This paper proposes an approach and demonstrates its application for cross-border exchange of clinical documents oriented towards the use of archetype concepts and international patient summary standards adopted in the European Union. A novelty in this approach is the management of native XML instances of an archetype concept in the CEN 13606 standard by means of a native XML database and XML technologies. The computer experiments demonstrate that it is suitable for representing relatively small clinical datasets such as those describing rare diseases like the Acromegaly illness, where the semantic context in the relatively small number of symptoms is practicable to tag in terms of SNOMED-CT terminology codes. Additionally, we demonstrate that the semantically enriched information model can facilitate secondary use of clinical data by visualizing the execution of queries based on standard terminologies. Finally, the compatibility of the information model with the IPS standard enables sharing of clinical data among different information models.

Influenced by research in biomechanics engineers attempt to achieve motion flexibility of the robot arm similar to that of a human hand motion. For this purpose the design of modern robot arms most often provides redundant degrees of freedom in executing the assigned tasks in world space. Typical industrial applications of robots involve motion planning subject to constraints in joint space. In the general case additional static constraints in world space can also be mapped into admissible ranges of variation of the joint variables. This paper presents a mathematical model for redundant robot motion control in case of hard constraints on the displacements in the joints. The novelty in this model is the application of sliding mode theory based on the separation of the immutable geometrical artefacts in path planning from the changes in the actual robot motion. This allows to replace the traditionally heavy optimization procedures used with redundant robot arms by computationally efficient and intuitive vector space methods. The sliding mode of control is seamlessly embedded in a uniform kinematic path control algorithm and it is activated only when needed. Unlike existing methods, the sliding mode for motion control in case of constraints on the joint variables can execute concurrently with other forms motion control.

Robotics is an interdisciplinary field and there exist several well-known approaches to represent the dynamics model of a robot arm. The robot arm is an open kinematic chain of links connected through rotational and translational joints. In the general case, it is very difficult to obtain explicit expressions for the forces and the torques in the equations where the driving torques of the actuators produce desired motion of the gripper. The robot arm control depends significantly on the accuracy of the dynamic model. In the existing literature, the complexity of the dynamic model is reduced by linearization techniques or techniques like machine learning for the identification of unmodelled dynamics. This paper proposes a novel approach for deriving the equations of motion and the actuator torques of a robot arm with an arbitrary number of joints. The proposed approach for obtaining the dynamic model in closed form employs graph theory and the orthogonality principle, a powerful concept that serves as a generalization for the law of conservation of energy. The application of this approach is demonstrated using a 3D-printed planar robot arm with three degrees of freedom. Computer experiments for this robot are executed to validate the dynamic characteristics of the mathematical model of motion obtained by the application of the proposed approach. The results from the experiments are visualized and discussed in detail.

This paper presents new data about diabetes prevalence and illness duration from a population of patients with diabetes Type 1(43,818) and Type 2 (457,247). Unlike the usual approach that employs adjusted estimates in similar prevalence reports, this study extracts data from a large number of original clinical documents such as all the outpatient records (6,887,876) issued in Bulgaria to all the 501,065 patients with diabetics during 2018 (9.77% of all the 5,128,172 patients recorded in 2018, 4.43% male and 5.35% female). Diabetes prevalence data are described in terms of distributions of Type 1 and Type 2 diabetes over age and gender. It is mapped to an Observational Medical Outcomes Partnership Common Data Model that is publicly available. The distribution of Type 2 diabetics agrees with peak values of BMI established in related research. A major novelty in this research are the data about the diabetes illness duration. It is an essential metric for evaluating the quality of processes evolving over time. Accurate estimates are obtained for the duration measured in years of Type 1 (95% CI 10.92, 11.08) and Type 2 (95% CI 7.97, 8.02) diabetics from the Bulgarian population. The patients with diabetes Type 1 have longer diabetes duration relatively to those with Type 2. It is recommended to include this metric in official diabetes prevalence reports.