Search Results (204)

Phishing attacks pose significant risks to security, drawing considerable attention from both security professionals and customers. Despite extensive research, the current phishing website detection mechanisms often fail to efficiently diagnose unknown attacks due to their poor performances in the feature selection stage. Many techniques suffer from overfitting when working with huge datasets. To address this issue, we propose a feature selection strategy based on a convolutional graph network, which utilizes a dataset containing both labels and features, along with hyperparameters for a Support Vector Machine (SVM) and a graph neural network (GNN). Our technique consists of three main stages: (1) preprocessing the data by dividing them into testing and training sets, (2) constructing a graph from pairwise feature distances using the Manhattan distance and adding self-loops to nodes, and (3) implementing a GraphSAGE model with node embeddings and training the GNN by updating the node embeddings through message passing from neighbors, calculating the hinge loss, applying the softmax function, and updating weights via backpropagation. Additionally, we compute the neighborhood random walk (NRW) distance using a random walk with restart to create an adjacency matrix that captures the node relationships. The node features are ranked based on gradient significance to select the top k features, and the SVM is trained using the selected features, with the hyperparameters tuned through cross-validation. We evaluated our model on a test set, calculating the performance metrics and validating the effectiveness of the PhishGNN dataset. Our model achieved a precision of 90.78%, an F1-score of 93.79%, a recall of 97%, and an accuracy of 93.53%, outperforming the existing techniques. Full article

Background: Duchenne muscular dystrophy (DMD), which affects 1 in 3500 to 5000 newborn boys worldwide, is characterized by progressive skeletal muscle weakness and degeneration. The reduced muscle regeneration capacity presented by patients is associated with increased fibrosis. Satellite cells (SCs) are skeletal muscle stem cells that play an important role in adult muscle maintenance and regeneration. The absence or mutation of dystrophin in DMD is hypothesized to impair SC asymmetric division, leading to cell cycle arrest. Methods: To overcome the limited availability of biopsies from DMD patients, we used our 3D skeletal muscle organoid (SMO) system, which delivers a stable population of myogenic progenitors (MPs) in dormant, activated, and committed stages, to perform SMO cultures using three DMD patient-derived iPSC lines. Results: The results of scRNA-seq analysis of three DMD SMO cultures versus two healthy, non-isogenic, SMO cultures indicate reduced MP populations with constant activation and differentiation, trending toward embryonic and immature myotubes. Mapping our data onto the human myogenic reference atlas, together with primary SC scRNA-seq data, indicated a more immature developmental stage of DMD organoid-derived MPs. DMD fibro-adipogenic progenitors (FAPs) appear to be activated in SMOs. Conclusions: Our organoid system provides a promising model for studying muscular dystrophies in vitro, especially in the case of early developmental onset, and a methodology for overcoming the bottleneck of limited patient material for skeletal muscle disease modeling. Full article

Background/Objectives: Severe malaria, mainly caused by Plasmodium falciparum, remains a significant therapeutic challenge due to increasing drug resistance and adverse effects. Flavonoids, known for their wide range of bioactivities, offer a promising route for antimalarial drug discovery. The aim of this study was to elucidate key structural features associated with antimalarial activity in flavonoids and to develop accurate, interpretable predictive models. Methods: Curated databases of flavonoid structures and their activity against P. falciparum strains and enzymes were constructed. Molecular fingerprinting and decision tree analyses were used to identify key pharmacophoric groups. Subsequently, molecular descriptors were generated and reduced to build multiple classification and regression models. Results: These models demonstrated high predictive accuracy, with test set accuracies ranging from 92.85% to 100%, and R² values from 0.64 to 0.97. Virtual screening identified novel flavonoid candidates with potential inhibitory activity. These were further evaluated using molecular docking and molecular dynamics simulations to assess binding affinity and stability with Plasmodium proteins (FabG, FabZ, and FabI). The predicted active ligands exhibited stable pharmacophore interactions with key protein residues, providing insights into binding mechanisms. Conclusions: This study provides highly predictive models for antimalarial flavonoids and enhances the understanding of structure–activity relationships, offering a strong foundation for further experimental validation. Full article

