Old truths and new politics:Does truth commission 'publicness' impact democratization?

This article analyzes the relationship between truth and politics by asking whether the 'publicness' of a truth commission - defined by whether it has public hearings, releases a public report, and names perpetrators - contributes to democratization. The article reviews scholarship relevant to the potential democratizing effects of truth commissions and derives mechanisms that help explain this relationship. Work from the transitional justice field as well as democratization and political transition more generally is considered. Using a newly-constructed Truth Commission Publicness Dataset (TCPD), the analysis finds that even after statistically controlling for initial levels of democracy, democratic trends in the years prior to a commission, level of wealth, amnesties and/or trials, the influence of the South African Truth and Reconciliation Commission, and different cutoff points for measuring democratization across a number of models, more publicness predicts higher levels of democracy years after the commission has finished its work. The more public a truth commission is, the more it will contribute to democratization. The finding that more public truth commissions are associated with higher levels of democratization indicates particular strategies that policymakers, donors, and civil society activists may take to improve prospects for democracy in a country planning a truth commission in the wake of violence and/or government abuse. © The Author(s) 2012.

Testing the cause of the Sphagnum austinii (Sull. ex Aust.) decline: Multiproxy evidence from a raised bog in Northern Ireland

We use a multiproxy palaeoecological dataset from Dead Island bog in Northern Ireland to examine the cause of the Sphagnum austinii (Sphagnum imbricatum) decline. The disappearance of this species from the peat record occurred just after the ‘AD 860’ tephra layer and is coeval with a rapid increase in bog surface wetness and increased mineral dust and charcoal abundance. Although it is difficult to identify one specific cause of the decline, the evidence for increased soil-derived dust is apparent and is supported by regional tephra-dated pollen diagrams that reveal extensive landscape changes due to agricultural intensification in early Medieval Ireland. As the decline of S. austinii occurred much later (~ AD 1860) in Fallahogy bog (~ 1.2 km away), we suggest that the decline of S. austinii at Dead Island was caused by a combination of fire and the deposition of soil-derived dust. We suggest that future studies should consider the use of multiple cores from each site to examine the within-site variability of the decline of S. austinii.

Sediment accumulation rates in subarctic lakes: insights into age-depth modeling from 22 dated lake records from the Northwest Territories, Canada

Age-depth modeling using Bayesian statistics requires well-informed prior information about the behavior of sediment accumulation. Here we present average sediment accumulation rates (represented as deposition times, DT, in yr/cm) for lakes in an Arctic setting, and we examine the variability across space (intra- and inter-lake) and time (late Holocene). The dataset includes over 100 radiocarbon dates, primarily on bulk sediment, from 22 sediment cores obtained from 18 lakes spanning the boreal to tundra ecotone gradients in subarctic Canada. There are four to twenty-five radiocarbon dates per core, depending on the length and character of the sediment records. Deposition times were calculated at 100-year intervals from age-depth models constructed using the ‘classical’ age-depth modeling software Clam. Lakes in boreal settings have the most rapid accumulation (mean DT 20 ± 10 years), whereas lakes in tundra settings accumulate at moderate (mean DT 70 ± 10 years) to very slow rates, (>100 yr/cm). Many of the age-depth models demonstrate fluctuations in accumulation that coincide with lake evolution and post-glacial climate change. Ten of our sediment cores yielded sediments as old as c. 9,000 cal BP (BP = years before AD 1950). From between c. 9,000 cal BP and c. 6,000 cal BP, sediment accumulation was relatively rapid (DT of 20 to 60 yr/cm). Accumulation slowed between c. 5,500 and c. 4,000 cal BP as vegetation expanded northward in response to warming. A short period of rapid accumulation occurred near 1,200 cal BP at three lakes. Our research will help inform priors in Bayesian age modeling.

The cross-section of stock returns in an early stock market

Using a new dataset which contains monthly data on 1015 stocks traded on the London Stock Exchange between 1825 and 1870, we investigate the cross section of stock returns in this early capital market. Unique features of this market allow us to evaluate the veracity of several popular explanations of asset pricing behavior. Using portfolio analysis and Fama–MacBeth regressions, we find that stock characteristics such as beta, illiquidity, dividend yield, and past-year return performance are all positively correlated with stock returns. However, market capitalization and past-three-year return performance have no significant correlation with stock returns.

