Design, modeling, and control of an autonomous legged-wheeled hybrid robotic vehicle with non-rigid joints

This paper presents a legged-wheeled hybrid robotic vehicle that uses a combination of rigid and non-rigid joints, allowing it to be more impact-tolerant. The robot has four legs, each one with three degrees of freedom. Each leg has two non-rigid rotational joints with completely passive components for damping and accumulation of kinetic energy, one rigid rotational joint, and a driving wheel. Each leg uses three independent DC motors—one for each joint, as well as a fourth one for driving the wheel. The four legs have the same position configuration, except for the upper hip joint. The vehicle was designed to be modular, low-cost, and its parts to be interchangeable. Beyond this, the vehicle has multiple operation modes, including a low-power mode. Across this article, the design, modeling, and control stages are presented, as well as the communication strategy. A prototype platform was built to serve as a test bed, which is described throughout the article. The mechanical design and applied hardware for each leg have been improved, and these changes are described. The mechanical and hardware structure of the complete robot is also presented, as well as the software and communication approaches. Moreover, a realistic simulation is introduced, along with the obtained results.info:eu-repo/semantics/publishedVersio

Life cycle in practice: capacity building aiming European SME’s

The application of life cycle approaches – including life cycle assessment, ecodesign and environmental labelling – is becoming an increasing reality for business, and a growing challenge in many economic sectors. Businesses are facing increasing legal and market requirements to enhance resource efficiency and reduce the environmental impact of their products & services. To significantly address this challenge, the Life Cycle in Practice (LCiP) project was conceived, aiming to promote the uptake of LC approaches particularly in SMEs. The LCiP project helps SMEs in France, Belgium, Portugal and Spain reduce the environmental impacts of their products and services across the entire Life Cycle in three sectors: Buildings & Construction, Waste Management and Energy Equipment. LCiP’s specific objectives are to foster the widespread uptake of these approaches by SMEs beyond the duration of the project, by (i) Demonstrating the environmental and business benefits of applying LC Approaches through practical application in 32 businesses; (ii) Providing physical and online resource centres to support regional application of LC approaches; (iii) Building capacity for on-going implementation of LC approaches through a network of Life Cycle Champions and (iv) (Re)designing practical tools & methods tailored to the needs of the three industrial sectors. This paper presents the project's activities and expected results, as well as the conclusions of a maturity assessment on life cycle approaches that has been performed in the three sectors and four partner regions, as a means to identify needs and gaps that LCiP should fulfil

Risk factors associated with preterm birth: identification, prediction and evaluation in the BRISA cohort

Problem: Preterm birth is the leading cause of death and can result in significant long-term loss of physical and psychological capacity among survivors.Background: An estimated 15 million babies are born preterm every year. Prediction models based on machine learning methods have reported promising results.Aims: To identify risk factors associated with preterm birth and to develop and validate a prediction model for this outcome in a Brazilian birth cohort.Methods: Cross-sectional study of all births that occurred in Ribeirão Preto-SP and of one in three births that occurred in São Luís-MA, Brazil, in 2010. Questionnaires were applied to obtain pregnancy-related data. Multivariate adaptive regression splines were used to determine the independent variables. Preterm birth, defined as birth before 37 weeks gestational age, was the dependent variable. A random forest model was developed and its performance was evaluated by ROC analysis.Findings: The preterm birth rates were 12.7% (RP) and 14.1% (SL). The prediction and validation accuracies of the RF-based model were 91.3% and 85.5% respectively. The model can be applied starting in the third month of gestation and is more effective in identifying preterm infants with GA<31 weeks and 6 days (AUC=0.98).Discussion: It was possible to build a prediction model based on easily accessible low-cost data, without the need for complementary tests, providing results similar to those of other studies.Conclusions: Previous preterm birth and prenatal care were determinants. The use of an application for individualized patient monitoring an early stage can have positive effects on the quality of life of mother and child

