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  • https://en.wikipedia.org/wiki/Rockwell_scale
    Rockwell scale
    The Rockwell scale is a hardness scale based on indentation hardness of a material. The Rockwell test measures the depth of penetration of an indenter under a large load (major load) compared to the penetration made by a preload (minor load). There are different scales, denoted by a single letter, that use different loads or indenters. The result is a dimensionless number noted as HRA, HRB, HRC, etc., where the last letter is the respective Rockwell scale. Higher numbers correspond to harder materials. When testing metals, indentation hardness correlates linearly with tensile strength. History The differential depth hardness measurement was conceived in 1908 by Viennese professor Paul Ludwik in his book Die Kegelprobe (crudely, "the cone test"). The differential-depth method subtracted out the errors associated with the mechanical imperfections of the system, such as backlash and surface imperfections. The Brinell hardness test, invented in Sweden, was developed earlier – in 1900 – but it was slow, not useful on fully hardened steel, and left too large an impression to be considered nondestructive. Hugh M. Rockwell...
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  • https://en.wikipedia.org/wiki/Geologic_time_scale
    Geologic time scale
    The geologic time scale, or geological time scale, (GTS) is a representation of time based on the rock record of Earth. It is a system of chronological dating that uses chronostratigraphy (the process of relating strata to time) and geochronology (scientific branch of geology that aims to determine the age of rocks). It is used primarily by Earth scientists (including geologists, paleontologists, geophysicists, geochemists, and paleoclimatologists) to describe the timing and relationships of events in geologic history. The time scale has been developed through the study of rock layers and the observation of their relationships and identifying features such as lithologies, paleomagnetic properties, and fossils. The definition of standardized international units of geologic time is the responsibility of the International Commission on Stratigraphy (ICS), a constituent body of the International Union of Geological Sciences (IUGS), whose primary objective is to precisely define global chronostratigraphic units of the International Chronostratigraphic Chart (ICC) that are used to define divisions of geologic time. The chronostratigraphic...
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  • https://arxiv.org/abs/2109.07745
    Estimating Wildfire Evacuation Decision and Departure Timing Using Large-Scale GPS Data
    With increased frequency and intensity due to climate change, wildfires have become a growing global concern. This creates severe challenges for fire and emergency services as well as communities in the wildland-urban interface (WUI). To reduce wildfire risk and enhance the safety of WUI communities, improving our understanding of wildfire evacuation is a pressing need. To this end, this study proposes a new methodology to analyze human behavior during wildfires by leveraging a large-scale GPS dataset. This methodology includes a home-location inference algorithm and an evacuation-behavior inference algorithm, to systematically identify different groups of wildfire evacuees (i.e., self-evacuee, shadow evacuee, evacuee under warning, and ordered evacuee). We applied the methodology to the 2019 Kincade Fire in Sonoma County, CA. We found that among all groups of evacuees, self-evacuees and shadow evacuees accounted for more than half of the evacuees during the Kincade Fire. The results also show that inside of the evacuation warning/order zones, the total evacuation compliance rate was around 46% among all the categorized people. The findings of this study can be used by emergency managers and planners to better target public outreach campaigns, training protocols, and emergency communication strategies to prepare WUI households for future wildfire events.
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    https://arxiv.org/abs/2109.07745
    Estimating Wildfire Evacuation Decision and Departure Timing Using Large-Scale GPS Data
    With increased frequency and intensity due to climate change, wildfires have become a growing global concern. This creates severe challenges for fire and emergency services as well as communities in the wildland-urban interface (WUI). To reduce wildfire risk and enhance the safety of WUI communities, improving our understanding of wildfire evacuation is a pressing need. To this end, this study proposes a new methodology to analyze human behavior during wildfires by leveraging a large-scale GPS dataset. This methodology includes a home-location inference algorithm and an evacuation-behavior inference algorithm, to systematically identify different groups of wildfire evacuees (i.e., self-evacuee, shadow evacuee, evacuee under warning, and ordered evacuee). We applied the methodology to the 2019 Kincade Fire in Sonoma County, CA. We found that among all groups of evacuees, self-evacuees and shadow evacuees accounted for more than half of the evacuees during the Kincade Fire. The results also show that inside of the evacuation warning/order zones, the total evacuation compliance rate was around 46% among all the categorized people. The findings of this study can be used by emergency managers and planners to better target public outreach campaigns, training protocols, and emergency communication strategies to prepare WUI households for future wildfire events.
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  • https://scaleofuniverse.com/
    Scale of the Universe: Discover the vast ranges of our visible and invisible world.
    Scale of Universe is an interactive experience to inspire people to learn about the vast ranges of the visible and invisible world.
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  • https://brianmeza.com/business-growth-strategies-for-startups/
    Business Growth Strategies For Startups: 15 Proven Ways To Scale Your Venture
    Discover 15 proven Business Growth Strategies for Startups to scale efficiently, attract customers, and achieve long-term success in 2025.
