Optic flow estimation on trajectories generated by bio-inspired closed-loop flight

We generated panoramic imagery by simulating a fly-like robot carrying an imaging sensor, moving in free flight through a virtual arena bounded by walls, and containing obstructions. Flight was conducted under closed-loop control by a bio-inspired algorithm for visual guidance with feedback signals corresponding to the true optic flow that would be induced on an imager (computed by known kinematics and position of the robot relative to the environment). The robot had dynamics representative of a housefly-sized organism, although simplified to two-degree-of-freedom flight to generate uniaxial (azimuthal) optic flow on the retina in the plane of travel. Surfaces in the environment contained images of natural and man-made scenes that were captured by the moving sensor. Two bio-inspired motion detection algorithms and two computational optic flow estimation algorithms were applied to sequences of image data, and their performance as optic flow estimators was evaluated by estimating the mutual information between outputs and true optic flow in an equatorial section of the visual field. Mutual information for individual estimators at particular locations within the visual field was surprisingly low (less than 1 bit in all cases) and considerably poorer for the bio-inspired algorithms that the man-made computational algorithms. However, mutual information between weighted sums of these signals and comparable sums of the true optic flow showed significant increases for the bio-inspired algorithms, whereas such improvement did not occur for the computational algorithms. Such summation is representative of the spatial integration performed by wide-field motion-sensitive neurons in the third optic ganglia of flies.     

Bacteria classification using Cyranose 320 electronic nose

Background  

An electronic nose (e-nose), the Cyrano Sciences' Cyranose 320, comprising an array of thirty-two polymer carbon black composite sensors has been used to identify six species of bacteria responsible for eye infections when present at a range of concentrations in saline solutions. Readings were taken from the headspace of the samples by manually introducing the portable e-nose system into a sterile glass containing a fixed volume of bacteria in suspension. Gathered data were a very complex mixture of different chemical compounds.     

Customized design of electronic noses placed on top of air-lift bioreactors for in situ monitoring the off-gas patterns

A specially designed electronic nose was coupled to an air-lift bioreactor in order to perform on-line monitoring of released vapors. The sensor array was placed at the top of the bioreactor sensing the headspace in equilibrium with the evolving liquor at any time without the need of aspiration and pumping of gases into a separated sensor chamber. The device was applied to follow the off-gas of a bioreactor with Acidithiobacillus thiooxidans grown on beds of elemental sulfur under aerobic conditions. Evolution was monitored by acid titration, pH and optical density measurements. The electronic nose was capable to differentiate each day of reactor evolution since inoculation within periods marked off culture medium replacements using multivariate data analysis. Excellent discrimination was obtained indicating the potentiality for on-line monitoring in non-perturbed bioreactors. The prospects for electronic nose/bioreactor merging are valuable for whatever the bacterial strain or consortium used in terms of scent markers to monitor biochemical processes.     

Label-free detection of single nucleotide polymorphisms utilizing the differential transfer function of field-effect transistors

We present a label-free method for the detection of DNA hybridization, which is monitored by non-metallized silicon field-effect transistors (FET) in a microarray approach. The described method enables a fast and fully electronic readout of ex situ binding assays. The label-free detection utilizing the field-effect is based on the intrinsic charge of the DNA molecules and/or on changes of the solid–liquid interface impedance, when biomolecules bind to the sensor surface. With our sensor system, usually a time-resolved, dc readout is used. In general, this FET signal suffers from sensor drift, temperature drift, changes in electrolyte composition or pH value, influence of the reference electrode, etc. In this article, we present a differential ac readout concept for FET microarrays, which enables a stable operation of the sensor against many of these side-parameters, reliable readout and a possibility for a quick screening of large sensor arrays. We present the detection of point mutations in short DNA samples with this method in an ex situ binding assay.     

