Incorporating Music Into The Economics Classroom: A Comparison Of Two Teaching Methods

There is always something mysterious about music as it affects us so powerfully. This paper looks at the role of music in enhancing students' understanding of economic concepts, such as money and inflation. Music lyrics were used as a source for teaching some economic concepts to a group of Office Management (OM) students. A quiz was given to test the students’ knowledge of these concepts. A comparison of marks was made with another group of Quantity Surveying (QS) students who were taught the same economic concepts but without promoting music integration in the classroom. Both groups of students were given the same quiz and both groups were taking Principles of Economics, a course for non-business majors. There was a difference in learning outcomes between the two groups of students. Students learning economic concepts in music recorded a higher value of mean and mode in their results compared with the other group of students who were taught the same economic concepts without music as a resource. The t-test result did not show any significant difference between male and female students. The quiz results are not affected by gender factor. The same conclusion also applied to the stream factor. The t-test result did not show any significant difference between science and arts stream students, hence the quiz results are not affected by stream factor. This study shows that music incorporated into the classroom can help students understand concepts better and the quiz results seem to give support to the theoretical claim that music helps students concentrate better

Analysis the f0(980)f_0(980) and a0(980)a_0(980) mesons as four-quark states with the QCD sum rules

In this article, we take the point of view that the scalar mesons $f_0(980)$ and $a_0(980)$ are diquark-antidiquark states $(qq)_{\bar{3}}(\bar{q}\bar{q})_3$, and devote to determine their masses in the framework of the QCD sum rules approach with the interpolating currents constructed from scalar-scalar type and pseudoscalar-pseudoscalar type diquark pairs respectively. The numerical results indicate that the scalar mesons $f_0(980)$ and $a_0(980)$ may have two possible diquark-antidiquark substructures.Comment: 8 pages, 1 figure, revised versio

Information-Theoretic Active Learning for Content-Based Image Retrieval

We propose Information-Theoretic Active Learning (ITAL), a novel batch-mode active learning method for binary classification, and apply it for acquiring meaningful user feedback in the context of content-based image retrieval. Instead of combining different heuristics such as uncertainty, diversity, or density, our method is based on maximizing the mutual information between the predicted relevance of the images and the expected user feedback regarding the selected batch. We propose suitable approximations to this computationally demanding problem and also integrate an explicit model of user behavior that accounts for possible incorrect labels and unnameable instances. Furthermore, our approach does not only take the structure of the data but also the expected model output change caused by the user feedback into account. In contrast to other methods, ITAL turns out to be highly flexible and provides state-of-the-art performance across various datasets, such as MIRFLICKR and ImageNet.Comment: GCPR 2018 paper (14 pages text + 2 pages references + 6 pages appendix

Towards a Robuster Interpretive Parsing

The input data to grammar learning algorithms often consist of overt forms that do not contain full structural descriptions. This lack of information may contribute to the failure of learning. Past work on Optimality Theory introduced Robust Interpretive Parsing (RIP) as a partial solution to this problem. We generalize RIP and suggest replacing the winner candidate with a weighted mean violation of the potential winner candidates. A Boltzmann distribution is introduced on the winner set, and the distribution’s parameter $T$ is gradually decreased. Finally, we show that GRIP, the Generalized Robust Interpretive Parsing Algorithm significantly improves the learning success rate in a model with standard constraints for metrical stress assignment

Effects of triptolide, an active ingredient of trypterygium Wilfordii Hook F (Thunder God Vine, a traditional Chinese herb), on rheumatoid synovial fibroblast function

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SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning

We present SeaEval, a benchmark for multilingual foundation models. In addition to characterizing how these models understand and reason with natural language, we also investigate how well they comprehend cultural practices, nuances, and values. Alongside standard accuracy metrics, we investigate the brittleness of foundation models in the dimensions of semantics and multilinguality. Our analyses span both open-sourced and closed models, leading to empirical results across classic NLP tasks, reasoning, and cultural comprehension. Key findings indicate (1) Most models exhibit varied behavior when given paraphrased instructions. (2) Many models still suffer from exposure bias (e.g., positional bias, majority label bias). (3) For questions rooted in factual, scientific, and commonsense knowledge, consistent responses are expected across multilingual queries that are semantically equivalent. Yet, most models surprisingly demonstrate inconsistent performance on these queries. (4) Multilingually-trained models have not attained "balanced multilingual" capabilities. Our endeavors underscore the need for more generalizable semantic representations and enhanced multilingual contextualization. SeaEval can serve as a launchpad for more thorough investigations and evaluations for multilingual and multicultural scenarios.Comment: 15 pages, 7 figure

