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Abstract
Further integration of distributed renewable energy sources in distribution systems requires a paradigm change in grid management by the distribution system operators (DSOs). DSOs are currently moving to an operational planning approach based on activating flexibility from distributed energy resources in day/hour-ahead stages. This paper follows the DSO trends by proposing a methodology for active grid management by which robust optimization is applied to accommodate spatial-temporal uncertainty. The proposed method entails the use of a multi-period AC-OPF, ensuring a reliable solution for the DSO. Wind and PV uncertainty is modeled based on spatial-temporal trajectories, while a convex hull technique to define uncertainty sets for the model is used. A case study based on real generation data allows illustration and discussion of the properties of the model. An important conclusion is that the method allows the DSO to increase system reliability in the real-time operation. However, the computational effort grows with increases in system robustness.

Abstract
Diabetic retinopathy (DR) detection is a critical retinal image analysis task in the context of early blindness prevention. Unfortunately, in order to train a model to accurately detect DR based on the presence of different retinal lesions, typically a dataset with medical expert's annotations at the pixel level is needed. In this paper, a new methodology based on the multiple instance learning (MIL) framework is developed in order to overcome this necessity by leveraging the implicit information present on annotations made at the image level. Contrary to previous MIL-based DR detection systems, the main contribution of the proposed technique is the joint optimization of the instance encoding and the image classification stages. In this way, more useful mid-level representations of pathological images can be obtained. The explainability of the model decisions is further enhanced by means of a new loss function enforcing appropriate instance and mid-level representations. The proposed technique achieves comparable or better results than other recently proposed methods, with 90% area under the receiver operating characteristic curve (AUC) on Messidor, 93% AUC on DR1, and 96% AUC on DR2, while improving the interpretability of the produced decisions.

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We explore the feasibility of a database storage engine housing up to 307 billion genetic Single Nucleotide Polymorphisms (SNP) for online access. We evaluate database storage engines and implement a solution utilizing factors such as dataset size, information gain, cost and hardware constraints. Our solution provides a full feature functional model for scalable storage and query-ability for researchers exploring the SNP's in the human genome. We address the scalability problem by building physical infrastructure and comparing final costs to a major cloud provider. © 2018 IEEE.

Abstract
Ancillary services play a fundamental role in the operation of electricity systems. In the Iberian Peninsula, since mid-2014, ancillary services have gained a transnational dimension, namely through the introduction of cross border balancing replacement reserves between the Portuguese and the Spanish Transmission System Operators (TSOs). This paper evaluates the impact of replacement reserves on the Portuguese electricity system, from the onset of this mechanism until the end of 2017, as a new contribution to earlier studies. It also describes the pecuniary impact of tertiary transactions, the identification, and categorization of possible different scenarios of tertiary mobilization, and the respective impact on the internal tertiary mobilization. On the one hand, the Iberian electricity system is one of the most influenced by a high penetration of intermittent renewables, and therefore one of the best candidates to experience increased benefits from the platform. On the other hand, the Portuguese TSO is one of the most peripheral TSOs in Europe that benefits more from the market integration in various dimensions of the electricity sector.

Abstract