Microbial fuel cells: a green and alternative source for bioenergy production

Microbial fuel cell (MFC) represents one of the green technologies for the production of bioenergy. MFCs using microalgae produce bioenergy by converting solar energy into electrical energy as a function of metabolic and anabolic pathways of the cells. In the MFCs with bacteria, bioenergy is generated as a result of the organic substrate oxidation. MFCs have received high attention from researchers in the last years due to the simplicity of the process, the absence in toxic by-products, and low requirements for the algae growth. Many studies have been conducted on MFC and investigated the factors affecting the MFC performance. In the current chapter, the performance of MFC in producing bioenergy as well as the factors which influence the efficacy of MFCs is discussed. It appears that the main factors affecting MFC’s performance include bacterial and algae species, pH, temperature, salinity, substrate, mechanism of electron transfer in an anodic chamber, electrodes materials, surface area, and electron acceptor in a cathodic chamber. These factors are becoming more influential and might lead to overproduction of bioenergy when they are optimized using response surface methodology (RSM)

A direct examination of the dynamics of dipolarization fronts using MMS

Energy conversion on the dipolarization fronts (DFs) has attracted much research attention through the suggestion that intense current densities associated with DFs can modify the more global magnetotail current system. The current structures associated with a DF are at the scale of one to a few ion gyroradii, and their duration is comparable to a spacecraft's spin period. Hence, it is crucial to understand the physical mechanisms of DFs with measurements at a timescale shorter than a spin period. We present a case study whereby we use measurements from the Magnetospheric Multiscale (MMS) Mission, which provides full 3-D particle distributions with a cadence much shorter than a spin period. We provide a cross validation amongst the current density calculations and examine the assumptions that have been adopted in previous literature using the advantages of MMS mission (i.e., small-scale tetrahedron and high temporal resolution). We also provide a cross validation on the terms in the generalized Ohm's law using these advantageous measurements. Our results clearly show that the majority of the currents on the DF are contributed by both ion and electron diamagnetic drifts. Our analysis also implies that the ion frozen-in condition does not hold on the DF, while electron frozen-in condition likely holds. The new experimental capabilities allow us to accurately calculate Joule heating within the DF, which shows that plasma energy is being converted to magnetic energy in our event

Mitochondrial and nuclear genes suggest that stony corals are monophyletic but most families of stony corals are not (Order Scleractinia, Class Anthozoa, Phylum Cnidaria)

Modern hard corals (Class Hexacorallia; Order Scleractinia) are widely studied because of their fundamental role in reef building and their superb fossil record extending back to the Triassic. Nevertheless, interpretations of their evolutionary relationships have been in flux for over a decade. Recent analyses undermine the legitimacy of traditional suborders, families and genera, and suggest that a non-skeletal sister clade (Order Corallimorpharia) might be imbedded within the stony corals. However, these studies either sampled a relatively limited array of taxa or assembled trees from heterogeneous data sets. Here we provide a more comprehensive analysis of Scleractinia (127 species, 75 genera, 17 families) and various outgroups, based on two mitochondrial genes (cytochrome oxidase I, cytochrome b), with analyses of nuclear genes (ßtubulin, ribosomal DNA) of a subset of taxa to test unexpected relationships. Eleven of 16 families were found to be polyphyletic. Strikingly, over one third of all families as conventionally defined contain representatives from the highly divergent "robust" and "complex" clades. However, the recent suggestion that corallimorpharians are true corals that have lost their skeletons was not upheld. Relationships were supported not only by mitochondrial and nuclear genes, but also often by morphological characters which had been ignored or never noted previously. The concordance of molecular characters and more carefully examined morphological characters suggests a future of greater taxonomic stability, as well as the potential to trace the evolutionary history of this ecologically important group using fossils

Dopamine Induced Neurodegeneration in a PINK1 Model of Parkinson's Disease

Parkinson's disease is a common neurodegenerative disease characterised by progressive loss of dopaminergic neurons, leading to dopamine depletion in the striatum. Mutations in the PINK1 gene cause an autosomal recessive form of Parkinson's disease. Loss of PINK1 function causes mitochondrial dysfunction, increased reactive oxygen species production and calcium dysregulation, which increases susceptibility to neuronal death in Parkinson's disease. The basis of neuronal vulnerability to dopamine in Parkinson's disease is not well understood

How do you say ‘hello’? Personality impressions from brief novel voices

On hearing a novel voice, listeners readily form personality impressions of that speaker. Accurate or not, these impressions are known to affect subsequent interactions; yet the underlying psychological and acoustical bases remain poorly understood. Furthermore, hitherto studies have focussed on extended speech as opposed to analysing the instantaneous impressions we obtain from first experience. In this paper, through a mass online rating experiment, 320 participants rated 64 sub-second vocal utterances of the word ‘hello’ on one of 10 personality traits. We show that: (1) personality judgements of brief utterances from unfamiliar speakers are consistent across listeners; (2) a two-dimensional ‘social voice space’ with axes mapping Valence (Trust, Likeability) and Dominance, each driven by differing combinations of vocal acoustics, adequately summarises ratings in both male and female voices; and (3) a positive combination of Valence and Dominance results in increased perceived male vocal Attractiveness, whereas perceived female vocal Attractiveness is largely controlled by increasing Valence. Results are discussed in relation to the rapid evaluation of personality and, in turn, the intent of others, as being driven by survival mechanisms via approach or avoidance behaviours. These findings provide empirical bases for predicting personality impressions from acoustical analyses of short utterances and for generating desired personality impressions in artificial voices

