Prevalence, Characteristics, Association Factors of and Management Strategies for Low Back Pain Among Italian Amateur Cyclists: an Observational Cross-Sectional Study

Background Low back pain (LBP) is a burdensome problem affecting amateur cyclists. This cross-sectional study analysed Italian amateur cycling cohort's demographic and sport-specific characteristics, the prevalence and characteristics of LBP among this population, its possible association factors, the management strategies adopted to deal with LBP and the sample's beliefs among possible LBP triggers. A web-based cross-sectional survey was created. The questionnaire included 56 questions divided into six sections, querying the sample's demographic, clinical, and cycling characteristics. Binomial logistic regression with a Wald backward method was performed to ascertain the effects of some covariates ("Sex", "Age", "Body Mass Index", "Sleep hours", "Work type", "Cycling year", "Number of training sessions per week", "Stretching sessions", "Being supervised by a coach or following a scheduled training", "Other sports practised regularly", "Number of cycling competitions per year", "Past biomechanic visits", "Specific pedal training", "LBP before cycling") on the likelihood of developing LBP in the last 12 months. Results A total of 1274 amateur cyclists answered the survey. The prevalence of LBP appeared to be 55.1%, 26.5% and 10.8% in life, in the last 12 months and the last 4 weeks, respectively. The final model of the logistic regression included the covariates "Sex", "Work type", "Cycling year", "Being supervised by a coach or following a scheduled training", "Other sports practised regularly", "Specific pedal training", "LBP before cycling", among which "Cycling year" (variable "Between 2 and 5 years" vs. "Less than 2 years", OR 0.48, 95% CI [0.26-0.89]), "Being supervised by a coach or following a scheduled training" (OR 0.53, 95% CI [0.37-0.74]), "Specific pedal training" (OR 0.69, 95% CI [0.51-0.94]), and "LBP before cycling" (OR 4.2, 95% CI [3.21-5.40]) were found to be significant. Conclusions The prevalence of LBP among Italian amateur cyclists seems to be less frequent compared to the general population. Moreover, undergoing previous specific pedal training and being supervised by a coach or following scheduled training drew a negative association with LBP development. This evidence highlights the importance of being overseen by specific sport figures that could offer a tailored evidence-based training to reach good physical level and to practise sports safely

Stability of Graph Convolutional Neural Networks through the lens of small perturbation analysis

In this work, we study the problem of stability of Graph Convolutional Neural Networks (GCNs) under random small perturbations in the underlying graph topology, i.e. under a limited number of insertions or deletions of edges. We derive a novel bound on the expected difference between the outputs of unperturbed and perturbed GCNs. The proposed bound explicitly depends on the magnitude of the perturbation of the eigenpairs of the Laplacian matrix, and the perturbation explicitly depends on which edges are inserted or deleted. Then, we provide a quantitative characterization of the effect of perturbing specific edges on the stability of the network. We leverage tools from small perturbation analysis to express the bounds in closed, albeit approximate, form, in order to enhance interpretability of the results, without the need to compute any perturbed shift operator. Finally, we numerically evaluate the effectiveness of the proposed bound.Comment: Accepted for publication in Proc. of 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024

Cell Attention Networks

Since their introduction, graph attention networks achieved outstanding results in graph representation learning tasks. However, these networks consider only pairwise relationships among nodes and then they are not able to fully exploit higher-order interactions present in many real world data-sets. In this paper, we introduce Cell Attention Networks (CANs), a neural architecture operating on data defined over the vertices of a graph, representing the graph as the 1-skeleton of a cell complex introduced to capture higher order interactions. In particular, we exploit the lower and upper neighborhoods, as encoded in the cell complex, to design two independent masked self-attention mechanisms, thus generalizing the conventional graph attention strategy. The approach used in CANs is hierarchical and it incorporates the following steps: i) a lifting algorithm that learns {\it edge features} from {\it node features}; ii) a cell attention mechanism to find the optimal combination of edge features over both lower and upper neighbors; iii) a hierarchical {\it edge pooling} mechanism to extract a compact meaningful set of features. The experimental results show that CAN is a low complexity strategy that compares favorably with state of the art results on graph-based learning tasks.Comment: Preprint, under revie

