USING 3D MODELS TO GENERATE LABELS FOR PANOPTIC SEGMENTATION OF INDUSTRIAL SCENES

Industrial companies often require complete inventories of their infrastructure. In many cases, a better inventory leads to a direct reduction of cost and uncertainty of engineering. While large scale panoramic surveys now allow these inventories to be performed remotely and reduce time on-site, the time and money required to visually segment the many types of components on thousands of high resolution panoramas can make the process infeasible. Recent studies have shown that deep learning techniques, namely deep neural networks, can accurately perform panoptic segmentation of things and stuff and hence be used to inventory the components of a picture. In order to train those deep architectures with specific industrial equipment, not available in public datasets, our approach uses an as-built 3D model of an industrial building to procedurally generate labels. Our results show that, despite the presence of errors during the generation of the dataset, our method is able to accurately perform panoptic segmentation on images of industrial scenes. In our testing, 80% of generated labels were correctly identified (non null intersection over union, i.e. true positive) by the panoptic segmentation, with great performance levels even for difficult classes, such as reflective heat insulators. We then visually investigated the 20% of true negative, and discovered that 80% were correctly segmented, but were counted as true negative because of errors in the dataset generation. Demonstrating this level of accuracy for panoptic segmentation on industrial panoramas for inventories also offers novel perspectives for 3D laser scan processing

State-of-practice on as-is modelling of industrial facilities

90% of the time needed for the conversion from point clouds to 3D models of industrial facilities is spent on geometric modelling due to the sheer number of Industrial Objects (IOs) of each plant. Hence, cost reduction is only possible by automating modelling. Our previous work has successfully identified the most frequent industrial objects which are in descending order: electrical conduit, straight pipes, circular hollow sections, elbows, channels, solid bars, I-beams, angles, flanges and valves. We modelled those on a state-of-theart software, EdgeWise and then evaluated the performance of this software for pipeline and structural modelling. The modelling of pipelines is summarized in three basic steps: (a) automated extraction of cylinders, (b) their semantic classification and (c) manual extraction and editing of pipes. The results showed that cylinders are modelled with 75 % recall and 62 % precision on average. We discovered that pipes, electrical conduit and circular hollow sections require 80 % of the Total Modelling Hours (TMH) of the 10 most frequent IOs to build the plant model. TMH was then compared to modelling hours in Revit and showed that 67 % of pipe modelling time is saved by EdgeWise. This paper is the first to evaluate state-of-the-art industrial modelling software. These findings help in better understanding the problem and serve as the foundation for researchers who are interested in solving i

Gold Nanoparticle Uptake in Tumor Cells: Quantification and Size Distribution by sp-ICPMS

Gold nanoparticles (AuNPs) are increasingly studied for cancer treatment purposes, as they can potentially improve both control and efficiency of the treatment. Intensive research is conducted in vitro on rodent and human cell lines to objectify the gain of combining AuNPs with cancer treatment and to understand their mechanisms of action. However, using nanoparticles in such studies requires thorough knowledge of their cellular uptake. In this study, we optimized single particle ICPMS (sp-ICPMS) analysis to qualify and quantify intracellular AuNP content after exposure of in vitro human breast cancer cell lines. To this aim, cells were treated with an alkaline digestion method with 5% TMAH, allowing the detection of gold with a yield of 97% on average. Results showed that under our experimental conditions, the AuNP size distribution appeared to be unchanged after internalization and that the uptake of particles depended on the cell line and on the exposure duration. Finally, the comparison of the particle numbers per cell with the estimates based on the gold masses showed excellent agreement, confirming the validity of the sp-ICPMS particle measurements in such complex samples

Assessing 3D metric data of digital surface models for extracting archaeological data from archive stereo-aerial photographs.

Archaeological remains are under increasing threat of attrition from natural processes and the continued mechanisation of anthropogenic activities. This research analyses the ability of digital photogrammetry software to reconstruct extant, damaged, and destroyed archaeological earthworks from archive stereo-aerial photographs. Case studies of Flower's Barrow and Eggardon hillforts, both situated in Dorset, UK, are examined using a range of imagery dating from the 1940s to 2010. Specialist photogrammetric software SocetGXP® is used to extract digital surface models, and the results compared with airborne and terrestrial laser scanning data to assess their accuracy. Global summary statistics and spatial autocorrelation techniques are used to examine error scales and distributions. Extracted earthwork profiles are compared to both current and historical surveys of each study site. The results demonstrate that metric information relating to earthwork form can be successfully obtained from archival photography. In some instances, these data out-perform airborne laser scanning in the provision of digital surface models with minimal error. The role of archival photography in regaining metric data from upstanding archaeology and the consequent place for this approach to impact heritage management strategies is demonstrated

Combined 1H-Detected solid-state NMR spectroscopy and electron cryotomography to study membrane proteins across resolutions in native environments

