cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.65cr3e
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Occurrence evidence",
 "Country is Germany",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Piciformes",
 "Year 2023-2024"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017268-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jx5k7t
title: Occurrence Download

description: A dataset containing 2315 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Reynoutria japonica Houtt.",
 "Country is Austria"
 ]
}

 The dataset includes 2315 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017267-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11127744
title: Exponential Synchronization of BAM Neural Networks with Delay on Arbitrary Time Domains

description: Code to reproduce the plots presented in our manuscript ``Exponential Synchronization of BAM Neural Networks with Delay on Arbitrary Time Domains''.
DOI: 10.15468/dl.7883tv
title: Occurrence Download

description: A dataset containing 3630 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Paracrinia haswelli (Fletcher, 1894)"
 ]
}

 The dataset includes 3630 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017270-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11127743
title: Exponential Synchronization of BAM Neural Networks with Delay on Arbitrary Time Domains

description: Code to reproduce the plots presented in our manuscript ``Exponential Synchronization of BAM Neural Networks with Delay on Arbitrary Time Domains''.
DOI: 10.5281/zenodo.13939014
title: Exponential Synchronization of BAM Neural Networks with Delay on Arbitrary Time Domains

description: Code to reproduce the plots presented in our manuscript ``Exponential Synchronization of BAM Neural Networks with Delay on Arbitrary Time Domains''.
DOI: 10.15468/dl.xbhrqj
title: Occurrence Download

description: A dataset containing 1168 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Reynoutria japonica Houtt.",
 "Country is Luxembourg"
 ]
}

 The dataset includes 1168 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017273-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jntrdw
title: Occurrence Download

description: A dataset containing 8332 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Scotland Otter Survey Database"
 ]
}

 The dataset includes 8332 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017274-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p446jj
title: Occurrence Download

description: A dataset containing 682 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Orchestes alni (C.Linnaeus, 1758)",
 "OccurrenceStatus is Present",
 "Country is not null",
 "Year is not null"
 ]
}

 The dataset includes 682 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017269-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y4fvzz
title: Occurrence Download

description: A dataset containing 2140 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Muschampia proto (Ochsenheimer, 1808)",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 34, 42 34, 42 70, -26 70, -26 34))"
 ]
}

 The dataset includes 2140 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017271-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/9640123
title: BBC Burmese News rss
DOI: 10.15468/dl.f8fgq9
title: Occurrence Download

description: A dataset containing 1604 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Derris trifoliata Lour."
 ]
}

 The dataset includes 1604 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017272-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2bzuhk
title: Occurrence Download

description: A dataset containing 14037 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyssopus officinalis L.",
 "OccurrenceStatus is Present",
 "Country is not null",
 "Year is not null"
 ]
}

 The dataset includes 14037 records from 373 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017266-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cyvd4n
title: Occurrence Download

description: A dataset containing 521 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Philoria frosti Spencer, 1901"
 ]
}

 The dataset includes 521 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017277-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hbmjvz
title: Occurrence Download

description: A dataset containing 346 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Philoria kundagungan (Ingram & Corben, 1975)"
 ]
}

 The dataset includes 346 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017280-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xen8rc
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dipturus intermedius (Parnell, 1837))",
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 78 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017279-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3wj88w
title: Occurrence Download

description: A dataset containing 7839 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Orchestes fagi (C.Linnaeus, 1758)",
 "OccurrenceStatus is Present",
 "Country is not null",
 "Year is not null"
 ]
}

 The dataset includes 7839 records from 222 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017276-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13130/rd_unimi/f0jgu8/pgmg4l
title: Maggio_1928_Pagina_031.jpg

description: Bulletin of 1928/05/08
DOI: 10.13130/rd_unimi/f0jgu8/5q3pvc
title: Maggio_1928_Pagina_032.jpg

description: Bulletin of 1928/05/08
DOI: 10.6084/m9.figshare.30883970
title: Supplementary Material for: Generalized Stable Population and Agent-Based Models of phenotypic transmission in human populations, with an application to body size

