The mismatch negativity (MMN) response to complex tones and spoken words in individuals with aphasia

Background: The mismatch negativity (MMN) is a fronto-centrally distributed event-related potential (ERP) that is elicited by any discriminable auditory change. It is an ideal neurophysiological tool for measuring the auditory processing skills of individuals with aphasia because it can be elicited even in the absence of attention. Previous MMN studies have shown that acoustic processing of tone or pitch deviance is relatively preserved in aphasia, whereas the basic acoustic processing of speech stimuli can be impaired (e.g., auditory discrimination). However, no MMN study has yet investigated the higher levels of auditory processing, such as language-specific phonological and/or lexical processing, in individuals with aphasia. Aims: The aim of the current study was to investigate the MMN response of normal and language-disordered subjects to tone stimuli and speech stimuli that incorporate the basic auditory processing (acoustic, acoustic-phonetic) levels of non-speech and speech sound processing, and also the language-specific phonological and lexical levels of spoken word processing. Furthermore, this study aimed to correlate the aphasic MMN data with language performance on a variety of tasks specifically targeted at the different levels of spoken word processing. Methods M Procedures: Six adults with aphasia (71.7 years +/- 3.0) and six healthy age-, gender-, and education-matched controls (72.2 years +/- 5.4) participated in the study. All subjects were right-handed and native speakers of English. Each subject was presented with complex harmonic tone stimuli, differing in pitch or duration, and consonant-vowel (CV) speech stimuli (non-word /de:/versus real world/deI/). The probability of the deviant for each tone or speech contrast was 10%. The subjects were also presented with the same stimuli in behavioural discrimination tasks, and were administered a language assessment battery to measure their auditory comprehension skills. Outcomes O Results: The aphasic subjects demonstrated attenuated MMN responses to complex tone duration deviance and to speech stimuli (words and non-words), and their responses to the frequency, duration, and real word deviant stimuli were found to strongly correlate with performance on the auditory comprehension section of the Western Aphasia Battery (WAB). Furthermore, deficits in attentional lexical decision skills demonstrated by the aphasic subjects correlated with a word-related enhancement demonstrated during the automatic MMN paradigm, providing evidence to support the word advantage effect, thought to reflect the activation of language-specific memory traces in the brain for words. Conclusions: These results indicate that the MMN may be used as a technique for investigating general and more specific auditory comprehension skills of individuals with aphasia, using speech and/or non-speech stimuli, independent of the individual's attention. The combined use of the objective MMN technique and current clinical language assessments may result in improved rehabilitative management of aphasic individuals.

Complex numbers and symmetries in quantum mechanics, and a nonlinear superposition principle for Wigner functions

Complex numbers appear in the Hilbert space formulation of quantum mechanics, but not in the formulation in phase space. Quantum symmetries are described by complex, unitary or antiunitary operators defining ray representations in Hilbert space, whereas in phase space they are described by real, true representations. Equivalence of the formulations requires that the former representations can be obtained from the latter and vice versa. Examples are given. Equivalence of the two formulations also requires that complex superpositions of state vectors can be described in the phase space formulation, and it is shown that this leads to a nonlinear superposition principle for orthogonal, pure-state Wigner functions. It is concluded that the use of complex numbers in quantum mechanics can be regarded as a computational device to simplify calculations, as in all other applications of mathematics to physical phenomena.

Quel role pour la langue de reference dans les representations des apprenants? Le cas de l'evaluation en langue etrangere

This research project explores learner’s representations of strategic L1 use in the foreign language classroom and highlights both the positive or negative roles attributed to the L1 in the language learning process - particularly with respect to language assessment - continuing to explore the relatively understudied domain of student representations within a scholarly context. Surveying a population of Australian (N=18) and French students (N=25), this study uses both questionnaire and interview responses in order to analyse the roles allocated to the L1 with respect to learning outcomes. The results indicate that students have a very balanced view of the L1 with respect to the learning of grammar, vocabulary and social aspects, yet its use in assessment aspects appears much more advantageous. The importance of this study and its findings is in recognizing the complex nature of learner representations in order to facilitate a discussion that is based more on the reality of language teaching, with the hope of renewing classroom practices.

Inscribing the organization:representations in dispute between accounting and production

This paper assumes that a primary function of management accounting is the representation of "accounting facts" for purposes such as organizational control. Accountants are able to offer conventional techniques of control, such as standard costing, as a consequence of their ability to deploy accounting representations within managerial and economic models of organizational processes. Accounting competes, at times, with other 'professional' groups, such as production planning or quality management people, in this role of representing the organization to management. The paper develops its arguments around a case illustration of cost accounting set in a low technology manufacturing environment. The research relates to a case organization in which accountants are attempting to establish the reliability of accounting inscriptions of a simple manufacturing process. The case research focuses on the documents, the inscriptions that vie for managements' attention. It is these sometimes messy and inaccurate representations which enable control of complex and heterogeneous activities at a distance. At the end of our site visits we observe quality management systems in the ascendancy over the accountants' standard costing systems. © 2006 Elsevier Ltd. All rights reserved.

