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687 results for “Nm”
GRIME AI Water Segmentation Model for the USGS Monitoring Site at Pecos River near Acme, NM, 2022-2024
Ground-based observations from fixed-mount cameras have the potential to fill an important role in environmental sensing, including direct measurement of water levels and qualitative observation of ecohydrological research sites. All of this is theoretically possible for anyone who can install a trail camera. Easy acquisition of ground-based imagery has resulted in millions of environmental images stored, some of which are public data, and many of which contain information that has yet to be used for scientific purposes. The goal of this project was to develop and document key image processing and machine learning workflows, primarily related to semi-automated image labeling, to increase the use and value of existing and emerging archives of imagery that is relevant to ecohydrological processes. This data package includes imagery, annotation files, water segmentation model and model performance plots, and model test results (overlay images and masks) USGS Monitoring Site at Pecos River near Acme, NM, 2022-2024. All imagery was acquired from the USGS Hydrologic Imagery Visualization and Information System (HIVIS; see https://apps.usgs.gov/hivis/camera/NM_Pecos_River_near_Acme for this specific data set) and/or the National Imagery Management System (NIMS) API. Water segmentation models were created by tuning the open-source Segment Anything Model 2 (SAM2, https://github.com/facebookresearch/sam2) using images that were annotated by team members on this project. The models were trained on the "water" annotations, but annotation files may include additional labels, such as "snow", "sky", and "unknown". Image annotation was done in Computer Vision Annotation Tool (CVAT) and exported in COCO format (.json). All model training and testing was completed in GaugeCam Remote Image Manager Educational Artificial Intelligence (GRIME AI, https://gaugecam.org/) software (Version: Beta 16). Model performance plots were automatically generated during this process. This project was
GRIME AI Water Segmentation Model for the USGS Monitoring Site at Rio Grande below Elephant Butte Dam, NM, 2023-2024
Ground-based observations from fixed-mount cameras have the potential to fill an important role in environmental sensing, including direct measurement of water levels and qualitative observation of ecohydrological research sites. All of this is theoretically possible for anyone who can install a trail camera. Easy acquisition of ground-based imagery has resulted in millions of environmental images stored, some of which are public data, and many of which contain information that has yet to be used for scientific purposes. The goal of this project was to develop and document key image processing and machine learning workflows, primarily related to semi-automated image labeling, to increase the use and value of existing and emerging archives of imagery that is relevant to ecohydrological processes. This data package includes imagery, annotation files, water segmentation model and model performance plots, and model test results (overlay images and masks) for the USGS Monitoring Site at Rio Grande below Elephant Butte Dam, NM, 2023-2024. All imagery was acquired from the USGS Hydrologic Imagery Visualization and Information System (HIVIS; see https://apps.usgs.gov/hivis/camera/NM_Rio_Grande_below_Elephant_Butte_Dam for this specific data set) and/or the National Imagery Management System (NIMS) API. Water segmentation models were created by tuning the open-source Segment Anything Model 2 (SAM2, https://github.com/facebookresearch/sam2) using images that were annotated by team members on this project. The models were trained on the "water" annotations, but annotation files may include additional labels, such as "snow", "sky", and "unknown". Image annotation was done in Computer Vision Annotation Tool (CVAT) and exported in COCO format (.json). All model training and testing was completed in GaugeCam Remote Image Manager Educational Artificial Intelligence (GRIME AI, https://gaugecam.org/) software (Version: Beta 16). Model performance plots were automatically generated du
Sky irradiance over photosynthetically active radiation wavelengths (400-700 nm) recorded shipboard during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains high resolution records of sky irradiance over photosynthetically active radiation wavelengths (PAR; 400-700 nm) recorded shipboard during the Antarctic Circumnavigation Expedition (ACE) Leg 1-3. A hemispherical PAR sensor was fixed to the bow of the RV Akademik Tryoshnikov ship at approximately 2 metres height above the main deck and continuously recorded the irradiance over PAR wavelengths (400-700 nm) at 1 minute intervals from 21st December 2016 to the 16th March 2017. This data provides high resolution information on the diel cycle in sky irradiance and absolute sky irradiance over PAR wavelengths (400-700 nm) along the ship track of the ACE expedition.</p> <p><strong>Dataset contents</strong></p> <ul> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>ace_par_20200526CURRSGCMR.csv, data file, comma-separated values</li> </ul>
Removal of Aqueous Uranyl and Arsenate Mixtures by Natural Limestone and Hydroxyapatite Precipitates, Rio Paguate, NM, 2022-2023
This dataset documents a series of laboratory batch experiments investigating the removal of aqueous uranyl (U) and arsenate (As) mixtures using natural limestone and precipitated hydroxyapatite (HAp, Ca₁₀(PO₄)₆(OH)₂) as reactive materials. The main objective of the study was to address the challenge of simultaneous removal of uranyl cations and arsenate oxyanions by using mineral-based adsorbents, such as limestone. The precipitation of HAp enhanced As removal while maintaining high uranium immobilization efficiency.The archived data include measurements of aqueous U and As at trace-level concentrations under varying experimental conditions, including pH (ranging from 7 to 11), initial contaminant concentrations (0.05–1 mM), and the addition of calcium (Ca²⁺) and phosphate (PO₄³⁻) to promote HAp precipitation. Experiments were conducted in triplicate to ensure reproducibility, and solid-phase characterization data (from pXRD, SEM/EDX, and electron microprobe analysis) are also included to support the interpretation of removal mechanisms. A key finding revealed from the data is that near-complete removal of U (>97%) with As removal between 30 and 98% were achieved under pH conditions around 9. This dataset provides a comprehensive record of solution chemistry and treatment performance, serving as a fundamental resource for evaluating the effectiveness of natural mineral-based approaches for remediating co-contaminated waters.
