cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1596002
title: European Buckthorn Abundance, Plant Species Richness, and Ground Temperature at York University

description: Three 3 m x 3 m quadrats were used to sample European buckthorn abundance, plant species richness, and ground temperature in three different plots at York University: Boyer woodlot, Osgoode woodlot, and Saywell woodlot. The quadrats were randomly within each woodlot. Coordinates of each quadrat were generated by MicrosoftExcel software with relation to a chosen corner of the woodlot. Distance was measured using a measuring wheel. Woodlot dimensions were calculated using MapDevelopers software. Number of European buckthorn plants in each quadrat was recorded as European buckthorn abundance, and number of plant species in each quadrat excluding European buckthorn was recorded as plant species richness. Plants species included moss (phylum Bryophyta), grass (phylum Tracheophyte), low-level plants, shrubs and trees. Any human activity proximal to the quadrats was measured, the ground temperature of a spot in each quadrat was measured (degrees Celsius), and the outside temperature (degree Celsius) on each day was measured. Sunlight coverage of each quadrat was estimated but not used as a factor in this lab report because a means of accurate measurement was not available. Replicates of these measurements were taken on three different days: October 1, October 8, and October 15, in order to eliminate variance due to changes in temperature and weather. These dates are referred to as week 1, week 2, and week 3.
DOI: 10.6084/m9.figshare.1596000
title: Relationship between gender and restaurant choices at York University(Keele Campus), Toronto, Canada.

description: The study was conducted in the food court located inside Student Center and York Lanes mall at York University(Keele Campus), Toronto. After examining menus of various restaurants, three restaurants- La Prep, Berries & Blooms and Brumount Bistro were chosen as the health-oriented restaurants because of low calories, low fat, high nutrition and high fibre content food items in their menu. In contrast, three restaurants, Hero Cetified Burgers, Popeyes Louisiana Kitchen and Wendy's were classified into unhealthy fast food restaurants because of high animal fat, high salt, high sweet content and poor nutrition value food items in their menu.Collection of Male and Female frequency data Each of the chosen restaurants were surveyed for one hour per week for three weeks and number of male or female customers that visited during that time were counted. Therefore, all six restaurants (three from each category) were surveyed for a total of three hours and number of male or female visitors were determined.
DOI: 10.6084/m9.figshare.1596000.v1
title: Relationship between gender and restaurant choices at York University(Keele Campus), Toronto, Canada.

description: The study was conducted in the food court located inside Student Center and York Lanes mall at York University(Keele Campus), Toronto. After examining menus of various restaurants, three restaurants- La Prep, Berries & Blooms and Brumount Bistro were chosen as the health-oriented restaurants because of low calories, low fat, high nutrition and high fibre content food items in their menu. In contrast, three restaurants, Hero Cetified Burgers, Popeyes Louisiana Kitchen and Wendy's were classified into unhealthy fast food restaurants because of high animal fat, high salt, high sweet content and poor nutrition value food items in their menu.Collection of Male and Female frequency data Each of the chosen restaurants were surveyed for one hour per week for three weeks and number of male or female customers that visited during that time were counted. Therefore, all six restaurants (three from each category) were surveyed for a total of three hours and number of male or female visitors were determined.
DOI: 10.6084/m9.figshare.1596002.v1
title: European Buckthorn Abundance, Plant Species Richness, and Ground Temperature at York University

description: Three 3 m x 3 m quadrats were used to sample European buckthorn abundance, plant species richness, and ground temperature in three different plots at York University: Boyer woodlot, Osgoode woodlot, and Saywell woodlot. The quadrats were randomly within each woodlot. Coordinates of each quadrat were generated by MicrosoftExcel software with relation to a chosen corner of the woodlot. Distance was measured using a measuring wheel. Woodlot dimensions were calculated using MapDevelopers software. Number of European buckthorn plants in each quadrat was recorded as European buckthorn abundance, and number of plant species in each quadrat excluding European buckthorn was recorded as plant species richness. Plants species included moss (phylum Bryophyta), grass (phylum Tracheophyte), low-level plants, shrubs and trees. Any human activity proximal to the quadrats was measured, the ground temperature of a spot in each quadrat was measured (degrees Celsius), and the outside temperature (degree Celsius) on each day was measured. Sunlight coverage of each quadrat was estimated but not used as a factor in this lab report because a means of accurate measurement was not available. Replicates of these measurements were taken on three different days: October 1, October 8, and October 15, in order to eliminate variance due to changes in temperature and weather. These dates are referred to as week 1, week 2, and week 3.
DOI: 10.6084/m9.figshare.1596004.v1
title: Bird Study Data Set Biol 3250

