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Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are persistent compounds characterized by stable C−F bonds giving them high thermal and chemical stability. Numerous studies have highlighted the presence of PFASs in the environment, surface waters and animals and humans. Exposure to these chemicals has been found to cause various health effects and has necessitated the need to develop methods to remove them from the environment. To date, the use of photocatalytic degradation and membrane separation to remove PFASs from water has been widely studied; however, these methods have drawbacks hindering them from being applied at full scale, including the recovery of the photocatalyst, uneven light distribution and membrane fouling. Therefore, to overcome some of these challenges, there has been research involving the coupling of photocatalysis and membrane separation to form photocatalytic membrane reactors which facilitate in the recovery of the photocatalyst, ensuring even light distribution and mitigating fouling. This review not only highlights recent advancements in the removal of PFASs using photocatalysis and membrane separation but also provides comprehensive information on the integration of photocatalysis and membrane separation to form photocatalytic membrane reactors. It emphasizes the performance of immobilized and slurry systems in PFAS removal while also addressing the associated challenges and offering recommendations for improvement. Factors influencing the performance of these methods will be comprehensively discussed, as well as the nanomaterials used for each technology. Additionally, knowledge gaps regarding the removal of PFASs using integrated photocatalytic membrane systems will be addressed, along with a comprehensive discussion on how these technologies can be applied in real-world applications. Full article

Research in the field of quantum physics is important for progress in many areas of exploration and development. Quantum computers and other quantum devices are promising technologies with numerous potential applications. On the other hand, understanding, interpreting, teaching, and learning quantum physics as part of an educational process is a major challenge. In the Republic of Croatia, students usually come in contact with the concepts of quantum physics towards the end of their high school education. These concepts are often abstract and represent a remarkable leap from the theories of classical physics. The aim of this study is to test the measurement properties of the instrument used to assess the progress of understanding and knowledge of quantum physics in a sample of Croatian high school students. The quantum physics conceptual survey (QPCS), developed and first tested in 2006 by Wuttiprom et al. at the University of Sydney, was the instrument we used in this study. The test was administered to 76 high school students. The results show that the QPCS test is valid and generally reliable in the context of Croatian secondary education, but for the topics Waves and particles and Uncertainty principle, the reliability needs further investigation. The results of the pretest and posttest were analysed and compared with each other and with previously published results. Quantitative methods were used to analyse the results obtained. We present several possible solutions to improve the teaching process, that we expect will lead to better results, especially for topics that are challenging for students. Full article

Background: Pulmonary hypertension (PH) can lead to cardiac failure, thereby significantly affecting life expectancy and quality of life. Due to inadequate disease surveillance and risk assessment, clinical challenges persist despite advances in diagnosis and treatment. We aimed to review the potential of high-sensitivity cardiac troponin (hs-cTn) as a biomarker for predicting outcomes in PH patients. Methods: A thorough examination of the PubMed and Google Scholar databases was conducted through March 2023. Studies involving adult PH patients and hsTn as a prognostic indicator of outcomes such as mortality, hospitalization, and disease progression were included, after screening their titles and abstracts. Two independent evaluators extracted data, with the quality assessed using the JBI critical appraisal tool. Results: This review uncovered eight studies that examined the prognostic value of hs-cTn in PH patients. Higher hs-cTn levels were associated with increased mortality and hospitalization rates, according to the studies. The severity of PH, cardiac dysfunction, right ventricular function, and systolic dysfunction were associated with hs-cTn. Multiple studies have demonstrated that hsTn has the potential to identify high-risk PH patients who could benefit from targeted therapies and increased clinical monitoring. Conclusions: This review suggests that hsTn may be a biomarker for PH risk stratification and prognosis. Across PH subtypes, elevated hsTn levels predict poor outcomes. However, large-scale prospective studies are needed to confirm hs-cTn’s function in diagnosing pulmonary hypertension and determine its potential value in treatment. Full article