Genetic characterization of Rarámuri Criollo cattle from the USDA-ARS Jornada Experimental Range, Las Cruces, NM, USA
Rarámuri Criollo (RC) cattle have been raised by isolated Tarahumara communities of Chihuahua, Mexico, for nearly 500 years, mostly under natural selection and minimal management. The RC cattle was introduced to the USDA Jornada Experimental Range (RCJER) in 2005 to begin evaluations of beef production performance and their adaptation to the harsh ecological and climatic conditions of the Northern Chihuahuan Desert. While this research unveiled crucial information on their phenotypic plasticity and adaptation, the genetic diversity and structure of the RCJER population remain poorly understood. This study analyzed the genetic diversity, population structure, ancestral composition, and selection signatures of the RCJER herd using a ~64K SNP array. The RCJER herd exhibits moderate genetic diversity and low population stratification with no evident clustering, suggesting a shared genetic background among different subfamilies. Admixture analysis revealed the RCJER herd represents a distinctive genetic pool within the Criollo cattle biotypes, with significant Iberian ancestry. Selection signatures identified candidate genes and Quantitative Trait Loci for traits associated with milk composition, growth, meat and carcass, reproduction, metabolic homeostasis, health, and coat color. The RCJER population represents a distinctive genetic resource adapted to harsh environmental conditions while maintaining productive and reproductive attributes. These findings are crucial to ensuring the long-term genetic conservation of the RCJER and their strategic expansion to locally adapted beef production systems in the US.
Size distribution of neutral and charged particles smaller than 42 nm measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition (ACE).
<p>The size distribution of neutral and charged particles was measured using a neutral cluster and air ion spectrometer (NAIS) instrument. The concentration was corrected for diffusional losses in the inlet.</p> <p>The concentration and temporal dynamics of small particles is fundamental to characterize the first step of new particle formation (NPF) and growth. Moreover, naturally charged particles and ions can provide information about the role of ion induced nucleation. Newly formed particles can grow to larger sizes where they act as cloud condensation nuclei, directly affecting the Earth radiative budget and cloud properties.</p> <p>Measurements were performed on the upper deck of icebreaker Akademik Tryoshnikov along the track of the Antarctic Circumnavigation expedition. Temporal coverage is from January 22, 2017 to April 11, 2017. The concentration is reported as dN/dlog(Dp) per cubic centimetre, where Dp indicates the corresponding diameter size bin. Data were collected with one-second time resolution and averaged automatically by the acquisition software to 120 seconds before January 31 2017 and to 90 seconds after that date. The instrument was calibrated before the campaign by the manufacturer and periodically cleaned during the campaign (one time per leg).</p> <p>Pollution from the ship exhaust and other human activities (e.g. helicopter flights) was identified as described in Schmale et al., 2019 (<a href="https://doi.org/10.1175/BAMS-D-18-0187.1">https://doi.org/10.1175/BAMS-D-18-0187.1</a>) and a corresponding flag was associated to the data (with 1 meaning clean data and 0 polluted data).</p> <p> </p> <p>***** Dataset contents *****</p> <p>- 01_neutral_particles_size_distribution.csv, data file, comma-separated values</p> <p>- 02_negative_ions_size_distribution.csv, data file, comma-separated values</p> <p>- 03_positive_ions_size_distribution.csv, data file, comma-separated values</p> <p>- 04_neutral_particles_size_distribution_header.txt, metadata, text</p> <p>- 05_negative_ions_size_distribution_header.txt, metadata, text</p> <p>- 06_positive_ions_size_distribution_header.txt, metadata, text</p> <p>- README.txt, metadata, text</p> <p>Data that were missing or bad because of instrumental problems were simply removed from the file (no entry).</p>
Sub-10 nm size-distribution data for "What controls the observed size-dependency of the growth rates of sub-10 nm atmospheric particles?"
