cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15139/s3/f22wng
title: Concepts of operations for autonomous vehicle dispatch operations [R9]

description: Once reliable vehicle-to-vehicle (V-to-V) and vehicle-to-infrastructure (V-to-I) networks are established, remote fleet management could aid in improved traffic flow as well as improving first response times for emergent situations that arise such as crashes or extreme weather events. Remote fleet managers of the future will monitor real-time traffic flows, ensure that disabled or crashed AVs receive assistance (including possibly taking control of individual vehicles), while also potentially redirecting traffic away from emergent events. Because these futuristic operators will have the ability to directly communicate with some, but not all, cars, they may be able to immediately communicate with equipped cars through the V-to-V network when problems emerge or congestion is high. Moreover, they may be able to change external signs and signals in order to communicate with non-equipped vehicles to ease traffic congestion and aid in emergency response. Remote fleet management of AVs will require an operations center staffed by personnel that resemble surface transportation dispatchers today, but these operators will have significantly more responsibilities. To this end, this report outlined three new functionalities unique to AV dispatchers as well as five broad Concepts of Operation (CONOPs) that illustrate how AV fleet management could develop, including Original Equipment Manufacturing (OEM) AV Dispatch Support, Robo-Taxi Dispatch, Autonomous Trucking Dispatch, Public Transportation AV Dispatch, and State/Regional AV Management and Dispatch.
DOI: 10.60863/sf/bccaek
title: Lemur Biorhythms and Life History Evolution

description: Raw Havers-Halberg Oscillation data from histological sections of primate teeth. Abstract: Skeletal histology supports the hypothesis that primate life histories are regulated by a neuroendocrine rhythm, the Havers-Halberg Oscillation (HHO). Interestingly, subfossil lemurs are outliers in HHO scaling relationships that have been discovered for haplorhine primates and other mammals. We present new data to determine whether these species represent the general lemur or strepsirrhine condition and to inform models about neuroendocrine-mediated life history evolution. We gathered the largest sample to date of HHO data from histological sections of primate teeth (including the subfossil lemurs) to assess the relationship of these chronobiological measures with life history-related variables including body mass, brain size, age at first female reproduction, and activity level. For anthropoids, these variables show strong correlations with HHO conforming to predictions, though body mass and endocranial volume are strongly correlated with HHO periodicity in this group. However, lemurs (possibly excepting Daubentonia) do not follow this pattern and show markedly less variability in HHO periodicity and lower correlation coefficients and slopes. Moreover, body mass is uncorrelated, and brain size and activity levels are more strongly correlated with HHO periodicity in these animals. We argue that lemurs evolved this pattern due to selection for risk-averse life histories driven by the unpredictability of the environment in Madagascar. These results reinforce the idea that HHO influences life history evolution differently in response to specific ecological selection regimes.
DOI: 10.5281/zenodo.10160381
title: SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark

description: In this repository, we present the PacBio and ONT simulated datasets used for benchmarking transcriptome reconstruction tools, as evaluated in the manuscript titled "SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark". The dataset includes simulated long reads, short reads, CAGE peaks, and a reduced reference annotation. Additionally, we have included reconstructed transcriptomes from each method, along with SQANTI3 output files. The SQANTI-SIM software can be accessed on GitHub at the following URL: https://github.com/ConesaLab/SQANTI-SIM.
description: - Please ensure to cite the original publication (listed below) when using these datasets.
DOI: 10.5281/zenodo.10160380
title: SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark

description: In this repository, we present the PacBio and ONT simulated datasets used for benchmarking transcriptome reconstruction tools, as evaluated in the manuscript titled "SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark". The dataset includes simulated long reads, short reads, CAGE peaks, and a reduced reference annotation. Additionally, we have included reconstructed transcriptomes from each method, along with SQANTI3 output files. The SQANTI-SIM software can be accessed on GitHub at the following URL: https://github.com/ConesaLab/SQANTI-SIM.
description: - Please ensure to cite the original publication (listed below) when using these datasets.
DOI: 10.25934/pr00009236
title: Validation of prognostic machine learning tools for forecasting clinical progression to enrich Alzheimer’s disease trials

description: It is estimated that around 50 million people currently live with dementia worldwide and this number will reach 152 million by 2050. Alzheimer’s disease is a neurodegenerative disorder and a leading cause of dementia as it is believed to account for 60-80% of cases. Over 90% of trials in Alzheimer’s disease have failed to demonstrate the effectiveness of the tested treatments. Key contributing factors to the failures of trials include individual heterogeneity (differences) in clinical progression and suboptimal patient selection. Clinical progression (progress of the disease) across Alzheimer’s disease patients is highly variable as some patients will decline very quickly and others will remain relatively stable for a long time. The inadvertent enrollment of patients who will remain stable into a trial is problematic because not only does it expose patients who are unlikely to benefit from treatment to unnecessary risks, but it also reduces a trial’s potential to detect treatment effects. Alzheimer’s disease trials therefore need enrichment strategies to select the most appropriate participants, individuals who will likely decline within the trials’ durations. 

