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Absolute Expressiveness of Subgraph-Based Centrality Measures
(Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 2023) Pieris, Andreas; Salas Cornejo, Jorge Eduardo
In graph-based applications, a common task is to pinpoint the most important or “central” vertex in a (directed or undirected) graph, or rank the vertices of a graph according to their importance. To this end, a plethora of so-called centrality measures have been proposed in the literature. Such measures assess which vertices in a graph are the most important ones by analyzing the structure of the underlying graph. A family of centrality measures that are suited for graph databases has been recently proposed by relying on the following simple principle: the importance of a vertex in a graph is relative to the number of “relevant” connected subgraphs surrounding it; we refer to the members of this family as subgraph-based centrality measures. Although it has been shown that such measures enjoy several favourable properties, their absolute expressiveness remains largely unexplored. The goal of this work is to precisely characterize the absolute expressiveness of the family of subgraph-based centrality measures by considering both directed and undirected graphs. To this end, we characterize when an arbitrary centrality measure is a subgraph-based one, or a subgraph-based measure relative to the induced ranking. These characterizations provide us with technical tools that allow us to determine whether well-established centrality measures are subgraph-based. Such a classification, apart from being interesting in its own right, gives useful insights on the structural similarities and differences among existing centrality measures.
Advancements in MELD Score and Its Impact on Hepatology
(Thieme Medical Publishers, Inc., 2024) Hudson, David; Valentin Cortez, Francisco Javier; Hurtado Díaz de León, Ivonne; Malhi, Gurpreet; Rivas, Angélica; Afzaal, Tamoor; Rad, Mahsa Rahmany; Díaz Piga, Luis Antonio; Khan, Mohammad Qasim; Arab Verdugo, Juan Pablo
There continues to be an ongoing need for fair and equitable organ allocation. The Model for End-Stage Liver Disease (MELD) score has evolved as a calculated framework to evaluate and allocate patients for liver transplantation objectively. The original MELD score has undergone multiple modifications as it is continuously scrutinized for its accuracy in objectively representing the clinical context of patients with liver disease. Several refinements and iterations of the score have been developed, including the widely accepted MELD-Na score. In addition, the most recent updated iteration, MELD 3.0, has been created. The MELD 3.0 calculator incorporates new variables such as patient sex and serum albumin levels and assigns new weights for serum sodium, bilirubin, international normalized ratio, and creatinine levels. It is anticipated that the use of MELD 3.0 scores will reduce overall waitlist mortality and enhance access for female liver transplant candidates. However, despite the emergence of the MELD score as one of the most objective measures for fair organ allocation, various countries and healthcare systems employ alternative methods for stratification and organ allocation. This review article will highlight the origins of the MELD score, its iterations, the current MELD 3.0, and future directions for managing liver transplantation organ allocation.
An integrated model for rapid and slow transit network design
(2021) Gonzalez-Blanco N.; Mesa J.A.; Marianov Kluge, Vladimir; Mesa, Juan A.
Usually, when a rapid transit line is planned a less efficient system already partially covers the demand of the new line. Thus, when the rapid transit starts its regular services, the slow mode (e.g. bus lines) have to be cancelled or their routes modified. Usually this process is planned according to a sequential way. Firstly, the rapid transit line is designed taking into account private and public flows, and possibly surveys on mobility in order to predict the future utilization of the new infrastructure and/or other criteria. Then, in a second stage, the bus route network is redesigned. However, this sequential process can lead to a suboptimal solution, for which reason in this paper a cooperative model for rapid and slow transit network design is studied. The aim is to design simultaneously both networks and the objective is to maximize the number of passengers captured by both public modes against the private mode. We present a mathematical programming formulation and solve the problem by an improved Benders decomposition approach.
