Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Using city gates as a means of estimating ancient traffic flows.

ABSTRACT: Despite the recent flurry of interest in various aspects of ancient urbanism, we still know little about how much traffic flowed in and out of ancient cities, in part because of problems with using commodities as proxies for trade. This article investigates another approach, which is to estimate these flows from the built environment, concentrating on transport infrastructure such as city gates. To do this, I begin by discussing a new model for how we would expect this kind of infrastructure to expand with population, before investigating the relationship between the populations of sites and the total numbers and widths of city gates, focusing on the Greek and Roman world. The results suggest that there is indeed a systematic relationship between the estimated populations of cities and transport infrastructure, which is entirely consistent with broader theoretical and empirical expectations. This gives us a new way of exploring the connectivity and integration of ancient cities, contributing to a growing body of general theory about how settlements operate across space and time.

SUBMITTER: Hanson JW

PROVIDER: S-EPMC7046228 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Using city gates as a means of estimating ancient traffic flows.

Hanson J W JW

PloS one 20200227 2

Despite the recent flurry of interest in various aspects of ancient urbanism, we still know little about how much traffic flowed in and out of ancient cities, in part because of problems with using commodities as proxies for trade. This article investigates another approach, which is to estimate these flows from the built environment, concentrating on transport infrastructure such as city gates. To do this, I begin by discussing a new model for how we would expect this kind of infrastructure to ...[more]

PMID: 32107498

Similar Datasets

Predicting subway passenger flows under different traffic conditions.

Project description:Passenger flow prediction is important for the operation, management, efficiency, and reliability of urban rail transit (subway) system. Here, we employ the large-scale subway smartcard data of Shenzhen, a major city of China, to predict dynamical passenger flows in the subway network. Four classical predictive models: historical average model, multilayer perceptron neural network model, support vector regression model, and gradient boosted regression trees model, were analyzed. Ordinary and anomalous traffic conditions were identified for each subway station by using the density-based spatial clustering of applications with noise (DBSCAN) algorithm. The prediction accuracy of each predictive model was analyzed under ordinary and anomalous traffic conditions to explore the high-performance condition (ordinary traffic condition or anomalous traffic condition) of different predictive models. In addition, we studied how long in advance that passenger flows can be accurately predicted by each predictive model. Our finding highlights the importance of selecting proper models to improve the accuracy of passenger flow prediction, and that inherent patterns of passenger flows are more prominently influencing the accuracy of prediction.

| S-EPMC6110475 | biostudies-literature

Estimating evolutionary rates in giant viruses using ancient genomes.

Project description:Pithovirus sibericum is a giant (610 Kpb) double-stranded DNA virus discovered in a purportedly 30,000-year-old permafrost sample. A closely related virus, Pithovirus massiliensis, was recently isolated from a sewer in southern France. An initial comparison of these two virus genomes assumed that P. sibericum was directly ancestral to P. massiliensis and gave a maximum evolutionary rate of 2.60 × 10-5 nucleotide substitutions per site per year (subs/site/year). If correct, this would make pithoviruses among the fastest-evolving DNA viruses, with rates close to those seen in some RNA viruses. To help determine whether this unusually high rate is accurate we utilized the well-known negative association between evolutionary rate and genome size in DNA microbes. This revealed that a more plausible rate estimate for Pithovirus evolution is ?2.23 × 10-6 subs/site/year, with even lower estimates obtained if evolutionary rates are assumed to be time-dependent. Hence, we estimate that Pithovirus has evolved at least an order of magnitude more slowly than previously suggested. We then used our new rate estimates to infer a time-scale for Pithovirus evolution. Strikingly, this suggests that these viruses could have diverged at least hundreds of thousands of years ago, and hence have evolved over longer time-scales than previously suggested. We propose that the evolutionary rate and time-scale of pithovirus evolution should be reconsidered in the light of these observations and that future estimates of the rate of giant virus evolution should be carefully examined in the context of their biological plausibility.

| S-EPMC5829572 | biostudies-literature

City structure shapes directional resettlement flows in Australia.

Project description:Modern urban science views differences in attractiveness of residential suburbs as the main driver of resettlement within a city. In particular, certain suburbs may attract residents due to lower commute costs, and this is believed to lead to compactification of a city, with highly populated central business district and sprawled suburbia. In this paper we assess residential resettlement patterns in Australian capital cities by analyzing the 2011 and 2016 Australian Census data. Rather than explicitly defining a residential attractiveness of each suburb in subjective terms, we introduce and calibrate a model which quantifies the intra-city migration flows in terms of the attractiveness potentials (and their differences), inferring these from the data. We discover that, despite the existence of well-known static agglomeration patterns favouring central districts over the suburbia, the dynamic flows that shape the intra-city migration over the last decade reveal the preference directed away from the central districts with a high density of jobs and population, towards the less populated suburbs on the periphery. Furthermore, we discover that the relocation distance of such resettlement flows plays a vital role, and explains a significant part of the variation in migration flows: the resettlement flow markedly decreases with the relocation distance. Finally, we propose a conjecture that these directional resettlement flows are explained by the cities' structure, with monocentric cities exhibiting outward flows with much higher reluctance to long-distance relocation. This conjecture is verified across the major Australian capitals: both monocentric (Sydney, Melbourne, Brisbane, Adelaide, Perth, Hobart) and polycentric (Darwin and Canberra).

| S-EPMC7237677 | biostudies-literature

Lead in ancient Rome's city waters.

