Establishing a minimum dataset for prospective registration of systematic reviews: an international consultation

Background: In response to growing recognition of the value of prospective registration of systematic review protocols, we planned to develop a web-based open access international register. In order for the register to fulfil its aims of reducing unplanned duplication, reducing publication bias, and providing greater transparency, it was important to ensure the appropriate data were collected. We therefore undertook a consultation process with experts in the field to identify a minimum dataset for registration. Methods and Findings: A two-round electronic modified Delphi survey design was used. The international panel surveyed included experts from areas relevant to systematic review including commissioners, clinical and academic researchers, methodologists, statisticians, information specialists, journal editors and users of systematic reviews. Direct invitations to participate were sent out to 315 people in the first round and 322 in the second round. Responses to an open invitation to participate were collected separately. There were 194 (143 invited and 51 open) respondents with a 100% completion rate in the first round and 209 (169 invited and 40 open) respondents with a 91% completion rate in the second round. In the second round, 113 (54%) of the participants reported having previously taken part in the first round. Participants were asked to indicate whether a series of potential items should be designated as optional or required registration items, or should not be included in the register. After the second round, a 70% or greater agreement was reached on the designation of 30 of 36 items. Conclusions: The results of the Delphi exercise have established a dataset of 22 required items for the prospective registration of systematic reviews, and 18 optional items. The dataset captures the key attributes of review design as well as the administrative details necessary for registration.

SVM Training Phase Reduction Using Dataset Feature Filtering for Malware Detection

N-gram analysis is an approach that investigates the structure of a program using bytes, characters, or text strings. A key issue with N-gram analysis is feature selection amidst the explosion of features that occurs when N is increased. The experiments within this paper represent programs as operational code (opcode) density histograms gained through dynamic analysis. A support vector machine is used to create a reference model, which is used to evaluate two methods of feature reduction, which are 'area of intersect' and 'subspace analysis using eigenvectors.' The findings show that the relationships between features are complex and simple statistics filtering approaches do not provide a viable approach. However, eigenvector subspace analysis produces a suitable filter.

Testate amoebae (thecamoebians) as water quality indicators in lakes: development of a modern distributional dataset from the Greater Toronto Area

Thecamoebians were examined from 123 surface sediment samples collected from 45 lakes in the Greater Toronto Area (GTA) and the surrounding region to i) elucidate the controls on faunal distribution in modern lake environments; and ii) to consider the utility of thecamoebians in quantitative studies of water quality change. This area was chosen because it includes a high density of lakes that are threatened by urban development and where water quality has deteriorated locally as a result of contaminant inputs, particularly nutrients. Canonical Correspondence analysis (CCA) and a series of partial CCAs were used to examine species-environment relationships. Twenty-four environmental variables were considered, including water properties (e.g. pH, DO, conductivity), substrate characteristics, nutrient loading, and environmentally available metals. The thecamoebian assemblages showed a strong association with Olsen's Phosphorus, reflecting the eutrophic status of many of the lakes, and locally to elevated conductivity measurements, which appear to reflect road salt inputs associated with winter de-icing operations. A transfer function was developed for Olsen P using this training set based on weighted averaging with inverse deshrinking (WA Inv). The model was applied to infer past changes in Phosphorus enrichment in core samples from several lakes, including eutrophic Haynes Lake within the GTA. Thecamoebian-inferred changes in sedimentary Phosphorus from a 210Pb dated core from Haynes Lake are related to i) widespread introduction of chemical fertilizers to agricultural land in the post WWII era; ii) a steep decline in Phosphorous with a change in agricultural practices in the late 1970s; and iii) the construction of a golf course in close proximity to the lake in the early 1990s. This preliminary study confirms that thecamoebians have considerable potential as indicators of eutrophication in lakes and can provide an estimate of baseline conditions.

No evidence that runs of homozygosity are associated with schizophrenia in an Irish genome-wide association dataset

Runs of homozygosity (ROH), regions of the genome containing many consecutive homozygous SNPs, may represent two copies of a haplotype inherited from a common ancestor. A rare variant on this haplotype could thus be present in a homozygous and potentially recessive state. To detect rare risk variants for schizophrenia, we performed an ROH analysis in a homogeneous Irish genome wide association study (GWAS) dataset consisting of 1606 cases and 1794 controls. There was no genome-wide excess of ROH in cases compared to controls (p=0.7986). No consensus ROH at individual loci showed association with schizophrenia after genome-wide correction.

Assessment of Polycyclic Aromatic Hydrocarbons in an Urban Soil Dataset

We compare a suite of Polycyclic Aromatic Hydrocarbons (Parent PAHs) in soils and air across an urban area (Belfast UK). Isomeric PAH ratios suggest that soil PAHs are mainly from a combustion source. Fugacity modelling across a range of soil temperatures predicts that four ring and larger PAHs from pyrene to indeno[1,2,3–cd]pyrene all partition strongly (>98%) to the soil compartment. This modelling also implies that these PAHs do not experience losses through partitioning to other phases (air, water) due to soil temperature effects. Such modelling may help in understanding the overall contaminantdistribution in soils. The air and soil data together with modelling suggests that care must be taken when considering isomeric ratios of compounds with mass lighter than 178 (i.e. phenanthrene and anthracene) in the soil phase. Comparison of duplicate and replicate samples suggest that field sampling of duplicates dominates uncertainty and validated methodologies for selection of field duplicates and lab splitting are required. As the urban soil four ring PAHs are at equilibrium in the soil phase, and have characteristic ratios that are dominated by a combustion source that is a single controlling factor over spatial distribution, methods that calculate background concentrations can be compared.

Data-Augmentation for Reducing Dataset Bias in Person Re-identification

In this paper we explore ways to address the issue of dataset bias in person re-identification by using data augmentation to increase the variability of the available datasets, and we introduce a novel data augmentation method for re-identification based on changing the image background. We show that use of data augmentation can improve the cross-dataset generalisation of convolutional network based re-identification systems, and that changing the image background yields further improvements.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost.

Testing solar forcing of pervasive Holocene climate cycles

The temporal and spatial extent of Holocene climate change is an area of considerable uncertainty, with solar forcing recently proposed to be the origin of cycles identified in the North Atlantic region. To address these issues we have developed an annually resolved record of changes in Irish bog tree populations over the last 7468 years which, together with radiocarbon-dated bog and lake-edge populations, extend the dataset back to 9000 yr ago. The Irish trees underpin the internationally accepted radiocarbon calibration curve, used to derive a proxy of solar activity, and allow us to test solar forcing of Holocene climate change. Tree populations and age structures provide unambiguous evidence of major shifts in Holocene surface moisture, with a dominant cyclicity of 800 yr, similar to marine cycles in the North Atlantic, indicating significant changes in the latitude and intensity of zonal atmospheric circulation across the region. The cycles, however, are not coherent with changes in solar activity (both being on the same absolute timescale), indicating that Holocene North Atlantic climate variability at the millennial and centennial scale is not driven by a linear response to changes in solar activity.