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2020


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Sampling on networks: estimating spectral centrality measures and their impact in evaluating other relevant network measures

Ruggeri, N., De Bacco, C.

Applied Network Science, 5:81, October 2020 (article)

Abstract
We perform an extensive analysis of how sampling impacts the estimate of several relevant network measures. In particular, we focus on how a sampling strategy optimized to recover a particular spectral centrality measure impacts other topological quantities. Our goal is on one hand to extend the analysis of the behavior of TCEC [Ruggeri2019], a theoretically-grounded sampling method for eigenvector centrality estimation. On the other hand, to demonstrate more broadly how sampling can impact the estimation of relevant network properties like centrality measures different than the one aimed at optimizing, community structure and node attribute distribution. Finally, we adapt the theoretical framework behind TCEC for the case of PageRank centrality and propose a sampling algorithm aimed at optimizing its estimation. We show that, while the theoretical derivation can be suitably adapted to cover this case, the resulting algorithm suffers of a high computational complexity that requires further approximations compared to the eigenvector centrality case.

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Code Preprint pdf DOI [BibTex]


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Optimal transport for multi-commodity routing on networks

Lonardi, A., Facca, E., Putti, M., De Bacco, C.

October 2020 (article) Submitted

Abstract
We present a model for finding optimal multi-commodity flows on networks based on optimal transport theory. The model relies on solving a dynamical system of equations. We prove that its stationary solution is equivalent to the solution of an optimization problem that generalizes the one-commodity framework. In particular, it generalizes previous results in terms of optimality, scaling, and phase transitions obtained in the one-commodity case. Remarkably, for a suitable range of parameters, the optimal topologies have loops. This is radically different to the one-commodity case, where within an analogous parameter range the optimal topologies are trees. This important result is a consequence of the extension of Kirkchoff's law to the multi-commodity case, which enforces the distinction between fluxes of the different commodities. Our results provide new insights into the nature and properties of optimal network topologies. In particular, they show that loops can arise as a consequence of distinguishing different flow types, and complement previous results where loops, in the one-commodity case, were arising as a consequence of imposing dynamical rules to the sources and sinks or when enforcing robustness to damage. Finally, we provide an efficient implementation for each of the two equivalent numerical frameworks, both of which achieve a computational complexity that is more efficient than that of standard optimization methods based on gradient descent. As a result, our model is not merely abstract but can be efficiently applied to large datasets. We give an example of concrete application by studying the network of the Paris metro.

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Code Preprint [BibTex]


AirCapRL: Autonomous Aerial Human Motion Capture Using Deep Reinforcement Learning
AirCapRL: Autonomous Aerial Human Motion Capture Using Deep Reinforcement Learning

Tallamraju, R., Saini, N., Bonetto, E., Pabst, M., Liu, Y. T., Black, M., Ahmad, A.

IEEE Robotics and Automation Letters, IEEE Robotics and Automation Letters, 5(4):6678 - 6685, IEEE, October 2020, Also accepted and presented in the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). (article)

Abstract
In this letter, we introduce a deep reinforcement learning (DRL) based multi-robot formation controller for the task of autonomous aerial human motion capture (MoCap). We focus on vision-based MoCap, where the objective is to estimate the trajectory of body pose, and shape of a single moving person using multiple micro aerial vehicles. State-of-the-art solutions to this problem are based on classical control methods, which depend on hand-crafted system, and observation models. Such models are difficult to derive, and generalize across different systems. Moreover, the non-linearities, and non-convexities of these models lead to sub-optimal controls. In our work, we formulate this problem as a sequential decision making task to achieve the vision-based motion capture objectives, and solve it using a deep neural network-based RL method. We leverage proximal policy optimization (PPO) to train a stochastic decentralized control policy for formation control. The neural network is trained in a parallelized setup in synthetic environments. We performed extensive simulation experiments to validate our approach. Finally, real-robot experiments demonstrate that our policies generalize to real world conditions.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Community detection with node attributes in multilayer networks

Contisciani, M., Power, E. A., De Bacco, C.

