Artificial Intelligence Assisted Dynamic Control of Environmental Emissions From Hybrid Energy Process Plants (HEPP)

A model digital data processing platform is proposed based on “deep-learning” methodology that can be used to identify the emissions patterns from process plants with hybrid energy recovery and energy generation facilities. The non-invasive dynamic monitoring and correlation of particulate, VOCs and other greenhouse gas emissions from semi-batch and continuous process plants is demonstrated with use of neural encoding and pattern recognition using a multi-layer perceptron and multi-stack encoder configuration. A multi-layer environmental perceptron (MLEP) is developed based on the above analyses that aims to detect patterns of emission types, rates and concentrations as a function of variation of plant operational conditions and process variables. Four different task algorithms are constructed and are currently trained for use in (i) In-Plant Product Quality Control Domain and (ii) In-Plant Process Efficiency Target Control Domain. As a further consequence, environmental impact assessment is considered within the hazards and process safety frameworks that conventionally issue sanctions and penalize non-compliance with imposition of environmental levy scales rather than offering process improvement incentives. The latter is demonstrated to be possible by facilitating dynamic corrective action and hazard prevention using MLEP platforms should emission ceilings be frequently and/or periodically exceeded in 24/7 continuous plant operations. Potential applications of the MLEP (MLEP) are illustrated in the context of dynamic emissions control and abatement in hybrid energy process plants (HEPP) and combined power plants using process-integrated CO2 capture and storage schemes

Size Segregation of Granular Matter in Silo Discharges

We present an experimental study of segregation of granular matter in a quasi-two dimensional silo emptying out of an orifice. Size separation is observed when multi-sized particles are used with the larger particles found in the center of the silo in the region of fastest flow. We use imaging to study the flow inside the silo and quantitatively measure the concentration profiles of bi-disperse beads as a function of position and time. The angle of the surface is given by the angle of repose of the particles, and the flow occurs in a few layers only near the top of this inclined surface. The flowing region becomes deeper near the center of the silo and is confined to a parabolic region centered at the orifice which is approximately described by the kinematic model. The experimental evidence suggests that the segregation occurs on the surface and not in the flow deep inside the silo where velocity gradients also are present. We report the time development of the concentrations of the bi-disperse particles as a function of size ratios, flow rate, and the ratio of initial mixture. The qualitative aspects of the observed phenomena may be explained by a void filling model of segregation.Comment: 6 pages, 10 figures (gif format), postscript version at http://physics.clarku.edu/~akudrolli/nls.htm

Granular discharge and clogging for tilted hoppers

We measure the flux of spherical glass beads through a hole as a systematic function of both tilt angle and hole diameter, for two different size beads. The discharge increases with hole diameter in accord with the Beverloo relation for both horizontal and vertical holes, but in the latter case with a larger small-hole cutoff. For large holes the flux decreases linearly in cosine of the tilt angle, vanishing smoothly somewhat below the angle of repose. For small holes it vanishes abruptly at a smaller angle. The conditions for zero flux are discussed in the context of a {\it clogging phase diagram} of flow state vs tilt angle and ratio of hole to grain size

Friction phenomena and their impact on the shear behaviour of granular material

In the discrete element simulation of granular materials, the modelling of contacts is crucial for the prediction of the macroscopic material behaviour. From the tribological point of view, friction at contacts needs to be modelled carefully, as it depends on several factors, e.g. contact normal load or temperature to name only two. In discrete element method (DEM) simulations the usage of Coulomb’s law of friction is state of the art in modelling particle–particle contacts. Usually in Coulomb’s law, for all contacts only one constant coefficient of friction is used, which needs to reflect all tribological effects. Thus, whenever one of the influence factors of friction varies over a wide range, it can be expected that the usage of only one constant coefficient of friction in Coulomb’s law is an oversimplification of reality. For certain materials, e.g. steel, it is known that a dependency of the coefficient of friction on the contact normal load exists. A more tribological tangential contact law is implemented in DEM, where the interparticle friction coefficient depends on the averaged normal stress in the contact. Simulations of direct shear tests are conducted, using steel spheres of different size distributions. The strong influence of interparticle friction on the bulk friction is shown via a variation of the constant interparticle friction coefficient. Simulations with constant and stress-dependent interparticle friction are compared. For the stress-dependent interparticle friction, a normal stress dependency of the bulk friction is seen. In the literature, measurements of different granular materials and small normal loads also show a stress dependency of the bulk friction coefficient. With increasing applied normal stress, the bulk friction coefficient reduces both in the experiments and in the simulations

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine: Brussels, Belgium. 15-18 March 2016.

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

A Survey of Genomic Traces Reveals a Common Sequencing Error, RNA Editing, and DNA Editing

While it is widely held that an organism's genomic information should remain constant, several protein families are known to modify it. Members of the AID/APOBEC protein family can deaminate DNA. Similarly, members of the ADAR family can deaminate RNA. Characterizing the scope of these events is challenging. Here we use large genomic data sets, such as the two billion sequences in the NCBI Trace Archive, to look for clusters of mismatches of the same type, which are a hallmark of editing events caused by APOBEC3 and ADAR. We align 603,249,815 traces from the NCBI trace archive to their reference genomes. In clusters of mismatches of increasing size, at least one systematic sequencing error dominates the results (G-to-A). It is still present in mismatches with 99% accuracy and only vanishes in mismatches at 99.99% accuracy or higher. The error appears to have entered into about 1% of the HapMap, possibly affecting other users that rely on this resource. Further investigation, using stringent quality thresholds, uncovers thousands of mismatch clusters with no apparent defects in their chromatograms. These traces provide the first reported candidates of endogenous DNA editing in human, further elucidating RNA editing in human and mouse and also revealing, for the first time, extensive RNA editing in Xenopus tropicalis. We show that the NCBI Trace Archive provides a valuable resource for the investigation of the phenomena of DNA and RNA editing, as well as setting the stage for a comprehensive mapping of editing events in large-scale genomic datasets

FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data

We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements

Molecular Trajectories Leading to the Alternative Fates of Duplicate Genes

Gene duplication generates extra gene copies in which mutations can accumulate without risking the function of pre-existing genes. Such mutations modify duplicates and contribute to evolutionary novelties. However, the vast majority of duplicates appear to be short-lived and experience duplicate silencing within a few million years. Little is known about the molecular mechanisms leading to these alternative fates. Here we delineate differing molecular trajectories of a relatively recent duplication event between humans and chimpanzees by investigating molecular properties of a single duplicate: DNA sequences, gene expression and promoter activities. The inverted duplication of the Glutathione S-transferase Theta 2 (GSTT2) gene had occurred at least 7 million years ago in the common ancestor of African great apes and is preserved in chimpanzees (Pan troglodytes), whereas a deletion polymorphism is prevalent in humans. The alternative fates are associated with expression divergence between these species, and reduced expression in humans is regulated by silencing mutations that have been propagated between duplicates by gene conversion. In contrast, selective constraint preserved duplicate divergence in chimpanzees. The difference in evolutionary processes left a unique DNA footprint in which dying duplicates are significantly more similar to each other (99.4%) than preserved ones. Such molecular trajectories could provide insights for the mechanisms underlying duplicate life and death in extant genomes

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]