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Journal articles on the topic 'Spatial Sorting'

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Published: 20 February 2023

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1

Eeckhout, Jan, Roberto Pinheiro, and Kurt Schmidheiny. "Spatial Sorting." Journal of Political Economy 122, no. 3 (June 2014): 554–620. http://dx.doi.org/10.1086/676141.

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2

Amos, Martyn, and Oliver Don. "Swarm‐based spatial sorting." International Journal of Intelligent Computing and Cybernetics 1, no. 3 (August 22, 2008): 454–73. http://dx.doi.org/10.1108/17563780810893491.

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3

Lee, M. S. Y. "Macroevolutionary consequences of "spatial sorting"." Proceedings of the National Academy of Sciences 108, no. 31 (June 28, 2011): E347. http://dx.doi.org/10.1073/pnas.1105702108.

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4

Combes, Pierre-Philippe, Gilles Duranton, and Laurent Gobillon. "Spatial wage disparities: Sorting matters!" Journal of Urban Economics 63, no. 2 (March 2008): 723–42. http://dx.doi.org/10.1016/j.jue.2007.04.004.

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5

Phillips, Ben L., and T. Alex Perkins. "Spatial sorting as the spatial analogue of natural selection." Theoretical Ecology 12, no. 2 (March 4, 2019): 155–63. http://dx.doi.org/10.1007/s12080-019-0412-9.

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6

Karavidas, Dionysios. "Firms' Spatial Sorting and Market Access." International Economic Journal 33, no. 4 (October 2, 2019): 573–84. http://dx.doi.org/10.1080/10168737.2019.1677741.

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7

Fajgelbaum, Pablo D., and Cecile Gaubert. "Optimal Spatial Policies, Geography, and Sorting*." Quarterly Journal of Economics 135, no. 2 (January 6, 2020): 959–1036. http://dx.doi.org/10.1093/qje/qjaa001.

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Abstract We study optimal spatial policies in a quantitative trade and geography framework with spillovers and spatial sorting of heterogeneous workers. We characterize the spatial transfers that must hold in efficient allocations, as well as labor subsidies that can implement them. There exists scope for welfare-enhancing spatial policies even when spillovers are common across locations. Using data on U.S. cities and existing estimates of the spillover elasticities, we find that the U.S. economy would benefit from a reallocation of workers to currently low-wage cities. The optimal allocation features a greater share of high-skill workers in smaller cities relative to the observed allocation. Inefficient sorting may lead to substantial welfare costs.
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8

Bailey, Nick. "How Spatial Segregation Changes over Time: Sorting Out the Sorting Processes." Environment and Planning A: Economy and Space 44, no. 3 (March 2012): 705–22. http://dx.doi.org/10.1068/a44330.

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9

SAMET, HANAN. "A Sorting Approach to Indexing Spatial Data." International Journal of Shape Modeling 14, no. 01 (June 2008): 15–37. http://dx.doi.org/10.1142/s021865430800104x.

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10

Modai-Snir, Tal, and Pnina Plaut. "The analysis of residential sorting trends: Measuring disparities in socio-spatial mobility." Urban Studies 56, no. 2 (November 27, 2018): 288–300. http://dx.doi.org/10.1177/0042098018798759.

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Ethnic and socioeconomic segregation levels vary over time and so do the spatial levels of these segregations. Although a large body of research has focused on how residential mobility patterns produce segregation, little is known about how changing mobility patterns translate into temporal and scale variations in sorting. This article develops a methodological framework designed to explore how changing mobility patterns reflect such trends. It introduces a measure of sorting that reflects the extent of disparities among groups in their socio-spatial mobility. Trends in the direction and the extent of sorting can be exposed by computing sorting measures over consecutive periods. The measure is broken down to capture the relative contributions of residential mobility to sorting at hierarchically nested geographical units, for example cities and their constituent neighbourhoods. An empirical demonstration shows that changes in residential mobility patterns affect the magnitude and spatial level of residential sorting, which vary even over the short term.
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11

Fretz, Stephan, Raphaël Parchet, and Frédéric Robert-Nicoud. "Erratum to Highways, Market Access and Spatial Sorting." Economic Journal 132, no. 643 (February 25, 2022): 1233. http://dx.doi.org/10.1093/ej/ueab100.