Nature Scientific Reports, 10, pages: 15736, September 2020 (article)

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Code Preprint pdf [BibTex]

Code Preprint pdf [BibTex]


Transient coarsening and the motility of optically heated Janus colloids in a binary liquid mixture
Transient coarsening and the motility of optically heated Janus colloids in a binary liquid mixture

Gomez-Solano, J., Roy, S., Araki, T., Dietrich, S., Maciolek, A.

Soft Matter, 16, pages: 8359-8371, Royal Society of Chemistry, August 2020 (article)

Abstract
A gold-capped Janus particle suspended in a near-critical binary liquid mixture can self-propel under illumination. We have immobilized such a particle in a narrow channel and carried out a combined experimental and theoretical study of the non-equilibrium dynamics of a binary solvent around it – lasting from the very moment of switching illumination on until the steady state is reached. In the theoretical study we use both a purely diffusive and a hydrodynamic model, which we solve numerically. Our results demonstrate a remarkable complexity of the time evolution of the concentration field around the colloid. This evolution is governed by the combined effects of the temperature gradient and the wettability, and crucially depends on whether the colloid is free to move or is trapped. For the trapped colloid, all approaches indicate that the early time dynamics is purely diffusive and characterized by composition layers travelling with constant speed from the surface of the colloid into the bulk of the solvent. Subsequently, hydrodynamic effects set in. Anomalously large nonequilibrium fluctuations, which result from the temperature gradient and the vicinity of the critical point of the binary liquid mixture, give rise to strong concentration fluctuations in the solvent and to permanently changing coarsening patterns not observed for a mobile particle. The early time dynamics around initially still Janus colloids produces a force which is able to set the Janus colloid into motion. The propulsion due to this transient dynamics is in the direction opposite to that observed after the steady state is attained.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


3D Morphable Face Models - Past, Present and Future
3D Morphable Face Models - Past, Present and Future

Egger, B., Smith, W. A. P., Tewari, A., Wuhrer, S., Zollhoefer, M., Beeler, T., Bernard, F., Bolkart, T., Kortylewski, A., Romdhani, S., Theobalt, C., Blanz, V., Vetter, T.

ACM Transactions on Graphics, 39(5), August 2020 (article)

Abstract
In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed. The challenges in building and applying these models, namely capture, modeling, image formation, and image analysis, are still active research topics, and we review the state-of-the-art in each of these areas. We also look ahead, identifying unsolved challenges, proposing directions for future research and highlighting the broad range of current and future applications.

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project page pdf preprint DOI [BibTex]

project page pdf preprint DOI [BibTex]


Analysis of motor development within the first year of life: 3-{D} motion tracking without markers for early detection of developmental disorders
Analysis of motor development within the first year of life: 3-D motion tracking without markers for early detection of developmental disorders

Parisi, C., Hesse, N., Tacke, U., Rocamora, S. P., Blaschek, A., Hadders-Algra, M., Black, M. J., Heinen, F., Müller-Felber, W., Schroeder, A. S.

Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, 63, pages: 881–890, July 2020 (article)

Abstract
Children with motor development disorders benefit greatly from early interventions. An early diagnosis in pediatric preventive care (U2–U5) can be improved by automated screening. Current approaches to automated motion analysis, however, are expensive, require lots of technical support, and cannot be used in broad clinical application. Here we present an inexpensive, marker-free video analysis tool (KineMAT) for infants, which digitizes 3‑D movements of the entire body over time allowing automated analysis in the future. Three-minute video sequences of spontaneously moving infants were recorded with a commercially available depth-imaging camera and aligned with a virtual infant body model (SMIL model). The virtual image generated allows any measurements to be carried out in 3‑D with high precision. We demonstrate seven infants with different diagnoses. A selection of possible movement parameters was quantified and aligned with diagnosis-specific movement characteristics. KineMAT and the SMIL model allow reliable, three-dimensional measurements of spontaneous activity in infants with a very low error rate. Based on machine-learning algorithms, KineMAT can be trained to automatically recognize pathological spontaneous motor skills. It is inexpensive and easy to use and can be developed into a screening tool for preventive care for children.