Automatic knowledge-graph creation from historical documents: The Chilean dictatorship as a case study
(2024) Díaz, Camila; Dunstan Escudero, Jocelyn Mariel; Etcheverry, Lorena; Fonck Larraín, Antonia; Grez, Alejandro; Mery Quiroz, Domingo Arturo; Reutter de la Maza, Juan Lorenzo; Rojas, Hugo
We present our results regarding the construction of a knowledge graph from historical documents related to the Chilean dictatorship period (1973-1990). Our approach uses LLMs to automatically recognize entities and relations between them and resolve conflicts between these values. To prevent hallucination, the interaction with the LLM is grounded in a simple ontology with four types of entities and seven types of relations. To evaluate our architecture, we use a gold standard graph constructed using a small subset of the documents, and compare this to the graph obtained from our approach when processing the same set of documents. Results show that the automatic construction manages to recognize a good portion of all the entities in the gold standard and that those not recognized are explained mainly by the level of granularity in which the information is structured in the graph and not because the automatic approach misses an important entity in the graph. Looking forward, we expect this report to encourage work on other similar projects focused on enhancing research in humanities and social science. However, we remark that better evaluation metrics are needed to accurately fine-tune these types of architectures.
CAI Asynchronous Methodology for Emergency Remote Teaching: An Experience in Introduction to Programming
(IEEE Computer Society, 2021) Muñoz Gama, Jorge; Salas-Morales J.; Herskovic V.
CLNews: The First Dataset of the Chilean Social Outbreak for Disinformation Analysis
(Association for Computing Machinery, 2022) Providel, Eliana; Toro, Daniel; Riquelme, Fabián; Mendoza Rocha, Marcelo Gabriel; Puraivan, E.
Disinformation is one of the main threats that loom on social networks. Detecting disinformation is not trivial and requires training and maintaining fact-checking teams, which is labor-intensive. Recent studies show that the propagation structure of claims and user messages allows a better understanding of rumor dynamics. Despite these findings, the availability of verified claims and structural propagation data is low. This paper presents a new dataset with Twitter claims verified by fact-checkers along with the propagation structure of retweets and replies. The dataset contains verified claims checked during the Chilean social outbreak, which allows for studying the phenomenon of disinformation during this crisis. We study propagation patterns of verified content in CLNews, showing differences between false rumors and other types of content. Our results show that false rumors are more persistent than the rest of verified contents, reaching more people than truthful news and presenting low barriers of readability to users. The dataset is fully available and helps understand the phenomenon of disinformation during social crises being one of the first of its kind to be released.
Control of ciliary movement in mammalian oviductal ciliated cells
(1991) Villalon M.; Verdugo P.
Development and Operationalisation of Local Sustainability Indicators - A Global South Perspective on Data Challenges and Opportunities for GIScience
(Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 2023) Steiniger, Stefan; Rojas Quezada, Carolina Alejandra; Truffello Robledo, Ricardo Enrique; Barton Jonathan, Richard
Evaluating and monitoring the sustainable development of nations and cities requires sets of indicators. Such indicator sets should measure equity, health, environmental, or governmental progress or recess - among other sustainability aspects. In 2015 the United Nations ratified 17 Sustainable Development Goals (SDG) assessed through 231 indicators. However, other - local - sets of indicators have been developed too. In this paper we review geodata challenges that emerged when we developed four sustainability indicator sets in Chile. Faced challenges include (geo)data availability and data representativeness, among others. We analyse how GIScience knowledge has contributed to indicator development and outline three priority research topics: (i) updating indicators based on automated processes, while respecting representativeness, (ii) tools for planning scenario generation, and (iii) methods for short- and long-term forecasting.
Economic and Environmental Impact of Military Electrical Vehicle Conversion and Solar Electricity Production
(2020) Pierre Simon, François; Roberts, C.; Girard, Aymeric; Ordoñez, Javier; Rossel, G.S.; CEDEUS (Chile)
Military vehicles carry out defence and training functions; however, they also participate extensively in military operations apart from war, such as supporting citizens in emergency situations. Nonetheless, they continue to contribute to pollution, and carbon emissions in Chile have doubled in recent years. Thus, this study seeks a partial solution to this problem, extending the useful life of an archetypal military vehicle, i.e. AIL Storm internal combustion engine vehicle (ICEV), 4.0L gasoline, through its conversion into an electric vehicle (EV) using lithium-ion batteries. AIL Storm ICE emissions are compared with an equivalent EV conversion prototype, analysing the CO emissions of the EV charged from the Chilean electricity grid or from a solar photovoltaic charging station, taking advantage of the high levels of solar radiation in Chile. This studied model obtains a travel cost of 0.04USD/km in the electric grid charge mode and 0.02USD/km in the Solar power station charge mode, affecting the environment with 155kgCO2 emissions per year of use. In the future, technologies to manufacture or assemble lithium batteries must be developed in the Chilean market. Given the availability of this mineral in Chile, this step would reduce costs and make electric mobility more attractive and affordable.
