An Inverse Optimal Control Approach to Explain Human Arm Reaching Control Based on Multiple Internal Models

Human motor control is highly efficient in generating accurate and appropriate motor behavior for a multitude of tasks. This paper examines how kinematic and dynamic properties of the musculoskeletal system are controlled to achieve such efficiency. Even though recent studies have shown that the human motor control relies on multiple models, how the central nervous system (CNS) controls this combination is not fully addressed. In this study, we utilize an Inverse Optimal Control (IOC) framework in order to find the combination of those internal models and how this combination changes for different reaching tasks. We conducted an experiment where participants executed a comprehensive set of free-space reaching motions. The results show that there is a trade-off between kinematics and dynamics based controllers depending on the reaching task. In addition, this trade-off depends on the initial and final arm configurations, which in turn affect the musculoskeletal load to be controlled. Given this insight, we further provide a discomfort metric to demonstrate its influence on the contribution of different inverse internal models. This formulation together with our analysis not only support the multiple internal models (MIMs) hypothesis but also suggest a hierarchical framework for the control of human reaching motions by the CNS

Modeling Megathrust Earthquakes Across Scales: One‐way Coupling From Geodynamics and Seismic Cycles to Dynamic Rupture

Taking the full complexity of subduction zones into account is important for realistic modeling and hazard assessment of subduction zone seismicity and associated tsunamis. Studying seismicity requires numerical methods that span a large range of spatial and temporal scales. We present the first coupled framework that resolves subduction dynamics over millions of years and earthquake dynamics down to fractions of a second. Using a two‐dimensional geodynamic seismic cycle (SC) model, we model 4 million years of subduction followed by cycles of spontaneous megathrust events. At the initiation of one such SC event, we export the self‐consistent fault and surface geometry, fault stress and strength, and heterogeneous material properties to a dynamic rupture (DR) model. Coupling leads to spontaneous dynamic rupture nucleation, propagation, and arrest with the same spatial characteristics as in the SC model. It also results in a similar material‐dependent stress drop, although dynamic slip is significantly larger. The DR event shows a high degree of complexity, featuring various rupture styles and speeds, precursory phases, and fault reactivation. Compared to a coupled model with homogeneous material properties, accounting for realistic lithological contrasts doubles the amount of maximum slip, introduces local pulse‐like rupture episodes, and relocates the peak slip from near the downdip limit of the seismogenic zone to the updip limit. When an SC splay fault is included in the DR model, the rupture prefers the splay over the shallow megathrust, although wave reflections do activate the megathrust afterward

Coupled, Physics-Based Modeling Reveals Earthquake Displacements are Critical to the 2018 Palu, Sulawesi Tsunami

The September 2018, Mw 7.5 Sulawesi earthquake occurring on the Palu-Koro strike-slip fault system was followed by an unexpected localized tsunami. We show that direct earthquake-induced uplift and subsidence could have sourced the observed tsunami within Palu Bay. To this end, we use a physics-based, coupled earthquake–tsunami modeling framework tightly constrained by observations. The model combines rupture dynamics, seismic wave propagation, tsunami propagation and inundation. The earthquake scenario, featuring sustained supershear rupture propagation, matches key observed earthquake characteristics, including the moment magnitude, rupture duration, fault plane solution, teleseismic waveforms and inferred horizontal ground displacements. The remote stress regime reflecting regional transtension applied in the model produces a combination of up to 6 m left-lateral slip and up to 2 m normal slip on the straight fault segment dipping 65∘ East beneath Palu Bay. The time-dependent, 3D seafloor displacements are translated into bathymetry perturbations with a mean vertical offset of 1.5 m across the submarine fault segment. This sources a tsunami with wave amplitudes and periods that match those measured at the Pantoloan wave gauge and inundation that reproduces observations from field surveys. We conclude that a source related to earthquake displacements is probable and that landsliding may not have been the primary source of the tsunami. These results have important implications for submarine strike-slip fault systems worldwide. Physics-based modeling offers rapid response specifically in tectonic settings that are currently underrepresented in operational tsunami hazard assessment

Comparative Genomics and Transcriptomics of Propionibacterium acnes

The anaerobic Gram-positive bacterium Propionibacterium acnes is a human skin commensal that is occasionally associated with inflammatory diseases. Recent work has indicated that evolutionary distinct lineages of P. acnes play etiologic roles in disease while others are associated with maintenance of skin homeostasis. To shed light on the molecular basis for differential strain properties, we carried out genomic and transcriptomic analysis of distinct P. acnes strains. We sequenced the genome of the P. acnes strain 266, a type I-1a strain. Comparative genome analysis of strain 266 and four other P. acnes strains revealed that overall genome plasticity is relatively low; however, a number of island-like genomic regions, encoding a variety of putative virulence-associated and fitness traits differ between phylotypes, as judged from PCR analysis of a collection of P. acnes strains. Comparative transcriptome analysis of strains KPA171202 (type I-2) and 266 during exponential growth revealed inter-strain differences in gene expression of transport systems and metabolic pathways. In addition, transcript levels of genes encoding possible virulence factors such as dermatan-sulphate adhesin, polyunsaturated fatty acid isomerase, iron acquisition protein HtaA and lipase GehA were upregulated in strain 266. We investigated differential gene expression during exponential and stationary growth phases. Genes encoding components of the energy-conserving respiratory chain as well as secreted and virulence-associated factors were transcribed during the exponential phase, while the stationary growth phase was characterized by upregulation of genes involved in stress responses and amino acid metabolism. Our data highlight the genomic basis for strain diversity and identify, for the first time, the actively transcribed part of the genome, underlining the important role growth status plays in the inflammation-inducing activity of P. acnes. We argue that the disease-causing potential of different P. acnes strains is not only determined by the phylotype-specific genome content but also by variable gene expression

