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Ore precipitation in porphyry copper systems is generally characterized by metal zoning (Cu-Mo to Zn-Pb-Ag), which is suggested to be variably related to solubility decreases during fluid cooling, fluid-rock interactions, partitioning during fluid phase separation and mixing with external fluids. Here, we present new advances of a numerical process model by considering published constraints on the temperature- and salinity-dependent solubility of Cu, Pb and Zn in the ore fluid. We quantitatively investigate the roles of vapor-brine separation, halite saturation, initial metal contents, fluid mixing and remobilization as first-order controls of the physical hydrology on ore formation. The results show that the magmatic vapor and brine phases ascend with different residence times but as miscible fluid mixtures, with salinity increases generating metal-undersaturated bulk fluids. The release rates of magmatic fluids affect the location of the thermohaline fronts, leading to contrasting mechanisms for ore precipitation: higher rates result in halite saturation without significant metal zoning, lower rates produce zoned ore shells due to mixing with meteoric water. Varying metal contents can affect the order of the final metal precipitation sequence. Redissolution of precipitated metals results in zoned ore shell patterns in more peripheral locations and also decouples halite saturation from ore precipitation.
We present a Reduced Order Model (ROM) which exploits recent developments in Physics Informed Neural Networks (PINNs) for solving inverse problems for the Navier-Stokes equations (NSE). In the proposed approach, the presence of simulated data for the fluid dynamics fields is assumed. A POD-Galerkin ROM is then constructed by applying POD on the snapshots matrices of the fluid fields and performing a Galerkin projection of the NSE (or the modified equations in case of turbulence modeling) onto the POD reduced basis. A POD-Galerkin PINN ROM is then derived by introducing deep neural networks which approximate the reduced outputs with the input being time and/or parameters of the model. The neural networks incorporate the physical equations (the POD-Galerkin reduced equations) into their structure as part of the loss function. Using this approach, the reduced model is able to approximate unknown parameters such as physical constants or the boundary conditions. A demonstration of the applicability of the proposed ROM is illustrated by three cases which are the steady flow around a backward step, the flow around a circular cylinder and the unsteady turbulent flow around a surface mounted cubic obstacle.
The oil palm (Elaeis guineensis Jacq.) produces a large amount of oil from the fruit. However, increasing the oil production in this fruit is still challenging. A recent study has shown that starch metabolism is essential for oil synthesis in fruit-producing species. Therefore, the transcriptomic analysis by RNA-seq was performed to observe gene expression alteration related to starch metabolism genes throughout the maturity stages of oil palm fruit with different oil yields. Gene expression profiles were examined with three different oil yields group (low, medium, and high) at six fruit development phases (4, 8, 12, 16, 20, and 22 weeks after pollination). We successfully identified and analyzed differentially expressed genes in oil palm mesocarps during development. The results showed that the transcriptome profile for each developmental phase was unique. Sucrose flux to the mesocarp tissue, rapid starch turnover, and high glycolytic activity have been identified as critical factors for oil production in oil palms. For starch metabolism and the glycolytic pathway, we identified specific gene expressions of enzyme isoforms (isozymes) that correlated with oil production, which may determine the oil content. This study provides valuable information for creating new high-oil-yielding palm varieties via breeding programs or genome editing approaches.
Background
Self-regulation (SR) as the ability to regulate one's own physical state, emotions, cognitions, and behavior, is considered to play a pivotal role in the concurrent and subsequent mental and physical health of an individual. Although SR skills encompass numerous sub-facets, previous research has often focused on only one or a few of these sub-facets, and only rarely on adolescence. Therefore, little is known about the development of the sub-facets, their interplay, and their specific contributions to future developmental outcomes, particularly in adolescence. To fill these research gaps, this study aims to prospectively examine (1) the development of SR and (2) their influence on adolescent-specific developmental outcomes in a large community sample.
