The objective of using the wireless sensors was to improve understanding of the heterogeneity of healthcare worker (HCW) contact with patients and the physical environment in patients’ rooms. The framework and design were based on contact networks with a) nodes defined by HCW’s, rooms, and items in the room and b) edges defined by HCW’s in the room, near the bed, and touching items. Nodes had characteristics of HCW role and room number. Edges had characteristics of day, start time, and duration. Thus, patterns and heterogeneity could be understood within contexts of time, space, roles, and patient characteristics. At the University of Utah Hospital Cardiovascular ICU (CVICU), a 20-bed unit, we collected data for 54 days. HCW contact with patients was measured using wireless sensors to capture time spent in patient rooms as well as time spent near the patient bed. HCW contact with the physical environment was measured using wireless sensors on the following items in patient rooms: door, sink, toilet, over-bed table, keyboard, vital signs monitor touchscreen, and cart. HCW’s clipped a sensor to their clothing or lanyard.
The data was obtained from the FDTD simulations. For one of the FDTD simulations, the conductivity data for British Columbia was used in order to obtain the simulated data. The data obtained from simulations are post-processed using MATLAB for plotting the figures in the paper.
This dataset summarizes burial counts according to burial type (free, temporary, or perpetual) for the cemeteries of Père-Lachaise, Montmartre, and Montparnasse in Paris. The data covers the period of 1804 to 1840 and was derived from the digitized daily records of burial for the city of Paris, which are currently held in the Archives de Paris. See Registres journaliers d'inhumation https://archives.paris.fr/r/216/cimetieres). These data are organized by the number of each burial type recorded per page of the digitized records.
This dataset accounts for all jobs undertaken by the Société Le Roy Bouillon, a funerary monuments company in Paris, from 1890 to 1902. The first sheet, “Activity Data” accounts for each job and the fee charged to the client for that job. It also categories each job as either a new cemetery construction, maintenance to existing cemetery structures, or other jobs unrelated to cemetery construction. The second sheet, “Outside Paris,” summarizes the annual activity, recording the number of projects undertaken within Paris versus outside of the city, new constructions versus maintenance work, and revenue coming in from each type of job. The original records are currently housed in a private collection in Paris and were manually transcribed by the author.
The dataset was collected in the process of carrying out a research on the effects of photochemical aging and interactions with secondary organic aerosols on cellular toxicity of combustion particles between the year 2021 to 2022
This dataset is based on the 1816, two-volume publication, Le champ du repos, ou le Cimetière Mont-Louis, dit du Père Delachaise. Compiled over the course of 1815 by MM. Roger and Roger (a father-son team), Le champ du repos contains the epitaphs and scale drawing of over 2000 monuments present in the cemetery of Père-Lachaise (Paris, France) by the end of 1815. The author of this dataset has combined the information from this volume (including demographics of the deceased drawn from epitaphs, visual characteristics of monuments, and the locations of monuments within the cemetery) with data from the digitized records of burial available from the Archives de Paris ( https://archives.paris.fr/r/216/cimetieres/). Thus, this dataset details every known monument present in the Cemetery of Père-Lachaise by the end of 1815 with information about the type of burial (free, temporary, or perpetual) that it marked.
This dataset covers all of the marbriers (stonecutters) listed in the commercial almanacs for the city of Paris from 1798 to 1907. The author used the almanacs available digitally on the Bibliothèque nationale de France's digital library, Gallica (gallica.bnf.fr). The dataset was initially compiled to study the development of the funerary monuments industry in Paris, although the dataset aggregates all stonemasons' enterprises and ateliers regardless of their field of specialization. Binary variables are included in the dataset, based on text descriptions in the almanacs, to indicate named areas of specialization.
Historically, the compilation of the annual commercial almanacs was a project undertaken by two different publishers (Bottin and Firmin Didot), who eventually merged in 1857. Every year, in addition to the information that had already been collected, corrections and additions were solicited from the general public. According to the notice included at the beginning of the 1838 issue, listing in the almanac was (and always had been) free. If one wanted details in addition to a general category of work to be included in a record, individuals needed to contact the editor directly (there is no mention of what this might have cost). See: Sébastien Bottin, Almanach du commerce de Paris, des départemens de la France, et des principals villes du monde (Paris, 1838); and Firmin Didot et Bottin Réunis, Annuaire et almanac du commerce, de l’industrie, de la magistrature et de l’administration (Paris: 1857).
We determined whether a large, multi-analyte panel of circulating biomarkers can improve detection of early-stage pancreatic ductal adenocarcinoma (PDAC). We defined a biologically relevant subspace of blood analytes based on previous identification in premalignant lesions or early-stage PDAC and evaluated each in pilot studies. The 31 analytes that met minimum diagnostic accuracy were measured in serum of 837 subjects (461 healthy, 194 benign pancreatic disease, 182 early stage PDAC). We used machine learning to develop classification algorithms using the relationship between subjects based on their changes across the predictors. Model performance was subsequently evaluated in an independent validation data set from 186 additional subjects.
This is the IDL code used to create the results published in Mace, G. G., Benson, S., Humphries, R., Gombert P. M., Sterner, E.: Natural marine cloud brightening in the Southern Ocean, Atmospheric Chemistry and Physics. The IDL code processes MOD03 geolocation fields, MOD06_L2 cloud retrievals, MODIS ocean color chlorophyll-a concentrations and CERES shortwave albedo data that is distributed by NASA data archives. It creates statistical results for non-precipitating or weakly precipitating warm, liquid, shallow, marine boundary layer clouds.
The data are bed-scale measurements taken from virtual outcrop models (Morris, E.A., Atlas, C.E., Johnson, C.L., 2023, Architectural analysis of the Panther Tongue - virtual outcrop models) and calibrated with measurements taken at outcrop in the field.