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Summary of the commercial and recreational striped bass fisheries conducted in Massachusetts from 1986 to present.
This dataset summarizes the commercial and recreational striped bass fisheries conducted in Massachusetts. Data sources used to characterize the state fisheries come from monitoring programs of the Massachusetts Division of Marine Fisheries (Marine Fisheries, the Division) and National Marine Fisheries Service (NOAA Fisheries), which are considered to be essential elements of the long-term management approach described in Section 3 of the Atlantic States Marine Fisheries Commission’s (ASMFC) Fisheries Management Report No. 41 (Amendment #6 to the Interstate Fishery management Plan for Atlantic Striped Bass (IFMP)). Fisheries data are compiled from four Massachusetts regions (Cape Cod Canal, Southern Massachusetts, Cape Cod Bay, Northern Massachusetts). Data begins with year 1986 and is updated to present years as data is made available.
Measured Commercial LED Spectra - Brendel (2020)
<p><strong>Source URL</strong>: <a href="https://www.rit.edu/cos/colorscience/re_AsanoObserverFunctions.php">https://community.acescentral.com/t/spectral-images-generation-and-processing/2590/8</a><br> <br> Measured spectra of 29 commercially available LEDs spanning the range from 380 to 660 nm peak wavelength. The file contains one SPD per line. Each spectrum is given in 176 samples from 350 to 700 nm normalised to a unity power integral.</p>
Data from: Stable isotopes reveal the effect of trawl fisheries on the diet of commercially exploited species
Bottom trawling can change food availability for benthivorous demersal species by (i) changing benthic prey composition through physical seabed impacts and (ii) by removing overall benthic consumer biomass increasing the net availability of benthic prey for remaining individuals. Thus trawling may both negatively and positively influence the quantity and quality of food available. Using δ13C and δ15N we investigated potential diet changes of three commercially exploited species across trawling gradients in the Kattegat (plaice, dab and Norway lobster (Nephrops)) and the Irish Sea (Nephrops). In the Kattegat, trawling affected primarily the biomass of benthic consumers, lowering competition. Nephrops showed significant positive relationships for δ13C and a domed relationship for δ15N with trawling. In the Irish Sea, intense trawling had a negative effect on benthic prey. δ13C and δ15N thus showed the inverse relationships to those observed in the Kattegat. Plaice from the Kattegat, showed a significant relationship with trawling intensity for δ13C, but not for δ15N. No relationship was found for dab. Changes of δ13C and δ15N correlated with changes in condition of species. The results show that the removal of demersal competitors and benthos by trawling can change the diets of commercial species, ultimately affecting their body condition.
Data from: Pollination treatment affects fruit set and modifies marketable and storable fruit quality of commercial apples
Insect-mediated pollination increases yields of many crop species and some evidence suggests that it also influences crop quality. However, the mechanistic linkages between insect-mediated pollination and crop quality are poorly known. In this study, we explored how different pollination treatments affected fruit set, dry matter content (DMC), mineral content and storability of apples. Apple flowers supplementary pollinated with compatible pollen resulted in higher initial fruit set rates, higher fruit DMC and a tendency for lower fruit K:Ca ratio than flowers that received natural or no pollination. These variables are related to desirable quality aspects, since higher DMC is connected to higher consumer preference and lower K:Ca ratio is related to lower incidence of postharvest disorders during storage. Using structural equation modelling, we showed an indirect effect of pollination treatment on storability, however mediated by complex interactions between fruit set, fruit weight and K:Ca ratio. The concentrations of several elements in apples (K, Zn, Mg) were affected by the interaction between pollination treatment and apple weight, indicating that pollination affects element allocation into fruits. In conclusion, our study shows that pollination and the availability of compatible pollen needs to be considered in the management of orchard systems, not only to increase fruit set, but also to increase the quality and potentially the storability of apples.
