we measure signal detection thresholds using a global-Gabor stimulus in the presence/absence of a synchronous event. We also examine the impact of the spatial proximity of the to-begrouped elements on the effectiveness of temporal synchrony, and the duration for which elements are bound together following a synchronous event in the absence of further segmentation cues. The results show that temporal synchrony (in isolation) is an effective cue for grouping local elements together to extract a global signal. Further, we find that the effectiveness of temporal synchrony as a cue for segmentation is modulated by the spatial proximity of signal elements. Finally, we demonstrate that following a synchronous event, elements are perceptually bound together for an average duration of 200 ms

Best practices and software for themanagement and sharing of camera trap data for small and large scales studies

Camera traps typically generate large amounts of bycatch data of non-target species that are secondary to the study’s objectives. Bycatch data pooled from multiple studies can answer secondary research questions; however, variation in field and data management techniques creates problems when pooling data from multiple sources. Multi-collaborator projects that use standardized methods to answer broad-scale research questions are rare and limited in geographical scope. Many small, fixed-term independent camera trap studies operate in poorly represented regions, often using field and data management methods tailored to their own objectives. Inconsistent data management practices lead to loss of bycatch data, or an inability to share it easily. As a case study to illustrate common problems that limit use of bycatch data, we discuss our experiences processing bycatch data obtained by multiple research groups during a range-wide assessment of sun bears Helarctos malayanus in Southeast Asia. We found that the most significant barrier to using bycatch data for secondary research was the time required, by the owners of the data and by the secondary researchers (us), to retrieve, interpret and process data into a form suitable for secondary analyses. Furthermore, large quantities of data were lost due to incompleteness and ambiguities in data entry. From our experiences, and from a review of the published literature and online resources, we generated nine recommendations on data management best practices for field site metadata, camera trap deployment metadata, image classification data and derived data products. We cover simple techniques that can be employed without training, special software and Internet access, as well as options for more advanced users, including a review of data management software and platforms. From the range of solutions provided here, researchers can employ those that best suit their needs and capacity. Doing so will enhance the usefulness of their camera trap bycatch data by improving the ease of data sharing, enabling collaborations and expanding the scope of research

An extended set of PRDM1/BLIMP1 target genes links binding motif type to dynamic repression

The transcriptional repressor B lymphocyte-induced maturation protein-1 (BLIMP1) regulates gene expression and cell fate. The DNA motif bound by BLIMP1 in vitro overlaps with that of interferon regulatory factors (IRFs), which respond to inflammatory/immune signals. At such sites, BLIMP1 and IRFs can antagonistically regulate promoter activity. In vitro motif selection predicts that only a subset of BLIMP1 or IRF sites is subject to antagonistic regulation, but the extent to which antagonism occurs is unknown, since an unbiased assessment of BLIMP1 occupancy in vivo is lacking. To address this, we identified an extended set of promoters occupied by BLIMP1. Motif discovery and enrichment analysis demonstrate that multiple motif variants are required to capture BLIMP1 binding specificity. These are differentially associated with CpG content, leading to the observation that BLIMP1 DNA-binding is methylation sensitive. In occupied promoters, only a subset of BLIMP1 motifs overlap with IRF motifs. Conversely, a distinct subset of IRF motifs is not enriched amongst occupied promoters. Genes linked to occupied promoters containing overlapping BLIMP1/IRF motifs (e.g. AIM2, SP110, BTN3A3) are shown to constitute a dynamic target set which is preferentially activated by BLIMP1 knock-down. These data confirm and extend the competitive model of BLIMP1 and IRF interaction

Expanding ART for Treatment and Prevention of HIV in South Africa: Estimated Cost and Cost-Effectiveness 2011-2050

Background: Antiretroviral Treatment (ART) significantly reduces HIV transmission. We conducted a cost-effectiveness analysis of the impact of expanded ART in South Africa. Methods: We model a best case scenario of 90% annual HIV testing coverage in adults 15-49 years old and four ART eligibility scenarios: CD4 count <200 cells/mm3(current practice), CD4 count <350, CD4 count <500, all CD4 levels. 2011-2050 outcomes include deaths, disability adjusted life years (DALYs), HIV infections, cost, and cost per DALY averted. Service and ART costs reflect South African data and international generic prices. ART reduces transmission by 92%. We conducted sensitivity analyses. Results: Expanding ART to CD4 count <350 cells/mm3prevents an estimated 265,000 (17%) and 1.3 million (15%) new HIV infections over 5 and 40 years, respectively. Cumulative deaths decline 15%, from 12.5 to 10.6 million; DALYs by 14% from 109 to 93 million over 40 years. Costs drop $504 million over 5 years and$3.9 billion over 40 years with breakeven by 2013. Compared with the current scenario, expanding to <500 prevents an additional 585,000 and 3 million new HIV infections over 5 and 40 years, respectively. Expanding to all CD4 levels decreases HIV infections by 3.3 million (45%) and costs by $10 billion over 40 years, with breakeven by 2023. By 2050, using higher ART and monitoring costs, all CD4 levels saves$0.6 billion versus current; other ART scenarios cost $9-194 per DALY averted. If ART reduces transmission by 99$17.5 billion. Sensitivity analyses suggest that poor retention and predominant acute phase transmission reduce DALYs averted by 26% and savings by 7%. Conclusion: Increasing the provision of ART to <350 cells/mm3 may significantly reduce costs while reducing the HIV burden. Feasibility including HIV testing and ART uptake, retention, and adherence should be evaluated

