Reply to the Editor

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SmartHeart CABG Edu

The paper reports on the SmartHeart CABG Edu Android app. The app was conceived to be an innovative and up-to-date tool for patient education, the first of its kind in the Italian context. In particular, the app was developed to provide educational material for patients about to undergo Coronary Artery Bypass Graft (CABG) surgery, a set of self-assessment tools concerning health status (i.e., BMI calculator, LDL cholesterol calculator and anxiety assessment tool) and usability questionnaires (i.e., SEQ and SUS). The paper initially describes the app, then reports on its evaluation, concerning both the app usability and the pre-operative anxiety, and ends by showing the improvements -- derived from the usability evaluation -- put into practice

Parachute emergency landing simulation and enhanced composite material characterization for General Aviation aircraft

General Aviation (GA) aircraft crashworthiness of the vehicle when it hits the ground after the parachute deployment is an important issue. The current dynamic emergency landing regulation (CS 23.562) defines the maximum human tolerant accelerations under both vertical and horizontal directions. This article aims to compare two different aircraft configurations: metal low-wing and composite high-wing ones. Both are two-seats and single-engine GA aircraft. The purpose of the analysis is to check whether the seats and restraint systems met human injury tolerance standards and to determine the possible impact on passengers in the cabin space due to shock loads. Finite element analysis of the fuselage sections for both configurations is performed using the commercial LS-Dyna solver. An extensive campaign of experimental tests has been performed on the composite samples for tuning and validating the model and to find the transition from an undamaged up to totally collapsed sample. The material of the composite fuselage has been characterized through experimental tests. The adopted material model has been refined to match with the performed experimental analysis, allowing high-fidelity modeling. A parametric analysis has been performed to determine the optimal impact angle in terms of lumbar injuries and loads transmitted by the seat belt due to aircraft contact with the ground, thereby increasing the level of safety. The investigations carried out may be an important indicator of the design of the parachute system

Giant metastatic myxoid liposarcoma of the mediastinum: A case report

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ColibriES: A Milliwatts RISC-V Based Embedded System Leveraging Neuromorphic and Neural Networks Hardware Accelerators for Low-Latency Closed-loop Control Applications

End-to-end event-based computation has the potential to push the envelope in latency and energy efficiency for edge AI applications. Unfortunately, event-based sensors (e.g., DVS cameras) and neuromorphic spike-based processors (e.g., Loihi) have been designed in a decoupled fashion, thereby missing major streamlining opportunities. This paper presents ColibriES, the first-ever neuromorphic hardware embedded system platform with dedicated event-sensor interfaces and full processing pipelines. ColibriES includes event and frame interfaces and data processing, aiming at efficient and long-life embedded systems in edge scenarios. ColibriES is based on the Kraken system-on-chip and contains a heterogeneous parallel ultra-low power (PULP) processor, frame-based and event-based camera interfaces, and two hardware accelerators for the computation of both event-based spiking neural networks and frame-based ternary convolutional neural networks. This paper explores and accurately evaluates the performance of event data processing on the example of gesture recognition on ColibriES, as the first step of full-system evaluation. In our experiments, we demonstrate a chip energy consumption of 7.7 \si{\milli\joule} and latency of 164.5 \si{\milli\second} of each inference with the DVS Gesture event data set as an example for closed-loop data processing, showcasing the potential of ColibriES for battery-powered applications such as wearable devices and UAVs that require low-latency closed-loop control

On the reliability of single-camera markerless systems for overground gait monitoring

Background and objective: Motion analysis is crucial for effective and timely rehabilitative interventions on people with motor disorders. Conventional marker-based (MB) gait analysis is highly time-consuming and calls for expensive equipment, dedicated facilities and personnel. Markerless (ML) systems may pave the way to less demanding gait monitoring, also in unsupervised environments (i.e., in telemedicine). However,scepticism on clinical usability of relevant outcome measures has hampered its use. ML is normally used to analyse treadmill walking, which is significantly different from the more physiological overground walking. This study aims to provide end-users with instructions on using a single-camera markerless system to obtain reliable motion data from overground walking, while clinicians will be instructed on the reliability of obtained quantities. Methods: The study compares kinematics obtained from ML systems to those concurrently obtained from marker-based systems, considering different stride counts and subject positioning within the capture volume. Results: The findings suggest that five straight walking trials are sufficient for collecting reliable kinematics with ML systems. Precision on joint kinematics decreased at the boundary of the capture volume. Excellent correlation was found between ML and MB systems for hip and knee angles (0.92<0.96), with slightly lower correlations observed for ankle plantar-dorsiflexion. The Bland-Altman analysis indicated the largest bias for hip flexion/extension ([0.2∘,10.9∘]) and the smallest for knee joint ([0.1∘,0.8∘]) when comparing MB-PiG and MB-JC approaches. For MB-JC vs. ML-JC comparison, the largest bias was for the ankle joint ([1.2∘,11.8∘]), while the smallest was for the hip joint ([0.2∘,7.3∘]). Conclusion: Single-camera markerless motion capture systems have great potential in assessing human joint kinematics during overground walking. Clinicians can confidently rely on estimated joint kinematics while walking, enabling personalized interventions and improving accessibility to remote evaluation and rehabilitation services, as long as: (i) the camera is positioned to capture someone walking back and forth at least five times with good visibility of the entire body silhouette; (ii) the walking path is at least 2 m long; and (iii) images captured at the boundaries of the camera image plane should be discarded

ColibriUAV: An Ultra-Fast, Energy-Efficient Neuromorphic Edge Processing UAV-Platform with Event-Based and Frame-Based Cameras

The interest in dynamic vision sensor (DVS)-powered unmanned aerial vehicles (UAV) is raising, especially due to the microsecond-level reaction time of the bio-inspired event sensor, which increases robustness and reduces latency of the perception tasks compared to a RGB camera. This work presents ColibriUAV, a UAV platform with both frame-based and event-based cameras interfaces for efficient perception and near-sensor processing. The proposed platform is designed around Kraken, a novel low-power RISC-V System on Chip with two hardware accelerators targeting spiking neural networks and deep ternary neural networks.Kraken is capable of efficiently processing both event data from a DVS camera and frame data from an RGB camera. A key feature of Kraken is its integrated, dedicated interface with a DVS camera. This paper benchmarks the end-to-end latency and power efficiency of the neuromorphic and event-based UAV subsystem, demonstrating state-of-the-art event data with a throughput of 7200 frames of events per second and a power consumption of 10.7 \si{\milli\watt}, which is over 6.6 times faster and a hundred times less power-consuming than the widely-used data reading approach through the USB interface. The overall sensing and processing power consumption is below 50 mW, achieving latency in the milliseconds range, making the platform suitable for low-latency autonomous nano-drones as well

Axial eccentric SynRel and SPM Motors analytical models validation using 3D finite element

This paper deals with the uniform and non-uniform axial eccentricity analyses of the surface mounted permanent magnet and synchronous reluctance machines. The analyses are carried out using an analytical model for each considered machine. Being the axial eccentricity a 3D physical phenomenon, the standard sliding approach used in the analytical models has been validated through accurate 3D FE simulations. The results presented in this paper verify the effectiveness of the analytical approaches quantifying the results deviations respect to the computational expensive 3D FE simulations. The results also confirms that synchronous reluctance machines show higher radial forces compared to the surface permanent magnet machines for the same eccentricity level, main geometry and operating condition

Should severe monolateral asymptomatic carotid artery stenosis be treated at the time of coronary artery bypass operation?

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