View-based approaches to spatial representation in human vision

In an immersive virtual environment, observers fail to notice the expansion of a room around them and consequently make gross errors when comparing the size of objects. This result is difficult to explain if the visual system continuously generates a 3-D model of the scene based on known baseline information from interocular separation or proprioception as the observer walks. An alternative is that observers use view-based methods to guide their actions and to represent the spatial layout of the scene. In this case, they may have an expectation of the images they will receive but be insensitive to the rate at which images arrive as they walk. We describe the way in which the eye movement strategy of animals simplifies motion processing if their goal is to move towards a desired image and discuss dorsal and ventral stream processing of moving images in that context. Although many questions about view-based approaches to scene representation remain unanswered, the solutions are likely to be highly relevant to understanding biological 3-D vision.

The best of both worlds: Producing national statistics using participatory methods

This paper presents our experience with combining statistical principles and participatory methods to generate national statistics. The methodology was developed in Malawi during 1999–2002. We demonstrate that if PRA is combined with statistical principles (including probability-based sampling and standardization), it can produce total population statistics and estimates of the proportion of households with certain characteristics (e.g., poverty). It can also provide quantitative data on complex issues of national importance such as poverty targeting. This approach is distinct from previous PRA-based approaches, which generate numbers at community level but only provide qualitative information at national level.

Use of auditory cues for wayfinding assistance in virtual environment: music aids route decision

This paper addresses the crucial problem of wayfinding assistance in the Virtual Environments (VEs). A number of navigation aids such as maps, agents, trails and acoustic landmarks are available to support the user for navigation in VEs, however it is evident that most of the aids are visually dominated. This work-in-progress describes a sound based approach that intends to assist the task of 'route decision' during navigation in a VE using music. Furthermore, with use of musical sounds it aims to reduce the cognitive load associated with other visually as well as physically dominated tasks. To achieve these goals, the approach exploits the benefits provided by music to ease and enhance the task of wayfinding, whilst making the user experience in the VE smooth and enjoyable.

A review of measurement-based assessments of the aerosol direct radiative effect and forcing

Aerosols affect the Earth's energy budget directly by scattering and absorbing radiation and indirectly by acting as cloud condensation nuclei and, thereby, affecting cloud properties. However, large uncertainties exist in current estimates of aerosol forcing because of incomplete knowledge concerning the distribution and the physical and chemical properties of aerosols as well as aerosol-cloud interactions. In recent years, a great deal of effort has gone into improving measurements and datasets. It is thus feasible to shift the estimates of aerosol forcing from largely model-based to increasingly measurement-based. Our goal is to assess current observational capabilities and identify uncertainties in the aerosol direct forcing through comparisons of different methods with independent sources of uncertainties. Here we assess the aerosol optical depth (τ), direct radiative effect (DRE) by natural and anthropogenic aerosols, and direct climate forcing (DCF) by anthropogenic aerosols, focusing on satellite and ground-based measurements supplemented by global chemical transport model (CTM) simulations. The multi-spectral MODIS measures global distributions of aerosol optical depth (τ) on a daily scale, with a high accuracy of ±0.03±0.05τ over ocean. The annual average τ is about 0.14 over global ocean, of which about 21%±7% is contributed by human activities, as estimated by MODIS fine-mode fraction. The multi-angle MISR derives an annual average AOD of 0.23 over global land with an uncertainty of ~20% or ±0.05. These high-accuracy aerosol products and broadband flux measurements from CERES make it feasible to obtain observational constraints for the aerosol direct effect, especially over global the ocean. A number of measurement-based approaches estimate the clear-sky DRE (on solar radiation) at the top-of-atmosphere (TOA) to be about -5.5±0.2 Wm-2 (median ± standard error from various methods) over the global ocean. Accounting for thin cirrus contamination of the satellite derived aerosol field will reduce the TOA DRE to -5.0 Wm-2. Because of a lack of measurements of aerosol absorption and difficulty in characterizing land surface reflection, estimates of DRE over land and at the ocean surface are currently realized through a combination of satellite retrievals, surface measurements, and model simulations, and are less constrained. Over the oceans the surface DRE is estimated to be -8.8±0.7 Wm-2. Over land, an integration of satellite retrievals and model simulations derives a DRE of -4.9±0.7 Wm-2 and -11.8±1.9 Wm-2 at the TOA and surface, respectively. CTM simulations derive a wide range of DRE estimates that on average are smaller than the measurement-based DRE by about 30-40%, even after accounting for thin cirrus and cloud contamination. A number of issues remain. Current estimates of the aerosol direct effect over land are poorly constrained. Uncertainties of DRE estimates are also larger on regional scales than on a global scale and large discrepancies exist between different approaches. The characterization of aerosol absorption and vertical distribution remains challenging. The aerosol direct effect in the thermal infrared range and in cloudy conditions remains relatively unexplored and quite uncertain, because of a lack of global systematic aerosol vertical profile measurements. A coordinated research strategy needs to be developed for integration and assimilation of satellite measurements into models to constrain model simulations. Enhanced measurement capabilities in the next few years and high-level scientific cooperation will further advance our knowledge.