description: Using four decimals scale, 900 grams of bird seed was measured three times and placed in three identical plastic containers. Each container was then treated with water and one dye colour: red, green or yellow. Water allowed the dye to be absorbed by seed in order for seed to express the desired colour. 30 grams of coloured seed was then placed in 25 empty white bowls, and this was repeated for each colour. In total there was 125 bowls of seed each with 30 grams of either yellow, red or green in each bow. Bowls were brought to five chosen forest on York University campus in Toronto Ontario on October 1st, 2015. The edges of each forest were designated with a number from 1-4; North-1, South-2, West-3, and East-4. Using a random number generator, one of the four edges of the forest was chosen. The chosen edge was further divided horizontally along the edge into four equal sections, each section was then designated with a number from 1-4. Using a random number generator one of the section along the chosen edge was selected. The trees along the edge of the chosen section was then numbered, and using a random number generator a tree was selected. Starting from the chosen tree, orientated perpendicularly to the edge of the forest, 20 meter of the transect tape was placed on the ground. Walking along the transect tape three bowls each containing 30.00 grams of bird seed was placed in triangular orientation on the ground at the 1-meter mark of the transect tape. Each bowl within the triangular orientation contained a different colour bird seed; 1 bowl contained green bird seed, 1 bowl contained red bird seed and 1 bowl contained yellow bird seeds. This was repeated at 5, 10, 15, and 20 meters’ mark of the transect tape. Next the recorder stood in close proximity of the bowls until exactly 3:00 p.m. Eastern Pacific time, ensuring that no birds began eating the birds seed. At exactly 3:00 p.m.- 5:00 p.m. Eastern Pacific time, the recorder moved 30 feet away from bowls allowing the birds to begin to eat the bird seeds. At 5:00 p.m. the bird seeds remaining in each bowl was then weighed and recorded. This was repeated again on Thursday October 8th , 2015 and Thursday October 15th, 2015.
DOI: 10.6084/m9.figshare.1595947
title: Distance from Water Affecting the Abundance and Height of White Aster and Yellow Solidago Plants at York University Freshwater Habitats

description: Data for this experiment was collected on three different days, October 1st 2015, October 8th 2015 and October 15th 2015, all between approximately 3:00 pm - 5:00pm. The sites of the experiment consisted of Stong Pond, Black Creek Pond and the Village Pond, all located at York University, Keele Campus. The site conditions were generally cool and dry for the duration of the three days, the temperature range was between 11°C - 19°C. The group collecting the data consisted of Cathy, April, Maya and Shahana. The purpose of this experiment was to observe the influence of the distribution of resources and competition on the abundance and height of plants by utilizing various sampling techniques with the aid of tools such as quadrats and transects. Variables that were tested in this experiment consisted of soil type, plant abundance and the height of two flowering plants, the White Aster and the Yellow Solidago. A total of 81 replicates were tested, each replicate consisted of using a transect to measure a series of three pre-determined distances that the plants were measured from the water source. These distances were 3.5, 12 and 15 metres. A quadrat was placed randomly by using a random number generator at one of the three pre-determined distances The plant abundance and height for each White Aster and Yellow Solidago plants was counted and measured. These two particular plants were used due to the fact that they persisted in cooler temperatures and they were easy to identify visually. The height of each plant was measured using a measuring tape from the base of the stem, to the tip of the highest flower, in centimetres. Soil type was identified visually, and put into one of three categories: wet, weathered and dry soil.
DOI: 10.6084/m9.figshare.1595945
title: ECO 2050 Lab Report

