Defining ecologically relevant water quality targets for lakes in Europe

1. The implementation of the Water Framework Directive requires EU member states to establish and harmonize ecological status class boundaries for biological quality elements. In this paper, we describe an approach for defining ecological class boundaries that delineates shifts in lake ecosystem functioning and, therefore, provides ecologically meaningful targets for water policy in Europe. 2. We collected an extensive data set of 810 lake-years from nine Central European countries, and we used phytoplankton chlorophyll a, a metric widely used to measure the impact of eutrophication in lakes. Our approach establishes chlorophyll a target values in relation to three significant ecological effects of eutrophication: the decline of aquatic macrophytes, the dominance of potentially harmful cyanobacteria and the major functional switch from a clear water to a turbid state. 3. Ranges of threshold chlorophyll a concentrations are given for the two most common lake types in lowland Central Europe: for moderately deep lakes (mean depth 3–15 m), the greatest ecological shifts occur in the range 10–12 lg L 1 chlorophyll a, and for shallow lakes (<3 m mean depth), in the range 21–23 lg L 1 chlorophyll a. 4. Synthesis and applications. Our study provides class boundaries for determining the ecological status of lakes, which have robust ecological consequences for lake functioning and which, therefore, provide strong and objective targets for sustainable water management in Europe. The results have been endorsed by all participant member states and adopted in the European Commission legislation, marking the first attempt in international water policy to move from physico-chemical quality standards to harmonized ecologically based quality targets.

Brain metastases in gastro-oesophageal adenocarcinoma: insights into the role of the human epidermal growth factor receptor 2 (HER2).

BACKGROUND: Gastro-oesophageal adenocarcinomas rarely metastasize to the central nervous system (CNS). The role of the human epidermal growth factor receptor 2 (HER2) in patients with these cancers and CNS involvement is presently unknown. PATIENTS AND METHODS: A multicentre registry was established to collect data from patients with gastro-oesophageal adenocarcinomas and CNS involvement both retrospectively and prospectively. Inclusion in the study required a predefined clinical data set, a central neuro-radiological or histopathological confirmation of metastatic CNS involvement and central assessment of HER2 by immunohistochemistry (IHC) and in situ hybridisation (ISH). In addition, expression of E-cadherin and DNA mismatch repair (MMR) proteins were assessed by IHC. RESULTS: One hundred patients fulfilled the inclusion criteria. The population's median age was 59 years (interquartile range: 54-68), of which 85 (85%) were male. Twenty-five patients were of Asian and 75 of Caucasian origin. HER2 status was positive in 36% (95% CI: 26.6-46.2) of cases. Median time from initial diagnosis to the development of brain metastases (BMets) or leptomeningeal carcinomatosis (LC) was 9.9 months (95% CI: 8.5-15.0). Median overall survival from diagnosis was 16.9 months (95% CI: 14.0-20.7) and was not related to the HER2 status. E-cadherin loss was observed in 9% of cases and loss of expression in at least one DNA MMR proteins in 6%. CONCLUSIONS: The proportion of a positive HER2 status in patients with gastro-oesophageal adenocarcinoma and CNS involvement was higher than expected. The impact of anti-HER2 therapies should be studied prospectively.

Embolic Strokes of Undetermined Source in the Athens Stroke Registry: an Outcome Analysis.

