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Journal articles on the topic 'Spatial mismatch'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 January 2023

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1

Hellerstein, Judith K., David Neumark, and Melissa McInerney. "Spatial mismatch or racial mismatch?" Journal of Urban Economics 64, no. 2 (September 2008): 464–79. http://dx.doi.org/10.1016/j.jue.2008.04.003.

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2

Zenou, Yves. "Spatial versus social mismatch." Journal of Urban Economics 74 (March 2013): 113–32. http://dx.doi.org/10.1016/j.jue.2012.11.002.

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3

Engberg, John, and Taeil Kim. "Intra-urban Earnings Differences: Spatial Mismatch or Selective Migration?" Korean Journal of Policy Studies 11 (December 31, 1996): 105–27. http://dx.doi.org/10.52372/kjps11007.

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We pose two models for earnings differences between residential locations in an urban area. The spatial mismatch model is based on barriers to labor mobility and suggests that observed earnings differences are real. The selective migration model suggests that observed earnings differences reflect unobserved differences in individual abilities. Using a sample of white men with a high school degree or less, we estimate a model of location choice and location-specific earnings for three portions of the Allegheny County (Pittsburgh). Our results indicate that the earnings decline in the old manufacturing portion of the county reflects selective emigration rather than continuing excess labor supply.

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4

Reinders, Stephanie, Li Lin, Yong Guan, Min Wu, and Jennifer Newman. "Algorithm Mismatch in Spatial Steganalysis." Electronic Imaging 2019, no. 5 (January 13, 2019): 535–1. http://dx.doi.org/10.2352/issn.2470-1173.2019.5.mwsf-535.

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5

Coulson, N. Edward, Derek Laing, and Ping Wang. "Spatial Mismatch in Search Equilibrium." Journal of Labor Economics 19, no. 4 (October 2001): 949–72. http://dx.doi.org/10.1086/322824.

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6

Brueckner, Jan K., and Richard W. Martin. "Spatial mismatch: An equilibrium analysis." Regional Science and Urban Economics 27, no. 6 (November 1997): 693–714. http://dx.doi.org/10.1016/s0166-0462(97)00004-5.

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7

Gobillon, Laurent, Harris Selod, and Yves Zenou. "The Mechanisms of Spatial Mismatch." Urban Studies 44, no. 12 (November 2007): 2401–27. http://dx.doi.org/10.1080/00420980701540937.

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8

Sjoquist, David L. "Spatial Mismatch and Social Acceptability." Journal of Urban Economics 50, no. 3 (November 2001): 474–90. http://dx.doi.org/10.1006/juec.2001.2229.

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9

Smith, Tony E., and Yves Zenou. "Spatial mismatch, search effort, and urban spatial structure." Journal of Urban Economics 54, no. 1 (July 2003): 129–56. http://dx.doi.org/10.1016/s0094-1190(03)00040-8.

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10

Theys, Tobias, Nick Deschacht, Stef Adriaenssens, and Dieter Verhaest. "The evolution of inter-regional spatial mismatch in the USA: The role of skills and spatial structure." Urban Studies 56, no. 13 (December 18, 2018): 2654–69. http://dx.doi.org/10.1177/0042098018803017.

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The literature on spatial mismatch often focuses on a mismatch within cities or local labour markets. This paper looks at the spatial mismatch between local labour markets. Using US data, we study the evolution of inter-regional mismatch between 1980 and 2010 and how this evolution varies across skill levels. Since we expect the spatial structure of supply and demand in the labour market to play a central role at this geographical level, we develop an extension of the spatial mismatch index, as the standard version does not take this spatial structure into account. Our results indicate that spatial mismatch has been increasing over the past decades, an increase that is largely attributable to spatial structure effects. The inter-regional spatial mismatch mainly affects low-skilled jobs and workers: our findings suggest that the degree of the spatial mismatch for low-skilled, relative to high-skilled workers, increased from a ratio of two in 1980 to almost four in 2010.

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11

Qi, Yunlei, Yingling Fan, Tieshan Sun, and Lingqian (Ivy) Hu. "Decade-long changes in spatial mismatch in Beijing, China: Are disadvantaged populations better or worse off?" Environment and Planning A: Economy and Space 50, no. 4 (February 5, 2018): 848–68. http://dx.doi.org/10.1177/0308518x18755747.

