Clustering and synchrony in laying hens: The effect of environmental resources on social dynamics

Laying hens generally choose to aggregate, but the extent to which the environments in which we house them impact on social group dynamics is not known. In this paper the effect of pen environment on spatial clustering is considered. Twelve groups of four laying hens were studied under three environmental conditions: wire floor (W), shavings (Sh) and perches, peat, nestbox and shavings (PPN). Groups experienced each environment twice, for five weeks each time, in a systematic order that varied from group to group. Video recordings were made one day per week for 30 weeks. To determine level of clustering, we recorded positional data from a randomly selected 20-min excerpt per video (a total of 20 min x 360 videos analysed). On screen, pens were divided into six equal areas. In addition, PPN pens were divided into an additional four (sub) areas, to account for the use of perches (one area per half perch). Every 5 s, we recorded the location of each bird and calculated location use over time, feeding synchrony and cluster scores for each environment. Feeding synchrony and cluster scores were compared against unweighted and weighted (according to observed proportional location use) Poisson distributions to distinguish between resource and social attraction.

WASP-34b: a near-grazing transiting sub-Jupiter-mass exoplanet in a hierarchical triple system

We report the discovery of WASP-34b, a sub-Jupiter-mass exoplanet transiting its 10.4-magnitude solar-type host star (1SWASP J110135.89-235138.4; TYC 6636-540-1) every 4.3177 days in a slightly eccentric orbit (e = 0.038±0.012). We find a planetary mass of 0.59±0.01 MJup and radius of 1.22-0.08+0.11 RJup. There is a linear trend in the radial velocities of 55±4 m s-1 y-1 indicating the presence of a long-period third body in the system with a mass ?0.45 MJup at a distance of ?1.2 AU from the host star. This third-body is either a low-mass star, a white dwarf, or another planet. The transit depth ((RP/Rstar)2 = 0.0126) and high impact parameter (b = 0.90) suggest that this could be the first known transiting exoplanet expected to undergo grazing transits, but with a confidence of only 80%. Radial velocity and photometric data are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/526/A130

A review of studies of ionizing radiation-induced double-strand break clustering

Underpinning current models of the mechanisms of the action of radiation is a central role for DNA damage and in particular double-strand breaks (DSBs). For radiations of different LET, there is a need to know the exact yields and distributions of DSBs in human cells. Most measurements of DSB yields within cells now rely on pulsed-field gel electrophoresis as the technique of choice. Previous measurements of DSB yields have suggested that the yields are remarkably similar for different types of radiation with RBE values less than or equal to1.0. More recent studies in mammalian cells, however, have suggested that both the yield and the spatial distribution of DSBs are influenced by radiation quality. RBE values for DSBs induced by high-LET radiations are greater than 1.0, and the distributions are nonrandom. Underlying this is the interaction of particle tracks with the higher-order chromosomal structures within cell nuclei. Further studies are needed to relate nonrandom distributions of DSBs to their rejoining kinetics. At the molecular level, we need to determine the involvement of clustering of damaged bases with strand breakage, and the relationship between higher-order clustering over sizes of kilobase pairs and above to localized clustering at the DNA level. Overall, these studies will allow us to elucidate whether the nonrandom distributions of breaks produced by high-LET particle tracks have any consequences for their repair and biological effectiveness. (C) 2001 by Radiation Research Society.

A Monte Carlo model of DNA double-strand break clustering and rejoining kinetics for the analysis of pulsed-field gel electrophoresis data

In studies of radiation-induced DNA fragmentation and repair, analytical models may provide rapid and easy-to-use methods to test simple hypotheses regarding the breakage and rejoining mechanisms involved. The random breakage model, according to which lesions are distributed uniformly and independently of each other along the DNA, has been the model most used to describe spatial distribution of radiation-induced DNA damage. Recently several mechanistic approaches have been proposed that model clustered damage to DNA. In general, such approaches focus on the study of initial radiation-induced DNA damage and repair, without considering the effects of additional (unwanted and unavoidable) fragmentation that may take place during the experimental procedures. While most approaches, including measurement of total DNA mass below a specified value, allow for the occurrence of background experimental damage by means of simple subtractive procedures, a more detailed analysis of DNA fragmentation necessitates a more accurate treatment. We have developed a new, relatively simple model of DNA breakage and the resulting rejoining kinetics of broken fragments. Initial radiation-induced DNA damage is simulated using a clustered breakage approach, with three free parameters: the number of independently located clusters, each containing several DNA double-strand breaks (DSBs), the average number of DSBs within a cluster (multiplicity of the cluster), and the maximum allowed radius within which DSBs belonging to the same cluster are distributed. Random breakage is simulated as a special case of the DSB clustering procedure. When the model is applied to the analysis of DNA fragmentation as measured with pulsed-field gel electrophoresis (PFGE), the hypothesis that DSBs in proximity rejoin at a different rate from that of sparse isolated breaks can be tested, since the kinetics of rejoining of fragments of varying size may be followed by means of computer simulations. The problem of how to account for background damage from experimental handling is also carefully considered. We have shown that the conventional procedure of subtracting the background damage from the experimental data may lead to erroneous conclusions during the analysis of both initial fragmentation and DSB rejoining. Despite its relative simplicity, the method presented allows both the quantitative and qualitative description of radiation-induced DNA fragmentation and subsequent rejoining of double-stranded DNA fragments. (C) 2004 by Radiation Research Society.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