We propose to use prognostic machine learning models that forecast disease progression to select participants who will likely decline within the typical trial duration as an enrichment strategy. We have previously trained and validated models on individuals with mild cognitive impairment (decline in mental abilities) and Alzheimer’s disease dementia who participated in observational studies (i.e. research that did not test potential treatments). With these models, we demonstrated enrichment with likely decliners can allow for substantial reductions in the number of patients that need to be recruited compared to standard clinical trial recruitment while preserving the same potential to detect treatment effects. We would like to validate these models on clinical trial subject groups to assess their generalizability, to quantify the impact of enriching trial samples with likely decliners, and to compare treatment efficacy in subgroups of likely decliners against the total patient populations.

Better patient selection is important for accelerating therapeutic development in Alzheimer’s disease. Prognostic models for enrichment can give trials higher chances for success by enhancing their power to detect treatment effects in the most appropriate patient populations.
DOI: 10.60863/sf/bbw6ig
title: A longitudinal study of the impact of COVID-19 restrictions on students’ health behavior, mental health and emotional well-being

description: The raw survey (longitudinal and cross-sectional) data on student health behavior and habits as well as their mental and emotional health during the COVID pandemic and the pre-COVID period. Background: COVID-related restrictions impacted the lives of students on and off campus during Academic Year 2020/2021. Methods: Our study collected data on student health behavior and habits as well as their mental and emotional health using anonymous surveys. We compared these data with data collected prior to COVID in the longitudinal part of our study (n = 721) and analyzed them for the cross-sectional part of the study (n = 506). Results: The longitudinal data show a significant difference for some student behaviors and habits, such as sleeping habits, physical activity, breakfast consumption, time spent online or playing video games, vaping, and marijuana use, during the COVID pandemic compared with pre-COVID data. Respondents also reported a significant increase in difficulty concentrating, remembering, or making decisions, as well as being impacted by feelings of sadness or hopelessness. Yet, there was no increase in the proportion of respondents considering, planning or attempting suicide during COVID. The cross-sectional data illuminate the negative effect of the overall situation and the restrictions on students’ mental and emotional well-being. Three-quarters of respondents reported having craved human interaction during the past six months, more than half felt that their mental/emotional health had been impacted by the lack of social events or the switch to virtual (online) teaching. Two-thirds or more of respondents also expressed that they felt less connected to their peers and less motivated in their studies than in previous semesters. Fifty percent or more of respondents selected anxious, stressed, overwhelmed, disconnected, tired, and fatigued as words that best described their emotional state during the pandemic. Conclusions: The impact of COVID-related restrictions on students’ behaviors and habits as well as their mental and emotional health was less severe than one would have expected based on studies during the early stage of the pandemic. While some behaviors and habits changed during the COVID pandemic compared with the pre-COVID period, the changes were not substantial overall. Our study did not find an increase in the proportion of respondents considering, planning or attempting suicide during COVID, although the cross-sectional data from our survey make the negative effect of the overall situation and the restrictions on students’ mental and emotional well-being evident. The impact of the pandemic will unquestionably be long-lasting and will necessitate further and future investigations.
DOI: 10.60863/sf/pgbo6r
title: Reliability of sonographic measurements of the ulnar collateral ligament: a multi-rater prospective study

