Cardiovascular medication, physical activity and mortality: cross-sectional population study with ongoing mortality follow up

Objective: to establish physical activity levels in relation to cardiovascular medication and to examine if physical activity is associated with benefit independently of medication among individuals with no diagnosis of cardiovascular disease (CVD). Design: Cross-sectional surveys in 1998 and 2003 with ongoing mortality follow up. Setting: Household-based interviews in England and Scotland. Participants: Population samples of adults aged 35 and over living in households, respondents of the Scottish Health Survey and the Health Survey for England. Main outcome measure: Moderate to vigorous physical activity (MVPA) levels and CVD mortality. Results: Fifteen percent (N=3,116) of the 20,177 respondents (8,791 men); were prescribed at least one cardiovascular medication. Medicated respondents were less likely than those unmedicated to meet the physical activity recommendations (OR:0.89, 95%CI: 0.81 to 0.99, p=0.028). The mean follow up (±SD) was 6.6 (2.3) years. There were 1,509 any-cause deaths and 427 CVD deaths. Increased physical activity was associated with all-cause and CVD mortality among both unmedicated (all-cause mortality HR for those with ≥150 min/wk of MVPA compared with those who reported no MVPA): 0.58, 95%CI: 0.48 to 0.69, p<0.001) ; CVD mortality: 0.65, 0.46 to 0.91, p=0.036) and medicated respondents (all-cause death: 0.54, 0.40 to 0.72, p<0.001; CVD death: 0.46 (0.27 to 0.78, p=0.008). Conclusions: Although physical activity protects against premature mortality among both medicated and unmedicated adults, cardiovascular medication is linked with lower uptake of health enhancing physical activity. These results highlight the importance of physical activity in the primary prevention of CVD over and above medication

Kinetic modelling of heterogeneous catalytic systems

The importance of heterogeneous catalysis in modern life is evidenced by the fact that numerous products and technologies routinely used nowadays involve catalysts in their synthesis or function. The discovery of catalytic materials is, however, a non-trivial procedure, requiring tedious trial-and-error experimentation. First-principles-based kinetic modelling methods have recently emerged as a promising way to understand catalytic function and aid in materials discovery. In particular, kinetic Monte Carlo (KMC) simulation is increasingly becoming more popular, as it can integrate several sources of complexity encountered in catalytic systems, and has already been used to successfully unravel the underlying physics of several systems of interest. After a short discussion of the different scales involved in catalysis, we summarize the theory behind KMC simulation, and present the latest KMC computational implementations in the field. Early achievements that transformed the way we think about catalysts are subsequently reviewed in connection to latest studies of realistic systems, in an attempt to highlight how the field has evolved over the last few decades. Present challenges and future directions and opportunities in computational catalysis are finally discussed

Physical activity education in the undergraduate curricula of all UK medical schools: are tomorrow's doctors equipped to follow clinical guidelines?

Physical activity (PA) is a cornerstone of disease prevention and treatment. There is, however, a considerable disparity between public health policy, clinical guidelines and the delivery of physical activity promotion within the National Health Service in the UK. If this is to be addressed in the battle against non-communicable diseases, it is vital that tomorrow's doctors understand the basic science and health benefits of physical activity. The aim of this study was to assess the provision of physical activity teaching content in the curricula of all medical schools in the UK. Our results, with responses from all UK medical schools, uncovered some alarming findings, showing that there is widespread omission of basic teaching elements, such as the Chief Medical Officer recommendations and guidance on physical activity. There is an urgent need for physical activity teaching to have dedicated time at medical schools, to equip tomorrow's doctors with the basic knowledge, confidence and skills to promote physical activity and follow numerous clinical guidelines that support physical activity promotion

On the stochastic modelling of surface reactions through reflected chemical Langevin equations

Modelling of small-scale heterogeneous catalytic systems with master equations captures the impact of molecular noise, but can be computationally expensive. On the other hand, the chemical Fokker-Planck approximation offers an excellent alternative from an efficiency perspective. The Langevin equation can generate stochastic realisations of the Fokker-Planck equation; yet, these realisations may violate the conditions 0 <= θ <= 1 (where θ is surface coverage). In this work, we adopt Skorokhod’s formulations to impose reflective boundaries that remedy this issue. We demonstrate the approach on a simple system involving a single species and describing adsorption, desorption, reaction and diffusion processes on a lattice. We compare different numerical schemes for the solution of the resulting reflected Langevin equation and calculate rates of convergence. Our benchmarks should guide the choice of appropriate numerical methods for the accurate and efficient simulation of chemical systems in the catalysis field

Steady-State CO Oxidation on Pd(111): First-Principles Kinetic Monte Carlo Simulations and Microkinetic Analysis

Using a kinetic Monte Carlo (KMC) approach with parameters derived from first-principles calculations, we modeled the steady-state of CO oxidation on Pd(111), a prototypical catalytic system with various practical applications, including the treatment of automotive gas exhausts. Focusing on the metallic phase of the catalyst, we studied how the rate of CO oxidation depends on temperature and pressure, at fixed gas phase composition. Comparing the results of our simulations with experimental data, we found that all the qualitative features of this catalytic system are correctly reproduced by our model. We show that, when raising the temperature, the system transitions from a CO-poisoned regime with high apparent activation energy to a regime where the rate is almost independent of the temperature. The almost zero apparent activation energy at high temperature stems from approximately equal and opposite values of the O2 adsorption energy and dissociation barrier, as revealed by a simple microkinetic analysis. In the CO-poisoned regime, the precursor-mediated dissociative adsorption of oxygen plays a crucial role: we find that small changes (within DFT error) in the parameters controlling this elementary step have large effects on the kinetics of CO oxidation at low temperature

Atomistic and electronic structure of metal clusters supported on transition metal carbides: implications for catalysis

