Journal articles on the topic 'Quantification'

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1

Gierasimczuk, N., and J. Szymanik. "Branching Quantification v. Two-way Quantification." Journal of Semantics 26, no. 4 (July 27, 2009): 367–92. http://dx.doi.org/10.1093/jos/ffp008.

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2

Koeva, Svetla. "Verb aspect, alternations and quantification." Cognitive Studies | Études cognitives, no. 11 (November 24, 2015): 125–34. http://dx.doi.org/10.11649/cs.2011.007.

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Verb aspect, alternations and quantificationIn this paper we are briefly discuss the nature of Bulgarian verb aspect and argue that the verb aspect pairs are different lexical units with different (although related) meaning, different argument structure (reflecting categories, explicitness and referential status of arguments) and different sets of semantic and syntactic alternations. The verb prefixes resulting in perfective verbs derivation in some cases can be interpreted as lexical quantifiers as well. Thus the Bulgarian verb aspect is related (in different way) both with the potential for the generation of alternations and with the prefixal lexical quantification. It is shown that the scope of the lexical quantification by means of verbal prefixes is the quantified verb phrase and the scope remains constant in all derived alternations. The paper concerns the basic issues of these complex problems, while the detailed description of the conditions satisfying particular alternation or particular lexical quantification are subject of a more detailed study.
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Syauqi, Ahmad, Muhamad Fuadi, and Hari Santoso. "Comparative Study of References and Protein Quantifications Using Biuret-Spectrophotometric Method." Chimica et Natura Acta 6, no. 2 (August 26, 2018): 42. http://dx.doi.org/10.24198/cna.v6.n2.19224.

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Comparison between the references and the quantification of biuret standard curves can be performed using statistical methods. The objective of this study was to select a method of protein quantification of the biuret-spectrophotometric based on the similar standard curve of the compound. The study used experimental methods in the laboratory and references from a comparative scheme of mean that has categories of statistics called academic and practical terms. Two standard curves were tested with the reference data. The academic way was performed with a comparison of 11.779-12.401% confidence, and the quantification of the results of the protein mean of 8.211% and 10.17% showed no significant difference. The practical methods were carried out with the original reference data of 10.8-12.8%, and the result of the test confidence values of 9.163-11.180% and 7.596-8.826% showed different accuracy results. The quantifications of the protein biuret method displayed different results on how to compare according to academic and practical ways. The quantification method using the Biuret-spectrophotometric practical way shows accuracy by a certain standard curve compared with the original values of references.
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4

Cacuci, Dan Gabriel. "Sensitivity Analysis, Uncertainty Quantification and Predictive Modeling of Nuclear Energy Systems." Energies 15, no. 17 (September 1, 2022): 6379. http://dx.doi.org/10.3390/en15176379.

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The Special Issue “Sensitivity Analysis, Uncertainty Quantification and Predictive Modeling of Nuclear Energy Systems” comprises nine articles that present important applications of concepts for performing sensitivity analyses and uncertainty quantifications of models of nuclear energy systems [...]
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5

Saltelli, Andrea. "Ethics of quantification or quantification of ethics?" Futures 116 (February 2020): 102509. http://dx.doi.org/10.1016/j.futures.2019.102509.

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Du, Zhe, and Sebastian F. Behrens. "Effect of target gene sequence evenness and dominance on real-time PCR quantification of artificial sulfate-reducing microbial communities." PLOS ONE 19, no. 3 (March 7, 2024): e0299930. http://dx.doi.org/10.1371/journal.pone.0299930.

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Quantitative real-time PCR of phylogenetic and functional marker genes is among the most commonly used techniques to quantify the abundance of microbial taxa in environmental samples. However, in most environmental applications, the approach is a rough assessment of population abundance rather than an exact absolute quantification method because of PCR-based estimation biases caused by multiple factors. Previous studies on these technical issues have focused on primer or template sequence features or PCR reaction conditions. However, how target gene sequence characteristics (e.g., evenness and dominance) in environmental samples affect qPCR quantifications has not been well studied. Here, we compared three primer sets targeting the beta subunit of the dissimilatory sulfite reductase (dsrB) to investigate qPCR quantification performance under different target gene sequence evenness and dominance conditions using artificial gBlock template mixtures designed accordingly. Our results suggested that the qPCR quantification performance of all tested primer sets was determined by the comprehensive effect of the target gene sequence evenness and dominance in environmental samples. Generally, highly degenerate primer sets have equivalent or better qPCR quantification results than a more target-specific primer set. Low template concentration in this study (~105 copies/L) will exaggerate the qPCR quantification results difference among tested primer sets. Improvements to the accuracy and reproducibility of qPCR assays for gene copy number quantification in environmental microbiology and microbial ecology studies should be based on prior knowledge of target gene sequence information acquired by metagenomic analysis or other approaches, careful selection of primer sets, and proper reaction conditions optimization.
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7

Ernst, Oliver, Fabio Nobile, Claudia Schillings, and Tim Sullivan. "Uncertainty Quantification." Oberwolfach Reports 16, no. 1 (February 26, 2020): 695–772. http://dx.doi.org/10.4171/owr/2019/12.

