What do faculty and students really think about e-books?

Purpose - The purpose of this article is to report on a large-scale survey that was carried Out to assess academic users' awareness, perceptions and existing levels of use of e-books. The survey also seeks to find out about the purposes to which electronic books were put, and to obtain an understanding of the most effective library marketing and communication channels.Design/methodology/approach - An e-mail invitation to participate in the survey was distributed to all UCL staff and students (approximately 27,000) in November 2006, and 1,818 completions were received, an effective response rate of at least 6.7 per cent. Statistical analyses were carried out on the data using Software Package for Social Sciences (SPSS).Findings - The survey findings point to various ways in which user uptake and acceptance of e-books may be encouraged. Book discovery behaviour, a key issue for publishers and librarians in both print and electronic environments, emerges as a critical focus for service delivery and enhancement.Originality/value - The survey is part of an action research project, CIBER's SuperBook, that will further investigate the issues raised in this initial benchmarking survey using deep log analysis and qualitative methods. The paper partly fills the gap in the literature on e-books which has mainly focused on usage and not the users

Robot-object contact perception using symbolic temporal pattern learning

This paper investigates application of machine learning to the problem of contact perception between a robots gripper and an object. The input data comprises a multidimensional time-series produced by a force/torque sensor at the robots wrist, the robots proprioceptive information, namely, the position of the end-effector, as well as the robots control command. These data are used to train a hidden Markov model (HMM) classifier. The output of the classifier is a prediction of the contact state, which includes no contact, a contact aligned with the central axis of the valve, and an edge contact. To distinguish between contact states, the robot performs exploratory behaviors that produce distinct patterns in the time-series data. The patterns are discovered by first analyzing the data using a probabilistic clustering algorithm that transforms the multidimensional data into a one-dimensional sequence of symbols. The symbols produced by the clustering algorithm are used to train the HMM classifier. We examined two exploratory behaviors: a rotation around the x-axis, and a rotation around the y-axis of the gripper. We show that using these two exploratory behaviors we can successfully predict a contact state with an accuracy of 88 ± 5 % and 81 ± 10 %, respectively

Application of the multigraph software architecture to intelligent patient monitoring

This project is concerned with the development of intelligent agents for use in the Intensive Care Unit (ICU), based on the Multigraph Architecture (MA). The objectives of the work are twofold: i. ) To consider the design issues of intelligent systems, using a model-based approach of adding intelligence to existing instrumentation and information systems, irrespective of their implementation. ii. ) More specifically, to investigate the role of MA in the implementation of such systems. The first objective will be achieved by writing a specification for an Integrated Model-based Development Environment (IMDE), identifying its functionality, user requirements, etc. The second objective is to implement a prototype of one such development environment. This will borrow concepts from a framework for intelligent process control for chemical plants, previously implemented in the MA. Finally an ICU application will be developed, using this IMDE, to monitor the respiratory system. The benefits associated with using such a model-based framework include modular design, reusability of software components, automatic synthesis of run-time system from the models and simpler consistency and validation procedures. Another benefit that is of particular interest in patient monitoring systems is the integration of different software components. Because the MA is generic, it can be extended to support any modelling paradigm. This means that the development framework can handle all aspects in design of the system, e.g. instrument interface, user interface, signal processing and knowledge-based signal interpretation. To demonstrate this, the IMDE has been extended to include the Causal Probabilistic Network (CPN) modelling paradigm as an integral component. This facilitates the modelling of uncertaiilty. Using the techniques described in summary above, the benefits gained from applying the multigraph architecture to intelligent patient monitoring can be ascertained. This forms the bulk of the work to be described in this thesis

Sensitivity Analysis for Optimal Parameters for Marine Radar Data Processing

A bird and bat monitoring system has been developed that uses marine radar, IR camera and acoustic recorders for wind farm applications. IR video recording is used to monitor birds and bats activity which will be useful for wildlife biologists in developing mit igation techniques to minimize impact of wind turbines on birds and bats. The goal is to quantify birds and bats activity near wind turbines. Radar will provide z-coordinate (alt itude) and IR camera will provide (x, y) coordinates of birds/bats. Acous tic monitoring is used to identify birds and bats at their species level. This paper deals with the use of marine radar for determining altitudes, direction and quantity (passage rates) of birds/bats. Data from the marine radar is digitized and processed with open source radR software. Since the data is unknown tracking and quantification can be very challenging. This paper deals with the sensitivity analysis and effects of various parameters used in the tracking algorithm so resulting data can be meaningful

