Construction Of Representations Research Articles

Intrincada construcción de identidad profesional y relaciones de poder: percepciones en docentes universitarios de Educación Física (Intricate construction of professional identity and power relations: perceptions in university Physical Education teachers)

Physical Education (PE) teachers, faced with the demands of a complex and changing society, warn that they are being placed before the educational system, as one of the main responsible for the crisis that university education is going through, events that disrupt the sense of professional identity forged during years of initial and in-service training. Aim. Understand the construction of representations of professional identity in a context of intersubjective positions of power based on interactive/reflective discourses among university PE teachers. Method. Qualitative, inductive, open coding, dynamic and interactive with support in Atlas.ti 8, for data analysis. Results. It is not possible to identify constructs-perceptions of professional identity, detached from a network, a field of very subtle arrangements and dissents that define positions, alliances, oppositions and intersubjective power relations among university PE teachers; Teachers go through tortuous experiences that prevent them from building their own identity; what exists is an attributed and pre-established identity; They associate their identity with “should be”, regulated-supervised by institutional-normative management and with ways of responding to the expectations and interests of others. Conclusion. In the current university management model, the teacher, in addition to assuming an attributed identity, linked to structural positions of dominance-subordination, experiences certain external pressures to abdicate his vocation and professional training in favor of the idea of ​​becoming a scientific and bureaucratic being. out of obligation. Institutional programs are needed to build university identity processes. Keywords: professional identity, university identity, university teaching, professional training, power relations, physical education teacher.

The curious case of seemingly incurious children

English-language teachers are increasingly recognizing the pedagogical value of using children’s literature that authentically represents diverse multilingual learners, including children who have sought refuge. This study analyses representations of children who have experienced displacement and sought refuge in picture books. Framed by a critical multicultural perspective of children’s literature, critical refugee studies and critical race theory, the study investigates how children’s emotions and agency are represented in focal stories. Our findings suggest that, contrary to the complex intellectual and emotional ways children and youth process displacement, picture books about seeking refuge tend to represent child protagonists as incurious about why they are forced to flee. Such representations construct legally scripted narratives associated with refugee status that normalize war and violence. These narratives ultimately mask colonialism, imperialism and racism that contribute to refugee flight around the world. We discuss how policies for seeking refuge influence picture books and invite educators to critically evaluate literature for their classrooms, directly engage families to foreground generative perspectives and develop comprehensive multilingual environments that affirm learners’ agency

Hyperspectral anomaly detection based on adaptive background dictionary construction and collaborative representation

ABSTRACT Collaborative representation-based (CR) methods have received widespread attention in hyperspectral anomaly detection, but the results are greatly affected by the quality of the background dictionary. Abnormal pixels and abnormal-mixed pixels in the background dictionary may affect the accuracy of linear representation and make its performance poor. To address the above problem, an adaptive background dictionary construction-based anomaly detection method is proposed. To ensure the purity of the background dictionary, abnormal pixels and abnormal-mixed pixels around each test pixel are removed adaptively through clustering and pure pixel extraction. Furthermore, the saliency weight of the test pixel is calculated through the pixels in the inner window and weighted into the linear representation process to improve the robustness of the method. Experimental results on four hyperspectral datasets show that the proposed method performs better than other CR methods and traditional detectors, and it can reduce the dependence of anomaly detection performance on dual window size.

The anterior cingulate cortex is involved in intero-exteroceptive integration for spatial image transformation of the self-body

Spatial image transformation of the self-body is a fundamental function of visual perspective-taking. Recent research underscores the significance of intero-exteroceptive information integration to construct representations of our embodied self. This raises the intriguing hypothesis that interoceptive processing might be involved in the spatial image transformation of the self-body. To test this hypothesis, the present study used functional magnetic resonance imaging to measure brain activity during an arm laterality judgment (ALJ) task. In this task, participants were tasked with discerning whether the outstretched arm of a human figure, viewed from the front or back, was the right or left hand. The reaction times for the ALJ task proved longer when the stimulus presented orientations of 0°, 90°, and 270° relative to the upright orientation, and when the front view was presented rather than the back view. Reflecting the increased reaction time, increased brain activity was manifested in a cluster centered on the dorsal anterior cingulate cortex (ACC), suggesting that the activation reflects the involvement of an embodied simulation in ALJ. Furthermore, this cluster of brain activity exhibited overlap with regions where the difference in activation between the front and back views positively correlated with the participants' interoceptive sensitivity, as assessed through the heartbeat discrimination task, within the pregenual ACC. These results suggest that the ACC plays an important role in integrating intero-exteroceptive cues to spatially transform the image of our self-body.

