Numerical Investigation on Guided Waves Dispersion and Scattering Phenomena in Stiffened Panels.

The aim of this work is to propose a numerical methodology based on the finite element (FE) method to investigate the dispersive behavior of guided waves transmitted, converted, and reflected by reinforced aluminum and composite structures, highlighting their differences. The dispersion curves of such modes can help designers in improving the damage detection sensitivity of Lamb wave based structural health monitoring (SHM) systems. A preliminary phase has been carried out to assess the reliability of the modelling technique.

Damage Detection in Flat Panels by Guided Waves Based Artificial Neural Network Trained through Finite Element Method.

Artificial Neural Networks (ANNs) have rapidly emerged as a promising tool to solve damage identification and localization problem, according to a Structural Health Monitoring approach. Finite Element (FE) Analysis can be extremely helpful, especially for reducing the laborious experimental campaign costs for the ANN development and training phases. The aim of the present work is to propose a guided wave-based ANN, developed through the use of the Finite Element Method, to determine the position of damages.

On Asymptotic Efficiency of the Signal-to-Noise Estimator for Deterministic Complex Sinusoids.

The moment-based M2M4 signal-to-noise (SNR) estimator was proposed for a complex sinusoidal signal with a but unknown phase corrupted by additive Gaussian noise by Sekhar and Sreenivas. The authors studied its performances only through numerical examples and concluded that the proposed estimator is asymptotically efficient and exhibits finite sample super-efficiency for some combinations of signal and noise power. In this paper, we derive the analytical asymptotic performances of the proposed M2M4 SNR estimator, and we show that, contrary to what it has been concluded by Sekhar and Sreenivas, the proposed estimator is neither (asymptotically) efficient nor super-efficient.

SARS-CoV-2 spike protein detection through a plasmonic D-shaped plastic optical fiber aptasensor.

A specific aptameric sequence has been immobilized on short polyethyleneglycol (PEG) interface on gold nano-film deposited on a D-shaped plastic optical fiber (POFs) probe, and the protein binding has been monitored exploiting the very sensitive surface plasmon resonance (SPR) phenomenon. The receptor-binding domain (RBD) of the SARS-CoV-2 spike glycoprotein has been specifically used to develop an aptasensor. Surface analysis techniques coupled to fluorescence microscopy and plasmonic analysis have been utilized to characterize the biointerface.

A Robust Numerical Methodology for Fatigue Damage Evolution Simulation in Composites.

Composite materials, like metals, are subject to fatigue effects, representing one of the main causes for component collapse in carbon fiber-reinforced polymers. Indeed, when subject to low stress cyclic loading, carbon fiber-reinforced polymers exhibit gradual degradation of the mechanical properties. The numerical simulation of this phenomenon, which can strongly reduce time and costs to market, can be extremely expensive in terms of computational effort since a very high number of static analyses need to be run to take into account the real damage propagation due the fatigue effects.

A Surface Plasmon Resonance Plastic Optical Fiber Biosensor for the Detection of Pancreatic Amylase in Surgically-Placed Drain Effluent.

Postoperative pancreatic fistula (POPF), the major driver of morbidity and mortality following pancreatectomy, is caused by an abnormal communication between the pancreatic ductal epithelium and another epithelial surface containing pancreas-derived, enzyme-rich fluid. There is a strong correlation between the amylase content in surgically-placed drains early in the postoperative course and the development of POPF. A simple and cheap method to determine the amylase content from the drain effluent has been eagerly advocated.

Insights into bioflocculation of filamentous cyanobacteria, microalgae and their mixture for a low-cost biomass harvesting system.

Cyanobacteria and microalgae are considered as interesting feedstocks for either the production of high value bio-based compounds and biofuels or wastewater treatment. Nevertheless, the high costs of production, mainly due to the harvesting process, hamper a wide commercialization of industrial cyanobacteria and microalgae based products. Recent studies have found in autoflocculation and bioflocculation promising spontaneous processes for a low-cost and environmentally sustainable cyanobacteria and microalgae biomass harvesting process.

