cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
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DOI: 10.1285/i15900932v32n2p135
title: A Note on Groups with Just-Infinite Automorphism Groups

description: An infinite group is said to be just-infinite if all its proper homomorphic images are finite.We investigate the structure of groups whose full automorphism group is just-infinite
DOI: 10.1285/i15900932v32n2p115
title: Weakly normal subgroups and classes of finite groups

description: A subgroup K of a group G is said to be weakly normal in G if Kg NG(K) implies g in NG(K). In this paper we establish certain characterizations of solvable PST-groups using some weakly normal subgroups.
DOI: 10.1285/i15910725v35p61
title: Considerazioni tassonomiche e fitogeografiche su Ophrys Mattinatae, specie nuova del Gargano
DOI: 10.1285/i15910725v35p67
title: Gli olivi monumentali pi� grandi del Salento meridionale

description: It
Lo scopo del seguente lavoro � stato quello di censire tra gli esemplari di olivo (Olea europaea L. ssp. sativa Hoffman  Link) presenti nella campagna del Salento leccese aventi le caratteristiche della monumentalit�, "i pi� grandi tra i grandi", ai fini della tutela degli esemplari, del loro germoplasma e della loro conoscenza. Si riportano per i venti esemplari monumentali censiti, i dati dendrometrici, coordinate geografiche (longitudine e latitudine) espresse in gradi decimali (DD) rilevate con sistema GPS, il paese, la localit�. Sebbene la Regione Puglia abbia emanato la Legge n 14 del 4 giugno 2007 "Tutela e valorizzazione del paesaggio degli olivi monumentali della Puglia", molti olivi presenti in questo lavoro non sono stati ancora censiti.
En
The purpose of this study was to conduct a census of the greatest monumental olive trees present in the countryside of Salento (Lecce) in order to protect. For each tree was measured the circumference of the trunk at ground level, to 1.30 m height, Crown diameter, and height of the tree. The location of the tree is determined by geographical coordinates in decimal degrees (DD). For each tree also shows the country where it grows.
DOI: 10.6073/pasta/28b3096702371ea5fc64d473ec4cb8d1
title: Geomorphology of Ball Creek and Coweeta Creek in 1989
DOI: 10.5066/f7b85653
title: Official Recognized Boundary of Fishers & Farmers Partnership, 2013
DOI: 10.5066/f7tb14xn
title: Official Recognized Boundary of Matanuska Susitna Basin Salmon Habitat Partnership, 2013
DOI: 10.17632/67nwr29ds3.1
title: Infection-related sexual conflict in mating behaviors of wolf spiders

description: Resistance to mating by females has been hypothesized as a tactic to assess potential mates and avoid undesirable ones. Previous studies show infection with the pathogenic bacteria, Pseudomonas aeruginosa, triggers a costly immune response and negatively impacts fitness in the wolf spider Schizocosa ocreata (Hentz 1844). Studies also show that infection can be transmitted during copulation, suggesting there are potential fitness costs associated with mating with an infected individual. We examined impacts of infection on mating interactions of male and female S. ocreata. As studies show infection can be detected through chemical cues, we tested whether males or females avoid mating with infected individuals when given the opportunity. We paired infected and uninfected (control) males and females and recorded their behavior. We found that mating outcome was independent of infection for males and females. While higher male courtship rates and more frequent female receptivity displays were associated with successful mating, we saw no direct effect of infection status on mating outcome. However, among spider pairs that did not mate, females were found to be significantly more resistant and aggressive toward infected males than control males. Male aggression, on the other hand, was greater in pairs that did result in mating. These results suggest sexual conflict in mating can be related to infection status, and that females can recognize infected males and alter their behavior in response.
DOI: 10.34740/kaggle/dsv/7584712
title: Mountain Climbing Accidents Dataset
DOI: 10.17909/rar9-cn43
title: TESS Cycle 1 FFIs for Blazar Variability paper
DOI: 10.34740/kaggle/dsv/7584830
title: BBC News
DOI: 10.25345/c54m91n28
title: MassIVE MSV000094033 - Deep Proteome Turnover of Human iPSC-derived Neurons
title: Proteostasis involves a dynamic network of biological pathways that regulate protein synthesis, maintenance, and degradation. As postmitotic cells, neurons are particularly sensitive to environmental changes, and dysfunction in cellular proteostasis can lead to an accumulation of aggregated and misfolded proteins. However, how proteins turnover on a global scale in human neurons is not well understood. In this study, we systematically improved a dynamic SILAC proteomic approach to enable a deep and accurate measurement of protein turnover in human induced pluripotent stem cell (iPSC)-derived cholinergic spinal motor and glutamatergic cortical neurons. Furthermore, we applied this deep proteome turnover method to evaluate how inhibiting the ubiquitin-proteasome and lysosome-autophagy pathway impacts proteostasis in iPSC-derived neurons. Using these datasets, we developed a freely available resource called Neuron Profile, an interactive website for visualizing and querying protein turnover in subcellular locations in human neurons.
DOI: 10.25346/s6/gcwyhp/7mjyas
title: anes_pilot_2019_questionnaire.pdf

