Environmental impact of combined ITS traffic management strategies

Transport was responsible for 20% of the total greenhouse gas emissions in Europe during 2011 (European Environmental Agency 2013) with road transport being the key contributor. To tackle this, targets have been established in Europe and worldwide to curb transport emissions. This poses a significant challenge on Local Government and transport operators who need to identify a set of effective measures to reduce the environmental impact of road transport and at the same time keep the traffic smooth. Of the road transport pollutants, this paper considers NOx, CO2 and black carbon (BC). A particular focus is put on black carbon, which is formed through incomplete combustion of carboneous materials, as it has a significant impact on the Earth’s climate system. It absorbs solar radiation, influences cloud processes, and alters the melting of snow and ice cover (Bond et al. 2013). BC also causes serious health concerns: black carbon is associated with asthma and other respiratory problems, heart attacks and lung cancer (Sharma 2010; United States Environmental Protection Agency 2012). Since BC emissions are mainly produced during the decelerating and accelerating phases (Zhang et al. 2009), ITS actions able to reduce stop&go phases have the potential to reduce BC emissions. This paper investigates the effectiveness of combined ITS actions in urban context in reducing CO2 and BC emissions and improving traffic conditions

Isotonic regression in general dimensions

We study the least squares regression function estimator over the class of real-valued functions on $[0,1]^d$ that are increasing in each coordinate. For uniformly bounded signals and with a fixed, cubic lattice design, we establish that the estimator achieves the minimax rate of order $n^{-\min\{2/(d+2),1/d\}}$ in the empirical $L_2$ loss, up to poly-logarithmic factors. Further, we prove a sharp oracle inequality, which reveals in particular that when the true regression function is piecewise constant on $k$ hyperrectangles, the least squares estimator enjoys a faster, adaptive rate of convergence of $(k/n)^{\min(1,2/d)}$, again up to poly-logarithmic factors. Previous results are confined to the case $d \leq 2$. Finally, we establish corresponding bounds (which are new even in the case $d=2$) in the more challenging random design setting. There are two surprising features of these results: first, they demonstrate that it is possible for a global empirical risk minimisation procedure to be rate optimal up to poly-logarithmic factors even when the corresponding entropy integral for the function class diverges rapidly; second, they indicate that the adaptation rate for shape-constrained estimators can be strictly worse than the parametric rate.The research of the first author is supported in part by NSF Grant DMS-1566514. The research of the second and fourth authors is supported by EPSRC fellowship EP/J017213/1 and a grant from the Leverhulme Trust RG81761

Day-to-day dynamic traffic assignment model with variable message signs and endogenous user compliance

This paper proposes a dual-time-scale, day-to-day dynamic traffic assignment model that takes into account variable message signs (VMS) and its interactions with drivers’ travel choices and adaptive learning processes. The within-day dynamic is captured by a dynamic network loading problem with en route update of path choices influenced by the VMS; the day-to-day dynamic is captured by a simultaneous route-and-departure-time adjustment process that employs bounded user rationality. Moreover, we describe the evolution of the VMS compliance rate by modeling drivers’ learning processes. We endogenize traffic dynamics, route and departure time choices, travel delays, and VMS compliance, and thereby captur their interactions and interdependencies in a holistic manner. A case study in the west end of Glasgow is carried out to understand the impact of VMS has on road congestion and route choices in both the short and long run. Our main find- ings include an adverse effect of the VMS on the network performance in the long run (the “rebound” effect), and existence of an equilibrium state where both traffic and VMS compliance are stabilized

Chemical characterization of water-soluble organic carbon aerosols at a rural site in the Pearl River Delta, China, in the summer of 2006

Online measurements of water-soluble organic carbon (WSOC) aerosols were made using a particle-into-liquid sampler (PILS) combined with a total organic carbon (TOC) analyzer at a rural site in the Pearl River Delta region, China, in July 2006. A macroporous nonionic (DAX-8) resin was used to quantify hydrophilic and hydrophobic WSOC, which are defined as the fractions of WSOC that penetrated through and retained on the DAX-8 column, respectively. Laboratory calibrations showed that hydrophilic WSOC (WSOCHPI) included low-molecular aliphatic dicarboxylic acids and carbonyls, saccharides, and amines, while hydrophobic WSOC (WSOCHPO) included longer-chain aliphatic dicarboxylic acids and carbonyls, aromatic acids, phenols, organic nitrates, cyclic acids, and fulvic acids. On average, total WSOC (TWSOC) accounted for 60% of OC, and WSOCHPO accounted for 60% of TWSOC. Both WSOC HIP and WSOCHPO increased with photochemical aging determined from the NOx/NOy ratio. In particular, the average WSOCHPO mass was found to increase by a factor of five within a timescale of ∼10 hours, which was substantially larger than that of WSOCHPI (by a factor of 2-3). The total increase in OC mass with photochemical aging was associated with the large increase in WSOCHPO mass. These results, combined with the laboratory calibrations, suggest that significant amounts of hydrophobic organic compounds (likely containing large carbon numbers) were produced by photochemical processing. By contrast, water-insoluble OC (WIOC) mass did not exhibit significant changes with photochemical aging, suggesting that chemical transformation of WIOC to WSOC was not a dominant process for the production of WSOC during the study period. Copyright 2009 by the American Geophysical Union