Methods/design
Based on previously collected data from the Potsdam Intrapersonal Developmental Risk (PIER) study with three measurement points, the present prospective, longitudinal study aims to add a fourth measurement point (PIERYOUTH). We aim to retain at least 1074 participants now between 16 and 23 years of the initially 1657 participants (6-11 years of age at the first measurement point in 2012/2013; 52.2% female). The study will continue to follow a multi-method (questionnaires, physiological assessments, performance-based computer tasks), multi-facet (assessing various domains of SR), and multi-rater (self-, parent-, and teacher-report) approach. In addition, a broad range of adolescent-specific developmental outcomes is considered. In doing so, we will cover the development of SR and relevant outcomes over the period of 10 years. In addition, we intend to conduct a fifth measurement point (given prolonged funding) to investigate development up to young adulthood.
Discussion
With its broad and multimethodological approach, PIERYOUTH aims to contribute to a deeper understanding of the development and role of various SR sub-facets from middle childhood to adolescence. The large sample size and low drop-out rates in the first three measurements points form a sound database for our present prospective research.Trial registration German Clinical Trials Register, registration number DRKS00030847.
Keeping cool on hot days
(2023)
Long-lived organisms are likely to respond to a rapidly changing climate with behavioral flexibility. Animals inhabiting the arid parts of southern Africa face a particularly rapid rise in temperature which in combination with food and water scarcity places substantial constraints on the ability of animals to tolerate heat. We investigated how three species of African antelope-springbok Antidorcas marsupialis, kudu Tragelaphus strepsiceros and eland T. oryx-differing in body size, habitat preference and movement ecology, change their activity in response to extreme heat in an arid savanna. Serving as a proxy for activity, dynamic body acceleration data recorded every five minutes were analyzed for seven to eight individuals per species for the three hottest months of the year. Activity responses to heat during the hottest time of day (the afternoons) were investigated and diel activity patterns were compared between hot and cool days. Springbok, which prefer open habitat, are highly mobile and the smallest of the species studied, showed the greatest decrease in activity with rising temperature. Furthermore, springbok showed reduced mean activity over the 24 h cycle on hot days compared to cool days. Large-bodied eland seemed less affected by afternoon heat than springbok. While eland also reduced diurnal activity on hot days compared to cool days, they compensated for this by increasing nocturnal activity, possibly because their predation risk is lower. Kudu, which are comparatively sedentary and typically occupy shady habitat, seemed least affected during the hottest time of day and showed no appreciable difference in diel activity patterns between hot and cool days. The interplay between habitat preference, body size, movement patterns, and other factors seems complex and even sub-lethal levels of heat stress have been shown to impact an animal's long-term survival and reproduction. Thus, differing heat tolerances among species could result in a shift in the composition of African herbivore communities as temperatures continue to rise, with significant implications for economically important wildlife-based land use and conservation.
Starch has been a convenient, economically important polymer with substantial applications in the food and processing industry. However, native starches present restricted applications, which hinder their industrial usage. Therefore, modification of starch is carried out to augment the positive characteristics and eliminate the limitations of the native starches. Modifications of starch can result in generating novel polymers with numerous functional and value-added properties that suit the needs of the industry. Here, we summarize the possible starch modifications in planta and outside the plant system (physical, chemical, and enzymatic) and their corresponding applications. In addition, this review will highlight the implications of each starch property adjustment.
Students enter school with a vast range of individual differences, resulting from the complex interplay between genetic dispositions and unequal environmental conditions. Schools thus face the challenge of organizing instruction and providing equal opportunities for students with diverse needs. Schools have traditionally managed student heterogeneity by sorting students both within and between schools according to their academic ability. However, empirical evidence suggests that such tracking approaches increase inequalities. In more recent years, driven largely by technological advances, there have been calls to embrace students' individual differences in the classroom and to personalize students' learning experiences. A central justification for personalized learning is its potential to improve educational equity. In this paper, we discuss whether and under which conditions personalized learning can indeed increase equity in K-12 education by bringing together empirical and theoretical insights from different fields, including the learning sciences, philosophy, psychology, and sociology. We distinguish between different conceptions of equity and argue that personalized learning is unlikely to result in "equality of outcomes" and, by definition, does not provide "equality of inputs". However, if implemented in a high-quality way, personalized learning is in line with "adequacy" notions of equity, which aim to equip all students with the basic competencies to participate in society as active members and to live meaningful lives.
