Genetic Algorithm Search for Predictive Patterns in Multidimensional Time Series

Based on an algorithm for pattern matching in character strings, we implement a pattern matching machine that searches for occurrences of patterns in multidimensional time series. Before the search process takes place, time series are encoded in user-designed alphabets. The patterns, on the other hand, are formulated as regular expressions that are composed of letters from these alphabets and operators. Furthermore, we develop a genetic algorithm to breed patterns that maximize a user-defined fitness function. In an application to financial data, we show that patterns bred to predict high exchange rates volatility in training samples retain statistically significant predictive power in validation samples.

Comparison of elicitation methods for moral and affective beliefs in the theory of planned behaviour

Although the theory of planned behaviour (TPB) has been applied successfully in the area of food choice, it has been criticized for its pure utilitarian approach to the factors determining behaviour. Despite the increase in predictive power of the model with added components such as affective attitude and moral and ethical concerns, in most studies the elicitation process still only addresses people's utilitarian beliefs about the behaviour with little attention paid to other aspects. This study compares the traditional method of elicitation of advantages and disadvantages with two other methods (word association and open-ended) in the elicitations of beliefs, attitudes and moral concerns in relation to the consumption of organic foods. Results show the traditional method to be best for eliciting cognitive beliefs, open-ended emotion task for eliciting emotional beliefs and open-ended beliefs task best for moral concerns. The advantages and disadvantages of each method are discussed.

How can a knowledge of the past help to conserve the future? Biodiversity conservation and the relevance of long-term ecological studies

This paper evaluates how long-term records could and should be utilized in conservation policy and practice. Traditionally, there has been an extremely limited use of long-term ecological records (greater than 50 years) in biodiversity conservation. There are a number of reasons why such records tend to be discounted, including a perception of poor scale of resolution in both time and space, and the lack of accessibility of long temporal records to non-specialists. Probably more important, however, is the perception that even if suitable temporal records are available, their roles are purely descriptive, simply demonstrating what has occurred before in Earth’s history, and are of little use in the actual practice of conservation. This paper asks why this is the case and whether there is a place for the temporal record in conservation management. Key conservation initiatives related to extinctions, identification of regions of greatest diversity/threat, climate change and biological invasions are addressed. Examples of how a temporal record can add information that is of direct practicable applicability to these issues are highlighted. These include (i) the identification of species at the end of their evolutionary lifespan and therefore most at risk from extinction, (ii) the setting of realistic goals and targets for conservation ‘hotspots’, and (iii) the identification of various management tools for the maintenance/restoration of a desired biological state. For climate change conservation strategies, the use of long-term ecological records in testing the predictive power of species envelope models is highlighted, along with the potential of fossil records to examine the impact of sea-level rise. It is also argued that a long-term perspective is essential for the management of biological invasions, not least in determining when an invasive is not an invasive. The paper concludes that often inclusion of a long-term ecological perspective can provide a more scientifically defensible basis for conservation decisions than the one based only on contemporary records. The pivotal issue of this paper is not whether long-term records are of interest to conservation biologists, but how they can actually be utilized in conservation practice and policy.

Integrating situational and dispositional determinants of job satisfaction: Findings from three samples of professionals

Job satisfaction can be conceptualized as a function of situational conditions, personal characteristics, and interactions between both groups of variables. The authors compared the relative predictive power of these determinants in 3 samples of professionals (total N = 1,065). Perceived job characteristics (qualification possibilities, social support, stress, autonomy, participatory leadership) uniquely explained 7-22% of the variance in job satisfaction, and dispositional factors (Big Five, occupational self-efficacy, work centrality, mastery goals) uniquely explained 8-12% of the variance. Dispositional influences were partially mediated by perceived job characteristics. Interactions between situational and dispositional factors were of little significance. The authors concluded that perceived job characteristics (especially autonomy and participatory leadership) are important determinants of job satisfaction, and neuroticism is an important determinant as well. Highly educated professionals job satisfaction also seems to be driven by qualification possibilities.