Growth of high-density carbon nanotube forests on conductive TiSiN supports

This is the accepted manuscript. The final version is available at http://scitation.aip.org/content/aip/journal/apl/106/8/10.1063/1.4913762.We grow vertically aligned carbon nanotube forests on refractory conductive films of TiSiN and achieve area densities of (5.1 ± 0.1) × 1012 tubes cm−2 and mass densities of about 0.3 g cm−3. The TiSiN films act as diffusion barriers limiting catalyst diffusion into the bulk of the support, and their low surface energy favours catalyst de-wetting, inducing forests to grow by the root growth mechanism. The nanotube area density is maximised by an additional discontinuous AlOx layer, which inhibits catalyst nanoparticle sintering by lateral surface diffusion. The forests and the TiSiN support show ohmic conduction. These results suggest that TiSiN is the favoured substrate for nanotube forest growth on conductors and liable of finding real applications in microelectronics.The authors acknowledge funding from European project Grafol. J.Y. thanks Sarah Fearn and David McPhail from Imperial College London for use of the SIMS instrument. A.W.R. is supported by EPSRC (Platform Grant Nos. EP/F048009/1 and EP/K032518/1) and Korean Institute for Energy Research. H.S. acknowledges a research fellowship from the Japanese Society for the Promotion of Science

Low-Temperature Growth of Carbon Nanotube Forests Consisting of Tubes with Narrow Inner Spacing Using Co/Al/Mo Catalyst on Conductive Supports.

We grow dense carbon nanotube forests at 450 °C on Cu support using Co/Al/Mo multilayer catalyst. As a partial barrier layer for the diffusion of Co into Mo, we apply very thin Al layer with the nominal thickness of 0.50 nm between Co and Mo. This Al layer plays an important role in the growth of dense CNT forests, partially preventing the Co-Mo interaction. The forests have an average height of ∼300 nm and a mass density of 1.2 g cm(-3) with tubes exhibiting extremely narrow inner spacing. An ohmic behavior is confirmed between the forest and Cu support with the lowest resistance of ∼8 kΩ. The forest shows a high thermal effusivity of 1840 J s(-0.5) m(-2) K(-1), and a thermal conductivity of 4.0 J s(-1) m(-1) K(-1), suggesting that these forests are useful for heat dissipation devices.This work has been funded by the European projects Technotubes and Grafol. H.S. acknowledges a research fellowship from the Japanese Society for the Promotion of Science (JSPS).This is the accepted manuscript. The final version is available at http://pubs.acs.org/doi/abs/10.1021/acsami.5b04846

Automated task load detection with electroencephalography: towards passive brain–computer interfacing in robotic surgery

Automatic detection of the current task load of a surgeon in the theatre in real time could provide helpful information, to be used in supportive systems. For example, such information may enable the system to automatically support the surgeon when critical or stressful periods are detected, or to communicate to others when a surgeon is engaged in a complex maneuver and should not be disturbed. Passive brain–computer interfaces (BCI) infer changes in cognitive and affective state by monitoring and interpreting ongoing brain activity recorded via an electroencephalogram. The resulting information can then be used to automatically adapt a technological system to the human user. So far, passive BCI have mostly been investigated in laboratory settings, even though they are intended to be applied in real-world settings. In this study, a passive BCI was used to assess changes in task load of skilled surgeons performing both simple and complex surgical training tasks. Results indicate that the introduced methodology can reliably and continuously detect changes in task load in this realistic environment

Psychometric properties of the quality of life scale Child Health and Illness Profile-Child Edition in a combined analysis of five atomoxetine trials

Our aim was to evaluate the psychometric properties of the generic quality of life (QoL) scale Child Health and Illness Profile-Child Edition (CHIP-CE) by means of a combined analysis of atomoxetine clinical trials in children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Individual patient-level data from five clinical trials were included in the combined analysis. Psychometric properties of the CHIP-CE were explored in terms of internal consistency and structure. Patients (n = 794) aged between 6 and 15 years (mean 9.7) with mean baseline ADHD Rating Scale of 41.8 ± 8.04 were included. On average, 0.7 (SD 2.23) items were missing for the whole CHIP-CE. The internal consistency of the CHIP-CE assessed by Cronbach’s alpha was good for all sub-domains at baseline and at endpoint. Considerable ceiling effects were only observed for the “restricted activity” sub-domain. No considerable floor effects were seen. The factor analysis supported the 12-factor solution for the sub-domains, but not the 5-factor solution for the domains. Our analyses were based on a large sample of non-US patients which allowed the measurement of clear changes in QoL over time. The results support that the CHIP-CE scale is psychometrically robust over time in terms of internal consistency and structure