Novel research avenues have been explored over the last decade on the use of transition metal carbides (TMCs) as catalytically active supports for metal nanoclusters, which display high catalytic activity despite the poor reactivity (or even inertness) of the bulk metal. It has been postulated that TMCs polarise the electron density of adsorbed metal particles in such a way that their catalytic activity ends up being superior to those dispersed on more traditional metal oxide supports. Herein, we investigate the structural and electronic properties of small clusters of precious metals (Rh, Pd, Pt and Au) and more affordable metals (Co, Ni and Cu) supported on TMCs with 1:1 stoichiometry (TiC, ZrC, HfC, VC, NbC, TaC, MoC and WC) by means of periodic Density Functional Theory calculations. Our high-throughput screening studies indicate that it is possible not only to have strongly bonded and stably dispersed metal nanoparticles on TMC surfaces, but also to manipulate their charge by carefully selecting elements with desired electronegativity for the host TMC and the metal cluster. By doing so, it is possible to tune the amount of charge density on the cluster hollow sites, which can facilitate the bonding of certain molecules. Moreover, we identify Pt, Pd and Rh clusters supported on hexagonal TMC (001) facets as the candidates with the highest potential catalytic activity -as estimated by the significant polarisation of the cluster electron density- and stability -as quantified by the strongly negative values of adsorption energy per atom and formation energy

On the behaviour of structure-sensitive reactions on single atom and dilute alloy surfaces

Materials that are composed of atomically dispersed platinum group metal (PGM) atoms on coinage metal surfaces show remarkable catalytic performance in a number of chemical reactions. On these single atom alloy (SAA) surfaces, the isolated PGM atoms exhibit unique reactivity features owing to their distinctive, and often limited, interactions with the surrounding coinage metal atoms. In this work, we use density functional theory to investigate the reactivity of numerous SAA(100) and (111) surfaces, focusing on typically structure-sensitive reactions, which include the direct dissociations of NO, CO_{2} and N_{2}. Our results suggest that the structure-sensitivity of these three reactions is considerably reduced on SAA surfaces as compared to pure platinum group metal surfaces (Rh, Pt, Pd and Ni). Additionally, we examine the reactivity of small Rh and Ni ensembles doped on Cu(100) and (111) facets. We determine that Ni–Ni dimers and Ni trimers outperform the studied SAAs in the activation of N[double bond, length as m-dash]O, C[double bond, length as m-dash]O and N[triple bond, length as m-dash]N bonds, and are also capable of performing facile association reactions. This work can guide future theoretical and surface science studies on SAAs, as well as the development of highly dilute alloys, which can efficiently catalyse chemistries of industrial significance

The Catalytic Decomposition of Nitrous Oxide and the NO + CO Reaction over Ni/Cu Dilute and Single Atom Alloy Surfaces: First-principles Microkinetic Modelling

The development of platinum group metal-free (PGM-free) catalysts, which can efficiently reduce pollution-causing emissions, is an important task for overcoming major environmental challenges. In particular, nitrogen oxides (NOx) are major contributors to air pollution, being one of the culprits for smog and ozone depletion. In this work, we employ density functional theory (DFT) and microkinetic modelling to investigate the decomposition of N2O and the NO + CO reaction over two PGM-free Ni/Cu dilute alloys. On the first surface, Ni atoms are isolated on the host Cu(111), thereby forming a single atom alloy surface (i.e. Ni/Cu(111) SAA), while on the second, the same atoms are organised as Ni-Ni dimers (i.e. Ni2Cu(111)). The same reactions are also simulated on pure Cu(111) (i.e. the host surface), and on Rh(111), which is used for benchmarking as Rh is a well-established PGM in emissions control catalysis. Our results suggest that the addition of trace amounts of Ni on Cu(111) may bring about significant improvement to the catalytic performance with regard to the catalytic decomposition of N2O. Additionally, we determine that Ni2Cu(111) shows equivalent, or under some circumstances even better, performance as compared to Rh(111) for the NO + CO reaction. This work contributes to the long–standing efforts toward the design of efficient PGM-free catalytic materials for the reduction of noxious gases

Comparison of Queueing Data-Structures for Kinetic Monte Carlo Simulations of Heterogeneous Catalysts

On-lattice Kinetic Monte Carlo (KMC) is a computational method used to simulate (among others) physico-chemical processes on catalytic surfaces. The KMC algorithm propagates the system through discrete configurations by selecting (with the use of random numbers) the next elementary process to be simulated, e.g. adsorption, desorption, diffusion or reaction. An implementation of such a selection procedure is the first-reaction method in which all realizable elementary processes are identified and assigned a random occurrence time based on their rate constant. The next event to be executed will then be the one with the minimum inter-arrival time. Thus, a fast and efficient algorithm for selecting the most imminent process and performing all the necessary updates on the list of realizable processes post-execution, is of great importance. In the current work, we implement five data-structures to handle the elementary process queue during a KMC run: an unsorted list, a binary heap, a pairing heap, a 1-way skip list, and finally, a novel 2-way skip list with a mapping array specialized for KMC simulations. We also investigate the effect of compiler optimizations on the performance of these data-structures on three benchmark models, capturing CO-oxidation, a simplified water-gas shift mechanism, and a temperature programmed desorption run. Excluding the least efficient and impractical for large problems unsorted list, we observe a 3× speedup of the binary or pairing heaps (most efficient) compared to the 1-way skip list (least efficient). Compiler optimizations deliver a speedup of up to 1.8×. These benchmarks provide valuable insight on the importance of, often-overlooked, implementation-related aspects of KMC simulations, such as the queueing data-structures. Our results could be particularly useful in guiding the choice of data-structures and algorithms that would minimize the computational cost of large-scale simulations