Socio-Cultural Representations and Therapeutic Itineraries of Parents of Autistic Children Followed in the INSP’s Children’s Mental Health Services

Pervasive developmental disorders (PDD) remain little known to populations in developing countries. In black Africa their social representations remain strongly influenced by local belief systems. The general objective of this study was to understand the perceptions and representations of Ivorian parents vis-à-vis PDD. This was a mixed (qualitative and quantitative) prospective cross-sectional study with a descriptive aim that involved a sample of 49 parents. The sampling was of the qualitative type by multiple cases with reasoned choice by saturation. Our results showed that male parents were mostly aged between 40 - 49 years (48.98%) with a higher level of education (67.34%) while mothers were mostly aged between 30 - 39 (61.22%) and a higher level (30.61%). Autistic children were negatively perceived by their parents: either as a source of psychological suffering (82.85%), or as mysterious children who sacrificed their parents (44.66%), or as “bobo” children (mute children in common Ivorian language) (16.66%) or like rude children (13.34%). The supposed origin of the disorder according to the parents was mystical-religious (60.94%);natural (25%);hereditary (6.25%). In 6.25% of cases, PDD were assumed to be of unknown or iatrogenic origin attributable to vaccination (1.56%). 75.51% of parents said that in addition to conventional medical therapies, they also used traditional therapies. The use of this therapeutic alternative would be linked to the perceptions and beliefs that feed the socio-cultural representations of our respondents.

Examination of the Illness Representations among Children with T1DM in Relation to Mental Health Factors

The most common comorbid psychiatric disorders in children with type 1 diabetes mellitus(T1DM)are depression,anxiety and behavioral disorders.Patients with comorbid psychopathology are less capable of psychically adjusting to the new life situation resulting from T1DM,which may negatively affect glycemic control and adherence related to the treatment.We aimed to investigate the association between mental health and type 1 diabetes including illness representation.115 children and adolescents with T1DM were recruited through the outpatient clinic in Debrecen,Hungary.Measures:PRISM-D,Child Depression Inventory(CDI),Cantril Ladder and Self-Rated Health,Glycosylaeted haemoglobin(HbA1C)were measured.Children having depressive symptoms drew fewer circles with less area.Children not drawing any important relationships possessed more depressive symptoms.Those diagnosed at a younger age displayed smaller distance between the Self-and Illness-circles.The PRISM-D test can be a promising tool to analyse emotional and cognitive representations and the psychological burden of T1DM.

Dynamical t/U Expansion of the Doped Hubbard Model

We construct a new U(1)slave-spin representation for the single-band Hubbard model in the large-U limit.The mean-field theory in this representation is more amenable to describe both the spin-charge-separation physics of the Mott insulator at half-filling and the strange metal behavior at finite doping.

IndRT-GCNets: Knowledge Reasoning with Independent Recurrent Temporal Graph Convolutional Representations

Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.

The breaking of spin symmetry in the single-particle resonances in deformed nuclei

The exploration of spin symmetry (SS) in nuclear physics has been instrumental in identifying atomic nucleus structures.In this study,we solve the Dirac equation from the relativistic mean field (RMF) in complex momentum representation.We investigated SS and its breaking in single-particle resonant states within deformed nuclei,with a focus on the illustrative nucleus168Er.This was the initial discovery of a resonant spin doublet in a deformed nucleus,with the expectation of the SS approaching the continuum threshold.With increasing single-particle energy,the splitting of the resonant spin doublets widened significantly.This escalating splitting implies diminishing adherence to the SS,indicating a departure from the expected behavior as the energy levels increase.We also analyzed the width of the resonant states,showing that lower orbital angular momentum resonances possess shorter decay times and that SS is preserved within broad resonant doublets,as opposed to narrow resonant doublets.Comparing the radial density of the upper components for the bound-state and resonant-state doublets,it becomes evident that while SS is well-preserved in the bound states,it deteriorates in the resonant states.The impact of nuclear deformation (β_(2)) on SS was examined,demonstrating that an increase in β_(2) resulted in higher energy and width splitting in the resonant spin doublets,which is attributed to increased component mixing.Furthermore,the sensitivity of spin doublets to various potential parameters such as surface diffuseness (a),radius (R),and depth (Σ0) is discussed,emphasizing the role of these parameters in SS.This study provides valuable insights into the behavior of spin doublets in deformed nuclei and their interplay with the nuclear structure,thereby advancing our understanding of SS in the resonance state.

