Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Evaluation of uv spectrophotometry for estimation of nitrite and nitrate in nitrified urine

Water is a limited resource for which demand is growing. Contaminated water from inadequate wastewater treatment provides one of the greatest health challenges as it restricts development and increases poverty in emerging and developing countries. Therefore, the connection between wastewater and human health is linked to access to sanitation and to human waste disposal. Adequate sanitation is expected to create a barrier between disposed human excreta and sources of drinking water. Different approaches to wastewater management are required for different geographical regions and different stages of economic governance depending on the capacity to manage wastewater. Effective wastewater management can contribute to overcome the challenges of water scarcity. Separate collection of human urine at its source is one promising approach that strongly reduces the economic and load demands on wastewater treatment plants (WWTP). Treatment of source-separated urine appears as a sanitation system that is affordable, produces a valuable fertiliser, reduces pollution of water resources and promotes health. However, the technical realisation of urine separation still faces challenges. Biological hydrolysis of urea causes a strong increase of ammonia and pH. Under these conditions ammonia volatilises which can cause odour problems and significant nitrogen losses. The above problems can be avoided by urine stabilisation. Biological nitrification is a suitable process for stabilisation of urine. Urine is a highly concentrated nutrient solution which can lead to strong inhibition effects during bacterial nitrification. This can further lead to process instabilities. The major cause of instability is accumulation of the inhibitory intermediate compound nitrite, which could lead to process breakdown. Enhanced on-line nitrite monitoring can be applied in biological source-separated urine nitrification reactors as a sustainable and efficient way to improve the reactor performance, avoiding reactor failures and eventual loss of biological activity. Spectrophotometry appears as a promising candidate for the development and application of on-line nitrite monitoring. Spectroscopic methods together with chemometrics are presented in this work as a powerful tool for estimation of nitrite concentrations. Principal component regression (PCR) is applied for the estimation of nitrite concentrations using an immersible UV sensor and off-line spectra acquisition. The effect of particles and the effect of saturation, respectively, on the UV absorbance spectra are investigated. The analysis allows to conclude that (i) saturation has a substantial effect on nitrite estimation; (ii) particles appear to have less impact on nitrite estimation. In addition, improper mixing together with instabilities in the urine nitrification process appears to significantly reduce the performance of the estimation model.

Development & evaluation of different acoustic models for Malayalam continuous speech recognition

Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.

Evaluation of Somaclonal Variation in Callus Cultures of Jatropha curcas Maintained on Different Hormonal Combinations Using RAPD Markers

Random genetic changes generated during in vitro culture are not desirable for plant micropropagation and genetic transformation. RAPD markers were used to detect the variation in leaf disc callus cultures of Jatropha curcas, maintained in Murashige and Skoog (MS) medium with different auxin and cytokinin combinations. In total 41 scorable bands were produced with 11 primers. Out of 41 bands, 37 were polymorphic (91.12%). The average number of polymorphic bands was 3.36 per primer. The highest similarity (0.82) with mother plant was seen in callus maintained on MS with hormonal combination Indole butyric acid - 0.4mg/l+ N6-benzyladenine purine - 4.0 mg/l. The callus grown on MS with hormonal combinations IBA- 0.4mg/l+ BAP- 2.0mg/l, IBA- 0.4mg/l+ BAP- 2.5mg/l and IBA- 0.6 mg/l+ BAP- 2.0 mg/l also showed similarity with the mother plant. Callus maintained on MS with hormonal combination IBA- 0.2mg/l+ BAP- 2.0 mg/l was found to show least similarity (0.53) with mother plant

Evaluation of suitable spectral intervals for near-IR laboratory detection of water vapour continuum absorption

The water vapour continuum absorption is an important component of molecular absorption of radiation in atmosphere. However, uncertainty in knowledge of the value of the continuum absorption at present can achieve 100% in different spectral regions leading to an error in flux calculation up to 3-5 W/m2 global mean. This work uses line-by-line calculations to reveal the best spectral intervals for experimental verification of the CKD water vapour continuum models in the currently least studied near-infrared spectral region. Possible sources of errors in continuum retrieval taken into account in the simulation include the sensitivity of laboratory spectrometers and uncertainties in the spectral line parameters in HITRAN-2004 and Schwenke-Partridge database. It is shown that a number of micro-windows in near-IR can be used at present for laboratory detection of the water vapour continuum with estimated accuracy from 30 to 5%.