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.

Genome Wide Association Mapping of Grain Arsenic, Copper, Molybdenum and Zinc in Rice (Oryza sativa L.) Grown at Four International Field Sites

The mineral concentrations in cereals are important for human health, especially for individuals who consume a cereal subsistence diet. A number of elements, such as zinc, are required within the diet, while some elements are toxic to humans, for example arsenic. In this study we carry out genome-wide association (GWA) mapping of grain concentrations of arsenic, copper, molybdenum and zinc in brown rice using an established rice diversity panel of,300 accessions and 36.9 k single nucleotide polymorphisms (SNPs). The study was performed across five environments: one field site in Bangladesh, one in China and two in the US, with one of the US sites repeated over two years. GWA mapping on the whole dataset and on separate subpopulations of rice revealed a large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc. Seventeen of these loci were detected in data obtained from grain cultivated in more than one field location, and six co-localise with previously identified quantitative trait loci. Additionally, a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs (within 200 kb, the estimated global linkage disequilibrium previously employed in this rice panel). This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally-variable traits in a highly genetically structured diversity panel.

MiR-433 induces cellular senescence rendering ovarian cancer cells less likely to undergo chemotherapy-induced apoptosis

Annually, ovarian cancer (OC) affects 240,000 women worldwide and is the most lethal gynaecological malignancy. Such mortality is predominantly associated with the development of an intrinsic and acquired resistance to chemotherapy, the lack of targeted therapies and the lack of biomarkers predicting therapeutic response.

Our clinical data demonstrates that increased miR-433 expression in primary high grade serous OC (HGSOCs) is significantly associated with poor PFS (n=46, p=0.024). Interestingly, the IHC analysis of two miR-433 targets: MAD2 [Furlong et al., 2012 PMID:22069160] and HDAC6 shows that low IHC levels of both proteins is also significantly associated with worse outcome (p=0.002 and 0.002 respectively; n=43). Additionally, the analysis of miR 433 in the publicly available TCGA dataset corroborates that high miR-433 is significantly correlated with worse OS for patients presenting with OC (n=558 and p=0.027). In vitro, in a panel of OC cell lines, higher miR-433 and lower MAD2 and HDAC6 levels were associated with resistance to paclitaxel.

To further investigate the role of miR-433 in the cellular response to chemotherapy, we generated an OC cell line stably expressing miR-433, or miR-control. MTT viability assays and Western Blot analyses established that miR-433 cells were more resistant to paclitaxel treatment (50nM) compared to miR-controls. Importantly, we have shown for the first time that miR 433 induced senescence, exemplified by a flattened morphology and down-regulation of phosphorylated Retinoblastoma (p-Rb), a molecular marker of senescence. Surprisingly, miR 433 induced senescence was independent from two well recognised senescent drivers: namely p53/p21 and p16. To explore this further we performed an in silico analysis of seven microRNA platforms which indicated that miR 433 potentially targets Cyclin-dependent kinase CDK6, which promotes sustained phosphorylation of Rb and thus cell cycle progression. In vitro, the overexpression of pre-miR-433 resulted in diminished CDK6 expression demonstrating a novel interaction between miR-433 and CDK6.

In conclusion, this study demonstrates that high miR-433 expression predicts poor outcome in OC patients by putatively rendering OC cells resistant to paclitaxel treatment through the induction of cellular senescence identifying this microRNA as a potential marker of chemoresponse.

MIR-433 Predicts poor response to chemotherapy in ovarian cancer patients by the induction of cellular senescence

Annually, ovarian cancer (OC) affects 240,000 women worldwide and is the most lethal gynaecological malignancy. Such mortality is predominantly associated with the development of an intrinsic and acquired resistance to chemotherapy, the lack of targeted therapies and the lack of biomarkers predicting response to standard treatment.

Our clinical data demonstrates that increased miR-433 expression in primary high grade serous OC (HGSOCs) is significantly associated with poor PFS (n=46, p=0.024). Interestingly, the IHC analysis of two miR-433 targets: MAD2 [1] and HDAC6 shows that low IHC levels of both proteins is also significantly associated with worse outcome (p=0.002 and 0.002 respectively; n=43). Additionally, the analysis of miR 433 in the publicly available TCGA dataset corroborates that high miR-433 is significantly correlated with worse OS for patients presenting with OC (n=558 and p=0.027). In vito, in a panel of OC cell lines, higher miR-433 and lower MAD2 and HDAC6 levels were associated with resistance to paclitaxel.

