Solving the median shortest path problem in the planning and design of urban transportation networks using a vector labeling algorithm

This paper proposes an alternative algorithm to solve the median shortest path problem (MSPP) in the planning and design of urban transportation networks. The proposed vector labeling algorithm is based on the labeling of each node in terms of a multiple and conflicting vector of objectives which deletes cyclic, infeasible and extreme-dominated paths in the criteria space imposing cyclic break (CB), path cost constraint (PCC) and access cost parameter (ACP) respectively. The output of the algorithm is a set of Pareto optimal paths (POP) with an objective vector from predetermined origin to destination nodes. Thus, this paper formulates an algorithm to identify a non-inferior solution set of POP based on a non-dominated set of objective vectors that leaves the ultimate decision to decision-makers. A numerical experiment is conducted using an artificial transportation network in order to validate and compare results. Sensitivity analysis has shown that the proposed algorithm is more efficient and advantageous over existing solutions in terms of computing execution time and memory space used.

Sindbis virus vectors elicit hemagglutinin-specific humoral and cellular immune responses and offer a dose-sparing strategy for vaccination

We report here on the use of a Sindbis virus-based DNA-launch RNA replicon vector (pSIN-HA) that expresses influenza hemagglutinin (HA) as an immunogen. Immunization of mice with pSIN-HA generated anti-HA antibody and CTL responses and resulted in lower lung viral titers after influenza challenge when compared to controls. Importantly, immunization with a low dose of pSIN-HA mediated significantly reduced lung viral titers following challenge at 43 weeks after the final immunization. In contrast, immunization with a non-replicon DNA vector expressing HA failed to mediate reduced lung viral titer at the same dose. This demonstrated the dose-sparing capacity of the SIN vector system and its ability to stimulate long-term memory responses, properties that are highly desirable in any vaccine formulation.

A multi-vector, multi-envelope HIV-1 vaccine

The St. Jude Children's Research Hospital (St. Jude) HIV-1 vaccine program is based on the observation that multiple, antigenically distinct HIV-1 envelope protein structures are capable of mediating HIV-1 infection. A cocktail vaccine comprising representatives of these diverse structures (immunotypes) is therefore considered necessary to elicit lymphocyte populations that prevent HIV-1 infection. This strategy is reminiscent of that used to design a currently licensed and successful 23-valent pneumococcus vaccine. Three recombinant vector systems are used for the delivery of envelope cocktails (DNA, vaccinia virus, and purified protein) and each of these has been tested individually in phase I safety trials. A fourth clinical trial, in which diverse envelopes and vectors are combined in a prime-boost vaccination regimen, has been FDA-approved and is expected to commence in 2007. This trial will continue to test the hypothesis that a multivector, multi-envelope vaccine can elicit diverse 8- and T-cell populations that can prevent HIV-1 infections in humans.

Attack vector analysis and privacy-preserving social network data publishing

This paper addresses the problem of privacy-preserving data publishing for social network. Research on protecting the privacy of individuals and the confidentiality of data in social network has recently been receiving increasing attention. Privacy is an important issue when one wants to make use of data that involves individuals' sensitive information, especially in a time when data collection is becoming easier and sophisticated data mining techniques are becoming more efficient. In this paper, we discuss various privacy attack vectors on social networks. We present algorithms that sanitize data to make it safe for release while preserving useful information, and discuss ways of analyzing the sanitized data. This study provides a summary of the current state-of-the-art, based on which we expect to see advances in social networks data publishing for years to come.

Beyond the topological map : developing alternate mappings in self organisation

The self organising map is a well established unsupervised
learning technique which is able to form sophisticated representations of an input data set. However, conventional Self Organising Map (SOM) algorithms are limited to the production of topological maps — that is, maps where distance between points on the map have a direct relationship to the Euclidean distance between the training vectors corresponding to those points.

It would be desirable to be able to create maps which form clusters on primitive attributes other than Euclidean distance; for example, clusters based upon orientation or shape. Such maps could provide a novel approach to pattern recognition tasks by providing a new method to associate groups of data.