OptFlux: an open-source software platform for in silico metabolic engineering

<p>Abstract</p> <p>Background</p> <p>Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications.</p> <p>Results</p> <p><it>OptFlux </it>is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes.</p> <p><it>OptFlux </it>also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms.</p> <p>The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. <it>OptFlux </it>has a visualization module that allows the analysis of the model structure that is compatible with the layout information of <it>Cell Designer</it>, allowing the superimposition of simulation results with the model graph.</p> <p>Conclusions</p> <p>The <it>OptFlux </it>software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community.</p> <p>Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.</p

Characterization and Evaluation of Layered Bi2WO6 Nanosheets as a New Antibacterial Agent

Background: Pathogenic microorganisms are causing increasing cases of mortality and morbidity, along with alarming rates of ineffectiveness as a result of acquired antimicrobial resistance. Bi2WO6 showed good potential to be used as an antibacterial substance when exposed to visible light. This study demonstrates for the first time the dimension-dependent antibacterial activity of layered Bi2WO6 nanosheets. Materials and methods: The synthesized layered Bi2WO6 nanosheets were prepared by the hydrothermal method and characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), and Raman and Fourier transform infrared spectroscopy (FTIR). Antibacterial and antibiotic-modulation activities were performed in triplicate by the microdilution method associated with visible light irradiation (LEDs). Results: Bi2WO6 nanosheets were effective against all types of bacteria tested, with MIC values of 256 µg/mL against Escherichia coli standard and resistant strains, and 256 µg/mL and 32 µg/mL against Staphylococcus aureus standard and resistant strains, respectively. Two-dimensional (2D) Bi2WO6 nanosheets showed antibacterial efficiency against both strains studied without the presence of light. Conclusions: Layered Bi2WO6 nanosheets revealed dimension-dependent antibacterial activity of the Bi2WO6 system.The authors thank Conselho Nacional de Desenvolvimento Científico e Tecnológico— CNPq, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—CAPES, and Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico—FUNCAP (Proc. BP4-00172-00232.01.00/20 and Proc. PR2-0101-00006.01.00/15) for the financial support. The authors would also like to thank the educational institutions UFCA, URCA, and UNILEÃO for their support during the experiments

Pluronic® F127 Thermoresponsive Viscum album Hydrogel: Physicochemical Features and Cellular In Vitro Evaluation

Viscum album L., popularly known as mistletoe, is well known for its anti-cancer properties, and the pharmaceutical application of hydroalcoholic dry extracts is still limited due to its low solubility in aqueous media, and physicochemical instability. The Pluronic® F127 is an amphiphilic polymer, which permits the solubilization of lipophilic and hydrophilic compounds. In this investigation, physicochemical features of hydrogel containing V. album dry extract (VADE-loaded-hydrogel) were performed by: dynamic light scattering (DLS), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and transmission electron microscopy (TEM). VADE-loaded-hydrogel presented nanometer-size micelles with volume distribution ranging from 10.58 nm to 246.7 nm, and a polydispersity index of 0.441. The sample thermal analyses (TG and DSC) showed similar decomposition curves; however, the thermal events indicated an increase in thermal stability in relation to the presence of the extract. In addition to these interesting pharmaceutical features, IC50 values of 333.40 µg/mL and >1000 µg/mL were obtained when tumor (SCC-25) and non-tumor (L929) cells were incubated with VADE-loaded-hydrogel, respectively. The optical and ultrastructural cellular analysis confirmed the tumor selectivity since the following alterations were detected only in SCC-25 cells: disorganization of plasmatic membrane; an increase of cytoplasmatic vacuole size; alteration in the cristae mitochondrial shape; and generation of amorphous cellular material. These results emphasize the promising antitumoral potential of VADE-loaded-hydrogel as an herbal drug delivery system via in vitro assays

An integrated network visualization framework towards metabolic engineering applications

Background Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential. Results In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks. Conclusions The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.This work is partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within project ref. COMPETE FCOMP-01-0124-FEDER-015079 and the FCT Strategic Project PEst-OE/EQB/LA0023/2013. The work of PV is funded by PhD grant ref. SFRH/BDE/51442/2011