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Cryo-electron tomography (cryo-ET) allows researchers to image cells in their native, hydrated state at the highest resolution currently possible. The technique has several limitations, however, that make analyzing the data it generates time-intensive and difficult. Hand segmenting a single tomogram can take from hours to days, but a microscope can easily generate 50 or more tomograms a day. Current deep learning segmentation programs for cryo-ET do exist, but are limited to segmenting one structure at a time. Here, multi-slice U-Net convolutional neural networks are trained and applied to automatically segment multiple structures simultaneously within cryo-tomograms. With proper preprocessing, these networks can be robustly inferred to many tomograms without the need for training individual networks for each tomogram. This workflow dramatically improves the speed with which cryo-electron tomograms can be analyzed by cutting segmentation time down to under 30 min in most cases. Further, segmentations can be used to improve the accuracy of filament tracing within a cellular context and to rapidly extract coordinates for subtomogram averaging.

A deep learning procedure has been examined for automatic segmentation of 3D tomography images from fiber-reinforced ceramic composites consisting of fibers and matrix of the same material (SiC), and thus identical image intensities. The analysis uses a neural network to distinguish phases from shape and edge information rather than intensity differences. It was used successfully to segment phases in a unidirectional composite that also had a coating with similar image intensity. It was also used to segment matrix cracks generated during in situ tensile loading of the composite and thereby demonstrate the influence of nonuniform fiber distribution on the nature of matrix cracking. By avoiding the need for manual segmentation of thousands of image slices, the procedure overcomes a major impediment to the extraction of quantitative information from such images. The analysis was performed using recently developed software that provides a general framework for executing both training and inference.

Monte Carlo simulations are commonly used in elemental quantification using energy-dispersive spectroscopy (EDS). Here, the Monte Carlo program MC X-ray was incorporated into the image processing software Dragonfly by Object Research Systems (ORS) as a simulation library. The simulation program has been transformed into a complete microscope simulator where the tools of Dragonfly allow complex voxel-based geometries to be constructed, and the electron beam and detectors can be freely placed inside the 3D space. Computation times of simulations have been improved drastically through new data structures and parallelization. Simulations of backscattered electron imaging and EDS mapping are presented here to demonstrate the capabilities of this new library.

There are many difficulties associated with forecasting high-energy solar particle events at Earth. One issue is understanding why some large solar eruptive events trigger ground level enhancement (GLE) events and others do not. In this work we perform 3D test particle simulations of a set of historic GLEs to understand more about what causes these powerful events. Particular focus is given to studying how the heliospheric current sheet (HCS) affects high-energy proton transport through the heliosphere following an event. Analysis of $\geq$M7.0 flares between 1976$-$2020 shows that active regions located closer to the HCS ($, ApJ accepted

The aurora is a readily visible phenomenon of interest to many members of the public. However, the aurora and associated phenomena can also significantly impact communications, ground-based infrastructure, and high-altitude radiation exposure. Forecasting the location of the auroral oval is therefore a key component of space weather forecast operations. A version of the OVATION-Prime 2013 auroral precipitation model (Newell et al., 2014, https://doi.org/10.1002/2014sw001056) was used by the UK Met Office Space Weather Operations Centre (MOSWOC). The operational implementation of the OVATION-Prime 2013 model at the UK Met Office delivered a 30-min forecast of the location of the auroral oval and the probability of observing the aurora. Using weather forecast evaluation techniques, we evaluate the ability of the OVATION-Prime 2013 model forecasts to predict the location and probability of the aurora occurring by comparing the forecasts with auroral boundaries determined from data from the IMAGE satellite between 2000 and 2002. Our analysis shows that the operational model performs well at predicting the location of the auroral oval, with a relative operating characteristic (ROC) score of 0.82. The model performance is reduced in the dayside local time sectors (ROC score = 0.59) and during periods of higher geomagnetic activity (ROC score of 0.55 for Kp = 8). As a probabilistic forecast, OVATION-Prime 2013 tends to underpredict the occurrence of aurora by a factor of 1.1–6, while probabilities of over 90% are overpredicted.

