cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.7d6zdh
title: Occurrence Download

description: A dataset containing 335 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Callicore tolima",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 335 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011408-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17732748
title: THE PELTIER-ROD THERMAL-CONTROL AND ENERGY-RECOVERY SUBSYSTEM

description: This 10,400-word chapter (Volume I, Chapter 8 of “Muscato Law”) presents the complete engineering specification and physical justification for the Peltier-rod thermal-control and energy-recovery subsystem — a solid-state, entropy-neutral replacement for classical neutron-absorbing control rods and pumped coolant loops in aneutronic fusion reactors. The hexagonal lattice of nanostructured Bi₂Te₃/Sb₂Te₃–graphene Peltier rods simultaneously (1) actively pumps waste heat against the thermal gradient, (2) directly converts that heat into 98–128 MW of electrical power per 500 MWth of fusion power, (3) stabilises plasma via 707–804 Hz acoustic resonance, and (4) absorbs and reclaims stray neutrons and gamma radiation — all while enforcing ∆S ≤ 0 per cycle and sustaining plasma coherence above 0.995 under q-lock = 0.69. No moving parts, no parasitic pumping load, no tritium breeding, and projected lifetime >25 years. All materials, equations, scaling laws, and verification methods are derived from public-domain physics and measured parameters; no proprietary data or restricted files are referenced. This subsystem turns the historical thermal-entropy bottleneck of fusion into its largest recoverable energy asset and is offered as an immediately testable engineering pathway toward high-Q aneutronic power.



https://zenodo.org/records/https://zenodo.org/records/https://doi.org/10.5281/ 10.5281/zenodo.17283550 https://zenodo.org/records/https://doi.org/10.5281/https://doi.org/10.5281/https://doi.org/10.5281/ “Codex Muscato Law did not emerge as a speculative synthesis but as the outcome of resolving a cross-disciplinary series of foundational inconsistencies in physics, mathematics, and information theory. Each classical ‘unsolved problem’ becomes a test case of the same lawful equations already verified by open-source analog experiments and public datasets. The Law therefore functions not as an hypothesis but as a mathematically complete framework with reproducible empirical reference.” 


# Muscato Law — Complete Works (Austin Muscato)

All publications are released under CC-BY-4.0 and permanently archived on Zenodo. Each record contains the full source (LaTeX, code, data) and is assigned a unique DOI.all might not be published yet but are complete as a corpus.
DOI: 10.15468/dl.tsjs2y
title: Occurrence Download

description: A dataset containing 361 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-5000.0",
 "Country is Germany",
 "GadmGid is one of (DEU.7_1, DEU.11_1, DEU.1_1, DEU.12_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IsInCluster is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ectobius lapponicus",
 "Year 2015-2025"
 ]
}

 The dataset includes 361 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011409-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4pbqpe
title: Occurrence Download

description: A dataset containing 136 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Myscelia leucocyana",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 136 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011410-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hyggfk
title: Occurrence Download

description: A dataset containing 1008 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((16.85651877920178 47.95885646217788, 16.910298344471144 47.9554802698633, 16.915248420863772 47.99187324047592, 16.861430903707838 47.995252214445806, 16.85651877920178 47.95885646217788))"
 ]
}

 The dataset includes 1008 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011411-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24397/pangloss-0010304
title: Zhimulin 02
DOI: 10.5281/zenodo.17697509
title: ExactCN: Predicting Exact Copy Numbers on Whole Exome Sequencing Data

description: The quantification of the precise copy number variations (CNVs) is crucial to understandingthe effects of gene dosage, disease severity, and therapeutic response. Although whole-exome sequencing(WES) offers a cost-effective solution for CNV detection in a clinical setting, it introduces several biases,including those related to sequence length, GC content, and the use of targeting probes. Consequently,estimating exact copy numbers remains challenging, especially for WES data. Here, we present Ex-actCN, a deep learning–based method for estimation of exact copy numbers from WES data per exon.The architecture integrates convolutional layers that extract local read-depth patterns with transformerencoder blocks that capture genomic context and handle sequencing noise. ExactCN is trained on WESsamples from the 1000 Genomes Project, using matching WGS-based calls as semi–ground truth. Inbenchmarks, ExactCN improves the state-of-the-art integer CNV calling performance by reducing themacro-averaged mean absolute error (MAE) from 0.91 to 0.62 and the macro-averaged root meansquared error (RMSE) from 1.31 to 0.78. It also achieves an overall Pearson correlation of 0.669 andSpearman correlation of 0.550, improving the second-best method by 0.641 and 0.482, respectively.Furthermore, a fine-tuned version of ExactCN demonstrated an overall F1-score of 0.657 for ag-gregate CNV detection performance on the clinically important duplicated genes SMN1/2, demon-strating its applicability to both research and clinical genomic analyses.
DOI: 10.5281/zenodo.17666700
title: ExactCN: Predicting Exact Copy Numbers on Whole Exome Sequencing Data

