[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Chile is facing one of the steepest increases in Colorectal cancer (CRC) incidence and mortality in the Southern Cone, with the greatest surge occurring in adults ≤ 50 years. Incidence is lowest in the far north and increases toward the south-central regions, mirroring a gradient in Aymara-Mapuche Native-American ancestry, an axis largely absent from the European reference cohorts that guide modern precision oncology. To fill this gap, we propose a four-year project to create the first Chile-specific, multi-omic and histopathological atlas of CRC and to explore ancestry-aware, AI-assisted diagnostics. Rationale and Hypothesis. We hypothesise that Chilean CRC shows (i) unique, ancestry-driven molecular patterns that differ from European tumors; (ii) AI models can detect these patterns directly on routine whole-slide images, and (iii) they shape distinct evolutionary paths in early- versus late-onset disease. Specific objectives. Molecular landscape & heterogeneity: Produce single-gland long-read WGS, methylome, and transcriptome profiles for 100 tumors (30 early-onset, 70 late-onset; ≥30× coverage, ≥50 % purity). Ancestry impact: Phase somatic alterations by local ancestry and contrast their frequencies with European CRC genomes (TCGA, PCAWG). AI-enhanced histopathology: Train and externally validate multi-instance-learning (MIL) models that predict microsatellite instability, driver mutations, and whole-genome doubling from matched WSIs, targeting AUC ≥ 0.80 (pilot: AUC ≥ 0.85 for whole-genome doubling on TCGA WSIs). Evolutionary trajectories: Multi-region sequence early-onset and late-onset tumors, reconstruct their clonal phylogenies, and contrast the resulting evolutionary patterns between the two age groups. Team capacity & resources. Computational biologist Alex Di Genova (genomics & AI), pathologist Juan Carlos Araya (digital pathology), and gastro-immunologist Tamara Pérez-Jeldres (clinical phenotyping) have prospective access to >220 new CRC resections and >1,800 registry entries each year. A biobank already houses 100 well-annotated tumour specimens from hospitals in Santiago and the O’Higgins Region, ready for immediate sequencing and imaging. As a team we are delivering important results as (i) the generation of the first telomere-to-telomere Chilean genome, establishing a population-specific reference; (ii) sequenced >270 high-coverage whole genomes of chileans individuals (70 healthy donors, 120 hereditary-breast-cancer cases, 80 primary gallbladder tumors); iii) built the first multi-omic atlas of gallbladder cancer by integrating our data with Korean (n = 94) and Indian (n = 64) cohorts, uncovering a Chile-enriched proliferative phenotype; and (iv) developed CRAB-MIL, a weakly supervised deep-learning framework that predicts whole-genome doubling from routine H&E slides with an AUC > 0.85 and provides attention maps for interpretability. These accomplishments demonstrate our ability to generate, integrate, and clinically interpret large-scale genomic and AI datasets—capabilities directly transferable to Chilean CRC. International collaborators Anaïs Baudot (Marseille) and Luis Zapata (Institute of Cancer Research, London) further contribute multi-omic network analysis and evolutionary-genomics expertise, respectively. Interdisciplinary workflow. Clinical phenotyping, computational histopathology, PromethION sequencing, and Nextflow harmonisation feed ancestry-aware genomic analyses; attention-based models are fine-tuned on TCGA and Chilean WSIs; computational, pathology, and gastroenterology teams jointly review outputs to prioritise clinically relevant signals. All variant calls, methylomes, expression matrices, AI prediction, and metadata will be released through an open and intuitive TumorMap portal. Expected Outcomes and Impact. The project will (i) reveal population-specific drivers and mutational processes, (ii) quantify the frequency of clinically actionable biomarkers originally identified in Europeans, (iii) deliver image-based tools that offer low-cost, molecular stratification and heterogeneity scoring, and (iv) provide a high-resolution evolutionary framework for EO versus LO CRC. Collectively, these data will offer the first high-resolution portrait of the Chilean CRC and lay the groundwork for ancestry-aware screening, diagnostic, and treatment strategies.