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Although recent studies have extended the U.S.-centered spatial mismatch hypothesis to Chinese cities, few have examined spatial mismatch conditions over time in Chinese Cities. This research responds to the knowledge gap by using longitudinal data to examine changes in the patterns and magnitudes of spatial mismatch between the 2000s and 2010s in Beijing, China. The longitudinal examination uniquely focuses on spatial mismatch between population and transit-accessible jobs, as opposed to spatial mismatch between population and any jobs. Results show that spatial mismatch conditions worsened among all population groups in the past decade in Beijing, China. When comparing across population groups, spatial mismatch worsened to a much higher degree among disadvantaged groups including the migrant population without local hukou and the low-educated population without college education. Further analyses show that changes in population distribution were primarily responsible for the worsened spatial mismatch conditions. Changes in job distribution and transit networks had limited impacts. Policy recommendations to mitigate spatial mismatch in Beijing include reconfiguration of transit networks and promotion of affordable housing development in transit- and/or job-rich areas.

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12

Houston, Donald. "Employability, Skills Mismatch and Spatial Mismatch in Metropolitan Labour Markets." Urban Studies 42, no. 2 (February 2005): 221–43. http://dx.doi.org/10.1080/0042098042000316119.

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13

Choi, Jihyun, Muwen Kong, Danielle N. Gallagher, Kevin Li, Gabriel Bronk, Yiting Cao, Eric Greene, and James E. Haber. "Repair of mismatched templates during Rad51-dependent Break-Induced Replication." PLOS Genetics 18, no. 9 (September 2, 2022): e1010056. http://dx.doi.org/10.1371/journal.pgen.1010056.

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Using budding yeast, we have studied Rad51-dependent break-induced replication (BIR), where the invading 3’ end of a site-specific double-strand break (DSB) and a donor template share 108 bp of homology that can be easily altered. BIR still occurs about 10% as often when every 6th base is mismatched as with a perfectly matched donor. Here we explore the tolerance of mismatches in more detail, by examining donor templates that each carry 10 mismatches, each with different spatial arrangements. Although 2 of the 6 arrangements we tested were nearly as efficient as the evenly-spaced reference, 4 were significantly less efficient. A donor with all 10 mismatches clustered at the 3’ invading end of the DSB was not impaired compared to arrangements where mismatches were clustered at the 5’ end. Our data suggest that the efficiency of strand invasion is principally dictated by thermodynamic considerations, i.e., by the total number of base pairs that can be formed; but mismatch position-specific effects are also important. We also addressed an apparent difference between in vitro and in vivo strand exchange assays, where in vitro studies had suggested that at a single contiguous stretch of 8 consecutive bases was needed to be paired for stable strand pairing, while in vivo assays using 108-bp substrates found significant recombination even when every 6th base was mismatched. Now, using substrates of either 90 or 108 nt–the latter being the size of the in vivo templates–we find that in vitro D-loop results are very similar to the in vivo results. However, there are still notable differences between in vivo and in vitro assays that are especially evident with unevenly-distributed mismatches. Mismatches in the donor template are incorporated into the BIR product in a strongly polar fashion up to ~40 nucleotides from the 3’ end. Mismatch incorporation depends on the 3’→ 5’ proofreading exonuclease activity of DNA polymerase δ, with little contribution from Msh2/Mlh1 mismatch repair proteins, or from Rad1-Rad10 flap nuclease or the Mph1 helicase. Surprisingly, the probability of a mismatch 27 nt from the 3’ end being replaced by donor sequence was the same whether the preceding 26 nucleotides were mismatched every 6th base or fully homologous. These data suggest that DNA polymerase δ “chews back” the 3’ end of the invading strand without any mismatch-dependent cues from the strand invasion structure. However, there appears to be an alternative way to incorporate a mismatch at the first base at the 3’ end of the donor.

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14

Easley, Janeria. "Spatial mismatch beyond black and white: Levels and determinants of job access among Asian and Hispanic subpopulations." Urban Studies 55, no. 8 (May 16, 2017): 1800–1820. http://dx.doi.org/10.1177/0042098017696254.

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United States (US) based research suggests that distance between residency and employment constrains labour market outcomes for black Americans. Work on this phenomenon, termed spatial mismatch, suggests that residential segregation from whites shapes labour market outcomes among blacks by restricting access to job-dense suburbs. However, few studies examine patterns and drivers of spatial mismatch among Asian and Hispanic subpopulations. Using data on job counts from the 2010 Zip Code Business Patterns data set and on population counts from the 2010 US decennial Censuses, I estimate spatial mismatch for the largest ethnoracial groups in the USA: black, white, Mexican, Puerto Rican, Cuban, Indian, Chinese, Filipino, Korean, Japanese and Vietnamese Americans. To measure spatial mismatch, I create indices of dissimilarity between jobs and residency for all Metropolitan Statistical Areas (MSAs) with available data. Estimates of spatial mismatch based on panethnic categories mask subpopulation heterogeneity. Most subgroups experience higher spatial mismatch than indicated by the panethnic category. The results also show novel racial differences: the average Vietnamese and Cuban American experience higher spatial mismatch than the average black American. Segregation from whites is a central predictor of exposure to spatial mismatch across all minority groups, though findings suggest that this relationship is not driven by suburbanisation.

