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¿Por qué tienen éxito (o fracasan) los movimientos opt-out en sistemas de rendición de cuentas con bajas consecuencias? Un estudio de caso de la Red de Escuelas Insumisas en Cataluña

External and standardized assessments based on student results are a contested education policy among school actors. Movements of opposition have emerged in different countries, especially in those contexts with high-stakes accountability systems. However, this phenomenon has not been analyzed in soft accountability systems. The objective of this article is to study the opt-out movement in Catalonia, understood as an anti-standardization movement in a system of soft accountability. In order to do so, we adopt the case study approach as a methodological strategy, based on the triangulation of semi-structured interviews with activists (n = 14), key stakeholders (n = 3), and document and press analysis (n = 25). The results shed light on the emergence and nature of the movement, its opportunity structures, the discursive frames and the repertoires of collective action. Our results show how accountability instruments have a 'life of their own' beyond their policy design. In this sense, the opt-out movement in Catalonia identifies potential risks and adverse effects similar to those reported in high-stakes systems, developing a repertoire of collective action and discursive frames similar to other emerging anti-standardization movements in high-stakes contexts

A production planning model considering uncertain demand using two-stage stochastic programming in a fresh vegetable supply chain context

Production planning models are achieving more interest for being used in the primary sector of the economy. The proposed model relies on the formulation of a location model representing a set of farms susceptible of being selected by a grocery shop brand to supply local fresh products under seasonal contracts. The main aim is to minimize overall procurement costs and meet future demand. This kind of problem is rather common in fresh vegetable supply chains where producers are located in proximity either to processing plants or retailers. The proposed two-stage stochastic model determines which suppliers should be selected for production contracts to ensure high quality products and minimal time from farm-to-table. Moreover, Lagrangian relaxation and parallel computing algorithms are proposed to solve these instances efficiently in a reasonable computational time. The results obtained show computational gains from our algorithmic proposals in front of the usage of plain CPLEX solver. Furthermore, the results ensure the competitive advantages of using the proposed model by purchase managers in the fresh vegetables industry.This work was supported by the MEyC under contracts TIN2011-28689-C02-02, TRA2013-48180-C3-P and TIN2014- 53234-C2-2-R. The authors are members of the research group 2014-SGR163 and 2014-SGR151, funded by the Generali- tat de Catalunya

A Reinforcement Learning Control in Hot Stamping for Cycle Time Optimization

Hot stamping is a hot metal forming technology increasingly in demand that produces ultra-high strength parts with complex shapes. A major concern in these systems is how to shorten production times to improve production Key Performance Indicators. In this work, we present a Reinforcement Learning approach that can obtain an optimal behavior strategy for dynamically managing the cycle time in hot stamping to optimize manufacturing production while maintaining the quality of the final product. Results are compared with the business-as-usual cycle time control approach and the optimal solution obtained by the execution of a dynamic programming algorithm. Reinforcement Learning control outperforms the business-as-usual behavior by reducing the cycle time and the total batch time in non-stable temperature phases

An Internet of Things Platform Based on Microservices and Cloud Paradigms for Livestock

With the growing adoption of the Internet of Things (IoT) technology in the agricultural sector, smart devices are becoming more prevalent. The availability of new, timely, and precise data offers a great opportunity to develop advanced analytical models. Therefore, the platform used to deliver new developments to the final user is a key enabler for adopting IoT technology. This work presents a generic design of a software platform based on the cloud and implemented using microservices to facilitate the use of predictive or prescriptive analytics under different IoT scenarios. Several technologies are combined to comply with the essential features¿scalability, portability, interoperability, and usability¿that the platform must consider to assist decision-making in agricultural 4.0 contexts. The platform is prepared to integrate new sensor devices, perform data operations, integrate several data sources, transfer complex statistical model developments seamlessly, and provide a user-friendly graphical interface. The proposed software architecture is implemented with open-source technologies and validated in a smart farming scenario. The growth of a batch of pigs at the fattening stage is estimated from the data provided by a level sensor installed in the silo that stores the feed from which the animals are fed. With this application, we demonstrate how farmers can monitor the weight distribution and receive alarms when high deviations happen.This research was partially supported by the Intelligent Energy Europe (IEE) program and the Ministerio de Economía y Competitividad under contract TIN2017-84553-C2-2-R, by the European Union FEDER (CAPAP-H6 network TIN2016-81840-REDT) and the demonstration activity financed by the Operation 01.02.01 of Technological Transfer from the Program of Rural Development in Catalunya 2014–2020 cofinanced by DARP and FEDER

Repolarization of tumor infiltrating macrophages and increased survival in mouse primary CNS lymphomas after XPO1 and BTK inhibition

Altres ajuts: This work was supported by research funding from the Instituto de Salud Carlos III, Fondo de Investigaciones Sanitarias cofinanced by the European Regional Development Fund (ERDF); Fundación Asociación Española Contra el Cáncer (M.C. and P.A.) and Gilead Fellowships (GLD16/00144, GLD18/00047, F.B). M.C. holds a contract from Ministerio de Ciencia, Innovación y Universidades. S.B. is the recipient of a postdoctoral fellowship from Fundación Alfonso Martin Escudero.Patients diagnosed with primary central nervous system lymphoma (PCNSL) often face dismal outcomes due to the limited availability of therapeutic options. PCNSL cells frequently have deregulated B-cell receptor (BCR) signaling, but clinical responses to its inhibition using ibrutinib have been brief. In this regard, blocking nuclear export by using selinexor, which covalently binds to XPO1, can also inhibit BCR signaling. Selinexor crosses the blood-brain barrier and was recently shown to have clinical activity in a patient with refractory diffuse large B-cell lymphoma in the CNS. We studied selinexor alone or in combination with ibrutinib in pre-clinical mouse models of PCNSL. Orthotopic xenograft models were established by injecting lymphoma cells into the brain parenchyma of athymic mice. Tumor growth was monitored by bioluminescence. Malignant cells and macrophages were studied by immunohistochemistry and flow cytometry. Selinexor blocked tumor growth and prolonged survival in a bioluminescent mouse model, while its combination with ibrutinib further increased survival. CNS lymphoma in mice was infiltrated by tumor-promoting M2-like macrophages expressing PD-1 and SIRPα. Interestingly, treatment with selinexor and ibrutinib favored an anti-tumoral immune response by shifting polarization toward inflammatory M1-like and diminishing PD-1 and SIRPα expression in the remaining tumor-promoting M2-like macrophages. These data highlight the pathogenic role of the innate immune microenvironment in PCNSL and provide pre-clinical evidence for the development of selinexor and ibrutinib as a new promising therapeutic option with cytotoxic and immunomodulatory potential. The online version of this article (10.1007/s11060-020-03580-y) contains supplementary material, which is available to authorized users

Memòria personal : una altra manera de llegir la història

El llibre proposa el consens assolit entre les diverses fórmules que s'han afirmat amb més o menys fortuna els darrers temps al voltant de la literatura personal, aquella del "jo", autobiogràfica, dietarística. Memòria personal entre històri