909 resultados para Lead-time and set-up optimization
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Divorce and remarriage usually imply a redefinition of family boundaries, with consequences for the production and availability of social capital. This research shows that bonding and bridging social capitals are differentially made available by families. It first hypothesizes that bridging social capital is more likely to be developed in stepfamilies, and bonding social capital in first-time families. Second, the boundaries of family configurations are expected to vary within stepfamilies and within first-time families creating a diversity of family configurations within both structures. Third, in both cases, social capital is expected to depend on the ways in which their family boundaries are set up by individuals by including or excluding ex-partners, new partner's children, siblings, and other family ties. The study is based on a sample of 300 female respondents who have at least one child of their own between 5 and 13 years, 150 from a stepfamily structure and 150 from a first-time family structure. Social capital is empirically operationalized as perceived emotional support in family networks. The results show that individuals in first-time families more often develop bonding social capital and individuals in stepfamilies bridging social capital. In both cases, however, individuals in family configurations based on close blood and conjugal ties more frequently develop bonding social capital, whereas individuals in family configurations based on in-law, stepfamily or friendship ties are more likely to develop bridging social capital.
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OBJECTIVE: Before a patient can be connected to a mechanical ventilator, the controls of the apparatus need to be set up appropriately. Today, this is done by the intensive care professional. With the advent of closed loop controlled mechanical ventilation, methods will be needed to select appropriate start up settings automatically. The objective of our study was to test such a computerized method which could eventually be used as a start-up procedure (first 5-10 minutes of ventilation) for closed-loop controlled ventilation. DESIGN: Prospective Study. SETTINGS: ICU's in two adult and one children's hospital. PATIENTS: 25 critically ill adult patients (age > or = 15 y) and 17 critically ill children selected at random were studied. INTERVENTIONS: To stimulate 'initial connection', the patients were disconnected from their ventilator and transiently connected to a modified Hamilton AMADEUS ventilator for maximally one minute. During that time they were ventilated with a fixed and standardized breath pattern (Test Breaths) based on pressure controlled synchronized intermittent mandatory ventilation (PCSIMV). MEASUREMENTS AND MAIN RESULTS: Measurements of airway flow, airway pressure and instantaneous CO2 concentration using a mainstream CO2 analyzer were made at the mouth during application of the Test-Breaths. Test-Breaths were analyzed in terms of tidal volume, expiratory time constant and series dead space. Using this data an initial ventilation pattern consisting of respiratory frequency and tidal volume was calculated. This ventilation pattern was compared to the one measured prior to the onset of the study using a two-tailed paired t-test. Additionally, it was compared to a conventional method for setting up ventilators. The computer-proposed ventilation pattern did not differ significantly from the actual pattern (p > 0.05), while the conventional method did. However the scatter was large and in 6 cases deviations in the minute ventilation of more than 50% were observed. CONCLUSIONS: The analysis of standardized Test Breaths allows automatic determination of an initial ventilation pattern for intubated ICU patients. While this pattern does not seem to be superior to the one chosen by the conventional method, it is derived fully automatically and without need for manual patient data entry such as weight or height. This makes the method potentially useful as a start up procedure for closed-loop controlled ventilation.
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This Master's thesis is devoted to semiconductor samples study using time-resolved photoluminescence. This method allows investigating recombination in semiconductor samples in order to develop quality of optoelectronic device. An additional goal was the method accommodation for low-energy-gap materials. The first chapter gives a brief intercourse into the basis of semiconductor physics. The key features of the investigated structures are noted. The usage area of the results covers saturable semiconductor absorber mirrors, disk lasers and vertical-external-cavity surface-emittinglasers. The experiment set-up is described in the second chapter. It is based on up-conversion procedure using a nonlinear crystal and involving the photoluminescent emission and the gate pulses. The limitation of the method was estimated. The first series of studied samples were grown at various temperatures and they suffered rapid thermal annealing. Further, a latticematched and metamorphically grown samples were compared. Time-resolved photoluminescence method was adapted for wavelengths up to 1.5 µm. The results allowed to specify the optimal substrate temperature for MBE process. It was found that the lattice-matched sample and the metamorphically grown sample had similar characteristics.
