Search Results (2,438)

Electric induction motors are fundamental to industry, where reliability and continuous operation are critical. Though robust, they are prone to faults, particularly in demanding environments such as highway tunnels. Non-invasive diagnostic techniques are widely used for condition monitoring, yet most studies occur under controlled laboratory conditions, limiting their applicability in real-world scenarios. This research investigates the feasibility of applying Motor Current Signature Analysis (MCSA) for monitoring highway tunnel axial fan motors, aiming to determine its effectiveness for real-time diagnostics in industrial environments. Measurements were performed under actual operating conditions, highlighting practical challenges. Data acquisition was implemented remotely from electrical cabins feeding tunnel services, reducing installation complexity and costs compared to in-tunnel measurements. This approach enabled monitoring of all motors in a tunnel using minimal hardware (a single acquisition system equipped with Rogowski sensors) making the solution cost-effective and suitable for periodic measurements. Frequency domain analysis focused on harmonics associated with rotor bar defects and eccentricity, selected for their slow degradation and diagnostic relevance. The magnitude of these harmonics was tracked over time and compared across motors of the same model. Since most of the time the ventilators are de-energized, the periodic measurements can be seen almost as a real-time monitoring, at least for the faults considered, with much lower costs. Results were validated against maintenance reports, confirming bearing faults with eccentricity in two motors, while suspected rotor porosity remained unverified, as expected at low severity. Findings demonstrate that MCSA can provide operational insights for fault detection in tunnel environments, supporting predictive maintenance strategies. A key outcome of this study was selecting and implementing an effective measurement setup for industrial applications, while preparing the base for future machine learning integration to estimate Remaining Useful Life. Full article

Background/Objectives: This study investigates whether a patient’s clinical status influences the evaluation of sacroiliac joint (SIJ) radiographs. Methods: The study involved analysing SIJ radiographs of patients diagnosed with spondyloarthritis (SpA) at our clinic. Two rheumatologists working at another centre evaluated the images independently. Three months were allowed to elapse so that the rheumatologists would forget the results of the first evaluation. The radiographs were then re-evaluated in a different order by the same rheumatologists. However, during the second evaluation, the evaluators were also provided with general clinical information about the patients. Inter- and intra-observer agreement were assessed. Results: In the first blinded evaluation of our study, we found moderate-to-substantial agreement between rheumatologists (right κ: 0.534; p < 0.001; left κ: 0.609; p < 0.001) and statistically significant interpretation agreement. In the second evaluation, we observed an increase in agreement (κ increased from 0.534 to 0.774 for the right SIJ and from 0.609 to 0.855 for the left SIJ), and these metrics were also significant. Conclusions: The interpretation of SIJ radiographs showed notable inter-observer variability in the absence of clinical information. Incorporating clinical context significantly improved the agreement between readers. As conventional radiography remains central to spondyloarthritis classification, these findings highlight the value of clinical data in enhancing the reliability of radiographic assessment. To our knowledge, this is the first study to systematically demonstrate the impact of clinical information on inter-observer agreement in SIJ radiograph interpretation. Full article

Rapid and accurate moisture detection is critical for alfalfa quality control, yet conventional methods are slow, and non-destructive techniques are challenged by different product forms. This study leveraged Short-Wave Infrared Hyperspectral Imaging (SWIR-HSI) to acquire spatially representative spectra, aiming to develop and validate robust, form-specific moisture prediction models for compressed and powdered alfalfa. For compressed alfalfa, a full-spectrum Support Vector Regression (SVR) model demonstrated stable and good performance (mean Prediction Coefficient of Determination ${\mathrm{R}}_{\mathrm{P}}^2$ = 0.880, Ratio of Performance to Deviation RPD = 2.93). In contrast, powdered alfalfa achieved superior accuracy (mean ${\mathrm{R}}_{\mathrm{P}}^2$ = 0.953, RPD = 5.29) using an optimized pipeline of Savitzky–Golay’s first derivative, Successive Projections Algorithm (SPA) for feature selection, and an SVR model. A key finding is that the optimal model for powdered alfalfa frequently converged to an ultra-sparse, single-band solution near water absorption shoulders (~970/1450 nm), highlighting significant potential for developing low-cost, filter-based agricultural sensors. While this minimalist model showed excellent average accuracy, rigorous repeated evaluations also revealed non-negligible performance variability across different data splits—a crucial consideration for practical deployment. Our findings underscore that tailoring models to specific product forms and explicitly quantifying their robustness is essential for reliable NIR sensing in agriculture and provides concrete wavelength targets for sensor development. Full article

