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4,182 results for “universities”
Database of the assessment of two instructional design variables in verbal reasoning and mathematical reasoning courses from the perspective of a Peruvian pre-university center students
<p>These are the data obtained from 4 evaluations made to a sample of 630 students of a Peruvian pre-university center. First, two study variables were evaluated: teaching sequence compliance and the student's educational need according to the perspective of 315 students of the verbal reasoning course. Second, the same study variables were assessed in the remaining 315 students of the mathematical reasoning course. This information is being used in research to obtain an academic degree and later to make a publication of a scientific article.</p> <p>For the treatment of these data, inferential statistics was used through the software R version 3.4.4 (2018) The R Foundation for Statistical Computing.</p>
Supplementary Material to the PhD Thesis of Luz, Zoneibe (University of Lausanne): Characterizing conodont bioapatite from the Early-Triassic: an analytical and palaeoclimatological approach
<p>The present dataset contains the Supplements cited in the PhD Thesis of Zoneibe Augusto Silva Luz (University of Lausanne), entitled '<em>Characterizing conodont bioapatite from the Early-Triassic: an analytical and palaeoclimatological approach</em>', defended the 29th of June in Lausanne. Three table of contents (TOC) are provided for each of the three thesis chapters. The main thesis is deposited at the Bibliothèque cantonale et universitaire de Lausanne, Section des thèses imprimées et des échanges,and digitally at the SERveur Académique Lausannois (Serval) ().</p> <p>Le présent set de données contient les Suppléments cités dans la thèse de doctorat de Zoneibe Augusto Silva Luz (Université de Lausanne), intitulée 'Characterizing conodont bioapatite from the Early-Triassic : an analytical and palaeoclimatological approach', soutenue le 29 juin à Lausanne. Trois tables des matières (TOC) sont fournies pour chacun des trois chapitres de la thèse. La thèse principale est déposée dans la Bibliothèque cantonale et universitaire de Lausanne, Section des thèses imprimées et des échanges, et électroniquement dans le SERveur Académique Lausannois (Serval) ().</p>
Cartolabe Paris-Saclay University 2000-2022
<p>Cartolabe Paris-Saclay University 2000-2022 dataset is generated using <a href="https://gitlab.inria.fr/cartolabe/cartolabe-data">cartolabe-data</a> with the data extracted from the <a href="https://hal.archives-ouvertes.fr">HAL open archive</a> which stores scholarly documents from all academic fields. We've filtered this dataset to include all articles published by the <a href="https://aurehal.archives-ouvertes.fr/structure/browse/critere/universite+paris+saclay/solR/1/page/1/nbResultPerPage/50/tri/valid/filter/valid/category/institution">valid institutions</a> representing <a href="https://www.universite-paris-saclay.fr">Paris-Saclay University</a> between 2000 and 2022.</p>
Dataset for "Universality of grain boundary phases in fcc metals: Case study on high-angle [111] symmetric tilt grain boundaries"
<p>This repository contains the input files, scripts, and raw data of the simulations for the paper "Universality of grain boundary phases in fcc metals: Case study on high-angle [111] symmetric tilt grain boundaries".</p> <p>This data comprises structures of grain boundaries in high-angle [111] symmetric tilt grain boundaries in fcc metals as modeled by various (M)EAM potentials. Investigations include ground state thermodynamic excess properties, excess free energy calculations under stress or strain and with varying temperature, and related molecular dynamics simulations.</p> <p>See README.md for details.</p>
University campus buildings electrical and thermal demand and generation.
