Abstract
Programming by demonstration allows non-experts in robot programming to train the robots in an intuitive manner. However, this learning paradigm requires multiple demonstrations of the same task, which can be time-consuming and annoying for the human tutor. To overcome this limitation, we propose a fast learning system - based on neural dynamics - that permits collaborative robots to memorize sequential information from single task demonstrations by a human-tutor. Important, the learning system allows not only to memorize long sequences of sub-goals in a task but also the time interval between them. We implement this learning system in Sawyer (a collaborative robot from Rethink Robotics) and test it in a construction task, where the robot observes several human-tutors with different preferences on the sequential order to perform the task and different behavioral time scales. After learning, memory recall (of what and when to do a sub-task) allows the robot to instruct inexperienced human workers, in a particular human-centered task scenario.

Abstract
Background The use of DNA barcoding allows unprecedented advances in biodiversity assessments and monitoring schemes of freshwater ecosystems; nevertheless, it requires the construction of comprehensive reference collections of DNA sequences that represent the existing biodiversity. Plecoptera are considered particularly good ecological indicators and one of the most endangered groups of insects, but very limited information on their DNA barcodes is available in public databases. Currently, less than 50% of the Iberian species are represented in BOLD. New information The InBIO Barcoding Initiative Database: contribution to the knowledge on DNA barcodes of Iberian Plecoptera dataset contains records of 71 specimens of Plecoptera. All specimens have been morphologically identified to species level and belong to 29 species in total. This dataset contributes to the knowledge on the DNA barcodes and distribution of Plecoptera from the Iberian Peninsula and it is one of the IBI database public releases that makes available genetic and distribution data for a series of taxa. The species represented in this dataset correspond to an addition to public databases of 17 species and 21 BINs. Fifty-eight specimens were collected in Portugal and 18 in Spain during the period of 2004 to 2018. All specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources and their DNA barcodes are publicly available in the Barcode of Life Data System (BOLD) online database. The distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).

Abstract
The literature on 'Sleeping Beauties' (SBs), papers that have been 'asleep' for a certain amount of time and that, suddenly, gain a significant amount of attention, is not very extensive, and has analyzed the phenomenon mainly in the Sciences. The present study seeks to find the SBs and their 'Princes' (first studies citing the SBs that have more citations and more co-citations with the SBs) in the field of International Business (IB). In terms of methodology we resort to a model that involves citation and co-citation analyses applied to a sample of 19419 papers on IB published in journals indexed in Web of Science bibliographic database. Four main findings can be highlighted: 1) SBs are a rare phenomenon in IB as only 8 SBs were found (0.04% of the total papers analyzed); 2) They focused issues related to the process of firm internationalization, international entrepreneurship, global strategies, and performance and risk management; 3) They were published in highly renowned journals, such as Journal of International Business Studies; Journal of Management Studies or Strategic Management Journal; and 4) They slept between 5 and 18 years and were awaked by 22 princes. Differently from what has been stressed in the literature about SBs, most SBs in IB presented more than one 'awakening time' and were composed by 'clusters' of princes instead of a single prince. The study of SBs is a useful and instructive model in studying the mechanisms of scientific information flow through citations. It highlights that the excessive reliance on articles' current citations might prevent the uncovering of studies that are ahead of their time.

Abstract
INTRODUCTION The COVID-19 pandemic is an ongoing event disrupting lives, health systems, and economies worldwide. Clear data about the pandemic's impact is lacking, namely regarding mortality. This work aims to study the impact of COVID-19 through the analysis of all-cause mortality data made available by different European countries, and to critique their mortality surveillance data. METHODS European countries that had publicly available data about the number of deaths per day/week were selected (England and Wales, France, Italy, Netherlands and Portugal). Two different methods were selected to estimate the excess mortality due to COVID19: (DEV) deviation from the expected value from homologue periods, and (RSTS) remainder after seasonal time series decomposition. We estimate total, age- and gender-specific excess mortality. Furthermore, we compare different policy responses to COVID-19. RESULTS Excess mortality was found in all 5 countries, ranging from 10.6% in Portugal (DEV) to 98.5% in Italy (DEV). Furthermore, excess mortality is higher than COVID-attributed deaths in all 5 countries. DISCUSSION The impact of COVID-19 on mortality appears to be larger than officially attributed deaths, in varying degrees in different countries. Comparisons between countries would be useful, but large disparities in mortality surveillance data could not be overcome. Unreliable data, and even a lack of cause-specific mortality data undermine the understanding of the impact of policy choices on both direct and indirect deaths during COVID-19. European countries should invest more on mortality surveillance systems to improve the publicly available data.

Abstract
Modern industry is shifting towards flexible, advanced robotic systems to meet the increasing demand for custom-made products with low manufacturing costs and to promote a collaborative environment for humans and robots. As a consequence of this industrial revolution, some traditional, mechanical- and hardware-based safety mechanisms are discarded in favour of a safer, more dependable robot software. This work presents a case study of assessing and improving the internal quality of a European research mobile manipulator, operating in a real industrial environment, using modern static analysis tools geared for robotic software. Following an iterative approach, we managed to fix about 90% of the reported issues, resulting in code that is easier to use and maintain.

Abstract
The purpose of this chapter is to identify and analyze the main organizational and technological factors that play a relevant role in a transformational strategic change inherent in changing the business model supported on the internet. An analysis was made of the different business models, as well as their connection to strategic management and how this is accomplished in the organizational and technological plan. This empirical study, based on the qualitative methodology, focuses on a single case study on a Portuguese company that recently changed its business model. The findings allowed the authors to assess the advantages and challenges posed by the transformation of an initial business based on a website that performs a comparison of prices for an integrated model based on a marketplace, in which customers can make their purchases and access all products, from different stores, in one place.