EUSAAR size distribution analysis database

Two years of harmonized aerosol number size distribution data from 24 European field monitoring sites have been analysed. The results give a comprehensive overview of the European near surface aerosol particle number concentrations and number size distributions between 30 and 500 nm of dry particle diameter. Spatial and temporal distribution of aerosols in the particle sizes most important for climate applications are presented. We also analyse the annual, weekly and diurnal cycles of the aerosol number concentrations, provide log-normal fitting parameters for median number size distributions, and give guidance notes for data users. Emphasis is placed on the usability of results within the aerosol modelling community. We also show that the aerosol number concentrations of Aitken and accumulation mode particles (with 100 nm dry diameter as a cut-off between modes) are related, although there is significant variation in the ratios of the modal number concentrations. Different aerosol and station types are distinguished from this data and this methodology has potential for further categorization of stations aerosol number size distribution types. The European submicron aerosol was divided into characteristic types: Central European aerosol, characterized by single mode median size distributions, unimodal number concentration histograms and low variability in CCN-sized aerosol number concentrations; Nordic aerosol with low number concentrations, although showing pronounced seasonal variation of especially Aitken mode particles; Mountain sites (altitude over 1000 m a.s.l.) with a strong seasonal cycle in aerosol number concentrations, high variability, and very low median number concentrations. Southern and Western European regions had fewer stations, which decreases the regional coverage of these results. Aerosol number concentrations over the Britain and Ireland had very high variance and there are indications of mixed air masses from several source regions; the Mediterranean aerosol exhibit high seasonality, and a strong accumulation mode in the summer. The greatest concentrations were observed at the Ispra station in Northern Italy with high accumulation mode number concentrations in the winter. The aerosol number concentrations at the Arctic station Zeppelin in Ny-Ålesund in Svalbard have also a strong seasonal cycle, with greater concentrations of accumulation mode particles in winter, and dominating summer Aitken mode indicating more recently formed particles. Observed particles did not show any statistically significant regional work-week or weekday related variation in number concentrations studied. Analysis products are made for open-access to the research community, available in a freely accessible internet site. The results give to the modelling community a reliable, easy-to-use and freely available comparison dataset of aerosol size distributions.

Long-term statin therapy in patients with systolic heart failure and normal cholesterol:effects on elevated serum markers of collagen turnover, inflammation, and B-type natriuretic peptide

BACKGROUND: The role of statin therapy in heart failure (HF) is unclear. The amino-terminal propeptide of procollagen type III (PIIINP) predicts outcome in HF, and yet there are conflicting reports of statin therapy effects on PIIINP.

OBJECTIVES: This study determined whether there was an increase in serum markers of inflammation, fibrosis (including PIIINP), and B-type natriuretic peptide (BNP) in patients with systolic HF and normal total cholesterol and determined the effects of long-term treatment with atorvastatin on these markers.

METHODS: Fifty-six white patients with systolic HF and normal cholesterol levels (age 72 [13] years; 68% male; body mass index 27.0 [7.3] kg/m(2); ejection fraction 35 [13]%; 46% with history of smoking) were randomly allocated to atorvastatin treatment for 6 months, titrated to 40 mg/d (A group) or not (C group). Age- and/or sex-matched subjects without HF (N group) were also recruited. Biomarkers were measured at baseline (all groups) and 6 months (A and C groups).

RESULTS: Serum markers of collagen turnover, inflammation, and BNP were significantly elevated in HF patients compared with normal participants (all P < 0.05). There were correlations between these markers in HF patients but not in normal subjects. Atorvastatin treatment for 6 months caused a significant reduction in the following biomarkers compared with baseline: BNP, from median (interquartile range) 268 (190-441) pg/mL to 185 (144-344) pg/mL; high-sensitivity C-reactive protein (hs-CRP), from 5.26 (1.95 -9.29) mg/L to 3.70 (2.34-6.81) mg/L; and PIIINP, from 4.65 (1.86) to 4.09 (1.25) pg/mL (all P < 0.05 baseline vs 6 months). Between-group differences were significant for PIIINP only (P = 0.027). There was a positive interaction between atorvastatin effects and baseline hs-CRP and PIIINP (P < 0.01).

