Construction Of Representations Research Articles

Bosonic field digitization for quantum computers

Quantum simulation of quantum field theory is a flagship application of quantum computers that promises to deliver capabilities beyond classical computing. The realization of quantum advantage will require methods that can accurately predict error scaling as a function of the resolution and parameters of the model and that can be implemented efficiently on quantum hardware. In this paper, we address the representation of lattice bosonic fields in a discretized field amplitude basis, develop methods to predict error scaling, and present efficient qubit implementation strategies. A low-energy subspace of the bosonic Hilbert space, defined by a boson occupation number cutoff, can be represented with exponentially good accuracy by a low-energy subspace of a finite-size Hilbert space. The finite representation construction and the associated errors are directly related to the accuracy of the Nyquist-Shannon sampling and the finite Fourier transforms of the boson number states in the field and the conjugate-field bases. We analyze the relation between the boson mass, the discretization parameters used for wave function sampling, and the finite representation size. Numerical simulations of small size ${\mathrm{\ensuremath{\Phi}}}^{4}$ problems demonstrate that the boson mass optimizing the sampling of the ground state wave function is a good approximation to the optimal boson mass yielding the minimum low-energy subspace size. However, we find that accurate sampling of general wave functions does not necessarily result in accurate representation. We develop methods for validating and adjusting the discretization parameters to achieve more accurate simulations.

Drawing and Building Your Way to Understanding: The Importance of Constructing Multiple Representations When Learning Anatomy

IntroductionLearning a concept through engaging with multiple representations of it, has long been recognized as a powerful way to facilitate understanding. Yet, learning through the active construction of multiple representations of a particular concept has only recently begun to receive attention, and has yet to be fully explored in anatomy. Research shows that learning is more successful when learners are active in the construction of their own understanding. As such, drawing and building physical models in order to learn are two methods through which a student can actively construct multiple representations of a concept. The act of drawing and building models in learning anatomy are powerful ways to make the unseen seen and the complex simple.MethodsThis was a two‐phase project, repeated across three cohorts (2019, 2020 and 2021) of first year medical students. Phase 1 included development and implementation of a series of original drawing (‘Draw‐It’) and model building (‘Do‐It’) tasks for first year medical students at Warwick Medical School (3 cohorts; n=604). Activities covered all anatomical systems and regions of the body, with particular focus on threshold topics students traditionally find challenging. All Year 1 medical students participated in twenty‐five ‘Draw‐It’ / ‘Do‐It’ sessions, each 40‐minutes in length, integrated within their core anatomical curriculum spread across the academic year. Phase 2 involved a two‐phase sequential explanatory mixed methods study exploring how students engaged with and perceived the impact of the integrated drawing and model building tasks in the year 1 curriculum. This phase included an end of year quantitative survey (3 cohorts; n=598) and follow‐up semi‐structured one‐on‐one interviews (3 cohorts; n=56).ResultsQuantitative results from this study showed that 88% strongly agreed that the ‘Draw‐It’ and ‘Do‐It’ tasks helped them to simplify complex anatomy, 74% reported these tasks improved the way they visualised anatomy, and 86% reported that these tasks were key in showing them where their weak areas were. Qualitative results showed the majority of students felt the activities exposed their areas of misunderstanding, challenged them to visualise anatomy in a simpler way, increased their ability to remember complex subjects/concepts, and required them to draw upon material previously taught in the course, and re‐create it in their own way. Many students felt the sessions positively ‘took away the mystery’ surrounding complex subject areas, made drawing an ‘approachable skill’, required them ‘to think about the same anatomy in ways they never expected’, and encouraged them to think about the ‘why’ behind their anatomical learning.Conclusion and ImplicationsThis study has practical and theoretical benefit to the anatomical and medical education community, namely that active construction of understanding involves cognitive processes central to deep learning and encourages critical thinking. It offers a new understanding into the ways that drawing and model building activities can effectively be integrated throughout a curriculum, and shows how these dynamic learning tools can be used to inspire learners to take an active role in the construction of their own understanding through multiple representations of a topic.