Sperm proteases are involved in several gamete interaction events leading to fertilization. This report presents a detailed analysis of the expression and localization of serine protease PRSS38 in human and in mouse spermatozoa and its involvement in fertilization-related events, using bioinformatics, cellular, biochemical, molecular, and functional approaches. Bioinformatics analyses included genomics and data analysis, prediction of protein subcellular localization and post-translational modifications, Self-Organizing Maps (SOMs) unsupervised training with other serine proteases, protein modeling (AlphaFold), and genetic variant analysis. For cellular, biochemical, and functional studies, human semen samples were obtained from healthy normozoospermic volunteers, and cauda epididymal sperm were collected from adult Balb-c/C57 mice. PRSS38 presence was detected in human and mouse sperm protein extracts by Western immunoblotting. Sperm PRSS38 subcellular localization was determined by fluorescence immunocytochemistry. Human sperm–oocyte interaction events were assessed by means of the mouse Cumulus Penetration Assay (CPA) using mouse COCs, the Human Hemizona Assay (HZA), and the ZP-free hamster egg Sperm Penetration Assay (SPA). Mouse sperm–oocyte interactions were evaluated by means of in vitro fertilization (IVF) with COCs and denuded oocytes. PRSS38 is proposed to be a GPI-anchored serine protease (active site: His-100, Asp-150, and Ser-245) based on bioinformatics analyses. Using commercial antibodies, protein forms of the expected Mr (human: 31 kDa; mouse: 32 and 24 kDa) were specifically immunodetected in protein sperm extracts. Immunocytochemical analysis revealed a specific PRSS38 signal in the human sperm acrosomal region, equatorial segment, and flagellum. Mouse sperm PRSS38 was immunolocalized in the equatorial segment and hook. Human sperm preincubation with specific antibodies resulted in inhibition (p < 0.05) of CPA, HZA, and SPA. Mouse sperm preincubation with PRSS38 antibodies impaired (p < 0.05) homologous IVF using COCs and denuded oocytes. Genetic variants affecting residues involved in the GPI anchor and the catalytic triad were found in individuals from the general population whose PRSS38 protease function could be altered. This study provides, for the first time, an integrated analysis of PRSS38 in human and mouse sperm, contributing to our understanding of mammalian fertilization and male infertility. Full article

The application of cryo-electron microscopy (cryo-EM) in membrane protein structural biology has catalyzed unprecedented advances in our understanding of fundamental biological processes and transformed drug discovery paradigms. This review briefly describes the biological achievements enabled using cryo-EM techniques, including single particle analysis (SPA), micro-electron diffraction (microED), and subtomogram averaging (STA), in elucidating the structures and functions of membrane proteins, ion channels, transporters, and viral glycoproteins. We highlight how these structural insights have revealed druggable sites, enabled structure-based drug design, and provided mechanistic understanding of disease processes. Key biological targets include G protein-coupled receptors (GPCRs), ion channels implicated in neurological disorders, respiratory chain complexes, viral entry machinery, and membrane transporters. The integration of cryo-EM with computational drug design has already yielded clinical candidates and approved therapeutics, marking a new era in membrane protein pharmacology. Full article

Objectives: The objective of this prospective, controlled observational study embedded in routine spa care was to evaluate the effectiveness of integrating immersive virtual reality (VR) into a three-week spa-based rehabilitation program to reduce pain and improve physical mobility in adults with chronic musculoskeletal or neurogenic disorders. Methods: In this study, fifty-five adults with chronic musculoskeletal or neurogenic disorders completed a three-week spa regimen combining natural therapies, physiotherapy and rehabilitation. Participants were allocated in a preference- and availability-based manner either to the VR-enhanced group (n = 37), which completed interactive 25 min VR sessions three times per week, or to the control group (n = 18) receiving standard care. Pain was assessed using a 100 mm Visual Analog Scale (VAS) and shoulder-related joint mobility by goniometry before and after the intervention. Wilcoxon signed-rank and Mann–Whitney U tests evaluated within- and between-group differences, with subgroup analyses according to disease duration (≤5 vs. >5 years). Results: Both groups achieved significant post-treatment reductions in VAS pain scores (p < 0.001). The VR group exhibited a greater median decrease in pain compared to controls (p = 0.048), with the largest effect among patients with disease duration ≤ 5 years (p = 0.024). Goniometric measurements demonstrated significant mobility improvements across all tested angles in the VR group (p < 0.001), while improvements in the control group were smaller. Conclusions: VR integrated into spa-based rehabilitation was associated with greater pain reduction and mobility gains than standard care. These preliminary, hypothesis-generating findings require confirmation in larger randomized trials with standardized protocols and long-term follow-up. Full article