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12

Forslid, Rikard, and Toshihiro Okubo. "Spatial sorting with heterogeneous firms and heterogeneous sectors." Regional Science and Urban Economics 46 (May 2014): 42–56. http://dx.doi.org/10.1016/j.regsciurbeco.2014.02.005.

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13

Lowe, Winsor H., Clint C. Muhlfeld, and Fred W. Allendorf. "Spatial sorting promotes the spread of maladaptive hybridization." Trends in Ecology & Evolution 30, no. 8 (August 2015): 456–62. http://dx.doi.org/10.1016/j.tree.2015.05.008.

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14

Ben-Moshe, Shani, Yonatan Shapira, Andreas E. Moor, Rita Manco, Tamar Veg, Keren Bahar Halpern, and Shalev Itzkovitz. "Spatial sorting enables comprehensive characterization of liver zonation." Nature Metabolism 1, no. 9 (September 2019): 899–911. http://dx.doi.org/10.1038/s42255-019-0109-9.

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15

Matano, A., and P. Naticchioni. "Wage distribution and the spatial sorting of workers." Journal of Economic Geography 12, no. 2 (June 30, 2011): 379–408. http://dx.doi.org/10.1093/jeg/lbr013.

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16

Rodriguez-Viciana, Pablo, and Frank McCormick. "Ras ubiquitination: Coupling spatial sorting and signal transmission." Cancer Cell 9, no. 4 (April 2006): 243–44. http://dx.doi.org/10.1016/j.ccr.2006.03.025.

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17

COUZIN, IAIN D., JENS KRAUSE, RICHARD JAMES, GRAEME D. RUXTON, and NIGEL R. FRANKS. "Collective Memory and Spatial Sorting in Animal Groups." Journal of Theoretical Biology 218, no. 1 (September 2002): 1–11. http://dx.doi.org/10.1006/jtbi.2002.3065.

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18

Barndorff-Nielsen, O. E. "Sorting, texture and structure." Proceedings of the Royal Society of Edinburgh. Section B. Biological Sciences 96 (1989): 167–79. http://dx.doi.org/10.1017/s0269727000010915.

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SynopsisSands are sorted by the actions of air and water. A mathematical–physical model for the ensuing spatial and temporal variations in the size distributions of the sand grains is outlined. A crucial element in aeolian sorting and transport of sand is the process that takes place when a saltating grain impinges on the sand surface. This raises the problem of describing the texture of sand surfaces. Some initial empirical and mathematical findings concerning this problem are discussed. A closely connected question is that of how the grains in a sand deposit are packed and how this relates to the size distribution. Voronoi tesselations in combination with random point processes seem to offer one useful approach to the question.
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19

Yeşilırmak, Muharrem. "Bonus pay for teachers, spatial sorting, and student achievement." European Journal of Political Economy 59 (September 2019): 129–58. http://dx.doi.org/10.1016/j.ejpoleco.2019.02.004.

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20

Mion, Giordano, and Paolo Naticchioni. "The spatial sorting and matching of skills and firms." Canadian Journal of Economics/Revue canadienne d'économique 42, no. 1 (January 28, 2009): 28–55. http://dx.doi.org/10.1111/j.1540-5982.2008.01498.x.

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21

Yu, Jianhong, Weijie Miao, Guangben Zhang, Kai Li, Yinggang Shi, and Li Liu. "Target Positioning and Sorting Strategy of Fruit Sorting Robot Based on Image Processing." Traitement du Signal 38, no. 3 (June 30, 2021): 797–805. http://dx.doi.org/10.18280/ts.380326.

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To a certain extent, automated fruit sorting systems reflect the degree of automated production in modern food industry, and boast a certain theoretical and application value. The previous studies mostly concentrate on the design of robot structure, and the control of robot motions. There is little report on the feature extraction of fruits in specific applications of fruit sorting. For this reason, this paper explores the target positioning and sorting strategy of fruit sorting robot based on image processing. Firstly, the authors constructed a visual sorting system for fruit sorting robot, and explained the way to recognize objects in three-dimensional (3D) scene and to reconstruct the spatial model based on sorting robot. Next, the maturity of the identified fruits was considered the prerequisite of dynamic sorting of fruit sorting robot. Finally, the program flow of the fruit sorting robot was given. The effectiveness of our strategy was verified through experiments.
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22

Powell, D. Mark. "Patterns and processes of sediment sorting in gravel-bed rivers." Progress in Physical Geography: Earth and Environment 22, no. 1 (March 1998): 1–32. http://dx.doi.org/10.1177/030913339802200101.

