cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15463724
title: The Leelamoy Series: An Original Integer Progression Beginning from L(1) = 9

description: Â that begins withÂ  L(1) = 9Â  andÂ  L(2) = 9 , with each subsequent term defined by the classical Fibonacci recurrence:

 

L(n) = L(n-1) + L(n-2)

 

Unlike the Fibonacci sequence, which begins with 0 and 1, the Leelamoy Series is centered upon the sacred digital root 9 and reveals a unique harmonic signature across its terms. The series preserves the cyclic structure of Fibonacci digital roots while shifting the foundational perspective to a 9-based recurrence field.

 

This record includes the first 24 terms of the series (L(1) to L(24)), along with their associated Classical Digital Roots and Leelamoy Digital Roots â€” a modified root operator developed to analyze digital symmetry in negative and positive integer fields.

 

This dataset is intended for inclusion in OEIS, preservation in open repositories, and formal mathematical exploration.

Further extensions, including the symmetrical regression and theoretical foundation, will be presented in the forthcoming manuscript The Leelamoy Magnum Opus.
DOI: 10.5281/zenodo.15463725
title: The Leelamoy Series: An Original Integer Progression Beginning from L(1) = 9

description: Â that begins withÂ  L(1) = 9Â  andÂ  L(2) = 9 , with each subsequent term defined by the classical Fibonacci recurrence:

 

L(n) = L(n-1) + L(n-2)

 

Unlike the Fibonacci sequence, which begins with 0 and 1, the Leelamoy Series is centered upon the sacred digital root 9 and reveals a unique harmonic signature across its terms. The series preserves the cyclic structure of Fibonacci digital roots while shifting the foundational perspective to a 9-based recurrence field.

 

This record includes the first 24 terms of the series (L(1) to L(24)), along with their associated Classical Digital Roots and Leelamoy Digital Roots â€” a modified root operator developed to analyze digital symmetry in negative and positive integer fields.

 

This dataset is intended for inclusion in OEIS, preservation in open repositories, and formal mathematical exploration.

Further extensions, including the symmetrical regression and theoretical foundation, will be presented in the forthcoming manuscript The Leelamoy Magnum Opus.
DOI: 10.15468/dl.psszxz
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Mundula"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007024-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mf8a97
title: Occurrence Download

description: A dataset containing 195 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year 2023-2025",
 "Geometry POLYGON((8.96136 47.7155,9.02477 47.7155,9.02477 47.74642,8.96136 47.74642,8.96136 47.7155))",
 "TaxonKey is Aves",
 "CoordinateUncertaintyInMeters is less than or equal to 100"
 ]
}

 The dataset includes 195 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007025-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mh8zcs
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Indonesia, Malaysia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pleiogynium Engl."
 ]
}

 The dataset includes 20 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007023-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.huzrmq
title: Occurrence Download

description: A dataset containing 2660 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Accipiter trivirgatus (Temminck, 1824)",
 "Year 2020-2025"
 ]
}

 The dataset includes 2660 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007027-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.udcbke
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-10.14189 36.1581,-6.24098 36.1581,-6.24098 42.49709,-10.14189 42.49709,-10.14189 36.1581))",
 "OccurrenceStatus is Present",
 "TaxonKey is Cephalanthera rubra (L.) Rich.",
 "Year 1975-2025"
 ]
}

 The dataset includes 27 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007028-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60797/irj.2025.155.100.8
title: Коэффициент сходства (Жаккара) видовых списков насаждений изученных прихрамовых территорий

description: Международный научно-исследовательский журнал, Выпуск 5 (155) 2025
DOI: 10.15468/dl.fe85y5
title: Occurrence Download

description: A dataset containing 2774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Mundulea (DC.) Benth."
 ]
}

 The dataset includes 2774 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007029-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3s6c8f
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-9.63865 36.31415,-6.19795 36.31415,-6.19795 42.2891,-9.63865 42.2891,-9.63865 36.31415))",
 "OccurrenceStatus is Present",
 "TaxonKey is Chaenorhinum serpyllifolium (Lange) Lange"
 ]
}

 The dataset includes 32 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007030-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bpsmku
title: Occurrence Download

description: A dataset containing 28456 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Herbario de la Universidad de Almería"
 ]
}

