The narrative coherence of witness transcripts in children on the autism spectrum

Background and Aims. Autistic children often recall fewer details about witnessed events than typically developing children (of comparable age and ability), although the information they recall is generally no less accurate. Previous research has not examined the narrative coherence of such accounts, despite higher quality narratives potentially being perceived more favourably by criminal justice professionals and juries. This study compared the narrative coherence of witness transcripts produced by autistic and typically developing (TD) children (ages 6-11 years, IQs 70+). Methods and Procedures. Secondary analysis was carried out on interview transcripts from a subset of 104 participants (autism=52, TD=52) who had taken part in a larger study of eyewitness skills in autistic and TD children. Groups were matched on chronological age, IQ and receptive language ability. Coding frameworks were adopted from existing narrative research, featuring elements of ‘story grammar’. Outcomes and Results. Whilst fewer event details were reported by autistic children, there were no group differences in narrative coherence (number and diversity of ‘story grammar’ elements used), narrative length or semantic diversity. Conclusions and Implications. These findings suggest that the narrative coherence of autistic children’s witness accounts is equivalent to TD peers of comparable age and ability

Terapia génica: desde los extractos y las píldoras a las pociones de ADN

La terapia génica es un tratamiento alternativo a los abordajes farmacológicos, quirúrgicos y de índole convencional que se está desarrollando tanto a nivel experimental como clínico. En esta revisión, más allá de mencionar los avances y presentar un panorama del tema en el área biomédica, se pretende ampliar el concepto de ADN, desde su función como reservorio fundamental de información para la síntesis de proteínas hasta sus acciones “como fármaco”. Se espera que el ADN encapsulado en vectores o directamente aplicado al tejido, cumpla la función que el gen defectuoso no puede realizar mediante su reemplazo, o impida que un gen desregulado permanezca activo, a través de mecanismos de interferencia. Estos objetivos no solo están dirigidos al tratamiento de pacientes de diferentes edades, sino también de individuos aún no natos, como lo evidencian numerosos abordajes experimentales de terapia génica intrauterina. Actualmente existen varios productos comerciales surgidos en el contexto de la terapia génica. Una vez que este tipo de tratamiento sortee aquellos aspectos que todavía constituyen importantes factores de riesgo, se establezcan acuerdos éticos y se equilibren los costos de las intervenciones, constituirá una alternativa a los métodos convencionales para tratar ciertas enfermedades. El ADN (y el ARN) se presentan como los futuros fármacos en acción de las próximas décadas.Abstract Gene therapy is a treatment that offers an alternative to pharmacological, surgical and conventional approaches that is being developed at an experimental and clinical level. In this review, apart from mentioning advances and presenting an overview of the subject in the biomedical field, our intention is to extend the concept of DNA. DNA is the store of information for protein synthesis and today it is also “a drug”. It is expected for the DNA embedded in vectors or directly applied to tissue to perform the function that the defective gene cannot perform by means of its replacement, or to prevent that gene from remaining active through mechanisms of interference. This is not only aimed at the treatment of patients of different ages but also unborn children, as it has been proved by several experimental approaches of intrauterine gene therapy. Currently there are several commercially available products that have emerged from the context of gene therapy. Once those aspects that still represent important risk factors are overcome, ethical agreements are reached and the costs of the interventions are leveled out, this type of treatment will constitute an alternative to conventional methods to treat certain diseases. DNA (and RNA) are proposed as the future drugs for the following decades.Fil: Santalla, Manuela. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Departamento de Ciencias Básicas y Experimentales; ArgentinaFil: Fesser, E.. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Departamento de Ciencias Básicas y Experimentales; ArgentinaFil: Asad, Antonela Sofía. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Departamento de Ciencias Básicas y Experimentales; ArgentinaFil: Acosta, D.. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Departamento de Ciencias Básicas y Experimentales; ArgentinaFil: Harnichar, E.. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnológico la Plata. Centro de Investigaciones Cardiovasculares "Dr. Horacio Eugenio Cingolani"; Argentina. Universidad Nacional de La Plata; ArgentinaFil: Ferrero, Paola Viviana. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Departamento de Ciencias Básicas y Experimentales; Argentina. Universidad Nacional de La Plata; Argentin

The conformation of conducting polymer chains: Hubbard polymers

The conformational and electronic properties of conducting flexible random and self-avoiding walk polymer chains are under investigation. A Hamiltonian for conjugated flexible polymers is introduced and its physical consequences are presented. One important result is that the electronic degrees of freedom greatly affect the conformational statistics of the walks and vice versa. The electronic degrees of freedom extend the size of the chain. The end-to-end distance behaves as $R\propto L^{\nu}$ with $\nu=(d+1)/(d+2)$, where $d$ is the spatial dimension.Comment: 11 pages of Latex + uuencoded postscript figur

