Trasparenza - PIAO - Piano Integrato di Attività e Organizzazione indice per anni

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Pubblicato il 31-01-2025
Aggiornato il 14-10-2025

[summary] => [format] => 2 [safe_value] =>

Pubblicato il 31-01-2025
Aggiornato il 14-10-2025

[safe_summary] => ) ) ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 121523 ) [1] => Array ( [nid] => 121524 ) [2] => Array ( [nid] => 116209 ) [3] => Array ( [nid] => 116212 ) [4] => Array ( [nid] => 116220 ) [5] => Array ( [nid] => 116221 ) [6] => Array ( [nid] => 116222 ) [7] => Array ( [nid] => 116223 ) [8] => Array ( [nid] => 116224 ) [9] => Array ( [nid] => 116225 ) [10] => Array ( [nid] => 116227 ) [11] => Array ( [nid] => 116228 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2025 - 2027 [format] => [safe_value] => 2025 - 2027 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 481130 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [2] => Array ( [nid] => 107329 [access] => 1 [node] => stdClass Object ( [vid] => 448347 [uid] => 5724 [title] => Trasparenza - PIAO - 2024 - 2026 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107329 [type] => elemento_accordion [language] => it [created] => 1706878528 [changed] => 1738336067 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1738336067 [revision_uid] => 26499 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( [und] => Array ( [0] => Array ( [value] =>

Pubblicato il 02-02-2024
Aggiornato il 09-10-2024

[summary] => [format] => 2 [safe_value] =>

Pubblicato il 02-02-2024
Aggiornato il 09-10-2024

[safe_summary] => ) ) ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 107335 ) [1] => Array ( [nid] => 113752 ) [2] => Array ( [nid] => 113753 ) [3] => Array ( [nid] => 107336 ) [4] => Array ( [nid] => 107337 ) [5] => Array ( [nid] => 107338 ) [6] => Array ( [nid] => 107339 ) [7] => Array ( [nid] => 107340 ) [8] => Array ( [nid] => 107341 ) [9] => Array ( [nid] => 107342 ) [10] => Array ( [nid] => 107343 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2024 - 2026 [format] => [safe_value] => 2024 - 2026 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448347 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [3] => Array ( [nid] => 107330 [access] => 1 [node] => stdClass Object ( [vid] => 448348 [uid] => 5724 [title] => Trasparenza - PIAO - 2023 - 2025 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107330 [type] => elemento_accordion [language] => it [created] => 1706878550 [changed] => 1734506590 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506590 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 104271 ) [1] => Array ( [nid] => 104270 ) [2] => Array ( [nid] => 98301 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2023 - 2025 [format] => [safe_value] => 2023 - 2025 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; 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Pubblicato il 31-01-2025
Aggiornato il 14-10-2025

[summary] => [format] => 2 [safe_value] =>

Pubblicato il 31-01-2025
Aggiornato il 14-10-2025

[safe_summary] => ) ) ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 121523 ) [1] => Array ( [nid] => 121524 ) [2] => Array ( [nid] => 116209 ) [3] => Array ( [nid] => 116212 ) [4] => Array ( [nid] => 116220 ) [5] => Array ( [nid] => 116221 ) [6] => Array ( [nid] => 116222 ) [7] => Array ( [nid] => 116223 ) [8] => Array ( [nid] => 116224 ) [9] => Array ( [nid] => 116225 ) [10] => Array ( [nid] => 116227 ) [11] => Array ( [nid] => 116228 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2025 - 2027 [format] => [safe_value] => 2025 - 2027 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 481130 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [2] => Array ( [nid] => 107329 [access] => 1 [node] => stdClass Object ( [vid] => 448347 [uid] => 5724 [title] => Trasparenza - PIAO - 2024 - 2026 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107329 [type] => elemento_accordion [language] => it [created] => 1706878528 [changed] => 1738336067 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1738336067 [revision_uid] => 26499 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( [und] => Array ( [0] => Array ( [value] =>