On the Product Functor on Inner forms of the General Linear Group Over A Non-Archimedean Local Field

AbstractLet $$G_n$$ G n be an inner form of a general linear group over a non-Archimedean local field. We fix an arbitrary irreducible representation $$\sigma $$ σ of $$G_n$$ G n . Building on the work of Lapid-Mínguez on the irreducibility of parabolic inductions, we show how to define a full subcategory of the category of smooth representations of some $$G_m$$ G m , on which the parabolic induction functor $$\tau \mapsto \tau \times \sigma $$ τ ↦ τ × σ is fully-faithful. A key ingredient of our proof for the fully-faithfulness is constructions of indecomposable representations of length 2. Such result for a special situation has been previously applied in proving the local non-tempered Gan-Gross-Prasad conjecture for non-Archimedean general linear groups. In this article, we apply the fully-faithful result to prove a certain big derivative arising from Jacquet functor satisfies the property that its socle is irreducible and has multiplicity one in the Jordan-Hölder sequence of the big derivative.

Mapping the neural mechanism that distinguishes between holistic thinking and analytic thinking

Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.

The Neural Corelates of Constructing Conceptual and Perceptual Representations of Autobiographical Memories.

Contemporary neurocognitive frameworks propose that conceptual and perceptual content of autobiographical memories-personal past experiences-are processed by dissociable neural systems. Other work has proposed a central role of the anterior hippocampus in initially constructing autobiographical memories, regardless of the content. Here, we report on an fMRI study that utilized a repeated retrieval paradigm to test these ideas. In a magnetic resonance imaging scanner, participants retrieved autobiographical memories at three timepoints. During the third retrieval, participants either shifted their focus to the conceptual content of the memory, the perceptual content of the memory, or retrieved the memory as they had done so on previous trials. We observed stronger anterior hippocampal activity for the first retrieval compared with later retrievals, regardless of whether there was a shift in content in those later trials. We also found evidence for separate cortical systems when constructing autobiographical memories with a focus on conceptual or perceptual content. Finally, we found that there was common engagement between later retrievals that required a shift toward conceptual content and the initial retrieval of a memory. This final finding was explored further with a behavioral experiment that provided evidence that focusing on conceptual content of a memory guides memory construction, whereas perceptual content adds precision to a memory. Together, these findings suggest there are distinct content-oriented cortical systems that work with the anterior hippocampus to construct representations of autobiographical memories.

Cross-level and multiscale CNN-Transformer network for automatic building extraction from remote sensing imagery

ABSTRACT Automatic building detection from remote sensing images holds significant applications in various domains, including cartography, land-use change detection, urban planning, and 3D intelligent city construction. Driven by the innovation of deep learning technology, convolutional neural networks (CNNs) have emerged as a powerful framework for automatic interpretation, exhibiting hierarchical feature generation and robust representation for building extraction. However, the inherent computational limitations of convolutional operators hinder the acquisition of an effective global receptive field. Recent advancements in deep learning have witnessed the adoption of the multi-head self-attention (MHSA) mechanism by Transformer, presenting the superiority of global context construction. Nonetheless, this network structure encounters difficulties in effectively modelling two-dimensional spatial structure features with scale variation in semantic segmentation and often has huge parameters with high algorithm complexity. To address the above problems, this paper proposed a hybrid deep neural network synergistically harnessing the superiority of CNN and Transformer to extract buildings from remote sensing images. Meanwhile, an improved MHSA mechanism is developed to facilitate the construction of multiscale global representations, concurrently reducing computational complexity. Furthermore, the cross-level MHSA modules the semantic correlation between the deep and shallow-level features to refine spatial fine-grained information. The proposed method was comprehensively evaluated on two building datasets via quantitative analysis and visualization. The experimental results confirmed that the developed network and modules outperform other state-of-the-art methods and can effectively improve the accuracy (93.4% F1-score on the WHU dataset, 89.38% F1-score on the CAMB dataset) with high efficiency for building extraction.

Dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis with incomplete pathology and genomic data

Objective. Effective fusion of histology slides and molecular profiles from genomic data has shown great potential in the diagnosis and prognosis of gliomas. However, it remains challenging to explicitly utilize the consistent-complementary information among different modalities and create comprehensive representations of patients. Additionally, existing researches mainly focus on complete multi-modality data and usually fail to construct robust models for incomplete samples. Approach. In this paper, we propose a dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis. DDM-net disentangles the latent features generated by two separate variational autoencoders (VAEs) into common and specific components through a dual-space disentangled approach, facilitating the construction of comprehensive representations of patients. More importantly, DDM-net imputes the unavailable modality in the latent feature space, making it robust to incomplete samples. Main results. We evaluated our approach on the TCGA-GBMLGG dataset for glioma grading and survival analysis tasks. Experimental results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with a competitive AUC of 0.952 and a C-index of 0.768. Significance. The proposed model may help the clinical understanding of gliomas and can serve as an effective fusion model with multimodal data. Additionally, it is capable of handling incomplete samples, making it less constrained by clinical limitations.

Реконструкция медийных социальных представлений с использованием показателей статистики текста (на материале медиадискурса о пандемии)

<p style="text-align: justify;"><strong>Objective. </strong>The aim is to present an algorithm to reconstruct media social representations based on indicators of text statistics and to conduct a comparative analysis of the construction of semantically similar media joint ventures, such as “pandemic”, “coronavirus”, “COVID-19” in Russian media. <br><strong>Background</strong>. Social representations perform the most important functions in the process of social functioning of an individual and a group, serve as a tool for cognition, adaptation and regulation of behavior and are formed taking into account the influence of media social representations. Methods for studying social representations for various social groups are presented in psychological studies, however, methods for studying media social representations are discussed in single scientific work. The presented scientific project is based on the theory of social representations by S. Moskovici and generalizations by B. Hoyer regarding the construction of media social representations (naming, emotional attachment, thematic attachment, metaphorical attachment and attachment through basic antinomies). <br><strong>Study design</strong>. The phenomenon of the coronavirus pandemic, presented in media discourse, was used as the signified in the study. The signifier is a trio of semantically similar concepts (“pandemic”, “COVID”, “coronavirus”). <br><strong>Measurements</strong>. To reconstruct media social representations, statistically stable collocations were identified to indicate the measure of association, logically close to the associative experiment. Hence, it was possible to identify thematic networks, axiological and evaluative components, components-characteristics of activity. The research material is represented by texts about the COVID-19 pandemic (January 2020-March 2022: “Rossiyskaya Gazeta”: 19471 texts, 7,97 million words; “Kommersant”: 1482 texts, 1,07 million words, “Novaya Gazeta”: 705 texts, 0,9 million words) and processed using BootCat, TreeTagger, AntConc (lemmatization, frequency analysis). <br><strong>Results</strong>. The associative fields of the joint ventures are different and contain anchoring and objectification resources when using concepts, only few elements of the associative field are similar. Thus, depending on the concept used to signify the intent of the text, stories about the fear of infection, the treatment of the disease, or resistance to the harsh elements are created. <br><strong>Conclusions</strong>. The similar algorithm based on media text statistics can be used to reconstruct any media social representation.</p>

Difficulty-Generating Features of Text-based Physics Tasks

Influencing the difficulty of performance tasks is of great interest in science education as in several other subjects. In the context of the VAMPS project, difficulty-generating features with respect to the cognitive demand of text-based physics tasks were systematically varied at three levels. Based on preliminary work and two pilot studies presented here briefly, a model was developed by which cognitive requirement was varied according to three features. The viability of this model was empirically tested with a sample of n = 414 secondary school students. The feature <i>cognitive activity</i> proved to be a significant factor influencing the empirically measured difficulty of tasks. With the help of the feature <i>number of information obtained from task stem</i> and <i>number of subject-specific mental procedures</i>, no systematic influence on task difficulty could be shown. The influence of the test persons’ individual prior knowledge on the actual task difficulty is generally assumed to be a confounding factor. Overall, the present study contributes to a better understanding of construct representation in assessments of subject-specific proficiency and empirically confirms that a systematic variation of the task feature <i>cognitive activity</i> on three levels affects task difficulty

Quantization of locally compact groups associated with essentially bijective 1-cocycles