<pre>Size-Distribution data from the CERN CLOUD experiment (Kirkby et al., 2011) measured with a DMA-train (Stolzenburg et al., 2017) Data acquired during the CLOUD10 (Fall 2015) and CLOUD12 (Fall 2017) campaigns. Data associated with the publication Kontkane et al. (2022). File name indicates the Experiment number as specified in Table 3, Kontkanen et al. (2022) and the internal CLOUD run numbers as given in Table S1, Kontaknen et al. (2022). Concentration of precursor gases are also given in these two Tables. Exp. 8 only used data from NAIS and is not included in this repository. Header indicates the diameter at which the size-distribution is measured. First column is time column with areadable timestamp in the format %Y-%m-%d %H:%M:%S. Data is dN/dlog_10 dp in unit cm^(-3). Full size-distribution (up to 400 nm) can be obtained from the author upon request. References: Kontkanen et al. (2022), What controls the observed size-dependency of the growth rates of sub-10 nm atmospheric particles?, Environ. Sci.: Atmos., accepted. Kirkby et al. (2011), Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation, Nature, 476, 429-433, http://dx.doi.org/10.1038/nature10343 Stolzenburg et al. (2017), A DMA-train for precision measurement of sub-10nm aerosol dynamics, Atmos. Meas. Tech., 10, 1639-1651, http://www.atmos-meas-tech.net/10/1639/2017/ </pre>
Mapping mineralogical heterogeneities at the nm-scale by scanning electron microscopy in modern Sardinian stromatolites: Deciphering the origin of their laminations
<p>These are the raw or processed data used for a paper published in Chemical Geology by Debrie et al. (2022), entitled "Mapping mineralogical heterogeneities at the nm-scale by scanning electron microscopy in modern Sardinian stromatolites: Deciphering the origin of their laminations", <a href="https://doi.org/10.1016/j.chemgeo.2022.121059">https://doi.org/10.1016/j.chemgeo.2022.121059</a></p> <p>The data content is summarized in the List_description_of_data.xlsx file</p>
Half-kilowatt high energy third harmonic conversion to 50 J @ 10 Hz at 343 nm [dataset]
<p>Dataset relevant to the publication "Half-kilowatt high energy third harmonic conversion to 50 J @ 10 Hz at 343 nm" in HPLSE</p>
Uranium mobility and accumulation along the Rio Paguate, Jackpile Mine in Laguna Pueblo, NM
The mobility and accumulation of uranium (U) along the Rio Paguate, adjacent to the Jackpile Mine, in Laguna Pueblo, New Mexico was investigated using aqueous chemistry, electron microprobe, X-ray diffraction and spectroscopy analyses. Given that it is not common to identify elevated concentrations of U in surface water sources, the Rio Paguate is a unique site that concerns the Laguna Pueblo community. This study aims to better understand the solid chemistry of abandoned mine waste sediments from the Jackpile Mine and identify key hydrogeological and geochemical processes that affect the fate of U along the Rio Paguate. Solid analyses using X-ray fluorescence determined that sediments located in the Jackpile Mine contain ranges of 320 to 9200 mg kg-1 U. The presence of coffinite, a U(IV)-bearing mineral, was identified by X-ray diffraction analyses in abandoned mine waste solids exposed to several decades of weathering and oxidation. The dissolution of these U-bearing minerals from abandoned mine wastes could contribute to U mobility during rain events. The U concentration in surface waters sampled closest to mine wastes are highest during the southwestern monsoon season. Samples collected from September 2014 to August 2016 showed higher U concentrations in surface water adjacent to the Jackpile Mine (35.3 to 772 mg L-1) compared with those at a wetland 4.5 kilometers downstream of the mine (5.77 to 110 mg L-1). Sediments co-located in the stream bed and bank along the reach between the mine and wetland had low U concentrations (range 1–5 mg kg-1) compared to concentrations in wetland sediments with higher organic matter (14–15%) and U concentrations (2–21 mg kg-1). Approximately 10% of the total U in wetland sediments was amenable to complexation with 1 mM sodium bicarbonate in batch experiments; a decrease of U concentration in solution was observed over time in these experiments likely due to re-association with sediments in the reactor. The findings from this study pro
Genetic characterization of 24 Angus × Hereford cows from the Jornada Experimental Range, Las Cruces, NM, USA
