Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank

Unbiased CLTR requires click propensities to compensate for the difference between user clicks and true relevance of search results via IPS. Current propensity estimation methods assume that user click behavior follows the PBM and estimate click propensities based on this assumption. However, in reality, user clicks often follow the CM, where users scan search results from top to bottom and where each next click depends on the previous one. In this cascade scenario, PBM-based estimates of propensities are not accurate, which, in turn, hurts CLTR performance. In this paper, we propose a propensity estimation method for the cascade scenario, called CM-IPS. We show that CM-IPS keeps CLTR performance close to the full-information performance in case the user clicks follow the CM, while PBM-based CLTR has a significant gap towards the full-information. The opposite is true if the user clicks follow PBM instead of the CM. Finally, we suggest a way to select between CM- and PBM-based propensity estimation methods based on historical user clicks.Comment: 4 pages, 2 figures, 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '20

Drops bouncing off macro-textured superhydrophobic surfaces

Recent experiments with droplets impacting a macro-textured superhydrophobic surfaces revealed new regimes of bouncing with a remarkable reduction of the contact time. We present here a comprehensive numerical study that reveals the physics behind these new bouncing regimes and quantify the role played by various external and internal forces that effect the dynamics of a drop impacting a complex surface. For the first time, three-dimensional simulations involving macro-textured surfaces are performed. Aside from demonstrating that simulations reproduce experiments in a quantitative manner, the study is focused on analyzing the flow situations beyond current experiments. We show that the experimentally observed reduction of contact time extends to higher Weber numbers, and analyze the role played by the texture density. Moreover, we report a non-linear behavior of the contact time with the increase of the Weber number for application relevant imperfectly coated textures, and also study the impact on tilted surfaces in a wide range of Weber numbers. Finally, we present novel energy analysis techniques that elaborate and quantify the interplay between the kinetic and surface energy, and the role played by the dissipation for various Weber numbers

Exploring Pre-service Language Teachers⿿ Perceptions and Actual Practices of Giving Feedback in Micro-teaching

AbstractFeedback has considerably been acknowledged as a significant component of language teaching. Although there are several studies on the effectiveness of giving feedback to pre-service language teachers to improve their teaching practices by their instructors or their peers, the actual feedback provided by them during their micro-teaching practices has not received adequate attention. Therefore, the aim is twofold: to investigate the perceptions of pre-service language teachers regarding their oral feedback providing practices during their micro-teaching implementations, and to carry out content analysis of their micro-teaching practices to determine the frequency and variety of the feedback provided by them during their micro-teaching practices. The study was carried out with 40 pre-service language teachers at Sakarya University. An open ended questionnaire with eight questions was employed in order to determine pre-service language teachers⿿ perceptions. For the actual practices, pre-service language teachers were asked to video record their micro-teachings, and two researchers watched them. The findings of the study have not been finalized yet. With the current study, similarities and differences between pre-service language teachers⿿ perceptions and their actual practices will be investigated

Eliciting ELT students’ Understanding of Plagiarism in Academic Writing

Given that the term ‘plagiarism’ is open to multiple interpretations, resulting in confusion among students and teachers alike, research that investigates the current state of empirical evidence and sheds light on students’ ability to define and detect this notion has important pedagogical implications. This study examines undergraduate English Language Teaching (ELT) students’ understanding of plagiarism in academic writing through qualitative data collection methods. After the focus group filled in the open-ended questionnaire, they were exposed to two sets of texts each containing an original, a plagiarized and non-plagiarized copy. The copy in the first set featured mainly word-for-word plagiarism while the copy in the second set was plagiarized in terms of illicit paraphrasing. The students were asked to identify whether there is any plagiarism in each copy and assess the texts regarding their acceptability in the format of an interview and think-aloud protocols. The results of the open-ended questionnaire and interviews were compared revealing that although all the students were able to define plagiarism correctly, most of them failed to identify it in the written text. The study also uncovered discrepancies in how the students view the aforementioned types of plagiarism

Polypeptide gels incorporating the exotic functional aromatic amino acid 4-amino-L-phenylalanine

High-molecular-weight polypeptides with functional aromatic side chains, poly(4-amino-l-phenylalanine), were prepared by the metal-initiated polymerization of the Nα-carboxyanhydride of the corresponding amino acid, which is a microbial derivative of phenylalanine

A Mission Based Fault Reconfiguration Framework for Spacecraft Applications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97079/1/AIAA2012-2403.pd

Superscattering of light optimized by a genetic algorithm

We analyse scattering of light from multi-layer plasmonic nanowires and employ a genetic algorithm for optimizing the scattering cross section. We apply the mode-expansion method using experimental data for material parameters to demonstrate that our genetic algorithm allows designing realistic core-shell nanostructures with the superscattering effect achieved at any desired wavelength. This approach can be employed for optimizing both superscattering and cloaking at different wavelengths in the visible spectral range.The authors acknowledge a support from the Australian Research Council through the Future Fellowship (FT110100037) and the Discovery Project programs

Automated 3D Axonal Morphometry of White Matter

Peer reviewe

DeepACSON automated segmentation of white matter in 3D electron microscopy

Tracing the entirety of ultrastructures in large three-dimensional electron microscopy (3D-EM) images of the brain tissue requires automated segmentation techniques. Current segmentation techniques use deep convolutional neural networks (DCNNs) and rely on high-contrast cellular membranes and high-resolution EM volumes. On the other hand, segmenting low-resolution, large EM volumes requires methods to account for severe membrane discontinuities inescapable. Therefore, we developed DeepACSON, which performs DCNN-based semantic segmentation and shape-decomposition-based instance segmentation. DeepACSON instance segmentation uses the tubularity of myelinated axons and decomposes under-segmented myelinated axons into their constituent axons. We applied DeepACSON to ten EM volumes of rats after sham-operation or traumatic brain injury, segmenting hundreds of thousands of long-span myelinated axons, thousands of cell nuclei, and millions of mitochondria with excellent evaluation scores. DeepACSON quantified the morphology and spatial aspects of white matter ultrastructures, capturing nanoscopic morphological alterations five months after the injury. With DeepACSON, Abdollahzadeh et al. combines existing deep learning-based methods for semantic segmentation and a novel shape decomposition technique for the instance segmentation. The pipeline is used to segment low-resolution 3D-EM datasets allowing quantification of white matter morphology in large fields-of-view.Peer reviewe