In this paper, it is shown that the type of map produced by SOM algorithms is a direct consequence of the lateral connection strategy employed. Given this knowledge, a technique is required to establish the feasability of using an alternative lateral connection strategy. Such a technique is presented. Using this technique, it is possible to rule out lateral connection strategies that will not produce output states useful to the organisation process. This technique is demonstrated using conventional Laplacian interconnection as well as a number of novel interconnection strategies.

Vector activity and propagule size affect dispersal potential by vertebrates

Many small organisms in various life stages can be transported in the digestive system of larger vertebrates, a process known as endozoochory. Potential dispersal distances of these “propagules” are generally calculated after monitoring retrieval in experiments with resting vector animals. We argue that vectors in natural situations will be actively moving during effective transport rather than resting. We here test for the first time how physical activity of a vector animal might affect its dispersal efficiency. We compared digestive characteristics between swimming, wading (i.e. resting in water) and isolation (i.e. resting in a cage) mallards (Anas platyrhynchos). We fed plastic markers and aquatic gastropods, and monitored retrieval and survival of these propagules in the droppings over 24 h. Over a period of 5 h of swimming, mallards excreted 1.5 times more markers than when wading and 2.3 times more markers than isolation birds, the pattern being reversed over the subsequent period of monitoring where all birds were resting. Retention times of markers were shortened for approximately 1 h for swimming, and 0.5 h for wading birds. Shorter retention times imply higher survival of propagules at increased vector activity. However, digestive intensity measured directly by retrieval of snail shells was not a straightforward function of level of activity. Increased marker size had a negative effect on discharge rate. Our experiment indicates that previous estimates of propagule dispersal distances based on resting animals are overestimated, while propagule survival seems underestimated. These findings have implications for the dispersal of invasive species, meta-population structures and long distance colonization events.

Role assessment of GIS analysis and its reliability while ranking urban sustainability using scenarios specific to regional climate, community and culture

Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period), current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation of urban sustainability using different indicator metrics, that implement vector GIS Analysis and Raster GIS analysis as basic tools to assist the evaluation and increase of its reliability besides assessing and decomposing it, after which a hypothetical implementation of the chosen evaluation model represented by various scenarios was implemented on the planned urban sustainability factors for a certain period of time to appraise the expected future grade of urban sustainability and come out with advises associated with scenarios for assuring gap filling and relative high urban future sustainability. The results this paper is reflecting are concentrating on the elements of vector and raster GIS analysis that assists the proper urban sustainability grading within the chosen model, the reliability of spatial data collected; analysis selected and resulted spatial information. Starting from selecting some important indicators to comprise the model which include regional culture, climate and community needs an example of what was used is Energy Demand & Consumption (Cooling systems). Thus, this factor is related to the climate and it‟s regional specific as the temperature varies around 30-45 degrees centigrade in city areas, GIS 3D Polygons of building data used to analyse the volume of buildings, attributes „building heights‟, estimate the number of floors from the equation, following energy demand was calculated and consumption for the unit volume, and compared it in scenario with possible sustainable energy supply or using different environmental friendly cooling systems this is followed by calculating the cooling system effects on an area unit selected to be 1 sq. km, combined with the level of greenery area, and open space, as represented by parks polygons, trees polygons, empty areas, pedestrian polygons and road surface area polygons. (initial measures showed that cooling system consumption can be reduced by around 15 -20 % with a well-planned building distributions, proper spaces and with using environmental friendly products and building material, temperature levels were also combined in the scenario extracted from satellite images as interpreted from thermal bands 3 times during the period of assessment. Other examples of the assessment of GIS analysis to urban sustainability took place included Waste Productivity, some effects of greenhouse gases measured by the intensity of road polygons and closeness to dwelling areas, industry areas as defined from land use land cover thematic maps produced from classified satellite images then vectors were created to take part in defining their role within the scenarios. City Noise and light intensity assessment was also investigated, as the region experiences rapid development and noise is magnified due to construction activities, closeness of the airports, and highways. The assessment investigated the measures taken by urban planners to reduce degradation or properly manage it. Finally as a conclusion tables were presented to reflect the scenario results in combination with GIS data types, analysis types, and the level of GIS data reliability to measure the sustainability level of a city related to cultural and regional demands.

