Time evolution of relativistic d + Au and Au + Au collisions

The evolution of charged-particle production in collisions of heavy ions at relativistic energies is investigated as function of centrality in a nonequilibrium-statistical framework. Precise agreement with recent d + Au and Au + Au data at sqrt(s_NN) = 200 GeV is found in a Relativistic Diffusion Model with three sources for particle production. Only the midrapidity source comes very close to local equilibrium, whereas the analyses of the overall pseudorapidity distributions show that the systems remain far from statistical equilibrium.Comment: 16 pages, 5 figures, 1 tabl

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

pp32 (ANP32A) Expression Inhibits Pancreatic Cancer Cell Growth and Induces Gemcitabine Resistance by Disrupting HuR Binding to mRNAs

The expression of protein phosphatase 32 (PP32, ANP32A) is low in poorly differentiated pancreatic cancers and is linked to the levels of HuR (ELAV1), a predictive marker for gemcitabine response. In pancreatic cancer cells, exogenous overexpression of pp32 inhibited cell growth, supporting its long-recognized role as a tumor suppressor in pancreatic cancer. In chemotherapeutic sensitivity screening assays, cells overexpressing pp32 were selectively resistant to the nucleoside analogs gemcitabine and cytarabine (ARA-C), but were sensitized to 5-fluorouracil; conversely, silencing pp32 in pancreatic cancer cells enhanced gemcitabine sensitivity. The cytoplasmic levels of pp32 increased after cancer cells are treated with certain stressors, including gemcitabine. pp32 overexpression reduced the association of HuR with the mRNA encoding the gemcitabine-metabolizing enzyme deoxycytidine kinase (dCK), causing a significant reduction in dCK protein levels. Similarly, ectopic pp32 expression caused a reduction in HuR binding of mRNAs encoding tumor-promoting proteins (e.g., VEGF and HuR), while silencing pp32 dramatically enhanced the binding of these mRNA targets. Low pp32 nuclear expression correlated with high-grade tumors and the presence of lymph node metastasis, as compared to patients' tumors with high nuclear pp32 expression. Although pp32 expression levels did not enhance the predictive power of cytoplasmic HuR status, nuclear pp32 levels and cytoplasmic HuR levels associated significantly in patient samples. Thus, we provide novel evidence that the tumor suppressor function of pp32 can be attributed to its ability to disrupt HuR binding to target mRNAs encoding key proteins for cancer cell survival and drug efficacy

INNOVATE HOW WE EDUCATE: UNDERSTANDING THE PHOTOELECTRIC EFFECT THROUGH PHYSICS, EDUCATION, AND DANCE

Can dance enhance students’ understanding of physics? We carry out two distinct experiments to test dance-based education: one involving the photoelectric effect and the other involving gravitational waves. Both experiments showed dramatic results. The photoelectric effect is the emission of electrons from matter illuminated by light. The deep implications and straightforward calculations of photoelectric problems as explained by Einstein make it a powerful tool for teaching he quantum postulate. The photon model introduced by Einstein to explain this effect in 1905 conflicted with Maxwell’s widely accepted theory of light. Their conflicting explanations exemplified the inability of classical concepts such as waves and particles to describe quantum scale objects such as light and electrons. Wave-particle duality became one of the fundamental paradoxes embedded in the foundation of quantum mechanics, one of the truly revolutionary ideas of the 20th century. Current educational studies are searching for ways to illuminate for novices how the photon model succeeds where the classical model fails. First, a dance performance was designed to address these learning goals. Subjects were exposed to the dance (N=239), PowerPoint (N=45) or nothing (N=183) and then tested for their understanding of the photoelectric effect. While both treatments fostered significantly higher scores than the control (M=2.94/5), a Fishers LSD test showed that participants who saw the dance (M=4.36) did significantly better than participants who saw the PowerPoint (M=3.91), F(2, 462)=100.147 p=.036. In a second experiment, pre/post-tests were administered to 166 participants who viewed a dance lecture on gravitational waves. Mean scores improved significantly after exposure to the dance lecture. Viewers achieved an average gain of D =0.51, which is high compared to the values reported by Hake in traditional physics courses. The results from both experiments strongly suggest that the use of dance in teaching physics can increase physics teaching effectiveness beyond that of traditional methods such as PowerPoint. This thesis also explores the history of the photoelectric effect. In the dance performance, as in most physics classes, we approach the physics in an ahistorical manner and try to convey our current understanding of the underlying physics. However, the historical path towards understanding the photoelectric effect is a complex one. We trace how advances in theory and novel experiments shaped our understanding of this fundamental effect

Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users

For many of the 700 million illiterate people around the world, speech recognition technology could provide a bridge to valuable information and services. Yet, those most in need of this technology are often the most underserved by it. In many countries, illiterate people tend to speak only low-resource languages, for which the datasets necessary for speech technology development are scarce. In this paper, we investigate the effectiveness of unsupervised speech representation learning on noisy radio broadcasting archives, which are abundant even in low-resource languages. We make three core contributions. First, we release two datasets to the research community. The first, West African Radio Corpus, contains 142 hours of audio in more than 10 languages with a labeled validation subset. The second, West African Virtual Assistant Speech Recognition Corpus, consists of 10K labeled audio clips in four languages. Next, we share West African wav2vec, a speech encoder trained on the noisy radio corpus, and compare it with the baseline Facebook speech encoder trained on six times more data of higher quality. We show that West African wav2vec performs similarly to the baseline on a multilingual speech recognition task, and significantly outperforms the baseline on a West African language identification task. Finally, we share the first-ever speech recognition models for Maninka, Pular and Susu, languages spoken by a combined 10 million people in over seven countries, including six where the majority of the adult population is illiterate. Our contributions offer a path forward for ethical AI research to serve the needs of those most disadvantaged by the digital divide

Let it go: the flexible engagement and disengagement of monitoring processes in a non-focal prospective memory task

Remembering to perform a delayed intention is referred to as prospective memory (PM). In two studies, participants performed an Eriksen flanker task with an embedded PM task (they had to remember to press F1 if a pre-specified cue appeared). In study 1, participants performed a flanker task with either a concurrent PM task or a delayed PM task (instructed to carry out the intention in a later different task). In the delayed PM condition, the PM cues appeared unexpectedly early and we examined whether attention would be captured by the PM cue even though they were not relevant. Results revealed ongoing task costs solely in the concurrent PM condition but no significant task costs in the delayed PM condition showing that attention was not captured by the PM cue when it appeared in an irrelevant context. In study 2, we compared a concurrent PM condition (exactly as in Study 1) to a PM forget condition in which participants were told at a certain point during the flanker task that they no longer had to perform the PM task. Analyses revealed that participants were able to switch off attending to PM cues when instructed to forget the PM task. Results from both studies demonstrate the flexibility of monitoring as evidenced by the presence versus absence of costs in the ongoing flanker task implying that selective attention, like a lens, can be adjusted to attend or ignore, depending on intention relevance