135,725 research outputs found

    Data for "Rapid seaward expansion of seaport footprints worldwide"

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    Data used in &quot;Rapid seaward expansion of seaport footprints worldwide&quot; (Sengupta &amp;amp; Lazarus, 2023: doi xxxxxxx). Data include five csv files: &#39;Sengupta_Lazarus_2023_F1_b&#39; &ndash; total reclaimed area (km^2) in 2020, ranked by magnitude &#39;Sengupta_Lazarus_2023_F2_a&#39; &ndash; normalised reclaimed area versus time for 68 seaports &#39;Sengupta_Lazarus_2023_F2_b&#39; &ndash; series of ranks by different metrics: Lloyd&#39;s List 2020 (Lloyd&#39;s, 2021), total reclaimed area in 2020, area under normalised curves of reclaimed area through time, and coastal &amp;amp; cyclone hazard (Verschuur et al., 2023). &#39;Sengupta_Lazarus_rec_TEU_2011_2020&#39; &ndash; data for container volume (in millions TEU) relative to reclamation area, 2011-2020; data for container volume sourced from UNCTD and the World Shipping Council. &#39;Sengupta_Lazarus_time_series_rec_data&#39; &ndash; data (raw and smoothed) for seaport reclamation (km^2), 1990&ndash;2020 The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Mapping_Coastal_land_reclamation Code for plotting these data are available here: https://github.com/edlazarus/Seaports</span

    Data for &quot;Rapid seaward expansion of seaport footprints worldwide&quot;

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    [updated October 2023] This dataset comprises data and code used in &quot;Rapid seaward expansion of seaport footprints worldwide&quot; (Sengupta &amp;amp; Lazarus, 2023; preprint: https://doi.org/10.31223/X5SD3T). The data include four csv files: &#39;Sengupta_Lazarus_REC_1990_2020_v05.csv&#39; &ndash; annual time series of seaward expansion (km^2) between 1990&ndash;2020 through coastal reclamation for 66 of the world&#39;s top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd&#39;s List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed]. To produce the smoothed data, the raw data are passed through a Savitzky&ndash;Golay filter. &#39;Sengupta_Lazarus_REC_TEU_2011_2020_v03.csv&#39; &ndash; annual time series of seaward expansion (km^2) and reported container throughput (millions TEU) between 2011&ndash;2020 for 43 of the world&#39;s top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd&#39;s List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed with a Savitzky&ndash;Golay filter], and TEU (millions), collated from archived Lloyd&#39;s List reports. &#39;Sengupta_Lazarus_REC_TEU_totals_v04.csv&#39; &ndash; Simplified dataset listing total seaward expansion (km^2) and container throughput in 2020 for 66 of the world&#39;s top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd&#39;s List, 2021). Dataset includes Seaport, Country, Region, Reclaimed area (km^2) [smoothed with a Savitzky&ndash;Golay filter], ranked list of seaports by expansion extent, and TEU (millions) handled in 2020, and Lloyd&#39;s List rank in 2020 (Lloyd&#39;s List, 2021). &#39;Sengupta_Lazarus_2023_ports_excluded.csv&#39; &ndash; contains list of 34 ports excluded from thus analysis because they are either not on an open coastline (e.g. estuarine, riverine) or expanded less than 1 km^2 seaward between 1990&ndash;2020. &#39;RECLAIM_port_trajectories_v11.ipynb&#39; &ndash; Jupyter notebook for data wrangling and plotting figures presented in Sengupta &amp;amp; Lazarus (2023). (Note that this notebook does not produce the map-based figures presented in that work.) The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Seaport_reclamation These data and code are also available here: https://github.com/edlazarus/Seaports</span

    Data for &quot;Rapid seaward expansion of seaport footprints worldwide&quot;

    No full text
    [updated July 2023] This dataset comprises data and code used in &quot;Rapid seaward expansion of seaport footprints worldwide&quot; (Sengupta &amp;amp; Lazarus, 2023; preprint: https://doi.org/10.31223/X5SD3T). The data include four csv files: &#39;Sengupta_Lazarus_REC_1990_2020_v02.csv&#39; &ndash; annual time series of seaward expansion (km^2) between 1990&ndash;2020 through coastal reclamation for 66 of the world&#39;s top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd&#39;s List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed]. To produce the smoothed data, the raw data are passed through a Savitzky&ndash;Golay filter. &#39;Sengupta_Lazarus_REC_TEU_2011_2020_v02.csv&#39; &ndash; annual time series of seaward expansion (km^2) and reported container throughput (millions TEU) between 2011&ndash;2020 for 43 of the world&#39;s top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd&#39;s List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed with a Savitzky&ndash;Golay filter], and TEU (millions), collated from archived Lloyd&#39;s List reports. Sengupta_Lazarus_REC_TEU_totals_v02.csv&#39; &ndash; Simplified dataset listing total seaward expansion (km^2) and container throughput in 2020 for 66 of the world&#39;s top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd&#39;s List, 2021). Dataset includes Seaport, Country, Region, Reclaimed area (km^2) [smoothed with a Savitzky&ndash;Golay filter], ranked list of seaports by expansion extent, and TEU (millions) handled in 2020, and Lloyd&#39;s List rank in 2020 (Lloyd&#39;s List, 2021). &#39;Sengupta_Lazarus_2023_ports_excluded.csv&#39; &ndash; contains list of 34 ports excluded from thus analysis because they are either not on an open coastline (e.g. estuarine, riverine) or expanded less than 1 km^2 seaward between 1990&ndash;2020. &#39;RECLAIM_port_trajectories_v7.ipynb&#39; &ndash; Jupyter notebook for data wrangling and plotting figures presented in Sengupta &amp;amp; Lazarus (2023). (Note that this notebook does not produce the map-based figures presented in that work.) The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Mapping_Coastal_land_reclamation These data and code are also available here: https://github.com/edlazarus/Seaports</span

