cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25205405.v1
title: Charge cluster occurrence in land plants’ mitochondrial proteomes with functional and structural insights

description: The Charge Clusters (CCs) are involved in key functions and are distributed according to the organism, the protein’s type, and the charge of amino acids. In the present study, we have explored the occurrence, position, and annotation as a first large-scale study of the CCs in land plants mitochondrial proteomes. A new python script was used for data curation. The Finding Clusters Charge in Protein Sequences Program was performed after adjusting the reading window size. A 44316 protein sequences belonging to 52 species of land plants were analysed. The occurrence of Negative Charge Clusters (NCCs) (1.2%) is two times more frequent than the Positive Charge Clusters (PCCs) (0.64%). Moreover, 39 and 30 NCCs were conserved in 88 and 41 proteins in intra and in inter proteomes respectively, while 14 and 21 PCCs were conserved in 53 and 85 protein sequences in intra and inter proteomes consecutively. Sequences carrying mixed CCs are rare (0.12%). Despite this low abundance, CCs play a crucial role in protein function. The CCs tend to be located mainly in the terminal regions of proteins which guarantees specific protein targeting and import into the mitochondria. In addition, the functional annotation of CCs according to Gene Ontology shows that CCs are involved in binding functions of either proteins or macromolecules which are deployed in different metabolic and cellular processes such as RNA editing and transcription. This study may provide valuable information while considering the CCs in understanding the environmental adaptation of plants.
DOI: 10.17182/hepdata.48154.v1/t13
title: "Table 13" of "Study of Vector Meson Baryon Resonance Production in pi+ p Interactions at 7.1-GeV/c"

description: HELICITY FRAME.
description: SEE ALSO PL 57B, 384 (1975). SLAC 82 IN HBC. THE HIGH MASS DELTA RESONANCE IS ENCODED AS DEL(1950F37)++, THE AUTHORS CALL IT DELTA(1880). THEY FIND THE MASS = 1881.2 +- 5.5 MEV, WIDTH = 219 +- 23 MEV WITH PROBABLY J = 7/2 POSITIVE PARITY.
DOI: 10.17182/hepdata.48154.v1/t14
title: "Table 14" of "Study of Vector Meson Baryon Resonance Production in pi+ p Interactions at 7.1-GeV/c"

description: JACKSON FRAME.
description: SEE ALSO PL 57B, 384 (1975). SLAC 82 IN HBC. THE HIGH MASS DELTA RESONANCE IS ENCODED AS DEL(1950F37)++, THE AUTHORS CALL IT DELTA(1880). THEY FIND THE MASS = 1881.2 +- 5.5 MEV, WIDTH = 219 +- 23 MEV WITH PROBABLY J = 7/2 POSITIVE PARITY.
DOI: 10.17182/hepdata.48154.v1/t15
title: "Table 15" of "Study of Vector Meson Baryon Resonance Production in pi+ p Interactions at 7.1-GeV/c"

description: HELICITY FRAME.
description: SEE ALSO PL 57B, 384 (1975). SLAC 82 IN HBC. THE HIGH MASS DELTA RESONANCE IS ENCODED AS DEL(1950F37)++, THE AUTHORS CALL IT DELTA(1880). THEY FIND THE MASS = 1881.2 +- 5.5 MEV, WIDTH = 219 +- 23 MEV WITH PROBABLY J = 7/2 POSITIVE PARITY.
DOI: 10.17182/hepdata.48156.v1/t1
title: "Table 1" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.6084/m9.figshare.25415779
title: Potential diagnostic value of serum microRNAs for 19 cancer types: a meta-analysis of bioinformatics data

