Exchange of polycyclic aromatic hydrocarbons across the air-water interface in the Bohai and Yellow Seas

In this study, air and surface seawater samples collected from the Bohai (BS) and Yellow Seas (YS) in May 2012 were determined exchange of PAHs, especially of low-molecular-weight (LMW) PAHs (three- and four-ring PAHs) at the air-water interface. Net volatilization fluxes of LMW PAHs were 266-1454 ng/m(2)/d and decreased with distance from the coast, indicating that these PAHs transported from coastal runoff were potential contributors to the atmosphere in the BS and YS. Moreover, LMW PAHs were enriched in the dissolved phase compared with those in the particulate phase in the water column, possibly suggesting that the volatilized LMW PAHs were directly derived from wastewater discharge or petroleum pollution rather than released from contaminated sediments. The air-sea exchange fluxes of the three-ring PAHs were 2- to 20-fold higher than their atmospheric deposition fluxes in the BS and YS. The input to and output from the water reached equilibrium for four-ring PAHs. Differently, five- and six-ring PAHs were introduced into the marine environment primarily through dry and wet deposition, indicating that the water column was still a sink of these PAHs from the surrounding atmosphere. (C) 2016 Elsevier Ltd. All rights reserved

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Host-guest complexation integrated in chemical reaction networks

Nature has proven to be a great source of inspiration for scientific research and technological innovation in various areas: food, medicine, architecture, chemistry, materials, algorithms, and many other fields. At the basis of sophisticated functions associated with life in nature are all kinds of chemical reactions which are mainly regulated by enzymes through molecular recognition of the substrates. Meanwhile, chemical signals are able to tune the catalytic activities of enzymes through noncovalent bonding or structural modification. Concomitantly, the formation of transient structures that are used temporarily, for instance the mitotic spindle, requires the conversion of energy, mainly in the form of high-energy chemical fuels. All of these phenomena combined endow living systems with high responsivity to various stimuli. Inspired by nature, regulating artificial catalysts in chemical reactions by noncovalent bonding, and controlling formation/deformation of supramolecular materials by chemical reactions are attracting researchers’ attention. This thesis integrates chemical reaction networks with host-guest complexation, aiming to bring about some of these advanced properties.ChemE/Advanced Soft Matte

Methane dehydroaromatization catalyzed by Mo/ZSM-5: location-steered activity and mechanism

This work examined the location-steered catalytic behavior of Mo/ZSM-5 catalyst for one-step methane dehydroaromatization to benzene reaction. The results indicated that α-site is the preferred location for the formation of ethylene, the main intermediate for aromatics production via the propagation pathway, while δ-site is favorable for the hydrocarbon pool aggregation reaction pathway.ChemE/Inorganic Systems Engineerin

How Far Ahead Should Autonomous Vehicles Start Resolving Predicted Conflicts? Exploring Uncertainty-Based Safety-Efficiency Trade-Off

Resolving predicted conflicts is vital for safe and efficient autonomous vehicles (AV). In practice, vehicular motion prediction faces inherent uncertainty due to heterogeneous driving behaviours and environments. This spatial uncertainty increases non-linearly with prediction time horizons, leading AVs to perceive more road space occupied by conflicting vehicles. Reacting early to resolve predicted conflicts can ensure safety but may adversely affect traffic efficiency. Therefore, determining how far ahead AVs should start resolving predicted conflicts based on safety and traffic efficiency constraints is crucial. To answer this question, this study proposes a novel approach to explore the trade-off between safety and traffic efficiency considering prediction uncertainty. Firstly, a continuous-time motion prediction framework is proposed for estimating the spatial probability distribution of a vehicle’s future position at any moment within the maximum time horizon. Subsequently, average driver space and the corresponding traffic flow are derived from the safety settings of AV and prediction uncertainty. As such, the safety-efficiency trade-off can be quantified. Experiments show that mandatory decision points, high speeds, and traffic state transitions usually cause fast-increasing prediction uncertainty. A case study of Intelligent Driver Models (IDM) shows that traffic efficiency drops rapidly when AVs resolve predicted conflicts longer than 1.5 seconds ahead. AVs can act earlier on motorways for efficiency concerns but must be myopic at urban intersections. Prediction uncertainty fundamentally constrains the safety-efficiency performance of AVs. These findings are instructive for designing traffic-compatible AVs.Transport and Plannin

