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SensorHub
(2022)
Observational studies are an important tool for determining whether the findings from controlled experiments can be transferred into scenarios that are closer to subjects' real-life circumstances. A rigorous approach to observational studies involves collecting data from different sensors to comprehensively capture the situation of the subject. However, this leads to technical difficulties especially if the sensors are from different manufacturers, as multiple data collection tools have to run simultaneously. We present SensorHub, a system that can collect data from various wearable devices from different manufacturers, such as inertial measurement units, portable electrocardiographs, portable electroencephalographs, portable photoplethysmographs, and sensors for electrodermal activity. Additionally, our tool offers the possibility to include ecological momentary assessments (EMAs) in studies. Hence, SensorHub enables multimodal sensor data collection under real-world conditions and allows direct user feedback to be collected through questionnaires, enabling studies at home. In a first study with 11 participants, we successfully used SensorHub to record multiple signals with different devices and collected additional information with the help of EMAs. In addition, we evaluated SensorHub's technical capabilities in several trials with up to 21 participants recording simultaneously using multiple sensors with sampling frequencies as high as 1000 Hz. We could show that although there is a theoretical limitation to the transmissible data rate, in practice this limitation is not an issue and data loss is rare. We conclude that with modern communication protocols and with the increasingly powerful smartphones and wearables, a system like our SensorHub establishes an interoperability framework to adequately combine consumer-grade sensing hardware which enables observational studies in real life.
A comprehensive workflow to analyze ensembles of globally inverted 2D electrical resistivity models
(2022)
Electrical resistivity tomography (ERT) aims at imaging the subsurface resistivity distribution and provides valuable information for different geological, engineering, and hydrological applications. To obtain a subsurface resistivity model from measured apparent resistivities, stochastic or deterministic inversion procedures may be employed. Typically, the inversion of ERT data results in non-unique solutions; i.e., an ensemble of different models explains the measured data equally well. In this study, we perform inference analysis of model ensembles generated using a well-established global inversion approach to assess uncertainties related to the nonuniqueness of the inverse problem. Our interpretation strategy starts by establishing model selection criteria based on different statistical descriptors calculated from the data residuals. Then, we perform cluster analysis considering the inverted resistivity models and the corresponding data residuals. Finally, we evaluate model uncertainties and residual distributions for each cluster. To illustrate the potential of our approach, we use a particle swarm optimization (PSO) algorithm to obtain an ensemble of 2D layer-based resistivity models from a synthetic data example and a field data set collected in Loon-Plage, France. Our strategy performs well for both synthetic and field data and allows us to extract different plausible model scenarios with their associated uncertainties and data residual distributions. Although we demonstrate our workflow using 2D ERT data and a PSObased inversion approach, the proposed strategy is general and can be adapted to analyze model ensembles generated from other kinds of geophysical data and using different global inversion approaches.
According to Radzikowski’s celebrated results, bisolutions of a wave operator on a globally hyperbolic spacetime are of the Hadamard form iff they are given by a linear combination of distinguished parametrices i2(G˜aF−G˜F+G˜A−G˜R) in the sense of Duistermaat and Hörmander [Acta Math. 128, 183–269 (1972)] and Radzikowski [Commun. Math. Phys. 179, 529 (1996)]. Inspired by the construction of the corresponding advanced and retarded Green operator GA, GR as done by Bär, Ginoux, and Pfäffle {Wave Equations on Lorentzian Manifolds and Quantization [European Mathematical Society (EMS), Zürich, 2007]}, we construct the remaining two Green operators GF, GaF locally in terms of Hadamard series. Afterward, we provide the global construction of i2(G˜aF−G˜F), which relies on new techniques such as a well-posed Cauchy problem for bisolutions and a patching argument using Čech cohomology. This leads to global bisolutions of the Hadamard form, each of which can be chosen to be a Hadamard two-point-function, i.e., the smooth part can be adapted such that, additionally, the symmetry and the positivity condition are exactly satisfied.
