The analysis starts from the Urban Audit Database, which collects data for European core cities (LAU-2 level). Due to rather poor data coverage, our analysis is limited to 181 cities in Western European Countries (i.e. EU-15 Member States). In terms of indicators, we collect the following structural variables: resident population; per capita GDP (in Euro); unemployment rate; proportion of employment in industrial sectors; proportion of graduates in population. To enrich the analysis, two other indicators are added: multimodal accessibility index 8 and total agricultural area (in ha.) per inhabitant. They do not strictly refer to urban areas as defined above, but they highlight geographic features of the NUTS-3 regions (e.g. Italian Province, French Department, German Kreis) which surround the 181 cities in the sample. (For a more detailed explanation of both the cities and the chosen indicators, see “Appendix – Cities and Indicators”). Although the latest Urban Audit collection round dates from 2006/2007, we use 2001 data to limit the number of missing values. The remaining missing values were replaced by data at the NUTS-3 or NUTS-2 level (the data source is REGIO-Eurostat). We are well aware of distortions deriving from the use of different geographic units. However, we are able to use data from Eurostat only, without mixing data from different national statistical sources.
within buildings. According to Leal and Sorando (2016), both professionalisation and residential entrapment of lower socio-economic groups are behind the dra- matic growth in levels of segregation in Madrid. Furthermore, the authors argue that the invasion of professionals into new parts of the city, for example as a result of gentrification, as well as in situ inter-generational social mobility both actually exerted lowering effects on levels of segregation. In Milan, Petsimeris and Rimoldi (2016) indicate that some of the important mechanisms behind segregation include self-segregation of business owners into the most exclusive residential areas of the city; in situ intra- and inter-generational social mobility; and the purchase of apartments by working-class households under the right-to- buy schemes and a later selling of their properties to more affluent social groups. In East Europe, we make a distinction between Visegrad and Baltic capitals; Budapest and Prague represent Visegrad cities. Based on the factors outlined in Table 1.1, we hypothesised Budapest to be moderately and Prague to be modestly segregated. The main findings confirm these hypotheses. More specifically, the D value between top and bottom socio-economic groups is as low as 26 in Prague and 32 in Budapest, with a slightly increasing trend in both cities. Budapest used to be the most segregated city in East Europe, but this is not the case anymore. Furthermore, instead of higher socio-economic groups, lower socio-economic groups became most segregated in the 2000s. Kovács and Szabó (2016) think that the most plausible reason for the decreasing segregation level of professionals is their more even distribution across neighbourhoods, triggered by new housing projects developed in the inner city and other areas with previously a high share of lower socio-economic groups. This is quite similar to what is taking place in Prague. Ouředníček et al. (2016) agree that low levels of socio-economic segrega- tion are mainly a consequence of the location of new housing and in-migration of higher socio-economic groups into the formerly poorer neighbourhoods, often in the inner city of Prague. Such changes are common to many other cities included into our analysis beyond Eastern Europe. In other words, the increase of social inequalities often goes hand-in-hand with gentrification, which, at least initially, brings down levels of segregation as different social groups begin to mix in the inner city.
