定价： 515元 / 折扣价： 438 元 加购物车

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4.1 An important aspect of the appearance of glossy coating surfaces is the distinctness (clarity) of images reflected by them. The values obtained in this measuring procedure correlate well with visual ratings for DOI (image clarity).4.2 Although Test Methods D523 and D4039 are useful in characterizing some aspects of glossy appearance, they do not provide satisfactory ratings for DOI (image clarity).4.3 The measurement conditions given conform to the conditions specified in Test Methods E430.4.4 The measurement conditions given in this test method conform to the conditions specified in ISO 10216.4.5 The scale values obtained with the measuring procedures of this test method range from 0 to 100 with a value of 100 representing perfect DOI (image clarity).4.6 The DOI (image clarity) scale value does not, of itself, indicate any specific cause for reduction in reflected image sharpness. Surface irregularities such as haze, orange peel, and wrinkle, when present, may be cited as causes for reduction of image sharpness.1.1 These test methods describe the measurement of the distinctness-of-image (DOI) gloss of coating surfaces using electro-optical measuring techniques.1.2 The coatings assessed shall be applied to planar rigid surfaces.1.3 Test Method—The light through a small slit is projected on the specimen surface and its reflected image intensity is measured through a sliding combed shutter to provide a value of image clarity.1.4 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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The following uses of imaging-guided stereotactic surgery have been documented in the literature, and are presented as examples. This list is not inclusive of all the techniques presently being used, and certainly does not reflect nor intend to impede the development of new techniques in the future:Biopsy of intracranial tissue,Implantation of radioisotopes by various techniques,Aspiration of cysts,Aspiration of abcesses,Instillation of therapeutic agents, including antibiotics, chemotherapeutic agents, tissue, drugs, and neurotransmitters,Insertion of electrodes for recording of electrical activity or impedance,Insertion of probes for lesion production in functional neurosurgery,Insertion of electrodes for stimulation,Aspiration of hematomas,Resection of mass lesions,Laser vaporization or removal of intracranial tissue,Guidance of externally delivered radiation therapy,Adjunct to open surgical procedures,Placement of catheters into ventricles, cysts, and so forth, andHyperthermia.AbstractThis specification covers the different types, appropriate applicability, and safety and sterilizability requirements that pertain to the combined use of stereotactic instruments or systems with imaging techniques, to direct a diagnostic or therapeutic modality into a specific target within the brain, based on localization information derived from such imaging techniques. A stereotactic instrument or system is a guiding, aiming, or viewing device used in human neurosurgery for the purpose of manually directing a system or treating modality to a specific point within the brain by radiographic, imaging, or other visualization or identification of landmarks or targets or lesions.1.1 This specification covers the combined use of stereotactic instruments or systems with imaging techniques, to direct a diagnostic or therapeutic modality into a specific target within the brain, based on localization information derived from such imaging techniques.1.2 For the purpose of this specification, a stereotactic instrument or system is a guiding, aiming, or viewing device used in human neurosurgery for the purpose of manually directing a system or treating modality to a specific point within the brain by radiographic, imaging, or other visualization or identification of landmarks or targets or lesions.1.3 Definition of Stereotactic Imaging Systems—Types of imaging-guided systems all require three components: an imaging system, a stereotactic frame, or other physical device to identify the position of a point in space, and a method to relate image-generated coordinates to frame or device coordinates. See Performance Specification F 1266. The imaging technique must reliably and reproducibly generate data concerning normal or abnormal anatomic structures, or both, that can interface with the coordinate system of the stereotactic frame or other stereotactic system. The imaging-guided systems must allow accurate direction of therapeutic, viewing or diagnostic modalities to a specific point or volume or along a specific trajectory within the brain or often accurate estimation of structure size and location allowing biopsy, resection, vaporization, implantation, aspiration, or other manipulation, or combination thereof. The standards of accuracy, reproducibility, and safety must be met for the imaging modality, the stereotactic system, and the method of interface between the two, and for the system as a whole. The mechanical parts of the imaging modality and the stereotactic