Multidimensional cerebellar computations for flexible kinematic control of movements

Both the environment and our body keep changing dynamically. Hence, ensuring movement precision requires adaptation to multiple demands occurring simultaneously. Here we show that the cerebellum performs the necessary multi-dimensional computations for the flexible control of different movement parameters depending on the prevailing context. This conclusion is based on the identification of a manifold-like activity in both mossy fibers (MF, network input) and Purkinje cells (PC, output), recorded from monkeys performing a saccade task. Unlike MFs, the properties of PC manifolds developed selective representations of individual movement parameters. Error feedback-driven climbing fiber input modulated the PC manifolds to predict specific, error type-dependent changes in subsequent actions. Furthermore, a feed-forward network model that simulated MF-to-PC transformations revealed that amplification and restructuring of the lesser variability in the MF activity is a pivotal circuit mechanism. Therefore, flexible control of movement by the cerebellum crucially depends on its capacity for multi-dimensional computations.

Differencing strategies for SLR observations at the Wettzell observatory

The precise estimation of geodetic parameters using single- and double-differenced SLR observations is investigated. While the differencing of observables is a standard approach for the GNSS processing, double differences of simultaneous SLR observations are practically impossible to obtain due to the SLR basic principle of observing one satellite at a time. Despite this, the availability of co-located SLR telescopes and the use of the alternative concept of quasi-simultaneity allow the forming of SLR differences under certain assumptions, thus enabling the use of these processing strategies. These differences are in principle almost free of both, satellite- and station-specific error sources, and are shown to be a valuable tool to obtain relative coordinates and range biases, and to validate local ties. Tested with the two co-located SLR telescopes at the Geodetic Observatory Wettzell (Germany) using SLR observations to GLONASS and LAGEOS, the developed differencing approach shows that it is possible to obtain single- and double-difference residuals at the millimetre level, and that it is possible to estimate parameters, such as range biases at the stations and the local baseline vector with a precision at the millimetre level and an accuracy comparable to traditional terrestrial survey methods. The presented SLR differences constitute a valuable alternative for the monitoring of the local baselines and the estimation of geodetic parameters.

A recurrent circuit links antagonistic cerebellar modules during associative motor learning

The neural architecture of the cerebellum is thought to be specialized for performing supervised learning: specific error-related climbing fiber inputs are used to teach sensorimotor associations to small ensembles of Purkinje cells located in functionally distinct modules that operate independently of each other in a purely feedforward manner. Here, we test whether the basic operation of the cerebellum complies with this basic architecture in mice that learned a simple sensorimotor association during eyeblink conditioning. By recording Purkinje cells in different modules and testing whether their responses rely on recurrent circuits, our results reveal three operational principles about the functional organization of the cerebellum that stand in stark contrast to the conventional view: (1) Antagonistic organization, (2) Recurrent network dynamics, and (3) Intermodular communication. We propose that the neural architecture of the cerebellum implements these three operational principles to achieve optimal performance and solve a number of problems in motor control.

Vertical Deformation and Residual Altimeter Systematic Errors around Continental Australia Inferred from a Kalman-Based Approach

We further developed a space-time Kalman approach to estimate time-variable signals in residual altimeter systematic errors and vertical land motion (VLM) around the Australian coast since the 1990s, through combining multi-mission absolute sea-level (ASL), relative sea-level (RSL) from tide gauges (TGs) and GPS heights records. Our results confirmed continent-wide subsidence and TG-specific VLMs yielding a ~40% reduction in RMSE of geographical ASL variability, compared with rates determined using spatially interpolated GPS velocities that fail to capture localized trends by up to ~1.5 mm/yr. Stacked time series of non-linear deformation at TGs and nearby GPS showed some correlation, suggesting the technique was partially successful in reflecting the surface loading. Site-by-site inspection revealed spurious non-linearity likely caused by residual oceanographic signals present between the TG and altimeter measurement locations. Our average mission-specific error estimates are small but significant, typically within ~±0.5-1.0 mm/yr, with negligible effect implied on the overall rate of ASL. Analysis of the time variability of altimeter errors confirmed stability for most missions except for Jason-2 with an anomaly reaching ~2.8 mm/yr in the first ~3.5 years of operation which is supported by analysis from the Bass Strait altimeter validation facility. Weak correlation with the dominant climate mode suggests potential deficiencies in the resolution of the time-variable gravity field used for orbit determination as a possible cause, yet other drivers cannot be discounted. Our approach advances the ability to estimate TG-specific VLMs and regional altimeter systematic errors, and highlights that residual oceanographic signals remain a fundamental limitation to such techniques.

USE OF VIBRODIAGNOSTICS TO PREDICT PHENOMENA IN SERIAL AUTOMOTIVE PRODUCTION

The paper discusses the use of vibrodiagnostics in automotive production. Describes the Fast Fourier Transformation and its importance in evaluating the measured values. It focuses on the process of honing the toothing of shafts used in series-produced gearboxes. Describes 3 different states of amplitude with consideration to the set limit. In the first state, all production criteria are met. In the second state, the limit is exceeded and the specific error and its impact on the continuation of production are described. The third state describes the extreme crossing of the limit and the consequences for this state. Finally, the importance and practicality of the method for predicting production conditions are summarized.