Knowledge on the response of sediment export to recent climate change in glacierized areas in the European Alps is limited, primarily because long-term records of suspended sediment concentrations (SSCs) are scarce. Here we tested the estimation of sediment export of the past five decades using quantile regression forest (QRF), a nonparametric, multivariate regression based on random forest. The regression builds on short-term records of SSCs and long records of the most important hydroclimatic drivers (discharge, precipitation and air temperature - QPT). We trained independent models for two nested and partially glacier-covered catchments, Vent (98 km(2)) and Vernagt (11.4 km(2)), in the upper otztal in Tyrol, Austria (1891 to 3772 m a.s.l.), where available QPT records start in 1967 and 1975. To assess temporal extrapolation ability, we used two 2-year SSC datasets at gauge Vernagt, which are almost 20 years apart, for a validation. For Vent, we performed a five-fold cross-validation on the 15 years of SSC measurements. Further, we quantified the number of days where predictors exceeded the range represented in the training dataset, as the inability to extrapolate beyond this range is a known limitation of QRF. Finally, we compared QRF performance to sediment rating curves (SRCs). We analyzed the modeled sediment export time series, the predictors and glacier mass balance data for trends (Mann-Kendall test and Sen's slope estimator) and step-like changes (using the widely applied Pettitt test and a complementary Bayesian approach).Our validation at gauge Vernagt demonstrated that QRF performs well in estimating past daily sediment export (Nash-Sutcliffe efficiency (NSE) of 0.73) and satisfactorily for SSCs (NSE of 0.51), despite the small training dataset. The temporal extrapolation ability of QRF was superior to SRCs, especially in periods with high-SSC events, which demonstrated the ability of QRF to model threshold effects. Days with high SSCs tended to be underestimated, but the effect on annual yields was small. Days with predictor exceedances were rare, indicating a good representativity of the training dataset. Finally, the QRF reconstruction models outperformed SRCs by about 20 percent points of the explained variance.Significant positive trends in the reconstructed annual suspended sediment yields were found at both gauges, with distinct step-like increases around 1981. This was linked to increased glacier melt, which became apparent through step-like increases in discharge at both gauges as well as change points in mass balances of the two largest glaciers in the Vent catchment. We identified exceptionally high July temperatures in 1982 and 1983 as a likely cause. In contrast, we did not find coinciding change points in precipitation. Opposing trends at the two gauges after 1981 suggest different timings of "peak sediment". We conclude that, given large-enough training datasets, the presented QRF approach is a promising tool with the ability to deepen our understanding of the response of high-alpine areas to decadal climate change.
Background:
Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination.
Results:
We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles.
Conclusion:
GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.
Background
The aggregation of a series of N-of-1 trials presents an innovative and efficient study design, as an alternative to traditional randomized clinical trials. Challenges for the statistical analysis arise when there is carry-over or complex dependencies of the treatment effect of interest.
Methods
In this study, we evaluate and compare methods for the analysis of aggregated N-of-1 trials in different scenarios with carry-over and complex dependencies of treatment effects on covariates. For this, we simulate data of a series of N-of-1 trials for Chronic Nonspecific Low Back Pain based on assumed causal relationships parameterized by directed acyclic graphs. In addition to existing statistical methods such as regression models, Bayesian Networks, and G-estimation, we introduce a carry-over adjusted parametric model (COAPM).
Results
The results show that all evaluated existing models have a good performance when there is no carry-over and no treatment dependence. When there is carry-over, COAPM yields unbiased and more efficient estimates while all other methods show some bias in the estimation. When there is known treatment dependence, all approaches that are capable to model it yield unbiased estimates. Finally, the efficiency of all methods decreases slightly when there are missing values, and the bias in the estimates can also increase.