Bioaugmentation strategy to enhance polycyclic aromatic hydrocarbons anaerobic biodegradation in contaminated soils.

This paper proposes an innovative bioaugmentation approach for the remediation of polycyclic aromatic hydrocarbon (PAH) contaminated soils, based on a novel habitat-based strategy. This approach was tested using two inocula (i-24 and i-96) previously enriched through an anaerobic digestion process on wheat straw. It relies on the application of allochthonous microorganisms characterized by specific functional roles obtained by mimicking a natural hydrolytic environment such as the rumen.

Scalable Distributed State Estimation in UTM Context.

This article proposes a novel approach to the Distributed State Estimation (DSE) problem for a set of co-operating UAVs equipped with heterogeneous on board sensors capable of exploiting certain characteristics typical of the UAS Traffic Management (UTM) context, such as high traffic density and the presence of limited range, Vehicle-to-Vehicle communication devices. The proposed algorithm is based on a scalable decentralized Kalman Filter derived from the Internodal Transformation Theory enhanced on the basis of the Consensus Theory. The general benefit of the proposed algorithm consists of, on the one hand, reducing the estimation problem to smaller local sub-problems, through a self-organization process of the local estimating nodes in response to the time varying communication topology; and on the other hand, of exploiting measures carried out nearby in order to improve the accuracy of the local estimates.

Experimental and Numerical Assessment of Fibre Bridging Toughening Effects on the Compressive Behaviour of Delaminated Composite Plates.

Increasing the Mode I inter-laminar fracture toughness of composite laminates can contribute to slowing down delamination growth phenomena, which can be considered one of the most critical damage mechanisms in composite structures. Actually, the Mode I interlaminar fracture toughness () in fibre-reinforced composite materials has been found to considerably increase with the crack length when the fibre bridging phenomenon takes place. Hence, in this paper, the fibre bridging phenomenon has been considered as a natural toughening mechanism able to replace embedded metallic or composite reinforcements, currently used to increase tolerance to inter-laminar damage.

Cross-Influence between Intra-Laminar Damages and Fibre Bridging at the Skin-Stringer Interface in Stiffened Composite Panels under Compression.

In this paper, the skin-stringer separation phenomenon that occurs in stiffened composite panels under compression is numerically studied. Since the mode I fracture toughness and, consequently, the skin-stringer separation can be influenced by the fibre bridging phenomenon at the skin-stringer interface, in this study, comparisons among three different material systems with different fibre bridging sensitivities have been carried out. Indeed, a reference material system has been compared, in terms of toughness performance, against two materials with different degrees of sensitivity to fibre bridging.

Supercritical Fluid Extraction of Lutein from .

Lutein has several benefits for human health, playing an important role in the prevention of age-related macular degeneration (AMD), cataracts, amelioration of the first stages of atherosclerosis, and some types of cancer. In this work, the microalga was used as a natural source for the supercritical fluid (SF) extraction of lutein. For this purpose, the optimization of the main parameters affecting the extraction, such as biomass pre-treatment, temperature, pressure, and carbon dioxide (CO₂) flow rate, was performed.

Eicosapentaenoic Acid Extraction from using Carbon Dioxide at Supercritical Conditions.

This research shows that carbon dioxide supercritical fluid (CO₂-SF) is an emerging technology for the extraction of high interest compounds for applications in the manufacturing of pharmaceuticals, nutraceuticals, and cosmetics from microalgae. The purpose of this study is to recover fatty acids (FAs) and, more precisely, eicosapentaenoic acid (EPA) from biomass by CO₂-SF extraction. In the paper, the effect of mechanical pre-treatment was evaluated with the aim of increasing FAs recovery.

The Relevance of Foreshocks in Earthquake Triggering: A Statistical Study.

An increase of seismic activity is often observed before large earthquakes. Events responsible for this increase are usually named foreshock and their occurrence probably represents the most reliable precursory pattern. Many foreshocks statistical features can be interpreted in terms of the standard mainshock-to-aftershock triggering process and are recovered in the Epidemic Type Aftershock Sequence ETAS model.