<p>UVTgv has agreed to share data for both generation and consumption profile of their buildings. The load data is provided as one .csv per building and year with 8760 rows each one representing one hourly consumption of the building. The load datasets comprise 2019 and 2020 load data for electricity and heat demand, for the following buildings: ABR, C, ICSTM. The generation profiles provided are for 3 PV installations (generation profile), one solar thermal plant (capacity factor), and a mini-wind turbine (generation profile).</p> <p> </p>
Data set from Fischertechnik Smart Factory Model at University of St.Gallen
<p>This is the data set of IoT data from the Fischertechnik Smart Factory Model deployed at the Institute of Computer Science at the University of St.Gallen. It is used as basis for the interactive identification of process activity executions from the IoT data. The corresponding publication can be found here:</p> <p>Seiger, R., Franceschetti, M., & Weber, B. (2023). An Interactive Method for Detection of Process Activity Executions from IoT Data. <em>Future Internet</em>, <em>15</em>(2), 77.<br> <a href="https://doi.org/10.3390/fi15020077">https://doi.org/10.3390/fi15020077</a></p> <p>The data set contains:</p> <ul> <li><strong>cps_log.txt:</strong> A file of all sensor and actuator readings (in JSON format) from the smart factory during the execution of 3 instances of the storage process and 3 instances of the production process. For visualization, it can be fed line-by-line into an <a href="https://www.influxdata.com/">Influx</a> database and <a href="https://grafana.com/">Grafana</a> can then be used to create visualizations of the data.</li> <li><strong>wfms_log.txt:</strong> A file containing the corresponding event log (in JSON format) recorded and extracted from the <a href="https://camunda.com/">Camunda Platform</a> workflow management system during the execution of the process instances. For visualization, it can be fed line-by-line into an <a href="https://www.influxdata.com/">Influx</a> database and <a href="https://grafana.com/">Grafana</a> can then be used to create visualizations of the data.</li> <li><strong>storage_process.bpmn:</strong> Executable BPMN 2.0 model of the storage process executed in the smart factory model.</li> <li><strong>production_process.bpmn:</strong> Executable BPMN 2.0 model of the storage process executed in the smart factory model.</li> </ul> <p>More details on the systems architecture used to execute the processes and record the data from the smart factory can be found in the follow publication:</p> <p>Ronny Seiger, Lukas Malburg, Barbara Weber, Ralph Bergmann,<br> Integrating process management and event processing in smart factories: A systems architecture and use cases,<br> Journal of Manufacturing Systems, Volume 63, 2022, Pages 575-592, ISSN 0278-6125,<br> <a href="https://doi.org/10.1016/j.jmsy.2022.05.012">https://doi.org/10.1016/j.jmsy.2022.05.012</a></p>
Universal Knowledge Graph Embeddings
<p>The dataset provides embeddings for entities and relations in DBpedia (English) and Wikidata. The two knowledge graphs are first merged using a novel approach that we developed by leveraging the sameAs links between them. Then, we used the state-of-the-art embedding model ConEx to compute embeddings of the merge. Our embeddings are called universal knowledge graph embeddings.</p>
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection
<p>We present the data used in "DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection". It was also used in the conference paper presented in Machine Learning and the Physical Sciences workshop at NeurIPS 2022: "Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection".</p> <p>A plethora of AI methods, has already shown huge promise in increasing quality and speed of work with astronomical datasets, but high complexity of AI methods leads to extraction of dataset-specific non-robust features, which leads to models that cannot work on multiple datasets at the same time. We develop a Universal Domain Adaptation method <em><strong>DeepAstroUDA</strong></em>, capable of performing <strong>semi-supervised domain adaptation, that can be applied to datasets with different data distributions and class overlap</strong>. Extra classes can be present in any of the two datasets, and the method can even be used in the presence of unknown classes. We apply our model to three examples of galaxy morphology classification tasks of different complexities (3-class and 10-class problems), with anomaly detection i.e. in all our experiments we have one extra class in the unlabeled target dataset, which represents our anomaly class.