Search

During a time of rapid urban growth and development, it is becoming ever more important to monitor the carbon fluxes of our cities. Unlike Canada's commercially managed forests that have a long history of inventory and modelling tools, there is both a lack of coordinated data and considerable uncertainty on assessment procedures for urban forest carbon. Nonetheless, independent studies have been carried out across Canada. To improve upon Canada's federal government reporting on carbon storage and sequestration by urban forests, this study builds on existing data to develop an updated assessment of carbon storage and sequestration for Canada's urban forests. Using canopy cover estimates derived from ortho-imagery and satellite imagery ranging from 2008 to 2012 and field-based urban forest inventory and assessment data from 16 Canadian cities and one US city, this study found that Canadian urban forests store approximately 27,297.8 kt C (− 37%, + 45%) in above and belowground biomass and sequester approximately 1497.7 kt C year−1 (− 26%, + 28%). In comparison with the previous national assessment of urban forest carbon, this study suggested that in urban areas carbon storage has been overestimated and carbon sequestration has been underestimated. Maximizing urban forest carbon sinks will contribute to Canada's mitigation efforts and, while being a smaller carbon sink compared to commercial forests, will also provide important ecosystem services and co-benefits to approximately 83% of Canadian people. [ABSTRACT FROM AUTHOR]

The aggregation kinetics of settling particles is studied theoretically and numerically using the advection–diffusion equation. Agglomeration caused by these mechanisms (diffusion and advection) is important for both small particles (e.g., primary ash or soot particles in the atmosphere) and large particles of identical or close size, where the spatial inhomogeneity is less pronounced. Analytical results can be obtained for small and large Péclet numbers, which determine the relative importance of diffusion and advection. For small numbers (spatial inhomogeneity is mainly due to diffusion), an expression for the aggregation rate is obtained using an expansion in terms of Péclet numbers. For large Péclet numbers, when advection is the main source of spatial inhomogeneity, the aggregation rate is derived from ballistic coefficients. Combining these results yields a rational approximation for the whole range of Péclet numbers. The aggregation rates are also estimated by numerically solving the advection–diffusion equation. The numerical results agree well with the analytical theory for a wide range of Péclet numbers (extending over four orders of magnitude). [ABSTRACT FROM AUTHOR]

This paper considers agglomeration economies. A new firm is planning to open a plant in a country divided into several regions. Each firm receives a positive externality if the new plant is located in its region. In a decentralized mechanism, the plant would be opened in the region where the new firm maximizes its individual benefit. Due to the externalities, it could be the case that the aggregate utility of all firms is maximized in a different region. Thus, the firms in the optimal region could transfer something to the new firm in order to incentivize it to open the plant in that region. We propose two rules that provide two different schemes for transfers between firms already located in the country and the newcomer. The first is based on cooperative game theory. This rule coincides with the τ -value, the nucleolus, and the per capita nucleolus of the associated cooperative game. The second is defined directly. We provide axiomatic characterizations for both rules. We characterize the core of the cooperative game. We prove that both rules belong to the core. [ABSTRACT FROM AUTHOR]

With the rapid development of urban agglomerations in northwest arid and semiarid regions of China, the scope of the urban heat island (UHI) effect has gradually expanded and gradually connected, and has formed a regional heat island (RHI) with a larger range of impact to the regional environment. However, there are few studies on the heat island effect of urban agglomerations in arid and semiarid regions, so this paper selects the urban agglomeration of Hohhot, Baotou and Ordos (HBO) of Inner Mongolia, China as the study area. Based on the 8-day composite Moderate-resolution Imaging Spectroradiometer (MODIS) surface temperature data (156 scenes in all) and land use maps for 2005, 2010, and 2015, we analyze the spatiotemporal distributions of regional heat (cool) islands (RH(C)I) and the responses of surface temperatures to land-use changes in the diurnal and interannual surface cities. The results showed that: 1) from 2005 to 2015, urban areas showed the cold island effect during the day, with the area of the cold island showing a shrinking feature; at night, they showed the heat island effect, with the area of the heat island showing a first decrease and then an increase. 2) From 2005 to 2015, the land development (unutilized land to building land) brings the greatest temperature increase (ΔT = 1.36°C) during the day, while the greatest temperature change at night corresponds to the conversion of cultivated land to building land (ΔT = 0.78°C) exhibited the largest changes at night. From 2010 to 2015, the land development (grassland to building land) bring the greatest temperature increase (ΔT = 0.85°C) during the day, while the great temperature change at night corresponds to the conversion of water areas to building land (ΔT = 1.38°C) exhibited the largest changes at night. Exploring the spatial and temporal evolution of surface urban heat (cool) islands in urban agglomerations in arid and semiarid regions will help to understand the urbanization characteristics of urban agglomerations and provide a reference for the formulation of policies for the coordinated and healthy development of the region and co-governance of regional environmental problems. [ABSTRACT FROM AUTHOR]

