River Restoration in the Twenty-First Century: Data and Experiential Knowledge to Inform Future Efforts

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71999/1/j.1526-100X.2007.00243.x.pd

Self-assembled monolayer of designed and synthesized triazinedithiolsilane molecule as interfacial adhesion enhancer for integrated circuit

Self-assembled monolayer (SAM) with tunable surface chemistry and smooth surface provides an approach to adhesion improvement and suppressing deleterious chemical interactions. Here, we demonstrate the SAM comprising of designed and synthesized 6-(3-triethoxysilylpropyl)amino-1,3,5-triazine-2,4-dithiol molecule, which can enhance interfacial adhesion to inhibit copper diffusion used in device metallization. The formation of the triazinedithiolsilane SAM is confirmed by X-ray photoelectron spectroscopy. The adhesion strength between SAM-coated substrate and electroless deposition copper film was up to 13.8 MPa. The design strategy of triazinedithiolsilane molecule is expected to open up the possibilities for replacing traditional organosilane to be applied in microelectronic industry

An ontology for strongly sustainable business models: Defining an enterprise framework compatible with natural and social science

Business is increasingly employing sustainability practices, aiming to improve environmental and social responsibility while maintaining and improving profitability. For many organizations, profit-oriented business models are a major constraint impeding progress in sustainability. A formally defined ontology, a model definition, for profit-oriented business models has been employed globally for several years. However, no equivalent ontology is available in research or practice that enables the description of strongly sustainable business models, as validated by ecological economics and derived from natural, social, and system sciences. We present a framework of strongly sustainable business model propositions and principles as findings from a transdisciplinary review of the literature. A comparative analysis was performed between the framework and the Osterwalder profit-oriented ontology for business models. We introduce an ontology that enables the description of successful strongly sustainable business models that resolves weaknesses and includes functionally necessary relationships

Sustainable procurement strategies for competitive advantage: An empirical study

Procurement plays a key role in sustainability as policies and practices need to extend beyond organisations' boundaries to incorporate their whole supply chains. There is, however, a paucity of empirical research on sustainable forms of procurement initiatives currently being implemented in the UK construction sector to improve competitiveness - which is the core driver of this paper. In order to achieve this aim, a mixed research methodological approach was adopted to collect and analyse data. The findings are based primarily on quantitative data obtained from 53 completed postal questionnaires and semi-structured interviews with 17 professionals from 12 UK construction organisations. As revealed by this study, sustainable procurement is becoming increasingly important in the UK construction sector. The paper concludes that the process of integrating sustainable procurement initiatives into existing business models is often a complex issue. Therefore, there is an urgent need to explore the drivers and impediments associated with the successful integration of sustainable procurement initiatives into existing construction business models. It is also suggested that there is a need for cross-sector collaboration to capture and share best and worst practices relating to sustainable procurement strategies

Tools and data services registry: a community effort to document bioinformatics resources.

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.Here we present a community-driven curation effort, supported by ELIXIR-the European infrastructure for biological information-that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools

Community-Driven Data Analysis Training for Biology

The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org. We developed an infrastructure that facilitates data analysis training in life sciences. It is an interactive learning platform tuned for current types of data and research problems. Importantly, it provides a means for community-wide content creation and maintenance and, finally, enables trainers and trainees to use the tutorials in a variety of situations, such as those where reliable Internet access is unavailable