La luz, un sabor inolvidable

La iluminación natural es un parámetro de diseño, el cual permite configurar diferentes ambientes interiores con bajo consumo energético. Actividades con una vista-lateral son muy comunes. Es una de las más antiguas aplicaciones de iluminación por su facilidad, practicismo y apertura accesible. Frecuentemente, esta entrada de luz esta proporcionada por la fachada y está complementada por la vista exterior. A este tipo de vista se le puede denominar vista-lateral.Postprint (published version

Boyeria Irene (Fonscolombe, 1838) y Cordulegaster Boltonii (Donovan, 1807) (Odonata): Dos estrategias en cuanto a sustratos de emergencia de larvas en un mismo hábitat.

Se presentan datos sobre emergencia de Cordulegaster boltonii y Boyeria irene en un río de montaña del centro de España (altitud 1200 m s.n.m.) donde coexisten ambas especies, basados en la recogida semanal de exuvias. Boyeria irene comenzó a emerger 28 días más tarde que C. boltonii. Los sustratos usados por las larvas de ambas especies para emerger se solaparon ampliamente, aunque C. boltonii utilizó significativamente más árboles. Con respecto a otras zonas geográficas, las dos especies han modificado su estrategia, retrasando el inicio del periodo de emergencia. Se discute la importancia de las condiciones ambientales (sobre todo temperatura) en este hecho

Coupling of centralized and decentralized scheduling for robust production in agile production systems

Individualized products and timely delivery require agile just-in-time manufacturing operations. Scheduling needs to deliver a robust performance with high and stable results even when facing disruptions such as machine failures. Existing approaches often generate predictive schedules and adjust them reactively as disturbances occur. However, the effectiveness of rescheduling approaches highly depends on the available degrees of freedom in the predictive schedule. In the proposed approach, a centralized robust scheduling procedure is coupled with a decentralized reinforcement learning algorithm in order to adjust the required degrees of freedom for a maximally efficient production control in real-time

Interoperability Issues Between Learning Object Repositories and Metadata Harvesters

In this paper we describe an open learning object repository on Statistics based on DSpace which contains true learning objects, that is, exercises, equations, data sets, etc. This repository is part of a large project intended to promote the use of learning object repositories as part of the learning process in virtual learning environments. This involves the creation of a new user interface that provides users with additional services such as resource rating, commenting and so. Both aspects make traditional metadata schemes such as Dublin Core to be inadequate, as there are resources with no title or author, for instance, as those fields are not used by learners to browse and search for learning resources in the repository. Therefore, exporting OAI-PMH compliant records using OAI-DC is not possible, thus limiting the visibility of the learning objects in the repository outside the institution. We propose an architecture based on ontologies and the use of extended metadata records for both storing and refactoring such descriptions

Interoperability Issues Between Learning Object Repositories and Metadata Harvesters

In this paper we describe an open learning object repository on Statistics based on DSpace which contains true learning objects, that is, exercises, equations, data sets, etc. This repository is part of a large project intended to promote the use of learning object repositories as part of the learning process in virtual learning environments. This involves the creation of a new user interface that provides users with additional services such as resource rating, commenting and so. Both aspects make traditional metadata schemes such as Dublin Core to be inadequate, as there are resources with no title or author, for instance, as those fields are not used by learners to browse and search for learning resources in the repository. Therefore, exporting OAI-PMH compliant records using OAI-DC is not possible, thus limiting the visibility of the learning objects in the repository outside the institution. We propose an architecture based on ontologies and the use of extended metadata records for both storing and refactoring such descriptions

Prädiktiv-reaktives Scheduling zur Steigerung der Robustheit in der Matrix-Produktion

