Policy gradient methods for free-electron laser and terahertz source optimization and stabilization at the FERMI free-electron laser at Elettra

In this article we report on the application of a model-free reinforcement learning method to the optimization of accelerator systems. We simplify a policy gradient algorithm to accelerator control from sophisticated algorithms that have recently been demonstrated to solve complex dynamic problems. After outlining a theoretical basis for the functioning of the algorithm, we explore the small hyperparameter space to develop intuition about said parameters using a simple number-guess environment. Finally, we demonstrate the algorithm optimizing both a free-electron laser and an accelerator-based terahertz source in-situ. The algorithm is applied to different accelerator control systems and optimizes the desired signals in a few hundred steps without any domain knowledge using up to five control parameters. In addition, the algorithm shows modest tolerance to accelerator fault conditions without any special preparation for such conditions

Resilient VAE: Unsupervised Anomaly Detection at the SLAC Linac Coherent Light Source

Significant advances in utilizing deep learning for anomaly detection have been made in recent years. However, these methods largely assume the existence of a normal training set (i.e., uncontaminated by anomalies) or even a completely labeled training set. In many complex engineering systems, such as particle accelerators, labels are sparse and expensive; in order to perform anomaly detection in these cases, we must drop these assumptions and utilize a completely unsupervised method. This paper introduces the Resilient Variational Autoencoder (ResVAE), a deep generative model specifically designed for anomaly detection. ResVAE exhibits resilience to anomalies present in the training data and provides feature-level anomaly attribution. During the training process, ResVAE learns the anomaly probability for each sample as well as each individual feature, utilizing these probabilities to effectively disregard anomalous examples in the training data. We apply our proposed method to detect anomalies in the accelerator status at the SLAC Linac Coherent Light Source (LCLS). By utilizing shot-to-shot data from the beam position monitoring system, we demonstrate the exceptional capability of ResVAE in identifying various types of anomalies that are visible in the accelerator

Coincident Learning for Unsupervised Anomaly Detection

Anomaly detection is an important task for complex systems (e.g., industrial facilities, manufacturing, large-scale science experiments), where failures in a sub-system can lead to low yield, faulty products, or even damage to components. While complex systems often have a wealth of data, labeled anomalies are typically rare (or even nonexistent) and expensive to acquire. Unsupervised approaches are therefore common and typically search for anomalies either by distance or density of examples in the input feature space (or some associated low-dimensional representation). This paper presents a novel approach called CoAD, which is specifically designed for multi-modal tasks and identifies anomalies based on \textit{coincident} behavior across two different slices of the feature space. We define an \textit{unsupervised} metric, $\hat{F}_\beta$, out of analogy to the supervised classification $F_\beta$ statistic. CoAD uses $\hat{F}_\beta$ to train an anomaly detection algorithm on \textit{unlabeled data}, based on the expectation that anomalous behavior in one feature slice is coincident with anomalous behavior in the other. The method is illustrated using a synthetic outlier data set and a MNIST-based image data set, and is compared to prior state-of-the-art on two real-world tasks: a metal milling data set and a data set from a particle accelerator

The Anatomical Society core embryology syllabus for undergraduate medicine

A modified Delphi methodology was used to develop a consensus regarding a series of learning outcome statements to act as the foundation of an undergraduate medical core embryology syllabus. A Delphi panel was formed by recruiting stakeholders with experience in leading undergraduate teaching of medical students. The panel (n = 18), including anatomists, embryologists and practising clinicians, were nominated by members of Council and/or the Education Committee of the Anatomical Society. Following development of an a priori set of learning outcome statements (n = 62) by the authors, panel members were asked in the first of a two‐stage process to ‘accept’, ‘reject’ or ‘modify’ each learning outcome, to propose additional outcomes if desired. In the second stage, the panel was asked to either accept or reject 16 statements which had either been modified, or had failed to reach consensus, during the first Delphi round. Overall, 61 of 62 learning outcome statements, each linked to examples of clinical conditions to provide context, achieved an 80% level of agreement following the modified Delphi process and were therefore deemed accepted for inclusion within the syllabus. The proposed syllabus allows for flexibility within individual curricula, while still prioritising and focusing on the core level of knowledge of embryological processes by presenting the essential elements to all newly qualified doctors, regardless of their subsequent chosen specialty

The influence of time to adrenaline administration in the Paramedic 2 randomised controlled trial