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The aim of this thesis was to create a process for all multi-site ramp-up (MSRU) projects in the case company in order to have simultaneous ramp-ups early in the market. The research was done through case study in one company and semi-structured interviews. There are already processes, which are now in use in MSRU-cases. Interviews of 20 ramp-up specialists revealed topics to be improved. Those were project team set up, roles and responsibilities and recommended project organization, communication, product change management practices, competence and know how transfer practices and support model. More R&D support and involvement is needed in MSRU-projects. DCM’s role is very important in the MSRU-projects among PMT-team; he should be the business owner of the project. Recommendation is that product programs could take care of the product and repair training of new products in volume factories. R&D’s participation in competence transfers is essential important in MSRU-projects. Communication in projects could be shared through special intranet commune. Blogging and tweeting could be considered in the communication plan. If hundreds of change notes are open in ramp-up phase, it should be considered not to approve the product into volume ramp-up. PMTs’ supports are also important and MSRU-projects should be planned, budgeted and executed together. Finally a new MSRU-process is presented in this thesis to be used in all MSRU-projects.
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The objective of the present study was to investigate clinical, echocardiographic and electrocardiographic (12-lead resting ECG, 24-h ambulatory ECG monitoring and signal-averaged ECG (SAECG)) parameters in subjects with chronic Chagas' disease in a long-term follow-up as prognostic markers for adverse outcomes. Fifty adult outpatients (34 to 74 years old, 31 females) staged according to Los Andes class I, II or III and complaining of palpitation were enrolled in a longitudinal study. SAECG was analyzed in time and frequency domains and the endpoint was a composite of cardiac death and ventricular tachycardia. During a follow-up of 84.2 ± 39.0 months, 34.0% of the patients developed adverse outcomes (9 cardiac deaths and 11 episodes of ventricular tachycardia). After optimal dichotomization, in a stepwise multivariate Cox-hazard regression model, apical aneurysm (HR = 3.7; 95% CI = 1.2-1.3; P = 0.02), left ventricular ejection fraction <62% (HR = 4.60; 95% CI = 1.39-15.24; P = 0.01) and incidence of ventricular premature contractions >614 per 24 h (hazard ratio = 6.1; 95% CI = 1.7-22.6; P = 0.006) were independent predictors of the composite endpoint. Although a high frequency content in SAECG demonstrated association with the presence of left ventricular dysfunction and myocardial fibrosis, its predictive value for the composite endpoint was not significant. Apical aneurysms, reduced left ventricular function and a high incidence of ventricular ectopic beats over a 24-h period have a strong predictive value for a composite endpoint of cardiac death and ventricular tachycardia in subjects with chronic Chagas' disease.
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Niagara Peninsula of Ontario is the largest viticultural area in Canada. Although it is considered to be a cool and wet region, in the last decade many water stress events occurred during the growing seasons with negative effects on grape and wine quality. This study was initiated to understand and develop the best strategies for water management in vineyards and those that might contribute to grape maturity advancement. The irrigation trials investigated the impact of time of initiation (fruit set, lag phase and veraison), water replacement level based on theoretical loss through crop evapotranspiration (ETc; 100,50 and 25%) and different irrigation strategies [partial root zone drying (PRD) versus regulated deficit irrigation (RD!)] on grape composition and wine sensory profiles. The irrigation experiments were conducted in a commercial vineyard (Lambert Vineyards Inc.) located in Niagara-on-the-Lake, Ontario, from 2005 through 2009. The two experiments that tested the combination of different water regimes and irrigation time initiation were set up in a randomized block design as follows: Baco noir - three replicates x 10 treatments [(25%, 50% and 100% of ETc) x (initiation at fruit set, lag phase and veraison) + control]; Chardonnay - three replicates x seven treatments [(25%, 50% and 100% of ETc) x (initiation at fruit set and veraison) + control]. The experiments that tested different irrigation strategies were set up on two cultivars as follows: Sauvignon blanc - four replicates x four treatments [control, fully irrigated (100% ETc), PRD (100% ETc) and RDI (25% ETc)]; Cabemet