system should be constructed to allow maximal interaction with minimal interference with each other, to minimize imaging artifact and distortion, and minimize potential contamination of the surgical field.1.4 General Types of Imaging that May Be Used With Stereotactic Systems—Currently employed imaging modalities used in imaging-guided stereotactic systems include radiography, angiography, computed tomography, magnetic resonance imaging, ultrasound, biplane and multiplane digital subtraction angiography, and positron emission scanning. However, it is recognized that other modalities may be interfaced with currently available and future stereotactic systems and that new imaging modalities may evolve in the future. Standards for imaging devices will be dealt with in documents concerning such devices, and will not be addressed herein.1.5 General types of diagnostic modalities include biopsy instruments, cannulas, endoscopes, electrodes, or other such instruments. Therapeutic modalities include, but are not limited to, heating, cooling, irradiation, laser, injection, tissue transplantation, mechanical or ultrasonic disruption, and any modality ordinarily used in cerebrospinal surgery.1.6 Probe—Any system or modality directed by stereotactic techniques, including mechanical or other probe, a device that is inserted into the brain or points to a target, and stereotactically directed treatment or diagnostic modality.Note 1—Examples presented throughout this specification are listed for clarity only; that does not imply that use should be restricted to the procedures or examples listed.1.7 Robot—A power-driven servo-controlled system for controlling and advancing a probe according to a predetermined targeting program.1.8 Digitizer—A device that is directed to indicate the position of a probe or point in stereotactic or other coordinates.1.9 Frameless System—A system that does not require a stereotactic frame, that identifies and localizes a point or volume in space by means of data registration, and a method to relate that point or volume to its representation derived from an imaging system.1.10 The values stated in SI units are to be regarded as the standard.1.11 The following precautionary caveat pertains only to the test method portion, Section 3, of this specification: This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

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5.1 Particle characterization, especially particle size distribution, has been an important parameter for quality control (QC) and research and development (R&D) in a very wide variety of industries and markets, anywhere a particulate system is a final product or an intermediate constituent somewhere in the process. But size alone is not a sufficient morphological measurement to use to understand many factors of the complete particle morphology of particulate systems and their effects on other properties. This information is expected to contribute to the understanding of the effects of shape on powder spreadability and flowability in the creation of the bed in powder bed fusion AM and the density and porosity of the final AM parts (definitions in ISO/ASTM 52900 and Terminology B243). Ultimately, specifications can be developed for quality control (QC) tolerances for these shape parameters that can be measured with a straightforward, fast automated analysis1.1 This guide explains how to characterize the quality of metal powder feedstock to additive manufacturing (AM) relative to the powder shape using automated static or dynamic image analysis by optical photography. This guide will describe the method(s) to measure powder shape parameters that can identify potentially detrimental powder characteristics and specifically describe how to identify and quantify the proportion of agglomerates/satellites and other irregularly shaped non-spherical powder particles in a powder batch.1.2 The values stated in SI units are to be regarded as the standard. No other units of measurement are included in this standard.1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.4 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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4.1 The Manual Observer-Dependent Assay—The manual quantification of cell and CFU cultures based on observer-dependent criteria or judgment is an extremely tedious and time-consuming task and is significantly impacted by user bias. In order to maintain consistency in data acquisition, pharmacological and drug discovery and development studies utilizing cell- and colony-based assays often require that a single observer count cells and colonies in hundreds, and potentially thousands of cultures. Due to observer fatigue, both accuracy and reproducibility of quantification suffer severely (5). When multiple observers are employed, observer fatigue is reduced, but the accuracy and reproducibility of cell and colony enumeration is still significantly compromised due to observer bias and significant intra- and inter-observer variability (2, 4) . Use of quantitative automated image analysis provides data for both the number of