Simulation of adaptive modification of the vestibulo-ocular reflex with an adaptive filter model of the cerebellum

An adaptive linear filter model of the cerebellum (Fujita, 1982), which functions as a phase lead or lag compensator with learning capability, is applied to a problem of the cerebellar control of the vestibuloocular reflex (VOR). Under the assumption that the cerebellar flocculus accounts for adaptive modification of dynamic characteristics of the VOR, the cerebellar model was incorporated into a linear control model of the oculomotor system. The results of a simulation study are in good agreement with experimental data on eye movement.     

Fault detection filter design for an anaerobic digestion process

In this paper, a Fault Detection and Isolation observer based method has been applied to biological wastewater treatment process. The method is designed with a dynamic model and the observer is determined using the eigenstructure assignment approach. The efficiency of the method is demonstrated for both detection and isolation of an actuator and a sensor failure using experimental data from a pilot scale anaerobic digestion process for the treatment of an industrial wine distillery vinasses.     

An adaptive management approach to an octocoral fishery based on the Beverton-Holt model

Coral reef species are frequently the focus of bio-prospecting, and when promising bioactive compounds are identified there is often a need for the development of responsible harvesting based on relatively limited data. The Caribbean gorgonian Pseudopterogorgia elisabethae has been harvested in the Bahamas for over a decade. Data on population age structure and growth rates in conjunction with harvest data provide an opportunity to compare fishery practices and outcomes to those suggested by a Beverton-Holt fishery model. The model suggests a minimum colony size limit of 7–9 years of age (21–28 cm height), which would allow each colony 2–4 years of reproduction prior to harvesting. The Beverton-Holt model assumes that colonies at or above the minimum size limit are completely removed. In the P. elisabethae fishery, colonies are partially clipped and can be repeatedly harvested. Linear growth of surviving colonies was up to 3 times that predicted for colonies that were not harvested and biomass increase was up to 9 times greater than that predicted for undisturbed colonies. The survival of harvested colonies and compensatory growth increases yield, and yields at sites that had previously been harvested were generally greater than predicted by the Beverton-Holt model. The model also assumes recruitment is independent of fishing intensity, but lower numbers of young colonies in the fished populations, compared to unfished populations, suggest possible negative effects of the harvest on reproduction. This suggests the need for longer intervals between harvests. Because it can be developed from data that can be collected at a single time, the Beverton-Holt model provides a rational starting point for regulating new fisheries where long-term characterizations of population dynamics are rarely available. However, an adaptive approach to the fishery requires the incorporation of reproductive data.     

A novel fluorescent aptasensor for the detection of theophylline based on cryonase-driven signal amplification strategy

In the study, we have developed an expedient and efficient method for the detection of theophylline based on the amplification of the signal intensity of fluorescence based on oxidized single-walled carbon nanohorns (oxSWCNHs)/cryonase. When theophylline was not present in the system, oxSWCNHs can adequately adsorb nucleic acid probes labeled by carboxyfluorescein (FAM). In the presence of theophylline, the nucleic acid probe forms the tertiary probe–theophylline complex, which detaches from the surface of the oxSWCNHs. Then, upon reaction with cryonase, the complex can release the FAM and theophylline into the next cycle. The fluorescence signal of the system exhibits a 1:N magnification, enabling quantitative detection of theophylline. The linear range was 30–150 ng/mL, and the limit of detection (LOD) was 6.04 ng/mL. At the same time, it can also be used to detect theophylline in mouse serum.     

Demodulation methods for an adaptive neural encoder model

An adaptive version of the integrate and fire-at-threshold model for the neural coding process is presented. The encoder transforms stimulus intensity information into sequences of identical membrane depolarization spikes, their times of occurrence defining a modulated point process. Several theoretical decoding schemes are then introduced and their performance analyzed. These implement simple, recursive parameter estimation algorithms and their output reproduces reliably; the encoded time-varying stimulus level.     