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pdf on-line w/ sup mat DOI [BibTex]

pdf on-line w/ sup mat DOI [BibTex]


Learning and Tracking the {3D} Body Shape of Freely Moving Infants from {RGB-D} sequences
Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences

Hesse, N., Pujades, S., Black, M., Arens, M., Hofmann, U., Schroeder, S.

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 42(10):2540-2551, 2020 (article)

Abstract
Statistical models of the human body surface are generally learned from thousands of high-quality 3D scans in predefined poses to cover the wide variety of human body shapes and articulations. Acquisition of such data requires expensive equipment, calibration procedures, and is limited to cooperative subjects who can understand and follow instructions, such as adults. We present a method for learning a statistical 3D Skinned Multi-Infant Linear body model (SMIL) from incomplete, low-quality RGB-D sequences of freely moving infants. Quantitative experiments show that SMIL faithfully represents the RGB-D data and properly factorizes the shape and pose of the infants. To demonstrate the applicability of SMIL, we fit the model to RGB-D sequences of freely moving infants and show, with a case study, that our method captures enough motion detail for General Movements Assessment (GMA), a method used in clinical practice for early detection of neurodevelopmental disorders in infants. SMIL provides a new tool for analyzing infant shape and movement and is a step towards an automated system for GMA.

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pdf Journal DOI [BibTex]

pdf Journal DOI [BibTex]


Interface-mediated spontaneous symmetry breaking and mutual communication between drops containing chemically active particles
Interface-mediated spontaneous symmetry breaking and mutual communication between drops containing chemically active particles

Singh, D., Domínguez, A., Choudhury, U., Kottapalli, S., Popescu, M., Dietrich, S., Fischer, P.

Nature Communications, 11(2210), May 2020 (article)

Abstract
Symmetry breaking and the emergence of self-organized patterns is the hallmark of com- plexity. Here, we demonstrate that a sessile drop, containing titania powder particles with negligible self-propulsion, exhibits a transition to collective motion leading to self-organized flow patterns. This phenomenology emerges through a novel mechanism involving the interplay between the chemical activity of the photocatalytic particles, which induces Mar- angoni stresses at the liquid–liquid interface, and the geometrical confinement provided by the drop. The response of the interface to the chemical activity of the particles is the source of a significantly amplified hydrodynamic flow within the drop, which moves the particles. Furthermore, in ensembles of such active drops long-ranged ordering of the flow patterns within the drops is observed. We show that the ordering is dictated by a chemical com- munication between drops, i.e., an alignment of the flow patterns is induced by the gradients of the chemicals emanating from the active particles, rather than by hydrodynamic interactions.

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link (url) DOI [BibTex]


General Movement Assessment from videos of computed {3D} infant body models is equally effective compared to conventional {RGB} Video rating
General Movement Assessment from videos of computed 3D infant body models is equally effective compared to conventional RGB Video rating

Schroeder, S., Hesse, N., Weinberger, R., Tacke, U., Gerstl, L., Hilgendorff, A., Heinen, F., Arens, M., Bodensteiner, C., Dijkstra, L. J., Pujades, S., Black, M., Hadders-Algra, M.

Early Human Development, 144, May 2020 (article)

