Explore the vast range of titles available.

The description of the dynamics of an electron in an external electromagnetic field of arbitrary intensity is one of the most fundamental outstanding problems in electrodynamics. Remarkably, to date, there is no unanimously accepted theoretical solution for ultrahigh intensities and little or no experimental data. The basic challenge is the inclusion of the self-interaction of the electron with the field emitted by the electron itself—the so-called radiation reaction force. We report here on the experimental evidence of strong radiation reaction, in an all-optical experiment, during the propagation of highly relativistic electrons (maximum energy exceeding 2 GeV) through the field of an ultraintense laser (peak intensity of4×1020W/cm2). In their own rest frame, the highest-energy electrons experience an electric field as high as one quarter of the critical field of quantum electrodynamics and are seen to lose up to 30% of their kinetic energy during the propagation through the laser field. The experimental data show signatures of quantum effects in the electron dynamics in the external laser field, potentially showing departures from the constant cross field approximation.

The dynamics of energetic particles in strong electromagnetic fields can be heavily influenced by the energy loss arising from the emission of radiation during acceleration, known as radiation reaction. When interacting with a high-energy electron beam, today’s lasers are sufficiently intense to explore the transition between the classical and quantum radiation reaction regimes. We present evidence of radiation reaction in the collision of an ultrarelativistic electron beam generated by laser-wakefield acceleration (ϵ>500MeV) with an intense laser pulse (a0>10). We measure an energy loss in the postcollision electron spectrum that is correlated with the detected signal of hard photons (γrays), consistent with a quantum description of radiation reaction. The generatedγrays have the highest energies yet reported from an all-optical inverse Compton scattering scheme, with critical energyϵcrit>30MeV.

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.

Two signatures of quantum effects on radiation reaction in the collision of a ${\\sim}$ GeV electron beam with a high intensity ( ${>}3\\times 10^{20}~\\text{W}~\\text{cm}^{-2}$ ) laser pulse have been considered. We show that the decrease in the average energy of the electron beam may be used to measure the Gaunt factor $g$ for synchrotron emission. We derive an equation for the evolution of the variance in the energy of the electron beam in the quantum regime, i.e. quantum efficiency parameter $\\unicode[STIX]{x1D702}\\not \\ll 1$ . We show that the evolution of the variance may be used as a direct measure of the quantum stochasticity of the radiation reaction and determine the parameter regime where this is observable. For example, stochastic emission results in a 25 % increase in the standard deviation of the energy spectrum of a GeV electron beam, 1 fs after it collides with a laser pulse of intensity $10^{21}~\\text{W}~\\text{cm}^{-2}$ . This effect should therefore be measurable using current high-intensity laser systems.

ABSTRACT BACKGROUND The Congress of Neurological Surgeons reviews its guidelines according to the Institute of Medicine's recommended best practice of reviewing guidelines every 5 yrs. The authors performed a planned 5-yr review of the medical literature used to develop the “Pediatric hydrocephalus: systematic literature review and evidence-based guidelines” and determined the need for an update to the original guideline based on new available evidence. OBJECTIVE To perform an update to include the current medical literature for the “Pediatric hydrocephalus: systematic literature review and evidence-based guidelines”, originally published in 2014. METHODS The Guidelines Task Force used the search terms and strategies consistent with the original guidelines to search PubMed and Cochrane Central for relevant literature published between March 2012 and November 2019. The same inclusion/exclusion criteria were also used to screen abstracts and to perform the full-text review. Full text articles were then reviewed and when appropriate, included as evidence and recommendations were added or changed accordingly. RESULTS A total of 41 studies yielded by the updated search met inclusion criteria and were included in this update. CONCLUSION New literature resulting from the update yielded a new recommendation in Part 2, which states that neuro-endoscopic lavage is a feasible and safe option for the removal of intraventricular clots and may lower the rate of shunt placement (Level III). Additionally a recommendation in part 7 of the guideline now states that antibiotic-impregnated shunt tubing reduces the risk of shunt infection compared with conventional silicone hardware and should be used for children who require placement of a shunt (Level I).

A machine-learning method to assess DNA can accurately classify brain tumours in real time. This rapid analysis might help surgeons to identify the tumour type when operating and to adjust their surgical strategy accordingly. DNA methylation assessed to classify tumours during an operation. Credit: Reza Estakhrian/Getty Female brain surgeon in operation, nurses standing by.

BACKGROUND:The incidence of spina bifida (SB) in the developing world is higher than in the United States because of malnutrition and folic acid deficiency during pregnancy. Advances in technology have made prenatal repair of myelomeningocele (MM) possible. OBJECTIVE:The objective of the guidelines are, (1) To create clinical recommendations for best practices, based on a systematic review and analysis of available literature, (2) to obtain multi-disciplinary endorsement of these guidelines from relevant organizations, and (3) to disseminate the educational content to physicians to improve the care of infants with MM. METHODS:The Guidelines Task Force developed search terms and strategies used to search PubMed and Embase for literature published between 1966 and September 2016. Strict inclusion/exclusion criteria were used to screen abstracts and to develop a list of relevant articles for full-text review. RESULTS:Guidelines authors aimed to systematically review the literature and make evidence based recommendations about the timing of closure after birth, hydrocephalus, the impact of prenatal closure, and the effect of prenatal closure on ambulation ability and tethered spinal cord. Evidence concerning persistent ventriculomegaly and cognitive impairment was also evaluated. Hundreds of abstracts were identified and reviewed for each of the 5 topics. A total of 14 studies met stringent inclusion criteria. CONCLUSION:Based on a comprehensive systematic review, a total of 5 clinical practice recommendations were developed, with 1 Level I, 2 Level II and 2 Level III recommendations.The full guideline can be found at https://www.cns.org/guidelines/guidelines-spina-bifida-chapter-1.

Modern laser technology is now sufficiently advanced that collisions between high-intensity laser pulses and laser-wakefield-accelerated (LWFA) electron beams can reach the strong-field regime, so that it is possible to measure the transition between the classical and quantum regimes of light-matter interactions. However, the energy spectrum of LWFA electron beams can fluctuate significantly from shot to shot, making it difficult to clearly discern quantum effects in radiation reaction (RR), for example. Here we show how this can be accomplished in only a single laser shot. A millimetre-scale pre-collision drift allows the electron beam to expand to a size larger than the laser focal spot and develop a correlation between transverse position and angular divergence. In contrast to previous studies, this means that a measurement of the beam's energy-divergence spectrum automatically distinguishes components of the beam that hit or miss the laser focal spot and therefore do and do not experience RR.

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.