Mendeley Data Showcase

This is a dataset containing panel data of HSR connection and intercity co-patents.

Palmistichus elaeisis (HYMENOPTERA: EULOPHIDAE) REARING IN Tenebrio molitor (COLEOPTERA: TENEBRIONIDAE) SUBMITTED TO DIFFERENT DIETS

Data related to analyses of the project FONDECYT DOI 1114 0143. Mothers and their children were evaluated comprising a sample of 101 subjects. Evaluations were conducted at the Universidad de Chile Clinical Hospital.

Supplemental Table Footnotes: Accuracy of Medicaid Physician Directories by state. States marked with an asterisk (*) have implemented Medicaid expansion. The accuracy of directories was calculated by dividing the number of dermatologists accepting Medicaid (verified by call) by the number of dermatologists appearing in the directory. Chi-square test does not show significant differences based on Medicaid expansion (p=0.27).

Golden Software Inc. included the method of cokriging in the newest version of SURFER 17. This has opened a new tool for interpreting geochemical data. We can use cokriging in SURFER 17 to improve the quality of maps and to predict similar targets in nearby areas. We use cokriging when we want to process data from different datasets. One dataset is always smaller than the other. Here, I first tasted the method with a hypothetical geochemical model combining a smaller dataset of FA gold results with a larger dataset of ICP-MS multi-elements. Later, I applied this method to real data from a soil sampling project in Mozambique. I tested a known mineralized target and also an extended area to predict gold targets. I also had the gold results for the extended area. They allowed me to confirm the effectiveness of cokriging in predicting the new targets. There are many opportunities where we can apply cokriging as a prediction tool. One situation is when an initial sampling returned a group of interesting but isolated gold results. We can then use a cheaper method, like ICP-MS, to better understand the gold distribution in the area.

Voice data of 23 different speakers (11 women and 12 men) were gathered for the experimental validation of the effectiveness of the developed methods. These persons dictated 64 responses present in the script tree using different variants of command formulations.

This data is the network information and demand of scenario 1 for the sample network

Database from Strong Treat 1 to 4 study - aimed to assess whether multiple doses of ivermectin were superior to a single dose for the treatment of strongyloidiasis.

The third-order elastic constants (TOECs) are fundamental to describe crystal’s nonlinear response to stress, and can be applied to explore anharmonic properties of crystals such as Grüneisen parameters, thermal expansion coefficient, and the effect of pressure on second-order elastic constants (SOECs). Here, we report an open-source python package, Elastic3rd, which is able to calculate the SOECs and TOECs using the strain–energy method for crystals with any symmetry from first-principles calculations. An algorithm to generate necessary strain modes and the corresponding coefficients for a given symmetry is proposed. These strain modes are then applied to the fully relaxed structure to generate the deformed structures. The total energies of the strained structures are calculated by a chosen first-principles code, and the SOECs and TOECs are determined by fitting the resulted strain–energy data. The present code has been validated by several case studies of C, Si and Mg, and the case of MnP4 shows the ability for low-symmetry crystals.

Antibacterial use in long-term care facilities in Canton VD, Switzerland