Segmenting bone from background is required to quantify bone architecture in computed tomography (CT) image data. A deep learning approach using convolutional neural networks (CNN) is a promising alternative method for automatic segmentation. The study objectives were to evaluate the performance of CNNs in automatic segmentation of human vertebral body (micro-CT) and femoral neck (nano-CT) data and to investigate the performance of CNNs to segment data across scanners.Scans of human L1 vertebral bodies (microCT [North Star Imaging], n=28, 53μm3) and femoral necks (nano-CT [GE], n=28, 27μm3) were used for evaluation. Six slices were selected for each scan and then manually segmented to create ground truth masks (Dragonfly 4.0, ORS). Two-dimensional U-Net CNNs were trained in Dragonfly 4.0 with images of the [FN] femoral necks only, [VB] vertebral bodies only, and [F+V] combined CT data. Global (i.e., Otsu and Yen) and local (i.e., Otsu r = 100) thresholding methods were applied to each dataset. Segmentation performance was evaluated using the Dice coefficient, a similarity metric of overlap. Kruskal-Wallis and Tukey-Kramer post-hoc tests were used to test for significant differences in the accuracy of segmentation methods.The FN U-Net had significantly higher Dice coefficients (i.e., better performance) than the global (Otsu: p=0.001; Yen: p=0.001) and local (Otsu [r=100]: p=0.001) thresholding methods and the VB U-Net (p=0.001) but there was no significant difference in model performance compared to the FN + VB U-net (p=0.783) on femoral neck image data. The VB U-net had significantly higher Dice coefficients than the global and local Otsu (p=0.001 for both) and FN U-Net (p=0.001) but not compared to the Yen (p=0.462) threshold or FN + VB U-net (p=0.783) on vertebral body image data.The results demonstrate that the U-net architecture outperforms common thresholding methods. Further, a network trained with bone data from a different system (i.e., different image acquisition parameters and voxel size) and a different anatomical site can perform well on unseen data. Finally, a network trained with combined datasets performed well on both datasets, indicating that a network can feasibly be trained with multiple datasets and perform well on varied image data.

Identifying the plasmapause location is crucial for forecasting and modelling the radiation belts, as well as larger scale models of the magnetosphere. The ionospheric footpoints of the plasmapause are thought to map to the equatorward edge of the diffuse aurora, with the first direct observation of an undulation of the plasmapause boundary and corresponding auroral features reported by He et al. (2020). Despite the importance of the plasmapause location, we do not have global observations of the plasmapause location.We provide a new statistical model of the plasmapause location determined from mapping the equatorward boundary of the observed auroral oval out to the inner magnetosphere. The model uses the equatorward boundary of the auroral oval determined from far-ultraviolet observations from the IMAGE spacecraft from Longden et al. (2010) to provide a statistical estimate of the plasmapause location for different levels of geomagnetic activity. Comparing the results of the statistical plasmapause model to other more direct measurements of the plasmapause shows a good agreement in the nightside local time sectors. The results of this analysis show that the equatorward boundary of the auroral oval statistically maps closely to the plasmapause boundary the nightside sectors and provides an alternative use for global auroral image data from the upcoming SMILE mission.

The open magnetic flux content of the magnetosphere varies during substorms as a result of dayside and nightside reconnection. The open flux can be calculated from the area of the polar cap, delineated by the open-closed field line boundary (OCB). This study presents a superposed epoch analysis of the location of the OCB and the change in the magnetic flux content in individual nightside MLT sectors during substorm growth, expansion, and recovery phases. Far ultraviolet (FUV) observations from the IMAGE satellite are used to derive a proxy of the OCB location. In the hour prior to substorm onset, the total nightside flux content increases by up to 0.12 GWb on average, resulting in an equatorward expansion of the OCB. Following substorm onset, the OCB contracts toward the pole as the open magnetic flux content decreases by up to 0.14 GWb on average, but the rate of decrease of the total nightside open flux content differs by 5–66% between the three IMAGE far ultraviolet instruments. The OCB does not contract poleward uniformly in all nightside magnetic local time (MLT) sectors after substorm onset. Close to the substorm onset MLT sector, the OCB contracts immediately following substorm onset; however, the OCB in more dawnward and duskward MLT sectors continues to expand equatorward for up to 120 minutes after substorm onset. Despite the continued increase in flux in these sectors after substorm onset, the total nightside flux content decreases immediately at substorm onset, indicating that the nightside reconnection rate exceeds the dayside rate following substorm onset.