Metal containing nanoclusters in zeolites

The molecular-sized void space of the zeolitic micropores is perfect matrices to encapsulate and stabilize multicomponent and multifunctional complexes that can be used as active sites for a wide range of important catalytic transformations. In this article, we discuss and analyze the key developments of the last decade in the catalytic chemistry of metal-containing nanoclusters confined in zeolite micropores. We will present a concise summary of the recent developments in the tailored synthesis strategies, the advanced in-situ and operando characterization techniques, the enhanced performances of zeolite stabilized nanoclusters in various catalytic processes, and the application of computational modeling approaches for addressing the puzzle of catalyst-reactivity relationships. The article will be concluded with a brief discussion on the perspective for future developments anticipated for this field.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.ChemE/Inorganic Systems Engineerin

Unravelling uncertainty in trajectory prediction using a non-parametric approach

Predicting the trajectories of road agents is fundamental for self-driving cars. Trajectory prediction contains many sources of uncertainty in data and modelling. A thorough understanding of this uncertainty is crucial in a safety-critical task like auto-piloting a vehicle. In practice, it is necessary to distinguish between the uncertainty caused by partial observability of all factors that may affect a driver's near-future decisions, the so-called aleatoric uncertainty, and the uncertainty of deploying a model in new scenarios that are possibly not present in the training set, the so-called epistemic uncertainty. They reflect the trade-off between data collection and model improvement In this paper, we propose a new framework to systematically quantify both sources of uncertainty. Specifically, to approximate the spatial distribution of an agent's future position, we propose a 2D histogram-based deep learning model combined with deep ensemble techniques for measuring aleatoric and epistemic uncertainty by entropy-based quantities. The proposed Uncertainty Quantification Network (UQnet) employs a causal part to enhance its generalizability so rare driving behaviours can be effectively identified. Experiments on the INTERACTION dataset show that UQnet is able to give more robust predictions in generalizability tests compared to the correlation-based models. Further analysis presents that high aleatoric uncertainty cases are mainly caused by heterogeneous driving behaviours and unknown intended directions. Based on this aleatoric uncertainty component, we estimate the lower bounds of mean-square-error and final-displacement-error as indicators for the predictability of trajectories. Furthermore, the analysis of epistemic uncertainty illustrates that domain knowledge of speed-dependent driving behaviour is essential for adapting a model from low-speed to high-speed situations. Our paper contributes to motion forecasting with a new framework, that recasts the problem of accuracy improvement in a way that focuses on differentiating between unpredictable components and rare cases for which more and different data should be collected.Transport and Plannin

CO2 hydrogenation to methanol over Cd4/TiO2 catalyst: Insight into multifunctional interface

Supported metal catalysts have shown to be efficient for CO 2 conversion due to their multifunctionality and high stability. Herein, we have combined density functional theory calculations with microkinetic modeling to investigate the catalytic reaction mechanisms of CO 2 hydrogenation to CH 3OH over a recently reported catalyst of Cd 4/TiO 2. Calculations reveal that the metal-oxide interface is the active center for CO 2 hydrogenation and methanol formation via the formate pathway dominates over the reverse water-gas shift (RWGS) pathway. Microkinetic modeling demonstrated that formate species on the surface of Cd 4/TiO 2 is the relevant intermediate for the production of CH 3OH, and CH 2O # formation is the rate-determining step. These findings demonstrate the crucial role of the Cd-TiO 2 interface for controlling the CO 2 reduction reactivity and CH 3OH selectivity. ChemE/Inorganic Systems Engineerin

The Nature and Catalytic Function of Cation Sites in Zeolites: a Computational Perspective

Zeolites have a broad spectrum of applications as robust microporous catalysts for various chemical transformations. The reactivity of zeolite catalysts can be tailored by introducing heteroatoms either into the framework or at the extraframework positions that gives rise to the formation of versatile Brønsted acid, Lewis acid and redox-active catalytic sites. Understanding the nature and catalytic role of such sites is crucial for guiding the design of new and improved zeolite-based catalysts. This work presents an overview of recent computational studies devoted to unravelling the molecular level details of catalytic transformations inside the zeolite pores. The role of modern computational chemistry in addressing the structural problem in zeolite catalysis, understanding reaction mechanisms and establishing structure-activity relations is discussed. Special attention is devoted to such mechanistic phenomena as active site cooperativity, multifunctional catalysis as well as confinement-induced and multisite reactivity commonly encountered in zeolite catalysis.ChemE/Catalysis EngineeringChemE/Inorganic Systems Engineerin