BACKGROUND AND PURPOSE: Information about outcomes in Embolic Stroke of Undetermined Source (ESUS) patients is unavailable. This study provides a detailed analysis of outcomes of a large ESUS population. METHODS: Data set was derived from the Athens Stroke Registry. ESUS was defined according to the Cryptogenic Stroke/ESUS International Working Group criteria. End points were mortality, stroke recurrence, functional outcome, and a composite cardiovascular end point comprising recurrent stroke, myocardial infarction, aortic aneurysm rupture, systemic embolism, or sudden cardiac death. We performed Kaplan-Meier analyses to estimate cumulative probabilities of outcomes by stroke type and Cox-regression to investigate whether stroke type was outcome predictor. RESULTS: 2731 patients were followed-up for a mean of 30.5±24.1months. There were 73 (26.5%) deaths, 60 (21.8%) recurrences, and 78 (28.4%) composite cardiovascular end points in the 275 ESUS patients. The cumulative probability of survival in ESUS was 65.6% (95% confidence intervals [CI], 58.9%-72.2%), significantly higher compared with cardioembolic stroke (38.8%, 95% CI, 34.9%-42.7%). The cumulative probability of stroke recurrence in ESUS was 29.0% (95% CI, 22.3%-35.7%), similar to cardioembolic strokes (26.8%, 95% CI, 22.1%-31.5%), but significantly higher compared with all types of noncardioembolic stroke. One hundred seventy-two (62.5%) ESUS patients had favorable functional outcome compared with 280 (32.2%) in cardioembolic and 303 (60.9%) in large-artery atherosclerotic. ESUS patients had similar risk of composite cardiovascular end point as all other stroke types, with the exception of lacunar strokes, which had significantly lower risk (adjusted hazard ratio, 0.70 [95% CI, 0.52-0.94]). CONCLUSIONS: Long-term mortality risk in ESUS is lower compared with cardioembolic strokes, despite similar rates of recurrence and composite cardiovascular end point. Recurrent stroke risk is higher in ESUS than in noncardioembolic strokes.

Combining niche modelling and landscape genetics to study local adaptation: A novel approach illustrated using alpine plants

Understanding the factors that shape adaptive genetic variation across species niches has become of paramount importance in evolutionary ecology, especially to understand how adaptation to changing climate affects the geographic range of species. The distribution of adaptive alleles in the ecological niche is determined by the emergence of novel mutations, their fitness consequences and gene flow that connects populations across species niches. Striking demographical differences and source sink dynamics of populations between the centre and the margin of the niche can play a major role in the emergence and spread of adaptive alleles. Although some theoretical predictions have long been proposed, the origin and distribution of adaptive alleles within species niches remain untested. In this paper, we propose and discuss a novel empirical approach that combines landscape genetics with species niche modelling, to test whether alleles that confer local adaptation are more likely to occur in either marginal or central populations of species niches. We illustrate this new approach by using a published data set of 21 alpine plant species genotyped with a total of 2483 amplified fragment length polymorphisms (AFLP), distributed over more than 1733 sampling sites across the Alps. Based on the assumption that alleles that were statistically associated with environmental variables were adaptive, we found that adaptive alleles in the margin of a species niche were also present in the niche centre, which suggests that adaptation originates in the niche centre. These findings corroborate models of species range evolution, in which the centre of the niche contributes to the emergence of novel adaptive alleles, which diffuse towards niche margins and facilitate niche and range expansion through subsequent local adaptation. Although these results need to be confirmed via fitness measurements in natural populations and functionally characterised genetic sequences, this study provides a first step towards understanding how adaptive genetic variation emerges and shapes species niches and geographic ranges along environmental gradients.

Use of asthma medication during pregnancy and risk of specific congenital anomalies: A European case-malformed control study.

BACKGROUND: Pregnant women with asthma need to take medication during pregnancy. OBJECTIVE: We sought to identify whether there is an increased risk of specific congenital anomalies after exposure to antiasthma medication in the first trimester of pregnancy. METHODS: We performed a population-based case-malformed control study testing signals identified in a literature review. Odds ratios (ORs) of exposure to the main groups of asthma medication were calculated for each of the 10 signal anomalies compared with registrations with nonchromosomal, nonsignal anomalies as control registrations. In addition, exploratory analyses were done for each nonsignal anomaly. The data set included 76,249 registrations of congenital anomalies from 13 EUROmediCAT registries. RESULTS: Cleft palate (OR, 1.63; 95% CI, 1.05-2.52) and gastroschisis (OR, 1.89; 95% CI, 1.12-3.20) had significantly increased odds of exposure to first-trimester use of inhaled β2-agonists compared with nonchromosomal control registrations. Odds of exposure to salbutamol were similar. Nonsignificant ORs of exposure to inhaled β2-agonists were found for spina bifida, cleft lip, anal atresia, severe congenital heart defects in general, or tetralogy of Fallot. None of the 4 literature signals of exposure to inhaled steroids were confirmed (cleft palate, cleft lip, anal atresia, and hypospadias). Exploratory analyses found an association between renal dysplasia and exposure to the combination of long-acting β2-agonists and inhaled corticosteroids (OR, 3.95; 95% CI, 1.99-7.85). CONCLUSIONS: The study confirmed increased odds of first-trimester exposure to inhaled β2-agonists for cleft palate and gastroschisis and found a potential new signal for renal dysplasia associated with combined long-acting β2-agonists and inhaled corticosteroids. Use of inhaled corticosteroids during the first trimester of pregnancy seems to be safe in relation to the risk for a range of specific major congenital anomalies.