description: We show that generalizations of stable population (GSPM) and agent based models (ABM) are useful tools to simulate the trajectory of a human phenotype. Although mathematically very different, both classes of models can simultaneously account for multiple determinants of the population distribution of a phenotype across time and space. These include genetic transmission, assortative mating, differential fertility, vertical and horizontal cultural heredity, gene-environments interactions (GxE), and environmental feedback. In principle, these models are generalizable to handle selection, drift as well as interactions of these and the other determinants. We illustrate with an application to obesity, a condition that has spread rapidly around the globe increasing the risk of adult chronic illnesses and mortality everywhere. If properly anchored on robust empirical estimates of model inputs, the models' results reproduce well observed trends of the phenotype and can be used as guides for policy interventions.
DOI: 10.6084/m9.figshare.30883970.v1
title: Supplementary Material for: Generalized Stable Population and Agent-Based Models of phenotypic transmission in human populations, with an application to body size

description: We show that generalizations of stable population (GSPM) and agent based models (ABM) are useful tools to simulate the trajectory of a human phenotype. Although mathematically very different, both classes of models can simultaneously account for multiple determinants of the population distribution of a phenotype across time and space. These include genetic transmission, assortative mating, differential fertility, vertical and horizontal cultural heredity, gene-environments interactions (GxE), and environmental feedback. In principle, these models are generalizable to handle selection, drift as well as interactions of these and the other determinants. We illustrate with an application to obesity, a condition that has spread rapidly around the globe increasing the risk of adult chronic illnesses and mortality everywhere. If properly anchored on robust empirical estimates of model inputs, the models' results reproduce well observed trends of the phenotype and can be used as guides for policy interventions.
DOI: 10.13130/rd_unimi/f0jgu8/hp2wj1
title: Maggio_1928_Pagina_034.jpg

description: Bulletin of 1928/05/09
DOI: 10.13130/rd_unimi/f0jgu8/y9lc6o
title: Maggio_1928_Pagina_033.jpg

description: Bulletin of 1928/05/09
DOI: 10.13130/rd_unimi/f0jgu8/giana1
title: Maggio_1928_Pagina_035.jpg

description: Bulletin of 1928/05/09
DOI: 10.13130/rd_unimi/f0jgu8/ool90w
title: Maggio_1928_Pagina_036.jpg

description: Bulletin of 1928/05/09
DOI: 10.6084/m9.figshare.30883973
title: Supplementary Material for: Association Between Hemoglobin-to-red Cell Distribution Width Ratio and Left Ventricular Hypertrophy in Non-Dialysis CKD Stage 3–5 Patients: A Cross-Sectional Study

description: Introduction: Left ventricular hypertrophy (LVH) is a common cardiovascular complication in chronic kidney disease (CKD), driven by anemia and nutritional deficiencies. The hemoglobin-to-red cell distribution width ratio (HRR) reflects these factors, but its association with LVH in CKD remains unclear. This study aimed to investigate the relationship between HRR and LVH in non-dialysis CKD stage 3–5 patients.
Methods: In this cross-sectional study, 195 patients were included. HRR was calculated from hemoglobin and red cell distribution width. LVH was diagnosed by echocardiography (LV mass index &gt;115 g/m² men, &gt;95 g/m² women). Logistic regression assessed HRR-LVH association, including subgroup and restricted cubic spline analyses. Mediation analysis explored the role of intact parathyroid hormone (iPTH) and N-terminal pro-brain natriuretic peptide (NT-proBNP).
Results: Patients with LVH (n=40) had significantly lower HRR (median 0.62 vs. 0.81, P&lt;0.001). HRR was inversely associated with LVH (adjusted OR 0.41 per SD increase, P=0.005), with the highest HRR tertile showing the lowest LVH risk (adjusted OR 0.23, P=0.044). Subgroup analyses showed consistent associations. Mediation analysis indicated iPTH and NT-proBNP explained 37% and 21.1% of the HRR-LVH relationship.
Conclusion: HRR may be a simple marker for cardiovascular risk stratification in CKD. Prospective studies should assess whether interventions targeting HRR reduce LVH incidence.
DOI: 10.6084/m9.figshare.30883973.v1
title: Supplementary Material for: Association Between Hemoglobin-to-red Cell Distribution Width Ratio and Left Ventricular Hypertrophy in Non-Dialysis CKD Stage 3–5 Patients: A Cross-Sectional Study

