A hydrochemical modelling framework for combined assessment of spatial and temporal variability in stream chemistry: application to Plynlimon, Wales

Recent concern about the risk to biota from acidification in upland areas, due to air pollution and land-use change (such as the planting of coniferous forests), has generated a need to model catchment hydro-chemistry to assess environmental risk and define protection strategies. Previous approaches have tended to concentrate on quantifying either spatial variability at a regional scale or temporal variability at a given location. However, to protect biota from ‘acid episodes’, an assessment of both temporal and spatial variability of stream chemistry is required at a catchment scale. In addition, quantification of temporal variability needs to represent both episodic event response and long term variability caused by deposition and/or land-use change. Both spatial and temporal variability in streamwater chemistry are considered in a new modelling methodology based on application to the Plynlimon catchments, central Wales. A two-component End-Member Mixing Analysis (EMMA) is used whereby low and high flow chemistry are taken to represent ‘groundwater’ and ‘soil water’ end-members. The conventional EMMA method is extended to incorporate spatial variability in the two end-members across the catchments by quantifying the Acid Neutralisation Capacity (ANC) of each in terms of a statistical distribution. These are then input as stochastic variables to a two-component mixing model, thereby accounting for variability of ANC both spatially and temporally. The model is coupled to a long-term acidification model (MAGIC) to predict the evolution of the end members and, hence, the response to future scenarios. The results can be plotted as a function of time and space, which enables better assessment of the likely effects of pollution deposition or land-use changes in the future on the stream chemistry than current methods which use catchment average values. The model is also a useful basis for further research into linkage between hydrochemistry and intra-catchment biological diversity.</p> <p style='line-height: 20px;'><b>Keywords:</b> hydrochemistry, End-Member Mixing Analysis (EMMA), uplands, acidificatio

III-V 4D Transistors

We fabricated for the first time vertically and laterally integrated III-V 4D transistors. III-V gate-all-around (GAA) nanowire MOSFETs with $3×4$ arrays show high drive current of $1.35mA/ \mu m$ and high transconductance of $0.85mS/ \mu m$. The vertical stacking of the III-V nanowires have provided an elegant solution to the drivability bottleneck of nanowire devices and is promising for future low-power logic and RF application.Chemistry and Chemical Biolog

Arable crop disease control, climate change and food security

Copyright Association of Applied BiologistsGlobal food security is threatened by crop diseases that account for average yield losses of 16%. Climate change is exacerbating threats to food security in much of the world, emphasising the need to increase food production in northern European countries such as the UK. However, to mitigate climate change, crops must be grown so as to minimise greenhouse gas emissions (GHG); results with UK oilseed rape demonstrate how disease control in arable crops can contribute to climate change mitigation. However, work examining impacts of climate change on UK epidemics of winter oilseed rape diseases illustrates unexpected, contrasting impacts of climate change on complex plant-disease interactions. In England, phoma stem canker is expected to become more severe whilst light leaf spot is expected to become less severe. Such work can provide guidance for government and industry planning for adaptation to impacts of climate change on crops to ensure future food securityFinal Accepted Versio

The effect of medium-term heat acclimation on endurance performance in a temperate environment

We investigated whether an 11-day heat acclimation programme (HA) enhanced endurance performance in a temperate environment, and the mechanisms underpinning any ergogenic effect. Twenty-four males (V̇O2max: 56.7±7.5 mL∙kg-1∙min-1) completed either: i) HA consisting of 11 consecutive daily exercise sessions (60-90 minutes·day-1; n=16) in a hot environment (40°C, 50% RH) or; ii) duration and exertion matched exercise in cool conditions (CON; n=8 [11°C, 60% RH]). Before and after each programme power at lactate threshold, mechanical efficiency, VO2max, peak power output (PPO) and work done during a 30-minute cycle trial (T30) were determined under temperate conditions (22°C, 50% RH). HA reduced resting (-0.34±0.30°C) and exercising (-0.43±0.30°C) rectal temperature, and increased whole-body sweating (+0.37±0.31 L·hr-1) (all P≤0.001), with no change in CON. Plasma volume increased in HA (10.1±7.2%, P<0.001) and CON (7.2±6.3%, P=0.015) with no between-groups difference, whereas exercise heart rate reduced in both groups, but to a greater extent in HA (-20±11 b·min-1) than CON (-6±4 b·min-1). VO2max, lactate threshold and mechanical efficiency were unaffected by HA. PPO increased in both groups (+14±18W), but this was not related to alterations in any of the performance or thermal variables, and T30 performance was unchanged in either group (HA: Pre=417±90 vs. Post=427±83 kJ; CON: Pre=418±63 vs. Post=423±56 kJ). In conclusion, 11-days HA induces thermophysiological adaptations, but does not alter the key determinants of endurance performance. In trained males, the effect of HA on endurance performance in temperate conditions is no greater than that elicited by exertion and duration matched exercise training in cool conditions

