Even though clustering algorithms in Wireless Sensor Networks (WSN) are a well investigate subject, the increasing interest in the Internet of Things (IoT) and 5G technologies has precipitated the need of new ways to comprehend and overcome a new set of challenges. While studies mainly propose new algorithms and compare these algorithms based on a set of properties (e.g. energy efficiency, scalability), none of them focuses on the underlying mechanisms and organizational patterns that lead to these properties. We address this lack of understanding by applying a complex systems science approach to investigate the properties of WSNs arising from the communication patterns of the network nodes. We represent different implementations of clustering in WSNs with a functional topology graph. Moreover, we employ a complexity metric - functional complexity (CF) - to explain how local interactions give rise to the global behavior of the network. Our analysis shows that higher values of CF indicate higher scalability and lower energy efficiency.

Objective. To compare the development of permanent teeth in a group of children with the congenitally missing permanent teeth (CMPT) and corresponding nonaffected group. Methods. The formation stages of all developing permanent teeth were determined on 345 panoramic radiographs (OPTs) by the method of Haavikko (1970), and dental age was calculated. The paired samples t-test was used to compare the differences between dental age (DA) and chronological age (CA) in those with CMPT and those not affected. Spearman test was used to evaluate the correlation between DA-CA and the number of missing teeth. The Wilcoxon signed rank test was used to compare the development of the teeth adjacent to the place of the agenesis with matched pair in corresponding nonaffected group. Results. Dental age was significantly delayed in CMPT children compared to the nonaffected group (p < 0.001). The mean differences were −0.57 ± 1.20 years and −0.61 ± 1.23 years in males and females, without difference between sexes (p = 0.763). The number of missing teeth affected the delay only in females (p = 0.024). Only mesial teeth in females were significantly delayed in development when compared to the nonaffected group (p = 0.007). Conclusion. Our findings show that the development of the permanent teeth is delayed when compared to the nonaffected group of the same sex and age.

In this paper will be observed the population dynamics of a three-species Lotka-Volterra model: two predators and their prey. This simplified model yields a more complicated dynamical system than classic Lotka-Volterra model. We will give the conditions under which one of the predators becomes extinct and when the coexistence between predators is possible. Given will be sufficient conditions for the existence of solutions for certain classes of Cauchy’s solutions of Lotka-Volterra model. The behavior of integral curves in the neighborhoods of an arbitrary integral curves will be considered.

The cranes are now not replaceable mode of transport of materials and finished products both in production halls and in the open space. This paper made the whole analytical calculation of double girder bridge cranes to be used in laboratories exclusively for testing, determined by the maximum bending stress and deflection of the main girder. After calculating the dimensions, we created a model cranes in software CATIA V5. The same model was subjected to FEM analysis of the same name software. At the end of the paper comparison has been done. The objective of the calculation and analysis of the model was to develop a model crane and to serve for the next tests. Dimensions of the crane are given according to the laboratory where it will be located.

Over the last decade, the idea that robots could become an integral part of groups and teams has developed from a promising vision into a reality. Robots are increasingly designed to interact with groups and teams of people, yet most human-robot interaction research still focuses on a single humans interacting with a single robot. The goal for the workshop is therefore to advance research in computer supported cooperative work (CSCW) and human robot interaction (HRI) by raising awareness for the social and technical challenges that surround the placement of robots within work-groups and teams. The workshop will be organized around three central questions: (1) How do robots shape the dynamics of groups and teams in existing settings? (2) How does a robot's behavior shape how humans interact with each other in dyads and in larger groups and teams? (3) How can robots improve the performance of work groups and teams by acting on social processes? These core issues will be covered across a set of presentations that initiate in- depth discussions around each question to improve the quality of and support the growth of research in the CSCW community that focuses on the intersection of robots, groups, and teams.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common and best known monogenic small vessel disease. Here, we review the clinical, neuroimaging, neuropathological, genetic, and therapeutic aspects based on the most relevant articles published between 1994 and 2016 and on the personal experience of the authors, all directly involved in CADASIL research and care. We conclude with some suggestions that may help in the clinical practice and management of these patients.

Humans excel at recognizing (or inferring) another's distal intentions, and recent experiments suggest that this may be possible using only subtle kinematic cues elicited during early phases of movement. Still, the cognitive and computational mechanisms underlying the recognition of intentional (sequential) actions are incompletely known and it is unclear whether kinematic cues alone are sufficient for this task, or if it instead requires additional mechanisms (e.g., prior information) that may be more difficult to fully characterize in empirical studies. Here we present a computationally-guided analysis of the execution and recognition of intentional actions that is rooted in theories of motor control and the coarticulation of sequential actions. In our simulations, when a performer agent coarticulates two successive actions in an action sequence (e.g., “reach-to-grasp” a bottle and “grasp-to-pour”), he automatically produces kinematic cues that an observer agent can reliably use to recognize the performer's intention early on, during the execution of the first part of the sequence. This analysis lends computational-level support for the idea that kinematic cues may be sufficiently informative for early intention recognition. Furthermore, it suggests that the social benefits of coarticulation may be a byproduct of a fundamental imperative to optimize sequential actions. Finally, we discuss possible ways a performer agent may combine automatic (coarticulation) and strategic (signaling) ways to facilitate, or hinder, an observer's action recognition processes.

To evaluate the quality of sleep, it is important to determine how much time was spent in each sleep stage during the night. The gold standard in this domain is an overnight polysomnography (PSG). But the recording of the necessary electrophysiological signals is extensive and complex and the environment of the sleep laboratory, which is unfamiliar to the patient, might lead to distorted results. In this paper, a sleep stage detection algorithm is proposed that uses only the heart rate signal, derived from electrocardiogram (ECG), as a discriminator. This would make it possible for sleep analysis to be performed at home, saving a lot of effort and money. From the heart rate, using the fast Fourier transformation (FFT), three parameters were calculated in order to distinguish between the different sleep stages. ECG data along with a hypnogram scored by professionals was used from Physionet database, making it easy to compare the results. With an agreement rate of 41.3%, this approach is a good foundation for future research.