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8

Castanié, Francis. "Quantification aléatoire." Annales des Télécommunications 41, no. 5-6 (May 1986): 235–45. http://dx.doi.org/10.1007/bf02998629.

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9

Mikolaj, Jan. "Risks Quantification." Communications - Scientific letters of the University of Zilina 4, no. 4 (December 31, 2002): 5–12. http://dx.doi.org/10.26552/com.c.2002.4.5-12.

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10

Unterberger, A. "Quantification relativiste." Mémoires de la Société mathématique de France 1 (1991): 1–215. http://dx.doi.org/10.24033/msmf.350.

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11

Roberts, Alexander. "Imprecise Quantification." Proceedings of the Aristotelian Society 119, no. 3 (May 11, 2019): 357–67. http://dx.doi.org/10.1093/arisoc/aoz007.

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Abstract Following David Lewis (1986), Ted Sider (2001) has famously argued that unrestricted first-order quantification cannot be vague. His argument was intended as a type of reductio: its strategy was to show that the mere hypothesis of unrestricted quantifier vagueness collapses into the claim that unrestricted quantification is precise. However, this short article considers two natural reconstructions of the argument, and shows that each can be resisted. The theme will be that each reconstruction of the argument involves assumptions which advocates of vague quantification have independent reason to reject.
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12

Murali, P., P. Rodrigo, K. Ranga, M. M., and G. S. "MRI quantification." Neurology 41, no. 6 (June 1, 1991): 954. http://dx.doi.org/10.1212/wnl.41.6.954.

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13

Sun, Wenjie. "Surfactant quantification." Nature Nanotechnology 14, no. 6 (June 2019): 498. http://dx.doi.org/10.1038/s41565-019-0482-2.

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14

Florio, Salvatore. "Unrestricted Quantification." Philosophy Compass 9, no. 7 (July 2014): 441–54. http://dx.doi.org/10.1111/phc3.12127.

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15

Morzycki, Marcin. "Quantification Galore." Linguistic Inquiry 42, no. 4 (October 2011): 671–82. http://dx.doi.org/10.1162/ling_a_00065.

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16

Chang, Li-Na, Shun-Long Luo, and Yuan Sun. "Superposition Quantification." Communications in Theoretical Physics 68, no. 5 (November 2017): 565. http://dx.doi.org/10.1088/0253-6102/68/5/565.

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17

Stepanchenko, N. S., G. V. Novikova, and I. E. Moshkov. "Protein quantification." Russian Journal of Plant Physiology 58, no. 4 (June 19, 2011): 737–42. http://dx.doi.org/10.1134/s1021443711040182.

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18

Dussaix, E. "Quantification virale." Revue Française des Laboratoires 1996, no. 283 (April 1996): 29–32. http://dx.doi.org/10.1016/s0338-9898(96)80179-x.

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19

Rovai, D. "Quantification methods." Annales de Cardiologie et d'Angéiologie 51, no. 4 (September 2002): 221–22. http://dx.doi.org/10.1016/s0003-3928(02)00110-5.

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20

Rubin, J. M. "Flow quantification." European Radiology 9, S3 (November 23, 1999): S368—S371. http://dx.doi.org/10.1007/pl00014076.

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21

Robertson, Alastair, Charles Godavitarne, and Jonathan Peters. "Bone quantification." Orthopaedics and Trauma 31, no. 5 (October 2017): 326–29. http://dx.doi.org/10.1016/j.mporth.2017.07.009.

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22

Winter, Yoad. "Functional Quantification." Research on Language and Computation 2, no. 3 (September 2004): 331–63. http://dx.doi.org/10.1007/s11168-004-0909-1.

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23

Kiselev, Valerij G., Gregor Körzdörfer, and Peter Gall. "Toward Quantification." Investigative Radiology 56, no. 1 (January 2021): 1–9. http://dx.doi.org/10.1097/rli.0000000000000738.