Abstract
Background: General Movement Assessment (GMA) is a powerful tool to predict Cerebral Palsy (CP). Yet, GMA requires substantial training hampering its implementation in clinical routine. This inspired a world-wide quest for automated GMA. Aim: To test whether a low-cost, marker-less system for three-dimensional motion capture from RGB depth sequences using a whole body infant model may serve as the basis for automated GMA. Study design: Clinical case study at an academic neurodevelopmental outpatient clinic. Subjects: Twenty-nine high-risk infants were recruited and assessed at their clinical follow-up at 2-4 month corrected age (CA). Their neurodevelopmental outcome was assessed regularly up to 12-31 months CA. Outcome measures: GMA according to Hadders-Algra by a masked GMA-expert of conventional and computed 3D body model (“SMIL motion”) videos of the same GMs. Agreement between both GMAs was assessed, and sensitivity and specificity of both methods to predict CP at ≥12 months CA. Results: The agreement of the two GMA ratings was substantial, with κ=0.66 for the classification of definitely abnormal (DA) GMs and an ICC of 0.887 (95% CI 0.762;0.947) for a more detailed GM-scoring. Five children were diagnosed with CP (four bilateral, one unilateral CP). The GMs of the child with unilateral CP were twice rated as mildly abnormal. DA-ratings of both videos predicted bilateral CP well: sensitivity 75% and 100%, specificity 88% and 92% for conventional and SMIL motion videos, respectively. Conclusions: Our computed infant 3D full body model is an attractive starting point for automated GMA in infants at risk of CP.

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DOI [BibTex]

DOI [BibTex]


Learning Multi-Human Optical Flow
Learning Multi-Human Optical Flow

Ranjan, A., Hoffmann, D. T., Tzionas, D., Tang, S., Romero, J., Black, M. J.

International Journal of Computer Vision (IJCV), (128):873-890, April 2020 (article)

Abstract
The optical flow of humans is well known to be useful for the analysis of human action. Recent optical flow methods focus on training deep networks to approach the problem. However, the training data used by them does not cover the domain of human motion. Therefore, we develop a dataset of multi-human optical flow and train optical flow networks on this dataset. We use a 3D model of the human body and motion capture data to synthesize realistic flow fields in both single-and multi-person images. We then train optical flow networks to estimate human flow fields from pairs of images. We demonstrate that our trained networks are more accurate than a wide range of top methods on held-out test data and that they can generalize well to real image sequences. The code, trained models and the dataset are available for research.

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pdf DOI poster link (url) DOI [BibTex]

pdf DOI poster link (url) DOI [BibTex]


Real Time Trajectory Prediction Using Deep Conditional Generative Models
Real Time Trajectory Prediction Using Deep Conditional Generative Models

Gomez-Gonzalez, S., Prokudin, S., Schölkopf, B., Peters, J.

IEEE Robotics and Automation Letters, 5(2):970-976, IEEE, January 2020 (article)

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arXiv DOI [BibTex]

arXiv DOI [BibTex]


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Axisymmetric spheroidal squirmers and self-diffusiophoretic particles

Pöhnl, R., Popescu, M. N., Uspal, W. E.

Journal of Physics: Condensed Matter, 32(16), IOP Publishing, Bristol, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Tracer diffusion on a crowded random Manhattan lattice

Mej\’\ia-Monasterio, C., Nechaev, S., Oshanin, G., Vasilyev, O.

New Journal of Physics, 22(3), IOP Publishing, Bristol, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Wetting transitions on soft substrates

Napiorkowski, M., Schimmele, L., Dietrich, S.

{EPL}, 129(1), EDP Science, Les-Ulis, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Blessing and Curse: How a Supercapacitor Large Capacitance Causes its Slow Charging

Lian, C., Janssen, M., Liu, H., van Roij, R.

Physical Review Letters, 124(7), American Physical Society, Woodbury, N.Y., 2020 (article)

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DOI [BibTex]

DOI [BibTex]


Wearable and Stretchable Strain Sensors: Materials, Sensing Mechanisms, and Applications
Wearable and Stretchable Strain Sensors: Materials, Sensing Mechanisms, and Applications

Souri, H., Banerjee, H., Jusufi, A., Radacsi, N., Stokes, A. A., Park, I., Sitti, M., Amjadi, M.

Advanced Intelligent Systems, 2020 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Interplay of quenching temperature and drift in Brownian dynamics

Khalilian, H., Nejad, M. R., Moghaddam, A. G., Rohwer, C. M.

EPL, 128(6), EDP Science, Les-Ulis, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


Occlusion Boundary: A Formal Definition & Its Detection via Deep Exploration of Context
Occlusion Boundary: A Formal Definition & Its Detection via Deep Exploration of Context

Wang, C., Fu, H., Tao, D., Black, M.