</p> <p> </p> <p><strong>DATA:</strong></p> <p><strong>1) DA across two different data releases of the same survey (LSST 1 and 10 years of observation):</strong> We use data from Ciprijanovic et al. 2022. which can also be found on Zenodoo: <a href="https://zenodo.org/record/5514180#.Y6SM7y-B2_w">https://zenodo.org/record/5514180</a> . Data contains three classes: spiral (0), elliptical (1) and merging galaxies (3, anomaly class).</p> <p><strong>2) DA across two surveys (SDSS and DeCALS): </strong>We create datasets using data and labels from the Galaxy Zoo project. Datasets contain 10 classes (9 known classes present in both SDSS and DeCALS data, and one unknown anomaly class present only in DeCALS data): disturbed (0), merging (1), round smooth (2), cigar shaped smooth (3), barred spiral (4), unbarred tight spiral (5), unbarred loose spiral (6), edge-on without bulge (7), edge-on with bulge (8), lenses (9, unknown anomaly class).</p> <p>SDSS (wide filed): datasets is split into two files - sdss_1.h5, sdss_2.h5</p> <p>DeCALS: decals.zip</p> <p><strong>3) DA between wide and deep observing fields of the same survey (SDSS):</strong> We create datasets using data and labels from the Galaxy Zoo project. Datasets contain same 10 classes as in 2), with the final lens anomaly class being only present in the SDSS deep field.</p> <p>SDSS (wide filed): the same data as in 2)</p> <p>SDSS (Strip 82 deep field): sdss_stripe82.zip</p> <p>All SDSS and DECaLS files contain full datasets (train, validation and test). Exact split that we performed (0.6 : 0.2 : 0.2) can be done using the code that accompanies this publication: <a href="https://github.com/deepskies/DeepAstroUDA">https://github.com/deepskies/DeepAstroUDA</a> .</p>
helwan university
<p>No description provided.</p>
BIGG universal model in COBRAPY format
<p>This provides the BIGG universal model in COBRAPY JSON format. The notebook for conversion is provided along with the converted model as well.</p>
Analytical Center of University Cultural Productions in the Context of the Conflict (caPAZ) - Temporality
<p>This dataset comprises a collection of journalistic articles written by young university students in Colombia, which is a product of the project: Analytical Center of University Cultural Productions in the Context of the Conflict (caPAZ), funded by the Ministry of Science, Technology and Innovation (Minciencias) and the National Center for Historical Memory (CNM) of Colombia (under the code: 1349-872-76354, agreement 872 of 2020) This corpus includes news written by the 24 colleges media of the Colombian Network of College Journalism from 2012 to 2016. The dataset includes digital news, for a total of <strong>589 </strong>news items related to the armed conflict, the memory of the victims and the peace process in Colombia. These news items were collected through a web-scraping technique, using 3 lemmatized keywords (conflicto armado, memoria de las víctimas y proceso de paz), with the aim of identifying these regular expressions in the logical operators that run through the HTML structure of each Web page</p>
Universal Chalcidoidea Database World Wide Web electronic publication. http://www.nhm.ac.uk/chalcidoids. hash://sha256/562fc5f7ac62b0dba9952e267dc839ab16be3efcf149b98a8d77f6e88bce4f53 hash://md5/de2883bc9f8b1e79c96f5d00d650f596
<p>This repository contains an archival copy of the Universal Chalcidoidea Database by J.S. Noyes in their original Paradox Database (https://en.wikipedia.org/wiki/Paradox_%28database%29) file format. </p> <p>Files were provided by J.S. Noyes in period 2023-03/2023-04 and gave consent to publish the data under CC0.</p> <p>For getting started, please read the 00-Instructions.pdf first. Then, suggest to take a look at a flowchart in 01-Flowchart.pdf and the Table Structure in 02-TableStructure.pdf.</p> <p><strong>Citation</strong><br> On use of this data, please follow academic tradition and cite the data using: </p> <p>Noyes, J.S. March 2019. Universal Chalcidoidea Database. World Wide Web electronic publication. http://www.nhm.ac.uk/chalcidoids. hash://sha256/562fc5f7ac62b0dba9952e267dc839ab16be3efcf149b98a8d77f6e88bce4f53 hash://md5/de2883bc9f8b1e79c96f5d00d650f596 .</p> <p><strong>Signed Content </strong></p> <p>Using Preston [1,2], the UCD content was packaged and their provenance was signed.