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24

Ravikiran, A. "Wear Quantification." Journal of Tribology 122, no. 3 (December 15, 1999): 650–56. http://dx.doi.org/10.1115/1.555416.

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Tribology literature shows considerable scatter in the wear rate of materials obtained by pin-on-disc type of studies. The general consensus thus far has been that this scatter is due to variations in the material properties and experimental conditions used by different investigators. However, the present paper shows that the scatter can also arise from the way wear is quantified by popular methods such as by m3/m, m3/Nm and so on. Therefore, an improved method of wear quantification indicated as “wear index” (WI) a non-dimensional quantity, has been proposed and it is expected to reduce scatter that arises from the way wear is quantified. Evidence for the improvement has been provided from the results obtained from the experiments reported in this paper as well as those reported by different researchers. Besides reducing scatter, WI is expected to improve correlation in the wear values between laboratory benchmark tests and actual industrial applications, and also that between different investigators. Hence WI is expected to enhance the general understanding on tribology. [S0742-4787(00)01103-6]
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25

Kellerer, A. M. "Risk quantification." Radiation and Environmental Biophysics 42, no. 1 (March 2003): 1–5. http://dx.doi.org/10.1007/s00411-003-0181-z.

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26

Christensen, Ryan. "Propositional Quantification." Russell: The Journal of Bertrand Russell Studies 31, no. 1 (June 2011): 109–20. http://dx.doi.org/10.1353/rss.2011.0013.

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27

Barbieri, Andrea, and Mauro Pepi. "Three-Dimensional Echocardiography Based on Automation and Machine Learning Principles and the Renaissance of Cardiac Morphometry." Journal of Clinical Medicine 11, no. 15 (July 27, 2022): 4357. http://dx.doi.org/10.3390/jcm11154357.

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Today, the core component of all transthoracic echocardiography reports is the quantification of cardiac chamber size and function using advanced echocardiography modalities such as three-dimensional echocardiography (3DE), in line with the rising demand for quantifications of cardiac chambers with high measurement accuracy and reproducibility [...]
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28

Pettinico, George, and George R. Milne. "Living by the numbers: understanding the “quantification effect”." Journal of Consumer Marketing 34, no. 4 (June 12, 2017): 281–91. http://dx.doi.org/10.1108/jcm-06-2016-1839.

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Purpose This paper aims to establish if quantified self-data positively impact motivation in a goal pursuit across a broad cross-section of consumers and in multiple contexts; and to understand the underlying causal mechanism and identify boundary conditions. Design/methodology/approach Exploratory qualitative research helped direct the hypotheses development. Two quantitative experiments were then conducted via MTURK, involving 331 respondents, to test the hypotheses in two different personal goal areas (fitness and carbon footprint reduction). Findings Self-quantification has a significant and positive impact on anticipated motivation in both contexts studied. The mediated model provides insight into the psychological process underlying self-quantification’s motivational impact, which involves strengthening user perceptions regarding feedback meaningfulness, self-empowerment and goal focus. Age (>50) was found to be a boundary condition; however, distance to goal was not. Research limitations/implications This paper focuses on initial (anticipated) motivation, which is the vital first step in behavior change. However, more work is needed to understand quantification’s long-term impact over the course of a behavior change process. Practical implications This research encourages firms to incorporate self-quantification features into products/services aimed at behavior change and helps firms better understand consumer-perceived benefits. It alerts firms regarding the extra effort needed to convince older consumers of these benefits. Originality/value This is the first study to confirm the “quantification effect” on motivation in multiple life areas and provide a causal model to explain how it works. It is also the first to highlight age as a boundary condition.
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29

Soneson, Charlotte, Avi Srivastava, Rob Patro, and Michael B. Stadler. "Preprocessing choices affect RNA velocity results for droplet scRNA-seq data." PLOS Computational Biology 17, no. 1 (January 11, 2021): e1008585. http://dx.doi.org/10.1371/journal.pcbi.1008585.