Given an extension [Formula: see text] of locally compact groups, with [Formula: see text] abelian, and a compatible essentially bijective [Formula: see text]-cocycle [Formula: see text], we define a dual unitary [Formula: see text]-cocycle on [Formula: see text] and show that the associated deformation of [Formula: see text] is a cocycle bicrossed product defined by a matched pair of subgroups of [Formula: see text]. We also discuss an interpretation of our construction from the point of view of Kac cohomology for matched pairs. Our setup generalizes that of Etingof and Gelaki for finite groups and its extension due to Ben David and Ginosar, as well as our earlier work on locally compact groups satisfying the dual orbit condition. In particular, we get a locally compact quantum group from every involutive nondegenerate set-theoretical solution of the Yang–Baxter equation, or more generally, from every brace structure. On the technical side, the key new points are constructions of an irreducible projective representation of [Formula: see text] on [Formula: see text] and a unitary quantization map [Formula: see text] of Kohn–Nirenberg type.

“And then We Were Taken to Ravensbrück.” Early Oral Testimonies About Ravensbrück and Its Sub Camps

Abstract This article focuses on the analysis and interpretation of 15 testimonies collected immediately after the war by David Boder and by the Polish Historical Institute in Sweden with women deported to Auschwitz, evacuated to Ravensbrück in its last two phases and then to Malchow. The study of their statements can provide both a historical overview of Ravensbrück and its sub camps in 1944 and 1945, and help identify the effects of the camp, an overthrown social context, on individuals, women in this case, and groups. The comparative exam of the interviews allows to identify the crucial events and experiences which constitute the core of the interviewees’narration and representation of the events. The situations and episodes they chose to recall may explain their perception of the events and reveals a gendered perspective which affected their memories in terms of the selection of the events and their focus on specific issues. The memories were recalled in relation to social frames, which were different from those the survivors were previously used to and pertained to the context of the camp. These coordinates constitute a net which can provide an insight into the mechanism of memory construction and early representation of the Holocaust.

ЗАСТОСУВАННЯ КОНСТРУКТИВНОГО МОДЕЛЮВАННЯ ПРИ ВИЗНАЧЕННІ АВТОРСТВА ТЕКСТІВ

The development of the constructor, which allows displaying the sentences construction peculiarities for different authors, is presented. This approach takes into account the sentences structure characteristic of an individual author and can be used to detect plagiarism and establish the authorship of texts in various genres and styles. Thanks to which, the usual paraphrasing of the work or changing the order of sections, sentences or words will not become an obstacle for authorship determining. The proposed approach is promising and low-cost in terms of calculation capacity, unlike the existing ones. This way of the sentences construction representation is presented for the very first.

The structure of appalachian coal: Experiments and Ab initio modeling

This study focuses on the construction of small-scale atomistic representations of three Appalachian coals of different ranks– high-volatile bituminous, low volatile bituminous, and semi-anthracite. Ultimate, proximate, 13C NMR, FTIR, and XPS data were used to infer 2D and construct multiple 3D molecular models for each coal. A new simulation strategy for structure optimization, termed “Sectioned Optimization”, is introduced to ensure energetically stable configurations of the 3D coal models. Density functional methods are applied to the models, improving their quality, and giving insight into the limitations of empirical simulations in this complex system. The structural models were validated ex post facto using a density functional code, VASP. We describe the distribution of local atomic environments in the models to emphasize the significant structural distinctions between the three coal ranks. We also report the first ab initio vibrational density of states calculations for coal and compare it to FTIR and Inelastic Neutron Scattering experiments and identify vibrational modes using ab initio calculations. We show that the specific heat capacity compares favorably with experimental data.

Robust returns ranking prediction and portfolio optimization for M6

The M6 competition aims to address challenging problems in stock returns ranking prediction and portfolio optimization. To tackle the volatility and low signal-to-noise ratio in the stock market, our team designs the overall solution from the perspective of robustness. On the task of returns ranking prediction, we present the MultiTask Deep Neural Network with Denoising Autoencoder Enhancement (MT-DNN-DAE), which incorporates the self-supervised learning of DAE and jointly optimizes the multi-task loss. Additionally, we propose Robust Feature Selection (RFS) to identify features with a high signal-to-noise ratio for DAE’s representation learning and construct a separate branch for important ID feature to prevent its information loss. Results show our solution is capable of accurately predicting returns ranking while maintaining generalization. On the task of portfolio optimization, a Differential Evolution algorithm is also presented to optimize asset allocation and maximize returns under risk constraints, demonstrating improved performance over traditional techniques. Taken together, these methods led to a 4th place global ranking in the M6 competition.