Pubblicato il 02-02-2024
Aggiornato il 09-10-2024

[summary] => [format] => 2 [safe_value] =>

Pubblicato il 02-02-2024
Aggiornato il 09-10-2024

[safe_summary] => ) ) ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 107335 ) [1] => Array ( [nid] => 113752 ) [2] => Array ( [nid] => 113753 ) [3] => Array ( [nid] => 107336 ) [4] => Array ( [nid] => 107337 ) [5] => Array ( [nid] => 107338 ) [6] => Array ( [nid] => 107339 ) [7] => Array ( [nid] => 107340 ) [8] => Array ( [nid] => 107341 ) [9] => Array ( [nid] => 107342 ) [10] => Array ( [nid] => 107343 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2024 - 2026 [format] => [safe_value] => 2024 - 2026 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448347 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [3] => Array ( [nid] => 107330 [access] => 1 [node] => stdClass Object ( [vid] => 448348 [uid] => 5724 [title] => Trasparenza - PIAO - 2023 - 2025 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107330 [type] => elemento_accordion [language] => it [created] => 1706878550 [changed] => 1734506590 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506590 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 104271 ) [1] => Array ( [nid] => 104270 ) [2] => Array ( [nid] => 98301 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2023 - 2025 [format] => [safe_value] => 2023 - 2025 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448348 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [4] => Array ( [nid] => 107331 [access] => 1 [node] => stdClass Object ( [vid] => 448349 [uid] => 5724 [title] => Trasparenza - PIAO 2022 - 2024 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107331 [type] => elemento_accordion [language] => it [created] => 1706878567 [changed] => 1734506677 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506677 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 96990 ) [1] => Array ( [nid] => 96991 ) [2] => Array ( [nid] => 88395 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2022 - 2024 [format] => [safe_value] => 2022 - 2024 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448349 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [5] => Array ( [nid] => 107332 [access] => 1 [node] => stdClass Object ( [vid] => 448350 [uid] => 5724 [title] => Trasparenza - PIAO 2021 - 2023 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107332 [type] => elemento_accordion [language] => it [created] => 1706878608 [changed] => 1734506599 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506599 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 83823 ) [1] => Array ( [nid] => 83824 ) [2] => Array ( [nid] => 74930 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2021 - 2023 [format] => [safe_value] => 2021 - 2023 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448350 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [6] => Array ( [nid] => 107333 [access] => 1 [node] => stdClass Object ( [vid] => 448351 [uid] => 5724 [title] => Trasparenza - PIAO 2020 - 2022 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107333 [type] => elemento_accordion [language] => it [created] => 1706878630 [changed] => 1734506590 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506590 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 79266 ) [1] => Array ( [nid] => 79284 ) [2] => Array ( [nid] => 64323 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2020 - 2022 [format] => [safe_value] => 2020 - 2022 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448351 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [7] => Array ( [nid] => 107334 [access] => 1 [node] => stdClass Object ( [vid] => 448352 [uid] => 5724 [title] => Trasparenza - PIAO 2019 - 2021 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107334 [type] => elemento_accordion [language] => it [created] => 1706878668 [changed] => 1734506677 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506677 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 57037 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2019 - 2021 [format] => [safe_value] => 2019 - 2021 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448352 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [8] => Array ( [nid] => 107345 [access] => 1 [node] => stdClass Object ( [vid] => 448371 [uid] => 5724 [title] => Trasparenza - PIAO 2018 - 2020 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107345 [type] => elemento_accordion [language] => it [created] => 1706880421 [changed] => 1734506599 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506599 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 49921 ) [1] => Array ( [nid] => 50656 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2018 - 2020 [format] => [safe_value] => 2018 - 2020 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448371 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [9] => Array ( [nid] => 107346 [access] => 1 [node] => stdClass Object ( [vid] => 448375 [uid] => 5724 [title] => Trasparenza - PIAO 2017 - 2019 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107346 [type] => elemento_accordion [language] => it [created] => 1706880469 [changed] => 1734506590 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506590 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 44682 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2017 - 2019 [format] => [safe_value] => 2017 - 2019 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448375 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [10] => Array ( [nid] => 107347 [access] => 1 [node] => stdClass Object ( [vid] => 448376 [uid] => 5724 [title] => Trasparenza - PIAO 2016 - 2018 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107347 [type] => elemento_accordion [language] => it [created] => 1706880504 [changed] => 1734506677 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506677 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 35408 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2016 - 2018 [format] => [safe_value] => 2016 - 2018 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448376 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [11] => Array ( [nid] => 107348 [access] => 1 [node] => stdClass Object ( [vid] => 448388 [uid] => 5724 [title] => Trasparenza - PIAO 2015 - 2017 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107348 [type] => elemento_accordion [language] => it [created] => 1706881723 [changed] => 1734506593 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506593 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 25250 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2015 - 2017 [format] => [safe_value] => 2015 - 2017 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448388 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) [12] => Array ( [nid] => 107349 [access] => 1 [node] => stdClass Object ( [vid] => 448389 [uid] => 5724 [title] => Trasparenza - PIAO 2014 - 2016 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107349 [type] => elemento_accordion [language] => it [created] => 1706881770 [changed] => 1734506599 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506599 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 20173 ) [1] => Array ( [nid] => 23540 ) [2] => Array ( [nid] => 20176 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2014 - 2016 [format] => [safe_value] => 2014 - 2016 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448389 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) ) [#formatter] => node_reference_default [0] => Array ( [#type] => link [#title] => Trasparenza - PIAO - 2026-2028 [#href] => node/126619 [#options] => Array ( [entity_type] => node [entity] => stdClass Object ( [vid] => 514198 [uid] => 29556 [title] => Trasparenza - PIAO - 2026-2028 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 126619 [type] => elemento_accordion [language] => it [created] => 1766414050 [changed] => 1774252450 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1774252450 [revision_uid] => 4 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => aperto ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 126609 ) [1] => Array ( [nid] => 126610 ) [2] => Array ( [nid] => 126611 ) [3] => Array ( [nid] => 126612 ) [4] => Array ( [nid] => 126613 ) [5] => Array ( [nid] => 126614 ) [6] => Array ( [nid] => 126615 ) [7] => Array ( [nid] => 126616 ) [8] => Array ( [nid] => 126617 ) [9] => Array ( [nid] => 126618 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2026-2028 [format] => [safe_value] => 2026-2028 ) ) ) [name] => jessica.russo [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 514198 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) ) [1] => Array ( [#type] => link [#title] => Trasparenza - PIAO - 2025 - 2027 [#href] => node/116210 [#options] => Array ( [entity_type] => node [entity] => stdClass Object ( [vid] => 481130 [uid] => 5724 [title] => Trasparenza - PIAO - 2025 - 2027 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 116210 [type] => elemento_accordion [language] => it [created] => 1738334031 [changed] => 1766413432 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1766413432 [revision_uid] => 29556 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( [und] => Array ( [0] => Array ( [value] =>