Data from: Human commercial models' eye colour shows negative frequency-dependent selection
In this study we investigated the eye colour of human commercial models registered in the UK (400 female and 400 male) and Brazil (400 female and 400 male) to test the hypothesis that model eye colour frequency was the result of negative frequency-dependent selection. The eye colours of the models were classified as: blue, brown or intermediate. Chi-square analyses of data for countries separated by sex showed that in the United Kingdom brown eyes and intermediate colours were significantly more frequent than expected in comparison to the general United Kingdom population (P<0.001). In Brazil, the most frequent eye colour brown was significantly less frequent than expected in comparison to the general Brazilian population. These results support the hypothesis that model eye colour is the result of negative frequency-dependent selection. This could be the result of people using eye colour as a marker of genetic diversity and finding rarer eye colours more attractive because of the potential advantage more genetically diverse offspring that could result from such a choice. Eye colour may be important because in comparison to many other physical traits (e.g., hair colour) it is hard to modify, hide or disguise, and it is highly polymorphic.
Wood transverse cross-section micro-imagery from 77 commercial Central-African timber species
<p>The database is composed by a total of 1221 images of 77 Congolese timber species belonging to 58 genera and 25 families. Based on this list, the transverse sections of all available anatomical slides of the Tervuren Xylarium (Royal Museum for Central Africa) were inspected under the light microscope. Only sections free of cracks and artifacts (e.g., enclosed air bubbles), uniform in texture, sufficiently thin and free of staining agents were selected. Cross-sections were cut with a sliding microtome, dehydrated in a graded ethanol series (50%, 75%, 96% and 100%) and fixed with Euparal.</p> <p> </p> <p>Please cite as:</p> <p>Rosa da Silva, N., De Ridder, M., Baetens, J.M. <em>et al.</em> Automated classification of wood transverse cross-section micro-imagery from 77 commercial Central-African timber species. <em>Annals of Forest Science</em> 74, 30 (2017). https://doi.org/10.1007/s13595-017-0619-0</p>
2023 Commercial Coincell 45mAh
<p>Dataset of 24 2023 Coincells with 45 mAh nominal capacity from manufacturer Conrad.</p><p>Acknowledge funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy (EXC 2154, Project No. 390874152).</p>
Accompanying Data - Nitrogenous Compound Utilization and Production of Volatile Organic Compounds among Commercial Wine Yeasts Highlight Strain-Specific Metabolic Diversity
<p>This repository contains all the data and some of the performed statistical analysis from all the measurements in the following paper: Scott Jr WT, Van Mastrigt O, Block DE, Notebaart RA, Smid EJ. Nitrogenous compound utilization and production of volatile organic compounds among commercial wine yeasts highlight strain-specific metabolic diversity. Microbiology spectrum. 2021 Aug 31;9(1):10-128.</p><p>Please cite: Scott Jr WT, Van Mastrigt O, Block DE, Notebaart RA, Smid EJ. Nitrogenous compound utilization and production of volatile organic compounds among commercial wine yeasts highlight strain-specific metabolic diversity. Microbiology spectrum. 2021 Aug 31;9(1):10-128.</p><p>Contact: Dr. William T. Scott (william.scott@wur.nl) or Dr. Eddy J. Smid (eddy.smid@wur.nl) for more information</p>
Drinking Fountain Commercial Road
A drinking fountain under the old railway bridge at the junction of Commercial Road and Lowell Street, London. Date: 1886 http://www.mdfcta.co.uk/details-f/f012.html 168 photos taken in April 2021 with a Sony a6000 and processed in Reality Capture. Source: Objaverse 1.0 / Sketchfab
Data from: "Lithium-ion battery degradation: comprehensive cycle ageing data and analysis for commercial 21700 cells"
