Farmland Control Decisions under Different Intertemporal Risk Behavioral Constructs

Simulation-optimization techniques are employed to analyze changes in farmland control arrangements as a result of using different constructs of intertemporal risk behavior. Risk behavior based on constant absolute risk aversion (CARA) and constant relative risk aversion (CRRA) mean-standard deviation functions are used to achieve this objective. Specfically, a multi-period programming framework for a representative grain farm is developed to explore farmland control decisions under these two behavioral assumptions. Our results suggest that the use of a CRRA behavioral construct in analyzing farmland control decisions produce predictions that are more consistent with observed farm behavior.Farm Management,

Methods for calculating solar position and day length including computer programs and subroutines

The theory of calculating solar position is described. Using this theory, a number of computing routines are prepared in the C programming language. These routines are suitable for users who program in C, and have an ANSI compatible C compiler. These routines are fully documented, with both the underlying theory, and code particulars, and may be used as a stand alone reference. The source code has also been published in appendix B of the report

OPPORTUNITY COSTS, SHARE LEASING, AND PREVENTED PLANTING CLAIMS IN CROP INSURANCE

This paper determines whether the opportunity costs of share leasing and the share amounts of farmers/tenants affect the likelihood of submitting a prevented planting claim. Results from our probit analysis shows that lower opportunity costs of share leasing and higher farmer/tenant share amount can increase the probability of submitting a prevented planting. These results have potential implications for setting prevented planting buy-up rates and crop insurance compliance procedures.Risk and Uncertainty,

Happiness as stable extraversion : internal consistency reliability and construct validity of the Oxford Happiness Questionnaire among undergraduate students

The Oxford Happiness Questionnaire (OHQ) was developed by Hills and Argyle (2002) to provide a more accessible equivalent measure of the Oxford Happiness Inventory (OHI). The aim of the present study was to examine the internal consistency reliability, and construct validity of this new instrument alongside the Eysenckian dimensional model of personality. The Oxford Happiness Questionnaire was completed by a sample of 131 undergraduate students together with the abbreviated form of the Revised Eysenck Personality Questionnaire. The data demonstrated good internal consistency reliability (alpha = .92) and good construct validity in terms of positive association with extraversion (r = .38 p < .001) and negative association with neuroticism (r = −.57 p < .001). The kind of happiness measured by the OHQ is clearly associated with stable extraversion

An optimality-based model of the coupled soil moisture and root dynamics

The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Modelling soil moisture dynamics therefore requires an interdisciplinary approach that links hydrological, atmospheric and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on vegetation optimality. Assuming that plants have evolved mechanisms that minimise costs related to the maintenance of the root system while meeting their demand for water, we develop a model that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics, root water uptake and fine root respiration in a tropical savanna over 12 months, and the results were compared with observations at the site and with a model based on a fixed root distribution. The optimality-based model reproduced the main features of the observations such as a shift of roots from the shallow soil in the wet season to the deeper soil in the dry season and substantial root water uptake during the dry season. At the same time, simulated fine root respiration rates never exceeded the upper envelope determined by the observed soil respiration. The model based on a fixed root distribution, in contrast, failed to explain the magnitude of water use during parts of the dry season and largely over-estimated root respiration rates. The observed surface soil moisture dynamics were also better reproduced by the optimality-based model than the model based on a prescribed root distribution. The optimality-based approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches, especially for simulating possible responses to environmental change

An optimality-based model of the dynamic feedbacks between natural vegetation and the water balance

The hypothesis that vegetation adapts optimally to its environment gives rise to a novel framework for modeling the interactions between vegetation dynamics and the catchment water balance that does not rely on prior knowledge about the vegetation at a particular site. We present a new model based on this framework that includes a multilayered physically based catchment water balance model and an ecophysiological gas exchange and photosynthesis model. The model uses optimization algorithms to find those static and dynamic vegetation properties that would maximize the net carbon profit under given environmental conditions. The model was tested at a savanna site near Howard Springs (Northern Territory, Australia) by comparing the modeled fluxes and vegetation properties with long-term observations at the site. The results suggest that optimality may be a useful way of approaching the prediction and estimation of vegetation cover, rooting depth, and fluxes such as transpiration and CO2 assimilation in ungauged basins without model calibration

Reasons for Adopting Precision Farming: A Case Study of U.S. Cotton Farmers

We used survey data collected from cotton farmers in 12 southern U.S. states to identify factors influencing cotton farmers’ decisions to adopt precision farming. Using a seemingly unrelated ordered probit model, we found that younger, educated and computer literate farmers chose precision farming for profit reason. Farmers who perceived precision farming to be profitable adopt it to be at the forefront of agricultural technology. We also found that farmers who were concerned with environment emphasize precision farming adoption as a reason to improve environmental quality. Our results also indicate that farmers in coastal states such as Alabama, Mississippi, and North Carolina chose environmental benefits as a reason for precision farming technology adoption.precision technologies, seemingly unrelated ordered probit, cotton, Agricultural Finance, Farm Management, Q16, C35,

Identification of F-box only protein 7 as a negative regulator of NF-kappaB signalling.

The nuclear factor κB (NF-κB) signalling pathway controls important cellular events such as cell proliferation, differentiation, apoptosis and immune responses. Pathway activation occurs rapidly upon TNFα stimulation and is highly dependent on ubiquitination events. Using cytoplasmic to nuclear translocation of the NF-κB transcription factor family member p65 as a read-out, we screened a synthetic siRNA library targeting enzymes involved in ubiquitin conjugation and de-conjugation for modifiers of regulatory ubiquitination events in NF-κB signalling. We identified F-box protein only 7 (FBXO7), a component of Skp, Cullin, F-box (SCF)-ubiquitin ligase complexes, as a negative regulator of NF-κB signalling. F-box protein only 7 binds to, and mediates ubiquitin conjugation to cIAP1 and TRAF2, resulting in decreased RIP1 ubiquitination and lowered NF-κB signalling activity

Making Use of Scenarios for Achieving Effective Use in Community Computing Contexts

The concept of effective use is gaining currency as a way of thinking about usability in community informatics. Broadly defined, effective use is the opportunity and capacity of a community group to leverage information communications technologies (ICTs) in order to achieve their goals. Although effective use is a worthy goal, a process for achieving effective use is not clearly defined. This paper combines the concept of scenarios from human-computer interaction (HCI) and participatory design (PD) in order to identify a design process to enhance participation and technological decision making in community information systems design projects. Our process for achieving effective use focuses first on the efficacy of scenarios as a tool to encourage and support participatory design, and second as an anchoring and adjustment heuristic. This study concludes with future research on effective use in community informatics