Mean reaction time (RTs; in ms) followed by the Standard Error of the Mean (SEM) and mean proportion of errors (ERR; in %) followed by standard deviation (SD), depicted separately for same and switched additions (+) and subtractions (−), for the original symbol-switching task (from Experiment 1), the symbol-switching task with letters (from Experiment 2), and the stimulus offset condition from Experiment 2, where the letters offset upon response (Fast Offset).

Different lowercase letters indicate significant differences among four study sites.

This dataset tracks annual math proficiency from 2011 to 2022 for Academy For Character Education vs. Oregon and South Lane SD 45j3 School District

This data set includes 956 polygons labeled with a sensitivity-unit code that represents the sensitivity of ground water to contamination in Lawrence County, SD. This data set is a result of a larger work (WRIR 00-4103 cited above), which includes a paper plate titled: "Map showing sensitivity of ground-water to contamination in Lawrence County, South Dakota." This data set is part of the digital data that was used to create that map. The sensitivity-unit code is an attribute that consists of a letter followed by three numerical digits, which characterizes sensitivity to contamination. Letter codes that begin with upper case letters (A-Z) and continue with lower case letters (a-s) represent characteristics of the rock and sediments, with 'A' being most sensitive and 's' being least sensitive. The first digit represents recharge rate with 1 being the most sensitive and 4 the least sensitive. Three quantitative categories (1-3) and two qualitative categories (4,5) represent depth to water. Groups 1 through 3 represent areas where data was available to estimate depth-to-water with 1 most sensitive and 3 least sensitive. Qualitative categories 4 and 5 represent areas that only can be compared to each other with 4 being the most sensitive. The third digit represents land-surface slope with 1 being the most sensitive and 5 being the least sensitive. An additional attribute, hydrologic setting, represents areas with common hydrologic characteristics. These 11 hydrologic settings are represented by a letter code symbol. The process step section below describes the attributes in more detail and how the attributes were developed from source data. The source data includes digital maps that characterize the geology, precipitation distribution, and water levels, which have been compiled at 1:100,000 scale and published in 1999 and 2000 as part of the Black Hills Hydrology Study. USGS Digital elevation models were used to describe land-surface altitudes. This data set has been archived at the USGS Water Resources National Spatial Data Information Node.

This dataset tracks annual hispanic student percentage from 2009 to 2023 for Academy For Character Education vs. Oregon and South Lane SD 45j3 School District

An Open Context "subjects" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Region" record is part of the "Open Context" data publication.

Version 10.0 (Alaska, Hawaii and Puerto Rico added) of these data are part of a larger U.S. Geological Survey (USGS) project to develop an updated geospatial database of mines, mineral deposits, and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, have been digitized from the 7.5-minute (1:24,000, 1:25,000-scale; and 1:10,000, 1:20,000 and 1:30,000-scale in Puerto Rico only) and the 15-minute (1:48,000 and 1:62,500-scale; 1:63,360-scale in Alaska only) archive of the USGS Historical Topographic Map Collection (HTMC), or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. The compilation of 725,690 point and polygon mine symbols from approximately 106,350 maps across 50 states, the Commonwealth of Puerto Rico (PR) and the District of Columbia (DC) has been completed: Alabama (AL), Alaska (AK), Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Connecticut (CT), Delaware (DE), Florida (FL), Georgia (GA), Hawaii (HI), Idaho (ID), Illinois (IL), Indiana (IN), Iowa (IA), Kansas (KS), Kentucky (KY), Louisiana (LA), Maine (ME), Maryland (MD), Massachusetts (MA), Michigan (MI), Minnesota (MN), Mississippi (MS), Missouri (MO), Montana (MT), Nebraska (NE), Nevada (NV), New Hampshire (NH), New Jersey (NJ), New Mexico (NM), New York (NY), North Carolina (NC), North Dakota (ND), Ohio (OH), Oklahoma (OK), Oregon (OR), Pennsylvania (PA), Rhode Island (RI), South Carolina (SC), South Dakota (SD), Tennessee (TN), Texas (TX), Utah (UT), Vermont (VT), Virginia (VA), Washington (WA), West Virginia (WV), Wisconsin (WI), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the U.S., but an approximate timeline of when these activities occurred. These data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. These data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.Datasets were developed by the U.S. Geological Survey Geology, Geophysics, and Geochemistry Science Center (GGGSC). Compilation work was completed by USGS National Association of Geoscience Teachers (NAGT) interns: Emma L. Boardman-Larson, Grayce M. Gibbs, William R. Gnesda, Montana E. Hauke, Jacob D. Melendez, Amanda L. Ringer, and Alex J. Schwarz; USGS student contractors: Margaret B. Hammond, Germán Schmeda, Patrick C. Scott, Tyler Reyes, Morgan Mullins, Thomas Carroll, Margaret Brantley, and Logan Barrett; and by USGS personnel Virgil S. Alfred, Damon Bickerstaff, E.G. Boyce, Madelyn E. Eysel, Stuart A. Giles, Autumn L. Helfrich, Alan A. Hurlbert, Cheryl L. Novakovich, Sophia J. Pinter, and Andrew F. Smith.USMIN project website: https://www.usgs.gov/USMIN

Source: German Socio-Economic Panel, pooled data for 2006 and 2012. Abbreviations: SDT—Symbol-Digit Test (cognition); PCS—composite score physical health; MCS—composite score mental health. The PCS, MCS, and SDT scores have been z-standardized with a mean of 50 and a SD of 10.Sample Characteristics.

