Filter Results
4150 results
Habenula QSM data upload test
Data Types:
  • Software/Code
  • Image
  • Dataset
Sharp ended α-Fe core microwire covered with PrDyFeCoB amorphous shell with enhanced stray magnetic field is proposed for magnetic tweezers, stepwise switchable in external homogeneous magnetic field. Four stable magnetic states of the microwire, controlled by external magnetic field, were determined by magneto-optical Kerr effect (MOKE) microscopy. Distribution of the stray field near the microwire tip was plotted by magneto-optical indicator film (MOIF) technique. Large gradient of the stray magnetic field in the vicinity of the microwire tip is quite enough to provide magnetic force ~ 2000 pN, well enough for capturing of the PrDyFeCoB microparticle. Significance of the obtained results is in switching of the focused stray field of the microwire under external homogeneous magnetic field. This provides simple way of stepwise attaching-detaching of microparticles without electromagnetic micro coils.
Data Types:
  • Software/Code
  • Image
  • Dataset
This is data collected on the nutritional status of non-academic staff of the Tamale Campus of University for Development Studies, Tamale - Ghana Interviews were conducted on staff nutrition and their dietary practices using questionnaires. Weight and height measurements were taken for anthropometric data of respondents to assess their nutritional status. Participants were also asked through the questionnaire, to indicate all foods and drinks that were consumed over the previous 24 hours whether at home or outside the home. As part of data collection, a table was created with various food groups and participants indicated which foods they consumed. The data should be interpreted taken into cognisance that these staff are at a higher institution of learning. The hypothesis was that poor nutrition knowledge result in poor dietary practices and nutritional status.
Data Types:
  • Software/Code
  • Dataset
This paper investigates the claim that the election of Donald Trump in 2016 prompted a decline in trust among Democrats and an increase in trust among Republicans. I test these hypotheses with four-wave panel data from Pew Research's American Trends Panel project, collected before and after the election. The evidence points to a relationship between Trump’s victory and a collapse of social trust among electoral losers with strong partisan attachments. From 2014 to 2018, the sharpest declines in trust occurred among Democrats in the pre- to post-electoral period (2016-2017). Pre-election Democrats were also the least likely to become and remain trusting of others following the election. No other partisan group experienced changes of trust in response to the election, including those who only weakly identify as Democrats. However, there is also evidence that the effect was temporary. By 2018, generalized trust among Democrats rebounded. The implication of these findings is that the 2016 election had a negative effect on America’s already depleted supply of social trust.
Data Types:
  • Software/Code
  • Dataset
A reliable and unobtrusive quantification of changes in cortical activity during short-term memory (STM) task can be used to evaluate the efficacy of interfaces and to provide real-time user-state information. In this dataset, we record electroencephalogram (EEG) signals in STM and baseline activity.
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset
  • File Set
The dataset consists of 3D scans of the upper and lower dentitions of 24 patients, all in their growth age, taken at different time intervals. All patients had normal occlusions with no history of orthodontic treatment. There are 3 scans avaialble for 8 out of 24 patients, and 2 scans available for the remaining 16 patients. The interval between each two consecutive scans is at least 2 years and at most 10 years. The dataset was created by 3D scanning of plaster models using a benchtop structured-light 3D scanner (Maestro 3D Desktop Scanner, Pontedera, Italy) with a point accuracy of <10 μm and resolution of <70 μm in all directions.
Data Types:
  • Software/Code
  • Dataset
The procreative statistical framework of musical note structures produces a crucial role in multimedia music classification and reconstruction strategies. Another most significant thing for harmonious music composition is the rhythmic structures that provide musical performance in a harmonic form. This paper has illustrated computational music theory and allied factors to regulate what human beings can acquire, remember, and reconstruct music for sustaining intangible cultural heritage. The music strings or symbols are also imperative factors that assist the musicians as performance guidelines. To afford a syntactic outline of musical note arrangements, a stochastic model along with probabilistic context-free music grammar has been illustrated in this paper. The state transition analysis has also been incorporated in terms of transition table and diagram to demonstrate which state can move to the other one within a finite automaton depending on the behaviors of the current state and associated transition rule. Petri net has been used for modeling and simulating the projected complex music composition framework to analyze system performances. The Petri net simulation-based reachability and system efficiency have been evaluated for analyzing the effectiveness of the proposed event-driven architecture. For incorporating real data into the projected framework, the music composition and reconstruction tool has also been demonstrated. The system performance evaluation metric has shown that around 92% efficiency level has been achieved by analyzing the projected music composition model.
Data Types:
  • Tabular Data
  • Dataset
  • Document
  • Audio
these data will be published in the "A phenomenological model for the spontaneous exchange bias effect" article
Data Types:
  • Software/Code
  • Dataset
In a scenario of expanding competition between tourist destinations, DMOs face the challenge of positioning them attractively. To this end, these organizations can make use of various communication marketing strategies, including social media, platforms whose effectiveness is measured through engagement. From these channels originate the digital influencers, which in recent years have gained greater academic and marketing prominence. Given this theoretical foundation, this research aimed to measure the degree of engagement in publications with digital influencers on Instagram of Brazilian DMOs, with time frame between December / 17 and December / 18. To achieve the necessary results for the proposed problem, the data mining technique was used in a sample of 11 Instagram profiles from Brazilian state DMOs, selected after a filtering process. The collected data were treated from a quantitative descriptive approach, having as parameter three main indicators, as follows: (1) total publications, (2) likes and (3) comments. All these indices were defined after consulting the engagement literature. In addition, a T Test was done between paired samples to verify if there was a significative difference on the means. In general, the results indicated that posts with digital influencers have better results, given the proposed time frame, especially when compared with the indexes of general posts. However, inferential statistics indicated that the differences between means were not relevant. In such a way, the strategy of endorsement by influencers does not seem to produce relevant effects on user interaction in the profiles of Brazilian DMOs.The innovative character of this research stems from the use of the data mining technique to deliver accurate results as to the effectiveness of a rising social media strategy, providing managers with a solid framework for analysis and fostering the field of discussion.
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset
  • Document
This data contains four variables, childhood psychological maltreatment, immorality, empathy and cyberbullying perpetration attitudes
Data Types:
  • Software/Code
  • Dataset
5