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  • https://ui.adsabs.harvard.edu/abs/2017CEUS...65..113L
    A machine learning-based method for the large-scale evaluation of the qualities of the urban environment
    Given the present size of modern cities, it is beyond the perceptual capacity of most people to develop a good knowledge about the qualities of the urban space at every street corner. Correspondingly, for planners, it is also difficult to accurately answer questions such as 'where the quality of the physical environment is the most dilapidated in the city that regeneration should be given first consideration' and 'in fast urbanising cities, how is the city appearance changing'. To address this issue, in the present study, we present a computer vision method that contains three machine learning models for the large-scale and automatic evaluation on the qualities of the urban environment by leveraging state-of-the-art machine learning techniques and wide-coverage street view images. From various physical qualities that have been identified by previous research to be important for the urban visual experience, we choose two key qualities, the construction and maintenance quality of building facade and the continuity of street wall, to be measured in this research. To test the validity of the proposed method, we compare the machine scores with public rating scores collected on-site from 752 passers-by at 56 locations in the city. We show that the machine learning models can produce a medium-to-good estimation of people's real experience, and the modelling results can be applied in many ways by researchers, planners and local residents.
    UI.ADSABS.HARVARD.EDU
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  • https://arxiv.org/abs/1611.00283
    How much a galaxy knows about its large-scale environment?: An information theoretic perspective
    The small-scale environment characterized by the local density is known to play a crucial role in deciding the galaxy properties but the role of large-scale environment on galaxy formation and evolution still remain a less clear issue. We propose an information theoretic framework to investigate the influence of large-scale environment on galaxy properties and apply it to the data from the Galaxy Zoo project which provides the visual morphological classifications of $sim 1$ million galaxies from the Sloan Digital Sky Survey. We find a non-zero mutual information between morphology and environment which decreases with increasing length scales but persists throughout the entire length scales probed. We estimate the conditional mutual information and the interaction information between morphology and environment by conditioning the environment on different length scales and find a synergic interaction between them which operates upto at least a length scales of $ sim 30 , h^{-1}, {rm Mpc}$. Our analysis indicates that these interactions largely arise due to the mutual information shared between the environments on different length scales.
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  • https://en.wikipedia.org/wiki/Chromatic_scale
    Chromatic scale
    The chromatic scale (or twelve-tone scale) is a set of twelve pitches (more completely, pitch classes) used in tonal music, with notes separated by the interval of a semitone. Chromatic instruments, such as the piano, are made to produce the chromatic scale, while other instruments capable of continuously variable pitch, such as the trombone and violin, can also produce microtones, or notes between those available on a piano. Most music uses subsets of the chromatic scale such as diatonic scales. While the chromatic scale is fundamental in western music theory, it is seldom directly used in its entirety in musical compositions or improvisation. Definition The chromatic scale is a musical scale with twelve pitches, each a semitone, also known as a half-step, above or below its adjacent pitches. As a result, in 12-tone equal temperament (the most common tuning in Western music), the chromatic scale covers all 12 of the available pitches. Thus, there is only one chromatic scale.In equal temperament, all the semitones have the same size (100 cents), and there are twelve semitones in an octave (1200 cents). As...
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  • https://arxiv.org/abs/astro-ph/9702135
    Voids in the Large-Scale Structure
    Voids are the most prominent feature of the LSS of the universe. Still, they have been generally ignored in quantitative analysis of it, essentially due to the lack of an objective tool to identify and quantify the voids. To overcome this, we present the Void-Finder algorithm, a novel tool for objectively quantifying galaxy voids. The algorithm classifies galaxies as either wall- or field-galaxies. Then it identifies voids in the wall-galaxy distribution. Voids are defined as continuous volumes that do not contain any wall-galaxies. The voids must be thicker than an adjustable limit, which is refined in successive iterations. We test the algorithm using Voronoi tessellations. By appropriate scaling of the parameters we apply it to the SSRS2 survey and to the IRAS 1.2 Jy. Both surveys show similar properties: ~50% of the volume is filled by the voids, which have a scale of at least 40 Mpc, and a -0.9 under-density. Faint galaxies populate the voids more than bright ones. These results suggest that both optically and IRAS selected galaxies delineate the same LSS. Comparison with the recovered mass distribution further suggests that the observed voids in the galaxy distribution correspond well to under-dense regions in the mass distribution. This confirms the gravitational origin of the voids.
    ARXIV.ORG
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  • =1.0">
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  • The Rockwell scale is a hardness scale used to measure the hardness of metals, plastics, and other materials. The scale is based on the indentation hardness of a material, which is determined by measuring the depth of an indentation made by pressing a diamond cone or hardened steel ball into the surface of the material. The Rockwell scale is divided into three different scales: A, B, and C. Each scale has its own range of values that indicate increasing levels of hardness.