description: The quantification of the precise copy number variations (CNVs) is crucial to understandingthe effects of gene dosage, disease severity, and therapeutic response. Although whole-exome sequencing(WES) offers a cost-effective solution for CNV detection in a clinical setting, it introduces several biases,including those related to sequence length, GC content, and the use of targeting probes. Consequently,estimating exact copy numbers remains challenging, especially for WES data. Here, we present Ex-actCN, a deep learning–based method for estimation of exact copy numbers from WES data per exon.The architecture integrates convolutional layers that extract local read-depth patterns with transformerencoder blocks that capture genomic context and handle sequencing noise. ExactCN is trained on WESsamples from the 1000 Genomes Project, using matching WGS-based calls as semi–ground truth. Inbenchmarks, ExactCN improves the state-of-the-art integer CNV calling performance by reducing themacro-averaged mean absolute error (MAE) from 0.91 to 0.62 and the macro-averaged root meansquared error (RMSE) from 1.31 to 0.78. It also achieves an overall Pearson correlation of 0.669 andSpearman correlation of 0.550, improving the second-best method by 0.641 and 0.482, respectively.Furthermore, a fine-tuned version of ExactCN demonstrated an overall F1-score of 0.657 for ag-gregate CNV detection performance on the clinically important duplicated genes SMN1/2, demon-strating its applicability to both research and clinical genomic analyses.
DOI: 10.15468/dl.q7fp4s
title: Occurrence Download

description: A dataset containing 5835 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hamadryas amphinome",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5835 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011412-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z838kv
title: Occurrence Download

description: A dataset containing 2214 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Adelpha basiloides",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2214 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011413-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rdpms4
title: Occurrence Download

description: A dataset containing 283 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is FALSE",
 "Geometry POLYGON ((-6.202309 37.24115, -6.202321 37.24152, -6.202358 37.2419, -6.202419 37.24227, -6.202505 37.24264, -6.202615 37.243, -6.202748 37.24336, -6.202905 37.24371, -6.203085 37.24406, -6.203288 37.2444, -6.203512 37.24473, -6.203758 37.24504, -6.204024 37.24535, -6.20431 37.24565, -6.204616 37.24594, -6.20494 37.24621, -6.205281 37.24646, -6.205638 37.24671, -6.206012 37.24694, -6.206399 37.24715, -6.2068 37.24734, -6.207213 37.24752, -6.207638 37.24768, -6.208072 37.24783, -6.208516 37.24795, -6.208967 37.24806, -6.209424 37.24814, -6.209886 37.24821, -6.210353 37.24826, -6.210822 37.24829, -6.211292 37.2483, -6.211762 37.24829, -6.212231 37.24826, -6.212697 37.24821, -6.213159 37.24814, -6.213617 37.24806, -6.214068 37.24795, -6.214511 37.24783, -6.214945 37.24768, -6.21537 37.24752, -6.215783 37.24734, -6.216184 37.24715, -6.216572 37.24694, -6.216945 37.24671, -6.217303 37.24646, -6.217644 37.24621, -6.217967 37.24594, -6.218273 37.24565, -6.218559 37.24535, -6.218826 37.24504, -6.219071 37.24473, -6.219296 37.2444, -6.219498 37.24406, -6.219678 37.24371, -6.219835 37.24336, -6.219969 37.243, -6.220079 37.24264, -6.220164 37.24227, -6.220226 37.2419, -6.220263 37.24152, -6.220275 37.24115, -6.220263 37.24078, -6.220226 37.2404, -6.220164 37.24003, -6.220079 37.23966, -6.219969 37.2393, -6.219835 37.23894, -6.219678 37.23859, -6.219498 37.23824, -6.219296 37.2379, -6.219071 37.23757, -6.218826 37.23725, -6.218559 37.23695, -6.218273 37.23665, -6.217967 37.23636, -6.217644 37.23609, -6.217303 37.23584, -6.216945 37.23559, -6.216572 37.23536, -6.216184 37.23515, -6.215783 37.23496, -6.21537 37.23478, -6.214945 37.23462, -6.214511 37.23447, -6.214068 37.23435, -6.213617 37.23424, -6.213159 37.23415, -6.212697 37.23409, -6.212231 37.23404, -6.211762 37.23401, -6.211292 37.234, -6.210822 37.23401, -6.210353 37.23404, -6.209886 37.23409, -6.209424 37.23415, -6.208967 37.23424, -6.208516 37.23435, -6.208072 37.23447, -6.207638 37.23462, -6.207213 37.23478, -6.2068 37.23496, -6.206399 37.23515, -6.206012 37.23536, -6.205638 37.23559, -6.205281 37.23584, -6.20494 37.23609, -6.204616 37.23636, -6.20431 37.23665, -6.204024 37.23695, -6.203758 37.23725, -6.203512 37.23757, -6.203288 37.2379, -6.203085 37.23824, -6.202905 37.23859, -6.202748 37.23894, -6.202615 37.2393, -6.202505 37.23966, -6.202419 37.24003, -6.202358 37.2404, -6.202321 37.24078, -6.202309 37.24115))"
 ]
}