Land use for England and Wales: evaluation of management options to support 'good ecological status' in surface freshwaters

This paper analyses historic records of agricultural land use and management for England and Wales from 1931 and 1991 and uses export coefficient modelling to hindcast the impact of these practices on the rates of diffuse nitrogen (N) and phosphorus (P) export to water bodies for each of the major geo-climatic regions of England and Wales. Key trends indicate the importance of animal agriculture as a contributor to the total diffuse agricultural nutrient loading on waters, and the need to bring these sources under control if conditions suitable for sustaining 'Good Ecological Status' under the Water Framework Directive are to be generated. The analysis highlights the importance of measuring changes in nutrient loading in relation to the catchment-specific baseline state for different water bodies. The approach is also used to forecast the likely impact of broad regional scale scenarios on nutrient export to waters and highlights the need to take sensitive land out of production, introduce ceilings on fertilizer use and stocking densities, and controls on agricultural practice in higher risk areas where intensive agriculture is combined with a low intrinsic nutrient retention capacity, although the uncertainties associated with the modelling applied at this scale should be taken into account in the interpretation of model output. The paper advocates the need for a two-tiered approach to nutrient management, combining broad regional policies with targeted management in high risk areas at the catchment and farm scale.

In vitro evaluation of fibrolytic enzymes as additives for maize (Zea mays L.) silage - III. Comparison of enzymes derived from psychrophilic, mesophilic or thermophilic sources

A completely randomised study was completed to examine the influence of fibrolytic enzymes derived from psychrophilic, (F), mesophilic, (L) or thermophilic (Ta) sources, applied at ensiling, on the chemical characteristics and in vitro rumen fermentation of maize silage, assessed using the Reading Pressure Technique (RPT). Treatments, all in triplicate, consisted of untreated maize forage or treated with preparations F, L, Ta or a mixture (1: 1, v/v) of F and L (FL), at two levels each, and ensiled for 210 days in plastic mini-silos. Addition of enzymes L decreased (P < 0.05) silage pH relative to the control, whereas enzyme Ta tended (P < 0.10) to reduce it. Preparations F, L and Ta tended to reduce (P < 0.10) the fibre contents of the silages, with effects being attributable to a decrease in the cellulose fraction. Starch contents were reduced (P < 0.05) in the treatments including enzyme F. End-point (96 h) gas production (GP) values did not differ among treatments, suggesting that enzymes did not change the total amount of fermentable substrate. However, consistent with the decrease in starch contents, adding enzyme F reduced (P < 0.05) GP at most incubation times. Addition of enzymes increased (P < 0.05) the initial (6 h) organic matter degradation (OMD) levels in all but one treatment (F), with increases of 14, 19, and 26% for preparations L, Ta, and FL, respectively, averaged across levels. Furthermore, the addition of enzymes increased (P < 0.05) the soluble OM losses, however, these increases did not fully account for the initial increase in OMD. The latter suggests that enzymes increased solubility and also altered silage structure, making it more amenable to degradation by ruminal microorganisms. As a result of the increase in OMD, without a concomitant increase in GP, the fermentation efficiency was greatly increased (P < 0.05) in enzyme treatments. Addition of enzymes to maize at ensiling, particularly those from the mesophilic and thermophilic sources used here, have the potential to increase the initial rate of silage OMD. (C) 2003 Elsevier B.V. All rights reserved.

Recovery of nitrogen from different sources following applications to winter wheat at and after anthesis

The effects of applying nitrogen (30 or 40 kg N/ha) to wheat crops at and after anthesis, after 200 kg N/ha had already been applied to the soil during stem extension, were studied in field experiments comprising complete factorial combinations of different cultivars, fungicide applications and nitrogen treatments. Actual recoveries of late-season fertilizer nitrogen (LSFN), as indicated by N-15 studies, interacted with cultivar and fungicide treatment, and depended on nitrogen source (Urea applied as a solution to the foliage, or as ammonium nitrate applied to the soil) and year. These interactions, however, were not reflected in apparent fertilizer recoveries ((N in grain with LSFN - N in grain without LSFN)/N applied as LSFN), or in the crude protein concentration. Apparent fertilizer recovery was always lower than actual recoveries, and declined during grain filling. Fertilizer treatments with higher actual fertilizer recoveries were associated with lower net renlobilisation of non-LSFN (net remobilised N = N in above ground crop at anthesis - N in non-grain, above ground crop at harvest). LSFN also increased mineral nitrogen in the soil at harvest even when applied as a solution to the foliage. These effects are discussed in relation to potential grain N demand. (c) 2006 Elsevier B.V. All rights reserved.

