The Conceptual Model of Well-Being Management Based on Achieving Requisite Personal Holism

Organizations should look at humans as multilayered, not only as professional entities. In synergy, not only individually, we define humans as: (1) physical, (2) mental, (3) social, (4) spiritual, and (5) economic entities, marked by requisitely holistic patterns of relatively permanent characteristics, due to which individuals differ from each other; they differ also as specialized professionals. All these and other attributes form synergies. On this basis, the behavior of individuals who are willing to practice interdisciplinary cooperation becomes socially responsible and they have a high level of well-being.

Individuals as well as organizations seek requisite personal holism (RPH) on the one hand and psychic well-being (PWB) on the other hand. Thus, individuals implement individual techniques and organizations implement special strategies, programs, and actions in the frame of human resource management (HRM). That is how organizations in the frame of HRM, more specifically in the frame of management well-being, are developing special programs for managing PWB. These programs are based on their RPH and organizations might help employees to feel respected and valued in their work settings, without regard to their culture, religion, ethnicity, gender, age, disability, or other individual differences. The most-often applied programs of the kind include: (1) stress management programs, (2) diversity management programs, (3) wellness programs, (4) employee assistance programs, and (5) programs for personal growth.     

Automated visual inspection of imprint quality of pharmaceutical tablets

Visual appearance is an important quality factor of pharmaceutical tablets. Moreover, it plays a key role in identification of tablets, which is needed to prevent mix-ups among various types of tablets. Since identification of tablets is most frequently done by imprints, good imprint quality, a property that makes the imprint readable, is of utmost importance in preventing mix-ups among the tablets. In this paper, we propose a novel method for automated visual inspection of tablets. Besides defect detection, imprint quality inspection is also considered. Performance of the method was evaluated on three different real tablet image databases of imprinted tablets. A “gold standard” was established by manually classifying tablets into a good and a defective class. The receiver operating characteristics (ROC) analysis indicated that the proposed method yields better sensitivity and specificity than the previous defect detection method.     

Variable neighborhood search algorithm for heterogeneous traveling repairmen problem with time windows

The focus of this paper is generalized traveling repairman problem (TRP), a special case of the well known and well studied traveling salesman problem (TSP). Because of its specific objective function, that minimizes the sum of overall time all clients wait for until the end of a service, TRP has great applicability potential in client oriented practical problems. Therefore it has been known in literature as traveling deliveryman problem, minimum latency problem and cumulative capacitated vehicle routing problem. However, most studies that have treated TRP related problems have implied that only one repairman is present in the system and/or that all clients are available for service at the beginning of the planning horizon. In this paper we consider a TRP with a heterogeneous fleet of repairmen serving a set of clients whose arrival times are distributed over a planning horizon, i.e. heterogeneous TRPTW (hetTRPTW). For the hetTRPTW we present a mixed integer linear programming model, and a heuristic algorithm based on a variable neighborhood search (VNS) framework. Additionally, we propose a reduction strategy for neighborhoods in the VNS algorithm and test efficiency of implemented algorithms on four benchmark sets of problem instances. Results show that proposed algorithms could be used in real systems for solving small and moderate problem instances.     

Computing median and antimedian sets in median graphs

The median (antimedian) set of a profile π=(u ₁,…,u _k ) of vertices of a graph G is the set of vertices x that minimize (maximize) the remoteness ∑ _i d(x,u _i ). Two algorithms for median graphs G of complexity O(n idim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes.     

Automatic recognition of gait-related health problems in the elderly using machine learning

This paper proposes a system for the early automatic recognition of health problems that manifest themselves in distinctive form of gait. Purpose of the system is to prolong the autonomous living of the elderly at home. When the system identifies a health problem, it automatically notifies a physician and provides an explanation of the automatic diagnosis. The gait of the elderly user is captured using a motion-capture system, which consists of body-worn tags and wall-mounted sensors. The positions of the tags are acquired by the sensors and the resulting time series of position coordinates are analyzed with machine-learning algorithms in order to recognize a specific health problem. Novel semantic features based on medical knowledge for training a machine-learning classifier are proposed in this paper. The classifier classifies the user’s gait into: 1) normal, 2) with hemiplegia, 3) with Parkinson’s disease, 4) with pain in the back and 5) with pain in the leg. The studies of 1) the feasibility of automatic recognition and 2) the impact of tag placement and noise level on the accuracy of the recognition of health problems are presented. The experimental results of the first study (12 tags, no noise) showed that the k-nearest neighbors and neural network algorithms achieved classification accuracies of 100%. The experimental results of the second study showed that classification accuracy of over 99% is achievable using several machine-learning algorithms and 8 or more tags with up to 15 mm standard deviation of noise. The results show that the proposed approach achieves high classification accuracy and can be used as a guide for further studies in the increasingly important area of Ambient Assisted Living. Since the system uses semantic features and an artificial-intelligence approach to interpret the health state, provides a natural explanation of the hypothesis and is embedded in the domestic environment of the elderly person; it is an example of the semantic ambient media for Ambient Assisted Living.     

Thermodynamic analysis of the refining of technical boron nitride

The efficiency of the process of refining technical boron nitride was assessed based on calculations of the chemical equilibrium in the B-N-O-C-Cl-H system. Three refining mixtures, CCl₄ + H₂, CCl₄ + NH₃ and CHCl₃ + NH₃, were considered. The analysis indicates that the use of ammonia-containing mixtures is more convenient, a lower residual oxygen content, lower contamination of the product by carbon and a better overall boron balance emerging. The calculations of the equilibrium composition of the solid phase enabled suitable technological conditions of the refining process (temperature and starting composition of the gaseous phase) to be established. The calculated results are compared with experimental data, and some observed differences are discussed.     

Multifunctional Gadolinium‐Doped Mesoporous TiO2 Nanobeads: Photoluminescence,Enhanced Spin Relaxation,and Reactive Oxygen Species Photogeneration,Beneficial for Cancer Diagnosis and Treatment

Materials with controllable multifunctional abilities for optical imaging (OI) and magnetic resonant imaging (MRI) that also can be used in photodynamic therapy are very interesting for future applications. Mesoporous TiO₂ sub‐micrometer particles are doped with gadolinium to improve photoluminescence functionality and spin relaxation for MRI, with the added benefit of enhanced generation of reactive oxygen species (ROS). The Gd‐doped TiO₂ exhibits red emission at 637 nm that is beneficial for OI and significantly improves MRI relaxation times, with a beneficial decrease in spin–lattice and spin–spin relaxation times. Density functional theory calculations show that Gd³⁺ ions introduce impurity energy levels inside the bandgap of anatase TiO₂, and also create dipoles that are beneficial for charge separation and decreased electron–hole recombination in the doped lattice. The Gd‐doped TiO₂ nanobeads (NBs) show enhanced ability for ROS monitored via ^?OH radical photogeneration, in comparison with undoped TiO₂ nanobeads and TiO₂ P25, for Gd‐doping up to 10%. Cellular internalization and biocompatibility of TiO₂@x Gd NBs are tested in vitro on MG‐63 human osteosarcoma cells, showing full biocompatibility. After photoactivation of the particles, anticancer trace by means of ROS photogeneration is observed just after 3 min irradiation.