The structure and dynamics of saxicolous lichen communities

The saxicolous lichen vegetation on Ordovician slate rock at the mouth of the River Dovey, South Merionethshire, Wales was described in relation to several environmental variables which include aspect, slope angle, light intensity, rock porosity, rock microtopography and rock stability. Each of the measured environmental variables was shown to influence the lichen vegetation. A number of groups of species which were characteristic of certain environments were described. The data from the saxicolous lichen communities were analysed using multivariate analysis. Qualitative and quantitative data were ordinated, the qualitative data being easier to interpret ecologically, and site number (which reflects distance from the sea and altitude), rock porosity and light intensity were shown to be important environmental variables. A classification of the data was also carried out. The results of the ordination and classification were combined together and a model constructed which describes saxicolous lichen vegetation. A method which uses the model as an aid to the design and interpretation of field experiments is described. The model is applied to an experiment which investigates the effect on growth of transplanting four saxicolous lichens to different aspects. Growth was inhibited in Physcia orbicularis and Parmelia conspersa on rock surfaces of northwest aspect compared with growth on rock surfaces of southeast aspect. Growth was inhibited in Parmelia glabratula ssp. fuliginosa on rock surfaces of southeast aspect compared with rock surfaces of northwesr aspect. The growth of Parmelia saxatilis was similar at both southeast and northwesr aspects. Growth inhibition or stimulation in thalli of Physcia orbicularis, Parmelia conspersa and Parmelia glabratula ssp. fuliginosa after transplantation was consistent with the predictions of the model while the results for Parmelia saxatilis were not as expected. There was evidence that the frequency of Parmelia conspersa and Parmelia glabratula at a site is related to an effect of the environment on the growth of the thalli. There was also evidence that the frequency of Physcia orbicularis at a site is related to an effect of the environment on the establishment phase of the thalli and for the competitive exclusion of Parmelia saxatilis thalli from southeast facing rock surfaces. The distribution of lichens in relation to height on nine rock surfaces was investigated. It was suggested that the distribution of the lichens was influenced by microclimatic factors which are related to height on the rock, environmental variables which are associated with the rock substratum (e.g. rock porosity and rock microtopography) and by historical factors. The pattern of one crustose and one foliose lichen on four rock surfaces of different aspect and slope was investigated. On the vertically inclined surface the density of small thalli of Buellia aethalea and Parmelia glabratula ssp fuliginosa was correlated with the microtopography of the surface in transects horizontally across the rock surface but not in transects vertically down the rock surface. there were consitent differences in the scale and intensity of pattern horizontally and vertically and also a decrease in the intensity of pattern vertically as the slope of the rock surface decreased. These results were consistent with the suggestion of a gradient of microclimatic factors up the rock. The differences in the scale and intensity of pattern in different size classes in the population were consistent with the changes in pattern with time which have been shown to occur during succession in sand dune and salt marsh vegetation. The relationship between thallus size and height on a rock surface and between the radial growth rate and location of a thallus on a rock surface were investigated. Thalli of Parmelia glabratula ssp. fuliginosa were larger at the top of the rock surface than at the bottom and the data were consistent with the suggestion that the colonisation of the rock surface began at the top and, in time, spread downwards. The radial growth rate of the thalli could not be related to variation in slope, porosity, microtopography or directly to height on the rock but could be related to the horizontal location of the thalli on the rock. These results were consistent with the suggestion that here is a gradient of microclimatic factors across the rock surface which is also modified by height on the rock surface. The succession of lichen communities was described by relating the vegetation to rock porosity, rock microtopography, species diversity and rock stability. An initial stage dominated by crustose lichens leads to communities dominated by crustose, foliose and fruticose species. In the late stages of the succession on some rock surfaces crustose species again become dominant. The occurrence of the climax state and cyclic vegetation change in lichen communities are discussed. A mthod of estimating the age structure of a lichen population by relating thallus size to growth rate is described. The sources of error in the method are discussed in some detail and several refinements suggested to increase the accuracy of the method. The population dynamics of Parmelia glabratula ssp. fuliginosa was investigated by applying life tables to the age structures of eight different populations. The data were consistent with a period of relatively constant recruitment of thalli into the populations. Mortality in lichen populations was divided into deaths which occur after fragmentation of the thallus and deaths which occur after catastrophic environmental events. THe data suggest that the rate of fragmenting death is dependent on the age of the thallus while the rate of catastrophic death is dependent on the number of thalli established in an age class. A comparison of the numbers of thalli in each age class in the eight populations suggested that population density is controlled firstly, by climate and secondly, by variables related to the local rock surface environment. The rate of fragmenting death is related to the diversity of the community and the influence of diversity together with environmental variables in fluctuating or cyclic changes in population number.

