831 resultados para Human-environment Coupling


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The manner in which remains decompose has been and is currently being researched around the world, yet little is still known about the generated scent of death. In fact, it was not until the Casey Anthony trial that research on the odor released from decomposing remains, and the compounds that it is comprised of, was brought to light. The Anthony trial marked the first admission of human decomposition odor as forensic evidence into the court of law; however, it was not "ready for prime time" as the scientific research on the scent of death is still in its infancy. This research employed the use of solid-phase microextraction (SPME) with gas chromatography-mass spectrometry (GC-MS) to identify the volatile organic compounds (VOCs) released from decomposing remains and to assess the impact that different environmental conditions had on the scent of death. Using human cadaver analogues, it was discovered that the environment in which the remains were exposed to dramatically affected the odors released by either modifying the compounds that it was comprised of or by enhancing/hindering the amount that was liberated. In addition, the VOCs released during the different stages of the decomposition process for both human remains and analogues were evaluated. Statistical analysis showed correlations between the stage of decay and the VOCs generated, such that each phase of decomposition was distinguishable based upon the type and abundance of compounds that comprised the odor. This study has provided new insight into the scent of death and the factors that can dramatically affect it, specifically, frozen, aquatic, and soil environments. Moreover, the results revealed that different stages of decomposition were distinguishable based upon the type and total mass of each compound present. Thus, based upon these findings, it is suggested that the training aids that are employed for human remains detection (HRD) canines should 1) be characteristic of remains that have undergone decomposition in different environmental settings, and 2) represent each stage of decay, to ensure that the HRD canines have been trained to the various odors that they are likely to encounter in an operational situation.

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Lecture given by Dr. John Stuart, Professor of Architecture and Department Chair of Architecture and the Arts at Florida International University. This lecture focuses on the aesthetics of edifices. Event held on April 18, 2012 at the Green Library, Modesto Maidique Campus, Florida International University.

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With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

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Acknowledgements This work was funded by the projects HAR2013-43701-P (Spanish Economy and Competitiveness Ministry) and CGL2010-20672 (Spanish Ministry of Science and Innovation). This research was also partially developed with Xunta de Galicia funding (grants R2014/001 and GPC2014/009). N. Silva-Sánchez is currently supported by a FPU pre-doctoral grant (AP2010-3264) funded by the Spanish Government. We are grateful to Ana Moreno, Mariano Barriendos and Gerardo Benito who kindly provide us data included in Figure 5a. We also want to thank constructive comments from two anonymous reviewers.

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Acknowledgements This work was funded by a PhD studentship to EM from the Natural Environment Research Council (2210 GG005 RGA1521) and an Arts and Humanities Research Council (AH/K006029/1) grant to RK, KB and Charlotta Hillerdal (Aberdeen). Material was excavated from Nunalleq by staff and students from the University of Aberdeen, volunteer excavators and residents of Quinhagak. Logistical and planning support for the excavation was provided by Qanirtuuq Incorporated, Quinhagak, and the residents of Quinhagak.

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Acknowledgments The authors are very grateful to Mr. Fabiano Bielefeld Nardotto, owner of the Tabapuã dos Pireneus farm, for allowing our free movement around the farm and collection of soil samples, as well as providing information about soybean cultivation. The authors also thank Dr. Plínio de Camargo, who performed the isotopic analysis in the CENA laboratory at the University of São Paulo (USP). This work was supported by grants from the National Council of Technological and Scientific Development (CNPq), Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES), and Foundation for Research Support of Distrito Federal (FAP-DF).

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Acknowledgements This work was funded by the projects HAR2013-43701-P (Spanish Economy and Competitiveness Ministry) and CGL2010-20672 (Spanish Ministry of Science and Innovation). This research was also partially developed with Xunta de Galicia funding (grants R2014/001 and GPC2014/009). N. Silva-Sánchez is currently supported by a FPU pre-doctoral grant (AP2010-3264) funded by the Spanish Government. We are grateful to Ana Moreno, Mariano Barriendos and Gerardo Benito who kindly provide us data included in Figure 5a. We also want to thank constructive comments from two anonymous reviewers.

