Modularised process-based modelling of phosphorus loss at farm and catchment scale

In recent years, a co-ordinated programme of data collection has resulted in the collation of sub-hourly time-series of hydrological, sediment and phosphorus loss data, together with soil analysis, cropping and management information for two small (< 200 ha) headwater agricultural catchments in the UK Midlands (Rosemaund, Herefordshire and Cliftonthorpe, Leicestershire). These data sets have allowed the dynamics of phosphorus loss to be characterised and the importance of both storm runoff and drainflow to be identified, together with incidental losses following manure and fertiliser additions in contributing to total annual loss. A modularised process-based model has been developed to represent current understanding of the dynamics of phosphorus loss. Modules describing runoff and sediment generation and associated phosphorus adsorption/desorption dynamics are described and tested. In the model, the effect of a growing crop on sediment detachment processes is represented and the stability of topsoil is considered so that, overall, the model is responsive to farm management factors. Importantly, using data sets available from national-scale survey programmes to estimate model parameters, a transferable approach is presented, requiring only sub-hourly rainfall data and field-specific landcover information for application of the model to new sites. Results from application of the model to the hydrological year 1998–99 are presented. Assessment of performance, which suggests that the timing of simulated responses is acceptable, has focused attention on quantifying landscape and in-stream retention and remobilisation processes.</b></p> <p style='line-height: 20px;'><b>Keywords: </b>phosphorus, erosion, process-based modelling, agricultur

Nutrient Cycles and Marine Microbes in a CO2-Enriched Ocean

The ocean carbon cycle is tightly linked with the cycles of the major nutrient elements nitrogen, phosphorus, and silicon. It is therefore likely that enrichment of the ocean with anthropogenic CO2 and attendant acidification will have large consequences for marine nutrient biogeochemistry, and for the microbes that mediate many key nutrient transformations. The best available evidence suggests that the nitrogen cycle may respond strongly to higher CO2 through increases in global N2 fixation and possibly denitrification, as well as potential decreases in nitrification. These trends could cause nitrification to become a nitrogen cycle bottleneck, by increasing the flux of N2 fixed into ammonium while decreasing the fraction being oxidized to nitrate and nitrate. The consequences could include reduced supplies of oxidized nitrogen substrates to denitrifiers, lower levels of nitrate-supported new primary production, and expansion of the regenerated production system accompanied by shifts in current phytoplankton communities. The phosphorus and silicon cycles seem less likely to be directly affected by enhanced CO2 conditions, but will undoubtedly respond indirectly to changing carbon and nitrogen biogeochemistry. A review of culture experiments that examined the effects of increased CO2 on elemental ratios of phytoplankton suggests that for most cyanobacteria and eukaryotes, C:N and N:P ratios will either remain at Redfield values or increase substantially. Natural plankton community CO2 manipulation experiments show much more mixed outcomes, with both increases and decreases in C:N and N:P ratios reported at future CO2 levels. We conclude our review with projections of overall trends in the cycles of nitrogen, phosphorus, and silicon over the next century as they respond to the steady accumulation of fossil-fuel derived CO2 in a rapidly changing ocean

Research Center for Quantitative Renal Imaging

poster abstractMission: The mission of the Research Center for Quantitative Renal Imaging is to provide a focused research environment and resource for the development, implementation, and dissemination of innovative, quantitative imaging methods designed to assess the status of and mechanisms associated with acute and chronic kidney disease and evaluate efficacy of therapeutic interventions. Nature of the Center: This Research Center provides a formal mechanism to link research programs focused on understanding the fundamental mechanisms associated with kidney diseases with those associated with the development of advanced imaging methods and quantitative analyses into a focused effort dedicated toward the development and implementation of quantitative renal imaging methods. Goals of the IUPUI Research Center for Quantitative Renal Imaging: Identify, develop, and implement innovative imaging methods that provide quantitative imaging biomarkers for assessing and inter-relating renal structure, function, hemodynamics and underlying tissue micro-environmental factors contributing to kidney disease. Establish an environment that facilitates and encourages interdisciplinary collaborations among investigators and offers research support to investigators focused on developing and utilizing innovative quantitative imaging methods in support of kidney disease research. Provide a resource to inform the greater research and healthcare communities of advances in quantitative renal imaging and its potential for enhanced patient management and care. Offer an imaging research resource to companies engaged in product development associated with the diagnosis and treatment of kidney diseases. Further Information: For further information regarding the IUPUI Research Center for Quantitative RenalImaging and its funding programs please visit http://www.renalimaging.iupui.edu/ or contact the Center at [email protected]. Acknowledgments: The IUPUI Research Center for Quantitative Renal Imaging is supported by contributions from the IUPUI Signature Center Initiative, the Department of Radiology & Imaging Sciences; the Division of Nephrology, the IUPUI School of Science, the IUPUI School of Engineering & Technology, and the Indiana Clinical and Translational Sciences Institute (CTSI)