Neuromorphic Neural Engineering Framework-Inspired Online Continuous Learning with Analog Circuitry

Neuromorphic hardware designs realize neural principles in electronics to provide high-performing, energy-efficient frameworks for machine learning. Here, we propose a neuromorphic analog design for continuous real-time learning. Our hardware design realizes the underlying principles of the neural engineering framework (NEF). NEF brings forth a theoretical framework for the representation and transformation of mathematical constructs with spiking neurons, thus providing efficient means for neuromorphic machine learning and the design of intricate dynamical systems. Our analog circuit design implements the neuromorphic prescribed error sensitivity (PES) learning rule with OZ neurons. OZ is an analog implementation of a spiking neuron, which was shown to have complete correspondence with NEF across firing rates, encoding vectors, and intercepts. We demonstrate PES-based neuromorphic representation of mathematical constructs with varying neuron configurations, the transformation of mathematical constructs, and the construction of a dynamical system with the design of an inducible leaky oscillator. We further designed a circuit emulator, allowing the evaluation of our electrical designs on a large scale. We used the circuit emulator in conjunction with a robot simulator to demonstrate adaptive learning-based control of a robotic arm with six degrees of freedom.

What Eye Movement Reveals Concerning Age-Related Dissociation in Syntactic Prediction: Evidence From a Verb-Final Language.

How older adults engage in predictive processing compared to young adults during sentence processing has been a controversial issue in psycholinguistic research. This study investigated whether age-related differences in predictive processing emerge and how they influence young and older adults' construction of sentential representations in a verb-final language using the visual world eye-tracking paradigm. Twenty-five young adults and 24 older adults participated in this study. They were administered a sentence-picture matching task under active and passive conditions during which their eye movements were recorded. Older adults showed a stronger reliance on predictive processing based on probabilistic constraints compared to young adults at the second noun phrase (NP2) for both active and passive sentences. Specifically, older adults showed significantly greater target advantage looks in actives but greater distractor advantage looks in passives before encountering the verb compared to young adults, revealing older adults' stronger preference for active sentence representations. This stronger predictive processing at the NP2 among older adults engendered greater reduction in fixation proportion on the target picture at the verb only under the passive condition, suggesting that older adults experienced greater difficulties with syntactic revision and integration in passives compared to young adults. The current findings support that older adults more strongly rely on predictive processing based on probabilistic constraints denoted by case markers when constructing sentential representation compared to young adults, and this processing pattern increases processing difficulties when their prediction is incongruent with linguistic input.

Text recall and use of advance organisers in first and second language

AbstractPrevious research identified that studying texts in a second language (L2) as opposed to the first (L1) results in substantially weaker recall. We hypothesized that use of advance organizers (AOs) might attenuate this L2 recall cost by supporting L2 users in the construction of more solid memory representations. One hundred Dutch-English bilinguals studied two texts in either L1 or L2, and with or without the help of a mind map. The previously reported L2 cost was replicated, with lower recall scores in L2 relative to L1. Whereas L1 and L2 students were equally aided by AO use, the initial cost dissipated when comparing L2 test scores in the AO condition with those of L1 in the non-AO condition. We therefore conclude that employing AOs does not entirely diminish L2 disadvantages but brings L2 students up to the initial level of L1 students.

Representations of Sexuality among Persons with Intellectual Disability, as Perceived by Professionals in Specialized Institutions: A Systematic Review.

The objective of this systematic review is to make an inventory of the representations of the professionals of specialized institutions on the sexuality of persons with intellectual disabilities. The scientific studies were identified according to the PRISMA protocol using 18 databases, with keywords on sexuality and parenthood. Studies were reviewed through a methodological assessment and then a thematic analysis. Twenty-four studies were reviewed and three themes were identified: professionals’ representations of gender, sexuality, and consent; professionals’ perceptions of their role in supporting people’s sexual lives; and the ways in which professionals construct representations of people’s sexual lives. This corpus highlights deep paradoxes in the representations of professionals concerning the socio-affective needs and sexuality of people with intellectual disabilities, creating what we could define as a “system of incompatibility” and leading to difficulties in positioning. Support is still too random and subject to control logics in the name of protecting users, who are perceived as vulnerable. Training and new ways of teamwork appear to be central to supporting the evolution of the representations and practices of professionals. Future research anchored in practices and involving users as well as professionals is necessary to better understand the paradoxical aspects of professionals’ representations and to draw alternative ways of constructing these representations.