River-valley morphology preserves information on tectonic and climatic conditions that shape landscapes. Observations suggest that river discharge and valley-wall lithology are the main controls on valley width. Yet, current models based on these observations fail to explain the full range of cross-sectional valley shapes in nature, suggesting hitherto unquantified controls on valley width. In particular, current models cannot explain the existence of paired terrace sequences that form under cyclic climate forcing. Paired river terraces are staircases of abandoned floodplains on both valley sides, and hence preserve past valley widths. Their formation requires alternating phases of predominantly river incision and predominantly lateral planation, plus progressive valley narrowing. While cyclic Quaternary climate changes can explain shifts between incision and lateral erosion, the driving mechanism of valley narrowing is unknown. Here, we extract valley geometries from climatically formed, alluvial river-terrace sequences and show that across our dataset, the total cumulative terrace height (here: total valley height) explains 90%–99% of the variance in valley width at the terrace sites. This finding suggests that valley height, or a parameter that scales linearly with valley height, controls valley width in addition to river discharge and lithology. To explain this valley-width-height relationship, we reformulate existing valley-width models and suggest that, when adjusting to new boundary conditions, alluvial valleys evolve to a width at which sediment removal from valley walls matches lateral sediment supply from hillslope erosion. Such a hillslope-channel coupling is not captured in current valley-evolution models. Our model can explain the existence of paired terrace sequences under cyclic climate forcing and relates valley width to measurable field parameters. Therefore, it facilitates the reconstruction of past climatic and tectonic conditions from valley topography.
Dynamic pricing is considered a possibility to gain an advantage over competitors in modern online markets. The past advancements in Reinforcement Learning (RL) provided more capable algorithms that can be used to solve pricing problems. In this paper, we study the performance of Deep Q-Networks (DQN) and Soft Actor Critic (SAC) in different market models. We consider tractable duopoly settings, where optimal solutions derived by dynamic programming techniques can be used for verification, as well as oligopoly settings, which are usually intractable due to the curse of dimensionality. We find that both algorithms provide reasonable results, while SAC performs better than DQN. Moreover, we show that under certain conditions, RL algorithms can be forced into collusion by their competitors without direct communication.
Beyond humanitarianism
(2022)
In numerical processing, the functional role of Spatial-Numerical Associations (SNAs, such as the association of smaller numbers with left space and larger numbers with right space, the Mental Number Line hypothesis) is debated. Most studies demonstrate SNAs with lateralized responses, and there is little evidence that SNAs appear when no response is required. We recorded passive holding grip forces in no-go trials during number processing. In Experiment 1, participants performed a surface numerical decision task (“Is it a number or a letter?”). In Experiment 2, we used a deeper semantic task (“Is this number larger or smaller than five?”). Despite instruction to keep their grip force constant, participants' spontaneous grip force changed in both experiments: Smaller numbers led to larger force increase in the left than in the right hand in the numerical decision task (500–700 ms after stimulus onset). In the semantic task, smaller numbers again led to larger force increase in the left hand, and larger numbers increased the right-hand holding force. This effect appeared earlier (180 ms) and lasted longer (until 580 ms after stimulus onset). This is the first demonstration of SNAs with passive holding force. Our result suggests that (1) explicit motor response is not a prerequisite for SNAs to appear, and (2) the timing and strength of SNAs are task-dependent. (216 words).
A conundrum of trends
(2022)
This comment is meant to reiterate two warnings: One applies to the uncritical use of ready-made (openly available) program packages, and one to the estimation of trends in serially correlated time series. Both warnings apply to the recent publication of Lischeid et al. about lake-level trends in Germany.
Numerical magnitude information is assumed to be spatially represented in the form of a mental number line defined with respect to a body-centred, egocentric frame of reference. In this context, spatial language skills such as mastery of verbal descriptions of spatial position (e.g., in front of, behind, to the right/left) have been proposed to be relevant for grasping spatial relations between numerical magnitudes on the mental number line. We examined 4- to 5-year-old’s spatial language skills in tasks that allow responses in egocentric and allocentric frames of reference, as well as their relative understanding of numerical magnitude (assessed by a number word comparison task). In addition, we evaluated influences of children’s absolute understanding of numerical magnitude assessed by their number word comprehension (montring different numbers using their fingers) and of their knowledge on numerical sequences (determining predecessors and successors as well as identifying missing dice patterns of a series). Results indicated that when considering responses that corresponded to the egocentric perspective, children’s spatial language was associated significantly with their relative numerical magnitude understanding, even after controlling for covariates, such as children’s SES, mental rotation skills, and also absolute magnitude understanding or knowledge on numerical sequences. This suggests that the use of egocentric reference frames in spatial language may facilitate spatial representation of numbers along a mental number line and thus seem important for preschoolers’ relative understanding of numerical magnitude.
