Diego Arenas

Antioquia Institute of Technology

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Vladímir V. Kouznetsov

Industrial University of Santander

F Salamanca

Centro Medico Nacional Siglo XXI

Francisco Mena

German Research Centre for Artificial Intelligence

Joaquín Rodríguez

Université Gustave Eiffel

Andreas Dengel

German Research Centre for Artificial Intelligence

Marlon Nuske

Federal Office for Food and Agriculture

Paola Pellegrini

Université Gustave Eiffel

Grégory Marlière

Université Gustave Eiffel

Marcela Charfuelàn

German Research Centre for Artificial Intelligence

Miro Miranda

German Research Centre for Artificial Intelligence

Cooperative Institutions

Mexican Social Security Institute

Universidad Nacional Autónoma de México

Centro Medico Nacional Siglo XXI

German Research Centre for Artificial Intelligence

Instituto Politécnico Nacional

The Alan Turing Institute

University of Kaiserslautern

Center for Research and Advanced Studies of the National Polytechnic Institute

National Cancer Institute

National Institutes of Health

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[Molecular biology of fragile chromosome X syndrome].

PubMed (1995)

Diego Arenas Fabio Salamanca-Gómez

Fragile X Syndrome

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Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications

arXiv (Cornell University) (2024)

Francisco Mena Diego Arenas Marcela Charfuelàn Marlon Nuske Andreas Dengel

Earth observation (EO) applications involving complex and heterogeneous data sources are commonly approached with machine learning models. However, there is a common assumption that data sources will be persistently available. Different situations could affect the availability of EO sources, like noise, clouds, or satellite mission failures. In this work, we assess the impact of missing temporal and static EO sources in trained models across four datasets with classification and regression tasks. We compare the predictive quality of different methods and find that some are naturally more robust to missing data. The Ensemble strategy, in particular, achieves a prediction robustness up to 100%. We evidence that missing scenarios are significantly more challenging in regression than classification tasks. Finally, we find that the optical view is the most critical view when it is missing individually.

10.48550/arxiv.2403.14297

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Design choices for productive, secure, data-intensive research at scale in the cloud

arXiv (Cornell University) (2019)

Diego Arenas Jon Atkins Clare Austin David Beavan Alvaro Cabres Egea

We present a policy and process framework for secure environments for productive data science research projects at scale, by combining prevailing data security threat and risk profiles into five sensitivity tiers, and, at each tier, specifying recommended policies for data classification, data ingress, software ingress, data egress, user access, user device control, and analysis environments. By presenting design patterns for security choices for each tier, and using software defined infrastructure so that a different, independent, secure research environment can be instantiated for each project appropriate to its classification, we hope to maximise researcher productivity and minimise risk, allowing research organisations to operate with confidence.

10.48550/arxiv.1908.08737

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RECIFE Class Manager

Diego Arenas Paola Pellegrini Grégory Marlière Joaquín Rodríguez

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LC₅₀ Determination and Phenotypic Analysis of Three C₆-C₁ and C₆-C₃ Bio-phenols Using Zebrafish (Danio rerio) Model

DOAJ (DOAJ: Directory of Open Access Journals) (2018)

Diego Arenas Carlos E. Puerto Galvis Vladímir V. Kouznetsov Claudia Marı́a Vargas

Danio

10.3303/cet1864051

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Identification of novel mutations in the RB1 gene in Mexican patients with retinoblastoma

Cancer Genetics and Cytogenetics (2002)

Maricela Rodrı́guez Mauricio Salcedo Marina González Ramón Mauricio Coral‐Vázquez F Salamanca

Single-strand conformation polymorphism

Retinoblastoma

10.1016/s0165-4608(02)00577-0

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Citations (11)

The Autonomous Train

Damien Trentesaux Rudy Dahyot Abel Ouedraogo Diego Arenas Sébastien Lefebvre

The development of autonomous transportation systems has become a major strategical competitiveness factor for industrialists and fleet operators. In this paper, we study the development of autonomous trains. The context of autonomous transportation systems is presented and the needs for autonomous trains are pointed out, as well as relevant risks. Issues that need to be solved to reach the full deployment of autonomous trains are discussed. An initial approach to design an autonomous train is finally presented.

Autonomous system (mathematics)

10.1109/sysose.2018.8428771

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Citations (30)

Pattern of deletions of the dystrophin gene in Mexican Duchenne/Becker muscular dystrophy patients: The use of new designed primers for the analysis of the major deletion “hot spot” region

American Journal of Medical Genetics (1997)

Ramón Mauricio Coral‐Vázquez Diego Arenas Bulmaro Cisneros Laura Peñaloza F Salamanca

10.1002/(sici)1096-8628(19970613)70:3<240::aid-ajmg5>3.3.co;2-y

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Train timetabling during infrastructure maintenance activities

Diego Arenas Paola Pellegrini Saïd Hanafi Joaquín Rodríguez

Maintenance activities are necessary to maintain the functionality of the railway infrastructure. Commonly, the maintenance activities are planned first. Then, the timetable is elaborated respecting the unavailability periods caused by the former. However, unplanned maintenance activities may have to be introduced at short notice, and the timetable must be rearranged. In addition, specific trains may be necessary to perform maintenance activities, and they are typically not scheduled in the timetable. In this case, the timetable may need to be further modified to integrate the maintenance trains. In this paper, we propose a mixed integer linear programming formulation that modifies a timetable to cope with maintenance activities. It includes the consideration of maintenance trains and other specific constraints, such as temporary speed limitations. In this formulation, the modified timetable is optimized based on a microscopic representation of both the infrastructure and the rolling stock. We test the proposed formulation on a real case study in the French railway network and we show its practical applicability.

Unavailability

Maintenance engineering

Planned maintenance

Maintenance actions

10.1109/icirt.2016.7588733

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Citations (1)

Scavenger Activity Evaluation of the Clove Bud Essential Oil (Eugenia caryophyllus) and Eugenol Derivatives Employing ABTS+ Decolorization

Scientia Pharmaceutica (2011)

Diego Arenas Amner Muñoz-Acevedo Leonor Y. Vargas Méndez Vladímir V. Kouznetsov

The essential oil (EO) of clove bud dried fruits from Eugenia caryophyllus was obtained by a conventional hydrodistillation process in an excellent yield (11.7 %). Its chemical composition was analyzed by GC-MS, identifying eugenol as a main constituent (60.5%). Four eugenol-like molecules, γ-diisoeugenol, hydroxymethyleugenol, dihydroeugenol and 1,3-dioxanylphenol, were synthe-sized using eugenol or isoeugenol as initial precursors under green chemistry protocols. To evaluate the possible antioxidant capacity of eugenol compounds including the clove bud EO, the Trolox® Equivalent Antioxidant Capacity value, obtained by the ABTS+• radical-cation discoloration method, was employed. The methodology was performed in a UV-Vis reader of 96-well microplates (dilution methodology), using well-known antioxidant agents (BHA, BHT and vitamin E) as reference compounds. It was found that the prepared eugenol derivatives had a more potent free radical scavenger activity than the reference compounds. In particular, the most active molecules, γ-diisoeugenol and 1,3-dioxanylphenol, were ca. 3-fold more potent than vitamin E.

Trolox

Isoeugenol

ABTS

Scavenger

Squalene

Free radical scavenger

10.3797/scipharm.1109-11

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Citations (31)