Enhancing Deep Learning Semantics:The Diffusion Sampling and Label-Driven Co-Attention Approach

The advent of self-attention mechanisms within Transformer models has significantly propelled the advancement of deep learning algorithms,yielding outstanding achievements across diverse domains.Nonetheless,self-attention mechanisms falter when applied to datasets with intricate semantic content and extensive dependency structures.In response,this paper introduces a Diffusion Sampling and Label-Driven Co-attention Neural Network(DSLD),which adopts a diffusion sampling method to capture more comprehensive semantic information of the data.Additionally,themodel leverages the joint correlation information of labels and data to introduce the computation of text representation,correcting semantic representationbiases in thedata,andincreasing the accuracyof semantic representation.Ultimately,the model computes the corresponding classification results by synthesizing these rich data semantic representations.Experiments on seven benchmark datasets show that our proposed model achieves competitive results compared to state-of-the-art methods.

Entropy variances of pure coherent states in the diffusion channel

Using the operator correspondence of the real and fictious modes in the thermo entangled state representation, wesolve the quantum master equation describing the diffusion channel and obtain the Kraus operator-sum representation ofits analytical solution. we find that the pure coherent states evolve into the new mixed thermal superposed states in thediffusion channel. Also, we investigate the statistical properties of the initial coherent states and their entropy evolutions inthe diffusion channel, and find that the entropy evolutions are only related to the decay time and without the amplitudes ofthe initial coherent states.

Systematic Method for Constructing Lewis Representations

The systematic method for constructing Lewis representations is a method for representing chemical bonds between atoms in a molecule. It uses symbols to represent the valence electrons of the atoms involved in the bond. Using a number of rules in a defined order, it is often better suited to complicated cases than the Lewis representation of atoms. This method allows us to determine the formal charge and oxidation number of each atom in the edifice more efficiently than other methods.

A Simple Embedding Method for the Laplace-Beltrami Eigenvalue Problem onImplicit Surfaces

We propose a simple embedding method for computing the eigenvalues and eigenfunctions of the Laplace-Beltrami operator on implicit surfaces.The approach follows an embedding approach for solving the surface eikonal equation.We replace the differential operator on the interface with a typical Cartesian differential operator in the surface neighborhood.Our proposed algorithm is easy to implement and efficient.We will give some two-and three-dimensional numerical examples to demonstrate the effectiveness of our proposed approach.

THE SPARSE REPRESENTATION RELATED WITH FRACTIONAL HEAT EQUATIONS

This study introduces a pre-orthogonal adaptive Fourier decomposition(POAFD)to obtain approximations and numerical solutions to the fractional Laplacian initial value problem and the extension problem of Caffarelli and Silvestre(generalized Poisson equation).As a first step,the method expands the initial data function into a sparse series of the fundamental solutions with fast convergence,and,as a second step,makes use of the semigroup or the reproducing kernel property of each of the expanding entries.Experiments show the effectiveness and efficiency of the proposed series solutions.

Examining Zhang Peiji’s Translation of Beiying:A Study on the Representation of Zhu Ziqing’s Linguistic Style

Based on Yan Fu’s translation norms of“faithfulness,expressiveness,and elegance”and Liu Miqing’s concept of aesthetic representation in translation,the present study employed a combined method of qualitative and quantitative analysis to investigate the linguistic styles employed by Zhu Ziqing in his renowned prose Beiying.Then,using relevant corpora and self-designed Python software,we investigated whether Zhang Peiji,as a translator,has successfully reproduced the simplistic,emotional,and realistic linguistic characteristics in Zhu Ziqing’s prose from the perspectives of“faithfulness,expressiveness,and elegance.”The findings of the research indicate that by employing a dynamic imitative translation approach,Zhang Peiji has successfully enhanced the linguistic aesthetic qualities of the source text,striving to reflect the distinctive linguistic style of Zhu Ziqing.

Wigner function of optical cumulant operator and its dissipation in thermo-entangled state representation

To conveniently calculate the Wigner function of the optical cumulant operator and its dissipation evolution in a thermal environment, in this paper, the thermo-entangled state representation is introduced to derive the general evolution formula of the Wigner function, and its relation to Weyl correspondence is also discussed. The method of integration within the ordered product of operators is essential to our discussion.

