Abstract
Net electricity consumption (NEC) is the result of the joint action of actual electricity consumption (AEC) and distributed photovoltaic (DPV) generation. The accuracy of NEC prediction affects the retailers' gaming and ultimate interests in electricity market. The ascending DPV installations present new challenges, with the modifications to the NEC curve becoming greater as DPV penetration increases. To track the changes in DPV penetration and improve the prediction accuracy under high penetration of DPV, a monthly NEC prediction model assembled by support vector regression and time series modeling under an online update framework is proposed. First, the DPV features are extracted from a few known solar customers' information to identify whether other customers install DPV or not. Second, an online update framework is proposed and its accuracy is verified by two validations regarding the conversion of non-solar customers to solar customers (namely the change of DPV penetration). Third, a NEC decoupling model based on historical NEC data of months without DPV installation is established. Finally, a monthly NEC prediction model under different DPV penetrations is proposed. Simulation results show that the proposed prediction method with an online update is more accurate than the individual time series model, and the performance of the prediction model is getting better with the increasing DPV penetration.

Abstract
This paper presents a multilevel ac-dc single-phase converter with cascaded transformers and two dc links. The configuration is composed by k cascaded transformers, which isolate the load from the power source, and 2(k + 1) two-level (2L) legs, in which some insulated-gate bipolar transistor (IGBT) legs can be replaced by diode legs if bidirectional operation is not required. The cascaded transformers have different turns ratio characterizing as an asymmetric configuration. In addition, the second dc link is used to increase the number of voltage levels, which results in better input voltage quality. This dc link has a lower voltage and can be a floating capacitor. The proposed configuration is compared with a conventional configuration. Simulation and experimental results are shown to demonstrate the feasibility of the system.

Abstract
We extend hybrid dynamic logic with binders (for state variables) by distinguishing between observable and silent transitions. This differentiation gives rise to two kinds of observational interpretations: The first one relies on observational abstraction from the ordinary model class of a specification Sp by considering its closure under weak bisimulation. The second one uses an observational satisfaction relation for the axioms of the specification Sp, which relaxes the interpretation of state variables and the satisfaction of modal formulae by abstracting from silent transitions. We establish a formal relationship between both approaches and show that they are equivalent under mild conditions. For the proof we instantiate the previously introduced concept of a behaviour-abstractor framework to the case of dynamic logic with binders and silent transitions. As a particular outcome we provide an invariance theorem and show the Hennessy-Milner property for weakly bisimilar labelled transition systems and observational satisfaction. In the second part of the paper we integrate our results in a development methodology for reactive systems leading to two versions of observational refinement. We provide conditions under which both kinds of refinement are semantically equivalent, involving implementation constructors for relabelling, hiding, and parallel composition.

Abstract
Temporary opportunities for studying and working abroad have been growing globally and intensifying the movement of highly skilled temporary populations. To attract this group, cities need to address their residential and mobility needs. This study focuses on factors influencing residential and travel satisfaction of transnational temporary residents, highlighting the occurrence of residential selfselection, its impacts on residential and travel choices and on derived levels of satisfaction. We have estimated a Bayesian Structural Equations Model and found that lower levels of residential satisfaction (residential dissonance) are associated with lower rents, living farther away from the place of study or work, and having higher transport expenditures. In contrast, higher levels of residential satisfaction (residential consonance) are related to individuals' stronger preferences for active modes, lower levels of public transport use, and reduced transport monthly expenditures, which suggest shorter commuting distances. These findings reveal the tradeoffs involving residential location, monthly rent, and transport expenditures, highlighting that providing good public transport connections can reduce the burden of commuting distances. Our results indicate that better transport supply and land-use balance near the residence can improve both residential and travel satisfaction.

Abstract
Model-driven engineering (MDE) addresses central aspects of robotics software development. MDE could enable domain experts to leverage the expressiveness of models, while implementation details on different hardware platforms would be handled by automatic code generation. Today, despite strong MDE efforts in the robotics research community, most evidence points to manual code development being the norm. A possible reason for MDE not being accepted by robot software developers could be the wide range of applications and target platforms, which make all-encompassing MDE IDEs hard to develop and maintain. Therefore, we chose to leverage a large corpus of open-source software widely adopted by the robotics community to extract common structures and gain insight on how and where MDE can support the developers to work more efficiently. We pursue modeling as a complement, rather than imposing MDE as separate solution. Our previous work introduced metamodels to describe components, their interactions, and their resulting composition. In this paper, we present two methods based on metamodels for automated generation of models from manually written artifacts: (1) through static code analysis and (2) by monitoring the execution of a running system. For both methods, we present tools that leverage the potentials of our contributions, with a special focus on their application at runtime to observe and diagnose a real system during its execution. A comprehensive example is provided as a walk-through for robotics software practitioners.

Abstract
The purpose of this paper is to grasp the connection between entrepreneurial ecosystems and sustainable entrepreneurship and its relevance for tackling societal challenges. In particular, the work investigates if entrepreneurial ecosystems, through the lens of education and social context, simulate social entrepreneurial orientation. To accomplish the research goals, an empirical study is conducted relying on Global Entrepreneurship Monitor from 2015, where 58 countries are analyzed based on the Entrepreneurial Ecosystem Taxonomy. The results point that education and social context are supporters of social entrepreneurship, emphasizing on both institutional and social networks role. However, the findings reveal that social context tends to instigate more regular entrepreneurship when compared to social entrepreneurship, although being a driver in both cases. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.