Search Results (73)

Flexible magnetic tactile sensors hold transformative potential in robotics and human–computer interactions by enabling precise force detection. However, existing sensors face challenges in balancing sensitivity, detection range, and structural adaptability for sensing force. This study proposed a pre-compressed magnetization method to address these limitations by amplifying the magnetoelastic effect through optimized magnetization direction distribution of the elastomer. A body-centered cubic lattice-structured magnetoelastomer featuring regular deformation under compression was fabricated via digital light processing (DLP) to validate this method. Finite element simulations and experimental analyses revealed that magnetizing the material under 60% compression strain optimized magnetization direction distribution, enhancing force–magnetic coupling. Integrating the magnetic elastomer with a hall sensor, the prepared tactile sensor demonstrated a low detection limit (1 mN), wide detection range (0.001–10 N), rapid response/recovery times (40 ms/50 ms), and durability (>1500 cycles). By using machine learning, the sensor enabled accurate 3D force prediction. Full article

Background/Objectives: In the Aosta Valley, the alpine grazing system integrates livestock production and land management. Valdostana breeding has adapted to this mountainous region, but the spread of Staphylococcus aureus within pastures may impact animal health. The aim of this study was to provide an overview of S. aureus genotypes associated with antimicrobial resistance (AMR) and virulence profiles in four dairy herds in the Aosta Valley from July 2022 to August 2023. Methods: A total of 468 composite milk samples were collected at three timepoints: T1 (pasture-livestock system), T2 (farm-livestock system), and T3 (pasture-livestock system). S. aureus isolates were characterized by antimicrobial susceptibility testing, ribosomal spacer (RS)-PCR, multilocus sequence typing (MLST), PCR analysis for 28 virulence genes and 6 AMR genes, and adlb-targeted real-time PCR. Results: RS-PCR analysis of 82 S. aureus strains revealed 12 genotypes (GT) in eight clusters (CL). The most prevalent variant was GTR^I (61%), followed by GTB (15%). Resistance to penicillin was high (69%), with CLR strains showing 88% resistance, and 51% resistance to amoxicillin plus clavulanate. All strains were susceptible to cephalosporins and oxacillin. Macrolide resistance was low (4%), and multi-drug resistance was 6%. AMR gene presence corresponded with susceptibility, with blaZ detected in 94% of CLR strains. CLR strains also possessed genes for biofilm formation and virulence factors. Conclusions: This study highlights the presence of AMR and virulence factors in S. aureus strains from alpine grazing systems, underscoring the need for ongoing monitoring to mitigate risks to animal health. Full article

Miniaturized components for enhanced integrated functionality or thin sheets for lightweight applications often consist of face-centered cubic metals. They exhibit good strength, corrosion resistance, formability and recyclability. Microfabrication technologies, however, may introduce cold work or detrimental heat-induced lattice defects into the material, with consequences for the mechanical properties. Austenitic stainless steels (1.4310, 1.4301) and aluminum alloys (EN AW-5005-H24, EN AW-6082-T6) were selected for this study. The influence of pulsed fiber laser cutting, microwaterjet cutting, and annealing on the strain–stress behavior was investigated. The micro-tensile test setup comprised a flex-structure force sensor, a laser extensometer, and a dedicated sample holder. Fiber laser cut 1.4310 samples exhibited early failure at low fracture strain in narrow shear band zones. The shear band zones were detectable on the sample surface, in the laser extensometer images, in the horizontal sections of the stress–strain curves, and in the microstructure. Inside the shear band zones, grains were strongly elongated and exhibited numerous parallel planar defects. Heat-induced chromium carbides, in combination with low stacking fault energy (SFE) and elevated carbon content, favored shear band zone formation in 1.4310. In contrast, microwaterjet cut high SFE materials EN AW-5005-H24 and EN AW-6082-T6, as well as low-carbon austenitic stainless steel 1.4301, exhibited uniform plastic deformation. Full article

