Abstract: The emergence of digital twin technologies offers a promising avenue for improving decision-making through the integrated use of up-to-date physical or synthetically simulated data. Nevertheless, the practical implementation of digital twins in the built environment remains a significant challenge. This paper describes a system that seamlessly integrates data into digital twins of built assets. The system uses a knowledge graph to achieve data integration, which is designed to be modular, flexible, and interoperable. The graph includes BIM models, metadata from an external IoT platform, and processrelated information. The system is microservice-based and revolves around a graph database housing the knowledge graph. It employs dynamic operations to update the knowledge graph and is tested using civil engineering infrastructure examples. Results from this work can be used to create pipelines that extract and operate with data connecting computational agents integrated into the system as microservices or connected through the system API.

Abstract: The forthcoming industrial environments will require a high level of automation to be flexible. In this sense, Industry 4.0 encourages the integration of new autonomous systems digitally interconnected that can interact with humans. This thesis is developed at CIM 4.0 in the frame of the FIXIT project aiming to produce an autonomous system integrated by a UAV and a UGV. As a result, a combined system that complies with the Industry 4.0 requirements is created and mainly serves an operator by performing inspection tasks. This work is focused on redesigning the UAV airframe. Normally these structures are manufactured with some conventional techniques like molding which limits building complex structures and presents high costs in most cases. In this sense, the scope is to create a personalized structure at a lower price than the standard airframes by implementing one of the industry 4.0 pillars: additive manufacturing. The topology optimization method is integrated into the design process to create a mass-customized structure with optimum structural properties. The role of Additive manufacturing in this work is crucial to obtain an innovative, customized system with an optimum cost considering the prices on the market. The thesis is performed in different phases, starting from the definition of the UAV configuration and the propulsion system. Then a multi-material comparison and the analysis of different airframe designs are performed considering the cost and structural performance. Following this is the detailed design, in which other necessary features like the landing system, devices’ supports, and protection structures are designed. Finally, is performed the manufacturing phase in which a functional prototype is printed through FDM technology. The result is a lightweight customized airframe with good mechanical properties and optimum cost that is well integrated with the electronic components and landing system, enabling its autonomous performance characterized by repeatability and effectiveness. Esta tesis se desarrolla en el marco del proyecto FIXIT en el Centro de Manufactura Integrada (CIM) 4.0 con el objetivo de crear un sistema autónomo integrado por un Vehículo Aéreo No Tripulado (UAV) y un Vehículo Terrestre No Tripulado (UGV). Resultado: Como resultado, se crea un sistema combinado que cumple con los requisitos de la Industria 4.0 y que principalmente sirve a un operador para realizar tareas de inspección. En este sentido, el objetivo de este proyecto de tesis es crear una estructura personalizada a un precio inferior al de las estructuras estándar mediante la implementación de uno de los pilares de la Industria 4.0: la fabricación aditiva. El método de optimización de la topología se integra en el proceso de diseño para crear una estructura personalizada con propiedades estructurales óptimas. El papel de la fabricación aditiva en este trabajo es crucial para obtener un sistema innovador y personalizado con un costo óptimo, teniendo en cuenta los precios del mercado. La tesis se realiza en diferentes fases, comenzando desde la definición de la configuración del UAV y el sistema de propulsión. Luego se realiza una comparación de materiales múltiples y se analizan diferentes diseños de la estructura del UAV teniendo en cuenta el costo y el rendimiento estructural. A continuación, se lleva a cabo el diseño detallado, en el que se diseñan otras características necesarias como el sistema de aterrizaje, los soportes de dispositivos y las estructuras de protección. Finalmente, se realiza la fase de fabricación en la que se imprime un prototipo funcional mediante la tecnología de Fabricación por Deposición Fundida (FDM). El resultado es una estructura personalizada y ligera con buenas propiedades mecánicas y un costo óptimo que se integra bien con los componentes electrónicos y el sistema de aterrizaje, lo que permite su funcionamiento autónomo caracterizado por la repetibilidad y la efectividad.

Abstract: Residency programs face overwhelming numbers of residency applications, limiting holistic review. Artificial intelligence techniques have been proposed to address this challenge but have not been created. Here, a multidisciplinary team sought to develop and validate a machine learning (ML)-based decision support tool (DST) for residency applicant screening and review. Results The ML model areas under the receiver operating characteristic and precision recall curves were 0.95 and 0.76, respectively; these changed to 0.94 and 0.72, respectively, with removal of USMLE scores. Applicants’ medical school information was an important driver of predictions—which had face validity based on the local selection process—but numerous predictors contributed. Program directors used the DST in the 2021 application cycle to select 20 applicants for interview that had been initially screened out during human review. Conclusions The authors developed and validated an ML algorithm for predicting residency interview offers from numerous application elements with high performance—even when USMLE scores were removed. Model deployment in a DST highlighted its potential for screening candidates and helped quantify and mitigate biases existing in the selection process. Further work will incorporate unstructured textual data through natural language processing methods.