<h1><strong>Intro</strong></h1> <p>Dataset from the publication "Lithium-ion battery degradation: comprehensive cycle ageing data and analysis for commercial 21700 cells", DOI: https://doi.org/10.1016/j.jpowsour.2024.234185</p> <p>Full details of the study can be found in the publication, including thorough descriptions of the experimental methods and structure. A basic desciption of the experimental procedure and data structure is included here for ease of use.</p> <p>Commercial 21700 cylindrical cells (LG M50T, LG GBM50T2170) were cycle aged under 3 different temperatures [10, 25, 40] °C and 4 different SoC ranges [0-30, 70-85, 85-100, 0-100]%, as well as a further [0-100]% SoC range experiment which utilised a drive-cycle discharge instead of constant-current. The same C-rates (0.3C / 1 C, for charge / discharge) were used in all tests; multiple cells were tested under each condition. These are listed in the table below.</p> <table> <tbody> <tr> <td> <div> <p><strong>Experiment</strong></p> </div> </td> <td> <div> <p><strong>SOC Window</strong></p> </div> </td> <td> <div> <p><strong>Cycles per ageing set</strong></p> </div> </td> <td> <div> <p><strong>Current</strong></p> </div> </td> <td> <div> <p><strong>Temperature</strong></p> </div> </td> <td> <div> <p><strong>Number of Cells</strong></p> </div> </td> </tr> <tr> <td> <div> <p>1</p> </div> </td> <td> <div> <p>0-30%</p> </div> </td> <td> <div> <p>257</p> </div> </td> <td> <div> <p>0.3C / 1D</p> </div> </td> <td> <div> <p>10°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> <div> <p> </p> </div> </td> <td> <div> <p> </p> </div> </td> <td> <div> <p> </p> </div> </td> <td> <div> <p> </p> </div> </td> <td> <div> <p>25°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>40°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> <div> <p>2,2</p> </div> </td> <td> <div> <p>70-85%</p> </div> </td> <td> <div> <p>515</p> </div> </td> <td> <div> <p>0.3C / 1D</p> </div> </td> <td> <div> <p>10°C</p> </div> </td> <td> <div> <p>2</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>25°C</p> </div> </td> <td> <div> <p>2</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>40°C</p> </div> </td> <td> <div> <p>2</p> </div> </td> </tr> <tr> <td> <div> <p>3</p> </div> </td> <td> <div> <p>85-100%</p> </div> </td> <td> <div> <p>515</p> </div> </td> <td> <div> <p>0.3C / 1D</p> </div> </td> <td> <div> <p>10°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>25°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>40°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> <div> <p>4</p> </div> </td> <td> <div> <p>0-100% (drive-cycle)</p> </div> </td> <td> <div> <p>78</p> </div> </td> <td> <div> <p>0.3C / noisy D</p> </div> </td> <td> <div> <p>10°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>25°C</p> </div> </td> <td> <div> <p>2</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>40°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> <div> <p>5</p> </div> </td> <td> <div> <p>0-100%</p> </div> </td> <td> <div> <p>78</p> </div> </td> <td> <div> <p>0.3C / 1D</p> </div> </td> <td> <div> <p>10°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>25°C</p> </div> </td> <td> <div> <p>2</p> </div> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> <div> <p>40°C</p> </div> </td> <td> <div> <p>3</p> </div> </td> </tr> </tbody> </table> <p>Cells were base-cooled at set temperatures using bespoke test rigs (see our linked publications for details; the supporting information file contains detailed descriptions and photographs). Cells were subject to break-in cycles prior to beginning of life (BoL) performance tests using the ‘Reference Performance Test’ (RPT) procedures. They were then alternately subject to ageing sets and RPTs until the end of testing. Full details of each of these procedures are described in the linked publication.</p> <p>The data contained in this repository is then described in the Data section below. This includes a description of the folder structure and naming conventions, file formats, and data analysis methods used for the ‘Processed Data’ which has been calculated from the raw data.</p> <p>An 'experimental_metadata' .xlsx file is included to aid parsing of data. A jupyter notebook has also been included to demonstate how to access some of the data.</p> <h1>Data</h1> <p>Data are organised according to their parent ‘Experiment’, as defined above, with a folder for each. Within each Experiment folder, there are 3 subfolders: ‘Summary Data’, ‘Processed Timeseries Data’, and ‘Raw Data’.</p> <h2>Summary Data</h2> <p>This folder contains data which has been extracted by processing the raw data in the ‘Degradation Cycling’ and ‘Performance Checks’ folders. In most cases, the data you are looking for will be stored here.