Pubblicato il 31-01-2025
Aggiornato il 14-10-2025

[summary] => [format] => 2 [safe_value] =>

Pubblicato il 31-01-2025
Aggiornato il 14-10-2025

[safe_summary] => ) ) ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 121523 ) [1] => Array ( [nid] => 121524 ) [2] => Array ( [nid] => 116209 ) [3] => Array ( [nid] => 116212 ) [4] => Array ( [nid] => 116220 ) [5] => Array ( [nid] => 116221 ) [6] => Array ( [nid] => 116222 ) [7] => Array ( [nid] => 116223 ) [8] => Array ( [nid] => 116224 ) [9] => Array ( [nid] => 116225 ) [10] => Array ( [nid] => 116227 ) [11] => Array ( [nid] => 116228 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2025 - 2027 [format] => [safe_value] => 2025 - 2027 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 481130 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) ) [2] => Array ( [#type] => link [#title] => Trasparenza - PIAO - 2024 - 2026 [#href] => node/107329 [#options] => Array ( [entity_type] => node [entity] => stdClass Object ( [vid] => 448347 [uid] => 5724 [title] => Trasparenza - PIAO - 2024 - 2026 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107329 [type] => elemento_accordion [language] => it [created] => 1706878528 [changed] => 1738336067 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1738336067 [revision_uid] => 26499 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( [und] => Array ( [0] => Array ( [value] =>

