Cholec80-CVS: An open dataset with an evaluation of Strasberg's critical view of safety for AI.

Strasberg's criteria to detect a critical view of safety is a widely known strategy to reduce bile duct injuries during laparoscopic cholecystectomy. In spite of its popularity and efficiency, recent studies have shown that human miss-identification errors have led to important bile duct injuries occurrence rates. Developing tools based on artificial intelligence that facilitate the identification of a critical view of safety in cholecystectomy surgeries can potentially minimize the risk of such injuries. With this goal in mind, we present Cholec80-CVS, the first open dataset with video annotations of Strasberg's Critical View of Safety (CVS) criteria. Our dataset contains CVS criteria annotations provided by skilled surgeons for all videos in the well-known Cholec80 open video dataset. We consider that Cholec80-CVS is the first step towards the creation of intelligent systems that can assist humans during laparoscopic cholecystectomy.

Resilient Structural Sparsity in the Design of Consensus Networks.

The consensus problem is relevant to different areas ranging from biology, social psychology, and physics to power systems and robotics. Two crucial aspects of the design of a consensus system are the implementation issues that arise in densely connected networks and the presence of malicious agents that try to cause a deviation from a synchronization state. In this article, we introduce a formulation to design the topology of a consensus network to improve its resilience to attacks while remaining sparse and consistent with the a priori structural relations between the agents. Through mathematical analysis and simulations on artificial and real-world cases, we show the benefits and usefulness of using this strategy to design resilient and structurally sparse consensus networks.

Information Optimization and Transferable State Abstractions in Deep Reinforcement Learning.

While humans and animals learn incrementally during their lifetimes and exploit their experience to solve new tasks, standard deep reinforcement learning methods specialize to solve only one task at a time. As a result, the information they acquire is hardly reusable in new situations. Here, we introduce a new perspective on the problem of leveraging prior knowledge to solve future tasks. We show that learning discrete representations of sensory inputs can provide a high-level abstraction that is common across multiple tasks, thus facilitating the transference of information. In particular, we show that it is possible to learn such representations by self-supervision, following an information theoretic approach. Our method is able to learn abstractions in locomotive and optimal control tasks that increase the sample efficiency in both known and unknown tasks, opening a new path to endow artificial agents with generalization abilities.

The impact of climate change on photovoltaic power potential in Southwestern Colombia.

In this paper, we present the first study of the long-term climate-change impact on photovoltaic power potential in Nariño, Colombia. In this region, more than half of the territory does not have a constant electricity supply, but it has great potential for solutions with renewable energy sources. Based on the Coordinated Regional Downscaling Experiment (CORDEX), we assess the change in photovoltaic power potential towards the end of this century, considering two climate change scenarios, one optimistic and the other pessimistic. Our results suggest that changes in photovoltaic power potential, by the end of the century, will have a maximum decrease of around 2.49% in the central zone of Nariño, with some non-affected areas, and a maximum increase of 2.52% on the southeastern side with respect to the pessimistic climate change scenario.

Machine learning for manually-measured water quality prediction in fish farming.

Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques have been proposed to model the dynamics of such variables to improve the fish farmer's decision-making. Most of the research on ML in aquaculture has focused on scenarios where devices for real-time data acquisition, storage, and remote monitoring are available, making it easy to develop accurate ML techniques. However, fish farmers do not necessarily have access to such devices. Many of them prefer to use equipment to manually measure these variables limiting the amount of available data to process. In this work, we study the use of random forests, multivariate linear regression, and artificial neural networks in scenarios with limited amount of measurements to analyze data from water-quality variables that are commonly measured in fish farming. We propose a methodology to build models in two scenarios: i) estimation of unobserved variables based on the observed ones, and ii) forecasting when a low amount of data is available for training. We show that random forests can be used to forecast dissolved oxygen, pond temperature, pH, ammonia, and ammonium when the water pond variables are measured only twice per day. Moreover, we showed that these prediction models can be implemented on a mobile-based information system and run in an average smartphone that fish farmers can afford.

Prediction of site-specific solar diffuse horizontal irradiance from two input variables in Colombia.

