Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

Upland development, climate-related risk and institutional conditions for adaptation in Vietnam

The paper argues that policies towards upland communities in Vietnam tend to reinforce land use strategies that increase vulnerability to climate-related risk and undermine adaptive capacity of upland communities. It is argued that the division of land use between intensive agriculture/tree plantation and protected forest is increasing both livelihood- and environmental risk. Qualitative interviews and group discussion with upland villagers and local government staff in two districts of north and central Vietnam suggest that farmers are facing frequent loss and damage due to floods, storms and drought. Changing production patterns, together with the increase in climate-related hazards and stresses, is changing the character of vulnerability of upland communities. The study primarily explores village-level perspectives regarding impacts of hazards and stresses, ideas of how to reduce risk, along with how related policies and institutions influence local possibilities of risk reduction and adaptation. Our fieldwork results suggest that many villagers and local leaders see adaptation and risk reduction in terms of improved irrigation and in terms of access to land and forests for their livelihoods. The findings support arguments for more integration of agriculture and forestry land use, allowing for more flexibility in the development of upland livelihoods, with the aim of facilitating adaptation to climate change

Gulf Estuarine Research Society 2014 Meeting

Table of Contents: Thank You to Our Sponsors! (p. 3) -- About the Gulf Estuarine Research Society (p. 4) -- Student Travel Award winners (p. 5) -- Abbreviated Schedule (p. 7) -- 2014 Plenary Speaker – Dr. Michael Osland (p. 8) -- 2014 Plenary Speaker – Dr. Maggie Walser (p. 9) -- Full Schedule (p. 10) -- Poster Session Directory (p. 17) -- Oral Presentation Abstracts (p. 21) -- Poster Presentation Abstracts (p. 38) -- Things to Do in Port Aransas (p. 52) -- Greening the Meeting (p. 53) -- Map of University of Texas Marine Science Institute (p. 54)Coastal and Estuarine Research Foundation, Port Aransas, Gulf of Mexico Foundation, Coastal Bend Bays & Estuaries Program, Lotek Wireless Fish & Wildlife Monitoring, Sea Grant Mississippi-Alabama, Sea Grant Louisiana, Sea Grant Texas, The University of Austin Marine Science Institute, Mission-Aransas National Estuarine Research ReserveMarine Scienc

Refining molecular stratigraphy through mass spectrometry imaging of sediments at sub-millimeter resolution

This dissertation focused on the implementation of a new, extraction-free approach to molecular stratigraphy by mass spectrometry imaging (MSI) that allows to increase the spatial and temporal resolution to the micrometer and subannual scale. With this novel technique, detailed insights into the drivers of lipid biomarker-derived proxies were gained by addressing the small-scale differences of the signal archived in the sedimentary record. Together with the improved understanding of the proxy signal, application of MSI to varved sediments from the Santa Barbara Basin, off Southern California revealed insights into the dynamics and interdependencies of ocean surface temperatures, upwelling strength, and bottom water oxygen content during the 20th century

Settlement of larval spotted sand bass (Paralabrax maculatofasciatus) within Mission Bay, San Diego CA in relation to environmental conditions

Monitoring the number of larvae that have recently settled and how this varies in relation to environmental conditions provides insight into future population strength, which is a fundamental goal of marine ecology as well as fisheries management. This research focused on characterizing the settlement patterns of spotted sand bass (Paralabrax maculatofasciatus), a recreationally important species that utilizes bays and estuaries as nursery habitat. To quantify P. maculatofasciatus settlement patterns, three larval collectors were installed near the mouth of Mission Bay, San Diego CA, and retrieved weekly from June – October of 2012 – 2015. Larvae were counted, and individuals were measured for standard length, dry weight, body condition, as well as otolith derived growth rates and age at settlement. To determine whether environmental conditions affected settlement, or individual characteristics of larvae at settlement, we examined how these factors varied in relation to chlorophyll a (Chl-a), sea surface temperature (SST), wind speed, wave height and direction, alongshore transport and upwelling. Settlement of P. maculatofasciatus was significantly lower in 2014-15, and appeared to be the result of low food conditions associated with the formation of the pacific warm anomaly, or “blob”, which reached the coast of southern California in the summer of 2014. The characteristics of larvae at settlement were also consistent with a poor feeding environment. This study has implications for understanding future settlement and recruitment of fishes in southern California, as ocean temperatures continue to rise in the face of climate change

Following Darwin's footsteps using 'the most wonderful plants in the world': the ecophysiological responses of the carnivorous plant Drosera rotundifolia to nitrogen availability.

