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A submerged elevation located off the coast of Le Castella, a small village on the Ionian Coast of Calabria (Italy) populated for thousands of years that features notable archaeological remains from the Great Greece (Magna Graecia) and the Middle Ages, was investigated through in-depth, multidisciplinary, geoarchaeological research. This submarine elevation, once aligned with the marine terrace MIS 3 of Le Castella and still completely emerged between 10 and 8 ka years ago, slowly sank due to erosion and local tectonic-structural subsidence and was also favoured by a submerged normal fault that cuts the terrace in two. The dismantling and sinking of this part of the marine terrace has significantly changed the Late Holocene shorelines, with notable consequences on a topographic and archaeological level. In fact, one of the consequences of the sinking of this ancient promontory was the disappearance of two small islands that were reported to be right in front of Le Castella by numerous historical and cartographic sources. In the last decades, there has been a scientific debate over the existence of these islets, but no convincing evidence has been found about their actual presence up until now. This research, funded by the Marine Protected Area “Capo Rizzuto”, was conducted by means of underwater archaeological and geological surveys, geophysical seabed mapping systems, and both direct and instrumental optical surveys made with an Autonomous Surface Vehicle. The outcomes allow us to confirm the presence of these two partially emerged rock bodies up to half a millennium ago. In addition, the presence of anthropogenic extrabasinal materials in a marine area corresponding to one of the highest points of the submerged elevation allows us to define the exact position of one of the two islets. These archaeological findings have been subject, for the first time ever, to a thorough topographical and architectural analysis, then compared with other near and very similar submerged structures. On the basis of these comparisons, the findings should be attributed to the Byzantine Age or, at most, to the Middle Ages. In-depth archival research on portolan charts and navigation maps, in many cases unpublished and dating from the Middle Ages to the early 18th century, supports the results of our marine investigations from a historical point of view.

Background: Multiple Sclerosis (MS) is the most prevalent autoimmune neurological condition in the world, leading to a wide variety of symptoms, including balance disorders. Objective: To evaluate the angular vestibulo–ocular reflex (aVOR) of all six semicircular canals (SCCs) through Head Impulse (HIMP) and Suppression HIMP (SHIMP) paradigms and any correlations with clinical balance scales. Methods: All participants were assessed using the Expanded Disability Status Scale (EDSS), Berg Balance Scale (BBS), and Mini-BESTest (MBT). Vestibular function was measured by video Head Impulse Test (vHIT), obtaining aVOR gain for each SSC. Results: Twenty-seven PwMS (mean age 47.93 ± 8.51 years old, 18 females) were recruited. Most of the patients (81.48%) presented abnormal aVOR gains for at least one SSC. A moderate to strong correlation between aVOR gains of the left anterior SSC and, respectively, the MBT and the BBS was found. The subgroup analysis, based on the EDSS class, confirmed the correlation with the BBS in the patients with the most significant disability. Conclusions: People with MS may present impairments of the aVOR in one or more semicircular canals. The aVOR gain impairment of the vertical semicircular canals correlates with balance and gait disorders identified through clinical scales in PwMS.

Background: Interventional radiology techniques have become pivotal in recent years in managing metastatic bone disease, which frequently results in skeletal complications such as fractures and severe pain. Thermoablative methods like radiofrequency ablation (RFA) and microwave ablation (MWA), when combined with vertebroplasty (VP), are proving increasingly beneficial for these patients. Methods: The search was independently conducted by two radiologists on MEDLINE databases, using specified strings up to April 2024. Methodological quality was assessed using PRISMA guidelines. Studies meeting inclusion criteria investigated thermoablation techniques (RFA and/or MWA) combined with VP, focusing on pain management and disease control outcomes in adults. Results: Among 147 results, 42 articles met the criteria, with varied prospective and retrospective designs and sample sizes averaging 49 patients, predominantly involving RFA (30 studies), MWA (11 studies), and one comparative study. Our review highlights significant pain reduction, effective local tumor control, and favorable safety of combined RFA or MWA with VP, supporting its potential in managing vertebral pathologies and warranting further clinical integration. Conclusions: The combined treatment of RFA/MWA with VP demonstrates significant pain reduction and local tumor control, with a rapid onset of analgesic effect. These findings support its crucial role in clinical practice for managing vertebral metastases.

(1) This study evaluates the impact of the CT-guided SIRIO augmented reality navigation system on the procedural efficacy and clinical outcomes of neuroprotection in vertebral thermal ablation (RTA) for primary and metastatic bone tumors. (2) Methods: A retrospective non-randomized analysis of 28 vertebral RTA procedures was conducted, comparing 12 SIRIO-assisted and 16 non-SIRIO-assisted procedures. The primary outcomes included dose-length product (DLP) and epidural dissection time. The secondary outcomes included technical success, complication rates, and pain scores at procedural time (VAS Time 0) and three months post-procedure (VAS Time 1). The statistical analyses included t-tests, Mann–Whitney U tests, and multiple regression. (3) Results: SIRIO-assisted procedures significantly reduced DLP (307.42 mGycm vs. 460.31 mGycm, p = 2.23 × 10−8) and procedural epidural dissection time (13.48 min vs. 32.26 min, p = 2.61 × 10−12) compared to non-SIRIO-assisted procedures. Multiple regression confirmed these reductions were significant (DLP: β = −162.38, p < 0.001; time: β = −18.25, p < 0.001). Pain scores (VAS Time 1) did not differ significantly between groups, and tumor type did not significantly influence outcomes. (4) Conclusions: The SIRIO system enhances neuroprotection efficacy and safety, reducing radiation dose and procedural time during spine tumoral ablation while maintaining consistent pain management outcomes.

In this scoping review, we delve into the transformative potential of artificial intelligence (AI) in addressing challenges inherent in whole-genome sequencing (WGS) analysis, with a specific focus on its implications in oncology. Unveiling the limitations of existing sequencing technologies, the review illuminates how AI-powered methods emerge as innovative solutions to surmount these obstacles. The evolution of DNA sequencing technologies, progressing from Sanger sequencing to next-generation sequencing, sets the backdrop for AI’s emergence as a potent ally in processing and analyzing the voluminous genomic data generated. Particularly, deep learning methods play a pivotal role in extracting knowledge and discerning patterns from the vast landscape of genomic information. In the context of oncology, AI-powered methods exhibit considerable potential across diverse facets of WGS analysis, including variant calling, structural variation identification, and pharmacogenomic analysis. This review underscores the significance of multimodal approaches in diagnoses and therapies, highlighting the importance of ongoing research and development in AI-powered WGS techniques. Integrating AI into the analytical framework empowers scientists and clinicians to unravel the intricate interplay of genomics within the realm of multi-omics research, paving the way for more successful personalized and targeted treatments.

