Mendeley Data Showcase

This e-commerce dataset is used to do experiment about repeat buyer classification. The dataset is taken from e-commerce environment in Indonesia, supported by a digital transformation services company in Indonesia.

LP-L

The dataset contains data from development work on an innovative cloud-based payment system using blockchain architecture. The project aimed to create a secure micropayment system designed for fast, low-value transactions, dedicated mainly to underage clients, with particular emphasis on applications in games and other types of digital publications. The development work focused on creating a solution enabling nano and micropayments (payments of very small value – where amounts are counted in single grosz, eurocents, cents), whose processing was previously unprofitable due to technological costs exceeding the transaction value. The system was specifically optimized for rapid transaction processing while maintaining low operational costs. The dataset contains test results conducted in three main project stages: Verification of the possibility of placing the client application in the cloud computing environment along with storing sensitive data Testing of the IT solution prototype under laboratory conditions Results of tests in real conditions of the integrated cloud-based payment system The data includes raw results of system performance tests, results of external audits comparing the Billon platform with other blockchain solutions, as well as data on the effectiveness of proprietary security methods and data storage in the public cloud. Based on the full project title, I would propose this dataset title: "Development and Testing Dataset: Blockchain-Based Electronic Money System for Fast, Low-Value Transactions

An alternative food production system using hydroponics is proposed to grow vegetables in a controlled environment that is implementable in space. The proposed system is an autonomous, modular, scalable, and soilless food production platform (ASFP) that can be installed in a spacecraft by meeting requirements and constraints set by the National Aeronautics and Space Administration (NASA). A suite of Internet of Things (IoT) sensors was used to monitor indoor climate as well as water quality in ASFP. Average values of air temperature and relative humidity in the environmentally-controlled room are maintained between 20 – 24 °C and 48 – 62%, while water quality components, including dissolved oxygen (DO, ppm), electrical conductivity (EC, µS/m), pH, and water temperature (WT, Celsius) are monitored by the IoT sensor in real-time during the growing period. Repeated measure analysis is also performed to evaluate the plant growth performance. The result indicates that plant growth is attributed significantly to pH and EC values. A real-time data visualization and sharing platform is another avenue for the space farming ecosystem in the years to come.

This dataset contains the experimental data found in the manuscript entitled " Mitochondrial Mayhem: How Cigarette Smoke Induces Placental Dysfunction Through MMS19 Degradation ". The data is ordered according to the figures and tables in which they are found. The compressed file package contains the unedited photo of WB and FCM experiments, etc, and the Excel table for statistical bar chart raw data.

Major facilitator superfamily (MFS) transporter; Leishmania infantum (strain JPCM5)

Best relocations through HypoDD of the 2023-2024 seismicity at CF.

Polyhydroxyalkanoate (PHA) is studied as a plastic alternative due to plastic pollution, with focus on production, characterisation, application, and degradation, but its potential to act as a vector for heavy metal pollutants and bioaccumulate in the food chain is underexplored. Therefore, data were curated from the analyses of pollutant sorption, pollutant bioaccumulation, and antioxidant-enzyme modulation of four microparticles, poly(3-hydroxybutyrate) [P(3HB)], poly(3-hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-4HB)], polylactic acid (PLA), and polyethylene (PE), in single and co-exposure with lead (Pb) and copper (Cu).

This dataset includes concentrations of eight nitro-aromatic compounds in fine particulate matters and trace gases, aerosol surface area density, meteorological data collected in different seasons at nine urban, rural and mountain sites in eastern China. They were inputted into the ensemble machine learning model and the receptor source apportionment model to obtain comprehensive understanding on the contributions of primary emission sources, secondary formation pathways, and meteorological conditions.

These different files are the supplementary data not added to Chapter V of the Ph.D. thesis "Experimental study of the origin of mass-independent isotopic fractionations in cosmochemistry" and of the article: "Condensation of the fallout glasses in the Hiroshima nuclear fireball resulting in oxygen Mass-independent Fractionation". The supplementary data (S7) are backscattered electron and optical images of the Hiroshima glasses. The two table files present the chemical, triple oxygen and silicon isotope compositions for Hiroshima glasses. The chemical data file (ST1) shows the chemical composition of 94 Hiroshima glasses. This data was obtained by analyses with a Zeiss-EVO Scanning Electron Microscope (IPGP-Paris), a CAMECA SX-100 electron microprobe (Camparis-Paris), and a JXA-8530F field emission electron microprobe (Natural History Museum of Vienna). The oxygen and silicon triple isotope composition data (ST2) presents the result of analyses realized with the CAMECA IMS 1270 E7 ion microprobe (CNRS-CRPG, Nancy) on 20 Hiroshima glasses.