Nitrogen (N) is an essential element to plants for growth, maintenance and reproduction, however most N does not exist in a form that is biologically available to plants. In order to maximise the acquisition and retention of N, plants have evolved a variety of morphological and physiological adaptations and life history strategies, as well as the ability to respond plastically to changes in resource availability in ecological time. Determining the ecophysiological responses of plants to changes in root N availability is crucial to further understanding of the mechanisms underlying competitive interactions between plants, and between plants and other organisms, that ultimately contribute to community structure and ecosystem functioning. Carnivorous plants are ideal systems for investigating ecophysiological responses to N availability as:- (i) they share a unique adaptation for obtaining supplemental N from captured prey, therefore ecological stoichiometry and energetic cost/benefit models may be explored; (ii) the trait of botanical carnivory is widely considered to have independently co-evolved as a response to N-deficient, sunny and wet environments, therefore resource allocation trade-offs between plant investment in N and carbon (C) acquisition may be observed, and (iii) they are extremely sensitive to changes in root N availability in ecological time. In this research, the carnivorous plant Drosera rotundifolia (round-leaved sundew) was used to address several unanswered ecophysiological and evolutionary questions relating to patterns and processes of prey capture and the N nutrition of carnivorous plants. Furthermore, the potential for reducing uncertainty in the calculation of plant reliance on carnivory using a δ15N natural abundance multi-level linear mixing model was explored. A combined approach of in-situ and ex-situ studies was employed, using co-occurring non-carnivorous plants or carnivorous plant species with differing evolutionary lineages or prey capture mechanisms respectively to provide context. Results show that the adaptations of carnivory, high reproductive investment and a relatively short life span enable Drosera rotundifolia to survive and thrive in an extreme, N deficient environment. Phenotypically plastic responses by the plant to light and root N availability provide evidence of resource allocation trade-offs between investment in carnivory for N acquisition and in photosynthesis for C acquisition. Plants invested less heavily in prey capture (measured as the stickiness of leaf mucilage) as N availability increased or light availability decreased. These results show that the energetic costs associated with carnivory are avoided by the plant when less costly sources of N are available for uptake and that the production of carbon-rich mucilage is only made under nutrient-limited and well-lit conditions. Results obtained from the comparison of captured insect prey with background invertebrates of potential prey indicate that Drosera rotundifolia is a dietary generalist, where the quantity of prey captured per plant is positively correlated with leaf stickiness and total leaf area. Plant reliance on prey-derived N decreased with increasing root N availability, providing evidence that carnivory is only of net benefit to the plant in N-deficient and well-lit environments, as the photosynthetic costs of investment in the trait are not exceeded by the energetic gain from prey N uptake in shady or dry habitats. A more accurate and precise method for calculating plant reliance on botanical carnivory is presented which incorporates the insect diet of the plant. This method has wider significance for reducing uncertainty in the calculation of relative source contributions to a mixture for most natural abundance applications using a multi-level linear mixing model. To conclude, results from this research further understanding of the ecophysiological mechanisms underlying plant responses to changes in resource availability and the selective pressures driving the evolution of plant adaptations. These results therefore assist with predicting how plants and plant communities may respond to sustained N deposition inputs and future environmental scenarios

What is cumulative cultural evolution?

This is the final version. Available from The Royal Society via the DOI in this record.In recent years, the phenomenon of cumulative cultural evolution (CCE) has become the focus of major research interest in biology, psychology and anthropology. Some researchers argue that CCE is unique to humans and underlies our extraordinary evolutionary success as a species. Others claim to have found CCE in non-human species. Yet others remain sceptical that CCE is even important for explaining human behavioural diversity and complexity. These debates are hampered by multiple and often ambiguous definitions of CCE. Here, we review how researchers define, use and test CCE. We identify a core set of criteria for CCE which are both necessary and sufficient, and may be found in non-human species. We also identify a set of extended criteria that are observed in human CCE but not, to date, in other species. Different socio-cognitive mechanisms may underlie these different criteria. We reinterpret previous theoretical models and observational and experimental studies of both human and non-human species in light of these more fine-grained criteria. Finally, we discuss key issues surrounding information, fitness and cognition. We recommend that researchers are more explicit about what components of CCE they are testing and claiming to demonstrate.Economic and Social Research Council (ESRC

Using power-law properties of social groups for cloud defense and community detection

The power-law distribution can be used to describe various aspects of social group behavior. For mussels, sociobiological research has shown that the Lévy walk best describes their self-organizing movement strategy. A mussel\u27s step length is drawn from a power-law distribution, and its direction is drawn from a uniform distribution. In the area of social networks, theories such as preferential attachment seek to explain why the degree distribution tends to be scale-free. The aim of this dissertation is to glean insight from these works to help solve problems in two domains: cloud computing systems and community detection. Privacy and security are two areas of concern for cloud systems. Recent research has provided evidence indicating how a malicious user could perform co-residence profiling and public to private IP mapping to target and exploit customers which share physical resources. This work proposes a defense strategy, in part inspired by mussel self-organization, that relies on user account and workload clustering to mitigate co-residence profiling. To obfuscate the public to private IP map, clusters are managed and accessed by account proxies. This work also describes a set of capabilities and attack paths an attacker needs to execute for targeted co-residence, and presents arguments to show how the defense strategy disrupts the critical steps in the attack path for most cases. Further, it performs a risk assessment to determine the likelihood an individual user will be victimized, given that a successful non-directed exploit has occurred. Results suggest that while possible, this event is highly unlikely. As for community detection, several algorithms have been proposed. Most of these, however, share similar disadvantages. Some algorithms require apriori information, such as threshold values or the desired number of communities, while others are computationally expensive. A third category of algorithms suffer from a combination of the two. This work proposes a greedy community detection heuristic which exploits the scale-free properties of social networks. It hypothesizes that highly connected nodes, or hubs, form the basic building blocks of communities. A detection technique that explores these characteristics remains largely unexplored throughout recent literature. To show its effectiveness, the algorithm is tested on commonly used real network data sets. In most cases, it classifies nodes into communities which coincide with their respective known structures. Unlike other implementations, the proposed heuristic is computationally inexpensive, deterministic, and does not require apriori information

Endogenous space in the Net era

Libre Software communities are among the most interesting and advanced socio-economic laboratories on the Net. In terms of directions of Regional Science research, this paper addresses a simple question: “Is the socio-economics of digital nets out of scope for Regional Science, or might the latter expand to a cybergeography of digitally enhanced territories ?” As for most simple questions, answers are neither so obvious nor easy. The authors start drafting one in a positive sense, focussing upon a file rouge running across the paper: endogenous spaces woven by socio-economic processes. The drafted answer declines on an Evolutionary Location Theory formulation, together with two computational modelling views. Keywords: Complex networks, Computational modelling, Economics of Internet, Endogenous spaces, Evolutionary location theory, Free or Libre Software, Path dependence, Positionality.