Introduction: This study investigated the effectiveness of e-learning compared to traditional teaching methods in ultrasound education, centring on a focus cardiac ultrasound (FoCUS) course for third-year undergraduate medical students. With the rise of digital teaching methods, it is essential to evaluate their impact on the development of theoretical and practical skills in ultrasound training. Methods: A prospective, randomised, controlled trial was conducted involving two groups of students participating in a one-day FoCUS course delivered in a flipped classroom format. The study group used e-learning resources, while the control group used hard-copy lecture notes. Assessments were conducted at three stages: before the course, during the preparation phase, and after the course. Evaluations included self-assessment surveys, theory tests, and practical exams using direct observation of procedural skills (DOPS) tests. The study group had 15% less practice time compared to the control group. Results: A total of 109 complete datasets (study group, n = 52; control group, n = 57) were analysed. Both groups showed an equivalent initial level of and a continuous and significant (p < 0.01) increase in subjective and objective skills over the evaluated time frame. The study group achieved significantly (p = 0.03) higher results in DOPS (T2) than the control group. No significant differences were found in the total scores of the theory tests (T2 + T3) or DOPS (T3). Both groups rated their teaching materials, motivation, and the course concept in similarly high scale ranges. Conclusions: The findings suggest that e-learning is as effective as traditional methods in developing ultrasound skills and may serve as a viable alternative, even with reduced face-to-face interaction. These results indicate that accreditation processes could be applied similarly to those for traditional formats without requiring in-person training as a prerequisite for quality Full article

Water, an essential asset for life and growth, is under growing pressure due to climate change, overpopulation, pollution, and industrialization. At the same time, water distribution within cities relies on piping networks that are over 30 years old and thereby prone to leaks, cracking, and losses. Taking this into account, non-revenue water (i.e., water that is distributed to homes and facilities but not returning revenues) is estimated at almost 50%. To this end, intelligent water management via computational advanced tools is required in order to optimize water usage, to mitigate losses, and, more importantly, to ensure sustainability. To address this issue, a case study was developed in this paper, following a step-by-step methodology for the city of Heraklion, Greece, in order to introduce an intelligent water management system that integrates advanced technologies into the aging water distribution infrastructure. The first step involved the digitalization of the network’s spatial data using geographic information systems (GIS), aiming at enhancing the accuracy and accessibility of water asset mapping. This methodology allowed for the creation of a framework that formed a “digital twin”, facilitating real-time analysis and effective water management. Digital twins were developed upon real-time data, validated models, or a combination of the above in order to accurately capture, simulate, and predict the operation of the real system/process, such as water distribution networks. The next step involved the incorporation of a hydraulic simulation and modeling tool that was able to analyze and calculate accurate water flow parameters (e.g., velocity, flowrate), pressure distributions, and potential inefficiencies within the network (e.g., loss of mass balance in/out of the district metered areas). This combination provided a comprehensive overview of the water system’s functionality, fostering decision-making and operational adjustments. Lastly, automatic meter reading (AMR) devices could then provide real-time data on water consumption and pressure throughout the network. These smart water meters enabled continuous monitoring and recording of anomaly detections and allowed for enhanced control over water distribution. All of the above were implemented and depicted in a web-based environment that allows users to detect water meters, check water consumption within specific time-periods, and perform real-time simulations of the implemented water network. Full article

A method for characterizing carbon nanotubes (CNTs) in powder form with different packing densities in the microwave regions is proposed. The CNTs were sandwiched between two dielectric walls in (Polyvinyl Chloride) PVC and put in a waveguide shim. We measured the transmission/reflection S-parameters of the waveguide using a Vector Network Analysis (VNA), and the impacts of the PVCs on the measured S-parameters were de-embedded by microwave network analysis. Then, the well-known Nicolson–Ross–Weir (NRW) method was processed to determine the complex permittivity and permeability of the CNTs. Furthermore, we pressed the PVC to increase the packing densities of the CNTs. The results of the characterization can be employed to design microwave devices using the CNTs. Full article