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As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

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As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

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Humans are profoundly affected by the surroundings which they inhabit. Environmental psychologists have produced numerous credible theories describing optimal human environments, based on the concept of congruence or “fit” (1, 2). Lack of person/environment fit can lead to stress-related illness and lack of psychosocial well-being (3). Conversely, appropriately designed environments can promote wellness (4) or “salutogenesis” (5). Increasingly, research in the area of Evidence-Based Design, largely concentrated in the area of healthcare architecture, has tended to bear out these theories (6). Patients and long-term care residents, because of injury, illness or physical/ cognitive impairment, are less likely to be able to intervene to modify their immediate environment, unless this is designed specifically to facilitate their particular needs. In the context of care settings, detailed design of personal space therefore takes on enormous significance. MyRoom conceptualises a personalisable room, utilising sensoring and networked computing to enable the environment to respond directly and continuously to the occupant. Bio-signals collected and relayed to the system will actuate application(s) intended to positively influence user well-being. Drawing on the evidence base in relation to therapeutic design interventions (7), real-time changes in ambient lighting, colour, image, etc. respond continuously to the user’s physiological state, optimising congruence. Based on research evidence, consideration is also given to development of an application which uses natural images (8). It is envisaged that actuation will require machine-learning based on interpretation of data gathered by sensors; sensoring arrangements may vary depending on context and end-user. Such interventions aim to reduce inappropriate stress/ provide stimulation, supporting both instrumental and cognitive tasks.

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The human ether-a-go-go-related gene (hERG) encodes the voltage-gated K+ channel, hERG (Kv11.1). This channel passes the rapidly-activating delayed rectifier K+ current (IKr), which is important for cardiac repolarization. A reduction in IKr due to loss-of-function mutations or drug interactions causes long QT syndrome (LQTS), which can lead to cardiac arrhythmias and sudden cardiac death. The density of hERG channels in the plasma membrane is a key determinant of normal physiological function, and is balanced by trafficking to and from the cell surface. Many LQTS-associated hERG mutations result in a trafficking deficiency of otherwise functional channels. Thus, elucidating mechanisms of hERG regulation at the plasma membrane is useful for the prevention and treatment of LQTS. We previously demonstrated that M3 muscarinic receptor activation increases mature hERG expression through a Gq protein-dependent protein kinase C (PKC) pathway. In addition to conventional Gq protein-coupling, M3 receptors recruit β-arrestins upon agonist binding. Traditionally known for their role in receptor desensitization and internalization, β-arrestins also act as adaptor proteins to facilitate G protein-independent signaling. In the present work, I investigated the exclusive effect of β-arrestin signaling on hERG expression by utilizing an arrestin-biased M3 designer receptor (M3D-arr) exclusively activated by clozapine-N-oxide (CNO). By expressing M3D-arr in hERG-HEK cells and treating with CNO under various conditions, I found that M3D-arr activation increased mature hERG expression and current. Within this paradigm, M3D-arr recruited β-arrestin to the plasma membrane, and promoted the PI3K-dependent activation of Akt. I further found that the activated Akt acted through phosphatidylinositol 3-phosphate 5-kinase (PIKfyve) and Rab11 to facilitate endosomal recycling of hERG channels to the plasma membrane.

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Niche construction is the process by which organisms construct important components of their local environment in ways that introduce novel selection pressures. Lactase persistence is one of the clearest examples of niche construction in humans. Lactase is the enzyme responsible for the digestion of the milk sugar lactose and its production decreases after the weaning phase in most mammals, including most humans. Some humans, however, continue to produce lactase throughout adulthood, a trait known as lactase persistence. In European populations, a single mutation (−13910*T) explains the distribution of the phenotype, whereas several mutations are associated with it in Africa and the Middle East. Current estimates for the age of lactase persistence-associated alleles bracket those for the origins of animal domestication and the culturally transmitted practice of dairying. We report new data on the distribution of −13910*T and summarize genetic studies on the diversity of lactase persistence worldwide. We review relevant archaeological data and describe three simulation studies that have shed light on the evolution of this trait in Europe. These studies illustrate how genetic and archaeological information can be integrated to bring new insights to the origins and spread of lactase persistence. Finally, we discuss possible improvements to these models.

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We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

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We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

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The transmission of water-borne pathogens typically occurs by a faecal–oral route, through inhalation of aerosols, or by direct or indirect contact with contaminated water. Previous molecular-based studies have identified viral particles of zoonotic and human nature in surface waters. Contaminated water can lead to human health issues, and the development of rapid methods for the detection of pathogenic microorganisms is a valuable tool for the prevention of their spread. The aims of this work were to determine the presence and identity of representative human pathogenic enteric viruses in water samples from six European countries by quantitative polymerase chain reaction (q-PCR) and to develop two quantitative PCR methods for Adenovirus 41 and Mammalian Orthoreoviruses. A 2-year survey showed that Norovirus, Mammalian Orthoreovirus and Adenoviruses were the most frequently identified enteric viruses in the sampled surface waters. Although it was not possible to establish viability and infectivity of the viruses considered, the detectable presence of pathogenic viruses may represent a potential risk for human health. The methodology developed may aid in rapid detection of these pathogens for monitoring