Object detection algorithms to identify skeletal components in carbonate cores

Identification of constituent grains in carbonate rocks requires specialist experience. A carbonate sedimentologist must be able to distinguish between skeletal grains that change through geological ages, preserved in differing alteration stages, and cut in random orientations across core sections. Recent studies have demonstrated the effectiveness of machine learning in classifying lithofacies from thin section, core, and seismic images, with faster analysis times and reduction of natural biases. In this study, we explore the application and limitations of convolutional neural network (CNN) based object detection frameworks to identify and quantify multiple types of carbonate grains within close-up core images of carbonate lithologies. We compiled nearly 400 images of high-resolution core images from three ODP and IODP expeditions. Over 9000 individual carbonate components of 11 different classes were manually labelled from this dataset. Using pre-trained weights, a transfer learning approach was applied to evaluate one-stage (YOLO v5) and two-stage (Faster R–CNN) detectors under different feature extractors (CSP-Darknet53 and ResNet50-FPN, respectively). Despite the current popularity of one-stage detectors, our results show Faster R–CNN with ResNet50-FPN backbone provides the most robust performance, achieving 0.73 mean average precision (mAP). Furthermore, we extend the approach by deploying the trained model to two ODP sites from Leg 194 that were not part of the training set (ODP Sites 1196 and 1199), providing a performance comparison with benchmark human interpretation

Impact of dataset size and convolutional neural network architecture on transfer learning for carbonate rock classification

Modern geological practices, in both industry and academia, rely largely on a legacy of observational data at a range of scales. However, widespread ambiguities in the petrographic description of rock facies reduce the reliability of descriptive data. Previous studies have demonstrated a great potential for the use of convolutional neural networks (CNNs) in the classification of facies from digital images; however, it remains to be determined which of the available CNN architectures performs best for a geological classification task. We evaluate the ability of top-performing CNNs to classify carbonate core images using transfer learning, systematically developing a performance comparison between these architectures on a complex geological dataset. Three datasets with orders of magnitude difference in data quantity (7000–104,000 samples) were created that contain images across seven classes from the modified Dunham Classification for carbonate rocks. Following training of nine different CNNs of four architectures on these datasets, we find the Inception-v3 architecture to be most suited to this classification task, achieving 92% accuracy when trained on the larger dataset. Furthermore, we show that even when using transfer learning the size of the dataset plays a key role in the performance of the models, with those trained on the smaller datasets showing a strong tendency to overfit. This has direct implications for the application of deep learning in geosciences as many papers currently published use very small datasets of less than 5000 samples. Application of the framework developed in this research could aid the future of deep learning based carbonate classification, with further potential to be easily modified to suit the classification of cores originating from different formations and lithologies

Methods to Assess the Direct Interaction of C. Jejuni With Mucins

Studies of the interaction of bacteria with mucus secreting cells can be complemented at a more mechanistic level by exploring the interaction of bacteria with purified mucins. Here we describe a far western blotting approach to show how C. jejuni proteins separated by SDS PAGE and transferred to a membrane or slot blotted directly onto a membrane can be probed biotinylated mucin. In addition we describe the use of novel mucin microarrays to assess bacterial interactions with mucins in a high throughput manner

Blind topological measurement-based quantum computation

Blind quantum computation is a novel secure quantum-computing protocol that enables Alice, who does not have sufficient quantum technology at her disposal, to delegate her quantum computation to Bob, who has a fully fledged quantum computer, in such a way that Bob cannot learn anything about Alice's input, output and algorithm. A recent proof-of-principle experiment demonstrating blind quantum computation in an optical system has raised new challenges regarding the scalability of blind quantum computation in realistic noisy conditions. Here we show that fault-tolerant blind quantum computation is possible in a topologically protected manner using the Raussendorf-Harrington-Goyal scheme. The error threshold of our scheme is 0.0043, which is comparable to that (0.0075) of non-blind topological quantum computation. As the error per gate of the order 0.001 was already achieved in some experimental systems, our result implies that secure cloud quantum computation is within reach.Comment: 17 pages, 5 figure

Control of breathing and respiratory gas exchange in high-altitude ducks native to the Andes