Accurate measurements of diffuse irradiance are essential to design a solar photovoltaic system. However, in-situ radiation measurements in Colombia, South America, can be limited by the costs of the implementation of meteorological stations equipped with a pyranometer mounted on a sun tracker with a shading device, which is required to measure diffuse irradiance. Furthermore, the databases found in Colombia contain missing data, which raises the need for implementing models that are trained with very few features. In this paper, we introduce a methodology based on simple angle calculations and a regression model to predict half-hourly diffuse horizontal solar irradiance from only the measure of global horizontal irradiance and a geographic coordinate as inputs. Using measurements taken from the national solar radiation database for 6 different sites in Colombia and state-of-the-art machine learning models for regression, we validated the accuracy prediction of the proposed methodology. The results showed a prediction error ranging from 5.86 to 9.36 [W/m 2], and a coefficient of determination ranging from 0.9974 to 0.9983. The data-set used along with the feature engineering process and the deep neural network model created can be found in a Github repository referenced in the paper.

Dynamics of Cooperation in a Task Completion Social Dilemma.

We study the situation where the members of a community have the choice to participate in the completion of a common task. The process of completing the task involves only costs and no benefits to the individuals that participate in this process. However, completing the task results in changes that significantly benefit the community and that exceed the participation efforts. A task completion social dilemma arises when the short-term participation costs dissipate any interest in the community members to contribute to the task completion process and therefore to obtain the benefits that result from completing the task. In this work, we model the task completion problem using a dynamical system that characterizes the participation dynamics in the community and the task completion process. We show how this model naturally allows for the incorporation of several mechanisms that facilitate the emergence of cooperation and that have been studied in previous research on social dilemmas, including communication across a network, and indirect reciprocity through relative reputation. We provide mathematical analyses and computer simulations to study the qualitative properties of the participation dynamics in the community for different scenarios.

Dynamics of Metabolism and Decision Making During Alcohol Consumption: Modeling and Analysis.

Heavy alcohol consumption is considered an important public health issue in the United States as over 88 000 people die every year from alcohol-related causes. Research is being conducted to understand the etiology of alcohol consumption and to develop strategies to decrease high-risk consumption and its consequences, but there are still important gaps in determining the main factors that influence the consumption behaviors throughout the drinking event. There is a need for methodologies that allow us not only to identify such factors but also to have a comprehensive understanding of how they are connected and how they affect the dynamical evolution of a drinking event. In this paper, we use previous empirical findings from laboratory and field studies to build a mathematical model of the blood alcohol concentration dynamics in individuals that are in drinking events. We characterize these dynamics as the result of the interaction between a decision-making system and the metabolic process for alcohol. We provide a model of the metabolic process for arbitrary alcohol intake patterns and a characterization of the mechanisms that drive the decision-making process of a drinker during the drinking event. We use computational simulations and Lyapunov stability theory to analyze the effects of the parameters of the model on the blood alcohol concentration dynamics that are characterized. Also, we propose a methodology to inform the model using data collected in situ and to make estimations that provide additional information to the analysis. We show how this model allows us to analyze and predict previously observed behaviors, to design new approaches for the collection of data that improves the construction of the model, and help with the design of interventions.

Modeling and Analysis of Group Dynamics in Alcohol-Consumption Environments.

High-risk drinking is considered a major concern in public health, being the third leading preventable cause of death in the United States. Several studies have been conducted to understand the etiology of high-risk drinking and to design prevention strategies to reduce unhealthy alcohol-consumption and related problems, but there are still major gaps in identifying and investigating the key components that affect the consumption patterns during the drinking event. There is a need to develop tools for the design of methodologies to not only identify such dangerous patterns but also to determine how their dynamics impact the event. In this paper, based on current empirical evidence and observations of drinking events, we model a human group that is in an alcohol-consumption scenario as a dynamical system whose behavior is driven by the interplay between the environment, the network of interactions between the individuals, and their personal motivations and characteristics. We show how this mathematical model complements empirical research in this area by allowing us to analyze, simulate, and predict the drinking group behaviors, to improve the methodologies for field data collection, and to design interventions. Through simulations and Lyapunov stability theory, we provide a computational and mathematical analysis of the impact of the model parameters on the predicted dynamics of the drinking group at the drinking event level. Also, we show how the dynamical model can be informed using data collected in situ and to generate information that can complement the analysis.