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15

Hagen, Snorre B., Jane U. Jepsen, Tino Schott, and Rolf A. Ims. "Spatially mismatched trophic dynamics: cyclically outbreaking geometrids and their larval parasitoids." Biology Letters 6, no. 4 (January 27, 2010): 566–69. http://dx.doi.org/10.1098/rsbl.2009.1002.

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For trophic interactions to generate population cycles and complex spatio-temporal patterns, like travelling waves, the spatial dynamics must be matched across trophic levels. Here, we propose a spatial methodological approach for detecting such spatial match–mismatch and apply it to geometrid moths and their larval parasitoids in northern Norway, where outbreak cycles and travelling waves occur. We found clear evidence of spatial mismatch, suggesting that the spatially patterned moth cycles in this system are probably ruled by trophic interactions involving other agents than larval parasitoids.

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16

Fan, Yingling. "The Planners’ War against Spatial Mismatch." Journal of Planning Literature 27, no. 2 (February 8, 2012): 153–69. http://dx.doi.org/10.1177/0885412211431984.

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17

Perle, Eugene D., Harald Bauder, and Nancy Beckett. "Accessibility Measures in Spatial Mismatch Models." Professional Geographer 54, no. 1 (February 2002): 106–10. http://dx.doi.org/10.1111/0033-0124.00319.

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18

Bauder, Haraid. "Reflections on the Spatial Mismatch Debate." Journal of Planning Education and Research 19, no. 3 (March 2000): 316–20. http://dx.doi.org/10.1177/0739456x0001900311.

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19

Chen, Jun, Jiayi Ma, Changcai Yang, and Jinwen Tian. "Mismatch removal via coherent spatial relations." Journal of Electronic Imaging 23, no. 4 (July 22, 2014): 043012. http://dx.doi.org/10.1117/1.jei.23.4.043012.

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20

Li, Yongling, Stan Geertman, Yanliu Lin, Pieter Hooimeijer, Wangtu Xu, and Jie Huang. "Spatial mismatch for distinct socioeconomic groups in Xiamen, China." Journal of Transport and Land Use 15, no. 1 (January 24, 2022): 53–70. http://dx.doi.org/10.5198/jtlu.2022.1884.

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Studies have found that spatial mismatch is a universal phenomenon, although both their substantive and methodological focus can differ substantially. In China, there is a growing body of literature on spatial mismatch, but few studies have measured the degree of spatial mismatch between local and migrant workers in different occupations. To fill this gap, this research investigates the spatial mismatch for different socioeconomic groups in Xiamen according to their “hukou” status and occupation. As one of the country’s first four special economic zones, Xiamen achieved housing marketization earlier than most other Chinese cities, attracting a large amount of capital and migrants, and shaping different spatial patterns of local workers and migrant workers. The findings show that blue-collar, pink-collar, and white-collar workers, who are further categorized as either locals or migrants, experience varying degrees of job accessibility and spatial mismatch. In addition, even though migrant workers experience less spatial mismatch, they still have disadvantages in terms of commuting time due to their travel mode. The results presented in this paper are helpful for understanding the spatial mismatch for various social groups and facilitating sustainable mobility and social equity.

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21

O’Higgins, Tim, Karen Alexander, and Marcello Graziano. "Mismatches in spatial scale of supply and demand and their consequences for local welfare in Scottish aquaculture." Anthropocene Coasts 2, no. 1 (January 1, 2019): 261–78. http://dx.doi.org/10.1139/anc-2018-0025.

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Mismatches in spatial scales, or spatial disconnections between causes and effects of ecosystem degradation, can reduce resilience in social–ecological systems. These mismatches can be particularly disruptive in coastal and marine areas, where multiple social and ecological systems are multi-layered. Scotland’s Western Isles have a history of local resource exploitation to meet extra-regional, larger-scale demands, which has resulted in a long process of socio-demographic decline. Salmon aquaculture is a major and expanding industry in the area, often linked to “Blue Growth”. The expansion of this industry operates within and contributes to create several scale mismatches. Combining a systems approach across nested scales with a classification of scale mismatches, this work analyses the characteristics of the Western Isles salmon aquaculture industry, and it explores effects on social–ecological resilience. An extent scale mismatch between the global stocks of fishmeal species and the local capacity to respond to fluctuations is identified. The implications for this mismatch for the Western Isles are discussed. Some potential policy arrangements for incorporating matched spatial scales are considered.

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22

Chai, Tiancong, Céline Terrettaz, and Justine Collier. "Spatial coupling between DNA replication and mismatch repair in Caulobacter crescentus." Nucleic Acids Research 49, no. 6 (March 2, 2021): 3308–21. http://dx.doi.org/10.1093/nar/gkab112.