description: Cancer is the second most common cause of mortality worldwide, accounting for almost 10 million deaths in 2020. These deaths were partly due to delayed diagnosis that led to deferred treatment. Therefore, new diagnostic methods are necessary to enhance the accuracy of noninvasive cancer detection. The present study developed a microRNA (miRNA)-based serum diagnostic marker for detecting a wide range of cancers. The study involved 61,019 serum samples from 19 different cancer types. A miRNA prediction model was established through bioinformatics analysis of serum samples from various cancer pathologies and qRT-PCR results from studies in PubMed aligned to the analysis criteria. R software v.4.1.1 with the limma data analysis package was used for single gene expression series data series, and batchNormalize and robustRankAggreg were used to predict the changes in miRNA expression in multiple datasets. GO and KEGG analyses showed that these miRNAs play a role in cancer-related biological signaling pathways. Finally, the diagnostic capability of these miRNA biomarkers was assessed using area under the curve analysis. The study predicted that 7 miRNAs were upregulated and 10 miRNAs were downregulated in 19 different types of cancer. Some miRNAs showed significant differential expression in a specific cancer type. Additionally, downstream genes regulated by miRNAs focused on many cancer-related molecular signaling pathways. In this review, we summarize the current understanding of miRNAs in various cancers, with a particular focus on their potential as future noninvasive diagnostic biomarkers. The emphasis is on their capacity for achieving high accuracy and cost savings compared to conventional biomarkers.
DOI: 10.6084/m9.figshare.25415779.v1
title: Potential diagnostic value of serum microRNAs for 19 cancer types: a meta-analysis of bioinformatics data

description: Cancer is the second most common cause of mortality worldwide, accounting for almost 10 million deaths in 2020. These deaths were partly due to delayed diagnosis that led to deferred treatment. Therefore, new diagnostic methods are necessary to enhance the accuracy of noninvasive cancer detection. The present study developed a microRNA (miRNA)-based serum diagnostic marker for detecting a wide range of cancers. The study involved 61,019 serum samples from 19 different cancer types. A miRNA prediction model was established through bioinformatics analysis of serum samples from various cancer pathologies and qRT-PCR results from studies in PubMed aligned to the analysis criteria. R software v.4.1.1 with the limma data analysis package was used for single gene expression series data series, and batchNormalize and robustRankAggreg were used to predict the changes in miRNA expression in multiple datasets. GO and KEGG analyses showed that these miRNAs play a role in cancer-related biological signaling pathways. Finally, the diagnostic capability of these miRNA biomarkers was assessed using area under the curve analysis. The study predicted that 7 miRNAs were upregulated and 10 miRNAs were downregulated in 19 different types of cancer. Some miRNAs showed significant differential expression in a specific cancer type. Additionally, downstream genes regulated by miRNAs focused on many cancer-related molecular signaling pathways. In this review, we summarize the current understanding of miRNAs in various cancers, with a particular focus on their potential as future noninvasive diagnostic biomarkers. The emphasis is on their capacity for achieving high accuracy and cost savings compared to conventional biomarkers.
DOI: 10.17182/hepdata.48156.v1/t2
title: "Table 2" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: NUCLEUS=12C 18H 7O.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t3
title: "Table 3" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: NUCLEUS=18C 38H 7O.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t4
title: "Table 4" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t5
title: "Table 5" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.6084/m9.figshare.25382470
title: Guideline directed medical therapy induced nephrotoxicity in HFrEF patients; an insight to its mechanism