Mesh representation matters:investigating the influence of different mesh features on perceptual and spatial fidelity of deep 3D morphable models

Background Deep 3D morphable models(deep 3DMMs)play an essential role in computer vision.They are used in facial synthesis,compression,reconstruction and animation,avatar creation,virtual try-on,facial recognition systems and medical imaging.These applications require high spatial and perceptual quality of synthesised meshes.Despite their significance,these models have not been compared with different mesh representations and evaluated jointly with point-wise distance and perceptual metrics.Methods We compare the influence of different mesh representation features to various deep 3DMMs on spatial and perceptual fidelity of the reconstructed meshes.This paper proves the hypothesis that building deep 3DMMs from meshes represented with global representations leads to lower spatial reconstruction error measured with L_(1) and L_(2) norm metrics and underperforms on perceptual metrics.In contrast,using differential mesh representations which describe differential surface properties yields lower perceptual FMPD and DAME and higher spatial fidelity error.The influence of mesh feature normalisation and standardisation is also compared and analysed from perceptual and spatial fidelity perspectives.Results The results presented in this paper provide guidance in selecting mesh representations to build deep 3DMMs accordingly to spatial and perceptual quality objectives and propose combinations of mesh representations and deep 3DMMs which improve either perceptual or spatial fidelity of existing methods.

Closing the Gap: Boosting Women’s Representation in Cybersecurity Leadership

The research consistently highlights the gender disparity in cybersecurity leadership roles, necessitating targeted interventions. Biased recruitment practices, limited STEM education opportunities for girls, and workplace culture contribute to this gap. Proposed solutions include addressing biased recruitment through gender-neutral language and blind processes, promoting STEM education for girls to increase qualified female candidates, and fostering inclusive workplace cultures with mentorship and sponsorship programs. Gender parity is crucial for the industry’s success, as embracing diversity enables the cybersecurity sector to leverage various perspectives, drive innovation, and effectively combat cyber threats. Achieving this balance is not just about fairness but also a strategic imperative. By embracing concerted efforts towards gender parity, we can create a more resilient and impactful cybersecurity landscape, benefiting industry and society.

The False Obvious:Gender Myth in Perfume Commercials

Perfume commercial,as a form of cultural text and practice,is relatively special in contemporary commercial advertising:The commodity qualities of perfume dictate that perfume advertisements must cater to the sexual fantasies of the audience,and therefore inevitably characterize the mainstream,dominant gender norms.At the same time,perfume commercial,as a unique marketing communication method,also unconsciously influences people’s values through sensory stimulation and emotional rendering.This article explores the connection between perfume and its commercials,sex,and gender,and discusses the generation of meaning in perfume commercials as texts and deconstructs the gender myth implied from the perspectives of representation and myth analysis,ultimately revealing that behind the gender myth of perfume commercials is but a false manifestation of the ideal self-image of the western white bourgeois heterosexuality.

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

Representation Theory of Three-Dimensional Elliptical Crack Under Dynamic Loading

The relation between the normal displacement on the surface of a dynamical elliptical crack and the normal stress over the crack surface was studied. The three dimensional elastodynamic equations and Fourier Laplace transforms are used. Based on the influence function and the inversion of integral transforms, one can find that if the distribution of normal displacement on the surface of a dynamic elliptical crack is a polynomial of degree n in x 1 and x 2 , then the normal pressure acting over the ellipse is also a polynomial P n(x 1,x 2) of the same degree in x 1 and x 2 .

bell hooks: To Resist Misrepresentations of the Outlaw Culture

The thesis summarizes bell hooks' stand and viewpoints as expressed in her book Outlaw Culture:Resisting Representations.In this collection,hooks argues that the outlaw culture,a culture of the marginalized groups including black people and women,is either distorted or misinterpreted by the mainstream culture which is a white supremacist patriarchal one.Therefore,she calls for a resistance against the mainstream culture's misrepresentations of the outlaw culture.

POLYNOMIAL REPRESENTATIONS OF THE AFFINE NAPPI-WITTEN LIE ALGEBRA H_4

In this paper, the representation theory for the arlene Lie algebra H4 associated to the Nappi-Witten Lie algebra H4 is studied. Polynomial representations of the affine Nappi-Witten Lie algebra H4 are given.

Representations in Genetic Algorithm for the Job Shop Scheduling Problem: A Computational Study

Due to the NP-hardness of the job shop scheduling problem (JSP), many heuristic approaches have been proposed;among them is the genetic algorithm (GA). In the literature, there are eight different GA representations for the JSP;each one aims to provide subtle environment through which the GA’s reproduction and mutation operators would succeed in finding near optimal solutions in small computational time. This paper provides a computational study to compare the performance of the GA under six different representations.