General Electric (Norway)

Drought is a worldwide phenomenon that originates from a prolonged deficiency in precipitation, often combined with high evaporation, over an extended region. The resultant meteorological water balance deficiency may cause a hydrological drought to develop into below normal levels of streamflow, lakes, and groundwater. Contemporary knowledge and experiences from an international team of drought experts are consolidated in a textbook (Tallaksen et al., 2023), which builds on an earlier edition (URL 1), however with significant new material added. An updated synthesis was needed because of hydrological drought-issues that has been emerged over the last 15 years, particularly when much of the topic is currently dominated by climate and climatology approaches. The textbook consists of three parts; Part I (Drought as a natural hazard) discusses the drought phenomenon, its main features, regional diversity and controlling processes. Part II (Estimation methods) presents contemporary approaches to drought estimation, including data and hydrological drought characteristics, statistical analysis of drought series, incl. frequency analysis, time series analysis and regionalization procedures, as well as process-based modelling. Part III (Living with drought) addresses aspects related to the interactions between water and people. Topics include historical and future drought, how human interventions influence drought, drought impacts and Drought Early Warning Systems. Knowledge and experiences shared in the book are from regions all over the world although somewhat biased to Europe and rivers that flow most of the year.This presentation aims to introduce the textbook, its motivation and content to a wide audience. The textbook is supported with worked examples and self-guided tours that are elaborated more extensively on Github. Worked examples include online procedures, code, and details of the calculation procedure that enable readers to repeat calculations in a stepwise manner, either with their own data or by using online datasets, and we encourage user’s feedbacks and experiences in testing these. Self-guided tours are demonstrations of advanced methodologies that involve several calculation steps and are given as an online presentations. Four datasets are included on Github; an international, a regional and two local datasets. The international dataset illustrates the drought phenomenon and its diversity across the world, whereas regional data and local aspects of drought are studied using a combination of hydroclimatological time series and catchment information. Hopefully, the textbook will contribute to an increased awareness of one of our main natural hazards, and thereby increase the preparedness and resilience of society to drought. ReferencesURL 1: http://europeandroughtcentre.com/resources/hydrological-drought-1st-edition/ Tallaksen, L.M., Van Lanen, H.A.J., Hannaford, J., Hisdal, H., Kingston, D.G., Laaha, G., Prudhomme, C., Stagge, J.H., Stahl, K., Van Loon, A.F., Wanders, N., Barker, L.J., Blauhut, V., Bloomfield, J.P., Cammalleri, C., Engeland, K., Everard, N., Facer-Childs, K., Fendeková, M., Fry, M., Gauster, T., Harrigan, S., Ionita, M., Marsh, T., Muchan, K., Ngongondo, C., Parry, S., Rees, G., Sauquet, E., Vidal, J-P. and Vogt, J. (2023). Hydrological Drought. Processes and Estimation Methods for Streamflow and Groundwater. Elsevier Publisher.

BACKGROUND: Iodinated contrast media cause both immediate and nonimmediate hypersensitivity reactions. The aim of this prospective study was to determine the specificity and sensitivity of skin tests in patients who have experienced such reactions. METHODS: Skin prick, intradermal and patch tests with a series of contrast media were conducted in 220 patients with either immediate or nonimmediate reaction. Positive skin tests were defined according to internationally accepted guidelines. Seventy-one never-exposed subjects and 11 subjects who had tolerated contrast medium exposure, served as negative controls. RESULTS: Skin test specificity was 96-100%. For tests conducted within the time period from 2 to 6 months after the reaction, up to 50% of immediate reactors and up to 47% of nonimmediate reactors were skin test positive. For immediate reactors, the intradermal tests were the most sensitive, whereas delayed intradermal tests in combination with patch tests were needed for optimal sensitivity in nonimmediate reactors. Contrast medium cross-reactivity was more common in the nonimmediate than in the immediate group. Interestingly, 49% of immediate and 52% of nonimmediate symptoms occurred in previously unexposed patients. Many of these patients were skin test positive, indicating that they were already sensitized at the time of first contrast medium exposure. CONCLUSIONS: These data suggest that at least 50% of hypersensitivity reactions to contrast media are caused by an immunological mechanism. Skin testing appears to be a useful tool for diagnosis of contrast medium allergy and may play an important role in selection of a safe product in previous reactors.