description: Guideline Directed Medical Therapy (GDMT) has been the standard pharmacotherapy for the treatment of Heart Failure patients with reduced Ejection Fraction (HFrEF) recommended by the European Society of Cardiology (ESC). However, patients on GDMT are likely to possess nephrotoxicity as an adverse effect. We utilized multiple system biology tools like ADVER-Pred, gene enrichment analysis, molecular docking, molecular dynamic simulations, and MMPBSA analysis to predict a possible molecular mechanism of how selected combinations of GDMT may cause nephrotoxicity. As per the ACC/AHA/ESC guidelines, we categorized the drugs as category 1 including β-blockers (BB), angiotensin receptor blockers (ARB), and sodium-glucose cotransporter-2 inhibitors (SGLT2I), category 2 includes BB’s, SGLT2I, and angiotensin receptor-neprilysin inhibitors (ARNI), and category 3 includes BB’s, SGLT2I, and angiotensin-converting enzyme (ACE) inhibitors. Enrichment analysis predicted category 2 drugs to possess the highest number of proteins to be involved in the development of nephrotoxicity i.e. 79.41%. The targets <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>SLC6A3</i> were the top hub genes with an edge count of 7 followed by <i>GPX1</i> with an edge count of 6. Molecular docking studies revealed candesartan-<i>SLC6A3</i> to possess the highest binding affinity of −10.2 kcal/mol. In addition, simulation studies displayed empagliflozin-<i>CBR1</i> to possess the highest stability followed by candesartan-<i>ATG5</i>. A combination of β-blockers, ARBs, and SGLT2I are predicted to likely possess nephrotoxicity which may be due to the modulation of <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>GPX1</i>. In conclusion, candesartan and empagliflozin are most likely to cause nephrotoxicity <i>via</i> the modulation of <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>GPX1</i>. GDMT drugs were predicted to possess nephrotoxicity as an adverse effect Category 2 drugs BB’s, SGLT2I, and ARNI were assessed to possess highest number of proteins to be involved in the development of nephrotoxicity which may be by modulating <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>GPX1.</i> Candesartan and empagliflozin are most likely to cause nephrotoxicity
DOI: 10.6084/m9.figshare.25382470.v1
title: Guideline directed medical therapy induced nephrotoxicity in HFrEF patients; an insight to its mechanism

description: Guideline Directed Medical Therapy (GDMT) has been the standard pharmacotherapy for the treatment of Heart Failure patients with reduced Ejection Fraction (HFrEF) recommended by the European Society of Cardiology (ESC). However, patients on GDMT are likely to possess nephrotoxicity as an adverse effect. We utilized multiple system biology tools like ADVER-Pred, gene enrichment analysis, molecular docking, molecular dynamic simulations, and MMPBSA analysis to predict a possible molecular mechanism of how selected combinations of GDMT may cause nephrotoxicity. As per the ACC/AHA/ESC guidelines, we categorized the drugs as category 1 including β-blockers (BB), angiotensin receptor blockers (ARB), and sodium-glucose cotransporter-2 inhibitors (SGLT2I), category 2 includes BB’s, SGLT2I, and angiotensin receptor-neprilysin inhibitors (ARNI), and category 3 includes BB’s, SGLT2I, and angiotensin-converting enzyme (ACE) inhibitors. Enrichment analysis predicted category 2 drugs to possess the highest number of proteins to be involved in the development of nephrotoxicity i.e. 79.41%. The targets <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>SLC6A3</i> were the top hub genes with an edge count of 7 followed by <i>GPX1</i> with an edge count of 6. Molecular docking studies revealed candesartan-<i>SLC6A3</i> to possess the highest binding affinity of −10.2 kcal/mol. In addition, simulation studies displayed empagliflozin-<i>CBR1</i> to possess the highest stability followed by candesartan-<i>ATG5</i>. A combination of β-blockers, ARBs, and SGLT2I are predicted to likely possess nephrotoxicity which may be due to the modulation of <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>GPX1</i>. In conclusion, candesartan and empagliflozin are most likely to cause nephrotoxicity <i>via</i> the modulation of <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>GPX1</i>. GDMT drugs were predicted to possess nephrotoxicity as an adverse effect Category 2 drugs BB’s, SGLT2I, and ARNI were assessed to possess highest number of proteins to be involved in the development of nephrotoxicity which may be by modulating <i>HBA1</i>, <i>CBR1</i>, <i>ATG5</i>, and <i>GPX1.</i> Candesartan and empagliflozin are most likely to cause nephrotoxicity
DOI: 10.17182/hepdata.48156.v1/t12
title: "Table 12" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t6
title: "Table 6" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t7
title: "Table 7" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t8
title: "Table 8" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: OBS=TOTAL CHARGE CHANGING C.S.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t9
title: "Table 9" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.5281/zenodo.17523619
title: Monte Carlo Simulation Data for "Decarbonizing Finance: Quantitative Risk Valuation of Nuclear Energy in the Net-Zero Portfolio"