A chronocoulometric aptasensor based on gold nanoparticles as a signal amplification strategy for detection of thrombin

A sensitive chronocoulometric aptasensor for the detection of thrombin has been developed based on gold nanoparticle amplification. The functional gold nanoparticles, loaded with link DNA (LDNA) and report DNA (RDNA), were immobilized on an electrode by thrombin aptamers performing as a recognition element and capture probe. LDNA was complementary to the thrombin aptamers and RDNA was noncomplementary, but could combine with [Ru(NH₃)₆]³⁺ (RuHex) cations. Electrochemical signals obtained by RuHex that bound quantitatively to the negatively charged phosphate backbone of DNA via electrostatic interactions were measured by chronocoulometry. In the presence of thrombin, the combination of thrombin and thrombin aptamers and the release of the functional gold nanoparticles could induce a significant decrease in chronocoulometric signal. The incorporation of gold nanoparticles in the chronocoulometric aptasensor significantly enhanced the sensitivity. The performance of the aptasensor was further increased by the optimization of the surface density of aptamers. Under optimum conditions, the chronocoulometric aptasensor exhibited a wide linear response range of 0.1–18.5 nM with a detection limit of 30 pM. The results demonstrated that this nanoparticle-based amplification strategy offers a simple and effective approach to detect thrombin.     

A novel microfluidic biosensor based on an electrical detection system for alpha-fetoprotein

Conventional immunoassays are labor intensive, expensive and time consuming and require large pieces of equipment for detection. Therefore, we have developed and characterized a novel immunoassay methodology comprised of microbeads and microbiochips. In this method, microbeads are used to filter and immobilize antibodies and an immuno-gold silver staining (IGSS) method is then used to amplify electrical signals that correspond to the bound antibodies. The chip used for this system is composed of an inexpensive and biocompatible polydimethylsiloxane (PDMS) layer over a Pyrex glass substrate that contains a platinum (Pt) microelectrode, which is used to detect the electrical signal in this system, the microelectrode is fabricated on the substrate and a microchannel and pillar-type microfilter is formed in the PDMS layer. A sandwich immunoassay approach was applied to detect alpha-fetoprotein (AFP), a cancer biomarker, using this system. The results of this study showed that the time required for a complete assay was reduced by 1h and a detection limit as low as 1 ng/mL was attained when this system used, which indicates that similar bead-based electrical detection systems could be used for the diagnosis of many forms of cancer.     

A visual model for object detection based on active contours and level-set method

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure–ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.This work was partially supported by Grants-in-Aid for Scientific Research (#14780254) from Japan Society of Promotion of Science.     

A wavelet-based adaptive filter for removing ECG interference in EMGdi signals

Diaphragmatic electromyogram (EMGdi) signals convey important information on respiratory diseases. In this paper, an adaptive filter for removing the electrocardiographic (ECG) interference in EMGdi signals based on wavelet theory is proposed. Power spectrum analysis was performed to evaluate the proposed method. Simulation results show that the power spectral density (PSD) of the extracted EMGdi signal from an ECG corrupted signal is within 1.92% average error relative to the original EMGdi signal. Testing on clinical EMGdi data confirm that this method is also efficient in removing ECG artifacts from the corrupted clinical EMGdi signal.     

A monolithic silicon based integrated signal generation and detection system for monitoring DNA hybridisation

The aim of this work was to develop an integrated solution to DNA hybridisation monitoring for diagnostics on a monolithic silicon platform. A fabrication process was developed incorporating a gold initiation electrode patterned directly onto a PIN photodiode detector. Patterned interdigitated type electrodes exhibited the smallest reduction in photodiode sensitivity, therefore these were chosen as the ECL initiator design. A novel DNA hybridisation assay was developed based on the displacement of a partially mismatched complementary strand by a perfectly matched labelled complementary strand. Pre-hybridised thiolated oligonucleotide and unlabelled 25% mismatched oligonucleotide were assembled on the gold initiation electrode. On addition of the labelled perfectly complementary oligonucleotide, the mismatched strands were displaced and a signal was generated. The sensitivity of the photodiode to light emitted at 620 nm, the ruthenium emission wavelength, was determined and subsequently, the diode current response to light generated by flow addition of ruthenium solution was found to be measurable to a concentration of 10 fM. Pre-hybridised duplex DNA, consisting of thiolated oligonucleotide and ruthenium labelled complementary oligonucleotide, was assembled on the gold initiation electrode. The difference between the current measured during flow of buffer and the ECL co-reactant TPA was three orders of magnitude, indicating that DNA assembled on the surface comprised sufficient ruthenium to generate a measurable signal. Finally, the displacement of unlabelled partial mismatch oligonucleotide from the sensor surface was monitored on addition of the ruthenium labelled perfectly complementary oligonucleotide in TPA flow and the measured photodiode current response was up to 50 times greater.     