</p> <p>It contains: </p> <h3>Performance Summary</h3> <p>A summary file for each cell which details key ageing metrics such as number of ageing cycles, charge throughput, cell capacity, resistance, and degradation mode analysis results. Each row of data corresponds to a different SoH.</p> <p>Degradation Mode Analysis (DMA) was also performed on the C/10 discharge data at each RPT. This analysis uses an optimisation function to determine the capacities and offset of the positive and negative electrodes by calculating a full cell voltage vs capacity curve using 1/2 cell data and comparing against the experimentally measured voltage vs capacity data from the C/10 discharge. See our <a href="https://doi.org/10.1021/acsaem.2c02047">ACS publication</a> for more details.</p> <p>Data includes:</p> <p>· Ageing Set: numbered 0 (BoL) to x, where x is the number of ageing sets the cell has been subject to.</p> <p>· Ageing Cycles: number of ageing cycles the cell has been subject to. *this is not equivalent full cycles.</p> <p>· Ageing Set Start Date/ End date: The date that each ageing set began/ ended.</p> <p>· Days of degradation: Number of days between the date of the first ageing set beginning and the current ageing set ending.</p> <p>· Age set average temperature: average recorded surface temperature of the cell during cycle ageing. Temperature was recorded approximately 1/2 way up the length of the cell (i.e. between positive and negative caps).</p> <p>· Charge throughput: total accumulated charge recorded during all cycles during ageing (i.e. sum of charge and discharge). This is the cumulative total since BoL (not including RPTs, and not including break-in cycles).</p> <p>· Energy throughput: as with "charge throughput", but for energy.</p> <p>· C/10 Capacity: the capacity recorded during the C/10 discharge test of each RPT.</p> <p>· C/2 Capacity: the capacity recorded during the C/2 discharge test of each even-numbered RPT.</p> <p>· 0.1s Resistance: The resistance calculated from the 25-pulse GITT test of each even-numbered RPT. This value is taken from the 12th pulse of the procedure (which corresponds to ~52% SoC at BoL). The resistance is calculated by dividing the voltage drop by the current at a timecale of 0.1 seconds after the current pulse is applied (the fastest timescale possible under the 10 Hz recording condition).</p> <p>· Fitting parameters: output from the DMA optimisation function; 5 parameters which detail the upper/lower SoCs of each electrode, and the capacity fraction of graphite in the negative electrode.</p> <p>· Capacity and offset data: calculated based on the fitting parameters above alongside the measured C/10 discharge capacity.</p> <p>· DM data: Quantities of LLI, LAM-PE, LAM-NE, LAM-NE-Gr, and LAM-NE-Si calculated from the change in capacities/offset of each electrode since BoL.</p> <p>· RMSE data: the root mean squared error of the optimisation function calculated from the residual between the measured and simulated voltage vs capacity profiles.</p> <h3>Ageing Sets Summary</h3> <p>Data from the ageing cycles, summarised on an average per cycle and an average per ageing set basis. Metrics include mean/ max/ min temperatures, voltages etc.</p> <h2>Processed Timeseries data</h2> <p>Timeseries data (voltage, current, temperature, etc.) from each subtest (pOCV, GITT, etc.) of the RPTs, all grouped by subtest-type and by cell ID.</p> <p>Contains the same data as in the ‘Performance Checks’ subfolder of the 'Raw Data' folder, but has been processed to slice into relevant subtests from the RPT procedure and includes only limited variables (time, voltage, current, charge, temperature). These are all saved as .csv files. In general this data will be easier to access than the raw data, but perhaps not as rich.</p> <h2>Raw Data</h2> <p>These are the raw data from the performance checks and from the degradation cycles themselves. The data from here has already been processed by me to get values of ‘energy throughput’, ‘charge throughput’, ‘average ageing temperature’, etc., which are all saved in the ‘Summary Data’ folder as described in the relevant section above.