Abstract

Abstract
Today, cloud platforms for Internet of Everything (IoE) are facilitating organizational and industrial growth, and have different requirements based on their different purposes. Usual task scheduling algorithms for distributed environments such as group of clusters, networks, and clouds, focus only on the shortest execution time, regardless of the power consumption. Network energy can be optimized if tasks are properly scheduled to be implemented in virtual machines, thus achieving green computing. In this research, Dynamic Voltage Frequency Dcaling (DVFS) is used in two different ways, to select a suitable candidate for scheduling the tasks with the help of an Artificial Intelligence (AI) approach. First, the GIoTDVFS_SFB method based on sorting processor elements in Cloud has been considered to handle Task Scheduling problem in the Clouds system. Alternatively, the GIoTDVFS_mGA microgenetic method has been used to select suitable candidates. The proposed mGA and SFB methods are compared with SLAbased suggested for Cloud environments, and it is shown that the Makespan and Gain in benchmarks 512 and 1024 are optimized in the proposed method. In addition, the Energy Consumption (EC) of Real PM (RPMs) against the numeral of Tasks has been considered with that of PAFogIoTDVFS and EnergyAwareDVFS methods in this area. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Abstract
Nowadays, public health and sustainable development go hand in hand towards the renovated percep-tion of the former. Indeed, "ensuring healthy lives and promoting the well-being for all at all ages", which established one of the United Nations (UN) Sustainable Development Goals (SDGs), seeks to ensure that this conception is not only reinforced, but also that saving lives takes into account the physical, mental, and social well-being of populations whose "development meets the needs of the present without com-promising the ability of future generations to meet their own needs". Accordingly, it is useful to interpret and convey information pertaining to this multidimensional concept in a way that encapsulates all its facets. Since this can be achieved through a composite indicator (CI), we propose a sustainable public health index framework, based on the 13 targets of the UN's SDG 3 between 2016 and 2020. For this rea-son, using the popular CI-generating 'Benefit-of-the-Doubt' approach while considering desirable and undesirable indicators, we apply this framework to 181 World Health Organization Member States. We show that, from 2016 to 2020, less than 28% of them remained efficient and the European Region clearly dominated the remaining regions, which tended to decrease their performance, on average. Finally, we also reveal the global efforts towards improving the Proportion of births attended by skilled health personnel and the Density of medical doctors per 10,000 population, and the failure in achieving an acceptable Neonatal mortality rate, Under-five mortality rate, and a Number of people requiring interven-tions against neglected tropical diseases.

Abstract

COVID-19 affects people and companies. They are experiencing dramatic changes in work processes, communication processes, and customer management. This whole new paradigm has brought new challenges to organizations, particularly to small and medium enterprises, which have limited budgets and resources to ensure their technological infrastructure. This study aims to explore how these companies have adapted to the challenges posed by COVID-19 in their compliance practices with general data protection regulation (GDPR), auditing, and forensic security analysis. Furthermore, this study analyzes the risks that have been amplified in this period and identifies new vulnerabilities that have arisen from increased dependence on information technology in a period when most organizations have their employees in teleworking.

Abstract
The sensing performance of two types of electromagnetic surface waves are compared, a Surface Plasmon Polariton, where a gold thin film is used, being a standard material in biosensing applications; and a Bloch Surface Wave, using a photonic crystal made of a stack of silica and titanium dioxide layers. It is verified that the sensing performance (as measured by the Figure of Merit) of the gold film is higher, even though the Bloch Surface Waves can serve specific applications due to its narrow bandwidth. At the same time, it is concluded that further research must be made in order to choose the right set of parameters that maximize the Bloch Surface Wave performance.

Abstract
Objective: Supervised exercise therapy is recommended as first line in the management of intermittent claudication. Its use is often limited by accessibility, compliance and cost. Home-based exercise therapy (HBET) programs emerged as an alternative solution, but have shown inferior results. The use of structured monitoring with the use of external wearable activity monitors (WAM) has been shown to improve outcomes. Mobile applications (apps) can make use of built-in accelerometers of modern smartphones and become an alternative solution for monitoring patients during HBET, potentially providing wider accessibility. This review aims to assess current use of smartphone technology (ie, mobile apps) for monitoring or tracking patients' activity in exercise therapy for peripheral arterial disease (PAD). Methods: The PubMed database was searched from January 2011 to September 2021. Eligible articles had to include a population of patients with PAD, conduct a mobile-health exercise intervention and use smartphone technology for monitoring or tracking patients' activity. Randomized controlled trials, prospective studies, and study protocols were included. Results: A total of seven artic les met the selection criteria. These articles described six different studies and five different mobile apps. Three were fitness apps (FitBit, Nike+ FuelBand, and Garmin Connect) that synchronized with commercially available WAMs to provide users with feedback. Two were PAD-specific apps (TrackPAD and Movn) developed specifically to assess patients' activity during exercise therapy. PAD-specific apps also incorporated coaching and educational elements such as weekly goal setting, claudication reminders, messaging, gamification, training advice, and PAD education. Conclusions: Current HBET programs use smartphone apps mainly via commercially available fitness apps that synchronize with WAM devices to register and access data. PAD-specific apps are scarce, but show promising features that can be used to monitor, train, coach, and educate patients during HBET programs. Larger studies combining these elements into HBET programs should provide future direction.