A molecular method for the identification of resting eggs of acartiid copepods in the Thau lagoon, France

Acartia and Paracartia species, often known to co-occur, can exhibit complex life cycles, including the production of resting eggs. Studying and understanding their population dynamics is hindered by the inability to identify eggs and early developmental stages using morphological techniques. We have developed a simple molecular technique to distinguish between the three species of the Acartiidae family (Acartia clausi, A. discaudata and Paracartia grani) that co-occur in the Thau lagoon (43�250N; 03�400E) in southern France. Direct amplification of a partial region of the mitochondrial cytochrome oxidase I gene by polymerase chain reaction and subsequent restriction fragment length polymorphism results in a unique restriction profile for each species. The technique is capable of determining the identity of individual eggs, including resting eggs retrieved from sediment samples, illustrating its application in facilitating population dynamic studies of this ubiquitous and important member of the zooplankton community.

Discrete-time modelling of woodwind instrument bores using wave variables

A method for simulation of acoustical bores, useful in the context of sound synthesis by physical modeling of woodwind instruments, is presented. As with previously developed methods, such as digital waveguide modeling (DWM) [Smith, Comput. Music J. 16, pp 74-91 (1992)] and the multi convolution algorithm (MCA) [Martinez et al., J. Acoust. Soc. Am. 84, pp 1620-1627 (1988)], the approach is based on a one-dimensional model of wave propagation in the bore. Both the DWM method and the MCA explicitly compute the transmission and reflection of wave variables that represent actual traveling pressure waves. The method presented in this report, the wave digital modeling (WDM) method, avoids the typical limitations associated with these methods by using a more general definition of the wave variables. An efficient and spatially modular discrete-time model is constructed from the digital representations of elemental bore units such as cylindrical sections, conical sections, and toneholes. Frequency-dependent phenomena, such as boundary losses, are approximated with digital filters. The stability of a simulation of a complete acoustic bore is investigated empirically. Results of the simulation of a full clarinet show that a very good concordance with classic transmission-line theory is obtained.

Factores explicativos de las actitudes hacia el castigo juvenil. Evidencias de un diseño factorial

El rol desempeñado por la opinión pública en el desarrollo de la política criminal actual justifica el incremento de investigaciones destinadas a evaluar las actitudes de los ciudadanos hacia el castigo. No obstante, los avances en este ámbito han sido limitados debido a la utilización de rudimentarios instrumentos de medida. Por ello, el presente trabajo tiene como propósito explorar el efecto que generan en la opinión ciudadana ciertas variables referidas al hecho delictivo y al infractor, precisando su contribución relativa y la interacción existente entre ellas. Para satisfacer este objetivo se recurrió a un diseño factorial de la encuesta, creando una población de 256 casos-escenario fruto de la combinación de cuatro factores: la edad del joven, su historial delictivo, el grado de implicación en el hecho y el tipo de delito cometido. Los mismos fueron distribuidos en grupos de ocho casos ordenados aleatoriamente y fueron suministrados a 32 sujetos. Posteriormente se aplicaron análisis de regresión logística binaria. Los resultados obtenidos revelan que la naturaleza violenta de los hechos, la implicación activa de los jóvenes y el historial delictivo son predictores importantes de las condenas punitivas. Sin embargo la edad, una variable fundamental en la configuración de la justicia juvenil, no resulta significativa. De este modo, el trabajo muestra el potencial explicativo de este conjunto de factores y debate sus implicaciones teóricas y metodológicas para la investigación futura en este terreno.

A dielectric continuum molecular dynamics method

We introduce a novel method to simulate hydrated macromolecules with a dielectric continuum representation of the surrounding solvent. In our approach, the interaction between the solvent and the molecular degrees of freedom is described by means of a polarization density free energy functional which is minimum at electrostatic equilibrium. After a pseudospectral expansion of the polarization and a discretization of the functional, we construct the equations of motion for the system based on a Car-Parrinello technique. In the limit of the adiabatic evolution of the polarization field variables, our method provides the solution of the dielectric continuum problem "on the fly," while the molecular coordinates are propagated. In this first study, we show how our dielectric continuum molecular dynamics method can be successfully applied to hydrated biomolecules, with low cost compared to free energy simulations with explicit solvent. To our knowledge, this is the first time that stable and conservative molecular dynamic simulations of solutes can be performed for a dielectric continuum model of the solvent. (C) 2001 American Institute of Physics.