</p> <p>The data in the ‘Degradation Cycling’ folder are organised by ageing set (where an ageing set is a defined number of ageing cycles, as described in the paper). In theory, each cell should have one datafile in each ageing set subfolder. However, due to experimental issues, tests can sometimes be interrupted midway though, requiring the test to be subsequently resumed. In this case, there may be multiple datafiles for each cell in a given ageing set; during analysis, these should be concatenated according to the descriptor in the filename (e.g., ‘cycling7’ + ‘cycling7 (part 2)').</p> <p>Similarly, the unprocessed raw data from the performance checks (i.e. RPTs) is stored in the 'Performance Checks' folder, and structured in the same way.</p> <p>The raw data are saved in the .mpr format produced by the Biologic battery cycler. This is a binary format which is storage-efficient but can be more difficult to process for analysis purposes. We have therefore also exported the data into .txt files (called .mpt) for the performance checks (RPTs) which make analysis easier. However, the exported .mpt files could not be included for the degradation cycling files due to their larger size. If you require access these degradation cycle data, the .mpr binary file can be parsed using the <a href="https://github.com/echemdata/galvani">Galvani</a> package in python, or you can use Biologic’s (proprietary) BT-Lab software to export the data into .txt files.</p> <h3>File Naming Convention</h3> <p>The raw datafiles are named with a standard format. This is:</p> <p> <em>NDK - LG M50 deg - exp 1 - rig 1 - 10degC - cell A - RPT1_01_MB_CB1</em></p> <p> {NDK - LG M50 deg} - {exp 1} – {rig 1} – {10degC} – {cell A} – {RPT1}_{01}_{MB}_{CB1}</p> <p>{Standard prefix} – {experiment number} – {ID of test rig} – {control temperature} – {Cell ID} – {RPT number <em>or</em> aging cycle number}_{step number for the characterisation procedure (see above)}_{experimental technique name (will always be “MB”)}_{battery cycler channel ID used (always the same for a particular cell/experiment)}</p> <p> </p>
Fig. 1. Tick species and the total monthly tick numbers collected during the 5 in Seasonal variations in ixodid tick populations on a commercial game farm in the Limpopo Province, South Africa
Fig. 1. Tick species and the total monthly tick numbers collected during the 5-year study period.
Data for: Estimation of genetic parameters for the implementation of selective breeding in commercial insect production
<p><strong>Background</strong></p> <p>There is a burgeoning interest in using insects as a sustainable source of food and feed, particularly by capitalising on various waste materials and by-products that are typically considered of low value. Enhancing the commercial production of insects can be achieved through two main approaches: optimising environmental conditions and implementing selective breeding strategies. In order to successfully target desirable traits through selective breeding, having a thorough understanding of the genetic parameters pertaining to those traits is essential. In this study, a full-sib half-sib mating design was used to estimate variance components and heritabilities for larval size and survival at day seven of development, development time and survival from egg to adult, and to estimate correlations between these traits, within an outbred population of house flies (<em>Musca domestica</em>), using high-throughput phenotyping for data collection.</p> <p><strong>Results</strong></p> <p>The results revealed low to intermediate heritabilities and positive genetic correlations between all traits except development time and survival to day seven of development and from egg to adulthood. Surprisingly, larval size at day seven exhibited a comparatively low heritability (0.10) in contrast to development time (0.25), a trait that is believed to have a stronger association with overall fitness. A decline in family numbers resulting from low mating success and high overall mortality reduced the amount of available data which resulted in large standard errors for the estimated parameters. Environmental factors made a substantial contribution to the phenotypic variation, which was overall high for all traits.</p> <p><strong>Conclusions</strong></p> <p>There is potential for genetic improvement in all studied traits and estimates of genetic correlations indicate a partly shared genetic architecture among the traits. All estimates have large standard errors. Implementing high-throughput phenotyping is imperative for the estimation of genetic parameters in fast developing insects, and facilitates age synchronisation, which is vital in a breeding population. In spite of endeavours to minimise non-genetic sources of variation, all traits demonstrated substantial influences from environmental components. This emphasises the necessity of thorough attention to the experimental design before breeding is initiated in insect populations.</p>
