Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

The three-dimensional morphology of simulated and observed convective storms over southern England

A set of high-resolution radar observations of convective storms has been collected to evaluate such storms in the UK Met Office Unified Model during the DYMECS project (Dynamical and Microphysical Evolution of Convective Storms). The 3-GHz Chilbolton Advanced Meteorological Radar was set up with a scan-scheduling algorithm to automatically track convective storms identified in real-time from the operational rainfall radar network. More than 1,000 storm observations gathered over fifteen days in 2011 and 2012 are used to evaluate the model under various synoptic conditions supporting convection. In terms of the detailed three-dimensional morphology, storms in the 1500-m grid-length simulations are shown to produce horizontal structures a factor 1.5–2 wider compared to radar observations. A set of nested model runs at grid lengths down to 100m show that the models converge in terms of storm width, but the storm structures in the simulations with the smallest grid lengths are too narrow and too intense compared to the radar observations. The modelled storms were surrounded by a region of drizzle without ice reflectivities above 0 dBZ aloft, which was related to the dominance of ice crystals and was improved by allowing only aggregates as an ice particle habit. Simulations with graupel outperformed the standard configuration for heavy-rain profiles, but the storm structures were a factor 2 too wide and the convective cores 2 km too deep.

Mechanisms for AMOC variability simulated by the NEMO model

We have investigated mechanisms for the Atlantic Meridional Overturning Circulation (AMOC) variability at 26.5° N (other than the Ekman component) that can be related to external forcings, in particular wind variability. Resolution dependence is studied using identical experiments with 1° and 1/4° NEMO model runs over 1960–2010. The analysis shows that much of the variability in the AMOC at 26° N can be related to the wind strength over the North Atlantic, through mechanisms lagged on different timescales. At ~ 1-year lag the January–June difference of mean sea level pressure between high and mid-latitudes in the North Atlantic explains 35–50% of the interannual AMOC variability (with negative correlation between wind strength and AMOC). At longer lead timescales ~ 4 years, strong (weak) winds over the northern North Atlantic (specifically linked to the NAO index) are followed by higher (lower) AMOC transport, but this mechanism only works in the 1/4° model. Analysis of the density correlations suggests an increase (decrease) in deep water formation in the North Atlantic subpolar gyre to be the cause. Therefore another 30% of the AMOC variability at 26° N can be related to density changes in the top 1000 m in the Labrador and Irminger seas occurring ~ 4 years earlier.

Simulated last glacial maximum D14Catm and the deep glacial ocean carbon reservoir

∆14Catm has been estimated as 420 ± 80‰ (IntCal09) during the Last Glacial Maximum (LGM) compared to preindustrial times (0‰), but mechanisms explaining this difference are not yet resolved. ∆14Catm is a function of both cosmogenic production in the high atmosphere and of carbon cycling and partitioning in the Earth system. 10Be-based reconstructions show a contribution of the cosmogenic production term of only 200 ± 200‰ in the LGM. The remaining 220‰ have thus to be explained by changes in the carbon cycle. Recently, Bouttes et al. (2010, 2011) proposed to explain most of the difference in pCO2atm and δ13C between glacial and interglacial times as a result of brine-induced ocean stratification in the Southern Ocean. This mechanism involves the formation of very saline water masses that contribute to high carbon storage in the deep ocean. During glacial times, the sinking of brines is enhanced and more carbon is stored in the deep ocean, lowering pCO2atm. Moreover, the sinking of brines induces increased stratification in the Southern Ocean, which keeps the deep ocean well isolated from the surface. Such an isolated ocean reservoir would be characterized by a low ∆14C signature. Evidence of such 14C-depleted deep waters during the LGM has recently been found in the Southern Ocean (Skinner et al. 2010). The degassing of this carbon with low ∆14C would then reduce ∆14Catm throughout the deglaciation. We have further developed the CLIMBER-2 model to include a cosmogenic production of 14C as well as an interactive atmospheric 14C reservoir. We investigate the role of both the sinking of brine and cosmogenic production, alongside iron fertilization mechanisms, to explain changes in ∆14Catm during the last deglaciation. In our simulations, not only is the sinking of brine mechanism consistent with past ∆14C data, but it also explains most of the differences in pCO2atm and ∆14Catm between the LGM and preindustrial times. Finally, this study represents the first time to our knowledge that a model experiment explains glacial-interglacial differences in pCO2atm, δ13C, and ∆14C together with a coherent LGM climate.

