Taxonomic revision of Rochefortia Sw. (Ehretiaceae, Boraginales)

Irimia, Ramona-Elena; Gottschling, Marc

doi:10.3897/bdj.4.e7720

Cited by 23 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During the classical groups' experiment, the selected music was played out loud from a school issued computer via the test proctor. This piece has been used for decades in Mozart Effect studies, such as in a published study by a master's student at Gardner-Webb University in which the focus was to determine how music affects the comprehension of a fourth grader (Huckabee, 2016). Group C students were to take the song they had chosen from the last question of the survey (Figure 1) and listen to it on repeat through headphones while completing the ACT test.…”

Section: Methodsmentioning

confidence: 99%

The Effects of Different Musical Auditory Backgrounds on a High School Student’s Comprehension Performance

Chrosniak

Talarczyk

2019

J Stud Res

View full text Add to dashboard Cite

The Mozart Effect is a phenomenon where it is believed that students benefit from listening to classical music while studying or completing a class task. Studies released about the Mozart Effect have proven to not be the most reliable or replicable of studies. Similarly, very few studies have been released using music other than classical to see how all genres of music impact a students performance in the classroom. This research study began with a pre-assessment survey to determine characteristics of the population sample, 79 students varying from grades 10-12 in both Advanced Placement and College Prep English courses. The next part of the study included an experiment where students were to complete a portion of a released ACT reading excerpt. Students were to perform the task in silence, listening to a Mozart Sonata, or while listening to one of five pieces deemed to be the most popular of the year 2018. Upon completion, students were to complete a post-assessment survey in which they reviewed how they felt about the experience. Through an ANOVA, the scores from all students in the silent group, the classical group, and the popular group were compared in order to determine if any one treatment group performed significantly better or worse than others in terms of accuracy, as well as to see if different auditory factors were to blame. The results proved to be insignificant, showing how students do not perform better or worse on comprehension tasks when different auditory backgrounds are applied.

show abstract

Section: Methodsmentioning

confidence: 99%

The Effects of Different Musical Auditory Backgrounds on a High School Student’s Comprehension Performance

Chrosniak

Talarczyk

2019

J Stud Res

View full text Add to dashboard Cite

show abstract

“…These were traditional multi-linear regression (MLR), generalized boosting model (GBM), RF, and artificial neural network (ANN) model. The last two models were suggested by previous research papers (Ramona-Gottschling & Gottschling, 2016), in which the researchers compared 11 models and illustrated the favorable performance of the GBM and RF in detail. In particular, the work explored the performance of the two models on predicting PM2.5 concentrations after wildfire events in California.…”

Section: Weather Data Processingmentioning

confidence: 99%

Wildfire Air Quality Prediction

Dhar,

Gao

2023

International Journal of Disaster Response and Emergency Management

View full text Add to dashboard Cite

Wildfires are extremely harmful to the environment. While producing gaseous pollutants and particles that cause smoke, wildfires also release carbon dioxide (CO2), a greenhouse gas that will continue to warm the planet after the wildfire ends. This article delves into the impact of wildfires and air quality on human living conditions. The authors' machine learning models use wildfire data to forecast air quality with detailed indexes and geographic information during a wildfire. The work evaluates the performance of each machine learning model via statistical metrics like mean absolute error (MAE), R-squared (R2), and root mean squared error (RMSE). The experimental results used neural networks to predict a specific value for carbon monoxide (CO), ozone, and PM2.5. These are both promising and accurate, providing meaningful insight into air quality within a region. This work will be useful for cities, governments, citizens, and public safety.

show abstract

“…According to Irimia and Gottschling (2016), the temperature emitted from buildings results in an increase of temperature in the environment. This can be done by finding the radiative forcing ∆F first (which is the change in the climate of the earth), as there is a difference in the incidence solar radiation and the absorption of this radiation by the earth which causes a defect in the concentration of the GHG.…”

Section: Temperatures Generated From Buildingsmentioning

confidence: 99%

A Comparative Study of Energy Performance in Educational Buildings in the UAE

Ahmed

Saboor

Almarzooqi

et al. 2021

CEB

View full text Add to dashboard Cite

Sustainability has gained popularity and importance around the globe due to the ever-increasing effects of climate change and global warming on Earth. As of the 21st century, human endeavour has caused an enormous amount of damage to the environmental ecological system. Among which, one of the major contributors to the increase in the environmental issues and CO2 emissions are the conventional sources of energy, especially in the built environment. Globally, the built environment accounts for 12 percent of the world’s drinkable water, 40 percent of energy wastage and 35 percent of scarce natural resources, which in turn produces 40 percent of the total global carbon emission. Among which are educational buildings which tend to be a major contributor (as most of these facilities are old and conventionally built in the mid-1900s) Thus, with the education sector being an essential part of society, it becomes important to determine the energy performance and carbon footprint of these buildings. The United Arab Emirates (UAE) vision 2021 highlights the country's approach to the importance of providing the best education and adopting sustainable environmental infrastructure. Therefore, this study adopts a methodological approach based on semi-structured interviews and surveys, in order to compare the energy performance of three educational buildings within Higher Education establishments in the UAE as a case study. The study also evaluates the end user’s awareness of the importance of sustainable practices in the buildings and their preference for these buildings. The findings of this study conclude that Net Zero Energy Buildings (NZEBs) are the most efficient buildings in terms of energy performance, carbon consumption and heat generated. Therefore, it is important that the integration of these types of buildings is considered in educational establishments.

show abstract

Taxonomic revision of Rochefortia Sw. (Ehretiaceae, Boraginales)

Cited by 23 publications

References 18 publications

The Effects of Different Musical Auditory Backgrounds on a High School Student’s Comprehension Performance

The Effects of Different Musical Auditory Backgrounds on a High School Student’s Comprehension Performance

Wildfire Air Quality Prediction

A Comparative Study of Energy Performance in Educational Buildings in the UAE

Contact Info

Product

Resources

About