Roche tomography of cataclysmic variables - I. Artefacts and techniques

Roche tomography is a technique used for imaging the Roche-lobe-filling secondary stars in cataclysmic variables (CVs). In order to interpret Roche tomograms correctly, one must determine whether features in the reconstruction are real, or the result of statistical or systematic errors. We explore the effects of systematic errors using reconstructions of simulated data sets, and show that systematic errors result in characteristic distortions of the final reconstructions that can be identified and corrected. In addition, we present a new method of estimating statistical errors on tomographic reconstructions using a Monte Carlo bootstrapping algorithm, and show this method to be much more reliable than Monte Carlo methods which 'jiggle' the data points in accordance with the size of their error bars.

Estimating trophic link density from quantitative but incomplete diet data

The trophic link density and the stability of food webs are thought to be related, but the nature of this relation is controversial. This article introduces a method for estimating the link density from diet tables which do not cover the complete food web and do not resolve all diet items to species level. A simple formula for the error of this estimate is derived. Link density is determined as a function of a threshold diet fraction below which diet items are ignored (

Alternative method for producing organic fertiliser from anaerobic digestion liquor and limestone powder:High Shear wet granulation

Generally, the solid and liquid fractions (digestate) from Anaerobic Digestion (AD) energy production are considered as waste. This has a negative impact on the sustainability of AD processes because of the financial outlay required to treat digestate before being discharged into municipal water treatment plants or natural water bodies. The main aim of this research was to investigate feasibility of producing an organic fertiliser using anaerobic digestate and limestone powders as the raw materials employing a high shear granulation process. Two-level factorial experimental design was used to determine the influence of granulation process variables on, the strength, resistance to attrition and yield of the granules. It was concluded from the study that it is technically feasible to produce organic fertiliser granules of acceptable strength and product yield. Increasing the liquid-to-solid ratio during granulation leads to increased granule strength and better product yield. Although the strength of the granules produced was lower than typical strength of commercial synthetic fertiliser granules (about 5 to 7. MPa), this could be improved by mixing the digestate with a polymeric binder or coating the particles post granulation. © 2012 Elsevier B.V.

The palliative care link nurse role in nursing homes: barriers and facilitators

Aim. This paper is a report of a study to explore link nurses' views and experiences regarding the development, barriers and facilitators to the implementation of the role in palliative care in the nursing home.
Background. The delivery of palliative care in nursing homes is widely advocated; one approach is to develop the link nurse role to cascade good practice and training to nurses and other care staff to enhance patient care.
Method. A descriptive qualitative study was conducted with a purposive sample of 14 link nurses from 10 nursing homes in Northern Ireland during 2006. Three focus groups, composed of all Registered Nurses currently acting as link nurses in their nursing homes participated, and the data were audio recorded, fully transcribed and content analysed.
Findings. The link nurse system shows potential to enhance palliative care within nursing homes. However, link nurses experienced a number of difficulties in implementing education programmes. Facilitators of the role included external support, monthly meetings, access to a resource file and peer support among link nurses themselves. Lack of management support, a transient workforce and lack of adequate preparation for link nurses were barriers to fulfilling this role.
Conclusion. Whilst palliative care link nurses can improve care for residents in nursing homes, consideration must be given to overcome the types of barriers identified in order to enable the link nurse system to function effectively. © 2008 The Authors.

