Genetic confirmation of the first Mediterranean record of Holacanthus africanus Cadenat, 1951

The first Mediterranean record of the pomacanthid Holacanthus africanus, caught within the Maltese waters, was assigned based on morphological and meristic characters. However, molecular and genetic analyses are required to confirm the taxonomic determination and avoid misidentification given the abundance of closely-related Pomacanthidae species and the biogeographic significance of this record for the Mediterranean. At the species level, the analyzed specimens gave a 99.7% identity match with H. africanus. This study represents yet another example of molecular analyses supplementing the conclusions of conventional morphological identification exercises.peer-reviewe

Anti-IL1 in patients with low penetrance mutations for autoinflammatory diseases: tuscany and sicilian case series from paediatric to adult age

Patients with low penetrance mutations for Autoinflammatory syndromes (AID) can have severe clinical manifestations, which require to be treated with biological drugs anti-IL-1. Objectives: To evaluate the response of AID to treatment with the recombinant human IL-1 receptor antagonist anakinra or with the anti-IL-1b

How does a dark compact object ringdown?

A generic feature of nearly out-of-equilibrium dissipative systems is that they resonate through a set of quasinormal modes. Black holes - the absorbing objects par excellence - are no exception. When formed in a merger, black holes vibrate in a process called "ringdown", which leaves the gravitational-wave footprint of the event horizon. In some models of quantum gravity which attempt to solve the information-loss paradox and the singularities of General Relativity, black holes are replaced by regular, horizonless objects with a tiny effective reflectivity. Motivated by these scenarios, here we develop a generic framework to the study of the ringdown of a compact object with various shades of darkness. By extending the black-hole membrane paradigm, we map the interior of any compact object in terms of the bulk and shear viscosities of a fictitious fluid located at the surface, with the black-hole limit being a single point in a three-dimensional parameter space. We unveil some remarkable features of the ringdown and some universal properties of the light ring in this framework. We also identify the region of the parameter space which can be probed by current and future gravitational-wave detectors. A general feature is the appearance of mode doublets which are degenerate only in the black-hole limit. We argue that the merger event GW150914 already imposes a strong lower bound on the compactness of the merger remnant of approximately 99% of the black-hole compactness. This places model-independent constraints on black-hole alternatives such as diffuse "fuzzballs" and nonlocal stars.Comment: 11+7 pages, 8 figures. v2: minor revisions to match the version to appear in PR

Vision-Based Terrain Relative Navigation on High-Altitude Balloon and Sub-Orbital Rocket

We present an experimental analysis on the use of a camera-based approach for high-altitude navigation by associating mapped landmarks from a satellite image database to camera images, and by leveraging inertial sensors between camera frames. We evaluate performance of both a sideways-tilted and downward-facing camera on data collected from a World View Enterprises high-altitude balloon with data beginning at an altitude of 33 km and descending to near ground level (4.5 km) with 1.5 hours of flight time. We demonstrate less than 290 meters of average position error over a trajectory of more than 150 kilometers. In addition to showing performance across a range of altitudes, we also demonstrate the robustness of the Terrain Relative Navigation (TRN) method to rapid rotations of the balloon, in some cases exceeding 20 degrees per second, and to camera obstructions caused by both cloud coverage and cords swaying underneath the balloon. Additionally, we evaluate performance on data collected by two cameras inside the capsule of Blue Origin's New Shepard rocket on payload flight NS-23, traveling at speeds up to 880 km/hr, and demonstrate less than 55 meters of average position error.Comment: Published in 2023 AIAA SciTec

Loc-NeRF: Monte Carlo Localization using Neural Radiance Fields

We present Loc-NeRF, a real-time vision-based robot localization approach that combines Monte Carlo localization and Neural Radiance Fields (NeRF). Our system uses a pre-trained NeRF model as the map of an environment and can localize itself in real-time using an RGB camera as the only exteroceptive sensor onboard the robot. While neural radiance fields have seen significant applications for visual rendering in computer vision and graphics, they have found limited use in robotics. Existing approaches for NeRF-based localization require both a good initial pose guess and significant computation, making them impractical for real-time robotics applications. By using Monte Carlo localization as a workhorse to estimate poses using a NeRF map model, Loc-NeRF is able to perform localization faster than the state of the art and without relying on an initial pose estimate. In addition to testing on synthetic data, we also run our system using real data collected by a Clearpath Jackal UGV and demonstrate for the first time the ability to perform real-time global localization with neural radiance fields. We make our code publicly available at https://github.com/MIT-SPARK/Loc-NeRF