Dynamic Task Performance, Cohesion, and Communications in Human Groups.

In the study of the behavior of human groups, it has been observed that there is a strong interaction between the cohesiveness of the group, its performance when the group has to solve a task, and the patterns of communication between the members of the group. Developing mathematical and computational tools for the analysis and design of task-solving groups that are not only cohesive but also perform well is of importance in social sciences, organizational management, and engineering. In this paper, we model a human group as a dynamical system whose behavior is driven by a task optimization process and the interaction between subsystems that represent the members of the group interconnected according to a given communication network. These interactions are described as attractions and repulsions among members. We show that the dynamics characterized by the proposed mathematical model are qualitatively consistent with those observed in real-human groups, where the key aspect is that the attraction patterns in the group and the commitment to solve the task are not static but change over time. Through a theoretical analysis of the system we provide conditions on the parameters that allow the group to have cohesive behaviors, and Monte Carlo simulations are used to study group dynamics for different sets of parameters, communication topologies, and tasks to solve.

Malacoplaquia de vesícula biliar. Aporte de un nuevo caso / A new case of malacoplakia of the gallbladder

Comunicamos un caso de malacoplaquia de vesícula biliar. Lo excepcional y las dificultades de diagnóstico diferencial histopatológico que palntea justifican su conocimiento (AU)

A new case of Malacoplakia of the gallbladder. To report on a case of gallbladder malaclopakia whose difficulties for diferential hyistopathologic diagnosis and rarity justify disclosure (AU)

Hemangiosarcoma de bazo / Splenic hemangiosarcoma

Se describe el caso de una paciente de 70 años con angiosarcoma de bazo, entidad clínica poco reportada en la literatura mundial. Se señalan los aspectos histopatológicos, clínicos y el tratamiento empleado en estos tumores. Notificamos que nuestra paciente después de tres años de su tratamiento se encuentra libre de síntomas (AU)

A 70 years old patient with spleen angiosarcoma is described. This clinical entity is seldom reported in the world literature. Histopathological, and clinical aspects are stated, together with the treatment used in these tumors. It is notified that our patient after three years of treatment, is free of symptoms (AU)

Mesotelioma pleural maligno. Comunicación de un caso y revisión de la literatura / No disponible

Presentamos un caso de mesotelioma pleural maligno de tipo epitelial papilar y patrón desmoplásicoinfiltrativo en una mujer de 28 años, diagnosticado por estudios citológicos del líquido pleural, biopsia por aspiración con aguja fina y corroborado por histopatología después de la intervención quirúrgica. La paciente no presentó ningún tipo de exposición al asbesto u otras sustancias tóxicas. Se realiza una revisión relativa a los aspectos epidemiológicos, fisiopatológicos, clínicos, imagenológicos y terapéuticos; resaltando que a pesar del adecuado diagnóstico, en esta enfermedad la supervivencia media es de 15-21 meses. No existe un criterio uniforme en relación al tratamiento del mesotelioma pleural maligno por lo que es imprescindible la presencia de estudios cooperativos interinstitucionales con elección terapéutica aleatoria (AU)

Here we report a 28-years female patient with a malignant pleural mesothelioma diagnosed through pleural fluid cytology, CT-guided core needle biopsy and confirmed by histopathologic examination after tumour resection. This patient denied exposition to asbestos or others toxic substances. We carried out a review related to epidemiologic, pathophysiologic, clinical, diagnostic and therapeutically aspects; we stood out the bad prognosis of this entity, with a median survival of15-21 months. Due to the failure of any single modality of treatment to significantly affect long-term survival, a variety of combinations of therapy have been used to treat malignant pleural mesothelioma. There are no uniform criteria. As with any rare disease, referral of the patient to a center with extensive experience and expertise in this disease is recommended (AU)