Quantifying neurological disorders from voice is a rapidly growing field of research and holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup and data analysis pipelines are both crucial aspects to effectively obtain relevant information from participants. Therefore, we performed a systematic review to provide a high-level overview of practices across various neurological disorders and highlight emerging trends. PRISMA-based literature searches were conducted through PubMed, Web of Science, and IEEE Xplore to identify publications in which original (i.e., newly recorded) datasets were collected. Disorders of interest were psychiatric as well as neurodegenerative disorders, such as bipolar disorder, depression, and stress, as well as amyotrophic lateral sclerosis amyotrophic lateral sclerosis, Alzheimer's, and Parkinson's disease, and speech impairments (aphasia, dysarthria, and dysphonia). Of the 43 retrieved studies, Parkinson's disease is represented most prominently with 19 discovered datasets. Free speech and read speech tasks are most commonly used across disorders. Besides popular feature extraction toolkits, many studies utilise custom-built feature sets. Correlations of acoustic features with psychiatric and neurodegenerative disorders are presented. In terms of analysis, statistical analysis for significance of individual features is commonly used, as well as predictive modeling approaches, especially with support vector machines and a small number of artificial neural networks. An emerging trend and recommendation for future studies is to collect data in everyday life to facilitate longitudinal data collection and to capture the behavior of participants more naturally. Another emerging trend is to record additional modalities to voice, which can potentially increase analytical performance.
This study examines the access to healthcare for children and adolescents with three common chronic diseases (type-1 diabetes (T1D), obesity, or juvenile idiopathic arthritis (JIA)) within the 4th (Delta), 5th (Omicron), and beginning of the 6th (Omicron) wave (June 2021 until July 2022) of the COVID-19 pandemic in Germany in a cross-sectional study using three national patient registries. A paper-and-pencil questionnaire was given to parents of pediatric patients (<21 years) during the routine check-ups. The questionnaire contains self-constructed items assessing the frequency of healthcare appointments and cancellations, remote healthcare, and satisfaction with healthcare. In total, 905 parents participated in the T1D-sample, 175 in the obesity-sample, and 786 in the JIA-sample. In general, satisfaction with healthcare (scale: 0–10; 10 reflecting the highest satisfaction) was quite high (median values: T1D 10, JIA 10, obesity 8.5). The proportion of children and adolescents with canceled appointments was relatively small (T1D 14.1%, JIA 11.1%, obesity 20%), with a median of 1 missed appointment, respectively. Only a few parents (T1D 8.6%; obesity 13.1%; JIA 5%) reported obstacles regarding health services during the pandemic. To conclude, it seems that access to healthcare was largely preserved for children and adolescents with chronic health conditions during the COVID-19 pandemic in Germany.
Background
Benefit finding, defined as perceiving positive life changes resulting from adversity and negative life stressors, gains growing attention in the context of chronic illness. The study aimed at examining the psychometric properties of the Benefit Finding Scale for Children (BFSC) in a sample of German youth facing chronic conditions.
Methods
A sample of adolescents with various chronic conditions (N = 304; 12 – 21years) completed the 10-item BFSC along with measures of intra- and interpersonal resources, coping strategies, and health-related quality of life (hrQoL). The total sample was randomly divided into two subsamples for conducting exploratory and confirmatory factor analyses (EFA/CFA).
Results
EFA revealed that the BFSC scores had a one-dimensional factor structure. CFA verified the one-dimensional factor structure with an acceptable fit. The BFSC exhibited acceptable internal consistency (α = 0.87 – 0.88) and construct validity. In line with our hypotheses, benefit finding was positively correlated with optimism, self-esteem, self-efficacy, sense of coherence, and support seeking. There were no correlations with avoidance, wishful thinking, emotional reaction, and hrQoL. Sex differences in benefit finding were not consistent across subsamples. Benefit finding was also positively associated with age, disease severity, and social status.