Objectives: Graves’ disease (GD) is the most common cause of hyperthyroidism and is associated with marked changes in body weight and body composition. Although weight loss is frequently reported, the extent and clinical relevance of body composition alterations, as well as their relationship with thyroid function, remain unclear. This study aimed to evaluate body composition and eating habits in patients with newly diagnosed hyperthyroid GD according to pre-morbid weight variation, and to compare these findings with those of matched euthyroid controls. Methods: Forty-four consecutive GD patients were enrolled and stratified based on the presence or absence of pre-morbid weight loss. Anthropometric measurements, thyroid function tests, thyroid volume, dietary habits (PREDIMED score, macronutrient intake and total daily caloric intake) and body composition assessed by bioelectrical impedance analysis (BIA) were collected. Standardized phase angle (SPA) and body cell mass index (BCMI) were calculated as nutritional indices. Body composition parameters and dietary adherence were compared with those of 44 age-, sex- and BMI-matched euthyroid controls. Results: Most GD patients (70.3%) reported weight loss before diagnosis; however, the magnitude of weight change did not correlate with the biochemical severity of thyrotoxicosis. Patients without weight loss showed higher fat mass percentage and higher caloric intake than those who lost weight. SPA was significantly associated with FT3, FT4 and TRAb levels, independently of age, sex, BMI and fat mass. Compared with controls, GD patients exhibited lower phase angle and SPA, higher extracellular water percentage and reduced BCMI, whereas fat mass and adherence to the Mediterranean diet were similar. Conclusions: Hyperthyroid GD patients display increased extracellular water and reduced body cell mass. SPA is inversely associated with GD severity and represents a valuable clinical tool for assessing nutritional status in thyrotoxic patients. Pre-morbid weight changes are not proportional to disease severity and may instead reflect increased caloric intake. Full article

Soft pneumatic actuators (SPAs) are gaining attention in the field of soft robotics due to their lightweight, highly flexible, and safer interaction while operated under an unstructured environment. They are easy to fabricate, produce high output force, and are relatively very inexpensive compared to other soft actuators. However, accurate prediction of their nonlinear bending behavior is one of the main challenges, which is mainly due to the complex material properties and high deformation patterns. Therefore, this study focused on a hybrid approach that accurately captures the bending behavior of a single-chambered SPAs. This approach integrates physics-based modeling (finite element analysis (FEA) and analytical modeling) with a data-driven (polynomial regression modeling) approach to analyze the bending of single-chambered SPAs. Initially, four different hyperelastic material models (Neo-Hookean, Yeoh, Arruda–Boyce, and Ogden) were tested using FEA to analyze how material selection affects the SPA response. It is found that the Arruda–Boyce model generates the highest bending of 101° at 30 kPa pressure, while the other models consistently underestimated deformation at higher pressures. Further, an enhanced mathematical or analytical model was developed using Euler and Timoshenko beam theory with certain assumptions, such as neutral axis shifting, chamber ballooning, and shear deformation. These assumptions significantly improve the prediction accuracy and generate a bending angle of 99°at 30 kPa, which closely matches FEA bending. Further, a polynomial regression-based machine learning (ML) model was trained using analytical or mathematical bending data for faster output prediction. This data-driven approach achieves very high accuracy in the validation range, with an average absolute percentage deviation of only 0.002%. Additionally, comparison with the analytical results showed a mean absolute error (MAE) of 0.00180°, root mean squared error (RMSE) of 0.00205°, and coefficient of determination (R²) value of 0.999999808. Overall, integrating physics-based modeling with a data-driven approach provides a reliable and scalable method for SPA design. It provides practical information on material selection, analytical correction, and ML modeling, which will reduce the need for time-consuming prototyping. Finally, this hybrid approach can help to accelerate the development of soft robotic grippers, rehabilitation tools, and other bio-inspired actuation systems. Full article

Solenoid valves are widely used for pressure regulation in soft pneumatic robots, but their inherent electromechanical nonlinearities—such as dead zones, saturation, and pressure-dependent dynamics—pose significant challenges for accurate control. Conventional pulse modulation techniques, including pulse-width modulation (PWM), often exacerbate these effects by neglecting valve-switching transients. This paper presents a physics-informed dynamic modelling framework that captures transient and pressure-dependent behaviours in solenoid valve-driven soft pneumatic systems operating under pulse modulation. The model is experimentally validated on a soft pneumatic actuator (SPA) platform using four modulation schemes: PWM, integral pulse frequency modulation (IPFM), its inverted variant (IIPFM), and $\Delta$$\Sigma$ modulation. Results demonstrate that only the IIPFM scheme produces near-linear input–pressure characteristics, in close agreement with model predictions. The proposed framework provides new physical insights into valve-induced nonlinearities and establishes a systematic basis for high-fidelity modelling and control of soft pneumatic robotic systems. Full article