An interactive web-GIS tool for risk analysis: a case study in the Fella River basin, Italy

This paper presents a prototype of an interactive web-GIS tool for risk analysis of natural hazards, in particular for floods and landslides, based on open-source geospatial software and technologies. The aim of the presented tool is to assist the experts (risk managers) in analysing the impacts and consequences of a certain hazard event in a considered region, providing an essential input to the decision-making process in the selection of risk management strategies by responsible authorities and decision makers. This tool is based on the Boundless (OpenGeo Suite) framework and its client-side environment for prototype development, and it is one of the main modules of a web-based collaborative decision support platform in risk management. Within this platform, the users can import necessary maps and information to analyse areas at risk. Based on provided information and parameters, loss scenarios (amount of damages and number of fatalities) of a hazard event are generated on the fly and visualized interactively within the web-GIS interface of the platform. The annualized risk is calculated based on the combination of resultant loss scenarios with different return periods of the hazard event. The application of this developed prototype is demonstrated using a regional data set from one of the case study sites, Fella River of northeastern Italy, of the Marie Curie ITN CHANGES project.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

Analysis of outliers in electricity spot prices with exampleof New England and New Zealand markets

Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

A hybrid feature selection approach for the early diagnosis of Alzheimer's disease

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5). Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

Factors Affecting Consumer’s Illicit Purchase of Copyrighted Digital Work

Peer-to-Peer (P2P) technology has revolutionized file exchange activities besides enhancing processing power distribution. As such, this technology which is nowadays made freely available to all internet users also imposes a threat as it enables the illegal distribution of copyrighted digital work. P2P technology continuously evolves in a greater pace than copyright legislation, leading to compatibility gaps between the applicability of copyright law and the illicit file sharing and downloading. Such issues give high incentives to consumers to practise piracy using P2P systems with a low perception of risk towards prosecution, leading to substantial losses for copyright owners. This study focuses on developing insights for content owners on consumer behaviour towards piracy in Finland, where quantitative analyses are assessed using a data set based on a survey conducted by the Helsinki Institute for IT. The research approach investigates the significance of three fundamental areas in relation to evaluate consumer behaviour as: environmental-related factors, innovation-related factors and consumer-related. each of these are integrates concepts derived in previous theoretical models such as the technology acceptance model, theory of reasoned action, theory of planned behaviour, the issue-risk-judgement model and the Hunt & Vitell’s model.

Present-day deformation of the Pyrenees revealed by GPS surveying and earthquake focal mechanisms until 2011

The Pyrenean mountain range is a slowly deforming belt with continuous and moderate seismic activity. To quantify its deformation field, we present the velocity field estimated from a GPS survey of the Pyrenees spanning 18 yr. The PotSis and ResPyr networks, including a total of 85 GPS sites, were installed and first measured in 1992 and 1995 1997, respectively, and remeasured in 2008 and 2010. We obtain a deformation field with velocities less than 1 mm yr−1 across the range. The estimated velocities for individual stations do not differ significantly from zero with 95 per cent confidence. Even so, we estimate a maximum extensional horizontal strain rate of 2.0 ± 1.7 nanostrain per year in a N S direction in the western part of the range. We do not interpret the vertical displacements due to their large uncertainties. In order to compare the horizontal strain rates with the seismic activity, we analyse a set of 194 focal mechanisms using three methods: (i) the 'r' factor relating their P and T axes, (ii) the stress tensors obtained by fault slip inversion and (iii) the strain-rate tensors. Stress and strain-rate tensors are estimated for: (i) the whole data set, (ii) the eastern and western parts of the range separately, and (iii) eight zones, which are defined based on the seismicity and the tectonic patterns of the Pyrenees. Each of these analyses reveals a lateral variation of the deformation style from compression and extension in the east to extension and strike-slip in the west of the range. Although the horizontal components of the strain-rate tensors estimated from the seismic data are slightly smaller in magnitude than those computed from the GPS velocity field, they are consistent within the 2σ uncertainties. Furthermore, the orientations of their principal axes agree with the mapped active faults.

