Abstract
The photovoltaic solar potential in an urban sector and the effects produced by the electricity input into a low-voltage grid are determined, the analysis is performed for one year. First, the generation profiles are estimated, assuming the incorporation limits of typical silica panels and using photovoltaic (PV) tiles on roofs as an architectural alternative. Then, the consumer class demand is estimated. Production-demand matching is performed at the load point level to avoid impacts on the grid. A scenario incorporating a new load, induction heating cookers (IHCs) for all residential users, is posed, the use of which coincides with high-radiation hours. Finally, electrical storage is assumed to maximise the PV supply. A 16% coverage with silica PV panels, or 33% with PV tiles, would supply 46% or 39% of the consumption, respectively. With massive incorporation of IHCs and storage, the supply is increased to 73% and 59% of the consumption with silica panels and PV tiles, respectively. An annual consumption reduction of 16 Tn of liquefied petroleum gas is attained in the cases studied. Additionally, it is necessary to redirect the current subsidies for hydro dams and the overall energy sector towards promoting distributed microgeneration.

Abstract
This work proposes a new design for the supporting data structures used to implement multithreaded tabling in Prolog systems. Tabling is an implementation technique that improves the expressiveness of traditional Prolog systems in dealing with recursion and redundant computations. Mode-directed tabling is an extension to the tabling technique that supports the definition of alternative criteria for specifying how answers are aggregated, thus being very suitable for problems where the goal is to dynamically calculate optimal or selective answers. In this work, we leverage the intrinsic potential that mode-directed tabling has to express dynamic programming problems by creating a new design that improves the representation of multi-dimensional arrays in the context of multithreaded tabling. To do so, we introduce a new mode for indexing arguments in mode-directed tabled evaluations, named dim, where each dim argument features a uni-dimensional lock-free array. Experimental results using well-known dynamic programming problems on a 32-core machine show that the new design introduces less overheads and clearly improves the execution time for sequential and multithreaded tabled evaluations.

Abstract
Time of use (TOU) rate has been regarded as an effective strategy to associate utility companies to avoid peak time financial risks and make the most profit out of the market, while most programs are not effective as expected to reduce peak time demand of residents. Exploring the impact factors of peak demand reduction (PDR) can help policy makers find reasons that weaken effects of programs and corresponding measures can be carried out to maximize the benefits. However, averaging quantitative indicators for program assessment and incomplete impactor analysis method in existing research show limitations of revealing the complex reasons behind it. In this paper, an association rule mining based quantitative analysis framework is built to explore the impact of household characteristics on PDR under TOU price making up for the deficiencies in current research. Firstly, a probability distribution based customer PDR characterizing model is proposed, in which difference-indifference model is adopted to quantify the effect of PDR and probability distribution fitting method is used to characterize the feature of PDR for households. Then a comprehensive association rule mining analysis using Apriori algorithm is presented to explore the impacts factors of PDR covering four categories of household characteristics including dwelling characteristics, socio-demographic, appliances and heating and attitudes towards energy. Finally, analysis results of a case study based on 2993 household records containing smart metering data and survey data illustrate that PDR level cannot be obtained simply based on the appliance's ownership and its usage habits. Socio-demographic information of households should be taken into consideration together; Internet connection and good house insulation contribute to the increase of PDR level. Moreover, the percentage of renewable generation for households also show a certain relationship with PDR. The proposed analysis framework and findings will associate retailer to improve the benefits of TOU programs and guide policy makers to design more efficient energy saving policies for residents.

Abstract
The Business Model is recognized as a valuable tool that helps companies leverage their competitive advantage while dealing with market uncertainty. It enables startups to organize in an efficient way, helping them to rapidly adapt to the different challenges they might face. By using a multiple case study this research aims at understanding how and why startups commercializing technology-based products that support healthcare providing activities changed their business model in the path to a sustainable growth. Based on the Business Model Canvas (BMC), it was possible to analyze different approaches used by those startups to face the challenges encountered. Three main challenges were identified that drove change in the business models: lack of knowledge about the customers' needs, lack of knowledge about the best fitting configuration of a standard product to the market, and lack of knowledge about configuration and interests of the different players. Moreover, even though the literature argues that business model evolution is driven by market and technology conditions, the business models of the startups included in this study changed exclusively due to market conditions.

Abstract
The growing importance of Radar solutions in automotive applications results in new standards to be met and more demanding performances to be assured. As such, Radar developers require testers capable of guaranteeing compliance with the specified criteria. This paper presents a preliminary approach to allow over-the-air (OTA) testing and validation of 76-77 GHz and 77-81 GHz Radar units in production lines, covering not only pass/fail conditions, but also determination of the Radar antenna array radiation diagrams (in azimuth and elevation) through a calibrated external power sensor. Preliminary measurements on an open environment test bench are shown for different Radar bandwidths (1 GHz and 4 GHz), illustrating the importance of a clean and shielded anechoic chamber environment as a baseline approach.

Abstract
Integrate-and-fire (IFN) model of a biological neuron is an amplitude-to-time conversion technique that encodes information in the time-spacing between action potentials (spikes). In principle, this encoding scheme can be used to modulate signals in an impulse radio ultra wide-band (IR-UWB) transmitter, making it suitable for low-power applications, such as in wireless sensor networks (WSN) and biomedical monitoring. This paper then proposes an architecture based on IFN encoding method applied to a UWB transceiver scenario, referred to herein as impulse-radio integrate-and-fire (IRIF) transceiver, followed by a system-level study to attest its effectiveness. The transmitter is composed of an integrate-and-fire modulator, a digital controller and memory block, followed by a UWB pulse generator and filter. At the receiver side, a low-noise amplifier, a squarer, a low-pass filter and a comparator form an energy-detection receiver. A processor reconstructs the original signal at the receiver, and the quality of the synthesized signal is then verified in terms of effective number of bits (ENOB). Finally, a link budget is performed. (C) 2019 Published by Elsevier GmbH.