This paper aims to identify methods for optimizing the geometry of dental prosthesis preparation, through both an analytical study and a numerical investigation. Assuming a 10° inclined load with respect to the median sagittal plane, a double algorithm was developed that was capable of calculating the axial resistance area and the cusp resistance area (if present) of a prosthetic abutment as the main geometric parameters vary. In particular, a coupling model with a pseudo-elliptical base was proposed, which is better than the circular shape representing the real shape assumed by the abutment following the dental intervention. The model also allows the presence of a cusp. This model was first analyzed using FEA, also simulating the presence of coupling cement between the abutment and the crown, and then physically made with a 10:1 scale prototype. The convergence of the experimental results found with the numerical–theoretical studies is an indication of the validity of the proposed model. A key contribution of this research using the proposed algorithm allowed to demonstrate that a superior limit of 0.25 for the ratio (HR) between the heights of the cusp sulcus (h-hc) and the abutment (h) is required to achieve good stability of the coupling. The methodology developed in this study is applicable to a variety of teeth, making it versatile and highly adaptable for broader clinical applications.

We used WRF-Chem to simulate ash transport from eruptions of Chile’s Calbuco volcano on 22–23 April 2015. Massive ash and SO2 ejections reached the upper troposphere, and particulates transported over South America were observed over Argentina, Uruguay, and Brazil via satellite and surface data. Numerical simulations with the coupled Weather Research and Forecasting–Chemistry (WRF-Chem) model from 22 to 27 April covered eruptions and particle propagation. Chemical and aerosol parameters utilized the GOCART (Goddard Chemistry Aerosol Radiation and Transport) model, while the meteorological conditions came from NCEP-FNL reanalysis. In WRF-Chem, we implemented a more efficient methodology to determine the Eruption Source Parameters (ESP). This permitted each simulation to consider a sequence of eruptions and a time varying ESP, such as the eruption height and mass and the SO2 eruption rate. We used two simulations (GCTS1 and GCTS2) differing in the ash mass fraction in the finest bins (0–15.6 µm) by 2.4% and 16.5%, respectively, to assess model efficiency in representing plume intensity and propagation. Analysis of the active synoptic components revealed their impact on particle transport and the Andes’ role as a natural barrier. We evaluated and compared the simulated Aerosol Optical Depth (AOD) with VIIRS Deep Blue Level 3 data and SO2 data from Ozone Mapper and Profiler Suite (OMPS) Limb Profiler (LP), both of which are sensors onboard the Suomi National Polar Partnership (NPP) spacecraft. The model successfully reproduced ash and SO2 transport, effectively representing influencing synoptic systems. Both simulations showed similar propagation patterns, with GCTS1 yielding better results when compared with AOD retrievals. These results indicate the necessity of specifying lower mass fraction in the finest bins. Comparison with VIIRS Brightness Temperature Difference data confirmed the model’s efficiency in representing particle transport. Overestimation of SO2 may stem from emission inputs. This study demonstrates the feasibility of our implementation of the WRF-Chem model to reproduce ash and SO2 patterns after a multi-eruption event. This enables further studies into aerosol–radiation and aerosol–cloud interactions and atmospheric behavior following volcanic eruptions.

Electrical stimulation can be used in several applications such as fatigue reduction, muscle rehabilitation, neurorehabilitation, neuro-prosthesis and pain relief. Moreover, electrical stimulation can be used for drug delivery applications or body fluids extraction (e.g., sweat and interstitial fluid) to successively monitor several parameters, such as glucose, lactate, etc. All these applications are performed using electrical stimulator devices capable of applying constant voltage pulses or constant current pulses via electrodes to human tissues. Usually, constant current stimulators are most widely used because of their safety, stability, and repeatability. Thus, the aim of this work was to design, realize and test a mixed-signal electronic interface capable of producing current pulses with custom amplitude, duration, frequency, polarity and symmetry with extended voltage compliance. To achieve this result, we developed a high-voltage current stimulator suitable for iontophoresis applications. Current stimuli can be applied setting the intensity, frequency and duty cycle of the stimulation patterns through a µC. A custom electronic interface was designed to allow the control of the injected current in real time and to prevent electrical injuries to the patient by avoiding potential unwanted short circuits. Moreover, the system was tested in a simulated environment demonstrating its effectiveness and applicability for transdermal monitoring applications. The obtained results show that the device is able to apply monophasic and biphasic pulses, ranging from 0.1 to 10 mA, with a maximum error of about 10% at the minimum intensity; in addition, current stimuli can be applied up to a maximum frequency of 100 kHz with a voltage compliance of 120 V.

This study presents an evaluation of the CHIMBO modeling chain applied to the Italian domain, specifically focusing on the Po Valley subdomain over the one-year period of 2019. The comparison between simulated and observed data indicates that the performance of the CHIMBO model aligns well with existing literature on other state-of-the-art models. The results demonstrate that the CHIMBO chain is particularly effective for regional-scale quantitative assessments of pollutant distribution, comparable to that of CAMS ensemble models. The analysis of key chemical species in particulate matter reveals that the CHIMBO model accurately represents the average concentrations of organic and elemental carbon, as well as secondary inorganic compounds (sulfate, nitrate, and ammonium), particularly at background monitoring stations in the flat terrain of the Po Valley, with the exception of Aosta, a city located at about 500 m asl. However, seasonal discrepancies were identified, especially during winter months, when significant underestimations were observed for several species, including elemental and organic carbon, predominantly at background sites. These underestimations are likely attributed to various factors: (i) inadequate estimations of primary emissions, particularly from domestic heating; (ii) the limited effectiveness of secondary formation processes under winter conditions characterized by low photochemical activity and high humidity; and (iii) excessive dilution of pollutants during calm wind conditions due to overestimation of wind intensity. In conclusion, while the CHIMBO modeling chain serves as a robust tool for mesoscale atmospheric composition investigations, limitations persist related to emissions inventories and meteorological parameters, which remain critical drivers of atmospheric processes.

Candida auris is an emerging yeast considered a serious threat to global health. We report the first case of C. auris candidemia in Southern Italy, characterized using whole genome sequencing (WGS), and compared with a second strain isolated from a patient who presented as C. auris-colonized following screening. The C. auris strain was isolated from clinical samples, identified via MALDI-TOF, and subjected to WGS. Antifungal susceptibility testing was performed using commercial broth microdilution plates, and resistance protein sequences were evaluated with TBLASTN-2.15.0. Following the initial C. auris isolation from patient A, active surveillance and environmental investigations were implemented for all ICU patients. Of the 26 ICU surfaces sampled, 46.1% tested positive for C. auris via real-time PCR. Screening identified a second patient (patient B) as C. auris-colonized. The phylogenetic characterization of strains from patients A and B, based on the D1/D2 region of the 28s rDNA and the internal transcribed spacer (ITS) region, showed high similarity with strains from Lebanon. SNP analysis revealed high clonality, assigning both strains to clade I, indicating a significant similarity with Lebanese strains. This case confirms the alarming spread of C. auris infections and highlights the need for stringent infection control measures to manage outbreaks.

