Contributors: Adrian Haas, Stephan Pfister, Christopher Zimdars
... This data is the result of the work and method developed in the scientific publication: "ENHANCING COMPREHENSIVE MEASUREMENT OF SOCIAL IMPACTS IN S-LCA BY INCLUDING ENVIRONMENTAL AND ECONOMIC ASPECTS", published in The International Journal of Life Cycle Assessment under DOI: 10.1007/s11367-017-1305-z It contains the limited version without the social hotspot database (SHDB). if you want to use the full version you need to have a license of SHDB and you can contact Stephan Pfister (firstname.lastname@example.org) to get further information on this. The data contains the MRIO data from EXIOBASE v2 and is only allowed to use with their data license: http://www.exiobase.eu/index.php/terms-of-use In summary, you need to pay a fee for commercial uses.
Contributors: Agnel Sfeir, Aaron Phillips, Marco tigano, ERIKA BRUNET
... Data included in Phillips et al.,
Contributors: Edoardo Paluan
... The aim of the project is to create an optical interferometer which can detect the acoustic analogue of a supernova explosion. The fingerprint of an acoustic wave propagating from a diapason will be measured. A Michelson Morley interferometer1 will be used, whereby analysis of the interference pattern will allow for the calculation of the frequency of the diapason.
Codes and Data for (Generalized entropy based possibilistic fuzzy C-Means for clustering noisy data and its convergence proof)
Contributors: Salar Askari Lasaki
... Dear Researcher, Thank you for using this code and datasets. I explain how GEPFCM code related to my paper "Generalized entropy based possibilistic fuzzy C-Means for clustering noisy data and its convergence proof" published in Neurocomputing, works. The main datasets mentioned in the paper together with GEPFCM code are included. If there is any question, feel free to contact me at: email@example.com firstname.lastname@example.org Regards, S. Askari
Contributors: Tejaswini Vuppu
... This is my Data Visuaization course project 2.
Contributors: Tejaswini Vuppu
... This is Visualization project 1
Parvalbumin expression in oligodendrocyte-like CG4 cells causes a reduction in mitochondrial volume, attenuation in reactive oxygen species production and a decrease in cell processes' length and branching
Contributors: Lucia Lichvarova, Walter Blum, Beat Schwaller and Viktoria Szabolcsi
... Forebrain glial cells - ependymal cells and astrocytes -acquire upon injury- a “reactive” phenotype associated with parvalbumin (PV) upregulation. Since free radicals, e.g. reactive oxygen species (ROS) play a role in the pathogenesis of multiple sclerosis, and that PV-upregulation in glial cells is inversely correlated with the level of oxidative stress, we hypothesized that PV-upregulation might also protect oligodendrocytes by decreasing ROS production. Lentiviral transduction techniques allowed for PV overexpression in CG4 oligodendrocyte progenitor cells (OPCs). Depending on the growth medium CG4 cells can be maintained in an OPC-like state, or induced to differentiate into an oligodendrocyte (OLG)-like phenotype. While increased levels of PV had no effect on cell proliferation and invasiveness in vitro, PV decreased the mitochondria volume in CG4 cell bodies, as well as the mitochondrial density in CG4 processes in both OPC-like and OLG-like states. In line with the PV-induced global decrease in mitochondrial volume, elevated PV levels reduced transcript levels of mitochondrial transcription factors involved in mitochondria biogenesis. In differentiated PV-overexpressing CG4 cells with a decreased mitochondrial volume, UV-induced ROS production was lower than in control CG4 cells hinting towards a possible role of PV in counteracting oxidative stress. Unexpectedly, PV also decreased the length of processes in undifferentiated CG4 cells and moreover diminished branching of differentiated CG4 cell processes, strongly correlated with the decreased density of mitochondria in CG4 cell processes. Thus besides conferring a protective role against oxidative stress, PV in a cell autonomous fashion additionally affects process’ growth and branching in CG4 cells.
Contributors: Danlei Qian
... It is a school project about the death causes and risk factors in USA
Contributors: HungChun Lin
... This is the report about the Suicide rate from 1985 to 2016, the dataset was got from Kaggle website (https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016), in this dataset, it contains country, year, sex, age, suicide number, population, suicide/100k pop, country-year, HDI for year, gdp_for_year, gdp_per_capita and generation. From this suicide rate dataset, we can know the trend of the suicide number by year, and also know which generation/age group has the highest suicide number. In this report, we also compared the suicide number to the other three factors to see is there any correlation between them, we compared the suicide number to GDP (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD), life expectancy (https://www.kaggle.com/kumarajarshi/life-expectancy-who) and happiness score to (http://worldhappiness.report/ed/2017/) find the correlation. Here are some conclusions for this report: •1. The suicide number of the male is higher than female. •2. The age group has the highest suicide number is 35-54 years. •3. The country which has the highest suicide number is Russian. •4. GDP, life expectancy and happiness score do not have a strong correlation with the suicide number. •5. Happiness score has a strong correlation with life expectancy. There are two files I attached, the ppt file is the result of my data mining, and the html file is about the processing I dealing with this data by Python.
... Data Source – The Organization for Economic Co-operation and Development (OECD) and World Bank Data bank. Got G-20 countries data from OECD and World Bank. Narrow down the selection to top ten countries in Healthcare, Educational and Military spending. Time Limit: I Used six years of data from 2010 to 2015 for my data analysis. Used Google API, Bar charts, Geo Maps, Stacked Bar Chart, Time series Line Chart and Pie charts to visualize my data.