Lower critical solution temperature versus volume phase transition temperature in thermoresponsive drug delivery systems

One of the most subtle problem in the characterization of thermoresponsive polymers is the evaluation of the relationship between the lower critical solution temperature (LCST) of the linear polymer and the volume phase transition temperature (VPTT) of the corresponding hydrogel. Here, the LCST and the onset temperature of linear poly(N-isopropy- lacrylamide-co-N-hydroxymethyl acrylamide) has been determined under pseudo-physiological conditions by cloud point (CP) measurements and by microcalorimetric analysis. The LCSTs, as well as the onset temperatures, determined by the CP method, decrease with increasing the concentration of the polymer solution. On the contrary, microcalorimetric analyses give almost the same values for LCSTs and the onset temperatures regardless of polymer concentration. The VPTT of the hydrogel, determined by the blue dextran method, was found to be closely similar to the LCST of the concentrated polymer solution (10%, w/v), determined by the CP method. In fact, the hydrogel could be considered as a concentrated polymer solution whose concentration could be related to the amount of water retained by the hydrogel. Hydrogel microspheres have been also reported to release diclofenac, a drug model system, in a pulsating way at temperatures slightly below and above the VPTT

FIM-SIM: Fault Injection Module for CloudSim Based on Statistical Distributions, Journal of Telecommunications and Information Technology, 2014, nr 4

The evolution of ICT systems in the way data is accessed and used is very fast nowadays. Cloud computing is an innovative way of using and providing computing resources to businesses and individuals and it has gained a faster popularity in the last years. In this context, the user’s expectations are increasing and cloud providers are facing huge challenges. One of these challenges is fault tolerance and both researchers and companies have focused on finding and developing strong fault tolerance models. To validate these models, cloud simulation tools are used as an easy, flexible and fast solution. This paper proposes a Fault Injector Module for CloudSim tool (FIM-SIM) for helping the cloud developers to test and validate their infrastructure. FIM-SIM follows the event- driven model and inserts faults in CloudSim based on statistical distributions. The authors have tested and validated it by conducting several experiments designed to highlight the statistical distribution influence on the failures generated and to observe the CloudSim behavior in its current state and implementation

Analysis of power consumption in heterogeneous virtual machine environments

Reduction of energy consumption in Cloud computing datacenters today is a hot a research topic, as these consume large amounts of energy. Furthermore, most of the energy is used inefficiently because of the improper usage of computational resources such as CPU, storage and network. A good balance between the computing resources and performed workload is mandatory. In the context of data-intensive applications, a significant portion of energy is consumed just to keep alive virtual machines or to move data around without performing useful computation. Moreover, heterogeneity of resources increases the difficulty degree, when trying to achieve energy efficiency. Power consumption optimization requires identification of those inefficiencies in the underlying system and applications. Based on the relation between server load and energy consumption, we study the efficiency of data-intensive applications, and the penalties, in terms of power consumption, that are introduced by different degrees of heterogeneity of the virtual machines characteristics in a cluster

Analysis of power consumption in heterogeneous virtual machine environments

Reduction of energy consumption in Cloud computing datacenters today is a hot a research topic, as these consume large amounts of energy. Furthermore, most of the energy is used inefficiently because of the improper usage of computational resources such as CPU, storage and network. A good balance between the computing resources and performed workload is mandatory. In the context of data-intensive applications, a significant portion of energy is consumed just to keep alive virtual machines or to move data around without performing useful computation. Moreover, heterogeneity of resources increases the difficulty degree, when trying to achieve energy efficiency. Power consumption optimization requires identification of those inefficiencies in the underlying system and applications. Based on the relation between server load and energy consumption, we study the efficiency of data-intensive applications, and the penalties, in terms of power consumption, that are introduced by different degrees of heterogeneity of the virtual machines characteristics in a cluster

The influence of brush cutter's vibrations on human body

Abstract. In recent years there have been many cases of HAVS being reported for people who work in agriculture, horticulture, landscape gardening and forestry. The work described in this paper assesses the transmitted vibration to the human body from a hand guided power tool, means a brushcutter. As it is known the brushcutters induce a high level of vibrations on human operators. Depending by brushcutter's type, exposure time and human subjectivity, we can discuss about the vibration influence on human body. Long exposure to hand-arm vibration, whole body vibration and mechanical overloading is considered a potential cause of professional diseases