Background and Objectives: In patients with severe aortic stenosis (AS), left ventricular systolic dysfunction is one of the main predictors of adverse events after surgical aortic valve replacement (SAVR). However, more patients undergo surgery earlier, often with preserved systolic function. In these cases, global longitudinal strain (GLS) has been proposed as a marker of ventricular remodeling post-surgery. This study aims to evaluate GLS variation in patients undergoing SAVR and explore differences across the diastolic dysfunction classes. Methods: From June 2020 to March 2023, patients with AS and preserved ejection fraction (EF) requiring SAVR were enrolled. Echocardiographic evaluations were conducted preoperatively, seven days post-surgery, and twelve months after surgery. Patients were divided into two groups based on the severity of diastolic dysfunction: Group A (grade I) and Group B (grades II–III). Results: The final analysis included 108 patients (mean age 71.3 ± 7.2 years). Twenty-two patients (20.4%) also underwent coronary artery bypass grafting (CABG). The preoperative EF averaged 61.6 ± 6.03%, with no significant differences between groups. Preoperative GLS was 16 ± 4.3%, decreasing to 12.8 ± 3.4% postoperatively (p < 0.0001). GLS was comparable between the groups preoperatively (p = 0.185) and postoperatively (0.854). After twelve months, GLS improved in both groups (Group A: 17.7 ± 3.4%, Group B: 15.7 ± 3.2%, p < 0.0001), but only Group A showed significant improvement from preoperative values (p = 0.018). SAVR improved GLS regardless of CABG intervention. Conclusions: SAVR in patients with preserved LVEF results in an early reduction in GLS, regardless of diastolic dysfunction. After twelve months, GLS improved significantly, with significant recovery only in patients with mild dysfunction.

Active life monitoring via chemosensitive sensors could hold promise for enhancing athlete monitoring, training optimization, and performance in athletes. The present work investigates a resistive flex sensor (RFS) in the guise of a chemical sensor. Its carbon ‘texture’ has shown to be sensitive to CO2, O2, and RH changes; moreover, different bending conditions can modulate its sensitivity and selectivity for these gases and vapors. A three-step feasibility study is presented including: design and fabrication of the electronic read-out and control; calibration of the sensors to CO2, O2 and RH; and a morphological study of the material when interacting with the gas and vapor molecules. The 0.1 mm−1 curvature performs best among the tested configurations. It shows a linear response curve for each gas, the ranges of concentrations are adequate, and the sensitivity is good for all gases. The curvature can be modulated during data acquisition to tailor the sensitivity and selectivity for a specific gas. In particular, good results have been obtained with a curvature of 0.1 mm−1. For O2 in the range of 20–70%, the sensor has a sensitivity of 0.7 mV/%. For CO2 in the range of 4–80%, the sensitivity is 3.7 mV/%, and for RH the sensitivity is 33 mV/%. Additionally, a working principle, based on observation via scanning electron microscopy, has been proposed to explain the chemical sensing potential of this sensor. Bending seems to enlarge the cracks present in the RFS coverage; this change accounts for the altered selectivity depending on the sensor’s curvature. Further studies are needed to confirm result’s reliability and the correctness of the interpretation.

Monitoring heart rate (HR) through photoplethysmography (PPG) signals is a challenging task due to the complexities involved, even during routine daily activities. These signals can indeed be heavily contaminated by significant motion artifacts resulting from the subjects’ movements, which can lead to inaccurate heart rate estimations. In this paper, our objective is to present an innovative necklace sensor that employs low-computational-cost algorithms for heart rate estimation in individuals performing non-abrupt movements, specifically drivers. Our solution facilitates the acquisition of signals with limited motion artifacts and provides acceptable heart rate estimations at a low computational cost. More specifically, we propose a wearable sensor necklace for assessing a driver’s well-being by providing information about the driver’s physiological condition and potential stress indicators through HR data. This innovative necklace enables real-time HR monitoring within a sleek and ergonomic design, facilitating seamless and continuous data gathering while driving. Prioritizing user comfort, the necklace’s design ensures ease of wear, allowing for extended use without disrupting driving activities. The collected physiological data can be transmitted wirelessly to a mobile application for instant analysis and visualization. To evaluate the sensor’s performance, two algorithms for estimating the HR from PPG signals are implemented in a microcontroller: a modified version of the mountaineer’s algorithm and a sliding discrete Fourier transform. The goal of these algorithms is to detect meaningful peaks corresponding to each heartbeat by using signal processing techniques to remove noise and motion artifacts. The developed design is validated through experiments conducted in a simulated driving environment in our lab, during which drivers wore the sensor necklace. These experiments demonstrate the reliability of the wearable sensor necklace in capturing dynamic changes in HR levels associated with driving-induced stress. The algorithms integrated into the sensor are optimized for low computational cost and effectively remove motion artifacts that occur when users move their heads.

The problem of Power Quality analysis is becoming crucial to ensuring the proper functioning of complex systems and big plants. In this regard, it is essential to rapidly detect anomalies in voltage and current signals to ensure a prompt response and maximize the system’s availability with the minimum maintenance cost. In this paper, anomaly detection algorithms based on machine learning, such as One Class Support Vector Machine (OCSVM), Isolation Forest (IF), and Angle-Based Outlier Detection (ABOD), are used as a first tool for rapid and effective clustering of the measured voltage and current signals directly on-line on the sensing unit. If the proposed anomaly detection algorithm detects an anomaly, further investigations using suitable classification algorithms are required. The main advantage of the proposed solution is the ability to rapidly and efficiently detect different types of anomalies with low computational complexity, allowing the implementation of the algorithm directly on the sensor node used for signal acquisition. A suitable experimental platform has been established to evaluate the advantages of the proposed method. All the different models were tested using a consistent set of hyperparameters and an output dataset generated from the principal component analysis technique. The best results achieved included models reaching 100% recall and a 92% F1 score.

The aim of this research is to propose simple and scalable processes to obtain bioactive peptides extensively hydrolyzed starting from a tuna mixed biomass. The upcycling of this powdered biomass is challenging since it comes from the unsorted industrial side streams of the tuna canning process (cooked residues from fillet trimming) after a patented mild dehydration useful for preventing its degradation until its exploitation. Two different protocols were proposed, with and without the inclusion of an exogenous enzyme (Enzymatic-Assisted Extraction, EAE), with no relevant differences in yields (24% vs. 22%) and a comparable amino acid composition. Nevertheless, the former protocol (with EAE) provided peptides with an average molecular weight of 1.3 kDa, and the second one (without EAE) provided peptides with an average molecular weight of 2.2 kDa. The two corresponding types of tuna protein hydrolysates (Enzymatic Hydrolysates (EH) and Non-Enzymatic Hydrolysates (NEH)) were characterized by proximate compositions, pH, color profile, amino acid analysis, FTIR spectra, and molecular weight distribution. In addition, several biological analyses were performed to assess their potential use as nutraceutical supplements: special attention has been paid to antioxidant activity using three different methods to quantify it. EH showed the most promising antioxidant activity which could be exploited also in other fields (e.g., biomaterials, cosmetics).