gies do urban authorities of downscaled, mid-sized cities develop to rescale their cities? How are these strate- gies related to the imagined ‘pathways of integration’ of asylum seekers? In addition to scale theory, the em- pirical basis for this article is ethnographic research on the Dutch downscaled mid-sized city Kerkrade, where I lived for seven months in the period of 2016 to 2018. There, I conducted expert interviews with nine agents of urban authorities (of the local government and hous- ing corporations), two group discussions with 8–10 vol- unteers supporting asylum seekers, and in-depths inter- views with 24 asylum seekers. In addition, I had sev- eral informal encounters with volunteers and asylum seekers. All of the interviews were recorded, and the transcripts coded, firstly, using the open coding method (Miles & Huberman, 1994), and secondly, axial cod- ing by rereading, comparing and validating coded text fragments to determine the main categories (Corbin & Strauss, 1990). Moreover, participant observation of pub- lic spaces and an analysis of policy documents were car- ried out (Krippendorff, 2004). This article does not deal with all of these different perspectives, but first and fore- most with the agency of urban planners and housing cor- porations, whilst suggesting that their ‘scalar narratives’ are neither new nor unique to this place, but rather illus- trate patterns of rescaling processes that probably char- acterise other European downscaled mid-sized cities. 2. Multiscalar Perspective on Mid-Sized Cities
Tokyo became the top ranked city in 2012, with New York as the second-ranked city (Fig. 2). In 2006 the two cities differed only by 0.2 index points, while in 2012 the difference was 8.54 points. This may suggest that the global economic crisis, which began in the United States in 2007 and spread to the European Union and other parts of the world by 2008 (Nowotnik, 2011), had a stronger impact on American cities than on Tokyo. One proof of this hypothesis may be the decline in the number of Type 1 cities in the United States between 2006 (15 cities) and 2012 (11 cities) the decreasing number of cities with the highest potential (over 20.0) from 15 in 2006 to 11 in 2012. On the other hand, London and Paris maintained their third and fourth place during the study period. The four top-ranked cities are not merely places where major corporations establish their headquarters, but also centers of global services and management (Taylor, 2004). The fifth-ranked city is Beijing at 70.42 points. Moscow can be found at 31.19 points, which gives it a rank of thirteen. The capital of Poland, Warsaw, is ranked at 7.17 points. Warsaw’s status has increased significantly in the last decade. Budapest is at a value of 4.63. The other studied cities did not exceed 2.5 points. This included Prague (2.48 points), Lubin (2.44 points), and Almetyevsk (2.35 points).
GRASS GIS provides the most accurate GIS hydrological analysis with its terrain analyses, r.terraflow and r.watershed, because the program uses algorithms that create a multiple flow direction (MFD) output for the stream networks. r.watershed was chosen as it has been proven to produce better and more accurate results for stream networks specifically in areas with low slope values (GRASS GIS manuals 2010). Tarboton’s (2013) Terrain Analysis Using Digital levation Models (TauDEM), a toolbox externally created for ArcGIS, was also tested for the regional scale of analysis as its algorithm is also based on MFD. MFD creates a more natural flow path output as it searches the DEM raster cells within 16 cells, instead of the 8 cells, used by the single flow direction (SFD). The SFD, also known as D8, assumes that there is only one direction of flow, that of the steepest downslope direction and creates unnatural flow paths especially in valleys (Neteller and Mitasova 2008). MFD algorithms create the flow path from each downslope neighbouring cell, or lower elevation cells, therefore, creating a more naturalistic flow path (ibid). Unfortunately for the regional scale of analysis r.watershed and TauDEM were not able to run such large, high-resolution input variables because of the size of the dataset and the number of rows and columns comprising the raster. The DEM was therefore cut into multiple areas that were of the correct size for analysis. Issues arose when merging the outputs together due to edge effects at the areas of overlap. It was decided to use ArcGIS Hydrology toolbox for the regional scale because even though the processing time was long, it could handle the size of the input data (ESRI 2011a). The problem is that ArcGIS runs the SFD algorithm, so the results are not as accurate or reflective of the natural flow paths. This creates a more general output for the large regional scale. Smaller scales of analysis were then run using r.watershed and are more accurate.
What are the most effective forms of intervention to reproduce this optimistic scenario? During the 20th century one option pursued (especially in the United States of America) was advanced technologies to diagnose earlier and mitigate or manage the disabling effects of chronic diseases. However, a consequence is increased per capita expenditure on health at any given age . Active Ageing advocates another less costly option: preventive measures in early and middle life course to reduce proximal risk factors for noncommunicable diseases, such as: smoking, unhealthy nutrition, physical inactivity, alcohol consumption and stress. WHO-EHCN cities have adopted a social model of health giving equal weight to distal determinants of health such as housing and employment . Cities forecast that this approach will expand the 3rd age and, consequently, compress the 4th age of their populations.
