Retrieving Regions of Interest for User Exploration

We consider an application scenario where points of interest (PoIs) each have a web presence and where a web user wants to iden- tify a region that contains relevant PoIs that are relevant to a set of keywords, e.g., in preparation for deciding where to go to conve- niently explore the PoIs. Motivated by this, we propose the length- constrained maximum-sum region (LCMSR) query that returns a spatial-network region that is located within a general region of in- terest, that does not exceed a given size constraint, and that best matches query keywords. Such a query maximizes the total weight of the PoIs in it w.r.t. the query keywords. We show that it is NP- hard to answer this query. We develop an approximation algorithm with a (5 + ǫ) approximation ratio utilizing a technique that scales node weights into integers. We also propose a more efficient heuris- tic algorithm and a greedy algorithm. Empirical studies on real data offer detailed insight into the accuracy of the proposed algorithms and show that the proposed algorithms are capable of computingresults efficiently and effectively.

Evidence-based policymaking and the public interest: lessons in legitimacy

This paper draws upon an analysis of regional spatial planning to highlight the centrality of ethics in praxis. In this context political liberalism is particularly helpful in developing a deeper understanding of the activities of those engaged in planning decision making. At the most basic level it demonstrates the importance of not only using shared liberal values as the foundation for public discourses but also achieving consensus through the development of an inclusive evidence base, derived from both lay and professional knowledge. Specifically, political liberalism provides a practical critique, enabling judgments to be made on problems which pervade operational planning practice and an evaluation to be conducted of the dynamic between and actions of participants.

Simple preparation of positively charged silver nanoparticles for detection of anions by surface-enhanced Raman spectroscopy

Modification of citrate and hydroxylamine reduced Ag colloids with thiocholine bromide, a thiol functionalized quaternary ammonium salt, creates particles where the zeta potential is switched from the normal values of ca. -50 mV to ca. + 50 mV. These colloids are stable but can be aggregated with metal salts in much the same way as the parent colloids. They are excellent SERS substrates for detection of anionic targets since their positive zeta potentials promote adsorption of negatively charged ions. This is important because the vast majority of published SERS studies involve cationic or neutral targets. Moreover, the fact that the modifier is a quaternary ammonium ion means that the negative surface charge is maintained even at alkaline pH. The modified colloids can be used to detect compounds which cannot be detected using conventional negatively-charged citrate or hydroxylamine reduced metal nanoparticles, for example the detection limit was 5.0 x 10(-5) M for perchlorate and

The heart of a dragon: 3D anatomical reconstruction of the 'scaly-foot gastropod' (Mollusca: Gastropoda: Neomphalina) reveals its extraordinary circulatory system

Introduction: The 'scaly-foot gastropod' (Chrysomallon squamiferum Chen et al., 2015) from deep-sea hydrothermal vent ecosystems of the Indian Ocean is an active mobile gastropod occurring in locally high densities, and it is distinctive for the dermal scales covering the exterior surface of its foot. These iron-sulfide coated sclerites, and its nutritional dependence on endosymbiotic bacteria, are both noted as adaptations to the extreme environment in the flow of hydrogen sulfide. We present evidence for other adaptations of the 'scaly-foot gastropod' to life in an extreme environment, investigated through dissection and 3D tomographic reconstruction of the internal anatomy.

Results: Our anatomical investigations of juvenile and adult specimens reveal a large unganglionated nervous system, a simple and reduced digestive system, and that the animal is a simultaneous hermaphrodite. We show that Chrysomallon squamiferum relies on endosymbiotic bacteria throughout post-larval life. Of particular interest is the circulatory system: Chrysomallon has a very large ctenidium supported by extensive blood sinuses filled with haemocoel. The ctenidium provides oxygen for the host but the circulatory system is enlarged beyond the scope of other similar vent gastropods. At the posterior of the ctenidium is a remarkably large and well-developed heart. Based on the volume of the auricle and ventricle, the heart complex represents approximately 4 % of the body volume. This proportionally giant heart primarily sucks blood through the ctenidium and supplies the highly vascularised oesophageal gland. Thus we infer the elaborate cardiovascular system most likely evolved to oxygenate the endosymbionts in an oxygen poor environment and/or to supply hydrogen sulfide to the endosymbionts.

Conclusions: This study exemplifies how understanding the autecology of an organism can be enhanced by detailed investigation of internal anatomy. This gastropod is a large and active species that is abundant in its hydrothermal vent field ecosystem. Yet all of its remarkable features-protective dermal sclerites, circulatory system, high fecundity-can be viewed as adaptations beneficial to its endosymbiont microbes. We interpret these results to show that, as a result of specialisation to resolve energetic needs in an extreme chemosynthetic environment, this dramatic dragon-like species has become a carrying vessel for its bacteria.

Assessment of the Activity of Photocatalytic Paint Using a Simple Smart Ink Designed for High Activity Surfaces

The use of an acid violet 7 (AV7) smart ink to assess the activity of photocatalytic paint is demonstrated. A linear correlation is established between the change in oxidized dye concentration, as measured by diffuse reflectance, and the change in the green component of the RGB color values, obtained using a portable hand-held scanner, suggesting that such tests can be monitored easily using an inexpensive piece of hand-held office equipment, as opposed to an expensive lab-based instrument, such as a diffuse reflectance UV/vis spectrophotometer. The bleaching of the AV7 follows first order kinetics, at a rate that is linearly dependent upon the UVA irradiance (0.30–3.26 mW cm–2). A comparison of relative rate of bleaching of the AV7 ink with the relative rate of removal of NOx, as determined using the ISO test (ISO 22197-1:2007), established a linear relationship between the two sets of results and the relevance of this correlation is discussed briefly.

