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opencc-by-4.0Nov 2023View details →

Data Set of Paper on An Architecture Model-Based Framework for Continuous Data Protection Legal Assessments

Data Set of Paper "An Architecture Model-Based Framework for Continuous Data Protection Legal Assessments". The data set contains illustrations of the example used for evaluating accuracy, including all variations, and model instances of the case studies used for evaluating applicability.

An empirical approach and practical framework for a decentralized Ethereum Ecosystem Index (EEI) datasets and codes

Open the record for dataset details and reuse information.

A Framework to Promote Diversity & Inclusion in Workforce Development in the Southeast States

The lack of workforce diversity has made it challenging for transportation agencies to incorporate resiliency into their long-term plans effectively. This project developed a framework for creating an inclusive and functional workforce environment for transportation agencies in the southeast region. The project identifies existing gaps, predicts future needs, and captures the role transportation agencies, research centers, Departments of Transportations (DOTs), and professional organizations can play to recruit, train, and maintain a diverse and inclusive workforce. This research will ultimately contribute to creating a resilient transportation workforce structure in the southeast region. The goal of this project is to present an Equity, Diversity, and Inclusion (EDI) -focused framework for promoting diversity and inclusion within the workforce.

Reconciling ASPP-p53 Binding Mode Discrepancies through an Ensemble Binding Framework that Bridges Crystallography and NMR Data

The trajectory of 'Reconciling ASPP-p53 Binding Mode Discrepancies through an Ensemble Binding Framework that Bridges Crystallography and NMR Data'

R code and supplementary data for : "A framework for mapping conservation agricultural fields using time-series optical and radar imagery"

Source code and cover crop maps for the paper "A framework for mapping conservation cropland using optical and radar time series imagery." (Zhou et al., 2025) https://doi.org/10.1016/j.rse.2025.114858   The entire workflow consists of these steps: 1. Obtain satellite data from Google Earth Engine platform. script path: (<a href="https://code.earthengine.google.com/?scriptPath=users%2Fyuez9466%2FCApractice%3ANDVI">https://code.earthengine.google.com/?scriptPath=users%2Fyuez9466%2FCApractice%3ANDVI</a>). You need to obtain the NDVI, NBR2, Sentinel-1 Radar dataset and Precipitation data for your research area and seltected time interval. Download .csv data from Google Cloud, then convert the format of the data for following calculations.(see 1_import_transfer_data.R) 2. Obtain the annual crop types in your study area, either through agricultural census data or remote sensing predictions (not mentioned in this paper), calculate organic carbon input based on the crop types. Extracting seasons based on time-series NDVI values using phenofit package. (see 2_NDVI_Smooth_Divide_seasons.R) 3. Calculating the length of the cover crop growing season and periods of bare soil, also get the nessasary covariates for tillage model meanwhile. (see 3_CC_BS_length_add_Tillage.R) 4. Build a tillage model. (see 4_Build_Tillage_model) Build your own conservation agriculture fields model.

opencc-by-4.0Sep 2023View details →

Hydrogen-Bonded Organic Frameworks Based on Endless-Stacked Amides for Iodine Capture and Detection

Raw data of

Non-crystalline Zeolitic Imidazolate Frameworks Tethered with Ionic Liquids as Catalysts for CO2 Conversion into Cyclic Carbonates

This folder /final_logs/ contains the DFT-optimized geometries (in .xyz format together with the gas-phase energy, E) accompanying the paper "Design of Non-crystalline Zeolitic Imidazolate Frameworks Tethered with Ionic Liquids as Highly Active and Stable Catalysts for Mild CO2 Conversion into Cyclic Carbonates" where conformers occur, they are always named from the lowest Gibbs energy to the highest in ascending order from c1 (sometimes omitted), c2, c3, ...

opencc-by-4.0Jun 2019View details →

COWORKER SUPPORT AS MODERATOR ON THE RELATIONSHIP BETWEEN HRM PRACTICES ANDORGANIZATIONAL COMMITMENT: A PROPOSED FRAMEWORK.