Aplicação de análise de componentes principais para verificação de atribuições de sinais nos espetros de RMN ¹H: o caso dos 3-aril (1,2,4)-oxadiazol-5-carboidrazida benzilidenos

The ¹H NMR data set of a series of 3-aryl (1,2,4)-oxadiazol-5-carbohydrazide benzylidene derivatives synthesized in our group was analyzed using the chemometric technique of principal component analysis (PCA). Using the original ¹H NMR data PCA allowed identifying some misassignments of the proton aromatic chemical shifts. As a consequence of this multivariate analysis, nuclear Overhauser difference experiments were performed to investigate the ambiguity of other assignments of the ortho and meta aromatic hydrogens for the compound with the bromine substituent. The effect of the 1,2,4-oxadiazol group as an electron acceptor, mainly for the hydrogens 12,13, has been highlighted.

Photometric and Halpha observations of LSI+61·303: detection of a 26 day V and JHK band modulation

We present new optical and infrared photometric observations and high resolution H α spectra of the periodic radio star LSI+61◦303. The optical photometric data set covers the time interval 1985-1993 and amounts to about a hundred nights. A period of ∼26 days is found in the V band. The infrared data also present evidence for a similar periodicity, but with higher amplitude of variation ((0.m 2). The spectroscopic observations include 16 intermediate and high dispersion spectra of LSI+61◦303 collected between January 1989 and February 1993. The H α emission line profile and its variations are analyzed. Several emission line parameters -- among them the H α EW and the width of the H α red hump -- change strongly at or close to radio maximum, and may exhibit periodic variability. We also observe a significant change in the peak separation. The H α profile of LSI+61◦303 does not seem peculiar for a Be star. However, several of the observed variations of the H α profile can probably be associated with the presence of the compact, secondary star.

Análisis composicional de datos en Ciencias Geoambientales

Compositional data (concentrations) are common in geosciences. Neglecting its character mey lead to erroneous conclusions. Spurious correlation (K. Pearson, 1897) has disastrous consequences. On the basis of the pioneering work by J. Aitchison in the 1980s, a methodology free of these drawbacks is now available. The geometry of the símplex allows the representation of compositions using orthogonal co-ordinares, to which usual statistical methods can be applied, thus facilating computation ans analysis. The use of (log) ratios precludes the interpretation of single concentrations disregarding their relative character. A hydro-chemical data set is used to illustrate the point

Assigning and combining probabilities in single-case designs: A second study

The present study builds on a previous proposal for assigning probabilities to the outcomes computed using different primary indicators in single-case studies. These probabilities are obtained comparing the outcome to previously tabulated reference values and reflect the likelihood of the results in case there was no intervention effect. The current study explores how well different metrics are translated into p values in the context of simulation data. Furthermore, two published multiple baseline data sets are used to illustrate how well the probabilities could reflect the intervention effectiveness as assessed by the original authors. Finally, the importance of which primary indicator is used in each data set to be integrated is explored; two ways of combining probabilities are used: a weighted average and a binomial test. The results indicate that the translation into p values works well for the two nonoverlap procedures, with the results for the regression-based procedure diverging due to some undesirable features of its performance. These p values, both when taken individually and when combined, were well-aligned with the effectiveness for the real-life data. The results suggest that assigning probabilities can be useful for translating the primary measure into the same metric, using these probabilities as additional evidence on the importance of behavioral change, complementing visual analysis and professional's judgments.