colonies as well as the number of cells in each colony. These data can also be used to calculate mean cells per colony. Traditional methods for quantification of colonies by hand-counting coupled with an assay for cell number (for example, DNA or mitochondrial) remains a viable method that can be used to calculate the mean number of cells per colony. These traditional methods have the advantage that they are currently less labor intensive and less technically demanding (8, 9). However, the traditional assays do not, provide colony level information (for example, variation and skew), nor do they provide a means for excluding cells that are not part of a colony from the calculation of mean colony size. As a result, the measurement of the mean number of cells per colony that is obtained from these alternative methods may differ when substantial numbers of cells in a sample are not associated with colony formation. By employing state-of-the-art image acquisition, processing and analysis hardware and software, an accurate, precise, robust and automated analysis system is realized.4.1.1 Areas of Application—Cell and colony enumeration (CFU assay) is becoming particularly important in the manufacture, quality assurance/control (QA/QC), and development of product safety and potency release criteria for cell-based regenerative medicine and cellular therapy. The U.S. Food and Drug Administration (FDA) has a guidance document that indicates that the CFU assay may be appropriate for testing stability of placental and umbilical cord blood-derived stem cells (7). Since cell source validation and QA/QC comprise approximately 50 % of the manufacturing cost of cellular therapies (10), developing a precise, robust, and cost-effective means for enumerating cells and colonies is vital to sustainability and growth in this industry. The broad areas of use for automated analysis of colony forming unit assays include:4.1.1.1 Characterization of a cell source by correlating biological potential and functional potency with CFU formation.4.1.1.2 Characterization of the effect of processing steps or biological or physical manipulation (for example, stimuli) on cells or colony formation.4.1.1.3 Cell and colony characterization using specific fluorescent and non-fluorescent (differentiation) markers.4.1.1.4 Extrapolation of the biological potency (for example, differentiation, proliferative, and so forth) of a larger sample from application of colony forming assay to sub-samples.4.1.1.5 Provision of criteria for sub-colony selection of preferred colonies (specific tissue type, proliferation rate, and so forth) for use and/or further expansion.4.2 The Technology (image acquisition, processing, and analysis)—Current standards utilize user input for defining the presence and location of colonies based on visualization of an entire culture surface at low magnification through the eyepieces of a microscope. In this case, the sample may be viewed in transmission light mode (unstained or with a histochemical marker) or fluorescently with a dye or antibody. For this practice, the colony count is the only measurable output parameter. Utilizing a microscope-based imaging system to stitch together high resolution image tiles into a single mosaic image of the entire culture surface and subsequently “clustering” segmented cells using image processing algorithms to delineate colonies, provides a fully automated, accurate, and precise method for characterizing the biological potential and functional potency of the cultured cells. Furthermore, extracted parameters in addition to colony number provide means of further characterization and sub-classification of colony level statistics. These parameters include, but are not limited to, cell/nuclear count, cell/nuclear density, colony morphology (shape and size parameters), secondary marker coverage, effective proliferation rates, and so forth (Fig. A1.2). In addition to human connective tissue progenitors (CTPs) derived from bone, bone marrow, cartilage, adipose tissue, muscle, periosteum, and synovium, this practice and technology has been implemented in the cell and colony identification and characterization of several cell and tissue types including: umbilical cord blood hematopoietic stem cells (Fig. X1.2); adipose-derived stem cells (Fig. X1.3); and human epidermal (Fig. X1.4) and dermal (Fig. X1.5) stem cells.4.3 Benefits of Automated Analysis of CFU Assays—Automated analysis is expected to provide more rapid, reproducible, and precise results in comparison to the manual enumeration of cells and colonies utilizing a microscope and hemocytometer. In addition to being time consuming, labor intensive, and subjective, manual enumeration has been shown to have a significant degree of intra- and inter-observer variability, with coefficients of variation (CV) ranging from 8.1 % to 40.0 % and 22.7 % to 80 %, respectively. Standard CVs for cell viability assessment and progenitor (colony) type enumeration have been shown to range from 19.4 % to 42.9 % and 46.6 % to 100 %, respectively (4, 11, 12). In contrast, studies focusing on bacteria, bone