Kinetic and Transport Equations for Localized Excitations in Sine-Gordon Model

We analyze the kinetic behavior of localized excitations - solitons, breathers and phonons - in Sine-Gordon model. Collision integrals for all type of localized excitation collision processes are constructed, and the kinetic equations are derived. We analyze the kinetic behavior of localized excitations - solitons, breathers and phonons - in Sine-Gordon model. Collision integrals for all type of localized excitation collision processes are constructed, and the kinetic equations are derived. We prove that the entropy production in the system of localized excitations takes place only in the case of inhomogeneous distribution of these excitations in real and phase spaces. We derive transport equations for soliton and breather densities, temperatures and mean velocities i.e. show that collisions of localized excitations lead to creation of diffusion, thermoconductivity and intrinsic friction processes. The diffusion coefficients for solitons and breathers, describing the diffusion processes in real and phase spaces, are calculated. It is shown that diffusion processes in real space are much faster than the diffusion processes in phase space.Comment: 23 pages, latex, no figure

Normative Influence on Athletes' Intentions to Intervene in Sport

Previous research in the activity area has found that descriptive norms can influence individual activity (Crozier, 2014; Priebe & Spink, 2014; 2015). While important, studies examining other important outcomes in the activity area have not been conducted. For example, no research has examined whether normative information can be used to influence athletes' intentions to intervene with other teammates. In an effort to address this gap in the literature, the purpose of the current experiment was to examine whether descriptive norms, that were either supported by a coach or not, would influence a player’s intentions to intervene when teammates made technical errors or did not exert enough effort. Canadian adult soccer players (N = 106) were recruited to participate in this online experimental study. Participants were assigned to one of three conditions: normative (teammates intervene)/coach support, normative (teammates intervene)/coach not support, or attention control. Participants in both of the normative conditions read two short vignettes describing how the players and coach on a hypothetical soccer team responded to a teammate’s technical mistakes and lack of effort, respectively. While imagining themselves as a member of this hypothetical team, participants then rated their intentions to intervene with other members of this team. Results from ANCOVAs (controlling for previous intervening behaviour) revealed different results for intentions to intervene following technical mistakes versus lack of effort. Results for technical mistakes revealed a significant main effect for condition F(2, 102) = 4.98, p 0.05, adj Cohen’s d = 0.13). There was no significant main effect for condition with respect to teammates exhibiting a lack of effort F(2, 95) = 1.82, p > 0.1). Results from this experiment provide initial evidence that descriptive norms supported by a coach may influence players' intentions to intervene when a teammate makes a mistake

Meta-scientific reflection of undergraduate students: is mathematics a natural science?

Reflecting on the nature of mathematics is an important activity for undergraduate students. To analyse students’ reflection, we address the questions how students categorize mathematics in the system of scientific disciplines and what arguments they use to support their decision, in particular. In an online-survey, we implemented two open-ended items to gather information about the meta-scientific reflection of 296 undergraduate students enrolled in a mathematics-related study program. By analysing students’ answers, we identified nine subthemes that can be grouped in three themes: (1) the content, (2) the method, and (3) the purpose of mathematics. Most of the students concentrated on only one of the three themes. Based on these results, we discuss in which way prompts can support students’ meta-scientific reflection

Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature

While Graph Neural Networks (GNNs) have been successfully leveraged for learning on graph-structured data across domains, several potential pitfalls have been described recently. Those include the inability to accurately leverage information encoded in long-range connections (over-squashing), as well as difficulties distinguishing the learned representations of nearby nodes with growing network depth (over-smoothing). An effective way to characterize both effects is discrete curvature: Long-range connections that underlie over-squashing effects have low curvature, whereas edges that contribute to over-smoothing have high curvature. This observation has given rise to rewiring techniques, which add or remove edges to mitigate over-smoothing and over-squashing. Several rewiring approaches utilizing graph characteristics, such as curvature or the spectrum of the graph Laplacian, have been proposed. However, existing methods, especially those based on curvature, often require expensive subroutines and careful hyperparameter tuning, which limits their applicability to large-scale graphs. Here we propose a rewiring technique based on Augmented Forman-Ricci curvature (AFRC), a scalable curvature notation, which can be computed in linear time. We prove that AFRC effectively characterizes over-smoothing and over-squashing effects in message-passing GNNs. We complement our theoretical results with experiments, which demonstrate that the proposed approach achieves state-of-the-art performance while significantly reducing the computational cost in comparison with other methods. Utilizing fundamental properties of discrete curvature, we propose effective heuristics for hyperparameters in curvature-based rewiring, which avoids expensive hyperparameter searches, further improving the scalability of the proposed approach

Effective Structural Encodings via Local Curvature Profiles

Structural and Positional Encodings can significantly improve the performance of Graph Neural Networks in downstream tasks. Recent literature has begun to systematically investigate differences in the structural properties that these approaches encode, as well as performance trade-offs between them. However, the question of which structural properties yield the most effective encoding remains open. In this paper, we investigate this question from a geometric perspective. We propose a novel structural encoding based on discrete Ricci curvature (Local Curvature Profiles, short LCP) and show that it significantly outperforms existing encoding approaches. We further show that combining local structural encodings, such as LCP, with global positional encodings improves downstream performance, suggesting that they capture complementary geometric information. Finally, we compare different encoding types with (curvature-based) rewiring techniques. Rewiring has recently received a surge of interest due to its ability to improve the performance of Graph Neural Networks by mitigating over-smoothing and over-squashing effects. Our results suggest that utilizing curvature information for structural encodings delivers significantly larger performance increases than rewiring