Urban surface energy balance models: model characteristics and methodology for a comparison study

Many urban surface energy balance models now exist. These vary in complexity from simple schemes that represent the city as a concrete slab, to those which incorporate detailed representations of momentum and energy fluxes distributed within the atmospheric boundary layer. While many of these schemes have been evaluated against observations, with some models even compared with the same data sets, such evaluations have not been undertaken in a controlled manner to enable direct comparison. For other types of climate model, for instance the Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS) experiments (Henderson-Sellers et al., 1993), such controlled comparisons have been shown to provide important insights into both the mechanics of the models and the physics of the real world. This paper describes the progress that has been made to date on a systematic and controlled comparison of urban surface schemes. The models to be considered, and their key attributes, are described, along with the methodology to be used for the evaluation.

Terrorist transgressions: gendered representations of the terrorist in visual culture

The aim of Terrorist Transgressions is to analyse the myths inscribed in images of the terrorist and identify how agency is attributed to representation through invocations and inversions of gender stereotypes. In modern discourses on the terrorist the horror experienced in Western societies was the appearance of a new sense of the vulnerability of the body politic, and therefore of the modern self with its direct dependency on security and property. The terrorist has been constructed as the epitome of transgression against economic resources and moral, physical and political boundaries. Although terrorism has been the focus of intense academic activity, cultural representations of the terrorist have received less attention. Yet terrorism is dependent on spectacle and the topic is subject to forceful exposure in popular media. While the terrorist is predominantly aligned with masculinity, women have been active in terrorist organisations since the late 19th century and in suicidal terrorist attacks since the 1980s. Such attacks have confounded constructions of femininity and masculinity, with profound implications for the gendering of violence and horror. The publication arises from an AHRC networking grant, 2011-12, with Birkbeck, and includes collaboration with the army at Sandhurst RMA. The project relates to a wider investigation into feminism, violence and contemporary art.

A generalised Bayesian instrumental variable approach under student t-distributed errors with application

Bayesian analysis is given of an instrumental variable model that allows for heteroscedasticity in both the structural equation and the instrument equation. Specifically, the approach for dealing with heteroscedastic errors in Geweke (1993) is extended to the Bayesian instrumental variable estimator outlined in Rossi et al. (2005). Heteroscedasticity is treated by modelling the variance for each error using a hierarchical prior that is Gamma distributed. The computation is carried out by using a Markov chain Monte Carlo sampling algorithm with an augmented draw for the heteroscedastic case. An example using real data illustrates the approach and shows that ignoring heteroscedasticity in the instrument equation when it exists may lead to biased estimates.

A semi-distributed ntegrated itrogen model for multiple source assessment in tchments (INCA): Part I — model structure and process equations

A new model has been developed for assessing multiple sources of nitrogen in catchments. The model (INCA) is process based and uses reaction kinetic equations to simulate the principal mechanisms operating. The model allows for plant uptake, surface and sub-surface pathways and can simulate up to six land uses simultaneously. The model can be applied to catchment as a semi-distributed simulation and has an inbuilt multi-reach structure for river systems. Sources of nitrogen can be from atmospheric deposition, from the terrestrial environment (e.g. agriculture, leakage from forest systems etc.), from urban areas or from direct discharges via sewage or intensive farm units. The model is a daily simulation model and can provide information in the form of time series at key sites, or as profiles down river systems or as statistical distributions. The process model is described and in a companion paper the model is applied to the River Tywi catchment in South Wales and the Great Ouse in Bedfordshire.

PERSiST: a flexible rainfall-runoff modelling toolkit for use with the INCA family of models

Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis

Socially anxious mothers’ narratives to their children, and their relation to child representations and adjustment

Anxious mothers’ parenting, particularly transfer of threat information, has been considered important in their children’s risk for social anxiety disorder (SAnxD), and maternal narratives concerning potential social threat could elucidate this contribution. Maternal narratives to their pre-school 4-5 year-old children, via a picture book about starting school, were assessed in socially anxious (N=73), and non-anxious (N=63) mothers. Child representations of school were assessed via Doll Play (DP). After one school term, mothers (CBCL) and teachers (TRF) reported on child internalizing problems, and child SAnxD was assessed via maternal interview. Relations between these variables, infant behavioral inhibition, and attachment, were examined. Socially anxious mothers showed more negative (higher threat attribution), and less supportive (lower encouragement) narratives, than controls, and their children’s DP representations, SAnxD and CBCL scores were more adverse. High narrative threat predicted child SAnxD; lower encouragement predicted negative child CBCL scores and, particularly for behaviorally inhibited children, TRF scores and DP representations. In securely attached children, CBCL scores and risk for SAnxD were affected by maternal anxiety and threat attributions, respectively. Low encouragement mediated the effects of maternal anxiety on child DP representations, and CBCL scores. Maternal narratives are affected by social anxiety, and contribute to adverse child outcome.