Abstract: The decarbonization of energy matrices is crucial to limit global warming below 2°C this century. An alternative capable of enabling zero or even negative CO2 emissions is bioenergy with carbon capture and storage (BECCS). In this sense, the Brazilian sugar–energy sector draws attention, as it would be possible to combine the production of fuel and electricity from renewable biomass. This paper is the final part of a study that aimed to research carbon capture and storage (CCS) in energy systems based on sugarcane. The case studied is CCS in thermal power plants considering two different technologies: the steam cycle based on the condensing–extraction steam turbine (CEST) and the combined cycle integrated to biomass gasification (BIG-CC). The results for the thermal power plant indicate that the CO2 capture costs may be lower than those in cogeneration systems, which were previously studied. The main reasons are the potential scale effects and the minimization of energy penalties associated with integrating the CCS system into the mills. In the best cases, capture costs can be reduced to EUR 54–65 per ton of CO2 for the CEST technology and EUR 57–68 per ton of CO2 for the BIG-CC technology.

Architecture and Urban planning have traditionally been viewed through an adult-centric lens, focusing on adult-scale and experience. However, this approach ignores the valuable insights and perspectives that children can bring to the transformation of our cities. Assemble story began from the desire to make children active participants of society´s transformation and its platform is an instrument to realize it. This is a sample of the process and results in 10 workshops (fall 2022), the collective carried out in Berlin with children between 9-14 years old.

Abstract: Older Colombians face significant adversities: poverty, violence and displacement. However, there is evidence that Latinos are often resilient. We examine resilience in older Colombians living in poverty using an ecological framework that identifies three levels: individual; community; and societal. In this paper we examine data from 16 semi-structured interviews with older Colombians that explore resilience within the context of poverty. We analyze our data using three stages: (1) modified grounded theory; (2) assignment of resilience status; (3) identification of components of the ecological framework which contribute to resilience in these participants. The most striking feature is that some participants are able to adapt to their situation, demonstrating resilience, whilst others are not. Individual characteristics such as psychological and material resources contribute to resilience. At the community level, family, social support, participation and cohesion promote resilience. Finally, at the societal level, social and welfare services, finance, religion and social policy, are important factors. These different levels of resilience are co-dependent, and we illustrate how this is so. We suggest that older Colombians living in poverty often demonstrate resilience, but that more can be done to enhance their lives. This includes interventions at the individual and community levels alongside changes in social policy.

Abstract: Soil available water capacity (AWC) is a key function for human survival and well-being. However, its direct measurement is laborious and spatial interpretation is complex. Digital soil mapping (DSM) techniques emerge as an alternative to spatial modeling of soil properties. DSM techniques commonly apply machine learning (ML) models, with a high level of complexity. In this context, we aimed to perform a digital mapping of soil AWC and interpret the results of the Random Forest (RF) algorithm and, in a case study, to show that digital AWC maps can support agricultural planning in response to the local effects of climate change. To do so, we divided this research into two approaches: In the first approach, we showed a DSM using 1857 sample points in a southeastern region of Brazil with laboratory-determined soil attributes, together with a pedotransfer function (PTF), remote sensing and DSM techniques. In the second approach, the constructed AWC digital soil map and weather station data were used to calculate climatological soil water balances for the periods between 1917–1946 and 1991–2020. The result showed the selection of covariates using Shapley values as a criterion contributed to the parsimony of the model, obtaining goodness-of-fit metrics of R2 0.72, RMSE 16.72 mm m?1, CCC 0.83, and Bias of 0.53 over the validation set. The highest contributing covariates for soil AWC prediction were the Landsat multitemporal images with bare soil pixels, mean diurnal, and annual temperature range. Under the current climate conditions, soil available water content (AW) increased during the dry period (April to August). May had the highest increase in AW (?17 mm m?1) and decrease in September (?14 mm m?1). The used methodology provides support for AWC modeling at 30 m resolution, as well as insight into the adaptation of crop growth periods to the effects of climate change.

Una nueva libertad. La vida, se pone a tus pies. Magazine. Las mujeres, que resisten en Kabul.  Moda. El talle bajo y el color, reconquistan el armario. 101 looks de pasarela. Belleza. Especial estética, tratamientos sin quirófano. Los mejores productos del año.

Fabia Delamoura. LifeStyle Ambassador. Valeria Rees. Miss Universe Costa Rica 2021. Chef Grce Ramirez. Jacqueline Perdomo, an example of female empowerment. Erika & Edgar Pimentel.  

A faltas de ideas... Por Daniel Samper Pizano. Tropero con corazón. Por Daniel Coronell. Razones para escapar a Ucrania. Por Daniel Samper Ospina. Invitados: Ana Bejarano Ricaurte y Enrique Santos Calderón. Caminando por la décima. Gerardo Martínez Martínez.