Recombinant influenza viruses as a vaccine vector for HIV

 Live recombinant influenza viruses were successfully used as HIV vaccine vectors in a mouse model. Following intranasal prime-boost vaccination, HIV-specific CD8+ T cell responses were detected in the spleen, broncho-alveolar lavage, mediastinal and inguinal lymph nodes. HIV+α4β7+ CD8+ T cells contributed to protection in pseudo-challenge experiments using recombinant vaccinia virus expressing HIV antigens. This research highlights the importance of mucosal CD8+ T cells in viral immunity and emphasizes the need for additional studies to provide key insights to underpin future vaccine development.

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

High-dimensional problem domains pose significant challenges for anomaly detection. The presence of irrelevant features can conceal the presence of anomalies. This problem, known as the '. curse of dimensionality', is an obstacle for many anomaly detection techniques. Building a robust anomaly detection model for use in high-dimensional spaces requires the combination of an unsupervised feature extractor and an anomaly detector. While one-class support vector machines are effective at producing decision surfaces from well-behaved feature vectors, they can be inefficient at modelling the variation in large, high-dimensional datasets. Architectures such as deep belief networks (DBNs) are a promising technique for learning robust features. We present a hybrid model where an unsupervised DBN is trained to extract generic underlying features, and a one-class SVM is trained from the features learned by the DBN. Since a linear kernel can be substituted for nonlinear ones in our hybrid model without loss of accuracy, our model is scalable and computationally efficient. The experimental results show that our proposed model yields comparable anomaly detection performance with a deep autoencoder, while reducing its training and testing time by a factor of 3 and 1000, respectively.

Ecology of urban malaria vectors in Niamey, Republic of Niger

BACKGROUND: Urbanization in African cities has major impact on malaria risk. Niamey, the capital of the Republic of Niger, is situated in the West African Sahel zone. The short rainy season and human activities linked with the Niger River influence mosquito abundance. This study aimed at deciphering the factors of distribution of urban malaria vectors in Niamey.

METHODS: The distribution of mosquito aquatic stages was investigated monthly from December 2002 to November 2003, at up to 84 breeding sites, throughout Niamey. An exploratory analysis of association between mosquito abundance and environmental factors was performed by a Principal Component Analysis and confirmed by Kruskall-Wallis non-parametric test. To assess the relative importance of significant factors, models were built for Anopheles and Culicinae. In a second capture session, adult mosquitoes were collected weekly with pyrethrum sprays and CDC light-traps from June 2008 to June 2009 in two differentiated urban areas chosen after the study's first step. Members of the Anopheles gambiae complex were genotyped and Anopheles females were tested for the presence of Plasmodium falciparum circumsporozoite antigens using ELISA.

RESULTS: In 2003, 29 % of 8420 mosquitoes collected as aquatic stages were Anopheles. They were significantly more likely to be found upstream, relatively close to the river and highly productive in ponds. These factors remained significant in regression and generalized linear models. The Culicinae were found significantly more likely close to the river, and in the main temporary affluent stream. In 2009, Anopheles specimens, including Anopheles gambiae s.l. (95 %), but also Anopheles funestus (0.6 %) accounted for 18 % of the adult mosquito fauna, with a large difference between the two sampled zones. Three members of the An. gambiae complex were found: Anopheles arabiensis, Anopheles coluzzii, and An. gambiae. Nineteen (1.3 %) out of 1467 females tested for P. falciparum antigen were found positive.

CONCLUSION: The study provides valuable update knowledge on malaria vector ecology and distribution in Niamey. The identification of spatial and environmental risk factors could pave the way to larval source management strategy and allow malaria vector control to focus on key zones for the benefit of the community.