Abstract
In sectorization problems (SPs), a large area is divided into smaller regions for administrative purposes. SPs have applications in many fields. Since real-life problems are often dynamic, in this study, a new model for dynamic SP is proposed. In the problem, points are assigned to service centres and in this way sectors are formed. The sectors must be balanced in terms of distance and demand, which is defined in the objective function and constraints of the model. In the problem, in a certain time period, the coordinates and demands of some points change according to certain statistical distributions. A two-stage solution method is suggested for this problem. In the first stage, the expected values of coordinates and demands of the points are estimated by a Monte Carlo simulation, and in the second stage, the problem is solved like a deterministic optimization problem. The model is nonlinear, but after linearization, it is solved in Python’s Pulp library for benchmarks of different sizes and the results are discussed.

Abstract
Geographically distributed wind turbines, photovoltaic panels and sensors (e.g., pyranometers) produce large volumes of data that can be used to improve renewable energy sources (RES) forecasting skill. However, data owners may be unwilling to share their data, even if privacy is ensured, due to a form of prisoner's dilemma: all could benefit from data sharing, but in practice no one is willing to do do. Our proposal hence consists of a data marketplace, to incentivize collaboration between different data owners through the monetization of data. We adapt here an existing auction mechanism to the case of RES forecasting data. It accommodates the temporal nature of the data, i.e., lagged time-series act as covariates and models are updated continuously using a sliding window. A test case with wind energy data is presented to illustrate and assess the effectiveness of such data markets. All agents (or data owners) are shown to benefit in terms of higher revenue resulting from the combination of electricity and data markets. The results support the idea that data markets can be a viable solution to promote data exchange between RES agents and contribute to reducing system imbalance costs.

Abstract
Distributed data management systems have increasingly been using variants of Snapshot Isolation (SI) as their transactional isolation criteria as it combines strong ACID guarantees with non-blocking reads and scalability. However, most existing proposals are limited by the performance of update propagation and stability detection, in particular, when execution and storage are disaggregated. In this paper, we propose TOPSI, an approach providing a restricted form of Parallel Snapshot Isolation (PSI) that allows partially ordering recent transactions to avoid waiting for remote updates or using a stale snapshot. Moreover, it has the interesting property of making a prefix of history in all sites converge to a common total order. This allows versions to be represented by a single scalar timestamp for certification and storage in a shared store. We demonstrate the impact on throughput and abort rate with a proof-of-concept implementation and the industry-standard TPC-C benchmark. © 2021 ACM.

Abstract
This paper presents how the InterConnect project is enhancing the relationship between smart buildings, energy communities and grids, enabling the potential of interoperable flexibility mechanisms and the offer of new energy and non-energy services. Within this framework DSO will leverage its role of neutral market facilitator acting as key enabler for new business models. The paper presents the first technical definition of the DSO Interface of the H2020 InterConnect project that will ensure interoperable integration of flexibility services between DSOs and the different market parties to support the grid operation towards an increasingly decentralized, digitalized and decarbonized electric system. © 2021 The Institution of Engineering and Technology.

Abstract
O presente artigo objetiva identificar estratégias metodológicas existentes no âmbito dos estudos métricos da informação que contribuem para o mapeamento de inovação. Em termos metodológicos, este estudo qualitativo de caráter exploratório e descritivo parte do levantamento da produção de conhecimento relacionada às tipologias dos estudos métricos na base de dados Web of Science, por meio da relação do termo inovação nas palavras-chave e keywords plus dos artigos. Os resultados destacam a aplicação da inovação nas metrias da informação no âmbito da altmetria, bibliometria, cientometria, patentometria e webometria.

Abstract
Heterogeneous platforms with FPGAs have started to be employed in the High-Performance Computing (HPC) field to improve performance and overall efficiency. These platforms allow the use of specialized hardware to accelerate software applications, but require the software to be adapted in what can be a prolonged and complex process. The main goal of this work is to describe and evaluate mechanisms that can transparently transfer the control flow between CPU and FPGA within the scope of HPC. Combining such a mechanism with transparent software profiling and accelerator configuration could lead to an automatic way of accelerating regular applications. In this work, a mechanism based on the ptrace system call is proposed, and its performance on the Intel Xeon+FPGA platform is evaluated. The feasibility of the proposed approach is demonstrated by a working prototype that performs the transparent control flow transfer of any function call to a matching hardware accelerator. This approach is more general than shared library interposition at the cost of a small time overhead in each accelerator use (about 1.3 ms in the prototype implementation).