We also control for several factors. We control for human capital given the importance of scale and size of economic activity (Armington and Acs, 2002; Saxenian, 1999) using a knowledge hub city dummy. We take this city classification from (State of EuropeanCities Report, 2007) It identifies a city which can host science clusters (Cooke et al., 2005) and universities (Audretsch and Lehmann, 2005) which in turn, can positively affect knowledge diffusion and clustering (Audretsch and Feldman, 1996). Knowledge hub cities, such as London, may rise above national urban hierarchy to the forefront of international industry, business and financial services, and become well-connected globally and attract high levels of talent (State of EuropeanCities Report, 2007). We control for the proportion of employment across sectors using NACE 3 classification (Thurik et al., 2008) and new firm entry rate (Audretsch and Feldman, 1996; Audretsch and Lehnmann, 2005; Audretsch and Keilbach, 2007). To account for location, which is important because of delocalization of IT services in Eastern Europe, we include a dummy “East” which assigns a value of one if a city is located in Eastern Europe and 0 if in Western Europe (Aidis et. al., 2008). This also captures competitive and institutional phenomenon such as labor market trends, e.g., informality (Sobel 2008; Manolova et al., 2008). Along with country- level institutional controls we include University-industry collaboration in R&D at a country level. This variable is normalised from 0 to 100 and illustrates to what extent do business and universities collaborate on research and development (R&D) in a country; 0 = do not collaborate at all; 100 = collaborate extensively. This is the only variable taken from the World economic Forum The Global Competitiveness Report 2012-2013. Finally, we include year dummies as a time dimension.
The three cities present different profiles in terms of the recognition of the im- portance of creative industries. In Birmingham and England, this recognition was characterised by a top-down approach with a strong impulse from the national government. As such, over the 2000s period, creative industries benefited from sectoral plans and strategies and were also part of more comprehensive strategies to develop the city and the region. There was a specific focus on jewellery and crafts, new media and film and video. In Poznań and Leipzig, this recognition fol- lows a more bottom-up approach. For instance, the cultural capital of Poland has traditionally been Cracow. Poznań was (and still is) a business city and creative industries are not considered as an important asset for the city and do not benefit from any specific policy. However, creative industries are present in the city and there is demand for “creative goods” as some inhabitants go even elsewhere to attend cultural events. In Leipzig, creative actors have a strong presence, espe- cially in Media, Art and Music and this has been recognised in the development of a sectoral policy by local and regional policy makers in the last few years.
Table 4 shows global network connectivities for the top 5 UK cities to illustrate how well the leading British cities are integrated into the world city network. The outstanding result is no surprise: the continuing dominance of London. While other UK cities are still not major players in the world city network, there are now some moderately important world cities that can be identified with about one fifth of London’s connectivity. Manchester, Glasgow and Birmingham have been in competition to be the UK’s “second city” for more than a century and they continue to be leading cities in globalization but are now joined by Edinburgh, Europe’s newest financial centre. Manchester and Birmingham are the centres of the two major economic regions outside the South East, the North West and West Midlands respectively, and are reinventing themselves as new European and world cities. Edinburgh is the fast riser based upon being the capital city of Scotland, the UK’s main political devolution (with its new service needs), as well as being home to successful banks (before the credit crisis when these data were collected; see Derudder et al., 2011). Glasgow has traditionally been the economic centre for Scotland but may now be being overtaken by its neighbour Edinburgh; however it is still of some importance within contemporary globalization. The overall message of this table is not that any UK city is seriously rivalling London but that leading British cities across the country are integrated into the world city network to a moderate degree.
(Pablo Gonzalez, male, National government official, July 2013, interview) Here, Gonzalez and the analysis of the document reveal a fundamental aspect, a kind of trend that is repeated among the institutional forms reviewed so far: it is a techno-centric approach with a belief that by mastering only the physical dimensions of hazards and vulnerability, disasters and risks will be reduced. The international and historical experience has demonstrated the opposite (UNISDR, 2015a), as a comprehensive social and environmental analysis of hazards and vulnerability is needed, including the capacities and resiliency of men and women, communities and institutions, as well as the political, economic, governance and cultural dimensions of risks at multiple levels, and all this intertwined with the history that comes with it (UNISDR, 2015b). Another interesting aspect emerges from the way in which vulnerability is conceived in the guide mentioned above, and of relevance for the implementation of PROTs: vulnerability and risks are limited to circumstances and conditions at local levels —neighbourhoods, city. Effectively, when I reviewed the section on vulnerability (SUBDERE, 2011b, pp.14-15), only local unsafe conditions had to be identified, but not the drivers of such conditions — neither the linkages of such conditions with dynamic pressures nor the root causes that could have generated them in the first place. It is like all multi-scale relations are missing.
