Farm income, population and farmland prices: a relative information approach

This paper uses an entropy-based information approach to determine if farmland values are more closely associated with urban pressure or farm income. The basic question is: how much information on changes in farm real estate values is contained in changes in population versus changes in returns to production agriculture? Results suggest population is informative, but changes in farmland values are more strongly associated with changes in the distribution of returns. However, this relationship is not true for every region nor does it hold over time, as for some regions and time periods changes in population are more informative. Results have policy implications for both equity and efficiency.

WREN: electronic management system for facilities management

This paper describes a case study of an electronic data management system developed in-house by the Facilities Management Directorate (FMD) of an educational institution in the UK. The FMD Maintenance and Business Services department is responsible for the maintenance of the built-estate owned by the university. The department needs to have a clear definition of the type of work undertaken and the administration that enables any maintenance work to be carried out. These include the management of resources, budget, cash flow and workflow of reactive, preventative and planned maintenance of the campus. In order to be more efficient in supporting the business process, the FMD had decided to move from a paper-based information system to an electronic system, WREN, to support the business process of the FMD. Some of the main advantages of WREN are that it is tailor-made to fit the purpose of the users; it is cost effective when it comes to modifications on the system; and the database can also be used as a knowledge management tool. There is a trade-off; as WREN is tailored to the specific requirements of the FMD, it may not be easy to implement within a different institution without extensive modifications. However, WREN is successful in not only allowing the FMD to carry out the tasks of maintaining and looking after the built-estate of the university, but also has achieved its aim to minimise costs and maximise efficiency.

Establishment of a Cross-European Field Site Network in the ALARM Project for Assessing Large-Scale Changes in Biodiversity

The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals

A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

The effect of the functional attributes of objects within the caged environment on interaction time in laboratory rats

Determining rat preferences for, and behaviour towards, environmental enrichment objects allows us to provide evidence-based information about how the caged environment may be enriched. In recent years there have been many studies investigating the preferences of laboratory rodents for a wide variety of environmental enrichment objects and materials. While these have provided important information regarding the animals' perception of the items, very few studies have attempted to systematically investigate the precise attributes that constitute a preferred object and the behaviour that these objects afford. We have designed a research program to systematically study rats' motivation to interact with enrichment objects. Here we present the results from two experiments which examined the time rats spent with objects that only differed in size. This showed that rats spent longer with large objects rather than small ones, even though objects were presented individually. We also investigated the rats' behaviour with the objects in an open field and found that rats spent longer climbing on top of the large object. This behaviour continued when the large objects were laid on their sides instead of placed upright in the arena, suggesting that the rats were not simply climbing on the objects to investigate the top of the arena and thus an escape route, but instead were genuinely motivated to climb. This suggests that rat welfare could be enhanced by the addition to their cages of objects that permit climbing. (C) 2009 Elsevier B.V. All rights reserved.

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality

A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Prefrontal control of familiarity and recollection in working memory

Left inferior frontal gyrus (IFG) is a critical neural substrate for the resolution of proactive interference (PI) in working memory. We hypothesized that left IFG achieves this by controlling the influence of familiarity- versus recollection-based information about memory probes. Consistent with this idea, we observed evidence for an early (200 msec)-peaking signal corresponding to memory probe familiarity and a late (500 msec)-resolving signal corresponding to full accrual of trial-related contextual ("recollection-based") information. Next, we applied brief trains of repetitive transcranial magnetic stimulation (rTMS) time locked to these mnemonic signals, to left IFG and to a control region. Only early rTMS of left IFG produced a modulation of the false alarm rate for high-PI probes. Additionally, the magnitude of this effect was predicted by individual differences in susceptibility to PI. These results suggest that left IFG-based control may bias the influence of familiarity- and recollection-based signals on recognition decisions.

Towards the design of a unified semantics model for OLTP and OLAP systems

The concepts of on-line transactional processing (OLTP) and on-line analytical processing (OLAP) are often confused with the technologies or models that are used to design transactional and analytics based information systems. This in some way has contributed to existence of gaps between the semantics in information captured during transactional processing and information stored for analytical use. In this paper, we propose the use of a unified semantics design model, as a solution to help bridge the semantic gaps between data captured by OLTP systems and the information provided by OLAP systems. The central focus of this design approach is on enabling business intelligence using not just data, but data with context.