Multi-attribute collaborative filtering recommendation based on improved group decision-making

Currently researchers in the field of personalized recommendations bear little consideration on users' interest differences in resource attributes although resource attribute is usually one of the most important factors in determining user preferences. To solve this problem, the paper builds an evaluation model of user interest based on resource multi-attributes, proposes a modified Pearson-Compatibility multi-attribute group decision-making algorithm, and introduces an algorithm to solve the recommendation problem of k-neighbor similar users. Considering the characteristics of collaborative filtering recommendation, the paper addresses the issues on the preference differences of similar users, incomplete values, and advanced converge of the algorithm. Thus the paper realizes multi-attribute collaborative filtering. Finally, the effectiveness of the algorithm is proved by an experiment of collaborative recommendation among multi-users based on virtual environment. The experimental results show that the algorithm has a high accuracy on predicting target users' attribute preferences and has a strong anti-interference ability on deviation and incomplete values.

Designing care bundle documentation to support the recognition and treatment of acute kidney injury: a route to quality improvement

The chapter describes development of care bundle documentation, through an iterative, user-centred design process, to support the recognition and treatment of acute kidney injury (AKI). The chapter details stages of user and stakeholder consultation, employed to develop a design response that was sensitive to user experience and need, culminating in simulation testing of a near final prototype. The development of supplementary awareness-raising materials, relating to the main care bundle tool is also discussed. This information design response to a complex clinical decision-making process is contrasted to other approaches to promoting AKI care. The need for different but related approaches to the working tool itself and the tool’s communication are discussed. More general recommendations are made for the development of communication tools to support complex clinical processes.

Farming systems methodology for efficient resource management at the farm level: a review from an Indian perspective

Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy Constituting 0.80 of the total farming community but possessing only 0.36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers Under a set of farm constraints and varying levels of resource availability and Opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by Way Of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make fanning profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable fanning.

Aligning sequences to structures

Most newly sequenced proteins are likely to adopt a similar structure to one which has already been experimentally determined. For this reason, the most successful approaches to protein structure prediction have been template-based methods. Such prediction methods attempt to identify and model the folds of unknown structures by aligning the target sequences to a set of representative template structures within a fold library. In this chapter, I discuss the development of template-based approaches to fold prediction, from the traditional techniques to the recent state-of-the-art methods. I also discuss the recent development of structural annotation databases, which contain models built by aligning the sequences from entire proteomes against known structures. Finally, I run through a practical step-by-step guide for aligning target sequences to known structures and contemplate the future direction of template-based structure prediction.

Novel high-resolution characterization of ancient DNA reveals C > U-type base modification events as the sole cause of post mortem miscoding lesions

Ancient DNA (aDNA) research has long depended on the power of PCR to amplify trace amounts of surviving genetic material from preserved specimens. While PCR permits specific loci to be targeted and amplified, in many ways it can be intrinsically unsuited to damaged and degraded aDNA templates. PCR amplification of aDNA can produce highly-skewed distributions with significant contributions from miscoding lesion damage and non-authentic sequence artefacts. As traditional PCR-based approaches have been unable to fully resolve the molecular nature of aDNA damage over many years, we have developed a novel single primer extension (SPEX)-based approach to generate more accurate sequence information. SPEX targets selected template strands at defined loci and can generate a quantifiable redundancy of coverage; providing new insights into the molecular nature of aDNA damage and fragmentation. SPEX sequence data reveals inherent limitations in both traditional and metagenomic PCR-based approaches to aDNA, which can make current damage analyses and correct genotyping of ancient specimens problematic. In contrast to previous aDNA studies, SPEX provides strong quantitative evidence that C U-type base modifications are the sole cause of authentic endogenous damage-derived miscoding lesions. This new approach could allow ancient specimens to be genotyped with unprecedented accuracy.

Application of computer-aided facilities management (CAFM) for intelligent buildings operation

Purpose – The purpose of this paper is to investigate the concepts of intelligent buildings (IBs), and the opportunities offered by the application of computer-aided facilities management (CAFM) systems. Design/methodology/approach – In this paper definitions of IBs are investigated, particularly definitions that are embracing open standards for effective operational change, using a questionnaire survey. The survey further investigated the extension of CAFM to IBs concepts and the opportunities that such integrated systems will provide to facilities management (FM) professionals. Findings – The results showed variation in the understanding of the concept of IBs and the application of CAFM. The survey showed that 46 per cent of respondents use a CAFM system with a majority agreeing on the potential of CAFM in delivery of effective facilities. Research limitations/implications – The questionnaire survey results are limited to the views of the respondents within the context of FM in the UK. Practical implications – Following on the many definitions of an IB does not necessarily lead to technologies of equipment that conform to an open standard. This open standard and documentation of systems produced by vendors is the key to integrating CAFM with other building management systems (BMS) and further harnessing the application of CAFM for IBs. Originality/value – The paper gives experience-based suggestions for both demand and supply sides of the service procurement to gain the feasible benefits and avoid the currently hindering obstacles, as the paper provides insight to the current and future tools for the mobile aspects of FM. The findings are relevant for service providers and operators as well.

Motion estimation through approximated densities

Many techniques are currently used for motion estimation. In the block-based approaches the most common procedure applied is the block-matching based on various algorithms. To refine the motion estimates resulting from the full search or any coarse search algorithm, one can find few applications of Kalman filtering, mainly in the intraframe scheme. The Kalman filtering technique applicability for block-based motion estimation is rather limited due to discontinuities in the dynamic behaviour of the motion vectors. Therefore, we propose an application of the concept of the filtering by approximated densities (FAD). The FAD, originally introduced to alleviate limitations due to conventional Kalman modelling, is applied to interframe block-motion estimation. This application uses a simple form of FAD involving statistical characteristics of multi-modal distributions up to second order.