The aim of this study is to identify autism spectrum disorder (ASD) and attention-deficit–hyperactivity disorder (ADHD) traits in adolescents who experience psychotic-like experiences (PLEs), often ignored in clinical practice but widely prevalent in the general population. A total of 57 adolescents and young adults (aged between 16 and 24 years old) were recruited consecutively in the outpatient services. A total of 37 were females (64.9%), 18 were males (31.6%), and two participants (3.5%) were non-binary or gender non-conforming, with a mean age at referral of 18.26 ± 2.06. To investigate these symptoms, three sets of standardized questionnaires were used, as follows: the Autism Spectrum Quotient–short form (AQ-10), the Community Assessment of Psychic Experiences (CAPE-42), and the Adult ADHD Self-Report Scale (ASRS). We found significant associations between the ASRS and AQ-10 total scores and all CAPE scales. The model which explained the highest variance was CAPE Score’s Total Frequency score (p < 0.001). Our findings underline the importance of investigating the presence of subthreshold ASD and ADHD symptoms in clinical populations, particularly in the period of adolescence and young adulthood, to promptly identify the presence of PLEs and, thus, prevent the onset of a frank psychotic disorder, particularly in the presence of a comorbid psychopathological condition, leading to better diagnosis and treatment for individuals with two or more of these conditions.

Glycopyrrolate is a competitive muscarinic receptor antagonist used in the treatment of sialorrhea, especially in pediatrics. Degradation research was conducted to better understand the stability of the active pharmaceutical ingredient (API). Using an HPLC-UV method, we evaluated the chemical stability of the oral solution of the galenic compound glycopyrrolate 0.5 mg/mL under different storage conditions. Method validation was performed according to the International Council for Harmonization (ICH) Q2(R2) guidelines. The results of the stability study of the galenic compound in different storage conditions, with the exception of those stored in glass containers at 45 °C for more than 3 months, were stable (100 ± 10% of the nominal concentration). The aim of this work was to study the stability of the galenic compound glycopyrrolate in two different types of containers and at three different storage temperatures. Glycopyrrolate showed degradation beyond the limits only in glass at 45 °C and after 2 months of storage. The results indicate that oral liquid dosage forms of glycopyrrolate are stable for at least 210 days when stored at room temperature or at 4 °C, in glass or PET, for at least 7 months, maintaining product quality according to the standards established by the European Pharmacopoeia, ensuring long-term coverage for pediatric patient therapies.

Liver fibrosis, a major global health issue, is marked by excessive collagen deposition that impairs liver function. Noninvasive methods for the direct visualization of collagen content are crucial for the early detection and monitoring of fibrosis progression. This study investigates the potential of spectral photoacoustic imaging (sPAI) to monitor collagen development in liver fibrosis. Utilizing a novel data-driven superpixel photoacoustic unmixing (SPAX) framework, we aimed to distinguish collagen presence and evaluate its correlation with fibrosis progression. We employed an established diethylnitrosamine (DEN) model in rats to study liver fibrosis over various time points. Our results revealed a significant correlation between increased collagen photoacoustic signal intensity and advanced fibrosis stages. Collagen abundance maps displayed dynamic changes throughout fibrosis progression. These findings underscore the potential of sPAI for the noninvasive monitoring of collagen dynamics and fibrosis severity assessment. This research advances the development of noninvasive diagnostic tools and personalized management strategies for liver fibrosis.

In 1979, NASA established the Great Observatory program, which included four telescopes (Hubble, Compton, Chandra, and Spitzer) to explore the Universe. The Spitzer Space Telescope was launched in 2003 into solar orbit, gradually drifting away from the Earth. Spitzer was operated very successfully until 2020 when NASA terminated observations and placed the telescope in safe mode. In 2028, the U.S. Space Force has the opportunity to demonstrate satellite servicing by telerobotically reactivating Spitzer for astronomical observations, and in a separate experiment, carry out novel Space Weather research and operations capabilities by observing solar Coronal Mass Ejections. This will be accomplished by launching a small satellite, the Spitzer-Resurrector Mission (SRM), to rendezvous with Spitzer in 2030, positioning itself around it, and serving as a relay for recommissioning and science operations. A sample of science goals for Spitzer is briefly described, but the focus of this paper is on the unique opportunity offered by SRM to demonstrate novel Space Weather research and operations capabilities.

Background: The craniovertebral junction is a complex region, connecting the occiput, the atlas, the axis, and the containing vital neural and vascular structures. There is a great variability in diseases involving the craniovertebral junction, of different nature, each rare in frequency. Methods: We conducted a retrospective chart review of the patients diagnosed with extremely rare pathologies of the craniovertebral junction that we have operated in the last 5 years. Results: After excluding the relatively more frequent pathologies, we identified nine cases of rare craniovertebral junction pathologies. Six were operated using an endoscopic endonasal approach, two using a far lateral transcranial approach, and one underwent a C1 hemilaminectomy. Conclusions: Diagnosis and management of the rare pathologies of the craniovertebral junction are challenging. A multidisciplinary approach is recommended for the proper management of these patients.

The aim of this study is to report the authors’ experience of percutaneous transarterial embolization (TAE) in patients with spontaneous soft tissue hematomas (SSTH) and active bleeding with anticoagulation impairment. The study retrospectively identified 78 patients who received a diagnosis of SSTH by CT scan and underwent TAE between 2010 and 2019 in a single trauma center. The patients were stratified using Popov classification into categories: 2A, 2B, 2C, and 3. The patient’s 30-day survival after TAE was considered the primary outcome; immediate technical success, the need for additional TAE, and TAE-related complications were considered secondary outcomes. Immediate technical success, complication rate, and risk factors for death were analyzed. Follow-up stopped on day 30 from TAE. 27 patients (35%) fell into category 2A, 8 (10%) into category 2B, 4 (5%) into category 2C, and 39 (50%) into category 3. Immediate technical success was achieved in 77 patients (98.7%). Complications included damage at the arterial puncture site (2 patients, 2.5%) and acute kidney injury (24 patients, 31%). Only 2 patients (2.5%) had been discharged with a new diagnosis of chronic kidney disease. The 30-day overall mortality rate was 19% (15 patients). The mortality rate was higher in hemodynamically unstable patients, in Popov categories 2B, 2C, and 3, and in patients with an initial eGFR < 30 mL/min × 1.73 m2. The study demonstrated a higher mortality risk for categories 2B, 2C, and 3 compared to category 2A. Nonetheless, TAE has proven effective and safe in type 2A patients. Even though it is unclear whether type 2A patients could benefit from conservative treatment rather than TAE, in the authors’ opinion, a TAE endovascular approach should be promptly considered for all patients in ACT with active bleeding demonstrated on CT scans.

