The Carbon_h-Factor: Predicting Individuals' Research Impact at Early Stages of Their Career

Assessing an individual's research impact on the basis of a transparent algorithm is an important task for evaluation and comparison purposes. Besides simple but also inaccurate indices such as counting the mere number of publications or the accumulation of overall citations, and highly complex but also overwhelming full-range publication lists in their raw format, Hirsch (2005) introduced a single figure cleverly combining different approaches. The so-called h-index has undoubtedly become the standard in scientometrics of individuals' research impact (note: in the present paper I will always use the term “research impact” to describe the research performance as the logic of the paper is based on the h-index, which quantifies the specific “impact” of, e.g., researchers, but also because the genuine meaning of impact refers to quality as well). As the h-index reflects the number h of papers a researcher has published with at least h citations, the index is inherently positively biased towards senior level researchers. This might sometimes be problematic when predictive tools are needed for assessing young scientists' potential, especially when recruiting early career positions or equipping young scientists' labs. To be compatible with the standard h-index, the proposed index integrates the scientist's research age (Carbon_h-factor) into the h-index, thus reporting the average gain of h-index per year. Comprehensive calculations of the Carbon_h-factor were made for a broad variety of four research-disciplines (economics, neuroscience, physics and psychology) and for researchers performing on three high levels of research impact (substantial, outstanding and epochal) with ten researchers per category. For all research areas and output levels we obtained linear developments of the h-index demonstrating the validity of predicting one's later impact in terms of research impact already at an early stage of their career with the Carbon_h-factor being approx. 0.4, 0.8, and 1.5 for substantial, outstanding and epochal researchers, respectively

Early Galactic Evolution of Carbon, Nitrogen and Oxygen

We present results on carbon, nitrogen, and oxygen abundances for a sample of unevolved metal-poor stars with metallicities in the range -0.3< [Fe/H]< -3. Oxygen abundances derived from different indicators are compared showing consistently that in the range 0.3 >[Fe/H]>-3.0, the [O/Fe] ratio increases from approximately 0 to 1. We find a good agreement between abundances based on the forbidden line, the OH and IR triplet lines when gravities based on Hipparcos} parallaxes are considered for the sample stars. Gravities derived from LTE ionization balance in metal-poor stars with [Fe/H]< -1 are likely too low, and could be responsible for an underestimation of the oxygen abundances derived using the [OI] line. [C/Fe] and [N/Fe] ratios appear to be constant, independently of metallicity, in the same range. However, they show larger scatter than oxygen at a given metallicity, which could reflect the larger variety of stellar production sites for these other elements.Comment: 10 pages, 3 figures, To appear in the proceedings of the conference "The Chemical Evolution of The Milky Way: Stars versus Clusters", eds. F. Matteucci and F. Giovannelli, Vulcano, Italy, September 20-24 199

Critical success factors for embedding carbon management in organizations: lessons from the UK higher education sector

Organizations are under increasing pressure from governments and stakeholders to reduce carbon emissions from their business operations for climate change mitigation. Universities are not exempt from this challenge and are operating in a complex external environment, not least responding to the UK government's Climate Change Act 2008 (80% carbon reductions by 2050 as per 1990 baseline). In 2012–2013, the UK Higher Education (HE) sector consumed 7.9 billion kWh of energy and produced 2.3 million tonnes of carbon emissions. This indicates the scale of the challenge and carbon management is central to reduce carbon emissions. However, effective processes for implementing and embedding carbon management in organizations in general, and universities in particular, have yet to be realized. This paper explores the critical success factors (CSFs) for embedding carbon management in universities and, more widely, in organizations. This exploratory study adopted a mixed-methods approach including the content analysis of universities' carbon management plans alongside semi-structured interviews in the UK HE sector. The paper identifies six key factors for successfully embedding carbon management that are pertinent not just for the HE sector, but to organizations broadly: senior management leadership; funding and resources; stakeholder engagement; planning; governance and management; and evaluation and reporting