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Abstract The DNA mismatch repair (MMR) process detects and corrects replication errors in organisms ranging from bacteria to humans. In most bacteria, it is initiated by MutS detecting mismatches and MutL nicking the mismatch-containing DNA strand. Here, we show that MMR reduces the appearance of rifampicin resistances more than a 100-fold in the Caulobacter crescentus Alphaproteobacterium. Using fluorescently-tagged and functional MutS and MutL proteins, live cell microscopy experiments showed that MutS is usually associated with the replisome during the whole S-phase of the C. crescentus cell cycle, while MutL molecules may display a more dynamic association with the replisome. Thus, MMR components appear to use a 1D-scanning mode to search for rare mismatches, although the spatial association between MutS and the replisome is dispensible under standard growth conditions. Conversely, the spatial association of MutL with the replisome appears as critical for MMR in C. crescentus, suggesting a model where the β-sliding clamp licences the endonuclease activity of MutL right behind the replication fork where mismatches are generated. The spatial association between MMR and replisome components may also play a role in speeding up MMR and/or in recognizing which strand needs to be repaired in a variety of Alphaproteobacteria.

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23

Wang, Liping, Cifang Wu, and Songnian Zhao. "A Review of Spatial Mismatch Research: Empirical Debate, Theoretical Evolution and Connotation Expansion." Land 11, no. 7 (July 11, 2022): 1049. http://dx.doi.org/10.3390/land11071049.

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At present, widespread urban expansion, regeneration, and transformation have inevitably led to the spatial separation of residence and employment, and negatively affected the employment welfare of the subjects concerned, which needs to be traced back to the theory of spatial mismatch to explore possible solutions. The theory of spatial mismatch has been proposed for more than sixty years, and its theoretical connotation has been continuously expanded through the heated debate on its objective existence. However, due to the lack of understanding of its expansion process and the essence of its theoretical connotation, its theoretical meaning is ambiguous and fails to truly guide its role in practice. Based on the structural analysis of the connotation of spatial mismatch, this study summarizes the theoretical evolution and empirical development of spatial mismatch from four levels: “objects of concern-influencing factors-spatial relations-consequential effects”. It is found that after half a century of evolution, the study of spatial mismatch has formed a relatively perfect theoretical and methodological system, and in the process of expansion, spatial mismatch has been given a deeper meaning, which can provide an important theoretical and practical reference for solving the separation of residential and spatial resources and the resultant welfare loss effects.

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24

Kain, John F. "The Spatial Mismatch Hypothesis: Three Decades Later." Housing Policy Debate 3, no. 2 (January 1992): 371–460. http://dx.doi.org/10.1080/10511482.1992.9521100.

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25

Ruef, Martin, and Angelina Grigoryeva. "Jim Crow and the Spatial Mismatch Hypothesis." American Journal of Sociology 126, no. 2 (September 1, 2020): 407–52. http://dx.doi.org/10.1086/711686.

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26

Houston, Donald S. "Methods to Test the Spatial Mismatch Hypothesis." Economic Geography 81, no. 4 (February 16, 2009): 407–34. http://dx.doi.org/10.1111/j.1944-8287.2005.tb00281.x.

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27

Ong, Paul M., and Douglas Miller. "Spatial and Transportation Mismatch in Los Angeles." Journal of Planning Education and Research 25, no. 1 (September 2005): 43–56. http://dx.doi.org/10.1177/0739456x04270244.

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28

Kawabata, Mizuki. "Spatial mismatch problem of childcare in Tokyo." Procedia - Social and Behavioral Sciences 21 (2011): 300–303. http://dx.doi.org/10.1016/j.sbspro.2011.07.007.

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29

Glaeser, Edward L., and Naomi Hausman. "The Spatial Mismatch between Innovation and Joblessness." Innovation Policy and the Economy 20 (December 2020): 233–99. http://dx.doi.org/10.1086/705646.

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30

Gordon, Peter, Ajay Kumar, and Harry W. Richardson. "The Spatial Mismatch Hypothesis: Some New Evidence." Urban Studies 26, no. 3 (June 1989): 315–26. http://dx.doi.org/10.1080/00420988920080321.

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31

Arnott, Richard. "Economic Theory and the Spatial Mismatch Hypothesis." Urban Studies 35, no. 7 (June 1998): 1171–85. http://dx.doi.org/10.1080/0042098984547.