marrow-derived stem cells and osteogenic progenitor cells have collectively concluded that automated enumeration provides significantly greater accuracy, precision, and/or speed for counting and sizing cells and colonies, relative to conventional manual methodologies (4-6). Automated methods for enumerating cells and colonies are less biased, less time consuming, less laborious, and provide greater qualitative and quantitative data for intrinsic characteristics of cell and colony type and morphology.4.4 Selection of Cell Culture Surface Area and Optimal Cell Seeding Density—When performing a CFU assay, optimizing the cell culture surface area and cell seeding density is critical to developing methods for generating reliable and reproducible colony- and cell-level data. If seeding density is too low, then the frequency of observed colonies is decreased. This can result in a sampling size that is inadequate to characterize the population of CFUs in the sample. If seeding density is too high, the colonies that are formed may be too closely spaced. Overlapping colony footprints compromise colony counting and characterization. Because the intrinsic range of CFU prevalence in a given cell source may vary widely, in many cases, a trial and error approach to optimizing cell seeding density (or range of densities) that are needed for a given cell source will be necessary. It is important to note that the more heterogeneous the cell source (for example, bone marrow), the more colonies that are needed to accurately represent the stem and progenitor cell constituents. Further, the cell type, effective proliferation rate (EPR) and specific cell culture conditions (for example, media, serum, factors, oxygen tension, and so forth) can impact colony formation. For example, the automated CFU assay depicted in Fig. A1.2 employs a six-day culture period, two media changes, 20 % oxygen tension, alpha-MEM media (with 25 % fetal bovine serum, ascorbate, dexamethasone and streptomycin), an optimized cell seeding density of 250 000 nucleated cells per cm2 (250 000 cells per 1 mL of cell culture medium) and a cell culture surface area of 22 mm by 22 mm (dual-chamber Lab-Tek culture slides) (12, 13).4.5 Useful Documents—A number of useful documents are available that address best practices for conducting quantitative measurements of cells using imaging approaches: Guide F2998, Guide F3294, ISO 20391-1, ISO 20391-2, and “FDA Guidance on Technical Performance Assessment of Digital Pathology Whole Slide Imaging Devices,” (14).1.1 This practice, provided its limitations are understood, describes a procedure for quantitative measurement of the number and biological characteristics of colonies derived from a stem cell or progenitor population using image analysis.1.2 This practice is applied in an in vitro laboratory setting.1.3 This practice utilizes: (a) standardized protocols for image capture of cells and colonies derived from in vitro processing of a defined population of starting cells in a defined field of view (FOV), and (b) standardized protocols for image processing and analysis.1.4 The relevant FOV may be two-dimensional or three-dimensional, depending on the CFU assay system being interrogated.1.5 The primary unit to be used in the outcome of analysis is the number of colonies present in the FOV. In addition, the characteristics and sub-classification of individual colonies and cells within the FOV may also be evaluated, based on extant morphological features, distributional properties, or properties elicited using secondary markers (for example, staining or labeling methods).1.6 Imaging methods require that images of the relevant FOV be captured at sufficient resolution to enable detection and characterization of individual cells and over a FOV that is sufficient to detect, discriminate between, and characterize colonies as complete objects for assessment.1.7 Image processing procedures applicable to two- and three-dimensional data sets are used to identify cells or colonies as discreet objects within the FOV. Imaging methods may be optimized for multiple cell types and cell features using analytical tools for segmentation and clustering to define groups of cells related to each other by proximity or morphology in a manner that is indicative of a shared lineage relationship (that is, clonal expansion of a single founding stem cell or progenitor).1.8 The characteristics of individual colony objects (cells per colony, cell density, cell size, cell distribution, cell heterogeneity, cell genotype or phenotype, and the pattern, distribution and intensity of expression of secondary markers) are informative of differences in underlying biological properties of the clonal progeny.1.9 Under appropriately controlled experimental conditions, differences between colonies can be informative of the biological properties and underlying heterogeneity of colony founding cells (CFUs) within a starting population.1.10 Cell and colony area/volume, number, and so forth may be expressed as a function of cell culture area (square millimeters), or initial cell suspension volume (milliliters).1.11 