Code Reuse in Open Source Software

Code reuse is a form of knowledge reuse in software development that is fundamental to innovation in many fields. However, to date there has been no systematic investigation of code reuse in open source software projects. This study uses quantitative and qualitative data gathered from a sample of six open source software projects to explore two sets of research questions derived from the literature on software reuse in firms and open source software development. We find that code reuse is extensive across the sample and that open source software developers, much like developers in firms, apply tools that lower their search costs for knowledge and code, assess the quality of software components, and have incentives to reuse code. Open source software developers reuse code because they want to integrate functionality quickly, because they want to write preferred code, because they operate under limited resources in terms of time and skills, and because they can mitigate development costs through code reuse

BioJS: An open source standard for biological visualisation - its status in 2014

BioJS is a community-based standard and repository of functional components to represent biological information on the web. The development of BioJS has been prompted by the growing need for bioinformatics visualisation tools to be easily shared, reused and discovered. Its modular architecture makes it easy for users to find a specific functionality without needing to know how it has been built, while components can be extended or created for implementing new functionality. The BioJS community of developers currently provides a range of functionality that is open access and freely available. A registry has been set up that categorises and provides installation instructions and testing facilities at http://www.ebi.ac.uk/tools/biojs/. The source code for all components is available for ready use at https://github.com/biojs/biojs

Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease

Background Prostate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes. Methods We sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants. Results Protein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects. Conclusions Inherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application

Carbon neutral policy in action: the case of Bhutan

Climate policy across the world is proceeding at a highly variable pace, with some places very committed to decarbonizing their economies and others just beginning. Emerging nations are generally just starting along this journey. However, among the few nation states that have pledged to achieve carbon neutrality, is Bhutan, a least developed country. Carbon neutrality is an ambitious climate policy that is increasingly being recognized as necessary in order to stabilize global temperature rise at 1.5°C. However, Bhutan is likely to face significant challenges in maintaining this status as the country balances its desire to grow in economic opportunities (GDP) and in human happiness (GNH). Little research has been conducted inside the policy processes to better understand how Bhutan will maintain carbon neutrality. Through open-ended, semi-structured interviews with key stakeholders, this study provides an inside view on the current situation and future challenges that Bhutan may face, along with the complexities associated with implementing and maintaining an ambitious carbon neutral policy. The paper highlights Bhutan's story and how it could be useful for policy learning and knowledge sharing, especially in the context of emerging nations’ climate governance

The role of configurality in the Thatcher illusion: an ERP study.

The Thatcher illusion (Thompson in Perception, 9, 483-484, 1980) is often explained as resulting from recognising a distortion of configural information when 'Thatcherised' faces are upright but not when inverted. However, recent behavioural studies suggest that there is an absence of perceptual configurality in upright Thatcherised faces (Donnelly et al. in Attention, Perception & Psychophysics, 74, 1475-1487, 2012) and both perceptual and decisional sources of configurality in behavioural tasks with Thatcherised stimuli (Mestry, Menneer et al. in Frontiers in Psychology, 3, 456, 2012). To examine sources linked to the behavioural experience of the illusion, we studied inversion and Thatcherisation of faces (comparing across conditions in which no features, the eyes, the mouth, or both features were Thatcherised) on a set of event-related potential (ERP) components. Effects of inversion were found at the N170, P2 and P3b. Effects of eye condition were restricted to the N170 generated in the right hemisphere. Critically, an interaction of orientation and eye Thatcherisation was found for the P3b amplitude. Results from an individual with acquired prosopagnosia who can discriminate Thatcherised from typical faces but cannot categorise them or perceive the illusion (Mestry, Donnelly et al. in Neuropsychologia, 50, 3410-3418, 2012) only differed from typical participants at the P3b component. Findings suggest the P3b links most directly to the experience of the illusion. Overall, the study showed evidence consistent with both perceptual and decisional sources and the need to consider both in relation to configurality

KG-Hub-building and exchanging biological knowledge graphs.

MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. RESULTS: Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract-transform-load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial-environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification. AVAILABILITY AND IMPLEMENTATION: https://kghub.org