Eneos (Japan)

This study proposes a method for change detection by extracting small image pairs from recorded video pairs in patrol inspections of oil plants using a mobile robot equipped with a camera. While change detection methods often perform well in controlled laboratory environments, their performance tends to degrade in plant environments. This is because, in plant environments, the regions of change caused by anomalies within the images are often small, and the environments are structurally complex. In this study, to address this issue, we adopt an approach that extracts small image pairs from the target and reference images for change detection. Additionally, we develop a method for extracting small image pairs that considers the consistency of three-dimensional coordinates based on multi-view stereo. As a result, the proposed method achieved high-precision change detection, demonstrating its potential for application in patrol inspections of oil plants using a mobile robot.

Abstract In this study, we investigated a method of utilizing the drone itself as a wind speed sensor without mounting a special observation device on the drone. As a result, we constructed a calibration formula to convert the flight record data to an arbitrary wind speed. Next, we applied this method to the airflow measurement in the wake region for the utility-scale wind turbine and succeeded in reproducing the airflow characteristics caused by the wind turbine wake phenomenon.

A crude oil aggregation-forming, strictly anaerobic, Gram-stain-positive, spore-forming, rod-shaped, motile and mesophilic bacterium, named strain SH18-2T, was isolated from marine sediment near Sado Island in the Sea of Japan. The temperature, salinity and pH ranges of this strain for the growth were 15-40 °C (optimum 35 °C), 0.5-6.0% NaCl (w/v; optimum 2.0%) and pH 6.0-8.0 (optimum 7.5), respectively. A phylogenetic analysis of the 16S rRNA gene sequence showed that this strain belongs to the genus Clostridium. It was most closely related to Clostridium grantii A-1T (97.02% homology). The draft genome size was 5616089 bp, with a G+C content of 29.7 mol%. The digital DNA-DNA hybridization values determined using the Genome-to-Genome Distance Calculator and the average nucleotide identity between this strain and C. grantii A-1T were 20.30 and 78.24%, respectively. Whole-organism hydrolysates of strain SH18-2T contained meso-diaminopimelic acid; the major fatty acid was C16:0, and the polar lipid pattern consisted of diphosphatidylglycerol, phosphatidylglycerol, glycolipid and three unidentified polar lipids. From the results of genotypic, phenotypic and chemotaxonomic analyses, SH18-2T (=NBRC 116030T=DSM 115762T) is the type strain and represents a novel species of the genus Clostridium, and the name Clostridium sediminicola sp. nov. is proposed.

Lead sulfide (PbS) quantum dots (QDs) are promising photovoltaic absorbers owing to their tunable absorption range from the visible to infrared regions. Realizing high efficiency in PbS QD/zinc oxide (ZnO) heterojunction solar cells requires precise energy-level alignment between the PbS QDs and ZnO, which significantly affects carrier transport and recombination processes, particularly when employing infrared-absorbing PbS QDs. In this study, we conducted systematic interfacial engineering through a small-molecule treatment to tailor the PbS QD/ZnO nanowire (NW) heterojunction for enhanced infrared solar cell performance. Five molecules featuring hydroxy (-OH), thiol (-SH), and methyl (-CH3) functional groups were strategically selected to tune the interfacial energetics based on their molecular dipoles, their electron-withdrawing abilities, and the surface coverage on ZnO, among other factors. These molecular modifications revealed the key parameters that influenced the energy levels of the conduction band minimum, the valence band maximum, and the Fermi level, thereby shaping the overall band structure of the PbS QD/ZnO NW heterojunction. Controlled interface engineering enables the transformation of spike-shaped heterojunctions, which impede carrier transport from the PbS QD region to the ZnO region, into cliff-shaped junctions, which are more favourable for carrier extraction. Solar cells with cliff-shaped heterojunctions exhibit increased short-circuit current densities and external quantum efficiencies. Importantly, the carrier-recombination frequency at the interface depended significantly on the type of functional group introduced by the modifying molecules. This study provides valuable insights into the selection and design of modifying molecules for controlling the properties of metal oxide/infrared QD heterojunction-based solar cells.

石油精製プラント等の大規模生産・製造現場では軽労化や省人化が望まれている．しかし，設備のロボット化等の自動化も改修コストが大規模となり即時には現実的ではない．そのため人手での作業が今後も一部継続されていく可能性が高い．また，このような作業現場は，従来は成人男性の作業者が殆どであったが，近年は労働人口の低下や全員参加社会の推進で高齢者や女性作業者等の多様性が増加している場合がある．従来，成人男性に対して設計運用されてきた設備は，このような多様な作業者に対して身体的な負担となっている可能性もある．本報告では石油精製プラントのバルブ開閉操作に着目して，その作業負担を実態調査した．

<strong class="journal-contentHeaderColor">Abstract.</strong> The majority of Earth&rsquo;s prokaryotes live under the deep sedimentary biosphere. Geochemical processes driven by geothermal heating may play a crucial role in fueling deep subsurface microbial biomass and activities, yet their full breadth remains uncaptured. Here, we investigated the microbial community composition and metabolism in microbial natural gas-bearing aquifers at temperatures ranging from 35&minus;80 &deg;C, situated above nonmicrobial gas and oil-bearing sediments at temperatures exceeding 90 &deg;C. Cultivation-based and molecular gene sequencing analyses, including radiotracer measurements, of formation water indicated variations in predominant methanogenic pathways across different temperature regimes of upper aquifers: high potential for hydrogenotrophic/methylotrophic, hydrogenotrophic and acetoclastic methanogenesis at depths with mesophilic, thermophilic and hyperthermophilic temperatures, respectively. The potential for acetoclastic methanogenesis correlated with elevated acetate concentrations with increasing depth, possibly due to the thermal decomposition of sedimentary organic matter. In addition to acetoclastic methanogenesis, in aquifers with hyperthermophilic temperatures, acetate is potentially utilized by microorganisms responsible for the dissimilatory reduction of sulfur compounds other than sulfate because of its high relative abundance at greater depths. The stable sulfur isotopic analysis of sulfur compounds in water and oil samples suggested that hydrogen sulfide generated through the thermal decomposition of sulfur compounds in oil migrates upward and is subsequently oxidized with iron oxides present in sediments, yielding elemental sulfur and thiosulfate. These compounds are consumed by sulfur-reducing microorganisms, possibly reflecting elevated microbial populations in aquifers with hyperthermophilic temperatures. These findings reveal previously overlooked geothermal heat-driven geochemical and microbiological processes involved in carbon and sulfur cycling in the deep sedimentary biosphere.

Computational pathway exploration can unravel complex catalytic mechanisms and even predict unexplored catalytic reactions when performed in a fully systematic and unbiased manner. However, such a comprehensive exploration typically requires years of computation or thousands of CPU cores even for small systems. Herein, a generic neural network potential (NNP) trained on a large structure–energy database and force- and kinetics-based pathway exploration algorithm were combined without any tuning. An interface code was developed to combine the NNP in the Matlantis platform with the search algorithm in the GRRM software. The combined approach automatically generated comprehensive pathway ensembles containing over 10,000 local minimum structures for methane oxidation on the Pd(111) and Pd(100) surfaces with reasonable computational effort. The kinetically most plausible mechanism derived from the ensemble was qualitatively consistent with that obtained by density functional theory. These results highlight the considerable predictive power of the proposed approach at low computational cost.