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Neutron activation analysis data of pottery, clay, and sand from Butarincon, Puren-Lumaco, Huitranlebu, and Maicoya, Chile and Huaca Prieta, Peru

Neutron activation analysis data of pottery, clay, and sand from Butarincon, Puren-Lumaco, Huitranlebu, and Maicoya, Araucanína Region, Chile, and Huaca Prieta, La Libertad Department, Peru.

NeuroVox: Bilingual Brain-to-Speech Translation and Neural Activity Detection

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Neutron activation analysis data of pottery and clays from Quillagua, Guatacondo, and other sites in Chile and Argentina

Neutron activation analysis data of pottery and clays from La Poroma, Punta Gualaguala, Hornitos, Michilla, Quillagua, Costa Sur, Desembocadura Loa, Chiu-Chiu, and Calama, Antofagasta Region, Caleta Huelén and Guatacondo, Tarapacá Region, Chile, and Puna, Jujuy Province, Argentina.

opencc-by-4.0May 2024View details →

The joint representation of self-motion and touch in superior colliculus neurons supporting active sensation

Localizing objects using active sensing requires the brain to integrate a map sensory space against an ongoing estimate of body position. While such computations are often ascribed to the cerebral cortex, we examined the midbrain superior colliculus (SC), due to its close relationship with the sensory periphery as well as higher, motor-related brain regions. Using high-density electrophysiology and movement tracking, we discovered that the on-going kinematics of whisker motion and locomotion speed accurately predict the firing rate of mouse SC neurons. Neural activity was best predicted by movements occurring either in the past, present, or future, revealing that the SC population continuously estimates a trajectory of self-motion. Neural selectivity for combinations of kinematic features built an accurate representation of whisker position with high temporal resolution. Half of all self-motion encoding neurons displayed a touch response as an object entered the active whisking field. Trial-to-trial variation in the size of this response was explained by the position of the whisker upon touch. Taken together, these data indicate that SC neurons linearly combine an internal estimate of body movements with external stimulation to enable active tactile localization.

Traversing Chemical Space with Active Deep Learning for Low-data Drug Discovery

Raw and processed data from LitPCBA used in the paper "Traversing Chemical Space with Active Deep Learning for Low-data Drug Discovery"

Neutron activation analysis data of pottery from Carrizales, Mocupe Viejo, Cherrepe, Magdalena de Cao Viejo, and other sites, Peru

Neutron activation analysis data of pottery from Carrizales, Mocupe Viejo, and other sites, Lambayeque Department, and Cherrepe and Magdalena de Cao Viejo, La Libertad Department, Peru.

Active fault surface traces of the southern Alpine Fault Zone, New Zealand

This repository contains detailed, lidar-enabled geomorphic mapping of active fault surface traces assoicated with the southern Alpine Fault Zone in New Zealand.

Neutron activation analysis data of pottery and clays from multiple sites in Argentina, Chile, and Bolivia

Neutron activation analysis data of pottery and clays from Potrero-Chaquiago, Agua Verde, Ingenio del Arenal Medanos, Santa Ana Abajo, Corral Blanco, Catamarca Province, Mancapa, Oloma Bajada, and Quimili Paso, Santiago del Estero Province, La Quiaca Vieja, Pena Blanca, and Yavi Chico, Jujuy Province, Potrero de Payogasta, Cortaderas, and Valdes, Salta Province, Argentina; Koati and Sun Islands, La Paz Department, Bolivia; and Caquena Este, Huaiharani, and Cachicoca, Arica and Parinacota Region, Chile.

Competing commercial catalysts: Unprecedented catalyst activity and stability of Mizoroki-Heck reaction in a continuous packed bed reactor

This dataset contains the measurement data for figures (graphs) published in journal article: Competing commercial catalysts: Unprecedented catalyst activity and stability of Mizoroki-Heck reaction in a continuous packed bed reactor by Nemanja Vucetic, Pasi Virtanen, Andrey Shchukarev, Tapio Salmi and Jyri-Pekka Mikkola Published in: Chemical Engineering Journal, Volume 433, Part 1, 2022, 134432 https://doi.org/10.1016/j.cej.2021.134432

Tuned Bis-Layered Supported Ionic Liquid Catalyst (SILCA) for Competitive Activity in the Heck Reaction of Iodobenzene and Butyl Acrylate

This dataset contains the measurement data for figures (graphs) published in journal article: Tuned Bis-Layered Supported Ionic Liquid Catalyst (SILCA) for Competitive Activity in the Heck Reaction of Iodobenzene and Butyl Acrylate by Nemanja Vucetic, Pasi Virtanen, Ayat Nuri, Andrey Shchukarev, Jyri-Pekka Mikkola, and Tapio Salmi Published in: Catalysts 2020, 10(9), 963  https://doi.org/10.3390/catal10090963

Data for paper: Analysis and control of untemplated DNA polymerase activity for guided synthesis of kilobase-scale DNA sequences