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 (article)

Abstract
Occlusion boundaries contain rich perceptual information about the underlying scene structure and provide important cues in many visual perception-related tasks such as object recognition, segmentation, motion estimation, scene understanding, and autonomous navigation. However, there is no formal definition of occlusion boundaries in the literature, and state-of-the-art occlusion boundary detection is still suboptimal. With this in mind, in this paper we propose a formal definition of occlusion boundaries for related studies. Further, based on a novel idea, we develop two concrete approaches with different characteristics to detect occlusion boundaries in video sequences via enhanced exploration of contextual information (e.g., local structural boundary patterns, observations from surrounding regions, and temporal context) with deep models and conditional random fields. Experimental evaluations of our methods on two challenging occlusion boundary benchmarks (CMU and VSB100) demonstrate that our detectors significantly outperform the current state-of-the-art. Finally, we empirically assess the roles of several important components of the proposed detectors to validate the rationale behind these approaches.

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official version DOI [BibTex]

official version DOI [BibTex]


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Fractal-seaweeds type functionalization of graphene

Amsharov, K., Sharapa, D. I., Vasilyev, O. A., Martin, O., Hauke, F., Görling, A., Soni, H., Hirsch, A.

Carbon, 158, pages: 435-448, Elsevier, Amsterdam, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Effective pair interaction of patchy particles in critical fluids

Farahmand Bafi, N., Nowakowski, P., Dietrich, S.

The Journal of Chemical Physics, 152(11), American Institute of Physics, Woodbury, N.Y., 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Cassie-Wenzel transition of a binary liquid mixture on a nanosculptured surface

Singh, S. L., Schimmele, L., Dietrich, S.

Physical Review E, 101(5), American Physical Society, Melville, NY, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Fish-like aquatic propulsion studied using a pneumatically-actuated soft-robotic model

Wolf, Z., Jusufi, A., Vogt, D. M., Lauder, G. V.

Bioinspiration & Biomimetics, 15(4):046008, Inst. of Physics, London, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Network extraction by routing optimization

Baptista, T. D., Leite, D., Facca, E., Putti, M., De Bacco, C.

2020 (article) In revision

Abstract
Routing optimization is a relevant problem in many contexts. Solving directly this type of optimization problem is often computationally unfeasible. Recent studies suggest that one can instead turn this problem into one of solving a dynamical system of equations, which can instead be solved efficiently using numerical methods. This results in enabling the acquisition of optimal network topologies from a variety of routing problems. However, the actual extraction of the solution in terms of a final network topology relies on numerical details which can prevent an accurate investigation of their topological properties. In this context, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. In particular, in this framework, final graph acquisition is a challenging problem in-and-of-itself. Here we introduce a method to extract networks topologies from dynamical equations related to routing optimization under various parameters’ settings. Our method is made of three steps: first, it extracts an optimal trajectory by solving a dynamical system, then it pre-extracts a network and finally, it filters out potential redundancies. Remarkably, we propose a principled model to address the filtering in the last step, and give a quantitative interpretation in terms of a transport-related cost function. This principled filtering can be applied to more general problems such as network extraction from images, thus going beyond the scenarios envisioned in the first step. Overall, this novel algorithm allows practitioners to easily extract optimal network topologies by combining basic tools from numerical methods, optimization and network theory. Thus, we provide an alternative to manual graph extraction which allows a grounded extraction from a large variety of optimal topologies.

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Code Preprint [BibTex]


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Energy storage in steady states under cyclic local energy input

Zhang, Y., Holyst, R., Maciolek, A.

Physical Review E, 101(1), American Physical Society, Melville, NY, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Numerical simulations of self-diffusiophoretic colloids at fluid interfaces

Peter, T., Malgaretti, P., Rivas, N., Scagliarini, A., Harting, J., Dietrich, S.

