Analysis of medications change in Parkinson’s disease progression data

Parkinson’s disease is a neurodegenerative disorder that affects people worldwide. Careful management of patient’s condition is crucial to ensure the patient’s independence and quality of life. This is achieved by personalized treatment based on individual patient’s symptoms and medical history. The aim of this study is to determine patient groups with similar disease progression patterns coupled with patterns of medications change that lead to the improvement or decline of patients’ quality of life symptoms. To this end, this paper proposes a new methodology for clustering of short time series of patients’ symptoms and prescribed medications data, and time sequence data analysis using skip-grams to monitor disease progression. The results demonstrate that motor and autonomic symptoms are the most informative for evaluating the quality of life of Parkinson’s disease patients. We show that Parkinson’s disease patients can be divided into clusters ordered in accordance with the severity of their symptoms. By following the evolution of symptoms for each patient separately, we were able to determine patterns of medications change which can lead to the improvement or worsening of the patients’ quality of life.     

Calibration and validation of a solar thermal system model in Modelica

Recent advancements in the domain of modeling physical processes offer opportunities to use equation based modeling environments, such as Modelica, for the simulation of building heating, ventilation, and air-conditioning (HVAC) systems. The current work demonstrates Modelica capabilities in a case study of real building solar thermal system simulation. The simulated system is part of an innovative ENERGYbase building, designed according to the so called Passivhaus standard. Model calibration and validation procedure is developed to include optimization based parametric adjustments of component models using the monitoring data during a single week. The calibrated system adequately reproduces half a year of real system operation. Future work will concentrate on application of the developed calibration and validation methodology in the whole year overall building energy simulation.     

Requirements for a virtual environment to support the social participation education of low-literates

People of low literacy experience difficulties while participating in society. Learning support software could help alleviate these difficulties. However, there is currently no overview of theoretically and empirically sound requirements for this kind of support. This paper uses the situated cognitive engineering method to create a requirements baseline for a virtual environment to support the societal participation education of low-literates (VESSEL), based on an analysis of the domain, human factors, and current applications. Four major outcomes are presented. First, a comprehensive overview is collected of the operational demands and human factors knowledge relevant to societal participation learning for low-literate citizens. Second, this overview is translated into a list of eight functional requirements: focused on low-literate learners, set in the context of societal participation, and supported by claims of cognitive, affective, and social benefits to learning. Third, a sample of Dutch societal participation learning support programs is assessed using these requirements, to highlight both current technology best practices and discrepancies between theory and practice. Fourth, virtual learning environment technology is suggested as an ‘enabling’ technology; an overview is shown of how virtual environments, actors, and objects can beneficially enable meeting the requirements baseline. Finally, directions for future study are discussed.

     

A data hiding technique for digital videos using entropy-based blocks selection

Microsystem Technologies - The technique of hiding knowledge in certain details is steganography. One of the main trends of computer infrastructure and connectivity following the advent of the...     

Effects of Various Energy Suppliers in Green Processes for Obtaining Silver Nanoparticles

The productions of stable suspensions of silver nanoparticles using a microwave reactor, an ultraviolet (UV) reactor, a low‐frequency low‐temperature plasma reactor, a high‐pressure reactor, and an open reactor are compared. All reactors served as sources of energy for stimulating the nanoparticle growth process. The silver nanoparticles were obtained based on the chemical reduction method. The processes were conducted using gallic acid as the reducing‐stabilizing substance. The influence of the variable parameters time (for all types of reactors), temperature (for the open and high‐pressure reactors), power (for the microwave reactor), energy density (for the UV reactor), and voltage (for the low‐frequency low‐temperature plasma reactor) was investigated. Temperature was found to be the most important factor influencing all processes.     

Does carbon nanopowder threaten amphibian development?

Lethal and teratogenic potentials of carbon nanoparticles (CNPs) in their amorphous form were investigated by the standardized Frog Embryo Teratogenesis Assay-Xenopus (FETAX), a 96-h in vitro whole-embryo toxicity test based on the amphibian Xenopus laevis. Embryos were acutely exposed to 1, 10, 100 and 500 mg/L CNP suspensions and evaluated for lethality, malformations and growth inhibition. Larvae were processed for histological and ultrastructural analyses to detect the main affected organs, to look for specific lesions at the subcellular level and to image and track CNPs into tissues. Only the highest CNP suspension resulted in being embryolethal for X. laevis larvae, while malformed larva percentages significantly differed from controls starting from 100 mg/L. The stomach and gut were the preferential CNP accumulation sites, on the contrary, the digestive epithelium remained intact. The analyses showed the presence of isolated nanoparticles and/or aggregates in different secondary target organs. CNPs were found in circulating erythrocytes. The research confirms the good tolerance of X. laevis towards pure elemental carbon in its nanoparticulate amorphous form, but highlights the possibility of CNP transfer toward all body areas.     

Part family identification using a simple genetic algorithm

Past research in part family identification has focused mainly on the development of efficient procedures for manufacturing-oriented part family formation in which similarities among parts are established primarily on machine or operation requirements. While these part families are essential in cellular manufacturing, they are not well suited for other areas of production, in particular, part design and process planning. A new part family identification technique using a simple genetic algorithm is proposed in this paper to first determine a set of part family differentiating attributes, and second to use these attributes to guide the formation of part families. The technique is implemented in C using a SUN SPARC workstation 1+. Empirical analyses of the technique on both artificially generated data and a real application are performed and discussed.