Utilizing plant-based resources, particularly their by-products, aligns with sustainability principles and circular bioeconomy, contributing to environmental preservation. The therapeutic potential of plant extracts is garnering increasing interest, and this study aimed to demonstrate promising outcomes from an extract obtained from an underutilized plant waste. Chaetomorpha linum, an invasive macroalga found in the Orbetello Lagoon, thrives in eutrophic conditions, forming persistent mats covering approximately 400 hectares since 2005. The biomass of C. linum undergoes mechanical harvesting and is treated as waste, requiring significant human efforts and economic resources—A critical concern for municipalities. Despite posing challenges to local ecosystems, the study identified C. linum as a natural source of bioactive metabolites. Phytochemical characterization revealed lipids, amino acids, and other compounds with potential anti-inflammatory activity in C. linum extract. In vitro assays with LPS-stimulated RAW 264.7 and TNF-α/IFN-γ-stimulated HaCaT cells showed the extract inhibited reactive oxygen species (ROS), nitric oxide (NO), and prostaglandin E2 (PGE2) productions, and reduced inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expressions via NF-κB nuclear translocation, in RAW 264.7 cells. It also reduced chemokines (TARC/CCL17, RANTES/CCL5, MCP-1/CCL2, and IL-8) and the cytokine IL-1β production in HaCaT cells, suggesting potential as a therapeutic candidate for chronic diseases like atopic dermatitis. Finally, in silico studies indicated palmitic acid as a significant contributor to the observed effect. This research not only uncovered the untapped potential of C. linum but also laid the foundation for its integration into the circular bioeconomy, promoting sustainable practices, and innovative applications across various industries.

Despite cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) being the current gold standard for non-invasive myocardial characterization and fibrosis quantification, its accessibility is limited, particularly in acute settings and in certain patient populations with contraindications to magnetic resonance imaging. Late iodine enhancement (LIE) in computed tomography (CT) imaging has emerged as a potential alternative, capitalizing on the similarities in the contrast kinetics between gadolinium and iodinated contrast agents. Studies have investigated LIE-CT’s effectiveness in myocardial infarction (MI) detection, revealing promising outcomes alongside some disparities compared to LGE-CMR. LIE-CT also proves beneficial in diagnosing non-ischemic heart diseases such as myocarditis, hypertrophic cardiomyopathy, and sarcoidosis. While LIE-CT demonstrates good accuracy in detecting certain myocardial pathologies, including acute MI and chronic fibrotic changes, it has limitations, such as the inability to detect diffuse myocardial enhancement. Nonetheless, thanks to the availability of optimized protocols with minimal radiation doses and contrast medium administration, integrating LIE-CT into cardiac CT protocols could enhance its clinical utility, particularly in acute settings, providing valuable prognostic and management insights across a spectrum of cardiac ischemic and non-ischemic conditions.

The enzymatic extraction of proteins from fish biomasses is being widely investigated. However, little or almost no research has paid attention to the exploitation of unsorted fishery biomasses. This work is part of a larger study, Part I of which has already been published, and focuses on an extensive characterization of two collagenous samples, namely gelatin (G) and hydrolyzed gelatin peptides (HGPs), extracted from a dehydrated fish biomass coming from unsorted canned yellowfin tuna side streams. The results indicate crude protein fractions of 90–93%, pH values between 3 and 5, white–yellow colors, collagen-like FTIR spectra, and 17% in terms of total amino acid content. Viscosity and the study of dynamic viscous–elastic behavior were analyzed. Thermo-gravimetric analysis was performed to assess the residual ashes. Both samples were investigated to determine their molecular weight distribution via size-exclusion chromatography, with a higher total average molecular weight for G compared to HGPs, with values of 17,265.5 Da and 2637.5 Da, respectively. G demonstrated technological properties similar to analogous marine gelatins. HGPs demonstrated antioxidant activity as per FRAP assay. All the results open up new perspectives for the potential use of these substances in biodegradable packaging, dietary supplements, and skin care cosmetics.

Fully coupled soil–structure analyses were performed for a building of strategic importance located in the city of Messina (Sicily, Italy). The structure was built after the destructive 1908 earthquake, also known as the ‘Messina and Reggio Calabria earthquake’, which caused severe ground shaking. A parametric study considering three seismograms of this earthquake was performed. Deep in situ and laboratory investigations allowed the definition of the geometric and geotechnical model of the subsoil. Numerical analyses were performed with PLAXIS3D finite element software (Version 21.01.00.479). The Hardening Soil model with small-strain stiffness was accurately calibrated using laboratory and field data. The dynamic response was investigated in terms of accelerations, response spectra, amplification functions, displacements and stress–strain hysteretic loops. The findings show that many aspects must be investigated for the retrofitting of buildings with shallow foundation in areas characterized by a medium to high level of seismic risk: (i) a key role is played by an accurate investigation of the soil; taking into account the specific conditions of the soil, it was possible to investigate its filtering effects; (ii) the dynamic response of the fully-coupled soil–structure system deviates from the free field-site response analysis; (iii) the results reveal the importance of considering the soil nonlinearity in seismic soil–structure interaction problems.

Modern “omics” sciences, including metabolomics and microbiomics, are currently being applied to inflammatory autoimmune diseases, such as rheumatoid arthritis (RA), to investigate the interplay between microbiota, metabolic function, and the immune system. In recent decades, robust evidence has suggested that disruption of the normal composition of the microbiome, known as dysbiosis, in the gut and mouth of RA patients contributes to immune dysregulation and alterations in the metabolic pathways, shaping the pathogenesis of the disease and playing a central role in the risk and progression of RA. Metabolic pathways can be influenced by various agents such as the surrounding environment, lifestyle, and exposure to microbiota imbalance. In turn, the body’s metabolic homeostasis influences the immune response, making metabolomics helpful not only to understand pathogenesis pathways, but also to improve early disease detection and therapeutic chances. Combined gut microbiome and metabolome studies set out to unravel the interactions between these two entities, providing insights to discover new treatment targets and potential biomarkers to prevent joint damage. The purpose of this review is to summarize the main recent findings that suggest promising new research directions for the pathogenesis of RA.

Hepaticojejunostomy is an essential component of many surgical procedures, including pancreaticoduodenectomy. Biliary leaks after HJS represent a major complication leading to relevant clinical problems: the postoperative mortality rate could reach 70% for surgical re-intervention, whereas endoscopic management is technically difficult due to the postoperative anatomy. Interventional Radiology plays a pivotal role for these patients. The case of a percutaneous biliary rendez-vous procedure performed to treat an HJA dehiscence after duodeno-cephalo-pancreasectomy is presented, which is successfully guaranteed to avoid a new surgical approach.

