Assessment of apparent nonstationarity in time series of annual inflow, daily precipitation, and atmospheric circulation indices: A case study from southwest Western Australia

The southwest region of Western Australia has experienced a sustained sequence of low annual inflows to major water supply dams over the past 30 years. Until recently, the dominant interpretation of this phenomenon has been predicated on the existence of one or more sharp breaks (change or jump points), with inflows fluctuating around relatively constant levels between them. This paper revisits this interpretation. To understand the mechanisms behind the changes, we also analyze daily precipitation series at multiple sites in the vicinity and time series for several indices of regional atmospheric circulation that may be considered as drivers of regional precipitation. We focus on the winter half-year for the region (May to October) as up to 80% of annual precipitation occurs during this "season". We find that the decline in the annual inflow is in fact more consistent with a smooth declining trend than with a sequence of sharp breaks, the decline is associated with decreases both in the frequency of daily precipitation occurrence and in wet-day amounts, and the decline in regional precipitation is strongly associated with a marked decrease in moisture content in the lower troposphere, an increase in regionally averaged sea level pressure in the first half of the season, and intraseasonal changes in the regional north-south sea level pressure gradient. Overall, our approach provides an integrated understanding of the linkages between declining dam inflows, declining precipitation, and changes in regional atmospheric circulation that favor drier conditions

Lightning prediction for Australia using multivariate analyses of large-scale atmospheric variables

Lightning is a natural hazard that can lead to the ignition of wildfires, disruption and damage to power and telecommunication infrastructures, human and livestock injuries and fatalities, and disruption to airport activities. This paper examines the ability of six statistical and machine-learning classification techniques to distinguish between non-lightning and lightning days at the coarse spatial and temporal scales of current general circulation models and reanalyses. The classification techniques considered were: a combination of principal component analysis and logistic regression; classification and regression trees; random forests; linear discriminant analysis; quadratic discriminant analysis; and logistic regression. Lightning flash count observations at six locations across Australia for the period 2004 to 2013 were used, together with atmospheric variables from the ERA-Interim reanalysis. Ten-fold cross validation was used to evaluate classification performance. It was found that logistic regression was superior to the other classifiers considered, and that its prediction skill is much better than climatology. The sets of atmospheric variables included in the final logistic regression models were primarily composed of spatial mean measures of instability and lifting potential, and atmospheric water content. However, the memberships of these sets varied between climatic zones

Classification of Australian Thunderstorms using Multivariate Analyses of Large-Scale Atmospheric Variables

Lightning accompanied by inconsequential rainfall (i.e., “dry” lightning) is the primary natural ignition source for wildfires globally. This paper presents a machine-learning and statistical-classification analysis of dry and “wet” thunderstorm days in relation to associated atmospheric conditions. The study is based on daily data for lightning-flash count and precipitation from ground-based sensors and gauges and a comprehensive set of atmospheric variables that are based on ERA-Interim for the period from 2004 to 2013 at six locations in Australia. These locations represent a wide range of climatic zones (temperate, subtropical, and tropical). Quadratic surface representations and low-dimensional summary statistics were used to characterize the main features of the atmospheric fields. Four prediction skill scores were considered, and 10-fold cross validation was used to evaluate the performance of each classifier. The results were compared with those obtained by adopting the approach used in an earlier study for the U.S. Pacific Northwest. It was found that both approaches have prediction skill when tested against independent data, that mean atmospheric field quantities proved to be the most influential variables in determining dry-lightning activity, and that no single classifier or set of atmospheric variables proved to be consistently superior to its counterpart for the six sites examined here

Estimating trends and seasonality in Australian monthly lightning flash counts

We present the results of a statistical analysis of lightning characteristics in mainland Australia for the period from approximately 1988 to 2012, based on monthly lightning flash count (LFC) series obtained from a network of 19 Comité Internationale des Grands Réseaux Electriques, 500 Hz peak transmission filter circuit sensors. The temporal structures of the series are examined in terms of detecting and characterizing seasonal cycles, long-term trends, and changes in seasonality over time. A generalized additive modeling approach is used to ensure that the estimated structures are determined by the data, rather than by the constraints of any assumed mathematical form for the trends and seasonal cycle. Results indicate strong seasonality at all sites, the presence of long-term trends at 16 sites, and interactions between trend and seasonality (corresponding to changes in seasonality over time) at 13 sites. The most systematic change corresponds to a progressive deepening of the seasonal cycle (i.e., an ongoing decline in winter lightning flash counts) and is most noticeable across southern Australia (south of 30°S). These results are consistent with previous analyses that have detected decreasing atmospheric instability during the austral winter since the mid-1970s. This is associated with increasing mean sea level pressure and declining rainfall

