The PASH Data Collection is comprised of Five data “realms”: 1) Survey and site data, 2) Settlement excavations, 3) Tumulus (burial mound) survey and excavations, 4) Artifact analysis, and 5) Geological data. All of the geological data from cores and auger holes have been made available in PASH Deep Blue Data Realm 5. , Much of the work conducted by PASH took place on a geomorphic feature we call the Shtoj alluvial fan. Geological research was done along the distal margins of the Shtoj alluvial fan in the fringing freshwater wetlands of Shkodër Lake. Field reconnaissance in 2010 consisted of drilling twelve 5-cm diameter auger holes across the fan to a maximum depth of 4.8 m. A composite sediment sample was collected every 0.3 m during drilling. Between 2012 and 2014, sediment cores were taken at four wetland locations on the southeastern shore of Shkodër Lake. North-south trending core locations were selected following results of samples collected during the 2010 reconnaissance and are 1 km east of the Shkodër Lake shoreline. Twenty-two cores, ranging in length from 0.24 m to 0.87 m, were taken from four sites using a 6.3-cm diameter polycarbonate piston corer. , and (See readme in Geological Data record for full documentation; Chapter linked to: Chapter Two).
The collection contains the code and the data used to train machine learning algorithms to emulate simplified physical parameterizations within the Community Atmosphere Model (CAM6). CAM6 is the atmospheric general circulation model (GCM) within the Community Earth System Model (CESM) framework, developed by the National Center for Atmospheric Research (NCAR). GCMs are made up of a dynamical core, responsible for the geophysical fluid flow calculations, and physical parameterization schemes, which estimate various unresolved processes. Simple physics schemes were used to train both random forests and neural networks in the interest of exploring the feasibility of machine learning techniques being used in conjunction with the dynamical core for improved efficiency of future climate and weather models. The results of the research show that various physical forcing tendencies and precipitation rates can be effectively emulated by the machine learning models.
This collection includes computed tomography (CT) scans of the cranial remains of Sanajeh indicus, a Late Cretaceous snake from Gujarat, India. In addition to the holotype (described by Wilson et al., 2010), a referred specimen (Zaher et al., 2022) has been collected from Dholi Dungri. The holotype includes a 'cranial block' (GSI/GC/2903) and the referred specimen also includes a partial skull (GSI/GC/DD4).
Both holotypic and referred specimens are housed in Geological Survey of India Palaeontology Division, Central Region in Nagpur, India. For assistance with access, please contact Dhananjay Mohabey ( dinomohabey@yahoo.com) or Bandana Samant ( bandanabhu@gmail.com). Casts of selected elements of Sanajeh indicus are available at the University of Michigan Museum of Paleontology.
The Sub-metered HVAC Implemented for Demand Response (SHIFDR) dataset is a massive dataset that captures the response of individual commercial building HVAC system components to demand response events. The dataset includes device-level power consumption during demand response events as well as during normal operation. We have organized the data into subsets, with each subset containing data from buildings in different parts of the world. Kindly refer to the README file within each subsection for specific information about how data is organized. Please reach out if you have data that you would like to share, find any mistakes in the data, or have any questions. We are always trying to improve SHIFDR.
This sub-collection includes Photographs and Photologs of the sites, a Site Database with information collected and observed about the site and Site documentation. Documentation consists of PDFs of scans of miscellaneous documents related to a particular site, including maps, wall drawings, original notes, etc. Data are organized according to site number: S001, S002, etc. There are 17 sites in total.