The marginal willingness-to-pay for attributes of a hypothetical HIV vaccine

This paper estimates the marginal willingness-to-pay for attributes of a hypothetical HIV vaccine using discrete choice modeling. We use primary data from 326 respondents from Bangkok and Chiang Mai, Thailand, in 2008–2009, selected using purposive, venue-based sampling across two strata. Participants completed a structured questionnaire and full rank discrete choice modeling task administered using computer-assisted personal interviewing. The choice experiment was used to rank eight hypothetical HIV vaccine scenarios, with each scenario comprising seven attributes (including cost) each of which had two levels. The data were analyzed in two alternative specifications: (1) best-worst; and (2) full-rank, using logit likelihood functions estimated with custom routines in Gauss matrix programming language. In the full-rank specification, all vaccine attributes are significant predictors of probability of vaccine choice. The biomedical attributes of the hypothetical HIV vaccine (efficacy, absence of VISP, absence of side effects, and duration of effect) are the most important attributes for HIV vaccine choice. On average respondents are more than twice as likely to accept a vaccine with 99% efficacy, than a vaccine with 50% efficacy. This translates to a willingness to pay US$383 more for a high efficacy vaccine compared with the low efficacy vaccine. Knowledge of the relative importance of determinants of HIV vaccine acceptability is important to ensure the success of future vaccination programs. Future acceptability studies of hypothetical HIV vaccines should use more finely grained biomedical attributes, and could also improve the external validity of results by including more levels of the cost attribute.

Food miles or carbon emissions? Exploring labeling preference for food transport footprint with a stated choice study

The ecological footprint of food transport can be communicated using carbon dioxide emissions (CO2 label) or by providing information about both the length of time and the mileage travelled (food miles label). We use stated choice data to estimate conventional unobserved taste heterogeneity models and extend them to a specification that also addresses attribute nonattendance. The implied posterior distributions of the marginal willingness to pay values are compared graphically and are used in validation regressions. We find strong bimodality of taste distribution as the emerging feature, with different groups of subjects having low and high valuations for these labels. The best fitting model shows that CO2 and food miles valuations are much correlated. CO2 valuations can be high even for those respondents expressing low valuations for food miles. However, the reverse is not true. Taken together, the results suggest that consumers tend to value the CO2 label at least as much and sometimes more than the food miles label.

Estimating Stellar Radial Velocity Variability from Kepler and GALEX: Implications for the radial velocity confirmation of exoplanets.

We cross match the GALEX and Kepler surveys to create a unique dataset with both ultraviolet (UV) measurements and highly precise photometric variability measurements in the visible light spectrum. As stellar activity is driven by magnetic field modulations, we have used UV emission from the magnetically heated gas in the stellar atmosphere to serve as our proxy for the more well-known stellar activity indicator, R' HK . The R' HK approximations were in turn used to estimate the level of astrophysical noise expected in radial velocity (RV) measurements and these were then searched for correlations with photometric variability. We find significant scatter in our attempts to estimate RV noise for magnetically active stars, which we attribute to variations in the phase and strength of the stellar magnetic cycle that drives the activity of these targets. However, for stars we deem to be magnetically quiet, we do find a clear correlation between photometric variability and estimated levels of RV noise (with variability up to ~10 m s–1). We conclude that for these quiet stars, we can use photometric measurements as a proxy to estimate the RV noise expected. As a result, the procedure outlined in this paper may help select targets best-suited for RV follow-up necessary for planet confirmation.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we present AGWAN (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the AGWAN model to real-world graphs and for generating random graphs from the model. Using the Enron “who communicates with whom” social graph, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to the structure of real-world graphs.

Fragmentos de Soto de Rojas: a ‘new’ mythological fable of the Spanish Baroque

The twentieth-century poet Gerardo Diego’s commitment to the recovery of a ‘sub-genre’, the mythological fable, evident in his Fábula de Equis y Zeda (1930) has been acknowledged by Peinado Elliot (2006), among others. However a recent discovery in his archive has revealed a hitherto unknown aspect of the poet’s scholarly commitment to this endeavour. A transcription of a previously unpublished, and until recently, unknown Baroque mythological fable with the title ‘Fábula de Alfeo y Aretusa’ was recently found by his daughter Elena, alongside an unpublished study by the young poet of said fable entitled ‘Un poema manuscrito del siglo XVII de la biblioteca Menéndez Pelayo’. Rosa Navarro Durán (2012) is convinced that the correspondences with Soto de Rojas’ 'Los fragmentos de Adonis' and the clear imprint of Góngora’s 'Soledades' and his 'Fábula de Píramo y Tisbe' permit us to attribute it, with some confidence, to Pedro Soto de Rojas. This essay will consider the significance of this exciting discovery for our reading of Soto de Rojas’ existing corpus, exploring in particular the poem’s links with the dark eroticism of the Fragmentos de Adonis, (1652) and the early Fábula de la Naya.(1623)