Due to the unique physical properties, graphene and its derivatives are often used as the reinforcements to improve and modulate mechanical performances and dynamic behaviors of composite materials. In this paper, a semi-analytical finite element method is utilized to analyze the wave properties of functionally graded graphene-reinforced piezoelectric nanocomposite cylindrical shells with graphene agglomeration effects. The effective micromechanics model, the first-order shear deformation shell theory, and the Hamiltonian principle are organically intergrated to derive the wave equation to analyze the modulation of wave propagation of functionally graded graphene-reinforced piezoelectric nanocomposite cylindrical shells by regulating agglomeration effects. The results indicate that the decrease in volume fraction of agglomeration phase and the raising of the amount of graphene sheets in agglomeration phase lead to the reduction of phase and group velocities and hinder the transmission of waves and wave energy. The higher the graphene total volume fraction, the more obvious the influence of the agglomeration effects on the structural wave properties. Meanwhile, it is found that the agglomeration effects can inhibit the modulation of the concentration and functional gradient distribution patterns of graphene on the wave properties. It is noted that the center conversion frequency of out-of-plane modes and the group velocity of the conversion intersection point of out-of-plane modes are sensitive to agglomeration effects, the values of the center conversion frequency and the group velocity of the conversion intersection point increase with the weakening of the agglomeration effects. This work can provide guidance and new thought for the design of smart nanocomposites and the application of elastic wave characteristics in non-destructive testing. [ABSTRACT FROM AUTHOR]

The thermal conditions that prevail in cities pose a number of challenges to urban residents and policy makers related to quality of life, health and welfare as well as to sustainable urban development. However, the changes in thermal stress due to climate change are probably not uniform among cities with different background climates. In this work, a comparative analysis of observed and projected thermal stress (cold stress, heat stress, no thermal stress) across four European cities (Helsinki, Rotterdam, Vienna, and Athens), which are representative of different geographical and climatic regions of the continent, for a recent period (1975 − 2004) and two future periods (2029 − 2058, 2069 − 2098) has been conducted. Applying a rational thermal index (Universal Thermal Climate Index) and considering two models of the EURO-CORDEX experiment (RCA4-MOHC, RCA4-MPI) under two Representative Concentration Pathways (RCP4.5, RCP8.5), the projected future changes in thermal conditions are inspected. The distribution of thermal stress in the current climate varies greatly between the cities, reflecting their climatic and urban heterogeneity. In the future climate, a reduction in the frequency of cold stress is expected across all cities, ranging between − 2.9% and − 16.2%. The projected increase in the frequency of optimal thermal conditions increases with increasing latitude, while the projected increase in the frequency of heat stress (ranging from + 0.2 to + 14.6%) decreases with increasing latitudes. Asymmetrical changes in cold- and heat-related stress between cities were found to affect the annual percentage of optimal (no thermal stress) conditions in future. Although future projections are expected to partly bridge the gap between the less-privileged cities (with respect to annual frequency of optimal thermal conditions) like Helsinki and Rotterdam and the more privileged ones like Athens, the former will still lag behind on an annual basis. [ABSTRACT FROM AUTHOR]

Actor-level data on large-scale commercial agriculture in Sub-Saharan Africa are scarce. The peculiar choice of transnational investing in African land has, therefore, been subject to conjecture. Addressing this gap, we reconstructed the underlying logics of investment location choices in a Bayesian network, using firm- and actor-level interview and spatial data from 37 transnational agriculture and forestry investments across 121 sites in Mozambique, Zambia, Tanzania, and Ethiopia. We distinguish four investment locations across gradients of resource frontiers and agglomeration economies to derive the preferred locations of different investors with varied skillsets and market reach (i.e., track record). In contrast to newcomers, investors with extensive track records are more likely to expand the land use frontier, but they are also likely to survive the high transaction costs of the pre-commercial frontier. We highlight key comparative advantages of Southern and Eastern African frontiers and map the most probable categories of investment locations. [ABSTRACT FROM AUTHOR]