Modelling of Solar Energetic Particles (SEPs) is usually carried out by means of the 1D focused transport equation and the same approach is adopted within several SEP Space Weather forecasting frameworks. We present an alternative approach, based on test particle simulations, which naturally describes 3D particle propagation. The SPARX forecasting system is an example of how test particle simulations can be used in real time in a Space Weather context. SPARX is currently operational within the COMESEP Alert System. The performance of the system, which is triggered by detection of a solar flare of class >M1.0 is evaluated by comparing forecasts for flare events between 1997 and 2017 with actual SEP data from the GOES spacecraft.

Tablet defects encountered during the manufacturing of oral formulations can result in quality concerns, timeline delays, and elevated financial costs. Internal tablet cracking is not typically measured in routine inspections but can lead to batch failures such as tablet fracturing. X-ray computed tomography (XRCT) has become well-established to analyze internal cracks of oral tablets. However, XRCT normally generates very large quantities of image data (thousands of 2D slices per data set) which require a trained professional to analyze. A user-guided manual analysis is laborious, time-consuming, and subjective, which may result in a poor statistical representation and inconsistent results. In this study, we have developed an analysis program that incorporates deep learning convolutional neural networks to fully automate the XRCT image analysis of oral tablets for internal crack detection. The computer program achieves robust quantification of internal tablet cracks with an average accuracy of 94%. In addition, the deep learning tool is fully automated and achieves a throughput capable of analyzing hundreds of tablets. We have also explored the adaptability of the deep learning analysis program toward different products (e.g., different types of bottles and tablets). Finally, the deep learning tool is effectively implemented into the industrial pharmaceutical workflow.

This guidance document by the British Menopause Society provides an overview of the management of women experiencing estrogen deficiency symptoms and arthralgia following a breast cancer diagnosis. It is now recommended that breast cancer patients are referred to health care professionals with an expertise in menopause for the management of such symptoms, which in turn often involves liaison with patients’ breast cancer teams. However, as many women initially present to primary health care professionals for advice, this statement is aimed to support the latter in such consultations by providing information about symptom aetiology, current management strategies and controversies and identifying useful practice points.

Telemetry has become an important method for studying the biology and ecology of animals. However, the impact of tracking devices and their method of attachment on different species across multiple temporal scales has seldom been assessed. We compared the behavioural and demographic responses of two species of seabird, Lesser Black-backed Gull Larus fuscus and Great Skua Stercorarius skua, to a GPS device attached using a crossover wing harness. We used telemetry information and monitoring of breeding colonies to compare birds equipped with a device and harness, and control birds without an attachment. We assessed whether tagged birds have lower short-term breeding productivity or lower longer term overwinter return rates (indicative of overwinter survival) than controls. For Great Skua, we also assessed whether territory attendance within the breeding season differed between tagged and control birds. As with previous studies on Lesser Black-backed Gull, we found no short-term impacts on breeding productivity or long-term impacts on overwinter return rates. For Great Skua, there was no evidence for impacts of the device and harness on territory attendance or breeding productivity. However, as found by a previous study of Great Skuas using a different (body) harness design, there was strong evidence of reduced overwinter return rates. Consequently, a device attached using a wing harness was considered suitable for long-term deployment on Lesser Black-backed Gulls, but not on Great Skuas. These findings will inform the planning of future tracking studies.

Instability of the distal ulna is a fairly common problem after acute distal radius fracture (DRF), distal radius malunion, triangular fibrocartilage complex injury, and a host of other types of trauma. We present a new anatomic technique to stabilize the distal ulna with a tendon graft augmented with Mersilene tape, which has been used primarily to treat unidirectional (dorsal or volar) instability, but could be used for global instability as well. Of the 12 patients who underwent this procedure, 9 had stability fully restored and the remaining 3 had only mild instability after surgery. The procedure is an effective treatment for distal radioulnar joint instability and we believe that this surgical technique will be a valuable adjunct to the existing described procedures for hand surgeons. We present a retrospective single-surgeon case series with outcome measures.