Privacy and the City:user identification and location semantics in location-based social networks

With the advent of GPS enabled smartphones, an increasing number of users is actively sharing their location through a variety of applications and services. Along with the continuing growth of Location-Based Social Networks (LBSNs), security experts have increasingly warned the public of the dangers of exposing sensitive information such as personal location data. Most importantly, in addition to the geographical coordinates of the user’s location, LBSNs allow easy access to an additional set of characteristics of that location, such as the venue type or popularity. In this paper, we investigate the role of location semantics in the identification of LBSN users. We simulate a scenario in which the attacker’s goal is to reveal the identity of a set of LBSN users by observing their check-in activity. We then propose to answer the following question: what are the types of venues that a malicious user has to monitor to maximize the probability of success? Conversely, when should a user decide whether to make his/her check-in to a location public or not? We perform our study on more than 1 million check-ins distributed over 17 urban regions of the United States. Our analysis shows that different types of venues display different discriminative power in terms of user identity, with most of the venues in the “Residence” category providing the highest re-identification success across the urban regions. Interestingly, we also find that users with a high entropy of their check-ins distribution are not necessarily the hardest to identify, suggesting that it is the collective behaviour of the users’ population that determines the complexity of the identification task, rather than the individual behaviour.

It's the way you check-in:identifying users in location-based social networks

In recent years, the rapid spread of smartphones has led to the increasing popularity of Location-Based Social Networks (LBSNs). Although a number of research studies and articles in the press have shown the dangers of exposing personal location data, the inherent nature of LBSNs encourages users to publish information about their current location (i.e., their check-ins). The same is true for the majority of the most popular social networking websites, which offer the possibility of associating the current location of users to their posts and photos. Moreover, some LBSNs, such as Foursquare, let users tag their friends in their check-ins, thus potentially releasing location information of individuals that have no control over the published data. This raises additional privacy concerns for the management of location information in LBSNs. In this paper we propose and evaluate a series of techniques for the identification of users from their check-in data. More specifically, we first present two strategies according to which users are characterized by the spatio-temporal trajectory emerging from their check-ins over time and the frequency of visit to specific locations, respectively. In addition to these approaches, we also propose a hybrid strategy that is able to exploit both types of information. It is worth noting that these techniques can be applied to a more general class of problems where locations and social links of individuals are available in a given dataset. We evaluate our techniques by means of three real-world LBSNs datasets, demonstrating that a very limited amount of data points is sufficient to identify a user with a high degree of accuracy. For instance, we show that in some datasets we are able to classify more than 80% of the users correctly.

Enabling long journeys in electric vehicles:design and demonstration of an infrastructure location model

This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.

Sensor Location Problem for a Multigraph

MSC 2010: 05C50, 15A03, 15A06, 65K05, 90C08, 90C35

GIS and optimisation:potential benefits for emergency facility location in humanitarian logistics

Floods are one of the most dangerous and common disasters worldwide, and these disasters are closely linked to the geography of the affected area. As a result, several papers in the academic field of humanitarian logistics have incorporated the use of Geographical Information Systems (GIS) for disaster management. However, most of the contributions in the literature are using these systems for network analysis and display, with just a few papers exploiting the capabilities of GIS to improve planning and preparedness. To show the capabilities of GIS for disaster management, this paper uses raster GIS to analyse potential flooding scenarios and provide input to an optimisation model. The combination is applied to two real-world floods in Mexico to evaluate the value of incorporating GIS for disaster planning. The results provide evidence that including GIS analysis for a decision-making tool in disaster management can improve the outcome of disaster operations by reducing the number of facilities used at risk of flooding. Empirical results imply the importance of the integration of advanced remote sensing images and GIS for future systems in humanitarian logistics.

