Experiments on barotropic–baroclinic conversion and the applicability of linear n-layer internal wave theories

Interfacial internal waves in a stratified fluid excited by periodic free-surface perturbations in a closed tank are studied experimentally. Barotropic-baroclinic energy conversion is induced by the presence of a bottom obstacle. The connection between horizontal surface velocities and internal wave amplitudes is investigated, the developing flow patterns are described qualitatively, and the wave speeds of internal waves are systematically analyzed and compared to linear 2- and 3-layer theories. We find that, despite of the fact that the observed internal waves can have considerable amplitudes, a linear 3-layer approximation still gives fairly good agreement with the experimental results

Is the Atlantic Multidecadal Oscillation (AMO) a statistical phantom?

In this work we critically compare the consequences of two assumptions on the physical nature of the AMO index signal. First, we show that the widely used approach based on red noise statistics cannot fully reproduce the empirical correlation properties of the record. Second, we consider a process of long range power-law correlations and demonstrate its better fit to the AMO signal. We show that in the latter case, the multidecadal oscillatory mode of the smoothed AMO index with an assigned period length of 50-70 years can be a simple statistical artifact, a consequence of limited record length. In this respect, a better term to describe the observed fluctuations of a smooth power-law spectrum is Atlantic Multidecadal Variability (AMV)

The performance of Marciniak–Kuczinsky approach on prediction of plastic instability of metals subjected to complex loadings

The objective of the present paper is to analyse the performance of Marciniak-Kuczinsky (MK) theory on the prediction of formability of sheet metals subjected to complex loadings. Advanced constitutive equations taking into account isotropic and anisotropic hardening are applied to describe the material mechanical behaviour under linear and complex loadings. A comparative study on their accuracy on predicting the forming limits for the studied material is performed. Two deep-drawing quality sheet metals are selected. Several strain path changes are taken into account. A good agreement between the theoretical and experimental results was obtained. MK theory is an efficient and valuable tool on the prediction of plastic flow localization of sheet metals under complex loadings when proper constitutive equations are used.publishe

Positive-unlabeled learning for open set domain adaptation

Open Set Domain Adaptation (OSDA) focuses on bridging the domain gap between a labeled source domain and an unlabeled target domain, while also rejecting target classes that are not present in the source as unknown. The challenges of this task are closely related to those of Positive-Unlabeled (PU) learning where it is essential to discriminate between positive (known) and negative (unknown) class samples in the unlabeled target data. With this newly discovered connection, we leverage the theoretical framework of PU learning for OSDA and, at the same time, we extend PU learning to tackle uneven data distributions. Our method combines domain adversarial learning with a new non-negative risk estimator for PU learning based on self-supervised sample reconstruction. With experiments on digit recognition and object classification, we validate our risk estimator and demonstrate that our approach allows reducing the domain gap without suffering from negative transfer

DGCM-Net: Dense Geometrical Correspondence Matching Network for Incremental Experience-Based Robotic Grasping.

This article presents a method for grasping novel objects by learning from experience. Successful attempts are remembered and then used to guide future grasps such that more reliable grasping is achieved over time. To transfer the learned experience to unseen objects, we introduce the dense geometric correspondence matching network (DGCM-Net). This applies metric learning to encode objects with similar geometry nearby in feature space. Retrieving relevant experience for an unseen object is thus a nearest neighbor search with the encoded feature maps. DGCM-Net also reconstructs 3D-3D correspondences using the view-dependent normalized object coordinate space to transform grasp configurations from retrieved samples to unseen objects. In comparison to baseline methods, our approach achieves an equivalent grasp success rate. However, the baselines are significantly improved when fusing the knowledge from experience with their grasp proposal strategy. Offline experiments with a grasping dataset highlight the capability to transfer grasps to new instances as well as to improve success rate over time from increasing experience. Lastly, by learning task-relevant grasps, our approach can prioritize grasp configurations that enable the functional use of objects

Temperature fluctuations in a changing climate: an ensemble-based experimental approach.

There is an ongoing debate in the literature about whether the present global warming is increasing local and global temperature variability. The central methodological issues of this debate relate to the proper treatment of normalised temperature anomalies and trends in the studied time series which may be difficult to separate from time-evolving fluctuations. Some argue that temperature variability is indeed increasing globally, whereas others conclude it is decreasing or remains practically unchanged. Meanwhile, a consensus appears to emerge that local variability in certain regions (e.g. Western Europe and North America) has indeed been increasing in the past 40 years. Here we investigate the nature of connections between external forcing and climate variability conceptually by using a laboratory-scale minimal model of mid-latitude atmospheric thermal convection subject to continuously decreasing 'equator-to-pole' temperature contrast DeltaT, mimicking climate change. The analysis of temperature records from an ensemble of experimental runs ('realisations') all driven by identical time-dependent external forcing reveals that the collective variability of the ensemble and that of individual realisations may be markedly different - a property to be considered when interpreting climate records

The formability prediction of twinning-induced plasticity steels

The proposal of this work is to predict and analyse the formability of twinning-induced plasticity steels through the Marciniak-Kuczinsky approach with emphasis on the solutions for improving the prediction results. The selected constitutive equations involve the Yld2000-2d plane stress yield function and the Swift strain-hardening power law. To understand the formability of the TWIP steel and the factors influencing it, a sensitive study on the effect of the mechanical properties of the TWIP steel on the Marciniak-Kuczinsky (MK) theory concept and the predicted forming limits is performed.publishe