A species concept for bacteria based on adaptive divergence

Bacterial strains are currently grouped into species based on overall genomic similarity and sharing of phenotypes deemed ecologically important. Many believe this polyphasic taxonomy is in need of revision because it lacks grounding in evolutionary theory, and boundaries between species are arbitrary. Recent taxonomy efforts using multilocus sequence typing (MLST) data are based on the identification of distinct phylogenetic clusters. However, these approaches face the problem of deciding the phylogenetic level at which clusters are representative of evolutionary or taxonomically distinct units. In this review, I propose classifying two phylogenetic clusters as separate species only when they have statistically significantly diverged as a result of adaptive evolution. More than a method for classification, the concept of adaptive divergence can be used in a 'reverse ecology' approach to identify lineages that are in the process of speciation or genes involved in initial adaptive divergence.     

Mathematical model for adaptive evolution of populations based on a complex domain

A mutation is ultimately essential for adaptive evolution in all populations. It arises all the time, but is mostly fixed by enzymes. Further, most do consider that the evolution mechanism is by a natural assortment of variations in organisms in line for random variations in their DNA, and the suggestions for this are overwhelming. The altering of the construction of a gene, causing a different form that may be communicated to succeeding generations, produced by the modification of single base units in DNA, or the deletion, insertion, or rearrangement of larger units of chromosomes or genes. This altering is called a mutation. In this paper, a mathematical model is introduced to this reality. The model describes the time and space for the evolution. The tool is based on a complex domain for the space. We show that the evolution is distributed with the hypergeometric function. The Boundedness of the evolution is imposed by utilizing the Koebe function.     

A comparison of signal detection between an echolocating dolphin and an optimal receiver

Summary An electronic simulated target apparatus was used in a two-experiment study to compare the target detection performance of an echolocating bottlenose dolphin with an optimal receiver. Random Gaussian noise with a relatively flat spectrum from 20 to 160 kHz was used as a masking source. Experiment I was conducted to establish a technique for estimating the echo energy-to-noise ratio,E _e /N, at the dolphin's threshold of detection. Dolphins typically vary the amplitude of their emitted signal over a large range making it difficult to estimateE _e /N. In the first part of experiment I, the simulated echo was a double click, the pulses separated by 200 s, with each pulse being a replica of the dolphin's transmitted signal. A staircase psychophysical procedure was used to obtain the detection threshold, and the echo energy-to-noise ratio based on the highest amplitude click emitted per trial, (E _e /N)_max, was determined at each reversal point. The second echo type consisted of one of the animal's echolocation clicks, previously measured, digitized and stored in an erasable programmable read-only memory (EPROM). The electronic target simulator was modified so that every time the dolphin emitted an echolocation signal, the EPROM was triggered to produce two pulses separated by 200 s. On any trial, the EPROM signal was played back at a fixed amplitude, regardless of the amplitude of the dolphin's emitted signal. TheE _e /N obtained with the EPROM signal at threshold was found to be 2.9 dB lower than (E _e /N)_max obtained with the normal phantom target. Therefore an estimate ofE _e /N can be obtained by subtracting 2.9 dB from (E _e /N)_max.Experiment II was conducted to obtain isosensitivity data that could be plotted in an ROC (receiver operating characteristic) format. The response bias of the dolphin was manipulated by varying the food reinforcement payoff matrix. In terms of the ratio of correct detections to correct rejections, the payoff matrix was varied over four values: 11, 41, 81, and 14. A modified method of constants procedure was used to obtain the dolphin target detection performance data. Each session consisted of two 20-trial blocks in which a strong echo was used in the first block and a weak echo in the second block. The energy-to-noise ratio required by an optimal detector to approximate the dolphin's performance was obtained by determining the appropriate detection sensitivity,d, that best fitted the dolphin's data plotted in an ROC format. The results of experiment II indicated that the dolphin required approximately 7.4 dB higherE _e /N than an optimal detector to detect the phantom target.Abbreviations response bias - d detection sensitivity - E _e echo energy flux density - EPROM erasable programmable read-only memory - N noise spectral density - p(t) instantaneous acoustic pressure - P(Y/SN) probability of detection - P(Y/N) probability of false alarm - ROC receiver-operating-characteristics - SE source energy flux density     

A universal platform for sensitive and selective colorimetric DNA detection based on Exo III assisted signal amplification

