Dietary differences among commercially important fishes in Lake Tanganyika assessed using stable isotope analysis

The pelagic fishery of Lake Tanganyika, which is largely made up of the three species Lates stappersii, Limnothrissa miodon, and Stolothrissa tanganicae, has been in decline, and there is no clear understanding of the primary underlying causes. It has been suggested that climate change has altered the primary productivity of the system, but detailed knowledge of the system's food web is required to elucidate the effect on higher trophic levels. The aim of this study is to determine the diet of the three commercially important fish species. Muscle tissue samples for stable isotope analysis were taken from February through April 2017, supplemented with stomach samples from L. stappersii for use in stomach content analysis. The stomach analysis showed an ontogenetic change in the diet composition of L. stappersii, shifting from copepods to fish larvae, supplemented with shrimp, to whole fish prey as the fish grew larger. Stable carbon and nitrogen isotope values from fish muscle were consistent with this observation, and also seemed to indicate that fish of similar sizes had similar diets, irrespective of species. This suggests that the diet of the pelagic fish species might be better explained by size, rather than species. The isotope data revealed a short range of δ¹⁵N values from primary consumers to fish, which may help explain the high fisheries productivity of Lake Tanganyika, and the strong impact of primary productivity changes on fisheries yield.     

Raft crystals of poly(isoprene)-block-poly(ferrocenyldimethylsilane) and their surface wetting behavior during melting as observed by AFM and NanoTA

We report on the morphology evolution during heating and melting of lamellar poly(isoprene)-block-poly(ferrocenyldimethylsilane) (PI₇₆-b-PFDMS₇₆) raft crystals deposited at the native oxide surface of silicon (SiO₂) or at a highly ordered pyrolytic graphite (HOPG) surface, studied by in situ temperature controlled atomic force microscopy. Crystals deposited on hydrophilic SiO₂ surfaces revealed an irreversible decrease in length at temperatures of up to tens of degrees above their expected melting temperature, while maintaining their platelet-like structure. Crystals deposited on hydrophobic HOPG surfaces initially decreased in length below their expected melting temperature, while at 120 °C and above a typical molten morphology was observed. In addition, the irreversible formation of a PI₇₆-b-PFDMS₇₆ wetting layer around the crystals was observed upon increasing the temperature. These observations in the morphological behavior upon heating emphasize the role of interfacial energy between a surface deposited block copolymer based macromolecular nanostructure and its supporting substrate.     

Model for microbiologically influenced corrosion potential assessment for the oil and gas industry

Corrosion is one of the major causes of failure in onshore and offshore oil and gas operations. Microbiologically influenced corrosion (MIC) is inherently more complex to predict, detect and measure because, for instance, the presence of biofilm and/or bacterial products is not sufficient to indicate active microbiological corrosion. The major challenge for current MIC models is to correlate factors that influence corrosion (i.e. chemical, physical, biological and molecular variables) with the potential of having MIC. Previous work has proposed the potential for MIC as a simple product of multiple factors, without fully considering the synergy or the interference among the factors. The present work proposes a network-based approach to analyse and predict MIC potential considering the complex interactions among a total of 60 influencing factors and 20 screening parameters. The proposed model has the ability to capture the complex interdependences and the synergic interactions of the factors used to assess MIC potential and uses an object-oriented approach based on a Bayesian Network. The model has been tested and verified using real data from a pipeline leakage incident that was a result of MIC. The proposed model constitutes a significant step in deepening the understanding of when MIC occurs and its predictability.