 The dataset includes 28456 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007032-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p3uwqy
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-9.75527 36.18694,-6.88674 36.18694,-6.88674 42.20867,-9.75527 42.20867,-9.75527 36.18694))",
 "OccurrenceStatus is Present",
 "TaxonKey is Cheilanthes guanchica Bolle",
 "Year 1975-2025"
 ]
}

 The dataset includes 5 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007034-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nfrmae
title: Occurrence Download

description: A dataset containing 1670 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Bucephala clangula (Linnaeus, 1758)",
 "Year 2020-2025"
 ]
}

 The dataset includes 1670 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007035-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.smznnc
title: Occurrence Download

description: A dataset containing 862 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Occurrence evidence",
 "Country is Romania",
 "OccurrenceStatus is Present",
 "Year 2007-2025"
 ]
}

 The dataset includes 862 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007037-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5sz7zy
title: Occurrence Download

description: A dataset containing 16498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Muntingia L."
 ]
}

 The dataset includes 16498 records from 326 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007036-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jkn5hg
title: Occurrence Download

description: A dataset containing 396 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Peganum harmala L."
 ]
}

 The dataset includes 396 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007040-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nu6s4r
title: Occurrence Download

description: A dataset containing 181 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is New Caledonia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Fontainea pancheri (Baill.) Heckel"
 ]
}

 The dataset includes 181 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007041-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15463817
title: Análisis sensorial de Pan Baguett
DOI: 10.5281/zenodo.15463818
title: Análisis sensorial de Pan Baguett
DOI: 10.5281/zenodo.15374260
title: Patterns of molecular conservation along tooth development are only partly shaped by evolutionary pressures on tooth

description: - tables with expression levels (raw counts and TPM)

- results of positive selection scans (from Selectome analysis) 
    - res.ham.tsv for cricetinae branch
    - res.mus.tsv for mus, murinae, muridae branches

- results of pleiotropy estimations 
    - from bgee data : 3 files depending on filters used (all development, only embryonic stages, only postembryonic stages). Column tau was used.
    - from incisors scRNA-seq
    - from molar scRNA-seq. 

- values of dN/dS between mouse and hamster

- a table with sample annotation : metadata.tsv
DOI: 10.5281/zenodo.15374261
title: Patterns of molecular conservation along tooth development are only partly shaped by evolutionary pressures on tooth

description: - tables with expression levels (raw counts and TPM)

- results of positive selection scans (from Selectome analysis) 
    - res.ham.tsv for cricetinae branch
    - res.mus.tsv for mus, murinae, muridae branches

- results of pleiotropy estimations 
    - from bgee data : 3 files depending on filters used (all development, only embryonic stages, only postembryonic stages). Column tau was used.
    - from incisors scRNA-seq
    - from molar scRNA-seq. 

- values of dN/dS between mouse and hamster

- a table with sample annotation : metadata.tsv
DOI: 10.5281/zenodo.14358348
title: RdRpCATCH databases

description: This directory contains the profile Hidden Markov models supported by RdRpCATCHCompressed .tar file of RdRpCATCH-supported databases: 

hmm_dbs:1. RVMT

2. NeoRdrp

3. NeoRdrp-2

4. LucaProt_HMM

5. RdRp-Scan

6. TSA_Olendraite_fam7. TSA_Olendraite_gen8. Zayed_HMM

mmseqs_dbs:

Riboviria RefSeq proteins formatted as an mmseqs compatible database
DOI: 10.5281/zenodo.14358349
title: ColabScan: Databases

description: Compressed .tar file of ColabScan-supported databases: 1. RVMT

2. NeoRdrp-2

3. LucaProt HMMs

4. RdRp-Scan

5. TSA_Olendraite
DOI: 10.5281/zenodo.14936013
title: RdRpCATCH databases

description: Compressed .tar file of ColabScan-supported databases: 

hmm_dbs:1. RVMT

2. NeoRdrp-2

3. LucaProt HMMs

4. RdRp-Scan

5. TSA_Olendraite_fam6. TSA_Olendraite_gen

mmseqs_dbs:

