Micrometre-long covalent organic fibres by photoinitiated chain-growth radical polymerization on an alkali-halide surface

On-surface polymerization is a promising technique to prepare organic functional nanomaterials that are challenging to synthesize in solution, but it is typically used on metal substrates, which play a catalytic role. Previous examples on insulating surfaces have involved intermediate self-assembled structures, which face high barriers to diffusion, or annealing to higher temperatures, which generally causes rapid dewetting and desorption of the monomers. Here we report the photoinitiated radical polymerization, initiated from a two-dimensional gas phase, of a dimaleimide monomer on an insulating KCl surface. Polymer fibres up to 1 μm long are formed through chain-like rather than step-like growth. Interactions between potassium cations and the dimaleimide’s oxygen atoms facilitate the propagation of the polymer fibres along a preferred axis of the substrate over long distances. Density functional theory calculations, non-contact atomic force microscopy imaging and manipulations at room temperature were used to explore the initiation and propagation processes, as well as the structure and stability of the resulting one-dimensional polymer fibres

The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008

Interdigitated conducting tetrathiafulvalene-based coordination networks

Assembly of a novel ethylenedithio-tetrathiafulvalene (EDT-TTF) derivative bearing two adjacent 4-thiopyridyl groups with M(NCS)2 nodes (M = Fe, Co) leads to two isostructural 1D coordination polymers showing an enhancement of their electronic conductivity by six orders of magnitude (10[superscript -6] vs. 10[superscript -12] S cm[superscript -1), upon surface oxidation by iodine and subsequent generation of EDT-TTF-based radicals.National Science Foundation (Award 1122374

Imbalanced weighting of proactive and reactive control as a marker of risk-taking propensity.

According to the dual mechanisms of control (DMC), reactive and proactive control are involved in adjusting behaviors when maladapted to the environment. However, both contextual and inter-individual factors increase the weight of one control mechanism over the other, by influencing their cognitive costs. According to one of the DMC postulates, limited reactive control capacities should be counterbalanced by greater proactive control to ensure control efficiency. Moreover, as the flexible weighting between reactive and proactive control is key for adaptive behaviors, we expected that maladaptive behaviors, such as risk-taking, would be characterized by an absence of such counterbalance. However, to our knowledge, no studies have yet investigated this postulate. In the current study, we analyzed the performances of 176 participants on two reaction time tasks (Simon and Stop Signal tasks) and a risk-taking assessment (Balloon Analog Risk Taking, BART). The post-error slowing in the Simon task was used to reflect the spontaneous individuals' tendency to proactively adjust behaviors after an error. The Stop Signal Reaction Time was used to assess reactive inhibition capacities and the duration of the button press in the BART was used as an index of risk-taking propensity. Results showed that poorer reactive inhibition capacities predicted greater proactive adjustments after an error. Furthermore, the higher the risk-taking propensity, the less reactive inhibition capacities predicted proactive behavioral adjustments. The reported results suggest that higher risk-taking is associated with a smaller weighting of proactive control in response to limited reactive inhibition capacities. These findings highlight the importance of considering the imbalanced weighting of reactive and proactive control in the analysis of risk-taking, and in a broader sense, maladaptive behaviors

Data_Sheet_1_Investigating risk-taking and executive functioning as predictors of driving performances and habits: a large-scale population study with on-road evaluation.docx

IntroductionMaladaptive behavior often results from poor decision-making and by extension poor control over decisions. Since maladaptive behavior in driving, such as excessive speed, can lead to dramatic consequences, identifying its causes is of particular concern. The present study investigated how risk-taking and executive functioning are related to driving performance and habits among the general population.MethodFive hundred and eighty-nine participants completed an on-road driving session with a professional driving instructor and a self-reported checklist of difficult driving situations typically avoided. Additionally, participants completed a set of experimental tasks assessing risk-taking tendencies, reactive adaptive mechanisms, and two distinct forms of inhibition: interference control and response inhibition.ResultsThe results of the present study revealed several significant findings. Firstly, poor driving performance was associated with a high avoidance of challenging driving situations. Secondly, neither form of inhibition studied (interference control or response inhibition) predicted driving performance. Thirdly, while greater involvement in reactive adaptive mechanisms did not predict better on-road performance, it was associated with a reduced tendency to avoid difficult situations. Surprisingly, a higher propensity for risk-taking predicted better on-road performance.DiscussionOverall, these results underline limited links between executive functioning and driving performance while highlighting a potentially more complex relationship between risk-taking tendencies and driving. Executive functioning, however, appears to be linked to driving habits.</p

Particulate Matter deposition on leaves across European urban environments: [i]Platanus[/i] sp. sampling campaign within COST Action FP1204

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