Evolving spiking networks with variable resistive memories

Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in spiking neural networks. The evolutionary design process exploits parameter self-adaptation and allows the topology and synaptic weights to be evolved for each network in an autonomous manner. Variable resistive memories are the focus of this research; each synapse has its own conductance profile which modifies the plastic behaviour of the device and may be altered during evolution. These variable resistive networks are evaluated on a noisy robotic dynamic-reward scenario against two static resistive memories and a system containing standard connections only. The results indicate that the extra behavioural degrees of freedom available to the networks incorporating variable resistive memories enable them to outperform the comparative synapse types. © 2014 by the Massachusetts Institute of Technology

How can we possibly resolve the planet's nitrogen dilemma?

Nitrogen is the most crucial element in the production of nutritious feeds and foods. The production of reactive nitrogen by means of fossil fuel has thus far been able to guarantee the protein supply for the world population. Yet, the production and massive use of fertilizer nitrogen constitute a major threat in terms of environmental health and sustainability. It is crucial to promote consumer acceptance and awareness towards proteins produced by highly effective microorganisms, and their potential to replace proteins obtained with poor nitrogen efficiencies from plants and animals. The fact that reactive fertilizer nitrogen, produced by the Haber Bosch process, consumes a significant amount of fossil fuel worldwide is of concern. Moreover, recently, the prices of fossil fuels have increased the cost of reactive nitrogen by a factor of 3 to 5 times, while international policies are fostering the transition towards a more sustainable agro-ecology by reducing mineral fertilizers inputs and increasing organic farming. The combination of these pressures and challenges opens opportunities to use the reactive nitrogen nutrient more carefully. Time has come to effectively recover used nitrogen from secondary resources and to upgrade it to a legal status of fertilizer. Organic nitrogen is a slow-release fertilizer, it has a factor of 2.5 or higher economic value per unit nitrogen as fertilizer and thus adequate technologies to produce it, for instance by implementing photobiological processes, are promising. Finally, it appears wise to start the integration in our overall feed and food supply chains of the exceptional potential of biological nitrogen fixation. Nitrogen produced by the nitrogenase enzyme, either in the soil or in novel biotechnology reactor systems, deserves to have a ‘renaissance’ in the context of planetary governance in general and the increasing number of people who desire to be fed in a sustainable way in particular

Electroactive biofilms: new means for electrochemistry

This work demonstrates that electrochemical reactions can be catalysed by the natural biofilms that form on electrode surfaces dipping into drinking water or compost. In drinking water, oxygen reduction was monitored with stainless steel ultra-microelectrodes under constant potential electrolysis at )0.30 V/SCE for 13 days. 16 independent experiments were conducted in drinking water, either pure or with the addition of acetate or dextrose. In most cases, the current increased and reached 1.5–9.5 times the initial current. The current increase was attributed to biofilm forming on the electrode in a similar way to that has been observed in seawater. Epifluorescence microscopy showed that the bacteria size and the biofilm morphology depended on the nutrients added, but no quantitative correlation between biofilm morphology and current was established. In compost, the oxidation process was investigated using a titanium based electrode under constant polarisation in the range 0.10–0.70 V/SCE. It was demonstrated that the indigenous micro-organisms were responsible for the current increase observed after a few days, up to 60 mA m)2. Adding 10 mM acetate to the compost amplified the current density to 145 mA m)2 at 0.50 V/SCE. The study suggests that many natural environments, other than marine sediments, waste waters and seawaters that have been predominantly investigated until now, may be able to produce electrochemically active biofilm

A Re-evaluation of Electron-Transfer Mechanisms in Microbial Electrochemistry: Shewanella Releases Iron that Mediates Extracellular Electron Transfer

Exoelectrogenic bacteria can couple their metabolism to extracellular electron acceptors, including macroscopic electrodes, and this has applications in energy production, bioremediation and biosensing. Optimisation of these technologies relies on a detailed molecular understanding of extracellular electron-transfer (EET) mechanisms, and Shewanella oneidensis MR-1 (MR-1) has become a model organism for such fundamental studies. Here, cyclic voltammetry was used to determine the relationship between the surface chemistry of electrodes (modified gold, ITO and carbon electrodes) and the EET mechanism. On ultra-smooth gold electrodes modified with self-assembled monolayers containing carboxylic-acid-terminated thiols, an EET pathway dominates with an oxidative catalytic onset at 0.1V versus SHE. Addition of iron(II)chloride enhances the catalytic current, whereas the siderophore deferoxamine abolishes this signal, leading us to conclude that this pathway proceeds via an iron mediated electron transfer mechanism. The same EET pathway is observed at other electrodes, but the onset potential is dependent on the electrolyte composition and electrode surface chemistry. EET pathways with onset potentials above -0.1V versus SHE have previously been ascribed to direct electron-transfer (DET) mechanisms through the surface exposed decaheme cytochromes (MtrC/OmcA) of MR-1. In light of the results reported here, we propose that the previously identified DET mechanism of MR-1 needs to be re-evaluated