CONCLUSIONS: Long-term statin therapy reduced PIIINP in this small, selected HF population with elevated baseline levels. Further evaluation of statin therapy in the management of HF patients with elevated PIIINP is warranted.

Local Storage Meets Local Demand: A Technical Solution to Future Power Distribution System

Future power systems are expected to integrate large-scale stochastic and intermittent generation and load due to reduced use of fossil fuel resources, including renewable energy sources (RES) and electric vehicles (EV). Inclusion of such resources poses challenges for the dynamic stability of synchronous transmission and distribution networks, not least in terms of generation where system inertia may not be wholly governed by large-scale generation but displaced by small-scale and localised generation. Energy storage systems (ESS) can limit the impact of dispersed and distributed generation by offering supporting reserve while accommodating large-scale EV connection; the latter (load) also participating in storage provision. In this paper, a local energy storage system (LESS) is proposed. The structure, requirement and optimal sizing of the LESS are discussed. Three operating modes are detailed, including: 1) storage pack management; 2) normal operation; and 3) contingency operation. The proposed LESS scheme is evaluated using simulation studies based on data obtained from the Northern Ireland regional and residential network.

Dynamic fator Models for bivariate Count Data: an application to fire activity

The study of forest re activity, in its several aspects, is essencial to understand the phenomenon and to prevent environmental public catastrophes. In this context the analysis of monthly number of res along several years is one aspect to have into account in order to better comprehend this tematic. The goal of this work is to analyze the monthly number of forest res in the neighboring districts of Aveiro and Coimbra, Portugal, through dynamic factor models for bivariate count series. We use a bayesian approach, through MCMC methods, to estimate the model parameters as well as to estimate the common latent factor to both series.