Conclusions
This study presents a systematic evaluation of existing and novel approaches for the statistical analysis of a series of N-of-1 trials. We derive practical recommendations which methods may be best in which scenarios.
Graphene is well-knownfor its unique combination of electricaland mechanical properties. However, its vanishing band gap limitsthe use of graphene in microelectronics. Covalent functionalizationof graphene has been a common approach to address this critical issueand introduce a band gap. In this Article, we systematically analyzethe functionalization of single-layer graphene (SLG) and bilayer graphene(BLG) with methyl (CH3) using periodic density functionaltheory (DFT) at the PBE+D3 level of theory. We also include a comparisonof methylated single-layer and bilayer graphene, as well as a discussionof different methylation options (radicalic, cationic, and anionic).For SLG, methyl coverages ranging from 1/8 to 1/1, (i.e.,the fully methylated analogue of graphane) are considered. We findthat up to a coverage theta of 1/2, graphene readily accepts CH3, with neighbor CH3 groups preferring trans positions. Above theta = 1/2, the tendency to accept further CH3 weakens and the lattice constant increases. The band gapbehaves less regularly, but overall it increases with increasing methylcoverage. Thus, methylated graphene shows potential for developingband gap-tuned microelectronics devices and may offer further functionalizationoptions. To guide in the interpretation of methylation experiments,vibrational signatures of various species are characterized by normal-modeanalysis (NMA), their vibrational density of states (VDOS), and infrared(IR) spectra, the latter two are obtained from ab initio moleculardynamics (AIMD) in combination with a velocity-velocity autocorrelationfunction (VVAF) approach.
Genomic and epigenomic determinants of heat stress-induced transcriptional memory in Arabidopsis
(2023)
Background
Transcriptional regulation is a key aspect of environmental stress responses. Heat stress induces transcriptional memory, i.e., sustained induction or enhanced re-induction of transcription, that allows plants to respond more efficiently to a recurrent HS. In light of more frequent temperature extremes due to climate change, improving heat tolerance in crop plants is an important breeding goal. However, not all heat stress-inducible genes show transcriptional memory, and it is unclear what distinguishes memory from non-memory genes. To address this issue and understand the genome and epigenome architecture of transcriptional memory after heat stress, we identify the global target genes of two key memory heat shock transcription factors, HSFA2 and HSFA3, using time course ChIP-seq.
Results
HSFA2 and HSFA3 show near identical binding patterns. In vitro and in vivo binding strength is highly correlated, indicating the importance of DNA sequence elements. In particular, genes with transcriptional memory are strongly enriched for a tripartite heat shock element, and are hallmarked by several features: low expression levels in the absence of heat stress, accessible chromatin environment, and heat stress-induced enrichment of H3K4 trimethylation. These results are confirmed by an orthogonal transcriptomic data set using both de novo clustering and an established definition of memory genes.
Conclusions
Our findings provide an integrated view of HSF-dependent transcriptional memory and shed light on its sequence and chromatin determinants, enabling the prediction and engineering of genes with transcriptional memory behavior.
Economic evaluation of digital therapeutic care apps for unsupervised treatment of low back pain
(2023)
Background:
Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany.
Objective:
The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results.
Methods:
The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany.
Results:
The Monte Carlo simulation yielded on average a euro135.97 (a currency exchange rate of EUR euro1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional euro34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently euro239.96 to euro164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%.
Conclusions:
Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.
