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.     

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.     

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.     

A new approach to two-machine flow shop problem with uncertain processing times

This paper deals with the problem of optimization of job sequence in a two-machine flow shop problem in the presence of uncertainty. It is assumed that the processing times of jobs on the machines are described by triangular fuzzy sets. A new optimization algorithm based on Johnson”s algorithm for deterministic processing times and on an improvement of McCahon and Lee”s algorithm is developed and presented. In order to compare fuzzy processing times, McCahon and Lee use mean values of their corresponding fuzzy sets. It is shown that this approach cannot fully explore possible relationships between fuzzy sets. In order to overcome this drawback we consider different fuzzy sets determined by λ-cuts of the fuzzy processing times. Extensive experiments show that the new algorithm gives better solutions with respect to makespan than existing McCahon and Lee's algorithm.     

A time-predefined local search approach to exam timetabling problems

In recent years the processing speed of computers has increased dramatically. This in turn has allowed search algorithms to execute more iterations in a given amount of real-time. Does this necessarily always lead to an improvement in the quality of final solutions? This paper is devoted to the investigation of that question. We present two variants of local search where the search time can be set as an input parameter. These two approaches are: a time-predefined variant of simulated annealing and an adaptation of the “great deluge” method. We present a comprehensive series of experiments which show that these approaches significantly outperform the previous best results (in terms of solution quality) on a range of benchmark exam timetabling problems. Of course, there is a price to pay for such better results: increased execution time. We discuss the impact of this trade-off between quality and execution time. In particular we discuss issues involving the proper estimation of the algorithm's execution time and the assessment of its importance.     

The economics of visual disamenity reductions of offshore wind farms—Review and suggestions from an emerging field

The offshore wind power generation market is currently experiencing large growth rates on a global scale and investments exceeding several billion euro are being made. From a welfare economic point of view there is a non-trivial economic trade-off between offshore wind generation costs and the visual impacts from offshore wind farms. Offshore wind farms close to the shore generate cheaper electricity, but also cause higher levels of visual impacts compared to locations at larger distances. In the present paper we carry out a review of the stated preference studies that have elicited the demand for visual disamenity reduction from offshore wind farms. The review has three objectives: (a) to present the results of the different surveys; (b) to explore the more technical parts of the different surveys; and (c) to present the frontiers in the assessment of the demand for visual disamenity reductions associated with offshore wind farm locations. The paper is based on the results from five different studies. The review indicates that locations of offshore wind farms which are close to the shore generate significant welfare losses and that these can be reduced by locating the wind farms at more distant locations. The results also show that the welfare economic costs vary in terms of a range of socio demographic characteristics, experience with wind turbines and recreational activities. Finally, the review suggests that the welfare impacts related to the spatial distribution of the wind farms, intergenerational effects and experience with wind turbines are potential areas that would be beneficial to explore in future studies.