Achieving the highest levels of compliance with the FAIR (findable, accessible, interoperable, reusable) principles for scientific data management and stewardship requires machine-actionable semantic representations of data and metadata. Human and machine interpretation and reuse of measurement datasets rely on metrological information that is often specified inconsistently or cannot be inferred automatically, while several ontologies to capture the metrological information are available, practical implementation examples are few. This work aims to close this gap by discussing how standardised measurement data and metadata could be presented using semantic web technologies. The examples provided in this paper are machine-actionable descriptions of Earth observation and bathymetry measurement datasets, based on two ontologies of quantities and units of measurement selected for their prominence in the semantic web. The selected ontologies demonstrated a good coverage of the concepts related to quantities, dimensions, and individual units as well as systems of units, but showed variations and gaps in the coverage, completeness and traceability of other metrology concept representations such as standard uncertainty, expanded uncertainty, combined uncertainty, coverage factor, probability distribution, etc. These results highlight the need for both (I) user-friendly tools for semantic representations of measurement datasets and (II) the establishment of good practices within each scientific community. Further work will consequently investigate how to support ontology modelling for measurement uncertainty and associated concepts.

Background: The aim of our study was to develop a radiomic tool for the prediction of clinically significant prostate cancer. Methods: From September 2020 to December 2021, 91 patients who underwent magnetic resonance imaging prostate fusion biopsy at our institution were selected. Prostate cancer aggressiveness was assessed by combining the three orthogonal planes-Llocal binary pattern the 3Dgray level co-occurrence matrix, and other first order statistical features with clinical (semantic) features. The 487 features were used to predict whether the Gleason score was clinically significant (≥7) in the final pathology. A feature selection algorithm was used to determine the most predictive features, and at the end of the process, nine features were chosen through a 10-fold cross validation. Results: The feature analysis revealed a detection accuracy of 83.5%, with a clinically significant precision of 84.4% and a clinically significant sensitivity of 91.5%. The resulting area under the curve was 80.4%. Conclusions: Radiomic analysis allowed us to develop a tool that was able to predict a Gleason score of ≥7. This new tool may improve the detection rate of clinically significant prostate cancer and overcome the limitations of the subjective interpretation of magnetic resonance imaging, reducing the number of useless biopsies.

Background: For selected women diagnosed with breast cancer (BC), partial reconstructive techniques involve displacement or replacement procedures to improve cosmesis without compromising oncological safety. This study aims to evaluate the surgical outcomes of the round block (RB) compared with the subaxillary flap (SF) technique for patients with upper outer tumor. Patients and Methods: Thirty-three patients treated with oncoplastic conserving surgery (15 RB and 18 SF) were enrolled in this retrospective study. After carrying out a comparison of baseline characteristics, all cases were recruited for postoperative evaluation of oncological and cosmetic parameters. Moreover, we investigated several scoring combinations to check whether they could discriminate surgeon and patient satisfaction according to different functional results. Results: Median age (p < 0.05), average tumor size (p > 0.05), estimated resection volume (p > 0.05), and nodal involvement (p > 0.05) were slightly higher in the SF group. A greater frequency of DCIS (p < 0.05) in the RB series correlated with reintervention for positive margins (p > 0.001). At a mean follow-up of 19 months, no locoregional recurrences were recorded and early and late complications were comparable (p > 0.05). The overall satisfaction with cosmesis was characterized by similar proportions of good results (p > 0.05), with some details more related to each procedure. Conclusion: The proposed techniques represent effective solutions for reshaping that follows upper outer wide excision, achieving comparable complication rates, low reinterventions, and good aesthetic results in relation to technical and social functioning evaluations. However, it is crucial to establish a careful patient selection in order to manage correct surgical planning while predicting any potential sequelae or complication.

Today, ground control points (GCPs) represent indispensable tools for products’ georeferencing in all the techniques concerning remote sensing (RS), particularly in monitoring activities from unmanned aircraft system (UAS) platforms. This work introduces an innovative tool, smart GCPs, which combines different georeferencing procedures, offering a range of advantages. It can serve three fundamental purposes concurrently: (1) as a drone takeoff platform; (2) as a base station, allowing the acquisition of raw global navigation satellite system (GNSS) data for post-processed kinematic (PPK) surveys or by providing real-time GNSS corrections for precision positioning; (3) as a rover in the network real-time kinematic (NRTK) mode, establishing its position in real time with centimetric precision. The prototype has undergone testing in a dedicated study area, yielding good results for all three geodetic correction techniques: PPK, RTK, and GCP, achieving centimeter-level accuracy. Nowadays, this versatile prototype represents a unique external instrument, which is also easily transportable and able to connect to the GNSS RING network, obtaining real-time positioning corrections for a wide range of applications that require precise positioning. This capability is essential for environmental applications that require a multitemporal UAS-based study. When the real-time RING data are accessible to the scientific community operating in RS surveying, this work could be a helpful guide for researchers approaching such investigations.

Breast cancer remains the most prevalent cancer among women worldwide, necessitating advancements in diagnostic methods. The integration of artificial intelligence (AI) into mammography has shown promise in enhancing diagnostic accuracy. However, understanding patient perspectives, particularly considering the psychological impact of breast cancer diagnoses, is crucial. This narrative review synthesizes literature from 2000 to 2023 to examine breast cancer patients’ attitudes towards AI in breast imaging, focusing on trust, acceptance, and demographic influences on these views. Methodologically, we employed a systematic literature search across databases such as PubMed, Embase, Medline, and Scopus, selecting studies that provided insights into patients’ perceptions of AI in diagnostics. Our review included a sample of seven key studies after rigorous screening, reflecting varied patient trust and acceptance levels towards AI. Overall, we found a clear preference among patients for AI to augment rather than replace the diagnostic process, emphasizing the necessity of radiologists’ expertise in conjunction with AI to enhance decision-making accuracy. This paper highlights the importance of aligning AI implementation in clinical settings with patient needs and expectations, emphasizing the need for human interaction in healthcare. Our findings advocate for a model where AI augments the diagnostic process, underlining the necessity for educational efforts to mitigate concerns and enhance patient trust in AI-enhanced diagnostics.

The production of “Nocciola Romana” hazelnuts in the province of Viterbo, Italy, has evolved into a highly efficient and profitable agro-industrial system. Our approach is based on a hierarchical framework utilizing aggregated data from multiple temporal data and sources, offering valuable insights into the spatial, temporal, and phenological distributions of hazelnut crops To achieve our goal, we harnessed the power of Google Earth Engine and utilized collections of satellite images from Sentinel-2 and Sentinel-1. By creating a dense stack of multi-temporal images, we precisely mapped hazelnut groves in the area. During the testing phase of our model pipeline, we achieved an F1-score of 99% by employing a Hierarchical Random Forest algorithm and conducting intensive sampling using high-resolution satellite imagery. Additionally, we employed a clustering process to further characterize the identified areas. Through this clustering process, we unveiled distinct regions exhibiting diverse spatial, spectral, and temporal responses. We successfully delineated the actual extent of hazelnut cultivation, totaling 22,780 hectares, in close accordance with national statistics, which reported 23,900 hectares in total and 21,700 hectares in production for the year 2022. In particular, we identified three distinct geographic distribution patterns of hazelnut orchards in the province of Viterbo, confined within the PDO (Protected Designation of Origin)-designated region. The methodology pursued, using three years of aggregate data and one for SAR with a spectral separation clustering hierarchical approach, has effectively allowed the identification of the specific perennial crop, enabling a deeper characterization of various aspects influenced by diverse environmental configurations and agronomic practices.The accurate mapping and characterization of hazelnut crops open opportunities for implementing precision agriculture strategies, thereby promoting sustainability and maximizing yields in this thriving agro-industrial system.