description: Raw sonographic measurement data of the ulnar collateral ligament. Background: The use of sonography is a cost-effective and reliable method to evaluate upper extremity superficial tissue structural integrity and pathology. Establishing the measurement reliability of widely used diagnostic ultrasound evaluation for musculoskeletal assessment is paramount enhance accurate clinical evaluations. The objective of this study was to establish the inter-rater and intra-rater reliability of select ulnar collateral ligament (UCL) thickness measures at two distinct anatomical locations in intercollegiate baseball athletes using ultrasound imaging (USI). Methods: This was a prospective cohort study conducted in a university research laboratory and included a total of 17 NCAA Division I baseball athletes (age 20.4 ± 1.43, height = 183.63 cm ± 6.27 cm, mass = 89.28 kg ± 8.24 kg). Two trained clinicians measured UCL mid-substance and apex thickness in the throwing extremity, prospectively, on 5 occasions at 1-month intervals during rest. Intraclass correlation coefficients (ICCs) (model 3,3), associated standard error of measurement, and 95% minimal detectable change in thickness were derived. Results: Intrarater reliability estimates for operator 1 were 0.90–0.98 (mid-substance) and 0.91–0.99 (apex). Operator 2’s values were 0.92–0.97 and 0.93–0.99, respectively. The standard error of measurement (SEM) ranged from 0.045–0.071 cm (mid-substance) and 0.023–0.067 cm (apex). The minimal detectable difference (MDD95) was 0.12–0.20 cm (mid-substance) and 0.07–0.19 cm (apex). Interrater reliability was 0.86–0.96 (mid-substance) and 0.79–0.98 (apex); most ICCs were &gt;0.90. Measurement of UCL thickness at two locations demonstrated very good to excellent reliability with high precision. Using this protocol, two evaluators can obtain consistent UCL measurement at two positions. This finding has significant implications for the clinical evaluation of superficial tissue pathology of the same individual by two experienced practitioners.
DOI: 10.60863/sf/hwi1mx
title: Student health behavior and academic performance

description: Survey data and form of university student health behaviors and habits, and academic achievement. Objective: To explore the association between health behaviors and habits of university students and academic achievement. Participants: Six hundred fourteen undergraduate students at a state university in the United States. Methods: Students were invited over a 2-year period to participate in an anonymous online survey that asked questions concerning a wide range of health behaviors and habits; participants were asked to report their current grade point average (GPA). Standard Least Squares Models were used to examine differences in self-reported GPA across the different health behaviors and habits, with individuals as replicates. Results: The study found positive associations between breakfast consumption, physical activity, and strength training and self-reported GPA, and negative associations between the hours of sleep per night, hours worked per week, fast food and energy drinks consumption, and use of marijuana, alcohol and electronic vaping products. Conclusions: While there is an association for some of the studied health behaviors and habits with self-reported GPA, the effect sizes for these health behaviors were low. The significant effect of vaping on GPA as well as the increased use reported in this study indicates that the topic should be explored further. Furthermore, students should be educated on the potential positive and negative effects of health behavior choices to help them make better choices.
DOI: 10.6084/m9.figshare.24595968
title: Pullout_evaluation_dataset.xlsx

description: This file shows the pull-out test results of corroded specimens and the related calculations of accelerated corrosion.
DOI: 10.6084/m9.figshare.24595968.v1
title: Pullout_evaluation_dataset.xlsx

description: This file shows the pull-out test results of corroded specimens and the related calculations of accelerated corrosion.
DOI: 10.6084/m9.figshare.24324406
title: LtEc Genome

description: FASTA file of Earthworm genome assembly.
DOI: 10.6084/m9.figshare.24324406.v1
title: LtEc Genome

description: FASTA file of Earthworm genome assembly.
DOI: 10.60863/sf/3c1mit
title: The immediate effect of a single session of pain neuroscience education on pain and the autonomic nervous system in subjects with persistent pain, a pilot study

description: File contains pupil diameter raw data collected from individuals with persistent pain. Background: The autonomic nervous system is a system that operates at the subconscious level and has been associated with neurobehavioral aspects of pain. Overall, persistent pain has a stimulating effect on the sympathetic nervous system. A promising emerging nonpharmacological treatment to manage persistent pain is neuroscience-based pain education. The overarching goal of neuroscience-based pain education is to change cognitions about pain and the pain experience through education. The aim was to determine the immediate and short-term impact of a neuroscience-based pain education video on the autonomic nervous system and pain in a subgroup of individuals with persistent pain. Methods: A convenience sample of 26 subjects were recruited for this study. Each subject indicated their pain level at the time of testing using a Visual Analogue Scale. Automated pupillometry was utilized to measure pupil diameter. After two minutes of accommodation to the goggles, the pupil was measured continuously for 60 s. Following this a 5-minute video presentation “Understanding Pain” was watched, followed by a continuous pupil measurement for 60 s. Three minutes after this measure, the final pupil diameter measurement was taken for 60 s. After completing the final pupil measure, the subject was asked to fill out a second Visual Analogue Scale and a Global Rate of Change. Outcomes: Each subject completed a Global Rating of Change Scale and the mean score was 1.14 (SD = 1.61 and a SEM = 0.), supporting the hypothesis of an overall self-perceived benefit from the intervention. There was a statistically significant difference in pain following the video, P &lt; 0.01. A significant correlation was observed between the self-perceived decrease in pain level and the Global Rating of Change score, p = 0.02. There was no statistically significant difference in the mean pupil diameter following the video with p = 0.76 for the right eye and p = 0.250 for the left eye. Discussion: This pilot study demonstrated that a 5-minute neuroscience-based pain education video reduced perceived pain in a small sample of subjects with persistent pain. Watching the neuroscience-based pain education video did not seem to result in an immediate generalized autonomic nervous system response. However, it resulted in a different reaction on each eye. This unequal response might be the result of the hemispheric lateralization of the ANS. This study supports the fact that the pain experience is determined by the balance between conscious cognitive processes and subconscious processes based on previous psychological experiences.
DOI: 10.5281/zenodo.10073442
title: Terraling SSWL Dataset