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32

BARONIO, FABIO, COSTANTINO DE ANGELIS, PAUL-HENRI PIOGER, VINCENT COUDERC, ALAIN BARTHÉLÉMY, YOOHONG MIN, VICTOR QUIRING, and WOLFGANG SOHLER. "DYNAMICS OF SPATIAL SOLITONS AT PHASE-MISMATCH INTERFACES." Journal of Nonlinear Optical Physics & Materials 13, no. 02 (June 2004): 243–57. http://dx.doi.org/10.1142/s0218863504001864.

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We studied the dynamics of spatial solitons at a phase-mismatch interface in quadratic nonlinear waveguides. We present here a simple formalism to analyze intensity-dependent reflection, refraction and emission of beams. Experimental demonstrations at a phase-mismatch PPLN/LiNbO3 interface are reported.

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33

Schuurman, Nadine, Darrin Grund, Michael Hayes, and Suzana Dragicevic. "Spatial/temporal mismatch: a conflation protocol for Canada Census spatial files." Canadian Geographer/Le G�ographe canadien 50, no. 1 (March 2006): 74–84. http://dx.doi.org/10.1111/j.0008-3658.2006.00127.x.

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34

Tang, Bo, and Hao Luo. "Mismatch and Coupling: A Study on the Synergistic Development of Tourism-Economy-Ecology Systems in the Pearl River Delta." Sustainability 14, no. 14 (July 12, 2022): 8518. http://dx.doi.org/10.3390/su14148518.

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The integrated study of the tourism-economy-ecosystem plays a significant role in regional high-quality development. In this study, methods including the Spatial Mismatch Hypothesis (SMH), coupling coordination degree and a gravity model are adopted in combination to explore the evolution characteristics of the Tourism-Economy-Ecology (TEE) systems in the Pearl River Delta (PRD) from 2009 to 2019 from four perspectives: development level, spatial mismatch, coupling coordination and spatial mismatch-coupling coordination. The research results are presented as follows. Firstly, the overall development level of the three subsystems shows improvement, the overall pattern of tourism and economic development levels shows similarity, the polarization of tourism development reaches a relatively significant level, and the changes in the ecological subsystem are more significant than those in other subsystems. Secondly, the spatial mismatch direction and level of cities are relatively stable, and the mismatch index of high-grade cities varies considerably, while the tourism subsystem contributes significantly to the occurrence of spatial mismatch in the regional system. Thirdly, the coupling and coordination level of the system in the east is higher than in the west, with a vast majority of them in the state of near-mismatch, while the coupling and coordination state is more stable in most cities and tends to be coordinated. Guangzhou, Shenzhen and Foshan represent the crucial nodes of regional system coupling and coordination. The opening of high-speed railway lines enhances the connection between cities, and it remains necessary to enhance the coupling and coordination across various economic circles. Lastly, according to the comparison of spatial mismatch-coupling coordination linkage, these cities can be classified into three categories: prominent core cities, coordinating sub-cities, and potential peripheral cities. To be specific, Guangzhou and Shenzhen represent prominent core cities, Dongguan, Foshan and Huizhou represent coordinated secondary cities, and Zhuhai, Zhongshan, Jiangmen and Zhaoqing represent potential peripheral cities.

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35

Yang, Zedong, Hui Sun, Weipeng Yuan, and Xuechao Xia. "The Spatial Pattern of the Prefecture-Level Carbon Emissions and Its Spatial Mismatch in China with the Level of Economic Development." Sustainability 14, no. 16 (August 17, 2022): 10209. http://dx.doi.org/10.3390/su141610209.

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Now, more and more attention is being paid to the deviation between economic benefits and environmental costs. Therefore, the research investigated the temporal variation in, and the spatial pattern of, carbon emissions systematically from the prefecture-level cities in China, and the spatial mismatch with the level of economic development from 2005 to 2020 by the spatial autocorrelation, the barycenter model, the spatial mismatch index and the standard deviation ellipse. The research results showed that: (1) The prefecture-level carbon emissions showed the characteristics of continuous expansion in time, decreasing from the north to the south and increasing from the southeast to the north-west in space. (2) The spatial distribution of high and low values of the prefecture-level carbon emissions in China showed significant spatial aggregation and positive correlation. Among them, the high-high (H-H) regions were mainly distributed in the city agglomerations of the mid-southern Liaoning, Beijing-Tianjin-Hebei, Huebaoyu, central Shanxi, Shandong Peninsula, and Yangtze River Delta. Low-low (L-L) regions continued to accelerate to the middle reaches of the Yangtze River, Guangdong, Fujian, Zhejiang and Macao, Pearl River Delta, Beibu Gulf, central Yunnan, central Guizhou, Chengdu-Chongqing, and other city agglomerations. (3) The barycenter of the carbon emissions has always been located in the north of the barycenter of economic development, and the spatial mismatch distance between the two showed the change characteristic of the type of N. It can be seen that the spatial mismatch was apparent. (4) The mismatch index and the mismatch contribution of the cities showed a significant regional differentiation pattern, decreasing from the east to the west.

