Development of a Bayesian recursive algorithm to find free-spaces for an intelligent wheelchair

This paper introduces a new shared control strategy for an intelligent wheelchair using a Bayesian recursive algorithm. Using the local environment information gathered by a laser range finder sensor and commands acquired through a user interface, a Bayesian recursive algorithm has been developed to find the most appropriate free-space, which corresponds to the highest posterior probability value. Then, an autonomous navigation algorithm will assist to manoeuvre the wheelchair in the chosen free-space. Experiment results demonstrate that the new method provides excellent performance with great flexibility and fast response. © 2011 IEEE

Shared control strategies for human - Machine interface in an intelligent wheelchair

In this paper, we introduce a shared control mechanism for an intelligent wheelchair designed to support people with mobility impairments, who also have visual, upper limb, or cognitive impairment. The method is designed to allow users to be involved in the movement as much as possible, while still providing the assistance needed to achieve the goal safely. The data collected through URG-04LX and user interface are analyzed to determine whether the desired action is safe to perform. The system then decides to provide assistance or to allow the user input to control the wheelchair. The experiment results indicate that the method performs effectively with high satisfaction. © 2013 IEEE

Molecular mechanism of MBX2319 inhibition of Escherichia coli AcrB multidrug efflux pump and comparison with other inhibitors

Efflux pumps of the resistance nodulation division (RND) superfamily, such as AcrB, make a major contribution to multidrug resistance in Gram-negative bacteria. The development of inhibitors of the RND pumps would improve the efficacy of current and next-generation antibiotics. To date, however, only one inhibitor has been cocrystallized with AcrB. Thus, in silico struc- ture-based analysis is essential for elucidating the interaction between other inhibitors and the efflux pumps. In this work, we used computer docking and molecular dynamics simulations to study the interaction between AcrB and the compound MBX2319, a novel pyranopyridine efflux pump inhibitor with potent activity against RND efflux pumps of Enterobacteriaceae species, as well as other known inhibitors (D13-9001, 1-[1-naphthylmethyl]-piperazine, and phenylalanylarginine-ß-naphthyl-amide) and the binding of doxorubicin to the efflux-defective F610A variant of AcrB. We also analyzed the binding of a sub- strate, minocycline, for comparison. Our results show that MBX2319 binds very tightly to the lower part of the distal pocket in the B protomer of AcrB, strongly interacting with the phenylalanines lining the hydrophobic trap, where the hydrophobic por- tion of D13-9001 was found to bind by X-ray crystallography. Additionally, MBX2319 binds to AcrB in a manner that is similar to the way in which doxorubicin binds to the F610A variant of AcrB. In contrast, 1-(1-naphthylmethyl)-piperazine and phenylalanylarginine-ß-naphthylamide appear to bind to somewhat different areas of the distal pocket in the B protomer of AcrB than does MBX2319. However, all inhibitors (except D13-9001) appear to distort the structure of the distal pocket, impairing the proper binding of substrates

The advancement of an obstacle avoidance bayesian neural network for an intelligent wheelchair

In this paper, an advanced obstacle avoidance system is developed for an intelligent wheelchair designed to support people with mobility impairments who also have visual, upper limb, or cognitive impairment. To avoid obstacles, immediate environment information is continuously updated with range data sampled by an on-board laser range finder URG-04LX. Then, the data is transformed to find the relevant information to the navigating process before being presented to a trained obstacle avoidance neural network which is optimized under the supervision of a Bayesian framework to find its structure and weight values. The experiment results showed that this method allows the wheelchair to avoid collisions while simultaneously navigating through an unknown environment in real-time. More importantly, this new approach significantly enhances the performance of the system to pass narrow openings such as door passing. © 2013 IEEE

Adaptive fuzzy observer based hierarchical sliding mode control for uncertain 2D overhead cranes

© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. This paper proposes a new approach to robustly control a 2D under-actuated overhead crane system, where a payload is effectively transported to a destination in real time with small sway angles, given its inherent uncertainties such as actuator nonlinearities and external disturbances. The control law is proposed to be developed by the use of the robust hierarchical sliding mode control (HSMC) structure in which a second-level sliding surface is formulated by two first-level sliding surfaces drawn on both actuated and under-actuated outputs of the crane. The unknown and uncertain parameters of the proposed control scheme are then adaptively estimated by the fuzzy observer (FO), where the adaptation mechanism is derived from the Lyapunov theory. More importantly, stability of the proposed strategy is theoretically proved. Effectiveness of the proposed adaptive FO-based HSMC approach was extensively validated by implementing the algorithm in both synthetic simulations and real-life experiments, where the results obtained by our method are highly promising

Application of rumen and anaerobic sludge microbes for bio harvesting from lignocellulosic biomass