The southwestern US is increasingly facing dry and variable climate conditions, requiring beef operations to adopt novel strategies to meet these emerging challenges. One potential approach is the use of locally adapted cattle breeds or biotypes. A distinctive Angus x Hereford (AH) research herd at the USDA Agricultural Research Service Jornada Experimental Range provides an opportunity to explore the genetic makeup of a desert-adapted cattle herd bred for over four decades under the extreme and harsh conditions of New Mexico’s Chihuahuan Desert. The objective of this study was to analyze the population structure, genetic diversity and signatures of selection of the AH research herd (n = 24). All cows were genotyped using a 64K SNP chip. Principal component and admixture analyses confirmed the mixed genetic background of the AH cows, predominantly of Angus ancestry. The heterozygosity level, effective population size, and inbreeding coefficient indicated that the AH cows maintain moderate genetic diversity and inbreeding levels. Genomic regions under positive selection revealed genes and Quantitative Trait Loci associated with beneficial carcass traits, milk composition, fertility, body homeostasis, antioxidant activity, immune response, and terrain utilization. This research herd could potentially serve as a valuable genetic resource for improving the adaptability and productivity of commercial beef cattle in harsh semi-arid and arid environments, balancing hardiness and performance.
Monsoon Rainfall Manipulation Experiment (MRME): Soil Carbon Dioxide Concentrations from the Sevilleta National Wildlife Refuge, NM
The Monsoon Rainfall Manipulation Experiment (MRME) is to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, which alters the pulses of soil moisture that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. These soil carbon dioxide data were collected at three depths.
Monsoon Rainfall Manipulation Experiment (MRME): Soil Temperature Data from the Sevilleta National Wildlife Refuge, NM
The Monsoon Rainfall Manipulation Experiment (MRME) is to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, which alters the pulses of soil moisture that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. These data are soil temperature data collected at two depths.
Vegetation surveys in the riparian (bosque) corridor of the Middle Rio Grande valley, NM
This dataset contains vegetation cover information from 34 long-term Bosque Ecosystem Monitoring Program (BEMP) sites from 2000 – 2021. Data were collected along ten 30-m transects at each site at the centimeter scale each year in August-early October as funding and site access allowed. At the fullest extent, sites spanned 520 km of the riparian forest along the Rio Grande. The purpose of this dataset is to track plant species at sites along the Rio Grande in New Mexico. From this dataset, changes in plant species abundance, richness, and species diversity can be tracked and analyzed with ecosystem drivers such as flooding, fire, species removal/fuel reduction projects, and climate change. Species are coded using USDA Plant Database codes, allowing species information to be added to each species, including origin (native or nonnative), duration (e.g., annual, biennial, perennial), and plant type (e.g., grass, forb, vine, shrub, tree). This dataset has allowed the tracking of the ascendance of nonnatives in some sites, the recovery of natives in other sites, success or lack of success following restoration projects, and records of new species occurring in various counties and the state of New Mexico.
Optical properties of marine aerosols with varying water content at wavelengths 532 and 1064 nm, modelled with a morphologically realistic aerosol model
<p>The data contain computational results obtained with the ADDA program at wavelengths 532 nm and 1064 nm, for particle sizes 0.04, 0.06, ..., 1.5 micrometers (where size = volume-equivalent dry radius), and for salt mass fractions 0.91, 0.94, 0.97, 1.00. The content of the data files is described in the README file.</p>
Deliverable D2 (D1.2) - FEBID of SiOx with lateral feature size of 20 nm
<p>Direct local nanofabrication of silicon oxide by Focused Electron Beam Induced Deposition (FEBID) can have a significant impact in the fabrication of nanoscale circuits for creating insulating barriers and may act as a mask in etching steps. It is known that SiOx can be grown by FEBID using Si precursors such as 2, 4, 6, 8, 10-pentamethyl-cyclopenta-siloxane (PMCPS) combined with water. High-resolution deposition of lines and dots by FEBID has been achieved in different electron microscope systems. However, high-resolution SiOx deposits using PMCPS combined with water has not been reported yet.<br> FEBID is out carried in an eLINE system (Raith) equipped with a Schottky-type electron emitter. The precursor gas is supplied in the chamber through a five-needle gas injection system (GIS). The reservoir’s temperature of PMCPS and water is 30°C. The GIS is positioned approximately 500μm above the sample. A Si/SiO2 (native) substrate with 5nm Pt on top was used. Single pixel lines with a length of 1μm were patterned with an electron beam energy of 30keV, a beam current of 32pA, a 10μs dwell time and at 10mm working distance. The Pt was deposited in order to enhance the contrast between the substrate and the deposited SiOx.</p>
