Identifying opportunities for engaging the ‘community’ in local alcohol decision-making: a literature review and synthesis

Introduction: Engaging communities in actions to reduce alcohol harms has been identified as an international priority. While there exist recommendations for community engagement within alcohol licensing legislation, there is limited understanding of how to involve communities in local decision-making to reduce harms from the alcohol environment. Methods: A scoping literature review was conducted on community engagement in local government decisionmaking with relevance to the alcohol environment. Academic and grey literature databases were searched between April and June 2018 to identify examples of community engagement in local government in the UK, published since 2000. Texts were excluded if they did not describe in detail the mechanisms or rationale for community engagement. Information was extracted and synthesised through a narrative approach. Results: 3030 texts were identified through the searches, and 30 texts were included in the final review. Only one text described community engagement in alcohol decision-making (licensing); other local government sectors included planning, regeneration and community safety. Four rationales for community engagement emerged: statutory consultation processes; non-statutory engagement; as part of broader participatory initiatives; and community-led activism. While not all texts reported outcomes, a few described direct community influence on decisions. Broader outcomes included improved relationships between community groups and local government. However, lack of influence over decisions was also common, with multiple barriers to effective engagement identified. Conclusion: The lack of published examples of community engagement in local alcohol decision-making relevant to the UK suggests little priority has been placed on sharing learning about supporting engagement in this area. Taking a place-shaping perspective, useful lessons can be drawn from other areas of local government with relevance for the alcohol environment. Barriers to engagement must be considered carefully, particularly around how communities are defined, and how different interests toward the local alcohol environment are represented, or not

Numerical evidence for phase transitions of NP-complete problems for instances drawn from Lévy-stable distributions

Random NP-Complete problems have come under study as an important tool used in the analysis of optimization algorithms and help in our understanding of how to properly address issues of computational intractability. In this thesis, the Number Partition Problem and the Hamiltonian Cycle Problem are taken as representative NP-Complete classes. Numerical evidence is presented for a phase transition in the probability of solution when a modified Lévy-Stable distribution is used in instance creation for each. Numerical evidence is presented that show hard random instances exist near the critical threshold for the Hamiltonian Cycle problem. A choice of order parameter for the Number Partition Problem’s phase transition is also given. Finding Hamiltonian Cycles in Erdös-Rényi random graphs is well known to have almost sure polynomial time algorithms, even near the critical threshold. To the author’s knowledge, the graph ensemble presented is the first candidate, without specific graph structure built in, to generate graphs whose Hamiltonicity is intrinsically hard to determine. Random graphs are chosen via their degree sequence generated from a discretized form of Lévy-Stable distributions. Graphs chosen from this distribution still show a phase transition and appear to have a pickup in search cost for the algorithms considered. Search cost is highly dependent on the particular algorithm used and the graph ensemble is presented only as a potential graph ensemble to generate intrinsically hard graphs that are difficult to test for Hamiltonicity. Number Partition Problem instances are created by choosing each element in the list from a modified Lévy-Stable distribution. The Number Partition Problem has no known good approximation algorithms and so only numerical evidence to show the phase transition is provided without considerable focus on pickup in search cost for the solvers used. The failure of current approximation algorithms and potential candidate approximation algorithms are discussed

An Analysis of Public Phenotype/Genotype Data with Arvados

It can be difficult to gain credentials to perform analysis on sensitive data as a researcher, especially as a student. Furthermore, with specific regard to genomic data, it is potentially identifiable, therefore individuals often do not wish to make these data available to bioinformaticians. The Harvard Personal Genome Project and the 1000 Genomes Project curate the genomes of volunteers who willing are to share it with biomedical researchers to aid the future of biology and genetics. Curoverse develops an open-source data analysis tool, Arvados; Arvados allows complex analysis on large datasets using a cluster of computers through “pipelines,” written in Common Workflow Language. With regard to this project, a team at the Università Degli Studi Di Padova in Italy developed a tool titled “BOOGIE” [BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data, Giollo, M. et al.], used to analyze genomes and predict a blood type, and BOOGIE claims to be 94% accurate. The goal of this project was to use Arvados to run BOOGIE on genomes available from the Personal Genome Project and the 1000 Genomes Project and compare the results to ethnicity data provided in genomic surveys, ultimately determining if these data match readily-available ethnicity and blood type information. A pipeline was written in Arvados incorporating BOOGIE through a Docker image to analyze the datasets. In under 10 hours, the tool was able to run BOOGIE on all 606 genomes available. This included 173 Genomes from the Personal Genome Project and 433 Genomes from the 1000 Genomes Project. After downloading all the data from Arvados and comparing it to the survey data provided from the Personal Genome Project using a Python script, BOOGIE was rated at an 86.67% accuracy, having correctly guessed 39/45 blood types from the Personal Genome Project. Through survey data, each genome analyzed had a blood type and ethnicity, and these data were used to compare the people who had each blood type to their ethnicity. The Personal Genome Project and the 1000 Genomes Project allow genomic data to be accessible and easily available for everyone to use. The Arvados Project records work and simplifies the process of doing so by using Docker images and pipelines. In addition, the Arvados Project allows analysis of massive data sets containing gigabytes to petabytes of information, aiming to create an efficient, common solution for data management across many platforms