Polyaniline−magnesia (PANI/MgO) composites with a fibrous nanostructure were synthesized via in situ oxidative polymerization, enabling uniform MgO integration into the polyaniline matrix. These composites were characterized using FTIR spectroscopy to analyze intermolecular bonding, XRD to assess crystallographic structure and phase purity, and SEM to examine surface morphology and topological features. The resulting PANI/MgO nanofibers were utilized to develop ammonia (NH₃) gas-sensing probes with evaluations conducted at room temperature. The study addresses the critical challenge of achieving high sensitivity and selectivity in ammonia detection at low concentrations, which is a problem that persists in many existing sensor technologies. The nanofibers demonstrated high selectivity and optimal sensitivity for ammonia detection, which was attributed to the synergistic effects between the polyaniline and MgO that enhance gas adsorption. Furthermore, the study revealed that the MgO content critically influences both the morphology and the sensing performance, with higher MgO concentrations improving sensor response. This work underscores the potential of PANI/MgO composites as efficient and selective ammonia sensors, highlighting the importance of MgO content in optimizing material properties for gas-sensing applications. Full article

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km² study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km²), 47.68% (3617.13 km²), 37.12% (2816.13 km²), and 5.97% (452.70 km²) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 10⁶ m³/year, constituting 22.7% of the total precipitation volume (11,227 × 10⁶ m³/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation. Full article

In recent years, with the development of the Internet of Things and distributed computing, the “server-edge device” architecture has been widely deployed. This study focuses on leveraging autoencoder technology to address the binary classification problem in network intrusion detection, aiming to develop a lightweight model suitable for edge devices. Traditional intrusion detection models face two main challenges when directly ported to edge devices: inadequate computational resources to support large-scale models and the need to improve the accuracy of simpler models. To tackle these issues, this research utilizes the Extreme Learning Machine for its efficient training speed and compact model size to implement autoencoders. Two improvements over the latest related work are proposed: First, to improve data purity and ultimately enhance detection performance, the data are partitioned into multiple regions based on the prediction results of these autoencoders. Second, autoencoder characteristics are leveraged to further investigate the data within each region. We used the public dataset NSL-KDD to test the behavior of the proposed mechanism. The experimental results show that when dealing with multi-class attacks, the model’s performance was significantly improved, and the accuracy and F1-Score were improved by 3.5% and 2.9%, respectively, maintaining its lightweight nature. Full article

This study adopts an integrative review approach to explore the differences and similarities between smart cities and sustainable cities. The research starts by performing two systematic literature reviews about both paradigms and, after that, employs a thematic analysis to identify key themes, definitions, and characteristics that differentiate and connect these two urban development concepts. The findings reveal more similarities than differences between the two paradigms. Despite this, some key differences are identified. Smart cities are characterized by their use of advanced information and communication technologies to enhance urban infrastructure, improve public services, and optimize resource management. In contrast, sustainable cities focus on environmental conservation, social equity, and economic viability to ensure long-term urban resilience and quality of life. This study is important because it clarifies both concepts and highlights the potential for integrating smart and sustainable city strategies to address contemporary urban challenges more holistically. The findings also suggest a convergence towards the concept of ‘smart sustainable cities’, which leverage technology to achieve sustainability goals. Finally, this study concludes by identifying research gaps and proposing a future research agenda to further understand and optimize the synergy between smart and sustainable urban development paradigms. Full article

