Supervised Learning in Multilayer Spiking Neural Networks

The current article introduces a supervised learning algorithm for multilayer spiking neural networks. The algorithm presented here overcomes some limitations of existing learning algorithms as it can be applied to neurons firing multiple spikes and it can in principle be applied to any linearisable neuron model. The algorithm is applied successfully to various benchmarks, such as the XOR problem and the Iris data set, as well as complex classifications problems. The simulations also show the flexibility of this supervised learning algorithm which permits different encodings of the spike timing patterns, including precise spike trains encoding.Comment: 38 pages, 4 figure

Microscopic modeling of photoluminescence of strongly disordered semiconductors

A microscopic theory for the luminescence of ordered semiconductors is modified to describe photoluminescence of strongly disordered semiconductors. The approach includes both diagonal disorder and the many-body Coulomb interaction. As a case study, the light emission of a correlated plasma is investigated numerically for a one-dimensional two-band tight-binding model. The band structure of the underlying ordered system is assumed to correspond to either a direct or an indirect semiconductor. In particular, luminescence and absorption spectra are computed for various levels of disorder and sample temperature to determine thermodynamic relations, the Stokes shift, and the radiative lifetime distribution.Comment: 35 pages, 14 figure

Exact exchange-correlation potential of a ionic Hubbard model with a free surface

We use Lanczos exact diagonalization to compute the exact exchange-correlation (xc) potential of a Hubbard chain with large binding energy ("the bulk") followed by a chain with zero binding energy ("the vacuum"). Several results of density functional theory in the continuum (sometimes controversial) are verified in the lattice. In particular we show explicitly that the fundamental gap is given by the gap in the Kohn-Sham spectrum plus a contribution due to the jump of the xc-potential when a particle is added. The presence of a staggered potential and a nearest-neighbor interaction V allows to simulate a ionic solid. We show that in the ionic regime in the small hopping amplitude limit the xc-contribution to the gap equals V, while in the Mott regime it is determined by the Hubbard U interaction. In addition we show that correlations generates a new potential barrier at the surface

Random-phase approximation and its applications in computational chemistry and materials science

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012

EANM guideline for ventilation/perfusion single-photon emission computed tomography (SPECT) for diagnosis of pulmonary embolism and beyond

These guidelines update the previous EANM 2009 guidelines on the diagnosis of pulmonary embolism (PE). Relevant new aspects are related to (a) quantification of PE and other ventilation/perfusion defects; (b) follow-up of patients with PE; (c) chronic PE; and (d) description of additional pulmonary physiological changes leading to diagnoses of left ventricular heart failure (HF), chronic obstructive pulmonary disease (COPD) and pneumonia. The diagnosis of PE should be reported when a mismatch of one segment or two subsegments is found. For ventilation, Technegas or krypton gas is preferred over diethylene triamine pentaacetic acid (DTPA) in patients with COPD. Tomographic imaging with V/P-SPECT has higher sensitivity and specificity for PE compared with planar imaging. Absence of contraindications makes V/P-SPECT an essential method for the diagnosis of PE. When V/P-SPECT is combined with a low-dose CT, the specificity of the test can be further improved, especially in patients with other lung diseases. Pitfalls in V/P-SPECT interpretation are discussed. In conclusion, V/P-SPECT is strongly recommended as it accurately establishes the diagnosis of PE even in the presence of diseases like COPD, HF and pneumonia and has no contraindications.Peer reviewe

NanoGalaxy: Nanopore long-read sequencing data analysis in Galaxy

Background: Long-read sequencing can be applied to generate very long contigs and even completely assembled genomes at relatively low cost and with minimal sample preparation. As a result, long-read sequencing platforms are becoming more popular. In this respect, the Oxford Nanopore Technologies–based long-read sequencing “nanopore” platform is becoming a widely used tool with a broad range of applications and end-users. However, the need to explore and manipulate the complex data generated by long-read sequencing platforms necessitates accompanying specialized bioinformatics platforms and tools to process the long-read data correctly. Importantly, such tools should additionally help democratize bioinformatic

Streaming histogram sketching for rapid microbiome analytics

Background: The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research, allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time. To address this need, we propose a new method for the compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching and classification of microbiome samples in near real time. Results: We apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed ‘histosketch’ that can efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using the pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we use a ‘real life’ example to show that histosketches can train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a random forest classifier that could accurately predict whether the neonate had received antibiotic treatment (97% accuracy, 96% precision) and could subsequently be used to classify microbiome data streams in less than 3 s. Conclusions: Our method offers a new approach to rapidly process microbiome data streams, allowing samples to be rapidly clustered, indexed and classified. We also provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2 GB microbiome in 50 s on a standard laptop using four cores, with the sketch occupying 3000 bytes of disk space

Selection analysis identifies unusual clustered mutational changes in Omicron lineage BA.1 that likely impact Spike function.

Among the 30 non-synonymous nucleotide substitutions in the Omicron S-gene are 13 that have only rarely been seen in other SARS-CoV-2 sequences. These mutations cluster within three functionally important regions of the S-gene at sites that will likely impact (i) interactions between subunits of the Spike trimer and the predisposition of subunits to shift from down to up configurations, (ii) interactions of Spike with ACE2 receptors, and (iii) the priming of Spike for membrane fusion. We show here that, based on both the rarity of these 13 mutations in intrapatient sequencing reads and patterns of selection at the codon sites where the mutations occur in SARS-CoV-2 and related sarbecoviruses, prior to the emergence of Omicron the mutations would have been predicted to decrease the fitness of any genomes within which they occurred. We further propose that the mutations in each of the three clusters therefore cooperatively interact to both mitigate their individual fitness costs, and adaptively alter the function of Spike. Given the evident epidemic growth advantages of Omicron over all previously known SARS-CoV-2 lineages, it is crucial to determine both how such complex and highly adaptive mutation constellations were assembled within the Omicron S-gene, and why, despite unprecedented global genomic surveillance efforts, the early stages of this assembly process went completely undetected

Theoretical study of the electronic spectra of small molecules that incorporate analogues of the copper-cysteine bond

The copper-sulphur bond which binds cysteinate to the metal centre is a key factor in the spectroscopy of blue copper proteins. We present theoretical calculations describing the electronically excited states of small molecules, including CuSH, CuSCH_3, (CH_3)_2SCuSH, (imidazole)-CuSH and (imidazole)_2-CuSH, derived from the active site of blue copper proteins that contain the copper-sulphur bond in order to identify small molecular systems that have electronic structure that is analogous to the active site of the proteins. Both neutral and cationic forms are studied, since these represent the reduced and oxidised forms of the protein, respectively. For CuSH and CuSH^+, excitation energies from time-dependent density functional theory with the B97-1 exchange-correlation functional agree well with the available experimental data and multireference configuration interaction calculations. For the positive ions, the singly occupied molecular orbital is formed from an antibonding combination of a 3d orbital on copper and a 3pπ orbital on sulphur, which is analogous to the protein. This leads several of the molecules to have qualitatively similar electronic spectra to the proteins. For the neutral molecules, changes in the nature of the low lying virtual orbitals leads the predicted electronic spectra to vary substantially between the different molecules. In particular, addition of a ligand bonded directly to copper results in the low-lying excited states observed in CuSH and CuSCH_33 to be absent or shifted to higher energies