Limb position effect identification rules for control characteristics metrics. by Heather E. Williams (4062955)

AFMUC- Restriction Rules. by Shumaila Iqbal (22238550)

“…The aspect threat model is then woven into the base use case model. Similarly, an aspect mitigation model is proposed to specify crosscutting mitigations following the AFMUC restriction rules. …”

Changes in choice representations across rule-based and residual-state decision-making. by R. Becket Ebitz (7841318)

“…This is calculated separately for both residual (red) and rule-based (blue) decisions. Error bars = STE across unique matrix elements, asterisks = significant contrasts in both the example pseudopopulation (all <i>p</i> < 0.001, paired <i>t</i> test) and across pseudopopulations (all <i>p</i> < 0.001, bootstrap test, <b><a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3000951#pbio.3000951.s002" target="_blank">S2 Fig</a></b>). …”

Cell Types and their Rules. by Bryan Shin (17833689)

Evolving flocking in embodied agents based on local and global application of Reynolds’ rules by Rita Parada Ramos (7571939)

“…However, only local, fragmented flocking behaviours tend to evolve when fitness scores are based on the individuals’ conformity to Reynolds’ rules. …”

Changes in choice representations across rule-based and residual-state decision-making across pseudopopulations. by R. Becket Ebitz (7841318)

“…This is calculated separately for both rule-based (blue) and residual (red) decisions. Dots = mean across pseudopopulations, error bars = 95% CI, asterisks = significant contrasts, all <i>p</i> < 0.0001. …”

Cross-validated changes in choice representations across rule-based and residual-state decision-making. by R. Becket Ebitz (7841318)

“…Residual choices that shared a feature were not closer together than choices that did not (mean difference = 0.01, 95% CI = [−0.31, 0.33], <i>p</i> = 0.48). However, rule-based choices that shared a feature were more similar than rule-based choices that did not share a feature (mean difference = 0.97, 95% CI = [0.68, 1.27]). …”

Outcome variables and assignment rules. by Kejun Wu (4800972)

The significant correlations between the selected variables. by Abdullah H. Alenezy (14241611)

Subjects:

Average risk tolerance statistics and the tests of equality comparison between two rules. by Teruko Takada (13977607)

Restrictiveness of AFMUC Restriction Rules. by Shumaila Iqbal (22238550)

“…The aspect threat model is then woven into the base use case model. Similarly, an aspect mitigation model is proposed to specify crosscutting mitigations following the AFMUC restriction rules. …”

Understandability of AFMUC restriction rules. by Shumaila Iqbal (22238550)

“…The aspect threat model is then woven into the base use case model. Similarly, an aspect mitigation model is proposed to specify crosscutting mitigations following the AFMUC restriction rules. …”

Applicability of AFMUC restriction rules. by Shumaila Iqbal (22238550)

“…The aspect threat model is then woven into the base use case model. Similarly, an aspect mitigation model is proposed to specify crosscutting mitigations following the AFMUC restriction rules. …”

Digital intellectual property rules in RTAs. by Zehui Yu (8116910)

“…<div><p>Based on the technology complexity data of bilateral digital service exports of 64 representative economies in the world from 2010 to 2021, this paper uses the gravity model to explore the heterogeneous trade effects of Regional Trade Agreements (RTAs) from the perspective of digital intellectual property rules. …”

Grid with 3x3 cells according to the Rule of Thirds. by Erich Tasser (6469177)

The top 15 association rules from frequent itemsets are sorted by support. by Xuankai Ma (17921454)

Data_Sheet_1_Physiological synchrony in electrodermal activity predicts decreased vigilant attention induced by sleep deprivation.docx by Ivo V. Stuldreher (11897870)

Intra-rater and inter-rater agreement of subjective image quality score. by Min Su Park (744914)

Lipinski Rule of five calculated for the selected compounds by SWISS-ADME. by Saud Almawash (4287541)

Evaluation metric values of the logistic regression model (LR), random forest classifier (RF), and the rule-based algorithm (RB) for each of the sociodemographic characteristics. by Rawan Abulibdeh (19206115)