As the leading urban agglomeration in China, the Yangtze River Delta (YRD) is experiencing a factor-driven to innovation-driven transition. However, the dynamics of regional innovation growth are not yet fully understood. This paper combines the complex network methodology with spatial econometrics to disentangle the contributions of innovation endowments, innovation network flows, and innovation network positions to regional innovation growth, as well as their spatial spillover effects. The primary findings suggest that regional innovation growth results from the networked agglomeration economies, which is shaped by the interactions between agglomeration factors and network factors. Specifically, agglomeration factors play a fundamental role in regional innovation growth. In contrast, network factors, such as the network flows and network positions, may contribute to new path creation by promoting access to external innovation resources. Additionally, the institutional factors show multiplexity in fostering regional innovation patterns. Such findings indicate that the YRD region should shift the innovation growth pattern from competitive involution to mutually beneficial cooperation to reduce regional disparities. In this regard, the institutional capacity of organizing network flows and fostering reciprocal inter-city partnerships has become increasingly critical for promoting sustainable innovation and regional development. [ABSTRACT FROM AUTHOR]

Cd1 − xMnxFe2O4 (x = 0, 0.25, 0.5, 0.75, 1) spinel ferrite nanoparticle samples were synthesized using a flash auto-combustion technique and analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier-transform infrared spectroscopy (FTIR). The inspection of dielectric and magnetic properties of the prepared ferrites was carried out by using broadband dielectric spectroscopy (BDS) and vibration sample magnetometer (VSM) measurements, respectively. X-ray diffraction analysis verified the formation of the main cubic phase with space group Fd3m and a decrease in lattice constants with the increase in Mn-content. FTIR study revealed the two characteristic absorption bands of spinel ferrites and their dependence on Mn-content was investigated and explained. Elastic moduli, bulk modulus, rigidity modulus, Young modulus, and calculated Debye temperature have been studied and found to decrease with the increase in Mn-content. SEM analysis revealed nanoparticles agglomeration of uniform grains with increasing in the average grain size as Mn-content increased. The VSM measurements showed an increase in saturation magnetization accompanied by a decrease in coercivity as Mn-content increased. Dielectric investigations showed very high values of permittivity and dielectric loss at lower frequencies (between 105 and 106 @ 0.1 Hz according to the manganese content) reflecting the combination of exchange of electrons between ferrous and ferric ions and ions' transport. The ac-conductivity showed a plateau that yields the dc-conductivity at lower frequencies followed by a characteristic frequency at which it tends out to follow a power law. The relation between these two parameters confirms the empirical BNN-relation. [ABSTRACT FROM AUTHOR]

Human settlements on Earth are scattered in a multitude of shapes, sizes and spatial arrangements. These patterns are often not random but a result of complex geographical, cultural, economic and historical processes that have profound human and ecological impacts. However, little is known about the global distribution of these patterns and the spatial forces that creates them. This study analyses human settlements from high-resolution satellite imagery and provides a global classification of spatial patterns. We find two emerging classes, namely agglomeration and dispersion. In the former, settlements are fewer than expected based on the predictions of scaling theory, while an unexpectedly high number of settlements characterizes the latter. To explain the observed spatial patterns, we propose a model that combines two agglomeration forces and simulates human settlements' historical growth. Our results show that our model accurately matches the observed global classification (F1: 0.73), helps to understand and estimate the growth of human settlements and, in turn, the distribution and physical dynamics of all human settlements on Earth, from small villages to cities. [ABSTRACT FROM AUTHOR]

Rapid urbanization leads to dramatic changes in land use patterns, and the land use/cover change (LUCC) can reflect the spatial impact of urbanization on the ecological environment. Simulating the process of LUCC and predicting the ecological risk future changes can provide supports for urban ecological management. Taking the Yangtze River Delta Urban Agglomeration (YRDUA), China as the study area, four developmental scenarios were set on the basis of the land use data from 2005 to 2015. The temporal land use changes were predicted by the integration of the system dynamic and the future land use simulation (SD-FLUS) model, and the geographically weighted regression (GWR) model was used to identify the spatial heterogeneity and evolution characteristics between ecological risk index (ERI) and socio-economic driving forces. Results showed that: 1) From 2005 to 2015, the expansion of construction land (7670.24 km2) mainly came from the occupation of cultivated land (7854.22 km2). The Kappa coefficient of the SD-FLUS model was 0.886, indicating that this model could be used to predict the future land use changes in the YRDUA. 2) Gross domestic production (GDP) and population density (POP) showed a positive effect on the ERI, and the impact of POP exceeded that of GDP. The ERI showed the characteristics of zonal diffusion and a slight upward trend, and the high ecological risk region increased by 6.09%, with the largest increase. 3) Under different developmental scenarios, the land use and ecological risk patterns varied. The construction land is increased by 5.76%, 7.41%, 5.25% and 6.06%, respectively. And the high ecological risk region accounted for 12.71%, 15.06%, 11.89%, and 12.94%, correspondingly. In Scenario D, the structure of land use and ecological risk pattern was better compared with other scenarios considering the needs of rapid economic and ecological protection. This study is helpful to understand the spatio-temporal pattern and demand of land use types, grasp the ecological security pattern of large-scale areas, and provide scientific basis for the territory development of urban agglomeration in the future. [ABSTRACT FROM AUTHOR]

