A Formal Context Representation Framework for Network-Enabled Cognition

Network-accessible resources are inherently contextual with respect to the specific situations (e.g., location and default assumptions) in which they are used. Therefore, the explicit conceptualization and representation of contexts is required to address a number of problems in Network- Enabled Cognition (NEC). We propose a context representation framework to address the computational specification of contexts. Our focus is on developing a formal model of context for the unambiguous and effective delivery of data and knowledge, in particular, for enabling forms of automated inference that address contextual differences between agents in a distributed network environment. We identify several components for the conceptualization of contexts within the context representation framework. These include jurisdictions (which can be used to interpret contextual data), semantic assumptions (which highlight the meaning of data), provenance information and inter-context relationships. Finally, we demonstrate the application of the context representation framework in a collaborative military coalition planning scenario. We show how the framework can be used to support the representation of plan-relevant contextual information

Effects of pH on Growth of Salvinia molesta Mitchell

Growth of giant salvinia ( Salvinia molesta Mitchell) under different pH regimes was examined at the Lewisville Aquatic Ecosystem Research Facility (LAERF) in Lewisville, Texas.(PDF has 5 pages.

Deep carbon storage potential of buried floodplain soils.

Soils account for the largest terrestrial pool of carbon and have the potential for even greater quantities of carbon sequestration. Typical soil carbon (C) stocks used in global carbon models only account for the upper 1 meter of soil. Previously unaccounted for deep carbon pools (>1 m) were generally considered to provide a negligible input to total C contents and represent less dynamic C pools. Here we assess deep soil C pools associated with an alluvial floodplain ecosystem transitioning from agricultural production to restoration of native vegetation. We analyzed the soil organic carbon (SOC) concentrations of 87 surface soil samples (0-15 cm) and 23 subsurface boreholes (0-3 m). We evaluated the quantitative importance of the burial process in the sequestration of subsurface C and found our subsurface soils (0-3 m) contained considerably more C than typical C stocks of 0-1 m. This deep unaccounted soil C could have considerable implications for global C accounting. We compared differences in surface soil C related to vegetation and land use history and determined that flooding restoration could promote greater C accumulation in surface soils. We conclude deep floodplain soils may store substantial quantities of C and floodplain restoration should promote active C sequestration

Supporting Distributed Coalition Planning with Semantic Wiki Technology

Contemporary and near-future military coalition environments present a number of challenges for military planning. Not only must military planners create plans against a backdrop of strict time constraints and uncertain information, they must also coordinate their planning efforts with other planning staff (often from different organizational, linguistic and cultural communities). This paper examines the potential for semantic wikis to support collaborative planning activities in the face of these challenges. Whilst we do not claim that semantic wikis could support all aspects of the collaborative planning process, we do suggest that semantic wikis can provide a highly configurable online editing environment which is likely to be of value in at least some coalition planning contexts. The strengths of semantic wikis include their support for distributed editing, their support for flexible forms of information presentation, and the opportunities they provide for new forms of inter-agent coordination. Their weaknesses include the absence of supportive plan editing interfaces and the limited support for the representation of highly expressive planning models. In the current paper, we discuss this profile of strengths and weaknesses, and we also discuss how a specific semantic wiki system, namely Semantic MediaWiki, could be used to support some aspects of collaborative planning

Assessing Short‐Term Impacts of Management Practices on N2O Emissions From Diverse Mediterranean Agricultural Ecosystems Using a Biogeochemical Model

Croplands are important sources of nitrous oxide (N2O) emissions. The lack of both long‐term field measurements and reliable methods for extrapolating these measurements has resulted in a large uncertainty in quantifying and mitigating N2O emissions from croplands. This is especially relevant in regions where cropping systems and farming management practices (FMPs) are diverse. In this study, a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC), was tested against N2O measurements from five cropping systems (alfalfa, wheat, lettuce, vineyards, and almond orchards) representing diverse environmental conditions and FMPs. The model tests indicated that DNDC was capable of predicting seasonal and annual total N2O emissions from these cropping systems, and the model\u27s performance was better than the Intergovernmental Panel on Climate Change emission factor approach. DNDC also captured the impacts on N2O emissions of nitrogen fertilization for wheat and lettuce, of stand age for alfalfa, as well as the spatial variability of N2O fluxes in vineyards and orchards. DNDC overestimated N2O fluxes following some heavy rainfall events. To reduce the biases of simulating N2O fluxes following heavy rainfall, studies should focus on clarifying mechanisms controlling impacts of environmental factors on denitrification. DNDC was then applied to assess the impacts on N2O emissions of FMPs, including tillage, fertilization, irrigation, and management of cover crops. The practices that can mitigate N2O emissions include reduced or no tillage, reduced N application rates, low‐volume irrigation, and cultivation of nonleguminous cover crops. This study demonstrates the necessity and potential of utilizing process‐based models to quantify N2O emissions from regions with highly diverse cropping systems