Geographic information system protocol for mapping areas targeted for mosquito control in North Carolina.

Geographic information systems (GIS) can be used to map mosquito larval and adult habitats and human populations at risk for mosquito exposure and possible arbovirus transmission. Along with traditional methods of surveillance-based targeted mosquito control, GIS can help simplify and target efforts during routine surveillance and post-disaster (e.g., hurricane-related flooding) to protect emergency workers and public health. A practical method for prioritizing areas for emergency mosquito control has been developed and is described here. North Carolina (NC) One Map was used to identify state-level data layers of interest based on human population distribution and mosquito habitat in Brunswick, Columbus, Onslow, and Robeson Counties in eastern NC. Relevant data layers were included to create mosquito control treatment areas for targeted control and an 18-step protocol for map development is discussed. This protocol is expected to help state, territorial, tribal, and/or local public health officials and associated mosquito control programs efficiently create treatment area maps to improve strategic planning in advance of a disaster. This protocol may be applied to any NC county and beyond, thereby increasing local disaster preparedness

Attempted Abstraction of the Halogenides in (HNEt3)Re(CH3CN)(2)Cl-4] and Crystal Structures of cis-Re(CH3CN)(2)Cl-4] center dot CH3CN and cis-Re(NHC(OCH3)CH3)(2)Cl-4]

The abstraction of the halogenide ligands in Re(CH3CN)(2)Cl-4](-) should result in a solvent-only stabilized Re-III complex. The reactions of salts of Re(CH3CN)(2)Cl-4](-) with silver(1) and thallium(I) salts were investigated and the solid-state structures of cis-Re(CH3CN)(2)Cl-4] center dot CH3CN and cisRe(NHC(OCH3)CH3)(2)Cl-4] are described

The whole genome sequences and experimentally phased haplotypes of over 100 personal genomes

Background: Since the completion of the Human Genome Project in 2003, it is estimated that more than 200,000 individual whole human genomes have been sequenced. A stunning accomplishment in such a short period of time. However, most of these were sequenced without experimental haplotype data and are therefore missing an important aspect of genome biology. In addition, much of the genomic data is not available to the public and lacks phenotypic information. Findings: As part of the Personal Genome Project, blood samples from 184 participants were collected and processed using Complete Genomics’ Long Fragment Read technology. Here, we present the experimental whole genome haplotyping and sequencing of these samples to an average read coverage depth of 100X. This is approximately three-fold higher than the read coverage applied to most whole human genome assemblies and ensures the highest quality results. Currently, 114 genomes from this dataset are freely available in the GigaDB repository and are associated with rich phenotypic data; the remaining 70 should be added in the near future as they are approved through the PGP data release process. For reproducibility analyses, 20 genomes were sequenced at least twice using independent LFR barcoded libraries. Seven genomes were also sequenced using Complete Genomics’ standard non-barcoded library process. In addition, we report 2.6 million high-quality, rare variants not previously identified in the Single Nucleotide Polymorphisms database or the 1000 Genomes Project Phase 3 data. Conclusions: These genomes represent a unique source of haplotype and phenotype data for the scientific community and should help to expand our understanding of human genome evolution and function. Electronic supplementary material The online version of this article (doi:10.1186/s13742-016-0148-z) contains supplementary material, which is available to authorized users

vgteam/vg: vg 1.52.0 - Bozen

tools for working with genome variation graph