Sequential imaging of the FOV using two or more optical methods may be valuable in accumulating quantitative information regarding individual cells or colony objects in the sample. In addition, repeated imaging of the same sample will be necessary in the setting of process tracking and validation. Therefore, this practice requires a means of reproducible identification of the location of cells and colonies (centroids) within the FOV area/volume using a defined coordinate system.1.12 To achieve a sufficiently large field-of-view (FOV), images of sufficient resolution may be captured as multiple image fields/tiles at high magnification and then combined together to form a mosaic representing the entire cell culture area.1.13 Cells and tissues commonly used in tissue engineering, regenerative medicine, and cellular therapy are routinely assayed and analyzed to define the number, prevalence, biological features, and biological potential of the original stem cell and progenitor population(s).1.13.1 Common applicable cell types and cell sources include, but are not limited to: mammalian stem and progenitor cells; adult-derived cells (for example, blood, bone marrow, skin, fat, muscle, mucosa) cells, fetal-derived cells (for example, cord blood, placental/cord, amniotic fluid); embryonic stem cells (ESC) (that is, derived from inner cell mass of blastocysts); induced pluripotent cells (iPC) (for example, reprogrammed adult cells); culture expanded cells; and terminally differentiated cells of a specific type of tissue.1.13.2 Common applicable examples of mature differentiated phenotypes which are relevant to detection of differentiation within and among clonal colonies include: hematopoietic phenotypes (erythrocytes, lymphocytes, neutrophiles, eosinophiles, basophiles, monocytes, macrophages, and so forth), adult tissue-specific progenitor cell phenotypes (oteoblasts, chondrocytes, adipocytes, and so forth), and other tissues (hepatocytes, neurons, endothelial cells, keratinocyte, pancreatic islets, and so forth).1.14 The number of stem cells and progenitor cells in various tissues can be assayed in vitro by liberating the cells from the tissues using methods that preserve the viability and biological potential of the underlying stem cell and/or progenitor population, and placing the tissue-derived cells in an in vitro environment that results in efficient activation and proliferation of stem and progenitor cells as clonal colonies. The true number of stem cells and progenitors (true colony forming units (tCFU)) can thereby be estimated on the basis of the number of colony-forming units observed (observed colony forming units (oCFU)) to have formed (1-3)2 (Fig. A1.1). The prevalence of stem cells and/or progenitors can be estimated on the basis of the number of observed colony-forming units (oCFU) detected, divided by the number of total cells assayed.1.15 The automated image acquisition and analysis approach (described herein) to cell and colony enumeration has been validated and found to provide superior accuracy and precision when compared to the current “gold standard” of manual observer defined visual cell and colony counting under a brightfield or fluorescent microscope with or without a hemocytometer (4), reducing both intra- and inter-observer variation. Several groups have attempted to automate this and/or similar processes in the past (5, 6) . Recent reports further demonstrate the capability of extracting qualitative and quantitative data for colonies of various cell types at the cellular and even nuclear level (4, 7).1.16 Advances in software and hardware now broadly enable systematic automated analytical approaches. This evolving technology creates the need for general agreement on units of measurement, nomenclature, process definitions, and analytical interpretation as presented in this practice.1.17 Standardized methods for automated CFU analysis open opportunities to enhance the value and utility of CFU assays in several scientific and commercial domains:1.17.1 Standardized methods for automated CFU analysis open opportunities to advance the specificity of CFU analysis methods though optimization of generalizable protocols and quantitative metrics for specific cell types and CFU assay systems which can be applied uniformly between disparate laboratories.1.17.2 Standardized methods for automated CFU analysis open opportunities to reduce the cost of colony analysis in all aspects of biological sciences by increasing throughput and reducing work flow demands.1.17.3 Standardized methods for automated CFU analysis open opportunities to improve the sensitivity and specificity of experimental systems seeking to detect the effects of in vitro conditions, biological stimuli, biomaterials and in vitro processing steps on the attachment, migration, proliferation, differentiation, and survival of stem cells and progenitors.1.18 Limitations are described as follows:1.18.1 Colony Identification—Cell Source/Colony Type/Marker Variability—Stem cells and progenitors from various tissue sources and in different in vitro environments will manifest different