To further investigate the role of miR-433 in the cellular response to chemotherapy, we generated an OC cell line stably expressing miR-433 or miR-control. MTT viability assays and Western Blot analyses established that miR-433 cells were more resistant to paclitaxel treatment (50nM) compared to miR-controls. Importantly, we have shown for the first time that miR 433 induced senescence resulting in a chracteristic flattened morphology and down-regulation of phosphorylated Retinoblastoma (p Rb), a molecular marker of senescence. Surprisingly, miR 433 induced senescence was independent from two well recognised senescent drivers: namely p53/p21 and p16. To explore this further we performed an in silico analysis of seven microRNA platforms which indicated that miR 433 potentially targets Cyclin-dependent kinase CDK6, which promotes sustained phosphorylation of Rb and thus cell cycle progression. In vitro, the overexpression of pre-miR-433 resulted in diminished CDK6 expression demonstrating a novel interaction between miR-433 and CDK6.

In conclusion, this study demonstrates that high miR-433 expression predicts poor outcome in OC patients by putatively rendering OC cells resistant to paclitaxel treatment through the induction of cellular senescence identifying this microRNA as a potential marker of chemoresponse.

Cross-participant modelling based on joint or disjoint feature selection: an fMRI conceptual decoding study

Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.

Turbo-smt: Accelerating coupled sparse matrix-tensor factorizations by 200x

How can we correlate the neural activity in the human brain as it responds to typed words, with properties of these terms (like ‘edible’, ‘fits in hand’)? In short, we want to find latent variables, that jointly explain both the brain activity, as well as the behavioral responses. This is one of many settings of the Coupled Matrix-Tensor Factorization (CMTF) problem.

Can we accelerate any CMTF solver, so that it runs within a few minutes instead of tens of hours to a day, while maintaining good accuracy? We introduce Turbo-SMT, a meta-method capable of doing exactly that: it boosts the performance of any CMTF algorithm, by up to 200x, along with an up to 65 fold increase in sparsity, with comparable accuracy to the baseline.

We apply Turbo-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Turbo-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy.

Bayesian network data imputation with application to survival tree analysis

Retrospective clinical datasets are often characterized by a relatively small sample size and many missing data. In this case, a common way for handling the missingness consists in discarding from the analysis patients with missing covariates, further reducing the sample size. Alternatively, if the mechanism that generated the missing allows, incomplete data can be imputed on the basis of the observed data, avoiding the reduction of the sample size and allowing methods to deal with complete data later on. Moreover, methodologies for data imputation might depend on the particular purpose and might achieve better results by considering specific characteristics of the domain. The problem of missing data treatment is studied in the context of survival tree analysis for the estimation of a prognostic patient stratification. Survival tree methods usually address this problem by using surrogate splits, that is, splitting rules that use other variables yielding similar results to the original ones. Instead, our methodology consists in modeling the dependencies among the clinical variables with a Bayesian network, which is then used to perform data imputation, thus allowing the survival tree to be applied on the completed dataset. The Bayesian network is directly learned from the incomplete data using a structural expectation–maximization (EM) procedure in which the maximization step is performed with an exact anytime method, so that the only source of approximation is due to the EM formulation itself. On both simulated and real data, our proposed methodology usually outperformed several existing methods for data imputation and the imputation so obtained improved the stratification estimated by the survival tree (especially with respect to using surrogate splits).

Evaluating the use of testate amoebae for palaeohydrological reconstruction in permafrost peatlands

The melting of high-latitude permafrost peatlands is a major concern due to a potential positive feedback on global climate change. We examine the ecology of testate amoebae in permafrost peatlands, based on sites in Sweden (~ 200 km north of the Arctic Circle). Multivariate statistical analysis confirms that water-table depth and moisture content are the dominant controls on the distribution of testate amoebae, corroborating the results from studies in mid-latitude peatlands. We present a new testate amoeba-based water table transfer function and thoroughly test it for the effects of spatial autocorrelation, clustered sampling design and uneven sampling gradients. We find that the transfer function has good predictive power; the best-performing model is based on tolerance-downweighted weighted averaging with inverse deshrinking (performance statistics with leave-one-out cross validation: R2 = 0.87, RMSEP = 5.25 cm). The new transfer function was applied to a short core from Stordalen mire, and reveals a major shift in peatland ecohydrology coincident with the onset of the Little Ice Age (c. AD 1400). We also applied the model to an independent contemporary dataset from Stordalen and find that it outperforms predictions based on other published transfer functions. The new transfer function will enable palaeohydrological reconstruction from permafrost peatlands in Northern Europe, thereby permitting greatly improved understanding of the long-term ecohydrological dynamics of these important carbon stores as well as their responses to recent climate change.