Background/Objectives: Risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM) remains challenging, especially in high-risk cohorts. This study evaluated the predictive utility of the ESC HCM Risk Score and the additive value of myocardial fibrosis assessment via cardiac magnetic resonance (CMR) in HCM patients with implantable cardioverter-defibrillators (ICDs) for primary prevention. Methods: A retrospective analysis was conducted on 108 HCM patients (mean age 49.4 ± 14.2 years; 30.6% female; 63.9% with LVOT obstruction) with ICDs for primary SCD prevention. The primary endpoint was a composite of all-cause mortality or appropriate ICD therapy for ventricular arrhythmia over a mean follow-up of 69.5 ± 22.8 months. ESC HCM Risk Scores, the presence of fibrosis on CMR, and clinical outcomes were analyzed using univariate and multivariate models, ROC curves, and Kaplan–Meier survival estimates. Results: The primary endpoint occurred in 25 patients (23.1%; 3.1%/year). An ESC HCM Risk Score ≥ 4% was common (81.5%) but did not significantly predict the primary outcome (the c-statistic 0.54; p = 0.08) and demonstrated low positive (25%) and high negative predictive values (85%). Severe fibrosis on CMR was significantly associated with events in univariate analysis (p = 0.04), and its inclusion improved the model’s predictive accuracy (the c-statistic increased to 0.65; p = 0.03). Kaplan–Meier analysis revealed worse event-free survival in patients with both elevated ESC scores and more than mild fibrosis (p = 0.028). Conclusions: In this high-risk HCM cohort with ICDs, the ESC risk score showed limited predictive performance, while myocardial fibrosis on CMR added significant prognostic value. Incorporating the fibrosis assessment into future risk models may enhance SCD prediction and refine ICD decision-making in HCM. Further multicenter studies are needed to validate these findings. Full article

Background/Objective: Previous studies have indicated a higher incidence of complications associated with dual-lead devices compared to single-lead devices. This retrospective study aimed to investigate the effect of lead count and other factors on peri/postoperative complications for new pacemaker (PM) or implantable cardioverter-defibrillator (ICD) implantations in a representative German cohort. Methods: In accordance with quality assurance (QS) requirements, all hospitals in Germany collect patient-specific data on cardiac device implantation. We utilized the QS database from North Rhine-Westphalia to analyze data from 169,547 patients who underwent PM (n = 137,208) or ICD (n = 32,339) implantation between 2010 and 2014. The primary endpoint was the incidence of perioperative complications in the PM and ICD groups, analyzed separately for single- and dual-lead systems. Regression analysis was performed to identify specific risk factors and the effect of lead number on complications. Results: In the PM group, patients with dual-lead devices experienced significantly more complications than those with single-lead devices (3.27% vs. 2.85%, p < 0.001), largely driven by lead dislocations. In the ICD group, no significant difference in complication rates was observed between single-lead and dual-lead devices (1.39% vs. 1.46%, p = 0.635). The risk of complications was over twice as high for PM implantation compared to ICD implantation (3.17% vs. 1.42%). Patients with intrahospital complications faced a significantly higher risk of mortality than those without complications (PM: 4.5% vs. 1.6%; ICD: 3.9% vs. 0.5%). Independent risk factors for complications and mortality were identified in both groups, with a notable increase in the risk of intrahospital mortality associated with complications. Conclusions: Complications of dual-lead PM implantations are higher than single-lead procedures, mostly due to lead dislocations. Such a difference, though, was not observed in ICD implantations. Our findings may help optimize procedural strategies to improve patient safety, especially in PM implantations. Full article

Smart cities integrate advanced technologies, data-driven decision-making, and interconnected infrastructure to enhance urban living and resource efficiency. Among these, Smart Water Management (SWM) is crucial for optimizing water distribution and reducing Non-Revenue Water (NRW) losses, a persistent challenge for utilities worldwide. Water leaks contribute significantly to NRW, necessitating real-time leak detection and management systems to minimize detection time and human effort. Achieving this requires seamless integration of SWM technologies, including advanced metering infrastructure, the Internet of Things (IoT), and Artificial Intelligence (AI). While previous studies have explored various leak detection techniques, many lack a focused analysis of real-time data integration and automated alerts in SWM systems. This Systematic Literature Review (SLR) addresses this gap by examining advancements in automatic data collection, leak detection models, and real-time alert mechanisms. The findings highlight the growing potential of data-driven approaches to enhance leak detection accuracy and efficiency, particularly those leveraging flow and pressure data. Despite advancements, model accuracy, scalability, and real-world applicability remain. This review provides critical insights for future research, guiding the development of automated, AI-driven leak management systems to improve water distribution, minimize losses, and enhance sustainability in smart cities. Full article