Effect of cooking method and rice type on arsenic concentration in cooked rice and the estimation of arsenic dietary intake in a rural village in West Bengal, India

Arsenic (As) contamination of rice plants can result in high total As concentrations (t-As) in cooked rice, especially if As-contaminated water is used for cooking. This study examines two variables: (1) the cooking method (water volume and inclusion of a washing step); and (2) the rice type (atab and boiled). Cooking water and raw atab and boiled rice contained 40 g As l-1 and 185 and 315 g As kg-1, respectively. In general, all cooking methods increased t-As from the levels in raw rice; however, raw boiled rice decreased its t-As by 12.7% when cooked by the traditional method, but increased by 15.9% or 23.5% when cooked by the intermediate or contemporary methods, respectively. Based on the best possible scenario (the traditional cooking method leading to the lowest level of contamination, and the atab rice type with the lowest As content), t-As daily intake was estimated to be 328 g, which was twice the tolerable daily intake of 150 g.

Roche tomography of cataclysmic variables - VI. Differential rotation of AE Aqr - not tidally locked!

We present Roche tomograms of the K4V secondary star in the cataclysmic variable AE Aqr, reconstructed from two data sets taken 9 d apart, and measure the differential rotation of the stellar surface. The tomograms show many large, cool starspots, including a large high-latitude spot and a prominent appendage down the trailing hemisphere. We find two distinct bands of spots around 22° and 43° latitude, and estimate a spot coverage of 15.4-17 per cent on the Northern hemisphere. Assuming a solar-like differential rotation law, the differential rotation of AE Aqr was measured using two different techniques. The first method yields an equator-pole lap time of 269 d and the second yields a lap time of 262 d. This shows that the star is not fully tidally locked, as was previously assumed for CVs, but has a co-rotation latitude of ˜40°. We discuss the implications that these observations have on stellar dynamo theory, as well as the impact that spot traversal across the L1 point may have on accretion rates in CVs as well as some of their other observed properties. The entropy landscape technique was applied to determine the system parameters of AE Aqr. For the two independent data sets, we find M1 = 1.20 and 1.17 M⊙, M2 = 0.81 and 0.78 M⊙, and orbital inclinations of 50° to 51° at optimal systemic velocities of γ = -64.7 and -62.9 km s-1.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

Learning Bayesian Networks with Thousands of Variables

We present a method for learning Bayesian networks from data sets containing thousands of variables without the need for structure constraints. Our approach is made of two parts. The first is a novel algorithm that effectively explores the space of possible parent sets of a node. It guides the exploration towards the most promising parent sets on the basis of an approximated score function that is computed in constant time. The second part is an improvement of an existing ordering-based algorithm for structure optimization. The new algorithm provably achieves a higher score compared to its original formulation. Our novel approach consistently outperforms the state of the art on very large data sets.

Application of Redundancy Analysis for Aerobiological Data

An aerobiological survey was conducted through five consecutive years (2006–2010) at Worcester (England).The concentration of 20 allergenic fungal spore types was measured using a 7-day volumetric spore trap. The relationship between investigated fungal spore genera and selected meteorological parameters (maximum, minimum, mean and dew point temperatures, rainfall, relative humidity, air pressure,wind direction) was examined using an ordination method(redundancy analysis) to determine which environmental factors favoured their most abundance in the air and whether it would be possible to detect similarities between different genera in their distribution pattern. Redundancy analysis provided additional information about the biology of the studied fungi through the results of the Spearman’s rank correlation. Application of the variance inflation factor in canonical correspondence analysis indicated which explanatory variables were auto-correlated and needed to be excluded from further analyses. Obtained information will be consequently implemented in the selection of factors that will be a foundation for forecasting models for allergenic fungal spores in the future.