Reliability of the active knee joint position sense test and influence of limb dominance and sex
(2023)
The output of a sensorimotor performance can be measured with the joint position sense (JPS) test. However, investigations of leg dominance, sex and quality measures on this test are limited. Therefore, these potential influencing factors as well as reliability and consistency measures were evaluated for angular reproduction performance and neuromuscular activity during the active knee JPS test in healthy participants. Twenty healthy participants (10 males; 10 females; age 29 +/- 8 years; height 165 +/- 39 cm; body mass 69 +/- 13 kg) performed a seated knee JPS test with a target angle of 50 degrees. Measurements were conducted in two sessions separated by two weeks and consisted of two blocks of continuous angular reproduction (three minutes each block). The difference between reproduced and target angle was identified as angular error measured by an electrogoniometer. During reproduction, the neuromuscular activity of the quadriceps muscle was assessed by surface electromyography. Neuromuscular activity was normalized to submaximal voluntary contraction (subMVC) and displayed per muscle and movement phase. Differences between leg dominance and sex were calculated using Friedman-test (alpha = 0.05). Reliability measures including intraclass correlation coefficient (ICC), Bland-Altman analysis (bias +/- limits of agreement (LoA)) and minimal detectable change (MDC) were analysed. No significant differences between leg dominance and sex were found in angular error and neuromuscular activity. Angular error demonstrated inter-session ICC scores of 0.424 with a bias of 2.4 degrees (+/- 2.4 degrees LoA) as well as MDC of 6.8 degrees and moderate intra-session ICC (0.723) with a bias of 1.4 degrees (+/- 1.65 degrees LoA) as well as MDC of 4.7 degrees. Neuromuscular activity for all muscles and movement phases illustrated inter-session ICC ranging from 0.432 to 0.809 with biases between - 2.5 and 13.6% subMVC and MDC from 13.4 to 63.9% subMVC. Intra-session ICC ranged from 0.705 to 0.987 with biases of - 7.7 to 2.4% subMVC and MDC of 2.7 to 46.5% subMVC. Leg dominance and sex seem not to influence angular reproduction performance and neuromuscular activity. Poor to excellent relative reliability paired with an acceptable consistency confirm findings of previous studies. Comparisons to pathological populations should be conducted with caution.
Poema
(2023)
POEMA ist ein komparatistisch angelegtes Jahrbuch, das sich der systematischen Erforschung von Lyrik und Gedicht widmet. Es richtet sich an Fachwissenschaftlerinnen und Fachwissenschaftler aller Philologien wie auch der mit anderen Kunstformen befassten Wissenschaften und der philosophischen Ästhetik. POEMA erscheint als Open-Access-Journal wie auch als Print-on-Demand-Fassung im Universitätsverlag Kiel | Kiel University Publishing. Die wissenschaftlichen Beiträge werden in einem double-blind Peer-Review-Verfahren begutachtet.
Quinoa (Chenopodium quinoa Willd.) is an herbaceous annual crop of the amaranth family (Amaranthaceae). It is increasingly cultivated for its nutritious grains, which are rich in protein and essential amino acids, lipids, and minerals. Quinoa exhibits a high tolerance towards various abiotic stresses including drought and salinity, which supports its agricultural cultivation under climate change conditions. The use of quinoa grains is compromised by anti-nutritional saponins, a terpenoid class of secondary metabolites deposited in the seed coat; their removal before consumption requires extensive washing, an economically and environmentally unfavorable process; or their accumulation can be reduced through breeding. In this study, we analyzed the seed metabolomes, including amino acids, fatty acids, and saponins, from 471 quinoa cultivars, including two related species, by liquid chromatography - mass spectrometry. Additionally, we determined a large number of agronomic traits including biomass, flowering time, and seed yield. The results revealed considerable diversity between genotypes and provide a knowledge base for future breeding or genome editing of quinoa.
