cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25380/iastate.7464500
title: Observation of η-Al41Sm5 reveals motif-aware structural evolution in Al-Sm alloys

description: Using an effective genetic algorithm, we uncover the structure of a metastable Al41Sm5 phase that supplements its family sharing similar short-range orders. The phase evolves upon heating an amorphous Al-9.7at.%Sm ribbon, produced by melt-spinning. The dynamical phase selection is discussed with respect to the structural connections between the short-range packing motifs in the amorphous precursor and those observed in the selected phases. This dataset includes information such as the crystal structure of Al41Sm5, the short-range packing motifs, experimental and calculated XRD, formation energy of stable and meta-stable phases in the Al-Sm system.<br>
DOI: 10.25380/iastate.7464500.v1
title: Observation of η-Al41Sm5 reveals motif-aware structural evolution in Al-Sm alloys

description: Using an effective genetic algorithm, we uncover the structure of a metastable Al41Sm5 phase that supplements its family sharing similar short-range orders. The phase evolves upon heating an amorphous Al-9.7at.%Sm ribbon, produced by melt-spinning. The dynamical phase selection is discussed with respect to the structural connections between the short-range packing motifs in the amorphous precursor and those observed in the selected phases. This dataset includes information such as the crystal structure of Al41Sm5, the short-range packing motifs, experimental and calculated XRD, formation energy of stable and meta-stable phases in the Al-Sm system.<br>
DOI: 10.7284/123877
title: GNSS (Global Navigation Satellite System) data collected during research cruise MGL1609 using a C&C C-Nav 2000 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123881
title: GNSS (Global Navigation Satellite System) data collected during research cruise MGL1609 using a C&C C-Nav 3050 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7464464
title: Efficiency of genomic prediction of non-assessed testcrosses

description: Data set of 12,000 DHs from three populations(biparental and open-pollinated) and 20,000 testcrosses (with two elite inbred lines)<br>
DOI: 10.7284/123878
title: Gravimeter data collected during research cruise MGL1609 using a Bell BGM-3 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7464452
title: Data for Paper: Advanced DNA fingerprints genotyping of chip electrophoresis samples

description: Large-scale comparative studies of DNA fingerprints prefer automated chip capillary electrophoresis instead of conventional gel planar electrophoresis due to the higher precision of the digitalization process. However, the determination of band sizes is still limited by the device resolution and sizing accuracy. Band matching, therefore, remains the key step in DNA fingerprint analysis. Current methods mostly evaluate only the pair similarity of the samples, using heuristically determined constant thresholds to evaluate the maximum allowed band size deviation. Such an approach significantly reduces the ability to distinguish between closely related samples. In this study, a new approach based on global multiple alignments of bands of all samples, with an adaptive threshold derived from the detailed migration analysis of a large number of real samples, is presented. The proposed approach allows accurate automated analysis of DNA fingerprint similarities for extensive epidemiological studies of bacterial strains, thereby helping to prevent the spread of dangerous microbial infections.
DOI: 10.6084/m9.figshare.7464464.v1
title: Efficiency of genomic prediction of non-assessed testcrosses

description: Data set of 12,000 DHs from three populations(biparental and open-pollinated) and 20,000 testcrosses (with two elite inbred lines)<br>
DOI: 10.7284/123876
title: Gyrocompass data collected during research cruise MGL1609 using a Kongsberg Simrad GC80 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7464452.v2
title: Data for Paper: Advanced DNA fingerprints genotyping of chip electrophoresis samples

description: Large-scale comparative studies of DNA fingerprints prefer automated chip capillary electrophoresis instead of conventional gel planar electrophoresis due to the higher precision of the digitalization process. However, the determination of band sizes is still limited by the device resolution and sizing accuracy. Band matching, therefore, remains the key step in DNA fingerprint analysis. Current methods mostly evaluate only the pair similarity of the samples, using heuristically determined constant thresholds to evaluate the maximum allowed band size deviation. Such an approach significantly reduces the ability to distinguish between closely related samples. In this study, a new approach based on global multiple alignments of bands of all samples, with an adaptive threshold derived from the detailed migration analysis of a large number of real samples, is presented. The proposed approach allows accurate automated analysis of DNA fingerprint similarities for extensive epidemiological studies of bacterial strains, thereby helping to prevent the spread of dangerous microbial infections.
DOI: 10.7284/123874
title: INS (Inertial Navigation System) data collected during research cruise MGL1609 using a Kongsberg Seapath 200 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7464452.v1
title: Data for Paper: Advanced DNA fingerprints genotyping of chip electrophoresis samples

