Unveiling the orbital angular momentum and acceleration of electron beams

New forms of electron beams have been intensively investigated recently, including vortex beams carrying orbital angular momentum, as well as Airy beams propagating along a parabolic trajectory. Their traits may be harnessed for applications in materials science, electron microscopy and interferometry, and so it is important to measure their properties with ease. Here we show how one may immediately quantify these beams' parameters without need for additional fabrication or non-standard microscopic tools. Our experimental results are backed by numerical simulations and analytic derivation.Comment: 2 figures in text, 2 in supplementar

Penerapan Media Virtual PowToon dengan Recitation Method terhadap Hasil Belajar ditinjau dari Minat Belajar Fisika Peserta Didik Kelas VIII SMPN 16 Bulukumba

Hasil penelitian menunjukkan bahwa; 1) terdapat perbedaan hasil belajar antara peserta didik yang diajar menggunakan media virtual PowToon dengan recitation method dan peserta didik yang diajar menggunakan media konvensional (2) terdapat perbedaan hasil belajar antara peserta didik yang memiliki minat belajar tinggi dan peserta didik yang memiliki minat belajar rendah (3) tidak terdapat interaksi antara media pembelajaran dan minat belajar terhadap hasil belajar (4) terdapat perbedaan hasil belajar antara peserta didik yang diajar menggunakan media virtual PowToon dengan recitation method dan peserta didik yang diajar menggunakan media konvensional (5) terdapat perbedaan hasil belajar antara peserta didik yang diajar menggunakan medi/a virtual PowToon dengan recitation method dan peserta didik yang diajar menggunakan media konvensional

Detecting Sarcasm in Multimodal Social Platforms

Sarcasm is a peculiar form of sentiment expression, where the surface sentiment differs from the implied sentiment. The detection of sarcasm in social media platforms has been applied in the past mainly to textual utterances where lexical indicators (such as interjections and intensifiers), linguistic markers, and contextual information (such as user profiles, or past conversations) were used to detect the sarcastic tone. However, modern social media platforms allow to create multimodal messages where audiovisual content is integrated with the text, making the analysis of a mode in isolation partial. In our work, we first study the relationship between the textual and visual aspects in multimodal posts from three major social media platforms, i.e., Instagram, Tumblr and Twitter, and we run a crowdsourcing task to quantify the extent to which images are perceived as necessary by human annotators. Moreover, we propose two different computational frameworks to detect sarcasm that integrate the textual and visual modalities. The first approach exploits visual semantics trained on an external dataset, and concatenates the semantics features with state-of-the-art textual features. The second method adapts a visual neural network initialized with parameters trained on ImageNet to multimodal sarcastic posts. Results show the positive effect of combining modalities for the detection of sarcasm across platforms and methods.Comment: 10 pages, 3 figures, final version published in the Proceedings of ACM Multimedia 201

Optimal Taxation with Endogenous Population Growth and the Risk of Environmental Disaster

This study considers a market economy where firms produce goods from labor and capital and households supply labor, rear children, save in capital, promote their members' health and longevity by health care and derive utility from their consumption and children, without caring of their adult offspring. There is a risk that population growth and capital accumulation trigger a lethal environmental disaster. Optimal policy is solved by a game where the government is the leader and the representative household the follower. The solution yields precautionary taxes on both capital income and health care.Peer reviewe

Competition and Selection Among Conventions

In many domains, a latent competition among different conventions determines which one will come to dominate. One sees such effects in the success of community jargon, of competing frames in political rhetoric, or of terminology in technical contexts. These effects have become widespread in the online domain, where the data offers the potential to study competition among conventions at a fine-grained level. In analyzing the dynamics of conventions over time, however, even with detailed on-line data, one encounters two significant challenges. First, as conventions evolve, the underlying substance of their meaning tends to change as well; and such substantive changes confound investigations of social effects. Second, the selection of a convention takes place through the complex interactions of individuals within a community, and contention between the users of competing conventions plays a key role in the convention's evolution. Any analysis must take place in the presence of these two issues. In this work we study a setting in which we can cleanly track the competition among conventions. Our analysis is based on the spread of low-level authoring conventions in the eprint arXiv over 24 years: by tracking the spread of macros and other author-defined conventions, we are able to study conventions that vary even as the underlying meaning remains constant. We find that the interaction among co-authors over time plays a crucial role in the selection of them; the distinction between more and less experienced members of the community, and the distinction between conventions with visible versus invisible effects, are both central to the underlying processes. Through our analysis we make predictions at the population level about the ultimate success of different synonymous conventions over time--and at the individual level about the outcome of "fights" between people over convention choices.Comment: To appear in Proceedings of WWW 2017, data at https://github.com/CornellNLP/Macro

String Indexing for Patterns with Wildcards

We consider the problem of indexing a string $t$ of length $n$ to report the occurrences of a query pattern $p$ containing $m$ characters and $j$ wildcards. Let $occ$ be the number of occurrences of $p$ in $t$, and $\sigma$ the size of the alphabet. We obtain the following results. - A linear space index with query time $O(m+\sigma^j \log \log n + occ)$. This significantly improves the previously best known linear space index by Lam et al. [ISAAC 2007], which requires query time $\Theta(jn)$ in the worst case. - An index with query time $O(m+j+occ)$ using space $O(\sigma^{k^2} n \log^k \log n)$, where $k$ is the maximum number of wildcards allowed in the pattern. This is the first non-trivial bound with this query time. - A time-space trade-off, generalizing the index by Cole et al. [STOC 2004]. We also show that these indexes can be generalized to allow variable length gaps in the pattern. Our results are obtained using a novel combination of well-known and new techniques, which could be of independent interest