Riboviria RefSeq proteins formatted as an mmseqs compatible database
DOI: 10.5281/zenodo.15118345
title: RdRpCATCH databases

description: Compressed .tar file of RdRpCATCH-supported databases: 

hmm_dbs:1. RVMT

2. NeoRdrp

3. NeoRdrp-2

4. LucaProt HMMs

5. RdRp-Scan

6. TSA_Olendraite_fam7. TSA_Olendraite_gen

mmseqs_dbs:

Riboviria RefSeq proteins formatted as an mmseqs compatible database
DOI: 10.5281/zenodo.15120486
title: RdRpCATCH databases

description: This directory contains the profile Hidden Markov models supported by RdRpCATCHCompressed .tar file of RdRpCATCH-supported databases: 

hmm_dbs:1. RVMT

2. NeoRdrp

3. NeoRdrp-2

4. LucaProt_HMM

5. RdRp-Scan

6. TSA_Olendraite_fam7. TSA_Olendraite_gen8. Zayed_HMM

mmseqs_dbs:

Riboviria RefSeq proteins formatted as an mmseqs compatible database
DOI: 10.5281/zenodo.15463729
title: RdRpCATCH databases

description: This directory contains the profile Hidden Markov models supported by RdRpCATCHCompressed .tar file of RdRpCATCH-supported databases: 

hmm_dbs:1. RVMT

2. NeoRdrp

3. NeoRdrp-2

4. LucaProt_HMM

5. RdRp-Scan

6. TSA_Olendraite_fam7. TSA_Olendraite_gen8. Zayed_HMM

mmseqs_dbs:

Riboviria RefSeq proteins formatted as an mmseqs compatible database
DOI: 10.15468/dl.7qs5x8
title: Occurrence Download

description: A dataset containing 113 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ukraine",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (ca2fd897-6108-4361-91f8-b39dc8d12d13, 93ee624c-1c8b-4f74-8797-1b72f0a9f9a1)",
 "TaxonKey is Myotis bechsteinii (Kuhl, 1817)"
 ]
}

 The dataset includes 113 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007045-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29098925
title: Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments

description: We propose a doubly robust inference method for causal effects of continuous treatment variables, under unconfoundedness and with nonparametric or high-dimensional nuisance functions. Our double debiased machine learning (DML) estimators for the average dose-response function (or the average structural function) and the partial effects are asymptotically normal with nonparametric convergence rates. The first-step estimators for the nuisance conditional expectation function and the conditional density can be nonparametric or ML methods. Utilizing a kernel-based doubly robust moment function and cross-fitting, we give high-level conditions under which the nuisance function estimators do not affect the first-order large sample distribution of the DML estimators. We provide sufficient low-level conditions for kernel, series, and deep neural networks. We justify the use of kernel to localize the continuous treatment at a given value by the Gateaux derivative. We implement various ML methods in Monte Carlo simulations and an empirical application on a job training program evaluation.
DOI: 10.6084/m9.figshare.29098925.v1
title: Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments

description: We propose a doubly robust inference method for causal effects of continuous treatment variables, under unconfoundedness and with nonparametric or high-dimensional nuisance functions. Our double debiased machine learning (DML) estimators for the average dose-response function (or the average structural function) and the partial effects are asymptotically normal with nonparametric convergence rates. The first-step estimators for the nuisance conditional expectation function and the conditional density can be nonparametric or ML methods. Utilizing a kernel-based doubly robust moment function and cross-fitting, we give high-level conditions under which the nuisance function estimators do not affect the first-order large sample distribution of the DML estimators. We provide sufficient low-level conditions for kernel, series, and deep neural networks. We justify the use of kernel to localize the continuous treatment at a given value by the Gateaux derivative. We implement various ML methods in Monte Carlo simulations and an empirical application on a job training program evaluation.
DOI: 10.15468/dl.twgmrs
title: Occurrence Download

description: A dataset containing 1515 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "DatasetKey is one of (iNaturalist Research-grade Observations, AMNH Mammal Collections, Field Museum of Natural History (Zoology) Mammal Collection, NABU|naturgucker, NMNH Extant Specimen Records (USNM, US))",
 "TaxonKey is Lycaon pictus (Temminck, 1820)"
 ]
}