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Sedimentological studies of coarse-grained alluvial rivers reveal patterns of bed material sorting at a variety of spatial scales ranging from downstream fining over the length of the long profile to the vertical segregation of a coarse surface layer at the scale of individual particles. This article reviews the mechanisms that sort bed material by size during sediment entrainment, transport and deposition and discusses some of the inter-relationships that exist between patterns and processes of sediment sorting at different spatial and temporal scales. At initiation of motion, sorting can arise from the preferential entrainment of the finer fractions from the heterogeneous bed sediments. Bedload grain-size distributions are modified during transport as different size fractions are routed along different transport pathways under the influence of nonuniform bed topography and associated flow patterns, and during deposition as the variable pocket geometry of the rough bed surface and turbulence intensity of the flow control the size of the particles that deposit. The review highlights the poor understanding of the many feedback linkages that exist between patterns and processes of sediment sorting at different scales and the need for a greater awareness of the spatial and temporal bounds of these linkages.
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23

Li, Chen, and Jie Liu. "An algorithm for 4D CT image sorting using spatial continuity." Journal of X-Ray Science and Technology 21, no. 3 (2013): 323–33. http://dx.doi.org/10.3233/xst-130381.

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24

Shine, R., G. P. Brown, and B. L. Phillips. "Reply to Lee: Spatial sorting, assortative mating, and natural selection." Proceedings of the National Academy of Sciences 108, no. 31 (June 28, 2011): E348. http://dx.doi.org/10.1073/pnas.1108240108.

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25

Ben-Moshe, S., K. Bahar Halpern, and S. Itzkovitz. "Spatial sorting of hepatocytes reveals broad zonation of liver proteome." Journal of Hepatology 68 (April 2018): S53. http://dx.doi.org/10.1016/s0168-8278(18)30327-1.

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26

Malheiros, Marcelo de Gomensoro, and Marcelo Walter. "Spatial sorting: An efficient strategy for approximate nearest neighbor searching." Computers & Graphics 57 (June 2016): 112–26. http://dx.doi.org/10.1016/j.cag.2016.03.006.

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27

Baldwin, Richard E., and Toshihiro Okubo. "Heterogeneous firms, agglomeration and economic geography: spatial selection and sorting." Journal of Economic Geography 6, no. 3 (November 10, 2005): 323–46. http://dx.doi.org/10.1093/jeg/lbi020.

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28

Han, Song, Xiaoping Liu, and Gang Wang. "Visual Sorting Method Based on Multi-Modal Information Fusion." Applied Sciences 12, no. 6 (March 14, 2022): 2946. http://dx.doi.org/10.3390/app12062946.

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Visual sorting of stacked parcels is a key issue in intelligent logistics sorting systems. In order to improve the sorting success rate of express parcels and effectively obtain the sorting order of express parcels, a visual sorting method based on multi-modal information fusion (VS-MF) is proposed in this paper. Firstly, an object detection network based on multi-modal information fusion (OD-MF) is proposed. The global gradient feature is extracted from depth information as a self-attention module. More spatial features are learned by the network, and the detection accuracy is improved significantly. Secondly, a multi-modal segmentation network based on Swin Transformer (MS-ST) is proposed to detect the optimal sorting positions and poses of parcels. More fine-grained information of the sorting parcels and the relationships between them are gained by adding Swin Transformer models. Frequency domain information and depth information are used as supervision signals to obtain the pickable areas and infer the occlusion degrees of parcels. A strategy for the optimal sorting order is also proposed to ensure the stability of the system. Finally, a sorting system with a 6-DOF robot is constructed to complete the sorting task of stacked parcels. The accuracy and stability the system are verified by sorting experiments.
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29

Hunt, Sylvie D., and David J. Stephens. "The role of motor proteins in endosomal sorting." Biochemical Society Transactions 39, no. 5 (September 21, 2011): 1179–84. http://dx.doi.org/10.1042/bst0391179.