Due to the increasing individualization of products, manufacturing companies are offering more and more variants with decreased quantities per variant. In addition, customer demand is becoming more volatile and difficult to predict. The main challenge is to eco-nomically produce a fluctuating mix of variants with fluctuating total quantities. Matrix-Production systems aiming for a production in batch size 1 decoupled from a takt are therefore a current object of research. In addition to the design of these systems, an increasingly important role is filled by production planning and control, since the material flows in such production systems are highly complex. The state of research is characterized by a multitude of predictive-reactive methods for scheduling even in complex production systems. However, there is no approach that specifically considers robustness in predictive planning in order to enable reactive rescheduling to maintain the desired logistical performance despite unforeseen disruptions. Therefore, a method for predictive-reactive product control of matrix-structured produc-tion systems was developed in this thesis, which allows the determination of an optimal degree of robustness in predictive robust scheduling and thus enables an optimal mix of prevention and reaction in production control. The method consists of three parts: First, in predictive robust scheduling, a schedule is generated on the basis of the pro-duction program, in which a desired extent of slip times between processing steps is then inserted. The robust schedules are then carried out in a discrete-event simulation. In the event of longer disturbances, a rescheduling corridor is determined secondly, which indicates which processing steps of which orders must be rescheduled depending on the duration of the disturbance and the underlying schedule. The rescheduling corridors are then rescheduled thirdly in reactive rescheduling and the results are transferred to the discrete event simulation for reintegration. Reactive rescheduling uses reinforcement learning based on a decentralized Markov process to learn optimal selection strategies for orders depending on the station. The method was tested in an application for a concept of a flexible body-in-white production with a partner from the automotive industry. The developed method contributes to the understanding of the concept of robustness as well as to the application possibilities and limits of reinforcement learning in production control. To the author’s knowledge, the work is the first approach to integrate robustness considerations directly into predictive-reactive scheduling approaches in order to improve the logistical performance

Microwave-assisted extraction with natural deep eutectic solvents for polyphenol recovery from agrifood waste: Mature for scaling-up?

Agrifood industries generate large amounts of waste that may result in remarkable environmental problems, such as soil and water contamination. Therefore, proper waste management and treatment have become an environmental, economic, and social challenge. Most of these wastes are exceptionally rich in bioactive compounds (e.g., polyphenols) with potential applications in the food, cosmetic, and pharmaceutical industries. Indeed, the recovery of polyphenols from agrifood waste is an example of circular bioeconomy, which contributes to the valorization of waste while providing solutions to environmental problems. In this context, unconventional extraction techniques at the industrial scale, such as microwave-assisted extraction (MAE), which has demonstrated its efficacy at the laboratory level for analytical purposes, have been suggested to search for more efficient recovery procedures. On the other hand, natural deep eutectic solvents (NADES) have been proposed as an efficient and green alternative to typical extraction solvents. This review aims to provide comprehensive insights regarding the extraction of phenolic compounds from agrifood waste. Specifically, it focuses on the utilization of MAE in conjunction with NADES. Moreover, this review delves into the possibilities of recycling and reusing NADES for a more sustainable and cost-efficient industrial application. The results obtained with the MAE-NADES approach show its high extraction efficiency while contributing to green practices in the field of natural product extraction. However, further research is necessary to improve our understanding of these extraction strategies, optimize product yields, and reduce overall costs, to facilitate the scaling-up.Peer ReviewedPostprint (published version

Demonstration of a Concept for Scalable Automation of Assembly Systems in a Learning Factory

Companies operating assembly systems in global production networks constantly have to deal with change drivers. For the design of adaptable assembly systems, change drivers can be considered as fluctuating KPIs, such as labor costs, as well as changing KPI targets, such as rising quality requirements. In this paper, a concept for the design of changeable assembly lines with scalable automation is introduced and applied to the Learning Factory Global Production at KIT. The change of the automation level over time is based on an ex ante evaluation and ex post performance assessment of the impact of change drivers

Epigenetic alterations in Fanconi Anaemia: Role in pathophysiology and therapeutic potential

Fanconi anaemia (FA) is an inherited disorder characterized by chromosomal instability. The phenotype is variable, which raises the possibility that it may be affected by other factors, such as epigenetic modifications. These play an important role in oncogenesis and may be pharmacologically manipulated. Our aim was to explore whether the epigenetic profiles in FA differ from non-FA individuals and whether these could be manipulated to alter the disease phenotype. We compared expression of epigenetic genes and DNA methylation profile of tumour suppressor genes between FA and normal samples. FA samples exhibited decreased expression levels of genes involved in epigenetic regulation and hypomethylation in the promoter regions of tumour suppressor genes. Treatment of FA cells with histone deacetylase inhibitor Vorinostat increased the expression of DNM3T beta and reduced the levels of CIITA and HDAC9, PAK1, USP16, all involved in different aspects of epigenetic and immune regulation. Given the ability of Vorinostat to modulate epigenetic genes in FA patients, we investigated its functional effects on the FA phenotype. This was assessed by incubating FA cells with Vorinostat and quantifying chromosomal breaks induced by DNA cross-linking agents. Treatment of FA cells with Vorinostat resulted in a significant reduction of aberrant cells (81\% on average). Our results suggest that epigenetic mechanisms may play a role in oncogenesis in FA. Epigenetic agents may be helpful in improving the phenotype of FA patients, potentially reducing tumour incidence in this population.publishersversionpublishe