Non-binary language in Spanish? Comprehension of non-binary morphological forms: a psycholinguistic study

There is empirical evidence in different languages on how the computation of gender morphology during psycholinguistic processing affects the construction of sex-generic representations. However, there are few experimental studies in Spanish and there is no empirical evidence about the psycholinguistic processing of morphological innovations used as non-binary forms (-x; -e) in contrast to the generic masculine variant (-o). To analyze this phenomenon, we designed a sentence comprehension task. We registered reading times, precision and response times. The results show the specialization of non-binary forms as generic morphological variants, as opposed to the generic masculine. The non-binary forms consistently elicited a reference to mixed groups of people and the response times indicated that these morphological variants do not carry a higher processing cost than the generic masculine. Contrary to what classical grammatical approaches propose, the generic masculine does not function in all cases as generic and its ability to refer to groups of people without uniform gender seems to be modulated by the stereotypicality of the role names.

Representation of insulin synthesis and construction of a three-dimensional insulin model as didactic tools in basic education

ABSTRACT Proteins are essential for cell function, and their biological performance depends on three-dimensional (3D) structures. Insulin is made up of 51 amino acids and is a critical hormone involved in glycaemia regulation. In basic education, concepts involving proteins (synthesis, structure, interactions, and function) are abstract and difficult for students to understand. The use of protein 3D models that assist in visualising biomolecular structures can be an important didactic tool to understand the complexity of protein structure. Here, we propose a practical activity for the construction of a 3D model of insulin, as a tool for teaching protein synthesis and structure to students in the 9th-grade of basic education. The activity involved three classes of one hour each. 62 students role-played the insulin mRNA translation and represented the primary structure through balloons tied to a string. They also built an 3D insulin model using Styrofoam balls and wire. The activities proved to be effective, as there was a better understanding by students regarding proteins and their characteristics. Therefore, practical classes for teaching proteins can be used in basic education to improve learning of abstract and sub-microscopic concepts.

THE INFLUENCE OF VARIATION AND EXPECTATION ON THE DEVELOPING AWARENESS OF DISTRIBUTION

This study considers the evolving influence of variation and expectation on the development of school students’ appreciation of distribution as displayed in their construction of graphical representations of data sets. Three interview protocols are employed, presenting different contexts within which 109 students, ranging in age from 6 to 15 years, could display and interpret their understanding. Responses are analyzed within a hierarchical cognitive framework. It is hypothesized from the analysis that, contrary to the order in which expectation and variation are introduced in the school curriculum, the natural tendency for students is to acknowledge variation first and then expectation. First published May 2009 at Statistics Education Research Journal Archives

Women first-person narrative as a tool for deconstructing stereotyped representations of gender-based violence

The social representation of gender-based violence constitutes a subject of increasing interest by researchers in many sub-disciplinary areas of sociology. The growing interest of social scientists in this topic is due to the crucial role of culturally transmitted social mechanisms, that are reflected in the language through which institutions and social actors represent male violence against women, thus reproducing the conditions underlying it. Every social phenomenon lies in its narrative, in the way it is constructed and, in the language chosen to represent it. Therefore, narrative constitutes a fundamental heuristic and hermeneutical instrument through which it is possible to give meaning to a social phenomenon. Nevertheless, it often happens that third people, institutions, or various social actors construct narrative of social phenomena, without involving the people that experienced it. This happens with the narration of gender-based violence that all too often comes from external social actors, while the women who are protagonists – against their will –of the episodes of violence, are excluded from the construction of the social representation of what they suffered. This work, after briefly illustrating the main characteristics of the dominant social representation of male violence against women, proposes a theoretical reflection on the importance of women first-person narrative, as a tool for deconstructing the distorted social representation of gender-based violence that contributes to the perpetuation of its normalization, to the “de-responsibilization” of its perpetrator and of the sexist prejudices against women victims of such violence.

