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  • Critical and creative thinking is very important to build students' cognitive processes in solving mathematical learning problems that are done logically and can be measured, in this case problem solving becomes very important in helping students think critically because it helps students think at a high level to find solutions in the form the answer to the problem mathematically. Therefore this article explains about critical thinking data, creative personal, with the ability to solve elementary school students' math problem. This research uses a survey method with statistical regression and correlation approaches. an example in this data is 30 students in elementary schools in the city of Yogyakarta. Data collection method is using a validated questionnaire. In this data collection we present several variable / item questions that are included in the data set. In general, the data findings indicate that there is a relationship of critical thinking, creative personality with significant mathematical problem solving abilities. so this data has particular implications for teachers to create examples of problems that build students' critical, creative thinking levels.
    Data Types:
    • Tabular Data
    • Dataset
  • Data set for publication in Cell Host Microbe, Bruggisser et al: Cell-specific targeting by Clostridium perfringens β-toxin unraveled: the role of CD31 as the toxin receptor.
    Data Types:
    • Image
    • Tabular Data
    • Dataset
    • Document
    • Text
  • The dataset is constructed for a project that investigates the coverage and the role of Semantic Scholar (S2) search engine in condunting secondary studies in software engineering.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Text
  • Behavioural dynamics gathered from a webchat app. EVTRACKINFO: 347 records. Static behaviour information. EVTRACKTRACK: 142691 records. 113471 for keystroke dynamics and 29220 for mouse dynamics. 11 users. A mean of 28524 +-18541 records has been obtained per user.
    Data Types:
    • Tabular Data
    • Dataset
  • The dataset in the file "combined1.csv" included 383 patient's clinical data, including 7 variables: age, sex, location, aneurysm, nidus size, draining type, the number of draining veins, and hemorrhage. Female was defined as 0, male as 1. Superficial AVM was defined as 0, deep AVM as 1, infratentorial AVM as 2. Only superficial draining vein was defined as 0, mixed superficial and deep draining vein as 1. A single draining vein was defined as 1, multiple draining veins as 2. Ruptured AVM was defined as 1, unruptured AVM as 0. The file "randomtestpredict.R" was the source file in RStudio, which was used to build and test prediction models based on the above data file.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
  • Background: Sedentary behaviour guidelines recommend that individuals should regularly break up sitting time. Accurately monitoring such breaks is needed to inform guidelines concerning how regularly to break up sitting time and to evaluate intervention effects. We investigated the concurrent validity of questionnaire items assessing number of breaks in sitting time among children and adolescents. Methods: Fifty-seven children and adolescents self-reported number of breaks from sitting taken at school, while watching TV and during other screen time activities. Participants also wore an activPAL monitor to objectively assess the number of sitting time breaks (frequency/hour). Concurrent validity was assessed using Spearman rank correlations. Results: Self-reported number of breaks/hour at school showed good concurrent validity (ρ=0.676). Results were moderate to good for self-reported number of breaks/hour while watching TV (ρ range: 0.482 to 0.536) and moderate for self-reported number of breaks/hour in total screen time (ρ range: 0.377 to 0.468). Poor concurrent validity was found for self-reported number of breaks/hour during other screen time activities (ρ range: 0.157 to 0.274). Conclusions: Only the questionnaire items about number of breaks at school and while watching TV appear to be appropriate for further use in research focussing on breaks in prolonged sitting among children and adolescents.
    Data Types:
    • Software/Code
    • Dataset
  • The attached experimental data of single Polymer Electrolyte Membrane (PEM) fuel cell aim for comparing the characteristics of two different testing hardware, namely the recently developed JRC ZERO∇CELL single cell reference testing hardware and the commonly used by the research community single-serpentine testing hardware. Data are presented in form of polarisation curves, temperature, pressure and voltage distributions, as well as electrochemical impedance spectroscopy measurements for a range of current densities. The electrochemical impedance spectroscopy data are also validated using the Kramers-Kronig transformation and presented as Nyquist and Bode plots.
    Data Types:
    • Tabular Data
    • Dataset
  • This dataset contains all source data for the manuscript.
    Data Types:
    • Tabular Data
    • Dataset
  • Real-time tracking of the spatial diffusion of airborne diseases, and especially COVID-19 is in the focal point of both recent academic studies and policymaking. Airborne pathogens are handed over by interpersonal encounters. Therefore, agent-based modelling provides a useful approach to grasp the complex and interrelated nature of spatiotemporal movement and the geographical spread of infectious diseases. Although technology development rendered it to be feasible to track the spatial spread of infected individuals, the spatial scale of data retrieval can cause challenging bottlenecks for academic analysis. Samples on community-scale, for instance, by crowdsourced data as well as the global level of international aircraft movements are addressed. However, regional-scale spread of airborne diseases conveyed by human mobility rarely comes into focus. By directing our efforts to the level of countrywide diffusion, we aim to disclose the spatial component of airborne pathogens’ infection carried over by interpersonal encounters. The mobile cell dataset we applied here is especially suitable to estimate the number of interpersonal encounters, that is enabled by co-locating the same space with an infected person within a definite timeframe. Consequently, we considered mobile phone data driven co-location as ‘locational chance’ of airborne pathogen spreading. The volume of spread, as we argue, is dependent on the interpersonal connections. According to the current results, the geographical spread of COVID-19 is dominantly carried over by latently infected individuals, who transmit the disease without showing any symptoms. We modelled the interpersonal encounters of a set of randomly chosen latent infected as an indicator of the further geographical spread of the disease. We applied two various sets of models running: one, that is based on real archive data, and the other, that simulates current mobility patterns ordered by relocation restrictions.
    Data Types:
    • Video
    • Tabular Data
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    • File Set
  • Data set contains the experimental results of Double pipe heat exchanger with flat spring turbulator.
    Data Types:
    • Tabular Data
    • Dataset