Prediction Markets to Forecast Electricity Demand

A preference is invariant with respect to a transformation tau if its ranking of acts is unaffected by a reshuffling of the states under tau. We show that any invariant preference must be parametric: there is a unique sufficient set of parameters such that the preference ranks acts according to their expected utility given the parameters. This property holds for all non-trivial preferences, provided only that they are reflexive, transitive, monotone, continuous and mixture linear.

Transaction Costs and the Robustness of the Coase Theorem

We develop a model of undescribable events. Examples of events that are well understood by economic agents but are prohibitively difficult to describe in advance abound in real-life. This notion has also pervaded a substantial amount of economic literature. We put forth a model of such events using a simple co-insurance problem as backdrop. Undescribable events in our model are understood by economic agents --- their consequences and probabilities are known --- but are such that every finite description of such events necessarily leaves out relevant features that have a non-negligible impact on the parties' expected utilities. We also show that two key ingredients of our model --- probabilities that are finitely additive but fail countable additivity, and a state space that is small (discrete in our model) in a measure-theoretic sense --- are necessary ingredients of any model of undescribable events that delivers our results.Undescribable Events, Incomplete Contracts, Finite Invariance, Fine Variability.

Effect of Stone Powder and Lime on Strength, Compaction and CBR Properties of Fine Soils

This research is an attempt to investigate the effect of stone powder and lime on the strength, compaction and CBR properties of fine grained soil. The basic properties: direct shear, compaction and CBR were determined first. The stone powder and lime were added at specific percentages (10%, 20% and 30%) by weight of soil and mixed with the optimum moisture content obtained from the compaction test. The direct shear, compaction and CBR tests were conducted directly without curing or soaking of the specimens. The results revealed that the addition of 30% stone powder has increased the angle of internal friction (φ) by about 50% and reduced cohesion by about 64%. The addition of 30% of lime has decreased the friction angle and cohesion by 57% and 28%, respectively. The maximum dry density and optimum moisture content decreased slightly by addition of 30% stone powder, however, the addition of 30% lime decreased the maximum dry density and optimum moisture content by 19% and 13.5%, respectively. The CBR values have increased from 5.2 to 16 and 18 by the addition of 30% stone powder and lime, respectively. The thicknesses of flexible pavement were determined based on the CBR values and assumed daily traffic volume and found to be reduced from 38 cm for soil without additives to 20 cm and 17cm by the addition of 30% of stone powder and lime, respectively

Variance Decomposition of Forecasted Water Budget and Sediment Processes under Changing Climate in Fluvial and Fluviokarst Systems

Variance decomposition is the partitioning of different factors affecting the variance structure of a response variable. The present research focuses on future streamflow and sediment transport processes projections as the response variables. The authors propose using numerous climate factors and hydrological modeling factors that can cause any response variable to vary from historic to future conditions in any given watershed system. The climate modeling factors include global climate model, downscaling method, emission scenario, project phase, bias correction. The hydrological modeling factor includes hydrological model parametrization, and meteorological variable inclusion in the analysis. This research uses a wide spectrum of data, including climate data of precipitation and temperature from GCM results, and observations of meteorological data, streamflow and spring flow data, and sediment yield data. This research focuses on employing an off-the-shelf hydrological model and developing different numerical models (using MATLAB) for simulating sediment transport processes and water movement in an epigenetic karst system. With regards to variance decomposition, the approach is to use a mixed statistical method of linear and nonlinear analysis by means of analysis of variance (ANOVA) and artificial neural networks (ANN) respectively. All the computational tools that will be used to perform the statistics are provided by SPSS software. Two study sites are considered in this work including South Elkhorn watershed and Cave Run watershed. South Elkhorn watershed is a fluvial system and is located in Lexington, Kentucky, USA. This system is characterized as a wet, temperate region in the central and eastern United States where a change in the climate is projected. The mean streamflow, extreme streamflow, and sediment processes forecast are investigated in this watershed. Royal Spring watershed is a fluviokarst system and is adjacent to the South Elkhorn watershed. In this watershed we investigate the water pathway connectivity as well as the impact of climate change on the mean annual spring flow and streamflow. Analysis of variance results indicate that the difference in forecast and hindcast mean streamflow predictions is a function of GCM type, climate model project phase, and downscaling approach. Predicted average monthly change in streamflow tends to follow precipitation changes and result in a net increase in the average annual precipitation and streamflow by 10% and 11%, respectively, when comparing historical period (1980-2000) to the future period (2045-2065). Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima method versus peak over threshold method. However, it was dependent all climate modeling factors. Ensemble projections forecast an increase of streamflow maxima of 51% for 100-year streamflow event. Hydrologic model parameterization was the greatest source of variance impacting forecasted sediment transport variables. Hydrologic inputs from climate change including forecasted precipitation, temperature, relative humidity, solar radiation and wind speed all impacted sediment transport. Ensemble average forecasts sediment yield to increase by 14% for the Upper South Elkhorn watershed. The numerical model of the Cave Run/ Royal Spring watershed suggests 30 to 45% of surface stream discharge originates from in-stream swallet reversal and hillside springs. Also, the hydrology of the floviokarst system might be altered by the impact of climate change where an increase in the surface flow and spring flow is projected to be 8.8% and 12.2%, respectively. The results show that the change in pathway connectivity is important on seasonal bases and follows the seasonal change in precipitations

