Mendeley Data Showcase

Do file and dataset for dominance analysis on US cause-deleted age-at-death distributions. Abstract: Comparisons of cause-of-death mortality burdens ignore contributions to lifespan inequality or assess them separately from life expectancy impacts. We compare cause-of-death mortality burdens that take account of contributions to both life expectancy and lifespan inequality. Using 2021 U.S. National Center for Health Statistics mortality data stratified by sex and race/ethnic group, we distinguish eight causes of death (deaths of despair, homicides, accidents, CVD, cancer, COVID-19, infectious diseases, and respiratory diseases), construct a cause-deleted life table for each and use it to simulate an age-at-death distribution if that cause were eliminated. We rank these distributions and the respective causes using (higher-order) stochastic dominance analysis founded on value judgments concerning the distribution of lifespan. If longer and more equal lifespans are considered better, then we find that among non-Hispanic (NH) Whites, deaths of despair impose a larger mortality burden than those generated by homicides, COVID-19 (males), cancers (males), infectious diseases and respiratory diseases. If concern about lifespan inequality is stronger around younger ages at death, then the mortality burden of deaths of despair is even larger than that of CVD for NH White males. For NH Black males, the mortality burden of homicides is larger than that of respiratory diseases if there is concern about lifespan inequality and it is larger than the burdens of COVID-19 and cancers if there is greater concern about inequality between younger ages of death. These and other results can inform inequality-sensitive decision-makers looking to prioritize interventions that target causes of death that contribute most to the mortality burden through both reduced life expectancy and increased lifespan dispersion.

The results of the tests conducted on the 30 different rock samples.

Supplemental material for "Food Restriction Patterns and Their Impact on Growth and Nutrition in Chinese Pediatric Atopic Dermatitis: A Cross-Sectional Study"

Wound dressings serve as a crucial first barrier against microbial contamination, particularly in severe wounds requiring rapid antimicrobial protection. Building on our previously established hydrogel system based on copolymers of oligo(ethylene glycol) methyl ether methacrylate (OEGMA) and 2-(dimethylamino)ethyl methacrylate (DMAEMA) crosslinked during quaternization with 1,6-dibromohexane, we extend the biological evaluation of this contact-active material to a broader spectrum of clinically relevant pathogens. The hydrogel was assessed against the complete multidrug resistant ESKAPE group, the Gram-positive bacterium Staphylococcus mutans, and the opportunistic yeast Candida albicans. Pronounced contact-mediated antimicrobial activity was observed against all tested organisms, resulting in a significant reduction of microbial viability. Importantly, the material retained excellent biocompatibility, showing no adverse effects on mammalian skin fibroblasts or human blood cells. The combination of broad-spectrum antimicrobial efficacy, biological compatibility, and a robust yet simple fabrication approach highlights the potential of this hydrogel as a next-generation wound dressing and a promising first-line option for emergency wound care of critical injuries.

The files contained in this folder allow replication of the analysis presented in “Cultural Industry Meets Tourism: Productive Intersectoral Spillovers and Cluster Synergies” (C. Bernini, S. Emili, F. Galli). Although the original data are confidential, following the procedures described in the README and the accompanying scripts allows reconstruction of the final dataset used for model estimation. For transparency and replication purposes, the folder also includes an example dataset with randomly generated (perturbed) data.

This data set contains files to allow the replication of results found in the article "Modelling electricity markets when renewable power increases" by Clas Eriksson, Johan Lindén and Christos Papahristodoulou. The abstract below describes the article, its research question and its findings. The files in the data set are the following. readme.txt - containing an overview of the material and instructions for replication elsim16.r - a program in the R programming language, used for simulating the theoretical model in the article plots16.zip - a compressed directory containing all graphs generated by the simulation model in the eps and png formats Abstract of the article We analyze theoretically a simple model of the electricity market where the supply of Variable Renewable Electricity (VRE) and demand are both shifting stochastically over time. The correlation between these shifts is crucial for the equilibrium price of electricity. Based on hourly equilibria we compute yearly producer surpluses, consumer utility and the value factor of VRE, under different conditions. While an increasing correlation between VRE and demand causes a decline in average price and total producer surplus, the VRE producer surplus increases, because these producers sell much when price is high. Higher VRE and peak capacities reduce the average price and the total producer surplus, but a negative correlation can counteract this, by causing high prices more frequently. In addition, the value factor of VRE does not decline monotonously, contrary to findings in previous studies.

Data para la creacion del poster del seminario Doctoral 1

Dataset for an experiment following robotics competition on an university

Data para Seminario de Investigación 2

This folder contains Stata code and associated data files for conducting regression analysis in the paper, "Water Resource Tax and Corporate Bank Debt: Evidence from China." The data used in this paper are publicly available, and the code is compatible with Stata version MP17.