The role of CO2 and dynamic vegetation on the impact of temperate land use change in the HadCM3 coupled climate model

Human induced land-use change (LUC) alters the biogeophysical characteristics of the land surface influencing the surface energy balance. The level of atmospheric CO2 is expected to increase in the coming century and beyond, modifying temperature and precipitation patterns and altering the distribution and physiology of natural vegetation. It is important to constrain how CO2-induced climate and vegetation change may influence the regional extent to which LUC alters climate. This sensitivity study uses the HadCM3 coupled climate model under a range of equilibrium forcings to show that the impact of LUC declines under increasing atmospheric CO2, specifically in temperate and boreal regions. A surface energy balance analysis is used to diagnose how these changes occur. In Northern Hemisphere winter this pattern is attributed in part to the decline in winter snow cover and in the summer due to a reduction in latent cooling with higher levels of CO2. The CO2-induced change in natural vegetation distribution is also shown to play a significant role. Simulations run at elevated CO2 yet present day vegetation show a significantly increased sensitivity to LUC, driven in part by an increase in latent cooling. This study shows that modelling the impact of LUC needs to accurately simulate CO2 driven changes in precipitation and snowfall, and incorporate accurate, dynamic vegetation distribution.

A low mortality, high morbidity reduced intensity status epilepticus (RISE) model of epilepsy and epileptogenesis in the rat

Animal models of acquired epilepsies aim to provide researchers with tools for use in understanding the processes underlying the acquisition, development and establishment of the disorder. Typically, following a systemic or local insult, vulnerable brain regions undergo a process leading to the development, over time, of spontaneous recurrent seizures. Many such models make use of a period of intense seizure activity or status epilepticus, and this may be associated with high mortality and/or global damage to large areas of the brain. These undesirable elements have driven improvements in the design of chronic epilepsy models, for example the lithium-pilocarpine epileptogenesis model. Here, we present an optimised model of chronic epilepsy that reduces mortality to 1% whilst retaining features of high epileptogenicity and development of spontaneous seizures. Using local field potential recordings from hippocampus in vitro as a probe, we show that the model does not result in significant loss of neuronal network function in area CA3 and, instead, subtle alterations in network dynamics appear during a process of epileptogenesis, which eventually leads to a chronic seizure state. The model’s features of very low mortality and high morbidity in the absence of global neuronal damage offer the chance to explore the processes underlying epileptogenesis in detail, in a population of animals not defined by their resistance to seizures, whilst acknowledging and being driven by the 3Rs (Replacement, Refinement and Reduction of animal use in scientific procedures) principles.

A mathematical model for the dynamics of Banana Xanthomonas Wilt with vertical transmission and inflorescence infection

A mathematical model for Banana Xanthomonas Wilt (BXW) spread by insect is presented. The model incorporates inflorescence infection and vertical transmission from the mother corm to attached suckers, but not tool-based transmission by humans. Expressions for the basic reproduction number R0 are obtained and it is verified that disease persists, at a unique endemic level, when R0 > 1. From sensitivity analysis, inflorescence infection rate and roguing rate were the parameters with most influence on disease persistence and equilibrium level. Vertical transmission parameters had less effect on persistence threshold values. Parameters were approximately estimated from field data. The model indicates that single stem removal is a feasible approach to eradication if spread is mainly via inflorescence infection. This requires continuous surveillance and debudding such that a 50% reduction in inflorescence infection and 2–3 weeks interval of surveillance would eventually lead to full recovery of banana plantations and hence improved production.