Evaluación por simulación de estrategias de control automático para fermentadores industriales de cerveza
(Institute of Electrical and Electronics Engineers Inc., 2024) Márquez Giordani, Cristóbal Alberto; Saa Higuera, Pedro; Pérez Correa, José Ricardo
The operation and control of beer fermentation at an industrial scale (> 3000 hL) pose significant challenges due to the dynamic nature of the process and the large reactor volumes involved. Effective control of fermentation temperature, a critical parameter, is hindered by the lack of advanced control models that consider volume heterogeneity. To address this, we implemented a compartmentalized phenomenological model to simulate the fermentation process, focusing on temperature control in the reactor. The model was utilized to compare two control strategies: a conventional Proportional-Integral-Derivative (PID) control system and a Model Predictive Control (MPC) framework, both designed to track a reference temperature profile. Simulation results highlight significant temperature variations across reactor compartments, necessitating the adoption of spatially aware control strategies. The MPC-based control system demonstrated superior performance compared to the PID approach, offering more precise tracking of the temperature reference in all compartments. These findings underscore the potential of MPC for optimizing temperature control in large-scale fermentation processes. Future work will focus on the industrial validation of the model and the control strategies for implementation in operational settings.
Expected First Occurrence Time of Uncertain Future Events in One-Dimensional Linear Systems
(Prognostics and Health Management Society, 2024) Acuña Ureta, David Esteban; Fuentealba Secul, Diego Ignacio; Orchard, Marcos E.
The rapid advancement of machine learning algorithms has significantly enhanced tools for monitoring system health, making data-driven approaches predominant in Prognostics and Health Management (PHM). In contrast, model-based approaches have seen modest progress, as they are often constrained by the need for prior knowledge of specific governing equations, limiting their applicability to a wide range of problems. Recently, rigorous theoretical foundations have been established to extend dynamical systems theory by incorporating prognosis of uncertain events. This article leverages this formal framework to introduce and demonstrate a fundamental mathematical result for one-dimensional linear dynamical systems. The presented theorem offers an analytical expression for approximating the expected time at which an event will first occur in the future. Unlike typical thresholds, this event is triggered by a hazard zone, defined as an uncertain event likelihood function over the system’s state space. Applications of this theorem can be found in implementing real-time prognostic frameworks, where it is crucial to quickly estimate the magnitude of impending failures. Emphasis is placed on minimizing computational burden to facilitate prognostic decision-making.
Exploring the Effects of Applying Learning Analytics for Teaching Procedural Skills in Health Sciences Education
(2021) Villagrán I.
© 2021 ACM.In Health Science Education (HSE), students must demonstrate technical skills in many procedures. However, traditional teaching methodologies limit the possibilities for personalized feedback from an instructor and generally do not allow students to achieve the required proficiency levels. Concerning this, technology has been installed as a learning resource with numerous benefits that allow new multidisciplinary lines of research, such as learning analytics (LA) and educational data mining (EDM). Both LA and EDM seek to improve educational practice based on the intensive use of educational data, such as analyzing online learning patterns, creating performance predictions, and incorporating artificial intelligence techniques. There is a range of possibilities in applying LA and EDM in teaching procedural skills that have not yet been explored. For this reason, this study aims to answer (1) How the educational data explain the development of procedural skills in virtual environments to support the teaching-learning process in Health Science Education?; and (2) How automatic feedback and adaptive personalization affect the performance and instructional design of the procedural skills learning process of health science students? We expect that this study contributes to the field of technical skills learning mediated by technology in higher education by using the data provided by the interaction of students with virtual resources to support educational decision-making and optimize the teaching and learning processes in HSE.
