Home, meaning and identity: learning from the English model of shared ownership

This article explores the problematic nature of the label “home ownership” through a case study of the English model of shared ownership, one of the methods used by the UK government to make home ownership affordable. Adopting a legal and socio-legal analysis, the article considers whether shared ownership is capable of fulfilling the aspirations households have for home ownership. To do so, the article considers the financial and nonfinancial meanings attached to home ownership and suggests that the core expectation lies in ownership of the value. The article demonstrates that the rights and responsibilities of shared owners are different in many respects from those of traditional home owners, including their rights as regards ownership of the value. By examining home ownership through the lens of shared ownership the article draws out lessons of broader significance to housing studies. In particular, it is argued that shared ownership shows the limitations of two dichotomies commonly used in housing discourse: that between private and social housing; and the classification of tenure between owner-occupiers and renters. The article concludes that a much more nuanced way of referring to home ownership is required, and that there is a need for a change of expectations amongst consumers as to what sharing ownership means.

fMRI evidence for the involvement of the procedural memory system in morphological processing of a second language

Behavioural evidence suggests that English regular past tense forms are automatically decomposed into their stem and affix (played  = play+ed) based on an implicit linguistic rule, which does not apply to the idiosyncratically formed irregular forms (kept). Additionally, regular, but not irregular inflections, are thought to be processed through the procedural memory system (left inferior frontal gyrus, basal ganglia, cerebellum). It has been suggested that this distinction does not to apply to second language (L2) learners of English; however, this has not been tested at the brain level. This fMRI study used a masked-priming task with regular and irregular prime-target pairs (played-play/kept-keep) to investigate morphological processing in native and highly proficient late L2 English speakers. No between-groups differences were revealed. Compared to irregular pairs, regular pairs activated the pars opercularis, bilateral caudate nucleus and the right cerebellum, which are part of the procedural memory network and have been connected with the processing of morphologically complex forms. Our study is the first to provide evidence for native-like involvement of the procedural memory system in processing of regular past tense by late L2 learners of English.

Improved seasonal prediction of the hot summer of 2003 over Europe through better representation of uncertainty in the land surface

Methods to explicitly represent uncertainties in weather and climate models have been developed and refined over the past decade, and have reduced biases and improved forecast skill when implemented in the atmospheric component of models. These methods have not yet been applied to the land surface component of models. Since the land surface is strongly coupled to the atmospheric state at certain times and in certain places (such as the European summer of 2003), improvements in the representation of land surface uncertainty may potentially lead to improvements in atmospheric forecasts for such events. Here we analyse seasonal retrospective forecasts for 1981–2012 performed with the European Centre for Medium-Range Weather Forecasts’ (ECMWF) coupled ensemble forecast model. We consider two methods of incorporating uncertainty into the land surface model (H-TESSEL): stochastic perturbation of tendencies, and static perturbation of key soil parameters. We find that the perturbed parameter approach considerably improves the forecast of extreme air temperature for summer 2003, through better representation of negative soil moisture anomalies and upward sensible heat flux. Averaged across all the reforecasts the perturbed parameter experiment shows relatively little impact on the mean bias, suggesting perturbations of at least this magnitude can be applied to the land surface without any degradation of model climate. There is also little impact on skill averaged across all reforecasts and some evidence of overdispersion for soil moisture. The stochastic tendency experiments show a large overdispersion for the soil temperature fields, indicating that the perturbation here is too strong. There is also some indication that the forecast of the 2003 warm event is improved for the stochastic experiments, however the improvement is not as large as observed for the perturbed parameter experiment.

Life history, morphological variability and growth rates of the life phases of Gracilaria tenuistipitata (Rhodophyta: Gracilariales) in vitro

Gracilaria tenuistipitata, a species of commercial interest, is becoming a model organism for studies on red algal physiology and molecular biology as it can be grown easily in vitro under a broad range of conditions. Most of the experiments carried out around the world have been based on a tetrasporophytic clone isolated in our laboratory from a specimen collected in China. Here we describe the life history of this species, give anatomic details of the reproductive structures, illustrate the morphological variability of tetraspore progeny and compare the growth rate of gametophytic and sporophytic thalli. Tetrasporophytic branches showed higher growth rates than gametophytic branches.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.

Newly Automated System For Integrated Assessment Of The Conditions Of Underwater Gas Pipelines

An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.

Learning-by-employing: the value of commitment

We analyze a dynamic principal–agent model where an infinitely-lived principal faces a sequence of finitely-lived agents who differ in their ability to produce output. The ability of an agent is initially unknown to both him and the principal. An agent’s effort affects the information on ability that is conveyed by performance. We characterize the equilibrium contracts and show that they display short–term commitment to employment when the impact of effort on output is persistent but delayed. By providing insurance against early termination, commitment encourages agents to exert effort, and thus improves on the principal’s ability to identify their talent. We argue that this helps explain the use of probationary appointments in environments in which there exists uncertainty about individual ability.

Ontogenetic Variation in Ammonia Excretion during the Early Life Stages of the Amazon River Prawn, Macrobrachium amazonicum

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fertility life table of Trichogramma pretiosum and Trichogramma acacioi (Hymenoptera : Trichogrammatidae) on Sitotroga cerealella (Lepidoptera : Gelechiidae) eggs at different constant temperatures

Fertility life tables were developed for both Trichogramma pretiosum and Trichogramma acacioi reared on Sitotroga cerealella eggs as an alternative host at five different temperatures. The egg parasitoids were first collected from Nipteria panacea eggs, a lepidopterous pest of avocado. Egg parasitoid females were individualized in small glass vials along with 40 eggs of the host during 24 h for parasitization. For evaluation of the parasitism capacity, a similar procedure was adopted, but cardboards with eggs were replaced every day. The net reproductive rate (Ro), intrinsic rate of increase (rm), finite rate of increase (lambda), and mean generation time (T) were estimated. Temperature affected all parameters for both Trichogramma species. The highest fecundity for both species was observed at 25degreesC. Extreme temperatures such as 15degreesC or 35degreesC negatively affect the development rate of both species.

Biology and fertility life table of the South American fruit fly Anastrepha fraterculus on grape

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Severity of banana leaf spot in an intercropping system in two cycles of banana Prata Ana

Prata Ana is the most planted banana cultivar in northern Minas Gerais, Brazil. It is however susceptible to several pathogens. This study was carried out to evaluate the disease severity of banana leaf spot in the Prata Ana cv. in the first and second cycle under six different planting systems. The randomized block experimental design was used with six treatments and four replications. lit an evaluation of the severity of banana leaf spot, no disease symptoms were found on Thap Maeo and Caipira. The evolution curve of the disease indicated seasonal effects in the first and second cycles. The severity, of banana leaf spot was highest soon after the regional rainy period from November to March. A comparison of the means of the evaluations indicated a reduction in disease severity from the first to the second cycle.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

First report of a B chromosome in a natural population of Astyanax altiparanae (Characiformes, Characidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)