Background/Objectives: Chronic venous disease is a very common disease. Recent studies suggest a potential link between this condition and cardiovascular disease or mortality. Common pathophysiological features include endothelial injury, hypercoagulability, and systemic inflammation. Conservative management of chronic venous disease includes compression therapy and pharmacological treatment. However, there is some controversy regarding the exact place of pharmacological treatment in the management of this condition. We conducted the VeinHeart Survey to gather information on the management of patients with chronic venous disease referred to vascular specialists in Italy. Methods: The present survey involved 78 Italian phlebologists, angiologists, and vascular surgeons, with data from a total of 1621 patients. Results: Drug therapies prescribed by vascular specialists participating in this survey included: glycosaminoglycans, topical phlebotonics, systemic phlebotonics, and supplements. The most commonly prescribed medications were glycosaminoglycans, both at the first visit and at follow-up. The meantime since the first visit was 56.4 days. Both symptoms and signs improved at follow-up. The most improved signs at follow-up were edema and venous ulcer healing. The prevalence of CEAP classes C3 and C4 also showed a decrease at the follow-up visit. Conclusions: The findings of this survey provide a picture of the state of the art of current pharmacological treatments prescribed by expert clinicians in the management of patients with chronic venous disease in Italy. This may offer some useful insights for the optimization of current therapeutic options, in order to improve the clinical management of this disease. Full article

Oral microbial biofilms play a critical role in the development of various oral infectious diseases, including periodontitis and tooth caries, with Streptococcus mutans recognized as a key biofilm-forming bacterium due to its strong adhesion and acidogenic capacity. Zinc oxide nanoparticles (ZnO NPs) have demonstrated antibacterial properties against various bacteria. This study investigated the antibacterial and antibiofilm properties of ZnO NPs on S. mutans and elucidated their mode of action. Bacterial cultures were exposed to increasing concentrations of ZnO NPs, and planktonic growth, biofilm biomass and biofilm metabolic activity were measured. Complementary assays assessed bacterial ATP content, pH shift in the media, reactive oxygen species (ROS) production, membrane integrity (SYTO 9/PI live/dead staining) and membrane potential. Morphological changes were examined by high-resolution scanning electron microscopy (HR-SEM), while gene expression was analyzed by real-time qPCR. We observed that ZnO NPs inhibited S. mutans growth and biofilm formation in a dose-dependent manner, with both the minimum inhibitory and biofilm inhibitory concentration of 0.5 mg/mL. ZnO NP treatment disrupted bacterial membranes, caused cytoplasmic leakage, and induced ROS production. EPS production determined by Congo Red staining was significantly reduced. Gene expression analysis revealed significant upregulation of vicR, luxS, wapA, gtpB, nox and ftsZ, and downregulation of spaP, gtpC and atpB. In conclusion, ZnO NPs compromise S. mutans viability and biofilm development through oxidative stress and membrane disruption, highlighting their potential use as bioactive materials in oral healthcare. Full article

Background: Evaluation of blood flow dynamics within the left atrium (LA) using cardiac imaging techniques, such as four-dimensional (4D) flow magnetic resonance imaging (MRI) and contrast and non-contrast ultrasound, is an area of increasing interest, especially in patients with atrial fibrillation (AF). While 4D flow MRI and contrast ultrasound are limited in their application in routine clinical practice, non-contrast ultrasound techniques have the potential for extensive clinical application. However, there are no studies on LA flow dynamics evaluated using these latter techniques. Here we present the first application of HyperDoppler, a non-contrast color Doppler-based technique, to the assessment of LA flow dynamics in a case series. Methods: The transthoracic color Doppler modified apical 4-chamber view of a normal healthy subject and two patients with AF (one with persistent and the other with permanent AF) were analyzed using HyperDoppler. The resulting velocity vector map was visually examined frame-by-frame to describe LA flow dynamics. Results: In the healthy subject, HyperDoppler showed a LA flow behavior consistent with findings from the literature employing 4D flow MRI. In both patients with AF, HyperDoppler showed alterations of the LA flow dynamics pattern. Conclusions: Our preliminary observations suggest that HyperDoppler may be a valuable tool for characterizing physiological and pathological LA flow dynamics. Further studies are needed to confirm, explain and expand our initial findings. Full article