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Experimental single-cell approaches are becoming widely used for many purposes, including investigation of the dynamic behaviour of developing biological systems. Consequently, a large number of computational methods for extracting dynamic information from such data have been developed. One example is RNA velocity analysis, in which spliced and unspliced RNA abundances are jointly modeled in order to infer a ‘direction of change’ and thereby a future state for each cell in the gene expression space. Naturally, the accuracy and interpretability of the inferred RNA velocities depend crucially on the correctness of the estimated abundances. Here, we systematically compare five widely used quantification tools, in total yielding thirteen different quantification approaches, in terms of their estimates of spliced and unspliced RNA abundances in five experimental droplet scRNA-seq data sets. We show that there are substantial differences between the quantifications obtained from different tools, and identify typical genes for which such discrepancies are observed. We further show that these abundance differences propagate to the downstream analysis, and can have a large effect on estimated velocities as well as the biological interpretation. Our results highlight that abundance quantification is a crucial aspect of the RNA velocity analysis workflow, and that both the definition of the genomic features of interest and the quantification algorithm itself require careful consideration.
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30

Halsall, Karen M., Vanessa M. Ellingsen, Johan Asplund, Richard HW Bradshaw, and Mikael Ohlson. "Fossil charcoal quantification using manual and image analysis approaches." Holocene 28, no. 8 (May 14, 2018): 1345–53. http://dx.doi.org/10.1177/0959683618771488.

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Charcoal particles are evidence of past fire events and macro-charcoal particles have been shown to represent local fire events. There are several methods for the preparation and quantification of macro-charcoal particles, none of which have been universally accepted as standard. Very few studies compare methodological differences and no studies to date compare quantification by mass with quantification by volume using image analysis. Using three cores taken from a peatland located in SE Norway, we compare these two established methods using a generalized linear mixed model (GLMM) and a split-plot ANOVA test. We show that charcoal volume (image analysis method) was a better predictor of charcoal mass than charcoal particle number and the same size classes of charcoal as size class distributions were not spatially and temporally correlated. Although there is still a need for a common and unifying method, our results show that quantification of charcoal particles by image analysis including size (e.g. height in mm) and area (mm2)/volume (mm3) measurements provides more significant results in cross-site or multiple-site studies than quantifications based on particle number. This has implications for the interpretation of charcoal data from regional studies that are used to model drivers of wildfire activity and environmental change in boreal–temperate landscapes during the Holocene.
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Hayward, Kristen M., Michelle P. Harwood, Stephen C. Lougheed, Zhengxin Sun, Peter Van Coeverden de Groot, and Evelyn L. Jensen. "A real-time PCR assay to accurately quantify polar bear DNA in fecal extracts." PeerJ 8 (April 7, 2020): e8884. http://dx.doi.org/10.7717/peerj.8884.

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DNA extracted from fecal samples contains DNA from the focal species, food, bacteria and pathogens. Most DNA quantification methods measure total DNA and cannot differentiate among sources. Despite the desirability of noninvasive fecal sampling for studying wildlife populations, low amounts of focal species DNA make it difficult to use for next-generation sequencing (NGS), where accurate DNA quantification is critical for normalization. Two factors are required prior to using fecal samples in NGS libraries: (1) an accurate quantification method for the amount of target DNA and (2) a determination of the relative amount of target DNA needed for successful single nucleotide polymorphism genotyping assays. Here, we address these needs by developing primers to amplify a 101 bp region of the nuclear F2 gene and a quantitative PCR (qPCR) assay that allows the accurate quantification of the amount of polar bear (Ursus maritimus) DNA in fecal extracts. We test the assay on pure polar bear DNA extracted from muscle tissue and find a high correlation between fluorometric and qPCR quantifications. The qPCR assay was also successfully used to quantify the amount of DNA derived from polar bears in fecal extractions. Orthologs of the F2 gene have been identified across vertebrates; thus, similar qPCR assays could be developed for other species to enable noninvasive studies.
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32

Yu, Hsiang-Ping, Yi-Ling Hsiao, Hung-Yin Pan, Chih-Hung Huang, and Shao-Yi Hou. "Micro-RNA quantification using DNA polymerase and pyrophosphate quantification." Analytical Biochemistry 419, no. 2 (December 2011): 228–33. http://dx.doi.org/10.1016/j.ab.2011.08.033.

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33

Verbeeck, Jo, and Giovanni Bertoni. "Model-based quantification of EELS: is standardless quantification possible?" Microchimica Acta 161, no. 3-4 (February 25, 2008): 439–43. http://dx.doi.org/10.1007/s00604-008-0948-7.

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34

FAGARAS, SIMONA-PIA. "Quantification the motivation level of the athletes." New Trends and Issues Proceedings on Humanities and Social Sciences 3, no. 1 (June 28, 2017): 560–63. http://dx.doi.org/10.18844/gjhss.v3i1.1820.

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35

Ebert, C., and S. Hinterwimmer. "Quantificational Variability Effects with Plural Definites: Quantification over Individuals or Situations?" Journal of Semantics 27, no. 2 (March 1, 2010): 139–76. http://dx.doi.org/10.1093/jos/ffq003.