description: Questionnaire Pdf format
DOI: 10.25346/s6/gcwyhp/amtijb
title: anes_pilot_2019.tab

description: Data csv format
DOI: 10.25346/s6/gcwyhp/jdzig9
title: r-notebook-test.ipynb

description: Jupyter notebook with R
DOI: 10.25346/s6/gcwyhp/l6izon
title: anes_pilot_2019-1.tab

description: Spss sav file
DOI: 10.25346/s6/gcwyhp/prxfvg
title: anes_pilot_2019-2.tab

description: Stata config files
DOI: 10.25346/s6/gcwyhp/udityi
title: anes_pilot_2019_userguidecodebook.pdf

description: Codebook Pdf format
DOI: 10.5281/zenodo.10632984
title: Coseismic Surface Ruptures of 20 Strike-Slip Earthquakes Measured from Geodetic Imaging Data

description: Coseismic surface displacement maps for 20 strike-slip surface rupturing earthquakes measured from radar and optical pixel tracking data.
DOI: 10.25346/s6/gcwyhp
title: American National Election Studies: ANES 2019 Pilot Study

description: The ANES 2019 Pilot Study was conducted for the purpose of testing new questions and conducting methodological research to inform the design of the ANES 2020 Time Series study, and to provide public opinion data in December 2019. Much of the content was based on ideas sent by the ANES user community in response to the most recent call for ideas. The 30 minute questionnaire includes questions about voting in 2016 and 2018, validated voter turnout, preferences for the Democratic presidential primaries and vote intentions in 2020, misinformation, and many topical issues including impeachment.
DOI: 10.25346/s6/gcwyhp/aryewj
title: mybinder-python-test-1.ipynb
DOI: 10.25346/s6/gcwyhp/wndqkg
title: anes64-1.tab
DOI: 10.25346/s6/gcwyhp/2gzv6p
title: runtime-1.txt
DOI: 10.25346/s6/gcwyhp/6cgku9
title: mybinder-python-test.ipynb
DOI: 10.25346/s6/gcwyhp/huhkno
title: anes64.csv
DOI: 10.25346/s6/gcwyhp/469cb8
title: runtime.txt

description: For use with mybinder
DOI: 10.5281/zenodo.10032369
title: Categorized Questions Dataset QuBAN

description: This dataset was made for the "A Query-Based Approach to Mitigate the Shortcomings of Widely Used Learning Methods through E-Learning" paper. The dataset contains questions categorized into CIS101 (Introduction to Computer & Research) and CSC203 (Data Structure) course's topics. It also includes the off-topic questions asked by students. All of the questions are scored using the proposed method.
DOI: 10.5281/zenodo.10032375
title: Categorized Questions Dataset QuBAN