Chile, the leading exporter of cherries (Prunus avium L.) in the southern hemisphere, faces sustained variations in precipitation patterns and high evaporative demand in its productive areas. The low availability of water during the period of highest environmental demand makes it essential to reduce or suspend irrigation applications. In this scenario, regulated deficit irrigation (RDI) after harvest is an efficient strategy for optimizing water use without compromising orchard yields. This study was conducted over three consecutive seasons in a traditional commercial orchard of ‘Santina’ cherry trees grafted onto Colt rootstock, evaluating the effect of two levels of RDI, moderate (MDI) and severe (SDI), on productive and ecophysiological parameters. Both treatments resulted in water savings of between 10% and 28%, without negatively affecting yield or fruit quality. The SDI treatment, despite reaching higher levels of cumulative water stress, improved intrinsic water use efficiency while maintaining stable photosynthetic efficiency. In addition, an increase in the abundance of fine roots and beneficial rhizosphere bacteria populations, such as Azospirillum and Bacillus, was observed, suggesting the activation of water resilience mechanisms mediated by plant–microbiota interaction, possibly associated with stress-induced ecological memory and microbial legacy effects. These results position after-harvest RDI as a sustainable tool for coping with climate variability and water scarcity in commercial cherry orchards. Full article

Methicillin-susceptible Staphylococcus aureus (MSSA) remains a major pathogen in neonatal intensive care units (NICUs), with colonization and infection posing significant risks. MSSA colonization occurs in up to 42.8% of neonates, while 12–41% of healthcare personnel also carry MSSA, contributing to nosocomial transmission. MSSA accounts for approximately 12% of neonatal S. aureus bloodstream infections, with mortality rates up to 20.5%, particularly among very-low-birth-weight infants. This review analyzes the molecular attributes, epidemiology, risk factors, clinical presentations, decontamination methods, and treatment alternatives for MSSA infections in newborns. MSSA strains show considerable genetic heterogeneity, being distinguished by a wide variety of sequence types (STs) and Staphylococcal Protein A types (SpA). They harbor several pathogenicity genes—including hemolysins, superantigens, adhesins, and Panton–Valentine leukocidin (PVL)—which are implicated in severe infections, while biofilm-associated genes enhance environmental persistence. Prematurity, low birth weight, prolonged hospitalization, and exposure to invasive devices are key risk factors. Active surveillance and decolonization programs have achieved reductions of up to 73% in MSSA infections. β-lactam antibiotics remain first-line therapy, with adjunctive aminoglycosides reserved for severe cases. Ongoing genomic surveillance and targeted preventive strategies are essential to reduce MSSA-associated morbidity and mortality in this vulnerable population. Full article

The aim of this study was to analyze long-term trends and spatial variability of PM10 concentrations in Poland during the period 2019–2024, based on data from the European Air Quality Monitoring System (EAQ). The analysis covered nine locations representing three types of areas: large agglomerations (Warsaw, Kraków, Katowice), medium-sized cities (Wrocław, Poznań), and spa towns (Ciechocinek, Lądek-Zdrój, Świnoujście). An integrated statistical approach was applied, including Welch’s ANOVA, Linear Mixed Models (LMM), Generalized Additive Models (GAM), and Quantile Regression (FDR–BH). Mean PM10 concentrations in the analyzed period ranged from 17.43 µg/m³ in Świnoujście to 31.16 µg/m³ in Kraków, with 30.17 µg/m³ in Katowice and 27.90 µg/m³ in Warsaw. The largest differences between locations were observed during smog episodes —the 90th percentile values reached 56.61 µg/m³ in Kraków, 49.99 µg/m³ in Katowice, and 29.19 µg/m³ in Świnoujście. In most locations, a downward trend in PM10 levels was recorded over time; however, regional differences persist. The GAMs confirmed strong seasonality (winter maximum, summer minimum), while quantile regression indicated that the highest risk of smog episodes occurs in southern Poland. The novelty of this study lies in the integration of three complementary modeling approaches (LMM, GAM, and Quantile Regression) in the analysis of the spatio-temporal variability of PM10, as well as in the innovative comparison-unique in the literature-of agglomerations, medium-sized cities, and spa towns in Poland based on a uniform, reference EAQ dataset. This approach made it possible to reveal persistent environmental disparities of significant relevance to the national anti-smog policy and enables a more realistic assessment of environmental risk within the European research context. Full article