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Global flood risk maps combine data from hydrodynamic models with gridded population or GDP data to estimate the amount of people or wealth likely to be exposed to future flood events. These estimates rarely incorporate measures of social vulnerability, which is a key source of variation in outcomes for exposed populations. They also use arbitrary return period thresholds, which can disguise potentially catastrophic hazards. To address these limitations, we integrate annual average exceedance probability estimates from a high-resolution (~90m) flood model with gridded population and economic data to create a global vulnerability-adjusted risk index for flooding (VARI Flood). This human welfare-centred approach radically alters how we perceive the geography of risk and could be used as a complement to traditional population or asset-centred approaches. We present global results for both unadjusted and vulnerability-adjusted risk at the subnational (Admin 2) level; country case studies illustrate how accounting for vulnerability changes the perceived subnational geography of risk. Globally, adjusting for vulnerability significantly reduces the total number of people estimated to be at ‘high risk’ from over 575 million to about 117 million. However, this latter estimate is likely an underestimate given the relatively coarse resolution of the economic data available, which disguises variation in vulnerability between communities within large cities and urban regions. Given the increasing concentration of the global human population in cities, there is an urgent need to improve the resolution of vulnerability mapping within large human settlements to inform mitigation measures.

Global flood risk maps combine data from hydrodynamic models with gridded population or GDP data to estimate the amount of people or wealth likely to be exposed to future flood events. These estimates rarely incorporate measures of social vulnerability, which is a key source of variation in outcomes for exposed populations. To address this lacuna, we integrate annual average exceedance probability estimates from a high-resolution (~90m) flood model with gridded population and economic data to create a global vulnerability-adjusted risk index for flooding (VARI Flood). Designed for decision makers, this approach radically alters how we perceive the geography of risk by identifying ‘hotspots’ characterised by high population density and high levels of social vulnerability. VARI Flood could be used as a complement to traditional population or asset-centred approaches. Our results also highlight the urgent need to improve social vulnerability mapping within cities and rapidly urbanizing regions.

We are living through a global urban transition, but the timing of this transition has varied significantly across countries and regions. This geographic variation in timing matters, both theoretically and substantively. Yet contemporary debates on urbanism hinge primarily on questions of universalism versus particularism, at the expense of attention to how history and geography collide to shape urban processes. Specifically, they neglect the critical fact that urbanisation in many countries today is late within the context of the global urban transition. We argue that trajectories of contemporary urbanisation must be understood in relation to a suite of conditions unique to the late 20th and early 21st centuries and partly shaped by early urbanisation, including historically unprecedented demographic intensity, hyperglobalisation, centripetal state politics and the spectre of environmental catastrophe in the late Anthropocene. These factors condition the range of possibilities for late urbanisers in ways that did not apply to early urbanisers yet can also produce diverse outcomes depending on local circumstances. We draw on a comparison between countries in sub-Saharan Africa and China to illustrate why the conditions of late urbanisation matter, but also why they have produced highly variable outcomes and are not deterministic of urban futures.

The quintessence of urbanity is a sustained geographic concentration of strangers. Physical congregation—or corporeal copresence—has wide-ranging environmental and social consequences that produce urban contexts. In practical terms, this means that demographic criteria alone are sufficient to classify a location, settlement, or region as more or less urban. We use a series of thought experiments to demonstrate the conceptual limitations of popular definitions of urbanity, such as the economic structure of a community, the presence of physical infrastructure, the political or administrative status of a geographic unit, or the degree of connectivity between people. We show that these are not essential to what makes a place urban but are instead common epiphenomena associated with places that have a sustained geographic concentration of strangers. This definition does not require a settlement to be permanent, allowing for ephemeral urbanity (dense but temporary settlements), resolving many classic exceptions to previous definitions of urbanity. We suggest that urbanity is best conceptualised and measured on a continuum and discuss how this can be done empirically to advance our theoretical and practical understanding of urban places and urban systems globally.

In the previous two reports in this series, we discussed the history and current status of quantitative geography. In this final report, we focus on the future. We argue that quantitative geographers are most helpful when we can simplify difficult problems using our distinct domain expertise. To do this, we must clarify the theory underpinning core conceptual problems in quantitative geography. Then, we examine the social forces that are shaping the future of quantitative geography. We conclude with criteria for how quantitative geography might succeed in addressing these challenges.