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36

Zhou, Yong, Kaixu Zhao, Junling Han, Sidong Zhao, and Jingyuan Cao. "Geographical Pattern Evolution of Health Resources in China: Spatio-Temporal Dynamics and Spatial Mismatch." Tropical Medicine and Infectious Disease 7, no. 10 (October 10, 2022): 292. http://dx.doi.org/10.3390/tropicalmed7100292.

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(1) Background: The rational allocation of limited medical resources is the premise of safeguarding the public health. Especially since the outbreak of COVID-19, the evolution dynamics and spatial mismatch of medical resources have been a focal and frontier issue in academic discussions. (2) Methods: Based on the competitive state model and spatial mismatch index, this paper uses GIS and Geodetector spatial analysis methods and three typical indicators of hospitals, doctors, and beds to conduct an empirical study on the evolutionary characteristics and degree of mismatch in the geographic pattern of health resources in China from 2010 to 2020 (the data are from official publications issued by the National Bureau of statistics in China), in two dimensions of resource supply (economic carrying capacity) and demand (potential demand or need of residents). (3) Results: The spatial pattern of health resources at the provincial level in China has been firmly established for a long time, and the children and elderly population, health care government investment, and service industry added value are the key factors influencing the geographical distribution of health resources. The interaction between the different influence factors is dominated by bifactor enhancement, and about 30–40% of the factor pairs are in a nonlinear enhancement relationship. Hospital, doctor, and bed evolution trends and the magnitude and speed of their changes vary widely in spatial differentiation, but all are characterized by a high level of geographic agglomeration, heterogeneity, and gradient. Dynamic matching is the mainstream of development, while the geographical distribution of negative and positive mismatch shows strong spatial agglomeration and weak spatial autocorrelation. The cold and hot spots with evolution trend and space mismatch are highly clustered, shaping a center-periphery or gradient-varying spatial structure. (4) Conclusions: Despite the variability in the results of the analyses by different dimensions and indicators, the mismatch of health resources in China should not be ignored. According to the mismatch types and change trend, and following the geographic differentiation and spatial agglomeration patterns, this paper constructs a policy design framework of “regionalized governance-classified management”, in line with the concept of spatial adaptation and spatial justice, in order to provide a decision making basis for the government to optimize the allocation of health resources and carry out health spatial planning.

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37

Liu, Huayan, Wenfa Xiao, Jianhua Zhu, Lixiong Zeng, and Qi Li. "Urbanization Intensifies the Mismatch between the Supply and Demand of Regional Ecosystem Services: A Large-Scale Case of the Yangtze River Economic Belt in China." Remote Sensing 14, no. 20 (October 14, 2022): 5147. http://dx.doi.org/10.3390/rs14205147.

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The process of rapid urbanization has been causing non-negligible disturbances to our ecosystems, which has aggravated the mismatch between ecosystem service (ES) supply and demand. A clear understanding of the relationship between the ES supply–demand mismatch and urbanization is crucial as it could have a lot of significance for implementing ecological compensation and conservation action. Although a large number of studies have explored this problem, previous studies have focused primarily on the spatial mismatching of the ESs, and only a few studies have considered the spatial relationship between the ES supply–demand mismatch and urbanization at the watershed scale. Taking the Yangtze River Economic Belt (YREB) as an example, this study quantitatively assesses the supply and demand of five ESs, including carbon sequestration, water retention, soil conservation, food production, and recreational opportunity. The bivariate Moran’s I method was used to analyze and visualize the spatial correlation between the ES supply–demand mismatch and urbanization. The results indicate that both the total supply and the total demand of the five ESs increased, while the increasing rate of total demand was higher than the total supply of the ESs; this resulted in a significant spatial mismatch between the supply and demand of the ESs from 2000 to 2020. There is also a negative spatial correlation between the ES supply–demand and urbanization, while the results of local spatial clustering have obvious spatial heterogeneity. The metropolis and its surrounding counties are mostly the ES supply and demand deficit area, but some surrounding counties have managed to transform a deficit into a surplus. These results indicate that urbanization has a certain interference on the mismatch of the ES supply and demand, and this interference is not irreversible. Moreover, this study provides a reliable reference for government management in the context of balancing urbanization and the ecosystem.

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38

Eom, Hyunjoo. "Does Job Accessibility Matter in the Suburbs? Black Suburbia, Job Accessibility, and Employment Outcomes." Land 11, no. 11 (November 1, 2022): 1952. http://dx.doi.org/10.3390/land11111952.

