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995 results for “Life cycle”
Supplement of "Algorithm for continual monitoring of fog life cycles based on geostationary satellite imagery as a basis for solar energy forecasting"
<p>The file uploaded here is an animation that visually illustrates the outputs of the a newly developed machine learning based FLS (<strong>F</strong>og and <strong>L</strong>ow <strong>S</strong>tratus) detection algorithm for the SEVIRI (<strong>S</strong>pinning <strong>E</strong>nhanced <strong>V</strong>isible and <strong>I</strong>nfra<strong>R</strong>ed <strong>I</strong>mager) instrument onboard the MSG (<strong>M</strong>eteosat <strong>S</strong>econd <strong>G</strong>eneration) geo-stationary satellites over the 24hr cycle of the day for the day of <strong>02/March/2021</strong> and compares them with the corresponding raw channel values observed by SEVIRI. The proposed algorithm classifies each SEVIRI pixel as "clear-sky", "FLS", or "non-FLS-cloud" (identified with Khaki, Red, and Blue in the animation) based on the SEVIRI pixel values of BT12.0, BT8.7 - BT12.0, BT10.8 - BT12.0, and BT12.0 - BT13.4 plus the standard deviation of each of these variables in a spatial window sized 3x3 pixels with the central pixel being the target pixel. </p><p><br>In this animation, the left-hand panel shows a false-color RGB image constructed based on the SEVIRI raw channel data with the red, green, and blue channels being BT12.0- BT13.4, BT8.7 - BT12.0, and BT10.8 - BT12.0, respectively. In this panel, the green color represents the high clouds, and the light and dark red colors represent the clear-sky and FLS, respectively. The right-hand panel of this animation also shows the outputs of the ML FLS detection algorithm developed in the present study.</p>
Long Cycle-Life Ca Batteries with Poly(anthraquinonylsulfide) Cathodes and Ca-Sn Alloy Anodes
<p>This is a collection featuring the data generated and used within the paper: "Long Cycle-Life Ca Batteries with Poly(anthraquinonylsulfide) Cathodes and Ca-Sn Alloy Anodes"</p>
Raw NMR and GC reports for the article Electrochemical Hydrogenation of Alkenes over a Nickel Foam Guided by Life Cycle, Safety and Toxicological Assessments, Green Chemistry, doi: https://doi.org/10.1039/D4GC02924K
<p>Raw NMR for the article Electrochemical Hydrogenation of Alkenes over a Nickel Foam Guided by Life Cycle, Safety and Toxicological Assessments, Green Chemistry, doi: https://doi.org/10.1039/D4GC02924K</p> <p>The raw NMR data files for all compounds reported in the article are included. The numbering corresponds to those in the article.</p> <p>Each parent folder contains subfolders with different files. In order to process this data, the full parent folder must be dragged into either Mestrenova or Topspin and then the data is automatically processed. If the name of the raw data files are renamed, the software (<a href="https://mestrelab.com/" target="_blank" rel="noopener noreferrer">Mestrenova</a> or <a href="https://www.bruker.com/en/products-and-solutions/mr/nmr-software/topspin.html" target="_blank" rel="noopener noreferrer">Topspin</a>) will not be able to process the files</p> <p> </p>
Dataset for An Automatized Rebalancing System to Address Faradaic Imbalance and Prolong Cycle Life in Alkaline Ferrocyanide – Anthraquinone Redox Flow Batteries
<p>Dataset for the results shown in the publications "An Automatized Rebalancing System to Address Faradaic Imbalance and Prolong Cycle Life in Alkaline Ferrocyanide – Anthraquinone Redox Flow Batteries"</p>
Chromosome Numbers and Reproductive Life Cycles in Green Plants: A phylo-transcriptomic perspective
<p>The supplemental dataset for "Chromosome Numbers and Reproductive Life Cycles in Green Plants: A phylo-transcriptomic perspective."</p>
Research Data Management Life Cycle
<p>An overview of the research data management life cycle with proper licensing.</p> <p> </p>
FIGURE 5 in Life Cycle Of Sarraceniopus Nipponensis (Histiostomatidae: Astigmata) From The Fluid-Filled Pitchers Of Sarracenia Alata (Sarraceniaceae)
FIGURE 5: SEM pictures of Sarraceniopus nipponensis (USA). a – Dorsal view of the deutonymph, b – Detail of the cuticle's surface, c – Ventral suckerplate, d – lightmicroscopic picture of two adult males trying to perform a precopulation.