Binarized neural networks (BNNs) have shown exciting potential for utilising neural networks in embedded implementations where area, energy and latency constraints are paramount. With BNNs, multiply-accumulate (MAC) operations can be simplified to XnorPopcount operations, leading to massive reductions in both memory and computation resources. Furthermore, multiple efficient implementations of BNNs have been reported on field-programmable gate array (FPGA) implementations. This paper proposes a smaller, faster, more energy-efficient approximate replacement for the XnorPopcountoperation, called XNorMaj, inspired by state-of-the-art FPGAlook-up table schemes which benefit FPGA implementations. Weshow that XNorMaj is up to 2x more resource-efficient than the XnorPopcount operation. While the XNorMaj operation has a minor detrimental impact on accuracy, the resource savings enable us to use larger networks to recover the loss., 4 pages

The global urban population is expected to grow by 2.5 billion over the next three decades, and 90% of this growth will occur in African and Asian countries. Urban expansion in these regions is often characterised by ‘informal urbanization’ whereby households self-build without planning permission in contexts of ambiguous, insecure or disputed property rights. Despite the scale of informal urbanization, it has received little attention from scholars working in the domains of urban analytics and city science. Towards addressing this gap, we introduce TI-City, an urban growth model designed to predict the locations, legal status and socio-economic status of future residential developments in an African city. In a bottom-up approach, we use agent-based and cellular automata modelling techniques to predict the geospatial behaviour of key urban development actors, including households, real estate developers and government. We apply the model to the city-region of Accra, Ghana, drawing on local data collection, including a household survey, to parameterise the model. Using a multi-spatial-scale validation technique, we compare TI-City’s ability to simulate historically observed built-up patterns with SLEUTH, a highly popular urban growth model. Results show that TI-City outperforms SLEUTH at each scale, suggesting the model could offer a valuable decision support tool in similar city contexts.

Low-precision training for Deep Neural Networks(DNN) has recently become a viable alternative to standard full-precision algorithms. Crucially, low-precision computation reduces both memory usage and computational cost, providing more scalability for Field Programmable Gate Arrays (FPGAs) with limited on-chip memory. In this paper, we describe and test a prototype training accelerator for Zynq All Programmable System on Chip (APSoC) devices using predominantly 8-bit integer numbers. Block floating-point quantisation and stochastic weight averaging techniques are applied during training toavoid any degradation in accuracy. Results of an implementation reveal memory savings and 17x speed-ups over processor only systems on several training tasks including the MNIST and CIFAR10 benchmarks, and online radio-frequency anomaly detection. Moreover, we propose modifications to the stochastic weight averaging low-precision (SWALP) algorithm to achieve a0.5% accuracy improvement for the abovementioned benchmarks with results within 0.1% of floating-point. We suggest that both inference and training can be deployed in the same package for stand-alone embedded applications.

The city of Yangon is home to over 5 million people, hosts Myanmar's largest port and produces a disproportionate share of national output. But a mobility crisis is undermining the city's economic potential and contributing to a deteriorating quality of life for its residents. The most obvious symptom of this crisis is acute traffic congestion. The proximate causes are clear: growing demand for journeys, a surge in vehicle numbers, a modal shift away from buses, and myriad ‘flow disruptions’. However, solving this mobility crisis requires recognizing the underlying causes, including a ‘congestion incentive spiral’ fuelled by rapid liberalisation of vehicle imports in a context where there are few viable alternatives to buses and private automobiles. This situation is a direct consequence of systematic failures in urban planning, investment and regulation linked to active neglect from successive military regimes and dysfunctional institutional arrangements. To preserve its rich urban heritage, Yangon will need to embrace 21st century integrated planning practices that seek to maximise accessibility and mobility for all people rather than minimise traffic congestion for those who use cars.

The stylized facts of Africa's urban transition highlight the limitations of traditional economic models of urbanization. Recent research has provided evidence that demographic rather than economic processes provide a more compelling explanation for observed trends in the region. In particular, mortality decline appears to be both a necessary and sufficient condition for urbanization to occur and a key driver of urban growth more broadly. The accumulation of survey data over the past few decades and the development of new geospatial datasets that incorporate satellite imagery are facilitating new, more spatially nuanced insights into the dynamics of urban population change in the region. This offers opportunity to develop better policies for managing urban change than those adopted in the past, which placed a misguided emphasis on manipulating migration incentives with little evidence of positive benefits.