</p> <pre><code>preston history\ --anchor hash://sha256/562fc5f7ac62b0dba9952e267dc839ab16be3efcf149b98a8d77f6e88bce4f53\ --remote https://raw.githubusercontent.com/jhpoelen/ucd/main/data\ --remote https://zenodo.org/record/7864604/files\ --remote https://softwareheritage.org\ --remote https://linker.bio </code></pre> <p>yielded:</p> <pre><code><hash://sha256/562fc5f7ac62b0dba9952e267dc839ab16be3efcf149b98a8d77f6e88bce4f53> <http://www.w3.org/ns/prov#wasDerivedFrom> <hash://sha256/dc3f137ed7e456dd964545527cfff3acc3c1655baeaebecb6d07cdf3e1bbd549> . <hash://sha256/dc3f137ed7e456dd964545527cfff3acc3c1655baeaebecb6d07cdf3e1bbd549> <http://www.w3.org/ns/prov#wasDerivedFrom> <hash://sha256/298581b34133b518f251f4321f1920488afd923f3308e45b9c1d169da0e16b5b> . <hash://sha256/298581b34133b518f251f4321f1920488afd923f3308e45b9c1d169da0e16b5b> <http://www.w3.org/ns/prov#wasDerivedFrom> <hash://sha256/ec1760dc83dfb17df003ef5e626b965dd4403850bc58286ac59c7ef3a447e063> . <hash://sha256/ec1760dc83dfb17df003ef5e626b965dd4403850bc58286ac59c7ef3a447e063> <http://www.w3.org/ns/prov#wasDerivedFrom> <hash://sha256/eb416c97bf52a36b31ece2b47431a6a4a9bda7f52b9bc8ccb92f91f5c1bdf268> . <urn:uuid:0659a54f-b713-4f86-a917-5be166a14110> <http://purl.org/pav/hasVersion> <hash://sha256/eb416c97bf52a36b31ece2b47431a6a4a9bda7f52b9bc8ccb92f91f5c1bdf268> . </code></pre> <p>This archive can be cloned using:</p> <pre><code>preston clone\ --anchor hash://sha256/562fc5f7ac62b0dba9952e267dc839ab16be3efcf149b98a8d77f6e88bce4f53\ --remote https://raw.githubusercontent.com/jhpoelen/ucd/main/data\ --remote https://zenodo.org/record/7864604/files\ --remote https://softwareheritage.org\ --remote https://linker.bio </code></pre> <p>or alternatively, by downloading a zip archive from :</p> <p>https://github.com/jhpoelen/ucd/archive/42a5815a2c50e396f1e34e9f73e0b13fcc67c44f.zip</p> <p><br> <strong>References</strong></p> <p>[1] MJ Elliott, JH Poelen, JAB Fortes (2020). Toward Reliable Biodiversity Dataset References. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2020.101132</p> <p>[2] Elliott, M. J., Poelen, J. H., & Fortes, J. (2023, accepted with minor revisions). Signed Citations: Making Persistent and Verifiable Citations of Digital Scientific Content. https://doi.org/10.31222/osf.io/wycjn<br> </p>
Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study
<p>This section highlights the various methods used for this study. It covered study setting, study design, study approach, study population, sampling techniques, sample size calculation, inclusion and exclusion criteria, ethical consideration, data collection, data management and data analysis<strong>. </strong></p> <p> </p> <p><strong>Study Setting</strong></p> <p>The study was carried out at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi between February to August, 2022. The study covered all the six (6) Colleges in the University.</p> <p> </p> <p><strong>Study Design</strong></p> <p>This was a cross sectional study to ascertain health check practices among university lecturers.</p> <p> </p> <p><strong>Study Approach</strong></p> <p>The study employed quantitative approach in which data was collected using questionnaires with both closed- and open-ended questions.</p> <p><strong>Study Population</strong></p> <p>The study population involved 838 Lecturers across the six Colleges at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi. A study of the lecturer population per college revealed that Colleges of Health Sciences (highest) and Agric /Natural resources (lowest) were the outliers (Quality Assurance and Planning Office, 2020).</p> <p> </p> <p><strong>Sampling Technique </strong></p> <p> </p> <p>Simple probability technique was used to select the name of a college and the day/date to visit. Two sets of papers were folded with names of colleges (set 1) and day/date of visit (set 2). A picker picked one folded paper from each set and the name of the college and the day/date to visit was matched. In this case, the ordering of date and visit gave 1<sup>st</sup> College of Humanities & Social Sciences, 2<sup>nd</sup> College of Agric and Natural Resources, 3<sup>rd</sup> College of Art & Built Environment, 4<sup>th</sup> College of Engineering, 5<sup>th</sup> College of Science and 6<sup>th</sup> College of Health Sciences. We then used the ‘walk in’’ system to select the study participants. Within the days to visit a college, any lecturer we meet in his/ her office was a potential study participant.