description: Introduction: Left ventricular hypertrophy (LVH) is a common cardiovascular complication in chronic kidney disease (CKD), driven by anemia and nutritional deficiencies. The hemoglobin-to-red cell distribution width ratio (HRR) reflects these factors, but its association with LVH in CKD remains unclear. This study aimed to investigate the relationship between HRR and LVH in non-dialysis CKD stage 3–5 patients.
Methods: In this cross-sectional study, 195 patients were included. HRR was calculated from hemoglobin and red cell distribution width. LVH was diagnosed by echocardiography (LV mass index &gt;115 g/m² men, &gt;95 g/m² women). Logistic regression assessed HRR-LVH association, including subgroup and restricted cubic spline analyses. Mediation analysis explored the role of intact parathyroid hormone (iPTH) and N-terminal pro-brain natriuretic peptide (NT-proBNP).
Results: Patients with LVH (n=40) had significantly lower HRR (median 0.62 vs. 0.81, P&lt;0.001). HRR was inversely associated with LVH (adjusted OR 0.41 per SD increase, P=0.005), with the highest HRR tertile showing the lowest LVH risk (adjusted OR 0.23, P=0.044). Subgroup analyses showed consistent associations. Mediation analysis indicated iPTH and NT-proBNP explained 37% and 21.1% of the HRR-LVH relationship.
Conclusion: HRR may be a simple marker for cardiovascular risk stratification in CKD. Prospective studies should assess whether interventions targeting HRR reduce LVH incidence.
DOI: 10.13130/rd_unimi/f0jgu8/aznkp7
title: Maggio_1928_Pagina_037.jpg

description: Bulletin of 1928/05/10
DOI: 10.13130/rd_unimi/f0jgu8/pef7ge
title: Maggio_1928_Pagina_038.jpg

description: Bulletin of 1928/05/10
DOI: 10.13130/rd_unimi/f0jgu8/jitdhc
title: Maggio_1928_Pagina_039.jpg

description: Bulletin of 1928/05/10
DOI: 10.13130/rd_unimi/f0jgu8/9vjt0a
title: Maggio_1928_Pagina_040.jpg

description: Bulletin of 1928/05/10
DOI: 10.13130/rd_unimi/f0jgu8/xr7qa2
title: Maggio_1928_Pagina_041.jpg

description: Bulletin of 1928/05/11
DOI: 10.6084/m9.figshare.30883976
title: Supplementary Material for: Predicting Incident Atrial Fibrillation After Stroke: A Scoping Review of Clinical Scores, Biomarkers, and AI-enhanced Strategies

description: Post-stroke atrial fibrillation (AFib) is a frequent yet undetected complication, particularly in resource-limited settings, where systematic screening remains challenging. Timely identification is essential for guiding anticoagulation strategies and reducing recurrent stroke risk. This scoping review synthesizes evidence on predictive strategies integrating artificial intelligence, circulating biomarkers, and advanced rhythm-monitoring modalities in adults with ischemic stroke or transient ischemic attack without known AFib. Predictive variables from conventional clinical scores and modern AI-based models were harmonized into a unified framework, highlighting incremental contributions from natriuretic peptides, imaging radiomics, and electronic health record–derived laboratory parameters. A novel analytical construct—area under the curve (AUC)–cost–feasibility mapping—was introduced to compare diagnostic strategies, including risk scores, handheld and patch electrocardiography, smartwatch-based photoplethysmography (with ECG confirmation required for diagnosis), and implantable loop recorders, with explicit consideration of scalability in low- and middle-income countries. Based on this synthesis, a tiered diagnostic pathway is proposed, combining clinical risk stratification with biomarker-guided triage (particularly NT-proBNP and MR-proANP) to inform allocation of extended monitoring resources, thereby optimizing diagnostic yield and cost-effectiveness. Persistent knowledge gaps include the absence of standardized biomarker thresholds, limited head-to-head evaluations of AI-enabled workflow in post-stroke populations, insufficient external validation in diverse populations, and a lack of prospective cost-effectiveness analyses. By integrating predictive domains, quantifying performance–cost trade-offs, and outlining an implementation-oriented, risk-stratified strategy, this review aims to inform AFib screening after stroke from theoretical innovation toward context-adapted clinical application, offering a structured framework to guide both research and practice in diverse healthcare environments.
DOI: 10.6084/m9.figshare.30883976.v1
title: Supplementary Material for: Predicting Incident Atrial Fibrillation After Stroke: A Scoping Review of Clinical Scores, Biomarkers, and AI-enhanced Strategies