TRIB2 in normal and malignant hematopoiesis - a transcription factor network

Hematopoiesis is the tightly controlled and complex process in which the entire blood system is formed and maintained by a rare pool of hematopoietic stem cells (HSCs), and its dysregulation results in the formation of leukaemia. TRIB2, a member of the Tribbles family of serine/threonine pseudokinases, has been implicated in a variety of cancers and is a potent murine oncogene that induces acute myeloid leukaemia (AML) in vivo via modulation of the essential myeloid transcription factor CCAAT-enhancer binding protein α (C/EBPα). C/EBPα, which is crucial for myeloid cell differentiation, is commonly dysregulated in a variety of cancers, including AML. Two isoforms of C/EBPα exist - the full-length p42 isoform, and the truncated oncogenic p30 isoform. TRIB2 has been shown to selectively degrade the p42 isoform of C/EBPα and induce p30 expression in AML. In this study, overexpression of the p30 isoform in a bone marrow transplant (BMT) leads to perturbation of myelopoiesis, and in the presence of physiological levels of p42, this oncogene exhibited weak transformative ability. It was also shown by BMT that despite their degradative relationship, expression of C/EBPα was essential for TRIB2 mediated leukaemia. A conditional mouse model was used to demonstrate that oncogenic p30 cooperates with TRIB2 to reduce disease latency, only in the presence of p42. At the molecular level, a ubiquitination assay was used to show that TRIB2 degrades p42 by K48-mediated proteasomal ubiquitination and was unable to ubiquitinate p30. Mutation of a critical lysine residue in the C-terminus of C/EBPα abrogated TRIB2 mediated C/EBPα ubiquitination suggesting that this site, which is frequently mutated in AML, is the site at which TRIB2 mediates its degradative effects. The TRIB2-C/EBPα axis was effectively targeted by proteasome inhibition. AML is a very difficult disease to target therapeutically due to the extensive array of chromosomal translocations and genetic aberrations that contribute to the disease. The cell from which a specific leukaemia arises, or leukaemia initiating cell (LIC), can affect the phenotype and chemotherapeutic response of the resultant disease. The LIC has been elucidated for some common oncogenes but it is unknown for TRIB2. The data presented in this thesis investigate the ability of the oncogene TRIB2 to transform hematopoietic stem and progenitor cells in vitro and in vivo. TRIB2 overexpression conferred in vitro serially replating ability to all stem and progenitor cells studied. Upon transplantation, only TRIB2 overexpressing HSCs and granulocyte/macrophage progenitors (GMPs) resulted in the generation of leukaemia in vivo. TRIB2 induced a mature myeloid leukaemia from the GMP, and a mixed lineage leukaemia from the HSC. As such the role of TRIB2 in steady state hematopoiesis was also explored using a Trib2-/- mouse and it was determined that loss of Trib2 had no effect on lineage distribution in the hematopoietic compartment under steady-state conditions. The process of hematopoiesis is controlled by a host of lineage restricted transcription factors. Recently members of the Nuclear Factor 1 family of transcription factors (NFIA, NFIB, NFIC and NFIX) have been implicated in hematopoiesis. Little is known about the role of NFIX in lineage determination. Here we describe a novel role for NFIX in lineage fate determination. In human and murine datasets the expression of Nfix was shown to decrease as cells differentiated along the lymphoid pathway. NFIX overexpression resulted in enhanced myelopoiesis in vivo and in vitro and a block in B cell development at the pre-pro-B cell stage. Loss of NFIX resulted in disruption of myeloid and lymphoid differentiation in vivo. These effects on stem and progenitor cell fate correlated with changes in the expression levels of key transcription factors involved in hematopoietic differentiation including a 15-fold increase in Cebpa expression in Nfix overexpressing cells. The data presented support a role for NFIX as an important transcription factor influencing hematopoietic lineage specification. The identification of NFIX as a novel transcription factor influencing lineage determination will lead to further study of its role in hematopoiesis, and contribute to a better understanding of the process of differentiation. Elucidating the relationship between TRIB2 and C/EBPα not only impacts on our understanding of the pathophysiology of AML but is also relevant in other cancer types including lung and liver cancer. Thus in summary, the data presented in this thesis provide important insights into key areas which will facilitate the development of future therapeutic approaches in cancer treatment.

STATISTICAL METHODS FOR ADVANCED ECONOMETRIC MODELS WITH APPLICATIONS TO VEHICLE HOLDING AND SPEED QUANTILES DISTRIBUTION

This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.

The influence of ApoE genotype on the lipid profile and lipoproteins during normal pregnancy in a Southern African population.

Background: Pregnancy is associated with increases in fasting triglycerides and total cholesterol.1 ApoE isoforms are known to influence the concentration of cholesterol, with apoE2 homozygosity lowering and apoE4 homozygosity raising the cholesterol concentration compared with E3 homozygosity.2 The lipid profiles ApoE status and prevalence of small dense LDL species were evaluated for subjects attending an antenatal clinic. Results: Samples from 690 women aged between 16 and 42 years of age were analyzed during and after pregnancy. The fasting plasma triglyceride concentration (in mmol/L) was significantly higher in pregnancy (median = 1.5, IQR 1.0-2.0 vs median = 0.6, IQR 0.5-0.8 respectively, p < 0.0001). Similarly, the total cholesterol (in mmol/L) was increased during pregnancy (median=4.1, IQR 3.6-4.7 vs median 3.5, IQR 3.1-3.5, respectively p=0.0167). The median LDL cholesterol and HDL cholesterol did not change. Higher proportions of small density LDL species were seen during pregnancy compared to after pregnancy. The distribution of the LDL species during pregnancy and 6 weeks post-partum were significantly different p<0.0001 with the smaller species being much higher during pregnancy. Conclusion: ApoE4 genotype was associated with increased total cholesterol and LDL cholesterol concentrations during pregnancy. Pregnancy results in a reversible remodeling of LDL to smaller species, the significance of which is unknown but may indicate a predisposition to atherosclerosis

Hypothesis test for changes in variance using a statistic based in P-values in a time series of normal independent observations.