description: Large-scale comparative studies of DNA fingerprints prefer automated chip capillary electrophoresis instead of conventional gel planar electrophoresis due to the higher precision of the digitalization process. However, the determination of band sizes is still limited by the device resolution and sizing accuracy. Band matching, therefore, remains the key step in DNA fingerprint analysis. Current methods mostly evaluate only the pair similarity of the samples, using heuristically determined constant thresholds to evaluate the maximum allowed band size deviation. Such an approach significantly reduces the ability to distinguish between closely related samples. In this study, a new approach based on global multiple alignments of bands of all samples, with an adaptive threshold derived from the detailed migration analysis of a large number of real samples, is presented. The proposed approach allows accurate automated analysis of DNA fingerprint similarities for extensive epidemiological studies of bacterial strains, thereby helping to prevent the spread of dangerous microbial infections.
DOI: 10.7284/123879
title: INS (Inertial Navigation System) data collected during research cruise MGL1609 using a Applanix POS/MV-320 V3 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123872
title: Multibeam Echosounder data collected during research cruise MGL1609 using a Kongsberg EM122 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123880
title: pCO2 (Partial Pressure of Carbon Dioxide) data collected during research cruise MGL1609 using a LDEO pCO2 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123873
title: Speedlog data collected during research cruise MGL1609 using a Furuno DS-50 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123875
title: TSG (Thermosalinograph) data collected during research cruise MGL1609 using a Sea-Bird SBE-21 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123649
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise MGL1610 using a Hawaii UHDAS instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123637
title: Expendable Probe data collected during research cruise MGL1610 using a Sippican MK21 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123646
title: GNSS (Global Navigation Satellite System) data collected during research cruise MGL1610 using a C&C C-Nav 2000 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123651
title: GNSS (Global Navigation Satellite System) data collected during research cruise MGL1610 using a C&C C-Nav 3050 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123647
title: Gravimeter data collected during research cruise MGL1610 using a Bell BGM-3 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7462220
title: Pretrained classifier.rar

description: Pretrained classifiers
DOI: 10.6084/m9.figshare.7462220.v1
title: Pretrained classifier.rar

description: Pretrained classifiers
DOI: 10.7284/123645
title: Gyrocompass data collected during research cruise MGL1610 using a Kongsberg Simrad GC80 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/123643
title: INS (Inertial Navigation System) data collected during research cruise MGL1610 using a Kongsberg Seapath 200 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7462139
title: Development of injury risk models to guide CT evaluation in the emergency department after motor vehicle collisions

description: <b>Objective:</b> The clinical evaluation of motor vehicle collision (MVC) victims is challenging and commonly relies on computed tomography (CT) to detect internal injuries. CT scans are financially expensive and each scan exposes the patient to additional ionizing radiation with an associated, albeit low, risk of cancer. Injury risk prediction based on regression modeling has been to be shown to be successful in estimating Injury Severity Scores (ISSs). The objective of this study was to (1) create risk models for internal injuries of occupants involved in MVCs based on CT body regions (head, neck, chest, abdomen/pelvis, cervical spine, thoracic spine, and lumbar spine) and (2) evaluate the performance of these risk prediction models to predict internal injury. <b>Methods:</b> All Abbreviated Injury Scale (AIS) 2008 injury codes were classified based on which CT body region would be necessary to scan in order to make the diagnosis. Cases were identified from the NASS-CDS. The NASS-CDS data set was queried for cases of adult occupants who sought medical care and for which key crash characteristics were all present. Forward stepwise logistic regression was performed on data from 2010–2014 to create models predicting risk of internal injury for each CT body region. Injury risk for each region was grouped into 5 levels: very low (&lt;2%), low (2–5%), medium (5–10%), high (10–20%), and very high (20%). The models were then tested using weighted data from 2015 in order to determine whether injury rates fell within the predicted risk level. <b>Results:</b> The inclusion and exclusion criteria identified 5,477 cases in the NASS-CDS database. Cases from 2010–2014 were used for risk modeling (<i>n</i> = 4,826). Seven internal injury risk models were created based on the CT body regions using data from 2010–2014. These models were tested against data from 2015 (<i>n</i> = 651). In all CT body regions, the majority of occupants fell in the very low or low predicted injury rate groups, except for the head. On average, 57% of patients were classified as very low risk and 15% as low risk for each body region. In most cases the actual rate of injury was within the predicted injury risk range. The 95% confidence interval overlapped with predicting injury risk range in all cases. <b>Conclusion:</b> This study successfully demonstrated the ability for internal injury risk models to accurately identify occupants at low risk for internal injury in individual body regions. This represents a step towards incorporating telemetry data into a clinical tool to guide physicians in the use of CT for the evaluation of MVC victims.
DOI: 10.7284/123648
title: INS (Inertial Navigation System) data collected during research cruise MGL1610 using a Applanix POS/MV-320 V3 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7462139.v1
title: Development of injury risk models to guide CT evaluation in the emergency department after motor vehicle collisions