This dataset tracks annual reading and language arts proficiency from 2011 to 2022 for Academy For Character Education vs. Oregon and South Lane SD 45j3 School District

Sample: Women and men aged 50–90, longitudinal sample for 2006 and 2012 waves. The sample excludes those giving oral responses in 2006. Change score = score in 2012 minus the score in 2006 for the same individual. Abbreviations: PF = physical functioning, MH = mental health, SDT = Symbol-Digit Test (cognition). The change score analysis draws on these SF-12 sub-dimensions instead of the composite indicators PCS and MCS, because the latter are orthogonal by construction, inducing a negative correlation of the change scores [48].Significance levels*** p

Mean reaction times (RTs; in ms) followed by the Standard Error of the Mean (SEM) and mean proportion of errors (ERR, in %) followed by standard deviation (SD) for same and switched addition (+) and subtraction (−) conditions, listed separately for the arithmetic task and the symbol-identification task of Experiment 1.

Sample: First-time participants in cognitive testing in the SOEP in 2006 or 2012. Population aged 50–90 at the time of interview. Abbreviations: SDT—Symbol-Digit Test (cognition); PCS—composite score physical health; MCS—composite score mental health. The PCS, MCS, and SDT scores have been z-standardized with a mean of 50 and a SD of 10.Significance levels*** p

Comprehensive collection of financial reports and documents for CREATE SD HOLDINGS CO.,LTD (3148)

This dataset tracks annual graduation rate from 2021 to 2022 for Academy For Character Education vs. Oregon and South Lane SD 45j3 School District

Sample: First-time participants in cognitive testing in the SOEP in 2006 or 2012. Population aged 50–90 at the time of interview. Regression analyses run for separate population groups and outcome measures; coefficients show time effects (2012 vs. 2006), controlling for age, age squared, and years of education. Abbreviations: SDT—Symbol-Digit Test (cognition); PCS—composite score physical health; MCS—composite score mental health. The PCS, MCS, and SDT scores have been z-standardized with a mean of 50 and a SD of 10.Significance levels*** p

This dataset tracks annual student-teacher ratio from 2010 to 2023 for Academy For Character Education vs. Oregon and South Lane SD 45j3 School District

The Secure Digital Card Market Report is Segmented by Card Type and Capacity (SD ≤2GB, SDHC 4GB-32GB, SDXC 64GB-2TB, SDUC >2TB), Form Factor (Full-Size SD, Minisd, Microsd), Application (Consumer Electronics, Automotive, Industrial and OT Devices, Security and Surveillance, Medical Devices, Others), Distribution Channel (Offline/Retail, Online/E-commerce), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

An Open Context "subjects" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Site" record is part of the "Digital Index of North American Archaeology, Linking Sites and Literature" data publication.

BackgroundAlthough active research is in progress in the fields of psychology and linguistics on the emotional characteristics of the symbol and meaning of sound itself, since the systematic emotional model is not applied, each researcher uses a subjective concept and acts as an obstacle to the expansion of research. There is a limitation in that it cannot be confirmed whether the sound symbol has universality regardless of cultural differences between different languages.MethodsIn this study, the difference between the arousal and valence of emotions felt toward Hangul phonemes was explored according to consonant and vowel through comparison between Korean and Chinese women. 38 Korean women and 32 Chinese women were recruited, and an online experiment was conducted in which arousal and valence were reported for 42 Hangeul phoneme sound stimuli.ResultsAs a result of comparing the arousal and valence of each group, Koreans showed significantly higher arousal scores than Chinese, and these results showed different differences according to consonant and vowel. In valence, there was a difference between nationalities only according to consonant indicating that Koreans showed lower positivity toward aspirated sounds than Chinese. Through these results, it was confirmed that the emotional meaning of the sound symbol between different languages is different, which can be affected by consonant and vowels.ConclusionThis study identified differences in emotional perception between cultures by using two dimensions of emotions, arousal, and valence, which are systematized for sound symbols, and suggests implications for the relationship between sound symbol and emotions and cultural differences in the future.

This dataset tracks annual asian student percentage from 2012 to 2023 for Academy For Character Education vs. Oregon and South Lane SD 45j3 School District