Unforeseen Contingencies

We develop a model of unforeseen contingencies. These are contingencies that are understood by economic agents - their consequences and probabilities are known - but are such that every description of such events necessarily leaves out relevant features that have a non-negligible impact on the parties' expected utilities. Using a simple co-insurance problem as a backdrop, we introduce a model where states are described in terms of objective features, and the description of an event specifies a finite number of such features. In this setting, unforeseen contingencies are present in the co-insurance problem when the first-best risk-sharing contract varies with the states of nature in a complex way that makes it highly sensitive to the component features of the states. In this environment, although agents can compute expected pay-offs, they are unable to include in any ex-ante agreement a description of the relevant contingencies that captures (even approximately) the relevant complexity of the risky environment.Unforeseen contingencies, incomplete contracts, finite invariance, fine variability.

Undescribable Events

We develop a model of undescribable events. Examples of events that are well understood by economic agents but are prohibitively difficult to describe in advance abound in real-life. This notion has also pervaded a substantial amount of economic literature. We put forth a model of such events using a simple co-insurance problem as backdrop. Undescribable events in our model are understood by economic agents - their consequences and probabilities are known - but are such that every finite description of such events necessarily leaves out relevant features that have a non-negligible impact on the parties’ expected utilities. We also show that two key ingredients of our model - probabilities that are finitely additive but fail countable additivity, and a state space that is small (discrete in our model) in a measure-theoretic sense -are necessary ingredients of any model of undescribable events that delivers our results.undescribable events, incomplete contracts, finite invariance, fine variability

Modulation of thiols and pulmonary immune responses due to diesel exhaust particle (DEP) exposure

Environmental exposure to diesel exhaust particles (DEP) has been of concern because of its potential contribution to the increased prevalence of acute and chronic airway diseases. The objective of this study was to investigate the role of thiol changes (due to DEP exposure) in immune responses. Rats were exposed to OVA, DEP, or both by intratracheal instillation (IT) and/or inhalation. IT-DEP exposure significantly increased the inflammatory parameters and thiol levels in both Sprague-Dawley and Brown Norway rats. Exposure to DEP and/or OVA resulted in significant increases in neutrophils, LDH, total protein, and albumin content in lavage fluid. Alveolar macrophage (AM) from DEP-exposed rats showed a time-dependent increase in intracellular cysteine (CYSH) and glutathione (GSH). In lymph node cells (LNC, the intracellular GSH increased significantly at 24 hours, and declined at 72 hours post exposure. LNC-CYSH, and AM-CYSH and -GSH were increased at both 24 and 72 hours. DEP acutely enhanced cystine uptake and reduction in both AM and LNC. In contrast, the intracellular level of GSH in DEP-exposed LNC was significantly reduced despite the increased CYSH level and GSH-ReductaseRTM activity when these cells were cultured with cystine. The DEP exposure stimulated GSH-R activity and resulted in increased conversion of cystine to CYSH in both cell types. Notable restoration of cystine uptake, reduction and GSH production was seen in AM of DEP-exposed OVA-challenged rats. Threshold effect on both CYSH and GSH levels in BAL and AM was seen after exposure to different concentrations of OVA alone. CB and DEP tended to increase lung IFN-gamma and IL-4 mRNA. The significant increases in serum OVA-specific IgG and IgE and the increase in IL-4 mRNA in lung tissue were consistent with an adjuvant effect of DEP or CB for OVA sensitization. In summary, DEP caused lung inflammation and thiol changes (in both AM and LNC and that these effects are particulate mediated