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Chile is facing one of the steepest increases in Colorectal cancer (CRC) incidence and mortality in the Southern Cone, with the greatest surge occurring in adults ≤ 50 years. Incidence is lowest in the far north and increases toward the south-central regions, mirroring a gradient in Aymara-Mapuche Native-American ancestry, an axis largely absent from the European reference cohorts that guide modern precision oncology. To fill this gap, we propose a four-year project to create the first Chile-specific, multi-omic and histopathological atlas of CRC and to explore ancestry-aware, AI-assisted diagnostics. Rationale and Hypothesis. We hypothesise that Chilean CRC shows (i) unique, ancestry-driven molecular patterns that differ from European tumors; (ii) AI models can detect these patterns directly on routine whole-slide images, and (iii) they shape distinct evolutionary paths in early- versus late-onset disease. Specific objectives. Molecular landscape & heterogeneity: Produce single-gland long-read WGS, methylome, and transcriptome profiles for 100 tumors (30 early-onset, 70 late-onset; ≥30× coverage, ≥50 % purity). Ancestry impact: Phase somatic alterations by local ancestry and contrast their frequencies with European CRC genomes (TCGA, PCAWG). AI-enhanced histopathology: Train and externally validate multi-instance-learning (MIL) models that predict microsatellite instability, driver mutations, and whole-genome doubling from matched WSIs, targeting AUC ≥ 0.80 (pilot: AUC ≥ 0.85 for whole-genome doubling on TCGA WSIs). Evolutionary trajectories: Multi-region sequence early-onset and late-onset tumors, reconstruct their clonal phylogenies, and contrast the resulting evolutionary patterns between the two age groups. Team capacity & resources. Computational biologist Alex Di Genova (genomics & AI), pathologist Juan Carlos Araya (digital pathology), and gastro-immunologist Tamara Pérez-Jeldres (clinical phenotyping) have prospective access to >220 new CRC resections and >1,800 registry entries each year. A biobank already houses 100 well-annotated tumour specimens from hospitals in Santiago and the O’Higgins Region, ready for immediate sequencing and imaging. As a team we are delivering important results as (i) the generation of the first telomere-to-telomere Chilean genome, establishing a population-specific reference; (ii) sequenced >270 high-coverage whole genomes of chileans individuals (70 healthy donors, 120 hereditary-breast-cancer cases, 80 primary gallbladder tumors); iii) built the first multi-omic atlas of gallbladder cancer by integrating our data with Korean (n = 94) and Indian (n = 64) cohorts, uncovering a Chile-enriched proliferative phenotype; and (iv) developed CRAB-MIL, a weakly supervised deep-learning framework that predicts whole-genome doubling from routine H&E slides with an AUC > 0.85 and provides attention maps for interpretability. These accomplishments demonstrate our ability to generate, integrate, and clinically interpret large-scale genomic and AI datasets—capabilities directly transferable to Chilean CRC. International collaborators Anaïs Baudot (Marseille) and Luis Zapata (Institute of Cancer Research, London) further contribute multi-omic network analysis and evolutionary-genomics expertise, respectively. Interdisciplinary workflow. Clinical phenotyping, computational histopathology, PromethION sequencing, and Nextflow harmonisation feed ancestry-aware genomic analyses; attention-based models are fine-tuned on TCGA and Chilean WSIs; computational, pathology, and gastroenterology teams jointly review outputs to prioritise clinically relevant signals. All variant calls, methylomes, expression matrices, AI prediction, and metadata will be released through an open and intuitive TumorMap portal. Expected Outcomes and Impact. The project will (i) reveal population-specific drivers and mutational processes, (ii) quantify the frequency of clinically actionable biomarkers originally identified in Europeans, (iii) deliver image-based tools that offer low-cost, molecular stratification and heterogeneity scoring, and (iv) provide a high-resolution evolutionary framework for EO versus LO CRC. Collectively, these data will offer the first high-resolution portrait of the Chilean CRC and lay the groundwork for ancestry-aware screening, diagnostic, and treatment strategies.