description: This dataset was made for the "A Query-Based Approach to Mitigate the Shortcomings of Widely Used Learning Methods through E-Learning" paper. The dataset contains questions categorized into CIS101 (Introduction to Computer & Research) and CSC203 (Data Structure) course's topics. It also includes the off-topic questions asked by students. All of the questions are scored using the proposed method.
DOI: 10.5281/zenodo.10051055
title: Categorized Questions Dataset QuBAN

description: This dataset was made for the "A Query-Based Approach to Mitigate the Shortcomings of Widely Used Learning Methods through E-Learning" paper. The dataset contains questions categorized into CIS101 (Introduction to Computer & Research) and CSC203 (Data Structure) course's topics. It also includes the off-topic questions asked by students. All of the questions are scored using the proposed method.
DOI: 10.5281/zenodo.10032368
title: Categorized Questions Dataset QuBAN

description: This dataset was made for the "A Query-Based Approach to Mitigate the Shortcomings of Widely Used Learning Methods through E-Learning" paper. This Dataset's Version 4 uses an updated algorithm for evaluating questions compared to the previous versions and has all the files separated into different csv files instead of excel sheets.

 

This dataset consists of 4 .csv files -



Data_Structure.csv

2. Introduction_to_Computers_and_Research.csv

3. Irrelevant_Questions.csv.

4. Blooms_Taxonomy.csv


File-1 consists of the scored and categorized questions from the "Data Structure" course.

File-2 consists of the scored and categorized questions from the "Introduction to Computers and Research" course.

File-3 consists of the irrelevant questions which do not belong to the courses above but were asked by the students from those courses.

File-4 consists of the keywords of Bloom's Taxonomy used to evaluate the questions in this dataset.

 

The first 3 files consists of questions asked by students of Independent University, Bangladesh on the Summer 2023 Semester in Computer Science Courses. The last file contains the Bloom's Taxonomy keywords that were used for the question evaluation.

This dataset was created to highlight the usage of AI in educational context. It particularly focuses on questions as our goal was to revive the innate curiosity of students to learn through querying. Computer science (CS) courses have been particularly focused as we found higher dropout rates in CS courses compared to others.

The questions in this dataset have been manually pre-processed and categorized according to their course and topics. They have also been scored using Bloom's taxonomy's six levels of questions [remember (10 points), understand (20 points), apply (20points), analyze (25 points), evaluate (35 points), create (40 points)]. Any question above 100 points is considered a high level question and the maximum attainable score for a single question is 150 points.
DOI: 10.5281/zenodo.10633113
title: Categorized Questions Dataset QuBAN

description: This dataset was made for the "A Query-Based Approach to Mitigate the Shortcomings of Widely Used Learning Methods through E-Learning" paper. This Dataset's Version 4 uses an updated algorithm for evaluating questions compared to the previous versions and has all the files separated into different csv files instead of excel sheets.

 

This dataset consists of 4 .csv files -



Data_Structure.csv

2. Introduction_to_Computers_and_Research.csv

3. Irrelevant_Questions.csv.

4. Blooms_Taxonomy.csv


File-1 consists of the scored and categorized questions from the "Data Structure" course.

File-2 consists of the scored and categorized questions from the "Introduction to Computers and Research" course.

File-3 consists of the irrelevant questions which do not belong to the courses above but were asked by the students from those courses.

File-4 consists of the keywords of Bloom's Taxonomy used to evaluate the questions in this dataset.

 

The first 3 files consists of questions asked by students of Independent University, Bangladesh on the Summer 2023 Semester in Computer Science Courses. The last file contains the Bloom's Taxonomy keywords that were used for the question evaluation.

This dataset was created to highlight the usage of AI in educational context. It particularly focuses on questions as our goal was to revive the innate curiosity of students to learn through querying. Computer science (CS) courses have been particularly focused as we found higher dropout rates in CS courses compared to others.

The questions in this dataset have been manually pre-processed and categorized according to their course and topics. They have also been scored using Bloom's taxonomy's six levels of questions [remember (10 points), understand (20 points), apply (20points), analyze (25 points), evaluate (35 points), create (40 points)]. Any question above 100 points is considered a high level question and the maximum attainable score for a single question is 150 points.