Novel strategy for encapsulation and targeted delivery of poorly water-soluble active substances

Carriers for targeted delivery and controlled release of poorly water-soluble active substances (PWSAS) are facing three challenges: (a) the encapsulation issues, (b) limitations of PWSAS water solubility, and (c) burst drug release which can be pharmacologically dangerous and economically inefficient. The present study brings a novel strategy for encapsulation and controlled release of PWSAS—caffeine in concentrations which are higher than its maximal water solubility without the possibility of burst effect. The modification of hydrophilic carrier based on poly(methacylic acid) was done using casein and liposomes. To further increase the maximal caffeine loading inside the carrier nicotinamide was used. The release study of the encapsulated PWSAS was elaborated with respect to morphology of the carriers and interactions that could be established between its structural components. The carriers swelling and the release of caffeine and nicotinamide were also investigated depending on caffeine concentration, the presence of different liposomal formulations and the volume ratio of liposomal formulation, in three media with different pH simulating the path of the carrier through the human gastrointestinal tract. The synthesized carriers are promising candidates for encapsulation of PWSAS in concentrations which are higher than its maximal water solubility and for the targeted delivery of those dosages.     

A multi-agent architecture for dynamic scheduling of steel hot rolling

Steel production is a complex process and finding coherent and effective schedules for the wide variety of production steps, in a dynamic environment, is a challenging task. In this paper, we propose a multi-agent architecture for integrated dynamic scheduling of the hot strip mill (HSM) and the continuous caster. The scheduling systems of these processes have very different objectives and constraints, and operate in an environment where there is a substantial quantity of real-time information concerning production failures and customer requests. Each process is assigned to an agent which independently, seeks an optimal dynamic schedule at a local level taking into account local objectives, real-time information and information received from other agents. Each agent can react to real-time events in order to fix any problems that occur. We focus here, particularly, on the HSM agent which uses a tabu search heuristic to create good predictive–reactive schedules quickly. The other agents simulate the production of the coil orders and the real-time events, which occur during the scheduling process. When real-time events occur on the HSM, the HSM agent might decide whether to repair the current schedule or reschedule from scratch. To address this problem, a range of schedule repair and complete rescheduling strategies are investigated and their performance is assessed with respect to measures of utility, stability and robustness, using an experimental simulation framework.     

The Spring kernel: a new paradigm for real-time systems

A real-time operating system kernel, called the Spring kernel, that provides some of the basic support required for large, complex, next-generation real-time systems, especially in meeting timing constraints, is presented. The approach meets the need to build predictable yet flexible real-time systems. Most current real-time operating systems contain the same basic paradigms found in time-sharing operating systems and often use a basic priority-scheduling mechanism that provides no direct support for meeting timing constraints. Spring uses two criteria to classify tasks' interaction with and effects on the environment: importance and timing requirements. Implementation experience with Spring is described     

Altered mRNA and Protein Expression of Monocarboxylate Transporter MCT1 in the Cerebral Cortex and Cerebellum of Prion Protein Knockout Mice

The effect of a cellular prion protein (PrP^c) deficiency on neuroenergetics was primarily analyzed via surveying the expression of genes specifically involved in lactate/pyruvate metabolism, such as monocarboxylate transporters (MCT1, MCT2, MCT4). The aim of the present study was to elucidate a potential involvement of PrP^c in the regulation of energy metabolism in different brain regions. By using quantitative real-time polymerase chain reaction (qRT-PCR), we observed a marked reduction in MCT1 mRNA expression in the cortex of symptomatic Zürich I Prnp^−/− mice, as compared to their wild-type (WT) counterparts. MCT1 downregulation in the cortex was accompanied with significantly decreased expression of the MCT1 functional interplayer, the Na⁺/K⁺ ATPase α2 subunit. Conversely, the MCT1 mRNA level was significantly raised in the cerebellum of Prnp^−/− vs. WT control group, without a substantial change in the Na⁺/K⁺ ATPase α2 subunit expression. To validate the observed mRNA findings, we confirmed the observed change in MCT1 mRNA expression level in the cortex at the protein level. MCT4, highly expressed in tissues that rely on glycolysis as an energy source, exhibited a significant reduction in the hippocampus of Prnp^−/− vs. WT mice. The present study demonstrates that a lack of PrP^c leads to altered MCT1 and MCT4 mRNA/protein expression in different brain regions of Prnp^−/− vs. WT mice. Our findings provide evidence that PrP^c might affect the monocarboxylate intercellular transport, which needs to be confirmed in further studies.     