Climate change-linked range expansion of Nathusius' pipistrelle bat, Pipistrellus nathusii (Keyserling & Blasius, 1839)

Aim To examine the effect of climate change on the occurrence and distribution of Pipistrellus nathusii (Nathusius' pipistrelle) in the United Kingdom (UK).Location We modelled habitat and climatic associations of P. nathusii in the UK and applied this model to the species' historical range in continental Europe.Methods A binomial logistic regression model was constructed relating the occurrence of P. nathusii to climate and habitat characteristics using historical species occurrence records (1940-2006) and CORINE land cover data. This model was applied to historical and projected climate data to examine changes in suitable range (1940-2080) of this species. We tested the predictive ability of the model with known records in the UK after 2006 and applied the model to the species' known range in Europe.Results The distribution of P. nathusii was related positively to the area of water bodies, woodland and small areas of urbanization, and negatively related to the area of peat/heathland. Species records were associated with higher minimum temperatures, low seasonal variation in temperature and intermediate rainfall. We found that suitable areas have existed in the UK since the 1940s and that these have expanded. The model had high predictive power when applied to new records after 2006, with a correct classification rate of 70%, estimated by receiver operating characteristic analysis. Based on climate projections, our model suggests a potential twofold increase in the area suitable for P. nathusii in the UK by 2050. The single most influential climate variable contributing to range increase was the projected increase in minimum temperature. When applied to Europe, the model predictions had best predictive capability of known records in western areas of the species' range, where P. nathusii is present during the winter.Main conclusions We show that a mobile, migratory species has adapted its range in response to recent climate change on a continental scale. We believe this may be the first study to demonstrate a case of range change linked to contemporary climate change in a mammal species in Europe.

Long-term return reversals-Value and growth or tax? UK evidence

This paper examines (i) whether value-growth characteristics have more power than past performance in predicting return reversals; and (ii) whether typical rational behaviour such as incentives to delay paying capital gain taxes can better explain long-term reversals than past performance. We find that value-growth characteristics generally provide better explanations for long-term stock returns than past performance. The evidence also shows that winners identified by capital gains dominate past performance winners in predicting reversals in the cross-sectional comparison. However, in the time-series analysis, when returns on capital gain winners are adjusted by the Fama and French (1996) risk factors, the predictive power of capital gain winners disappears. Our results show that capital gain winners are heavily featured as growth stocks. Return reversals in capital gain winners potentially reflect market price corrections for growth stocks. We conclude that investors’ incentives to delay paying capital gain taxes cannot fully rationalise long-term reversals in the UK market. Our results also imply that the long-term return pattern potentially reflects a mixture of investor rational and irrational behaviour.

The impact of biomarkers in multivariate algorithms for bladder cancer diagnosis in patients with hematuria

BACKGROUND: We appraised 23 biomarkers previously associated with urothelial cancer in a case-control study. Our aim was to determine whether single biomarkers and/or multivariate algorithms significantly improved on the predictive power of an algorithm based on demographics for prediction of urothelial cancer in patients presenting with hematuria. METHODS: Twenty-two biomarkers in urine and carcinoembryonic antigen (CEA) in serum were evaluated using enzyme-linked immunosorbent assays (ELISAs) and biochip array technology in 2 patient cohorts: 80 patients with urothelial cancer, and 77 controls with confounding pathologies. We used Forward Wald binary logistic regression analyses to create algorithms based on demographic variables designated prior predicted probability (PPP) and multivariate algorithms, which included PPP as a single variable. Areas under the curve (AUC) were determined after receiver-operator characteristic (ROC) analysis for single biomarkers and algorithms. RESULTS: After univariate analysis, 9 biomarkers were differentially expressed (t test; P

Essay - The role of ecological theory in microbial ecology

Microbial ecology is currently undergoing a revolution, with repercussions spreading throughout microbiology, ecology and ecosystem science. The rapid accumulation of molecular data is uncovering vast diversity, abundant uncultivated microbial groups and novel microbial functions. This accumulation of data requires the application of theory to provide organization, structure, mechanistic insight and, ultimately, predictive power that is of practical value, but the application of theory in microbial ecology is currently very limited. Here we argue that the full potential of the ongoing revolution will not be realized if research is not directed and driven by theory, and that the generality of established ecological theory must be tested using microbial systems.

