Evolving localizations in reaction-diffusion cellular automata

We consider hexagonal cellular automata with immediate cell neighbourhood and three cell-states. Every cell calculates its next state depending on the integral representation of states in its neighbourhood, i.e. how many neighbours are in each one state. We employ evolutionary algorithms to breed local transition functions that support mobile localizations (gliders), and characterize sets of the functions selected in terms of quasi-chemical systems. Analysis of the set of functions evolved allows to speculate that mobile localizations are likely to emerge in the quasi-chemical systems with limited diffusion of one reagent, a small number of molecules is required for amplification of travelling localizations, and reactions leading to stationary localizations involve relatively equal amount of quasi-chemical species. Techniques developed can be applied in cascading signals in nature-inspired spatially extended computing devices, and phenomenological studies and classification of non-linear discrete systems.Comment: Accepted for publication in Int. J. Modern Physics

A study of volatile compounds in the breath of children with type 1 diabetes

A pilot study of exhaled volatile compounds and their correlation with blood glucose levels in eight children with type 1 diabetes is reported. Five paired blood and breath samples were obtained from each child over a 6 hour period. The blood glucose concentration ranged from 41.4 to 435.6 mg/dL. Breath samples were collected in Tedlar bags and immediately evacuated through thermal desorption tubes packed with Carbopack B and C. The VOCs were later recovered by thermal desorption and analysed using gas chromatography mass spectrometry. The study identified 74 volatile compounds present in at least 10% of the patient samples. Of these 74 volatiles 36 were found in all patient samples tested. Further analysis of the 36 compounds found that none showed significant overall correlation with blood glucose levels. Isoprene showed a weak negative correlation with blood glucose levels. Acetone was found to have no correlation with blood glucose levels for the patients studied. Some patients showed significant individual correlation between the relative peak areas of certain compounds and blood glucose levels. However, there was no consistent pattern observed within these results across all 8 patients. Additional breath samples were collected in Tedlar bags and analysed using SIFTMS for 3 of the patients and a healthy control. The levels of 24 volatiles are reported and were found to be generally consistent with previously reported SIFT-MS data. In agreement with the GCMS data, no compounds exhibited a significant overall correlation with blood glucose level

Investigation of the semiochemicals of confused flour beetle Tribolium confusum Jaquelin du Val and grain weevil Sitophilus granarius (L.) in stored wheat grain and flour

This investigation sets out to identify specific volatile compounds from both flour infested with the confused flour beetle, Tribolium confusum and wheat grain infested with the grain weevil, Sitophilus granarius. These volatiles could help to aid the early detection of infestation by these pests. Volatiles by the infestation of these insect pests were entrained and analysed using Solid-Phase Micro-Extraction (SPME) coupled with gas chromatography-mass spectrometry (GCMS). Several volatile compounds were identified specific to T. confusum and S. granarius, including the known semiochemicals of T. confusum. The T. confusum larvae specifically emitted the volatiles 1-octen-3-one, benzeneacetaldehyde and decanal, whilst the adults specifically emitted the volatiles 2-methyl and 2- ethyl-1,3-benzenediols, the known semiochemicals 1-pentadecene, 2-methyl and 2-ethyl-1,4- benzoquinones and a series of yet to be fully identified unsaturated hydrocarbons. Both T. confusum adults and larvae emitted 2-methylbutanal and 2-butanone. Furthermore, four volatiles were identified unique to flour infested by T. confusum, 3-penten-2-one, 3-octanone, 2-octenal and 2-butyl-1-octanol. The S. granarius adults specifically emitted the volatiles 2-methylpropanoic acid and 3-methylbutanoic acid, whilst infested wheat grain produced the following volatile organic compounds, 2-methylfuran, 2- ethylfuran, 2-methyl-1-butanol, 2-ethyl-2-pentenal and 2,5-dimethylpyrazine. We believe these specific volatiles may act as semiochemicals for these insects and could aid in semiochemical monitoring for the early detection of infestation by these insects.Keywords: Tribolium confusum, Sitophilus granarius, GC-MS, SPME, Semiochemicals

Computing Naturally in the Billiard Ball Model

Fredkin's Billiard Ball Model (BBM) is considered one of the fundamental models of collision-based computing, and it is essentially based on elastic collisions of mobile billiard balls. Moreover, fixed mirrors or reflectors are brought into the model to deflect balls to complete the computation. However, the use of fixed mirrors is "physically unrealistic" and makes the BBM not perfectly momentum conserving from a physical point of view, and it imposes an external architecture onto the computing substrate which is not consistent with the concept of "architectureless" in collision-based computing. In our initial attempt to reduce mirrors in the BBM, we present a class of gates: the m-counting gate, and show that certain circuits can be realized with few mirrors using this gate. We envisage that our findings can be useful in future research of collision-based computing in novel chemical and optical computing substrates.Comment: 10 pages, 7 figure

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

The role of measuring exhaled breath biomarkers in sarcoidosis: A systematic review