Sauvignon - four replicates x five treatments [control, fully irrigated (100% ETc), PRD (100% ETc), RDI (50% ETc) and RDI (25% ETc)]. The controls in each experiment were nonirrigated. The irrigation treatments were compared for many variables related to soil water status, vine physiology, berry composition, wine sensory profile, and hormone composition [(abscisic acid (ABA) and its catabolites]. Soil moisture profile was mostly affected by irrigation treatments between 20 and 60 em depth depending on the grapevine cultivar and the regime of water applied. Overall soil moisture was consistently higher throughout the season in 100 and 50% ETc compare to the control. Transpiration rates and leaf temperature as well as shoot growth rate were the most sensitive variables to soil water status. Drip irrigation associated with RDI treatments (50% ETc and 25% ETc) had the most beneficial effects on vine physiology, fruit composition and wine varietal typicity, mainly by maintaining a balance between vegetative and reproductive parts of the vine. Neither the control nor the 100 ETc had overall a positive effect on grape composition and wine sensory typicity. The time of irrigation initiation affected the vine physiology and grape quality, the most positive effect was found in treatments initiated at lag phase and veraison. RDI treatments were overall more consistent in their positive effect on grape composition and wine varietal typicity comparing to PRD treatment. The greatest difference between non-irrigated and irrigated vines in most of the variables studied was found in 2007, the driest and hottest season of the experimental period. Soil water status had a greater and more consistent effect on red grapevine cultivars rather than on white winegrape cultivars. To understand the relationships among soil and plant water status, plant physiology and the hormonal profiles associated with it, abscisic acid (ABA) and its catabolites [phaseic acid (PA), dihydrophaseic acid (DPA), 7-hydroxy-ABA (TOH-ABA), 8' -hydroxy-ABA, neophaseic acid and abscisic acid glucose ester (ABA-GE)] were analyzed in leaves and berries from the Baco noir and Chardonnay irrigation trials over two growing seasons. ABA and some of its catabolites accurately described the water status in the vines. Endogenous ABA and some of its catabolites were strongly affected in Baco noir and Chardonnay by both the water regime (i.e. ET level) and timing of irrigation initiation. Chardonnay grapevines produced less ABA in both leaves and berries compared to Baco noir, which indicated that ABA synthesis is also cultivar dependant. ABA-GE was the main catabolite in treatments with high water deficits, while PA and DPA were higher in treatments with high water status, suggesting that the vine produced more ABA-GE under water deficits to maintain rapid control of the stomata. These differences between irrigation treatments with respect to ABA and catabolites were particularly noticeable in the dry 2007 season. Two trials using exogenous ABA investigated the effect of different concentrations of ABA and organs targeted for spraying, on grape maturation and berry composition of Cabemet Sauvignon grapevines, in two cool and wet seasons (2008-2009). The fIrst experiment consisted of three replicates x three treatments [(150 and 300 mg/L, both applications only on clusters) + untreated control] while the second experiment consisted in three replicates x four treatments [(full canopy, only clusters, and only leaves sprayed with 300 ppm ABA) + untreated control]. Exogenous ABA was effective in hastening veraison, and improving the composition of Cabemet Sauvignon. Ability of ABA to control the timing of grape berry maturation was dependant on both solution concentration and the target organ. ABA affected not only fruit composition but also yield components. Berries treated with ABA had lower weight and higher skin dry mass, which constitutes qualitative aspects desired in the wine grapes. Temporal advancement of ripening through hormonal control can lead to earlier fruit maturation, which is a distinct advantage in cooler areas or areas with a high risk of early frost occurrence. Exogenous ABA could provide considerable benefits to wine industry in terms of grape composition, wine style and schedule activities in the winery, particularly in wet and cool years. These trials provide the ftrst comprehensive data in eastern North America on the response of important hybrid and Vitis vinifera winegrape cultivars to irrigation management. Results from this study additionally might be a forward step in understanding the ABA metabolism, and its relationship with water status. Future research should be focused on ftnding the ABA threshold required to trigger the ripening process, and how this process could be controlled in cool climates.