Reasoning Method between Polynomial Error Assertions

Error coefficients are ubiquitous in systems. In particular, errors in reasoning verification must be considered regarding safety-critical systems. We present a reasoning method that can be applied to systems described by the polynomial error assertion (PEA). The implication relationship between PEAs can be converted to an inclusion relationship between zero sets of PEAs; the PEAs are then transformed into first-order polynomial logic. Combined with the quantifier elimination method, based on cylindrical algebraic decomposition, the judgment of the inclusion relationship between zero sets of PEAs is transformed into judgment error parameters and specific error coefficient constraints, which can be obtained by the quantifier elimination method. The proposed reasoning method is validated by proving the related theorems. An example of intercepting target objects is provided, and the correctness of our method is tested through large-scale random cases. Compared with reasoning methods without error semantics, our reasoning method has the advantage of being able to deal with error parameters.

Tools for measuring technical skills during gynaecologic surgery: a scoping review

Background Standardised assessment is key to structured surgical training. Currently, there is no consensus on which surgical assessment tool to use in live gynaecologic surgery. The purpose of this review is to identify assessment tools measuring technical skills in gynaecologic surgery and evaluate the measurement characteristics of each tool. Method We utilized the scoping review methodology and searched PubMed, Medline, Embase and Cochrane. Inclusion criteria were studies that analysed assessment tools in live gynaecologic surgery. Kane’s validity argument was applied to evaluate the assessment tools in the included studies. Results Eight studies out of the 544 identified fulfilled the inclusion criteria. The assessment tools were categorised as global rating scales, global and procedure rating scales combined, procedure-specific rating scales or as a non-procedure-specific error assessment tool. Conclusion This scoping review presents the current different tools for observational assessment of technical skills in intraoperative, gynaecologic surgery. This scoping review can serve as a guide for surgical educators who want to apply a scale or a specific tool in surgical assessment.

Violating the normality assumption may be the lesser of two evils

When data are not normally distributed, researchers are often uncertain whether it is legitimate to use tests that assume Gaussian errors, or whether one has to either model a more specific error structure or use randomization techniques. Here we use Monte Carlo simulations to explore the pros and cons of fitting Gaussian models to non-normal data in terms of risk of type I error, power and utility for parameter estimation. We find that Gaussian models are robust to non-normality over a wide range of conditions, meaning that p values remain fairly reliable except for data with influential outliers judged at strict alpha levels. Gaussian models also performed well in terms of power across all simulated scenarios. Parameter estimates were mostly unbiased and precise except if sample sizes were small or the distribution of the predictor was highly skewed. Transformation of data before analysis is often advisable and visual inspection for outliers and heteroscedasticity is important for assessment. In strong contrast, some non-Gaussian models and randomization techniques bear a range of risks that are often insufficiently known. High rates of false-positive conclusions can arise for instance when overdispersion in count data is not controlled appropriately or when randomization procedures ignore existing non-independencies in the data. Hence, newly developed statistical methods not only bring new opportunities, but they can also pose new threats to reliability. We argue that violating the normality assumption bears risks that are limited and manageable, while several more sophisticated approaches are relatively error prone and particularly difficult to check during peer review. Scientists and reviewers who are not fully aware of the risks might benefit from preferentially trusting Gaussian mixed models in which random effects account for non-independencies in the data.

Error Analysis of LAI Measurements with LAI-2000 Due to Discrete View Angular Range Angles for Continuous Canopies

As a widely used ground-based optical instrument, the LAI-2000 or LAI-2200 plant canopy analyzer (PCA) (Li-Cor, Inc., Lincoln, NE) is designed to measure the plant effective leaf area index (Le) by measuring the canopy gap fraction at several limited or discrete view zenith angles (VZAs) (usually five VZAs: 7, 23, 38, 53, and 68°) based on Miller’s equation. Miller’s equation requires the probability of radiative transmission through the canopy to be measured over the hemisphere, i.e., VZAs in the range from 0 to 90°. However, the PCA view angle ranges are confined to several limited ranges or discrete sectors. The magnitude of the error produced by the discretization of VZAs in the leaf area index measurements remains difficult to determine. In this study, a theoretical deduction was first presented to definitely prove why the limited or discrete VZAs or ranges can affect the Le measured with the PCA, and the specific error caused by the limited or discrete VZAs was described quantitatively. The results show that: (1) the weight coefficient of the last PCA ring is the main cause of the error; (2) the error is closely related to the leaf inclination angles (IAs)—the Le measured with the PCA can be significantly overestimated for canopies with planophile IAs, whereas it can be underestimated for erectophile IAs; and (3) the error can be enhanced with the increment of the discrete degree of PCA rings or VZAs, such as using four or three PCA rings. Two corrections for the error are presented and validated in three crop canopies. Interestingly, although the leaf IA type cannot influence the Le calculated by Miller’s equation in the hemispheric space, it affects the Le measured with the PCA using the discrete form of Miller’s equation for several discrete VZAs.

How Many Soil Samples Do We Need to Take to Determine Concentrations of Micro- and Nanoplastics in Terrestrial Systems?

<p>Plastics pollution of terrestrial environments is a global problem, and plastics have been observed even in remote areas. However, how much plastic is present in terrestrial ecosystems is not well known. Here, we present a theoretical framework for representative sampling of randomly distributed plastic particles in soils or sediments. Based on geostatistical analysis, we determined optimal sampling strategies to quantify micro- and nanoplastics in soils or sediments. We used numerical simulations to test the sampling of randomly distributed plastic particles, and determined the sampling support (number of cores or sampling area) needed to obtain plastic concentrations within a specific error. Plastic pollution in the field was numerically simulated by placing plastic particles randomly in two dimensional space. We then took soil samples with differently sized cores, and determined plastic concentration as a function of number of cores taken. We will show how many cores are needed to determine the plastic concentrations within a given error.</p>