A randomised controlled trial evaluation of the Lifestart parenting programme in Ireland

This randomised controlled trial evaluated the impact of the Lifestart parenting initiative, a five-year home visiting programme, on parent and child outcomes. 424 parents and children aged less than 12 months were recruited from across Ireland and randomly assigned to either the intervention or control group. The intervention group received the programme for five years; the control group did not, but continued as normal. Both groups were tested at three time points: pre-test, mid-point (child aged 3 years) and post-test (child aged 5 years). Post-test data collection is still on-going and will be completed by November 2014. Indicative findings (using available data) are presented here, however the analysis of the full dataset will be presented at the April 2015 meeting.

Consensus and Confusion in Molluscan Trees: Evaluating Morphological and Molecular Phylogenies

Mollusks are the most morphologically disparate living animal phylum, they have diversified into all habitats, and have a deep fossil record. Monophyly and identity of their eight living classes is undisputed, but relationships between these groups and patterns of their early radiation have remained elusive. Arguments about traditional morphological phylogeny focus on a small number of topological concepts but often without regard to proximity of the individual classes. In contrast, molecular studies have proposed a number of radically different, inherently contradictory, and controversial sister relationships. Here, we assembled a dataset of 42 unique published trees describing molluscan interrelationships. We used these data to ask several questions about the state of resolution of molluscan phylogeny compared to a null model of the variation possible in random trees constructed from a monophyletic assemblage of eight terminals. Although 27 different unique trees have been proposed from morphological inference, the majority of these are not statistically different from each other. Within the available molecular topologies, only four studies to date have included the deep-sea class Monoplacophora; but 36.4% of all trees are not significantly different. We also present supertrees derived from 2 data partitions and 3 methods, including all available molecular molluscan phylogenies, which will form the basis for future hypothesis testing. The supertrees presented here were not constructed to provide yet another hypothesis of molluscan relationships, but rather to algorithmically evaluate the relationships present in the disparate published topologies. Based on the totality of available evidence, certain patterns of relatedness among constituent taxa become clear. The internodal distance is consistently short between a few taxon pairs, particularly supporting the relatedness of Monoplacophora and the chitons, Polyplacophora. Other taxon pairs are rarely or never found in close proximity, such as the vermiform Caudofoveata and Bivalvia. Our results have specific utility for guiding constructive research planning in order to better test relationships in Mollusca as well as other problematic groups. Taxa with consistently proximate relationships should be the focus of a combined approach in a concerted assessment of potential genetic and anatomical homology, while unequivocally distant taxa will make the most constructive choices for exemplar selection in higher-level phylogenomic analyses.

Ellerman Bombs with Jets: Cause and Effect

Ellerman Bombs (EBs) are thought to arise as a result of photospheric magnetic reconnection. We use data from the Swedish 1-m Solar Telescope(SST), to study EB events on the solar disk and at the limb. Both datasets show that EBs are connected to the foot-points of forming chromospheric jets. The limb observations show that a bright structure in the H$\alpha$ blue wing connects to the EB initially fuelling it,leading to the ejection of material upwards. The material moves along a loop structure where a newly formed jet is subsequently observed in the red wing of H$\alpha$. In the disk dataset, an EB initiates a jet which propagates away from the apparent reconnection site within the EB flame.The EB then splits into two, with associated brightenings in the inter-granular lanes (IGLs). Micro-jets are then observed, extending to500 km with a lifetime of a few minutes. Observed velocities of themicro-jets are approximately 5-10 km s$^{-1}$, while their chromospheric counterparts range from 50-80 km s$^{-1}$. MURaM simulations of quiet Sun reconnection show that micro-jets with similar properties to that of the observations follow the line of reconnection in the photosphere,with associated H$\alpha$ brightening at the location of increased temperature.