Exact Simulation of Max-Infinitely Divisible Processes

Max-infinitely divisible (max-id) processes play a central role in extreme-value theory and include the subclass of all max-stable processes. They allow for a constructive representation based on the pointwise maximum of random functions drawn from a Poisson point process defined on a suitable function space. Simulating from a max-id process is often difficult due to its complex stochastic structure, while calculating its joint density in high dimensions is often numerically infeasible. Therefore, exact and efficient simulation techniques for max-id processes are useful tools for studying the characteristics of the process and for drawing statistical inferences. Inspired by the simulation algorithms for max-stable processes, theory and algorithms to generalize simulation approaches tailored for certain flexible (existing or new) classes of max-id processes are presented. Efficient simulation for a large class of models can be achieved by implementing an adaptive rejection sampling scheme to sidestep a numerical integration step in the algorithm. The results of a simulation study highlight that our simulation algorithm works as expected and is highly accurate and efficient, such that it clearly outperforms customary approximate sampling schemes. As a by-product, new max-id models, which can be represented as pointwise maxima of general location-scale mixtures and possess flexible tail dependence structures capturing a wide range of asymptotic dependence scenarios, are also developed.

Construction of the Canonical Representation from a Noncanonical Representation

Construction of the Canonical Representation from a Noncanonical Representation

Teaching About Electricity in Primary School Multimodality and Variation Theory as Analytical Lenses

AbstractPrimary school topics involving abstract concepts are challenging to teach. Electric circuits can be simply constructed but complex to explain. New approaches in teaching students for understanding are needed to advance practice in primary science. This paper combines the strengths of multimodality research perspectives with variation theory to provide insights into a teaching sequence designed for year 6 students. Application of a representation construction approach (RCA) provides opportunities for multimodal meaning-making of electric circuits. The case study adopted a design-based research method to investigate teaching electric circuits. Data collection involved video capture of classroom practice, teacher and student interviews, student journal entries and assessment artefacts, field notes, and pre-test and post-test results. Design principles included identifying key ideas, devising a lesson sequence emphasising energy transfer and transformation, hands-on exploration using multimodal representations in response to learning challenges, and student journaling. Students’ metarepresentational competence was also developed through evaluation, negotiation, and creation of representations and models of electric circuits. Representational challenges followed by strategic teacher-led discussion facilitated students’ developing understanding through focusing attention on critical features. Deep learning was evidenced by journal records, formative and summative assessment artefacts, and post-test responses. RCA principles were instrumental in the successful design of an effective teaching sequence through focus on critical aspects of energy. We advocate a RCA for the design of a multimodal learning sequence. Variation theory was a useful analytical framework to understand the enactment of the design sequence. The study contributes to the challenge of rethinking traditional teaching practices in primary science.

Developing a local academic English listening test using authentic unscripted audio-visual texts

Despite consistent calls for authentic stimuli in listening tests for better construct representation, unscripted texts have been rarely adopted in high-stakes listening tests due to perceived inefficiency. This study details how a local academic listening test was developed using authentic unscripted audio-visual texts from the local target language use (TLU) domain without compromising the reliability of the test results and validity of the score interpretations. The purpose of the listening test was to identify international students who need additional language support at a U.S. university. We show that efficiency persists when using authentic unscripted texts that are representative of the local context both at the test development phase and at the classification phase where placement decisions are made in a dependable manner. Expert judgments highlighted the improved correspondence of the listening test using locally sourced audio-visual texts to the local TLU domain, providing additional support for using the listening test for local placement purposes. Additionally, dimensionality assessments demonstrated that test design decisions inevitably entailed with using authentic unscripted texts did not threaten the internal structure of the test. We argue that local resources are indispensable in developing authentic test stimuli and in supporting the validity of local test interpretation and use.