Introduction: Sarcoidosis is a chronic granulomatous disease of unknown aetiology with a variable clinical course and prognosis. There is a growing need to identify non-invasive biomarkers to differentiate between clinical phenotypes, identify those at risk of disease progression and monitor response to treatment. Objectives: We undertook a systematic review and meta-analysis, to evaluate the utility of breath-based biomarkers in discriminating sarcoidosis from healthy controls, alongside correlation with existing non-breath based biomarkers used in clinical practice, radiological stage, markers of disease activity and response to treatment. Methods: Electronic searches were undertaken during November 2017 using PubMed, Ebsco, Embase and Web of Science to capture relevant studies evaluating breath-based biomarkers in adult patients with sarcoidosis. Results: 353 papers were screened; 21 met the inclusion criteria and assessed 25 different biomarkers alongside VOCs in exhaled breath gas or condensate. Considerable heterogeneity existed amongst the studies in terms of participant characteristics, sampling and analytical methods. Elevated biomarkers in sarcoidosis included 8-isoprostane, carbon monoxide, neopterin, TGF-β1, TNFα, CysLT and several metallic elements including chromium, silicon and nickel. Three studies exploring VOCs were able to distinguish sarcoidosis from controls. Meta-analysis of four studies assessing alveolar nitric oxide showed no significant difference between sarcoidosis and healthy controls (2.22ppb; 95% CI -0.83, 5.27) however, a high degree of heterogeneity was observed with an I2 of 93.4% (p<0.001). Inconsistent or statistically insignificant results were observed for correlations between several biomarkers and radiological stage, markers of disease activity or treatment. Conclusions: The evidence for using breath biomarkers to diagnose and monitor sarcoidosis remains inconclusive with many studies limited by small sample sizes and lack of standardisation. VOCs have shown promising potential but further research is required to evaluate their prognostic role

Solid-Phase Microextraction and the Human Fecal VOC Metabolome

The diagnostic potential and health implications of volatile organic compounds (VOCs) present in human feces has begun to receive considerable attention. Headspace solid-phase microextraction (SPME) has greatly facilitated the isolation and analysis of VOCs from human feces. Pioneering human fecal VOC metabolomic investigations have utilized a single SPME fiber type for analyte extraction and analysis. However, we hypothesized that the multifarious nature of metabolites present in human feces dictates the use of several diverse SPME fiber coatings for more comprehensive metabolomic coverage. We report here an evaluation of eight different commercially available SPME fibers, in combination with both GC-MS and GC-FID, and identify the 50/30 µm CAR-DVB-PDMS, 85 µm CAR-PDMS, 65 µm DVB-PDMS, 7 µm PDMS, and 60 µm PEG SPME fibers as a minimal set of fibers appropriate for human fecal VOC metabolomics, collectively isolating approximately 90% of the total metabolites obtained when using all eight fibers. We also evaluate the effect of extraction duration on metabolite isolation and illustrate that ex vivo enteric microbial fermentation has no effect on metabolite composition during prolonged extractions if the SPME is performed as described herein

Towards a Physarum learning chip

Networks of protoplasmic tubes of organism Physarum polycehpalum are macro-scale structures which optimally span multiple food sources to avoid repellents yet maximize coverage of attractants. When data are presented by configurations of attractants and behaviour of the slime mould is tuned by a range of repellents, the organism preforms computation. It maps given data configuration into a protoplasmic network. To discover physical means of programming the slime mould computers we explore conductivity of the protoplasmic tubes; proposing that the network connectivity of protoplasmic tubes shows pathway-dependent plasticity. To demonstrate this we encourage the slime mould to span a grid of electrodes and apply AC stimuli to the network. Learning and weighted connections within a grid of electrodes is produced using negative and positive voltage stimulation of the network at desired nodes; low frequency (10 Hz) sinusoidal (0.5 V peak-to-peak) voltage increases connectivity between stimulated electrodes while decreasing connectivity elsewhere, high frequency (1000 Hz) sinusoidal (2.5 V peak-to-peak) voltage stimulation decreases network connectivity between stimulated electrodes. We corroborate in a particle model. This phenomenon may be used for computation in the same way that neural networks process information and has the potential to shed light on the dynamics of learning and information processing in non-neural metazoan somatic cell networks

Urinary volatile organic compounds for the detection of prostate cancer

© 2015 Khalid et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy because of an elevated prostate specific antigen (PSA) level or abnormal findings on digital rectal examination. Urine samples were collected from patients with prostate cancer (n = 59) and cancer-free controls (n = 43), on the day of their biopsy, prior to their procedure. VOCs from the headspace of basified urine samples were extracted using solid-phase micro-extraction and analysed by gas chromatography/mass spectrometry. Classifiers were developed using Random Forest (RF) and Linear Discriminant Analysis (LDA) classification techniques. PSA alone had an accuracy of 62-64% in these samples. A model based on 4 VOCs, 2,6-dimethyl-7-octen-2-ol, pentanal, 3-octanone, and 2-octanone, was marginally more accurate 63-65%. When combined, PSA level and these four VOCs had mean accuracies of 74% and 65%, using RF and LDA, respectively. With repeated double cross-validation, the mean accuracies fell to 71% and 65%, using RF and LDA, respectively. Results from VOC profiling of urine headspace are encouraging and suggest that there are other metabolomic avenues worth exploring which could help improve the stratification of men at risk of prostate cancer. This study also adds to our knowledge on the profile of compounds found in basified urine, from controls and cancer patients, which is useful information for future studies comparing the urine from patients with other disease states