(1) Background: Gangliogliomas are rare tumors accounting for about 0.4% of all central nervous system tumors. They are usually located in the temporal lobes of children and young adults, though such tumors in the infratentorial region and adult-age patients rarely reported. (2) Methods: A systematic review on ganglioglioma with infratentorial location in the adult population was conducted in accordance with the PRISMA guidelines. A total of 275 articles were found, and 23 were included. Demographic data, the location and histology of the lesion, pre-operative neurological status, the type of surgery, recurrence, radiotherapy/chemotherapy adjuvant treatments, neurological outcomes and follow-up information were collected. We also presented an illustrative case. (3) Results: A total of 27 patients were included. In 51%, the location was the cerebellum; in 40%, it was the fourth ventricle; in 11%, it was brainstem; and in 4%, it was the cerebellopontine angle. STR was performed in 44%, GTR in 26% and biopsy in 15% of the cases. Adjuvant radiotherapy was found in 22% of cases. Disease recurrence occurred in 15% of patients between 1 and 12 months after surgery with a diagnosis of high-grade ganglioglioma, while in six cases, no disease recurrence was documented. (4) Conclusions: Infratentorial glioneuronal tumors are rare findings in the adult population. Histopathological characterization does not seem to fully reflect their true behavior. Future studies are warranted for better characterizing histopathological findings and treatment.

Liver transplantation (LT) has significantly transformed the prognosis of patients with end-stage liver disease and hepatocellular carcinoma (HCC). The traditional epidemiology of liver diseases has undergone a remarkable shift in indications for LT, marked by a decline in viral hepatitis and an increase in metabolic dysfunction-associated steatotic liver disease (MASLD), along with expanded indications for HCC. Recent advancements in surgical techniques, organ preservation and post-transplant patients’ management have opened new possibilities for LT. Conditions that were historically considered absolute contraindications have emerged as potential new indications, demonstrating promising results in terms of patient survival. While these expanding indications provide newfound hope, the ethical dilemma of organ scarcity persists. Addressing this requires careful consideration and international collaboration to ensure equitable access to LT. Multidisciplinary approaches and ongoing research efforts are crucial to navigate the evolving landscape of LT. This review aims to offer a current overview of the primary emerging indications for LT, focusing on acute-on-chronic liver failure (ACLF), acute alcoholic hepatitis (AH), intrahepatic and perihilar cholangiocarcinoma (i- and p-CCA), colorectal liver metastasis (CRLM), and neuroendocrine tumor (NET) liver metastases.

Ribociclib plus an aromatase inhibitor and ovarian function suppression is the preferred first-line option for pre-/perimenopausal women with hormone receptor-positive/human epidermal growth factor receptor-2-negative advanced or metastatic breast cancer. We opened an italian managed access program (MAP) that permitted access to ribociclib to selected patients and allowed to collect informative results on the clinical impact of the therapy. The MAP (April 2018–May 2020) included 64 premenopausal patients, with characteristics similar to those of the MONALEESA-7 trial. Of 57 patients with a known response, 48 (84.2%) achieved a clinical benefit (i.e., complete response, N = 7 (12.3%); partial response, N = 17 (29.8%); stable disease, N = 24 (42.1%)), while 9 (15.8%) experienced tumor progression. Some patients (N = 15–23.4%) needed ribociclib dose reduction because of adverse events. Thereafter, the treatment was well tolerated, and no new safety signals emerged. Our study is the first reported Italian real-world evidence of ribociclib effectiveness in premenopausal HR+/HER2− advanced breast cancer patients. Response and clinical benefit rates were particularly encouraging compared with those of the ribociclib group of MONALEESA-7. Our work confirms that ribociclib in combination with endocrine therapy is highly effective in the treatment of premenopausal HR+/HER2− advanced breast cancer patients with an expected safety profile.

Background: To evaluate the clinical utility of an Artificial Intelligence (AI) radiology solution, Quantib Prostate, for prostate cancer (PCa) lesions detection on multiparametric Magnetic Resonance Images (mpMRI). Methods: Prostate mpMRI exams of 108 patients were retrospectively studied. The diagnostic performance of an expert radiologist (>8 years of experience) and of an inexperienced radiologist aided by Quantib software were compared. Three groups of patients were assessed: patients with positive mpMRI, positive target biopsy, and/or at least one positive random biopsy (group A, 73 patients); patients with positive mpMRI and a negative biopsy (group B, 14 patients), and patients with negative mpMRI who did not undergo biopsy (group-C, 21 patients). Results: In group A, the AI-assisted radiologist found new lesions with positive biopsy correlation, increasing the diagnostic PCa performance when compared with the expert radiologist, reaching an SE of 92.3% and a PPV of 90.1% (vs. 71.7% and 84.4%). In group A, the expert radiologist found 96 lesions on 73 mpMRI exams (17.7% PIRADS3, 56.3% PIRADS4, and 26% PIRADS5). The AI-assisted radiologist found 121 lesions (0.8% PIRADS3, 53.7% PIRADS4, and 45.5% PIRADS5). At biopsy, 33.9% of the lesions were ISUP1, 31.4% were ISUP2, 22% were ISUP3, 10.2% were ISUP4, and 2.5% were ISUP5. In group B, where biopsies were negative, the AI-assisted radiologist excluded three lesions but confirmed all the others. In group-C, the AI-assisted radiologist found 37 new lesions, most of them PIRADS 3, with 32.4% localized in the peripherical zone and 67.6% in the transition zone. Conclusions: Quantib software is a very sensitive tool to use specifically in high-risk patients (high PIRADS and high Gleason score).

In this paper, the design of a new laminar shear box at the Laboratory of Earthquake Engineering and Dynamic Analysis (L.E.D.A.) of the University of Enna “Kore” (Sicily, Italy), is presented. The laminar box has been developed to investigate the liquefaction phenomenon and to validate advanced numerical models and/or the numerical approaches assessed to simulate and prevent related effects. The first part of the paper describes in detail the types of soil containers that have been used in the last three decades around the world. Particular attention is paid to laminar shear box and liquefaction studies. Moreover, the most important factors that affect the performance of a laminar shear box are reported. The last part of the paper describes components, properties, and design advantages of the new laminar shear box for 1g shaking table tests at L.E.D.A. The new laminar box has a rectangular cross section and consists of 16 layers. Each layer is composed of two frames: an inner frame and an outer frame. The inner frame has an internal dimension of 2570 mm by 2310 mm, while the outer frame has an internal dimension of 2700 mm by 2770 mm. Between the layers, there is a 20 mm gap, making the total height 1600 mm.

