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.
Contributors:Alejandro G. Martin, Marta Beltrán, Alberto Fernández-Isabel, ISAAC MARTIN
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.
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.
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.
Contributors:Tünde Szabó, Márton Prorok, Bence Berkes
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.
This dataset was created using an environmentally extended multi-region input-output (EE-MRIO) model, which uses an input and output approach that tracks flows of monetary values of trade to allot environmental impacts between regions and sectors. The MRIO model is a predominant method for the estimation of consumption-based greenhouse gas (GHG) accounting. Our particular model was constructed using Python.
The tabulated results show the flows of emissions embodied in imports, exports, and domestic consumption of a region. In our case, we calculated the consumption emissions of all Canadian provinces and territories from 2010-2015. The tables show intersectoral, interprovincial, and international flows of embodied emissions, presented in the North American Industry Classification System (NAICS)"
Regarding our model’s inputs for estimating embodied emissions in international trade, we utilized the Environmental Accounts and financial input-output tables from the World Input-Output Database (WIOD). For estimating embodied emissions in Canada and Canada’s trade, we used Canada’s Physical Flow Accounts, Interprovincial Input-Output and Supply-Use Tables, and Canada’s Trade Online Data. These datasets were accessed in August 2019 from the following websites (see links):
• WIOD Input-Output Tables: http://www.wiod.org/home
• WIOD Environmental Accounts 2013: http://www.wiod.org/home
• WIOD Environmental Accounts 2019: https://ec.europa.eu/jrc/en/research-topic/economic-environmental-and-social-effects-of-globalisation
• Interprovincial Input-Output Tables: https://www150.statcan.gc.ca/n1/en/catalogue/15-211-X
• Interprovincial Supply-Use Tables: https://www150.statcan.gc.ca/n1/en/catalogue/15-602-X
• Physical Flow Accounts: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3810009701
• Canada’s Trade Online Data: https://www.ic.gc.ca/eic/site/tdo-dcd.nsf/eng/Home