Intercomparison of methods of coupling between convection and large-scale circulation: 1. Comparison over uniform surface conditions

As part of an international intercomparison project, a set of single column models (SCMs) and cloud-resolving models (CRMs) are run under the weak temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistent implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics. CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large-scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation. When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations.

Evaluation of positioning error-induced pixel shifts on satellite linear push-broom imagery

Georeferencing is one of the major tasks of satellite-borne remote sensing. Compared to traditional indirect methods, direct georeferencing through a Global Positioning System/inertial navigation system requires fewer and simpler steps to obtain exterior orientation parameters of remotely sensed images. However, the pixel shift caused by geographic positioning error, which is generally derived from boresight angle as well as terrain topography variation, can have a great impact on the precision of georeferencing. The distribution of pixel shifts introduced by the positioning error on a satellite linear push-broom image is quantitatively analyzed. We use the variation of the object space coordinate to simulate different kinds of positioning errors and terrain topography. Then a total differential method was applied to establish a rigorous sensor model in order to mathematically obtain the relationship between pixel shift and positioning error. Finally, two simulation experiments are conducted using the imaging parameters of Chang’ E-1 satellite to evaluate two different kinds of positioning errors. The experimental results have shown that with the experimental parameters, the maximum pixel shift could reach 1.74 pixels. The proposed approach can be extended to a generic application for imaging error modeling in remote sensing with terrain variation.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Edible oil from Tiger nut (Cyperus esculentus L.): mechanical pressing and aqueous enzymatic extraction methods

The tiger nut tuber of the Cyperus esculentus L. plant is an unusual storage system with similar amounts of starch and lipid. The extraction of its oil employing both mechanical pressing and aqueous enzymatic extraction (AEE) methods was investigated and an examination of the resulting products was carried out. The effects of particle size and moisture content of the tuber on the yield of tiger nut oil with pressing were initially studied. Smaller particles were found to enhance oil yields while a range of moisture content was observed to favour higher oil yields. When samples were first subjected to high pressures up to 700 MPa before pressing at 38 MPa there was no increase in the oil yields. Ground samples incubated with a mixture of α- Amylase, Alcalase, and Viscozyme (a mixture of cell wall degrading enzyme) as a pre-treatment, increased oil yield by pressing and 90% of oil was recovered as a result. When aqueous enzymatic extraction was carried out on ground samples, the use of α- Amylase, Alcalase, and Celluclast independently improved extraction oil yields compared to oil extraction without enzymes by 34.5, 23.4 and 14.7% respectively. A mixture of the three enzymes further augmented the oil yield and different operational factors were individually studied for their effects on the process. These include time, total mixed enzyme concentration, linear agitation speed, and solid-liquid ratio. The largest oil yields were obtained with a solid-liquid ratio of 1:6, mixed enzyme concentration of 1% (w/w) and 6 h incubation time although the longer time allowed for the formation of an emulsion. Using stationary samples during incubation surprisingly gave the highest oil yields, and this was observed to be as a result of gravity separation occurring during agitation. Furthermore, the use of high pressure processing up to 300 MPa as a pre-treatment enhanced oil yields but additional pressure increments had a detrimental effect. The quality of oils recovered from both mechanical and aqueous enzymatic extraction based on the percentage free fatty acid (% FFA) and peroxide values (PV) all reflected the good stabilities of the oils with the highest % FFA of 1.8 and PV of 1.7. The fatty acid profiles of all oils also remained unchanged. The level of tocopherols in oils were enhanced with both enzyme aided pressing (EAP) and high pressure processing before AEE. Analysis on the residual meals revealed DP 3 and DP 4 oligosaccharides present in EAP samples but these would require further assessment on their identity and quality.