This paper is concerned with a morphological-stylistic and archaeometric study of two small pottery statues, confiscated by the Cosenza Carabinieri Unit for the Protection of Cultural Heritage and Anti-Counterfeiting (Calabria, Italy). The research aimed to establish the authenticity of the artworks and to verify a possible origin from the same workshop manufacturing, by providing indications about the textural features and raw materials used for their production. For these purposes, the analytical approach involved the use of minero-petrographic and physical analysis, as follows: petrographic analysis (OM), X-ray diffraction (XRD) and thermoluminescence tests (TL). The preliminary observation, which highlights differences in the stylistic features of the two statuettes as well as in the color, morphology and distribution of the white-greyish patina, is further confirmed by the TL investigations. The TL test revealed an ancient production only for one of the analyzed finds and the investigations on the raw materials allowed to relate this to a possible local historical-artistic context. The second statuette, on the other hand, is attributable to a modern production as confirmed by TL measurement.

Electromagnetic compatibility issues must be considered from the early steps in the design of electronic devices. A specific topic is the near-field emission generated by the device due to the traces on a printed circuit board and the specific routing. The analysis of near-field emission is essential to detect potential electromagnetic interference with nearby devices. This problem is crucial in high power density applications. Therefore, especially in these applications, it is necessary to optimize the circuit and the layout to minimize the generated noise. The design and construction of systems able to scan volumes to determine the spatial distribution of electrical E and/or magnetic B fields in the near-field region of a device under test is a very complex process. The realization of equipment that explores a given surface at a given distance from the device is easier. The main purpose of this paper is to show how it is possible to build a cheap two-dimensional scanner, starting from simple hardware not explicitly designed for near-field scan operations. The presented firmware and software solution can map, with good accuracy, the spatial distribution of fields B and E on a fixed plan close to the board. Finally, the developed system has been used in a GaN-based bi-directional DC/DC Converter.

This study aims to evaluate the precision of nine distinct hyperelastic models using experimental data sourced from the existing literature. These models rely on parameters obtained through curve-fitting functions. The complexity in finite element models of elastomers arises due to their nonlinear, incompressible behaviour. To achieve accurate representations, it is imperative to employ sophisticated hyperelastic models and appropriate element types and formulations. Prior published work has primarily focused on the comparison between the fitting models and the experimental data. Instead, in this study, the results obtained from finite element analysis are compared against the original data to assess the impact of element formulation, strain range, and mesh type on the ability to accurately predict the response of elastomers over a wide range of strain values. This comparison confirms that the element formulation and strain range can significantly influence result accuracy, yielding different responses in various strain ranges also because of the limitation with the curve fitting tools.

Considering the global increase in fish consumption, the growing side-streams coming from the fish supply chain (e.g., skin, fins, tail, heads…), also including undersized or “unwanted catches”, have been recently proposed as source of high-value bioactive compounds (e.g., peptides and fatty acids). In this case study, hydrolyzed collagen peptides (HCPs) were extracted from different parts of Mugil cephalus L. using environmentally friendly techniques such as ultrasounds and enzymatic treatments. Both a mixed biomass derived from the skin, fins, and tail, and a whole fish, were considered as starting biomass, simulating the unsorted processing side-streams and an undersized/unwanted catch, respectively. The extracted HCPs were purified in fractions (3 KDa) whose yields (about 5% and 0.04–0.3%, respectively) demonstrated the efficiency of the hydrolysis process. The extraction protocol proposed allowed us to also isolate the intermediate products, namely the lipids (about 8–10%) and the non-collagenous proteins (NCs, 16–23%), whose exploitation could be considered. Each sample was characterized using Sircol, UltraViolet-Spectra, and hydroxyproline assay, and the viability of their collagen fractions was tested on human endothelial cells. Significant effects were obtained at a fraction of

The ever-increasing penetration of renewable energy sources and distributed generation needs developing and deploying more sophisticated and precise control techniques. The paradigm shift from high-rotational inertia towards inverter-connected facilities has made modern power systems subject to strongly non-stationary operating conditions. In this context, phasor measurement units (PMUs) represent a promising solution due to their accuracy and time synchronization. The current paper further develops the concepts recently published proposing performance assessment of PMUs relying on metrics specifically defined to quantify the estimation accuracy, reporting latency, and response time. Our focus is on determining the confidence interval associated with these metrics and thus derive a robust approach for their application in measurement-based network controlling efforts. The configuration of the used simulation model is detailed, and the state estimation results as a function of the selected measurement weighing criteria are presented, concluding as a possible application of the reliability metrics in Weighted Least Squares and Discrete Kalman Filter state estimators, highlighting the performance enhancement as well as the theoretical limits of the proposed approach.

This paper presents an extensive review of the most effective and modern monitoring methods for electrical power lines, with particular attention to high-voltage (HV) and medium-voltage (MV) systems. From a general point of view, the main objective of these techniques is to prevent catastrophic failures by detecting the partial damage or deterioration of components and allowing maintenance operations to be organized. In fact, the protection devices commonly used in transmission and distribution networks guarantee the location of faults, such as short-circuits, putting the non-functioning branch of the network out of service. Nowadays, alongside these devices, it is possible to introduce new intelligent algorithms capable of avoiding the total loss of functionality, thus improving the reliability of the entire network. This is one of the main challenges in modern smart grids, which are characterized by the massive integration of renewable energy sources and a high level of complexity. Therefore, in the first part of this paper, a general overview of the most common protection devices is proposed, followed by an analysis of the most modern prevention algorithms. In the first case, the coordination of the relays plays a fundamental role in obtaining the fault location with a high level of selectivity, while in the field of preventive analysis, it is necessary to address the implementation of artificial intelligence methods. The techniques presented in this paper provide a comprehensive description of the different monitoring approaches currently used in distribution and transmission lines, highlighting the coordination of protection relays, the computational algorithms capable of preventing failures, and the influence of the distributed generation in their management. Therefore, this paper offers an overview of the main diagnostic techniques and protection devices, highlights the critical issues that can be overcome through the introduction of artificial intelligence, and describes the main prognostic methods, focusing on their invasive level and the possibility of operating directly online. This work also highlights the main guidelines for the classification and choice between the different approaches.

The insulin-degrading enzyme (IDE) is a Zn2+ peptidase originally discovered as the main enzyme involved in the degradation of insulin and other amyloidogenic peptides, such as the β-amyloid (Aβ) peptide. Therefore, a role for the IDE in the cure of diabetes and Alzheimer’s disease (AD) has been long envisaged. Anyway, its role in degrading amyloidogenic proteins remains not clearly defined and, more recently, novel non-proteolytic functions of the IDE have been proposed. From a structural point of view, the IDE presents an atypical clamshell structure, underscoring unique enigmatic enzymological properties. A better understanding of the structure–function relationship may contribute to solving some existing paradoxes of IDE biology and, in light of its multifunctional activity, might lead to novel therapeutic approaches.