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Laser wakefield accelerators promise to revolutionize many areas of accelerator science. However, one of the greatest challenges to their widespread adoption is the difficulty in control and optimization of the accelerator outputs due to coupling between input parameters and the dynamic evolution of the accelerating structure. Here, we use machine learning techniques to automate a 100 MeV-scale accelerator, which optimized its outputs by simultaneously varying up to six parameters including the spectral and spatial phase of the laser and the plasma density and length. Most notably, the model built by the algorithm enabled optimization of the laser evolution that might otherwise have been missed in single-variable scans. Subtle tuning of the laser pulse shape caused an 80% increase in electron beam charge, despite the pulse length changing by just 1%. Laser wakefield accelerators are compact sources of ultra-relativistic electrons which are highly sensitive to many control parameters. Here the authors present an automated machine learning based method for the efficient multi-dimensional optimization of these plasma-based particle accelerators.

Purpose Physical activity is beneficial across the lifespan, but most Americans do not meet physical activity guidelines. Multiple sources exist that identify opportunities to address gaps in physical activity research knowledge and implementation. Several of these opportunities have important considerations for populations experiencing health inequities. The goal of this study was to identify, synthesize, and categorize opportunities for research (i.e., systematic investigations to develop generalizable knowledge) into a conceptual framework to advance physical activity research in a cohesive and efficient manner. Methods The National Collaborative on Childhood Obesity Research convened subject matter experts to conduct five qualitative document analysis steps: (1) identify sources published by United States government, intergovernmental, or national non-profit organizations related to physical activity, (2) review sources to extract research opportunities, (3) code the opportunities by variables (translational research phase, social ecological level, setting, and priority population) determined by the expert group, (4) synthesize data on similar opportunities, and (5) review crosstabulation data to examine coding patterns and develop a framework. Results Opportunities ( n  = 385) were extracted from sources ( n  = 11) and combined into condensed opportunity statements ( n  = 87). Most called for effectiveness research ( n  = 44, 51%) or dissemination and implementation science research ( n  = 14, 16%). 38% were related to policy, systems, and environmental interventions ( n  = 33), and 70% mentioned community settings ( n  = 61). Additionally, 76% did not include health equity considerations ( n  = 66), and 75% mentioned no specific population or populations across the lifespan ( n  = 65). The resultant Physical Activity Research Opportunities (PARO) framework details opportunities by translational research phase (methods/measures development, etiology, efficacy, effectiveness, dissemination and implementation, and surveillance) and social ecological level (individual or interpersonal, policy/systems/environmental, and crosscutting), including health equity considerations. Conclusions The resultant PARO framework highlights gaps in current evidence and reveals opportunities for physical activity funders, researchers, policymakers, and practitioners to strategically advance their work. There are prospects for designing efficacy and effectiveness trials with an eye toward dissemination and implementation, developing strategies for improving dissemination and implementation, and using community- and practitioner-engaged approaches across translational research phases to advance health equity. Health equity can also be addressed by tailoring interventions, enhancing reach to priority populations, and improving social determinants of health.

Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully emulates simulations in 10 scientific cases including astrophysics, climate science, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more extensive parameters exploration, and enable new, previously unfeasible computational discovery.

Considerable progress towards the achievement of thermonuclear burn using inertial confinement fusion has been achieved at the National Ignition Facility in the USA in the last few years. Other drivers, such as the Z-machine at Sandia, are also making progress towards this goal. A burning thermonuclear plasma would provide a unique and extreme plasma environment; in this paper we discuss (a) different theoretical challenges involved in modelling burning plasmas not currently considered, (b) the use of novel machine learning-based methods that might help large facilities reach ignition, and (c) the connections that a burning plasma might have to fundamental physics, including quantum electrodynamics studies, and the replication and exploration of conditions that last occurred in the first few minutes after the Big Bang. This article is part of a discussion meeting issue ‘Prospects for high gain inertial fusion energy (part 1)’.