Pubblicato il 02-02-2024
Aggiornato il 09-10-2024

[summary] => [format] => 2 [safe_value] =>

Pubblicato il 02-02-2024
Aggiornato il 09-10-2024

[safe_summary] => ) ) ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 107335 ) [1] => Array ( [nid] => 113752 ) [2] => Array ( [nid] => 113753 ) [3] => Array ( [nid] => 107336 ) [4] => Array ( [nid] => 107337 ) [5] => Array ( [nid] => 107338 ) [6] => Array ( [nid] => 107339 ) [7] => Array ( [nid] => 107340 ) [8] => Array ( [nid] => 107341 ) [9] => Array ( [nid] => 107342 ) [10] => Array ( [nid] => 107343 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2024 - 2026 [format] => [safe_value] => 2024 - 2026 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448347 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) ) [3] => Array ( [#type] => link [#title] => Trasparenza - PIAO - 2023 - 2025 [#href] => node/107330 [#options] => Array ( [entity_type] => node [entity] => stdClass Object ( [vid] => 448348 [uid] => 5724 [title] => Trasparenza - PIAO - 2023 - 2025 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107330 [type] => elemento_accordion [language] => it [created] => 1706878550 [changed] => 1734506590 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506590 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 104271 ) [1] => Array ( [nid] => 104270 ) [2] => Array ( [nid] => 98301 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2023 - 2025 [format] => [safe_value] => 2023 - 2025 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448348 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) ) [4] => Array ( [#type] => link [#title] => Trasparenza - PIAO 2022 - 2024 [#href] => node/107331 [#options] => Array ( [entity_type] => node [entity] => stdClass Object ( [vid] => 448349 [uid] => 5724 [title] => Trasparenza - PIAO 2022 - 2024 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107331 [type] => elemento_accordion [language] => it [created] => 1706878567 [changed] => 1734506677 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506677 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 96990 ) [1] => Array ( [nid] => 96991 ) [2] => Array ( [nid] => 88395 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2022 - 2024 [format] => [safe_value] => 2022 - 2024 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; [num_revisions] => 1 [current_revision_id] => 448349 [is_current] => 1 [is_pending] => [revision_moderation] => ) ) ) [5] => Array ( [#type] => link [#title] => Trasparenza - PIAO 2021 - 2023 [#href] => node/107332 [#options] => Array ( [entity_type] => node [entity] => stdClass Object ( [vid] => 448350 [uid] => 5724 [title] => Trasparenza - PIAO 2021 - 2023 [log] => [status] => 1 [comment] => 0 [promote] => 1 [sticky] => 0 [nid] => 107332 [type] => elemento_accordion [language] => it [created] => 1706878608 [changed] => 1734506599 [tnid] => 0 [translate] => 0 [revision_timestamp] => 1734506599 [revision_uid] => 102 [taxonomy_vocabulary_8] => Array ( ) [body] => Array ( ) [field_accordion_state] => Array ( [und] => Array ( [0] => Array ( [value] => chiuso ) ) ) [field_allegato_element] => Array ( [und] => Array ( [0] => Array ( [nid] => 83823 ) [1] => Array ( [nid] => 83824 ) [2] => Array ( [nid] => 74930 ) ) ) [field_outline_level] => Array ( [und] => Array ( [0] => Array ( [value] => h3 ) ) ) [field_titolo_frontend] => Array ( [und] => Array ( [0] => Array ( [value] => 2021 - 2023 [format] => [safe_value] => 2021 - 2023 ) ) ) [name] => trasparenza [picture] => 0 [data] => b:0; 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Quantitative and Computational Biosciences

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VAI AL SITO >

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2024/25

STESSO CODICE

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Il corso di laurea magistrale in Quantitative and Computational Biosciences combina corsi dell’ambito biologico e delle scienze matematiche, fisiche e statistiche, con una particolare attenzione all’applicazione pratica nei vari ambiti della bioinformatica. Questo approccio transdisciplinare è pensato per riunire studentesse e studenti da vari ambiti STEM all’interno di un unico percorso di studi, sviluppando contaminazioni culturali orientate dal comune interesse in Big Data nell’ambito delle discipline omiche, biologia evoluzionistica, ecologia e fisiologia.
Il Corso, erogato in lingua inglese e in modalità blended, prepara laureate e laureati a lavorare come bioinformatici data scientist nel campo della biologia, analisti di big data e sistemi complessi e sviluppatori di nuovi metodi analitici in biologia.