IPCC global coupled model simulations of the South America monsoon system

This study examines the variability of the South America monsoon system (SAMS) over tropical South America (SA). The onset, end, and total rainfall during the summer monsoon are investigated using precipitation pentad estimates from the global precipitation climatology project (GPCP) 1979-2006. Likewise, the variability of SAMS characteristics is examined in ten Intergovernmental Panel on Climate Change (IPCC) global coupled climate models in the twentieth century (1981-2000) and in a future scenario of global change (A1B) (2081-2100). It is shown that most IPCC models misrepresent the intertropical convergence zone and therefore do not capture the actual annual cycle of precipitation over the Amazon and northwest SA. Most models can correctly represent the spatiotemporal variability of the annual cycle of precipitation in central and eastern Brazil such as the correct phase of dry and wet seasons, onset dates, duration of rainy season and total accumulated precipitation during the summer monsoon for the twentieth century runs. Nevertheless, poor representation of the total monsoonal precipitation over the Amazon and northeast Brazil is observed in a large majority of the models. Overall, MI-ROC3.2-hires, MIROC3.2-medres and MRI-CGCM3.2.3 show the most realistic representation of SAMS`s characteristics such as onset, duration, total monsoonal precipitation, and its interannual variability. On the other hand, ECHAM5, GFDL-CM2.0 and GFDL-CM2.1 have the least realistic representation of the same characteristics. For the A1B scenario the most coherent feature observed in the IPCC models is a reduction in precipitation over central-eastern Brazil during the summer monsoon, comparatively with the present climate. The IPCC models do not indicate statistically significant changes in SAMS onset and demise dates for the same scenario.

Celecoxib prevents tumor growth in an animal model by a COX-2 independent mechanism

Nonsteroidal antiinflammatory drugs (NSAIDs) have been shown to reduce cell growth in several tumors. Among these possible antineoplastic drugs are cyclooxygenase-2 (COX-2)-selective drugs, such as celecoxib, in which antitumoral mechanisms were evaluated in rats bearing Walker-256 (W256) tumor. W256 carcinosarcoma cells were inoculated subcutaneously (10(7) cells/rat) in rats submitted to treatment with celecoxib (25 mg kg(-1)) or vehicle for 14 days. Tumor growth, body-weight gain, and survival data were evaluated. The mechanisms, such as COX-2 expression and activity, oxidative stress, by means of enzymes and lipoperoxidation levels, and apoptosis mediators were also investigated. A reduction in tumor growth and an increased weight gain were observed. Celecoxib provided a higher incidence of survival compared with the control group. Cellular effects are probably COX-2 independent, because neither enzyme expression nor its activity, measured by tumoral PGE(2), showed significant difference between groups. It is probable that this antitumor action is dependent on an apoptotic way, which has been evaluated by the expression of the antiapoptotic protein Bcl-xL, in addition to the cellular changes observed by electronic microscopy. Celecoxib has also a possible involvement with redox homeostasis, because its administration caused significant changes in the activity of oxidative enzymes, such as catalase and superoxide dismutase. These results confirm the antitumor effects of celecoxib in W256 cancer model, contributing to elucidating its antitumoral mechanism and corroborating scientific literature about its effect on other types of cancer.

An artificial nanoemulsion carrying paclitaxel decreases the transplant heart vascular disease: A study in a rabbit graft model