Environmental Hazard Analysis - a Variant of Preliminary Hazard Analysis for Autonomous Mobile Robots

Robot manufacturers will be required to demonstrate objectively that all reasonably foreseeable hazards have been identified in any robotic product design that is to be marketed commercially. This is problematic for autonomous mobile robots because conventional methods, which have been developed for automatic systems do not assist safety analysts in identifying non-mission interactions with environmental features that are not directly associated with the robot’s design mission, and which may comprise the majority of the required tasks of autonomous robots. In this paper we develop a new variant of preliminary hazard analysis that is explicitly aimed at identifying non-mission interactions by means of new sets of guidewords not normally found in existing variants. We develop the required features of the method and describe its application to several small trials conducted at Bristol Robotics Laboratory in the 2011–2012 period.     

Experiences with Ozone Treatment Of Drinking Water in Yugoslavia

Ozone currently is being used in several drinking water treatment plants in Yugoslavia. The new Belgrade water treatment plant “Makis” is the largest one with 42 kg/h of installed ozone generating capacity and has been in operation since 1987. This paper describes the main features of ozone application in drinking water treatment. The experimental results of “Makis” pilot-plant investigations and a few examples of ozone application in Yugoslavia are presented.     

Scalable Video Multicast Using Expanding Window Fountain Codes

Fountain codes were introduced as an efficient and universal forward error correction (FEC) solution for data multicast over lossy packet networks. They have recently been proposed for large scale multimedia content delivery in practical multimedia distribution systems. However, standard fountain codes, such as LT or Raptor codes, are not designed to meet unequal error protection (UEP) requirements typical in real-time scalable video multicast applications. In this paper, we propose recently introduced UEP expanding window fountain (EWF) codes as a flexible and efficient solution for real-time scalable video multicast. We demonstrate that the design flexibility and UEP performance make EWF codes ideally suited for this scenario, i.e., EWF codes offer a number of design parameters to be ldquotunedrdquo at the server side to meet the different reception criteria of heterogeneous receivers. The performance analysis using both analytical results and simulation experiments of H.264 scalable video coding (SVC) multicast to heterogeneous receiver classes confirms the flexibility and efficiency of the proposed EWF-based FEC solution.     

Uncertainty explicit assessment of off-the-shelf software: A Bayesian approach

Assessment of software COTS components is an essential part of component-based software development. Poorly chosen components may lead to solutions of low quality and that are difficult to maintain. The assessment may be based on incomplete knowledge about the COTS component itself and other aspects (e.g. vendor’s credentials, etc.), which may affect the decision of selecting COTS component(s). We argue in favor of assessment methods in which uncertainty is explicitly represented (‘uncertainty explicit’ methods) using probability distributions. We provide details of a Bayesian model, which can be used to capture the uncertainties in the simultaneous assessment of two attributes, thus, also capturing the dependencies that might exist between them. We also provide empirical data from the use of this method for the assessment of off-the-shelf database servers which illustrate the advantages of ‘uncertainty explicit’ methods over conventional methods of COTS component assessment which assume that at the end of the assessment the values of the attributes become known with certainty.     

Validation of plant part measurements using a 3D reconstruction method suitable for high-throughput seedling phenotyping

In plant phenotyping, there is a demand for high-throughput, non-destructive systems that can accurately analyse various plant traits by measuring features such as plant volume, leaf area, and stem length. Existing vision-based systems either focus on speed using 2D imaging, which is consequently inaccurate, or on accuracy using time-consuming 3D methods. In this paper, we present a computer-vision system for seedling phenotyping that combines best of both approaches by utilizing a fast three-dimensional (3D) reconstruction method. We developed image processing methods for the identification and segmentation of plant organs (stem and leaf) from the 3D plant model. Various measurements of plant features such as plant volume, leaf area, and stem length are estimated based on these plant segments. We evaluate the accuracy of our system by comparing the measurements of our methods with ground truth measurements obtained destructively by hand. The results indicate that the proposed system is very promising.     

Genetic algorithms for match-up rescheduling of the flexible manufacturing systems

Scheduling plays a vital role in ensuring the effectiveness of the production control of a flexible manufacturing system (FMS). The scheduling problem in FMS is considered to be dynamic in its nature as new orders may arrive every day. The new orders need to be integrated with the existing production schedule immediately without disturbing the performance and the stability of existing schedule. Most FMS scheduling methods reported in the literature address the static FMS scheduling problems. In this paper, rescheduling methods based on genetic algorithms are described to address arrivals of new orders. This study proposes genetic algorithms for match-up rescheduling with non-reshuffle and reshuffle strategies which accommodate new orders by manipulating the available idle times on machines and by resequencing operations, respectively. The basic idea of the match-up approach is to modify only a part of the initial schedule and to develop genetic algorithms (GAs) to generate a solution within the rescheduling horizon in such a way that both the stability and performance of the shop floor are kept. The proposed non-reshuffle and reshuffle strategies have been evaluated and the results have been compared with the total-rescheduling method.