</p> <p> </p> <p> </p> <p> </p> <p><strong>Sample Size Calculation</strong></p> <p>The sample size was obtained using Yamane, 1967 formulae as shown below:</p> <p> </p> <p> </p> <p>Where n= is the population of Lecturers in at KNUST</p> <p>E= is the level of precision</p> <p>Therefore: n= 838</p> <p> 1+838 (0.0025)</p> <p>n = 838</p> <p>1+ 2.098</p> <p> </p> <p>838</p> <p>3.095</p> <p> </p> <p> n=270 </p> <p>However, due to logistical constrains, 205 participants were contacted across the 6 Colleges at Kwame Nkrumah University of Science and Technology. We then applied simple proportions to get the number of lecturers to be consulted in each college.</p> <p> </p> <p><strong>Inclusion and Exclusions Criteria</strong></p> <p>Inclusion criteria was made up of all Lecturers on KNUST campus who are in active service and consented to participate. All other staff not within this category were excluded from this research.</p> <p> </p> <p><strong>Ethical Considerations</strong></p> <p>Ethical approval was sought from the CHRPE, KNUST with approval reference no: CHRPE/AP/581/21. The aim of the research was explained to participants. Those who consented to participate in the research were given consent forms to sign and date. Again, participants were assured of confidentiality. Participants were told that, they were free to withdraw from the study in the cause of time. In other words, study participants were not coerced into the study.</p> <p> </p> <p><strong>Data Collection Tool</strong></p> <p>Data was collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues on physical inactivity and tobacco use. Aside these four main risk factors of NCDs, the questionnaire also captured frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-up, frequency of anthropometric measurement checks (weight and height), an assessment of impressions about the outcome of weight and height checks, an assessment of intended measures to be taken depending on the outcomes of weight and health checked. Again, the general observation of the nature of job as a lecturer and health status especially the outcome of blood pressure monitoring were also assessed. The questionnaire also captured the socio-demographic status of Lecturers,</p> <p> </p> <p><strong>Data Management</strong></p> <p>Only the Research Team had access to data. Data was kept confidential. The researchers had planned of disposing data from the storage 5 years after the publication of this research. Collected data was entered and cleaned using Microsoft Excel spread sheet, and then imported into STATA version 14.0 (Stata Corp LP, College Station, Texas, USA) for statistical analysis and results.</p> <p> </p> <p><strong>Data Analysis</strong></p> <p>Descriptive statistics were used to summarize the characteristics of the study population by employing frequencies and percentages for categorical data. In addition, the degree of relatedness (association) was evaluated using Chi-square (χ<sup>2</sup>) or Fisher’s exact tests where appropriate with a p ≤0.05 assumed to be statistically significant. Both bivariate and multivariate logistic regression analyses were performed and adjusted for colleges effect to identify associations among the variables of interest. Variables having significant association in the logistic regression models were set at p≤0.05 with 95% confidence interval (95% CI) for both unadjusted and adjusted odds ratios (OR, AOR).</p> <p> </p> <p><strong>Variables</strong></p> <p>BP was selected as the dependent variable, and in turn define as Normal: ≤ 120/80 mmHg; Elevated: Systolic between 120-129 and diastolic ≤ 80; Hypertension: Systolic ≥ 130 or diastolic ≥ 80. Then dichotomized into Normal blood pressure: ≤ 120/80 mmHg and high blood pressure (Hypertension): ≥ 130/90 mmHg for logistic regression analyses. Independent variables were socio-demographics; gender, age, marital status, staff rank and lecturer’s colleges (categorized into binary variable; COHS /COS/COE and CABE/CANR/COHSS), family history of NCDs and health check status. In this study, the variable “very often” denotes (doing the activity in question more than 4 times a month), “often” denotes (doing the activity in question at least twice a month), and “not often” denotes (doing the activity in question once a month).</p> <p> </p> <p> </p>
Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study