The heat is on
(2023)
Climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe. Wildlife can respond to new climatic conditions, but the pace of human-induced change limits opportunities for adaptation or migration. Thus, how these changes affect behavior, movement patterns, and activity levels remains unclear. In this study, we investigate how extreme weather conditions affect the activity of European hares (Lepus europaeus) during their peak reproduction period. When hares must additionally invest energy in mating, prevailing against competitors, or lactating, we investigated their sensitivities to rising temperatures, wind speed, and humidity. To quantify their activity, we used the overall dynamic body acceleration (ODBA) calculated from tri-axial acceleration measurements of 33 GPS-collared hares. Our analysis revealed that temperature, humidity, and wind speed are important in explaining changes in activity, with a strong response for high temperatures above 25 & DEG;C and the highest change in activity during temperature extremes of over 35 & DEG;C during their inactive period. Further, we found a non-linear relationship between temperature and activity and an interaction of activity changes between day and night. Activity increased at higher temperatures during the inactive period (day) and decreased during the active period (night). This decrease was strongest during hot tropical nights. At a stage of life when mammals such as hares must substantially invest in reproduction, the sensitivity of females to extreme temperatures was particularly pronounced. Similarly, both sexes increased their activity at high humidity levels during the day and low wind speeds, irrespective of the time of day, while the effect of humidity was stronger for males. Our findings highlight the importance of understanding the complex relationships between extreme weather conditions and mammal behavior, critical for conservation and management. With ongoing climate change, extreme weather events such as heat waves and heavy rainfall are predicted to occur more often and last longer. These events will directly impact the fitness of hares and other wildlife species and hence the population dynamics of already declining populations across Europe.
Perception of peripersonal space (PPS) and interpersonal distance (IPD) has been shown to be modified by external factors such as perceived danger, the use of tools, and social factors. Especially in times of social distancing in the context of the COVID-19 pandemic, it is vital to study factors that modify PPS and IPD. The present work addresses the question of whether wearing a face mask as a protection tool and social interaction impact the perception of IPD. We tested estimated IPD in pictures at three distances: 50 cm, 90 cm, and 150 cm in both social interaction (shaking hands) and without interaction and when the two people in the pictures wore a face mask or not. Data from 60 subjects were analyzed in a linear mixed model (on both difference in distance estimation to the depicted distance and in absolute distance estimation) and in a 3 (distance: 50, 90, 150) x 2 (interaction: no interaction, shake hands), x 2 face mask (no mask, mask) rmANOVA on distance estimation difference. All analyses showed that at a distance of 50 and 90 cm, participants generally underestimated the IPD while at an IPD of 150 cm, participants overestimated the distance. This could be grounded in perceived danger and avoidance behavior at closer distances, while the wider distance between persons was not perceived as dangerous. Our findings at an IPD of 90 cm show that social interaction has the largest effect at the border of our PPS, while the face mask did not affect social interaction at either distance. In addition, the ANOVA results indicate that when no social interaction was displayed, participants felt less unsafe when depicted persons wore a face mask at distances of 90 and 150 cm. This shows that participants are on the one hand aware of the given safety measures and internalized them; on the other hand, that refraining from physical social interaction helps to get close to other persons.
Sensorimotor control can be impaired by slacked muscle spindles. This was shown for reflex responses and, recently, also for muscular stability in the sense of Adaptive Force (AF). The slack in muscle spindles was generated by contracting the lengthened muscle followed by passive shortening. AF was suggested to specifically reflect sensorimotor control since it requires tension-length control in adaptation to an increasing load. This study investigated AF parameters in reaction to another, manually performed slack procedure in a preselected sample (n = 13). The AF of 11 elbow and 12 hip flexors was assessed by an objectified manual muscle test (MMT) using a handheld device. Maximal isometric AF was significantly reduced after manual spindle technique vs. regular MMT. Muscle lengthening started at 64.93 & PLUSMN; 12.46% of maximal voluntary isometric contraction (MVIC). During regular MMT, muscle length could be maintained stable until 92.53 & PLUSMN; 10.12% of MVIC. Hence, muscular stability measured by AF was impaired after spindle manipulation. Force oscillations arose at a significantly lower level for regular vs. spindle. This supports the assumption that they are a prerequisite for stable adaptation. Reduced muscular stability in reaction to slack procedures is considered physiological since sensory information is misled. It is proposed to use slack procedures to test the functionality of the neuromuscular system, which is relevant for clinical practice.