List of acronyms: APB: acid producing bacteria; Aw: water activity; BN: Bayesian network; MIC: microbiologically influenced corrosion; MMMs: molecular microbiological methods; NRB: nitrate-reducing bacteria; OOBN: object-oriented Bayesian network; PWRI: produced water re-injection; SPs: screening parameters; SRB: sulphate-reducing bacteria; SRPs: sulphate-reducing prokaryotes; TDSs: total dissolved solids     

Synthesis and thermal decomposition of potassium tetraamidoboranealuminate,K[Al(NH2BH3)4]

A new potassium tetraamidoboranealuminate, K[Al(NH₂BH₃)₄], has been synthesized by a mechanochemical reaction between KAlH₄ and NH₃BH₃. The compound, K[Al(NH₂BH₃)₄], crystallizes in a triclinic unit cell with space group symmetry P?1. The crystal structure consists of [K(NH₂BH₃)₆]^5? octahedra which facilitate the bridging between K⁺ in 1D chains, while also bridging K⁺ to Al³⁺ to connect the 1D chains in a 3D network. Thermal analysis reveals that K[Al(NH₂BH₃)₄] decomposes in two exothermic steps at T ～ 94 and 138 °C and releases primarily hydrogen. The total gas release amounts to ～6.0 wt% H₂. The decomposition products are investigated ex situ by powder X-ray diffraction, infrared spectroscopy, and ¹¹B and ²⁷Al NMR and identified as KBH₄ and amorphous phases, possibly BN₃, N₂BH, and/or NBH₂ whereas aluminum is found in four-, five-, and six-fold coordination. Unfortunately, the decomposed sample shows no hydrogen absorption at T = 260 °C and p(H₂) = 110 bar.     

Augmented semantic segmentation for the digitization of grinding tools based on deep learning

In order to analyze various process characteristics, grinding simulations can be used, which need accurate models of the tool and the individual grains. For this purpose, grinding tools can be digitized. To identify characteristic grains from a large number of measurements, each individual grain has to be analyzed and separated from the bond manually. Therefore, a deep learning-based methodology was developed to achieve a high segmentation accuracy of the grain boundaries efficiently. Additionally, a data augmentation approach was investigated to limit the data necessary for learning. The model transferability was quantified by analyzing different states of tool wear.     

Baseline layout and design of a 0.8 GW reference wind farm in the North Sea

The paper presents a model of a reference wind farm. The model considers the wind and wave climatologies for a specific site from which two different wind farm layouts are derived. These layouts are examined through the effective wake‐enhanced turbulence intensity at the hub height for a given climatology, and a simple model for the influence on capital expenditures is proposed. An electrical design is presented, the cable losses are calculated and the energy yield is determined. An operation and maintenance model is established, and the associated operating expenditure is obtained. All of the models are then summarized in terms of a levelized cost of energy using a numerical simulation tool, which allows the layouts to be compared. The data and models are freely available online for others to use and may serve as a baseline for benchmarking and allow researchers to compare and discuss their results. Copyright © 2017 John Wiley & Sons, Ltd.     

Characterizing delamination of fibre composites by mixed mode cohesive laws

A novel method is used for the determination of mixed mode cohesive laws and bridging laws for the characterisation of crack bridging in composites. The approach is based on an application of the J integral. The obtained cohesive laws were found to possess high peak stress values. Mixed mode cohesive stresses were found to depend on both the normal and tangential crack opening displacements. The bridging laws, which are to be used together with a mode mixity dependent crack tip fracture energy, were found to possess relative low bridging stresses; the peak normal bridging stress was approximately 2 MPa during pure Mode I and the maximum shear stress during pure Mode II was about 10 MPa.     

Heavy Metal and PAH Concentrations in Highway Runoff Deposits Fractionated on Settling Velocities

The correlation between settling velocity and associated pollutant concentrations is of major importance for best management practice in designing, redesigning, or evaluation of the efficiency of existing pond facilities for retaining unwanted pollutants. The prospect of this note is to state the relationship between the settling velocity of the runoff particles and the corresponding metal and polyaromatic hydrocarbon (PAH) concentration directly instead of dealing with two unknowns—the density and the shape of a single particle fraction in a settling velocity calculations. The measurements show that the highest cadmium, chromium, zinc, and nickel concentrations is associated with the most slowly falling particles and the lowest concentration associated within the faster falling fraction. This tendency is not clear for some of the sediments due to high content of organic matter and clearly not for lead and copper and there is no significant correlation between PAH concentration and settling velocity. The largest mass of metals and PAH within each pond can be found on the particle fraction with a settling velocity of 5.5–2.5 mm/s.