Medical image computing researchers often face the problem of moving promising new algorithms from the proof of concept stage into a form compatible with clinical use. Algorithm developers lack the time and resources to engineer their code for robustness and compatibility, while end-users are anxious to try new techniques but require well designed and tested user interfaces to make practical use of them. The NA-MIC Kit is a collection of software and methodology specifically designed to address these problems and facilitate the rapid advancement of the field

This paper provides a self-healing strategy to deal with catastrophic events when power system vulnerability analysis indicates that the system is approaching an extreme emergency state. In the authors' approach, the system is adaptively divided into smaller islands with consideration of quick restoration. Then, a load shedding scheme based on the rate of frequency decline is applied. The proposed scheme is tested on a 179-bus, 20-generator sample system and shows very good performance.

Improved safety is one of the main drivers for microreactor application in chemical process development and small-scale production.

Abstract Deep-learning methods have proved successful recently for solving problems in image analysis and natural language processing. One of these methods, convolutional neural networks (CNNs), is revolutionizing the field of image analysis and pushing the state of the art. CNNs consist of layers of convolutions with trainable filters. The input to the network is the raw image or seismic amplitudes, removing the need for feature/attribute engineering. During the training phase, the filter coefficients are found by iterative optimization. The network thereby learns how to compute good attributes to solve the given classification task. However, CNNs require large amounts of training data and must be carefully designed and trained to perform well. We look into the intuition behind this method and discuss considerations that must be made in order to make the method reliable. In particular, we discuss how deep learning can be used for automated seismic interpretation. As an example, we show how a CNN can be used for automatic interpretation of salt bodies.

High-frequency electrostatic waves have been observed in a two-electron-temperature plasma. Both bi-Maxwellian and Maxwellian-waterbag models were found to be inadequate in explaining the observed dispersion and damping rates. However, modelling of the hot electron component with a κ-distribution function confirms that the experiments represent observation of the electron-acoustic wave in the laboratory.

Abstract Surface-related multiples (i.e., all seismic waves reflected at the free surface at least once) often severely contaminate seismic recordings. Because conventional imaging techniques require input data that consist of primary reflections only, significant processing effort is commonly dedicated to attenuating multiples prior to migration. On the other hand, surface-related multiples provide additional illumination of the subsurface and, therefore, should not be considered as noise. We present a prestack depth-migration method that allows primary and multiple reflections to be imaged simultaneously. Depth imaging using primary and multiple reflections (DIPMR) involves decomposing the datainto upgoing and downgoing wave constituents, followed by downward extrapolation. Artifacts generated by interference of upgoing and downgoing events not associated with the same subsurface reflection points (crosstalk) are attenuated by using a 2D deconvolution imaging condition. In contrast to existing methods, DIPMR does not require a priori information about the source signature or directivity, because the illuminating source wavefield is extracted directly from the data themselves via the up/down separation. Moreover, there is no need for elimination nor identification of multiples prior to migration. By including surface-related multiples in the imaging procedure, the effective source wavefield is stronger, the spatial aperture is wider, and a higher vertical resolution is enabled through the application of a deconvolution-based imaging condition.

One of the challenges of optimizing signal-to-noise ratio (SNR) and image quality in (13)C metabolic imaging using hyperpolarized (13)C-pyruvate is associated with the different MR signal time-courses for pyruvate and its metabolic products, lactate and alanine. The impact of the acquisition time window, variation of flip angles, and order of phase encoding on SNR and image quality were evaluated in mathematical simulations and rat experiments, based on multishot fast chemical shift imaging (CSI) and three-dimensional echo-planar spectroscopic imaging (3DEPSI) sequences. The image timing was set to coincide with the peak production of lactate. The strategy of combining variable flip angles and centric phase encoding (cPE) improved image quality while retaining good SNR. In addition, two aspects of EPSI sampling strategies were explored: waveform design (flyback vs. symmetric EPSI) and spectral bandwidth (BW = 500 Hz vs. 267 Hz). Both symmetric EPSI and reduced BW trended toward increased SNR. The imaging strategies reported here can serve as guidance to other multishot spectroscopic imaging protocols for (13)C metabolic imaging applications.

