Simulations Clause Samples

Simulations. The simulated proporuon of subjects with peak-and trough levels within the target range are displayed in Figure 6. Applying tdm using saliva led to a higher percentage of sub- jects reaching target aчainment compared to no tdm (>75% vs 48%, respecuvely). How- ever, saliva tdm led to a lower percentage of target aчainment compared to blood tdm. Obtaining more than four samples for saliva tdm did not result in increased tdm per- formance. On the contrary, obtaining addiuonal samples at 18h and 1h pre-dose led to a slightly decreased performance (-3% and -4%, respecuvely) compared to the strategy using four samples.

Simulations. Providing formative and summative evaluations.

Simulations. CUSTOMER shall perform the pre-layout simulation and post-layout simulation and release to HSA for delivery to FOUNDRY, a GDSII formatted data base tape conforming to FOUNDRY process design rules and which is subject to acceptance by FOUNDRY. FOUNDRY shall perform design rule checks (“DRC”) on the CUSTOMER database. Should the CUSTOMER database have design rule (DRC) errors, those errors shall be reported in writing and the data base tape shall be returned to CUSTOMER for correction. Upon completion of an error free design rules check, written authorization of the CUSTOMER and the written acceptance of HSA and FOUNDRY, FOUNDRY shall release the data base for fabrication of Prototypes.

Simulations. Four facilities, all motion-based generic simulators with six degree of freedom, were involved in ARISTOTEL (see Figure 2): two for fixed wing research - FS-102 simulator at TsaGI and GRACE (Generic Research Aircraft Cockpit Environment) at NLR – and two for rotorcraft research - ▇▇▇▇▇▇ (Simulation Motion and Navigation Technologies) Research Simulator at Delft University and HELIFLIGHT-R at The Bibby flight simulation facility at the University of Liverpool. First simulator tests were performed in March 2012 and the results are under analysis. The use of multiple simulation facilities brings with it a number of advantages: • The occurrence of A/RPCs is greatly dependent on the evaluation pilot, his or her training and instructions and the evaluation task the pilot is asked to perform. Simulators can be used to explore different approaches and assess their effectiveness in predicting A/RPC events. • A simulator‟s level of fidelity influences its ability to reliably predict A/RPC occurrences. Accuracy of the mathematical model, realism of the control feel system, quality of visual and vestibular cues all play a role in shaping the pilot‟s behaviour. A systematic study to identify the relative importance of these aspects, as well as the development of guidelines for adjusting a simulator‟s characteristics, can help A/RPC researchers focus their efforts on tuning their simulator in ways that maximize the accuracy of RPC predictions. The project involves also biodynamic tests. Trials have taken place in February and July 2011 (▇▇▇▇▇▇ and HELIFLIGHT-R) and April 2011 (FS-102). The goal of these biodynamic tests is to understand what particular helicopter vibrations induce adverse biodynamic couplings (BDC) effects and what mission tasks are more prone to such effects. For helicopters, the results revealed some important conclusions, for example: • BDC depends on the control tasks: for the different control tasks (i.e., different neuromuscular settings), a different level of BDC was measured; • BDC depends also on the control (disturbance) axis: the highest level of BDC is measured in sway direction, followed by the surge direction. The least amount of BDC is measured in the heave direction. This demonstrates that the biodynamic couplings (coming only from neuromuscular adaptation in this experiment) depend not only on more obvious features such as pilot weight and posture (which can vary from pilot to pilot) but also on more elusive factors such as pilot worklo...

Simulations. For P. molurus movement simulations, each individual was assigned a random home range center within 7 km (A = 14 km) of a linear road bisecting a uniform landscape. This landscape size was selected to ensure that the model had a high likelihood of simulating all snakes with a chance to cross the road; using A = 14 km, snakes had a less than 0.005% chance of crossing a road from that distance if the snake moved directly toward the road. Each time step was considered two days, and each simulation was run for 31 steps. We calculated the proportion of snakes that crossed the road on the 31st time step of the simulation to estimate probability over each two day step, and then divided by 18 h (assuming all road crossing activity occurs within an 9 h period each night) to calculate hourly individual road crossing probability (ρ). We simulated the movement of snakes under different movement scenarios. For each replicate simulation, we specified the following movement parameters: mean vector length (parameter defining turning angle distribution), strength of bias in response to road or home range center, and mean step size. Mean step size was a measure of the net distance a snake moved per day on average; this was parameterized using only daily relocations from the radiotelemetry data. The radiotelemetric data in our case study included limited numbers of road crossings, and thus we were unable to precisely parameterize the road bias component of our model. We therefore simulated a range of possible values for road bias, including both road avoidance and road attraction, and explored the sensitivity of our model output to assumptions about road behavior. The road bias parameter as defined in our model ranged from ‐0.3 to .3. A road bias value of 0 indicated that the snake biased its movement toward the home range center and displayed no behavioral response to the road. We considered this scenario our ‘null’ road bias scenario. A road bias value of 0.1 indicated that the snake biased its movement 10% toward the road and 90% toward the home range center. Similarly, a road bias value of ‐0.1 indicated that the snake biased its movement 10% away from the road and 90% toward the home range center. The mean vector length was a measure of the straightness of a snake’s movement path – a mean vector length of 0 indicates a fully random walk and a mean vector length of 1 indicates a completely straight movement path (100% probability of turning 0 degrees). We explored the se...