Chalcogenide Glass-on-Graphene Photonics

Two-dimensional (2-D) materials are of tremendous interest to integrated photonics given their singular optical characteristics spanning light emission, modulation, saturable absorption, and nonlinear optics. To harness their optical properties, these atomically thin materials are usually attached onto prefabricated devices via a transfer process. In this paper, we present a new route for 2-D material integration with planar photonics. Central to this approach is the use of chalcogenide glass, a multifunctional material which can be directly deposited and patterned on a wide variety of 2-D materials and can simultaneously function as the light guiding medium, a gate dielectric, and a passivation layer for 2-D materials. Besides claiming improved fabrication yield and throughput compared to the traditional transfer process, our technique also enables unconventional multilayer device geometries optimally designed for enhancing light-matter interactions in the 2-D layers. Capitalizing on this facile integration method, we demonstrate a series of high-performance glass-on-graphene devices including ultra-broadband on-chip polarizers, energy-efficient thermo-optic switches, as well as graphene-based mid-infrared (mid-IR) waveguide-integrated photodetectors and modulators

Wide-Scale Analysis of Human Functional Transcription Factor Binding Reveals a Strong Bias towards the Transcription Start Site

We introduce a novel method to screen the promoters of a set of genes with shared biological function, against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. The gene sets were obtained from the functional Gene Ontology (GO) classification; for each set and motif we optimized the sequence similarity score threshold, independently for every location window (measured with respect to the TSS), taking into account the location dependent nucleotide heterogeneity along the promoters of the target genes. We performed a high throughput analysis, searching the promoters (from 200bp downstream to 1000bp upstream the TSS), of more than 8000 human and 23,000 mouse genes, for 134 functional Gene Ontology classes and for 412 known DNA motifs. When combined with binding site and location conservation between human and mouse, the method identifies with high probability functional binding sites that regulate groups of biologically related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were put to several experimental tests. By allowing a "flexible" threshold and combining our functional class and location specific search method with conservation between human and mouse, we are able to identify reliably functional TF binding sites. This is an essential step towards constructing regulatory networks and elucidating the design principles that govern transcriptional regulation of expression. The promoter region proximal to the TSS appears to be of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.Comment: 31 pages, including Supplementary Information and figure

Mixture models for analysis of melting temperature data

<p>Abstract</p> <p>Background</p> <p>In addition to their use in detecting undesired real-time PCR products, melting temperatures are useful for detecting variations in the desired target sequences. Methodological improvements in recent years allow the generation of high-resolution melting-temperature (T_m) data. However, there is currently no convention on how to statistically analyze such high-resolution T_mdata.</p> <p>Results</p> <p>Mixture model analysis was applied to T_mdata. Models were selected based on Akaike's information criterion. Mixture model analysis correctly identified categories in T_mdata obtained for known plasmid targets. Using simulated data, we investigated the number of observations required for model construction. The precision of the reported mixing proportions from data fitted to a preconstructed model was also evaluated.</p> <p>Conclusion</p> <p>Mixture model analysis of T_mdata allows the minimum number of different sequences in a set of amplicons and their relative frequencies to be determined. This approach allows T_mdata to be analyzed, classified, and compared in an unbiased manner.</p

Predicting active site residue annotations in the Pfam database

<p>Abstract</p> <p>Background</p> <p>Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families (<0.5%) have had the residues responsible for catalysis determined. To increase the active site annotations in the Pfam database, we have developed a strict set of rules, chosen to reduce the rate of false positives, which enable the transfer of experimentally determined active site residue data to other sequences within the same Pfam family.</p> <p>Description</p> <p>We have created a large database of predicted active site residues. On comparing our active site predictions to those found in UniProtKB, Catalytic Site Atlas, PROSITE and <it>MEROPS </it>we find that we make many novel predictions. On investigating the small subset of predictions made by these databases that are not predicted by us, we found these sequences did not meet our strict criteria for prediction. We assessed the sensitivity and specificity of our methodology and estimate that only 3% of our predicted sequences are false positives.</p> <p>Conclusion</p> <p>We have predicted 606110 active site residues, of which 94% are not found in UniProtKB, and have increased the active site annotations in Pfam by more than 200 fold. Although implemented for Pfam, the tool we have developed for transferring the data can be applied to any alignment with associated experimental active site data and is available for download. Our active site predictions are re-calculated at each Pfam release to ensure they are comprehensive and up to date. They provide one of the largest available databases of active site annotation.</p