Generalized Simplicial Attention Neural Networks

The aim of this work is to introduce Generalized Simplicial Attention Neural Networks (GSANs), i.e., novel neural architectures designed to process data defined on simplicial complexes using masked self-attentional layers. Hinging on topological signal processing principles, we devise a series of self-attention schemes capable of processing data components defined at different simplicial orders, such as nodes, edges, triangles, and beyond. These schemes learn how to weight the neighborhoods of the given topological domain in a task-oriented fashion, leveraging the interplay among simplices of different orders through the Dirac operator and its Dirac decomposition. We also theoretically establish that GSANs are permutation equivariant and simplicial-aware. Finally, we illustrate how our approach compares favorably with other methods when applied to several (inductive and transductive) tasks such as trajectory prediction, missing data imputation, graph classification, and simplex prediction.Comment: arXiv admin note: text overlap with arXiv:2203.0748

Robustness and static-positional accuracy of the SteamVR 1.0 virtual reality tracking system

The use of low-cost immersive virtual reality systems is rapidly expanding. Several studies started to analyse the accuracy of virtual reality tracking systems, but they did not consider in depth the effects of external interferences in the working area. In line with that, this study aimed at exploring the static-positional accuracy and the robustness to occlusions inside the capture volume of the SteamVR (1.0) tracking system. To do so, we ran 3 different tests in which we acquired the position of HTC Vive PRO Trackers (2018 version) on specific points of a grid drawn on the floor, in regular tracking conditions and with partial and total occlusions. The tracking system showed a high inter- and intra-rater reliability and detected a tilted surface with respect to the floor plane. Every acquisition was characterised by an initial random offset. We estimated an average accuracy of 0.5 +/- 0.2 cm across the entire grid (XY-plane), noticing that the central points were more accurate (0.4 +/- 0.1 cm) than the outer ones (0.6 +/- 0.1 cm). For the Z-axis, the measurements showed greater variability and the accuracy was equal to 1.7 +/- 1.2 cm. Occlusion response was tested using nonparametric Bland-Altman statistics, which highlighted the robustness of the tracking system. In conclusion, our results promote the SteamVR system for static measures in the clinical field. The computed error can be considered clinically irrelevant for exercises aimed at the rehabilitation of functional movements, whose several motor outcomes are generally measured on the scale of metres

MOSAICS AND MYSTERIES: WEAVING LIFE

Entrevista realizada com Janete Santos, docente e pesquisadora da Universidade Federal do Tocantins, membro da ACALANTO (Academia de Letras de Araguaína e Norte do Tocantins). Na entrevista, realizada no mês de setembro de 2020, Janete fala principalmente de sua produção literária.Interview conducted with Janete Santos, professor and researcher at the Federal University of Tocantins, member of ACALANTO (Academy of Letters of Araguaína and Norte do Tocantins). In the interview, held in September 2020, Janete talks mainly about her literary production

Selección por capacidad germinativa de especies nativas para uso en praderas ornamentales sustentables

PosterEl paisajismo sustentable propone sistemas que reduzcan el consumo energético, minimizando la huella de carbono y constituye una de las oportunidades de diseño ecológicamente más beneficiosas para los espacios verdes urbanos. Estos sistemas favorecen el uso de plantas nativas ya que requieren una menor inversión en establecimiento y mantenimiento por reducir las labores culturales. Además, aumentan la oferta de alimento y proveen refugio para insectos y pequeños animales, beneficiando la biodiversidadInstituto de FloriculturaFil: Testa, Rodrigo. ACUMAR; ArgentinaFil: Facciuto, Gabriela Rosa. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Floricultura; ArgentinaFil: Bugallo, Verónica Lucia. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Floricultura; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Catedra de Genética; Argentin