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The spatial mismatch hypothesis of John Kain proposes that geographic separation between residential locations and jobs creates a spatial barrier in accessing job opportunities, which has a negative impact on labor market outcomes. A key hypothesis is that Black populations have limited accessibility to suburban job opportunities due to residential segregation in the city, resulting in lower employment and earnings. However, the spatial structure of the U.S. metropolitan area has changed since then, with increased polycentric employment growth and Black suburbanization. This challenges Kain’s original hypothesis that residential segregation in the city creates a spatial barrier in accessing jobs. The spatial pattern of mismatch has changed and demonstrates a mismatch between Black suburbs and suburban jobs. Then, what role does job accessibility play in the change in the spatial pattern of mismatch? Does job accessibility continue to matter in the suburbs? Or, are there other more important neighborhood characteristics affecting labor market outcomes? The findings demonstrate that job accessibility remains closely associated with Black labor market outcomes. In Chicago, job accessibility has higher marginal effects on Black employment, especially in predominantly Black neighborhoods. However, in Atlanta, where a majority of the Black population lives in the suburbs, having a higher percentage of Black residents in the neighborhood negates the effects of job accessibility. Instead, the share of Black residents becomes a more significant factor in employment. The findings demonstrate that the effect of job accessibility varies by the spatial pattern of mismatch. Job accessibility becomes less important in highly segregated suburbs, but the share of Black residents matters more in labor market outcomes. In metropolitan areas with the traditional mismatch pattern, job accessibility is significantly associated with employment and earnings, especially in neighborhoods where the majority of the Black population remains segregated in the city.

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Frings, Christian, Frank Mast, and Charles Spence. "Tactile spatial negative priming occurs without feature mismatch." Attention, Perception, & Psychophysics 76, no. 8 (June 19, 2014): 2305–14. http://dx.doi.org/10.3758/s13414-014-0721-4.

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Bauder, H., and E. Perle. "Spatial and Skills Mismatch for Labor-Market Segments." Environment and Planning A: Economy and Space 31, no. 6 (June 1999): 959–77. http://dx.doi.org/10.1068/a310959.

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41

Rosenthal, Stuart S., and William C. Strange. "Female Entrepreneurship, Agglomeration, and a New Spatial Mismatch." Review of Economics and Statistics 94, no. 3 (August 2012): 764–88. http://dx.doi.org/10.1162/rest_a_00193.

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Kain, John F. "A Pioneer's Perspective on the Spatial Mismatch Literature." Urban Studies 41, no. 1 (January 2004): 7–32. http://dx.doi.org/10.1080/0042098032000155669.

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43

Stoll, Michael A. "Job sprawl, spatial mismatch, and black employment disadvantage." Journal of Policy Analysis and Management 25, no. 4 (September 2006): 827–54. http://dx.doi.org/10.1002/pam.20210.

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Weinberg, Bruce A. "Black Residential Centralization and the Spatial Mismatch Hypothesis." Journal of Urban Economics 48, no. 1 (July 2000): 110–34. http://dx.doi.org/10.1006/juec.1999.2159.

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Dai, Tian, Lingjuan Miao, and Yanbing Guo. "A Real-Time Mismatch Detection Method for Underwater Database-Referenced Navigation." Sensors 19, no. 2 (January 14, 2019): 307. http://dx.doi.org/10.3390/s19020307.

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Database-referenced navigation (DBRN) using geophysical information is often implemented on autonomous underwater vehicles (AUVs) to correct the positional errors of the inertial navigation system (INS). The matching algorithm is a pivotal technique in DBRN. However, it is impossible to completely eliminate mismatches in practical application. Therefore, it is necessary to perform a mismatch detection method on the outputs of DBRN. In this paper, we propose a real-time triple constraint mismatch detection method. The proposed detection method is divided into three modules: the model fitting detection module, the spatial structure detection module, and the distance ratio detection module. In the model fitting detection module, the navigation characteristics of AUVs are used to select the fitting model. In the spatial structure detection module, the proposed method performs the mismatch detection based on the affine transformation relationship between the INS-indicated trajectory and the corresponding matched trajectory. In the distance ratio detection module, we derive the distance ratio constraint between the INS-indicated trajectory and the corresponding matched trajectory. Simulations based on an actual geomagnetic anomaly base map have been performed for the validation of the proposed method.

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Blumenberg, Evelyn, and Daniel Hess Hess. "Measuring the Role of Transportation in Facilitating Welfare-to-Work Transition: Evidence from Three California Counties." Transportation Research Record: Journal of the Transportation Research Board 1859, no. 1 (January 2003): 93–101. http://dx.doi.org/10.3141/1859-12.