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Microtubule motor proteins play key roles in the spatial organization of intracellular organelles as well as the transfer of material between them. This is well illustrated both by the vectorial transfer of biosynthetic cargo from the endoplasmic reticulum to the Golgi apparatus as well as the sorting of secretory and endocytic cargo in the endosomal system. Roles have been described for dynein and kinesin motors in each of these steps. Cytoplasmic dynein is a highly complex motor comprising multiple subunits that provide functional specialization. The family of human kinesins includes over 40 members. This complexity provides immense functional diversity, yet little is known of the specific requirements and functions of individual motors during discrete membrane trafficking steps. In the present paper, we describe some of the latest findings in this area that seek to define the mechanisms of recruitment and control of activity of microtubule motors in spatial organization and cargo trafficking through the endosomal network.
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30

LANZONI, STEFANO, and MARCO TUBINO. "Grain sorting and bar instability." Journal of Fluid Mechanics 393 (August 25, 1999): 149–74. http://dx.doi.org/10.1017/s0022112099005583.

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A two-dimensional model of flow and bed topography is proposed to investigate the effect of sediment heterogeneity on the development of alternate bars. Within the context of a linear stability theory the flow field, the bed topography and the grain size distribution function are perturbed leading to an integro-differential linear eigenvalue problem. It is shown that the selective transport of different grain size fractions and the resulting spatial pattern of sorting may appreciably affect the balance between stabilizing and destabilizing actions which govern bar instability. Theoretical results suggest that sediment heterogeneity leads to a damping of both growth rate and migration speed of bars, while bar wavelength is shortened with respect to the case of uniform sediment. The above findings conform, at least qualitatively, to the experimentally detected reduction of bar height, length and celerity. The observed tendency of coarser particles to pile up towards bar crests is also reproduced by theoretical results.
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31

Kleinhans, Maarten G. "Sorting out river channel patterns." Progress in Physical Geography: Earth and Environment 34, no. 3 (June 2010): 287–326. http://dx.doi.org/10.1177/0309133310365300.

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Rivers self-organize their pattern/planform through feedbacks between bars, channels, floodplain and vegetation, which emerge as a result of the basic spatial sorting process of wash load sediment and bed sediment. The balance between floodplain formation and destruction determines the width and pattern of channels. Floodplain structure affects the style and rate of channel avulsion once aggradation takes place. Downstream fining of bed sediment and the sediment balance of fines in the pores of the bed sediment provide the ‘template’ or sediment boundary conditions, from which sorting at smaller scales leads to the formation of distinct channel patterns. Bar patterns provide the template of bank erosion and formation as well as the dynamics of the channel network through bifurcation destabilization. However, so far we have been unable to obtain dynamic meandering in laboratory experiments and in physics-based models that can also produce braiding, which reflects our lack of understanding of what causes the different river patterns.
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32

Davies, Brian A., Ishara F. Azmi, and David J. Katzmann. "Regulation of Vps4 ATPase activity by ESCRT-III." Biochemical Society Transactions 37, no. 1 (January 20, 2009): 143–45. http://dx.doi.org/10.1042/bst0370143.

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MVB (multivesicular body) formation occurs when the limiting membrane of an endosome invaginates into the intraluminal space and buds into the lumen, bringing with it a subset of transmembrane cargoes. Exvagination of the endosomal membrane from the cytosol is topologically similar to the budding of retroviral particles and cytokinesis, wherein membranes bud away from the cytoplasm, and the machinery responsible for MVB sorting has been implicated in these phenomena. The AAA (ATPase associated with various cellular activities) Vps4 (vacuolar protein sorting 4) performs a critical function in the MVB sorting pathway. Vps4 appears to dissociate the ESCRTs (endosomal sorting complexes required for transport) from endosomal membranes during the course of MVB sorting, but it is unclear how Vps4 ATPase activity is synchronized with ESCRT release. We have investigated the mechanisms by which ESCRT components stimulate the ATPase activity of Vps4. These studies support a model wherein Vps4 activity is subject to spatial and temporal regulation via distinct mechanisms during MVB sorting.
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33

Kumar, Upkar, Sreenath Bolisetty, Raffaele Mezzenga, Christian Girard, Erik Dujardin, and Aurélien Cuche. "Single plasmon spatial and spectral sorting on a crystalline two-dimensional plasmonic platform." Nanoscale 12, no. 25 (2020): 13414–20. http://dx.doi.org/10.1039/d0nr02066d.