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  • The Rockwell scale is a hardness scale used to measure the hardness of materials such as metals. It was developed in the early 1900s by Stanley P. Rockwell and is based on the concept of measuring the depth of penetration of an indenter under a large load compared to the penetration made by a preload. The scale typically ranges from 20 (very soft) to 70 (very hard).

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  • The Rockwell scale is a hardness scale used to measure the hardness of materials. It is based on the indentation of a diamond-tipped cone into the material being tested. The hardness of a material is determined by measuring the depth of the indentation and comparing it to a chart that correlates depth to hardness. The Rockwell scale is used for testing metals, plastics, and other materials.

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  • The Rockwell scale is a hardness scale used to measure the hardness of materials. It is based on the indentation hardness principle, which states that the depth of an indentation in a material is proportional to the load applied to create it. The Rockwell scale is divided into several different scales, each with its own range and values. The most commonly used scales are the A, B, C, and D scales. Each scale measures a different range of hardness; for example, the A scale measures very soft materials such as aluminum, while the D scale measures very hard materials such as steel.

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  • The Rockwell scale is a hardness scale used to measure the hardness of materials. It is based on the indentation of a diamond-tipped cone or ball into the material being tested. The hardness number is determined by measuring the depth of the indentation and comparing it to a chart. The Rockwell scale is used in many industries, such as automotive, aerospace, and metalworking. It is also used to measure the hardness of metals, plastics, ceramics, and other materials.

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  • The Rockwell scale is a hardness scale used to measure the hardness of materials, such as metals. It is based on the indentation that a harder material makes in a softer material when a load is applied. The Rockwell scale consists of several different scales, each of which is designated by a letter. The most commonly used scales are the A, B, C and E scales. Each scale has its own range and uses different loads to measure hardness.

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  • The Rockwell scale is a hardness scale used to measure the hardness of materials. It is based on the indentation hardness principle, which states that the depth of penetration of an indenter into a material is a function of the applied load and the properties of the material such as its elastic modulus, yield strength, and hardness. The Rockwell scale consists of several different scales, each denoted by a letter, that use different loads or indenters. Each scale produces a numerical value that corresponds to a particular level of hardness. The most commonly used scales are A, B, C, and D.

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  • The Rockwell scale is a hardness scale used to measure the hardness of materials. It is based on the indentation of a diamond cone or hardened steel ball into the surface of the material. The hardness value is then determined by measuring the depth of the indentation and comparing it to a reference chart. The Rockwell scale has several different scales, each designed to measure different types of materials. The most commonly used scales are the A, B, C, and E scales.

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  • The Rockwell scale is a hardness scale used to measure the hardness of metals. It was developed by Stanley P. Rockwell in the 1920s and is used to measure the hardness of metals, plastics, and other materials. The Rockwell scale is based on a system of indentation tests that measure the depth of an indentation made by a diamond cone or ball indenter pressed into the material being tested. The resulting number indicates how hard the material is, with higher numbers indicating harder materials.

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