This deposit contains data for the paper entitled: "Analysis and control of untemplated DNA polymerase activity for guided synthesis of kilobase-scale DNA sequences" Contents include: <ul> <li>00_sequencing-metadata.xlsx - Metadata for each sequencing sample.</li> <li>01_raw-fastqs.zip - Raw basecalled FASTQ data.</li> <li>02_clean-fastas.zip - Cleaned FASTA files (removal of adapters and barcode sequences).</li> <li>03_read-statistics.zip - Read statistics for all samples.</li> <li>04_sequence-analysis.zip - Sequence analysis output for all samples.</li> <li>05_qpcr-data.xlsx - qPCR data for all the dNTP mixes studied.</li> <li>06_analysis-scripts.zip - Analysis scripts.</li> </ul>

Local wakefulness-like activity of layer 5 cortex under general anaesthesia [Dataset]

These datasets contain the raw electrophysiology recordings analysed in the article "Local wakefulness-like activity of layer 5 cortex under general anaesthesia". Recordings are stored in MATLAB format (.mat). The sampling frequency of the recordings is 16667 Hz in all cases. Further information can be found in the main article.

Activation and connectivity maps - A chronometric relationship between circuits underlying learning and error monitoring in the basal ganglia and salience network

Activation and connectivity maps of the study "A chronometric relationship between circuits underlying learning and error monitoring in the basal ganglia and salience network". <ul> <li>Error-correct.nii corresponds to the statistical map of group-level differences in BOLD signal between correct and erroneous responses shown in figure 4;</li> <li>Late-initial.nii corresponds to the statistical map of group-level differences in BOLD signal between the initial and late learning periods shown in figure 5;</li> <li>Conn_error-correct_dACC.nii corresponds to the results from the seed-to-voxel gPPI analysis, using the dACC as seed region, showing areas of higher functional connectivity in erroneous compared to correct responses, shown in figure 8.</li> </ul>

opencc-by-4.0Jul 2024View details →

Data for Exploring Inhomogeneous Surfaces: Ti-rich SrTiO3(110) Reconstructions via Active Learning

The archive "supplementary_data.tar.gz" contains structures, training data, training scripts, models and an evolution script obtained and reported in the study: "Exploring Inhomogeneous Surfaces: Ti-rich SrTiO3(110) Reconstructions via Active Learning". See README for more information on the archive content.

Educational data collected from students - regarding the analysis of online activities in schools in Romania (during the Covid-19 pandemic, March 2020 - April 2020)

The student questionnaire was designed with 20 questions. It was completed by 1,088 respondents and focuses on students' experiences related to online education. The collected data provides a broad perspective on various aspects of this, including access to technology, experiences with different platforms, perceptions of the advantages and disadvantages of this form of education, as well as direct feedback from students regarding their experiences. The full questionnaire can be accessed at: <a href="https://forms.gle/fhgzCUx1SDnxbCfZ6" target="_new" rel="noopener">https://forms.gle/fhgzCUx1SDnxbCfZ6</a> To protect the identity of the respondents and to obtain accurate responses, all data collected from teachers was anonymous. We did not collect any personal information whatsoever. This aspect was made clear to the respondents in the description of the questionnaire.

Educational data collected from teachers - for the analysis of online activities in schools in Romania (during the Covid-19 pandemic, March 2020 - April 2020)

The dataset comes from a questionnaire structured into 24 questions, which can be accessed at <a href="https://forms.gle/bUgYMfoNHh7r6ebs6" target="_new" rel="noopener">https://forms.gle/bUgYMfoNHh7r6ebs6</a>. This questionnaire was completed by 956 respondents and aims to analyze the online activities carried out during March - April 2020, being distributed to teachers. Each question is designed to reveal different aspects of the experiences, skills, and perspectives of teaching staff regarding online teaching and learning. To protect the identity of the respondents and to obtain accurate responses, all data collected from teachers was anonymous. We did not collect any personal information whatsoever. This aspect was made clear to the respondents in the description of the questionnaire.

Out-of-Distribution Evaluation of Active Learning Pipelines for Molecular Property Prediction Dataset

Data for the paper "Out-of-Distribution Evaluation of Active Learning Pipelines for Molecular Property Prediction"

Characterization of Patient Activation Among Childhood Cancer Survivors in the St. Jude Lifetime Cohort (SJLIFE)

This dataset corresponds to a manuscript titled "Characterization of Patient Activation Among Childhood Cancer Survivors in the St. Jude Lifetime Cohort (SJLIFE) which can be found in the journal Cancers.

opencc-by-4.0Dec 2022View details →

Table 3 in Phytochemical characterization, and antioxidant and antibacterial activities of the hydroethanolic extract of Anadenanthera peregrina stem bark

Table 3. Diameter of the inhibitory zone of the hydroethanolic extract of Anadenanthera peregrina stem bark against Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922).<table><tbody><tr><th></th><th>A. peregrina extract concentration</th><th></th><th></th></tr></tbody><tbody><tr><th>Strain</th><td></td><td></td><td></td><td>C +</td><td>C -</td></tr><tr><th></th><td>50 µL</td><td>100 µL</td><td>200 µL</td><td></td><td></td></tr><tr><th>E. coli</th><td>-</td><td>-</td><td>-</td><td>29 mm</td><td>-</td></tr><tr><th>S. aureus</th><td>10 mm</td><td>16 mm</td><td>20 mm</td><td>35 mm</td><td>-</td></tr></tbody></table>