This study aims to develop an integrated monitoring system using a fiber Bragg grating sensor network to record the structural response of a landing gear system under operational loads to detect hard landing conditions on soils with different absorbing characteristics and to differentiate between soil types during landings. This paper refers to drop tests carried out at a drop tower of the test article, an integrated leaf spring landing gear with fiber Bragg grating sensors, measuring strain to evaluate landings from different heights on different soil types: hard soil, sand, and gravel. Cross-correlation and fast Fourier transform analyses can help to assess the repeatability of the impact tests, to assess the developed system as very reliable in detecting landing conditions and ensure very low error in the accuracy of the sensor placement, or to assess whether different impacts under different conditions produce consistent responses. Full article

Fiber-optic sensing has shown promising development for use in detecting magnetic fields for downhole and biomedical applications. Coupling existing fiber-based strain sensors with highly magnetostrictive materials allows for a new method of magnetic characterization capable of distributed and high-sensitivity field measurements. This study investigates the strain response of the highly magnetostrictive alloys Metglas^® 2605SC and Vitrovac^® 7600 T70 using Fiber Bragg Grating (FBG) acoustic sensors and an applied AC magnetic field. Sentek Instrument’s picoDAS interrogated the distributed FBG sensors set atop a ribbon of magnetostrictive material, and the corresponding strain response transferred to the fiber was analyzed. Using the Vitrovac^® ribbon, a minimal detectable field amplitude of 60 nT was achieved. Using Metglas^®, an even better sensitivity was demonstrated, where detected field amplitudes as low as 3 nT were measured via the strain response imparted to the FBG sensor. Distributed FBG sensors are readily available commercially, easily integrated into existing interrogation systems, and require no bonding to the magnetostrictive material for field detection. The simple sensor configuration with nanotesla-level sensitivity lends itself as a promising means of magnetic characterization and demonstrates the potential of fiber-optic acoustic sensors for distributed measurements. Full article

Caliciviruses including noro- and sapoviruses of family Caliciviridae are important enteric human and swine pathogens, while others, like valoviruses, are less known. In this study, we developed a detection and typing pipeline for the most prevalent swine enteric caliciviruses—sapovirus GIII (Sw-SaV), norovirus GII (Sw-NoV), and valovirus GI (Sw-VaV). The pipeline integrates triplex RT-qPCR, 3′RACE semi-nested PCR, and next-generation sequencing (NovaSeq, Illumina) techniques. A small-scale epidemiological investigation was conducted on archived enteric and, for the first time, on oral fluid/saliva samples of diarrheic and asymptomatic swine of varying ages from Hungary and Slovakia. In enteric samples, Sw-SaV was the most prevalent, detected in 26.26% of samples, primarily in diarrheic pigs with low Cq values, followed by Sw-NoV (2.53%) in nursery pigs. In oral fluid samples, Sw-NoV predominated (7.46%), followed by Sw-SaV (4.39%). Sw-VaVs were sporadically found in both sample types. A natural, asymptomatic Sw-SaV outbreak was retrospectively detected where the transient shedding of the virus was <2 weeks. Complete capsid sequences (n = 59; 43 Sw-SaV, 13 Sw-NoV, and 3 Sw-VaV) including multiple (up to five) co-infecting variants were identified. Sw-SaV sequences belong to seven genotypes, while Sw-NoV and Sw-VaV strains clustered into distinct sub-clades, highlighting the complex diversity of these enteric caliciviruses in swine. Full article

MEMS acoustic sensors are a type of physical quantity sensor based on MEMS manufacturing technology for detecting sound waves. They utilize various sensitive structures such as thin films, cantilever beams, or cilia to collect acoustic energy, and use certain transduction principles to read out the generated strain, thereby obtaining the targeted acoustic signal’s information, such as its intensity, direction, and distribution. Due to their advantages in miniaturization, low power consumption, high precision, high consistency, high repeatability, high reliability, and ease of integration, MEMS acoustic sensors are widely applied in many areas, such as consumer electronics, industrial perception, military equipment, and health monitoring. Through different sensing mechanisms, they can be used to detect sound energy density, acoustic pressure distribution, and sound wave direction. This article focuses on piezoelectric, piezoresistive, capacitive, and optical MEMS acoustic sensors, showcasing their development in recent years, as well as innovations in their structure, process, and design methods. Then, this review compares the performance of devices with similar working principles. MEMS acoustic sensors have been increasingly widely applied in various fields, including traditional advantage areas such as microphones, stethoscopes, hydrophones, and ultrasound imaging, and cutting-edge fields such as biomedical wearable and implantable devices. Full article