Rapid, simple method for determining the porosity of mesoporous TiO2 films using a quartz crystal microbalance (QCM)

Two different mesoporous films of TiO2 were coated onto a QCM disc and fired at 450o C for 30 min. The first film was derived from a sol-gel paste that was popular in the early days of dye-sensitised solar cell, i.e. dssc, research, a TiO2(sg) film. The other was a commercial colloidal paste used to make examples of the current dssc cell; a TiO2(ds) film. A QCM was used to determine the mass of the TiO2 film deposited on each disc and the increase in the mass of the film when immersed in water/glycerol solutions with wt% values spanning the range 0-70%. The results of this work reveal that with both TiO2 mesoporous films the solution fills the film's pores and acts as a rigid mass, thereby allowing the porosity of each film to be calculated as: 59.1% and 71.6% for the TiO2(sg) and TiO2(ds) films, respectively. These results, coupled with surface area data, allowed the pore radii of the two films to be calculated as: 9.6 and 17.8 nm, respectively. This method is then simplified further, to just a few frequency measurements in water and only air to reveal the same porosity values. The value of the latter ‘one point’ method for making porosity measurements is discussed briefly.

Fast Byzantine Leader Election in Dynamic Networks

We study the fundamental Byzantine leader election problem in dynamic networks where the topology can change from round to round and nodes can also experience heavy {\em churn} (i.e., nodes can join and leave the network continuously over time). We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power and can deviate arbitrarily from the protocol. The churn is controlled by an adversary that has complete knowledge and control over which nodes join and leave and at what times and also may rewire the topology in every round and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is an $O(\log^3 n)$ round algorithm that achieves Byzantine leader election under the presence of up to $O({n}^{1/2 - \epsilon})$ Byzantine nodes (for a small constant $\epsilon > 0$) and a churn of up to \\$O(\sqrt{n}/\poly\log(n))$ nodes per round (where $n$ is the stable network size).The algorithm elects a leader with probability at least $1-n^{-\Omega(1)}$ and guarantees that it is an honest node with probability at least $1-n^{-\Omega(1)}$; assuming the algorithm succeeds, the leader's identity will be known to a $1-o(1)$ fraction of the honest nodes. Our algorithm is fully-distributed, lightweight, and is simple to implement. It is also scalable, as it runs in polylogarithmic (in $n$) time and requires nodes to send and receive messages of only polylogarithmic size per round.To the best of our knowledge, our algorithm is the first scalable solution for Byzantine leader election in a dynamic network with a high rate of churn; our protocol can also be used to solve Byzantine agreement in a straightforward way.We also show how to implement an (almost-everywhere) public coin with constant bias in a dynamic network with Byzantine nodes and provide a mechanism for enabling honest nodes to store information reliably in the network, which might be of independent interest.

A Simple Model to Quantify Radiolytic Production following Electron Emission from Heavy-Atom Nanoparticles Irradiated in Liquid Suspensions

We present a simple model for a component of the radiolytic production of any chemical species due to electron emission from irradiated nanoparticles (NPs) in a liquid environment, provided the expression for the G value for product formation is known and is reasonably well characterized by a linear dependence on beam energy. This model takes nanoparticle size, composition, density and a number of other readily available parameters (such as X-ray and electron attenuation data) as inputs and therefore allows for the ready determination of this contribution. Several approximations are used, thus this model provides an upper limit to the yield of chemical species due to electron emission, rather than a distinct value, and this upper limit is compared with experimental results. After the general model is developed we provide details of its application to the generation of HO(•) through irradiation of gold nanoparticles (AuNPs), a potentially important process in nanoparticle-based enhancement of radiotherapy. This model has been constructed with the intention of making it accessible to other researchers who wish to estimate chemical yields through this process, and is shown to be applicable to NPs of single elements and mixtures. The model can be applied without the need to develop additional skills (such as using a Monte Carlo toolkit), providing a fast and straightforward method of estimating chemical yields. A simple framework for determining the HO(•) yield for different NP sizes at constant NP concentration and initial photon energy is also presented.

Turing’s Menagerie: Talking Lions, Virtual Bats, Electric Sheep and Analogical Peacocks: Common Ground and Common Interest are Necessary Components of Engagement

This theoretical paper attempts to define some of the key components and challenges required to create embodied conversational agents that can be genuinely interesting conversational partners. Wittgenstein’s argument concerning talking lions emphasizes the importance of having a shared common ground as a basis for conversational interactions. Virtual bats suggests that–for some people at least–it is important that there be a feeling of authenticity concerning a subjectively experiencing entity that can convey what it is like to be that entity. Electric sheep reminds us of the importance of empathy in human conversational interaction and that we should provide a full communicative repertoire of both verbal and non-verbal components if we are to create genuinely engaging interactions. Also we may be making the task more difficult rather than easy if we leave out non-verbal aspects of communication. Finally, analogical peacocks highlights the importance of between minds alignment and establishes a longer term goal of being interesting, creative, and humorous if an embodied conversational is to be truly an engaging conversational partner. Some potential directions and solutions to addressing these issues are suggested.

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.