The value of water quality improvements in the region Berlin-Brandenburg as a function of distance and state residency

This study uses a discrete choice experiment (DCE) to elicit willingness to pay estimates for changes in the water quality of three rivers. As many regions the metropolitan region Berlin-Brandenburg struggles to achieve the objectives of the Water Framework Directive until 2015. A major problem is the high load of nutrients. As the region is part of two states (Länder) and the river sections are common throughout the whole region we account for the spatial context twofold. Firstly, we incorporate the distance between each respondent and all river stretches in all MNL and RPL models, and, secondly, we consider whether respondents reside in the state of Berlin or Brandenburg. The compensating variation (CV) calculated for various scenarios shows that overall people would significantly benefit from improved water quality. The CV measures, however, also reveal that not considering the spatial context would result in severely biased welfare measures. While the distance decay effect lowers CV, state residency is connected to the frequency of status quo choices and not accounting for residency would underestimate possible welfare gains in one state. Another finding is that the extent of the market varies with respect to attributes (river stretches) and attribute levels (water quality levels).

The influence of the magnetic field on running penumbral waves in the solar chromosphere

We use images of high spatial and temporal resolution, obtained using both ground- and space-based instrumentation, to investigate the role magnetic field inclination angles play in the propagation characteristics of running penumbral waves in the solar chromosphere. Analysis of a near-circular sunspot, close to the center of the solar disk, reveals a smooth rise in oscillatory period as a function of distance from the umbral barycenter. However, in one directional quadrant, corresponding to the north direction, a pronounced kink in the period-distance diagram is found. Utilizing a combination of the inversion of magnetic Stokes vectors and force-free field extrapolations, we attribute this behavior to the cut-off frequency imposed by the magnetic field geometry in this location. A rapid, localized inclination of the magnetic field lines in the north direction results in a faster increase in the dominant periodicity due to an accelerated reduction in the cut-off frequency. For the first time, we reveal how the spatial distribution of dominant wave periods, obtained with one of the highest resolution solar instruments currently available, directly reflects the magnetic geometry of the underlying sunspot, thus opening up a wealth of possibilities in future magnetohydrodynamic seismology studies. In addition, the intrinsic relationships we find between the underlying magnetic field geometries connecting the photosphere to the chromosphere, and the characteristics of running penumbral waves observed in the upper chromosphere, directly supports the interpretation that running penumbral wave phenomena are the chromospheric signature of upwardly propagating magneto-acoustic waves generated in the photosphere.

Effect of laser treatment on the attachment and viability of mesenchymal stem cell responses on shape memory NiTi alloy

The objectives of this study were to investigate the effect of laser-induced surface features on the morphology, attachment and viability of mesenchymal stem cells (MSCs) at different periods of time, and to evaluate the biocompatibility of different zones: laser-melted zone (MZ), heat-affected zone (HAZ) and base metal (BM) in laser-treated NiTi alloy. The surface morphology and composition were studied by scanning electron microscope (SEM) and X-ray photoemission spectroscopy (XPS), respectively. The cell morphology was examined by SEM while the cell counting and viability measurements were done by haemocytometer and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) colorimetric assay. The results indicated that the laser-induced surface features, such as surface roughening, presence of anisotropic dendritic pattern and complete surface Ni oxidation were beneficial to improve the biocompatibility of NiTi as evidenced by the highest cell attachment (4 days of culture) and viability (7 days of culture) found in the MZ. The biocompatibility of the MZ was the best, followed by the BM with the HAZ being the worst. The defective and porous oxide layer as well as the coarse grained structure might attribute to the inferior cell attachment (4 days of culture) and viability (7 days of culture) on the HAZ compared with the BM which has similar surface morphology.

Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels

Many graph datasets are labelled with discrete and numeric attributes. Most frequent substructure discovery algorithms ignore numeric attributes; in this paper we show how they can be used to improve search performance and discrimination. Our thesis is that the most descriptive substructures are those which are normative both in terms of their structure and in terms of their numeric values. We explore the relationship between graph structure and the distribution of attribute values and propose an outlier-detection step, which is used as a constraint during substructure discovery. By pruning anomalous vertices and edges, more weight is given to the most descriptive substructures. Our method is applicable to multi-dimensional numeric attributes; we outline how it can be extended for high-dimensional data. We support our findings with experiments on transaction graphs and single large graphs from the domains of physical building security and digital forensics, measuring the effect on runtime, memory requirements and coverage of discovered patterns, relative to the unconstrained approach.