Ranking firms in an inter-firm transaction network is a crucial task for identifying key players in an industry, thereby explaining the agglomeration of economic activities and assisting with competitor identification. To the best of our knowledge, despite the advantages of network-based approaches in market analysis, few studies have employed network analysis tools to rank firms. However, these studies failed to capture the characteristics of inter-firm transaction networks (i.e., evolving over time, having multiple edges between nodes, among others). In this study, we propose a new ranking method, FirmRank, that identifies key players based on centrality metrics in network analysis, leveraging inter-firm transactions to discern the characteristics of an inter-firm transaction network. Our proposed ranking method is evaluated using real-world datasets from a corporate information database, and the evaluation results demonstrate the superiority of our method over well-known ranking methods—PageRank and age-based PageRank. [ABSTRACT FROM AUTHOR]

Formal models of appearance and reality have proved fruitful for investigating structural properties of perceptual knowledge. This paper applies the same approach to epistemic justification. Our central goal is to give a simple account of The Preface, in which justified belief fails to agglomerate. Following recent work by a number of authors, we understand knowledge in terms of normality. An agent knows p iff p is true throughout all relevant normal worlds. To model The Preface, we appeal to the normality of error. Sometimes, it is more normal for reality and appearance to diverge than to match. We show that this simple idea has dramatic consequences for the theory of knowledge and justification. Among other things, we argue that a proper treatment of The Preface requires a departure from the internalist idea that epistemic justification supervenes on the appearances and the widespread idea that one knows most when free from error. [ABSTRACT FROM AUTHOR]

Although technology innovation management has been extensively studied, little research has been conducted in nanotechnology-focused innovation management. No model currently exists on nanotechnology innovation management and the related critical success factors. Based on a literature review of nanotechnology characteristics and reported successful nanotechnology research, six essential factors of success were identified. These factors are consumer acceptance of nanotechnology, hybridisation of nanotechnology innovations into existing industries and markets, multidisciplinary project teams, agglomeration and clustering of nanotechnology research projects, research and development (R&D) and commercialisation skills and capabilities, and working within a conducive innovation environment. These six factors were crystallised into the "Nanotechnology Innovation Diamond", a model for successful nanoscience research and development. The proposed model was then validated using confirmatory factor analysis (CFA) from a survey of 167 nanotechnology experts from South Africa. The results indicate that at 95% confidence level, the proposed model satisfied the minimum CFA model fit requirements, and the six proposed critical success factors are significant for successful nanotechnology R&D. The presented model can be used to increase the rate of success of nanotechnology R&D projects, nanotechnology project portfolio selection, and nanotechnology foresight exercises. [ABSTRACT FROM AUTHOR]

With economic development and rapid urbanization, increases in Gross Domestic Product and population in fast-growing cities since the turn of the 21st Century have led to increases in energy consumption. Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events. To investigate the effects of energy consumption on urban extreme temperature events, including extreme heat and cold events, a dynamic representation scheme of anthropogenic heat release (AHR) was implemented in the Advanced Research version of the Weather Research and Forecasting (WRF) model, and AHR data were developed based on energy consumption and population density in a case study of Beijing, China. Two simulations during 1999–2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme. It was shown that the mean temperature increased with the increase in AHR, and more frequent extreme heat events were produced, with an annual increase of 0.02–0.19 days, as well as less frequent extreme cold events, with an annual decrease of 0.26–0.56 days, based on seven extreme temperature indices in the city center. AHR increased the sensible heat flux and led to surface energy budget changes, strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter. In addition, it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of urbanization is essential to the sustainable development of cities. Meanwhile the analysis of urban development can also provide scientifically and effective information for decision-making. With the long-term Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) nighttime light images, a pixel level assessment of urbanization of China from 1992 to 2013 was conducted in this study, and the spatio-temporal dynamics and future trends of urban development were fully detected. The results showed that the urbanization and urban dynamics of China experienced drastic fluctuations from 1992 to 2013, especially for those in the coastal and metropolitan areas. From a regional perspective, it was found that the urban dynamics and increasing trends in North Coast China, East Coast China and South Coast China were much more stable and significant than that in other regions. Moreover, with the sustainability estimating of nighttime light dynamics, the regional agglomeration trends of urban regions were also detected. The light intensity in nearly 50% of lighted pixels may continuously decrease in the future, indicating a severe situation of urbanization within these regions. In this study, The results revealed in this study can provided a new insight in long time urbanization detecting and is thus beneficial to the better understanding of trends and dynamics of urban development. [ABSTRACT FROM AUTHOR]

