Application of multi-criteria decision-making to risk prioritisation in tidal energy developments

This paper presents an analytical multi-criterion analysis for the prioritisation of risks for the development of tidal energy projects. After a basic identification of risks throughout the project and relevant stakeholders in the UK, classified through a political, economic, social, technological, legal and environmental analysis, relevant questionnaires provided scores to each risk and corresponding weights for each of the different sectors. Employing an extended technique for order of preference by similarity to ideal solution as well as the weighted sum method based on the data obtained, the risks identified are ranked based on their criticality, drawing attention of the industry in mitigating the ones scoring higher. Both methods were modified to take averages at different stages of the analysis in order to observe the effects on the final risk ranking. A sensitivity analysis of the results was also carried out with regard to the weighting factors given to the perceived expertise of participants, with different results being obtained whether a linear, squared or square root regression is used. Results of the study show that academics and industry have conflicting opinions with regard to the perception of the most critical risks.     

Enrichment of Inorganic Martian Dust Simulant with Carbon Component can Provoke Neurotoxicity

Carbon is the most abundant dust-forming element in the interstellar medium. Tremendous amount of meteorites containing plentiful carbon and carbon-enriched dust particles have reached the Earth daily. National Institute of Health panel accumulates evidences that nano-sized air pollution components may have a significant impact on the central nervous system (CNS) in health and disease. During inhalation, nano-/microsized particles are efficiently deposited in nasal, tracheobronchial, and alveolar regions and can be transported to the CNS. Based on above facts, here we present the study, the aims of which were: 1) to upgrade inorganic Martian dust simulant derived from volcanic ash (JSC-1a/JSC, ORBITEC Orbital Technologies Corporation, Madison, Wisconsin) by the addition of carbon components, that is, nanodiamonds and carbon dots; 2) to analyse acute effects of upgraded simulant on key characteristics of synaptic neurotransmission; and 3) to compare above effects with those of inorganic dust and carbon components per se. Acute administration of carbon-containing Martian dust analogues resulted in a significant decrease in transporter-mediated uptake of L-[¹⁴C]glutamate (the major excitatory neurotransmitter) and [³H]GABA (the main inhibitory neurotransmitter) by isolated rat brain nerve terminals. The extracellular level of both neurotransmitters increased in the presence of carbon-containing Martian dust analogues. These effects were associated with action of carbon components of upgraded Martian dust simulant, but not with its inorganic constituent. This fact indicates that carbon component of native Martian dust can have deleterious effects on extracellular glutamate and GABA homeostasis in the CNS, and so glutamate- and GABA-ergic neurotransmission disballansing exitation and inhibition.     

Analysis of observer performance in unknown-location tasks for tomographic image reconstruction

Our goal is to optimize regularized image reconstruction for emission tomography with respect to lesion detectability in the reconstructed images. We consider model observers whose decision variable is the maximum value of a local test statistic within a search area. Previous approaches have used simulations to evaluate the performance of such observers. We propose an alternative approach, where approximations of tail probabilities for the maximum of correlated Gaussian random fields facilitate analytical evaluation of detection performance. We illustrate how these approximations, which are reasonably accurate at low probability of false alarm operating points, can be used to optimize regularization with respect to lesion detectability.     

Esterase Activity of Serum Albumin Studied by 1H NMR Spectroscopy and Molecular Modelling

Serum albumin possesses esterase and pseudo-esterase activities towards a number of endogenous and exogenous substrates, but the mechanism of interaction of various esters and other compounds with albumin is still unclear. In the present study, proton nuclear magnetic resonance (¹H NMR) has been applied to the study of true esterase activity of albumin, using the example of bovine serum albumin (BSA) and p-nitrophenyl acetate (NPA). The site of BSA esterase activity was then determined using molecular modelling methods. According to the data obtained, the accumulation of acetate in the presence of BSA in the reaction mixture is much more intense as compared with the spontaneous hydrolysis of NPA, which indicates true esterase activity of albumin towards NPA. Similar results were obtained for p-nitophenyl propionate (NPP) as substrate. The rate of acetate and propionate release confirms the assumption that there is a site of true esterase activity in the albumin molecule, which is different from the site of the pseudo-esterase activity Sudlow II. The results of molecular modelling of BSA and NPA interaction make it possible to postulate that Sudlow site I is the site of true esterase activity of albumin.     