The continued rise in antimicrobial resistance poses a serious threat to public health worldwide. The use of phages that can have bactericidal activity without disrupting the normal flora represents a promising alternative treatment method. This practice has been successfully applied for decades, mainly in Eastern Europe, and has recently been used as an emergency therapy for compassionate care in the United States. Here, we provide a comprehensive review of the pre-clinical and clinical applications of phage therapy concerning three major Gram-negative pathogens: Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. The advantages and the challenges of expanding the usage of phages as an alternative or adjunctive treatment for antimicrobial-resistant bacterial infections are discussed. We emphasize the virologic complexities of using the highly adaptable phage populations as molecular tools, along with antibiotic chemical compounds, to effectively combat rapidly coevolving pathogenic bacteria in the host microenvironment. Pre-clinical studies, isolated clinical reports and a few randomized clinical trials have shown that bacteriophages can be effective in treating multidrug-resistant bacterial infections. The ability of some phages to revert the resistance against antibiotics, and possibly also against the human complement and other phages, appears to be a great advantage of phage therapy despite the inevitable emergence of phage-resistant strains. Bacteriophages (or specific phage-derived products) can enhance antimicrobial efficacy by reducing bacterial virulence via the alteration of basic bacterial structures, primarily of the cellular wall and membrane. Although several issues remain open regarding their effective clinical application, it appears that phage-based therapeutics in combination with antibiotics can provide an effective solution to the spread of antimicrobial resistance. Full article

Background/Objectives: Luteolin (LUT) is a natural flavonoid with known anti-inflammatory, antioxidant, and anti-cancer properties. Cervical cancer, particularly prevalent in certain regions, remains a significant health challenge due to its high recurrence and poor response to treatment. This study aimed to investigate the anti-tumor effects of LUT on human cervical epidermoid carcinoma cells (Ca Ski), focusing on cell growth inhibition, apoptosis induction, and regulation of mitochondrial membrane potential. Methods: Ca Ski cells were treated with varying concentrations of LUT (0, 25, 50, 100 µM) for different time periods (24, 48, 72 hours). Cell viability was measured using the MTT assay, apoptosis was assessed by flow cytometry with annexin V-FITC/PI staining, and changes in mitochondrial membrane potential were evaluated using JC-1 staining. Caspase-3 activation was examined by flow cytometry, and expression of apoptosis-related proteins (caspase-3, -8, -9, AIF) was analyzed via Western blotting. Results: LUT significantly inhibited the growth of Ca Ski cells in a dose- and time-dependent manner, with the most pronounced effects observed at 100 µM over 72 hours. Flow cytometry confirmed that LUT induced apoptosis without causing necrosis. Mitochondrial membrane potential was reduced after LUT treatment, coinciding with increased caspase-3 activation. Western blot analysis revealed the upregulation of pro-apoptotic proteins caspase-3, -8, -9, and AIF, indicating that LUT induces apoptosis through the intrinsic mitochondrial pathway. Conclusions: Luteolin effectively inhibits cervical cancer cell proliferation and induces apoptosis by disrupting mitochondrial membrane potential and activating caspases. These findings suggest that LUT holds potential as a therapeutic agent for cervical cancer, with further studies needed to explore its in vivo efficacy and broader clinical applications. Full article

Background: Malignant eyelid tumours present a considerable challenge in the field of ophthalmic oncology, necessitating a combination of precision oncological care and meticulous reconstruction to ensure the preservation of eyelid functionality and the maintenance of facial aesthetics. Method: This study presents a review of the outcomes of 167 patients who underwent eyelid reconstruction following the excision of primary non-melanocytic malignant tumours. The choice of reconstruction technique was dependent on a number of factors, including the stage of the tumour, its location, and the characteristics of the patient. The most commonly used techniques included regional flaps, local flaps, and skin grafts. The most frequently employed reconstruction techniques were forehead flaps (59 cases), simple excisions (38 cases), and Mustarde cheek flaps (16 cases). Result: The postoperative complications, including ectropion, epiphora, and flap necrosis, were recorded. However, no significant correlation was found between the risk of complications and either the location of the tumour or the reconstruction method employed. Despite the complexity of medial canthal and lower eyelid reconstruction, satisfactory aesthetic and functional outcomes were generally achieved. Conclusions: This study emphasises the importance of individualised surgical planning, highlighting the advantages and limitations of various techniques to optimise both the functional and aesthetic results. Full article