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34

Chen, Si, Likang Zhou, Zhihang An, Huiwen He, Meng Ma, Yanqin Shi, and Xu Wang. "Driving force balance—the “identity card” of supramolecules in a self-sorting multicomponent assembly system." Soft Matter 17, no. 1 (2021): 153–59. http://dx.doi.org/10.1039/d0sm01405b.

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35

Chung, Su-Yeul, and Lawrence A. Brown. "Racial/Ethnic Residential Sorting in Spatial Context: Testing the Explanatory Frameworks1." Urban Geography 28, no. 4 (June 2007): 312–39. http://dx.doi.org/10.2747/0272-3638.28.4.312.

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36

Comerford, Mattheau, and Scott P. Egan. "The potential role of spatial sorting in speciation and adaptive radiations." Population Ecology 64, no. 2 (January 6, 2022): 119–26. http://dx.doi.org/10.1002/1438-390x.12108.

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37

Schaffer, Laszlo, Zoltan Nagy, Zoltan Kincses, Richard Fiath, and Istvan Ulbert. "Spatial Information Based OSort for Real-Time Spike Sorting Using FPGA." IEEE Transactions on Biomedical Engineering 68, no. 1 (January 2021): 99–108. http://dx.doi.org/10.1109/tbme.2020.2996281.

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38

Clark, William A. V. "Who Moves Into what Kinds of Neighbourhoods: Spatial Sorting and Integration." Tijdschrift voor economische en sociale geografie 110, no. 3 (April 4, 2017): 303–18. http://dx.doi.org/10.1111/tesg.12264.

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39

Sontag, Emily, Jian-Hua Chen, Gerry McDermott, Dan Gestaut, Carolyn Larabell, and Judith Frydman. "Sorting Out the JUNQ: the Spatial Nature of Protein Quality Control." Microscopy and Microanalysis 23, S1 (July 2017): 994–95. http://dx.doi.org/10.1017/s1431927617005633.

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40

Tabalin, S. E. "Matched spatial filtering method for the sorting of optical fiber billets." Measurement Techniques 34, no. 6 (June 1991): 534–37. http://dx.doi.org/10.1007/bf00978757.

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41

Schindler, Mirjam, Marion Le Texier, and Geoffrey Caruso. "Spatial sorting, attitudes and the use of green space in Brussels." Urban Forestry & Urban Greening 31 (April 2018): 169–84. http://dx.doi.org/10.1016/j.ufug.2018.02.009.

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42

Livingston, George, Kayoko Fukumori, Diogo B. Provete, Masanobu Kawachi, Noriko Takamura, and Mathew A. Leibold. "Predators regulate prey species sorting and spatial distribution in microbial landscapes." Journal of Animal Ecology 86, no. 3 (February 22, 2017): 501–10. http://dx.doi.org/10.1111/1365-2656.12639.

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43

Berthouly-Salazar, Cécile, Berndt J. van Rensburg, Johannes J. Le Roux, Bettine J. van Vuuren, and Cang Hui. "Spatial Sorting Drives Morphological Variation in the Invasive Bird, Acridotheris tristis." PLoS ONE 7, no. 5 (May 31, 2012): e38145. http://dx.doi.org/10.1371/journal.pone.0038145.

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44

Schmutz, Benoît. "Spatial sorting of African Immigrants in the French Public Housing Market." Review of Black Political Economy 42, no. 3 (January 2015): 247–70. http://dx.doi.org/10.1007/s12114-014-9205-y.

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45

Widmer, Sarah, and Francisco Klauser. "Foams of togetherness in the digital age: Sloterdijk, software sorting and Foursquare." Geographica Helvetica 75, no. 3 (September 4, 2020): 259–69. http://dx.doi.org/10.5194/gh-75-259-2020.

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Abstract. The article brings together Peter Sloterdijk's theory of spheres and literatures on the socio-spatial implications of the functioning of software. By examining the growing personalization of search results for recreational places on spatial media like Foursquare, we make the case for Sloterdijk's conceptualization of “foam” offering an interesting contribution to the analysis and critique of contemporary algorithmic life, in particular with regard to the liquidity and fragility of the forms of togetherness in “co-isolation” created by such applications. In emphasizing the impermanence and ambiguities of these fleeting mediations, the article also points to the politics of these algorithmic foams, whose logics of categorization and socio-spatial sorting become increasingly difficult to understand, politically address or challenge.
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46

Diamond, Rebecca. "The Determinants and Welfare Implications of US Workers' Diverging Location Choices by Skill: 1980–2000." American Economic Review 106, no. 3 (March 1, 2016): 479–524. http://dx.doi.org/10.1257/aer.20131706.