Several factors have been proposed to have influence over organizational commitment; among some  of those prominent factors are human resource management practices. However, among the  prominent studies on the said relationship; the reported findings are inconsistent. Therefore, it is proposed to incorporate a moderating variable to further explain this relationship. The current study  proposed coworker support as moderator on the relationship between HRM practices and organizational commitment.

dryad32/100

An evolution-based framework for describing human gut bacteria

The human gut microbiome contains many bacterial strains of the same species ('strain-level variants'). Describing strains in a biologically meaningful manner rather than purely taxonomic objects is an important goal but challenging due to the complexity of strain-level variation. Here, we measured patterns of co-evolution across >7,000 strains spanning the bacterial tree-of-life. Using these patterns as a prior for studying hundreds of gut commensal strains that we isolated, sequenced, and metabolically profiled revealed widespread structure beneath the phylogenetic level of species. Defining strains by their co-evolutionary signatures enabled predicting their metabolic phenotypes and engineering consortia from strain genome content alone. Our findings demonstrate a biologically relevant organization to strain-level variation and motivate a new schema for describing bacterial strains based on their evolutionary history.

opencc-zeroDec 2023View details →

Fig. 11 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 11.—ICAMER (Iteration of Cuspal Area with Mirror Effect and Rotation) topology analysis of the m1 and M1 of: (A, E) Onychomys leucogaster (MVZ 76624); (B, F) O. torridus (CNMA 3345); (C, G) O. arenicola (CNMA 46447); (D) Acrolophomys rhodopetros (LACM 124878). See Barbière et al (2019) and Supplementary Data SD1 for ICAMER nomenclature and color coding. All scaled to the same size.

Fig. 8 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 8.—Majority-rule consensus tree obtained from Bayesian inference analysis of combined morphological and molecular data sets, in part. Details of the consensus tree corresponding to the ingroup taxa less the Neotomini tribe and outgroups. See Fig. 9 for part of the consensus tree corresponding to Neotominae and non-neotomine outgroup taxa. Posterior probabilities values are indicated in grayscale circles for each node. Terminals in bold indicate the Onychomyini and fossil species (†, extinct).

Fig. 6 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 6.—Phylogenetic consensus tree obtained from maximum likelihood (ML) analysis of the concatenated mitochondrial and nuclear independent loci. Bootstrap support is indicated in grayscale circles for each node. Terminal in bold indicates the Onychomyini species.

Fig. 7 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 7.—Phylogenetic consensus tree obtained from maximum parsimony (MP) analysis of the concatenated mitochondrial and nuclear independent loci. MP analysis yielded a single most parsimonious tree of 14,471 steps (consistency index [CI] = 0.399, retention index [RI] = 0.546). Bootstrap support is indicated in grayscale circles for each node. Terminal in bold indicates the Onychomyini species.

Fig. 3 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 3.—Examples of upper molars of species included in the morphological cladistic analysis, upper molars unknown for Acrolophomys. A— LM1–3, UCMP 317400, from Ronez et al. (2020). B—RM1–3, reversed, FMNH 230688, photo by C. Ronez. C—LM1–3, MVZ 105624, photo by A. Pacheco-Castro. D—LM1–3, MNCN-275, photo by P. Peláz-Campomanes. E—LM1–3, USNM 272116, photo by R. Martin. F—LM1–3, USNM 272176, photo by R. Martin. G—RM1–3, reversed, MVZ 219614. H—RM1–3, reversed, MVZ 225121. I—RM1–3, reversed, MVZ 219161. Photos G, H, and I by Jessica L. Blois, UC Merced. All occlusal views. Not to scale, all M1s adjusted to equal lengths.

Fig. 5 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 5.—Phylogenetic consensus tree obtained from Bayesian inference (BI) analysis of the concatenated mitochondrial and nuclear independent loci. Posterior probabilities support are indicated in grayscale circles for each node. Terminal in bold indicates the Onychomyini species.