Inspecting the concept knowledge graph encoded by modern language models
(Association for Computational Linguistics (ACL), 2021) Aspillaga, Carlos; Soto, Alvaro; Mendoza Rocha, Marcelo Gabriel
The field of natural language understanding has experienced exponential progress in the last few years, with impressive results in several tasks. This success has motivated researchers to study the underlying knowledge encoded by these models. Despite this, attempts to understand their semantic capabilities have not been successful, often leading to non-conclusive, or contradictory conclusions among different works. Via a probing classifier, we extract the underlying knowledge graph of nine of the most influential language models of the last years, including word embeddings, text generators, and context encoders. This probe is based on concept relatedness, grounded on WordNet. Our results reveal that all the models encode this knowledge, but suffer from several inaccuracies. Furthermore, we show that the different architectures and training strategies lead to different model biases. We conduct a systematic evaluation to discover specific factors that explain why some concepts are challenging. We hope our insights will motivate the development of models that capture concepts more precisely.
Mathematics learning opportunities for students with learning disabilities at special schools
(Psychology of Mathematics Education (PME), 2019) Martin, Constanza San; Rojas, Francico; Martinez, Maria; Ramirez, Chenda; Vega, Vanessa; Paniagua, Ximena
Protobject as a tool for teaching computational thinking to designers: Student perceptions on usability
(Association for Computing Machinery, 2023) Bellino, Alessio; Herskovic, Maida Valeria Paz
Due to the proliferation of technology in daily life and the growing number of ways in which humans and machines interact, the process of designing interactive elements has become critical. Nevertheless, design students are seldom able to design and implement interactive elements because of their limited programming skills. Although there have been some approaches to teach computational thinking using physical computing and focusing on solving real-world problems (e.g., electronic devices such as Arduino, using sensors and actuators), they often entail monetary expenses and require knowledgeable instructors, and are not catered to students without prior programming or electronics knowledge. Hence, we propose the use of Protobject, a low-cost tool that focuses on real-world applications that could be used to teach programming to design students. This study aims to evaluate students' perceptions regarding the usability of Protobject as a tool for learning computational thinking, as well as the clarity of the learning activities designed to teach computational thinking concepts by using Protobject.
Recent Advances in Least-Squares and Discontinuous Petrov-Galerkin Finite Element Methods
(De Gruyter, 2019) Bertrand F.; Demkowicz L.; Gopalakrishnan J.; Heuer N.
© 2019 Walter de Gruyter GmbH, Berlin/Boston 2019.Least-squares (LS) and discontinuous Petrov-Galerkin (DPG) finite element methods are an emerging methodology in the computational partial differential equations with unconditional stability and built-in a posteriori error control. This special issue represents the state of the art in minimal residual methods in the L2-norm for the LS schemes and in dual norm with broken test-functions in the DPG schemes.
Redesigning a Cornerstone Course, Lessons Learned from a Pandemic
(American Society for Engineering Education, 2023) Cortázar Valdés, Catalina; Hilliger Carrasco, Isabel; Astudillo Laroze, Gabriel Alejandro
This evidence-based paper describes the process of implementing and evaluating a flipped classroom approach, in conjunction with a project-based learning methodology, in a remote Cornerstone Engineering course and how it was kept in the face-to-face return. In the first year, cornerstone engineering courses are taught mainly using project-based learning. This methodology allows students to develop teamwork and communication skills and promotes critical thinking allowing students to solve real-world problems. Traditionally, project-based learning courses are taught face-to-face. Due to COVID-19, educational institutions were forced to move from face-to-face teaching to remote teaching and learning. In this new setting, enhancing online teamwork became a challenge. In order to promote teamwork, a flipped classroom methodology with project-based learning was introduced into a Cornerstone Course during the lockdown in 2020. The flipped classroom is a teaching methodology where students learn the concepts before class meetings. In the classroom, the students apply the concepts learned asynchronously. This methodology allows students to take responsibility for their learning and to interact with their peers during classroom hours. It also allows professors to have a more productive time with students. In 2022, educational institutions returned to face-to-face teaching; this course was no exception. The teaching team maintained the flipped classroom methodology with project-based learning face-to-face. A survey was conducted to understand the students' perceptions concerning this methodology. The survey took place at the middle and end of the semester in conjunction with a small discussion group once the semester finished. The student body values the activities in class, where collaboration and teamwork are encouraged. However, they perceive an additional burden by having to watch videos before class. This article contributes to Engineering Education by providing guidelines for implementing a flipped classroom in a Cornerstone project-based learning (PBL) course.