Recent intensification of urban heat islands (UHIs) poses a great threat to public health, promoting studies on UHI mitigation strategies. However, the question about the transferability of a mitigation method from a specific city to another remains largely unanswered. This study compares common UHI mitigation strategies (including green roofs, cool roofs, and changing urban building structure) for two Chinese megacities suffered from summer heat stress: Xi'an with a semi-humid climate and Wuhan with a humid climate, through the use of the urbanized-high-resolution land data assimilation system (u-HRLDAS) modeling tool and remote-sensing data. The results reveal that (1) all UHI mitigation strategies work more efficiently for Xi'an than that for Wuhan, particularly for the strategy of modifying urban fraction and associated green roof fraction; (2) the difference in cooling efficacy between the two cities is insignificant during relatively cool periods. Under hot weather conditions, the best choice of UHI mitigation strategy depends on urban land use categories in Xi'an; and (3) the differences in UHI mitigation efficacy are likely caused by the differing regional climate. This study highlights the need to better understand the transferability of UHI mitigation strategies in different climate zones. [ABSTRACT FROM AUTHOR]

We analyze the spatio-temporal agglomeration dynamics that occurred in the Italian manufacturing industry during the recent period of the Great Recession. To study this phenomenon, we employ three different statistical methods—namely, Ellison and Glaeser's index of industrial geographic concentration, the spatial K-function, and the space–time K-function—, and rely on a large sample of geo-referenced, single-plant manufacturing firms observed over the period 2007–2012. First, we demonstrate that different statistical techniques can lead to (very) different results. Second, we find that most Italian manufacturing sectors experienced spatial dispersion processes during the period of the Great Recession. Finally, we show that space–time dispersion processes occurred at small spatial distances and short time horizon, although we do not detect statistically significant space–time interactions. [ABSTRACT FROM AUTHOR]

Using micro data from the 2010 National Survey on Households’ Budget, Consumption and Standard of Living, this study aims to investigate main factors contributing to poverty distribution, one of the most severe socioeconomic problems in Tunisia. To this end, we use a multilevel Logit model and a multilevel mixed linear model to simultaneously analyze the micro-level (household) and macro-level (governorate) factors that might affect the household poverty status. Household size, household composition, occupation, education levels, the gender of the household head and the number of earner by household variables were assessed at the micro-level. Unemployment rate, poverty rate, industrial and agriculture parts and the migration are included to control the effect of contextual effects. Our findings showed that the likelihood of household being poor is positively and significantly related to household size, more children and lower education level. Extreme poverty is more likely to occur in rural than urban areas. Macro-level analyses indicated that greater neighbourhood unemployment rate was associated with higher odds of poverty, while greater industrial agglomeration and migration balance were associated with reduced odds of poverty. [ABSTRACT FROM AUTHOR]

This paper analyses region-level technical efficiency in nine European countries over the 1995-2007 period. We propose the application of a nonparametric conditional frontier approach to account for the presence of heterogeneous conditions in the form of geographical externalities. Such environmental factors are beyond the control of regional authorities, but may affect the production function. Therefore, they need to be considered in the frontier estimation. Specifically, a spatial autoregressive term is included as an external conditioning factor in a robust order- m model. Thus we can test the hypothesis of non-separability (the external factor impacts both the input-output space and the distribution of efficiencies), demonstrating the existence of significant global interregional spillovers into the production process. Our findings show that geographical externalities affect both the frontier level and the probability of being more or less efficient. Specifically, the results support the fact that the spatial lag variable has an inverted U-shaped non-linear impact on the performance of regions. This finding can be interpreted as a differential effect of interregional spillovers depending on the size of the neighboring economies: positive externalities for small values, possibly related to agglomeration economies, and negative externalities for high values, indicating the possibility of production congestion. Additionally, evidence of the existence of a strong geographic pattern of European regional efficiency is reported and the levels of technical efficiency are acknowledged to have converged during the period under analysis. [ABSTRACT FROM AUTHOR]