Rapid growth of available sequence data has made the detection of nucleic acids critical to the development of modern life sciences. Many amplification methods based on gold nanoparticles and endonuclease for sensitive DNA detection have been developed. However, these approaches require specific target sequence for endonuclease recognition, which cannot be fulfilled in all systems. Replacing the restriction enzyme with a nuclease that does not require any specific recognition sequence may offer a universally adaptable system. Here we have developed a novel homogeneous, colorimetric DNA detection method, which consists of Exo III, a linker DNA, and two DNA-modified gold nanoparticles. This system is simple, low-cost, sensitive and selective. By coupling cyclic enzymatic cleavage and gold nanoparticle for signal amplification, our system provides a colorimetric detection limit of 15 pM, which is 3 orders of magnitude more sensitive than that of a general three-component sandwich assay format. Due to the intrinsic property of Exo III, our method shows excellent detection selectivity for single-base discrimination. More importantly, superior to other methods based on nicking and FokI endonuclease, our target sequence-independent platform is generally applicable for DNA sensing. This new approach could be widely applied to sensitive nucleic acids detection.     

A model for the emergence of adaptive subsystems

We investigate the interaction of learning and evolution in a changing environment. A stable learning capability is regarded as an emergent adaptive system evolved by natural selection of genetic variants. We consider the evolution of an asexual population. Each genotype can have ‘fixed’ and ‘flexible’ alleles. The former express themselves as synaptic connections that remain unchanged during ontogeny and the latter as synapses that can be adjusted through a learning algorithm. Evolution is modelled using genetic algorithms and the changing environment is represented by two optimal synaptic patterns that alternate a fixed number of times during the ‘life’ of the individuals. The amplitude of the change is related to the Hamming distance between the two optimal patterns and the rate of change to the frequency with which both exchange roles. This model is an extension of that of Hinton and Nowlan in which the fitness is given by a probabilistic measure of the Hamming distance to the optimum. We find that two types of evolutionary pathways are possible depending upon how difficult (costly) it is to cope with the changes of the environment. In one case the population loses the learning ability, and the individuals inherit fixed synapses that are optimal in only one of the environmental states. In the other case a flexible subsystem emerges that allows the individuals to adapt to the changes of the environment. The model helps us to understand how an adaptive subsystem can emerge as the result of the tradeoff between the exploitation of a congenital structure and the exploration of the adaptive capabilities practised by learning.     

Basic module for an adaptive control system based on neurone information processing

The design of such devices as robotic aids for handicapped people, powered prostheses and manipulative aids such as page turners would benefit from the use of an adaptive control system. Much recent work on adaptive networks has been based on simplified models of the information processing capabilities of neurones. Neurones are now known to be capable of association learning and memory and this study incorporates these features in a neurone model. A single neuronal input system, the NMDA-type glutamate receptor, is modelled by deriving finite difference equations from its reaction dynamics so that the concentration of several molecules in the receptor can be plotted as a function of time. The model shows association learning taking place at the glutamate receptor. A whole neurone with ten glutamate receptor regions is also modelled and shows that a neurone should be capable of recognizing patterns of inputs. As the neurone model is complicated and slow to run, a much simplified form of the model is described which embodies the basic features of neurone information processing in a simple algorithm.     

An ultrasensitive fluorescent aptasensor for adenosine detection based on exonuclease III assisted signal amplification

We report here a graphene oxide (GO)-based fluorescent aptasensor for adenosine detection by employing exonuclease III (Exo III) as a signal amplifying element. In the absence of adenosine, the adenosine aptamers hybridized with the complementary DNA (cDNA), and the Exo III could not cleave the single-strand signal probes labeled with carboxylfluorescein (FAM) at its 5' ends. When the graphene oxide was finally added, it could strongly adsorb the single-strand signal probes and quenched the fluorophore effectively. In the presence of adenosine, the aptamers associated with the targets, which led to the formation of duplex DNAs between the cDNAs and the signal probes. The Exo III thereafter could digest the duplex DNAs from 3' blunt terminus of signal probes, liberating the fluorophore. Upon adding the GO, the fluorophore could not be adsorbed and quenched. By coupling cyclic enzymatic cleavage, a remarkable fluorescent increase was obtained. Due to the specific recognition ability of the aptamer for the target and the powerful quenching property of GO for signal probe, this proposed approach has a good selectivity and high sensitivity for adenosine. In the optimum conditions described, >100% signal enhancement was achieved and a limit of detection as low as 1 nM was obtained, which is lower than those of commonly used fluorescent aptamer sensors. Moreover, the biosensor exhibited an ultrahigh sensitivity and held a versatile platform for clinical diagnostics, molecular biology and drug developments.