 The dataset includes 1515 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007046-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e3wkr3
title: Occurrence Download

description: A dataset containing 58 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-10.05155 36.5113,-6.02219 36.5113,-6.02219 42.12362,-10.05155 42.12362,-10.05155 36.5113))",
 "TaxonKey is Cirsium welwitschii Coss.",
 "Year 1975-2025"
 ]
}

 The dataset includes 58 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007048-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29098926
title: Factor Modelling for High-dimensional Functional Time Series

description: Many economic and scientific problems involve the analysis of high-dimensional functional time series, where the number of functional variables <i>p</i> diverges as the number of serially dependent observations <i>n</i> increases. In this paper, we present a novel functional factor model for high-dimensional functional time series that maintains and makes use of the functional and dynamic structure to achieve great dimension reduction and find the latent factor structure. To estimate the number of functional factors and the factor loadings, we propose a fully functional estimation procedure based on an eigenanalysis for a nonnegative definite and symmetric matrix. Our proposal involves a weight matrix to improve the estimation efficiency and tackle the issue of heterogeneity, the rationale of which is illustrated by formulating the estimation from a novel regression perspective. Asymptotic properties of the proposed method are studied when <i>p</i> diverges at some polynomial rate as <i>n</i> increases. To provide a parsimonious model and enhance interpretability for near-zero factor loadings, we impose sparsity assumptions on the factor loading space and then develop a regularized estimation procedure with theoretical guarantees when <i>p</i> grows exponentially fast relative to <i>n</i>. Finally, we demonstrate the superiority of our proposed estimators over the alternatives/competitors through simulations and applications to a U.K. temperature data set and a Japanese mortality data set.
DOI: 10.6084/m9.figshare.29098926.v1
title: Factor Modelling for High-dimensional Functional Time Series

description: Many economic and scientific problems involve the analysis of high-dimensional functional time series, where the number of functional variables <i>p</i> diverges as the number of serially dependent observations <i>n</i> increases. In this paper, we present a novel functional factor model for high-dimensional functional time series that maintains and makes use of the functional and dynamic structure to achieve great dimension reduction and find the latent factor structure. To estimate the number of functional factors and the factor loadings, we propose a fully functional estimation procedure based on an eigenanalysis for a nonnegative definite and symmetric matrix. Our proposal involves a weight matrix to improve the estimation efficiency and tackle the issue of heterogeneity, the rationale of which is illustrated by formulating the estimation from a novel regression perspective. Asymptotic properties of the proposed method are studied when <i>p</i> diverges at some polynomial rate as <i>n</i> increases. To provide a parsimonious model and enhance interpretability for near-zero factor loadings, we impose sparsity assumptions on the factor loading space and then develop a regularized estimation procedure with theoretical guarantees when <i>p</i> grows exponentially fast relative to <i>n</i>. Finally, we demonstrate the superiority of our proposed estimators over the alternatives/competitors through simulations and applications to a U.K. temperature data set and a Japanese mortality data set.
DOI: 10.15468/dl.mmjwy5
title: Occurrence Download

description: A dataset containing 10484 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Muraltia Neck."
 ]
}

 The dataset includes 10484 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007047-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15462745
title: Data for "Floquet-Engineering of Feshbach Resonances in Ultracold Gases"

description: This repository contains the data presented in the figures of the preprint Floquet-Engineering of Feshbach Resonances in Ultracold Gases. Data for scatter and line plots are provided as CSV files, while the 2D colormesh data from Figure 3 is stored in HDF5 format. For figures that include fits, the fitting function and corresponding parameters are documented in the first lines of the respective CSV file. All units match those shown in the figures and are additionally specified in the CSV header.
DOI: 10.5281/zenodo.15462746
title: Data for "Floquet-Engineering of Feshbach Resonances in Ultracold Gases"

description: This repository contains the data presented in the figures of the preprint Floquet-Engineering of Feshbach Resonances in Ultracold Gases. Data for scatter and line plots are provided as CSV files, while the 2D colormesh data from Figure 3 is stored in HDF5 format. For figures that include fits, the fitting function and corresponding parameters are documented in the first lines of the respective CSV file. All units match those shown in the figures and are additionally specified in the CSV header.