Non-Zhang-Rice singlet character of the first ionization state of T-CuO

We argue that tetragonal CuO (T-CuO) has the potential to finally settle long-standing modelling issues for cuprate physics. We compare the one-hole quasiparticle (qp) dispersion of T-CuO to that of cuprates, in the framework of the strongly-correlated ($U_{dd}\rightarrow \infty$) limit of the three-band Emery model. Unlike in CuO$_2$, magnetic frustration in T-CuO breaks the $C_4$ rotational symmetry and leads to strong deviations from the Zhang-Rice singlet picture in parts of the reciprocal space. Our results are consistent with angle-resolved photoemission spectroscopy data but in sharp contradiction to those of a one-band model previously suggested for them. These differences identify T-CuO as an ideal material to test a variety of scenarios proposed for explaining cuprate phenomenology.Comment: 4 pages, 2 figure

Emotion classification in Parkinson's disease by higher-order spectra and power spectrum features using EEG signals: A comparative study

Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed by clinical diagnosis. Electroencephalogram (EEG) signals, being an activity of central nervous system (CNS), can reflect the underlying true emotional state of a person. This study applied machine-learning algorithms to categorize EEG emotional states in PD patients that would classify six basic emotions (happiness and sadness, fear, anger, surprise and disgust) in comparison with healthy controls (HC). Emotional EEG data were recorded from 20 PD patients and 20 healthy age-, education level- and sex-matched controls using multimodal (audio-visual) stimuli. The use of nonlinear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to classify the emotional states. In this work, we made the comparative study of the performance of k-nearest neighbor (kNN) and support vector machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Analysis of variance (ANOVA) showed that power spectrum and HOS based features were statistically significant among the six emotional states (p < 0.0001). Classification results shows that using the selected HOS based features instead of power spectrum based features provided comparatively better accuracy for all the six classes with an overall accuracy of 70.10% ± 2.83% and 77.29% ± 1.73% for PD patients and HC in beta (13-30 Hz) band using SVM classifier. Besides, PD patients achieved less accuracy in the processing of negative emotions (sadness, fear, anger and disgust) than in processing of positive emotions (happiness, surprise) compared with HC. These results demonstrate the effectiveness of applying machine learning techniques to the classification of emotional states in PD patients in a user independent manner using EEG signals. The accuracy of the system can be improved by investigating the other HOS based features. This study might lead to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders

The Physical Basis for Long-lived Electronic Coherence in Photosynthetic Light Harvesting Systems

The physical basis for observed long-lived electronic coherence in photosynthetic light-harvesting systems is identified using an analytically soluble model. Three physical features are found to be responsible for their long coherence lifetimes: i) the small energy gap between excitonic states, ii) the small ratio of the energy gap to the coupling between excitonic states, and iii) the fact that the molecular characteristics place the system in an effective low temperature regime, even at ambient conditions. Using this approach, we obtain decoherence times for a dimer model with FMO parameters of $\approx$ 160 fs at 77 K and $\approx$ 80 fs at 277 K. As such, significant oscillations are found to persist for 600 fs and 300 fs, respectively, in accord with the experiment and with previous computations. Similar good agreement is found for PC645 at room temperature, with oscillations persisting for 400 fs. The analytic expressions obtained provide direct insight into the parameter dependence of the decoherence time scales.Comment: 5 figures; J. Phys. Chem. Lett. (2011

The gray matter volume of the amygdala is correlated with the perception of melodic intervals: a voxel-based morphometry study

Music is not simply a series of organized pitches, rhythms, and timbres, it is capable of evoking emotions. In the present study, voxel-based morphometry (VBM) was employed to explore the neural basis that may link music to emotion. To do this, we identified the neuroanatomical correlates of the ability to extract pitch interval size in a music segment (i.e., interval perception) in a large population of healthy young adults (N = 264). Behaviorally, we found that interval perception was correlated with daily emotional experiences, indicating the intrinsic link between music and emotion. Neurally, and as expected, we found that interval perception was positively correlated with the gray matter volume (GMV) of the bilateral temporal cortex. More important, a larger GMV of the bilateral amygdala was associated with better interval perception, suggesting that the amygdala, which is the neural substrate of emotional processing, is also involved in music processing. In sum, our study provides one of first neuroanatomical evidence on the association between the amygdala and music, which contributes to our understanding of exactly how music evokes emotional responses

Role of quantum coherence in chromophoric energy transport

The role of quantum coherence and the environment in the dynamics of excitation energy transfer is not fully understood. In this work, we introduce the concept of dynamical contributions of various physical processes to the energy transfer efficiency. We develop two complementary approaches, based on a Green's function method and energy transfer susceptibilities, and quantify the importance of the Hamiltonian evolution, phonon-induced decoherence, and spatial relaxation pathways. We investigate the Fenna-Matthews-Olson protein complex, where we find a contribution of coherent dynamics of about 10% and of relaxation of 80%.Comment: 5 pages, 3 figures, included static disorder, correlated environmen

A double-edged sword: the merits and the policy implications of Google Translate in higher education

Machine translation, specifically Google Translate is freely available on a number of devices, and is improving in its ability to provide grammatically accurate translations. This development has the potential to provoke a major transformation in the internationalisation process at universities, since students may be, in the future, able to use technology to circumvent traditional language learning processes. While this is a potentially empowering move that may facilitate academic exchange and the diversification of the learner and researcher community at an international level, it is also a potentially problematic issue in two main respects. Firstly, the technology is at present unable to align to the socio-linguistic aspects of university level writing and may be misunderstood as a remedy to lack of writer language proficiency – a role it is not able to fulfil. Secondly, it introduces a new dimension to the production of academic work that may clash with Higher Education policy and, thus, requires legislation, in particular in light issues such as plagiarism and academic misconduct. This paper considers these issues against the background of English as a Global Lingua Franca, and argues two points. First of these is that HEIs need to develop an understanding and code of practice for the use of this technology. Secondly, three strands of potential future research will be presente

Spelling errors and keywords in born-digital data: a case study using the Teenage Health Freak Corpus

The abundance of language data that is now available in digital form, and the rise of distinct language varieties that are used for digital communication, means that issues of non-standard spellings and spelling errors are, in future, likely to become more prominent for compilers of corpora. This paper examines the effect of spelling variation on keywords in a born-digital corpus in order to explore the extent and impact of this variation for future corpus studies. The corpus used in this study consists of e-mails about health concerns that were sent to a health website by adolescents. Keywords are generated using the original version of the corpus and a version with spelling errors corrected, and the British National Corpus (BNC) acts as the reference corpus. The ranks of the keywords are shown to be very similar and, therefore, suggest that, depending on the research goals, keywords could be generated reliably without any need for spelling correction