A skeletal muscle fiber that is stimulated to contract and then stretched from L₁ to L₂ produces more force after the initial transient decays than if it is stimulated at L₂. This behavior has been well studied experimentally, and is known as residual force enhancement. The underlying mechanism remains controversial. We hypothesized that residual force enhancement could reflect mechanical interactions between heterogeneous half-sarcomeres. To test this hypothesis, we subjected a computational model of interacting heterogeneous half-sarcomeres to the same activation and stretch protocols that produce residual force enhancement in real preparations. Following a transient period of elevated force associated with active stretching, the model predicted a slowly decaying force enhancement lasting >30 seconds after stretch. Enhancement was on the order of 13% above isometric tension at the post-stretch muscle length, which agrees well with experimental measurements. Force enhancement in the model was proportional to stretch magnitude but did not depend strongly on the velocity of stretch, also in agreement with experiments. Even small variability in the strength of half-sarcomeres (2.1% standard deviation, normally distributed) was sufficient to produce a 5% force enhancement over isometric tension. Analysis of the model suggests that heterogeneity in half-sarcomeres leads to residual force enhancement by storing strain energy introduced during active stretch in distributions of bound cross-bridges. Complex interactions between the heterogeneous half-sarcomeres then dissipate this stored energy at a rate much slower than isolated cross-bridges would cycle. Given the variations in half-sarcomere length that have been observed in real muscle preparations and the stochastic variability inherent in all biological systems, half-sarcomere heterogeneity cannot be excluded as a contributing source of residual force enhancement.

Summary Research indicates that most college students are not meeting dietary and physical activity guidelines, and the average student gains an estimated 1.6–3.0 kg during 4 years of study. College administrations are well‐positioned to influence student weight‐related health behaviours by ensuring that campus environments/policies promote health. However, to date, campus health interventions have largely addressed individual and interpersonal factors rather than environmental/policy‐level changes. Using an ecological perspective, this narrative review synthesizes the literature on campus environmental/policy‐level factors (e.g., food availability, physical activity requirements) associated with student diet, physical activity and weight, as well as campus interventions to address these factors. Web of Science and PubMed databases were searched between December 2018 and November 2019. Results indicate that campus food environments may contribute to overconsumption and weight gain, and the number of campuses requiring students to participate in physical activity courses is in decline. Eight examples of environmental/policy‐level campus interventions are presented: nutrition labels in dining halls, campus‐wide healthy choice marketing campaigns, restricted payment methods for à la cart dining, trayless dining, health‐themed residence halls, peer health education programmes, active classroom spaces and physical activity course requirements. Implications for research and health promotion programmes/policies in the field of college health are discussed.

We describe a laser–plasma platform for photon–photon collision experiments to measure fundamental quantum electrodynamic processes. As an example we describe using this platform to attempt to observe the linear Breit–Wheeler process. The platform has been developed using the Gemini laser facility at the Rutherford Appleton Laboratory. A laser Wakefield accelerator and a bremsstrahlung convertor are used to generate a collimated beam of photons with energies of hundreds of MeV, that collide with keV x-ray photons generated by a laser heated plasma target. To detect the pairs generated by the photon–photon collisions, a magnetic transport system has been developed which directs the pairs onto scintillation-based and hybrid silicon pixel single particle detectors (SPDs). We present commissioning results from an experimental campaign using this laser–plasma platform for photon–photon physics, demonstrating successful generation of both photon sources, characterisation of the magnetic transport system and calibration of the SPDs, and discuss the feasibility of this platform for the observation of the Breit–Wheeler process. The design of the platform will also serve as the basis for the investigation of strong-field quantum electrodynamic processes such as the nonlinear Breit–Wheeler and the Trident process, or eventually, photon–photon scattering.