From detection of complex motion to descriptions of moving surfaces in human vision

A preliminary study by Freeman et al (1996b) has suggested that when complex patterns of motion elicit impressions of 2-dimensionality, odd-item-out detection improves given targets can be differentiated on the basis of surface properties. Their results can be accounted for, it if is supposed that observers are permitted efficient access to 3-D surface descriptions but access to 2-D motion descriptions is restricted. To test the hypothesis, a standard search technique was employed, in which targets could be discussed on the basis of slant sign. In one experiment, slant impressions were induced through the summing of deformation and translation components. In a second theory were induced through the summing of shear and translation components. Neither showed any evidence of efficient access. A third experiment explored the possibility that access to these representations may have been hindered by a lack of grouping between the stimuli. Attempts to improve grouping failed to produce convincing evidence in support of life. An alternative explanation is that complex patterns of motion are simply not processed simultaneously. Psychophysical and physiological studies have, however, suggested that multiple mechanisms selective for complex motion do exist. Using a subthreshold summation technique I found evidence supporting the notion that complex motions are processed in parallel. Furthermore, in a spatial summation experiment, coherence thresholds were measured for displays containing different numbers of complex motion patches. Consistent with the idea that complex motion processing proceeds in parallel, increases in the number of motion patches were seen to decrease thresholds, both for expansion and rotation. Moreover, the rates of decrease were higher than those typically expected from probability summation, thus implying mechanisms are available, which can pool signals from spatially distinct complex motion flows.

Resisting the final word:challenging stale media and policy representations of students’ performative technological encounters in university education

This article explores powerful, constraining representations of encounters between digital technologies and the bodies of students and teachers, using corpus-based Critical Discourse Analysis (CDA). It discusses examples from a corpus of UK Higher Education (HE) policy documents, and considers how confronting such documents may strengthen arguments from educators against narrow representations of an automatically enhanced learning. Examples reveal that a promise of enhanced ‘student experience’ through information and communication technologies internalizes the ideological constructs of technology and policy makers, to reinforce a primary logic of exchange value. The identified dominant discursive patterns are closely linked to the Californian ideology. By exposing these texts, they provide a form of ‘linguistic resistance’ for educators to disrupt powerful processes that serve the interests of a neoliberal social imaginary. To mine this current crisis of education, the authors introduce productive links between a Networked Learning approach and a posthumanist perspective. The Networked Learning approach emphasises conscious choices between political alternatives, which in turn could help us reconsider ways we write about digital technologies in policy. Then, based on the works of Haraway, Hayles, and Wark, a posthumanist perspective places human digital learning encounters at the juncture of non-humans and politics. Connections between the Networked Learning approach and the posthumanist perspective are necessary in order to replace a discourse of (mis)representations with a more performative view towards the digital human body, which then becomes situated at the centre of teaching and learning. In practice, however, establishing these connections is much more complex than resorting to the typically straightforward common sense discourse encountered in the Critical Discourse Analysis, and this may yet limit practical applications of this research in policy making.

Complex functions with Geogebra

Complex functions, generally feature some interesting peculiarities, seen as extensions real functions, complementing the study of real analysis. However, the visualization of some complex functions properties requires the simultaneous visualization of two-dimensional spaces. The multiple Windows of GeoGebra, combined with its ability of algebraic computation with complex numbers, allow the study of the functions defined from ℂ to ℂ through traditional techniques and by the use of Domain Colouring. Here, we will show how we can use GeoGebra for the study of complex functions, using several representations and creating tools which complement the tools already provided by the software. Our proposals designed for students of the first year of engineering and science courses can and should be used as an educational tool in collaborative learning environments. The main advantage in its use in individual terms is the promotion of the deductive reasoning (conjecture / proof). In performed the literature review few references were found involving this educational topic and by the use of a single software.

E-polynomial of SL(2,C)-character varieties of complex curves of genus 3.

We compute the E-polynomials of the moduli spaces of representations of the fundamental group of a complex curve of genus g = 3 into SL(2, C), and also of the moduli space of twisted representations. The case of genus g = 1, 2 has already been done in [12]. We follow the geometric technique introduced in [12], based on stratifying the space of representations, and on the analysis of the behaviour of the E-polynomial under fibrations.

Embedded representations of social interactions

Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.

Deploying and processing neural representations of signals

Neural representations (NR) have emerged in the last few years as a powerful tool to represent signals from several domains, such as images, 3D shapes, or audio. Indeed, deep neural networks have been shown capable of approximating continuous functions that describe a given signal with theoretical infinite resolution. This finding allows obtaining representations whose memory footprint is fixed and decoupled from the resolution at which the underlying signal can be sampled, something that is not possible with traditional discrete representations, e.g., grids of pixels for images or voxels for 3D shapes. During the last two years, many techniques have been proposed to improve the capability of NR to approximate high-frequency details and to make the optimization procedures required to obtain NR less demanding both in terms of time and data requirements, motivating many researchers to deploy NR as the main form of data representation for complex pipelines. Following this line of research, we first show that NR can approximate precisely Unsigned Distance Functions, providing an effective way to represent garments that feature open 3D surfaces and unknown topology. Then, we present a pipeline to obtain in a few minutes a compact Neural Twin® for a given object, by exploiting the recent advances in modeling neural radiance fields. Furthermore, we move a step in the direction of adopting NR as a standalone representation, by considering the possibility of performing downstream tasks by processing directly the NR weights. We first show that deep neural networks can be compressed into compact latent codes. Then, we show how this technique can be exploited to perform deep learning on implicit neural representations (INR) of 3D shapes, by only looking at the weights of the networks.

Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Albumin Is Synthesized In Epididymis And Aggregates In A High Molecular Mass Glycoprotein Complex Involved In Sperm-egg Fertilization.

The epididymis has an important role in the maturation of sperm for fertilization, but little is known about the epididymal molecules involved in sperm modifications during this process. We have previously described the expression pattern for an antigen in epididymal epithelial cells that reacts with the monoclonal antibody (mAb) TRA 54. Immunohistochemical and immunoblotting analyses suggest that the epitope of the epididymal antigen probably involves a sugar moiety that is released into the epididymal lumen in an androgen-dependent manner and subsequently binds to luminal sperm. Using column chromatography, SDS-PAGE with in situ digestion and mass spectrometry, we have identified the protein recognized by mAb TRA 54 in mouse epididymal epithelial cells. The ∼65 kDa protein is part of a high molecular mass complex (∼260 kDa) that is also present in the sperm acrosomal vesicle and is completely released after the acrosomal reaction. The amino acid sequence of the protein corresponded to that of albumin. Immunoprecipitates with anti-albumin antibody contained the antigen recognized by mAb TRA 54, indicating that the epididymal molecule recognized by mAb TRA 54 is albumin. RT-PCR detected albumin mRNA in the epididymis and fertilization assays in vitro showed that the glycoprotein complex containing albumin was involved in the ability of sperm to recognize and penetrate the egg zona pellucida. Together, these results indicate that epididymal-derived albumin participates in the formation of a high molecular mass glycoprotein complex that has an important role in egg fertilization.

Effects Of Partial Inhibition Of Respiratory Complex I On H2o 2 Production By Isolated Brain Mitochondria In Different Respiratory States.

The aim of this work was to characterize the effects of partial inhibition of respiratory complex I by rotenone on H2O2 production by isolated rat brain mitochondria in different respiratory states. Flow cytometric analysis of membrane potential in isolated mitochondria indicated that rotenone leads to uniform respiratory inhibition when added to a suspension of mitochondria. When mitochondria were incubated in the presence of a low concentration of rotenone (10 nm) and NADH-linked substrates, oxygen consumption was reduced from 45.9 ± 1.0 to 26.4 ± 2.6 nmol O2 mg(-1) min(-1) and from 7.8 ± 0.3 to 6.3 ± 0.3 nmol O2 mg(-1) min(-1) in respiratory states 3 (ADP-stimulated respiration) and 4 (resting respiration), respectively. Under these conditions, mitochondrial H2O2 production was stimulated from 12.2 ± 1.1 to 21.0 ± 1.2 pmol H2O2 mg(-1) min(-1) and 56.5 ± 4.7 to 95.0 ± 11.1 pmol H2O2 mg(-1) min(-1) in respiratory states 3 and 4, respectively. Similar results were observed when comparing mitochondrial preparations enriched with synaptic or nonsynaptic mitochondria or when 1-methyl-4-phenylpyridinium ion (MPP(+)) was used as a respiratory complex I inhibitor. Rotenone-stimulated H2O2 production in respiratory states 3 and 4 was associated with a high reduction state of endogenous nicotinamide nucleotides. In succinate-supported mitochondrial respiration, where most of the mitochondrial H2O2 production relies on electron backflow from complex II to complex I, low rotenone concentrations inhibited H2O2 production. Rotenone had no effect on mitochondrial elimination of micromolar concentrations of H2O2. The present results support the conclusion that partial complex I inhibition may result in mitochondrial energy crisis and oxidative stress, the former being predominant under oxidative phosphorylation and the latter under resting respiration conditions.

A New Platinum Complex With Tryptophan: Synthesis, Structural Characterization, Dft Studies And Biological Assays In Vitro Over Human Tumorigenic Cells.

A new platinum(II) complex with the amino acid L-tryptophan (trp), named Pt-trp, was synthesized and characterized. Elemental, thermogravimetric and ESI-QTOF mass spectrometric analyses led to the composition [Pt(C11H11N2O2)2]⋅6H2O. Infrared spectroscopic data indicate the coordination of trp to Pt(II) through the oxygen of the carboxylate group and also through the nitrogen atom of the amino group. The (13)C CP/MAS NMR spectroscopic data confirm coordination through the oxygen atom of the carboxylate group, while the (15)N CP/MAS NMR data confirm coordination of the nitrogen of the NH2 group to the metal. Density functional theory (DFT) studies were applied to evaluate the cis and trans coordination modes of trp to platinum(II). The trans isomer was shown to be energetically more stable than the cis one. The Pt-trp complex was evaluated as a cytotoxic agent against SK-Mel 103 (human melanoma) and Panc-1 (human pancreatic carcinoma) cell lines. The complex was shown to be cytotoxic over the considered cells.