The quality of ultrasound color flow images is highly dependent on sufficient attenuation of the clutter signals originating from stationary and slowly moving tissue. Without sufficient clutter rejection, the detection of low velocity blood flow will be poor, and the velocity estimates will have a large bias. In some situations, e.g., when imaging the coronary arteries or when the operator moves the probe in search for small vessels, there is considerable movement of tissue. It has been suggested that clutter rejection can be improved by mixing down the signal with an estimate of the mean frequency prior to high pass filtering. In this paper, we compare this algorithm with several other adaptive clutter filtering algorithms using both experimental data and simulations. We found that realistic accelerations of the tissue have a large effect on the clutter rejection. The best results were obtained by mixing down the signal with non-constant phase increments estimated from the signal. This adapted the filter to a possibly accelerated tissue motion and produced a significant improvement in clutter rejection.

BACKGROUND: Breastfeeding confers substantial benefits to child health and has also been associated with lower risk of maternal cardiovascular diseases (CVDs) in later life. However, the evidence on the effects of CVD is still inconsistent, especially in East Asians, in whom the frequency and duration of breastfeeding significantly differ from those in the West. METHODS AND RESULTS: In 2004-2008, the nationwide China Kadoorie Biobank recruited 0.5 million individuals aged 30 to 79 years from 10 diverse regions across China. During 8 years of follow-up, 16 671 incident cases of coronary heart disease and 23 983 cases of stroke were recorded among 289 573 women without prior CVD at baseline. Cox regression yielded adjusted hazard ratios (HRs) and 95% CIs for incident CVD by breastfeeding. Overall, ≈99% of women had given birth, among whom 97% reported a history of breastfeeding, with a median duration of 12 months per child. Compared with parous women who had never breastfed, ever breastfeeding was associated with a significantly lower risk of CVD, with adjusted HRs of 0.91 (95% CI, 0.84-0.99) for coronary heart disease and 0.92 (95% CI, 0.85-0.99) for stroke. Women who had breastfed for ≥24 months had an 18% (HR, 0.82; 0.77-0.87) lower risk of coronary heart disease and a 17% (HR, 0.83; 0.79-0.87) lower risk of stroke compared with women who had never breastfed. Among women who ever breastfed, each additional 6 months of breastfeeding per child was associated with an adjusted HR of 0.96 (95% CI, 0.94-0.98) for coronary heart disease and 0.97 (95% CI, 0.96-0.98) for stroke. CONCLUSIONS: Among Chinese women, a history of breastfeeding was associated with an ≈10% lower risk of CVD in later life and the magnitude of the inverse association was stronger among those with a longer duration of breastfeeding.

This guideline on current good radiopharmacy practice (cGRPP) for small-scale preparation of radiopharmaceuticals represents the view of the Radiopharmacy Committee of the European Association of Nuclear Medicine (EANM). The guideline is laid out in the format of the EU Good Manufacturing Practice (GMP) guidelines as defined in EudraLex volume 4. It is intended for non-commercial sites such as hospital radiopharmacies, nuclear medicine departments, research PET centres and in general any healthcare establishments. In the first section, general aspects which are applicable to all levels of operations are discussed. The second section discusses the preparation of small-scale radiopharmaceuticals (SSRP) using licensed generators and kits. Finally, the third section goes into the more complex preparation of SSRP from non-licensed starting materials, often requiring a purification step and sterile filtration. The intention is that the guideline will assist radiopharmacies in the preparation of diagnostic and therapeutic SSRP's safe for human administration.

Abstract Finite-difference (FD) techniques are widely used to model wave propagation through complex structures. Two main sources of error can be identified: (1) from numerical dispersion and numerical anisotropy and (2) by modeling the response of internal grid boundaries. Conventional discretization criteria to reduce the effects of numerical dispersion and numerical anisotropy have long been established (5–8 gridpoints per wavelength for a fourth-order accurate FD scheme). We analyze the second source of errors, comparing different staggered-grid FD solutions to the Cagniard-de Hoop solution in models with fluid–solid contacts. Our results confirm that it is sufficient to rely on conventional discretization criteria if the fluid–solid interface is aligned with the grid. If accurate modeling of the Scholte wave is required, then a new imaging method we propose should be used to allow for conventional sampling of the wavefield to minimize numerical dispersion. However, for an interface not aligned with the grid (irregular interfaces), a spatial sampling of at least 15 gridpoints per minimum wavelength is required to obtain acceptable results, particularly in seismic seabed applications where Scholte waves may need to be modeled more accurately.