A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.

On the accuracy of nonsurvey regional input-output multipliers: An empirical study

Correct specification of the simple location quotients in regionalizing the national direct requirements table is essential to the accuracy of regional input-output multipliers. The purpose of this research is to examine the relative accuracy of these multipliers when earnings, employment, number of establishments, and payroll data specify the simple location quotients.^ For each specification type, I derive a column of total output multipliers and a column of total income multipliers. These multipliers are based on the 1987 benchmark input-output accounts of the U.S. economy and 1988-1992 state of Florida data.^ Error sign tests, and Standardized Mean Absolute Deviation (SMAD) statistics indicate that the output multiplier estimates overestimate the output multipliers published by the Department of Commerce-Bureau of Economic Analysis (BEA) for the state of Florida. In contrast, the income multiplier estimates underestimate the BEA's income multipliers. For a given multiplier type, the Spearman-rank correlation analysis shows that the multiplier estimates and the BEA multipliers have statistically different rank ordering of row elements. The above tests also find no significant different differences, both in size and ranking distributions, among the vectors of multiplier estimates. ^

An investigation of location effect on trip production using artificial neural networks

As traffic congestion exuberates and new roadway construction is severely constrained because of limited availability of land, high cost of land acquisition, and communities' opposition to the building of major roads, new solutions have to be sought to either make roadway use more efficient or reduce travel demand. There is a general agreement that travel demand is affected by land use patterns. However, traditional aggregate four-step models, which are the prevailing modeling approach presently, assume that traffic condition will not affect people's decision on whether to make a trip or not when trip generation is estimated. Existing survey data indicate, however, that differences exist in trip rates for different geographic areas. The reasons for such differences have not been carefully studied, and the success of quantifying the influence of land use on travel demand beyond employment, households, and their characteristics has been limited to be useful to the traditional four-step models. There may be a number of reasons, such as that the representation of influence of land use on travel demand is aggregated and is not explicit and that land use variables such as density and mix and accessibility as measured by travel time and congestion have not been adequately considered. This research employs the artificial neural network technique to investigate the potential effects of land use and accessibility on trip productions. Sixty two variables that may potentially influence trip production are studied. These variables include demographic, socioeconomic, land use and accessibility variables. Different architectures of ANN models are tested. Sensitivity analysis of the models shows that land use does have an effect on trip production, so does traffic condition. The ANN models are compared with linear regression models and cross-classification models using the same data. The results show that ANN models are better than the linear regression models and cross-classification models in terms of RMSE. Future work may focus on finding a representation of traffic condition with existing network data and population data which might be available when the variables are needed to in prediction.

On the accuracy of nonsurvey regional input-output multipliers : An empirical study

Correct specification of the simple location quotients in regionalizing the national direct requirements table is essential to the accuracy of regional input-output multipliers. The purpose of this research is to examine the relative accuracy of these multipliers when earnings, employment, number of establishments, and payroll data specify the simple location quotients. For each specification type, I derive a column of total output multipliers and a column of total income multipliers. These multipliers are based on the 1987 benchmark input-output accounts of the U.S. economy and 1988-1992 state of Florida data. Error sign tests, and Standardized Mean Absolute Deviation (SMAD) statistics indicate that the output multiplier estimates overestimate the output multipliers published by the Department of Commerce-Bureau of Economic Analysis (BEA) for the state of Florida. In contrast, the income multiplier estimates underestimate the BEA's income multipliers. For a given multiplier type, the Spearman-rank correlation analysis shows that the multiplier estimates and the BEA multipliers have statistically different rank ordering of row elements. The above tests also find no significant different differences, both in size and ranking distributions, among the vectors of multiplier estimates.

Radiocarbon dates of peatland initiation across the northern high latitudes

A compilation of basal dates of peatland initiation across the northern high latitudes, associated metadata including location, age, raw and calibrated radiocarbon ages, and associated references. Includes previously published datasets from sources below as well as 365 new data points.