The present work proposes a Hypothesis Test to detect a shift in the variance of a series of independent normal observations using a statistic based on the p-values of the F distribution. Since the probability distribution function of this statistic is intractable, critical values were we estimated numerically through extensive simulation. A regression approach was used to simplify the quantile evaluation and extrapolation. The power of the test was simulated using Monte Carlo simulation, and the results were compared with the Chen test (1997) to prove its efficiency. Time series analysts might find the test useful to address homoscedasticity studies were at most one change might be involved.

A pilot study to determine the normal haematological indices for young Malawian adults in Blantyre, Malawi

Aim To determine the distribution of haematological parameters in healthy individuals residing in Blantyre, Malawi. We also examined the effect of sociodemographic and nutritional factors on the haematological variables. Methods We conducted a proof-of-concept cross-sectional study, involving 105 healthy blood donors at Malawi Blood Transfusion Service in Blantyre. Eligible participants were HIV-negative males and females, aged 19 to 35 years, who did not have any evidence of acute or chronic illness, or bloodborne infection. We performed the haematological tests at the Malawi-Liverpool Wellcome Trust laboratory in Blantyre, and the screening tests at Malawi Blood Transfusion Service laboratories. Results Out of 170 consenting healthy volunteers, haematological results were available for 105 participants. The proportions of results which were below the lower limit of the manufacturer’s reference ranges were 35.2% (37/105) for haemoglobin, 15.2% (16/105) for neutrophils, 23.8% (25/105) for eosinophils, and 88.6 % (93/105) for basophils. The proportions of results that were above the upper limit of the manufacturer’s reference ranges were 9.5% (10/105) for platelets and 12.4% (13/105) for monocytes. We also observed that the mean leucocyte and basophil counts were significantly higher in males than females (p = 0.042 and p = 0.015, respectively). There were no statistically significant differences in haematological results observed among different ethnic, age, and body mass index groups. Conclusions Over half of otherwise healthy study participants had at least one abnormal haematological result, using previously established foreign standards. More detailed studies are needed to establish locally relevant normal ranges for different age groups and other demographic characteristics of the Malawian population. This will lead to accurate interpretation of laboratory results.

BIAS-CORRECTED MAXIMUM LIKELIHOOD ESTIMATION OF THE PARAMETERS OF THE WEIGHTED LINDLEY DISTRIBUTION

This report discusses the calculation of analytic second-order bias techniques for the maximum likelihood estimates (for short, MLEs) of the unknown parameters of the distribution in quality and reliability analysis. It is well-known that the MLEs are widely used to estimate the unknown parameters of the probability distributions due to their various desirable properties; for example, the MLEs are asymptotically unbiased, consistent, and asymptotically normal. However, many of these properties depend on an extremely large sample sizes. Those properties, such as unbiasedness, may not be valid for small or even moderate sample sizes, which are more practical in real data applications. Therefore, some bias-corrected techniques for the MLEs are desired in practice, especially when the sample size is small. Two commonly used popular techniques to reduce the bias of the MLEs, are ‘preventive’ and ‘corrective’ approaches. They both can reduce the bias of the MLEs to order O(n−2), whereas the ‘preventive’ approach does not have an explicit closed form expression. Consequently, we mainly focus on the ‘corrective’ approach in this report. To illustrate the importance of the bias-correction in practice, we apply the bias-corrected method to two popular lifetime distributions: the inverse Lindley distribution and the weighted Lindley distribution. Numerical studies based on the two distributions show that the considered bias-corrected technique is highly recommended over other commonly used estimators without bias-correction. Therefore, special attention should be paid when we estimate the unknown parameters of the probability distributions under the scenario in which the sample size is small or moderate.