Mechanical properties of a bio-inspired robotic knifefish with an undulatory propulsor

South American electric knifefish are a leading model system within neurobiology. Recent efforts have focused on understanding their biomechanics and relating this to their neural processing strategies. Knifefish swim by means of an undulatory fin that runs most of the length of their body, affixed to the belly. Propelling themselves with this fin enables them to keep their body relatively straight while swimming, enabling straightforward robotic implementation with a rigid hull. In this study, we examined the basic properties of undulatory swimming through use of a robot that was similar in some key respects to the knifefish. As we varied critical fin kinematic variables such as frequency, amplitude, and wavelength of sinusoidal traveling waves, we measured the force generated by the robot when it swam against a stationary sensor, and its velocity while swimming freely within a flow tunnel system. Our results show that there is an optimal operational region in the fin's kinematic parameter space. The optimal actuation parameters found for the robotic knifefish are similar to previously observed parameters for the black ghost knifefish, Apteronotus albifrons. Finally, we used our experimental results to show how the force generated by the robotic fin can be decomposed into thrust and drag terms. Our findings are useful for future bio-inspired underwater vehicles as well as for understanding the mechanics of knifefish swimming.     

POEtic: an electronic tissue for bio-inspired cellular applications

In this paper, we introduce the general architecture of a new electronic tissue called POEtic. This reconfigurable circuit is designed to ease the implementation of bio-inspired systems that bring cellular applications into play. It contains special features that allow a developer to realize systems that require evolution (Phylogenesis), development (Ontogenesis), and/or learning (Epigenesis). A dynamic routing algorithm has been added to a structure similar to that of common commercial FPGAs, in order to allow the creation of data paths between cells. As the creation of these paths is dynamic, it is possible to add new cells or to repair faulty ones at runtime.     

Biomimetic sensing layer based on electrospun conductive polymer webs

The aim of the present study is to combine a bio-inspired nanofibrous artificial epithelium to the electronic nose (e-nose) principles. The sensing device set up was an electronic nose consisting of an array of 9 micro-chemoresistors (Cr-Au, 3×3) coated with electrospun nanofibrous structures. These were comprised of doped polyemeraldine base blended with 3 different polymers: polyethylene oxide, polyvinilpyrrolidone and polystyrene, which acted as carriers for the conducting polymer and were the major responsible of the features of each fibrous overlay (electrical parameters, selectivity and sensitivity ranges). The two sensing strategies here adopted and compared consisted in the use of 2 different textural coatings: a single- and a double-overlay, where the double-overlay resulting from overdeposition of 2 different polymer blends. Such e-nose included a plurality of nanofibres whose electrical parameters were at the same time depending on each polymer exposure to analytes (NO(2), NH(3)) and on the spatial distribution of the interlacing fibres. The morphology of the coating arrangements of this novel e-nose was investigated by scanning electron microscopy (SEM) and its sensor responses were processed by multicomponent data analyses (PCA and PLS) reporting encouraging results for detection and recognition of analytes at ppb levels.     

A multiscale investigation of mechanical properties of bio-inspired scaffolds

Abstract

Finding a structural design which allows the scaffold to have a high porosity and large pore size while retaining high strength is essential. Here, a bio-inspired scaffold is designed based on the observed geometrical pattern of the apatite atomic crystal structure, and mechanical properties are compared with other common scaffold geometries. The bio-inspired scaffold design is proven superior using a multiscale computational approach, which combines density functional theory and finite element analysis to predict the stress reaction and substitution effects on the scaffolds. This study provides insight into better scaffold design using bio-inspired structures and the effect of substitutions.     

Rapid Identification of Rice Samples Using an Electronic Nose

Four rice samples of long grain type were tested using an electronic nose (Cyranose-320).Samples of 5 g of each variety ofrice were placed individually in vials and were analyzed with the electronic nose unit consisting of 32 polymer sensors.TheCyranose-320 was able to differentiate between varieties of rice.The chemical composition of the rice odors for differentiatingrice samples needs to be investigated.The optimum parameter settings should be considered during the Cyranose-320 trainingprocess especially for multiple samples,which are helpful for obtaining an accurate training model to improve identificationcapability.Further,it is necessary to investigate the E-nose sensor selection for obtaining better classification accuracy.A re-duced number of sensors could potentially shorten the data processing time,and could be used to establish an application pro-cedure and reduce the cost for a specific electronic nose.Further research is needed for developing analytical procedures thatadapt the Cyranose-320 as a tool for testing rice quality.     