The National Early Warning Score and its subcomponents recorded within ±24 hours of emergency medical admission are poor predictors of hospital-acquired acute kidney injury

YesBackground: Hospital-acquired Acute Kidney Injury (H-AKI) is a common cause of avoidable morbidity and mortality. Aim: To determine if the patients’ vital signs data as defined by a National Early Warning Score (NEWS), can predict H-AKI following emergency admission to hospital. Methods: Analyses of emergency admissions to York hospital over 24-months with NEWS data. We report the area under the curve (AUC) for logistic regression models that used the index NEWS (model A0), plus age and sex (A1), plus subcomponents of NEWS (A2) and two-way interactions (A3). Likewise for maximum NEWS (models B0,B1,B2,B3). Results: 4.05% (1361/33608) of emergency admissions had H-AKI. Models using the index NEWS had the lower AUCs (0.59 to 0.68) than models using the maximum NEWS AUCs (0.75 to 0.77). The maximum NEWS model (B3) was more sensitivity than the index NEWS model (A0) (67.60% vs 19.84%) but identified twice as many cases as being at risk of H-AKI (9581 vs 4099) at a NEWS of 5. Conclusions: The index NEWS is a poor predictor of H-AKI. The maximum NEWS is a better predictor but seems unfeasible because it is only knowable in retrospect and is associated with a substantial increase in workload albeit with improved sensitivity.The Health Foundatio

A Multivariate Bayesian Approach to Modeling Vulnerability Discovery in the Software Security Lifecycle

Software vulnerabilities that enable well-known exploit techniques for committing computer crimes are preventable, but they continue to be present in releases. When Blackhats (i.e., malicious researchers) discover these vulnerabilities they oftentimes release corresponding exploit software and malware. If vulnerabilities—or discoveries of them—are not prevented, mitigated, or addressed, customer confidence could be reduced. In addressing the issue, software-makers must choose which mitigation alternatives will provide maximal impact and use vulnerability discovery modeling (VDM) techniques to support their decision-making process. In the literature, applications of these techniques have used traditional approaches to analysis and, despite the dearth of data, have not included information from experts and do not include influential variables describing the software release (SR) (e.g., code size and complexity characteristics) and security assessment profile (SAP) (e.g., security team size or skill). Consequently, they have been limited to modeling discoveries over time for SR and SAP scenarios of unique products, whose results are not readily comparable without making assumptions that equate all SR and SAP combinations under study. This research takes an alternative approach, applying Bayesian methods to modeling the vulnerability-discovery phenomenon. Relevant data were obtained from expert judgment (i.e., information elicited from security experts in structured workshops) and from public databases. The open-source framework, MCMCBayes, was developed to perform Bayesian model averaging (BMA). It combines predictions of interval-grouped discoveries by performance-weighting results from six variants of the non-homogeneous Poisson process, two regression models, and two growth-curve models. Utilizing expert judgment also enables forecasting expected discoveries over time for arbitrary SR and SAP combinations, thus helping software-makers to better understand the effects of influential variables they control on the phenomenon. This requires defining variables that describe arbitrary SR and SAP combinations as well as constructing VDM extensions that parametrically scale results from a defined baseline SR and SAP to the arbitrary SR and SAP of interest. Scaling parameters were estimated using elicited multivariate data gathered with a novel paired comparison approach. MCMCBayes uses the multivariate data with the BMA model for the baseline to perform predictions for desired SR and SAP combinations and to demonstrate how multivariate VDM techniques could be used. The research is applicable to software-makers and persons interested in applications of expert-judgment elicitation or those using Bayesian analysis techniques with phenomena having non-decreasing counts over time

Temporal synchrony is an effective cue for grouping and segmentation in the absence of form cues

The synchronous change of a feature across multiple discrete elements, i.e., temporal synchrony, has been shown to be a powerful cue for grouping and segmentation. This has been demonstrated with both static and dynamic stimuli for a range of tasks. However, in addition to temporal synchrony, stimuli in previous research have included other cues which can also facilitate grouping and segmentation, such as good continuation and coherent spatial configuration. To evaluate the effectiveness of temporal synchrony for grouping and segmentation in isolation, here we measure signal detection thresholds using a global-Gabor stimulus in the presence/absence of a synchronous event. We also examine the impact of the spatial proximity of the to-begrouped elements on the effectiveness of temporal synchrony, and the duration for which elements are bound together following a synchronous event in the absence of further segmentation cues. The results show that temporal synchrony (in isolation) is an effective cue for grouping local elements together to extract a global signal. Further, we find that the effectiveness of temporal synchrony as a cue for segmentation is modulated by the spatial proximity of signal elements. Finally, we demonstrate that following a synchronous event, elements are perceptually bound together for an average duration of 200 ms