<p><strong>Data Collection Tool</strong></p> <p>Data were collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues with physical inactivity, and tobacco use. Aside from these four main risk factors of NCDs, the questionnaire also captured the frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-ups, frequency of anthropometric measurement checks (weight and height), an assessment of impressions about the outcome of weight and height checks, an assessment of intended measures to be taken depending on the outcomes of weight and health checked. Again, the general observation of the nature of the job as a lecturer and health status especially the outcome of blood pressure monitoring were also assessed. The questionnaire also captured the socio-demographic status of Lecturers,</p> <p> </p> <p><strong>Data Management</strong></p> <p>Only the Research Team had access to data. Data was kept confidential. The researchers had planned of disposing data from the storage 5 years after the publication of this research. Collected data was entered and cleaned using Microsoft Excel spread sheet, and then imported into STATA version 14.0 (Stata Corp LP, College Station, Texas, USA) for statistical analysis and results.</p> <p> </p> <p><strong>Data Analysis</strong></p> <p>Descriptive statistics were used to summarize the characteristics of the study population by employing frequencies and percentages for categorical data. In addition, the degree of relatedness (association) was evaluated using Chi-square (χ<sup>2</sup>) or Fisher’s exact tests where appropriate with a p ≤0.05 assumed to be statistically significant. Both bivariate and multivariate logistic regression analyses were performed and adjusted for colleges' effect to identify associations among the variables of interest. Variables having significant association in the logistic regression models were set at p≤0.05 with 95% confidence interval (95% CI) for both unadjusted and adjusted odds ratios (OR, AOR).</p> <p> </p> <p><strong>Variables</strong></p> <p>BP was selected as the dependent variable, and in turn define as Normal: ≤ 120/80 mmHg; Elevated: Systolic between 120-129 and diastolic ≤ 80; Hypertension: Systolic ≥ 130 or diastolic ≥ 80. Then dichotomized into Normal blood pressure: ≤ 120/80 mmHg and high blood pressure (Hypertension): ≥ 130/90 mmHg for logistic regression analyses. Independent variables were socio-demographics; gender, age, marital status, staff rank, and lecturer’s colleges (categorized into binary variables; Colleges, family history of NCDs, and health check status. In this study, the variable “very often” denotes (doing the activity in question more than 4 times a month), “often” denotes (doing the activity in question at least twice a month), and “not often” denotes (doing the activity in question once a month).</p> <p> </p>
American University Men of China (1936)
<p>The following dataset is based on American University Club of Shanghai. <em>American University Men in China</em>. Shanghai: Comacrib Press, 1936. </p> <p>It provides information on the 418 members - both Chinese and non-Chinese - of the American University Club of China (Shanghai) recorded in the directory. Established around 1902, the American University Club (AUC) was one of the earliest and largest organizations of American university alumni in pre-Communist China. </p> <p>The attached file comprises two tabs, one for the data and one for describing the variables (key).</p>
Universal microbial reworking of dissolved organic matter along environmental gradients
<p>Soils are losing increasing amounts of carbon annually to freshwaters as dissolved organic matter (DOM), which, if degraded, can increasingly offset their carbon sink capacity. DOM is more susceptible to degradation closer to its source and becomes increasingly dominated by the same (i.e., universal), difficult-to-degrade compounds as degradation proceeds. However, the processes underlying DOM degradation across environments are poorly understood. Here we found DOM changed similarly along soil-aquatic gradients irrespective of differences in environmental conditions. Using ultrahigh-resolution mass spectrometry, we tracked DOM along soil depths and hillslope positions in forest headwater catchments and related its composition to soil microbiomes and physico-chemical conditions. Along depths and hillslopes, carbohydrate-like and unsaturated hydrocarbon-like compounds increased in abundance-weighted mass, suggestive of microbial reworking of plant material. More than half of the variation in the abundance of these compounds was related to the expression of genes essential for degrading plant-derived carbohydrates. Our results implicate continuous microbial reworking in shifting DOM towards universal compounds in soils. By synthesising data from the land-to-ocean continuum, we suggest these processes can be generalised across ecosystems and spatiotemporal scales. Such general degradation patterns can be leveraged to predict DOM composition and its downstream reactivity along environmental gradients to inform management of soil-to-stream carbon losses.</p>