Use of simulated intestinal fluids with Caco-2 cells and rat ileum

In most in vitro studies of oral drug permeability, little attempt is made to reproduce the gastrointestinal lumenal environment. The aim of this study was to evaluate the compatibility of simulated intestinal fluid (SIF) solutions with Caco-2 cell monolayers and Ussing chamber-mounted rat ileum under standard permeability experiment protocols. In preliminary experiments, fasted-state simulated intestinal fluid (FaSSIF) and fed-state simulated intestinal fluid (FeSSIF) solutions based on the dissolution medium formulae of Dressman and co-workers (1998) were modified for compatibility with Caco-2 cells to produce FaS-SIF and FeSSIF "transport" solutions for use with in vitro permeability models. For Caco-2 cells exposed to FaSSIF and FESSIF transport solutions, the transepithelial electrical resistance was maintained for over 4 h and mannitol permeability was equivalent to that in control (Hank's Balanced Salt Solution-treated) cell layers. Scanning electron microscopy revealed that microvilli generally maintained a normal distribution, although some shortening of microvilli and occasional small areas of denudation were observed. For rat ileum in the Ussing chambers, the potential difference (PD) collapsed to zero over 120 min when exposed to the FaSSIF transport solution and an even faster collapse of the PD was observed when the FeSSIF transport solution was used. Electron micrographs revealed erosion of the villi tips and substantial denudation of the microvilli after exposure of ileal tissue to FaSSIF and FeSSIF solutions, and permeability to mannitol was increased by almost two-fold. This study indicated that FaSSIF and FeSSIF transport solutions can be used with Caco-2 monolayers to evaluate drug permeability, but rat ileum in Ussing chambers is adversely affected by these solutions. Metoprolol permeability in Caco-2 experiments was reduced by 33% using the FaSSIF and 75% using the FeSSIF compared to permeability measured using HBSS. This illustrates that using physiological solutions can influence permeability measurements.

Simulated climate change impact on summer dissolved organic carbon release from peat and surface vegetation: implications for drinking water treatment

Uncertainty regarding changes in dissolved organic carbon (DOC) quantity and quality has created interest in managing peatlands for their ecosystem services such as drinking water provision. The evidence base for such interventions is, however, sometimes contradictory. We performed a laboratory climate manipulation using a factorial design on two dominant peatland vegetation types (Calluna vulgaris and Sphagnum Spp.) and a peat soil collected from a drinking water catchment in Exmoor National Park, UK. Temperature and rainfall were set to represent baseline and future conditions under the UKCP09 2080s high emissions scenario for July and August. DOC leachate then underwent standard water treatment of coagulation/flocculation before chlorination. C. vulgaris leached more DOC than Sphagnum Spp. (7.17 versus 3.00 mg g−1) with higher specific ultraviolet (SUVA) values and a greater sensitivity to climate, leaching more DOC under simulated future conditions. The peat soil leached less DOC (0.37 mg g−1) than the vegetation and was less sensitive to climate. Differences in coagulation removal efficiency between the DOC sources appears to be driven by relative solubilisation of protein-like DOC, observed through the fluorescence peak C/T. Post-coagulation only differences between vegetation types were detected for the regulated disinfection by-products (DBPs), suggesting climate change influence at this scale can be removed via coagulation. Our results suggest current biodiversity restoration programmes to encourage Sphagnum Spp. will result in lower DOC concentrations and SUVA values, particularly with warmer and drier summers.

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system.

Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

A study on the sensitivities of simulated aerosol optical properties to composition and size distribution using airborne measurements

We present a flexible framework to calculate the optical properties of atmospheric aerosols at a given relative humidity based on their composition and size distribution. The similarity of this framework to climate model parameterisations allows rapid and extensive sensitivity tests of the impact of uncertainties in data or of new measurements on climate relevant aerosol properties. The data collected by the FAAM BAe-146 aircraft during the EUCAARI-LONGREX and VOCALS-REx campaigns have been used in a closure study to analyse the agreement between calculated and measured aerosol optical properties for two very different aerosol types. The agreement achieved for the EUCAARI-LONGREX flights is within the measurement uncertainties for both scattering and absorption. However, there is poor agreement between the calculated and the measured scattering for the VOCALS-REx flights. The high concentration of sulphate, which is a scattering aerosol with no absorption in the visible spectrum, made the absorption measurements during VOCALS-REx unreliable, and thus no closure study was possible for the absorption. The calculated hygroscopic scattering growth factor overestimates the measured values during EUCAARI-LONGREX and VOCALS-REx by ∼30% and ∼20%, respectively. We have also tested the sensitivity of the calculated aerosol optical properties to the uncertainties in the refractive indices, the hygroscopic growth factors and the aerosol size distribution. The largest source of uncertainty in the calculated scattering is the aerosol size distribution (∼35%), followed by the assumed hygroscopic growth factor for organic aerosol (∼15%), while the predominant source of uncertainty in the calculated absorption is the refractive index of organic aerosol (28–60%), although we would expect the refractive index of black carbon to be important for aerosol with a higher black carbon fraction.