A novel determination of the local dark matter density

We present a novel study on the problem of constructing mass models for the Milky Way, concentrating on features regarding the dark matter halo component. We have considered a variegated sample of dynamical observables for the Galaxy, including several results which have appeared recently, and studied a 7- or 8-dimensional parameter space - defining the Galaxy model - by implementing a Bayesian approach to the parameter estimation based on a Markov Chain Monte Carlo method. The main result of this analysis is a novel determination of the local dark matter halo density which, assuming spherical symmetry and either an Einasto or an NFW density profile is found to be around 0.39 GeV cm$^{-3}$ with a 1-$\sigma$ error bar of about 7%; more precisely we find a $\rho_{DM}(R_0) = 0.385 \pm 0.027 \rm GeV cm^{-3}$ for the Einasto profile and $\rho_{DM}(R_0) = 0.389 \pm 0.025 \rm GeV cm^{-3}$ for the NFW. This is in contrast to the standard assumption that $\rho_{DM}(R_0)$ is about 0.3 GeV cm$^{-3}$ with an uncertainty of a factor of 2 to 3. A very precise determination of the local halo density is very important for interpreting direct dark matter detection experiments. Indeed the results we produced, together with the recent accurate determination of the local circular velocity, should be very useful to considerably narrow astrophysical uncertainties on direct dark matter detection.Comment: 31 pages,11 figures; minor changes in the text; two figures adde

A method for isolating and culturing placental cells from failed early equine pregnancies

Early pregnancy loss occurs in 6–10% of equine pregnancies making it the main cause of reproductive wastage. Despite this, reasons for the losses are known in only 16% of cases. Lack of viable conceptus material has inhibited investigations of many potential genetic and pathological causes. We present a method for isolating and culturing placental cells from failed early equine pregnancies. Trophoblast cells from 18/30 (60%) failed equine pregnancies of gestational ages 14–65 days were successfully cultured in three different media, with the greatest growth achieved for cells cultured in AmnioChrome™ Plus. Genomic DNA of a suitable quality for molecular assays was also isolated from 29/30 of these cases. This method will enable future investigations determining pathologies causing EPL

Naturalness and Higgs Decays in the MSSM with a Singlet

The simplest extension of the supersymmetric standard model - the addition of one singlet superfield - can have a profound impact on the Higgs and its decays. We perform a general operator analysis of this scenario, focusing on the phenomenologically distinct scenarios that can arise, and not restricting the scope to the narrow framework of the NMSSM. We reexamine decays to four b quarks and four tau's, finding that they are still generally viable, but at the edge of LEP limits. We find a broad set of Higgs decay modes, some new, including those with four gluon final states, as well as more general six and eight parton final states. We find the phenomenology of these scenarios is dramatically impacted by operators typically ignored, specifically those arising from D-terms in the hidden sector, and those arising from weak-scale colored fields. In addition to sensitivity of m_Z, there are potential tunings of other aspects of the spectrum. In spite of this, these models can be very natural, with light stops and a Higgs as light as 82 GeV. These scenarios motivate further analyses of LEP data as well as studies of the detection capabilities of future colliders to the new decay channels presented.Comment: 3 figures, 1 appendix; version to appear in JHEP; typos fixed and additional references and acknowledgements adde

Reverse sequence polymerization-induced self-assembly in aqueous media: a counter-intuitive approach to sterically-stabilized diblock copolymer nano-objects