The Structure of Sub-nm Platinum Clusters at Elevated Temperatures (Supplementary Information)
<p><strong><em>This dataset consists of raw data and denoised scanning transmission electron microscopy videos of sub-nm sized clusters of Pt on a carbon substrate. The data is used in the article "The Structure of Sub-nm Platinum Clusters at Elevated Temperatures" published in Angewandte Chemie International Edition, 2019, DOI:10.1002/anie.201911068</em></strong><strong><em> </em></strong></p> <p><strong>Video S1.</strong> A typical sub-nm amorphous cluster at room temperature. 0.5 nm scale bar.</p> <p><strong>Video S2.</strong> Two typical crystalline sub-nm clusters at 350°C. 0.5 nm scale bar.</p> <p><strong>Video S3. </strong>In this high-speed recording at 147 fps, the high beam current required for this fast imaging has suppressed the crystallinity of the cluster, despite the temperature of 350°C. 0.5 nm scale bar.</p> <p><strong>Video S4. </strong>The unusually stable 13-atom cluster at the bottom forms an fcc cuboid, and can be seen rotating at three orientations, as shown by the inset model and in Fig. 3a-c. 0.5 nm scale bar.</p> <p><strong>Video S5. </strong>This 15-atom cluster initially forms an fcc cube, then transforms into multiple hcp structures. (Recorded at 2 fps, but animated at 5x real time at 10fps). 0.5 nm scale bar.</p> <p><strong>Video S6. </strong>The cluster in this movie is a 22-atom truncated rectangular cuboid. 0.5 nm scale bar.</p> <p><strong>Video S7. </strong>In the center and bottom, two 6-atom octagons are rotating (shown in Fig. S4) as they add onto their larger neighboring clusters. The 13-atom cluster in the top forms an unusually stable fcc cuboctahedron from frame 219. 0.5 nm scale bar.</p> <p><strong>Video S8. </strong>The cluster on the bottom left forms a fleeting icosahedron-like structure. 0.5 nm scale bar.</p> <p><strong>Video S9. </strong>This cluster shows fcc structures, despite being recorded at 200°C, but with a very low beam dose. (Recorded at 2 fps, but animated at 5x real time at 10fps). 0.5 nm scale bar.</p>
Time series of turbidity in Northern Patagonia using the Nechad algorithms (v2009 and v2016) at 665 nm. Time series 2016-2020.
<p>Time series of turbidity in Northern Patagonia using the Nechad algorithms (v2009 and v2016) at 665 nm. Time series 2016-2020.</p> <p>Our study aimed to evaluate the spatio-temporal variability of turbidity from Sentinel-2 (S2) images in the Reloncaví sound and fjord, in Northern Patagonia, Chile, a coastal ecosystem that is intensively used by finfish and shellfish aquaculture. To this end, we downloaded 123 S2 images and assembled a five-year time series (2016-2020) covering five study sites (R1 to R5) located along the axis of the fjord and seaward into the sound. We used Acolite to perform the atmospheric correction and estimate turbidity with two algorithms proposed by Nechad et al. (2009, 2016 Nv09 and Nv16, respectively).</p> <p>Columns (R) represent the spatial distribution of study sites (see Figure 2).</p> <p>Link: https://doi.org/10.1016/j.ecoinf.2024.102814</p> <p>For more information see materials and methods.</p> <p>Nv2009 or Nv09 are the results obtained for the Nechad algorithm version 2009. Similar to Nv2016 or Nv16 are the results obtained for the Nechad algorithm version 2016.</p>
Zeppelin station absorption coefficient data (Mm-1) obtained by aethalometer at 880 nm wavelength
<p>Black Carbon measurements at 880 nm wavelength during the period 2001-2015 at Zeppelin station, Svalbard.</p> <p>Data of absorption coefficient are obtained by the Aethalometer AE31 Light Attenuation through an aerosol loaded filter</p>
NO2 Corrected Timeseries of AOD at 440,400 nm, Angstrom Exponent for Two Sites in Rome
<p>Dataset Created in the framework of QA4EO wp2360. Timeseries of AOD 440nm for AERONET stations SAP and ISAC in Rome, Italy, AOD 400nm for Skynet station in SAP and corresponding ånström exponents, corrected for Total NO2 effect, using PNG data. Time period 2017-2022</p>
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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.