A Refined Approach to Model Anisotropy in the Lowermost Mantle

© 2018 Institute of Physics Publishing. All rights reserved. Seismic anisotropy in the lowermost mantle has been attributed to texture development during mantle convection. This study models texture evolution in a subducting slab impinging on the core-mantle boundary. Using a 3-dimensional geodynamic model with tracers recording the deformation history, a visco-plastic self-consistent (VPSC) model for polycrystal deformation, and relying on experimentally determined slip systems, aggregate grains with volume fractions of 60% orthorhombic silicate perovskite (MgSiO3), 20% cubic calcium perovskite (CaSiO3), and 20% cubic ferropericlase ((Mg,Fe)O) were deformed plastically and developed crystal preferred orientation. Forward and reverse perovskite (Pv)-postperovskite (PPv) phase transitions were included by allowing for likely orientation variant selections. Grain orientations, P (compression) and S (shear) wave velocity pole figures were calculated for each phase as well as the aggregate. The results show that dominant (001) slip on PPv can produce strong texture and shear wave anisotropy of 0.01-3.07% with VSH >VSV which agrees with seismological observations in selected areas of the D" layer

'So wide and varied': The origins and character of British information science

This paper examines some characteristics of the ‘British School’ of information science. Three main forces driving the development of the new subject in Britain are identified: the documentation movement; special libraries; and the need for better treatment of scientific and technical information. Five characteristics which, taken together, distinguish the early British approach to information science from those adopted elsewhere are identified: its subject-based nature; its broad approach to information and information science; its status as an academic subject with a strong professional remit; its involvement with, but distinction from, information technology; and its involvement with memory institutions. Lessons are drawn for the future development of the information sciences

Natural images from the birthplace of the human eye

Here we introduce a database of calibrated natural images publicly available through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we acquired about 5000 six-megapixel images of Okavango Delta of Botswana, a tropical savanna habitat similar to where the human eye is thought to have evolved. Some sequences of images were captured unsystematically while following a baboon troop, while others were designed to vary a single parameter such as aperture, object distance, time of day or position on the horizon. Images are available in the raw RGB format and in grayscale. Images are also available in units relevant to the physiology of human cone photoreceptors, where pixel values represent the expected number of photoisomerizations per second for cones sensitive to long (L), medium (M) and short (S) wavelengths. This database is distributed under a Creative Commons Attribution-Noncommercial Unported license to facilitate research in computer vision, psychophysics of perception, and visual neuroscience.Comment: Submitted to PLoS ON

Transcriptome profile analysis of flowering molecular processes of early flowering trifoliate orange mutant and the wild-type [Poncirus trifoliata (L.) Raf.] by massively parallel signature sequencing

<p>Abstract</p> <p>Background</p> <p>After several years in the juvenile phase, trees undergo flowering transition to become mature (florally competent) trees. This transition depends on the balanced expression of a complex network of genes that is regulated by both endogenous and environmental factors. However, relatively little is known about the molecular processes regulating flowering transition in woody plants compared with herbaceous plants.</p> <p>Results</p> <p>Comparative transcript profiling of spring shoots after self-pruning was performed on a spontaneously early flowering trifoliate orange mutant (precocious trifoliate orange, <it>Poncirus trifoliata</it>) with a short juvenile phase and the wild-type (WT) tree by using massively parallel signature sequencing (MPSS). A total of 16,564,500 and 16,235,952 high quality reads were obtained for the WT and the mutant (MT), respectively. Interpretation of the MPSS signatures revealed that the total number of transcribed genes in the MT (31,468) was larger than in the WT (29,864), suggesting that newly initiated transcription occurs in the MT. Further comparison of the transcripts revealed that 2735 genes had more than twofold expression difference in the MT compared with the WT. In addition, we identified 110 citrus flowering-time genes homologous with known elements of flowering-time pathways through sequencing and bioinformatics analysis. These genes are highly conserved in citrus and other species, suggesting that the functions of the related proteins in controlling reproductive development may be conserved as well.</p> <p>Conclusion</p> <p>Our results provide a foundation for comparative gene expression studies between WT and precocious trifoliate orange. Additionally, a number of candidate genes required for the early flowering process of precocious trifoliate orange were identified. These results provide new insight into the molecular processes regulating flowering time in citrus.</p