Isotopes content, mineralogical composition, Uranium and Thorium contents and determined activity ratios from METEOR cruise M74/3 in 2007

Authigenic carbonate deposits have been sampled with the remotely operated vehicle 'MARUM-QUEST 4000 m' from five methane seeps between 731 and 1823 m water depth along the convergent Makran continental margin, offshore Pakistan (northern Arabian Sea). Two seeps on the upper slope are located within the oxygen minimum zone (OMZ; ca. 100 to 1100 m water depth), the other sites are situated in oxygenated water below the OMZ (below 1100 m water depth). The carbonate deposits vary with regard to their spatial extent, sedimentary fabrics, and associated seep fauna: Within the OMZ, carbonates are spatially restricted and associated with microbial mats, whereas in the oxygenated zone below the OMZ extensive carbonate crusts are exposed on the seafloor with abundant metazoans (bathymodiolin mussels, tube worms, galatheid crabs). Aragonite and Mg-calcite are the dominant carbonate minerals, forming common early diagenetic microcrystalline cement and clotted to radial-fibrous cement. The delta18O carbonate values range from 1.3 to 4.2 per mil V-PDB, indicating carbonate precipitation at ambient bottom-water temperature in shallow sediment depth. Extremely low delta13Ccarbonate values (as low - 54.6per mil V-PDB) point to anaerobic oxidation of methane (AOM) as trigger for carbonate precipitation, with biogenic methane as dominant carbon source. Prevalence of biogenic methane in the seepage gas is corroborated by delta13C methane values ranging from - 70.3 to - 66.7per mil V-PDB, and also by back-calculations considering delta 13C methane values of carbonate and incorporated lipid biomarkers.

Iterative Phase Optimization of Elementary Quantum Error Correcting Codes

Performing experiments on small-scale quantum computers is certainly a challenging endeavor. Many parameters need to be optimized to achieve high-fidelity operations. This can be done efficiently for operations acting on single qubits, as errors can be fully characterized. For multiqubit operations, though, this is no longer the case, as in the most general case, analyzing the effect of the operation on the system requires a full state tomography for which resources scale exponentially with the system size. Furthermore, in recent experiments, additional electronic levels beyond the two-level system encoding the qubit have been used to enhance the capabilities of quantum-information processors, which additionally increases the number of parameters that need to be controlled. For the optimization of the experimental system for a given task (e.g., a quantum algorithm), one has to find a satisfactory error model and also efficient observables to estimate the parameters of the model. In this manuscript, we demonstrate a method to optimize the encoding procedure for a small quantum error correction code in the presence of unknown but constant phase shifts. The method, which we implement here on a small-scale linear ion-trap quantum computer, is readily applicable to other AMO platforms for quantum-information processing.

Occupant location prediction in smart buildings using association rule mining

Heating, ventilation, air conditioning (HVAC) systems are significant consumers of energy, however building management systems do not typically operate them in accordance with occupant movements. Due to the delayed response of HVAC systems, prediction of occupant locations is necessary to maximize energy efficiency. We present an approach to occupant location prediction based on association rule mining, allowing prediction based on historical occupant locations. Association rule mining is a machine learning technique designed to find any correlations which exist in a given dataset. Occupant location datasets have a number of properties which differentiate them from the market basket datasets that association rule mining was originally designed for. This thesis adapts the approach to suit such datasets, focusing the rule mining process on patterns which are useful for location prediction. This approach, named OccApriori, allows for the prediction of occupants’ next locations as well as their locations further in the future, and can take into account any available data, for example the day of the week, the recent movements of the occupant, and timetable data. By integrating an existing extension of association rule mining into the approach, it is able to make predictions based on general classes of locations as well as specific locations.

Isotope analysis and heat flow measurements of Maria S. Merian cruise MSM21/4 on the western Svalbard margin

Methane hydrate is an ice-like substance that is stable at high-pressure and low temperature in continental margin sediments. Since the discovery of a large number of gas flares at the landward termination of the gas hydrate stability zone off Svalbard, there has been concern that warming bottom waters have started to dissociate large amounts of gas hydrate and that the resulting methane release may possibly accelerate global warming. Here, we can corroborate that hydrates play a role in the observed seepage of gas, but we present evidence that seepage off Svalbard has been ongoing for at least three thousand years and that seasonal fluctuations of 1-2°C in the bottom-water temperature cause periodic gas hydrate formation and dissociation, which focus seepage at the observed sites.