Background/Objectives: Subsequent to surgical procedures under cardiopulmonary bypass, at least one third of the patients experience delirium. Among others, the disruption of the blood–brain barrier results from the release of natriuretic peptides during surgery. Furthermore, natriuretic peptides increase the effect of dopamine agonists, which is a key element in the pathomechanism of delirium. The primary endpoint of this study was the adjusted mean difference in natriuretic peptide concentration before surgery between patients with and without delirium. The secondary endpoints were the differences in cognitive performance and quality of life, and physical performance. Methods: Single center observational study. Setting in the Cardiac surgery and intensive care at a German tertiary medical center. Eighty patients for elective cardiac surgery under cardiopulmonary bypass for valve replacement or coronary artery bypass grafting. Preoperative NT-pro C-type natriuretic peptide (CNP) was determined. After surgery, delirium was assessed five times daily using the confusion assessment method for intensive care until 72 h after surgery and before hospital discharge. Data on quality of life and physical performance were also collected. Results: Overall, 28/80 (35%) patients developed delirium. Patients with delirium showed an increased concentration of NT-proCNP preoperatively (p = 0.016) compared to those who did not experience delirium. Patients with delirium during hospitalization reported deterioration in their physical role function (p = 0.036), vitality (p = 0.004), and social function (p = 0.008) before surgery. Conclusions: Increased NT-proCNP before surgery is associated with the occurrence of delirium. A relevant reduction in cognitive and physical performance and quality of life may be a new risk factor for delirium. Full article

A novel hot-melt cyclic olefin-based adhesive was designed as a transparent, non-tacky film of amorphous thermoplastic with a unique polymer micro-structure. The aim of the present paper is to assess the mechanical properties of the 0.1 mm thick COP hot-melt adhesive film through adhesive characterizations tests. The glass transition temperature was determined using dynamic mechanical analysis (DMA). For mechanical characterization, bulk and thick adherend shear specimens were manufactured and tested at a quasi-static rate, where at least three specimens were used to calculate the average and standard deviation values. Tensile tests revealed the effects of molecular chain drawing and reorientation before the onset of strain hardening. Thick adherend shear specimens were used to retrieve shear properties. Fracture behaviour was assessed with the double cantilever beam (DCB) test and end-notched flexure (ENF) test, for characterization under modes I and II, respectively. To study the in-joint behaviour, single lap joints (SLJs) of aluminium and carbon fibre-reinforced polymer (CFRP) were manufactured and tested under different temperatures. Results showed a progressive interfacial failure following adhesive plasticization, allowing deformation prior to failure at 8 MPa. An adhesive failure mode was confirmed through scanning electron microscopy (SEM) analysis of aluminium SLJ. The adhesive exhibits tensile properties comparable to existing adhesives, while demonstrating enhanced lap shear strength and a distinctive failure mechanism. These characteristics suggest potential advantages in applications involving heat and pressure across automotive, electronics and structural bonding sectors. Full article

Healthcare professionals are particularly vulnerable to mental health issues during epidemics, as evidenced by the COVID-19 crisis. German public health authorities, crucial for disease prevention, faced significant strain from chronic understaffing and resource limitations exacerbated by the pandemic. The study was designed as a cross-sectional, observational online survey. This study conducted an online needs assessment survey among heads of municipal public health authorities in Thuringia, Saxony, North Rhine-Westphalia, Bavaria, and Berlin between June and November 2023. Of the 191 contacted authorities, 74 responses (38.7%) were analyzed, focusing on professional demands, recognition, stress resilience, general life satisfaction, operational organization, and communication during the pandemic. Validated scales such as ERI, RS-13, L-1, and the COVID-19 add-on module of the COPSOQ were utilized. Statistical tests included descriptive statistics, correlation coefficients, Chi-Square tests, linear regression, T-tests, and ANOVA with a significance level set at p < 0.05. Respondents were mainly from North Rhine-Westphalia (43.3%) and Bavaria (24.3%), predominantly female (54.1%), and had a mean age of 52.7 years. The majority were medical specialists (71.9%). The RS-13 mean score was 72.66 (SD = 12.42), with 58.9% demonstrating high stress resilience. Public health degree holders showed the highest resilience. The ER-ratio indicated high effort versus reward for 96.7% of heads. Larger districts showed lower ER-ratios, suggesting resilient organizational structures. The study highlights high psychosocial workload and resilience among German public health authority heads during COVID-19, suggesting the need for optimized crisis management and scalable staffing for future pandemics and crises. Full article