Female social and sexual interest across the menstrual cycle: the roles of pain, sleep and hormones

<p>Abstract</p> <p>Background</p> <p>Although research suggests that socio-sexual behavior changes in conjunction with the menstrual cycle, several potential factors are rarely taken into consideration. We investigated the role of changing hormone concentrations on self-reported physical discomfort, sleep, exercise and socio-sexual interest in young, healthy women.</p> <p>Methods</p> <p>Salivary hormones (dehydroepiandrosterone sulfate-DHEAS, progesterone, cortisol, testosterone, estradiol and estriol) and socio-sexual variables were measured in 20 women taking oral contraceptives (OC group) and 20 not using OCs (control group). Outcome measures were adapted from questionnaires of menstrual cycle-related symptoms, physical activity, and interpersonal relations. Testing occurred during menstruation (T1), mid-cycle (T2), and during the luteal phase (T3). Changes in behavior were assessed across time points and between groups. Additionally, correlations between hormones and socio-behavioral characteristics were determined.</p> <p>Results</p> <p>Physical discomfort and sleep disturbances peaked at T1 for both groups. Exercise levels and overall socio-sexual interest did not change across the menstrual cycle for both groups combined. However, slight mid-cycle increases in general and physical attraction were noted among the control group, whereas the OC group experienced significantly greater socio-sexual interest across all phases compared to the control group. Associations with hormones differed by group and cycle phase. The estrogens were correlated with socio-sexual and physical variables at T1 and T3 in the control group; whereas progesterone, cortisol, and DHEAS were more closely associated with these variables in the OC group across test times. The direction of influence further varies by behavior, group, and time point. Among naturally cycling women, higher concentrations of estradiol and estriol are associated with lower attraction scores at T1 but higher scores at T3. Among OC users, DHEAS and progesterone exhibit opposing relationships with attraction scores at T1 and invert at T3.</p> <p>Conclusions</p> <p>Data from this study show no change across the cycle in socio-sexual interest among healthy, reproductive age women but higher social and physical attraction among OC users. Furthermore, a broader range of hormones may be associated with attraction than previously thought. Such relationships differ by use of oral contraceptives, and may either reflect endogenous hormone modulation by OCs and/or self-selection of sexually active women to practice contraceptive techniques.</p

Feature engineering and a proposed decision-support system for systematic reviewers of medical evidence

Objectives: Evidence-based medicine depends on the timely synthesis of research findings. An important source of synthesized evidence resides in systematic reviews. However, a bottleneck in review production involves dual screening of citations with titles and abstracts to find eligible studies. For this research, we tested the effect of various kinds of textual information (features) on performance of a machine learning classifier. Based on our findings, we propose an automated system to reduce screeing burden, as well as offer quality assurance. Methods: We built a database of citations from 5 systematic reviews that varied with respect to domain, topic, and sponsor. Consensus judgments regarding eligibility were inferred from published reports. We extracted 5 feature sets from citations: alphabetic, alphanumeric +, indexing, features mapped to concepts in systematic reviews, and topic models. To simulate a two-person team, we divided the data into random halves. We optimized the parameters of a Bayesian classifier, then trained and tested models on alternate data halves. Overall, we conducted 50 independent tests. Results: All tests of summary performance (mean F3) surpassed the corresponding baseline, P<0.0001. The ranks for mean F3, precision, and classification error were statistically different across feature sets averaged over reviews; P-values for Friedman's test were .045, .002, and .002, respectively. Differences in ranks for mean recall were not statistically significant. Alphanumeric+ features were associated with best performance; mean reduction in screening burden for this feature type ranged from 88% to 98% for the second pass through citations and from 38% to 48% overall. Conclusions: A computer-assisted, decision support system based on our methods could substantially reduce the burden of screening citations for systematic review teams and solo reviewers. Additionally, such a system could deliver quality assurance both by confirming concordant decisions and by naming studies associated with discordant decisions for further consideration. © 2014 Bekhuis et al