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L’apprentissage supervisé de réseaux hiérarchiques à grande échelle connaît présentement un succès fulgurant. Malgré cette effervescence, l’apprentissage non-supervisé représente toujours, selon plusieurs chercheurs, un élément clé de l’Intelligence Artificielle, où les agents doivent apprendre à partir d’un nombre potentiellement limité de données. Cette thèse s’inscrit dans cette pensée et aborde divers sujets de recherche liés au problème d’estimation de densité par l’entremise des machines de Boltzmann (BM), modèles graphiques probabilistes au coeur de l’apprentissage profond. Nos contributions touchent les domaines de l’échantillonnage, l’estimation de fonctions de partition, l’optimisation ainsi que l’apprentissage de représentations invariantes. Cette thèse débute par l’exposition d’un nouvel algorithme d'échantillonnage adaptatif, qui ajuste (de fa ̧con automatique) la température des chaînes de Markov sous simulation, afin de maintenir une vitesse de convergence élevée tout au long de l’apprentissage. Lorsqu’utilisé dans le contexte de l’apprentissage par maximum de vraisemblance stochastique (SML), notre algorithme engendre une robustesse accrue face à la sélection du taux d’apprentissage, ainsi qu’une meilleure vitesse de convergence. Nos résultats sont présent ́es dans le domaine des BMs, mais la méthode est générale et applicable à l’apprentissage de tout modèle probabiliste exploitant l’échantillonnage par chaînes de Markov. Tandis que le gradient du maximum de vraisemblance peut-être approximé par échantillonnage, l’évaluation de la log-vraisemblance nécessite un estimé de la fonction de partition. Contrairement aux approches traditionnelles qui considèrent un modèle donné comme une boîte noire, nous proposons plutôt d’exploiter la dynamique de l’apprentissage en estimant les changements successifs de log-partition encourus à chaque mise à jour des paramètres. Le problème d’estimation est reformulé comme un problème d’inférence similaire au filtre de Kalman, mais sur un graphe bi-dimensionnel, où les dimensions correspondent aux axes du temps et au paramètre de température. Sur le thème de l’optimisation, nous présentons également un algorithme permettant d’appliquer, de manière efficace, le gradient naturel à des machines de Boltzmann comportant des milliers d’unités. Jusqu’à présent, son adoption était limitée par son haut coût computationel ainsi que sa demande en mémoire. Notre algorithme, Metric-Free Natural Gradient (MFNG), permet d’éviter le calcul explicite de la matrice d’information de Fisher (et son inverse) en exploitant un solveur linéaire combiné à un produit matrice-vecteur efficace. L’algorithme est prometteur: en terme du nombre d’évaluations de fonctions, MFNG converge plus rapidement que SML. Son implémentation demeure malheureusement inefficace en temps de calcul. Ces travaux explorent également les mécanismes sous-jacents à l’apprentissage de représentations invariantes. À cette fin, nous utilisons la famille de machines de Boltzmann restreintes “spike & slab” (ssRBM), que nous modifions afin de pouvoir modéliser des distributions binaires et parcimonieuses. Les variables latentes binaires de la ssRBM peuvent être rendues invariantes à un sous-espace vectoriel, en associant à chacune d’elles, un vecteur de variables latentes continues (dénommées “slabs”). Ceci se traduit par une invariance accrue au niveau de la représentation et un meilleur taux de classification lorsque peu de données étiquetées sont disponibles. Nous terminons cette thèse sur un sujet ambitieux: l’apprentissage de représentations pouvant séparer les facteurs de variations présents dans le signal d’entrée. Nous proposons une solution à base de ssRBM bilinéaire (avec deux groupes de facteurs latents) et formulons le problème comme l’un de “pooling” dans des sous-espaces vectoriels complémentaires.