Genomic Regions Associated with Fusarium Wilt Resistance in Flax

Modern flax cultivars are susceptible to many diseases; arguably, the most economically damaging of these is the Fusarium wilt fungal disease. Over the past decades international flax breeding initiatives resulted in the development of resistant cultivars. However, much remains to be learned about the mechanisms of resistance to Fusarium infection in flax. As a first step to uncover the genetic factors associated with resistance to Fusarium wilt disease, we performed a genome-wide association study (GWAS) using 297 accessions from the collection of the Federal Research Centre of the Bast Fiber Crops, Torzhok, Russia. These genotypes were infected with a highly pathogenic Fusarium oxysporum f.sp. lini MI39 strain; the wilt symptoms were documented in the course of three successive years. Six different single-locus models implemented in GAPIT3 R package were applied to a selected subset of 72,526 SNPs. A total of 15 QTNs (Quantitative Trait Nucleotides) were detected during at least two years of observation, while eight QTNs were found during all three years of the experiment. Of these, ten QTNs occupied a region of 640 Kb at the start of chromosome 1, while the remaining QTNs mapped to chromosomes 8, 11 and 13. All stable QTNs demonstrate a statistically significant allelic effect across 3 years of the experiment. Importantly, several QTNs spanned regions that harbored genes involved in the pathogen recognition and plant immunity response, including the KIP1-like protein (Lus10025717) and NBS-LRR protein (Lus10025852). Our results provide novel insights into the genetic architecture of flax resistance to Fusarium wilt and pinpoint potential candidate genes for further in-depth studies.     

Long‐Aliphatic‐Segment Polyamides: Salt Preparation and Subsequent Anhydrous Polymerization

Long‐aliphatic‐segment polyamides were prepared based on hexamethylenediamine and α,ω‐(CH₂)_x biosynthetic diacids (x = 10, 11, 12). The pertinent monomers (salts) were isolated as solids, thoroughly characterized for the first time, and then submitted to an anhydrous melt prepolymerization technique. The obtained prepolymers exhibited in the range of 5 100–11 800 g · mol^?1, and the molecular weight was further increased by up to 55% through solid‐state finishing. The suggested overall polyamidation cycle was conducted at short melt‐reaction times, so as to avoid any thermal degradation, and was proved efficient, indicating similar reactants polymerizability independently of the methylene content.

     

Ru-Containing Polymeric Catalysts for Cellulose Conversion to Polyols

In this paper Ru-containing catalysts based on hypercrosslinked polystyrene (MN-270) and its functional analogues (MN-100 and MN-500) were studied for the first time in cellulose hydrolytic hydrogenation. The catalysts were characterized using transmission electron microscopy (TEM), high resolution TEM, and porosity measurements. Catalytic studies demonstrated that the catalyst containing 1.0 % Ru and based on MN-270 is the most active. The total yield of sorbitol and mannitol was 50 % on the average at 85 % cellulose conversion.     

On a New Method for Iterative Calculation of Crack Trajectory

A new efficient iterative procedure to follow automatically crack trajectory is suggested. Parameters of the procedure and illustrative examples are given.     

Deep Learning Based Prediction of Gas Chromatographic Retention Indices for a Wide Variety of Polar and Mid-Polar Liquid Stationary Phases

Prediction of gas chromatographic retention indices based on compound structure is an important task for analytical chemistry. The predicted retention indices can be used as a reference in a mass spectrometry library search despite the fact that their accuracy is worse in comparison with the experimental reference ones. In the last few years, deep learning was applied for this task. The use of deep learning drastically improved the accuracy of retention index prediction for non-polar stationary phases. In this work, we demonstrate for the first time the use of deep learning for retention index prediction on polar (e.g., polyethylene glycol, DB-WAX) and mid-polar (e.g., DB-624, DB-210, DB-1701, OV-17) stationary phases. The achieved accuracy lies in the range of 16–50 in terms of the mean absolute error for several stationary phases and test data sets. We also demonstrate that our approach can be directly applied to the prediction of the second dimension retention times (GC × GC) if a large enough data set is available. The achieved accuracy is considerably better compared with the previous results obtained using linear quantitative structure-retention relationships and ACD ChromGenius software. The source code and pre-trained models are available online.