Modular Hydraulic Propulsion: A Robot that Moves by Routing Fluid Through Itself

This paper introduces the concept of Modular Hydraulic Propulsion, in which a modular robot that operates in a fluid environment moves by routing the fluid through itself. The robot’s modules represent sections of a hydraulics network. Each module can move fluid between any of its faces. The modules (network sections) can be rearranged into arbitrary topologies. We propose a decentralized motion controller, which does not require modules to communicate, compute, nor store information during run-time. We use 3-D simulations to compare the performance of this controller to that of a centralized controller with full knowledge of the task. We also detail the design and fabrication of six 2-D prototype modules, which float in a water tank. Results of systematic experiments show that the decentralized controller, despite its simplicity, reliably steers modular robots towards a light source. Modular Hydraulic Propulsion could offer new solutions to problems requiring reconfigurable systems to move precisely in 3-D, such as inspection of pipes, vascular systems or other confined spaces

A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems

Copyright @ Springer-Verlag 2008Dynamic optimization problems challenge traditional evolutionary algorithms seriously since they, once converged, cannot adapt quickly to environmental changes. This paper investigates the application of memetic algorithms, a class of hybrid evolutionary algorithms, for dynamic optimization problems. An adaptive hill climbing method is proposed as the local search technique in the framework of memetic algorithms, which combines the features of greedy crossover-based hill climbing and steepest mutation-based hill climbing. In order to address the convergence problem, two diversity maintaining methods, called adaptive dual mapping and triggered random immigrants, respectively, are also introduced into the proposed memetic algorithm for dynamic optimization problems. Based on a series of dynamic problems generated from several stationary benchmark problems, experiments are carried out to investigate the performance of the proposed memetic algorithm in comparison with some peer evolutionary algorithms. The experimental results show the efficiency of the proposed memetic algorithm in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant Nos. 70431003 and 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, and the National Support Plan of China under Grant No. 2006BAH02A09 and the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01

Improving GHB withdrawal with baclofen: study protocol for a feasibility study for a randomised controlled trial

Background: GHB (gamma-hydroxybutyrate) and its pro-drugs GBL (gamma-butyrolactone) and 1,4-butanediol (1,4-BD) are central nervous system depressants whose street names include ‘G’ and ‘liquid ecstasy’. They are used recreationally predominately for their stimulant and pro-sexual effects or for sedation to help with sleep and/or to ‘come down’ after using stimulant recreational drugs. Although overall population prevalence is low (0.1 %), in some groups such as men who have sex with men, GHB/GBL use may reach 20 %. GHB/GBL dependence may be associated with severe withdrawal with individuals presenting either acutely to emergency departments or to addiction services for support. Benzodiazepines are currently prescribed for GHB/GBL detoxification but do not prevent all complications, such as behavioural disinhibition, that may require hospitalisation or admission to a high dependency /intensive care unit. The GABAB receptor mediates most effects of GHB/GBL and the GABAB agonist, baclofen, has shown promise as an adjunct to benzodiazepines in reducing withdrawal severity when prescribed both during withdrawal and as a 2-day ‘preload’ prior to detoxification. The key aim of this feasibility study is provide information about recruitment and characteristics of the proposed outcome measure (symptom severity, complications including delirium and treatment escalation) to inform an application for a definitive randomised placebo controlled trial to determine the role of baclofen in the management of GHB/GBL withdrawal and whether starting baclofen 2 days earlier improves outcomes further. Methods/design: This is a prospective, randomised, double-blind, placebo-controlled feasibility study that will recruit participants (aged over 18 years) who are GHB/GBL- dependent and wish to undergo planned GHB/GBL detoxification or are at risk of acute withdrawal and are inpatients requiring unplanned withdrawal. We aim to recruit 88 participants: 28 unplanned inpatients and 60 planned outpatients. During detoxification we will compare baclofen 10 mg three times a day with placebo as an adjunct to the usual benzodiazepine regimen. In the planned outpatient arm, we will also compare a 2-day preload of baclofen 10 mg three times a day with placebo. Ratings of GHB/GBL withdrawal, sleep, depression, anxiety as well as GHB/GBL use will be collected. The main data analyses will be descriptive about recruitment and characterising the impact of adding baclofen to the usual benzodiazepine regimen on measures and outcomes of GHB/GBL withdrawal to provide estimates of variability and effect size. A qualitative approach will evaluate research participant and clinician acceptability and data collected to inform cost-effectiveness. Discussion: This feasibility study will inform a randomised controlled trial to establish whether adding baclofen to a benzodiazepine regimen reduces the severity and complications of GHB/GBL withdrawal

A particle swarm optimization based memetic algorithm for dynamic optimization problems

Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic algorithm is robust and adaptable in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 70431003 and Grant No. 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, the National Support Plan of China under Grant No. 2006BAH02A09 and the Ministry of Education, science, and Technology in Korea through the Second-Phase of Brain Korea 21 Project in 2009, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and the Hong Kong Polytechnic University Research Grants under Grant G-YH60