Fig. 1 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 1.—First lower molars of Onychomys and Acrolophomys. Onychomys: A—Lm1, UALP 13963, 111 Ranch, Arizona, Blancan (from Tomida, 1985); B—Rm1, FHSM VP-19867, reversed, Hornet, Meade Basin, Kansas, Blancan, photo by P. Peláez-Campomanes; C—Lm1, USNM 525590; D—Lm1, USNM 017881; E—Lm1, USNM 272116; F–H—Rm1, FHSM VP-19868, reversed, Borchers, Meade Basin, Kansas, Blancan; I–K— Lm1, FHSM VP-19869, Borchers, Meade Basin, Kansas. Acrolophomys: L–N—Rm1, reversed, LACM 124878; O–Q—Lm1, LACM 124912; R–T—Rm1, reversed, LACM 156372, Dove Springs, California, latest Hemphillian–earliest Blancan, from Kelly and Whistler (2014). Occlusal views, A–F, I, L, O, and R. Labial views, G, J, M, P, and S. Lingual views, H, K, N, Q. All m1s adjusted to equal length.

Fig. 2 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 2.—Examples of lower molars of species included in the morphological cladistic analysis. A—Rm1–3, reversed, UCMP 317546, from Ronez et al. (2020). B—Rm1–3, reversed, MVZ 105624, photo by A. Pacheco-Castro. C—Rm1–3, reversed, MNCN-275, photo by P. PeláezCompomanes. D—Rm1–3, reversed, USNM 27211. E—Rm1–3, reversed, LACM 125052, from Kelly and Whistler (2014). F—Lm1–3, FMNH 230688, photo by C. Ronez. G—Lm1–3, UNSM 272173, photo by R. Martin. H—Rm1–3, reversed, MVZ 219614. I—Lm1–3, MVZ 225121. J—Lm1–3, MVZ 219161. Photos H, I, and J by Jessica L. Blois, UC Merced. All occlusal views. Not to scale, all m1s adjusted to equal length.

Fig. 4 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 4.—Single most parsimonious tree, 42 steps, consistency index (CI) = 0.857, retention index (RI) = 0.926. The cladogram is supported by the following list of hypothesized ancestral synapomorphies (number to left of period denotes character number and to right of period character state). Node 1, 6.1, 13.1, 17.1; Node 2, 5.2, 7.1, 11.2, 15.1, 18.1, 25.1; Node 3, 20.1, 21.1, 24.1; Node 4, 3.1, 16.1, 17.2, 23.2; Node 5, 5.1, 11.1; Node 6, 1.1, 16.2; Node 7, 12.2, 14.1; Node 8, 2.1, 4.1, 7.1, 8.1, 9.1, 10.1. Additional apomorphies for terminal taxa are: B. taylori, 5.2; R. montanus, 15.2; and O. leucogaster, 12.1, 14.1, 15.2.

Fig. 10 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 10.—Divergence times tree for Neotominae subfamily based on a concatenated analysis of the mitochondrial protein-coding gene cytochrome-b, and intron 2 and parts of exons 2 and 3 of acid phosphatase type V, intron 2 of the alcohol dehydrogenase gene, exon 6 of the protein-coding dentin matrix protein 1 gene, intron 7 of the beta-fibrinogen gene, exon 10 of the growth hormone receptor, single exon of the recombination activation 1 gene, and the first exon of the nuclear gene interphotoreceptor retinoid-binding protein. Divergence date estimates are indicated in millions of years. Bars indicate the minimum and maximum date at the 95% highest posterior density for node height (95% HPD).

Fig. 13 in Morphology and genetics of grasshopper mice revisited in a paleontological framework: reinstatement of Onychomyini (Rodentia, Cricetidae)

Fig. 13.—Relative proportions of crown divisions in extant genera of tribes of Neotominae following the interpretation of Koenigswald (2020). Relative lengths of differentiated roots of some taxa not available due to breakage or buried in alveolus. Numbers correspond to the following genera: 1, Neotoma; 2, Ochrotomys; 3, Scotinomys; 4, Baiomys; 5, Isthmomys; 6, Reithrodontomys; 7, Onychomys; 8, Acrolophomys; 9, Habromys; 10, Megadontomys; 11, Neotomodon; 12, Osgoodomys; 13, Peromyscus; 14, Podomys.