The complexity of unconventional reservoirs is manifested both in compositional variance of the matrix and the vast heterogeneity of the pore geometry. These complications confound proper understanding of transport properties and, consequently, recoverability for all stages in the production life cycle. Imaging techniques have emerged as a technical solution to aid how we decipher these complexities at the appropriate scales. In this study, we use the Woodford Shale as a representative of a commercially viable unconventional reservoir, and we apply multi-scale imaging analytics to a core sample. Our observations across four different length scales from imaging results of micro-x-ray microscopy (micro-XRM), nano-x-ray microscopy (nano-XRM), and focused ion-beam scanning electron microscopy (FIB-SEM) demonstrate both heterogeneity and anisotropy at every scale. We describe our multi-scale imaging workflow, which proved necessary to capture the multi-scale variability. In this instance of siliceous type II source rock, we find that micro-XRM was insufficient to visualize porosity, nano-XRM was sufficient for visualization of only limited porosity, whereas FIB-SEM yielded the resolved pore network. We further find that discrimination of the pore types, with the aid of image segmentation, helps define the connectivity and nature of the transport system. Collectively, the application of imaging across scales with appropriate image processing is required to adequately understand the transport-governing microstructure.

Understanding the transport of Solar Energetic Particles (SEPs) from acceleration sites at the Sun into interplanetary space and to the Earth is an important question for forecasting space weather. The Interplanetary Magnetic Field (IMF), with two distinct polarities and a complex structure, governs energetic particle transport and drifts. We analyse for the first time the effect of a wavy Heliospheric Current Sheet (HCS) on the propagation of SEPs. We inject protons close to the Sun and propagate them by integrating fully 3D trajectories within the inner heliosphere in the presence of weak scattering. We model the HCS position using fits based on neutral lines of magnetic field source surface maps (SSMs). We map 1 au proton crossings, which show efficient transport in longitude via HCS, depending on the location of the injection region with respect to the HCS. For HCS tilt angles around $30^\circ-40^\circ$, we find significant qualitative differences between A+ and A$-$ configurations of the IMF, with stronger fluences along the HCS in the former case but with a distribution of particles across a wider range of longitudes and latitudes in the latter. We show how a wavy current sheet leads to longitudinally periodic enhancements in particle fluence. We show that for an A+ IMF configuration, a wavy HCS allows for more proton deceleration than a flat HCS. We find that A$-$ IMF configurations result in larger average fluences than A+ IMF configurations, due to a radial drift component at the current sheet., Comment: 16 pages, 8 figures and 1 table, plus appendix of 2 pages, 1 figure and 1 table

Tracking devices are useful in studying the movement and behaviour of birds throughout the year. However, the effects of device attachment must be monitored for bird welfare and the scientific veracity of information gathered. We report on a trial of three different harness types (leg-loop, body and wing) for attaching GPS devices to Lesser Black-backed Gulls Larus fuscus and of a leg-loop harness on Great Skuas Stercorarius skua. This trial evaluated the functionality of the device whilst deployed, harness retention and the effects of each harness on the birds. The leg-loop harness prevented the devices from charging, due to feathers overlapping their solar panels, and individuals of both species shed this attachment during the first breeding season. For Lesser Black-backed Gull, devices functioned properly when attached using body and wing harnesses; foraging behaviour and territory attendance of birds were similar to the findings of other studies. Despite small sample sizes, annual adult survival rates...

Michaela K Mooney and co-authors evaluate a space weather forecast model in the same way that weather forecasts are assessed, work that won the 2019 Rishbeth Prize for best poster.