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VAI AL SITO >

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2024/25

STESSO CODICE

) ) ) [field_next] => Array ( [und] => Array ( [0] => Array ( [value] => 0 ) ) ) [field_search_content_group] => Array ( [und] => Array ( [0] => Array ( [tid] => 2335 ) ) ) [field_anno_acc] => Array ( [und] => Array ( [0] => Array ( [value] => 2025 ) ) ) [field_search_index] => Array ( [und] => Array ( [0] => Array ( [value] => 1 ) ) ) [field_classe] => Array ( ) [field_durata] => Array ( ) [field_sede] => Array ( ) [field_lingua_erogazione] => Array ( ) [field_accesso] => Array ( ) [field_content_descr_type] => Array ( ) [field_qs_ranking_image] => Array ( [und] => Array ( [0] => Array ( [fid] => 138235 [uid] => 102 [filename] => 2025-Biological Sciences-Subject 2025-150.png [uri] => public://QS/2025-Biological Sciences-Subject 2025-150.png [filemime] => image/png [filesize] => 10071 [status] => 1 [timestamp] => 1741879212 [type] => image [field_file_image_alt_text] => Array ( [und] => Array ( [0] => Array ( [value] => 2025-Biological Sciences-Subject 2025-150.png [format] => [safe_value] => 2025-Biological Sciences-Subject 2025-150.png ) ) ) [field_file_image_title_text] => Array ( ) [field_folder] => Array ( [und] => Array ( [0] => Array ( [tid] => 2414 ) ) ) [alt] => 2025-Biological Sciences-Subject 2025-150.png [metadata] => Array ( [height] => 89 [width] => 100 ) [height] => 89 [width] => 100 [title] => ) ) ) [field_qs_ranking_link] => Array ( [und] => Array ( [0] => Array ( [value] => https://www.topuniversities.com/university-subject-rankings/biological-sciences [format] => [safe_value] => https://www.topuniversities.com/university-subject-rankings/biological-sciences ) ) ) [field_desc_testo_breve] => Array ( [und] => Array ( [0] => Array ( [value] => Il corso di laurea magistrale in Quantitative and Computational Biosciences combina corsi dell’ambito biologico e delle scienze matematiche, fisiche e statistiche, con una particolare attenzione all’applicazione pratica nei vari ambiti della bioinformatica. Questo approccio transdisciplinare è pensato per riunire studentesse e studenti da vari ambiti STEM all’interno di un unico percorso di studi, sviluppando contaminazioni culturali orientate dal comune interesse in Big Data nell’ambito delle discipline omiche, biologia evoluzionistica, ecologia e fisiologia. Il Corso, erogato in lingua inglese e in modalità blended, prepara laureate e laureati a lavorare come bioinformatici data scientist nel campo della biologia, analisti di big data e sistemi complessi e sviluppatori di nuovi metodi analitici in biologia. [format] => 3 [safe_value] =>

Il corso di laurea magistrale in Quantitative and Computational Biosciences combina corsi dell’ambito biologico e delle scienze matematiche, fisiche e statistiche, con una particolare attenzione all’applicazione pratica nei vari ambiti della bioinformatica. Questo approccio transdisciplinare è pensato per riunire studentesse e studenti da vari ambiti STEM all’interno di un unico percorso di studi, sviluppando contaminazioni culturali orientate dal comune interesse in Big Data nell’ambito delle discipline omiche, biologia evoluzionistica, ecologia e fisiologia.
Il Corso, erogato in lingua inglese e in modalità blended, prepara laureate e laureati a lavorare come bioinformatici data scientist nel campo della biologia, analisti di big data e sistemi complessi e sviluppatori di nuovi metodi analitici in biologia.

