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%.
The role of electron-electron interactions in two-dimensional Dirac fermion systems remains enigmatic. Using a combination of nonperturbative numerical and analytical techniques that incorporate both ...the contact and long-range parts of the Coulomb interaction, we identify the two previously discussed regimes: a Gross-Neveu transition to a strongly correlated Mott insulator and a semimetallic state with a logarithmically diverging Fermi velocity accurately described by the random phase approximation. We predict that experimental realizations of Dirac fermions span this crossover and that this determines whether the Fermi velocity is increased or decreased by interactions. We explain several long-standing mysteries, including why the observed Fermi velocity in graphene is consistently about 20% larger than values obtained from ab initio calculations and why graphene on different substrates shows different behaviors.
Near neutral pH values are widely thought to be optimum for uptake of phosphate. This belief is based on an outdated view of soil phosphate chemistry. The literature on uptake by plants from solution ...and from soil, and especially on desorption by soil, are all consistent with a much lower pH optimum.
Exaggerated postprandial secretion of glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) may explain appetite reduction and weight loss after Roux-en-Y gastric bypass (RYGB), but causality has not ...been established. We hypothesized that food intake decreases after surgery through combined actions from GLP-1 and PYY. GLP-1 actions can be blocked using the GLP-1 receptor antagonist Exendin 9-39 (Ex-9), whereas PYY actions can be inhibited by the administration of a dipeptidyl peptidase-4 (DPP-4) inhibitor preventing the formation of PYY
.
Appetite-regulating gut hormones and appetite ratings during a standard mixed-meal test and effects on subsequent ad libitum food intake were evaluated in two studies: in study 1, nine patients with type 2 diabetes were examined prospectively before and 3 months after RYGB with and without Ex-9. In study 2, 12 RYGB-operated patients were examined in a randomized, placebo-controlled, crossover design on four experimental days with: (1) placebo, (2) Ex-9, (3) the DPP-4 inhibitor, sitagliptin, to reduce formation of PYY
and (4) Ex-9/sitagliptin combined.
In study 1, food intake decreased by 35% following RYGB compared with before surgery. Before surgery, GLP-1 receptor blockage increased food intake but no effect was seen postoperatively, whereas PYY secretion was markedly increased. In study 2, combined GLP-1 receptor blockage and DPP-4 inhibitor mediated lowering of PYY
increased food intake by ~20% in RYGB patients, whereas neither GLP-1 receptor blockage nor DPP-4 inhibition alone affected food intake, perhaps because of concomitant marked increases in the unblocked hormone.
Blockade of actions from only one of the two L-cell hormones, GLP-1 and PYY
, resulted in concomitant increased secretion of the other, probably explaining the absent effect on food intake on these experimental days. Combined blockade of GLP-1 and PYY actions increased food intake after RYGB, supporting that these hormones have a role in decreased food intake postoperatively.
Superconductivity is among the most fascinating and well-studied quantum states of matter. Despite over 100 years of research, a detailed understanding of how features of the normal-state electronic ...structure determine superconducting properties has remained elusive. For instance, the ability to deterministically enhance the superconducting transition temperature by design, rather than by serendipity, has been a long sought-after goal in condensed matter physics and materials science, but achieving this objective may require new tools, techniques and approaches. Here, we report the transmutation of a normal metal into a superconductor through the application of epitaxial strain. We demonstrate that synthesizing RuO
thin films on (110)-oriented TiO
substrates enhances the density of states near the Fermi level, which stabilizes superconductivity under strain, and suggests that a promising strategy to create new transition-metal superconductors is to apply judiciously chosen anisotropic strains that redistribute carriers within the low-energy manifold of d orbitals.
Information about the long-term clinical survival of large amalgam and composite restorations is still lacking. This retrospective study compares the longevity of three- and four-/five-surface ...amalgam and composite restorations relative to patients’ caries risk. Patient records from a general practice were used for data collection. We evaluated 1949 large class II restorations (1202 amalgam/747 composite). Dates of placement, replacement, and failure were recorded, and caries risk of patients was assessed. Survival was calculated from Kaplan-Meier statistics. After 12 years, 293 amalgam and 114 composite restorations had failed. Large composite restorations showed a higher survival in the combined population and in the low-risk group. For three-surface restorations in high-risk patients, amalgam showed better survival.
Community detection is often used to understand the structure of large and complex networks. One of the most popular algorithms for uncovering community structure is the so-called Louvain algorithm. ...We show that this algorithm has a major defect that largely went unnoticed until now: the Louvain algorithm may yield arbitrarily badly connected communities. In the worst case, communities may even be disconnected, especially when running the algorithm iteratively. In our experimental analysis, we observe that up to 25% of the communities are badly connected and up to 16% are disconnected. To address this problem, we introduce the Leiden algorithm. We prove that the Leiden algorithm yields communities that are guaranteed to be connected. In addition, we prove that, when the Leiden algorithm is applied iteratively, it converges to a partition in which all subsets of all communities are locally optimally assigned. Furthermore, by relying on a fast local move approach, the Leiden algorithm runs faster than the Louvain algorithm. We demonstrate the performance of the Leiden algorithm for several benchmark and real-world networks. We find that the Leiden algorithm is faster than the Louvain algorithm and uncovers better partitions, in addition to providing explicit guarantees.
Measurements of 21 cm Epoch of Reionization (EoR) structure are subject to systematics originating from both the analysis and the observation conditions. Using 2013 data from the Murchison Widefield ...Array (MWA), we show the importance of mitigating both sources of contamination. A direct comparison between results from Beardsley et al. and our updated analysis demonstrates new precision techniques, lowering analysis systematics by a factor of 2.8 in power. We then further lower systematics by excising observations contaminated by ultra-faint RFI, reducing by an additional factor of 3.8 in power for the zenith pointing. With this enhanced analysis precision and newly developed RFI mitigation, we calculate a noise-dominated upper limit on the EoR structure of Δ2 ≤ 3.9 × 103 mK2 at k = 0.20 h Mpc−1 and z = 7 using 21 hr of data, improving previous MWA limits by almost an order of magnitude.
Cells acting at the intersection of immunityFor years, scientists divided the immune system into two arms: innate and adaptive. The cell types involved in the two arms differ in specificity and in ...how quickly they respond to infections. More recently, immunologists discovered a family of immune cells termed "innate lymphoid cells," which straddle these two arms. Eberl et al. review current understanding of innate lymphoid cells. Like innate immune cells, they respond to infection quickly and do not express antigen receptors; however, they secrete a similar suite of inflammatory mediators as T lymphocytes. Better understanding of the processes regulating these cells may allow for their therapeutic manipulation.Science, this issue 10.1126/science.aaa6566 Innate lymphoid cells (ILCs) are a growing family of immune cells that mirror the phenotypes and functions of T cells. However, in contrast to T cells, ILCs do not express acquired antigen receptors or undergo clonal selection and expansion when stimulated. Instead, ILCs react promptly to signals from infected or injured tissues and produce an array of secreted proteins termed cytokines that direct the developing immune response into one that is adapted to the original insult. The complex cross-talk between microenvironment, ILCs, and adaptive immunity remains to be fully deciphered. Only by understanding these complex regulatory networks can the power of ILCs be controlled or unleashed in order to regulate or enhance immune responses in disease prevention and therapy.
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