OBJECTIVES: The gut microbiota and its metabolites – namely short chain volatile fatty acids (SCVFAs) – interact with the digestive, immune, and nervous systems. States of microbiome dysbiosis are highly associated with obesity and GI symptoms, and profiles of SCVFAs, which serve functions as fuel sources and signaling molecules, mimic this dysbiotic state. This study aimed to further our understanding of associations between bacterial diversity and GI symptoms, BMI, immune markers, and SCVFAs and to identify bacteria differentially abundant with changes to the previously mentioned variables. METHODS: Data (measures of GI distress, BMI, immunoglobulins, fecal proximate analysis, SCVFAs, and 16s RNA sequences) was extracted from a study containing non-celiac gluten-sensitive and control participants. QIIME2 was used to process 16s RNA data, analyze quantitative, qualitative, phylogenetic quantitative, and phylogenetic qualitative measures of alpha and beta diversity and to perform an analysis of composition of microbes (ANCOM) for differential abundances data. RESULTS: Many significant differences were seen, namely in multiple measures of alpha diversity for IgG4 (P

Nigeria contains some of Africa’s oldest and newest cities, hosts five of the 30 largest urban settlements on the continent, and is estimated to have the biggest urban population on the continent. Yet many of the basic ‘facts’ about spatial-demographic trends in Nigeria have been contested. Most recently, an article published in World Development in 2012 claimed that urbanisation had stalled in Nigeria. In an effort to establish and explain the stylised facts of Nigeria’s urban transition we analyse demographic and spatial trends drawing on diverse sources, including censuses, household surveys, remotely sensed data and migration studies conducted over the past three decades. The evidence does not support the claim of stalled urbanisation: Nigeria’s urban population is growing rapidly in absolute terms and will continue to increase as a share of the national population because of both rural–urban migration and rural transformation. These drivers of urbanisation are a product of persistently high fertility in a context of declining mortality in both rural and urban areas. Robust economic growth over the past decade likely accelerated urbanisation, but even as the economy slows demographic fundamentals will continue to drive rapid urban growth and urbanisation.

In this paper, we describe a systolic Field Programmable Gate Array (FPGA) implementation of the Fastfood algorithm that is optimised to run at a high frequency. The Fastfood algorithm supports online learning for large scale kernel methods. Empirical results show that 500 MHz clock rates can be sustained for an architecture that can solve problems with input dimensions that are $10^3$ times larger than previously reported. Unlike many recent deep learning publications, this design implements both training and prediction. This enables the use of kernel methods in applications requiring a rare combination of capacity, adaption and speed.

We argue that Frey’s proposals are utopian and impractical, focusing on four key issues: the complexity of decision-making; politicians’ and technocrats’ importance in decision making processes; reconciling the geography of political rights in a globalising world; and recognizing how power frames political discourse and outcomes.

Over 800 million people in Africa, Asia, and Latin America live in slums. Why? I argue that slums are a result of “disjointed modernization” and show that 70% of cross-country variation in slum incidence is explained by demographic, economic, and institutional factors. I trace the origins of disjointed modernization in sub-Saharan Africa back to the colonial period and show that colonial era investments and institutions are reflected in contemporary variation in slum incidence. I argue that status quo interests and the rise of an anti-urbanization bias in development discourse have inhibited investment and reform in the postcolonial era.

OBJECTIVES: This research project focused on the inhibitory effectiveness of a novel antimicrobial gel (AMG) towards a panel of common microbes involved in wound infections. METHODS: A novel antimicrobial topical gel consisting of vitamin E TPGS (tocopherol polyethylene glycol succinate), ascorbyl palmitate, zinc aspartate, lavender oil and deionized distilled water was developed in our laboratory. Various in vitro techniques were used to determine the effectiveness of AMG on prokaryotic and eukaryotic microbes. RESULTS: In vitro experiments show that while AMG had varying inhibitory effects on both prokaryotic and eukaryotic microbes, there was a predilection for AMG to inhibit planktonic growth and biofilm formation of Staphylococcus species, most notably Methicillin Resistant Staphylococcus aureus (MRSA). The inhibitory effect of the AMK on planktonic growth was immediate with a four-fold reduction in growth, compared to controls, within 4 to 6 hrs of induction. Within 24 hrs S. aureus growth was minimal and complete inhibition of growth was achieved within 48 hrs. In an in vitro biofilm model, the AMG inhibited Staphylococcus biofilm attachment by 67% (density), 82% (mass) and 95% (viability). On pre-formed established biofilms, the AMG was able to inhibit 47% (density), 47% (mass) and 44% (viability) Staphylococcus biofilms. Antibiotic comparison experiments demonstrated that the MIC (minimum inhibitory concentration) of Mupirocin was

