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The COVID-19 pandemic negatively impacted adolescent mental health on a global scale. However, many students were resilient during this crisis, despite exposure to COVID-related stressors. We aimed to study the protective effects of growth mindset on school-related resilience during the COVID-19 pandemic, and the mediating effects of coping styles. The two-year follow-up of an ongoing Randomized Controlled Trial, involving a growth mindset and control intervention, took place during the pandemic. We measured growth mindset, school burnout symptoms, COVID-19-specific stressor exposure, coping styles, and calculated a resilience score (corrected for pre-pandemic school burnout symptoms). Mediation analyses were performed in the total sample ( N  = 261), and exploratory in the intervention subsamples, to test whether the associations between mindset and resilience were mediated by coping styles. Growth-mindset students were more resilient during the pandemic and used less maladaptive and more adaptive (acceptance) coping styles. Coping mediated the relation between mindset and resilience in the total sample (both coping styles), and growth mindset intervention subsample (maladaptive coping). We found unique evidence for the beneficial effects of growth mindset on school-related resilience during the pandemic, and the mediating effect of coping styles as explanatory mechanism. This work contributes to a growing literature that shows positive effects of growth mindset on mental health.

Vulnerable or \"frail\" patients are susceptible to the development of delirium when exposed to triggers such as surgical procedures. Once delirium occurs, interventions have little effect on severity or duration, emphasizing the importance of primary prevention. This review provides an overview of interventions to prevent postoperative delirium in elderly patients undergoing elective surgery. A literature search was conducted in March 2018. Randomized controlled trials (RCTs) and before-and-after studies on interventions with potential effects on postoperative delirium in elderly surgical patients were included. Acute admission, planned ICU admission, and cardiac patients were excluded. Full texts were reviewed, and quality was assessed by two independent reviewers. Primary outcome was the incidence of delirium. Secondary outcomes were severity and duration of delirium. Pooled risk ratios (RRs) were calculated for incidences of delirium where similar intervention techniques were used. Thirty-one RCTs and four before-and-after studies were included for analysis. In 19 studies, intervention decreased the incidences of postoperative delirium. Severity was reduced in three out of nine studies which reported severity of delirium. Duration was reduced in three out of six studies. Pooled analysis showed a significant reduction in delirium incidence for dexmedetomidine treatment, and bispectral index (BIS)-guided anaesthesia. Based on sensitivity analyses, by leaving out studies with a high risk of bias, multicomponent interventions and antipsychotics can also significantly reduce the incidence of delirium. Multicomponent interventions, the use of antipsychotics, BIS-guidance, and dexmedetomidine treatment can successfully reduce the incidence of postoperative delirium in elderly patients undergoing elective, non-cardiac surgery. However, present studies are heterogeneous, and high-quality studies are scarce. Future studies should add these preventive methods to already existing multimodal and multidisciplinary interventions to tackle as many precipitating factors as possible, starting in the pre-admission period.

Modern machine learning methods offer great potential for increasing the efficiency of Monte Carlo event generators. We present the latest developments in the context of the SHERPA event generation framework. These include phase space sampling amended by normalizing flows and a new unweighting procedure based on neural-network surrogates for the full matrix elements. We discuss corresponding general construction criteria and show examples of efficiency gains for selected LHC production processes.

Background The ability to adapt walking to environmental properties and hazards, a prerequisite for safe ambulation, is often impaired in persons after stroke. Research question The aim of this study was to compare the efficacy of two walking-adaptability interventions: a novel treadmill-based C-Mill therapy (using gait-dependent augmented reality) and the standard overground FALLS program (using physical context). We expected sustained improvements for both treatment groups combined but hypothesized better outcomes for C-Mill therapy than the FALLS program due to its expected greater amount of walking practice. Methods In this pre-registered single-centre parallel group randomized controlled trial, forty persons after stroke (≥ 3 months ago) with walking and/or balance deficits were randomly allocated to either 5 weeks of C-Mill therapy or the FALLS program. The primary outcome measure was the standard walking speed as determined with the 10-meter walking test (10MWT). Additionally, context-specific walking speed was assessed in environments enriched with either stationary physical context (10MWT context) or suddenly appearing visual images (Interactive Walkway obstacles). The walking-adaptability scores of those enriched walking tests served as secondary outcome measures. Furthermore, a cognitive task was added to all three assessments to evaluate dual-task performance in this context. Finally, the participants’ experience and amount of walking practice were scored. The outcome measures were assessed at four test moments: pre-intervention (T0), post-intervention (T1), 5-week post-intervention retention (T2), and 1-year post-intervention follow-up (T3). Results No significant group differences were found between the interventions for the primary outcome measure standard walking speed, but we found a greater improvement in context-specific walking speed with stationary physical context of the C-Mill therapy compared to the FALLS program at the post-intervention test, which was no longer significant at retention. Both interventions were well received, but C-Mill therapy scored better on perceived increased fitness than the FALLS program. C-Mill therapy resulted in twice as many steps per session of equal duration than the FALLS program. The “change-over-time” analyses for participants of both interventions combined showed no significant improvements in the standard walking speed; however, significant improvements were found for context-specific walking speed, walking adaptability, and cognitive dual-task performance. Significance This study showed no between-group differences between the novel treadmill-based C-Mill therapy and the standard overground FALLS program with respect to the primary outcome measure standard walking speed. However, the greater amount of walking practice observed for the C-Mill group, an essential aspect of effective intervention programs after stroke, may underlie the reported increased perceived fitness and observed increased context-specific walking speed for the C-Mill group directly after the intervention. Although the “change-over-time” results for all participants combined showed no improvement in the standard walking speed, context-specific walking speed and walking adaptability showed sustained improvements after the interventions, underscoring the importance of including walking-adaptability training and assessment in rehabilitation post stroke. Trial registration The Netherlands Trial Register NTR4030. Registered 11 June 2013.