Short photoperiod-induced decrease of histamine H3 receptors facilitates activation of hypothalamic neurons in the Siberian Hamster

Nonhibernating seasonal mammals have adapted to temporal changes in food availability through behavioral and physiological mechanisms to store food and energy during times of predictable plenty and conserve energy during predicted shortage. Little is known, however, of the hypothalamic neuronal events that lead to a change in behavior or physiology. Here we show for the first time that a shift from long summer-like to short inter-like photoperiod, which induces physiological adaptation to winter in the Siberian hamster, including a body weight decrease of up to 30%, increases neuronal activity in the dorsomedial region of the arcuate nucleus (dmpARC) assessed by electro physiological patch-clamping recording. Increased neuronal activity in short days is dependent on a photoperiod-driven down-regulation of H3 receptor expression and can be mimicked in long-day dmpARC neurons by the application of the H3 receptor antagonist, clobenproprit. Short-day activation of dmpARC neurons results in increased c-Fos expression. Tract tracing with the trans-synaptic retrograde tracer, pseudorabies virus, delivered into adipose tissue reveals a multisynaptic neuronal sympathetic outflow from dmpARC to white adipose tissue. These data strongly suggest that increased activity of dmpARC neurons, as a consequence of down-regulation of the histamine H3 receptor, contributes to the physiological adaptation of body weight regulation in seasonal photoperiod

Land use change and the impact on greenhouse gas exchange in north Australian savanna soils

Savanna ecosystems are subjected to accelerating land use change as human demand for food and forest products increases. Land use change has been shown to both increase and decrease greenhouse gas fluxes from savannas and considerable uncertainty exists about the non-CO₂ fluxes from the soil. We measured methane (CH₄), nitrous oxide (N₂O) and carbon dioxide (CO₂) over a complete wet-dry seasonal cycle at three replicate sites of each of three land uses: savanna, young pasture and old pasture (converted from savanna 5–7 and 25–30 yr ago, respectively) in the Douglas Daly region of Northern Australia. The effect of break of season rains at the end of the dry season was investigated with two irrigation experiments. Land use change from savanna to pasture increased net greenhouse gas fluxes from the soil. Pasture sites were a weaker sink for CH₄ than savanna sites and, under wet conditions, old pastures turned from being sinks to a significant source of CH₄. Nitrous oxide emissions were generally very low, in the range of 0 to 5 μg N₂O-N m⁻² h⁻¹, and under dry conditions soil uptake of N₂O was apparent. Break of season rains produced a small, short lived pulse of N₂O up to 20 μg N₂O-N m⁻² h⁻¹, most evident in pasture soil. Annual cumulative soil CO₂ fluxes increased after clearing, with savanna (14.6 t CO₂-C ha⁻¹ yr⁻¹) having the lowest fluxes compared to old pasture (18.5 t CO₂-C ha⁻¹ yr⁻¹) and young pasture (20.0 t CO₂-C ha⁻¹ yr⁻¹). Clearing savanna increased soil-based greenhouse gas emissions from 53 to ∼ 70 t CO₂-equivalents, a 30% increase dominated by an increase in soil CO₂ emissions and shift from soil CH₄ sink to source. Seasonal variation was clearly driven by soil water content, supporting the emerging view that soil water content is a more important driver of soil gas fluxes than soil temperature in tropical ecosystems where temperature varies little among seasons

Evaluating aflatoxin gene expression in Aspergillus section Flavi

The determination of aflatoxin production ability and differentiation of aflatoxigenic strains can be assessed by monitoring the expression of one or several key genes using reverse transcription polymerase chain reaction (RT-PCR). We herein describe the methods for RNA induction, extraction, and quality determination, and the RT-PCR conditions used to evaluate the ability of a given Aspergillus strain to produce aflatoxins.info:eu-repo/semantics/publishedVersio