This paper describes the system integration and performance evaluation testing of a high speed, 250 kW starter/generator [S/G] system used for starting and secondary electrical power extraction from an aircraft propulsion gas turbine. The effort described here is part a contract sponsored by the USAF, Wright Laboratories, WPAFB. The paper describes a switched reluctance [SR] machine which is operating both as a motor and generator in a speed range of 0 to 22,224 r.p.m. Additionally it is one of the highest rated motor/generator systems in the SR technology. The system employs two independent channels consisting of two groups of three phase windings, two three phase inverters, and two controllers and can provide two different power output buses for independent loading. The system hardware is described briefly followed by a detail description of the test results. These show some surprises with regards to single channel operating mode. A brief derivation and explanation of the findings is provided. The motor/generator system is planned to be part of a more electric aircraft power system.

Abstract The anisotropy of physical properties is a well-known characteristic of many clay-bearing rocks. This anisotropy has important implications for elastic properties of rocks and must be considered in seismic modeling. Preferred orientation of clay minerals is an important factor causing anisotropy in clay-bearing rocks such as shales and mudstones that are the main cap rocks of oil reservoirs. The preferred orientation of clays depends mostly on the amount of clays and the degree of compaction. To study the effect of these parameters, we prepared several samples compressing (at two effective vertical stresses) a mixture of clays (illite and kaolinite) and quartz (silt) with different clay/quartz ratios. The preferred orientation of the phases was quantified with Rietveld analysis on synchrotron hard X-ray images. Pole figures for kaolinite and illite display a preferred orientationof clay platelets perpendicular to the compaction direction, increasing in strength with clay content and compaction pressure. Quartz particles have a random orientation distribution. Aggregate elastic properties can be estimated by averaging the single-crystal properties over the orientation distribution obtained from the diffraction data analysis. Calculated P-wave velocity anisotropy ranges from 0% (pure quartz sample) to 44% (pure clay sample, highly compacted), but calculated velocities are much higher than measured velocities. This is attributed to uncertainties about single-crystal elastic properties and oriented micropores and limited grain contacts that are not accounted for in the model. In this work, we present an effective method to obtain quantitative data, helping to evaluate the role of clay percentage and compaction pressure on the anisotropy of elastic properties of clay-bearing rocks.

Two puzzling traits of giant rock avalanches (sturzstroms) are the decrease of the effective friction coefficient as a function of the volume (volume effect) and the remarkable preservation of large geological structures during the flow, demonstrating that the upper cap of a sturzstrom travels coherently on top of a basal shear layer. Hence, frictional heat is rapidly produced along the shear layer, which could explain the formation of sheets of molten rock inside certain landslide deposits. It has been conjectured that a molten layer could potentially self‐lubricate the base of the sturzstrom. To theoretically investigate this scenario, we consider the model of a rock slab sliding on an inclined surface. We present a set of coupled differential equations to calculate the frictional heat produced, the properties of the molten layer (thickness, temperature, and velocity distribution), and the motion of the slab. Our simulations illustrate the onset of self‐lubrication and show the volume effect when the melt viscosity is low, corresponding to a simulated mafic composition of the rock. For a felsic composition (and to some extent also for intermediate melts) we find that the melting introduces more resistance at the beginning of the melting process, in close similarity with frictional melting in tectonic faults. However, in contrast to faults, the rock avalanche is capable of overcoming the initial resistance in at least two situations: if the rock is rigid and the landslide is sufficiently thick or else if the material of the landslide is disintegrated. The simulations also show that although self‐lubrication is a viable possibility to explain the runout of sturzstroms, there are rather stringent conditions for the formation of a molten layer of good lubricating qualities. More generally, we suggest that the properties of the Coulomb frictional law at the interfaces may change radically during sliding and that the assumption of constant friction does not represent a good model in landslide calculations.