ACTIONS OF MONOIDAL CATEGORIES AND REPRESENTATIONS OF CARTAN TYPE LIE ALGEBRAS

AbstractUsing crossed homomorphisms, we show that the category of weak representations (respectively admissible representations) of Lie–Rinehart algebras (respectively Leibniz pairs) is a left module category over the monoidal category of representations of Lie algebras. In particular, the corresponding bifunctor of monoidal categories is established to give new weak representations (respectively admissible representations) of Lie–Rinehart algebras (respectively Leibniz pairs). This generalises and unifies various existing constructions of representations of many Lie algebras by using this new bifunctor. We construct some crossed homomorphisms in different situations and use our actions of monoidal categories to recover some known constructions of representations of various Lie algebras and to obtain new representations for generalised Witt algebras and their Lie subalgebras. The cohomology theory of crossed homomorphisms between Lie algebras is introduced and used to study linear deformations of crossed homomorphisms.

Designing and delivering representation-focused science lessons in a digital learning environment

Inquiry-based representation-focused approaches in science education have shown promising outcomes when students engage in knowledge building via an active process of constructing, coordinating, and evaluating representations. To date, much of the existing research around these approaches has taken place in pre-digital classrooms, but the increasing importance of digital technologies in contemporary science classrooms that has heightened during the on-going Covid pandemic could have ramifications for such approaches. To explore the potential for productive integration of a digital technology with active learning processes, this study investigated the role an interactive online learning platform played in supporting the construction and refinement of representations by students. This paper draws on research generated in the context of an Australian Grade 9 science class studying a physics unit focused on energy transfer considerations for sustainable housing. The research design featured an exploratory case study approach using multiple methods for data collection including video capture, interviews, and student artefacts. Data analysis involved the application of socio-semiotic perspectives to understand the nature of students’ meaning-making processes through their generation and coordination of both digital and non-digital multimodal representations. This study found that the online platform allowed for extended access and the flexible use of multimodal resources facilitated students’ representation construction activities. However, activities involving teacher-guided discussions and ongoing feedback were limited. The socio-semiotic analysis provided insights into the effective design of online learning sequences to guide conceptual development. This paper concludes by suggesting how specific affordances of interactive online platforms can effectively facilitate the design and delivery of active learning approaches involving representation construction.

Symmetry-based representation for registration of multimodal images.

We propose a new two-dimensional structural representation method for registration of multimodal images by using the local structural symmetry of images, which is similar at different modalities. The symmetry is measured in various orientations and the best is mapped and used for the representation image. The optimum performance is obtained when using only two different orientations, which is called binary dominant symmetry representation (BDSR). This representation is highly robust to noise and intensity non-uniformity. We also propose a new objective function based on L2 distance with low sensitivity to the overlapping region. Then, five different meta-heuristic algorithms are comparatively applied. Two of them have been used for the first time on image registration. BDSR remarkably outperforms the previous successful representations, such as entropy images, self-similarity context, and modality-independent local binary pattern, as well as mutual information-based registration, in terms of success rate, runtime, convergence error, and representation construction.