    An efficient plate element for the vibration of composite plates

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    Abstract not availableP. Dey, S. Haldar, D. Sengupta, A.H. Sheik

    Uniform Bounds on Product Sylvester-Gallai Configurations

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    In this work, we explore a non-linear extension of the classical Sylvester-Gallai configuration. Let be an algebraically closed field of characteristic zero, and let ℱ = {F_1, …, F_m} ⊂ [x_1, …, x_N] denote a collection of irreducible homogeneous polynomials of degree at most d, where each F_i is not a scalar multiple of any other F_j for i ≠ j. We define ℱ to be a product Sylvester-Gallai configuration if, for any two distinct polynomials F_i, F_j ∈ ℱ, the following condition is satisfied: ∏_{k≠i, j} F_k ∈ rad (F_i, F_j) . We prove that product Sylvester-Gallai configurations are inherently low dimensional. Specifically, we show that there exists a function λ : ℕ → ℕ, independent of , N, and m, such that any product Sylvester-Gallai configuration must satisfy: dim(span_(ℱ)) ≤ λ(d). This result generalizes the main theorems from (Shpilka 2019, Peleg and Shpilka 2020, Oliveira and Sengupta 2023), and gets us one step closer to a full derandomization of the polynomial identity testing problem for the class of depth 4 circuits with bounded top and bottom fan-in

    Rapid seaward expansion of seaport footprints worldwide

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    As global maritime traffic increases, seaports grow to accommodate and compete for higher volumes of trade throughput. However, growth trajectories of seaport footprints around the world have gone unmeasured, likely because of a lack of readily available spatio-temporal data. Here, we use geospatial analysis of global satellite imagery from 1990–2020 to show that 65 seaports among the world’s top 100 container ports, as ranked by reported throughput, have been expanding rapidly seaward. Collectively, these seaports have added approximately 978 km2 in gross port area in three decades through coastal land reclamation. We also find that the relationship between footprint expansion and throughput volume is highly variable among seaports. Understanding patterns of seaport expansion in space and time informs global assessments of critical infrastructure and supply chain vulnerability to climate-driven hazard. Seaport expansion also sets up complex trade-offs in the context of environmental impacts and climate adaptation

    Replication data for, "A multiple life history trait-based and time-resolved assessment of imidacloprid effects and recovery in the widely distributed collembolan Folsomia quadrioculata"

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    This data was collected as a part of the MULTICLIM project (https://www.mn.uio.no/ibv/english/research/sections/aqua/research-projects/144612/). In this study, we determined the sublethal effects of short-term imidacloprid exposure and post-exposure recovery in the collembolan Folsomia quadrioculata, which occurs abundantly across the northern hemisphere. Imidacloprid is a globally-used neonicotinoid insecticide, which can persist in the soil long enough to elicit adverse responses in non-target organisms. We assessed survival, egg production, and hatching success in adult springtails exposed for 14 d through the diet to imidacloprid followed by a 28 d post-exposure phase. Our findings suggest that low imidacloprid exposures can restrict reproduction, with potentially severe consequences for the population, notwithstanding the partial recovery in egg productio

    Free vibration analysis of composite right angle triangular plate using a shear flexible element

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    © 2003 SAGE Publications A high precision triangular plate bending element proposed by the second author of this paper has been upgraded for the free vibration analysis of laminated composite right angle triangular plates. The effect of shear deformation has been incorporated. An efficient mass lumping scheme with rotary inertia has been recommended. Numerical examples of composite triangular plates having different thickness ratios, side ratios, fibre-orientations, number of layers and boundary conditions have been solved by this element. For validation of the present formulation and element few results on isotropic and orthotropic plates have been compared with those obtained from literatures. The results on composite plates have been presented as new results. S. Haldar, D. Sengupta, and A. H. Sheik

    Dataset to accompany "Deposition of brown carbon onto snow: changes of snow optical and radiative properties" by Beres et al., 2020

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    This dataset, organized in an Excel spreadsheet, accompanies: Beres, N. D., Sengupta, D., Samburova, V., Khlystov, A. Y., and Moosmüller, H.: Deposition of brown carbon onto snow: changes in snow optical and radiative properties, Atmos. Chem. Phys., 20, 6095–6114, https://doi.org/10.5194/acp-20-6095-2020, 2020. Each tab of the spreadsheet represents data presented in Tables and Figures of the manuscript, which allows for the replication of the figure or for use in calculations presented throughout the manuscript. Any questions or comments should be forwarded to the corresponding author

    A general skew-t mixed model that allows different degrees of freedom for random effects and error distributions

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    Abstract not availablePankaj K. Choudhary, Dishari Sengupta, Phillip Casse
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