1H NMR Data of Commercial Honey Analysed by 400 and 700 MHz Spectrometers
<p>Datasets (*.xlsx) contain the 1H NMR Raw (.fid) and Binning data (.xlsx) of commercial honey analysed using 400 MHz and 700 MHz NMR spectrometers</p>
Co-formulant in a commercial fungicide product causes lethal and sub-lethal effects in bumble bees
<p>The dataset and code behind an experimental paper in Scientific Reports. </p> <p>Paper DOI: https://doi.org/10.1038/s41598-021-00919-x</p> <p>Pollinators, particularly wild bees, are suffering declines across the globe, and pesticides are thought to be drivers of these declines. Research into, and regulation of pesticides has focused on the active ingredients, and their impact on bee health. In contrast, the additional components in pesticide formulations have been overlooked as potential threats. By testing an acute oral dose of the fungicide product Amistar, and equivalent doses of each individual co-formulant, we were able to measure the toxicity of the formulation and identify the ingredient responsible. We found that a co-formulant, alcohol ethoxylates, caused a range of damage to bumble bee health. Exposure to alcohol ethoxylates caused 30% mortality and a range of sublethal effects. Alcohol ethoxylates treated bees consumed half as much sucrose as negative control bees over the course of the experiment and lost weight. Alcohol ethoxylates treated bees had significant melanisation of their midguts, evidence of gut damage. We suggest that this gut damage explains the reduction in appetite, weight loss and mortality, with bees dying from energy depletion. Our results demonstrate that sublethal impacts of pesticide formulations need to be considered during regulatory consideration, and that co-formulants can be more toxic than active ingredients.</p>
Pinpointing genetic breaks in the southeastern Pacific: phylogeography and genetic structure of Pyura chilensis, a commercially important tunicate
<p><strong>Aim</strong>: Accurate characterization of evolutionary units (species or populations) underlies all ecological and evolutionary studies and is crucial to conservation planning. Seascapes have long been thought to be highly permeable to gene flow, yet over the last decade building evidence has shown that barriers to gene flow in marine environments are much more common than previously thought. Here, we precisely characterize barriers to gene flow in the tunicate Pyura chilensis across 26° of latitude in the southeastern Pacific, assess the magnitude of said barriers, and explore their congruence with current biogeographic patterns of this region.</p> <p><strong>Location</strong>: The southeastern Pacific (SEP), from Ilo, Perú (17ºS) to Chiloe, Chile (43ºS).</p> <p><strong>Taxon: </strong><em>Pyura chilensis</em></p> <p><strong>Methods</strong>: We used a combination of highly polymorphic microsatellite markers and a 540 bp fragment of the Cytochrome Oxidase subunit I (COI) to compare individuals sampled at 26 localities spanning approximately 2500 km of the SEP. Genetic diversity was analyzed using Bayesian clustering, haplotype networks, Isolation by Distance, and cline models. Coalescent simulators were used to estimate migration rates.</p> <p><strong>Results</strong>: The results from both the microsatellite and COI markers indicate the presence of two genetic discontinuities: one at 34°S and one at 39°S which coincide with genetic breaks reported for other species. Interestingly, we were able to determine that genetic transitions occur abruptly and within short geographic distances (~ 30 km) compared with previous studies of this tunicate. Coalescent simulations indicate the 34ºS break is less permeable than the 39ºS break, and gene flow appears to be mostly unidirectional from north to south.</p> <p><strong>Main conclusions</strong>: Our results support other studies that show that seascapes are complex, and also highlight the importance of accurately sampling distribution ranges when making conclusions about gene flow. Overall, the two main biogeographic barriers to gene flow characterized in the southeastern Pacific are not homogenously permeable and can be narrow (< 30 km). These results are relevant for the management of fisheries in this region and specifically for this commercially important species.</p>