OBJECTIVES: We sought to evaluate the effect of the particle size and coating material of various iron oxide preparations on the rate of rat liver clearance. MATERIALS AND METHODS: The following iron oxide formulations were used in this study: dextran-coated ferumoxide (size = 97 nm) and ferumoxtran-10 (size = 21 nm), carboxydextran-coated SHU555A (size = 69 nm) and fractionated SHU555A (size = 12 nm), and oxidized-starch coated materials either unformulated NC100150 (size = 15 nm) or formulated NC100150 injection (size = 12 nm). All formulations were administered to 165 rats at 2 dose levels. Quantitative liver R2* values were obtained during a 63-day time period. The concentration of iron oxide particles in the liver was determined by relaxometry, and these values were used to calculate the particle half-lives in the liver. RESULTS: After the administration of a high dose of iron oxide, the half-life of iron oxide particles in rat liver was 8 days for dextran-coated materials, 10 days for carboxydextran materials, 14 days for unformulated oxidized-starch, and 29 days for formulated oxidized-starch. CONCLUSIONS: The results of the study indicate that materials with similar coating but different sizes exhibited similar rates of liver clearance. It was, therefore, concluded that the coating material significantly influences the rate of iron oxide clearance in rat liver.

Abstract trans ‐3‐Sulfonyloxy‐4‐alkylthio‐2‐azetidinone 1 reagieren mit Natriumazid in Dimethylsulfoxid unter Inversion zu cis ‐3‐Azido‐4‐alkylthio‐2‐azetidinonen 2 , die zu den Aminoverbindungen 4 reduziert werden können. Acylierung von 4 liefert die cis ‐3‐Acylamino‐4‐alkylthio‐2‐azetidinone 5 . Die Reaktion der Sulfonyloxygruppe mit weiteren Nucleophilen, wie Halogeniden, Thiocyanaten, Sauerstoffnucleophilen, Thioacetat und anderen wird beschrieben.

Deep learning can bring time savings and increased reproducibility to medical image analysis. However, acquiring training data is challenging due to the time-intensive nature of labeling and high inter-observer variability in annotations. Rather than labeling images, in this work we propose an alternative pipeline where images are generated from existing high-quality annotations using generative adversarial networks (GANs). Annotations are derived automatically from previously built anatomical models and are transformed into realistic synthetic ultrasound images with paired labels using a CycleGAN. We demonstrate the pipeline by generating synthetic 2D echocardiography images to compare with existing deep learning ultrasound segmentation datasets. A convolutional neural network is trained to segment the left ventricle and left atrium using only synthetic images. Networks trained with synthetic images were extensively tested on four different unseen datasets of real images with median Dice scores of 91, 90, 88, and 87 for left ventricle segmentation. These results match or are better than inter-observer results measured on real ultrasound datasets and are comparable to a network trained on a separate set of real images. Results demonstrate the images produced can effectively be used in place of real data for training. The proposed pipeline opens the door for automatic generation of training data for many tasks in medical imaging as the same process can be applied to other segmentation or landmark detection tasks in any modality. The source code and anatomical models are available to other researchers. <xref ref-type="fn" rid="fn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¹</xref> <fn id="fn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><label>¹</label> <uri>https://adgilbert.github.io/data-generation/</uri> </fn>

ABSTRACT For economic and efficiency reasons, blended acquisition of seismic data is becoming increasingly commonplace. Seismic deblending methods are computationally demanding and normally consist of multiple processing steps. Furthermore, the process of selecting parameters is not always trivial. Machine-learning-based processing has the potential to significantly reduce processing time and to change the way seismic deblending is carried out. We have developed a data-driven deep-learning-based method for fast and efficient seismic deblending. The blended data are sorted from the common-source to the common-channel domain to transform the character of the blending noise from coherent events to incoherent contributions. A convolutional neural network is designed according to the special characteristics of seismic data and performs deblending with results comparable to those obtained with conventional industry deblending algorithms. To ensure authenticity, the blending was performed numerically and only field seismic data were used, including more than 20,000 training examples. After training and validating the network, seismic deblending can be performed in near real time. Experiments also indicate that the initial signal-to-noise ratio is the major factor controlling the quality of the final deblended result. The network is also demonstrated to be robust and adaptive by using the trained model to first deblend a new data set from a different geologic area with a slightly different delay time setting and second to deblend shots with blending noise in the top part of the record.