Understanding of auditory discourse in older adults: the effects of syntax and working memory

Background: As people age, language-processing ability changes. While several factors modify discourse comprehension ability in older adults, syntactic complexity of auditory discourse has received scant attention. This is despite the widely researched domain of syntactic processing of single sentences in older adults. Aims: The aims of this study were to investigate the ability of healthy older adults to understand stories that differed in syntactic complexity, and its relation to working memory. Methods & Procedures: A total of 51 healthy adults (divided into three age groups) took part. They listened to brief stories (syntactically simple and syntactically complex) and had to respond to false/true comprehension probes following each story. Working memory capacity (digit span, forward and backward) was also measured. Outcomes & Results: Differences were found in the ability of healthy older adults to understand simple and complex discourse. The complex discourse in particular was more sensitive in discerning age-related language patterns. Only the complex discourse task correlated moderately with age. There was no correlation between age and simple discourse. As far as working memory is concerned, moderate correlations were found between working memory and complex discourse. Education did not correlate with discourse, neither simple, nor complex. Conclusions: Older adults may be less efficient in forming syntactically complex representations and this may be influenced by limitations in working memory.

Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

Effect of improving representation of horizontal and vertical cloud structure on the Earth's global radiation budget. Part I: review and parametrization

A poor representation of cloud structure in a general circulation model (GCM) is widely recognised as a potential source of error in the radiation budget. Here, we develop a new way of representing both horizontal and vertical cloud structure in a radiation scheme. This combines the ‘Tripleclouds’ parametrization, which introduces inhomogeneity by using two cloudy regions in each layer as opposed to one, each with different water content values, with ‘exponential-random’ overlap, in which clouds in adjacent layers are not overlapped maximally, but according to a vertical decorrelation scale. This paper, Part I of two, aims to parametrize the two effects such that they can be used in a GCM. To achieve this, we first review a number of studies for a globally applicable value of fractional standard deviation of water content for use in Tripleclouds. We obtain a value of 0.75 ± 0.18 from a variety of different types of observations, with no apparent dependence on cloud type or gridbox size. Then, through a second short review, we create a parametrization of decorrelation scale for use in exponential-random overlap, which varies the scale linearly with latitude from 2.9 km at the Equator to 0.4 km at the poles. When applied to radar data, both components are found to have radiative impacts capable of offsetting biases caused by cloud misrepresentation. Part II of this paper implements Tripleclouds and exponential-random overlap into a radiation code and examines both their individual and combined impacts on the global radiation budget using re-analysis data.

Effect of improving representation of horizontal and vertical cloud structure on the Earth's global radiation budget. Part II: The global effects

Reliably representing both horizontal cloud inhomogeneity and vertical cloud overlap is fundamentally important for the radiation budget of a general circulation model. Here, we build on the work of Part One of this two-part paper by applying a pair of parameterisations that account for horizontal inhomogeneity and vertical overlap to global re-analysis data. These are applied both together and separately in an attempt to quantify the effects of poor representation of the two components on radiation budget. Horizontal inhomogeneity is accounted for using the “Tripleclouds” scheme, which uses two regions of cloud in each layer of a gridbox as opposed to one; vertical overlap is accounted for using “exponential-random” overlap, which aligns vertically continuous cloud according to a decorrelation height. These are applied to a sample of scenes from a year of ERA-40 data. The largest radiative effect of horizontal inhomogeneity is found to be in areas of marine stratocumulus; the effect of vertical overlap is found to be fairly uniform, but with larger individual short-wave and long-wave effects in areas of deep, tropical convection. The combined effect of the two parameterisations is found to reduce the magnitude of the net top-of-atmosphere cloud radiative forcing (CRF) by 2.25 W m−2, with shifts of up to 10 W m−2 in areas of marine stratocumulus. The effects of the uncertainty in our parameterisations on radiation budget is also investigated. It is found that the uncertainty in the impact of horizontal inhomogeneity is of order ±60%, while the uncertainty in the impact of vertical overlap is much smaller. This suggests an insensitivity of the radiation budget to the exact nature of the global decorrelation height distribution derived in Part One.