Hemangiosarcoma de bazo / Splenic hemangiosarcoma

Se describe el caso de una paciente de 70 años con angiosarcoma de bazo, entidad clínica poco reportada en la literatura mundial. Se señalan los aspectos histopatológicos, clínicos y el tratamiento empleado en estos tumores. Notificamos que nuestra paciente después de tres años de su tratamiento se encuentra libre de síntomas, lo cual no es usual, pues estos procesos son de mal pronóstico y muy pocos presentan esta evolución

A 70 years old patient with spleen angiosarcoma is described. This clinical entity is seldom reported in the world literature. Histopathological, and clinical aspects are stated, together with the treatment used in these tumors. It is notified that our patient after three years of treatment, is free of symptoms, which is not usual because these processes have bad prognosis and few of them present this evolution

Manifestaciones cutáneas de la sarcoidosis / No disponible

Aunque las manifestaciones cutáneas de la sarcoidosis, las agudas, pueden presentar remisiones, las crónicas pueden ser persistentes, y ser motivo importante de consulta. En nuestra serie de 110 pacientes, 25 presentaron afección cutánea (22,52%), de estos 20 tenían lesiones dérmicas específicas (18,2%) y 5 (4,5%) lesiones inespecíficas. Las lesiones específicas que predominaron fueron las erupciones maculopapulares y las placas y todas presentaron relaciones con estadios radiográficos de esta entidad, fundamentalmente en el estadio I y II. La presencia de afectación clínica fue más representativa en forma de erupciones maculopapulares y en placas, al igual que la evolución crónica. El estudio histopatológico, que según el órgano afectado ayudará al diagnóstico, y la piel por su accesibilidad y su especificidad con la demostración de granulomas sarcoideos, orienta a su confirmación y evita otros exámenes más agresivos y más costosos

Although acute cutaneous manifestations of sarcoidosis may present recurrences, those chronic may persist and be important causes of patient remission to health clinics and dermatologists. In our serie of 110 patients, 25 presented cutaneous affection (22,52 %), 20 out of them had specific skin lesions (18,2%) and 5 (4,5%) non specific lesions. The specific lesions that prevailed were maculopapular eruptions and plates, and all had relationships with radiographic studies of this entity, mainly in I and II stages. The persistence of affections were more representative in maculopapular eruptions and disease, biopsy with the histopathology study which depends of the affected organ, will help to the diagnosis; and the skin due to its accessibility and specificity with the demonstration in sarcoid granulomas guides to its confirmation and prevent more aggressive and expensive exams

Manifestaciones cutáneas de la sarcoidosis / No disponible

Aunque las manifestaciones cutáneas de la sarcoidosis, las agudas, pueden presentar remisiones, las crónicas pueden ser persistentes, y ser motivo importante de consulta. En nuestra serie de 110 pacientes, 25 presentaron afección cutánea (22,52%), de estos 20 tenían lesiones dérmicas específicas (18,2%) y 5 (4,5%) lesiones inespecíficas. Las lesiones específicas que predominaron fueron las erupciones maculopapulares y las placas y todas presentaron relaciones con estadios radiográficos de esta entidad, fundamentalmente en el estadio I y II. La presencia de afectación clínica fue más representativa en forma de erupciones maculopapulares y en placas, al igual que la evolución crónica. El estudio histopatológico, que según el órgano afectado ayudará al diagnóstico, y la piel por su accesibilidad y su especificidad con la demostración de granulomas sarcoideos, orienta a su confirmación y evita otros exámenes más agresivos y más costosos (AU)

Although acute cutaneous manifestations of sarcoidosis may present recurrences, those chronic may persist and be important causes of patient remission to health clinics and dermatologists. In our serie of 110 patients, 25 presented cutaneous affection (22,52 %), 20 out of them had specific skin lesions (18,2%) and 5 (4,5%) non specific lesions. The specific lesions that prevailed were maculopapular eruptions and plates, and all had relationships with radiographic studies of this entity, mainly in I and II stages. The persistence of affections were more representative in maculopapular eruptions and disease, biopsy with the histopathology study which depends of the affected organ, will help to the diagnosis; and the skin due to its accessibility and specificity with the demonstration in sarcoid granulomas guides to its confirmation and prevent more aggressive and expensive exams (AU)