description: The experiment took place on November 15th and 22nd. The materials were; two transects, twenty-four pans (eight yellow, eight white, eight blue), soapy water and strainer. Day One of the experiment will be divided into two sections, mowed/unmowed grassland treatment, and performed in the same way for each. A transect will be randomly laid in a straight line among each grassland treatment at the exact same time. Four of each pan color (white, blue and yellow) will be placed 1m apart along each transect, for a total 12 pans per transect. The order of color along the transect will be white, blue and yellow respectively, and this is repeated four times. Once soapy water is poured into each pan the timer begins and the results are collected after an hour. After the hour’s conclusion the soapy water is finally poured through a strainer and the insect abundance determined. The experiment is repeated a second time with the transect location randomly selected. Day Two of the experiment follows the same method.
DOI: 10.6084/m9.figshare.1595940
title: Mining Company's Global Supply Chain - Uniformly Random Logistics Data for a Medium Size Excavator

description: The company which provided the dataset is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of the company is estimated to be on the order of tens of billions and they sell products and parts via a worldwide dealer network. The company sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of the company - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been generated according to a normal distribution with the same mean and standard deviation as in the original dataset (e.g. the demand figures have the same mean and standard deviation as those found in the original problem).
DOI: 10.6084/m9.figshare.1595927
title: Leishmania mexicana promastigote and amastigote flagellar pocket tomograms

description: Eight tomograms of the flagellar pocket of <em>Leishmania</em><em> mexicana</em>.
DOI: 10.6084/m9.figshare.1595936
title: Single nucleotide polymorphisms in the D-loop region of mitochondrial DNA is associated with colorectal cancer outcome

description: Single nucleotide polymorphisms (SNPs) in the displacement loop (D-Loop) of mitochondrial DNA (mtDNA) has been identified for their association with the risk and outcome in many cancers. We have identified risk associated D-loop SNPs for colorectal cancer previously, in the present study, we evaluate their prognostic value for postoperative survival of colorectal cancer (CRC). The minor haplotype of nucleotides 16290T and frequent haplotype of nucleotide 16298T in the hypervariable segment 1 (HV1) region of the D-loop were identified for their association with high survival rate of CRC. After adjusted with COX proportional hazard model, the nucleotide site of 16290 was identified as independent predictor for CRC (RR, 0.379; 95% CI, 0.171–0.839; <i>p</i> = 0.017). In conclusion, SNPs in the mtDNA D-Loop were found to be valuable markers for colorectal cancer outcome evaluation.
DOI: 10.6084/m9.figshare.1595938
title: Mining Company's Global Supply Chain - Logistics Data for a Medium Size Excavator

description: The company which provided the dataset is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of the company is estimated to be on the order of tens of billions and they sell products and parts via a worldwide dealer network. The company sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of the company - a medium size excavator.
DOI: 10.6084/m9.figshare.1595927.v1
title: Leishmania mexicana promastigote and amastigote flagellar pocket tomograms

description: Eight tomograms of the flagellar pocket of <em>Leishmania</em><em> mexicana</em>.
DOI: 10.6084/m9.figshare.1595936.v1
title: Single nucleotide polymorphisms in the D-loop region of mitochondrial DNA is associated with colorectal cancer outcome

description: Single nucleotide polymorphisms (SNPs) in the displacement loop (D-Loop) of mitochondrial DNA (mtDNA) has been identified for their association with the risk and outcome in many cancers. We have identified risk associated D-loop SNPs for colorectal cancer previously, in the present study, we evaluate their prognostic value for postoperative survival of colorectal cancer (CRC). The minor haplotype of nucleotides 16290T and frequent haplotype of nucleotide 16298T in the hypervariable segment 1 (HV1) region of the D-loop were identified for their association with high survival rate of CRC. After adjusted with COX proportional hazard model, the nucleotide site of 16290 was identified as independent predictor for CRC (RR, 0.379; 95% CI, 0.171–0.839; <i>p</i> = 0.017). In conclusion, SNPs in the mtDNA D-Loop were found to be valuable markers for colorectal cancer outcome evaluation.
DOI: 10.6084/m9.figshare.1595939.v1
title: Global Supply Chain - Random Logistics Data from a Caterpillar's Test Case

description: Caterpillar Inc. is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of Caterpillar is on the order of tens of billions and they sell products and parts via a worldwide dealer network. Caterpillar sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of Caterpillar - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been randomly generated in an interval between 0 and an upper limit which is a random increase over the maximum value in the original data, according to a negative exponential distribution.
DOI: 10.6084/m9.figshare.1595940.v1
title: Global Supply Chain - Uniformly Random Logistics Data from a Caterpillar's Test Case