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Welfare-to-Work transportation programs are premised on a conceptualization of the spatial mismatch hypothesis that focuses on the physical separation between the central city locations of welfare participants, rapidly expanding job opportunities in the suburbs, and the long commutes needed to connect them. Using data from three diverse California counties, welfare recipients’ spatial access to employment was examined. The results indicate that the traditional notion of the spatial mismatch is less relevant to welfare recipients, many of whom live in counties in which the urban structure does not fit the simple model of poor, central-city neighborhoods and distant, job-rich suburbs. Many welfare recipients live in job-rich areas; others live in neighborhoods that are spatially isolated from employment. Therefore, to be effective, transportation policies must be tailored to the diverse characteristics of the neighborhoods in which welfare recipients live.

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Reid, Emma, Delyth Graham, M. Rosario Lopez-Gonzalez, William M. Holmes, I. Mhairi Macrae, and Christopher McCabe. "Penumbra Detection using PWI/DWI Mismatch MRI in a Rat Stroke Model with and without Comorbidity: Comparison of Methods." Journal of Cerebral Blood Flow & Metabolism 32, no. 9 (June 6, 2012): 1765–77. http://dx.doi.org/10.1038/jcbfm.2012.69.

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Perfusion-diffusion (perfusion-weighted imaging (PWI)/diffusion-weighted imaging (DWI)) mismatch is used to identify penumbra in acute stroke. However, limitations in penumbra detection with mismatch are recognized, with a lack of consensus on thresholds, quantification and validation of mismatch. We determined perfusion and diffusion thresholds from final infarct in the clinically relevant spontaneously hypertensive stroke-prone (SHRSP) rat and its normotensive control strain, Wistar-Kyoto (WKY) and compared three methods for penumbra calculation. After permanent middle cerebral artery occlusion (MCAO) (WKY n=12, SHRSP n=15), diffusion-weighted (DWI) and perfusion-weighted (PWI) images were obtained for 4 hours post stroke and final infarct determined at 24 hours on T2 scans. The PWI/DWI mismatch was calculated from volumetric assessment (perfusion deficit volume minus apparent diffusion coefficient (ADC)-defined lesion volume) or spatial assessment of mismatch area on each coronal slice. The ADC-derived lesion growth provided the third, retrospective measure of penumbra. At 1 hour after MCAO, volumetric mismatch detected smaller volumes of penumbra in both strains (SHRSP: 31±50 mm3, WKY: 22±59 mm3, mean±s.d.) compared with spatial assessment (SHRSP: 36±15 mm3, WKY: 43±43 mm3) and ADC lesion expansion (SHRSP: 41±45 mm3, WKY: 65±41 mm3), although these differences were not statistically significant. Spatial assessment appears most informative, using both diffusion and perfusion data, eliminating the influence of negative mismatch and allowing the anatomical location of penumbra to be assessed at given time points after stroke.

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Zeng, Xiangjing, Yong Ma, Jie Ren, and Biao He. "Analysis of the Green Development Effects of High-Speed Railways Based on Eco-Efficiency: Evidence from Multisource Remote Sensing and Statistical Data of Urban Agglomerations in the Middle Reaches of the Yangtze River, China." International Journal of Environmental Research and Public Health 19, no. 24 (December 7, 2022): 16431. http://dx.doi.org/10.3390/ijerph192416431.

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As part of the modern transport infrastructure, high-speed railways (HSRs) have been considered an important factor affecting eco-efficiency (EE). This study used multisource remote sensing and statistical data from 185 counties representing urban agglomerations in the middle reaches of the Yangtze River (UAMRYR) in China from 2009 to 2018. The study integrated ArcGIS analysis, the Super-SBM (super slack-based measure) model, and the DSPDM (dynamic spatial panel Durbin model) to explore the spatial effects of HSRs on EE. The results showed that the coordinates of the interannual centers of gravity for EE and HSRs both fell in the same county, possessing similar parameter values for the standard deviation elliptical, a negative spatial mismatch index, and obvious spatial mismatch characteristics. In different spatially dislocated areas, the spatial effects of HSRs on EE are variable. Overall, the short-term effects are more intense than the long-term effects, and both the long-term and short-term effects are dominated by the effects of spatial spillover. A new perspective is proposed to explore the green development effects of HSRs, with a view to providing policy implications for the enhancement of EE and the planning of HSRs.

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Sun, Wenwen, Hongyu Jin, Yan Chen, Xin Hu, Zhuoran Li, Akari Kidd, and Chunlu Liu. "Spatial mismatch analyses of school land in China using a spatial statistical approach." Land Use Policy 108 (September 2021): 105543. http://dx.doi.org/10.1016/j.landusepol.2021.105543.

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Blumenberg, Evelyn, and Michael Manville. "Beyond the Spatial Mismatch: Welfare Recipients and Transportation Policy." Journal of Planning Literature 19, no. 2 (November 2004): 182–205. http://dx.doi.org/10.1177/0885412204269103.

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