Abstract
Purpose The entrepreneurial initiative is believed as being a prosperity engine. Islamic organizations are presently committed to promoting entrepreneurship to generate economic growth, provide job opportunities, reduce government centrality, enhance innovation and sustainable development. The purpose of this paper is to identify which factors affect Islamic entrepreneurial endeavors with particular emphasis on the role of gender. Additionally, how education, age, moral constraints, self-perception and social support will affect those entrepreneurial intentions based on Islamic principles. Once identified, policy actions will help to overcome extant gaps, reinforcing the entrepreneurial ecosystem. Design/methodology/approach Determinants of the entrepreneurial initiative will be appraised in the set Islamic countries present in the Global Entrepreneurship Monitor (GEM) data set from 2016. Following the Organization of Islamic Cooperation list, 14 countries were identified establishing a total sample of 36,407 individuals. Using a set of predictors included in the theoretical framework a statistical analysis was performed followed by logit estimations. The significance of explanatory variables such as gender, age and social context toward entrepreneurial propensity reinforced the importance of specific tools rather than broad policies. Findings An entrepreneurial propensity is affected by three branches of factors: individual characteristics, individual behavior and individual perceptions along with the economic environment. The analysis shows that holding equal conditions, Islamic women in the sample are less prone to start a business compared to their male counterparts. Knowing other entrepreneurial endeavors enhance the entrepreneurial initiative. Fearing failure unconstraint entrepreneurial projects, but the self-perception of skills strongly triggers these initiatives. Research limitations/implications The empirical analysis relates to the GEM database, and, as a consequence, only 14 countries were considered, but it covers 36,407 individuals whose representativeness cannot be statistically proved, however, due to sample dimension the robustness is granted. Second, the sample is sectional covering the 2016 year, as a consequence results may be classified as exceptional.Finally, other factors such as institutional and behavioral determinants were not considered, despite their theoretical importance, due to their absence in the database. Still, the empirical results reinforce the theoretical debate and offer robust evidence to build a policy package, adapted to the Islamic singularities. Practical implications Still, the empirical results reinforce the theoretical debate and offer robust evidence to build a policy package, adapted to the Islamic singularities. Originality/value The paper identifies gender differences in entrepreneurial propensity among Islamic economics. The potential enhancers of the entrepreneurial initiative are first put in theoretical terms followed by an empirical analysis, encompassing descriptive analysis and econometric estimations. The results allow identification of gender gaps, as well as other individual and context characteristics affecting entrepreneurial endeavors. Empirical evidence casts light on policymakers elaborating accurate policy packages fostering gender equality in entrepreneurship in Islamic economics, aiming to increase overall entrepreneurial activity and leveraging socio-economic development. Finally, the study addresses recommendations to overcome gender differences relating to entrepreneurial activity considering the singularities of the context.

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.

Abstract
Dermoscopic images allow the detailed examination of subsurface characteristics of the skin, which led to creating several substantial databases of diverse skin lesions. However, the dermoscope is not an easily accessible tool in some regions. A less expensive alternative could be acquiring medium resolution clinical macroscopic images of skin lesions. However, the limited volume of macroscopic images available, especially mobile-acquired, hinders developing a clinical mobile-based deep learning approach. In this work, we present a technique to efficiently utilize the sizable number of dermoscopic images to improve the segmentation capacity of macroscopic skin lesion images. A Cycle-Consistent Adversarial Network is used to translate the image between the two distinct domains created by the different image acquisition devices. A visual inspection was performed on several databases for qualitative evaluation of the results, based on the disappearance and appearance of intrinsic dermoscopic and macroscopic features. Moreover, the Frechet Inception Distance was used as a quantitative metric. The quantitative segmentation results are demonstrated on the available macroscopic segmentation databases, SMARTSKINS and Dermofit Image Library, yielding test set thresholded Jaccard Index of 85.13% and 74.30%. These results establish a new state-of-the-art performance in the SMARTSKINS database.

Abstract
In Europe, clean distributed generation, DG, is perceived as a crucial instrument to build the path towards carbon emission neutrality. DG already reached a large share in the generation mix of several countries and the reduction of technical losses is one of its most mentioned advantages. In this scope, this paper discusses the weaknesses of this postulation using real networks. The adopted methodology involves the power flow simulation of a collection of real networks, using 15 min real measurements of loads and generations for a whole year. The clustering of similar cases allows identifying the situations that cause higher losses. A complementary objective of this research was to define an approach to mitigate this problem in terms of identifying the branches that, if reinforced, most contribute to losses reduction. The results obtained confirm the rationality of the proposed methodology.