In the past few years, 3D electron microscopy (3DEM) has undergone a revolution in instrumentation and methodology. One of the central players in this wide-reaching change is the continuous development of image processing software. Here we present Scipion, a software framework for integrating several 3DEM software packages through a workflow-based approach. Scipion allows the execution of reusable, standardized, traceable and reproducible image-processing protocols. These protocols incorporate tools from different programs while providing full interoperability among them. Scipion is an open-source project that can be downloaded from http://scipion.cnb.csic.es.

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Background and aims SARS-CoV-2 pandemic has spurred scientific production in diverse fields of knowledge, including mental health. Yet, the quality of current research may be challenged by the urgent need to provide immediate results to understand and alleviate the consequences of the pandemic. This study aims to examine compliance with basic methodological quality criteria and open scientific research practices on the mental health effects of the COVID-19 pandemic. Method and results Twenty-eight studies were identified through a systematic search. Most of them met the requirements related to reporting key methodological and statistical information. However, the widespread use of convenience samples and the lack of a priori power analysis, coupled with low compliance with open science recommendations, such as pre-registration of studies and availability of databases, raise concerns about the validity, generalisability, and reproducibility of the findings. Conclusions While the importance of offering rapid evidence-based responses to mitigate mental health problems stemming from the COVID-19 pandemic is undeniable, it should not be done at the expense of sacrificing scientific rigor. The results of this study may stimulate researchers and funding agencies to try to orchestrate efforts and resources and follow standard codes of good scientific practice.

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Abstract. As embedded systems must constantly integrate new functionalities, their developement cycles must be based on high-level abstractions, making the software design more flexible. CBSE provides an approach to these new requirements. However, low-level services provided by operating systems are an integral part of embedded applications, furthermore deployed on resource-limited devices. Therefore, the expected benefits of CBSE must not impact on the constraints imposed by the targetted domain, such as memory footprint, energy consumption, and execution time. In this paper, we present the componentization of a legacy industry-established Real-Time Operating System, and how componentbased applications are built on top of it. We use the Think framework that allows to produce flexible systems while paying for flexibility only where desired. Performed experimentions show that the induced overhead is negligeable.

Component-Based Software Engineering (CBSE) does not yet fully address non-functional requirements of embedded systems. To reach this goal, we show how to extend a component model like FRACTAL with relevant abstractions such as threads, protection rings, or security domains. The FRACTAL Architecture Description Language (ADL) is extended by means of properties that tag components, bindings, and interfaces of the system architectural definition with execution schemes, dynamic reconfiguration strategies, protection and isolation patterns, or QoS features. Each extension captures a property-specific "system view" offering a sound basis to address some non-functional requirement. These extensions were experimented in the THINK framework, a C-based implementation of FRACTAL. Results show that THINK provides a generic and efficient approach to fully support these extensions thanks to a customizable toolchain.

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Background: Difficulties in emotion regulation and craving regulation have been linked to eating symptomatology in patients with anorexia nervosa (AN), contributing to the maintenance of their eating disorder. Methods: To investigate clinical and electrophysiological correlates of these processes, 20 patients with AN and 20 healthy controls (HC) completed a computerized task during EEG recording, where they were instructed to down-regulate negative emotions or food craving. Participants also completed self-report measures of emotional regulation and food addiction. The P300 and Late Positive Potential (LPP) ERPs were analysed. Results: LPP amplitudes were significantly smaller during down-regulation of food craving among both groups. Independent of task condition, individuals with AN showed smaller P300 amplitudes compared to HC. Among HC, the self-reported use of re-appraisal strategies positively correlated with LPP amplitudes during emotional regulation task, while suppressive strategies negatively correlated with LPP amplitudes. The AN group, in comparison to the HC group, exhibited greater food addiction, greater use of maladaptive strategies, and emotional dysregulation. Conclusions: Despite the enhanced self-reported psychopathology among AN, both groups indicated neurophysiological evidence of food craving regulation as evidenced by blunted LPP amplitudes in the relevant task condition. Further research is required to delineate the mechanisms associated with reduced overall P300 amplitudes among individuals with AN.