Mean and standard error of pupil diameter in the dim states. by Tomoe Hayakawa (20978784)

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Penalty conversions yield large practical decreases, but robustness and generalizability of result are limited by data quality and sample selection. by Ryan J. Treves (13527735)

NSC population and proliferation decrease drastically during the second postnatal week of DG development. by Cristina Medina-Menéndez (21800157)

Mean and standard error of sensory properties. by Tomoe Hayakawa (20978784)

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The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. by Gui Araujo (22170819)

“…When they stop being introduced in further assembly events (i.e. introduced species do not carry any mutualistic interactions), their proportion slowly decreases with successive invasions. (B) Even though higher proportions of mutualism promote higher richness, introducing this type of interaction into already assembled large communities promotes a sudden drop in richness, while stopping mutualism promotes a slight boost in richness increase. …”

Participant demographics. * P-values were determined using Fisher-Freeman-Halton test when contingency tables are larger than 2 × 2. by Elie Mulhem (22537863)

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Regional contemporary (1990–1999 mean) precipitation and JULES inundation fraction over the Amazon basin. by Nic Gedney (19762301)

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<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

“…<p dir="ltr">The CSV file 'Eyreetal_DrainingVein_SourceData' contains the averaged time series traces and extracted metrics from individual experiments used across Figures 1-5 in the manuscript "Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins". The following acronyms included in the CSV file are defined as follows: Hbt is total hemoglobin, Art is artery region, DV is draining vein region, WV is whisker vein region, SEM is standard error mean, TS is time series, max peak is maximum peak, min peak is minima, AUC is area under the curve, WT is wild-type, AD is Alzheimer's disease, ATH is atherosclerosis and MIX is mixed AD/atherosclerosis. …”

Water Withdrawal and Consumption Trends for Thermoelectric-Power Plants in the Conterminous United States, 2008–2020 by Kenneth D. Skinner (22280459)

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Large state-wide variation (8.6-fold) in number of clozapine prescriptions per thousand Medicare Part D enrollees in 2018 ^a indicates ≥1.50 SD (17.9) from the mean (32.9... by Luke R. Cavanah (19022435)

Large state-wide variation (11.1-fold) in number of clozapine prescriptions per thousand Medicare Part D enrollees in 2015 ^a indicates ≥1.50 SD (20.2) from the mean (36.... by Luke R. Cavanah (19022435)

Large state-wide variation (8.6-fold) in number of clozapine prescriptions per thousand Medicare Part D enrollees in 2017 ^a indicates ≥1.50 SD (18.0) from the mean (33.1... by Luke R. Cavanah (19022435)

Large state-wide variation (8.5-fold) in number of clozapine prescriptions per thousand Medicare Part D enrollees in 2019 ^a indicates ≥1.50 SD (16.8) from the mean (31.0... by Luke R. Cavanah (19022435)

Large state-wide variation (8.6-fold) in number of clozapine prescriptions per thousand Medicare Part D enrollees in 2020 ^a indicates ≥1.50 SD (16.0) from the mean (29.9... by Luke R. Cavanah (19022435)

Large state-wide variation (10.2-fold) in number of clozapine prescriptions per thousand Medicare Part D enrollees in 2016 ^a indicates ≥1.50 SD (19.2) from the mean (34.... by Luke R. Cavanah (19022435)

Label distributions across mental states and dataset splits. by Thierry Jean (20691795)

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State transition dynamics of reputation considering third-order information and multiple reputation values: by Hitoshi Yamamoto (738861)

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Modelled policy outcomes, with posterior values for individual nodes ranked from 1-5 across the parties - Green, Reform UK, Liberal Democrat, Conservative, and Labour, where 1 is the lowest rank and 5 is the highest. The parties are ranked for each policy node in the network (e.g., income tax), based on the direction of change (“performance indicator”) stated in the first column (e.g., lowest, highest, most, improvement). For example, a value of 5 for Green tax means that green tax is lowest under Reform UK’s policies, while a value of 1 means that green tax is highest under the Green Party’s policies. Larger text in bold and italic font indicates that the directional change (i.e., increase or decrease) of a node under a party’s policies is consistent with the direction indicated, whereas black text indicates an opposite directional change (e.g., income tax is predicted to decrease under Reform UK in alignment with the performance indicator, and increase under Green and Labour). by Richard Stafford (174326)

“…Larger text in bold and italic font indicates that the directional change (i.e., increase or decrease) of a node under a party’s policies is consistent with the direction indicated, whereas black text indicates an opposite directional change (e.g., income tax is predicted to decrease under Reform UK in alignment with the performance indicator, and increase under Green and Labour).…”

Dynamic system state in demand scenarios 2. by Bin Zhao (276445)

“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”

Dynamic system state in demand scenarios 3. by Bin Zhao (276445)

“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”