description: Caterpillar Inc. is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of Caterpillar is on the order of tens of billions and they sell products and parts via a worldwide dealer network. Caterpillar sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of Caterpillar - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been generated according to a normal distribution with the same mean and standard deviation as in the original dataset (e.g. the demand figures have the same mean and standard deviation as those found in the original problem).
DOI: 10.6084/m9.figshare.1595913
title: Appendix to: Understanding the Dynamics of Test Driven Development

description: A lab package for the studies included in Fucci D. Ph.D. dissertation<em> Understanding the </em>Dynanics<em> of Test-Driven Development </em>
DOI: 10.6084/m9.figshare.1595915
title: Experimental Design Lab 1 - Field Data

description: Design Preparation To observe the effects of habitat type, and functional diversity on species richness at York University, a total of six locations were chosen. Three of which were grasslands and three of which were woodlots. The six locations chosen were: Stong Grassland, Danby Grassland, Boynton Grassland, Boyer Woodlot, Danby Woodlot and Boynton Woodlot. Each location was divided into a grid where all the quadrats were numbered. The size of each quadrat was 5 m x 5 m and every location had three quadrats that were randomly selected (with a random number generator) for every data collection period. The study occurred weekly over a course of 3 weeks and each field data collection period was consistently at the same three hour time period every week (2:30 pm – 5:30 pm). To gather data from all six locations within the three hour period, the group was divided into two pairs and both pairs collected data from three locations (out of six), both of which were randomly selected before each data collection period. Each pair carried brought with them 1-2 field guides and 1-2 transect measures and for every location, the pair had to count using steps or the transect measures to go to the selected quadrat. Data Collection To measure species richness and abundance, each pair formed a 5 m x 5 m quadrat using 1 or 2 of the transect measures taken and recorded the species that were observed as well as the number of each observed species within the quadrat. The data was recorded on a data sheet that was prepared beforehand. This process was repeated three times at each of the three locations. For those species that could not be identified, photographic evidence and/or a description of the unknown species was taken for later identification. Once all the species were identified, the functional group (forbs, shrubs, trees, grasses and herbs) for every observed species were identified and recorded. Statistical Methods To determine if the hypothesis and predications were supported or rejected, two statistical methods were used: t-test and correlation test. A t-test was used on the average species richness of all the grassland and woodlot locations to calculate the p-value. The p-value indicated if our results had been statistically significant (p-value &lt; 0.05) or not (p-value &gt; 0.05) i.e. it helped us determine if our results supported our prediction that grasslands had more species richness than woodlots. A correlation test was used to test if there was a correlation between species richness and functional groups. The test also indicated what type of correlation i.e. it indicated whether there was a positive correlation (0 &lt; correlation coefficient &lt; +1), or a negative correlation (-1 &lt; correlation coefficient &lt; 0) or no relationship at all (correlation coefficient equals approximately 0). So this test helped determine if number of tree species affected species richness negatively or if at all.
DOI: 10.6084/m9.figshare.1595939.v2
title: Mining Company's Global Supply Chain - Random Logistics Data from a Caterpillar

description: The company which provided the dataset is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of the company is estimated to be on the order of tens of billions and they sell products and parts via a worldwide dealer network. The company sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of the company - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been randomly generated in an interval between 0 and an upper limit which is a random increase over the maximum value in the original data, according to a negative exponential distribution.
DOI: 10.6084/m9.figshare.1595940.v2
title: Mining Company's Global Supply Chain - Uniformly Random Logistics Data from a Caterpillar

description: The company which provided the dataset is the world leader in manufacturing of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The current revenue of the company is estimated to be on the order of tens of billions and they sell products and parts via a worldwide dealer network. The company sells more than 3 million products and 700,000 parts in more than 20 countries around the world every year. They operate with more than 3,000 suppliers and 3,000 dealerships and their logistics operations alone are worth more than 60 million dollars per year. The dataset provided is one example of supply chain problem for one product of the company - a medium size excavator. In the current dataset, the number of dealers, production facilities and shipping ports is the same as in the original problem; it is only the demand figures, the production capacities, the transportation times and costs and the sale prices that have been randomly generated. The figures have been generated according to a normal distribution with the same mean and standard deviation as in the original dataset (e.g. the demand figures have the same mean and standard deviation as those found in the original problem).