Socially-distributed cognition and cognitive architectures: towards an ACT-R-based cognitive social simulation capability

ACT-R is one of the most widely used cognitive architectures, and it has been used to model hundreds of phenomena described in the cognitive psychology literature. In spite of this, there are relatively few studies that have attempted to apply ACT-R to situations involving social interaction. This is an important omission since the social aspects of cognition have been a growing area of interest in the cognitive science community, and an understanding of the dynamics of collective cognition is of particular importance in many organizational settings. In order to support the computational modeling and simulation of socially-distributed cognitive processes, a simulation capability based on the ACT-R architecture is described. This capability features a number of extensions to the core ACT-R architecture that are intended to support social interaction and collaborative problem solving. The core features of a number of supporting applications and services are also described. These applications/services support the execution, monitoring and analysis of simulation experiments. Finally, a system designed to record human behavioral data in a collective problem-solving task is described. This system is being used to undertake a range of experiments with teams of human subjects, and it will ultimately support the development of high fidelity ACT-R cognitive models. Such models can be used in conjunction with the ACT-R simulation capability to test hypotheses concerning the interaction between cognitive, social and technological factors in tasks involving socially-distributed information processing

Photoperiodic effects on precocious maturation, growth and smoltification in Atlantic salmon, Salmo salar

Current Atlantic salmon farming practice induces early smoltification with artificial photoperiod regimes, however the importance of these photoperiods on parr maturation and interactions with smoltification are poorly understood. These questions were addressed in the present investigation, which examined the effects of photoperiod manipulation on the development, maturation and smoltification of individually tagged parr. Approximately 9000 salmon parr from a high grilsing stock were exposed to continuous light (LL) from first feeding. Three sub-groups of 2400 parr, each sub-group in triplicate tanks, were then exposed to an 8 week “winter photoperiod” (LD 10:14) starting on either the 18th May, the 9th August or the 20th September (defined respectively as the May, August and September groups). Following the artificial winter each group was returned to LL. A fourth group of 1600 fish was maintained in replicate tanks on LL throughout. The highest levels of maturation (approx. 20%) were recorded in the May group. August and September groups showed low levels of maturity

Monitoring Crop Evapotranspiration and Crop Coefficients over an Almond and Pistachio Orchard Throughout Remote Sensing

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California’s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ψstem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an R2 ≥ 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm·day−1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions

Soil and Land-Use Change Sustainability in the Northern Great Plains of the USA

In the Northern Great Plains (NGP), the combined impacts of land-use and climate variability have the potential to place many soils on the tipping point of sustainability. The objectives of this study were to assess if the conversion of grassland to croplands occurred on fragile landscapes in the North America Northern Great Plains. South Dakota and Nebraska were selected for this study because they are located in a climate transition zone. We visually classified 43,200 and 38,400 points in South Dakota and Nebraska, respectively, from high-resolution imagery in 2006, 2012, and 2014 into five different categories (cropland, grassland, habitat, NonAg, and water). The sustainability risk of the land-use changes was assessed based on the land capability class (LCC) scores at the selected sites. Sites with LCC scores ≤ 4 are considered sustainable for crop production if appropriate management practices are followed. Scores ≥ 6 are not considered suitable for row crop production. From 2006 to 2014, 910,000 and 360,000 ha of land were converted from grassland to cropland in South Dakota and Nebraska, respectively. Approximately 92 and 80% of the grassland conversion to croplands occurred on land suitable for crop production (land capability class, LCC ≤ 4) in South Dakota and Nebraska, respectively