Membrane proteins remain challenging targets for structural biology, despite much effort, as their native environment is heterogeneous and complex. Most methods rely on detergents to extract membrane proteins from their native environment, but this removal can significantly alter the structure and function of these proteins. Here, we overcome these challenges with a hybrid method to study membrane proteins in their native membranes, combining high-resolution solid-state nuclear magnetic resonance spectroscopy and electron cryotomography using the same sample. Our method allows the structure and function of membrane proteins to be studied in their native environments, across different spatial and temporal resolutions, and the combination is more powerful than each technique individually. We use the method to demonstrate that the bacterial membrane protein YidC adopts a different conformation in native membranes and that substrate binding to YidC in these native membranes differs from purified and reconstituted system

Genomics, evolution, and crystal structure of a new family of bacterial spore kinases

Bacterial spore formation is a complex process of fundamental relevance to biology and human disease. The spore coat structure is complex and poorly understood, and the roles of many of the protein components remain unclear. We describe a new family of spore coat proteins, the bacterial spore kinases (BSKs), and the first crystal structure of a BSK, YtaA (CotI) from Bacillus subtilis. BSKs are widely distributed in spore-forming Bacillus and Clostridium species, and have a dynamic evolutionary history. Sequence and structure analyses indicate that the BSKs are CAKs, a prevalent group of small molecule kinases in bacteria that is distantly related to the eukaryotic protein kinases. YtaA has substantial structural similarity to CAKs, but also displays distinctive features that broaden our understanding of the CAK group. Evolutionary constraint analysis of the protein surfaces indicates that members of the BSK family have distinct clade-conserved patterns in the substrate binding region, and probably bind and phosphorylate distinct targets. Several classes of BSKs have apparently independently lost catalytic activity to become pseudokinases, indicating that the family also has a major noncatalytic function. Proteins 2010. © 2009 Wiley-Liss, Inc

Comparative Genomic Analyses of Copper Transporters and Cuproproteomes Reveal Evolutionary Dynamics of Copper Utilization and Its Link to Oxygen

Copper is an essential trace element in many organisms and is utilized in all domains of life. It is often used as a cofactor of redox proteins, but is also a toxic metal ion. Intracellular copper must be carefully handled to prevent the formation of reactive oxygen species which pose a threat to DNA, lipids, and proteins. In this work, we examined patterns of copper utilization in prokaryotes by analyzing the occurrence of copper transporters and copper-containing proteins. Many organisms, including those that lack copper-dependent proteins, had copper exporters, likely to protect against copper ions that inadvertently enter the cell. We found that copper use is widespread among prokaryotes, but also identified several phyla that lack cuproproteins. This is in contrast to the use of other trace elements, such as selenium, which shows more scattered and reduced usage, yet larger selenoproteomes. Copper transporters had different patterns of occurrence than cuproproteins, suggesting that the pathways of copper utilization and copper detoxification are independent of each other. We present evidence that organisms living in oxygen-rich environments utilize copper, whereas the majority of anaerobic organisms do not. In addition, among copper users, cuproproteomes of aerobic organisms were larger than those of anaerobic organisms. Prokaryotic cuproproteomes were small and dominated by a single protein, cytochrome c oxidase. The data are consistent with the idea that proteins evolved to utilize copper following the oxygenation of the Earth

Characterization of an Alkali- and Halide-Resistant Laccase Expressed in E. coli: CotA from <i>Bacillus clausii</i>

The limitations of fungal laccases at higher pH and salt concentrations have intensified the search for new extremophilic bacterial laccases. We report the cloning, expression, and characterization of the bacterial cotA from Bacillus clausii, a supposed alkalophilic ortholog of cotA from B. subtilis. Both laccases were expressed in E. coli strain BL21(DE3) and characterized fully in parallel for strict benchmarking. We report activity on ABTS, SGZ, DMP, caffeic acid, promazine, phenyl hydrazine, tannic acid, and bilirubin at variable pH. Whereas ABTS, promazine, and phenyl hydrazine activities vs. pH were similar, the activity of B. clausii cotA was shifted upwards by ~0.5-2 pH units for the simple phenolic substrates DMP, SGZ, and caffeic acid. This shift is not due to substrate affinity (K(M)) but to pH dependence of catalytic turnover: The k(cat) of B. clausii cotA was 1 s⁻¹ at pH 6 and 5 s⁻¹ at pH 8 in contrast to 6 s⁻¹ at pH 6 and 2 s⁻¹ at pH 8 for of B. subtilis cotA. Overall, k(cat)/K(M) was 10-fold higher for B. subtilis cotA at pH(opt). While both proteins were heat activated, activation increased with pH and was larger in cotA from B. clausii. NaCl inhibited activity at acidic pH, but not up to 500-700 mM NaCl in alkaline pH, a further advantage of the alkali regime in laccase applications. The B. clausii cotA had ~20 minutes half-life at 80°C, less than the ~50 minutes at 80°C for cotA from B. subtilis. While cotA from B. subtilis had optimal stability at pH~8, the cotA from B. clausii displayed higher combined salt- and alkali-resistance. This resistance is possibly caused by two substitutions (S427Q and V110E) that could repel anions to reduce anion-copper interactions at the expense of catalytic proficiency, a trade-off of potential relevance to laccase optimization