The statistic shows the computer graphics software market value in the vector graphics segment from 2009 to 2013. In 2010, there was a market value of 200 million U.S. dollars.

The Vector Graphics Software market has emerged as a crucial segment within the broader software industry, catering to the evolving needs of designers, artists, and businesses alike. By enabling the creation and manipulation of scalable graphics, vector graphics software plays a pivotal role across various sectors,

This graph shows the total number of vector-borne disease cases in the U.S. from 2004 to 2018. In the year 2004, there were 27,388 cases of vector-borne disease, while in 2018 there were 53,591 such cases.

The 2D CAM software market plays a pivotal role in the manufacturing and fabrication industries, enabling businesses to streamline their production processes through precise and automated machining. By transforming 2D vector graphics into machine-readable codes, these software solutions enhance efficiency and accura

Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and recreation access across the nation. The PAD-US 3.0 Combined Fee, Designation, Easement feature class in the full geodatabase inventory (with Military Lands and Tribal Areas from the Proclamation and Other Planning Boundaries feature class) was modified to prioritize overlapping designations, avoiding massive overestimation in protected area statistics, and simplified by the following PAD-US attributes to support user needs for raster analysis data: Manager Type, Manager Name, Designation Type, GAP Status Code, Public Access, and State Name. The rasterization process (see processing steps below) prioritized overlapping designations previously identified (GAP_Prity field) in the Vector Analysis File (e.g. Wilderness within a National Forest) based upon their relative biodiversity conservation (e.g. GAP Status Code 1 over 2). The 30-meter Image (IMG) grid Raster Analysis Files area extents were defined by the Census state boundary file used to clip the Vector Analysis File, the data source for rasterization ("PADUS3_0VectorAnalysis_State_Clip_CENSUS2020" feature class from ("PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.gdb"). Alaska (AK) and Hawaii (HI) raster data are separated from the contiguous U.S. (CONUS) to facilitate analyses at manageable scales. Note, the PAD-US inventory is now considered functionally complete with the vast majority of land protection types (with a legal protection mechanism) represented in some manner, while work continues to maintain updates, improve data quality, and integrate new data as it becomes available (see inventory completeness estimates at: http://www.protectedlands.net/data-stewards/ ). In addition, protection status represents a point-in-time and changes in status between versions of PAD-US may be attributed to improving the completeness and accuracy of the spatial data more than actual management actions or new acquisitions. USGS provides no legal warranty for the use of this data. While PAD-US is the official aggregation of protected areas ( https://www.fgdc.gov/ngda-reports/NGDA_Datasets.html ), agencies are the best source of their lands data.

Selections were point-and-click classifications of objects either individually or over a rectangular volume.

The smallest and largest radii delimit the range of the characteristic radii of the convolutional matching kernels used, and the “scales per octave” parameter determined the sampling density in the scale coordinate.

In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the geophysical and sample data collected from the St. Clair River, May 29-June 6, 2008 as part of the International Upper Great Lakes Study, a 5-year project funded by the International Joint Commission of the United States and Canada to examine whether physical changes in the St. Clair River are affecting water levels within the upper Great Lakes, to assess regulation plans for outflows from Lake Superior, and to examine the potential effect of climate change on the Great Lakes water levels ( http://www.iugls.org). This document makes available the data that were used in a separate report, U.S. Geological Survey Open-File Report 2009-1137, which detailed the interpretations of the Quaternary geologic framework of the region. This report includes a description of the suite of high-resolution acoustic and sediment-sampling systems that were used to map the morphology, surficial sediment distribution, and underlying geology of the Upper St. Clair River during USGS field activity 2008-016-FA . Video and photographs of the riverbed were also collected and are included in this data release. Future analyses will be focused on substrate erosion and its effects on river-channel morphology and geometry. Ultimately, the International Upper Great Lakes Study will attempt to determine where physical changes in the St. Clair River affect water flow and, subsequently, water levels in the Upper Great Lakes.

Note that the endothelium (vessel wall) was labeled in Image 1.

To determine behavioural stress, polyp activity states of Primnoella chilensis colonies were observed for 21 hours after eleven days under turbid seawater exposure in an experimental setup (Treatment: equals sedimentation rate of 450 mm/y; control group: ambient seawater). Image analysis was conducted by drawing a segmented selection line along the centre of the colonies' internal axis using the image-processing program ImageJ. This line was moved to the side by 175 % of the internal axis' width measured in pixels and 250 % respectively, resulting in two lines that were named selection A and B. These distances were chosen because fully expanded polyps showed a horizontal spread of about two times the internal axis' diameter and fully closed polyps less than one time respectively. For both lines, a plot profile was created showing grey values of all pixels under the segmented selection line. Lighter pixels of the extended polyps in comparison to the black background resulted in countable peaks. Therefore, the plot was divided by the highest and lowest grey values and bisected horizontally using the vector graphics editor Adobe Illustrator. The number of peaks in the upper part of the divided plot-image was then counted in ImageJ using the function 'analyze particles'. Lastly, the number of polyps of a category was calculated: category 0 (closed): = total polyps observed minus counted peaks for selection line A; category 1 (semi-open): = counted peaks for selection line A minus counted peaks for selection line B; category 2: = counted peaks for selection B.