Background: Infant meningitis, particularly caused by Escherichia coli, remains a life-threatening condition, especially in premature and low-weight infants. Infections of the central nervous system can be fatal, necessitating prompt diagnosis and appropriate treatment. Acute infections caused by various pathogens, including E. coli, often present with similar clinical symptoms. The rapid identification of pathogens and their antimicrobial resistance mechanisms is critical for timely and effective treatment. We report the case of an 8-month-old patient who presented with fever, diarrhea, and convulsive seizures and was subsequently diagnosed with meningitis. Despite initial empirical treatment with ceftriaxone, the patient’s condition worsened. Methods: At Bambino Gesù Children’s Hospital, molecular diagnostic tools, including the FilmArray Meningitis/Encephalitis and Blood Culture Identification panels, were employed. Results: Although the Meningitis panel did not detect any pathogens due to the lack of the specific bacterial target, the off-label use of the Blood Culture Identification panel identified a non-K1 Escherichia coli strain carrying the CTX-M resistance gene, an extended-spectrum beta-lactamase (ESBL). Despite the rapid diagnostic approach and adjustment of antibiotic therapy, the patient succumbed to the infection due to the strain’s high virulence and multidrug resistance. Whole-genome sequencing further characterized the strain, revealing that it belonged to the ST131 group, a highly resistant and virulent strain associated with sepsis. Conclusions: This case highlights the importance of integrating advanced molecular diagnostics, such as whole-genome sequencing, with traditional methods to improve pathogen detection, especially in cases of emerging resistant strains that are not covered by standard diagnostic panels. It also emphasizes the need for the continuous adaptation of diagnostic tools to include non-K1 E. coli strains for more comprehensive and timely meningitis diagnosis. Full article

Within the domain of Structural Health Monitoring (SHM), conventional approaches generally are complicated, destructive, and time-consuming. It also necessitates an extensive array of sensors to effectively evaluate and monitor the structural integrity. In this research work, we present a novel, non-destructive SHM framework based on machine learning (ML) for the accurate detection and localisation of structural cracks. This approach leverages a minimal number of strain gauge sensors linked via Bluetooth Low Energy (BLE) communication. The framework is validated through empirical data collected from 3D carbon fibre-reinforced composites, including three distinct specimens, ranging from crack-free samples to specimens with up to ten cracks of varying lengths and depths. The methodology integrates an analytical examination of the Shewhart chart, Grubbs’ test (GT), and hierarchical clustering (HC) algorithm, tailored towards the metrics of fracture measurement and classification. Our novel ML framework allows one to replace exhausting laboratory procedures with a modern and quick mechanism for the material, with unprecedented properties that could provide potential applications in the composites industry. Full article

This comprehensive review examines the phenomena of stress corrosion cracking (SCC) and chloride-induced stress corrosion cracking (Cl-SCC) in materials commonly used in the oil and gas industry, with a focus on austenitic stainless steels. The study reveals that SCC initiation can occur at temperatures as low as 20 °C, while Cl-SCC propagation rates significantly increase above 60 °C, reaching up to 0.1 mm/day in environments with high chloride concentrations. Experimental methods such as Slow Strain Rate Tests (SSRTs), Small Punch Tests (SPTs), and Constant-Load Tests (CLTs) were employed to quantify the impacts of temperature, chloride concentration, and pH on SCC susceptibility. The results highlight the critical role of these factors in determining the susceptibility of materials to SCC. The review emphasizes the importance of implementing various mitigation strategies to prevent SCC, including the use of corrosion-resistant alloys, protective coatings, cathodic protection, and corrosion inhibitors. Additionally, regular monitoring using advanced sensor technologies capable of detecting early signs of SCC is crucial for preventing the onset of SCC. The study concludes with practical recommendations for enhancing infrastructure resilience through meticulous material selection, comprehensive environmental monitoring, and proactive maintenance strategies, aimed at safeguarding operational integrity and ensuring environmental compliance. The review underscores the significance of considering the interplay between mechanical stresses and corrosive environments in the selection and application of materials in the oil and gas industry. Low pH levels and high temperatures facilitate the rapid progression of SCC, with experimental results indicating that stainless steel forms passive films with more defects under these conditions, reducing corrosion resistance. This interplay highlights the need for a comprehensive understanding of the complex interactions between materials, environments, and mechanical stresses to ensure the long-term integrity of critical infrastructure. Full article

