Table of step height. by Jianbo Jia (717814)

“…Finally, by making corresponding test blocks, it was found that the peak value of forward resistance when the 10.5°test block crossed the steps of 1mm, 2mm and 3mm height decreased by 19.8%, 25.0% and 13.9% respectively, and the mean value decreased by 30.8%, 27.2% and 24.1% respectively, which was close to the simulation results, and verified the accuracy of the finite element analysis results.…”

The well wall step. by Jianbo Jia (717814)

“…Finally, by making corresponding test blocks, it was found that the peak value of forward resistance when the 10.5°test block crossed the steps of 1mm, 2mm and 3mm height decreased by 19.8%, 25.0% and 13.9% respectively, and the mean value decreased by 30.8%, 27.2% and 24.1% respectively, which was close to the simulation results, and verified the accuracy of the finite element analysis results.…”

Different steps of the fabrication process. by Md. Abu Daud (21485629)

Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Decrease in loss during the training process. by Muhammad Idrees (92773)

Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

Descriptive statistics of the mean %MVC values for each stage. by Brienna Eteson (21416834)

Kolmogorov-Smirnov (KS) test for the different parameter value pairs at a 95% confidence level. We tested the null hypothesis for all parameters: The RMSEs obtained for one pair of... by Cyrine Chenaoui (22177098)

This is the data set that we used to reach the conclusions drawn in the manuscript with related metadata and methods. by Farayi Kaseke (19560197)

All TPM values. by Hyuk Sung Yoon (20208672)

Presentation 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Data Sheet 1_Tracking priming-induced language recovery in aphasia with pre-trained language models.zip by Yan Cong (1491478)

Adjustment step size. by Qingnan Ji (22662198)

“…The data undergo preprocessing steps including noise reduction, feature extraction (e.g., Mel Frequency Cepstral Coefficients and keypoint detection), and temporal alignment. …”

Salience of authority-vice phrases by year. by Daniel Hart (440152)

“…Similarly, we anticipated that the salience of phrases consistent with fidelity to members of one’s social group (“allegiance”, “one for all”, <i>loyalty-virtue</i>), would decrease, and those suggestive of social corrosion (“betrays”, “back stabs”, <i>loyalty-vice</i>) would increase. …”

Salience of fear words by year by country. by Daniel Hart (440152)

“…Similarly, we anticipated that the salience of phrases consistent with fidelity to members of one’s social group (“allegiance”, “one for all”, <i>loyalty-virtue</i>), would decrease, and those suggestive of social corrosion (“betrays”, “back stabs”, <i>loyalty-vice</i>) would increase. …”

Salience of authority-virtue phrases by year. by Daniel Hart (440152)

“…Similarly, we anticipated that the salience of phrases consistent with fidelity to members of one’s social group (“allegiance”, “one for all”, <i>loyalty-virtue</i>), would decrease, and those suggestive of social corrosion (“betrays”, “back stabs”, <i>loyalty-vice</i>) would increase. …”

Salience of loyalty-virtue phrases by year. by Daniel Hart (440152)

“…Similarly, we anticipated that the salience of phrases consistent with fidelity to members of one’s social group (“allegiance”, “one for all”, <i>loyalty-virtue</i>), would decrease, and those suggestive of social corrosion (“betrays”, “back stabs”, <i>loyalty-vice</i>) would increase. …”

Salience of loyalty-vice phrases by year. by Daniel Hart (440152)

“…Similarly, we anticipated that the salience of phrases consistent with fidelity to members of one’s social group (“allegiance”, “one for all”, <i>loyalty-virtue</i>), would decrease, and those suggestive of social corrosion (“betrays”, “back stabs”, <i>loyalty-vice</i>) would increase. …”

Salience of vice and virtue by year in U.S. by Daniel Hart (440152)

“…Similarly, we anticipated that the salience of phrases consistent with fidelity to members of one’s social group (“allegiance”, “one for all”, <i>loyalty-virtue</i>), would decrease, and those suggestive of social corrosion (“betrays”, “back stabs”, <i>loyalty-vice</i>) would increase. …”

Characteristic size values. by Junxia Zhou (14381598)