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Ciro Esposito, Agnese Roberti, Francesco Turrà, Maria Escolino, Mariapina Cerulo, Alessandro Settimi, Alessandra Farina, Pietro Vecchio, Antonio Di Mezza Department of Translational Medical Sciences, Pediatric Surgery, “Federico II” University of Naples, Naples, Italy Abstract: Gastroesophageal reflux (GER), defined as the passage of gastric contents into the esophagus, is a physiologic process that occurs throughout the day in healthy infants and children. Gastroesophageal reflux disease (GERD) occurs when gastric contents flow back into the esophagus and produce symptoms. The most common esophageal symptoms are vomiting and regurgitation. Lifestyle changes are the first-line therapy in both GER and GERD; medications are explicitly indicated only for patients with GERD. Surgical therapies are reserved for children with intractable symptoms or who are at risk for life-threatening complications of GERD. The laparoscopic Nissen antireflux procedure is the gold standard for the treatment of this pathology. A literature search on PubMed and Cochrane Database was conducted with regard to the management of GERD in children to provide a view of state-of-the-art treatment of GERD in pediatrics. Keywords: gastroesophageal reflux, children, medical therapy of GERD, surgical treatment of GERD, laparoscopic Nissen procedure

Summary: Background: Research in healthy young adults shows that characteristic patterns of brain activity define individual “brain-fingerprints” that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson’s disease (PD). Methods: We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. Findings: The arrhythmic spectral components of cortical activity in patients with Parkinson’s disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson’s brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson’s symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson’s brain-fingerprint aligns with that of neurotransmitter systems affected by the disease’s pathophysiology. Interpretation: The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson’s disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson’s disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. Funding: Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).

Abstract Research on irregular stone masonry walls is hampered by the lack of detailed geometrical models of their internal micro-structure, i.e. the shape and size of each stone and its position within the wall. Without such a geometric digital twin of walls tested in the laboratory, it is difficult to evaluate the accuracy of existing numerical simulation techniques. Here, we describe the generation of geometrical digital twins of three irregular stone masonry walls built in the laboratory. We labelled each stone manually and then obtained the geometry of the individual stones using a portable laser scanning device. With the same device we scanned the wall after the construction of each layer. We then registered the position of each stone in the layer. This paper outlines the methodology for the data acquisition and digital reconstruction and presents the datasets for the walls. The developed geometrical digital twins provide unique information regarding the micro-structure of constructed walls that is key for the development and validation of numerical simulation techniques for stone masonry.

The free wave propagation of periodic flexural waves on an infinite elastic Euler-Bernoulli nonlocal beam embedded in bilinear Winkler-type foundation is investigated. A general formulation of the elastic potential energy leads to a nonlinear nonlocal model with spatial derivatives up to the sixth order. The effect of the nonlocal parameters and of the different soil stiffnesses on the dynamical characteristics of the system is critically discussed. An enrichment of the system response with respect to the local beam is unveiled, and the crucial role played by the sixth-order nonlocal term is highlighted

We present TimberTool (TTool v2.1.1), a software designed for woodworking tasks assisted by augmented reality (AR), emphasizing its essential function of the real-time localization of a tool head’s poses within camera frames. The localization process, a fundamental aspect of AR-assisted tool operations, enables informed integration with contextual tracking, facilitating the computation of meaningful feedback for guiding users during tasks on the target object. In the context of timber construction, where object pose tracking has been predominantly explored in additive processes, TTool addresses a noticeable gap by focusing on subtractive tasks with manual tools. The proposed methodology utilizes a machine learning (ML) classifier to detect tool heads, offering users the capability to input a global pose and utilizing an automatic pose refiner for final pose detection and model alignment. Notably, TTool boasts adaptability through a customizable platform tailored to specific tool sets, and its open accessibility encourages widespread utilization. To assess the effectiveness of TTool in AR-assisted woodworking, we conducted a preliminary experimental campaign using a set of tools commonly employed in timber carpentry. The findings suggest that TTool can effectively contribute to AR-assisted woodworking tasks by detecting the six-degrees-of-freedom (6DoF) pose of tool heads to a satisfactory level, with a millimetric positional error of 3.9 ± 1 mm with possible large room for improvement and 1.19 ± 0.6° for what concerns the angular accuracy.

Different studies have tried to establish a relationship between dyslexia and the vestibular system function. Subjective Visual Vertical/Horizontal (SVV and SVH) and Video Head Impulse Test (VHIT) are useful for studying the vestibular system and can be easily performed in children. Our aim was to evaluate the vestibular function in dyslexic children by SVV/SVH and VHIT. We enrolled 18 dyslexic children (10M/8F; mean age 10.7 ± 2.3 years; range 7–14 years) and 18 age‐matched children with typical development of learning abilities. All children performed VHIT, SVV and SVH. We found normal gain and symmetry of vestibulo‐ocular‐reflex both in dyslexic and typically developing children. Fifteen out of 18 dyslexic children (83.3%) showed a difference of at least one amongst SVV or SVH. The mean value of SVV was 2.3° and the mean value of SVH was 2.6°. Statistical analysis showed a significant difference between typically developing and dyslexic children for both SVV and SVH. We confirm a relationship between dyslexia and the alteration of SVV and SVH. Our results could be related to the pathogenetic hypothesis of a visual processing impairment related to a dysfunction of the magnocellular pathway or to a general deficit related to a multimodal cortical network. [ABSTRACT FROM AUTHOR]

Ensuring safe and continuous autonomous navigation in long-term mobile robot applications is still challenging. To ensure a reliable representation of the current environment without the need for periodic remapping, updating the map is recommended. However, in the case of incorrect robot pose estimation, updating the map can lead to errors that prevent the robot’s localisation and jeopardise map accuracy. In this paper, we propose a safe Lidar-based occupancy grid map-updating algorithm for dynamic environments, taking into account uncertainties in the estimation of the robot’s pose. The proposed approach allows for robust long-term operations, as it can recover the robot’s pose, even when it gets lost, to continue the map update process, providing a coherent map. Moreover, the approach is also robust to temporary changes in the map due to the presence of dynamic obstacles such as humans and other robots. Results highlighting map quality, localisation performance, and pose recovery, both in simulation and experiments, are reported.

Super-duplex stainless steel (SDSS) shows high mechanical and corrosion resistance because of the balanced structure of austenite and ferrite. However, maintaining this phase ratio after welding is a challenge. The use of austenite stabilizing components is recommended to balance the microstructure. The addition of alloying elements presents a challenge because of the characteristics of Nd:YAG pulsed laser welding. An approach, which has proven to be effective, is to use metal electroplating to prepare the surfaces of the mechanical SDSS components that will be welded, therefore promoting the phase balance in the fusion zone. While the effects of metals such as nickel as an austenite stabilizer are well recognized, cobalt’s effects require more research. The present work investigated the influence of the use of cobalt addition in the joining process by preliminary electroplating on UNS S32750 SDSS Nd: YAG pulsed laser welding, specifically regarding microstructure and microhardness. Three conditions were investigated, changing the thickness of the deposited cobalt layer. The addition of cobalt modified the morphology and increased the volume fraction of austenite. An austenite volume fraction of around 48% was obtained using a 35 μm thick cobalt coating. The microhardness was affected by austenite/ferrite proportions. The microhardness dropped from about 375 HV to 345 HV as the cobalt layer’s thickness rose, being similar to that of the base metal. The effect of cobalt as an austenite stabilizer was observed, and the cobalt electroplating technique was effective to correct the phase balance on UNS S32750 laser welding.