Boundary quotient C*‐algebras of semigroups

We study two classes of operator algebras associated with a unital subsemigroup P $P$ of a discrete group G $G$ : one related to universal structures and one related to co-universal structures. First we provide connections between universal C*-algebras that arise variously from isometric representations of P $P$ that reflect the space J $\mathcal {J}$ of constructible right ideals, from associated Fell bundles, and from induced partial actions. This includes connections of appropriate quotients with the strong covariance relations in the sense of Sehnem. We then pass to the reduced representation C λ ∗ ( P ) $\mathrm{C}^*_\lambda (P)$ , and we consider the boundary quotient ∂ C λ ∗ ( P ) $\partial \mathrm{C}^*_\lambda (P)$ related to the minimal boundary space. We show that ∂ C λ ∗ ( P ) $\partial \mathrm{C}^*_\lambda (P)$ is co-universal in two different classes: (a) with respect to the equivariant constructible isometric representations of P $P$ ; and (b) with respect to the equivariant C*-covers of the reduced non-selfadjoint semigroup algebra A ( P ) $\mathcal {A}(P)$ . If P $P$ is an Ore semigroup, or if G $G$ acts topologically freely on the minimal boundary space, then ∂ C λ ∗ ( P ) $\partial \mathrm{C}^*_\lambda (P)$ coincides with the usual C*-envelope C env ∗ ( A ( P ) ) $\mathrm{C}^*_{\text{env}}(\mathcal {A}(P))$ in the sense of Arveson. This covers total orders, finite type and right-angled Artin monoids, the Thompson monoid, multiplicative semigroups of non-zero algebraic integers, and the a x + b $ax+b$ -semigroups over integral domains that are not a field. In particular, we show that P $P$ is an Ore semigroup if and only if there exists a canonical ∗ $*$ -isomorphism from ∂ C λ ∗ ( P ) $\partial \mathrm{C}^*_\lambda (P)$ , or from C env ∗ ( A ( P ) ) $\mathrm{C}^*_{\text{env}}(\mathcal {A}(P))$ , onto C λ ∗ ( G ) $\mathrm{C}^*_\lambda (G)$ . If any of the above holds, then A ( P ) $\mathcal {A}(P)$ is shown to be hyperrigid.

Artificial Subjectivity: Personal Semantic Memory Model for Cognitive Agents

Personal semantic memory is a way of inducing subjectivity in intelligent agents. Personal semantic memory has knowledge related to personal beliefs, self-knowledge, preferences, and perspectives in humans. Modeling this cognitive feature in the intelligent agent can help them in perception, learning, reasoning, and judgments. This paper presents a methodology for the development of personal semantic memory in response to external information. The main contribution of the work is to propose and implement the computational version of personal semantic memory. The proposed model has modules for perception, learning, sentiment analysis, knowledge representation, and personal semantic construction. These modules work in synergy for personal semantic knowledge formulation, learning, and storage. Personal semantics are added to the existing body of knowledge qualitatively and quantitatively. We performed multiple experiments where the agent had conversations with the humans. Results show an increase in personal semantic knowledge in the agent’s memory during conversations with an F1 score of 0.86. These personal semantics evolved qualitatively and quantitatively with time during experiments. Results demonstrated that agents with the given personal semantics architecture possessed personal semantics that can help the agent to produce some sort of subjectivity in the future.

Development and Content Validation of a Comprehensive Health Literacy Survey Instrument for Use in Individuals with Asthma during the COVID-19 Pandemic.

Individuals with chronic conditions have been faced with many additional challenges during the COVID-19 pandemic. Individual health literacy (HL) as the ability to access, understand, evaluate, and apply pandemic-related information has thus become ever more important in these populations. The purpose of this study was to develop and content-validate a comprehensive HL survey instrument for people with asthma based on an integrated framework, and on previous surveys and other instruments for use in the general population and vulnerable groups. Beside HL, assumed determinants, mediators, and health outcomes were embraced in the framework. A mixed-method design was used. A comprehensive examination of the available literature yielded an initial pool of 398 single items within 20 categories. Based on content validity indices (CVI) of expert ratings (n = 11) and the content analysis of cognitive interviews with participants (n = 9), the item pool was reduced, and individual items/scales refined or modified. The instrument showed appropriate comprehensibility (98.0%), was judged relevant, and had an acceptable CVI at scale level (S-CVI/Ave = 0.91). The final version comprises 14 categories measured by 38 questions consisting of 116 single items. In terms of content, the instrument appears a valid representation of behavioural and psychosocial constructs pertaining to a broad HL understanding and relevant to individuals with asthma during the COVID-19 pandemic. Regular monitoring of these behavioural and psychosocial constructs during the course of the pandemic can help identify needs as well as changes during the course of the pandemic, which is particularly important in chronic disease populations.