Retrofitting strategies for social housing buildings in different climate conditions.: The Corvi 1010-1020 block type in three Chilean cities
(MDPI Open Access Journals, 2018) Bustamante Gómez, Waldo; Schmitt Rivera, Cristián; Bunster Milnes, Víctor Andrés; Martínez Torres, María Paula; Chateau Gannon, Francisco; CEDEUS (Chile)
Currently, less than 2% of the residential building stock in Chile meets minimum of thermal performance conditions while the current approach to social housing development has proved incapable of ensuring appropriate living standards. Demolishing housing blocks to replace them with new buildings is economically inefficient, environmentally damaging and socially unacceptable, as these structures represent an opportunity to renovate and upgrade existing buildings without disrupting consolidated communities. This ongoing research focuses on renovating the CORVI 1010-1020 housing blocks, a building type that was massively built across the country between 1968 and 1978. Today it is possible to find more than 2,000 units of this type of building—with no significant design variations—throughout Chile, hence between latitudes 18°S and 53°S of extremely diverse climates. This paper analyses the impact of different energy retrofitting strategies in the thermal performance of these emblematic housing estates. Accordingly, building energy simulation is used to evaluate three scenarios, i.e., the original design without changes, a retrofitting proposal focused on meeting current thermal code requirements, and an expansion proposal aimed at increasing both thermal performance and life quality conditions. In order to assess the performance of these scenarios, the simulations focused on three cities with contrasting climatic conditions, i.e., hot-arid (Arica, 18°27'S), Mediterranean (Santiago, 33°27′S) and tundra (Punta Arenas, 53°08′S). Operational energy demand, accumulated hours of thermal discomfort, and payback time periods are considered for comparative analysis. Whereas the results evidence that the cost-effectiveness of the proposed alternatives increases in colder climatic conditions dependant on space heating; overall, this study demonstrates that the retrofitting of these social housing buildings can help achieving significant heating and cooling energy savings as well as improving indoor thermal comfort conditions.
REVIEW AND COMPARISON OF DIFFERENT TIMBER BUILDING PRODUCTS' EMBODIED EMISSIONS USING FREE DATABASES
(World Conference on Timber Engineering, 2023) Victorero Castaño, Felipe Andrés; Mendez, Daniela; Bascuñan, Felipe; Bustamante Gómez, Waldo; CEDEUS (Chile)
This paper aims to present a brief review of sources of information for studying the variability of embodied carbon emissions in structural wood products commonly used in construction. The review considered 13 primary sources, focused on EPDs and generic databases, and allowed the collection of data for the study of 140 products divided into Sawn lumber, Glulam, OSB, and Plywood. The information collected made it possible to identify factors such as the variability of density properties, wood species, the origin of the products, among others. In addition to analyzing the variations in the biogenic carbon of the different products studied. The results allow us to conclude that although the variability of wood products can be significant, like any product of natural origin, when they are studied within the framework of the analysis of the materials of a building, they can present a smaller fluctuation than other materials such as concrete. Moreover, this effect can be accentuated in wood products with greater density or have undergone processes that increase the mass of biogenic carbon per cubic meter in the final product.
Speakers counting by proposed nested microphone array in combination with limited space SRP
(European Signal Processing Conference, EUSIPCO, 2021) Firoozabadi A.D.; Durney H.; Sanhueza M.; Irarrazaval P.; Adasme P.; Zabala-Blanco D.; Palacios-Jativa P.; Azurdia-Meza C.
© 2021 European Signal Processing Conference. All rights reserved.In this paper, a novel method is presented for estimating the number of speakers based on the microphone arrays. Firstly, a 3D snowflake nested microphone array (SNMA) is proposed for recording the speech signals. In the following, the steered response power (SRP) algorithm is implemented on subbands in limited spaces conditions for all microphone pairs related to the subarrays. Therefore, a weighted averaging method is implemented on subband limited spaces SRPs (LSRP), and the final energy map is compared with the histogram of the maximums of the SRP function on different subbands for various time frames. The passed candidate points are categorized by unsupervised K-means clustering and the number of speakers is estimated by the silhouette criteria. The accuracy of the proposed method is compared with PENS, i-vector PLDA, and wavelet-GEVD algorithms. The results show the superiority of the proposed method in comparison with other previous research.

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