The quantum Hall effect 1 allows the international standard for resistance to be defined in terms of the electron charge and Planck's constant alone. The effect comprises the quantization of the Hall resistance in two-dimensional electron systems in rational fractions of R K  =  h / e 2  = 25 812.807 557(18) Ω, the resistance quantum 2 . Despite 30 years of research into the quantum Hall effect, the level of precision necessary for metrology—a few parts per billion—has been achieved only in silicon and iii – v heterostructure devices 3 , 4 , 5 . Graphene should, in principle, be an ideal material for a quantum resistance standard 6 , because it is inherently two-dimensional and its discrete electron energy levels in a magnetic field (the Landau levels 7 ) are widely spaced. However, the precisions demonstrated so far have been lower than one part per million 8 . Here, we report a quantum Hall resistance quantization accuracy of three parts per billion in monolayer epitaxial graphene at 300 mK, four orders of magnitude better than previously reported. Moreover, by demonstrating the structural integrity and uniformity of graphene over hundreds of micrometres, as well as reproducible mobility and carrier concentrations across a half-centimetre wafer, these results boost the prospects of using epitaxial graphene in applications beyond quantum metrology. The quantum Hall effect has been measured in epitaxial graphene to an accuracy of a few parts per billion, potentially establishing a new quantum resistance standard.

Electron pumps generate a macroscopic electric current by controlled manipulation of single electrons. Despite intensive research towards a quantum current standard over the last 25 years, making a fast and accurate quantized electron pump has proved extremely difficult. Here we demonstrate that the accuracy of a semiconductor quantum dot pump can be dramatically improved by using specially designed gate drive waveforms. Our pump can generate a current of up to 150 pA, corresponding to almost a billion electrons per second, with an experimentally demonstrated current accuracy better than 1.2 parts per million (p.p.m.) and strong evidence, based on fitting data to a model, that the true accuracy is approaching 0.01 p.p.m. This type of pump is a promising candidate for further development as a realization of the SI base unit ampere, following a redefinition of the ampere in terms of a fixed value of the elementary charge. Single electron pumps have been proposed as potential candidates for redefining the ampere. This study reports measurements of the quantized current flowing through a semiconductor electron pump with a precision that makes a substantial step towards establishing a direct metric for electrical currents.

Magnetic materials play a vital role in energy-efficient data storage technologies, combining very fast switching with long-term retention of information. However, it has been shown that, at very short time scales, magnetisation dynamics become chaotic due to internal instabilities, resulting in incoherent spin-wave excitations that ultimately destroy magnetic ordering. Here, contrary to expectations, we show that such chaos gives rise to a periodic pattern of reversed magnetic domains, with a feature size far smaller than the spatial extent of the excitation. We explain this pattern as a result of phase-synchronisation of magnon-polaron quasiparticles, driven by strong coupling of magnetic and elastic modes. Our results reveal not only the peculiar formation and evolution of magnon-polarons at short time-scales, but also present an alternative mechanism of magnetisation reversal driven by coherent packets of short-wavelength magnetoelastic waves. Increasing the speed of magnetization switching is an obvious pathway to improve spintronic device performance. However, very fast magnetization switching is accompanied by instabilities. Here, Gidding et al study these instabilities using optical pumping, and show that instability generated spin-waves can achieve a high enough amplitude to drive switching of the magnetization, with a distinctive coherent pattern.