Objective Social media are promising channels for health communication promoting positive weight‐related behaviors, but no prior studies have synthesized evidence on the independent effects of social media campaigns focused on promoting healthy eating, physical activity (PA), and healthy weight. This study aimed to fill that gap and inform future social media‐based obesity‐prevention research and practice by reviewing findings from studies testing the effects of such campaigns on individual‐level cognitive, behavioral, and anthropometric outcomes. Method The Web of Science and PubMed databases were searched for peer‐reviewed articles published between 2012 and 2023 that explored the independent effects of social media campaigns related to healthy eating, PA, or weight management. Study characteristics and outcomes were extracted and summarized. Results Eleven studies were included in this review describing campaigns targeting healthy eating‐related outcomes (e.g., fruit and vegetable consumption, meal preparation, nutrition label reading), PA, or weight management. Most campaigns (n = 7) were developed by universities or research centers. Priority audiences included parents, adult females, adolescents, college students, and adult government employees. The majority (n = 8) of the campaigns used single platforms, with the most common being Facebook, Instagram, blogs, and YouTube. Campaigns had mixed effects on cognitive outcomes (e.g., intention, attitude, knowledge), behavioral outcomes (e.g., food choices, PA), and anthropometric outcomes (e.g., weight, waist circumference). Conclusion Social media campaigns focused on promoting healthy eating, PA, and healthy weight had mixed effects on individual‐level cognitive, behavioral, and anthropometric outcomes. Various limitations of the included studies make it difficult to ascertain which factors influence campaign effectiveness. Advancing knowledge in this area is important, particularly given social media's widespread use and potential for broad reach. New research with features such as rigorous study designs, larger and more diverse samples, and strong theoretical foundations may provide important insights into what types of interventions are effective or not and under what conditions.

Theory-informed strategies for engaging parents in children's physical activity (PA) promotion show promise. However, behavior-change interventions must become more rigorous in both their application of theory and the reporting of its use to continue to advance the field. This study aims to elucidate how 2 behavior change theories were used to develop parent communication materials in a 20-week communications campaign, nested within a multilevel (school-home) intervention to promote children's PA. The innovation described in this study is derived from the Supporting Physical Literacy at School and Home (SPLASH) feasibility study (2021-2022). A team of 7 experts, including graduate students, researchers, faculty, and child PA specialists, collaboratively designed the process used to develop the intervention content. With experience in theory-informed interventions and health-related communication campaigns, they held recurring meetings to refine the approach. A four-step process was used to develop the theory-informed parent communication materials: (1) establish a theoretical foundation for communication materials (ie, social cognitive theory and self-determination theory) and conduct focus groups with the priority population; (2) identify and select PA parenting behaviors aligned with evidence and behavioral theories to form PA parenting objectives that advance children's PA; (3) identify theoretical determinants of parent behavior change and outline methods for applying determinants to address PA parenting objectives; (4) operationalize theory-informed strategy and draft, review, and finalize materials. Parent communications were delivered through print materials and electronic channels, including email, text messages, Facebook (Meta Platforms, Inc), and activity videos. This descriptive study advances progress in the development of school-based PA promotion efforts seeking to incorporate parent engagement strategies by detailing how behavior-change theories can be operationalized to improve PA parenting behaviors. This methodology is valuable for others seeking to translate theoretical constructs into behavior-change communication messages.

Background: Patients with advanced renal failure are increasingly opting for conservative treatment, yet little is known of their palliative care needs. Methods: We performed a cross-sectional study, examining symptom burden and quality of life in patients with advanced renal failure (estimated GFR < 17 mL/min; n = 11). A contemporary cohort with terminal malignancy acted as comparators (n = 11). Symptom burden was scored using an extended Memorial Symptom Assessment Scale Short Form questionnaire. Quality of life was assessed using the Euroqol-5Q questionnaire. Demographic and pathological data, performance status and co-morbidity were also recorded. Results: Baseline characteristics were similar for the two groups. Symptom burden (renal 17; cancer 15; P =NS) and quality of life scores (renal 60; cancer 60; P =NS) were remarkably similar. Both groups reported high levels of psychological distress. Conclusions: Patients with advanced renal failure experience a symptom burden and impairment of quality of life similar to that of patients with terminal malignancy.