The Effect of Transposable Element Insertions on Gene Expression Evolution in Rodents

Background:Many genomes contain a substantial number of transposable elements (TEs), a few of which are known to be involved in regulating gene expression. However, recent observations suggest that TEs may have played a very important role in the evolution of gene expression because many conserved non-genic sequences, some of which are know to be involved in gene regulation, resemble TEs. Results:Here we investigate whether new TE insertions affect gene expression profiles by testing whether gene expression divergence between mouse and rat is correlated to the numbers of new transposable elements inserted near genes. We show that expression divergence is significantly correlated to the number of new LTR and SINE elements, but not to the numbers of LINEs. We also show that expression divergence is not significantly correlated to the numbers of ancestral TEs in most cases, which suggests that the correlations between expression divergence and the numbers of new TEs are causal in nature. We quantify the effect and estimate that TE insertion has accounted for ~20% (95% confidence interval: 12% to 26%) of all expression profile divergence in rodents. Conclusions:We conclude that TE insertions may have had a major impact on the evolution of gene expression levels in rodents

Reducing environmental impact by adaptive traffic control and management for urban road networks

This paper investigates the effectiveness of traffic signal control and variable message sign (VMS) as environmental traffic management tool. The focus is on black carbon and CO2, which are among the highest contributors to climate change. The modelling tool chain adopted to support this study includes traffic microsimulation, emission modelling and dispersion modelling. A number of scenarios have been simulated with different levels of demand and VMS compliance rates. The results demonstrate the potential of these interventions in reducing black carbon and CO2 emissions and improving air quality, as well as reducing traffic congestion and travel delays

An Overview of the Use of Neural Networks for Data Mining Tasks

In the recent years the area of data mining has experienced a considerable demand for technologies that extract knowledge from large and complex data sources. There is a substantial commercial interest as well as research investigations in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from datasets. Artificial Neural Networks (NN) are popular biologically inspired intelligent methodologies, whose classification, prediction and pattern recognition capabilities have been utilised successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks

Увеличение темпов прироста запасов углеводородов с помощью инновационных технологий на примере Омской области

Проведен анализ перспектив нефтегазоносности Омской области на основе данных инновационной технологии квантово-оптической фильтрации космоснимков. Приведены физические принципы технологии квантово-оптической фильтрации. На примере Омской области показана эффективность применения технологии квантово-оптической фильтрации при решении задачи повышения темпов прироста запасов углеводородного сырья

Facile Synthesis of High Quality Graphene Nanoribbons

Graphene nanoribbons have attracted attention for their novel electronic and spin transport properties1-6, and because nanoribbons less than 10 nm wide have a band gap that can be used to make field effect transistors. However, producing nanoribbons of very high quality, or in high volumes, remains a challenge. Here, we show that pristine few-layer nanoribbons can be produced by unzipping mildly gas-phase oxidized multiwalled carbon nanotube using mechanical sonication in an organic solvent. The nanoribbons exhibit very high quality, with smooth edges (as seen by high-resolution transmission electron microscopy), low ratios of disorder to graphitic Raman bands, and the highest electrical conductance and mobility reported to date (up to 5e2/h and 1500 cm2/Vs for ribbons 10-20 nm in width). Further, at low temperature, the nanoribbons exhibit phase coherent transport and Fabry-Perot interference, suggesting minimal defects and edge roughness. The yield of nanoribbons was ~2% of the starting raw nanotube soot material, which was significantly higher than previous methods capable of producing high quality narrow nanoribbons1. The relatively high yield synthesis of pristine graphene nanoribbons will make these materials easily accessible for a wide range of fundamental and practical applications.Comment: Nature Nanotechnology in pres

Impaired decisional impulsivity in pathological videogamers

Abstract Background Pathological gaming is an emerging and poorly understood problem. Impulsivity is commonly impaired in disorders of behavioural and substance addiction, hence we sought to systematically investigate the different subtypes of decisional and motor impulsivity in a well-defined pathological gaming cohort. Methods Fifty-two pathological gaming subjects and age-, gender- and IQ-matched healthy volunteers were tested on decisional impulsivity (Information Sampling Task testing reflection impulsivity and delay discounting questionnaire testing impulsive choice), and motor impulsivity (Stop Signal Task testing motor response inhibition, and the premature responding task). We used stringent diagnostic criteria highlighting functional impairment. Results In the Information Sampling Task, pathological gaming participants sampled less evidence prior to making a decision and scored fewer points compared with healthy volunteers. Gaming severity was also negatively correlated with evidence gathered and positively correlated with sampling error and points acquired. In the delay discounting task, pathological gamers made more impulsive choices, preferring smaller immediate over larger delayed rewards. Pathological gamers made more premature responses related to comorbid nicotine use. Greater number of hours played also correlated with a Motivational Index. Greater frequency of role playing games was associated with impaired motor response inhibition and strategy games with faster Go reaction time. Conclusions We show that pathological gaming is associated with impaired decisional impulsivity with negative consequences in task performance. Decisional impulsivity may be a potential target in therapeutic management