How local media coverage of voter fraud influences partisan perceptions in the United States

Extant findings show that voter fraud is extremely rare and difficult to prove in the United States. Voter’s knowledge about voter fraud allegations likely comes through the media, who tend to sensationalize the issue. In this study, we argue that the more voters are exposed to media coverage of voter fraud allegations, the more likely that they will perceive that voter fraud is a frequent problem. We merge the 2012 Survey of Performance of American Elections with state-level media coverage of voter fraud leading up to the 2012 election. Our results show that media coverage of voter fraud is associated with public beliefs about voter fraud. In states where fraud was more frequently featured in local media outlets, public concerns about voter fraud were heightened. In particular, we find that press attention to voter fraud has a larger influence on Republicans than Democrats and Independents. We further find that media coverage of voter fraud does not further polarize partisan perceptions of voter fraud. Rather, political interest moderates state media coverage on voter fraud beliefs only among Republicans. Lastly, our results provide no support that demographic changes, approval of election administration, or information concerning actual reported voting irregularities have any discernable effects on partisan perceptions

A model for the wind direction signature in the stokes smissin sector from the ocean surfaces at microwave frequencies

This paper presents a model of the Stokes emission vector from the ocean surface. The ocean surface is described as an ensemble of facets with Cox and Munk's (1954) Gram-Charlier slope distribution. The study discusses the impact of different up-wind and cross-wind rms slopes, skewness, peakedness, foam cover models and atmospheric effects on the azimuthal variation of the Stokes vector, as well as the limitations of the model. Simulation results compare favorably, both in mean value and azimuthal dependence, with SSM/I data at 53/spl deg/ incidence angle and with JPL's WINDRAD measurements at incidence angles from 30/spl deg/ to 65/spl deg/, and at wind speeds from 2.5 to 11 m/s.Peer ReviewedPostprint (published version

Retrieving Infinite Numbers of Patterns in a Spin-Glass Model of Immune Networks

The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), and show how the finite connectivity enables the system to manage an extensive number of immune clones simultaneously, even above the percolation threshold. The system exhibits only weak ergodicity breaking, so that both multiple antigen defense and homeostasis can be accomplished.Comment: Editor's Choice 201

Immune networks: multi-tasking capabilities at medium load

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low load regime, where the number $P$ of simultaneously retrievable patterns scales with the number $N$ of nodes as $P\sim \log N$. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium load regime, $P \sim N^{\delta}$ with $\delta \in (0,1]$. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for $\delta<1$ the existence of large regions in the phase diagram where the network can retrieve all stored patterns simultaneously. Finally, in the high load regime $\delta=1$ we find that the system behaves as a spin glass, suggesting that finite-connectivity frameworks are required to achieve effective retrieval.Comment: 26 pages, 10 figure

The Noncommutative Doplicher-Fredenhagen-Roberts-Amorim Space

This work is an effort in order to compose a pedestrian review of the recently elaborated Doplicher, Fredenhagen, Roberts and Amorim (DFRA) noncommutative (NC) space which is a minimal extension of the DFR space. In this DRFA space, the object of noncommutativity ($\theta^{\mu\nu}$) is a variable of the NC system and has a canonical conjugate momentum. The DFRA formalism is constructed in an extended space-time with independent degrees of freedom associated with the object of noncommutativity $\theta^{\mu\nu}$. A consistent algebra involving the enlarged set of canonical operators is described, which permits one to construct theories that are dynamically invariant under the action of the rotation group. A consistent classical mechanics formulation is analyzed in such a way that, under quantization, it furnishes a NC quantum theory with interesting results. The Dirac formalism for constrained Hamiltonian systems is considered and the object of noncommutativity $\theta^{ij}$ plays a fundamental role as an independent quantity. It is also explained about the generalized Dirac equation issue, that the fermionic field depends not only on the ordinary coordinates but on $\theta^{\mu\nu}$ as well. The dynamical symmetry content of such fermionic theory is discussed, and we show that its action is invariant under ${\cal P}'$. In the last part of this work we analyze the complex scalar fields using this new framework. As said above, in a first quantized formalism, $\theta^{\mu\nu}$ and its canonical momentum $\pi_{\mu\nu}$ are seen as operators living in some Hilbert space. In a second quantized formalism perspective, we show an explicit form for the extended Poincar\'e generators and the same algebra is generated via generalized Heisenberg relations. We also consider a source term and construct the general solution for the complex scalar fields using the Green function technique

Analisis Yuridis Atas Turunnya Kekuatan Pembuktian Akta Notaris Menurut Uujn No. 2 Tahun 2014 Tentang Jabatan Notaris

The result of the research showed that the lower level of the force of evidence of Notarial deeds was based on Article 16, paragraph 1, paragraph 7, and paragraph 8, Article 41 with reference to Article 38, Article 39, Article 40, Article 44, Article 48, Article 50, and article 52 of Notarial Act No. 2/2014. Violating these Articles will cause an authentic deed to be lower so thast it turned to an underhanded deed. These articles do not legally protect the position of a Notary because they are not needed through a judge's verdict to prove the force of evidence of a Notarial deed. Verification for a Notarial deed which has the force of evidence as an underhanded deed must be done through a claim to a District Court to prove whether it violates the Articles above or not. If a Notary violates the provision under the Articles above, through the court's verdict, he will be given a written warning, suspension, honorable discharge, and dishonorable discharge; according to the civil law, he has to reimburse the cost, the compensation, and interest

Fusing Audio, Textual and Visual Features for Sentiment Analysis of News Videos

This paper presents a novel approach to perform sentiment analysis of news videos, based on the fusion of audio, textual and visual clues extracted from their contents. The proposed approach aims at contributing to the semiodiscoursive study regarding the construction of the ethos (identity) of this media universe, which has become a central part of the modern-day lives of millions of people. To achieve this goal, we apply state-of-the-art computational methods for (1) automatic emotion recognition from facial expressions, (2) extraction of modulations in the participants' speeches and (3) sentiment analysis from the closed caption associated to the videos of interest. More specifically, we compute features, such as, visual intensities of recognized emotions, field sizes of participants, voicing probability, sound loudness, speech fundamental frequencies and the sentiment scores (polarities) from text sentences in the closed caption. Experimental results with a dataset containing 520 annotated news videos from three Brazilian and one American popular TV newscasts show that our approach achieves an accuracy of up to 84% in the sentiments (tension levels) classification task, thus demonstrating its high potential to be used by media analysts in several applications, especially, in the journalistic domain.Comment: 5 pages, 1 figure, International AAAI Conference on Web and Social Medi