Objective: In previous studies cholesterol-rich nanoemulsions (LDE) resembling low-density lipoprotein were shown to concentrate in atherosclerotic lesions of rabbits. Lesions were pronouncedly reduced by treatment with paclitaxel associated with LDE. This study aimed to test the hypothesis of whether LDE-paclitaxel is able to concentrate in grafted hearts of rabbits and to ameliorate coronary allograft vasculopathy after the transplantation procedure. Methods: Twenty-one New Zealand rabbits fed 0.5% cholesterol were submitted to heterotopic heart transplantation at the cervical position. All rabbits undergoing transplantation were treated with cyclosporin A (10 mg . kg(-1) . d(-1) by mouth). Eleven rabbits were treated with LDE-paclitaxel (4 mg/kg body weight paclitaxel per week administered intravenously for 6 weeks), and 10 control rabbits were treated with 3 mL/wk intravenous saline. Four control animals were injected with LDE labeled with [(14)C]-cholesteryl oleate ether to determine tissue uptake. Results: Radioactive LDE uptake by grafts was 4-fold that of native hearts. In both groups the coronary arteries of native hearts showed no stenosis, but treatment with LDE-paclitaxel reduced the degree of stenosis in grafted hearts by 50%. The arterial luminal area in grafts of the treated group was 3-fold larger than in control animals. LDE-paclitaxel treatment resulted in a 7-fold reduction of macrophage infiltration. In grafted hearts LDE-paclitaxel treatment reduced the width of the intimal layer and inhibited the destruction of the medial layer. No toxicity was observed in rabbits receiving LDE-paclitaxel treatment. Conclusions: LDE-paclitaxel improved posttransplantation injury to the grafted heart. The novel therapeutic approach for heart transplantation management validated here is thus a promising strategy to be explored in future clinical studies. (J Thorac Cardiovasc Surg 2011;141:1522-8)

A reduction of CETP activity, not an increase, is associated with modestly impaired postprandial lipemia and increased HDL-Cholesterol in adult asymptomatic women

Background: The relationship between CETP and postprandial hyperlipemia is still unclear. We verified the effects of varying activities of plasma CETP on postprandial lipemia and precocious atherosclerosis in asymptomatic adult women. Methods: Twenty-eight women, selected from a healthy population sample (n = 148) were classified according to three CETP levels, all statistically different: CETP deficiency (CETPd <= 4.5%, n = 8), high activity (CETPi >= 23.8, n = 6) and controls (CTL, CETP >= 4.6% and <= 23.7%, n = 14). After a 12 h fast they underwent an oral fat tolerance test (40 g of fat/m(2) of body surface area) for 8 hours. TG, TG-rich-lipoproteins (TRL), cholesterol and TRL-TG measurements (AUC, AUIC, AR, RR and late peaks) and comparisons were performed on all time points. Lipases and phospholipids transfer protein (PLTP) were determined. Correlation between carotid atherosclerosis (c-IMT) and postprandial parameters was determined. CETP TaqIB and I405V and ApoE-epsilon 3/epsilon 2/epsilon 4 polymorphisms were examined. To elucidate the regulation of increased lipemia in CETPd a multiple linear regression analysis was performed. Results: In the CETPi and CTL groups, CETP activity was respectively 9 and 5.3 higher compared to the CETPd group. Concentrations of all HDL fractions and ApoA-I were higher in the CETPd group and clearance was delayed, as demonstrated by modified lipemia parameters (AUC, AUIC, RR, AR and late peaks and meal response patterns). LPL or HL deficiencies were not observed. No genetic determinants of CETP deficiency or of postprandial lipemia were found. Correlations with c-IMT in the CETPd group indicated postprandial pro-atherogenic associations. In CETPd the regression multivariate analysis (model A) showed that CETP was largely and negatively predicted by VLDL-C lipemia (R(2) = 92%) and much less by TG, LDL-C, ApoAI, phospholipids and non-HDL-C. CETP (model B) influenced mainly the increment in ApoB-100 containing lipoproteins (R(2) = 85% negatively) and phospholipids (R(2) = 13%), at the 6(th)h point. Conclusion: The moderate CETP deficiency phenotype included a paradoxically high HDL-C and its sub fractions (as earlier described), positive associations with c-IMT, a postprandial VLDL-C increment predicting negatively CETP activity and CETP activity regulating inversely the increment in ApoB100-containing lipoproteins. We hypothesize that the enrichment of TG content in triglyceride-rich ApoB-containing lipoproteins and in TG rich remnants increases lipoproteins` competition to active lipolysis sites, reducing their catabolism and resulting on postprandial lipemia with atherogenic consequences.