גבול (Border)

This paper is a reexamination of the concept of the geopolitical border through a critical analysis of prevalent conceptualizations of borders, as they are articulated in the fields of geopolitics, political theory and international relations. Suggesting that thinking of borders as the derivative of territorial definitions disregards the dependency of territoriality and sovereign space on the praxes of border making, this paper offers an analytic distinction between normative articulations of borders and the border as a political practice. This distinction enables the identification of partial and incoherent border making processes. Consequently, the creation of borders can be analyzed as an effect of a multiplicity of performative praxes, material, juridical and otherwise discursive, that operate in relation to the management of space and attribute it with geopolitical distinctions. Furthermore, the paper suggests that these praxes, which appear in dispersed sites and in a wide variety of loci, are intrinsically linked to different spatial practices of population management, of governmentality. Thus, I offer a reading of borders as a praxis which manages binary differentiations of matrixes of governmentality, which create schisms in the population as a totality, through the deployment of the evocation of sovereignty as the legitimizing source of this differentiation or for the means necessary for its sustainment.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we presentAgwan (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the Agwanmodel to real-world graphs and for generating random graphs from the model. Using real-world directed and undirected graphs as input, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to graph structure.

Pattern Recognition Approach for Road Collision Hotspots Analysis: Case Study of Northern Ireland

In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.

Holding parties responsible at election time: Multi-level, multi-party government and electoral accountability

This paper highlights the crucial role played by party-specific responsibility attributions in performance-based voting. Three models of electoral accountability, which make distinct assumptions regarding citizens' ability to attribute responsibility to distinct governing parties, are tested in the challenging Northern Ireland context - an exemplar case of multi-level multi-party government in which expectations of performance based voting are low. The paper demonstrates the operation of party-attribution based electoral accountability, using data from the 2011 Northern Ireland Assembly Election Study. However, the findings are asymmetric: accountability operates in the Protestant/unionist bloc but not in the Catholic/nationalist bloc. This asymmetry may be explained by the absence of clear ethno-national ideological distinctions between the unionist parties (hence providing political space for performance based accountability to operate) but the continued relevance in the nationalist bloc of ethno-national difference (which limits the scope for performance politics). The implications of the findings for our understanding of the role of party-specific responsibility attribution in performance based models of voting, and for our evaluation of the quality of democracy in post-conflict consociational polities, are discussed. 

Vulnerability and robustness of SME supply chains: An empirical study of risk and disturbance management of fresh food processors in a developing market

The aim of this paper is to analyse vulnerability and robustness of small and medium size enterprises (SMEs) supply chains and to consider contextual factors that might influence the success of their disturbance management: Risky product and business environment. By using an exploratory case study it is shown how these contextual factors attribute vulnerability sources, contribute to the robustness of a company’s performance and supply chain vulnerability, as well as how a company seeks to manage internal and external vulnerability sources. The exploratory case is based on a fresh food supply chain of a manufacturing SME operating in a developing market.
Case findings suggest that fresh food supply chains of a manufacturing SME in developing markets are prone to disruptions of their logistics and production processes due to ‘riskiness’ of fresh food products, the ‘riskiness’ of developing markets, as well as ‘riskiness’ of SMEs themselves. However, this does not necessarily indicate the vulnerability of an SME and its entire supply chain. Findings indicate that SMEs can be very successful in disturbance management by selective use of redesign strategies that aim to prevent or reduce the impact of disturbances. More precise, it is likely that an SME can achieve robust performance by employing preventive redesign strategies in managing disturbances that result from internal, company related vulnerability sources, while impact reduction strategies are likely to contribute to robust performance of an SME if used to manage disturbances that result from internal, supply chain related vulnerability sources, as well as external vulnerability sources.

Vertex Clustering of Augmented Graph Streams

In this paper we propose a graph stream clustering algorithm with a unied similarity measure on both structural and attribute properties of vertices, with each attribute being treated as a vertex. Unlike others, our approach does not require an input parameter for the number of clusters, instead, it dynamically creates new sketch-based clusters and periodically merges existing similar clusters. Experiments on two publicly available datasets reveal the advantages of our approach in detecting vertex clusters in the graph stream. We provide a detailed investigation into how parameters affect the algorithm performance. We also provide a quantitative evaluation and comparison with a well-known offline community detection algorithm which shows that our streaming algorithm can achieve comparable or better average cluster purity.