Modular fluidic propulsion robots

We propose a novel concept for modular robots, termed modular fluidic propulsion (MFP), which promises to combine effective propulsion, a large reconfiguration space, and a scalable design. MFP robots are modular fluid networks. To propel, they route fluid through themselves. In this article, both hydraulic and pneumatic implementations are considered. The robots move towards a goal by way of a decentralized controller that runs independently on each module face, uses two bits of sensory information and requires neither run-time memory, nor communication. We prove that 2-D MFP robots reach the goal when of orthogonally convex shape, or reach a morphology-dependent distance from it when of arbitrary shape. We present a 2-D hydraulic MFP prototype and show, experimentally, that it succeeds in reaching the goal in at least 90% of trials, and that 71% less energy is expended when modules can communicate. Moreover, in simulations with 3-D hydraulic MFP robots, the decentralized controller performs almost as well as a state-of-the-art and centralized controller. Given the simplicity of the hardware requirements, the MFP concept could pave the way for modular robots to be used at sub-centimeter-scale, where effective modular propulsion systems have not been demonstrated

Tissue Type-Specific Expression of the dsRNA-Binding Protein 76 and Genome-Wide Elucidation of Its Target mRNAs

Background: RNA-binding proteins accompany all steps in the life of mRNAs and provide dynamic gene regulatory functions for rapid adjustment to changing extra-or intracellular conditions. The association of RNA-binding proteins with their targets is regulated through changing subcellular distribution, post-translational modification or association with other proteins. Methodology: We demonstrate that the dsRNA binding protein 76 (DRBP76), synonymous with nuclear factor 90, displays inherently distinct tissue type-specific subcellular distribution in the normal human central nervous system and in malignant brain tumors of glial origin. Altered subcellular localization and isoform distribution in malignant glioma indicate that tumor-specific changes in DRBP76-related gene products and their regulatory functions may contribute to the formation and/or maintenance of these tumors. To identify endogenous mRNA targets of DRBP76, we performed RNA-immunoprecipitation and genome-wide microarray analyses in HEK293 cells, and identified specific classes of transcripts encoding critical functions in cellular metabolism. Significance: Our data suggest that physiologic DRBP76 expression, isoform distribution and subcellular localization are profoundly altered upon malignant transformation. Thus, the functional role of DRBP76 in co- or post-transcriptional gene regulation may contribute to the neoplastic phenotype

BioDMET: a physiologically based pharmacokinetic simulation tool for assessing proposed solutions to complex biological problems

We developed a detailed, whole-body physiologically based pharmacokinetic (PBPK) modeling tool for calculating the distribution of pharmaceutical agents in the various tissues and organs of a human or animal as a function of time. Ordinary differential equations (ODEs) represent the circulation of body fluids through organs and tissues at the macroscopic level, and the biological transport mechanisms and biotransformations within cells and their organelles at the molecular scale. Each major organ in the body is modeled as composed of one or more tissues. Tissues are made up of cells and fluid spaces. The model accounts for the circulation of arterial and venous blood as well as lymph. Since its development was fueled by the need to accurately predict the pharmacokinetic properties of imaging agents, BioDMET is more complex than most PBPK models. The anatomical details of the model are important for the imaging simulation endpoints. Model complexity has also been crucial for quickly adapting the tool to different problems without the need to generate a new model for every problem. When simpler models are preferred, the non-critical compartments can be dynamically collapsed to reduce unnecessary complexity. BioDMET has been used for imaging feasibility calculations in oncology, neurology, cardiology, and diabetes. For this purpose, the time concentration data generated by the model is inputted into a physics-based image simulator to establish imageability criteria. These are then used to define agent and physiology property ranges required for successful imaging. BioDMET has lately been adapted to aid the development of antimicrobial therapeutics. Given a range of built-in features and its inherent flexibility to customization, the model can be used to study a variety of pharmacokinetic and pharmacodynamic problems such as the effects of inter-individual differences and disease-states on drug pharmacokinetics and pharmacodynamics, dosing optimization, and inter-species scaling. While developing a tool to aid imaging agent and drug development, we aimed at accelerating the acceptance and broad use of PBPK modeling by providing a free mechanistic PBPK software that is user friendly, easy to adapt to a wide range of problems even by non-programmers, provided with ready-to-use parameterized models and benchmarking data collected from the peer-reviewed literature

Remote-controlled experiments with cloud chemistry

Developing cleaner chemical processes often involves sophisticated flow-chemistry equipment that is not available in many economically developing countries. For reactions where it is the data that are important rather than the physical product, the networking of chemists across the internet to allow remote experimentation offers a viable solution to this problem

An Efficient Vector System to Modify Cells Genetically

The transfer of foreign genes into mammalian cells has been essential for understanding the functions of genes and mechanisms of genetic diseases, for the production of coding proteins and for gene therapy applications. Currently, the identification and selection of cells that have received transferred genetic material can be accomplished by methods, including drug selection, reporter enzyme detection and GFP imaging. These methods may confer antibiotic resistance, or be disruptive, or require special equipment. In this study, we labeled genetically modified cells with a cell surface biotinylation tag by co-transfecting cells with BirA, a biotin ligase. The modified cells can be quickly isolated for downstream applications using a simple streptavidin bead method. This system can also be used to screen cells expressing two sets of genes from separate vectors