The branch-site test of positive selection is surprisingly robust but lacks power under synonymous substitution saturation and variation in GC

Positive selection is widely estimated from protein coding sequence alignments by the nonsynonymous-to-synonymous ratio omega. Increasingly elaborate codon models are used in a likelihood framework for this estimation. Although there is widespread concern about the robustness of the estimation of the omega ratio, more efforts are needed to estimate this robustness, especially in the context of complex models. Here, we focused on the branch-site codon model. We investigated its robustness on a large set of simulated data. First, we investigated the impact of sequence divergence. We found evidence of underestimation of the synonymous substitution rate for values as small as 0.5, with a slight increase in false positives for the branch-site test. When dS increases further, underestimation of dS is worse, but false positives decrease. Interestingly, the detection of true positives follows a similar distribution, with a maximum for intermediary values of dS. Thus, high dS is more of a concern for a loss of power (false negatives) than for false positives of the test. Second, we investigated the impact of GC content. We showed that there is no significant difference of false positives between high GC (up to similar to 80%) and low GC (similar to 30%) genes. Moreover, neither shifts of GC content on a specific branch nor major shifts in GC along the gene sequence generate many false positives. Our results confirm that the branch-site is a very conservative test.

Height distributions of Scots pine sapling stands affected by retained tree and edge stand competition

Abstract

Finite mixture analysis of beauty-contest data using generalised beta distributions

This paper introduces a mixture model based on the beta distribution, without preestablishedmeans and variances, to analyze a large set of Beauty-Contest data obtainedfrom diverse groups of experiments (Bosch-Domenech et al. 2002). This model gives a bettert of the experimental data, and more precision to the hypothesis that a large proportionof individuals follow a common pattern of reasoning, described as iterated best reply (degenerate),than mixture models based on the normal distribution. The analysis shows thatthe means of the distributions across the groups of experiments are pretty stable, while theproportions of choices at dierent levels of reasoning vary across groups.

On an asymptotic formula for the maximum voltage drop in a on-chip power distribution network

We present a new asymptotic formula for the maximum static voltage in a simplified model for on-chip power distribution networks of array bonded integrated circuits. In this model the voltage is the solution of a Poisson equation in an infinite planar domain whose boundary is an array of circular pads of radius ", and we deal with the singular limit Ɛ → 0 case. In comparison with approximations that appear in the electronic engineering literature, our formula is more complete since we have obtained terms up to order Ɛ15. A procedure will be presented to compute all the successive terms, which can be interpreted as using multipole solutions of equations involving spatial derivatives of functions. To deduce the formula we use the method of matched asymptotic expansions. Our results are completely analytical and we make an extensive use of special functions and of the Gauss constant G

Expanding Combined Heat and Power in Iowa, October 2015

Combined Heat and Power (CHP) refers to the onsite production of electricity and thermal energy from the same fuel source. Integrating power and thermal energy production is more efficient than separate generating systems and used in the right situation can yield several benefits.

Combined Heat and Power Resource Guide, December 2015

Combined Heat and Power (CHP) refers to the onsite production of electricity and thermal energy from the same fuel source. Integrating power and thermal energy production is more efficient than separate generating systems and used in the right situation can yield several benefits.

Financial Power of Attorney

A financial power of attorney (FPOA) is a document authorizing someone else (an agent) to manage your finances on your behalf if you (the principal) become incapacitated and are unable to make financial management decisions for yourself. If you become unable to decide for yourself and you have not prepared a financial power of attorney, a court proceeding will likely be required before a loved one will be able to assume authority over at least some of your financial affairs. Your FPOA can be drafted to go into effect as soon as you sign it or it can become effective at a later date or only in the case that a physician certifies that you have become incapacitated.

Healthcare Power of Attorney

A health care power of attorney (HC-POA) is a document authorizing an attorney-in-fact (your designated agent) to make health care decisions on your behalf if you (the principal) are unable, in the judgment of your attending physician, to make health care decisions. Health care is defined as any care, treatment, service or procedure required to maintain, diagnose or treat a physical or mental condition. Through your HC-POA, you may authorize someone else to consent, refuse or withdraw consent to health care on your behalf. The attorney-in-fact is permitted to make only health care-related decisions on your behalf. In exercising this authority, the attorney-in-fact must act consistently with your desires (as stated in the HC-POA document).

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Health Care Power of Attorney FAQs

A health care power of attorney (HC-POA) is a document authorizing an attorney-in-fact (your designated agent) to make health care decisions on your behalf if you (the principal) are unable, in the judgment of your attending physician, to make health care decisions. Health care is defined as any care, treatment, service or procedure required to maintain, diagnose or treat a physical or mental condition. Through your HC-POA, you may authorize someone else to consent, refuse or withdraw consent to health care on your behalf.

Calibrating predicted tree diameter distributions in Catalonia, Spain

Abstract

Accuracy of indirect estimation of power output from uphill performance in cycling.

PURPOSE: To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. METHODS: Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. RESULTS: Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. CONCLUSIONS: Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.

The Internet as an enhancer of the consumers' empowerment - A power to be managed by online firms?

Abstract.

Prediction of plant species distributions across six millennia.

The usefulness of species distribution models (SDMs) in predicting impacts of climate change on biodiversity is difficult to assess because changes in species ranges may take decades or centuries to occur. One alternative way to evaluate the predictive ability of SDMs across time is to compare their predictions with data on past species distributions. We use data on plant distributions, fossil pollen and current and mid-Holocene climate to test the ability of SDMs to predict past climate-change impacts. We find that species showing little change in the estimated position of their realized niche, with resulting good model performance, tend to be dominant competitors for light. Different mechanisms appear to be responsible for among-species differences in model performance. Confidence in predictions of the impacts of climate change could be improved by selecting species with characteristics that suggest little change is expected in the relationships between species occurrence and climate patterns.

Report on theorerical results of power generation and conversion

Experimental results of a new controller able to support bidirectional power flow in a full-bridge rectifier with boost-like topology are obtained. The controller is computed using port Hamiltonian passivity techniques for a suitable generalized state space averaging truncation system, which transforms the control objectives, namely constant output voltage dc-bus and unity input power factor, into a regulation problem. Simulation results for the full system show the essential correctness of the simplifications introduced to obtain the controller, although some small experimental discrepancies point to several aspects that need further improvement.