description: Post-stroke atrial fibrillation (AFib) is a frequent yet undetected complication, particularly in resource-limited settings, where systematic screening remains challenging. Timely identification is essential for guiding anticoagulation strategies and reducing recurrent stroke risk. This scoping review synthesizes evidence on predictive strategies integrating artificial intelligence, circulating biomarkers, and advanced rhythm-monitoring modalities in adults with ischemic stroke or transient ischemic attack without known AFib. Predictive variables from conventional clinical scores and modern AI-based models were harmonized into a unified framework, highlighting incremental contributions from natriuretic peptides, imaging radiomics, and electronic health record–derived laboratory parameters. A novel analytical construct—area under the curve (AUC)–cost–feasibility mapping—was introduced to compare diagnostic strategies, including risk scores, handheld and patch electrocardiography, smartwatch-based photoplethysmography (with ECG confirmation required for diagnosis), and implantable loop recorders, with explicit consideration of scalability in low- and middle-income countries. Based on this synthesis, a tiered diagnostic pathway is proposed, combining clinical risk stratification with biomarker-guided triage (particularly NT-proBNP and MR-proANP) to inform allocation of extended monitoring resources, thereby optimizing diagnostic yield and cost-effectiveness. Persistent knowledge gaps include the absence of standardized biomarker thresholds, limited head-to-head evaluations of AI-enabled workflow in post-stroke populations, insufficient external validation in diverse populations, and a lack of prospective cost-effectiveness analyses. By integrating predictive domains, quantifying performance–cost trade-offs, and outlining an implementation-oriented, risk-stratified strategy, this review aims to inform AFib screening after stroke from theoretical innovation toward context-adapted clinical application, offering a structured framework to guide both research and practice in diverse healthcare environments.
DOI: 10.13130/rd_unimi/f0jgu8/hyawua
title: Maggio_1928_Pagina_042.jpg

description: Bulletin of 1928/05/11
DOI: 10.13130/rd_unimi/f0jgu8/r5i5hz
title: Maggio_1928_Pagina_044.jpg

description: Bulletin of 1928/05/11
DOI: 10.13130/rd_unimi/f0jgu8/tvdgmj
title: Maggio_1928_Pagina_043.jpg

description: Bulletin of 1928/05/11
DOI: 10.13130/rd_unimi/f0jgu8/f1zpdp
title: Maggio_1928_Pagina_045.jpg

description: Bulletin of 1928/05/12
DOI: 10.13130/rd_unimi/f0jgu8/723b1v
title: Maggio_1928_Pagina_046.jpg

description: Bulletin of 1928/05/12
DOI: 10.13130/rd_unimi/f0jgu8/lbdyv7
title: Maggio_1928_Pagina_047.jpg

description: Bulletin of 1928/05/12
DOI: 10.13130/rd_unimi/f0jgu8/ondsfl
title: Maggio_1928_Pagina_049.jpg

description: Bulletin of 1928/05/13
DOI: 10.13130/rd_unimi/f0jgu8/upllea
title: Maggio_1928_Pagina_048.jpg

description: Bulletin of 1928/05/12
DOI: 10.13130/rd_unimi/f0jgu8/snyn3h
title: Maggio_1928_Pagina_050.jpg

description: Bulletin of 1928/05/13
DOI: 10.13130/rd_unimi/f0jgu8/xjbetl
title: Maggio_1928_Pagina_051.jpg

description: Bulletin of 1928/05/13
DOI: 10.13130/rd_unimi/f0jgu8/oljt66
title: Maggio_1928_Pagina_052.jpg

description: Bulletin of 1928/05/13
DOI: 10.13130/rd_unimi/f0jgu8/fpaeju
title: Maggio_1928_Pagina_053.jpg

description: Bulletin of 1928/05/14
DOI: 10.13130/rd_unimi/f0jgu8/puoa0d
title: Maggio_1928_Pagina_054.jpg

description: Bulletin of 1928/05/14
DOI: 10.13130/rd_unimi/f0jgu8/w0bkdp
title: Maggio_1928_Pagina_055.jpg

description: Bulletin of 1928/05/14
DOI: 10.13130/rd_unimi/f0jgu8/cjhrcl
title: Maggio_1928_Pagina_056.jpg

description: Bulletin of 1928/05/14
DOI: 10.13130/rd_unimi/f0jgu8/xpn46x
title: Maggio_1928_Pagina_057.jpg