Evolving unipolar memristor spiking neural networks

© 2015 Taylor & Francis. Neuromorphic computing – brain-like computing in hardware – typically requires myriad complimentary metal oxide semiconductor spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are frequently cited as strong synapse candidates due to their statefulness and potential for low-power implementations. To date, plentiful research has focused on the bipolar memristor synapse, which is capable of incremental weight alterations and can provide adaptive self-organisation under a Hebbian learning scheme. In this paper, we consider the unipolar memristor synapse – a device capable of non-Hebbian switching between only two states (conductive and resistive) through application of a suitable input voltage – and discuss its suitability for neuromorphic systems. A self-adaptive evolutionary process is used to autonomously find highly fit network configurations. Experimentation on two robotics tasks shows that unipolar memristor networks evolve task-solving controllers faster than both bipolar memristor networks and networks containing constant non-plastic connections whilst performing at least comparably

Effect of non-linearity in predicting doppler waveforms through a novel model

BACKGROUND: In pregnancy, the uteroplacental vascular system develops de novo locally in utero and a systemic haemodynamic & bio-rheological alteration accompany it. Any abnormality in the non-linear vascular system is believed to trigger the onset of serious morbid conditions like pre-eclampsia and/or intrauterine growth restriction (IUGR). Exact Aetiopathogenesis is unknown. Advancement in the field of non-invasive doppler image analysis and simulation incorporating non-linearities may unfold the complexities associated with the inaccessible uteroplacental vessels. Earlier modeling approaches approximate it as a linear system. METHOD: We proposed a novel electrical model for the uteroplacental system that uses MOSFETs as non-linear elements in place of traditional linear transmission line (TL) model. The model to simulate doppler FVW's was designed by including the inputs from our non-linear mathematical model. While using the MOSFETs as voltage-controlled switches, a fair degree of controlled-non-linearity has been introduced in the model. Comparative analysis was done between the simulated data and the actual doppler FVW's waveforms. RESULTS & DISCUSSION: Normal pregnancy has been successfully modeled and the doppler output waveforms are simulated for different gestation time using the model. It is observed that the dicrotic notch disappears and the S/D ratio decreases as the pregnancy matures. Both these results are established clinical facts. Effects of blood density, viscosity and the arterial wall elasticity on the blood flow velocity profile were also studied. Spectral analysis on the output of the model (blood flow velocity) indicated that the Total Harmonic Distortion (THD) falls during the mid-gestation. CONCLUSION: Total harmonic distortion (THD) is found to be informative in determining the Feto-maternal health. Effects of the blood density, the viscosity and the elasticity changes on the blood FVW are simulated. Future works are expected to concentrate mainly on improving the load with respect to varying non-linear parameters in the model. Heart rate variability, which accounts for the vascular tone, should also be included. We also expect the model to initiate extensive clinical or experimental studies in the near future

Engineering a novel self-powering electrochemical biosensor

This paper records the efforts of a multi-disciplinary team of undergraduate students from Glasgow University to collectively design and carry out a 10 week project in Synthetic Biology as part of the international Genetic Engineered Machine competition (iGEM). The aim of the project was to design and build a self-powering electrochemical biosensor called ‘ElectrEcoBlu’. The novelty of this engineered machine lies in coupling a biosensor with a microbial fuel cell to transduce a pollution input into an easily measurable electrical output signal. The device consists of two components; the sensor element which is modular, allowing for customisation to detect a range of input signals as required, and the universal reporter element which is responsible for generating an electrical signal as an output. The genetic components produce pyocyanin, a competitive electron mediator for microbial fuel cells, thus enabling the generation of an electrical current in the presence of target chemical pollutants. The pollutants tested in our implementation were toluene and salicylate. ElectrEcoBlu is expected to drive forward the development of a new generation of biosensors. Our approach exploited a range of state-of-the-art modelling techniques in a unified framework of qualitative, stochastic and continuous approaches to support the design and guide the construction of this novel biological machine. This work shows that integrating engineering techniques with scientific methodologies can provide new insights into genetic regulation and can be considered as a reference framework for the development of biochemical systems in synthetic biology

Heterogeneous 2.5D integration on through silicon interposer

© 2015 AIP Publishing LLC. Driven by the need to reduce the power consumption of mobile devices, and servers/data centers, and yet continue to deliver improved performance and experience by the end consumer of digital data, the semiconductor industry is looking for new technologies for manufacturing integrated circuits (ICs). In this quest, power consumed in transferring data over copper interconnects is a sizeable portion that needs to be addressed now and continuing over the next few decades. 2.5D Through-Si-Interposer (TSI) is a strong candidate to deliver improved performance while consuming lower power than in previous generations of servers/data centers and mobile devices. These low-power/high-performance advantages are realized through achievement of high interconnect densities on the TSI (higher than ever seen on Printed Circuit Boards (PCBs) or organic substrates), and enabling heterogeneous integration on the TSI platform where individual ICs are assembled at close proximity

Long-term performance of a plant microbial fuel cell with Spartina anglica

The plant microbial fuel cell is a sustainable and renewable way of electricity production. The plant is integrated in the anode of the microbial fuel cell which consists of a bed of graphite granules. In the anode, organic compounds deposited by plant roots are oxidized by electrochemically active bacteria. In this research, salt marsh species Spartina anglica generated current for up to 119 days in a plant microbial fuel cell. Maximum power production was 100 mW m−2 geometric anode area, highest reported power output for a plant microbial fuel cell. Cathode overpotential was the main potential loss in the period of oxygen reduction due to slow oxygen reduction kinetics at the cathode. Ferricyanide reduction improved the kinetics at the cathode and increased current generation with a maximum of 254%. In the period of ferricyanide reduction, the main potential loss was transport loss. This research shows potential application of microbial fuel cell technology in salt marshes for bio-energy production with the plant microbial fuel cell