This mod attempts to fix all known typos, subtitle mismatches, bad punctuation and other grammatical sloppiness found in the first KotOR game. I'd like to give a huge thanks to Gimmick5000 for discovering the overwhelming majority of these issues while working on his "eXtensive Dialog Overhaul" mod, and Fair Strides for his TLK>TXT tool. Gimmick's "eXtensive" project aims to replace a lot of player responses, though, while this one keeps those as is... sort of. Kainzorus Prime was kind enough to let me use his "PC Response Moderation" as the basis for this mod, which is a massive improvement over Bioware's player responses. If you're interested in Gimmick's dialog overhaul, be sure to follow it here:
Standardisation provides schools with assurance that LA moderation teams have the required knowledge to undertake moderation of key stage 1 (KS1) and key stage 2 (KS2) English writing teacher assessment (TA).
Pc Response Moderation K1
Download: https://shurll.com/2vBLQo
The principle can be stated in two ways, formally different, but substantially equivalent, and, in a sense, mutually 'reciprocal'. The two ways illustrate the Maxwell relations, and the stability of thermodynamic equilibrium according to the second law of thermodynamics, evident as the spread of energy amongst the state variables of the system in response to an imposed change.
The two ways of statement share an 'index' experimental protocol (denoted P i ) , \displaystyle \mathcal P_\mathrm i ), that may be described as 'changed driver, feedback permitted'. Along with the driver change Δ L , \displaystyle \Delta L, it imposes a constant Y , \displaystyle Y, with δ i Y = 0 , \displaystyle \delta _\mathrm i Y=0, and allows the uncontrolled 'moderating' variable response δ i X , \displaystyle \delta _\mathrm i X, along with the 'index' response of interest δ i M . \displaystyle \delta _\mathrm i M.
While well rooted in chemical equilibrium, Le Chatelier's principle can also be used in describing mechanical systems in that a system put under stress will respond in such a way as to reduce or minimize that stress. Moreover, the response will generally be via the mechanism that most easily relieves that stress. Shear pins and other such sacrificial devices are design elements that protect systems against stress applied in undesired manners to relieve it so as to prevent more extensive damage to the entire system, a practical engineering application of Le Chatelier's principle.
A body can also be in a stationary state with non-zero rates of flow and chemical reaction; sometimes the word "equilibrium" is used in reference to such states, though by definition they are not thermodynamic equilibria. Sometimes, it is proposed to consider Le Chatelier's principle for such states. For this exercise, rates of flow and of chemical reaction must be considered. Such rates are not supplied by equilibrium thermodynamics. For such states, it has turned out to be difficult or unfeasible to make valid and very general statements that echo Le Chatelier's principle.[11] Prigogine and Defay demonstrate that such a scenario may or may not exhibit moderation, depending upon exactly what conditions are imposed after the perturbation.[12]
I concluded by running lab measurements of the amplifiers to confirm (or, as it turned out, deny) their power ratings and other specifications according to Texas Instruments guidelines (PDF). I focused on two measurements. The first was frequency response, which measures how evenly an amplifier reproduces sound throughout the audio spectrum. Amps with poor frequency response can make bass sound weak or might make high-frequency instruments such as cymbals sound dull.
In this paper, a meta-analysis is performed in order to quantitatively analyze the body of scholarly work relating to demographic determinants of human behavior in the context of epidemic and pandemic respiratory diseases, specifically avian influenza, swine influenza, Middle East respiratory syndrome (MERS), and severe acute respiratory syndrome (SARS). To our knowledge, no previous study has quantified the direction and magnitude of the relationship between demographic characteristics and protective behavior in the general population in response to respiratory epidemics/pandemics. Potential moderating influences of study characteristics on this relationship are also tested. The results of this analysis will inform decision makers, public health officials, and modelers as to the differing behavioral response by men and women during epidemic and pandemic respiratory disease outbreaks.
For studies that did not include results on the basis of nonsignificance, the primary authors of these publications were contacted requesting results and associated error terms. In the case of nonresponse, missing nonsignificant results were excluded from the analysis. Although missing nonsignificant results may be treated as a perfect null value, meaning an effect size of zero, this approach is adequate only for rejecting the null hypothesis that gender plays no role in behavioral response and not for answering questions about size of effect and effect moderators [15]. Sensitivity analysis was performed to assess whether study results differed if missing nonsignificant results were treated as zeros rather than excluded.