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Le présent mémoire décrit le développement d’une méthode de synthèse des hélicènes catalysée par la lumière visible. Les conditions pour la formation de [5]hélicène ont été établies par une optimisation du photocatalyseur, du solvant, du système d’oxydation et du temps réactionnel. Suite aux études mécanistiques préliminaires, un mécanisme oxydatif est proposé. Les conditions optimisées ont été appliquées à la synthèse de [6]hélicènes pour laquelle la régiosélectivité a été améliorée en ajoutant des substituants sur la colonne hélicale. La synthèse de thiohélicènes a aussi été testée en utilisant les mêmes conditions sous irradiation par la lumière visible. La méthode a été inefficace pour la formation de benzodithiophènes et de naphtothiophènes, par contre elle permet la formation du phenanthro[3,4-b]thiophène avec un rendement acceptable. En prolongeant la surface-π de la colonne hélicale, le pyrène a été fusionné aux motifs de [4]- et [5]hélicène. Trois dérivés de pyrène-hélicène ont été synthétisés en utilisant les conditions optimisées pour la photocyclisation et leurs caractéristiques physiques ont été étudiées. La méthode de cyclisation sous l’action de la lumière visible a aussi été étudiée en flux continu. Une optimisation du montage expérimental ainsi que de la source lumineuse a été effectuée et les meilleures conditions ont été appliquées à la formation de [5]hélicène et des trois dérivés du pyrène-hélicène. Une amélioration ou conservation des rendements a été observée pour la plupart des produits formés en flux continu comparativement à la synthèse en batch. La concentration de la réaction a aussi été conservée et le temps réactionnel a été réduit par un facteur de dix toujours en comparaison avec la synthèse en batch.
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The main source of protein for human and animal consumption is from the agricultural sector, where the production is vulnerable to diseases, fluctuations in climatic conditions and deteriorating hydrological conditions due to water pollution. Therefore Single Cell Protein (SCP) production has evolved as an excellent alternative. Among all sources of microbial protein, yeast has attained global acceptability and has been preferred for SCP production. The screening and evaluation of nutritional and other culture variables of microorganisms are very important in the development of a bioprocess for SCP production. The application of statistical experimental design in bioprocess development can result in improved product yields, reduced process variability, closer confirmation of the output response to target requirements and reduced development time and overall cost.The present work was undertaken to develop a bioprocess technology for the mass production of a marine yeast, Candida sp.S27. Yeasts isolated from the offshore waters of the South west coast of India and maintained in the Microbiology Laboratory were subjected to various tests for the selection of a potent strain for biomass production. The selected marine yeast was identified based on ITS sequencing. Biochemical/nutritional characterization of Candida sp.S27 was carried out. Using Response Surface Methodology (RSM) the process parameters (pH, temperature and salinity) were optimized. For mass production of yeast biomass, a chemically defined medium (Barnett and Ingram, 1955) and a crude medium (Molasses-Yeast extract) were optimized using RSM. Scale up of biomass production was done in a Bench top Fermenter using these two optimized media. Comparative efficacy of the defined and crude media were estimated besides nutritional evaluation of the biomass developed using these two optimized media.
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The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.
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The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.
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Bone meal amendments are being considered as a remediation method for metal-contaminated wastes. In various forms (biogenic, geogenic or synthetic), apatite, the principal mineral constituent of bone, has shown promise as an amendment to remediate metal-contaminated soils via the formation of insoluble phosphates of Pb and possibly other metals. The efficacy of commercially available bovine bone meal in this role was investigated in a field trial at Nenthead, Cumbria with a mine waste derived soil contaminated with Zn, Pb and Cd. Two 5 m(2) plots were set up: the first as a control and the second, a treatment plot where the soil was thoroughly mixed with bone meal to a depth of 50 cm at a soil to amendment ratio of 25:1 by weight. An array of soil solution samplers (Rhizon SMS (TM)) were installed in both plots and the soil pore water was collected and analysed for Ca, Cd, Zn and Pb regularly over a period of 2 a. Concurrently with the field trial, a laboratory trial with 800 mm high and 100 mm wide leaching Columns Was conducted using identical samplers and with soil from the held site. A substantial release of Zn, Pb, Cd and Ca was observed associated with the bone meal treatment. This release was transient in the case of the leaching columns, and showed seasonal variation in the case of the field trial. It is proposed that this effect resulted from metal complexation with organic acids released during breakdown of the bone meal organic fraction and was facilitated by the relatively high soil pH of 7.6-8.0. Even after this transient release effect had subsided or when incinerated bone meal was substituted in order to eliminate the organic fraction, no detectable decrease in dissolved metals was observed and no P was detected in solution, in contrast with an earlier small column laboratory study. It is concluded that due to the relative insolubility of apatite at above-neutral pH, the rate of supply of phosphate to soil solution was insufficient to result in significant precipitation of metal phosphates and that this may limit the effectiveness of the method to more acidic soils. (c) 2008 Elsevier Ltd. All rights reserved.