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]La producción de semillas de sandía en Chile es una de las que genera mayores volúmenes (12,5%) y mejores precios (26 MM U$FOB) de exportación respecto del total de semillas exportadas. En los últimos 5 años su exportación ha aumentado considerablemente ocupando el segundo lugar en este mercado. Derivado del procesamiento de los frutos se genera un alto porcentaje de pulpa y cáscara; residuos no aprovechables como subproducto para otras industrias como cuarta gama y/o farmacéutica. El elevado contenido antioxidantes de la sandía representa una oportunidad para su extracción y uso en otras industrias. La solución innovadora permitirá reutilizar grandes volúmenes de la pulpa y cáscara, mitigando su disposición inadecuada y mejorando prácticas agrícolas y biotecnológicas. El objetivo de la propuesta es desarrollar un paquete tecnológico consistente en tres aplicaciones que permiten valorizar los residuos de cáscara y pulpa de sandía para la producción de nutracéuticos, bioenmienda de suelos provenientes de relaves mineros, y sustrato para el crecimiento de microorganismos. El proyecto busca generar innovaciones que promuevan la transformación de los residuos agrícolas, proyectando así nuevos negocios para los productores hortícolas en la industria de los alimentos dando valor agregado a los residuos derivados del procesamiento de semillas. Los resultados esperados de esta iniciativa son: Portafolio de al menos 2 ingredientes funcionales (Licopeno y Citrulina) desarrollados y caracterizados; validación técnica del ingrediente principal (Licopeno o citrulina) con actividad antioxidante; bioenmienda validada en un entorno operacional (campo), alcanzando el nivel de madurez tecnológica TRL7; análisis de mercado robusto que incluye un plan de escalamiento técnico de la bioenmienda; medio de cultivo validado en un entorno operacional (empresas), alcanzando el nivel de madurez tecnológica TRL7; y análisis de mercado robusto que incluye un plan de escalamiento técnico.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]This project will address the implementation of distributed controllers in intelligent agents within AC/DC electrical microgrids. Specifically, this project will address open issues in the distributed control literature for microgrids; these include optimal parameter tuning and resilience to communications disturbances such as transport delays, packet loss, and communication failures due to cyberattacks. All of these are important components that prevent the proliferation of microgrid projects throughout the country and the world. Microgrids have the potential to improve the energy management of renewable resources and the resilience of current and future electrical systems. Furthermore, they aid in decarbonization and benefit the energization of isolated communities and national industries. Based on the above, the main objective of this research is to formulate, implement, and validate distributed intelligent controllers, using reinforcement learning, in agents that comprise interconnected AC/DC microgrids, in order to achieve optimal operation concerning available energy resources despite disturbances and failures in communication channels. To achieve this objective, the following specific objectives are specified: (i) investigate the state of the art in the use of reinforcement learning algorithms in cooperative multi-agent system control and their application to microgrids; (ii) design a deep reinforcement learning algorithm to auxiliary control an ILC of a hybrid AC/DC microgrid with communication loss and variable time delays; (iii) design a distributed controller with parameter and structure adjustment capability through deep reinforcement learning algorithms for the agents of an AC/DC multi-microgrid with communication losses and variable time delay; (iv) design a robust distributed controller through deep reinforcement learning algorithms that allows agents in an AC/DC multi-microgrid to be resilient to heterogeneous and variable transport delays, loss of data packets, and DoS cyber-attacks; (v) build a prototyping platform for multi-agent-based intelligent agent control schemes with digital twin co-simulation; (vi) implement and validate the proposed reinforcement learning controllers in an AC/DC multi-microgrid experimental setup.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Implementación de una ruta de turismo arqueológica y paleontológica que abarque tres comunas: San Vicente de Tagua Tagua, Navidad y San Fernando.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Implementación de una ruta de turismo arqueológica y paleontológica que abarque tres comunas: San Vicente de Tagua Tagua, Navidad y San Fernando.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]