Reduction of Models in the Presence of Nuisance Parameters

In many statistical inference problems, there is interest in estimation of only some elements of the parameter vector that defines the adopted model. In general, such elements are associated to measures of location and the additional terms, known as nuisance parameters, to control the dispersion and asymmetry of the underlying distributions. To estimate all the parameters of the model and to draw inferences only on the parameters of interest. Depending on the adopted model, this procedure can be both algebraically is common and computationally very costly and thus it is convenient to reduce it, so that it depends only on the parameters of interest. This article reviews estimation methods in the presence of nuisance parameters and consider some applications in models recently discussed in the literature.

Synthesis of NiO-MgO-ZrO(2) catalysts and their performance in reforming of model biogas

Catalysts containing NiO/MgO/ZrO(2) mixtures were synthesized by the polymerization method in a single step. They were characterized by X-ray diffraction (XRD), temperature programmed reduction (TPR) and physisorption of N(2) (BET) and then tested in the reforming of a model biogas (1.5CH4:1CO(2)) in the presence of air (1.5CH(4) + 1CO(2) + 0.25O(2)) at 750 degrees C for 6h. It was observed that the catalyst Ni20MZ performed better in catalytic processes than the well known catalysts, Ni/ZrO(2) and Ni/MgO, synthesized under the same conditions. The formation of solid solutions, MgO-ZrO(2) and NiO-MgO, increased the rate of conversion of reactants (CH(4) and CO(2)) into synthesis gas (H(2) + CO). The formation of oxygen vacancies (in samples containing ZrO(2) and MgO) seems to promote removal of the coke deposited on the nickel surface. The values of the H(2)/CO ratio were generally found to be slightly lower than stoichiometric, owing to the reverse water gas shift reaction occurring in parallel. (C) 2011 Elsevier B.V. All rights reserved.

City Of Toronto’S Approach On Implementing The New Federal Wastewater Effluent Regulations Using A GIS-Based Hydrologic And Hydraulic Model

Canada releases over 150 billion litres of untreated and undertreated wastewater into the water environment every year1. To clean up urban wastewater, new Federal Wastewater Systems Effluent Regulations (WSER) on establishing national baseline effluent quality standards that are achievable through secondary wastewater treatment were enacted on July 18, 2012. With respect to the wastewater from the combined sewer overflows (CSO), the Regulations require the municipalities to report the annual quantity and frequency of effluent discharges. The City of Toronto currently has about 300 CSO locations within an area of approximately 16,550 hectares. The total sewer length of the CSO area is about 3,450 km and the number of sewer manholes is about 51,100. A system-wide monitoring of all CSO locations has never been undertaken due to the cost and practicality. Instead, the City has relied on estimation methods and modelling approaches in the past to allow funds that would otherwise be used for monitoring to be applied to the reduction of the impacts of the CSOs. To fulfill the WSER requirements, the City is now undertaking a study in which GIS-based hydrologic and hydraulic modelling is the approach. Results show the usefulness of this for 1) determining the flows contributing to the combined sewer system in the local and trunk sewers for dry weather flow, wet weather flow, and snowmelt conditions; 2) assessing hydraulic grade line and surface water depth in all the local and trunk sewers under heavy rain events; 3) analysis of local and trunk sewer capacities for future growth; and 4) reporting of the annual quantity and frequency of CSOs as per the requirements in the new Regulations. This modelling approach has also allowed funds to be applied toward reducing and ultimately eliminating the adverse impacts of CSOs rather than expending resources on unnecessary and costly monitoring.