Simulations. Information established from another vessel of similar power, rudder, propeller, and hull form, or

Simulations. We use a modified version of the N-body/TreePM/SPH code GADGET-2 (Springel 2005) to perform a suite of cosmological SPH simulations including radiative cooling. The initial particle positions and velocities are obtained from glass-like initial conditions using CMBFAST (version 4.1; ▇▇▇▇▇▇ & Zaldarriaga 1996) and employing the Zeldovich approx- imation to linearly evolve the particles down to redshift z = 127. We assume a flat ΛCDM universe and employ the set of cosmological parameters [Ωm, Ωb, ΩΛ, σ8, ns, h] given by [0.258, 0.0441, 0.742, 0.796, 0.963, 0.719], in agreement with the WMAP 5-year observations (Komatsu et al. 2008). For comparison, we also perform some simulations employing the set of cosmo- logical parameters [0.238, 0.0418, 0.762, 0.74, 0.951, 0.73] and [0.25, 0.045, 0.75, 0.9, 1, 0.73], consistent with WMAP 3-year (▇▇▇▇▇▇▇ et al. 2007) and WMAP 1-year (▇▇▇▇▇▇▇ et al. 2003) ob- servations, respectively. Data is generated at 50 equally spaced redshifts between z = 20 and z = 6. The parameters of the simulations employed for the present work are summarised in Table 2.1. H −1 −3 3 −3 ∗ γeff ∗ The gravitational forces are softened over a length of 1/25 of the mean dark matter inter- particle distance. We employ the star formation recipe of Schaye & Dalla Vecchia (2008), to which we refer the reader for details. Briefly, gas with densities exceeding the critical den- sity for the onset of the thermo-gravitational instability (hydrogen number densities nH = 10−2 − 10−1 cm−3) is expected to be multiphase and star-forming (Schaye 2004). We there- fore impose an effective equation of state (EoS) with pressure P ∝ ρ for densities nH > n , H where n∗ ≡ 10 cm , normalised to P/k = 10 cm K at the critical density nH. We use γeff = 4/3 for which both the Jeans mass and the ratio of the Jeans length and the SPH kernel are independent of the density, thus preventing spurious fragmentation due to a lack of numer- ical resolution. Gas on the effective EoS is allowed to form stars using a pressure-dependent rate that reproduces the observed ▇▇▇▇▇▇▇▇▇-▇▇▇▇▇▇▇ law (▇▇▇▇▇▇▇▇▇ 1998), renormalised by a factor2 of 1/1.65 to account for the fact that it assumes a Salpeter IMF whereas we are using a Chabrier IMF. 2This conversion factor between SFRs has been computed using the Bruzual & ▇▇▇▇▇▇▇ (2003) population syn- thesis code for model galaxies of age > 10 yr forming stars at a constant rate and is insensitive to the assumed metallicity.

Simulations. We define “backtests” and “paper traders” as simulations.  Open Gekko is collecting the market and exchange rate data used in all simulations:  The raw market and exchange rate data is downloaded directly from the exchanges. The correctness of this data is the responsibility of the exchange in question.  Open Gekko is used to aggregate this data into various summarized forms such as can- dles. Open Gekko is responsible for correctly aggregating this data.  Open Gekko is running the simulations: o The simulations are completed using a limited set of market data, as such the results are a proximation. Read here more (todo: link) on what this means. o Gekko Plus is not responsible for any discrepancies in the results of the simulations. Ei- ther due to bugs or due to the limited input described above.

Simulations. The AICPA has also announced a new type of TBS called Document Review Simulation (DRS), which is tested on the AUD, REG and FAR exam sections. As of now, this is the only significant CPA Exam change that affected the exam prior to Q2 of 2017. DRSs test candidates’ Application skills, and evolve to test Evaluation and Analysis. The purpose of these new simulation questions is to increase the authenticity of the CPA Exam by testing real-life tasks performed by CPAs. In short, candidates are required to reference documents, such as legal letters, phone conversation transcripts, and authoritative literature to discern what is and is not important. CURRENT 60% MCQ 40% TBS 85% MCQ 15% WC 60% MCQ 40% TBS 60% MCQ 40% TBS 2017 50% MCQ 50% TBS 50% MCQ 35% TBS 15% WC 50% MCQ 50% TBS 50% MCQ 50% TBS The chart below shows the changes in question type on the 2017 CPA Exam.