biological features. Therefore, the specific means to detect cells or nuclei and secondary markers utilized and the implementation of their respective staining protocols will differ depending on the CFU assay system, cell type(s) and markers being interrogated. Optimized protocols for image capture and image analysis to detect cells and colonies, to define colony objects and to characterize colony objects will vary depending on the cell source being utilized and CFU system being used. These protocols will require independent optimization, characterization and validation in each application. However, once defined, these can be generalized between labs and across clinical and research domains.1.18.2 Instrumentation-Induced Variability in Image Capture—Choice of image acquisition components described above may adversely affect segmentation of cells and subsequent colony identification if not properly addressed. For example, use of a mercury bulb rather than a fiber-optic fluorescent light source or the general misalignment of optics could produce uneven illumination or vignetting of tiled images comprising the primary large FOV image. This may be corrected by applying background subtraction routines to each tile in a large FOV image prior to tile stitching.1.18.3 CFU Assay System Associated Variation in Imaging Artifacts—In addition to the presentation of colony objects with unique features that must be utilized to define colony identification, each image from each CFU system may present non-cell and non-colony artifacts (for example, cell debris, lint, glass aberrations, reflections, autofluorescence, and so forth) that may confound the detection of cells and colonies if not identified and managed.1.18.4 Image Capture Methods and Quality Control Variation—Variation in image quality will significantly affect the precision and reproducibility of image analysis methods. Variation in focus, illumination, tile registration, exposure time, quenching, and emission spectral bleeding, are all important potential limitations or threats to image quality and reproducibility.1.19 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.1.20 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.1.21 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

定价： 590元 / 折扣价： 502 元 加购物车

定价： 590元 / 折扣价： 502 元 加购物车

5.1 These test methods cover procedures for determining the mean grain size, and the distribution of grain intercept lengths or grain areas, for polycrystalline metals and nonmetallic materials with equiaxed or deformed grain shapes, with uniform or duplex grain size distributions, and for single phase or multiphase grain structures.5.2 The measurements are performed using semiautomatic digitizing tablet image analyzers or automatic image analyzers. These devices relieve much of the tedium associated with manual measurements, thus permitting collection of a larger amount of data and more extensive sampling which will produce better statistical definition of the grain size than by manual methods.5.3 The precision and relative accuracy of the test results depend on the representativeness of the specimen or specimens, quality of specimen preparation, clarity of the grain boundaries (etch technique and etchant used), the number of grains measured or the measurement area, errors in detecting grain boundaries or grain interiors, errors due to detecting other features (carbides, inclusions, twin boundaries, and so forth), the representativeness of the fields measured, and programming errors.5.4 Results from these test methods may be used to qualify material for shipment in accordance with guidelines agreed upon between purchaser and manufacturer, to compare different manufacturing processes or process variations, or to provide data for structure-property-behavior studies.1.1 These test methods are used to determine grain size from measurements of grain intercept lengths, intercept counts, intersection counts, grain boundary length, and grain areas.1.2 These measurements are made with a semiautomatic digitizing tablet or by automatic image analysis using an image of the grain structure produced by a microscope.1.3 These test methods are applicable to any type of grain structure or grain size distribution as long as the grain boundaries can be clearly delineated by etching and subsequent image processing, if necessary.1.4 These test methods are applicable to measurement of other grain-like microstructures, such as cell structures.1.5 This standard deals only with the recommended test methods and nothing in it should be construed as defining or establishing limits of acceptability or fitness for purpose of the materials tested.1.6 The sections appear in the following order:Section Section  1Referenced Documents  2Terminology  3 Definitions  3.1 Definitions of Terms Specific to This Standard  3.2 Symbols  3.3Summary of Test Method  4  5Interferences  6Apparatus  7Sampling  8Test Specimens  9Specimen Preparation 10Calibration 11Procedure:   Semiautomatic Digitizing Tablet 12 Intercept Lengths 12.3 Intercept and Intersection Counts 12.4 Grain Counts 12.5 Grain Areas 12.6 ALA Grain Size 12.6.1 Two-Phase Grain Structures 12.7Procedure:   Automatic Image Analysis 13 Grain Boundary Length 13.5 Intersection Counts 13.6 Mean Chord (Intercept) Length/Field 13.7.2 Individual Chord (Intercept) Lengths 13.7.4 Grain Counts 13.8 Mean Grain Area/Field 13.9 Individual Grain Areas 13.9.4 ALA Grain Size 13.9.8 Two-Phase Grain Structures 13.10Calculation of Results 14Test Report 15Precision and Bias 16Grain Size of Non-Equiaxed Grain Structure Specimens Annex A1Examples of Proper and Improper Grain Boundary Delineation Annex A21.7 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.1.8 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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定价： 646元 / 折扣价： 550 元 加购物车