FIGURE 3 in Life Cycle Of Sarraceniopus Nipponensis (Histiostomatidae: Astigmata) From The Fluid-Filled Pitchers Of Sarracenia Alata (Sarraceniaceae)
FIGURE 3: Aggregation of Sarraceniopus nipponensis (USA) deutonymphs during molting into tritonymphs.
FIGURE 2 in Life Cycle Of Sarraceniopus Nipponensis (Histiostomatidae: Astigmata) From The Fluid-Filled Pitchers Of Sarracenia Alata (Sarraceniaceae)
FIGURE 2: Individual whole development period of Sarraceniopus nipponensis (USA) males and females, which were observed from the larval stage until adulthood at a temperature of 24°C (± 3°C) on daytime. On average, males need 6.2 days (n = 16), females need 5.7 days (n = 22) to complete their development.
FIGURE 1 in Life Cycle Of Sarraceniopus Nipponensis (Histiostomatidae: Astigmata) From The Fluid-Filled Pitchers Of Sarracenia Alata (Sarraceniaceae)
FIGURE 1: Schematized life cycle of Sarraceniopus nipponensis (USA) – big cycle: obligate cycle, small cycle: optional part with molting into deutonymphs, grey: ecdysis stages, slightly grey: active developmental stage. The first ecdysis from prelarva to larva occurs within the egg. Development from larva to adult without forming a deutonymph takes on average 6 days for both sexes. Sex ratio males: females ≈ 1: 2.6.
A critical perspective on uncertainty appraisal and sensitivity analysis in life cycle assessment - supporting material
<p>Publication dataset - A critical perspective on uncertainty appraisal and sensitivity analysis in life cycle assessment (<em>accepted for publication in the Journal of Industrial Ecology</em>).</p>
Life-cycle greenhouse gas emissions in power generation using palm kernel shell
<p>Although the Japanese feed-in tariff was introduced to expand renewable energy, leading to the expansion of palm kernel shell (PKS) use, the greenhouse gas (GHG) emission reduction effect is evaluated using the limited life-cycle of PKS, focusing on processes after PKS generation point. Therefore, this study aimed to elucidate the life-cycle GHG emissions of power generation using PKS. We targeted two PKS-firing power plants as these are the first two instances of the use of PKS in power plants in Japan. A system boundary was established to cover palm plantation management in Indonesia and Malaysia, as both power plants import PKS from these countries. The GHG emissions were derived from land-use change, palm plantation, oil extraction, PKS transportation, and power plants. Six scenarios were examined for the emissions based on the type of land-use change and the existence of biogas capture in oil extraction. CO<sub>2</sub> emissions from PKS combustion were also calculated by assuming that carbon neutrality was lost because of cultivation abandonment. The GHG emissions in one scenario, where the plantations were replanted and continuously managed and no biogas capture implemented in oil extraction, exhibited an average of 0.134 kg-CO<sub>2</sub>eq/kWh reduction in a plant in Kyushu District, and 0.043 kg-CO<sub>2</sub>eq/kWh reduction in a plant in Shikoku District for liquid natural gas-fired steam power generation, respectively. More than 65% of life-cycle GHG emissions originate from biogas generated during oil extraction; thus, biogas capture is an effective strategy to reduce current emissions. In contrast, in the case of accompanying land-use change or collapse of carbon neutrality, the emissions considerably exceeded those of fossil fuels. These findings indicated that the FIT fails to consider the risk of increased emissions or further substantial emission reductions. Therefore, the feasibility of FIT application to PKS needs to be re-established by evaluating the entire PKS life-cycle. </p>
Process simulation-based inventory data for the perovskite single-junction, Silicon (PERC) and four-terminal perovskite/silicon tandem solar photovoltaic system life cycles