description: This dataset contains all simulation scripts, input parameters, and generated data for stochastic risk analysis (LCOE, NPV, IRR) under carbon-pricing uncertainty.
DOI: 10.17182/hepdata.48156.v1/t10
title: "Table 10" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: NUCLEUS=18C 38H O.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t11
title: "Table 11" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: NUCLEUS=18C 38H 7O.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t13
title: "Table 13" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t14
title: "Table 14" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t16
title: "Table 16" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48156.v1/t17
title: "Table 17" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: OBS= TOTAL CHARGE CHANGING C.S.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.6084/m9.figshare.25794571
title: <i>In silico</i> analysis and characterization of potential inhibitors of MmaA3, a methoxy mycolic acid synthase from <i>Mycobacterium tuberculosis</i>

description: The emergence of the multi-and extensively drug-resistant (MDR and XDR) strains of <i>Mycobacterium tuberculosis</i> <i>(M.tb),</i> necessitates paradigm-shifting therapeutic approaches. The impermeable waxy lipid layer, primarily composed of mycolic acids, is a key factor in conferring resistance to conventional drugs. This study introduces a novel strategy to combat drug resistance by targeting Methoxy mycolic acid synthase 3 (MmaA3), a critical enzyme in the mycolic acid biosynthesis pathway. MmaA3 is responsible for the O-methylation of hydroxymycolate precursors and emerges as a promising therapeutic target. Through homology-based modeling, we generated a three-dimensional structure of MmaA3, providing crucial insights into its structural characteristics. High throughput virtual screening was performed against the MmaA3 model, using diverse sources: knowledge-based, FDA-approved Drugbank, and Asinex-Elite libraries. Through rigorous computational analyses, including binding affinity assessments, molecular interactions analysis, and binding free energy calculations, potential inhibitors of MmaA3 have been identified. Subsequent validation studies evaluated the stability of top protein-ligand complexes, and free energy calculations using molecular dynamics simulations. The stability of complexes within the catalytic site was confirmed through RMSD and RMSF profile analyses. Furthermore, binding free energy calculations using the MM-GBSA approach revealed significant binding affinity of identified ligands for MmaA3 target protein, comparable to its substrate/cofactors. These findings underscore the potential of the proposed molecules as candidates for further experimental exploration, offering promising avenues for the development of effective inhibitors against <i>M.tb.</i> Overall, our research contributes to significantly advancing the formulation of progressive therapeutic strategies in combating drug-resistant tuberculosis.
DOI: 10.6084/m9.figshare.25794571.v1
title: <i>In silico</i> analysis and characterization of potential inhibitors of MmaA3, a methoxy mycolic acid synthase from <i>Mycobacterium tuberculosis</i>

description: The emergence of the multi-and extensively drug-resistant (MDR and XDR) strains of <i>Mycobacterium tuberculosis</i> <i>(M.tb),</i> necessitates paradigm-shifting therapeutic approaches. The impermeable waxy lipid layer, primarily composed of mycolic acids, is a key factor in conferring resistance to conventional drugs. This study introduces a novel strategy to combat drug resistance by targeting Methoxy mycolic acid synthase 3 (MmaA3), a critical enzyme in the mycolic acid biosynthesis pathway. MmaA3 is responsible for the O-methylation of hydroxymycolate precursors and emerges as a promising therapeutic target. Through homology-based modeling, we generated a three-dimensional structure of MmaA3, providing crucial insights into its structural characteristics. High throughput virtual screening was performed against the MmaA3 model, using diverse sources: knowledge-based, FDA-approved Drugbank, and Asinex-Elite libraries. Through rigorous computational analyses, including binding affinity assessments, molecular interactions analysis, and binding free energy calculations, potential inhibitors of MmaA3 have been identified. Subsequent validation studies evaluated the stability of top protein-ligand complexes, and free energy calculations using molecular dynamics simulations. The stability of complexes within the catalytic site was confirmed through RMSD and RMSF profile analyses. Furthermore, binding free energy calculations using the MM-GBSA approach revealed significant binding affinity of identified ligands for MmaA3 target protein, comparable to its substrate/cofactors. These findings underscore the potential of the proposed molecules as candidates for further experimental exploration, offering promising avenues for the development of effective inhibitors against <i>M.tb.</i> Overall, our research contributes to significantly advancing the formulation of progressive therapeutic strategies in combating drug-resistant tuberculosis.
DOI: 10.17182/hepdata.48156.v1/t15
title: "Table 15" of "Fragmentation Cross-sections of $^{32}$S at 0.7-{GeV}/nucleon, 1.2-{GeV}/nucleon and 200-{GeV}/nucleon"

