Plasmons in gold-induced quantum wires

[no abstract

Two-dimensional crossover and strong coupling of plasmon excitations in arrays of one-dimensional atomic wires

The collective electronic excitations of arrays of Au chains on regularly stepped Si(553) and Si(775) surfaces were studied using electron loss spectroscopy with simultaneous high energy and momentum resolution (ELS-LEED) in combination with low energy electron diffraction (SPA-LEED) and tunneling microscopy. Both surfaces contain a double chain of gold atoms per terrace. Although one-dimensional metallicity and plasmon dispersion is observed only along the wires, two-dimensional effects are important, since plasmon dispersion explicitly depends both on the structural motif of the wires and the terrace width. The electron density on each terrace turns out to be modulated, as seen by tunneling spectroscopy (STS). The effective wire width of 7.5\,\AA\ for Si(553)-Au -- 10.2\,\AA\ for Si(775)-Au -- , determined from plasmon dispersion is in good agreement with STS data. Clear evidence for coupling between wires is seen beyond nearest neighbor coupling.Comment: 5 pages, 4 figure

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe

Traces of trauma – a multivariate pattern analysis of childhood trauma, brain structure and clinical phenotypes

Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research

Quantification of the information loss resulting from temporal aggregation of wind turbine operating data

SCADA operating data are more and more used across the wind energy domain, both as a basis for power output prediction and turbine health status monitoring. Current industry practice to work with this data is by aggregating the signals at coarse resolution of typically 10-min averages, in order to reduce data transmission and storage costs. However, aggregation, i.e., downsampling, induces an inevitable loss of information and is one of the main causes of skepticism towards the use of SCADA operating data to model complex systems such as wind turbines. This research aims to quantify the amount of information that is lost due to this downsampling of SCADA operating data and characterize it with respect to the external factors that might influence it. The issue of information loss is framed by three key questions addressing effects on the local and global scale as well as the influence of external conditions. Moreover, recommendations both for wind farm operators and researchers are provided with the aim to improve the information content. We present a methodology to determine the ideal signal resolution that minimized storage footprint, while guaranteeing high quality of the signal. Data related to the wind, electrical signals, and temperatures of the gearbox resulted as the critical signals that are largely affected by an information loss upon aggregation and turned out to be best recorded and stored at high resolutions. All analyses were carried out using more than one year of 1 Hz SCADA data of onshore wind farm counting 12 turbines located in the UK.This research was partially funded by the German Federal Ministry for Economic Affairs and Energy (BMWi), grant numbers 0324336A and 03EE3016B, Centro para el Desarollo Tecnológico Industrial, grant number CDTI-IDI 20191294, and Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR), grant number DOCTORADO AGAUR-2017-DI 004.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.2 - Per a 2030, augmentar substancialment el percentatge d’energia renovable en el con­junt de fonts d’energiaObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version

Norm Values of Muscular Strength Across the Life Span in a Healthy Swiss Population: The COmPLETE Study

Grip strength is used to estimate whole-body strength for health surveillance purposes. Explosive strength is considered important, yet economic measures able to detect early deterioration of neuromuscular capabilities are lacking. Whether handgrip maximum rate of force development (GRFD) or whole-body strength tests are better predictors of lower body power than handgrip maximum strength (GF; max; ) and their trajectories throughout the life span are unknown.; GRFD should be more closely related to lower body power than GF; max; , and its trajectories over the life span should more closely follow that of lower body power.; Cross-sectional.; Level 2b.; A total of 613 healthy participants aged 20 to 91 years were tested for countermovement jump peak power, GF; max; , handgrip rate of force development, and midthigh pull peak force (MTP). Cubic splines and linear models were built for age trajectories, generalized additive models for quintile curves, and linear regression was used to assess predictive quality.; Peak power (P; max; ) declined linearly to 60% of young adult level, with GRFD, GF; max; , and MTP remaining stable up to age 50 years and then declining more sharply to 52% to 71% of young adult levels. Trajectories were similar for male and female participants. GRFD (β = 0.17) and MTP (β = 0.08) were worse predictors of P; max; than GF; max; (β = 0.24) in models adjusted for age, sex, lean body mass, and vigorous physical activity levels.; GRFD was not superior to maximum strength in predicting lower body power. For health surveillance purposes, it therefore appears that GF; max; tests are more economical and equally good predictors of lower body explosive strength at older age. The data provided can be used as norm values for healthy subjects.; Incorporating countermovement jump testing for early detection of declines in explosive capabilities might be advised