Cluster analysis of downscaled and explicitly simulated North Atlantic tropical cyclone tracks

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in US landfalling systems. Here we present a tentative study, which examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1° to 0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and sub-tropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity and power dissipation index in each cluster are documented for both configurations. Our results show that except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. We also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, we examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.

The endophytic fungus Piriformospora indica protects wheat from Fusarium crown rot disease in simulated UK autumn conditions

The root endophytic fungus Piriformospora indica (Sebacinacea) forms mutualistic symbioses with a broad range of host plants, increasing their biomass production and resistance to fungal pathogens. We evaluated the effect of P. indica on Fusarium crown rot disease of wheat, under in vitro and glasshouse conditions. Interaction of P. indica and Fusarium isolates under axenic culture conditions indicated no direct antagonistic activity of P. indica against Fusarium isolates. Seedlings of wheat were inoculated with P. indica and pathogenic Fusarium culmorum or F. graminearum and grown in sterilised soil-free medium or in a non-sterilised mix of soil and sand. Fusarium alone reduced emergence and led to visible browning and reduced root growth. Roots of seedlings in pots inoculated with both Fusarium isolates and P. indica were free of visible symptoms; seed emergence and root biomass were equivalent to the uninoculated. DNA was quantified by real-time polymerase chain reaction (qPCR). The ratio of Fusarium DNA to wheat DNA rose rapidly in the plants inoculated with Fusarium alone; isolates and species were not significantly different. P. indica inoculation reduced the ratio of Fusarium to host DNA in the root systems. The reduction increased with time. The ratio of P. indica to wheat DNA initially rose but then declined in root systems without Fusarium. With Fusarium, the ratio rose throughout the experiment. The absolute amount of Fusarium DNA in root systems increased in the absence of P. indica but was static in plants co-inoculated with P. indica.

A diabatically-generated potential vorticity structure near the extratropical tropopause in three simulated extratropical cyclones

The structure of near-tropopause potential vorticity (PV) acts as a primary control on the evolution of extratropical cyclones. Diabatic processes such as the latent heating found in ascending moist warm conveyor belts modify PV. A dipole in diabatically-generated PV (hereafter diabatic PV) straddling the extratropical tropopause, with the positive pole above the negative pole, was diagnosed in a recently published analysis of a simulated extratropical cyclone. This PV dipole has the potential to significantly modify the propagation of Rossby waves and the growth of baroclinically-unstable waves. This previous analysis was based on a single case study simulated with 12-km horizontal grid spacing and parameterized convection. Here, the dipole is investigated in three additional cold-season extratropical cyclones simulated in both convection-parameterizing and convection-permitting model configurations. A diabatic PV dipole across the extratropical tropopause is diagnosed in all three cases. The amplitude of the dipole saturates approximately 36 hours from the time diabatic PV is accumulated. The node elevation of the dipole varies between 2-4 PVU in the three cases, and the amplitude of the system-averaged dipole varies between 0.2-0.4 PVU. The amplitude of the negative pole is similar in the convection-parameterizing and convection-permitting simulations. The positive pole, which is generated by long-wave radiative cooling, is weak in the convection-permitting simulations due to the small domain size which limits the accumulation of diabatic tendencies within the interior of the domain. The possible correspondence between the diabatic PV dipole and the extratropical tropopause inversion layer is discussed.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Rapid preconditioning of data for accelerating convex hull algorithms

Given a dataset of two-dimensional points in the plane with integer coordinates, the method proposed reduces a set of n points down to a set of s points s ≤ n, such that the convex hull on the set of s points is the same as the convex hull of the original set of n points. The method is O(n). It helps any convex hull algorithm run faster. The empirical analysis of a practical case shows a percentage reduction in points of over 98%, that is reflected as a faster computation with a speedup factor of at least 4.

A cross layer protocol for energy aware and critical data delivered applications using Wireless Sensor Networks

Environment monitoring applications using Wireless Sensor Networks (WSNs) have had a lot of attention in recent years. In much of this research tasks like sensor data processing, environment states and events decision making and emergency message sending are done by a remote server. A proposed cross layer protocol for two different applications where, reliability for delivered data, delay and life time of the network need to be considered, has been simulated and the results are presented in this paper. A WSN designed for the proposed applications needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from source nodes to the sink. A cross layer based on the design given in [1] has been extended and simulated for the proposed applications, with new features, such as routes discovery algorithms added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability.