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"Robinson, D"
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The Italic people of ancient Apulia : new evidence from pottery for workshops, markets, and customs
\"The focus of this book is on the Italic people of Apulia during the fourth century BC, when Italic culture seems to have reached its peak of affluence. Scholars have largely ignored these people and the region they inhabited. During the past several decades archaeologists have made significant progress in revealing the cultures of Apulia through excavations of habitation sites and un-plundered tombs, often published in Italian journals. This book makes the broad range of recent scholarship--from new excavations and contexts to archaeometric testing of production hypotheses to archaeological evidence for reconsidering painter attributions--available to English-speaking audiences. In it thirteen scholars from Italy, the United States, Great Britain, France, and Australia present targeted essays on aspects of the cultures of the Italic people of Apulia during the fourth century BC and the surrounding decades\"-- Provided by publisher.
Book
The diversity and evolution of ecological and environmental citizen science
Citizen science-the involvement of volunteers in data collection, analysis and interpretation-simultaneously supports research and public engagement with science, and its profile is rapidly rising. Citizen science represents a diverse range of approaches, but until now this diversity has not been quantitatively explored. We conducted a systematic internet search and discovered 509 environmental and ecological citizen science projects. We scored each project for 32 attributes based on publicly obtainable information and used multiple factor analysis to summarise this variation to assess citizen science approaches. We found that projects varied according to their methodological approach from 'mass participation' (e.g. easy participation by anyone anywhere) to 'systematic monitoring' (e.g. trained volunteers repeatedly sampling at specific locations). They also varied in complexity from approaches that are 'simple' to those that are 'elaborate' (e.g. provide lots of support to gather rich, detailed datasets). There was a separate cluster of entirely computer-based projects but, in general, we found that the range of citizen science projects in ecology and the environment showed continuous variation and cannot be neatly categorised into distinct types of activity. While the diversity of projects begun in each time period (pre 1990, 1990-99, 2000-09 and 2010-13) has not increased, we found that projects tended to have become increasingly different from each other as time progressed (possibly due to changing opportunities, including technological innovation). Most projects were still active so consequently we found that the overall diversity of active projects (available for participation) increased as time progressed. Overall, understanding the landscape of citizen science in ecology and the environment (and its change over time) is valuable because it informs the comparative evaluation of the 'success' of different citizen science approaches. Comparative evaluation provides an evidence-base to inform the future development of citizen science activities.
Journal Article
Doublet identification in single-cell sequencing data using scDblFinder version 1; peer review: 1 approved, 1 approved with reservations
Doublets are prevalent in single-cell sequencing data and can lead to artifactual findings. A number of strategies have therefore been proposed to detect them. Building on the strengths of existing approaches, we developed
scDblFinder, a fast, flexible and accurate Bioconductor-based doublet detection method. Here we present the method, justify its design choices, demonstrate its performance on both single-cell RNA and accessibility sequencing data, and provide some observations on doublet formation, detection, and enrichment analysis. Even in complex datasets,
scDblFinder can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives.
Journal Article
The Eagle has landed : 50 years of lunar science fiction
\"In celebration of the 50th anniversary of the Apollo 11 landing, the endlessly-mysterious moon is explored in this reprint short science fiction anthology from award-winning editor and anthologist Neil Clarke ... On July 20, 1969, mankind made what had only years earlier seemed like an impossible leap forward: when Apollo 11 became the first manned mission to land on the moon, and Neil Armstrong the first person to step foot on the lunar surface. While there have only been a handful of new missions since, the fascination with our planet's satellite continues, and generations of writers and artists have imagined the endless possibilities of lunar life. From adventures in the vast gulf of space between the earth and the moon, to journeys across the light face to the dark side, to the establishment of permanent residences on its surface, science fiction has for decades given readers bold and forward-thinking ideas about our nearest interstellar neighbor and what it might mean to humankind, both now and in our future. [This book] collects the best stories written in the fifty years since mankind first stepped foot on the lunar surface, serving as a shining reminder that the moon is and always has been our most visible and constant example of all the infinite possibility of the wider universe\"-- Provided by publisher.
BOOK
Identifying Key Challenges Facing Healthcare Systems In Africa And Potential Solutions
Healthcare systems in Africa suffer from neglect and underfunding, leading to severe challenges across the six World Health Organization (WHO) pillars of healthcare delivery. We conducted this study to identify the principal challenges in the health sector in Africa and their solutions for evidence-based decisions, policy development and program prioritization.
The study was conducted as part of a recent African Epidemiological Association Meeting in Maputo, Mozambique with participants drawn from 11 African countries, Cuba, Portugal and the United Kingdom. Participants were divided into 10 groups, consisting of 7 to 10 persons each. Brainstorming approaches were used in a structured, modified nominal group process exercise to identify key challenges and strategies to mitigate healthcare service challenges in Africa. Identified challenges and solutions were prioritised by ranking 1-5, with 1 most important and 5 being least important.
The first three challenges identified were inadequate human resources (34.29%), inadequate budgetary allocation to health (30%) and poor leadership and management (8.45%). The leading solutions suggested included training and capacity building for health workers (29.69%), increase budgetary allocation to health (20.31%) and advocacy for political support and commitment (12.31%).
The underdeveloped healthcare systems in Africa need radical solutions with innovative thought to break the current impasse in service delivery. For example, public-private initiatives should be sought, where multinational companies extracting resources from Africa might be encouraged to plough some of the profits back into healthcare for the communities providing the workforce for their commercial activities. Most problems and their solutions lie within human resources, budget allocation and management. These should be accorded the highest priority for better health outcomes.
Journal Article
A Review of Merged High-Resolution Satellite Precipitation Product Accuracy during the Tropical Rainfall Measuring Mission (TRMM) Era
A great deal of expertise in satellite precipitation estimation has been developed during the Tropical Rainfall Measuring Mission (TRMM) era (1998–2015). The quantification of errors associated with satellite precipitation products (SPPs) is crucial for a correct use of these datasets in hydrological applications, climate studies, and water resources management. This study presents a review of previous work that focused on validating SPPs for liquid precipitation during the TRMM era through comparisons with surface observations, both in terms of mean errors and detection capabilities across different regions of the world. Several SPPs have been considered: TMPA 3B42 (research and real-time products), CPC morphing technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP; both the near-real-time and the Motion Vector Kalman filter products), PERSIANN, and PERSIANN–Cloud Classification System (PERSIANN-CCS). Topography, seasonality, and climatology were shown to play a role in the SPP’s performance, especially in terms of detection probability and bias. Regions with complex terrain exhibited poor rain detection and magnitude-dependent mean errors; low probability of detection was reported in semiarid areas. Winter seasons, usually associated with lighter rain events, snow, and mixed-phase precipitation, showed larger biases.
Journal Article
pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single cell RNA-seq preprocessing tools
We present
pipeComp
(
https://github.com/plger/pipeComp
), a flexible R framework for pipeline comparison handling interactions between analysis steps and relying on multi-level evaluation metrics. We apply it to the benchmark of single-cell RNA-sequencing analysis pipelines using simulated and real datasets with known cell identities, covering common methods of filtering, doublet detection, normalization, feature selection, denoising, dimensionality reduction, and clustering.
pipeComp
can easily integrate any other step, tool, or evaluation metric, allowing extensible benchmarks and easy applications to other fields, as we demonstrate through a study of the impact of removal of unwanted variation on differential expression analysis.
Journal Article
Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences
High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.
Journal Article
muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data
Single-cell RNA sequencing (scRNA-seq) has become an empowering technology to profile the transcriptomes of individual cells on a large scale. Early analyses of differential expression have aimed at identifying differences between subpopulations to identify subpopulation markers. More generally, such methods compare expression levels across sets of cells, thus leading to cross-condition analyses. Given the emergence of replicated multi-condition scRNA-seq datasets, an area of increasing focus is making sample-level inferences, termed here as differential state analysis; however, it is not clear which statistical framework best handles this situation. Here, we surveyed methods to perform cross-condition differential state analyses, including cell-level mixed models and methods based on aggregated pseudobulk data. To evaluate method performance, we developed a flexible simulation that mimics multi-sample scRNA-seq data. We analyzed scRNA-seq data from mouse cortex cells to uncover subpopulation-specific responses to lipopolysaccharide treatment, and provide robust tools for multi-condition analysis within the
muscat
R package.
Single-cell transcriptomics enhanced our ability to profile heterogeneous cell populations. It is not known which statistical frameworks are performant to detect subpopulation-level responses. Here, the authors developed a simulation framework to evaluate various methods across a range of scenarios.
Journal Article