Conclusions
The BFSC is a psychometrically sound instrument to assess benefit finding in adolescents with chronic illness and may facilitate further research on positive adaptation processes in adolescents, irrespective of their specific diagnosis.
Nationality traditionally is one of imagology’s key terms. In this article, I propose an intersectional understanding of this category, conceiving nationality as an interdependent dynamic. I thus conclude it to be always internally constructed by notions of gender, sexuality, race, class, religion, age, ability, and other identity categories. This complex and multi-layered construct, I argue, is formed narratively. To exemplify this, I analyse practices of stereotyping in Honoré de Balzac’s Illusions perdues (1843) and Henry James’s The American (1877) which construct the so-called Parisienne as a synecdoche for nineteenth-century France.
Due to the COVID pandemic, the introductory course on organic chemistry was developed and conducted as anonline course. To ensure methodical variety in this course,educational games and quizzes have been developed, used, and evaluated. The attendance of the course, and therefore also the use of the quizzes and games, was voluntary. The quizzes'main goalwas to give the students the opportunity to check whether they had memorized the knowledge needed in the course. Another goal was to make transparent which knowledge the students shouldmemorize by rote. The evaluation shows that the students hadnot internalized all knowledge which they should apply in severaltasks on organic chemistry. They answered multiselect questions in general less well than single-select questions. The games shouldcombine fun with learning. The evaluation of the games shows that the students rated them very well. The students used thosegames again for their exam preparation, as the monitoring of accessing the games showed. Students'experiences with usingelectronic devices in general or for quizzes and games have also been evaluated, because their experience could influence thestudents'assessment of the quizzes and games used in our study. However, the students used electronic devices regularly and shouldtherefore be technically competent to use our quizzes and games. The evaluation showed that the use of digital games for learningpurposes is not very common, neither at school nor at university, although the students had worked with such tools before. Thestudents are also very interested in using and developing such digital games not only for their own study, but also for their future work at school
We report a modified approach to the batch scale preparation of completely engulfed core-shell emulsions or partially engulfed Janus emulsions with colorful optical properties, containing water, olive oil, and silicone oil. The in situ reduction of gold chloride, forming gold nanoparticles (AuNPs) at the olive oil interface in the absence or presence of chitosan, leads to the formation of compartmentalized olive-silicone oil emulsion droplets in water. In the absence of additional reducing components, time-dependent morphological transformations from partial engulfment to complete engulfment were observed. Similar experiments in the presence of chitosan or presynthesized AuNPs show an opposite time-dependent trend of transformation of core-shell structures into partially engulfed ones. This behavior can be understood by a time-dependent rearrangement of the AuNPs at the interface and changes of the interfacial tension. The Pickering effect of AuNPs at oil-water and oil-oil interfaces brings not only color effects to individual microdroplets, which are of special relevance for the preparation of new optical elements, but also a surprising self-assembly of droplets.
Extreme value statistics is a popular and frequently used tool to model the occurrence of large earthquakes. The problem of poor statistics arising from rare events is addressed by taking advantage of the validity of general statistical properties in asymptotic regimes. In this note, I argue that the use of extreme value statistics for the purpose of practically modeling the tail of the frequency-magnitude distribution of earthquakes can produce biased and thus misleading results because it is unknown to what degree the tail of the true distribution is sampled by data. Using synthetic data allows to quantify this bias in detail. The implicit assumption that the true M-max is close to the maximum observed magnitude M-max,M-observed restricts the class of the potential models a priori to those with M-max = M-max,M-observed + Delta M with an increment Delta M approximate to 0.5... 1.2. This corresponds to the simple heuristic method suggested by Wheeler (2009) and labeled :M-max equals M-obs plus an increment." The incomplete consideration of the entire model family for the frequency-magnitude distribution neglects, however, the scenario of a large so far unobserved earthquake.