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Drought is a global problem that has far-reaching impacts and especially 47 on vulnerable populations in developing regions. This paper highlights the need for a Global Drought Early Warning System (GDEWS), the elements that constitute its underlying framework (GDEWF) and the recent progress made towards its development. Many countries lack drought monitoring systems, as well as the capacity to respond via appropriate political, institutional and technological frameworks, and these have inhibited the development of integrated drought management plans or early warning systems. The GDEWS will provide a source of drought tools and products via the GDEWF for countries and regions to develop tailored drought early warning systems for their own users. A key goal of a GDEWS is to maximize the lead time for early warning, allowing drought managers and disaster coordinators more time to put mitigation measures in place to reduce the vulnerability to drought. To address this, the GDEWF will take both a top-down approach to provide global real-time drought monitoring and seasonal forecasting, and a bottom-up approach that builds upon existing national and regional systems to provide continental to global coverage. A number of challenges must be overcome, however, before a GDEWS can become a reality, including the lack of in-situ measurement networks and modest seasonal forecast skill in many regions, and the lack of infrastructure to translate data into useable information. A set of international partners, through a series of recent workshops and evolving collaborations, has made progress towards meeting these challenges and developing a global system.
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Drinking water utilities in urban areas are focused on finding smart solutions facing new challenges in their real-time operation because of limited water resources, intensive energy requirements, a growing population, a costly and ageing infrastructure, increasingly stringent regulations, and increased attention towards the environmental impact of water use. Such challenges force water managers to monitor and control not only water supply and distribution, but also consumer demand. This paper presents and discusses novel methodologies and procedures towards an integrated water resource management system based on advanced ICT technologies of automation and telecommunications for largely improving the efficiency of drinking water networks (DWN) in terms of water use, energy consumption, water loss minimization, and water quality guarantees. In particular, the paper addresses the first results of the European project EFFINET (FP7-ICT2011-8-318556) devoted to the monitoring and control of the DWN in Barcelona (Spain). Results are split in two levels according to different management objectives: (i) the monitoring level is concerned with all the aspects involved in the observation of the current state of a system and the detection/diagnosis of abnormal situations. It is achieved through sensors and communications technology, together with mathematical models; (ii) the control level is concerned with computing the best suitable and admissible control strategies for network actuators as to optimize a given set of operational goals related to the performance of the overall system. This level covers the network control (optimal management of water and energy) and the demand management (smart metering, efficient supply). The consideration of the Barcelona DWN as the case study will allow to prove the general applicability of the proposed integrated ICT solutions and their effectiveness in the management of DWN, with considerable savings of electricity costs and reduced water loss while ensuring the high European standards of water quality to citizens.
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The biosorption of Cd(II) and Pb(II) ions on biomass and exopolysaccharide (EPS) produced by Colletotrichum sp. fungus has been investigated as a function of contact time, initial pH, initial metal ion concentration, and initial adsorbent concentration in a batch system. Adsorption equilibrium was described by Freundlich and Langmuir isotherms. Adsorption was characterized through granulometry, SEM and EDX analysis. Then, studies were performed to regenerate the adsorbent. Biosorption of metals by biomass and EPS were best described by the Langmuir and Freundlich isotherm, respectively. Results of thermodynamic investigations showed that adsorption reactions were spontaneous (ΔG° < 0), exothermal, and mainly physical. The EPS was able to remove 79 and 98% of cadmium and lead, respectively, and the biomass removed 85 and 84% of cadmium and lead, respectively, in a solution with initial concentration 100 mg L-1, and the four adsorption-desorption cycles of all adsorbents showed up with great regenerative capacity and relative stability after these four cycles, the high potential of these biological materials in sorption has been shown. © 2013 Copyright Balaban Desalination Publications.