Monitoring cellular state transitions in a production-scale CHO-cell process using an electronic nose

An electronic nose is used to monitor the bioreactor off-gas composition in perfused cultivations of a CHO-cell line producing recombinant human blood coagulation factor VIII. The applicability of the electronic nose for monitoring cellular state transitions and process control is explained. It is shown that the instrument can reveal characteristic process states related to product and lactate formation, and detect microbial infections in a very early stage of the infection. The visualization of ideal process conditions is realized by using principal component analysis (PCA) and the on-line applicability of this method is outlined. The results illustrate the potential of the electronic nose as on-line sensor for ensuring product and process quality in production-scale bioprocesses.     

Olfactory cell-based biosensor: a first step towards a neurochip of bioelectronic nose

Human olfactory system can distinguish thousands of odors. In order to realize the biomimetic design of electronic nose on the principle of mammalian olfactory system, this article reports an olfactory cell-based biosensor as a real bionic technique for odorants detection. Effective cultures of olfactory receptor neurons and olfactory bulb cells have been achieved on the semiconductor chip. Using light-addressable potentiometric sensor (LAPS) as sensing chip to monitor extracellular potential of the neurons, the response under stimulations of the odorants or neurotransmitters, such as acetic acid and glutamic acid, was tested. The results demonstrate that this kind of hybrid system of LAPS and olfactory neurons, which is sensitive to odorous changes, has great potential and is promising to be used as a novel neurochip of bioelectronic nose for detecting odors.     

Recent advances in electronic and bioelectronic noses and their biomedical applications

Significant effort has been made in the development of an artificial nose system for various applications. Advances in sensor technology have facilitated the development of high-performance electronic and bioelectronic noses. Numerous articles describe the advantages of artificial nose systems for biomedical applications. Recent advances in the development of electronic and bioelectronic noses and their biomedical applications are reviewed in this article.     

A bio-inspired flying robot sheds light on insect piloting abilities

When insects are flying forward, the image of the ground sweeps backward across their ventral viewfield and forms an "optic flow," which depends on both the groundspeed and the groundheight. To explain how these animals manage to avoid the ground by using this visual motion cue, we suggest that insect navigation hinges on a visual-feedback loop we have called the optic-flow regulator, which controls the vertical lift. To test this idea, we built a micro-helicopter equipped with an optic-flow regulator and a bio-inspired optic-flow sensor. This fly-by-sight micro-robot can perform exacting tasks such as take-off, level flight, and landing. Our control scheme accounts for many hitherto unexplained findings published during the last 70 years on insects' visually guided performances; for example, it accounts for the fact that honeybees descend in a headwind, land with a constant slope, and drown when travelling over mirror-smooth water. Our control scheme explains how insects manage to fly safely without any of the instruments used onboard aircraft to measure the groundheight, groundspeed, and descent speed. An optic-flow regulator is quite simple in terms of its neural implementation and just as appropriate for insects as it would be for aircraft.     

NEURAL METHODS OF CALIBRATION OF SENSORS FOR GAS MEASUREMENTS AND AROMA IDENTIFICATION SYSTEM

The article presents the neural methods of calibration of gas sensors for use in an artificial electronic nose for gas measurements. Different neural network solutions will be presented and compared. They include the classical multilayer perceptron, neuro-fuzzy networks and support vector machines. The other aspect illustrated in the article is the introductory preprocessing of the measured sensor signals in order to attain the highest possible efficiency of the gas measuring system. The theoretical considerations will be supported by the numerical experiments concerning the application of the electronic nose. The first practical aspect is concerned with the application of the developed system for classification problems and will be illustrated in the examples of the recognition of the biocomponents in the gasoline and the recognition of smells of cosmetic cream at the aging process. The second one belongs to the estimation problem and is concerned with the determination of the concentration of the particular gas components in the mixture of gases.

PRACTICAL APPLICATIONS

The results presented in the article may find practical application for calibration of the electronic nose in gas measurements. The electronic nose is widely used for smell recognition. It may find practical application in the petroleum, cosmetics or food industry for the assessment of the quality of their products. Military application is also of great interest.     

The use of gas-sensor arrays to diagnose urinary tract infections

Sensorial analysis based on the utilisation of human senses, is one of the most important and straightforward investigation methods in food and chemical analysis. An electronic nose has been used to detect in vivo Urinary Tract Infections from 45 suspected cases that were sent for analysis in a UK Health Laboratory environment. These samples were analysed by incubation in a volatile generation test tube system for 4-5 h. The volatile production patterns were then analysed using an electronic nose system with 14 conducting polymer sensors. An intelligent model consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on learning techniques has been considered. The implementation of an Extended Normalised Radial Basis Function network with advanced features for determining its size and parameters and the concept of fusion of multiple classifiers dedicated to specific feature parameters has been also adopted in this study. The proposed scheme achieved a very high classification rate of the testing dataset, demonstrating in this way the efficiency of the proposed scheme compared with other approaches. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology.     