Validity and reliability of a novel integrative motor performance testing course for seniors: The “Agility Challenge for the Elderly (ACE)”

Background: Assessing traditional neuromuscular fall risk factors (i.e., balance, gait, strength) in the elderly has so far mainly been done independently. Functional and integrative testing approaches are scarce. The present study proposes an agility course for an integrative assessment of neuromuscular and also cardiocirculatory capacity in seniors - and tests its criterion validity and reliability. Methods: Thirty-six seniors (age: 69.0 ± 2.8 years; BMI: 25.4 ± 3.5 kg/m 2 ; sex: 19 males/17 females; weekly physical activity: 9.4 ± 5.5 h) participated. They completed four trials of the Agility Challenge for the Elderly (ACE)-course in two sessions separated by 1 week. The course consists of three segments focusing on different agility aspects. Cardiovascular capacity was assessed by 6-min walk test (6MWT), neuromuscular capacity by static, dynamic and perturbed standing balance tasks, habitual gait speed assessment, and rate of torque development testing. Parameters' predictive strength for the ACE performance was assessed by regression analysis. Reliability was calculated with intraclass correlation coefficients and coefficients of variation. Results: Men completed the course in 43.0 ± 5.7 s and women in 51.9 ± 4.0 s. Overall and split times were explained by 6MWT time (ηp2 = 0.38-0.44), gait speed (ηp2 = 0.29-0.43), and to a lesser extent trunk rotation explosive strength (ηp2 = 0.05-0.12). Static and dynamic balance as well as plantar flexion strength explained the performance in some segments to a very small extent (ηp2 = 0.06-0.08). Good between- and within-day reliability were observed for total course and split times: The ICC for the between-day comparison was 0.93 (0.88-0.96) and ranged between 0.84 and 0.94 for split times. The within-day ICC was 0.94 (0.91-0.97) for overall time and 0.92-0.97 for split times. Coefficients of variation were smaller than 5.7% for within and between day analyses. Conclusion: The ACE course reflects cardiocirculatory and neuromuscular capacity, with the three ACE segments potentially reflecting slightly different domains of neuromuscular (static and dynamic balance, ankle, and trunk strength) performance, whereas cardiocirculatory fitness and gait speed contribute to all segments. Our test can detect changes in overall performance greater than 5.7% and can thus be useful for documenting changes due to interventions in seniors

Composite Measures of Physical Fitness to Discriminate Between Healthy Aging and Heart Failure: The COmPLETE Study

Aging and changing age demographics represent critical problems of our time. Physiological functions decline with age, often ending in a systemic process that contributes to numerous impairments and age-related diseases including heart failure (HF). We aimed to analyze whether differences in composite measures of physiological function [health distance (HD)], specifically physical fitness, between healthy individuals and patients with HF, can be observed.; The COmPLETE Project is a cross-sectional study of 526 healthy participants aged 20-91 years and 79 patients with stable HF. Fifty-nine biomarkers characterizing fitness (cardiovascular endurance, muscle strength, and neuromuscular coordination) and general health were assessed. We computed HDs as the Mahalanobis distance for vectors of biomarkers (all and domain-specific subsets) that quantified deviations of individuals' biomarker profiles from "optimums" in the "reference population" (healthy participants aged <40 years). We fitted linear regressions with HD outcomes and disease status (HF/Healthy) and relevant covariates as predictors and logistic regressions for the disease outcome and sex, age, and age; 2; as covariates in the base model and the same covariates plus combinations of one or two HDs.; Nine out of 10 calculated HDs showed evidence for group differences between Healthy and HF (; p; ≤ 0.002) and most models presented a negative estimate of the interaction term age by group (; p; < 0.05 for eight HDs). The predictive performance of the base model for HF cases significantly increased by adding HD; General health; or HD; Fitness; [areas under the receiver operating characteristic (ROC) curve (AUCs) 0.63, 0.89, and 0.84, respectively]. HD; Cardiovascular endurance; alone reached an AUC of 0.88. Further, there is evidence that the combination of HDs; Cardiovascular endurance; and; General health; shows superior predictive power compared to single HDs.; HD composed of physical fitness biomarkers differed between healthy individuals and patients with HF, and differences between groups diminished with increasing age. HDs can successfully predict HF cases, and HD; Cardiovascular endurance; can significantly increase the predictive power beyond classic clinical biomarkers. Applications of HD could strengthen a comprehensive assessment of physical fitness and may present an optimal target for interventions to slow the decline of physical fitness with aging and, therefore, to increase health span