description: No description provided.
description: AC=LBL-BEVALAC. OBS=ELEMENTAL FRAGMENTATION CROSS SECTION.
DOI: 10.17182/hepdata.48158.v1/t1
title: "Table 1" of "Measurement of the multiplicity of charm quark pairs from gluons in hadronic Z0 decays"

description: Axis error includes +- 8.4/8.4 contribution (Total generator error for the electron channel due to the uncertainties in parameters of Peterson model of fragmentation, LAMBDA_QCD, ALPHA_S, Lund fragmentation parameters and lepton decay model).
description: OPAL collaboration. Measurement of the multiplicity of charmed quarks pairs produced from gluon splitting in hadronic Z0 decay.
DOI: 10.17182/hepdata.48168.v1/t1
title: "Table 1" of "A Measurement of charged particle multiplicity in Z0 --&gt; c anti-c and Z0 --&gt; b anti-b events"

description: Second systematic error is a common scale uncertainty.
description: CERN-LEP. Measurement of the single hemisphere charged particle multiplicity in quark tagged events.
DOI: 10.17182/hepdata.48168.v1/t2
title: "Table 2" of "A Measurement of charged particle multiplicity in Z0 --&gt; c anti-c and Z0 --&gt; b anti-b events"

description: Difference in the TOTAL charged particle multiplicity.
description: CERN-LEP. Measurement of the single hemisphere charged particle multiplicity in quark tagged events.
DOI: 10.17182/hepdata.48177.v1/t1
title: "Table 1" of "Test of the flavor independence of alpha-s"

description: No description provided.
description: CERN-LEP. Test of the flavor independence of ALPHAS.
DOI: 10.17182/hepdata.48180.v1/t1
title: "Table 1" of "Production of charged particles, K0(s), K+-, p and Lambda in Z --&gt; b anti-b events and in the decay of b hadrons"

description: Event multiplicity in bottom events.
description: CERN-LEP. Measurement of the production of charged particles, K0, K+-, p and lambda in Z0 --& gt; BOTTOM BOTTOMBAR events and in the decay of bottom hadrons using the DELPHI detector at LEP. Data come from the 1992 and 1993 running periods. Data are selected by the presence of secondary decay vertices from short-lived particles.
DOI: 10.17182/hepdata.48180.v1/t2
title: "Table 2" of "Production of charged particles, K0(s), K+-, p and Lambda in Z --&gt; b anti-b events and in the decay of b hadrons"

description: Differential cross section for charged particles in BOTTOM tagged hemispheres.
description: CERN-LEP. Measurement of the production of charged particles, K0, K+-, p and lambda in Z0 --& gt; BOTTOM BOTTOMBAR events and in the decay of bottom hadrons using the DELPHI detector at LEP. Data come from the 1992 and 1993 running periods. Data are selected by the presence of secondary decay vertices from short-lived particles.
DOI: 10.17182/hepdata.48180.v1/t3
title: "Table 3" of "Production of charged particles, K0(s), K+-, p and Lambda in Z --&gt; b anti-b events and in the decay of b hadrons"

description: Differential cross section for charged particles in untagged hemispheres.
description: CERN-LEP. Measurement of the production of charged particles, K0, K+-, p and lambda in Z0 --& gt; BOTTOM BOTTOMBAR events and in the decay of bottom hadrons using the DELPHI detector at LEP. Data come from the 1992 and 1993 running periods. Data are selected by the presence of secondary decay vertices from short-lived particles.