A Shortlist of Diamond Open Access Journals for the Faculty of Science at Utrecht University
<p><strong>Context</strong></p> <p>The following shortlist of diamond open-access journals was compiled to increase awareness of alternative scholarly publication models among the six departments of the <a href="https://www.uu.nl/en/organisation/faculty-of-science">Faculty of Science at Utrecht University</a>. The list is relevant to the six disciplines at the Faculty of Science: Biology, Chemistry, Mathematics, Information and Computing Sciences, Physics, and Pharmaceutical Sciences. For this purpose, a "diamond journal" is defined as a journal indexed in the <a href="https://www.doaj.org/">Directory of Open Access Journals (DOAJ)</a> that does not charge an article processing charge (APC).</p> <p> </p> <p><strong>Contents and Results</strong></p> <p>The Excel file titled “Diamond_journals_faculty_of_science_UU” contains the list of selected diamond journals based on the following criteria: they allow submissions in English, have a plagiarism screening policy, possess an electronic ISSN number, and accept submissions in Biology, Chemistry, Mathematics, Information and Computing Sciences, Physics, and Pharmaceutical Sciences. In this shortlist, 355 journals meet the criteria. Out of these 355 journals, only 29 have received a DOAJ seal, 150 journals are indexed in <a href="https://www.scopus.com/">Scopus</a>, and 94 journals are indexed in <a href="https://mjl.clarivate.com/home">Web of Science</a>.</p> <p>A detailed description of the methods employed to obtain this shortlist can be found in the Word file titled "Methods_and_Results".</p> <p>The raw CSV data has been included under the name "Raw_DOAJ_journal_metadata_2023_07_25".</p> <p> </p> <p><strong>Limitations</strong></p> <p>The compilers of this shortlist are aware that some current diamond journals could change their status to non-diamond by charging article processing fees at a later stage. Since the journal record is not always updated by the publishers, we strongly recommend the users double-check the latest open access status directly on the journal's homepage (journal URLs are provided in the Excel file). The same applies for Scopus and WOS indexations.</p>
A scalable, accurate, and universal analysis framework using individual-level allele frequency for large-scale genetic association studies in an admixed population
<p>Inclusion of individuals with diverse or admixed genetic ancestries is crucial to discover novel findings that may be missed by genomics analyses rooted solely in Caucasian population. Here, we present an analysis framework, SPAmix, which is scalable to a large-scale biobank data analysis including hundreds of thousands of admixed individuals and is universally applicable to various types of complex traits including binary trait, quantitative trait, time-to-event trait, longitudinal traits, etc. For each genetic variant, SPAmix uses genotype data and genetic principal components (PCs) to estimate individual-level allele frequency, which is subsequently used to calibrate p values via a retrospective analysis. A hybrid strategy including saddlepoint approximation (SPA) can greatly increase the accuracy to analyze rare genetic variants, especially if the phenotypic distribution is unbalanced or extremely unbalanced. Compared to Tractor, SPAmix does not require local ancestry information and can be straightforwardly applicable to a multi-way admixed population. Meanwhile, SPAmix can also be extended to SPAmix<sub>local</sub> in which the local ancestry can be incorporated if available. In addition, we propose SPAmix<sub>CCT</sub> to combine the p values of SPAmix and SPAmix<sub>local</sub> via Cauchy combination (CCT). SPAmix<sub>local</sub> performs close to Tractor when analyzing quantitative traits and is more accurate when analyzing binary traits with an unbalanced case-control ratio. And SPAmix<sub>CCT </sub>is an optimal unified approach for various cross-ancestry genetic architectures. Extensive simulation studies and real data analyses of 369,314 UK Biobank individuals from multiple ancestries demonstrated that SPAmix is scalable and can discover novel hits while controlling type I error rates well.</p>