<p>Process simulation-based inventory data (mass and energy balances) for the perovskite single-junction, silicon (PERC architecture), and four-terminal perovskite/silicon tandem solar photovoltaic system life cycles. The file "0 Overview of simulation flowsheets.xlsx" contains images of the 11 flowsheets that constitute the perovskite/silicon tandem simulation model, which encompasses the perovskite single-junction and silicon (PERC) simulation models. For each unit process shown in each of the flowsheet images, the corresponding Excel file in this repository (with the same name) contains the detailed mass and energy balances, as well as full compositions and thermochemical properties of all streams and the compounds in them. That is, streams are not assumed to consist of pure elements simply moving through the system together, but rather taking into account that streams consist of compounds in solution, which have different thermochemical properties than simple mixtures of the elements involved.</p> <p>Nine additional data files, the names of which start with "Inventory - " contain summarized inventory data for the production of 1000 perovskite single-junction, silicon (PERC), and silicon/perovskite tandem PV modules, each with no Si recycling (i.e. zero circularity), 50% Si recycling, and 100% Si recycling (i.e. full Si circularity).</p>
Dataset related to the publication "New Technique for Probing the Protecting Character of the Solid Electrolyte Interphase as a Critical but Elusive Property for Pursuing Long Cycle Life Lithium-Ion Batteries"
<p>The formation of a protecting nano-layer, so-called Solid Electrolyte Interphase (SEI), on the negative electrode of Li-ion batteries (LIBs) from product precipitation of the cathodic decomposition of the electrolyte is a blessing since the electrically-insulating nature of this nano-layer protect the electrode surface preventing continuous electrolyte decomposition and enabling the large nominal cell voltage of LIBs, e.g. 3.3 – 3.8 V. Thus, the protecting performance of the nano-layer SEI is essential for LIBs to achieve long cycle life. Unfortunately, evaluation of this critical property of the SEI is not trivial. Herein, a new, cheap and easily-implementable methodology is presented to estimate the protecting quality of the SEI; the redox-mediated enhanced coulometry. The key element of the methodology is the addition of a redox-mediator in the electrolyte during degassing step (after the SEI formation cycle). The redox-mediator leads to an internal self-discharge process that is inversely proportional to the protecting character of the SEI. And the self-discharge process results in an easily-measurable decrease in coulombic efficiency. The influence of vinylene carbonate as electrolyte additive in the resulting SEI is used as case study to showcase the potential of the proposed methodology</p>
Figs 2–8 in Life cycle of ground beetle Chlaenius tristis reticulatus Motschulsky, 1844 (Coleoptera: Carabidae) in the condition of Western Transbaikalia
Figs 2–8. Stages of development Chlaenius tristis reticulatus.2, 3 – larvae of third age
Fig. 7 in LIFE CYCLE AND GROWTH OF METRELETUS OMELKOI TIUNOVA, 2010 (EPHEMEROPTERA: AMELETIDAE) IN A TEMPORARY STREAM IN PRIMORSKII KRAI, RUSSIA
Fig. 7. The growth of the head capsule width of larvae of Metreletus omelkoi.
Fig. 5 in LIFE CYCLE AND GROWTH OF METRELETUS OMELKOI TIUNOVA, 2010 (EPHEMEROPTERA: AMELETIDAE) IN A TEMPORARY STREAM IN PRIMORSKII KRAI, RUSSIA
Fig. 5. Size frequency histogram for Metreletus omelkoi larvae.
Figs 1–4. Metreletus omelkoi. 1 in LIFE CYCLE AND GROWTH OF METRELETUS OMELKOI TIUNOVA, 2010 (EPHEMEROPTERA: AMELETIDAE) IN A TEMPORARY STREAM IN PRIMORSKII KRAI, RUSSIA
Figs 1–4. Metreletus omelkoi. 1 – biotope: temporary stream flowing along the road of
Fig. 8. A in LIFE CYCLE AND GROWTH OF METRELETUS OMELKOI TIUNOVA, 2010 (EPHEMEROPTERA: AMELETIDAE) IN A TEMPORARY STREAM IN PRIMORSKII KRAI, RUSSIA
Fig. 8. A relationship between growth rate (dW/dt, mg day-1) and body weight (W, mg)
Fig. 6 in LIFE CYCLE AND GROWTH OF METRELETUS OMELKOI TIUNOVA, 2010 (EPHEMEROPTERA: AMELETIDAE) IN A TEMPORARY STREAM IN PRIMORSKII KRAI, RUSSIA
Fig. 6. Dynamics of development of larvae of Metreletus omelkoi during April – June
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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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.