Transcatheter aortic valve implantation (TAVI) was initially developed for adult patients, but there is a growing interest to expand this procedure to younger individuals with longer life expectancies. However, the gradual degradation of biological valve leaflets in transcatheter heart valves (THV) presents significant challenges for this extension. This study aimed to establish a multiphysics computational framework to analyze structural and flow measurements of TAVI and evaluate the integration of optical fiber and photoplethysmography (PPG) sensors for monitoring valve function. A two-way fluid–solid interaction (FSI) analysis was performed on an idealized aortic vessel before and after the virtual deployment of the SAPIEN 3 Ultra (S3) THV. Subsequently, an analytical analysis was conducted to estimate the PPG signal using computational flow predictions and to analyze the effect of different pressure gradients and distances between PPG sensors. Circumferential strain estimates from the embedded optical fiber in the FSI model were highest in the sinus of Valsalva; however, the optimal fiber positioning was found to be distal to the sino-tubular junction to minimize bending effects. The findings also demonstrated that positioning PPG sensors both upstream and downstream of the bioprosthesis can be used to effectively assess the pressure gradient across the valve. We concluded that computational modeling allows sensor design to quantify vessel wall strain and pressure gradients across valve leaflets, with the ultimate goal of developing low-cost monitoring systems for detecting valve deterioration. Full article

The application of antimicrobials in aquaculture primarily aims to prevent and treat bacterial infections in fish, but their inappropriate use may result in the emergence of zoonotic antibiotic-resistant bacteria and the subsequent transmission of resistant strains to humans via food consumption. The aquatic environment serves as a potential reservoir for resistant bacteria, providing an ideal breeding ground for development of antimicrobial resistance (AMR). The mutual inter-connection of intensive fish-farming systems with terrestrial environments, the food processing industry and human population creates pathways for the transmission of resistant bacteria, exacerbating the problem further. The aim of this study was to provide an overview of the most effective and available risk mitigation strategies to tackle AMR in aquaculture, based on the One Health (OH) concept. The stringent antimicrobial use guidelines, promoting disease control methods like enhanced farm biosecurity measures and vaccinations, alternatives to antibiotics (ABs) (prebiotics, probiotics, immunostimulants, essential oils (EOs), peptides and phage therapy), feeding practices, genetics, monitoring water quality, and improving wastewater treatment, rather than applying excessive use of antimicrobials, can effectively prevent the development of AMR and release of resistant bacteria into the environment and food. The contribution of the environment to AMR development traditionally receives less attention, and, therefore, environmental aspects should be included more prominently in OH efforts to predict, detect and prevent the risks to health. This is of particular importance for low and middle-income countries with a lack of integration of the national AMR action plans (NAPs) with the aquaculture-producing environment. Integrated control of AMR in fisheries based on the OH approach can contribute to substantial decrease in resistance, and such is the case in Asia, where in aquaculture, the percentage of antimicrobial compounds with resistance exceeding 50% (P50) decreased from 52% to 22% within the period of the previous two decades. Full article