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Quantitative and Computational Biosciences

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Scienza dei materiali

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Scienza dei materiali

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VAI AL SITO DEL CORSO >

 

SCOPRI DI PIÙ SUI CORSI DI LAUREA DELLA SCUOLA DI SCIENZE >

[format] => 2 [safe_value] =>

VAI AL SITO DEL CORSO >

 

SCOPRI DI PIÙ SUI CORSI DI LAUREA DELLA SCUOLA DI SCIENZE >

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2024/2025

stesso codice

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2024/2025

stesso codice

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Con un percorso formativo suddiviso in due fasi, dedicato prima alla preparazione di base nelle discipline chimiche generali, inorganiche e organiche, nella fisica classica e nella matematica e successivamente all'insegnamento delle discipline specifiche della scienza dei materiali (fisica e chimica quantistica, fisica dello stato solido, cristallografia e struttura dei solidi, chimica dello stato solido e organica) questo Corso fornisce una preparazione interdisciplinare consolidata anche dalle attività di laboratorio che si svolgono prevalentemente nella seconda fase del percorso.
Chi si laurea in Scienza dei materiali utilizza e sviluppa materiali innovativi sostenibili e caratterizzati da specifiche funzioni e può svolgere attività di tecnico di alto livello nelle aziende ad elevato contenuto tecnologico e nei settori industriali relativi all’energia, alle materie plastiche, alla microelettronica, alla meccanica, all’aerospazio, all’ottica, alla medicina e alla gioielleria.

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VAI AL SITO DEL CORSO >

 

SCOPRI DI PIÙ SUI CORSI DI LAUREA DELLA SCUOLA DI SCIENZE >

[format] => 2 [safe_value] =>

VAI AL SITO DEL CORSO >

 

SCOPRI DI PIÙ SUI CORSI DI LAUREA DELLA SCUOLA DI SCIENZE >

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2024/2025

stesso codice

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2024/2025

stesso codice

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Con un percorso formativo suddiviso in due fasi, dedicato prima alla preparazione di base nelle discipline chimiche generali, inorganiche e organiche, nella fisica classica e nella matematica e successivamente all'insegnamento delle discipline specifiche della scienza dei materiali (fisica e chimica quantistica, fisica dello stato solido, cristallografia e struttura dei solidi, chimica dello stato solido e organica) questo Corso fornisce una preparazione interdisciplinare consolidata anche dalle attività di laboratorio che si svolgono prevalentemente nella seconda fase del percorso.
Chi si laurea in Scienza dei materiali utilizza e sviluppa materiali innovativi sostenibili e caratterizzati da specifiche funzioni e può svolgere attività di tecnico di alto livello nelle aziende ad elevato contenuto tecnologico e nei settori industriali relativi all’energia, alle materie plastiche, alla microelettronica, alla meccanica, all’aerospazio, all’ottica, alla medicina e alla gioielleria.

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Network Science: Structure and Function

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The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


[summary] => [format] => 2 [safe_value] =>

The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


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The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


[summary] => [format] => 2 [safe_value] =>

The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


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The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

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The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


[summary] => [format] => 2 [safe_value] =>

The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


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The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


[summary] => [format] => 2 [safe_value] =>

The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


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The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


[summary] => [format] => 2 [safe_value] =>

The Department of Mathematics "Tullio Levi-Civita", Room 1A150, Torre Archimede, on Friday, March 1, at 13:30, hosts Network Science: Structure and Function a lecture in the constest of Colloquia Patavina for students, by Remco van der Hofstad, Eindhoven University of Technology.

Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks. Many large-scale networks have, despite their diversity in backgrounds, surprisingly much in common. Many of these networks are small worlds, in the sense that one requires few links to hop between pairs of vertices. Also the variability of the number of connections between elements tends to be enormous, which is related to the scale-free phenomenon.

In this guest lecture, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modelling in terms of graphs and how real-world networks can be modelled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion, such as the spread of fake news, and competition on such scale-free networks.
We assume no prior knowledge in graph theory, probability or otherwise.

To participate, reservation is required.


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Food Industry Engineering

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