This evaluation indicates that the level of understanding of the significance of planning for health by the Healthy Cities movement has developed significantly over the period of phase IV, but still has some way to go. A broad conclusion is that the Healthy Cities programme can be effective in promoting the critical importance of linking health and planning, and in disseminating and developing good practice. In many cities it has helped to transform the political and professional agenda, integrating health with sustainable development and the planning of the human environment. However, many cities are still struggling with the more strategic and holistic approach of level 3. Two common factors seem to be that they are hampered by internal institutional barriers and by an evolving spatial form which is driven by ‘what the market can deliver’. Such barriers militate against any form of integrated working; it is not just HUP that will be disadvantaged. Any city, as a large complex organisation, will suffer from this to an extent and we can see that the successful cities are those that engage a broad range of stakeholders and form wide ranging partnerships providing a continual bulwark against sectoral silos.
better test the feasibility of different bubonic transmission routes in Europe.
The use of metapopulation dynamics in disease modeling has been key to understanding the geographic spread of disease (Keeling and Rohani 2007 ). Therefore, we used a metapopulation structure in the models, in which the amount of connectivity between subpopulations was determined by q. We considered the same values of q for each model, which had a relatively small effect on the simulations. By design, the connectivity in the models focused on the impact of spatial structure, rather than a social network, on the spread of disease. Social networks have been used in disease models and generally take into account demography, travel habits, and mixing behavior, both in neighboring and distant subpopulations (e.g., Eubank et al. 2004 ; Balcan et al. 2010 ). Additional heterogeneity in our models would have increased the spread of disease, particularly in large cities, where having infectious individuals moving large distances would introduce the disease to new localities faster. To further complicate modeling networks, human behaviors are likely to change during a large scale epidemic, for example if quarantine and sanitation procedures are enacted. During the Black Death cities in Croatia, Italy, and France enacted coordinated public health measures against plague, such as maritime quarantines, or ‘lazzarettos’ (Conrad et al. 1995 ).
In terms of geographical distribution, there is no specific pattern to be identified. Nevertheless, more than 60% of respondents in all 4 Turkish cities included in the survey agree with the idea that foreigners living in their city are well integrated. The results among EU capital cities range from 73% in Ljubljana to only 14% in Athina. A majority of respondents agree with this statement in 17 of the EU capital cities, but in 11 capitals less than 50% of respondents agree and in 3 capitals the level of agreement is below 40%: Athina (14%), Berlin (30%) and Stockholm (38%).
son. From the connected quark correlator C ss , at hopping parameters ⫽ 0.14077 and 0.13843, we find scalar qq ¯ masses of 1.39 共 5 兲 , 1.36 共 2 兲 respectively in lattice units, fitting local and two types of smeared operator to one state in the t range 2 to 8. Note that the mass ordering is not as expected 共 namely meson with lighter quarks being lighter 兲 but the errors are large enough to cover near equality. This meson mass value is somewhat larger than that reported 关 9 兴 at the same ␤ value but using Wilson quarks of mass correspond- ing to strange 共 i.e., our ⫽ 0.14077), namely 1.29 共 2 兲 . This discrepancy is not surprising since the SW-clover formalism we use has improved control of order a effects compared to the Wilson discretization.
For the most part we were overly pessimistic in our 2013 forecasts and trading turned out stronger than we predicted. Many cities saw a volatile performance but fared better than their GDP forecasts or low confidence levels suggested at the time of our forecast. Indeed a year ago the EU was in the middle of a double-dip recession. Despite this many economies saw unexpected improvement as 2013 unfolded and Dublin enjoyed RevPAR growth of 11% in 2013; Zurich and Edinburgh saw around 8% RevPAR growth; Lisbon saw 6% and Frankfurt and Milan saw 5% apiece. Madrid, Geneva, Vienna and Paris underperformed compared to our expectations but all for different reasons.