description: <b>Objective:</b> The clinical evaluation of motor vehicle collision (MVC) victims is challenging and commonly relies on computed tomography (CT) to detect internal injuries. CT scans are financially expensive and each scan exposes the patient to additional ionizing radiation with an associated, albeit low, risk of cancer. Injury risk prediction based on regression modeling has been to be shown to be successful in estimating Injury Severity Scores (ISSs). The objective of this study was to (1) create risk models for internal injuries of occupants involved in MVCs based on CT body regions (head, neck, chest, abdomen/pelvis, cervical spine, thoracic spine, and lumbar spine) and (2) evaluate the performance of these risk prediction models to predict internal injury. <b>Methods:</b> All Abbreviated Injury Scale (AIS) 2008 injury codes were classified based on which CT body region would be necessary to scan in order to make the diagnosis. Cases were identified from the NASS-CDS. The NASS-CDS data set was queried for cases of adult occupants who sought medical care and for which key crash characteristics were all present. Forward stepwise logistic regression was performed on data from 2010–2014 to create models predicting risk of internal injury for each CT body region. Injury risk for each region was grouped into 5 levels: very low (&lt;2%), low (2–5%), medium (5–10%), high (10–20%), and very high (20%). The models were then tested using weighted data from 2015 in order to determine whether injury rates fell within the predicted risk level. <b>Results:</b> The inclusion and exclusion criteria identified 5,477 cases in the NASS-CDS database. Cases from 2010–2014 were used for risk modeling (<i>n</i> = 4,826). Seven internal injury risk models were created based on the CT body regions using data from 2010–2014. These models were tested against data from 2015 (<i>n</i> = 651). In all CT body regions, the majority of occupants fell in the very low or low predicted injury rate groups, except for the head. On average, 57% of patients were classified as very low risk and 15% as low risk for each body region. In most cases the actual rate of injury was within the predicted injury risk range. The 95% confidence interval overlapped with predicting injury risk range in all cases. <b>Conclusion:</b> This study successfully demonstrated the ability for internal injury risk models to accurately identify occupants at low risk for internal injury in individual body regions. This represents a step towards incorporating telemetry data into a clinical tool to guide physicians in the use of CT for the evaluation of MVC victims.
DOI: 10.6084/m9.figshare.7462178.v1
title: A1. Roadside Reveg An Integrated Approach to Establishing Native Plants

description: File set of 26 publications put into this data repository program for a published journal article.<br>
DOI: 10.7284/123640
title: Magnetometer data collected during research cruise MGL1610 using a Geometrics G-882 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7462094
title: Fig 3 S2.xlsx

description: Raw data about behavioral response of Aedes aegypti larvae
DOI: 10.6084/m9.figshare.7462082
title: Fig 1 S1.xlsx

description: Raw data from dose-response curve
DOI: 10.6084/m9.figshare.7462178.v2
title: Reference A1-A26. Roadside Reveg An Integrated Approach to Establishing Native Plants

description: File set of 26 publications put into this data repository program for a published journal article.<br>
DOI: 10.7284/123638
title: Multibeam Echosounder data collected during research cruise MGL1610 using a Kongsberg EM122 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7462082.v1
title: Fig 1 S1.xlsx

description: Raw data from dose-response curve
DOI: 10.6084/m9.figshare.7462094.v1
title: Fig 3 S2.xlsx

description: Raw data about behavioral response of Aedes aegypti larvae
DOI: 10.6084/m9.figshare.7462178.v3
title: References A1-A26. Roadside Reveg An Integrated Approach to Establishing Native Plants