Patterns of cortisol and DHEA secretion and relationships with attachment style and psychosocial variables in female adolescents: a developmental psychopathology approach

This programme of research used a developmental psychopathology approach to investigate females across the adolescent period. A two-sided story is presented; first, a study of neuroendocrine and psychosocial parameters in a group of healthy female adolescents (N = 63), followed by a parallel study of female adolescents with anorexia nervosa (AN) (N = 8). A biopsychosocial, multi-method measurement approach was taken, which utilised self-report, interview and hypothalamic-pituitary-adrenocortical (HPA) axis measures. Saliva samples for the measurement of cortisol and DHEA were collected using the best-recommended methodology: multiple samples over the day, strict reference to time of awakening, and two consecutive sampling weekdays. The research was adolescent-orientated: specifically, by using creative and ageappropriate strategies to ensure participant adherence to protocol, as well as more generally by adopting various procedures to facilitate engagement with the research process. In the healthy females mean (± SD) age 13.9 (± 2.7) years, cortisol and DHEA secretion exhibited typical adult-like diurnal patterns. Developmental markers of chronological age, menarche status and body mass index (BMI) had differential associations with cortisol and DHEA secretory activity. The pattern of the cortisol awakening response (CAR) was sensitive to whether participants had experienced first menses, but not to chronological age or BMI. Those who were post-menarche generally reached their peak point of cortisol secretion at 45 minutes post-awakening, in contrast to the pre-menarche group who were more evenly spread. Subsequent daytime cortisol levels were also higher in post-menarche females, and this effect was also noted for increasing age and BMI. Both morning and evening DHEA were positively associated with developmental markers. None of the situational or self-report psychosocial variables that were measured modulated any of the key findings regarding cortisol and DHEA secretion. The healthy group of girls were within age-appropriate norms for all the self-report measures used, however just under half of this group were insecurely attached (as assessed by interview). Only attachment style was associated with neuroendocrine parameters. In particular, those with an anxious insecure style exhibited a higher awakening sample (levels were 7.16 nmol/l, 10.40 nmol/l and 7.93 nmol/l for secure, anxious and avoidant groups, respectively) and a flatter CAR (mean increases over the awakening period were 6.38 nmol/l, 2.32 nmol/l and 8.61 nmol/l for secure, anxious and avoidant groups, respectively). The afore-mentioned pattern is similar to that consistently associated with psychological disorder in adults, and so this may be a pre-clinical vulnerability factor for subsequent mental health problems. A group of females with AN, mean (± SD) age 15.1 (± 1.6) years, were recruited from a specialist residential clinic and compared to the above group of healthy control (HC) female adolescents. A general picture of cortisol and DHEA hypersecretion was revealed in those with AN. The mean (± SD) change exhibited in cortisol levels over the 30 minute post-awakening period was 7.05 nmol/l (± 5.99) and 8.33 nmol/l (± 6.41) for HC and AN groups, respectively. The mean (± SD) evening cortisol level for the HC girls was 1.95 nmol/l (± 2.11), in comparison to 6.42 nmol/l (± 11.10) for the AN group. Mean (± SD) morning DHEA concentrations were 1.47 nmol/l (± 0.85) and 2.25 nmol/l (± 0.88) for HC and AN groups, respectively. The HC group’s mean (± SD) concentration of 12 hour DHEA was 0.55 nmol/l (± 0.46) and the AN group’s mean level was 0.89 nmol/l (± 0.90). This adrenal steroid hypersecretion evidenced by the AN group was not associated with BMI or eating disorder symptomatology. Insecure attachment characterised by fearfulness and anger was most apparent; a style which was unparalleled in the healthy group of female adolescents. The causal directions of the AN group findings remain unclear. Examining some of the participants with AN as case studies one year post-discharge from the clinic illustrated that for one participant who was recovered, in terms of returning to ordinary school life and no longer exhibiting clinical levels of eating disorder symptomatology, her CARs were no longer inconsistent over sampling days and her DHEA levels were also now generally comparable to the healthy control group. For another participant who had not recovered from her AN one year later, the profile of her CAR continued to be inconsistent over sampling days and her DHEA concentrations over the diurnal period were significantly higher in comparison to the healthy control group. In its entirety, this work’s unique contribution lies in its consideration of methodological and developmental issues specifically pertaining to adolescents. Findings also contribute to knowledge of AN and understanding of vulnerability factors, and how these may be used to develop interventions dedicated to improving adolescent health.