Acoustic flow sensor using a passive bell transducer

Sensing based on a passive transducer that is wirelessly linked to a nearby data collection node can offer an attractive solution for use in remote, inaccessible, or harsh environments. Here we report a pipe flow sensor based on this principle. A transducer mounted inside the pipe generates an acoustic signal that is picked up by an external microphone. The passive transducer comprises a cavity with a trapped ball that can oscillate in response to flow. Its collisions generate an acoustic signal correlated to the flow speed. The transducer is implemented on a 6 mm diameter probe and characterized as a water flow meter. The time - average microphone voltage output is calculated by an analogue circuit, without any further signal processing. With the microphone mounted on the probe, and for flow rates in the range 0.35 m/s to 6.5 m/s, correlation between the sensor voltage output and flow rate data from a commercial flow meter is demonstrated with a worst-case accuracy of 2%. This was achieved by simple averaging of the acoustic pulse train over a 5-second time interval. Consistent correlation with the microphone mounted on the pipe wall at distances up to 150 mm from the probe location is also reported. These results demonstrate the viability of remote acoustic flow sensing using passive structures and offer a simple and minimally invasive flow monitoring method

Epistasis not needed to explain low dN/dS

An important question in molecular evolution is whether an amino acid that occurs at a given position makes an independent contribution to fitness, or whether its effect depends on the state of other loci in the organism's genome, a phenomenon known as epistasis. In a recent letter to Nature, Breen et al. (2012) argued that epistasis must be "pervasive throughout protein evolution" because the observed ratio between the per-site rates of non-synonymous and synonymous substitutions (dN/dS) is much lower than would be expected in the absence of epistasis. However, when calculating the expected dN/dS ratio in the absence of epistasis, Breen et al. assumed that all amino acids observed in a protein alignment at any particular position have equal fitness. Here, we relax this unrealistic assumption and show that any dN/dS value can in principle be achieved at a site, without epistasis. Furthermore, for all nuclear and chloroplast genes in the Breen et al. dataset, we show that the observed dN/dS values and the observed patterns of amino acid diversity at each site are jointly consistent with a non-epistatic model of protein evolution.Comment: This manuscript is in response to "Epistasis as the primary factor in molecular evolution" by Breen et al. Nature 490, 535-538 (2012

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

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

Monotone iterative technique for semilinear elliptic systems

We develop monotone iterative technique for a system of semilinear elliptic boundary value problems when the forcing function is the sum of Caratheodory functions which are nondecreasing and nonincreasing, respectively. The splitting of the forcing function leads to four different types of coupled weak upper and lower solutions. In this paper, relative to two of these coupled upper and lower solutions, we develop monotone iterative technique. We prove that the monotone sequences converge to coupled weak minimal and maximal solutions of the nonlinear elliptic systems. One can develop results for the other two types on the same lines. We further prove that the linear iterates of the monotone iterative technique converge monotonically to the unique solution of the nonlinear BVP under suitable conditions

Towards Emotion Recognition: A Persistent Entropy Application

Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real number from each raw signal. These data are used as input of a support vector machine to classify signals into 8 different emotions (calm, happy, sad, angry, fearful, disgust and surprised)

On-chip adiabatic couplers for broadband quantum-polarization state preparation

© 2018 OSA. We present a unique wavelength-dependent polarization splitter based on asymmetric adiabatic couplers designed for integration with type-II spontaneous parametric-down-conversion sources. The system can be used for preparing different quantum polarization-path states over a broad band

Asymmetric adiabatic couplers for fully-integrated broadband quantum-polarization state preparation

© 2017 The Author(s). Spontaneous parametric down-conversion (SPDC) is a widely used method to generate entangled photons, enabling a range of applications from secure communication to tests of quantum physics. Integrating SPDC on a chip provides interferometric stability, allows to reduce a physical footprint, and opens a pathway to true scalability. However, dealing with different photon polarizations and wavelengths on a chip presents a number of challenging problems. In this work, we demonstrate an on-chip polarization beam-splitter based on z-cut titanium-diffused lithium niobate asymmetric adiabatic couplers (AAC) designed for integration with a type-II SPDC source. Our experimental measurements reveal unique polarization beam-splitting regime with the ability to tune the splitting ratios based on wavelength. In particular, we measured a splitting ratio of 17 dB over broadband regions (>60 nm) for both H-and V-polarized lights and a specific 50%/50% splitting ratio for a cross-polarized photon pair from the AAC. The results show that such a system can be used for preparing different quantum polarization-path states that are controllable by changing the phase-matching conditions in the SPDC over a broad band. Furthermore, we propose a fully integrated electro-optically tunable type-II SPDC polarization-path-entangled state preparation circuit on a single lithium niobate photonic chip

Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion

Personalised randomised controlled trial designs—a new paradigm to define optimal treatments for carbapenem-resistant infections

Antimicrobial resistance is impacting treatment decisions for, and patient outcomes from, bacterial infections worldwide, with particular threats from infections with carbapenem-resistant Enterobacteriaceae, Acinetobacter baumanii, or Pseudomonas aeruginosa. Numerous areas of clinical uncertainty surround the treatment of these highly resistant infections, yet substantial obstacles exist to the design and conduct of treatment trials for carbapenem-resistant bacterial infections. These include the lack of a widely acceptable optimised standard of care and control regimens, varying antimicrobial susceptibilities and clinical contraindications making specific intervention regimens infeasible, and diagnostic and recruitment challenges. The current single comparator trials are not designed to answer the urgent public health question, identified as a high priority by WHO, of what are the best regimens out of the available options that will significantly reduce morbidity, costs, and mortality. This scenario has an analogy in network meta-analysis, which compares multiple treatments in an evidence synthesis to rank the best of a set of available treatments. To address these obstacles, we propose extending the network meta-analysis approach to individual randomisation of patients. We refer to this approach as a Personalised RAndomised Controlled Trial (PRACTical) design that compares multiple treatments in an evidence synthesis, to identify, overall, which is the best treatment out of a set of available treatments to recommend, or how these different treatments rank against each other. In this Personal View, we summarise the design principles of personalised randomised controlled trial designs. Specifically, of a network of different potential regimens for life-threatening carbapenem-resistant infections, each patient would be randomly assigned only to regimens considered clinically reasonable for that patient at that time, incorporating antimicrobial susceptibility, toxicity profile, pharmacometric properties, availability, and physician assessment. Analysis can use both direct and indirect comparisons across the network, analogous to network meta-analysis. This new trial design will maximise the relevance of the findings to each individual patient, and enable the top-ranked regimens from any personalised randomisation list to be identified, in terms of both efficacy and safety