description: Bulletin of 1928/05/15
DOI: 10.13130/rd_unimi/f0jgu8/zf5u22
title: Maggio_1928_Pagina_058.jpg

description: Bulletin of 1928/05/15
DOI: 10.13130/rd_unimi/f0jgu8/aykwr0
title: Maggio_1928_Pagina_060.jpg

description: Bulletin of 1928/05/15
DOI: 10.13130/rd_unimi/f0jgu8/jct9qb
title: Maggio_1928_Pagina_059.jpg

description: Bulletin of 1928/05/15
DOI: 10.13130/rd_unimi/f0jgu8/f5i6v1
title: Maggio_1928_Pagina_061.jpg

description: Bulletin of 1928/05/16
DOI: 10.13130/rd_unimi/f0jgu8/t5dhdb
title: Maggio_1928_Pagina_062.jpg

description: Bulletin of 1928/05/16
DOI: 10.13130/rd_unimi/f0jgu8/rtnfbs
title: Maggio_1928_Pagina_063.jpg

description: Bulletin of 1928/05/16
DOI: 10.13130/rd_unimi/f0jgu8/srziez
title: Maggio_1928_Pagina_064.jpg

description: Bulletin of 1928/05/16
DOI: 10.13130/rd_unimi/f0jgu8/n6tpxv
title: Maggio_1928_Pagina_065.jpg

description: Bulletin of 1928/05/17
DOI: 10.13130/rd_unimi/f0jgu8/sb7vqt
title: Maggio_1928_Pagina_066.jpg

description: Bulletin of 1928/05/17
DOI: 10.13130/rd_unimi/f0jgu8/ey1yhh
title: Maggio_1928_Pagina_067.jpg

description: Bulletin of 1928/05/17
DOI: 10.13130/rd_unimi/f0jgu8/3uffcq
title: Maggio_1928_Pagina_068.jpg

description: Bulletin of 1928/05/17
DOI: 10.13130/rd_unimi/f0jgu8/vtmhdv
title: Maggio_1928_Pagina_069.jpg

description: Bulletin of 1928/05/18
DOI: 10.13130/rd_unimi/f0jgu8/q1ellg
title: Maggio_1928_Pagina_070.jpg

description: Bulletin of 1928/05/18
DOI: 10.13130/rd_unimi/f0jgu8/n0w80n
title: Maggio_1928_Pagina_071.jpg

description: Bulletin of 1928/05/18
DOI: 10.13130/rd_unimi/f0jgu8/081ufd
title: Maggio_1928_Pagina_072.jpg

description: Bulletin of 1928/05/18
DOI: 10.13130/rd_unimi/f0jgu8/abwdhs
title: Maggio_1928_Pagina_073.jpg

description: Bulletin of 1928/05/19
DOI: 10.13130/rd_unimi/f0jgu8/fuk6hz
title: Maggio_1928_Pagina_074.jpg

description: Bulletin of 1928/05/19
DOI: 10.13130/rd_unimi/f0jgu8/mfjze8
title: Maggio_1928_Pagina_075.jpg

description: Bulletin of 1928/05/19
DOI: 10.13130/rd_unimi/f0jgu8/jwqevl
title: Maggio_1928_Pagina_076.jpg

description: Bulletin of 1928/05/19
DOI: 10.13130/rd_unimi/f0jgu8/mbrpbp
title: Maggio_1928_Pagina_077.jpg

description: Bulletin of 1928/05/20
DOI: 10.13130/rd_unimi/f0jgu8/e1juek
title: Maggio_1928_Pagina_079.jpg

description: Bulletin of 1928/05/20
DOI: 10.13130/rd_unimi/f0jgu8/pyj9nw
title: Maggio_1928_Pagina_078.jpg

description: Bulletin of 1928/05/20
DOI: 10.13130/rd_unimi/f0jgu8/tagrog
title: Maggio_1928_Pagina_080.jpg

description: Bulletin of 1928/05/20
DOI: 10.13130/rd_unimi/f0jgu8/3hwety
title: Maggio_1928_Pagina_081.jpg

description: Bulletin of 1928/05/21
DOI: 10.13130/rd_unimi/f0jgu8/splbbe
title: Maggio_1928_Pagina_082.jpg

description: Bulletin of 1928/05/21