Polymerization-induced self-assembly (PISA) is a powerful platform technology for the efficient synthesis of block copolymer nanoparticles in many types of solvents, including water. In PISA, a soluble precursor block is used to grow a second insoluble block, which leads to in situ self-assembly of the block copolymer chains. Thus, in the case of aqueous PISA, the water-soluble block is always prepared first because this confers steric stabilization. Herein, we challenge this paradigm by demonstrating that amphiphilic diblock copolymer chains can be prepared in water by preparing the hydrophobic block first via reversible addition–fragmentation chain transfer (RAFT) polymerization. This counter-intuitive reverse sequence PISA formulation utilizes an ionic RAFT agent to conduct the RAFT aqueous dispersion polymerization of 2-hydroxypropyl methacrylate (HPMA), which results in the formation of charge-stabilized PHPMA latex particles of ∼500 nm diameter. Initial attempts to chain-extend these hydrophobic PHPMA chains with water-miscible monomers such as glycerol monomethacrylate (GMA) were unsuccessful, with only uncontrolled free radical polymerization being observed in the aqueous phase. However, using a water-immiscible monomer such as isopropylideneglycerol methacrylate (IPGMA) enabled the synthesis of charge-stabilized PHPMA-PIPGMA latex particles. Subsequent acid hydrolysis of the PIPGMA block led to the in situ formation of sterically-stabilized PHPMA-PGMA diblock copolymer spheres. Alternatively, dissolution of the precursor PHPMA latex in a methanol/water binary mixture enables RAFT solution polymerization of water-miscible monomers such as GMA or N,N′-dimethylacrylamide (DMAC) to be achieved with good control. The resulting amphiphilic diblock copolymer chains then undergo self-assembly in aqueous solution after removal of the methanol co-solvent. Finally, this reverse sequence PISA protocol can also be applied to other vinyl monomers such as 2-methoxyethyl methacrylate (MOEMA) or diacetone acrylamide (DAAM), which significantly broadens its scope

PAMELA, DAMA, INTEGRAL and Signatures of Metastable Excited WIMPs

Models of dark matter with ~ GeV scale force mediators provide attractive explanations of many high energy anomalies, including PAMELA, ATIC, and the WMAP haze. At the same time, by exploiting the ~ MeV scale excited states that are automatically present in such theories, these models naturally explain the DAMA/LIBRA and INTEGRAL signals through the inelastic dark matter (iDM) and exciting dark matter (XDM) scenarios, respectively. Interestingly, with only weak kinetic mixing to hypercharge to mediate decays, the lifetime of excited states with delta < 2 m_e is longer than the age of the universe. The fractional relic abundance of these excited states depends on the temperature of kinetic decoupling, but can be appreciable. There could easily be other mechanisms for rapid decay, but the consequences of such long-lived states are intriguing. We find that CDMS constrains the fractional relic population of ~100 keV states to be <~ 10^-2, for a 1 TeV WIMP with sigma_n = 10^-40 cm^2. Upcoming searches at CDMS, as well as xenon, silicon, and argon targets, can push this limit significantly lower. We also consider the possibility that the DAMA excitation occurs from a metastable state into the XDM state, which decays via e+e- emission, which allows lighter states to explain the INTEGRAL signal due to the small kinetic energies required. Such models yield dramatic signals from down-scattering, with spectra peaking at high energies, sometimes as high as ~1 MeV, well outside the usual search windows. Such signals would be visible at future Ar and Si experiments, and may be visible at Ge and Xe experiments. We also consider other XDM models involving ~ 500 keV metastable states, and find they can allow lighter WIMPs to explain INTEGRAL as well.Comment: 22 pages, 7 figure

Fast supersymmetry phenomenology at the Large Hadron Collider using machine learning techniques

A pressing problem for supersymmetry (SUSY) phenomenologists is how to incorporate Large Hadron Collider search results into parameter fits designed to measure or constrain the SUSY parameters. Owing to the computational expense of fully simulating lots of points in a generic SUSY space to aid the calculation of the likelihoods, the limits published by experimental collaborations are frequently interpreted in slices of reduced parameter spaces. For example, both ATLAS and CMS have presented results in the Constrained Minimal Supersymmetric Model (CMSSM) by fixing two of four parameters, and generating a coarse grid in the remaining two. We demonstrate that by generating a grid in the full space of the CMSSM, one can interpolate between the output of an LHC detector simulation using machine learning techniques, thus obtaining a superfast likelihood calculator for LHC-based SUSY parameter fits. We further investigate how much training data is required to obtain usable results, finding that approximately 2000 points are required in the CMSSM to get likelihood predictions to an accuracy of a few per cent. The techniques presented here provide a general approach for adding LHC event rate data to SUSY fitting algorithms, and can easily be used to explore other candidate physics models.Comment: 20 pages, 7 figures, replaced to correct author contact detail