Experiment replication - Plattes 1639 (Johns Hopkins University, Baltimore, USA, 02/28/2023 - 03/01/2023)
<p>Replication in laboratory of an experiment reported by Gabriel Plattes, <em>A Discovery of Subterraneall Treasure</em> (1639):</p> <p>“Now for a plaine demonstration [of how mineral ores are generated], let this experiment following be tryed, and I make no question, but that it will satisfie every one that hath an inquisitive disposition. Let there bee had a great retort of glasse, and let the same be halfe filled with brimstone, sea-coale, and as many bituminous and sulphurious subterraneall substances as can bee gotten: then fill the necke thereof halfe full with the most free earth from stones that can be found, but thrust it not in too hard, then let it bee luted, and set in an open furnace to distill with a temperate fire, which may onely kindle the said substances, and if you worke exquisitely, you shall finde the said earth petrified, and turned into a stone: you shall also finde cracks and chinkes in it, filled with the most tenacious, clammy, and viscous parts of the said vapours, which ascended from the subterraneall combustible substances. Wereby it appeareth that the same thing is done by Nature, and that the rocks and craggy mountaines are caused by the vapours of bituminous and sulphurious substances kindled in the bowells of the earth, of which there bee divers so well knowne, that they neede not bee heere mentioned [...]” (pp. 5-7). This experiment is also mentioned in Emerton 1984, p. 249. See also Debus 1961.</p> <p>“Take a peece of the blacke fat earth, which is usually digged up in the west countrey, where there are such a multitude of firre trees covered therewith, and which the people use to cut in the forme of bricks, and to drye them, & so to burne them in stead of coales; use this substance as you did the other earth in the beginning of the booke, to find out the natural cause of rocks, stones, and mettalls, and let it receive the vapours of the cumbustible substances, and you shall find this fat earth hardned into a plaine coale; even as you found the other leane earth hardned into a stone” (p. 50).</p>
Experiment replication - Plattes 1639 (Johns Hopkins University, Baltimore, USA, 6/15/2022)
<p>Replication in laboratory of an experiment reported by Gabriel Plattes, <em>A Discovery of Subterraneall Treasure</em> (1639):</p> <p>“Now for a plaine demonstration [of how mineral ores are generated], let this experiment following be tryed, and I make no question, but that it will satisfie every one that hath an inquisitive disposition. Let there bee had a great retort of glasse, and let the same be halfe filled with brimstone, sea-coale, and as many bituminous and sulphurious subterraneall substances as can bee gotten: then fill the necke thereof halfe full with the most free earth from stones that can be found, but thrust it not in too hard, then let it bee luted, and set in an open furnace to distill with a temperate fire, which may onely kindle the said substances, and if you worke exquisitely, you shall finde the said earth petrified, and turned into a stone: you shall also finde cracks and chinkes in it, filled with the most tenacious, clammy, and viscous parts of the said vapours, which ascended from the subterraneall combustible substances. Wereby it appeareth that the same thing is done by Nature, and that the rocks and craggy mountaines are caused by the vapours of bituminous and sulphurious substances kindled in the bowells of the earth, of which there bee divers so well knowne, that they neede not bee heere mentioned [...]” (pp. 5-7). This experiment is also mentioned in Emerton 1984, p. 249. See also Debus 1961.</p> <p>“Take a peece of the blacke fat earth, which is usually digged up in the west countrey, where there are such a multitude of firre trees covered therewith, and which the people use to cut in the forme of bricks, and to drye them, & so to burne them in stead of coales; use this substance as you did the other earth in the beginning of the booke, to find out the natural cause of rocks, stones, and mettalls, and let it receive the vapours of the cumbustible substances, and you shall find this fat earth hardned into a plaine coale; even as you found the other leane earth hardned into a stone” (p. 50).</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.