Optimal Rehabilitation Strategy In Water Distribution Systems Considering Reduction In Greenhouse Gas Emissions

Most of water distribution systems (WDS) need rehabilitation due to aging infrastructure leading to decreasing capacity, increasing leakage and consequently low performance of the WDS. However an appropriate strategy including location and time of pipeline rehabilitation in a WDS with respect to a limited budget is the main challenge which has been addressed frequently by researchers and practitioners. On the other hand, selection of appropriate rehabilitation technique and material types is another main issue which has yet to address properly. The latter can affect the environmental impacts of a rehabilitation strategy meeting the challenges of global warming mitigation and consequent climate change. This paper presents a multi-objective optimization model for rehabilitation strategy in WDS addressing the abovementioned criteria mainly focused on greenhouse gas (GHG) emissions either directly from fossil fuel and electricity or indirectly from embodied energy of materials. Thus, the objective functions are to minimise: (1) the total cost of rehabilitation including capital and operational costs; (2) the leakage amount; (3) GHG emissions. The Pareto optimal front containing optimal solutions is determined using Non-dominated Sorting Genetic Algorithm NSGA-II. Decision variables in this optimisation problem are classified into a number of groups as: (1) percentage proportion of each rehabilitation technique each year; (2) material types of new pipeline for rehabilitation each year. Rehabilitation techniques used here includes replacement, rehabilitation and lining, cleaning, pipe duplication. The developed model is demonstrated through its application to a Mahalat WDS located in central part of Iran. The rehabilitation strategy is analysed for a 40 year planning horizon. A number of conventional techniques for selecting pipes for rehabilitation are analysed in this study. The results show that the optimal rehabilitation strategy considering GHG emissions is able to successfully save the total expenses, efficiently decrease the leakage amount from the WDS whilst meeting environmental criteria.

Development and evaluation of a range anxiety-reducing business model for connected full electric vehicles

This thesis develops and evaluates a business model for connected full electric vehicles (FEV) for the European market. Despite a promoting political environment, various barriers have thus far prevented the FEV from becoming a mass-market vehicle. Besides cost, the most noteworthy of these barriers is represented by range anxiety, a product of FEVs’ limited range, lacking availability of charging infrastructure, and long recharging times. Connected FEVs, which maintain a constant connection to the surrounding infrastructure, appear to be a promising element to overcome drivers’ range anxiety. Yet their successful application requires a well functioning FEV ecosystem which can only be created through the collaboration of various stakeholders such as original equipment manufacturers (OEM), first tier suppliers (FTS), charging infrastructure and service providers (CISP), utilities, communication enablers, and governments. This thesis explores and evaluates how a business model, jointly created by these stakeholders, could look like, i.e. how stakeholders could collaborate in the design of products, services, infrastructure, and advanced mobility management, to meet drivers with a sensible value proposition that is at least equivalent to that of internal combustion engine (ICE) cars. It suggests that this value proposition will be an end-2-end package provided by CISPs or OEMs that comprises mobility packages (incl. pay per mile plans, battery leasing, charging and battery swapping (BS) infrastructure) and FEVs equipped with an on-board unit (OBU) combined with additional services targeted at range anxiety reduction. From a theoretical point of view the thesis answers the question which business model framework is suitable for the development of a holistic, i.e. all stakeholder-comprising business model for connected FEVs and defines such a business model. In doing so the thesis provides the first comprehensive business model related research findings on connected FEVs, as prior works focused on the much less complex scenario featuring only “offline” FEVs.

From commitment to non-commitment: allowing type dynamic in Laffont and Tirole's regulation model

This paper investigates the introduction of type dynamic in the La ont and Tirole's regulation model. The regulator and the rm are engaged in a two period relationship governed by short-term contracts, where, the regulator observes cost but cannot distinguish how much of the cost is due to e ort on cost reduction or e ciency of rm's technology, named type. There is asymmetric information about the rm's type. Our model is developed in a framework in which the regulator learns with rm's choice in the rst period and uses that information to design the best second period incentive scheme. The regulator is aware of the possibility of changes in types and takes that into account. We show how type dynamic builds a bridge between com- mitment and non-commitment situations. In particular, the possibility of changing types mitigates the \ratchet e ect". We show that for small degree of type dynamic the equilibrium shows separation and the welfare achived is close to his upper bound (given by the commitment allocation).

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Bank networks and firm credit: an agent based model approach

Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market.