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Vilasó Cadre, Javier Ernesto, Daniel Benítez Fernández, Héctor Rodríguez de la Rosa, and María de los Ángeles Arada Pérez. "Voltammetric method for chemical oxygen demand in a dairy wastewater using homemade minimal instrumentation." Afinidad. Journal of Chemical Engineering Theoretical and Applied Chemistry 80, no. 598 (March 30, 2023): 3–7. http://dx.doi.org/10.55815/413408.

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This paper presents a voltammetric method for Chemical Oxygen Demand (COD) quantification in a dairy wastewater using homemade minimal electrochemical instrumentation. The working electrode was a carbon microdisc, the auxiliary electrode was a carbon rod, and a silver electrode was used as reference. A low-cost non-commercial potentiostat was employed. The linear working range was 1-20 g/L. Repeatability was evaluated on 10 sample quantifications, the coefficient of variation was 3.6%, lower than that obtained for the reference spectrophotometric method (8.2%). The voltammetric method did not require treatment of the sample. The trueness was evaluated by comparing the voltammetric results with the spectrophotometric method. Mean COD of 10 quantifications using low-cost voltammetry was 10.2 g/L, whereas for the spectrophotometric method it was 11.0 g/L. A Paired Sample t-Test did not show statistically significant differences between both. Detection limit was 0.6 g/L, and quantification limit was 1.8 g/L. Both are acceptable for the sample in which there is a high organic content.
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Alexeyenko, Sascha. "The semantics of habituality as an argument for event-mediated quantification." Semantics and Linguistic Theory 28 (December 21, 2018): 768. http://dx.doi.org/10.3765/salt.v28i0.4441.

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The goals of this paper are two-fold. On the one hand, it has as its aim an analysis of the semantics of habituality in the framework of event semantics. In particular, it will be argued that a proper treatment of habituality must minimally meet the following desiderata: (a) allow a unified analysis of the habitual and the progressive as different subtypes of the imperfective, (b) work both for bare habituals and for habituals that contain certain kinds of quantificational elements, and (c) be able to model the scope behavior of indefinites in habituals of both types. Based on various existing proposals, an analysis along these lines will be put forward and formalized. On the other hand, the paper also seeks to show that a habitual semantics that meets these desiderata cannot be implemented in combination with a classical GQ analysis of quantificational DPs, but follows without any additional stipulations if an event-based approach to quantification is adopted. Thus, habituals provide a further argument in favor of modeling distributive quantification with the mediation of events.
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Döbelin, Nicola. "Validation of XRD phase quantification using semi-synthetic data." Powder Diffraction 35, no. 4 (October 13, 2020): 262–75. http://dx.doi.org/10.1017/s0885715620000573.

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Validating phase quantification procedures of powder X-ray diffraction (XRD) data for an implementation in an ISO/IEC 17025 accredited environment has been challenging due to a general lack of suitable certified reference materials. The preparation of highly pure and crystalline reference materials and mixtures thereof may exceed the costs for a profitable and justifiable implementation. This study presents a method for the validation of XRD phase quantifications based on semi-synthetic datasets that reduces the effort for a full method validation drastically. Datasets of nearly pure reference substances are stripped of impurity signals and rescaled to 100% crystallinity, thus eliminating the need for the preparation of ultra-pure and -crystalline materials. The processed datasets are then combined numerically while preserving all sample- and instrument-characteristic features of the peak profile, thereby creating multi-phase diffraction patterns of precisely known composition. The number of compositions and repetitions is only limited by computational power and storage capacity. These datasets can be used as input files for the phase quantification procedure, in which statistical validation parameters such as precision, accuracy, linearity, and limits of detection and quantification can be determined from a statistically sound number of datasets and compositions.
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Feghoul, Linda, Maud Salmona, Janine Cherot, Mony Fahd, Jean-Hugues Dalle, Carole Vachon, Aurélie Perrod, et al. "Evaluation of a New Device for Simplifying and Standardizing Stool Sample Preparation for Viral Molecular Testing with Limited Hands-On Time." Journal of Clinical Microbiology 54, no. 4 (January 13, 2016): 928–33. http://dx.doi.org/10.1128/jcm.02816-15.