Simply too much
(2022)
Purpose Weight bias internalization (WBI) is associated with negative health consequences such as eating disorders and psychosocial problems in children. To date, it is unknown to what extent WBI considerably raises the risk of negative outcomes. Methods Analyses are based on cross-sectional data of 1,061 children (9-13 years, M = 11, SD = 0.9; 52.1% female) who filled in the WBI scale (WBIS-C). First, ROC analyses were run to identify critical cut-off values of WBI (WBIS-C score) that identify those who are at higher risk for psychosocial problems or eating disorder symptoms (as reported by parents). Second, it was examined whether WBI is more sensitive than the relative weight status in that respect. Third, to confirm that the cut-off value is also accompanied by higher psychological strain, high- and low-risk groups were compared in terms of their self-reported depressive symptoms, anxious symptoms, body dissatisfaction, and self-esteem. Results WBIS-C scores >= 1.55 were associated with a higher risk of disturbed eating behavior; for psychosocial problems, no cut-off score reached adequate sensitivity and specificity. Compared to relative weight status, WBI was better suited to detect disturbed eating behavior. Children with a WBIS-C score >= 1.55 also reported higher scores for both depressive and anxious symptoms, higher body dissatisfaction, and lower self-esteem. Conclusion The WBIS-C is suitable for identifying risk groups, and even low levels of WBI are accompanied by adverse mental health. Therefore, WBI is, beyond weight status, an important risk factor that should be considered in prevention and intervention.
Wild bee species are important pollinators in agricultural landscapes. However, population decline was reported over the last decades and is still ongoing. While agricultural intensification is a major driver of the rapid loss of pollinating species, transition zones between arable fields and forest or grassland patches, i.e., agricultural buffer zones, are frequently mentioned as suitable mitigation measures to support wild bee populations and other pollinator species. Despite the reported general positive effect, it remains unclear which amount of buffer zones is needed to ensure a sustainable and permanent impact for enhancing bee diversity and abundance. To address this question at a pollinator community level, we implemented a process-based, spatially explicit simulation model of functional bee diversity dynamics in an agricultural landscape. More specifically, we introduced a variable amount of agricultural buffer zones (ABZs) at the transition of arable to grassland, or arable to forest patches to analyze the impact on bee functional diversity and functional richness. We focused our study on solitary bees in a typical agricultural area in the Northeast of Germany. Our results showed positive effects with at least 25% of virtually implemented agricultural buffer zones. However, higher amounts of ABZs of at least 75% should be considered to ensure a sufficient increase in Shannon diversity and decrease in quasi-extinction risks. These high amounts of ABZs represent effective conservation measures to safeguard the stability of pollination services provided by solitary bee species. As the model structure can be easily adapted to other mobile species in agricultural landscapes, our community approach offers the chance to compare the effectiveness of conservation measures also for other pollinator communities in future.
Artificial light at night (ALAN) is altering the behaviour of nocturnal animals in a manifold of ways. Nocturnal invertebrates are particularly affected, due to their fatal attraction to ALAN. This selective pressure has the potential to reduce the strength of the flight-to-light response in insects, as shown recently in a moth species. Here we investigated light attraction of ground beetles (Coleoptera: Carabidae).We compared among animals (three genera) from a highly light polluted (HLP) grassland in the centre of Berlin and animals collected at a low-polluted area in a Dark Sky Reserve (DSR), captured using odour bait. In an arena setting tested at night time, HLP beetles (n = 75 across all genera) showed a reduced attraction towards ALAN. Tested during daytime, HLP beetles were less active in an open field test (measured as latency to start moving), compared to DSR (n = 143). However, we did not observe a reduced attraction towards ALAN within the species most common at both sides, Calathus fuscipes (HLP = 37, DSR = 118 individuals) indicating that not all species may be equally affected by ALAN. Reduced attraction to ALAN in urban beetles may either be a result of phenotypic selection in each generation removing HLP individuals that are attracted to light, or an indication for ongoing evolutionary differentiation among city and rural populations in their light response. Reduced attraction to light sources may directly enhance survival and reproductive success of urban individuals. However, decrease in mobility may negatively influence dispersal, reproduction and foraging success, highlighting the selective pressure that light pollution may have on fitness, by shaping and modifying the behaviour of insects.