OBJECTIVES: Chronic gastrointestinal distress (GID) effects up to 33.8% of people and results in over 15 million outpatient visits in the US annually. Currently, probiotic and prebiotic supplements are recommended by physicians, dietitians, and other healthcare providers to normalize GI function and to mitigate symptoms associated with certain disease states. GlutenShield (GS) is a commercially available nutritional supplement designed to contain an appropriate balance of pre- and probiotics as well as digestive enzymes to improve symptoms associated with GID. The aim of this study was to determine the tolerance to and/or benefits of GS supplementation on adults with GID. METHODS: This was a partially blinded pilot study in which all subjects completed a 2-week washout and were then randomized to receive GS or the placebo 3 times/day with meals. Participants completed a pre-treatment FFQ as well as a pre- and post-treatment GID questionnaire, POMS questionnaire, blood draw, and stool sample. RESULTS: No differences between placebo and treatment groups were found for serum inflammatory cytokines or fecal volatile fatty acids (area % or concentration) (P > 0.05). A significant reduction in IgG2 was observed in the GS group (7110.4 vs 4185.56; P = 0.008) as well as a significant reduction in self-reported bloating (P = 0.038) and approaching significant reduction in total GID (P = 0.083). Fecal insoluble dietary fiber (IDF) percentage significantly increased in the placebo group (P = 0.012), with no change in the GS group (P > 0.05). CONCLUSIONS: Research findings suggest that GS was well tolerated and perceived to be beneficial compared to placebo; however, further research is needed to identify the specific patient population of GID patients who could most benefit from GS supplementation. Future analysis of microbiome data of subjects could provide additional insight. Clinical trial ID: NCT03403387. FUNDING SOURCES: ETSU (CCRHS, Dean's Research Enhancement Award and CPH, Health Sciences Funding) and Shield Nutraceuticals, LLC.

The distribution of voting rights in the UK is an artefact of history rather than a product of clear legal or philosophical principles. Consequently, some resident aliens (i.e. immigrants) have the right to vote in all UK elections; others can vote in local elections but are excluded from national elections; still others are excluded from all elections. In England and Wales alone, roughly 2.3 million immigrants are excluded from voting in national elections. This exclusion is inconsistent with the founding principle of democracy and distorts political discourse. What if all immigrants could vote in national elections? We estimate that up to ninety-five parliamentary seats could have been won by a different party in the 2015 general election. More substantially, enfranchising all immigrants would require re-drawing UK constituency boundaries. The new electoral map would increase the relative power of urban constituencies and would incentivise some political entrepreneurs and parties to temper anti-immigration rhetoric.

Urbanization has long been seen by scholars and policymakers as a disruptive process that can contribute to social and political unrest, yet there is little cross-national quantitative empirical research on the topic. In this paper we provide a comprehensive analysis of the links between urban geography and the incidence of protests (i.e. demonstrations, riots and strikes) in African countries since 1990. In contrast to previous studies, we are careful to distinguish between urban population scale effects, urban population ratio effects, population rate-of-change effects and urban population distribution effects. We also provide an explicit test of the long-standing hypothesis that ‘over-urbanization’ increases the risk of civil unrest. Employing multilevel negative binomial models that control for key political and economic variables we find that urban population size and the number of large cities in a country are both positively and significantly associated protest incidence. By contrast, we find that a country's level of urbanization is negatively associated with protest incidence and reject the over-urbanization hypothesis: higher levels of urbanization are associated with less frequent protests at all income levels. We find no evidence that the pace of urban population growth or urban primacy significantly influence protest mobilization. In sum, our results provide a nuanced picture of the relationship between urban geography and protest incidence that challenges conventional wisdom and contemporary hyperbole about the dangers of ‘rapid urbanization’ in Africa in particular, and developing countries more generally.