The key paradigm of digital rock physics (DRP) ''image and compute'' implies imaging and digitizing the pore space and mineral matrix of natural rock and then numerically simulating various physical processes in this digital object to obtain such macroscopic rock properties as permeability, electrical conductivity, and elastic moduli. The steps of this process include image acquisition, image processing (noise reduction, smoothing, and segmentation); setting up the numerical experiment (object size and resolution as well as the boundary conditions); and numerically solving the field equations. Finally, we need to interpret the solution thus obtained in terms of the desired macroscopic properties. For each of these DRP steps, there is more than one method and implementation. Our goal is to explore and record the variability of the computed effective properties as a function of using different tools and workflows. Such benchmarking is the topic of the two present companion papers. Here, in the first part, we introduce four 3D microstructures, a segmented Fontainebleau sandstone sample (porosity 0.147), a gray-scale Berea sample; a gray-scale Grosmont carbonate sample; and a numerically constructed pack of solid spheres (porosity 0.343). Segmentation of the gray-scale images by three independent teams reveals the uncertainty of this process: the segmented porosity range is between 0.184 and 0.209 for Berea and between 0.195 and 0.271 for the carbonate. The implications of the uncertainty associated with image segmentation are explored in a second paper.

Many surgical procedures have been described for the treatment of thumb basilar joint osteoarthritis. Augmentation of the standard ligament reconstruction tendon interposition procedure with the use of a Mersilene suture tape suspension-plasty, to recreate the stability provided by the anterior oblique ligament and increase pinch strength, will be described. Satisfaction with this procedure was evaluated through surveys completed by patients. In addition, independent physical assessments were performed to demonstrate stability, range of motion, and strength.

This article shows measured results of the different spectra of different protocols using advanced spectrum analyzers and signal generators. These results allow an understanding of the issues involved and indicate why a change from certain protocols that are currently promoted needs to be made as the industry matures. This paper shows that RFID systems operating in the 860 to 960 MHz UHF bands will have the optimum performance.

Placenta accreta is a rare but serious obstetric condition that is associated with considerable maternal morbidity and mortality. 1 A preoperative diagnosis of placenta accreta is difficult, and it is usually established at cesarean delivery or on histologic examination after obstetric hysterectomy for post-partum hemorrhage. In women with placenta previa, an abnormally adherent placenta is suspected when there is an absent decidual interface between the placenta and the myometrium. Another sign is the presence of unusually dilated vessels at the placental site. 2 , 3 Although the reported accuracy of sonographic diagnosis in the third trimester is reasonably high, late detection is of limited value because it does not prevent the serious complications of placenta accreta. The first-trimester diagnosis of pregnancy implantation in a previous cesarean delivery scar has been reported in recent years. 4 , 5 This condition is difficult to differentiate from cervical pregnancy, and it is likely that before the use of high-resolution transvaginal sonography, cesarean scar pregnancies were diagnosed and treated as cervical ectopic pregnancies. Cervical pregnancies rarely progress to term, whereas cesarean scar pregnancies may do so because of their position at the level of the internal os. In 60% to 70% of cesarean scar pregnancies, there is clear evidence of trophoblast penetrating the endometrial-myometrial junction. It has been postulated that first-trimester cesarean scar pregnancies that invade the myometrium may develop into placenta previa/accreta if the pregnancy is allowed to progress. 5 In this report, we describe the case of a first-trimester cesarean scar pregnancy with evidence of myometrial involvement that was managed expectantly and developed into placenta previa/accreta at term.

Given the massive increase in the number of new sequences and structures, a critical problem is how to integrate these raw data into meaningful biological information. One approach, the Evolutionary Trace, or ET, uses phylogenetic information to rank the residues in a protein sequence by evolutionary importance and then maps those ranked at the top onto a representative structure. If these residues form structural clusters, they can identify functional surfaces such as those involved in molecular recognition. Now that a number of examples have shown that ET can identify binding sites and focus mutational studies on their relevant functional determinants, we ask whether the method can be improved so as to be applicable on a large scale. To address this question, we introduce a new treatment of gaps resulting from insertions and deletions, which streamlines the selection of sequences used as input. We also introduce objective statistics to assess the significance of the total number of clusters and of the size of the largest one. As a result of the novel treatment of gaps, ET performance improves measurably. We find evolutionarily privileged clusters that are significant at the 5% level in 45 out of 46 (98%) proteins drawn from a variety of structural classes and biological functions. In 37 of the 38 proteins for which a protein-ligand complex is available, the dominant cluster contacts the ligand. We conclude that spatial clustering of evolutionarily important residues is a general phenomenon, consistent with the cooperative nature of residues that determine structure and function. In practice, these results suggest that ET can be applied on a large scale to identify functional sites in a significant fraction of the structures in the protein databank (PDB). This approach to combining raw sequences and structure to obtain detailed insights into the molecular basis of function should prove valuable in the context of the Structural Genomics Initiative.