AFM-IR images and spectra of commercial polymers
<p>This data set contains photothermal IR images (AFM-IR) and spectra of a commercial polymers taken with a Bruker nanoIR3. A Daylight solutions MIRcat-QT external cavity quantum cascade laser. Fourier transform infrared (FTIR) spectra were recorded with Bruker Tensor 35 spectrometer using a "Platinum ATR" (Bruker) attenuated total reflection sampling accessory with a diamond ATR element.</p> <p> </p> <p>The AFM-IR raw data files (".axz") are gzipped XML files that can be opened with the <a href="https://github.com/GeorgRamer/anasys-python-tools">anasyspythontools</a> python library. FTIR files (".txt") are CSV files. The first column represents wavenumbers, the second column represents absorption.</p>
Fig. 1 in Mercury bioaccumulation in fish of commercial importance from different trophic categories in an Amazon floodplain lake
Fig. 1. Map of lago Grande de Mancapuru.
Dataset for "Integrated acoustic resonators in commercial fin field-effect transistor technology"
<p>Companion dataset and code for "Integrated acoustic resonators in commercial fin field-effect transistor technology" by Anderson, He, Bahr, and Weinstein.</p> <p>https://www.nature.com/articles/s41928-022-00827-6</p> <p>https://arxiv.org/abs/2107.00608</p> <p> </p>
Whole genome resequencing reveals signatures of rapid selection in a virus affected commercial fishery
<p>Infectious diseases are recognised as one of the greatest global threats to biodiversity and ecosystem functioning. Consequently, there is a growing urgency to understand the speed at which adaptive phenotypes can evolve and spread in natural populations to inform future management. Here we provide evidence of rapid genomic changes in wild Australian blacklip abalone (<em>Haliotis rubra</em>) following a major population crash associated with an infectious disease. Genome scans on <em>H. rubra</em> were performed using pooled whole genome re-sequencing data from commercial fishing stocks varying in historical exposure to haliotid herpesvirus-1 (HaHV-1). Approximately 25,000 SNP loci associated with virus exposure were identified, many of which mapped to genes known to contribute to HaHV-1 immunity in the New Zealand pāua (<em>H. iris</em>) and herpesvirus response pathways in haliotids and other animal systems. These findings indicate genetic changes across a single generation in <em>H. rubra </em>fishing stocks decimated by HaHV-1, with stock recovery potentially determined by rapid evolutionary changes leading to virus resistance. This is a novel example of rapid adaptation in natural populations of a non-model marine organism, highlighting the pace at which selection can potentially act to counter disease in wildlife communities.</p>
Biofouling data from underwater surveys of commercial ships in Canada
<p>Ship biofouling is a major vector for the introduction and spread of harmful marine species globally. Comprehensive underwater sampling and video recording of ship hulls was conducted to assess biofouling extent (percent cover, total abundance and species richness) on a subset of ships arriving to Canadian waters. The dataset includes underwater biofouling assessments from 53 commercial ships arriving at Halifax, Nova Scotia (20 international ships), Vancouver, British Columbia (20 international ships) during 2007–2009, and Churchill, Manitoba (11 international and 2 domestic ships) in 2010–2011. Potential explanatory variables in the dataset include ship size, typical sailing speed, port residence time, age of antifouling coating system and travel history (number of biogeographic realms visisted, and average, minimum and maximum port latititude).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.