During the past two decades, the exhibition industry in China has been developing rapidly and has become an important part of the modern service industry, particularly the agglomeration characteristics of exhibition enterprises highlighted on the regional scale. Although the development of theoretical research on the western exhibition industry has taken place over time, the spatial perspective has not been at the centre of attention so far. This paper aims to fill this gap and report on the agglomeration characteristics of exhibition enterprises and their influential factors. Based on data about exhibition enterprises in the Pearl River Delta (PRD) during 1991-2013, using the Ripley K function analysis and kernel density estimation, this research identifies that: 1) the exhibition enterprise on the regional scale is significantly characterized by spatial agglomeration, and the agglomeration density and scale are continuously increasing; 2) the spatial pattern of agglomeration has developed from a single-center to multi-center form. Meanwhile, this paper profiles the factors influencing the spatial agglomeration of exhibition enterprises by selecting the panel data of nine cities in the PRD in 1999, 2002, 2006 and 2013. The results show that market capacity, urban informatization level and exhibition venues significantly influence the location choice of exhibition enterprises. Among them, the market capacity is a variable that exerts a far greater impact than other factors do. [ABSTRACT FROM AUTHOR]

In this paper, we put forth the view that the potential for urbanization economies increases with interaction opportunities. From that premise follow three fundamental properties that an agglomeration index should possess: (1) to increase with the concentration of population and conform to the Pigou-Dalton transfer principle; (2) to increase with the absolute size of constituent population interaction zones; and (3) to be consistent in aggregation. Limiting our attention to pairwise interactions, and invoking the space-analytic foundations of local labor market area (LLMA) delineation, we develop an index of agglomeration based on the number of interaction opportunities per capita in a geographical area. This leads to Arriaga's mean city-population size, which is the mathematical expectation of the size of the LLMA in which a randomly chosen individual lives. The index has other important properties. It does not require an arbitrary population threshold to separate urban from non-urban areas. It is easily adapted to situations where an LLMA lies partly outside the geographical area for which agglomeration is measured. Finally, it can be satisfactorily approximated when data is truncated or aggregated into size-classes. We apply the index to the Spanish NUTS III regions, and evaluate its performance by examining its correlation with the location quotients of several knowledge intensive business services known to be highly sensitive to urbanization economies. The Arriaga index's correlations are clearly stronger than those of either the classical degree of urbanization or the Hirshman-Herfindahl concentration index. [ABSTRACT FROM AUTHOR]

This paper presents a novel density based agglomerative clustering algorithm named TOBAE which is a parameter-less algorithm and automatically filters noise. It finds the appropriate number of clusters while giving a competitive running time. TOBAE works by tracking the cumulative density distribution of the data points on a grid and only requires the original data set as input. The clustering problem is solved by automatically finding the optimal density threshold for the clusters. It is applicable to any N-dimensional data set which makes it highly relevant for real world scenarios. The algorithm outperforms state of the art clustering algorithms by the additional feature of automatic noise filtration around clusters. The concept behind the algorithm is explained using the analogy of puddles (' tobae'), which the algorithm is inspired from. This paper provides a detailed algorithm for TOBAE along with the complexity analysis for both time and space. We show experimental results against known data sets and show how TOBAE competes with the best algorithms in the field while providing its own set of advantages. [ABSTRACT FROM AUTHOR]

Where firms cluster together, there are efficiency gains from outsourcing, labour pooling and knowledge spillovers. Earlier research into agglomeration in South Africa focussed on sub-national regions and found that capital stock, human capital, access to markets and exports are significant determinants of output growth. This paper examines whether location explains differences in efficiency at firm level. Data from the 2003 and 2007 World Bank Enterprise Surveys allow one to examine firms in the four major South African cities. This paper reports estimates of a firm-level production function that incorporates location-specific explanatory variables to examine the scope of agglomeration economies. The place-specific size of the home market, level of education and share of exports are found to be positively related to output per worker at firm level. A description of the survey data identifies possible indicators of the sources of agglomeration economies. The size and significance of the inland Gauteng Province's economy is reflected in its firms' use of intermediate inputs and skilled labour. [ABSTRACT FROM AUTHOR]