© 2019 Elsevier Ltd This study investigated the production of biogas, volatile fatty acids (VFAs), and other soluble organic from lignocellulosic biomass by two microbial communities (i.e. rumen fluid and anaerobic sludge). Four types of abundant lignocellulosic biomass (i.e. wheat straw, oaten hay, lurence hay and corn silage)found in Australia were used. The results show that rumen microbes produced four-time higher VFAs level than that of anaerobic sludge reactors, indicating the possible application of rumen microorganism for VFAs generation from lignocellulosic biomass. VFA production in the rumen fluid reactors was probably due to the presence of specific hydrolytic and acidogenic bacteria (e.g. Fibrobacter and Prevotella). VFA production corroborated from the observation of pH drop in the rumen fluid reactors indicated hydrolytic and acidogenic inhibition, suggesting the continuous extraction of VFAs from the reactor. Anaerobic sludge reactors on the other hand, produced more biogas than that of rumen fluid reactors. This observation was consistent with the abundance of methanogens in anaerobic sludge inoculum (3.98% of total microbes)compared to rumen fluid (0.11%). VFA production from lignocellulosic biomass is the building block chemical for bioplastic, biohydrogen and biofuel. The results from this study provide important foundation for the development of engineered systems to generate VFAs from lignocellulosic biomass

Portable sensor based dynamic estimation of human oxygen uptake via nonlinear multivariable modelling

Noninvasive portable sensors are becoming popular in biomedical engineering practice due to its ease of use. This paper investigates the estimation of human oxygen uptake (VO2) of treadmill exercises by using multiple portable sensors (wireless heart rate sensor and triaxial accelerometers). For this purpose, a multivariable Hammerstein model identification method is developed. Well designed PRBS type of exercises protocols are employed to decouple the identification of linear dynamics with that of nonlinearities of Hammerstein systems. The support vector machine regression is applied to model the static nonlinearities. Multivariable ARX modelling approach is used for the identification of dynamic part of the Hammerstein systems. It is observed the obtained nonlinear multivariable model can achieve better estimations compared with single input single output models. The established multivariable model has also the potential to facilitate dynamic estimation of energy expenditure for outdoor exercises, which is the next research step of this study. © 2008 IEEE

Time-course global expression profiles of Chlamydomonas reinhardtii during photo-biological H₂ production.

We used a microarray study in order to compare the time course expression profiles of two Chlamydomonas reinhardtii strains, namely the high H₂ producing mutant stm6glc4 and its parental WT strain during H₂ production induced by sulfur starvation. Major cellular reorganizations in photosynthetic apparatus, sulfur and carbon metabolism upon H₂ production were confirmed as common to both strains. More importantly, our results pointed out factors which lead to the higher H₂ production in the mutant including a higher starch accumulation in the aerobic phase and a lower competition between the H₂ase pathway and alternative electron sinks within the H₂ production phase. Key candidate genes of interest with differential expression pattern include LHCSR3, essential for efficient energy quenching (qE). The reduced LHCSR3 protein expression in mutant stm6glc4 could be closely related to the high-light sensitive phenotype. H₂ measurements carried out with the LHCSR3 knock-out mutant npq4 however clearly demonstrated that a complete loss of this protein has almost no impact on H₂ yields under moderate light conditions. The nuclear gene disrupted in the high H₂ producing mutant stm6glc4 encodes for the mitochondrial transcription termination factor (mTERF) MOC1, whose expression strongly increases during -S-induced H₂ production in WT strains. Studies under phototrophic high-light conditions demonstrated that the presence of functional MOC1 is a prerequisite for proper LHCSR3 expression. Furthermore knock-down of MOC1 in a WT strain was shown to improve the total H₂ yield significantly suggesting that this strategy could be applied to further enhance H₂ production in other strains already displaying a high H₂ production capacity. By combining our array data with previously published metabolomics data we can now explain some of the phenotypic characteristics which lead to an elevated H₂ production in stm6glc4

Dynamic Consensus: Increasing Blockchain Adaptability to Enterprise Applications

Decentralization powered by blockchain is validated for its capability to build trust like no other computational system before. The evolution of blockchain models has opened new use-cases that are becoming operational in many industry fields such as: energy, healthcare, banking, cross-border trade, aerospace, supply chain, and others. The core component of a decentralized architecture is the consensus algorithm - the set of rules that ensures an automated and fair agreement between the actors in the same network. Classic consensus algorithms are tailored to solve specific problems, but in an open ecosystem, each business case is unique and needs a certain level of customization. This paper introduces a new meta-consensus model called Dynamic Consensus, an architecture extension that allows multiple, complementary, consensus algorithms to run on the same platform. While classic consensus mechanisms are more appropriate for public or private systems (narrow set of rules), a dynamic approach would fit better for federated business consortiums (more rules and higher need for adaptability). The model is illustrated and analyzed as an ongoing experimental feature that can be added to enterprise blockchains designed to operate in cross-domain environments

On form factors in N=4 sym

In this paper we study the form factors for the half-BPS operators $\mathcal{O}^{(n)}_I$ and the $\mathcal{N}=4$ stress tensor supermultiplet current $W^{AB}$ up to the second order of perturbation theory and for the Konishi operator $\mathcal{K}$ at first order of perturbation theory in $\mathcal{N}=4$ SYM theory at weak coupling. For all the objects we observe the exponentiation of the IR divergences with two anomalous dimensions: the cusp anomalous dimension and the collinear anomalous dimension. For the IR finite parts we obtain a similar situation as for the gluon scattering amplitudes, namely, apart from the case of $W^{AB}$ and $\mathcal{K}$ the finite part has some remainder function which we calculate up to the second order. It involves the generalized Goncharov polylogarithms of several variables. All the answers are expressed through the integrals related to the dual conformal invariant ones which might be a signal of integrable structure standing behind the form factors.Comment: 35 pages, 7 figures, LATEX2