The demand for fiber-reinforced polymers (FRPs) has significantly increased in various industries due to their attributes, including low weight, high strength, corrosion resistance, and cost-efficiency. Nevertheless, FRPs, such as glass and Kevlar fiber composites, exhibit anisotropic properties and relatively low interlaminar strength, rendering them susceptible to undetected damage. The integration of real-time damage detection processes can effectively mitigate this issue. This paper introduces a novel method for fabricating embedded capacitive sensors within FRPs using a coating technique. The study encompasses two types of fibers, namely glass and Kevlar fiber/epoxy composites. The physical vapor deposition (PVD) technique is employed to coat bundle fibers with conductive material, thus creating embedded electrodes. The results demonstrate the uniform distribution of nanoparticles of gold (Au) along the fibers using PVD, resulting in a favorable resistance of approximately ≈100 Ω. Two sensor configurations are explored: axial and lateral embedding of the coated yarn (electrodes) to investigate the influence of load direction on the coating yarn. Axial-sensor configuration specimens undergo tensile testing, showcasing a linear response to axial loads with average sensitivities of 1 for glass and 1.5 for Kevlar fiber/epoxy composites. Additionally, onset damage is detected in both types of fiber composites, occurring before final fracture, with average stress at the turning point measuring 208 MPa for glass and 144 MPa for Kevlar. The lateral-sensor configuration for glass fiber-reinforced polymer (GFRP) exhibits good linearity towards strain until failure, with average gauge factors of 0.25 and −2.44 in the x and y axes, respectively. Full article

This study introduces a novel wearable Inertial Measurement Unit (IMU)-based system for an objective and comprehensive assessment of Work-Related Musculoskeletal Disorders (WMSDs), thus enhancing workplace safety. The system integrates wearable technology with a user-friendly interface, providing magnetometer-free orientation estimation, joint angle measurements, and WMSDs risk evaluation. Tested in a cable manufacturing facility, the system was evaluated with ten female employees. The evaluation involved work cycle identification, inter-subject comparisons, and benchmarking against standard WMSD risk assessments like RULA, REBA, Strain Index, and Rodgers Muscle Fatigue Analysis. The evaluation demonstrated uniform joint patterns across participants ($ICC=0.72\pm 0.23$) and revealed a higher occurrence of postures warranting further investigation, which is not easily detected by traditional methods such as RULA. The experimental results showed that the proposed system’s risk assessments closely aligned with the established methods and enabled detailed and targeted risk assessments, pinpointing specific bodily areas for immediate ergonomic interventions. This approach not only enhances the detection of ergonomic risks but also supports the development of personalized intervention strategies, addressing common workplace issues such as tendinitis, low back pain, and carpal tunnel syndrome. The outcomes highlight the system’s sensitivity and specificity in identifying ergonomic hazards. Future efforts should focus on broader validation and exploring the relative influence of various WMSDs risk factors to refine risk assessment and intervention strategies for improved applicability in occupational health. Full article

We applied an interdisciplinary approach to analyze the late Quaternary activity of the Sava Fault in the Slovenian Southern Alps. The Sava Fault is an active strike-slip fault, and part of the Periadriatic Fault System that accommodated the convergence of Adria and Europe. It is one of the longest faults in the Southern Alps. Using high-resolution digital elevation models from lidar and photogrammetric surveys, we were able to overcome the challenges of assessing fault activity in a region with intense surface processes, dense vegetation, and relatively low fault slip rates. By integrating remote sensing analysis, geomorphological mapping, structural geological investigations, and near-surface geophysics (electrical resistivity tomography and ground penetrating radar), we were able to find subtle geomorphological indicators, detect near-surface deformation, and show distributed surface deformation and a complex fault pattern. Using optically stimulated luminescence dating, we tentatively estimated a slip rate of 1.8 ± 0.4 mm/a for the last 27 ka, which exceeds previous estimates and suggests temporal variability in fault behavior. Our study highlights the importance of modern high-resolution remote sensing techniques and interdisciplinary approaches in detecting tectonic deformation in relatively low-strain rate environments with intense surface processes. We show that slip rates can vary significantly depending on the studied time window. This is a critical piece of information since slip rates are a key input parameter for seismic hazard studies. Full article