The effect size and confidence interval of each study are indicated by a square and a horizontal line, respectively. The weight of each study in the model is indicated by the size of its square. A log odds ratio of 0, indicated by the dashed reference line, corresponds to no gender difference in behavioral response. Positive log odds ratios correspond to greater behavioral response by females, while negative log odds ratios correspond to greater behavioral response by males. The population mean effect size of the random-effects model incorporating these studies is given by the placement of the diamond, while the horizontal corners of the diamond illustrate the 95% CI of this mean effect size.
The effect size and confidence interval of each study are indicated by a square and a horizontal line, respectively. The weight of each study in the model is indicated by the size of its square. A log odds ratio of 0, indicated by the dashed reference line, corresponds to no gender difference in behavioral response. Positive log odds ratios correspond to greater behavioral response by females, while negative log odds ratios correspond to greater behavioral response by males. The population mean effect size of the random-effects model incorporating these studies is given by the placement of the diamond, while the horizontal corners of the diamond illustrate the 95% CI of this mean effect size. Publications with the same author(s) and year of publication are differentiated by the first word of their title. Publications including multiple studies are denoted by labeling the studies A, B, etc.
In Figs 4 and 5 the distribution of study effect sizes and their corresponding 95% confidence intervals are shown. The dashed reference line, placed at a log odds ratio of 0, corresponds to no gender difference in behavioral response. Studies with squares to the right of the reference line exhibit more female response, while studies with squares to the left of the reference exhibit more male response. The population mean effect size of the random-effects model incorporating these studies is given by the placement of the diamond at the bottom of the figure, while the horizontal corners of the diamond illustrate the 95% CI of this mean effect size.
The random-effects model for pharmaceutical behaviors suggests that men in the general population are slightly (specifically, 12.1%, 95% CI 1.6% to 23.6%) more likely than women to practice and/or increase pharmaceutical health-protective behaviors in the context of epidemics/pandemics. However, nearly all of the variability in the effect size estimates was due to heterogeneity among the true effects, none of which could be accounted for by including moderators. Furthermore, the addition of studies based on the trim-and-fill method rendered the observed relationship non-significant. Although the study design of this meta-analysis limits the danger of publication bias influencing the results, the random-effects model using the filled-in study set implies that if publication bias is indeed present, then it has falsely skewed the results in favor of significance. In spite of this finding, the results of the other sensitivity analyses still favor a mildly positive relationship between male gender and uptake of pharmaceutical behaviors. Of the studies addressing pharmaceutical behaviors for which a direction (but not an effect size) was reported males tended to exhibit more behavioral response than females, but this observed relationship has little value given the small sample size (5 studies).
While no significant moderators were found for the non-pharmaceutical or pharmaceutical study sets, the set of moderators tested in this study was not comprehensive. There are a variety of study-level differences that were not tested as moderators in this analysis, including perceived severity of the disease, demographic characteristics of the study sample other than gender (including mean age, income, education level, minority status, and risk status), and whether the response addressed absolute uptake or increase in uptake of behavior. While the perception of the severity of a disease likely impacts health-protective behavior and may act as a moderator of the relationship we address, we do not have adequate data to create a metric for perceived severity for the publications that did not explicitly report it. Data on the severity of a given epidemic/pandemic respiratory disease outbreak are available in terms of case counts and mortality rates, but data on perceived severity are not so easily obtained. Perceived severity may depend on the proximity of the study population to high-risk areas, news media focus and tone, phase of epidemic/pandemic in which surveys/questionnaires were administered, and a host of other intangibles that extend beyond the scope of this analysis. Similarly, while study-level demographic differences (i.e., one study administering questionnaires to mostly young people, another to mostly old people) could have an effect, there are not enough studies coming from heavily age-skewed demographic groups to make claims about the impact of age (or other demographic differences in study populations) on the relationship between gender and health-protective behavior. 2ff7e9595c
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