Instance-Aware Multi-Camera 3D Object Detection with Structural Priors Mining and Self-Boosting Learning

Camera-based bird-eye-view (BEV) perception paradigm has made significant progress in the autonomous driving field. Under such a paradigm, accurate BEV representation construction relies on reliable depth estimation for multi-camera images. However, existing approaches exhaustively predict depths for every pixel without prioritizing objects, which are precisely the entities requiring detection in the 3D space. To this end, we propose IA-BEV, which integrates image-plane instance awareness into the depth estimation process within a BEV-based detector. First, a category-specific structural priors mining approach is proposed for enhancing the efficacy of monocular depth generation. Besides, a self-boosting learning strategy is further proposed to encourage the model to place more emphasis on challenging objects in computation-expensive temporal stereo matching. Together they provide advanced depth estimation results for high-quality BEV features construction, benefiting the ultimate 3D detection. The proposed method achieves state-of-the-art performances on the challenging nuScenes benchmark, and extensive experimental results demonstrate the effectiveness of our designs.

Enhancing XML-based Compiler Construction with Large Language Models: A Novel Approach

Considering the prevailing rule of Large Language Models (LLMs) applications and the benefits of XML in a compiler context. This manuscript explores the synergistic integration of Large Language Models with XML-based compiler tools and advanced computing technologies. Marking a significant stride toward redefining compiler construction and data representation paradigms. As computing power and internet proliferation advance, XML emerges as a pivotal technology for representing, exchanging, and transforming documents and data. This study builds on the foundational work of Chomsky's Context-Free Grammar (CFG). Recognized for their critical role in compiler construction, to address and mitigate the speed penalties associated with traditional compiler systems and parser generators through the development of an efficient XML parser generator employing compiler techniques. Our research employs a methodical approach to harness the sophisticated capabilities of LLMs, alongside XML technologies.  The key is to automate grammar optimization, facilitate natural language processing capabilities, and pioneer advanced parsing algorithms. To demonstrate their effectiveness, we thoroughly run experiments and compare them to other techniques. This way, we call attention to the efficiency, adaptability, and user-friendliness of the XML-based compiler tools with the help of these integrations. And the target will be the elimination of left-recursive grammars and the development of a global schema for LL(1) grammars, the latter taking advantage of the XML technology, to support the LL(1) grammars construction. The findings in this research not only underscore the signification of these innovations in the field of compilation construction but also indicate a paradigm move towards the use of AI technologies and XML in the context of the resolution of programming traditional issues. The outlined methodology serves as a roadmap for future research and development in compiler technology, which paves the way for open-source software to sweep across all fields. Gradually ushering in a new era of compiler technology featuring better efficiency, adaptability, and all CFGs processed through existing XML utilities on a global basis.

An integrated conceptual model for enhancing refugee education

AbstractThis paper introduces a unified conceptual framework for understanding refugee identity construction within educational contexts, drawing on theories of social justice (Fraser, 2008), affective relations (Lynch, 2012), the resumption of ordinary life (Kohli, 2011) and ecological systems (Bronfenbrenner, 1977). Addressing a gap in the existing scholarship, the model emphasises the importance of affective relations in shaping refugee identities in education alongside other factors. The study examines the macro constructs of redistribution, recognition, representation and relational affect, highlighting their impact on refugee children's educational experiences. Further, it considers the micro constructs of safety, sense of belonging and success in integration and attainment in educational environments. The constructs are examined across various levels of Bronfenbrenner's ecological system, demonstrating the complexity of refugees’ needs. This model aims to facilitate a holistic, justice‐oriented approach to refugee education, which is crucial given the rise in global displacement. The study has significant implications for refugee education research and policymaking, potentially informing targeted interventions and programmes that foster academic success, overall well‐being, and practice in refugee education.

"Don't Call Me Angel": The Construction of Female Representation from a Postfeminist Perspective

"Don't Call Me Angel": The Construction of Female Representation from a Postfeminist Perspective