Enhanced affective brain representations of chocolate in cravers vs. non-cravers

To examine the neural circuitry involved in food craving, in making food particularly appetitive and thus in driving wanting and eating, we used fMRI to measure the response to the flavour of chocolate, the sight of chocolate and their combination in cravers vs. non-cravers. Statistical parametric mapping (SPM) analyses showed that the sight of chocolate produced more activation in chocolate cravers than non-cravers in the medial orbitofrontal cortex and ventral striatum. For cravers vs. non-cravers, a combination of a picture of chocolate with chocolate in the mouth produced a greater effect than the sum of the components (i.e. supralinearity) in the medial orbitofrontal cortex and pregenual cingulate cortex. Furthermore, the pleasantness ratings of the chocolate and chocolate-related stimuli had higher positive correlations with the fMRI blood oxygenation level-dependent signals in the pregenual cingulate cortex and medial orbitofrontal cortex in the cravers than in the non-cravers. To our knowledge, this is the first study to show that there are differences between cravers and non-cravers in their responses to the sensory components of a craved food in the orbitofrontal cortex, ventral striatum and pregenual cingulate cortex, and that in some of these regions the differences are related to the subjective pleasantness of the craved foods. Understanding individual differences in brain responses to very pleasant foods helps in the understanding of the mechanisms that drive the liking for specific foods and thus intake of those foods.

Expected value, reward outcome, and temporal difference error representations in a probabilistic decision task

In probabilistic decision tasks, an expected value (EV) of a choice is calculated, and after the choice has been made, this can be updated based on a temporal difference (TD) prediction error between the EV and the reward magnitude (RM) obtained. The EV is measured as the probability of obtaining a reward x RM. To understand the contribution of different brain areas to these decision-making processes, functional magnetic resonance imaging activations related to EV versus RM (or outcome) were measured in a probabilistic decision task. Activations in the medial orbitofrontal cortex were correlated with both RM and with EV and confirmed in a conjunction analysis to extend toward the pregenual cingulate cortex. From these representations, TD reward prediction errors could be produced. Activations in areas that receive from the orbitofrontal cortex including the ventral striatum, midbrain, and inferior frontal gyrus were correlated with the TD error. Activations in the anterior insula were correlated negatively with EV, occurring when low reward outcomes were expected, and also with the uncertainty of the reward, implicating this region in basic and crucial decision-making parameters, low expected outcomes, and uncertainty.

Semantic self-knowledge and episodic self-knowledge: Independent or interrelated representations?

In this study of the structure of self-knowledge, we examined priming effects for the recall of personal episodes in order to investigate whether abstract trait knowledge and personal episodes are independent mental representations. We found that accessing similar abstract representations of traits facilitated a faster recall of related personal episodes than did accessing irrelevant abstract representations of traits (Experiments 1 and 2), reading a nonword prime (Experiments 2 and 3), accessing knowledge of one's mother (Experiment 3), or accessing semantic knowledge (Experiment 3). Contrary to previous findings, which indicated that abstract trait knowledge is represented independently of related personal episodes (e.g., Klein & Loftus, 1993, our results suggest that abstract trait knowledge is associated with personal episodes, and therefore that semantic self-knowledge is associated with episodic self-knowledge in long-term self-knowledge.

The absent body: representations of dying early modern women in a selection of seventeenth-century diaries

This article seeks to explore the absence of the body in the depiction of dying women in a selection of seventeenth-century diaries. It considers the cultural forces that made this absence inevitable, and the means by which the physical body was replaced in death by a spiritual presence. The elevation of a dying woman from physical carer to spiritual nurturer in the days before death ensured that gender codes were not broken. The centrality of the body of the dying woman, within a female circle of care and support, was paradoxically juxtaposed with an effacement of the body in descriptions of a good death. In death, a woman might achieve the stillness, silence and compliance so essential to perfect early modern womanhood, and retrospective diary entries can achieve this ideal by replacing the body with images that deflect from the essential physicality of the woman.

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.

Calibration of structure in a distributed forecasting model for a semiarid flash flood: dynamic surface storage and channel roughness

Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.

Assessing the sensitivities of a distributed snow model to forcing data resolution

Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.

Energy-efficient resource allocation in OFDM systems with distributed antennas

In this paper, we develop an energy-efficient resource-allocation scheme with proportional fairness for downlink multiuser orthogonal frequency-division multiplexing (OFDM) systems with distributed antennas. Our aim is to maximize energy efficiency (EE) under the constraints of the overall transmit power of each remote access unit (RAU), proportional fairness data rates, and bit error rates (BERs). Because of the nonconvex nature of the optimization problem, obtaining the optimal solution is extremely computationally complex. Therefore, we develop a low-complexity suboptimal algorithm, which separates subcarrier allocation and power allocation. For the low-complexity algorithm, we first allocate subcarriers by assuming equal power distribution. Then, by exploiting the properties of fractional programming, we transform the nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form, which includes a tractable solution. Next, an optimal energy-efficient power-allocation algorithm is developed to maximize EE while maintaining proportional fairness. Through computer simulation, we demonstrate the effectiveness of the proposed low-complexity algorithm and illustrate the fundamental trade off between energy and spectral-efficient transmission designs.