4.1 Each Facility Rating Scale (see Figs. 1-7) in this classification provides a means to estimate the level of serviceability of a building or facility for one topic of serviceability and to compare that level against the level of any other building or facility.4.2 This classification can be used for comparing how well different buildings or facilities meet a particular requirement for serviceability. It is applicable despite differences such as location, structure, mechanical systems, age, and building shape.4.3 This classification can be used to estimate the amount of variance of serviceability from target or from requirement for a single office facility or within a group of office facilities.4.4 This classification can be used to estimate the following:4.4.1 Serviceability of an existing facility for uses other than its present use.4.4.2 Serviceability (potential) of a facility that has been planned but not yet built.4.4.3 Serviceability (potential) of a facility for which remodeling has been planned.4.5 Use of this classification does not result in building evaluation or diagnosis. Building evaluation or diagnosis generally requires a special expertise in building engineering or technology and the use of instruments, tools, or measurements.4.6 This classification applies only to facilities that are building constructions, or parts thereof. (While this classification may be useful in rating the serviceability of facilities that are not building constructions, such facilities are outside the scope of this classification.)4.7 This classification is not intended for, and is not suitable for, use for regulatory purposes, nor for fire hazard assessment nor for fire risk assessment.1.1 This classification covers pairs of scales for classifying an aspect of the serviceability of an office facility, that is, the capability of an office facility to meet certain possible requirements for image to the public and occupants.1.2 Within that aspect of serviceability, each pair of scales, shown in Figs. 1-7, are for classifying one topic of serviceability. Each paragraph in an Occupant Requirement Scale (see Figs. 1-7) summarizes one level of serviceability on that topic, which occupants might require. The matching entry in the Facility Rating Scale (see Figs. 1-7) is a translation of the requirement into a description of certain features of a facility which, taken in combination, indicate that the facility is likely to meet that level of required serviceability.FIG. 1 Scale A.11.1 for Exterior AppearanceFIG. 1 Scale A.11.1 for Exterior Appearance (continued)FIG. 2 Scale A.11.2 for Public Lobby of BuildingFIG. 2 Scale A.11.2 for Public Lobby of Building (continued)FIG. 3 Scale A.11.3 for Public Spaces Within the BuildingFIG. 3 Scale A.11.3 for Public Spaces Within the Building (continued)FIG. 4 Scale A.11.4 for Appearance and Spaciousness of Office SpacesFIG. 5 Scale A.11.5 for Finishes and Materials in Office SpacesFIG. 6 Scale A.11.6 for Identity Outside the BuildingFIG. 6 Scale A.11.6 for Identity Outside the Building (continued)FIG. 7 Scale A.11.7 for Neighborhood and SiteFIG. 7 Scale A.11.7 for Neighborhood and Site (continued)1.3 The entries in the Facility Rating Scale (see Figs. 1-7) are indicative and not comprehensive. They are for quick scanning to estimate approximately, quickly, and economically, how well an office facility is likely to meet the needs of one or another type of occupant group over time. The entries are not for measuring, knowing, or evaluating how an office facility is performing.1.4 This classification can be used to estimate the level of serviceability of an existing facility. It can also be used to estimate the serviceability of a facility that has been planned but not yet built, such as one for which single-line drawings and outline specifications have been prepared.1.5 This classification indicates what would cause a facility to be rated at a certain level of serviceability but does not state how to conduct a serviceability rating nor how to assign a serviceability score. That information is found in Practice E1334. The scales in this classification are complimentary to and compatible with Practice E1334. Each requires the other.1.6 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

定价： 646元 / 折扣价： 550 元 加购物车

定价： 590元 / 折扣价： 502 元 加购物车

定价： 515元 / 折扣价： 438 元 加购物车

定价： 590元 / 折扣价： 502 元 加购物车