Use of an electronic nose system for diagnoses of urinary tract infections

The use of volatile production patterns produced by bacterial contaminants in urine samples were examined using electronic nose technology. In two experiments 25 and 45 samples from patients were analysed for specific bacterial contaminants using agar culture techniques and the major UTI bacterial species identified. These samples were also analysed by incubation in a volatile generation test tube system for 4-5 h. The volatile production patterns were then analysed using an electronic nose system with 14 conducting polymer sensors. In the first experiment analysis of the data using a neural network (NN) enabled identification of all but one of the samples correctly when compared to the culture information. Four groups could be distinguished, i.e. normal urine, Escherichia coli infected, Proteus spp. and Staphylococcus spp. In the second experiment it was again possible to use NN systems to examine the volatile production patterns and identify 18 of 19 unknown UTI cases. Only one normal patient sample was mis-identified as an E. coli infected sample. Discriminant function analysis also differentiated between normal urine samples, that infected with E. coli and with Staphylococcus spp. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology for the first time. These findings will have implications for the development of rapid systems for use in clinical practice.     

Real-time odor discrimination using a bioelectronic sensor array based on the insect electroantennogram

Current trends in artificial nose research are strongly influenced by knowledge of biological olfactory systems. Insects have evolved over millions of years to detect and maneuver toward a food source or mate, or away from predators. The insect olfactory system is able to identify volatiles on a time scale that matches their ability to maneuver. Here, biological olfactory sense organs, insect antennae, have been exploited in a hybrid-device biosensor, demonstrating the ability to identify individual strands of odor in a plume passing over the sensor on a sub-second time scale. A portable system was designed to utilize the electrophysiological responses recorded from a sensor array composed of male or female antennae from four or eight different species of insects (a multi-channel electroantennogram, EAG). A computational analysis strategy that allows discrimination between odors in real time is described in detail. Following a training period, both semi-parametric and k-nearest neighbor (k-NN) classifiers with the ability to discard ambiguous responses are applied toward the classification of up to eight odors. EAG responses to individual strands in an odor plume are classified or discarded as ambiguous with a delay (sensor response to classification report) on the order of 1 s. The dependence of classification error rate on several parameters is described. Finally, the performance of the approach is compared to that of a minimal conditional risk classifier.     

Assessment of the performance of a fed-batch cultivation from the preculture quality using an electronic nose

An electronic nose, a gas-phase multisensor system, was used to monitor precultivations of a recombinant tryptophan-producing Escherichia coli strain. The electronic nose signals showed a high correlation toward the main stages of the precultivations, namely, exponential growth, oxygen-limited growth, and glucose depletion. Principal component analysis (PCA) of the electronic nose signals was performed and shown to be useful for monitoring preculture progression. More importantly, PCA also allowed a qualitative assessment of the preculture performance during subsequent fed-batch cultivations. The electronic nose signals from the precultures showed, furthermore, a high correlation to the time of phosphate limitation and the tryptophan yield coefficient of the subsequent fed-batch cultivations, which allowed an accurate prediction of these process variables using partial least squares (PLS). The results demonstrate on data from 12 cultivations how the electronic nose can be a useful tool for the assessment of inoculum quality, thereby providing means of reducing batch-to-batch variation and increasing the productivity of bioprocesses.     

仿生纳米材料的设计与未来

自然合成了大量结构复杂、性能优越的有机、无机或有机无机杂化材料。这些材料与常规材料相比有着特殊的物理性质,从而造就了生物体各种奇异的功能。随着纳米技术的发展,研究发现许多生物体的特殊能力都与纳米技术息息相关。自然是一个先进的合成工厂,不断制造出具有各种奇异功能的生物体。而这些功能的实现,往往要依靠基本物质单元在微尺度上的有序或无序组装。对这些材料的探索和研究,为人们在微尺度上的仿生开辟了新的道路。本文针对仿生纳米材料的研究近况,展望此类材料的设计与未来发展趋势。