Effects of soil conditions and drought on egg hatching and larval survival of the clover root weevil (Sitona lepidus)

Soil-dwelling insect herbivores are significant pests in many managed ecosystems. Because eggs and larvae are difficult to observe, mathematical models have been developed to predict life-cycle events occurring in the soil. To date, these models have incorporated very little empirical information about how soil and drought conditions interact to shape these processes. This study investigated how soil temperature (10, 15, 20 and 25 °C), water content (0.02 (air dried), 0.10 and 0.25 g g−1) and pH (5, 7 and 9) interactively affected egg hatching and early larval lifespan of the clover root weevil (Sitona lepidus Gyllenhal, Coleoptera: Curculionidae). Eggs developed over 3.5 times faster at 25 °C compared with 10 °C (hatching after 40.1 and 11.5 days, respectively). The effect of drought on S. lepidus eggs was investigated by exposing eggs to drought conditions before wetting the soil (2–12 days later) at four temperatures. No eggs hatched in dry soil, suggesting that S. lepidus eggs require water to remain viable. Eggs hatched significantly sooner in slightly acidic soil (pH 5) compared with soils with higher pH values. There was also a significant interaction between soil temperature, pH and soil water content. Egg viability was significantly reduced by exposure to drought. When exposed to 2–6 days of drought, egg viability was 80–100% at all temperatures but fell to 50% after 12 days exposure at 10 °C and did not hatch at all at 20 °C and above. Drought exposure also increased hatching time of viable eggs. The effects of soil conditions on unfed larvae were less influential, except for soil temperature which significantly reduced larval longevity by 57% when reared at 25 °C compared with 10 °C (4.1 and 9.7 days, respectively). The effects of soil conditions on S. lepidus eggs and larvae are discussed in the context of global climate change and how such empirically based information could be useful for refining existing mathematical models of these processes.

Dynamic auroral structure in the vicinity of the polar cusp - multipoint observations during southward and northward IMF

The low- and high-latitude boundary layers of the earth's magnetosphere [low-latitude boundary layer (LLBL) and mantle] play important roles in transferring momentum and energy from the solar wind to the magnetosphere-ionosphere system. Particle precipitation, field-aligned current, auroral emission, ionospheric ion drift and ground magnetic perturbations are among the low-altitude parameters that show signatures of various plasma processes in the LLBL and the magnetopause current layer. Magnetic merging events, Kelvin-Helmholtz waves, and pressure pulses excited by the variable solar wind/magnetosheath plasma are examples of boundary phenomena that may be coupled to the ionosphere via field-aligned currents. Optical auroral observation, by photometry and all-sky TV cameras, is a unique technique for investigating the spatial and temporal structure of the electron precipitation associated with such phenomena. However, the distinction between the different boundary layer plasma populations cannot in general be unambiguously determined by optics alone. Additional information, such as satellite observations of particle boundaries and field-aligned currents, is needed in order to identify the plasma source(s) and the magnetosphere-ionosphere coupling mode(s). Two categories of auroral activity/structure in the vicinity of the polar cusp are discussed in this paper, based on combined ground and satellite data. In one case, the quasi-periodic sequence of auroral events at the polar cap boundary involves accelerated electrons (< 1 keV) moving poleward (< 1 km s-1) and azimuthally along the persistent cusp/cleft arc poleward boundary with velocities (< 4 km s-1), comparable to the local ionospheric ion drift during periods of southward IMF. A critical question is whether or not the optical events signify a corresponding plasma flow across the open/closed field line boundary in such cases. Near-simultaneous observations of magnetopause flux transfer events (FTEs) and such optical/ion drift events are reported. The reverse pattern of motion of discrete auroral forms is observed during positive interplanetary magnetic field (IMF) B(Z), i.e. equatorward motion into the cusp/cleft background arc from the poleward edge. Combined satellite and ground-based information for the latter cases indicate a source mechanism, poleward of the cusp at the high-latitude magnetopause or plasma mantle, giving rise to strong momentum transfer and electron precipitation structures within a approximately 200 km-wide latitudinal zone at the cusp/cleft poleward boundary. The striking similarities of auroral electrodynamics in the cleft/mantle region during northward and southward IMF indicate that a qualitatively similar solar wind-magnetosphere coupling mode is operating. It is suggested that, in both cases, the discrete auroral forms represent temporal/spatial structure of larger-scale convection over the polar magnetosphere.

Requirements for building information modeling based lean production management systems for construction

Smooth flow of production in construction is hampered by disparity between individual trade teams' goals and the goals of stable production flow for the project as a whole. This is exacerbated by the difficulty of visualizing the flow of work in a construction project. While the addresses some of the issues in Building information modeling provides a powerful platform for visualizing work flow in control systems that also enable pull flow and deeper collaboration between teams on and off site. The requirements for implementation of a BIM-enabled pull flow construction management software system based on the Last Planner System™, called ‘KanBIM’, have been specified, and a set of functional mock-ups of the proposed system has been implemented and evaluated in a series of three focus group workshops. The requirements cover the areas of maintenance of work flow stability, enabling negotiation and commitment between teams, lean production planning with sophisticated pull flow control, and effective communication and visualization of flow. The evaluation results show that the system holds the potential to improve work flow and reduce waste by providing both process and product visualization at the work face.

Communicating neurons: a connectionist spiking neuron implementation of stochastic diffusion search

An information processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus, the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the swarm intelligence paradigm, stochastic diffusion search, it will find the best-fit to the memory with linear time complexity. information multiplexing enables neurons to process knowledge as 'tokens' rather than 'types'. The network illustrates possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. (C) 2007 Elsevier B.V. All rights reserved.