description: File set of 26 publications put into this data repository program for a published journal article.<br>
DOI: 10.7284/123650
title: pCO2 (Partial Pressure of Carbon Dioxide) data collected during research cruise MGL1610 using a LDEO pCO2 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.17028/rd.lboro.7462064
title: Supplementary information files for article: 'Simple and ultrafast resonance frequency and dissipation shift measurements using a fixed frequency drive'

description: Supplementary information files for article: 'Simple and ultrafast resonance frequency and dissipation shift measurements using a fixed frequency drive'. A new method for determination of resonance frequency and dissipation of a mechanical oscillator is presented. Analytical expressions derived using the Butterworth-Van Dyke equivalent electrical circuit allow the determination of resonance frequency and dissipation directly from each impedance datapoint acquired at a fixed amplitude and frequency of drive, with no need for numerical fitting or measurement dead time unlike the conventional impedance or ring-down analysis methods. This enables an ultrahigh time resolution and superior noise performance with relatively simple instrumentation. Quantitative validations were carried out successfully against the impedance analysis method for inertial and viscous loading experiments on a 14.3 MHz quartz crystal resonator (QCR). Resonance frequency shifts associated with the transient processes of quick needle touches on a thiol self-assembled-monolayer functionalised QCR in liquid were measured with a time resolution of 112 μs, which is nearly two orders of magnitude better than the fastest reported quartz crystal microbalance. This simple and fast fixed frequency drive (FFD) based method for determination of resonance frequency and dissipation is potentially more easily multiplexable and implementable on a single silicon chip delivering economies of scale.
DOI: 10.7284/123641
title: Singlebeam Echosounder data collected during research cruise MGL1610 using a Knudsen 3260 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.25377/sussex.7462016
title: Research data for technical report: PhD supervisors and faculty members might help to avoid burnout as well as enhance engagement and organisational citizenship behaviour (OCB) among PhD students.

description: <b>Description:</b><br>The original dataset with responses to survey questions in .dta and .sav formats. A copy of STATA and SPSS for Statistics is required to view these datasets offline. <br>A .inp and .dat file are attached to carry out Structural Equation Modeling (SEM). A copy of Mplus software is required to view and manipulate these datasets offline. <br> The original survey showing the question export tags is available in Word format (PhD_students_survey_uk.docx). <br>An excel file (var_list_phd_survey_uk.xlsx) contains the following information regarding the items used in this study: a) Question export tags (codes in the dataset)b) Construct measuredc) Dimension of the construct measuredd) Source of the item or scale.<br> <b>Abstract:</b> There has been increased interest in the wellbeing and mental health of postgraduate students in light of the recent portrayal of the academic career as overworked and isolated. Research points to PhD students as being particularly at risk, yet the factors that contribute to PhD students’ compromised wellbeing are unclear. In this study (<i>N</i>= 392), we combine the social cure approach in social psychology with advances in organizational psychology to investigate potential predictors of work-related wellbeing and organisational citizenship behaviour (OCB) among PhD students in the UK. In particular, we explore the relationships between social support, willingness to support others, clarity of role, group belonging, engagement, and burnout using structural equation modelling (SEM). Our results point to the importance of support provided by both the supervisor and faculty members in helping to avoid burnout and enhance engagement among students. We also found that students’ identification with supervisors and faculty members together with clarity of role are positively associated with students’ work-related well-being. Moreover, although particular processes differ for early vs. late stage PhD students, our findings suggest that support from faculty members is a key predictor of intentions to perform OCB. Thus, received support is positively related to performing OCB both directly and indirectly via a sense of identification with faculty members. We discuss the implications of our findings in relation to policies aiming at improving the well-being of PhD students.
DOI: 10.25392/leicester.data.7461986
title: Assessing Member States’ capacity for reliable ‘authorisation of PPPs’, and its uniformity - Report for EIA on Regulation (EC) 1107/2009 on the Placing of Plant Protection Products on the Market

description: Data relating to a research project into the EU zonal system of authorising pesticides under the Plant Protection Product Regulation, Regulation (EU) 1107/2009. Data includes: empirical data, largely questionnaires, emails to which questionnaires are attached and other documents produced as part of the methodology, eg stakeholder lists and early drafts of the report which contain confidential information.