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Sensitive molecular assays have greatly improved the diagnosis of viral gastroenteritis. However, the proper preparation of stool samples for clinical testing remains an issue. bioMérieux has developed a stool preprocessing device (SPD) that includes a spoon for calibrated sampling and a vial containing buffer, glass beads, and two filters. The resulting stool filtrate is used for nucleic acid extraction. The purpose of this study was to evaluate the performance of the SPD for the quantification of human adenovirus (HAdV) DNA in stool samples collected from hematopoietic stem cell transplant (HSCT) recipients. HAdV DNA was quantified with the Adenovirus R-gene kit. The suitability of the device to reproducibly quantify HAdV DNA in stools using different extraction platforms (easyMAG and QIAsymphony) was determined using archived HAdV-positive stool samples. Coefficients of variation of HAdV DNA quantifications ranged from 1.79% to 1.83%, and no difference in quantification was observed between the two extraction systems. The HAdV DNA limit of quantification using the SPD was 3.75 log10copies/g of stool. HAdV DNA quantification using the SPD was then compared to that of the routine preprocessing technique on 75 fresh stool samples collected prospectively from pediatric HSCT recipients at risk for HAdV infections. Thirty-eight samples were HAdV DNA positive with both the SPD and routine preprocessing methods. HAdV DNA loads were on average 1.14-log10copies/g of stool higher with the SPD (P< 0.0001) than with routine methods. This new device enabled a standardized preparation of stool samples in <5 min and a reproducible and sensitive quantification of HAdV DNA. The use of the SPD for the detection of other gastrointestinal infections warrants further evaluation.
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40

Denney, Dennis. "Depth-Accuracy Quantification." Journal of Petroleum Technology 58, no. 05 (May 1, 2006): 49–50. http://dx.doi.org/10.2118/0506-0049-jpt.

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41

Molczanow, Aleksy. "Quantification and Inference." Monist 85, no. 4 (2002): 535–54. http://dx.doi.org/10.5840/monist200285431.

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Malago, Roberto, Mirko D'Onofrio, Marco Ferdeghini, William Mantovani, Chiara Colato, Paolo Brazzarola, Massimiliano Motton, and Roberto Pozzi Mucelli. "Thyroid Volumetric Quantification." Journal of Ultrasound in Medicine 27, no. 12 (December 2008): 1727–33. http://dx.doi.org/10.7863/jum.2008.27.12.1727.

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43

Lawson, Brendan T. "Quantification and Humanitarianism." Journal of Humanitarian Affairs 3, no. 1 (January 1, 2021): 53–60. http://dx.doi.org/10.7227/jha.059.

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Over the past 25 years, the humanitarian sector has become increasingly dominated by numbers. This has been reflected in the growth of academic work that explores this relationship between humanitarianism and quantification. The most recent contribution to this literature is Joël Glasman’s Humanitarianism and the Quantification of Humanitarian Needs. Through his empirical and theoretical contributions, Glasman draws our attention to the different ways that academics approach this topic. These four strands structure the literature review: knowledge – the technical difficulties in quantifying phenomena; governance – how numbers help humanitarian organisations manage the sector; effects – the impact that quantification has had on the sector as a whole; meaning – the importance of rhetoric, discourse, representation and communication when it comes to understanding the quantitative. As part of the review, the essay also identifies how academics can better engage with each of the four strands.
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44

Picinbono, Bernard, and Patrick Duvaut. "Quantification et détection." Annales des Télécommunications 41, no. 5-6 (May 1986): 246–51. http://dx.doi.org/10.1007/bf02998630.

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Venkatesh, Sudhakar K., and Michael S. Torbenson. "Liver fibrosis quantification." Abdominal Radiology 47, no. 3 (January 12, 2022): 1032–52. http://dx.doi.org/10.1007/s00261-021-03396-y.

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46

Rescher, Nicholas. "Plurality Quantification Revisited." Philosophical Inquiry 26, no. 1 (2004): 1–6. http://dx.doi.org/10.5840/philinquiry2004261/21.

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47

Clark, William R. "Quantification of Dialysis." Seminars in Dialysis 14, no. 4 (July 2001): 237. http://dx.doi.org/10.1046/j.1525-139x.2001.00062.x.

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48

Bonevac, Daniel. "Quantity and Quantification." Noûs 19, no. 2 (June 1985): 229. http://dx.doi.org/10.2307/2214931.

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49

Jarchum, Irene. "Proteome quantification compared." Nature Methods 13, no. 12 (November 29, 2016): 972. http://dx.doi.org/10.1038/nmeth.4096.

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Alexander, I. "'If' and quantification." Analysis 45, no. 4 (October 1, 1985): 186–90. http://dx.doi.org/10.1093/analys/45.4.186.

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