Solar Energetic Particles (SEPs), a major component of space weather, propagate through the interplanetary medium strongly guided by the Interplanetary Magnetic Field (IMF). In this work, we analyse the implications a flat Heliospheric Current Sheet (HCS) has on proton propagation from SEP release sites to the Earth. We simulate proton propagation by integrating fully 3-D trajectories near an analytically defined flat current sheet, collecting comprehensive statistics into histograms, fluence maps and virtual observer time profiles within an energy range of 1--800 MeV. We show that protons experience significant current sheet drift to distant longitudes, causing time profiles to exhibit multiple components, which are a potential source of confusing interpretation of observations. We find that variation of current sheet thickness within a realistic parameter range has little effect on particle propagation. We show that IMF configuration strongly affects deceleration of protons. We show that in our model, the presence of a flat equatorial HCS in the inner heliosphere limits the crossing of protons into the opposite hemisphere., 16 pages, 15 figures, accepted for publication in The Astrophysical Journal

The history, taxonomy, distribution, habitat and cultivation requirements of the unusual woody legume Andira inermis (W. Wright) DC. subsp. inermis (Leguminosae) are discussed; a full botanical description, watercolour illustration and dissection drawings are also provided.

The aim of this study was to articulate the potential of medical computed tomographic (CT) scanning for analyzing soil structure (macroporosity, soil matrix density, number of macropores) and how these estimates compare with, and complement, traditional laboratory measurements (bulk density, total porosity, effective air-filled porosity, and air permeability). Undisturbed soil cores were sampled at two depths (0.35 and 0.7 m) in a long-term soil compaction experiment in southern Sweden 14 years after its establishment. Persistence of subsoil compaction was detectable by CT-estimated soil matrix density, bulk density, and total porosity. Vertical distribution of CT-estimated airfilled macroporosity between 0.25- and 0.45-m depth showed that biologicalactivity effect on macroporosity was largest in the top of the soil columns from the compacted plots, whereas reduction of macroporosity was significant at the bottom of the same columns. This was not detectable by classical laboratory measurements. Variations in air permeability could be related to the CT-estimated number of pores but not to the CT-estimated air-filled macroporosity. Despite using a coarse resolution, the combination of visualization and traditional laboratory measurements proved valuable in identifying the persistent effects of subsoil compaction and the differences in soil structure among the twoinvestigated subsoil layers. However, we recommend to systematically perform a sensitivity analysis to the segmentation threshold before any further analysis of CT-estimated parameters.

Provides an overview of recent developments in the Records Management and IT software vendor sectors, showing the interaction between the two. Presents an overview of record‐keeping requirements based on technical references; an illustrative sample of recent (2001‐2004) events, which provide an overview of trends in the IT software market; show the impact of regulations and newly introduced standards in driving user demand; and how that influences the vendors. Provides reference information, summarizes the key points and draws conclusions. Recognizes the impact that well‐informed records management professionals, by applying current standards, have on influencing the evolution of products and the approach taken by software providers. Provides an interesting, slightly provocative new perspective on events which might otherwise go unremarked, with food for thought, and highlights the current importance and influence of records management professionals.

Extended abstract of a paper presented at Microscopy and Microanalysis 2012 in Phoenix, Arizona, USA, July 29 – August 2, 2012.

The use of photons to create intricate three-dimensional and buried structures [1] in photo-structurable glass has been well demonstrated at several institutions [2]. In these instances the glass used whether it be Foturan™, made by the Schott Group or a similar product made by Corning Glass, forms a silver nucleation sites on exposure to intense UV laser light via a two-photon process. Subsequent annealing causes a localized crystal growth to form a meta-silicate phase which can be etched in dilute hydrofluoric acid at rates of 20 to 50 times that of the unprocessed glass. The same formulation of glass can be “exposed” using a particle beam to create the nucleation site. In the case of particle beam exposure, experiments have shown that the mechanisms that cause this initial nucleation and eventual stochiometric transformation, after annealing, depend largely on the beam energy.