 The dataset includes 283 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011414-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17054210
title: LNB

description: Database including 303 patients evaluated for Lyme Neuroborreliosis (LNB) in Northwestern Romania
DOI: 10.5281/zenodo.17732813
title: LNB

description: Database including 303 patients evaluated for Lyme Neuroborreliosis (LNB) in Northwestern Romania
DOI: 10.6084/m9.figshare.30251905
title: <b><i>Future focus under friction: Survey data on time perspective and money-management stress in Armenia</i></b>

description: We examine whether individual differences in time perspective–Future and Present-Fatalistic–explain financial functioning beyond income and demographics. In a preregistered cross-sectional survey, we modeled Financial Preparedness/Efficacy (FPE) and Current Money-Management Stress (CMMS) using hierarchical regressions (HC3 SEs, FDR control), bootstrapped mediation, and preregistered Future×PF moderation.
DOI: 10.6084/m9.figshare.30251905.v3
title: <b><i>Future focus under friction: Survey data on time perspective and money-management stress in Armenia</i></b>

description: We examine whether individual differences in time perspective–Future and Present-Fatalistic–explain financial functioning beyond income and demographics. In a preregistered cross-sectional survey, we modeled Financial Preparedness/Efficacy (FPE) and Current Money-Management Stress (CMMS) using hierarchical regressions (HC3 SEs, FDR control), bootstrapped mediation, and preregistered Future×PF moderation.
DOI: 10.6084/m9.figshare.30251905.v2
title: <b>Temporal orientation and money-management stress</b>

description: We examine whether individual differences in time perspective–Future and Present-Fatalistic–explain financial functioning beyond income and demographics. In a preregistered cross-sectional survey, we modeled Financial Preparedness/Efficacy (FPE) and Current Money-Management Stress (CMMS) using hierarchical regressions (HC3 SEs, FDR control), bootstrapped mediation, and preregistered Future×PF moderation.
DOI: 10.15468/dl.t2d3fy
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((104.01 33.46,104.48 33.46,104.48 34.23,104.01 34.23,104.01 33.46))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Angelica sinensis"
 ]
}

 The dataset includes 22 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011415-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tgx46r
title: Occurrence Download

description: A dataset containing 232 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Catoblepia orgetorix",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 232 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011416-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7bedqf
title: Occurrence Download

description: A dataset containing 1790 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Siderone galanthis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1790 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011418-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.738ewt
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Living Specimen, Occurrence evidence, Material citation)",
 "OccurrenceStatus is Present",
 "TaxonKey is Trachypithecus francoisi"
 ]
}

 The dataset includes 23 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011419-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.82143/xvvb-mq92
title: ทำเนียบโครงการวิจัยซึ่งได้รับทุนอุดหนุนจากสำนักงานคณะกรรมการวิจัยแห่งชาติ ตั้งแต่ พ.ศ. 2503-2515

description: เนื้อหาภายในหนังสือทำเนียบโครงการวิจัยภายในประเทศซึ่งได้รับทุนอุดหนุนจากสำนักงานคณะกรรมการวิจัยแห่งชาติ ตั้งแต่ พ.ศ. 2503-2515 จะเป็นรายชื่อโครงการวิจัยแบ่งตามสาขาวิชาการ โดยจะมีรายละเอียด รหัสโครงการวิจัย ชื่อโครงการ สถานที่ทำการวิจัย ผู้วิจัย และทุนอุดหนุนการวิจัย
DOI: 10.82143/jyre-1926
title: ทำเนียบโครงการวิจัยซึ่งได้รับทุนอุดหนุนจากสำนักงานคณะกรรมการวิจัยแห่งชาติ ตั้งแต่ พ.ศ. 2516-2520

description: เนื้อหาภายในหนังสือทำเนียบโครงการวิจัยภายในประเทศซึ่งได้รับทุนอุดหนุนจากสำนักงานคณะกรรมการวิจัยแห่งชาติ ตั้งแต่ พ.ศ. 2516-2520 จะเป็นรายชื่อโครงการวิจัยแบ่งตามสาขาวิชาการ โดยจะมีรายละเอียด รหัสโครงการวิจัย ชื่อโครงการ สถานที่ทำการวิจัย ผู้วิจัย และทุนอุดหนุนการวิจัย
DOI: 10.82143/njaj-tg24
title: ทำเนียบโครงการวิจัยซึ่งได้รับทุนอุดหนุนการวิจัย ประจำปี 2527