Neural competition for conscious representation across time: An fMRI study

Background The information processing capacity of the human mind is limited, as is evidenced by the attentional blink (AB) - a deficit in identifying the second of two temporally-close targets (T1 and T2) embedded in a rapid stream of distracters. Theories of the AB generally agree that it results from competition between stimuli for conscious representation. However, they disagree in the specific mechanisms, in particular about how attentional processing of T1 determines the AB to T2. Methodology/Principal Findings The present study used the high spatial resolution of functional magnetic resonance imaging (fMRI) to examine the neural mechanisms underlying the AB. Our research approach was to design T1 and T2 stimuli that activate distinguishable brain areas involved in visual categorization and representation. ROI and functional connectivity analyses were then used to examine how attentional processing of T1, as indexed by activity in the T1 representation area, affected T2 processing. Our main finding was that attentional processing of T1 at the level of the visual cortex predicted T2 detection rates Those individuals who activated the T1 encoding area more strongly in blink versus no-blink trials generally detected T2 on a lower percentage of trials. The coupling of activity between T1 and T2 representation areas did not vary as a function of conscious T2 perception. Conclusions/Significance These data are consistent with the notion that the AB is related to attentional demands of T1 for selection, and indicate that these demands are reflected at the level of visual cortex. They also highlight the importance of individual differences in attentional settings in explaining AB task performance.

Application of Gaussian multi-scale representation to feature tracking in meteorological satellite imagery

Gaussian multi-scale representation is a mathematical framework that allows to analyse images at different scales in a consistent manner, and to handle derivatives in a way deeply connected to scale. This paper uses Gaussian multi-scale representation to investigate several aspects of the derivation of atmospheric motion vectors (AMVs) from water vapour imagery. The contribution of different spatial frequencies to the tracking is studied, for a range of tracer sizes, and a number of tracer selection methods are presented and compared, using WV 6.2 images from the geostationary satellite MSG-2.

Career journeys and turning points of senior female managers in small construction firms

There is under-representation of senior female managers within small construction firms in the United Kingdom. The position is denying the sector a valuable pool of labour to address acute knowledge and skill shortages. Grounded theory on the career progression of senior female managers in these firms is developed from biographical interviews. First, a turning point model which distinguishes the interplay between human agency and work/home structure is given. Second, four career development phases are identified. The career journeys are characterized by ad hoc decisions and opportunities which were not influenced by external policies aimed at improving the representation of women in construction. Third, the 'hidden', but potentially significant, contribution of women-owned small construction firms is noted. The key challenge for policy and practice is to balance these external approaches with recognition of the 'inside out' reality of the 'lived experiences' of female managers. To progress this agenda there is a need for: appropriate longitudinal statistical data to quantify the scale of senior female managers and owners of small construction firms over time; and, social construction and gendered organizational analysis research to develop a general discourse on gender difference with these firms.

Subjectively construed identities and discourse: towards a research agenda for construction management

Identity issues are under-explored in construction management. We provide a brief introduction to the organization studies literature on subjectively construed identities, focusing on discourse, agency, relations of power and identity work. The construction management literature is investigated in order to examine identity concerns as they relate to construction managers centred on (1) professionalism; (2) ethics; (3) relational aspects of self-identity; (4) competence, knowledge and tools; and (5) national culture. Identity, we argue, is a key performance issue, and needs to be accounted for in explanations of the success and failure of projects. Our overriding concern is to raise identity issues in order to demonstrate their importance to researchers in construction management and to spark debate. The purpose of this work is not to provide answers or to propose prescriptive models, but to explore ideas, raise awareness and to generate questions for further programmatic research. To this end, we promote empirical work and theorizing by outlining elements of a research agenda which argues that 'identity' is a potentially generative theme for scholars in construction management.

The representation of fathers by children of depressed mothers: refining the meaning of parentification in high-risk samples

Background: Children’s representations of mothers in doll-play are associated with child adjustment. Despite the importance of fathers for children’s adjustment, especially in the context of maternal psychopathology, few studies have considered children’s representations of their fathers. Method: We examined the portrayal of fathers by 5-year-old children of depressed (N = 55) and non-depressed (N = 39) mothers in a doll-play procedure concerning family experience. Results: Children gave equal prominence in their play to mothers and fathers. Representations of fathers were unrelated to maternal mood, but were associated with parental conflict. Representations of child care for the father that was unreciprocated predicted poor child adjustment in school, but only in children exposed to maternal postnatal depression. Conclusions: It may be clinically useful to consider children’s distinctive representations of their mother and father; but the concept of parentification in relation to risk and resilience effects requires refinement.

Dynamic knowledge representation in connectionist systems

One of the most pervading concepts underlying computational models of information processing in the brain is linear input integration of rate coded uni-variate information by neurons. After a suitable learning process this results in neuronal structures that statically represent knowledge as a vector of real valued synaptic weights. Although this general framework has contributed to the many successes of connectionism, in this paper we argue that for all but the most basic of cognitive processes, a more complex, multi-variate dynamic neural coding mechanism is required - knowledge should not be spacially bound to a particular neuron or group of neurons. We conclude the paper with discussion of a simple experiment that illustrates dynamic knowledge representation in a spiking neuron connectionist system.