Optimisation of an acoustic resonator for particle manipulation in air

An acoustic resonator system has been investigated for the manipulation and entrapment of micron-sized particles in air. Careful consideration of the effect of the thickness and properties of the materials used in the design of the resonator was needed to ensure an optimised resonator. This was achieved using both analytical and finite-element modelling, as well as predictions of acoustic attenuation in air as a function of frequency over the 0.8 to 2.0 MHz frequency range. This resulted in a prediction of the likely operational frequency range to obtain particle manipulation. Experimental results are presented to demonstrate good capture of particles as small as 15 µm in diameter

Tracking advanced persistent threats in critical infrastructures through opinion dynamics

Advanced persistent threats pose a serious issue for modern industrial environments, due to their targeted and complex attack vectors that are difficult to detect. This is especially severe in critical infrastructures that are accelerating the integration of IT technologies. It is then essential to further develop effective monitoring and response systems that ensure the continuity of business to face the arising set of cyber-security threats. In this paper, we study the practical applicability of a novel technique based on opinion dynamics, that permits to trace the attack throughout all its stages along the network by correlating different anomalies measured over time, thereby taking the persistence of threats and the criticality of resources into consideration. The resulting information is of essential importance to monitor the overall health of the control system and cor- respondingly deploy accurate response procedures. Advanced Persistent Threat Detection Traceability Opinion Dynamics.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Gesture analysis for physics education researchers

Systematic observations of student gestures can not only fill in gaps in students' verbal expressions, but can also offer valuable information about student ideas, including their source, their novelty to the speaker, and their construction in real time. This paper provides a review of the research in gesture analysis that is most relevant to physics education researchers and illustrates gesture analysis for the purpose of better understanding student thinking about physics.Comment: 14 page

Using a magnetite/thermoplastic composite in 3D printing of direct replacements for commercially available flow sensors

Flow sensing is an essential technique required for a wide range of application environments ranging from liquid dispensing to utility monitoring. A number of different methodologies and deployment strategies have been devised to cover the diverse range of potential application areas. The ability to easily create new bespoke sensors for new applications is therefore of natural interest. Fused deposition modelling is a 3D printing technology based upon the fabrication of 3D structures in a layer-by-layer fashion using extruded strands of molten thermoplastic. The technology was developed in the late 1980s but has only recently come to more wide-scale attention outside of specialist applications and rapid prototyping due to the advent of low-cost 3D printing platforms such as the RepRap. Due to the relatively low-cost of the printers and feedstock materials, these printers are ideal candidates for wide-scale installation as localized manufacturing platforms to quickly produce replacement parts when components fail. One of the current limitations with the technology is the availability of functional printing materials to facilitate production of complex functional 3D objects and devices beyond mere concept prototypes. This paper presents the formulation of a simple magnetite nanoparticle-loaded thermoplastic composite and its incorporation into a 3D printed flow-sensor in order to mimic the function of a commercially available flow-sensing device. Using the multi-material printing capability of the 3D printer allows a much smaller amount of functional material to be used in comparison to the commercial flow sensor by only placing the material where it is specifically required. Analysis of the printed sensor also revealed a much more linear response to increasing flow rate of water showing that 3D printed devices have the potential to at least perform as well as a conventionally produced sensor

In-depth analysis of the Naming Game dynamics: the homogeneous mixing case

Language emergence and evolution has recently gained growing attention through multi-agent models and mathematical frameworks to study their behavior. Here we investigate further the Naming Game, a model able to account for the emergence of a shared vocabulary of form-meaning associations through social/cultural learning. Due to the simplicity of both the structure of the agents and their interaction rules, the dynamics of this model can be analyzed in great detail using numerical simulations and analytical arguments. This paper first reviews some existing results and then presents a new overall understanding.Comment: 30 pages, 19 figures (few in reduced definition). In press in IJMP

The value of diversity in cognitive science

A recent article (Núñez et al., 2019) claims that cognitive science, while starting off as a multidisciplinary enterprise, has “failed to transition to a mature inter‐disciplinary coherent field.” Two indicators reported in support of this claim target one of the two journals of the Cognitive Science Society, Cognitive Science , depicting cognitive science as an increasingly monodisciplinary subfield which is dominated by psychology. With a focus on the society's other journal, Topics in Cognitive Science , the present commentary reveals a greater degree of interdisciplinarity and discusses the relative values of diversity and integration for the field.publishedVersio