Abstract: Purpose: To examine the time to drug administration in patients with a witnessed cardiac arrest enrolled in the Pre-Hospital Assessment of the Role of Adrenaline: Measuring the Effectiveness of Drug Administration in Cardiac Arrest (PARAMEDIC2) randomised controlled trial. Methods: The PARAMEDIC2 trial was undertaken across 5 NHS ambulance services in England and Wales with randomisation between December 2014 and October 2017. Patients with an out-of-hospital cardiac arrest who were unresponsive to initial resuscitation attempts were randomly assigned to 1 mg intravenous adrenaline or matching placebo according to treatment packs that were identical apart from treatment number. Participants and study staff were masked to treatment allocation. Results: 8016 patients were enrolled, 4902 sustained a witnessed cardiac arrest of whom 2437 received placebo and 2465 received adrenaline. The odds of return of spontaneous circulation decreased in both groups over time but at a greater rate in the placebo arm odds ratio (OR) 0.93 (95% CI 0.92–0.95) compared with the adrenaline arm OR 0.96 (95% CI 0.95–0.97); interaction OR: 1.03, 95% CI 1.01–1.05, p = 0.005. By contrast, although the rate of survival and favourable neurological outcome decreased as time to treatment increased, the rates did not differ between the adrenaline and placebo groups. Conclusion: The rate of return of spontaneous circulation, survival and favourable neurological outcomes decrease over time. As time to drug treatment increases, adrenaline increases the chances of return of spontaneous circulation. Longer term outcomes were not affected by the time to adrenaline administration. (ISRCTN73485024)

Breaking the Attosecond, Angstrom and TV/M Field Barriers with Ultra-Fast Electron Beams

Recent initiatives at UCLA concerning ultra-short, GeV electron beam generation have been aimed at achieving sub-fs pulses capable of driving X-ray free-electron lasers (FELs) in single-spike mode. This use of very low Q beams may allow existing FEL injectors to produce few-100 attosecond pulses, with very high brightness. Towards this end, recent experiments at the LCLS have produced {approx}2 fs, 20 pC electron pulses. We discuss here extensions of this work, in which we seek to exploit the beam brightness in FELs, in tandem with new developments in cryogenic undulator technology, to create compact accelerator-undulator systems that can lase below 0.15 {angstrom}, or be used to permit 1.5 {angstrom} operation at 4.5 GeV. In addition, we are now developing experiments which use the present LCLS fs pulses to excite plasma wakefields exceeding 1 TV/m, permitting a table-top TeV accelerator for frontier high energy physics applications

Comparative Genomics of the Mating-Type Loci of the Mushroom Flammulina velutipes Reveals Widespread Synteny and Recent Inversions

Mating-type loci of mushroom fungi contain master regulatory genes that control recognition between compatible nuclei, maintenance of compatible nuclei as heterokaryons, and fruiting body development. Regions near mating-type loci in fungi often show adapted recombination, facilitating the generation of novel mating types and reducing the production of self-compatible mating types. Compared to other fungi, mushroom fungi have complex mating-type systems, showing both loci with redundant function (subloci) and subloci with many alleles. The genomic organization of mating-type loci has been solved in very few mushroom species, which complicates proper interpretation of mating-type evolution and use of those genes in breeding programs.We report a complete genetic structure of the mating-type loci from the tetrapolar, edible mushroom Flammulina velutipes mating type A3B3. Two matB3 subloci, matB3a that contains a unique pheromone and matB3b, were mapped 177 Kb apart on scaffold 1. The matA locus of F. velutipes contains three homeodomain genes distributed over 73 Kb distant matA3a and matA3b subloci. The conserved matA region in Agaricales approaches 350 Kb and contains conserved recombination hotspots showing major rearrangements in F. velutipes and Schizophyllum commune. Important evolutionary differences were indicated; separation of the matA subloci in F. velutipes was diverged from the Coprinopsis cinerea arrangement via two large inversions whereas separation in S. commune emerged through transposition of gene clusters.In our study we determined that the Agaricales have very large scale synteny at matA (∼350 Kb) and that this synteny is maintained even when parts of this region are separated through chromosomal rearrangements. Four conserved recombination hotspots allow reshuffling of large fragments of this region. Next to this, it was revealed that large distance subloci can exist in matB as well. Finally, the genes that were linked to specific mating types will serve as molecular markers in breeding

CNS targets of adipokines

This is the author accepted manuscript. The final version is available from American Physiological Society via the DOI in this record.Our understanding of adipose tissue as an endocrine organ has been transformed over the last twenty years. During this time a number of adipocyte-derived factors or adipokines have been identified. This paper will review evidence for how adipokines acting via the central nervous system (CNS) regulate normal physiology and disease pathology. The reported CNS-mediated effects of adipokines are varied and include the regulation of energy homeostasis, autonomic nervous system activity, the reproductive axis, neurodevelopment, cardiovascular function, and cognition. Due to the wealth of information available and the diversity of their known functions, the archetypal adipokines leptin and adiponectin will be the focused on extensively. Other adipokines with established CNS actions will also be discussed. Due to the difficulties associated with studying CNS function on a molecular level in humans, the majority of our knowledge, and as such the studies described in this paper, comes from work in experimental animal models; however, where possible the relevant data from human studies are also highlighted

Implementation of corticosteroids in treating COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK:prospective observational cohort study

BACKGROUND: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. METHODS: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. FINDINGS: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70–0·89], p=0·0001, for 70–79 years; 0·52 [0·46–0·58], p80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75–80% in January, 2021. INTERPRETATION: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. FUNDING: UK National Institute for Health Research and UK Medical Research Council