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6 results for “Industrial Ecology”
Competitive growth experiments with a high-lipid Chlamydomonas reinhardtii mutant strain and its wild-type to predict industrial and ecological risks
<p>Key microalgal species are currently being exploited as biomanufacturing platforms using mass cultivation systems. The opportunities to enhance productivity levels or produce non-native compounds are increasing as genetic manipulation and metabolic engineering tools are rapidly advancing. Regardless of the end product, there are both environmental and industrial risks associated to open pond cultivation of mutant microalgal strains. A mutant escape could be detrimental to local biodiversity and increase the risk of algal blooms. Similarly, if the cultivation pond is invaded by a wild-type microalgae or the mutant reverts to wild-type phenotypes, productivity could be impacted. To investigate these potential risks, a response surface methodology was applied to determine the competitive outcome of two <em>Chlamydomonas reinhardtii</em> strains, a wild-type (CC-124) and a high-lipid accumulating mutant (CC-4333), grown in mixotrophic conditions, with differing levels of nitrogen and initial wild-type to mutant ratios. Results of the growth experiments show that mutant cells have double the exponential growth rate of the wild-type in monoculture. However, due to a slower transition from lag phase to exponential phase, mutant cells are outcompeted by the wild-type in every co-culture treatment. This suggests that, under the conditions tested, outdoor cultivation of the <em>C. reinhardtii</em> cell wall-deficient mutant strains does not carry a significant environmental risk to its wild-type in an escape scenario. Furthermore, lipid results show the mutant strain accumulates over 200% more TAGs per cell, at 50 mg/L NH<sub>4</sub>Cl, compared to the wild-type, therefore, the fragility of the mutant strain could impact on overall industrial productivity.</p>
Industrial Ecology Data Commons (iedc) December 2024 update
<p>The Industrial Ecology Data Commons (iedc) is a database that contains more than 200 IE-related datasets from the literature, including stocks, flows, process descriptions, IO tables, material composition of products, and many more. Launched in 2018, the iedc is continuously improved and expanded. </p> <p>The homepage of the project is https://www.database.industrialecology.uni-freiburg.de/</p> <p>This Zenodo backup contains a .zip file with 156 parameter templates (xlsx), which where all uploaded to the iedc (SQL database) and are available online.</p> <p>This backup is for archiving the intermediate step between raw data and uploaded data.</p> <p>It contains all data that were gathered up to and including November 2024 except for those data that were uploaded directly via Pyhton scripts from other sources (like .csv) and not via the xlsx templates.</p>
Data and Python script for article "A text mining analysis of the climate change literature in industrial ecology'
<p>The data and Python script are part of the forum article "A text mining analysis of the climate change literature in industrial ecology" authored by Dayeen, F.R., Sharma, A.S., and Derrible, S., and published in the <em>Journal of Industrial Ecology</em> in 2020.</p> <p>The Python script and instructions are included in the LiTCoF_v1.00-py.zip file. The original data is available in two formats: .csv and .pkl.</p> <p>Updates of the script will be posted at https://github.com/csunlab/LiTCoF and at https://csun.uic.edu/codes/LiTCoF.html. The data is also available at https://csun.uic.edu/datasets.html#AbstractsIE.</p> <p>Feel free to contact any of the authors for information and questions about the data and code.</p>
Supporting Data for: Resource requirements for ecosystem conservation: A combined industrial and natural ecology approach to quantifying natural capital use in nature
<p>Data used to derive allometric equations for land area use by mammals, birds, reptiles, and insects, and data for the analysis of natural resource use at the Natural Capital Laboratory site.</p>
HOW TO FORM A PRODUCER SERVICING ECOLOGY LEADING TO COMPETITIVE DIGITAL TRADE? -FROM INDUSTRIAL CLUSTER PERSPECTIVE
<p>Digital trade includes cross-border e-commerce focus on goods trade and digital service trade focus on service trade. Digital service trade refers to the service trade that can be delivered digitally or has the potential of digital delivery, including insurance services, financial services, intellectual property services, telecommunications, computer and information services, other business services and cultural and entertainment services (UNCTAD,2020), this study mainly examine the contribution of 28 manufacturing industries in China to the competitiveness of digital services trade in these six categories.</p> <p>Data are drawn from Ministry of Commerce, State Administration of Foreign Exchange, International Trade Center (ITC),China Statistical Yearbook, ILO Statistics, China Input-Output Table.</p>
Data from: Fine-scale ecological and genetic population structure of two whitefish (Coregoninae) species in the vicinity of industrial thermal emissions
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.