An evaluation of different growth functions for describing the profile of live weight with time (age) in meat and egg strains of chicken

A total of 86 profiles from meat and egg strains of chickens (male and female) were used in this study. Different flexible growth functions were evaluated with regard to their ability to describe the relationship between live weight and age and were compared with the Gompertz and logistic equations, which have a fixed point of inflection. Six growth functions were used: Gompertz, logistic, Lopez, Richards, France, and von Bertalanffy. A comparative analysis was carried out based on model behavior and statistical performance. The results of this study confirmed the initial concern about the limitation of a fixed point of inflection, such as in the Gompertz equation. Therefore, consideration of flexible growth functions as an alternatives to the simpler equations (with a fixed point of inflection) for describing the relationship between live weight and age are recommended for the following reasons: they are easy to fit, they very often give a closer fit to data points because of their flexibility and therefore a smaller RSS value, than the simpler models, and they encompasses simpler models for the addition of an extra parameter, which is especially important when the behavior of a particular data set is not defined previously.

Field evaluation of systemic inducing resistance chemicals at different growth stages for the control of apple (Venturia inaequalis) and pear (Venturia pirina) scab

Two field trials were conducted using established apple (Malus cv. Golden Delicious) and pear (Pyrus communis 'Williams' Bon Chretien') to assess the efficacy of three commercially available systemic inducing resistance (SIR) products, Messenger (a.i. Harpin protein), Phoenix (a.i. Potassium phosphite) and Rigel (a.i. Salicylic acid derivative) applied at four different growth stages of tree development (bud break, green cluster, 90% petal fall, early fruitlet) against the foliar pathogens Venturia inaequalis and Venturia pirina which cause apple and pear scab respectively. A conventional synthetic fungicide (penconazole) used within the UK for apple and pear scab control was included for comparison. Little efficacy as scab protectants was demonstrated when each SIR product and penconazole was applied at only two growth stages (bud break, green cluster). However when the above compounds were applied at three or more growth stages efficacy as scab protectants was confirmed. The synthetic fungicide penconazole provided greatest protection against apple and pear scab in both the 2006 and 2007 field trials. There was little difference in the magnitude of scab protection conferred by each SIR agent. Results suggest application of at least three sprays during bud break to early fruitlet formation with an appropriate SIR agent may provide a useful addition to existing methods of apple and pear scab management under field conditions. (C) 2009 Published by Elsevier Ltd.

In vitro evaluation of the microbiota modulation abilities of different sized whole oat grain flakes.

Epidemiological studies and healthy eating guidelines suggest a positive correlation between ingestion of whole grain cereal and food rich in fibre with protection from chronic diseases. The prebiotic potential of whole grains may be related, however, little is known about the microbiota modulatory capability of oat grain or the impact processing has on this ability. In this study the fermentation profile of whole grain oat flakes, processed to produce two different sized flakes (small and large), by human faecal microbiota was investigated in vitro. Simulated digestion and subsequent fermentation by gut bacteria was investigated using pH controlled faecal batch cultures inoculated with human faecal slurry. The different sized oat flakes, Oat 23’s (0.53–0.63 mm) and Oat 25’s/26’s (0.85–1.0 mm) were compared to oligofructose, a confirmed prebiotic, and cellulose, a poorly fermented carbohydrate. Bacterial enumeration was carried out using the culture independent technique, fluorescent in situ hybridisation, and short chain fatty acid (SCFA) production monitored by gas chromatography. Significant changes in total bacterial populations were observed after 24 h incubation for all substrates except Oat 23’s and cellulose. Oats 23’s fermentation resulted in a significant increase in the Bacteroides–Prevotella group. Oligofructose and Oats 25’s/26’s produced significant increases in Bifidobacterium in the latter stages of fermentation while numbers declined for Oats 23’s between 5 h and 24 h. This is possibly due to the smaller surface area of the larger flakes inhibiting the simulated digestion, which may have resulted in increased levels of resistant starch (Bifidobacterium are known to ferment this dietary fibre). Fermentation of Oat 25’s/26’s resulted in a propionate rich SCFA profile and a significant increase in butyrate, which have both been linked to benefiting host health. The smaller sized oats did not produce a significant increase in butyrate concentration. This study shows for the first time the impact of oat grain on the microbial ecology of the human gut and its potential to beneficially modulate the gut microbiota through increasing Bifidobacterium population.

Evaluation of water and energy budgets in regional climate models applied over Europe

This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.

Evaluation of water and energy budgets in regional climate models applied over Europe

Abstract This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.

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.