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From 1980 to 2000, the rise in the US college/high school graduate wage gap coincided with increased geographic sorting as college graduates concentrated in high wage, high rent cities. This paper estimates a structural spatial equilibrium model to determine causes and welfare consequences of this increased skill sorting. While local labor demand changes fundamentally caused the increased skill sorting, it was further fueled by endogenous increases in amenities within higher skill cities. Changes in cities' wages, rents, and endogenous amenities increased inequality between high school and college graduates by more than suggested by the increase in the college wage gap alone. (JEL D31, I26, J24, J31, J61, R23)
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47

Xue, Jie, Jia Qiang Lei, Sheng Yu Li, Cui Wang, Jie Zhou, and Dong Lei Mao. "Variability of Grain Size of Surface Sand on Nebkhas at the Southern Fringe of the Taklimakan Desert, China." Advanced Materials Research 1092-1093 (March 2015): 1275–82. http://dx.doi.org/10.4028/www.scientific.net/amr.1092-1093.1275.

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Nebkha plays a major role in the ecological and environmental stabilization by accumulating wind-blown sediments around shrubs. Grain-size characteristics of different positions on nebkha reflect the sorting effect of aeolian dynamics. Based on the collected sand grains of different positions on four types of nebkhas at the southern fringe of Taklimakan Desert, China, this paper provided detailed insight into variability of the grain size of surface sand on nebkhas. The results showed that: a) Grain-size distributions on shield-shaped Karelinia caspica Nebkhas under natural condition had the larger spatial variability in comparison with the others. b) Grain size on nebkhas regularly showed the spatial variation. Grain size was increasingly larger along the windward slope upward, and then became finer along the leeward slope downward. c) The grain-size sortings of different positions on shield-shaped Alhagi sparsifolia Nebkhas under new reclaimed land were the best.
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48

Singh, Satinderjit. "An Alternate Algorithm for (3x3) Median Filtering of Digital Images." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 1 (February 2, 2012): 7–9. http://dx.doi.org/10.24297/ijct.v1i1.6732.

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Median filtering is a commonly used technique in image processing. The main problem of the median filter is its high computational cost (for sorting N pixels, the temporal complexity is O(N·log N), even with the most efficient sorting algorithms). When the median filter must be carried out in real time, the software implementation in general-purpose processorsdoes not usually give good results. This Paper presents an efficient algorithm for median filtering with a 3x3 filter kernel with only about 9 comparisons per pixel using spatial coherence between neighboring filter computations. The basic algorithm calculates two medians in one step and reuses sorted slices of three vertical neighboring pixels. An extension of this algorithm for 2D spatial coherence is also examined, which calculates four medians per step.
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49

Klamser, Pascal P., and Pawel Romanczuk. "Collective predator evasion: Putting the criticality hypothesis to the test." PLOS Computational Biology 17, no. 3 (March 15, 2021): e1008832. http://dx.doi.org/10.1371/journal.pcbi.1008832.

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According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the “criticality hypothesis”, appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the “criticality hypothesis”, but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality.
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Schraivogel, Daniel, Terra M. Kuhn, Benedikt Rauscher, Marta Rodríguez-Martínez, Malte Paulsen, Keegan Owsley, Aaron Middlebrook, et al. "High-speed fluorescence image–enabled cell sorting." Science 375, no. 6578 (January 21, 2022): 315–20. http://dx.doi.org/10.1126/science.abj3013.

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Abstract:
Fast and selective isolation of single cells with unique spatial and morphological traits remains a technical challenge. Here, we address this by establishing high-speed image-enabled cell sorting (ICS), which records multicolor fluorescence images and sorts cells based on measurements from image data at speeds up to 15,000 events per second. We show that ICS quantifies cell morphology and localization of labeled proteins and increases the resolution of cell cycle analyses by separating mitotic stages. We combine ICS with CRISPR-pooled screens to identify regulators of the nuclear factor κB (NF-κB) pathway, enabling the completion of genome-wide image-based screens in about 9 hours of run time. By assessing complex cellular phenotypes, ICS substantially expands the phenotypic space accessible to cell-sorting applications and pooled genetic screening.
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