Pyrosequencing-Based Assessment of Bacterial Community Structure Along Different Management Types in German Forest and Grassland Soils

BACKGROUND: Soil bacteria are important drivers for nearly all biogeochemical cycles in terrestrial ecosystems and participate in most nutrient transformations in soil. In contrast to the importance of soil bacteria for ecosystem functioning, we understand little how different management types affect the soil bacterial community composition. METHODOLOGY/PRINCIPAL FINDINGS: We used pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to identify changes in bacterial diversity and community structure in nine forest and nine grassland soils from the Schwäbische Alb that covered six different management types. The dataset comprised 598,962 sequences that were affiliated to the domain Bacteria. The number of classified sequences per sample ranged from 23,515 to 39,259. Bacterial diversity was more phylum rich in grassland soils than in forest soils. The dominant taxonomic groups across all samples (>1% of all sequences) were Acidobacteria, Alphaproteobacteria, Actinobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Firmicutes. Significant variations in relative abundances of bacterial phyla and proteobacterial classes, including Actinobacteria, Firmicutes, Verrucomicrobia, Cyanobacteria, Gemmatimonadetes and Alphaproteobacteria, between the land use types forest and grassland were observed. At the genus level, significant differences were also recorded for the dominant genera Phenylobacter, Bacillus, Kribbella, Streptomyces, Agromyces, and Defluviicoccus. In addition, soil bacterial community structure showed significant differences between beech and spruce forest soils. The relative abundances of bacterial groups at different taxonomic levels correlated with soil pH, but little or no relationships to management type and other soil properties were found. CONCLUSIONS/SIGNIFICANCE: Soil bacterial community composition and diversity of the six analyzed management types showed significant differences between the land use types grassland and forest. Furthermore, bacterial community structure was largely driven by tree species and soil pH

Sequence of the hyperplastic genome of the naturally competent Thermus scotoductus SA-01

<p>Abstract</p> <p>Background</p> <p>Many strains of <it>Thermus </it>have been isolated from hot environments around the world. <it>Thermus scotoductus </it>SA-01 was isolated from fissure water collected 3.2 km below surface in a South African gold mine. The isolate is capable of dissimilatory iron reduction, growth with oxygen and nitrate as terminal electron acceptors and the ability to reduce a variety of metal ions, including gold, chromate and uranium, was demonstrated. The genomes from two different <it>Thermus thermophilus </it>strains have been completed. This paper represents the completed genome from a second <it>Thermus </it>species - <it>T. scotoductus</it>.</p> <p>Results</p> <p>The genome of <it>Thermus scotoductus </it>SA-01 consists of a chromosome of 2,346,803 bp and a small plasmid which, together are about 11% larger than the <it>Thermus thermophilus </it>genomes. The <it>T. thermophilus </it>megaplasmid genes are part of the <it>T. scotoductus </it>chromosome and extensive rearrangement, deletion of nonessential genes and acquisition of gene islands have occurred, leading to a loss of synteny between the chromosomes of <it>T. scotoductus and T. thermophilus</it>. At least nine large inserts of which seven were identified as alien, were found, the most remarkable being a denitrification cluster and two operons relating to the metabolism of phenolics which appear to have been acquired from <it>Meiothermus ruber</it>. The majority of acquired genes are from closely related species of the Deinococcus-Thermus group, and many of the remaining genes are from microorganisms with a thermophilic or hyperthermophilic lifestyle. The natural competence of <it>Thermus scotoductus </it>was confirmed experimentally as expected as most of the proteins of the natural transformation system of <it>Thermus thermophilus </it>are present. Analysis of the metabolic capabilities revealed an extensive energy metabolism with many aerobic and anaerobic respiratory options. An abundance of sensor histidine kinases, response regulators and transporters for a wide variety of compounds are indicative of an oligotrophic lifestyle.</p> <p>Conclusions</p> <p>The genome of <it>Thermus scotoductus </it>SA-01 shows remarkable plasticity with the loss, acquisition and rearrangement of large portions of its genome compared to <it>Thermus thermophilus</it>. Its ability to naturally take up foreign DNA has helped it adapt rapidly to a subsurface lifestyle in the presence of a dense and diverse population which acted as source of nutrients. The genome of <it>Thermus scotoductus </it>illustrates how rapid adaptation can be achieved by a highly dynamic and plastic genome.</p

A Hybrid Framework for Understanding and Predicting Human Reaching Motions

Robots collaborating naturally with a human partner in a confined workspace need to understand and predict human motions. For understanding, a model-based approach is required as the human motor control system relies on the biomechanical properties to control and execute actions. The model-based control models explain human motions descriptively, which in turn enables predicting and analyzing human movement behaviors. In motor control, reaching motions are framed as an optimization problem. However, different optimality criteria predict disparate motion behavior. Therefore, the inverse problem—finding the optimality criterion from a given arm motion trajectory—is not unique. This paper implements an inverse optimal control (IOC) approach to determine the combination of cost functions that governs a motion execution. The results indicate that reaching motions depend on a trade-off between kinematics and dynamics related cost functions. However, the computational efficiency is not sufficient for online prediction to be utilized for HRI. In order to predict human reaching motions with high efficiency and accuracy, we combine the IOC approach with a probabilistic movement primitives formulation. This hybrid model allows an online-capable prediction while taking into account motor variability and the interpersonal differences. The proposed framework affords a descriptive and a generative model of human reaching motions which can be effectively utilized online for human-in-the-loop robot control and task execution