Investigation of the Human Brain Metabolome to Identify Potential Markers for Early Diagnosis and Therapeutic Targets of Alzheimer’s Disease

A study combining high resolution mass spectrometry (liquid chromatography-quadrupole time-of-flight-mass spectrometry, UPLC-QTof-MS) and chemometrics for the analysis of post-mortem brain tissue from subjects with Alzheimer’s disease (AD) (n = 15) and healthy age-matched controls (n = 15) was undertaken. The huge potential of this metabolomics approach for distinguishing AD cases is underlined by the correct prediction of disease status in 94–97% of cases. Predictive power was confirmed in a blind test set of 60 samples, reaching 100% diagnostic accuracy. The approach also indicated compounds significantly altered in concentration following the onset of human AD. Using orthogonal partial least-squares discriminant analysis (OPLS-DA), a multivariate model was created for both modes of acquisition explaining the maximum amount of variation between sample groups (Positive Mode-R2 = 97%; Q2 = 93%; root mean squared error of validation (RMSEV) = 13%; Negative Mode-R2 = 99%; Q2 = 92%; RMSEV = 15%). In brain extracts, 1264 and 1457 ions of interest were detected for the different modes of acquisition (positive and negative, respectively). Incorporation of gender into the model increased predictive accuracy and decreased RMSEV values. High resolution UPLC-QTof-MS has not previously been employed to biochemically profile post-mortem brain tissue, and the novel methods described and validated herein prove its potential for making new discoveries related to the etiology, pathophysiology, and treatment of degenerative brain disorders.

Accounting for the effects of lipids in stable isotope (δ13C and δ15N values) analysis of skin and blubber of balaenopterid whales

RATIONALE Stable isotope values (d¹³C and d¹⁵N) of darted skin and blubber biopsies can shed light on habitat use and diet of cetaceans, which are otherwise difficult to study. Non-dietary factors affect isotopic variability, chiefly the depletion of C due to the presence of C-rich lipids. The efficacy of post hoc lipid-correction models (normalization) must be tested. METHODS For tissues with high natural lipid content (e.g., whale skin and blubber), chemical lipid extraction or normalization is necessary. C:N ratios, d¹³C values and d¹⁵N values were determined for duplicate control and lipid-extracted skin and blubber of fin (Balaenoptera physalus), humpback (Megaptera novaeangliae) and minke whales (B. acutorostrata) by continuous-flow elemental analysis isotope ratio mass spectrometry (CF-EA-IRMS). Six different normalization models were tested to correct d¹³C values for the presence of lipids. RESULTS Following lipid extraction, significant increases in d¹³C values were observed for both tissues in the three species. Significant increases were also found for d¹⁵N values in minke whale skin and fin whale blubber. In fin whale skin, the d¹⁵N values decreased, with no change observed in humpback whale skin. Non-linear models generally out-performed linear models and the suitability of models varied by species and tissue, indicating the need for high model specificity, even among these closely related taxa. CONCLUSIONS Given the poor predictive power of the models to estimate lipid-free d13C values, and the unpredictable changes in d N values due to lipid-extraction, we recommend against arithmetical normalization in accounting for lipid effects on d13C values for balaenopterid skin or blubber samples. Rather, we recommend that duplicate analysis of lipid-extracted (d13C values) and non-treated tissues (d15N values) be used. Copyright © 2012 John Wiley & Sons, Ltd.

Psychic Distance, its Business Impact and Modes of Coping: A Study of British and Indian Partner SMEs

This paper reports one of the first investigations to analyze inter-partner perceptions of psychic distance between two countries. Its empirical focus is British and Indian SMEs engaged in business with each other. It examines different dimensions of psychic distance, their impact and modes of coping with them. Potential firm-level and individual influences are also taken into account. The paper aims to transcend some of the conceptual and methodological limitations of previous research on the subject and to identify the theoretical and practical implications that arise. A ‘mirror’ approach is applied, accessing both partners’ perceptions. These are assessed through a ‘mixed’ method combining quantitative measurement with qualitative interpretations. Psychic distance dimensions are found to vary in their impact on doing business with the other country, and there is also variation according to the firm’s sector. There is considerable asymmetry in British and Indian partners’ perceptions of psychic distance but the degree of difference between their psychic distance evaluations lacks predictive power. Culturally embedded psychic distance dimensions tend to have less impact and to be easier to cope with than institutionally embedded dimensions. Four categories of coping are identified. The principal theoretical implication of this study is that a contingency perspective needs to be adopted in the field of ‘distance’ research, taking account of factors such as a firm’s sector, and that this will require a more complex analytical framework that hitherto.