description: เนื้อหาภายในหนังสือจะเป็นรายชื่อโครงการวิจัยแบ่งตามสาขาวิชาการ โดยจะมีรายละเอียด รหัสโครงการวิจัย ชื่อโครงการ สถานที่ทำการวิจัย ผู้วิจัย และทุนอุดหนุนการวิจัย ประจำปี 2527
DOI: 10.82143/3whk-p675
title: ทำเนียบโครงการวิจัยซึ่งได้รับทุนอุดหนุนการวิจัยจากสำนักงานคณะกรรมการวิจัยแห่งชาติ ตั้งแต่ปีงบประมาณ 2521-2525

description: เนื้อหาภายในหนังสือจะเป็นรายชื่อโครงการวิจัยที่ได้รับทุนอุดหนุนการวิจัยตั้งแต่ปีงบประมาณ 2521-2525 โดยแบ่งตามสาขาวิชาการ และจะมีรายละเอียด ได้แก่ รหัสโครงการวิจัย ชื่อโครงการ สถานที่ทำการวิจัย ผู้วิจัย และทุนอุดหนุนการวิจัย นอกจากนั้น ยังมีโครงการพิเศษ โครงการวิจัยที่เสร็จสมบูรณ์แล้ว ข้อมูลทางสถิติและแผนภูมิด้วย
DOI: 10.82143/2gen-4963
title: ทำเนียบโครงการวิจัยซึ่งได้รับทุนอุดหนุนการวิจัยประจำปี 2526

description: เนื้อหาภายในหนังสือจะเป็นรายชื่อโครงการวิจัยแบ่งตามสาขาวิชาการ โดยจะมีรายละเอียด รหัสโครงการวิจัย ชื่อโครงการ สถานที่ทำการวิจัย ผู้วิจัย และทุนอุดหนุนการวิจัย ประจำปี 2526 โดยได้เพิ่มเติมเนื้อหาบทคัดย่อรายงานการวิจัยฉบับสมบูรณ์ซึ่งได้รับทุนอุดหนุนการวิจัยในปีต่าง ๆ บางส่วนเข้าไว้ด้วย
DOI: 10.15468/dl.5x4u9q
title: Occurrence Download

description: A dataset containing 259 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zaretis isidora",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 259 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011420-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cdfn67
title: Occurrence Download

description: A dataset containing 8968 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Marpesia petreus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8968 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011422-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pr8hfw
title: Occurrence Download

description: A dataset containing 48130 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ursus arctos",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 48130 records from 259 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011421-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17732803
title: source data all submit
DOI: 10.5281/zenodo.17732804
title: source data all submit
DOI: 10.15468/dl.etj69j
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "Geometry POLYGON((86.91837 25.41157,90.93465 25.41157,90.93465 28.2829,86.91837 28.2829,86.91837 25.41157))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Elephas maximus"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011423-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/dans-x3g-2hgj
title: Een Inventariserend Veldonderzoek door middel van proefsleuven te Lierop (Sluis 10), gemeente Someren

description: &lt;p&gt;In het kader van een geplande oeververbinding (weg) over de Zuid-Willemsvaart bij Sluis 10 te Lierop, heeft Archol BV in opdracht van de provincie Noord-Brabant een inventariserend archeologisch proefsleuvenonderzoek uitgevoerd. Het plangebied bestaat grotendeels uit een dekzandrug; in het oosten gaat deze over in het beekdal van de Aa. Het grootste deel van het plangebied blijkt verstoord door recente zandafgravingen. Twee zones hebben niet te lijden gehad onder deze verstoringen: het lage deel van de dekzandrug in het noorden en de flank van het beekdal in het zuidoosten. De noordelijke zone bleek geen archeologische resten te bevatten. In de zuidoostelijke zone zijn op de overgang van het dekzand naar het beekdal wel resten aangetroffen. Het gaat om nederzettingsporen uit de vroege tot midden-ijzertijd en om een oude landweg met naast gelegen greppel uit de nieuwe tijd. De ijzertijdsporen vertegenwoordigen vermoedelijk de randzone van een nederzetting die zich oorspronkelijk uitstrekte over de hoge dekzandrug. De kern van de nederzetting is echter bij de voornoemde zandafgravingen verstoord. De oude landweg is ook maar gedeeltelijk bewaard, dateert op zijn vroegst uit de 17e-18e eeuw en is nog tot begin van de 20e eeuw in gebruik geweest.&lt;/p&gt;