Delirium is a common and serious complication in elderly patients undergoing major abdominal surgery, with significant adverse outcomes. Successful strategies or therapies to reduce the incidence of delirium are scarce. The objective of this study was to assess the role of prehabilitation in reducing the incidence of delirium in elderly patients. A single-center uncontrolled before-and-after study was conducted, including patients aged 70 years or older who underwent elective abdominal surgery for colorectal carcinoma or an abdominal aortic aneurysm between January 2013 and October 2015 (control group) and between November 2015 and June 2018 (prehabilitation group). The prehabilitation group received interventions to improve patients' physical health, nutritional status, factors of frailty and preoperative anaemia prior to surgery. The primary outcome was incidence of delirium, diagnosed with the DSM-V criteria or the confusion assessment method. Secondary outcomes were additional complications, length of stay, unplanned ICU admission, length of ICU stay, readmission rate, institutionalization, and in-hospital or 30-day mortality. A total of 360 control patients and 267 prehabilitation patients were included in the final analysis. The mean number of prehabilitation days was 39 days. The prehabilitation group had a higher burden of comorbidities and was more physically and visually impaired at baseline. At adjusted logistic regression analysis, delirium incidence was reduced significantly from 11.7 to 8.2% (OR 0.56; 95% CI 0.32-0.98; P = 0.043). No statistically significant effects were seen on secondary outcomes. Current prehabilitation program is feasible and safe, and can reduce delirium incidence in elderly patients undergoing elective major abdominal surgery. This program merits further evaluation. Dutch Trial Registration, NTR5932.

A distributed sensor network of over 100 free-drifting, real-time marine weather sensors was deployed in the Pacific Ocean beginning in early 2019. The Spotter buoys used in the network represent a next-generation ocean weather sensor designed to measure surface waves, wind, currents, and sea surface temperature. Large distributed sensor networks like these provide much needed long-dwell sensing capabilities in open-ocean regions. Despite the demand for better weather forecasts and climate data in the oceans, direct in situ measurements of marine surface weather (waves, winds, currents) remain exceedingly sparse in the open oceans. Because of the large expanse of Earth’s oceans, distributed paradigms are necessary to create sufficient data density at global scale, similar to advances in sensing on land and in space. Here we discuss initial findings from this long-dwell open-ocean distributed sensor network. Through triple-collocation analysis, we determine errors in collocated satellite-derived observations and model estimates. The correlation analysis shows that the Spotter network provides wave height data with lower errors than both satellites and models. The wave spectrum was also further used to infer wind speed. Buoy drift dynamics are similar to established drogued drifters, particularly when accounting for windage. We find a windage correction factor for the Spotter buoy of approximately 1%, which is in agreement with theoretical estimates. Altogether, we present a completely new open-ocean weather dataset and characterize the data quality against other observations and models to demonstrate the broad value for ocean monitoring and forecasting that can be achieved using large-scale distributed sensor networks in the oceans.

Whole genome sequencing (WGS) enables detailed characterization of bacteria at single nucleotide resolution. It provides data about acquired resistance genes and mutations leading to resistance. Although WGS is becoming an essential tool to predict resistance patterns accurately, comparing genotype to phenotype with WGS is still in its infancy. Additional data and validation are needed. In this retrospective study, we analysed 234 E. coli isolates from positive blood cultures using WGS as well as microdilution for 11 clinically relevant antibiotics, to compare the two techniques. We performed whole genome sequencing analyses on 234 blood culture isolates (genotype) to detect acquired antibiotic resistance. Minimal inhibitory concentrations (MIC) for E. coli were performed for amoxicillin, cefepime, cefotaxime, ceftazidime, meropenem, amoxicillin/clavulanic acid, piperacillin/tazobactam, amikacin, gentamicin, tobramycin, and ciprofloxacin, using the ISO 20776-1 standard broth microdilution method as recommended by EUCAST (phenotype). We then compared the two methods for statistical ‘agreement’. A perfect (100%) categorical agreement between genotype and phenotype was observed for gentamicin and meropenem. However, no resistance to meropenem was observed. A high categorical agreement (> 95%) was observed for amoxicillin, cefepime, cefotaxime, ceftazidime, amikacin, and tobramycin. A categorical agreement lower than 95% was observed for amoxicillin/clavulanic acid, piperacillin/tazobactam, and ciprofloxacin. Most discrepancies occurred in isolates with MICs within ± 1 doubling dilution of the breakpoint and 22.73% of the major errors were samples that tested phenotypically susceptible at higher antibiotic exposure and were therefore considered as ‘not resistant’. This study shows that WGS can be used as a valuable tool to predict phenotypic resistance against most of the clinically relevant antibiotics used for the treatment of E. coli bloodstream infections.