Corrigendum: How path integration abilities of blind people change in different exploration conditions.

[This corrects the article DOI: 10.3389/fnins.2024.

Unsupervised Active Visual Search With Monte Carlo Planning Under Uncertain Detections.

We propose a solution for Active Visual Search of objects in an environment, whose 2D floor map is the only known information. Our solution has three key features that make it more plausible and robust to detector failures compared to state-of-the-art methods: i) it is unsupervised as it does not need any training sessions. ii) During the exploration, a probability distribution on the 2D floor map is updated according to an intuitive mechanism, while an improved belief update increases the effectiveness of the agent's exploration.

Corrigendum to "Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities" [Comput Struct Biotechnol J vol. 23 (2024) 2141-2151].

[This corrects the article DOI: 10.1016/j.csbj.

Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities.

Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds.

How path integration abilities of blind people change in different exploration conditions.

For animals to locate resources and stay safe, navigation is an essential cognitive skill. Blind people use different navigational strategies to encode the environment. Path integration significantly influences spatial navigation, which is the ongoing update of position and orientation during self-motion.

No Adversaries to Zero-Shot Learning: Distilling an Ensemble of Gaussian Feature Generators.

In zero-shot learning (ZSL), the task of recognizing unseen categories when no data for training is available, state-of-the-art methods generate visual features from semantic auxiliary information (e.g., attributes).

Leveraging Commonsense for Object Localisation in Partial Scenes.

We propose an end-to-end solution to address the problem of object localisation in partial scenes, where we aim to estimate the position of an object in an unknown area given only a partial 3D scan of the scene. We propose a novel scene representation to facilitate the geometric reasoning, Directed Spatial Commonsense Graph (D-SCG), a spatial scene graph that is enriched with additional concept nodes from a commonsense knowledge base. Specifically, the nodes of D-SCG represent the scene objects and the edges are their relative positions.

Computational modeling of human multisensory spatial representation by a neural architecture.

Our brain constantly combines sensory information in unitary percept to build coherent representations of the environment. Even though this process could appear smooth, integrating sensory inputs from various sensory modalities must overcome several computational issues, such as recoding and statistical inferences problems. Following these assumptions, we developed a neural architecture replicating humans' ability to use audiovisual spatial representations.

Unsupervised Synthetic Acoustic Image Generation for Audio-Visual Scene Understanding.

Acoustic images are an emergent data modality for multimodal scene understanding. Such images have the peculiarity of distinguishing the spectral signature of the sound coming from different directions in space, thus providing a richer information as compared to that derived from single or binaural microphones. However, acoustic images are typically generated by cumbersome and costly microphone arrays which are not as widespread as ordinary microphones.

SANReSP: A new Italian questionnaire to screen patients for obstructive sleep apnea.

Purpose: Obstructive sleep apnea (OSA) is a common, prevalent, and underdiagnosed disorder. Its lack of diagnosis and treatment is associated with increased morbidity and mortality. Previous screening questionnaires investigated parameters including body mass index, age, neck circumference, and sex, in addition to symptoms.

An online yarn spinning dataset.

This data article presents an online yarn spinning dataset for evaluation and benchmarking of a variety of image processing algorithms and computer vision models for imaging based testing of textile yarn quality. The dataset comprises of continuous yarn spinning videos of 59.05 tex, 29.

Nanocatalyst-Enabled Physically Unclonable Functions as Smart Anticounterfeiting Tags with AI-Aided Smartphone Authentication.

Counterfeiting is a worldwide issue affecting many industrial sectors, ranging from specialized technologies to retail market, such as fashion brands, pharmaceutical products, and consumer electronics. Counterfeiting is not only a huge economic burden (>$ 1 trillion losses/year), but it also represents a serious risk to human health, for example, due to the exponential increase of fake drugs and food products invading the market. Considering such a global problem, numerous anticounterfeit technologies have been recently proposed, mostly based on tags.

AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study.

Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem.

Addressing signal alterations induced in CT images by deep learning processing: A preliminary phantom study.

Purpose: We investigate, by an extensive quality evaluation approach, performances and potential side effects introduced in Computed Tomography (CT) images by Deep Learning (DL) processing.

Method: We selected two relevant processing steps, denoise and segmentation, implemented by two Convolutional Neural Networks (CNNs) models based on autoencoder architecture (encoder-decoder and UNet) and trained for the two tasks. In order to limit the number of uncontrolled variables, we designed a phantom containing cylindrical inserts of different sizes, filled with iodinated contrast media.

Obstructive sleep apnea in developmental age. A narrative review.

Sleep is a physiological function that undergoes, at different stages of life, to considerable variations in neurophysiological and behavioral functions. The developmental age is a period characterized by a continuous process of physical and neuropsychological changes and synaptic remodeling processes that are the neurophysiological basis of brain plasticity, typical of this developmental phase, occurring mainly during sleep. In the description of obstructive sleep apnea (OSA) in children, two main points should be highlighted: its variability in different age groups, and its specificity compared with OSA in adults.

Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets.

In this article, we explore the correlation between people trajectories and their head orientations. We argue that people trajectory and head pose forecasting can be modelled as a joint problem. Recent approaches on trajectory forecasting leverage short-term trajectories (aka tracklets) of pedestrians to predict their future paths.

OSA and CPAP therapy: effect of gender, somnolence, and treatment adherence on health-related quality of life.

Background: Obstructive sleep apnea (OSA) often has a significant impact on health-related quality of life (HRQoL) with social and psychological implications. For most OSA patients, a reduction in their HRQoL is due to symptoms such as poor sleep quality, excessive daytime somnolence, and fatigue with differences between gender.

Purpose: This study explores the CPAP treatment effect on self-perceived HRQoL related to gender, somnolence, and CPAP adherence.

Revisiting Projective Structure from Motion: A Robust and Efficient Incremental Solution.

This paper presents a solution to the Projective Structure from Motion (PSfM) problem able to deal efficiently with missing data, outliers and, for the first time, large scale 3D reconstruction scenarios. By embedding the projective depths into the projective parameters of the points and views, we decrease the number of unknowns to estimate and improve computational speed by optimizing standard linear Least Squares systems instead of homogeneous ones. In order to do so, we show that an extension of the linear constraints from the Generalized Projective Reconstruction Theorem can be transferred to the projective parameters, ensuring also a valid projective reconstruction in the process.

Machine learning approach for single molecule localisation microscopy.

Single molecule localisation (SML) microscopy is a fundamental tool for biological discoveries; it provides sub-diffraction spatial resolution images by detecting and localizing "all" the fluorescent molecules labeling the structure of interest. For this reason, the effective resolution of SML microscopy strictly depends on the algorithm used to detect and localize the single molecules from the series of microscopy frames. To adapt to the different imaging conditions that can occur in a SML experiment, all current localisation algorithms request, from the microscopy users, the choice of different parameters.

Tales of diversity: Genomic and morphological characteristics of forty-six Arthrobacter phages.

The vast bacteriophage population harbors an immense reservoir of genetic information. Almost 2000 phage genomes have been sequenced from phages infecting hosts in the phylum Actinobacteria, and analysis of these genomes reveals substantial diversity, pervasive mosaicism, and novel mechanisms for phage replication and lysogeny. Here, we describe the isolation and genomic characterization of 46 phages from environmental samples at various geographic locations in the U.

3D Object Localisation from Multi-View Image Detections.

In this work we present a novel approach to recover objects 3D position and occupancy in a generic scene using only 2D object detections from multiple view images. The method reformulates the problem as the estimation of a quadric (ellipsoid) in 3D given a set of 2D ellipses fitted to the object detection bounding boxes in multiple views. We show that a closed-form solution exists in the dual-space using a minimum of three views while a solution with two views is possible through the use of non-linear optimisation and object constraints on the size of the object shape.

Excessive Daytime Sleepiness and Sleep Disorders in a Population of Patients with Epilepsy: a Case-Control Study.

Background And Purpose: There are several primary causes for excessive daytime sleepiness (EDS) and sleep disorders in patients with epilepsy. Up to now, studies in the literature report conflicting data in terms of both prevalence and aetiology. The aim of our study was therefore to evaluate the prevalence of EDS and some sleep disorders in a population of patients with epilepsy treated with no more than two antiepileptic drugs (AEDs).

Nanoscale Molecular Reorganization of the Inhibitory Postsynaptic Density Is a Determinant of GABAergic Synaptic Potentiation.

Gephyrin is a key scaffold protein mediating the anchoring of GABAA receptors at inhibitory synapses. Here, we exploited superresolution techniques combined with proximity-based clustering analysis and model simulations to investigate the single-molecule gephyrin reorganization during plasticity of inhibitory synapses in mouse hippocampal cultured neurons. This approach revealed that, during the expression of inhibitory LTP, the increase of gephyrin density at postsynaptic sites is associated with the promoted formation of gephyrin nanodomains.

Immediate effect of CPAP titration on perceived health related quality of life: a prospective observational study.

Background: Perceived Health Related Quality of Life (HRQoL) is impaired in obstructive sleep apnea (OSA). This study examines changes in HRQoL aspects occurring immediately after CPAP titration. Furthermore, we analyzed variations in each gender and in patients undergoing home or laboratory-based CPAP titration pathways.

Gel pillow designed specifically for obstructive sleep apnea treatment with continuous positive airway pressure.

Objective:: To determine whether the use of a gel pillow with side cutouts designed to accommodate a continuous positive airway pressure (CPAP) mask and reduce head temperature improves the efficacy of and adherence to auto-CPAP therapy.

Methods:: Twenty-three consecutive CPAP-naïve patients with obstructive sleep apnea were enrolled in the study. Patients were given an auto-CPAP machine with an appropriate CPAP mask and were instructed to use CPAP for 15 nights.