As a result of the high warming experienced in inner districts of settlements, in these areas the air strongly rises and its place is taken by the inflow of cooler air coming from the outskirts of the settlements and neighbouring regions. In case of clear and calm weather an individual local wind system, so-called urban wind develops in areas that can be characterised with high built-up density. Urban wind has a dual significance. On the one hand, being particularly strong in the evenings it helps to mitigate and to bear more easily the urban heat island effect. On the other hand, it helps to clear the polluted air of cities. In forming the urban structure, the prevalence of these favourable impacts is assisted by taking the wind directions and channel effects into account and preventing or terminating the establishment of potential blocks. In case of settlements located on hillsides with surrounding areas covered with forest (which warm up less during the daytime) cold air ‘flowing down’ from the higher levels has great significance. Favourable effects similar to those mentioned with respect to urban wind can be achieved by developing the urban structure optimally, enabling cool air coming from higher parts of the hill to flow unobstructed towards the slopes. As a result of special urban circulation systems (characterised by frequent lifting) and the great number of condensation cores originating from dust pollution, the quantity of precipitation in densely inhabited settlements is on average 5 to 10% higher than in the neighbouring areas.
2012 ; Qian 2013 ; Dheer 2017 ), broadly rooted in the Information, Consumption and Reinvention approaches to city development (Glaeser et al. 2004 ) discussed above, we operationalise cultural diversity as a complex systemic scale variable based on a number of relevant variables and construct an index which includes diver- sity embedded in foreign temporary visitors and resi- dents (i.e. a number of tourists (business and leisure) overnight stays per resident, and proportion of non-EU nationals as percentage of total population 3 ) creating a social network effects and ideation, blended with avail- ability and usage of local cultural amenities and infra- structure (i.e. number of cinemas, theatres, museums) (Audretsch et al. 2015b ). Although cultural amenities may not become forums for entrepreneurial knowledge sharing, they will serve as diversified cultural areas to attract diverse cultures in cities as per Glaeser et al. ( 2004 ) consumption view. Of course, an increase in number of cinemas, theatres and museums may be as- sociated with a particular public investment strategy in culture or historical philanthropy and not with an influx of creative class (Florida 2002 ). However, it does not change the mechanism which attracts diverse cultural groups into a city which further enables the KSTE mechanism. Urban amenities enhance and create an ecosystem of entrepreneurship and innovation (Acs et al. 2014 ; Autio et al. 2014 ; Audretsch and Belitski
The teaching of definitions in school mathematics is recognised as challenging for those who see the learning of mathematics in terms of sense making (Lakatos, 1976; Vinner, 1991; Foster, 2014a; Tall, 2013). Definitions make no logical claims, so require no mathematical justification, and yet students may be reluctant to accept them, or may appear to accept them but do so only superficially. Rabin, Fuller and Harel (2013) have shown that students may expect too much from a definition by demanding that the teacher demonstrate that it is true. It might be thought that this could be prevented if the teacher were to be explicit about the difference between a definition and a theorem, and that a definition may just be seen as something that is assumed true. In this paper we examine a classroom episode in which the teacher attempted to do exactly that when introducing the definition of the scalar product to a class of 17-18-year-old secondary school students. However, a student rejected the standard definition in favour of his own alternative. We analyse this episode and draw out ways in which teachers can introduce formal mathematical definitions to students so as to support their mathematical sense making rather than attempt to circumvent it.
Opportunities for cities in partnering with business in pre-procurement phase
1. Draw important knowledge and expertise from businesses to use in advancing and fine-tuning urban sustainability strategies 2. Improved access to finance to support
We know that the binary representation of any number is unique and consists of two digits 0 or 1 . However, if we use negative number too, in the representation then there exist infinite number of representations for a number hav- ing different lengths and density.Density means the number of non - zero digits. Inclusion of negative digits in the rep- resentation leads to requirement of inverse. In case of El- liptic curves inversion of a point is very simple, i.e. just the negation of the Y- co-ordinate, in case of primary field or addition of X and Y coordinate in case of binary fields. These operations are very low cost and can be neglected. Out of all such representations, there exist exactly one rep- resentation in which there are no consecutive non zero dig- its . This representation is known as the NAF representa- tion and is important because it puts an upper bound on the density of any l- bit scalar k. The Non Adjacent Form (NAF) representation of a number consists of three digits 0, 1 or -1. The representation ensures that there cannot be any two or more contiguous non zero digits in the representa- tion. As an example, suppose k = 15, in the computation of kP. Binary representation of (15) 10 is (1111) 2 , while if we