Hierarchical zeolites prepared by organosilane templating: A study of the synthesis mechanism and catalytic activity

The crystallization of hierarchical ZSM-5 in the presence of the organosilane octadecyl-dimethyl-(3-trimethoxysilyl-propyl)-ammonium chloride as the mesoporogen was investigated as a function of time and temperature. The synthesis by this method proceeds in two steps. The rapid formation of a predominantly amorphous disordered mesoporous aluminosilicate precursor phase is followed by the formation of globular highly mesoporous zeolite particles involving dissolution of the precursor phase. It is difficult to completely convert the initial phase into the final hierarchical zeolite. This limits the amount of aluminium built into the MFI network and the resulting Bronsted acidity. In the presence of iron, more crystalline hierarchical zeolite is obtained. These Fe-containing zeolites are excellent catalysts for the selective oxidation of benzene to phenol. Their hierarchical pore structure leads to higher reaction rates due to increased mass transfer and increased catalyst longevity despite more substantial coke formation. (C) 2011 Elsevier B.V. All rights reserved.

Hierarchical VHDL libraries for DSP ASIC design

Methods are presented for the rapid design of DSP ASICs based on the use of hierarchical VHDL libraries. These are portable across many silicon foundries and allow complex DSP silicon systems to be developed in a fraction of the time normally required. Resulting designs are highly competitive with ones created using conventional methods. The approach is illustrated by its application to ADPCM codec and DCT cores.

Rapid design of DSP ASIC cores using hierarchical VHDL libraries

Methods are presented for the rapid design of DSP ASICs based on the use of a series of hierarchical VHDL libraries which are portable across many silicon foundries. These allows complex DSP silicon systems to be developed in a small fraction of the time normally required. Resulting designs are highly competitive with those developed using more conventional methods. The approach is illustrated using several examples. These include ADPCM codecs, as well as DCT and FFT cores.

Hair cortisol reflects socio-economic factors and hair zinc in preschoolers

This study examined the relationship between children's hair cortisol and socioeconomic status of the family, as measured by parental education and income. Low family socioeconomic status has traditionally been considered a long-term environmental stressor. Measurement of hair cortisol provides an integrated index of cumulative stress exposure across an extended period of time. The present study is the first to examine the relationship between hair cortisol and parental education as well as parental income in a representative sample of preschoolers. Data on hair cortisol, family income, and parental education were collected for a representative sample of 339 children (Mean age=4.6 years; SD=.5 years) from across 23 neighbourhoods of the city of Vancouver, Canada. As maternal education was shown previously to be associated with hair zinc level, hair zinc measurements were included as well in order to explore potential relationships between hair zinc and hair cortisol. The relationship between hair cortisol and parental education was examined using hierarchical regression, with hair zinc, gender, age, and single parenthood included as covariates. Maternal and paternal education both were correlated significantly with hair cortisol (r=-0.18; p=.001). The relationship remained statistically significant even after controlling for all demographic covariates as well as for hair zinc and after taking the neighbourhood-level clustering of the data into account. Parental income, on the other hand, was not related significantly to children's hair cortisol. This study provides evidence that lower maternal and paternal education are associated with higher hair cortisol levels. As hair cortisol provides an integrated index of cortisol exposure over an extended time period, these findings suggest a possibly stable influence of SES on the function of the hypothalamic-pituitary-adrenal (HPA) axis. Cumulative exposure to cortisol during early childhood may be greater in children from low socio-economic backgrounds, possibly through increased exposure to environmental stressors.

Self-reported teamwork in family health team practices in Ontario:Organizational and cultural predictors of team climate

Objective: To determine the organizational predictors of higher scores on team climate measures as an indicator of the functioning of a family health team (FHT). Design: Cross-sectional study using a mailed survey. Setting: Family health teams in Ontario. Participants: Twenty-one of 144 consecutively approached FHTs; 628 team members were surveyed. Main outcome measures: Scores on the team climate inventory, which assessed organizational culture type (group, developmental, rational, or hierarchical); leadership perceptions; and organizational factors, such as use of electronic medical records (EMRs), team composition, governance of the FHT, location, meetings, and time since FHT initiation. All analyses were adjusted for clustering of respondents within the FHT using a mixed random-intercepts model. Results: The response rate was 65.8% (413 of 628); 2 were excluded from analysis, for a total of 411 participants. At the time of survey completion, there was a median of 4 physicians, 11 other health professionals, and 4 management and clerical staff per FHT. The average team climate score was 3.8 out of a possible 5. In multivariable regression analysis, leadership score, group and developmental culture types, and use of more EMR capabilities were associated with higher team climate scores. Other organizational factors, such as number of sites and size of group, were not associated with the team climate score. Conclusion: Culture, leadership, and EMR functionality, rather than organizational composition of the teams (eg, number of professionals on staff, practice size), were the most important factors in predicting climate in primary care teams.