Project description:It is now universally accepted that utilization of lead for domestic purposes and water distribution presents a major health hazard. The ancient Roman world was unaware of these risks. How far the gigantic network of lead pipes used in ancient Rome compromised public health in the city is unknown. Lead isotopes in sediments from the harbor of Imperial Rome register the presence of a strong anthropogenic component during the beginning of the Common Era and the Early Middle Ages. They demonstrate that the lead pipes of the water distribution system increased Pb contents in drinking water of the capital city by up to two orders of magnitude over the natural background. The Pb isotope record shows that the discontinuities in the pollution of the Tiber by lead are intimately entwined with the major issues affecting Late Antique Rome and its water distribution system.

| S-EPMC4020092 | biostudies-literature

Estimating money laundering flows with a gravity model-based simulation.

Project description:It is important to understand the amounts and types of money laundering flows, since they have very different effects and, therefore, need different enforcement strategies. Countries that mainly deal with criminals laundering their proceeds locally, need other measures than countries that mainly deal with foreign illegal investments or dirty money just flowing through the country. This paper has two main contributions. First, we unveil the country preferences of money launderers empirically in a systematic way. Former money laundering estimates used assumptions on which country characteristics money launderers are looking for when deciding where to send their ill-gotten gains. Thanks to a unique dataset of transactions suspicious of money laundering, provided by the Dutch Institute infobox Criminal and Unexplained Wealth (iCOV), we can empirically test these assumptions with an econometric gravity model estimation. We use this information for our second contribution: iteratively simulating all money laundering flows around the world. This allows us, for the first time, to provide estimates that distinguish between three different policy challenges: the laundering of domestic crime proceeds, international investment of dirty money and money just flowing through a country.

| S-EPMC7596494 | biostudies-literature

Estimating Traffic Disruption Patterns with Volunteered Geographic Information.

Project description:Accurate understanding and forecasting of traffic is a key contemporary problem for policymakers. Road networks are increasingly congested, yet traffic data is often expensive to obtain, making informed policy-making harder. This paper explores the extent to which traffic disruption can be estimated using features from the volunteered geographic information site OpenStreetMap (OSM). We use OSM features as predictors for linear regressions of counts of traffic disruptions and traffic volume at 6,500 points in the road network within 112 regions of Oxfordshire, UK. We show that more than half the variation in traffic volume and disruptions can be explained with OSM features alone, and use cross-validation and recursive feature elimination to evaluate the predictive power and importance of different land use categories. Finally, we show that using OSM's granular point of interest data allows for better predictions than the broader categories typically used in studies of transportation and land use.

| S-EPMC6985234 | biostudies-literature

Switch between critical percolation modes in city traffic dynamics.

Project description:Percolation transition is widely observed in networks ranging from biology to engineering. While much attention has been paid to network topologies, studies rarely focus on critical percolation phenomena driven by network dynamics. Using extensive real data, we study the critical percolation properties in city traffic dynamics. Our results suggest that two modes of different critical percolation behaviors are switching in the same network topology under different traffic dynamics. One mode of city traffic (during nonrush hours or days off) has similar critical percolation characteristics as small world networks, while the other mode (during rush hours on working days) tends to behave as a 2D lattice. This switching behavior can be understood by the fact that the high-speed urban roads during nonrush hours or days off (that are congested during rush hours) represent effective long-range connections, like in small world networks. Our results might be useful for understanding and improving traffic resilience.

| S-EPMC6320510 | biostudies-literature

Retroviral DNA Sequences as a Means for Determining Ancient Diets.

Project description:For ages, specialists from varying fields have studied the diets of the primeval inhabitants of our planet, detecting diet remains in archaeological specimens using a range of morphological and biochemical methods. As of recent, metagenomic ancient DNA studies have allowed for the comparison of the fecal and gut microbiomes associated to archaeological specimens from various regions of the world; however the complex dynamics represented in those microbial communities still remain unclear. Theoretically, similar to eukaryote DNA the presence of genes from key microbes or enzymes, as well as the presence of DNA from viruses specific to key organisms, may suggest the ingestion of specific diet components. In this study we demonstrate that ancient virus DNA obtained from coprolites also provides information reconstructing the host's diet, as inferred from sequences obtained from pre-Columbian coprolites. This depicts a novel and reliable approach to determine new components as well as validate the previously suggested diets of extinct cultures and animals. Furthermore, to our knowledge this represents the first description of the eukaryotic viral diversity found in paleofaeces belonging to pre-Columbian cultures.

| S-EPMC4682816 | biostudies-literature

Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows.

Project description:Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach.

| S-EPMC8412247 | biostudies-literature

Evolutionary design optimization of traffic signals applied to Quito city.

Project description:This work applies evolutionary computation and machine learning methods to study the transportation system of Quito from a design optimization perspective. It couples an evolutionary algorithm with a microscopic transport simulator and uses the outcome of the optimization process to deepen our understanding of the problem and gain knowledge about the system. The work focuses on the optimization of a large number of traffic lights deployed on a wide area of the city and studies their impact on travel time, emissions and fuel consumption. An evolutionary algorithm with specialized mutation operators is proposed to search effectively in large decision spaces, evolving small populations for a short number of generations. The effects of the operators combined with a varying mutation schedule are studied, and an analysis of the parameters of the algorithm is also included. In addition, hierarchical clustering is performed on the best solutions found in several runs of the algorithm. An analysis of signal clusters and their geolocation, estimation of fuel consumption, spatial analysis of emissions, and an analysis of signal coordination provide an overall picture of the systemic effects of the optimization process.

| S-EPMC5728506 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data