Abstract
A key aspect of any hash map design is the problem of dynamically resizing it in order to deal with hash collisions. In this context, elasticity refers to the ability to automatically resize the internal data structures that support the hash map operations in order to meet varying workloads, thus optimizing the overall memory consumption of the hash map. This work extends a previous lock-free hash trie design to support elastic hashing, i.e., expand saturated hash levels and compress unused hash levels, such that, at each point in time, the number of levels in a path matches the current demand as closely as possible. Experimental results show that elasticity effectively improves the search operation and, in doing so, our design becomes very competitive when compared to other state-of-the-art designs implemented in Java.

Abstract
This article proposes four converters for interfacing a single dc power source and loads of a single-phase three-wire system. The topologies of the proposed converters are based on two-level (2L) and three-level neutral point clamped (NPC) legs. For regulating the dc-link capacitors of the NPC-based converters, a dc-link voltage-balancing technique is proposed to balance the neutral-point voltage using the space-vector pulsewidth modulation, considering the harmonic distortion of the output voltages and the semiconductor losses from an algorithm that defines the vector sequences to be applied. These characteristics make the proposed converters suitable for applications in microgrid employing dc distributed energy resources or ac power supply by adding ac-dc stage. The proposed converters are compared to a conventional 2 L converter from simulated results for evaluating the semiconductor losses in balanced and unbalanced load scenarios. Experimental results are presented to verify the effectiveness of the proposed voltage-balancing technique and to validate the converters.

Abstract
The main goal of this article is to appraise the existence of different patterns of the Entrepreneurial Ecosystems, to identify its relationship with Entrepreneurial Initiative, and recommend entrepreneurship policies that may influence the growth of entrepreneurial action. Without evidence on entrepreneurial ecosystems landscape and what determinants stimulate entrepreneurship in a given environment, policies could become flawed and miss the target. To address research purposes, the analysis was performed using data extracted from the Global Entrepreneurship Monitor (GEM) Database carried out between 2010 and 2016. To ensure a longitudinal perspective, it was used a balanced panel approach followed by Logistic Regression estimations. The article offers a novel and systematic approach, the Entrepreneurial Ecosystem Taxonomy, to overcome a disaggregated perspective on entrepreneurial ecosystems, between individual and context levels. Empirical findings capture four different country profiles, based on two measures: Entrepreneurial ecosystems and entrepreneurial initiative. The results allow to compare the four groups and appraise significant disparities around entrepreneurship determinants, namely, the education factor. While education is commonly recognized as a positive influence on entrepreneurship, the results suggest a contradictory effect. The existence of differentiated profiles and its determinants points outs the importance of developing specific entrepreneurship policy packages attending group specificities.

Abstract
Designing a science activity for middle school children is a challenging task, especially if it aims to be interdisciplinary. One may ask if it is possible to craft a positive learning experience from different areas such as history of science, chemistry, or ethics. In this paper, we argue it can be achieved if we use the right tools to engage a young audience. A combination of gamification, hands-on activities, and storytelling techniques was successfully used, providing a unique form to approach chemistry and ethics subjects in an "edutainment" format. The result is a game that challenges participants to solve a crime, while addressing chemistry topics to gather pieces of evidence and facing science-related ethical conundrums. In our pilot study, participants evaluated this activity positively, identifying the innovation and entertaining features as the most relevant in their gaming experience.

Abstract
The present work aims to compare several load disaggregation methods. While the supervised alternative was found to be the most competent, the semi-supervised is proved to be close in terms of potential, while the unsupervised alternative seems insufficient. By the same token, the tests with long-lasting data prove beneficial to confirm the long-term performance since no significant loss of performance is noticed with the scalar of the time-horizon. Finally, the patchwork of new parametrization and methodology fine-tuning also proves interesting for improving global performance in several methods.

Abstract
This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of IoT devices (e.g., sensors) visited by UAVs is also addressed. The flight plan generated from the model focuses on preventing breakdowns due to a lack of battery charge to maximize the number of nodes visited. In addition to the drone autonomous flight planning, a data storage limitation aspect is also considered. We have presented the energy consumption of drones based on the aerodynamic characteristics of the type of aircraft. Simulations show the algorithm's behavior in generating routes, and the model is evaluated using a reliability metric.