Abstract
We are going through perhaps the greatest crisis of our lives, where the pace of decision making, and the adoption of new public policies may indelibly condition individual and collective futures. Among other megatrends, Covid-19's impact on the digital world will facilitate the trend towards osmosis between real and virtual, human, machine and nature, public and private. The migration of all economic activities to digital, for safety and business survival reasons, will require adaptation and transition models to the new digital reality. The acceleration of digital transformation in hardware and software infrastructures will also lead to remodelling and innovate in all socio-economic, labour, and educational activities. The trend towards skills and qualifications will become more imperative. Higher Education Institutions can have a central role in developing the needed skills with their students, providing digital skills as well as pedagogical policies that stimulates them, specially focused on leadership, critical thinking, and creativity. This research aims to understand what the perceptions of the demand for digital workforce competencies are. It also intends to comprehend how those competencies are linked with entrepreneurship and leadership. After a literature review, data are presented and discussed, as well as conclusions and future potential research directions.

Abstract
Internet-of-Things has reshaped the way people interact with their surroundings and automatize the once manual actions. In a smart home, controlling the Internet-connected lights is as simple as speaking to a nearby conversational assistant. However, specifying interaction rules, such as making the lamp turn on at specific times or when someone enters the space is not a straightforward task. The complexity of doing such increases as the number and variety of devices increases, along with the number of household members. Thus, managing such systems becomes a problem, including finding out why something has happened. This issue lead to the birth of several low-code development solutions that allow users to define rules to their systems, at the cost of discarding the easiness and accessibility of voice interaction. In this paper we extend the previous published work on Jarvis [1], a conversational interface to manage IoT systems that attempts to address these issues by allowing users to specify time-based rules, use contextual awareness for more natural interactions, provide event management and support causality queries. A proof-of-concept is presented, detailing its architecture and natural language processing capabilities. A feasibility experiment was carried with mostly non-technical participants, providing evidence that Jarvis is intuitive enough to be used by common end-users, with participants showcasing an overall preference by conversational assistants over visual low-code solutions.

Abstract
Consuming Semantic Web data presents several challenges, from the number of datasets it is composed of, to the (very) large size of some of those datasets and the uncertain availability of querying endpoints. According to its core principles, accessing linked data can be done simply by dereferencing the IRIs of RDF resources. This is a light alternative both for clients and servers when compared to dataset dumps or SPARQL endpoints. The linked data interface does not support complex querying, but using it recursively may suffice to gather information about RDF resources, or to extract the relevant sub-graph which can then be processed and queried using other methods. We present Derzis¹, an open source semantic web crawler capable of traversing the linked data cloud starting from a set of seed resources. Derzis maintains information about the paths followed while crawling, which allows to define property path-based restrictions to the crawling frontier.

Abstract

Abstract
Thrombocytosis is a disorder with an excessive number of platelets in the blood, where total platelet counts (TPC) are crucial for diagnosis. This condition predisposes to blood vessels clotting and diseases such as stroke or heart attack. TPC is generally performed at the laboratory by flow cytometry with laser scattering or impedance detection. Due to the limited capacity of automated hematology in performing TPC quantification, a manual microscopy count is a very common quality assurance measure undertaken by clinical pathologists. Monitoring coagulation risk is key in many health conditions, and point-of-care platforms would simplify this procedure by taking platelet counts to the bedside. Spectroscopy has high potential for reagent-less point-of-care miniaturized technologies. However, platelets are difficult to detect in blood by standard spectroscopy analysis, due to their small size, low number when compared to red blood cells, and low spectral contrast to hemoglobin. In this exploratory research, we show that it is possible to perform TPC by advanced spectroscopy analysis, using a new processing methodology based on self-learning artificial intelligence. The results show that TPC can be measured by visible–near-infrared spectroscopy above the standard error limit of 61.19 × 109 cells/L (R2 = 0.7016), tested within the data range of 53 × 109 to 860 × 109 cells/L of dog blood. These results open the possibility for using spectroscopy as a diagnostic technology for the detection of high levels of platelets directly in whole blood, towards the rapid diagnosis of thrombocytosis and stroke prevention.

Abstract
Background: Several guidelines recommend that patients with chronic kidney disease treated by haemodialysis (HD) take care of their own arteriovenous fistula (AVF). The dialysis nurse plays an important role in the development of such self-care behaviours. A very small number of instruments are available to assess self-care behaviours with AVF in Turkey. Objective: Cultural adaptation and psychometric testing of the Turkish version of the scale of assessment of self-care behaviours with arteriovenous fistula in haemodialysis (ASBHD-AVF) patients. Design: Cross-sectional validation study. Participants and Measurements: This study was conducted involving 160 patients in the Bolu region in Turkey. The guidelines provided by Sousa and Rojjanasrirat were taken into account in the scale translation, adaptation and validation process. Validity was analysed through content validity and construct validity. The latter was measured through principal component analysis with varimax rotation, considering only factor loadings of 0.30 or larger. Reliability analysis was based on internal consistency measured by Cronbach's alpha. Results: A two-factor structure was extracted explaining 59.01% of the total variance. Cronbach's alpha was 0.91, 0.85 and 0.84 for the overall scale, the self-care in prevention of complications subscale and the self-care in management of signs and symptoms subscale, respectively. Conclusions: The Turkish version of the scale of ASBHD-AVF patients is a reliable and valid instrument and can therefore be used.