description: This is the Terraling SSWL dataset of November 5th 2023. The dataset can be found on https://terraling.com/groups/7.
We are still deciding who to list as creators  (probably, editors, all property authors, and architect and developpers of the webapplication.)
For citation purposes,  the names of those contributors who contributed data, is available on request. Note that the contributed data and examples are publicly accessible on the TerraLing website. In the dataset version posted here, the names are coded as numbers for security reasons.
DOI: 10.5281/zenodo.10073443
title: Terraling SSWL Dataset

description: This is the Terraling SSWL dataset of November 5th 2023. The dataset can be found on https://terraling.com/groups/7.
We are still deciding who to list as creators  (probably, editors, all property authors, and architect and developpers of the webapplication.)
For citation purposes,  the names of those contributors who contributed data, is available on request. Note that the contributed data and examples are publicly accessible on the TerraLing website. In the dataset version posted here, the names are coded as numbers for security reasons.
DOI: 10.3886/e186521v2-143183
title: Income and Inequality in the Aztec Empire on the Eve of the Spanish Conquest

description: Today, Latin American countries are characterized by relatively high levels of economic inequality. This circumstance has often been considered a long-run consequence of the Conquest and of the highly extractive institutions imposed by the colonizers. We show that, in the case of the Aztec Empire, high inequality predates the Spanish Conquest. We reach this conclusion by estimating levels of income inequality and of imperial extraction across the Empire. We find that the richest 1% earned 41.8% of the total income, while the income share of the poorest 50% was just 23.3%. We also argue that those provinces which had resisted the Aztec expansion suffered from relatively harsh conditions, including higher taxes, in the context of the imperial system – and were the first to rebel, allying themselves with the Spaniards. After the Spanish-Aztec War, the colonial elites inherited pre-existing extractive institutions, and added additional layers of social and economic inequality. <br><br><br><br><br>
DOI: 10.25452/figshare.plus.24503680
title: Image Data for "Quantum Computing Dataset of Maximum Independent Set Problem on King’s Lattice of over Hundred Rydberg Atoms" from Exp 1 to 30

description: This is Image Data for Exp 1 to 30 described from "Quantum Computing Dataset of Maximum Independent Set Problem on King’s Lattice of over Hundred Rydberg Atoms". Raw image files are in TIF format, constituting a list of image files structured as a three-dimensional array. The first two dimensions denote the image, while the third dimension represents the stack of images across experimental repetitions. Due to the substantial file size, raw data is segmented into multiple files for the same experiments, named as ‘Exp{Exp#}_X{#}.tif’, where Exp# corresponds to the experiment index, and # is assigned in sequential order. The raw data can be utilized to generate fluorescence data (‘flouAreshape’) and digitized data (‘floudigreshape’), provided in https://doi.org/10.6084/m9.figshare.23828004, using the code (‘Digitze_Data.m’) available on https://doi.org/10.6084/m9.figshare.23911368.Finding the maximum independent set (MIS) of a large-size graph is a nondeterministic polynomial-time (NP)-complete problem not efficiently solvable with classical computations but may be suitable for quantum computation. In recent years, there are growing interests in using Rydberg-atom arrays to solve the MIS problem. Here, we report a set of quantum adiabatic computing data of Rydberg-atom experiments performed with up to 141 atoms randomly arranged on the King’s lattice. A total of 582,916 events of Rydberg-atom measurements are collected for experimental MIS solutions of 733,853 different graphs. We provide the raw image data along with the entire binary determinations of the measured many-body ground states and the classified graph data, to offer bench-mark testing and advanced data-driven analyses for validation of the performance of the Rydberg-atom approach as well as system improvements.