Background/Objectives: Risk assessment in pediatric myocarditis is challenging, particularly when left ventricular ejection fraction (LVEF) is preserved. This study aimed to evaluate LV myocardial deformation using speckle-tracking echocardiography (STE)-derived longitudinal +strain (LS) and assessed its diagnostic and prognostic value in children with myocarditis. Methods: Retrospective STE-derived layer-specific LV LS analysis was performed on echocardiograms from patients within the multicenter, prospective registry for pediatric myocarditis “MYKKE”. Age- and sex-adjusted logistic regression and ROC analysis identified predictors of cardiac arrhythmias (ventricular tachycardia, ventricular fibrillation, atrioventricular blockage III°) and major adverse cardiac events (MACE: need for mechanical circulatory support (MCS), cardiac transplantation, and/or cardiac death). Results: Echocardiograms from 175 patients (median age 15 years, IQR 7.9–16.5 years; 70% male) across 13 centers were included. Cardiac arrhythmias occurred in 36 patients (21%), and MACE in 28 patients (16%). Impaired LV LS strongly correlated with reduced LVEF (r > 0.8). Impaired layer-specific LV LS, reduced LVEF, LV dilatation, and increased BSA-indexed LV mass, were associated with the occurrence of MACE and cardiac arrhythmias. In patients with preserved LVEF, LV LS alone predicted cardiac arrhythmias (p < 0.001), with optimal cutoff values of −18.0% for endocardial LV LS (sensitivity 0.69, specificity 0.94) and –17.0% for midmyocardial LV LS (sensitivity 0.81, specificity 0.75). Conclusions: In pediatric myocarditis, STE-derived LV LS is not only a valuable tool for assessing systolic myocardial dysfunction and predicting MACE but also identifies patients at risk for cardiac arrhythmias, even in the context of preserved LVEF. Full article

The prevalence of plant parasitic nematodes (PPN) in the Irish peatlands was investigated in five different peatland habitats—raised bog, cutover scrub/woodlands, fens and peat grasslands, which were further sub-categorised into fourteen different sub-habitats. Within the raised bog habitat were healthy bog hummock (HBH), healthy bog lawn (HBL), degraded bog hummock (DBH) and degraded bog lawn (DBL) and the fen habitats were fen peat (FP) and rich fen peat (R-FP). Cutover scrub or woodland habitat included cutover scrub rewetted (C-RW), cutover scrub non-rewetted (C-NRW), woodlands rewetted (W-RW) and woodlands non-rewetted (W-NRW). Grassland included wasted peat (WP), rough grazing (RG-I) and improved fen peat grassland (IFPG-RW and IFPG-NRW). Soil samples from peatlands were all collected between July and December 2023 when the temperature ranged from 12 to 20 °C. One half of each sample was used for molecular nematode analysis and the other half for morphological identification of nematodes. For the morphological identification, a specific nematode extraction protocol was optimised for peatland soils, and the extracted nematodes were fixed onto slides to be studied under a high-power light microscope. Subsequently, the other part of the soil was processed to isolate total DNA, from which the 18S rRNA gene was sequenced for the identification of nematode taxa. The extracted DNA was also used for randomly amplified polymorphic DNA (RAPD) fingerprinting analysis to determine banding patterns that could classify different bog habitats based on PPN random primers. Compared to that in the climax habitats (HBH, HBL, DBH, DBL, FP, R-FP), PPN prevalence was recorded as being higher in grasslands (WP, RG-I, IFPG-RW and IFPG-NRW) and scrub/woodland ecosystems (C-RW, C-NRW, W-RW, W-NRW). The results indicate that nematode populations are different across the various bog habitats. Emerging and current quarantine PPN belonging to the families Pratylenchidae, Meloidogynidae, Anguinidae and Heteroderidae were noted to be above the threshold limits mentioned under EPPO guidelines, in grassland and wooded peatland habitats. Future actions for PPN management may need to be considered, along with the likelihood that these PPN might impact future paludiculture and other crops and trees growing in nearby agricultural lands. Full article