Explainable AI for Machine Fault Diagnosis: Understanding Features' Contribution in Machine Learning Models for Industrial Condition Monitoring

Although the effectiveness of machine learning (ML) for machine diagnosis has been widely established, the interpretation of the diagnosis outcomes is still an open issue. Machine learning models behave as black boxes; therefore, the contribution given by each of the selected features to the diagnosis is not transparent to the user. This work is aimed at investigating the capabilities of the SHapley Additive exPlanation (SHAP) to identify the most important features for fault detection and classification in condition monitoring programs for rotating machinery. The authors analyse the case of medium-sized bearings of industrial interest. Namely, vibration data were collected for different health states from the test rig for industrial bearings available at the Mechanical Engineering Laboratory of Politecnico di Torino. The Support Vector Machine (SVM) and k-Nearest Neighbour (kNN) diagnosis models are explained by means of the SHAP. Accuracies higher than 98.5% are achieved for both the models using the SHAP as a criterion for feature selection. It is found that the skewness and the shape factor of the vibration signal have the greatest impact on the models’ outcomes

TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting

none6We introduce TAASRAD19, a high-resolution radar reflectivity dataset collected by the Civil Protection weather radar of the Trentino South Tyrol Region, in the Italian Alps. The dataset includes 894,916 timesteps of precipitation from more than 9 years of data, offering a novel resource to develop and benchmark analog ensemble models and machine learning solutions for precipitation nowcasting. Data are expressed as 2D images, considering the maximum reflectivity on the vertical section at 5 min sampling rate, covering an area of 240 km of diameter at 500 m horizontal resolution. The TAASRAD19 distribution also includes a curated set of 1,732 sequences, for a total of 362,233 radar images, labeled with precipitation type tags assigned by expert meteorologists. We validate TAASRAD19 as a benchmark for nowcasting methods by introducing a TrajGRU deep learning model to forecast reflectivity, and a procedure based on the UMAP dimensionality reduction algorithm for interactive exploration. Software methods for data pre-processing, model training and inference, and a pre-trained model are publicly available on GitHub (https://github.com/MPBA/TAASRAD19) for study replication and reproducibility.noneFranch, Gabriele; Maggio, Valerio; Coviello, Luca; Pendesini, Marta; Jurman, Giuseppe; Furlanello, CesareFranch, Gabriele; Maggio, Valerio; Coviello, Luca; Pendesini, Marta; Jurman, Giuseppe; Furlanello, Cesar

The spectral element method as an effective tool for solving large scale dynamic soil-structure interaction problems

The spectral element method (SEM) is a powerful numerical technique naturally suited for wave propagation and dynamic soil-structure interaction (DSSI) analyses. A class of SEM has been widely used in the seismological field (local or global seismology) thanks to its capability of providing high accuracy and allowing the implementation of optimized parallel algorithms. We illustrate inthis contribution how the SEM can be effectively used also for the numerical analysis of DSSI problems, with reference to the 3D seismic response of a railway viaduct in Italy. This numerical analysis includes the combined effect of: a) strong lateral variations of soil properties; b) topographic amplification; c) DSSI; d) spatial variation of earthquake ground motion in the structural response. Some hints on the work in progress to effectively handle nonlinear problems with SEM are also given

PEelse: a 2D parallel spectral code for linear elastic analysis of seismic wave propagation. Implementation of seismic sources (plane wave and seismic moment tensor), absorbing boundaries and damping factor

PEelse2D is a spectral element, parallel, computer program for the analysis of complex 2D structure system, subject to transient dynamic loading conditions. PEelse2D is developed by the CRS4 team. The co-operation between the CRS4 and the Technical school of Milan (Department of Structural Engineering) is intended to equip the program of typical tools necessary for the simulation of seismic wave propagation into linear visco-elastic medium. The goal of the present report is to present the results obtained during the period 15 July – 14 September 2002, on three important topics: portability of PEelse2D; functionality of PEelse2D; implementation of the necessary tools for the analysis in the seismic wave field: most common sources in the seismic field (plane wave in the form of Ricker wavelet and seismic moment tensor (Madariaga, 1983)); internal soil dissipation as described by Kosloff and Kosloff (1986); Absorbing boundaries condition (Stacey, 1988)