Energy expenditure during activity in the American lobster Homarus americanus:Correlations with body acceleration

How animals manage time and expend energy has implications for survivorship. Being able to measure key metabolic costs of animals under natural conditions is therefore an important tool in behavioral ecology. One method for estimating activity-specific metabolic rate is via derived measures of acceleration, often 'overall dynamic body acceleration' (ODBA), recorded by an instrumented acceleration logger. ODBA has been shown to correlate well with rate of oxygen consumption (V ?o) in a range of species during activity in the laboratory. This study devised a method for attaching acceleration loggers to decapod crustaceans and then correlated ODBA against concurrent respirometry readings to assess accelerometry as a proxy for activity-specific energy expenditure in a model species, the American lobster Homarus americanus. Where the instrumented animals exhibited a sufficient range of activity levels, positive linear relationships were found between V ?o and ODBA over 20min periods at a range of ambient temperatures (6, 13 and 20°C). Mixed effect linear models based on these data and morphometrics provided reasonably strong predictive power for estimating activity-specific V ?o from ODBA. These V ?o-ODBA calibrations demonstrate the potential of accelerometry as an effective predictor of behavior-specific metabolic rate of crustaceans in the wild during periods of activity. © 2013 Elsevier Inc.

Geometrical characterization of non-Markovianity

We introduce a tool for the quantitative characterization of the departure from Markovianity of a given dynamical process. Our tool can be applied to a generic N-level system and extended straightforwardly to Gaussian continuous-variable systems. It is linked to the change of the volume of physical states that are dynamically accessible to a system and provides qualitative expectations in agreement with some of the analogous tools proposed so far. We illustrate its predictive power by tackling a few canonical examples.

Interpretable semantic vectors from a joint model of brain-and text-based meaning

Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to create VSMs: brain activation data recorded while people read words. The resulting model takes advantage of the complementary strengths and weaknesses of corpus and brain activation data to give a more complete representation of semantics. Evaluations show that the model 1) matches a behavioral measure of semantics more closely, 2) can be used to predict corpus data for unseen words and 3) has predictive power that generalizes across brain imaging technologies and across subjects. We believe that the model is thus a more faithful representation of mental vocabularies.

Evaluating the use of testate amoebae for palaeohydrological reconstruction in permafrost peatlands

The melting of high-latitude permafrost peatlands is a major concern due to a potential positive feedback on global climate change. We examine the ecology of testate amoebae in permafrost peatlands, based on sites in Sweden (~ 200 km north of the Arctic Circle). Multivariate statistical analysis confirms that water-table depth and moisture content are the dominant controls on the distribution of testate amoebae, corroborating the results from studies in mid-latitude peatlands. We present a new testate amoeba-based water table transfer function and thoroughly test it for the effects of spatial autocorrelation, clustered sampling design and uneven sampling gradients. We find that the transfer function has good predictive power; the best-performing model is based on tolerance-downweighted weighted averaging with inverse deshrinking (performance statistics with leave-one-out cross validation: R2 = 0.87, RMSEP = 5.25 cm). The new transfer function was applied to a short core from Stordalen mire, and reveals a major shift in peatland ecohydrology coincident with the onset of the Little Ice Age (c. AD 1400). We also applied the model to an independent contemporary dataset from Stordalen and find that it outperforms predictions based on other published transfer functions. The new transfer function will enable palaeohydrological reconstruction from permafrost peatlands in Northern Europe, thereby permitting greatly improved understanding of the long-term ecohydrological dynamics of these important carbon stores as well as their responses to recent climate change.