We examined the control of breathing and respiratory gas exchange in six species of high-altitude duck that independently colonized the high Andes. We compared ducks from high-altitude populations in Peru (Lake Titicaca at ∼3800 m above sea level; Chancay River at ∼3000–4100 m) with closely related populations or species from low altitude. Hypoxic ventilatory responses were measured shortly after capture at the native altitude. In general, ducks responded to acute hypoxia with robust increases in total ventilation and pulmonary O2 extraction. O2 consumption rates were maintained or increased slightly in acute hypoxia, despite ∼1–2°C reductions in body temperature in most species. Two high-altitude taxa – yellow-billed pintail and torrent duck – exhibited higher total ventilation than their low-altitude counterparts, and yellow-billed pintail exhibited greater increases in pulmonary O2 extraction in severe hypoxia. In contrast, three other high-altitude taxa – Andean ruddy duck, Andean cinnamon teal and speckled teal – had similar or slightly reduced total ventilation and pulmonary O2 extraction compared with low-altitude relatives. Arterial O2 saturation (SaO2) was elevated in yellow-billed pintails at moderate levels of hypoxia, but there were no differences in SaO2 in other high-altitude taxa compared with their close relatives. This finding suggests that improvements in SaO2 in hypoxia can require increases in both breathing and haemoglobin–O2 affinity, because the yellow-billed pintail was the only high-altitude duck with concurrent increases in both traits compared with its low-altitude relative. Overall, our results suggest that distinct physiological strategies for coping with hypoxia can exist across different high-altitude lineages, even among those inhabiting very similar high-altitude habitats

Optical one-way quantum computing with a simulated valence-bond solid

One-way quantum computation proceeds by sequentially measuring individual spins (qubits) in an entangled many-spin resource state. It remains a challenge, however, to efficiently produce such resource states. Is it possible to reduce the task of generating these states to simply cooling a quantum many-body system to its ground state? Cluster states, the canonical resource for one-way quantum computing, do not naturally occur as ground states of physical systems. This led to a significant effort to identify alternative resource states that appear as ground states in spin lattices. An appealing candidate is a valence-bond-solid state described by Affleck, Kennedy, Lieb, and Tasaki (AKLT). It is the unique, gapped ground state for a two-body Hamiltonian on a spin-1 chain, and can be used as a resource for one-way quantum computing. Here, we experimentally generate a photonic AKLT state and use it to implement single-qubit quantum logic gates.Comment: 11 pages, 4 figures, 8 tables - added one referenc

Investigating the effects of external fields polarization on the coupling of pure magnetic waves in the human body in very low frequencies

In this paper we studied the effects of external fields' polarization on the coupling of pure magnetic fields into human body. Finite Difference Time Domain (FDTD) method is used to calculate the current densities induced in a 1 cm resolution anatomically based model with proper tissue conductivities. Twenty different tissues have been considered in this investigation and scaled FDTD technique is used to convert the results of computer code run in 15 MHz to low frequencies which are encountered in the vicinity of industrial induction heating and melting devices. It has been found that external magnetic field's orientation due to human body has a pronounced impact on the level of induced currents in different body tissues. This may potentially help developing protecting strategies to mitigate the situations in which workers are exposed to high levels of external magnetic radiation

Managerial Work in a Practice-Embodying Institution - The role of calling, the virtue of constancy

What can be learned from a small scale study of managerial work in a highly marginal and under-researched working community? This paper uses the ‘goods-virtues-practices-institutions’ framework to examine the managerial work of owner-directors of traditional circuses. Inspired by MacIntyre’s arguments for the necessity of a narrative understanding of the virtues, interviews explored how British and Irish circus directors accounted for their working lives. A purposive sample was used to select subjects who had owned and managed traditional touring circuses for at least 15 years, a period in which the economic and reputational fortunes of traditional circuses have suffered badly. This sample enabled the research to examine the self-understanding of people who had, at least on the face of it, exhibited the virtue of constancy. The research contributes to our understanding of the role of the virtues in organizations by presenting evidence of an intimate relationship between the virtue of constancy and a ‘calling’ work orientation. This enhances our understanding of the virtues that are required if management is exercised as a domain-related practice