Soft Matter, 16(14):3536-3547, Royal Society of Chemistry, Cambridge, UK, 2020 (article)

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DOI [BibTex]

DOI [BibTex]

2010


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Comment on biomimetic ultrathin whitening by capillary-force-induced random clustering of hydrogel micropillar arrays

Bernardino, N. R., Dietrich, S.

ACS Applied Materials \& Interfaces, 2(3):603-604, 2010 (article)

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DOI [BibTex]

2010


DOI [BibTex]


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Wetting of surfaces covered by elastic hairs

Bernardino, N. R., Blickle, V., Dietrich, S.

Langmuir, 26(10):7233-7241, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Phase diagrams of binary mixtures of oppositely charged colloids

Bier, M., van Roij, R., Dijkstra, M.

Journal of Chemical Physics, 133(12), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Narrow-escape times for diffusion in microdomains with a particle-surface affinity: mean-field results

Oshanin, G., Tamm, M., Vasilyev, O.

Journal of Chemical Physics, 132(23), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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The localization transition of the two-dimensional Lorentz model

Bauer, T., Höfling, Felix, Munk, T., Frey, E., Franosch, T.

European Physical Journal - Special Topics, 189(1):103-118, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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DDFT for Brownian particles and hydrodynamics

Rauscher, M.

Journal of Physics: Condensed Matter, 22(36), 2010 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Colloidal particles in liquid crystal films and at interfaces

Tasinkevych, M., Andrienko, D.

Condensed Matter Physics, 13(3), 2010 (article)

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[BibTex]

[BibTex]


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Phase behavior of ionic liquid crystals

Kondrat, S., Bier, M., Harnau, L.

The Journal of Chemical Physics, 132, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Nanoindentation studies on crosslinking and curing effects of PDMS

Deuschle, J. K., de Souza, E. J., Arzt, E., Enders, S.

International Journal of Materials Research, 101(8):1014-1023, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Fundamental measure theory for hard-sphere mixtures: a review

Roth, R.

Journal of Physics: Condensed Matter, 22(6), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Universality of the glassy transitions in the two-dimensional \pmJ Ising model

Parisen Toldin, F., Pelissetto, A, Vicari, E.

Physical Review E, 82(2), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Phoretic motion of spheroidal particles due to self-generated solute gradients

Popescu, M. N., Dietrich, S., Tasinkevych, M., Ralston, J.

European Physical Journal E, 31(04):351-367, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Vapor pressure of ionic liquids

Bier, M., Dietrich, S.

Molecular Physics, 108(2):211-214, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Colloidal aggregation and critical Casimir forces

Gambassi, A., Dietrich, S.

Physical Review Letters, 105(5), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Localization phenomena in models of ion-conduction glass formers

Horbach, J., Voigtmann, T., Höfling, F., Franosch, T.

European Physical Journal - Special Topics, 189(1):141-145, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Tensorial density functional theory for non-spherical hard-body fluids

Hansen-Goos, H., Mecke, K.

Journal of Physics: Condensed Matter, 22(36), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Thermoresponsive colloidal molecules

Hoffmann, M., Siebenbürger, M., Harnau, L., Hund, M., Hanske, C., Wagner, C. S., Drechsler, M., Ballauff, M.

Soft Matter, 6, pages: 1125-1128, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Critical Casimir forces and adsorption profiles in the presence of a chemically structured substrate

Parisen Toldin, F., Dietrich, S.

Journal of Statistical Mechanics: Theory and Experiment, (Nov.), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Free energy of colloidal particles at the surface of sessile drops

Guzowski, J., Tasinkevych, M., Dietrich, S.

European Physical Journal, 33(3):219-242, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Casimir interactions in Ising strips with boundary fields: exact results

Abraham, D. B., Maciolek, A.

Physical Review Letters, 105(5), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Ballistic deposition patterns beneath a growing Kardar-Parisi-Zhang interface

Khanin, K., Nechaev, S., Oshanin, G., Sobolevski, A., Vasilyev, O.

Physical Review E, 82(6), 2010 (article)

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DOI [BibTex]

DOI [BibTex]