Sub-national governments (SNGs) in developing countries have increasingly explored green municipal bonds as a financing tool, driven by promises of lower borrowing costs, enhanced reputation, and support for sustainable economic development. This study aims to critically examine these claims by analysing the actual costs and complexities associated with green municipal bonds (GMBs). The research involves a comparative analysis of traditional municipal bonds and GMBs, focusing on the financial and operational challenges faced by SNGs. Detailed case studies from Mexico City and Cape Town are used to illustrate the practical implications of issuing GMBs. The findings reveal that, despite similar or slightly lower interest rates, GMBs often entail higher issuance costs due to the need for certification, monitoring, and reporting of green projects. These additional costs, coupled with the necessity of hiring external consultants, make GMBs more expensive and difficult to replicate after initial transactions. Furthermore, the study highlights that the demand from investors has not met initial expectations. While green-aligned investors show a higher appetite for GMBs, they constitute only a small portion of the finance market. Traditional investors, primarily focused on financial returns, are less inclined to invest in GMBs solely based on their green label. Consequently, many SNGs are increasingly turning to traditional “vanilla” municipal bonds as a more viable option for financing green initiatives. This shift underscores the practical challenges of GMB issuance in developing countries and calls for a strategic approach to balance the use of GMBs with other financing options to promote sustainable economic development. Full article

Ventricular pre-excitation (VP) is a cardiac disorder characterized by the presence of an accessory pathway (AP) that bypasses the atrioventricular node (AVN), which, although often asymptomatic, exposes individuals to an increased risk of re-entrant supraventricular tachycardias and sudden cardiac death (SCD) due to rapid atrial fibrillation (AF) conduction. This condition is particularly significant in sports cardiology, where preparticipation ECG screening is routinely performed on athletes. Professional athletes, given their elevated risk of developing malignant arrhythmias, require careful assessment. Early identification of VP and proper risk stratification are crucial for determining the most appropriate management strategy and ensuring the safety of these individuals during competitive sports. Non-invasive tools, such as resting electrocardiograms (ECGs), ambulatory ECG monitoring, and exercise stress tests, are commonly employed, although their interpretation can sometimes be challenging. This review aims to provide practical tips and electrocardiographic clues for detecting VP beyond the classical triad (short PR interval, delta wave, and prolonged QRS interval) and offers guidance on non-invasive risk stratification. Although the diagnostic gold standard remains invasive electrophysiological study, appropriate interpretation of the ECG can help limit unnecessary referrals for young, often asymptomatic, athletes. Full article

Introduction: Clinical simulation has been used as a teaching strategy for students in health programmes, fostering greater preparedness and confidence in performing procedures. Objective: This study aimed to analyse the perception of fourth-semester nursing students and teachers regarding the simulated practice methodology implemented in a private university in Cali, Colombia. Method: A robust mixed-methods approach was used, incorporating quantitative surveys and qualitative interviews with 41 students and 5 teaching nursing faculty members. Data triangulation was applied to ensure the robustness of the results. Results: Both students and teachers reported a positive perception of simulated practice, which contributes to knowledge acquisition and contextual learning. Students emphasised that simulation improved their prior knowledge and motivated them to explore new topics. Lecturers emphasised the importance of well-trained instructors in simulation environments. However, participants identified challenges affecting performance, including simulation duration, group size, realism, and resource constraints. Conclusions: Students and teachers recommend strategic changes to the curriculum to optimise simulation practices. Full article

This study presents an optimized container-stowage plan using reinforcement learning to tackle the complex logistical challenges in maritime shipping. Traditional stowage-planning methods often rely on manual processes that account for factors like container weight, unloading order, and balance, which results in significant time and resource consumption. To address these inefficiencies, we developed a two-phase stowage plan: Phase 1 involves bay selection using a Proximal Policy Optimization (PPO) algorithm, while Phase 2 focuses on row and tier placement. The proposed model was evaluated against traditional methods, demonstrating that the PPO algorithm provides more efficient loading plans with faster convergence compared to Deep Q-Learning (DQN). Additionally, the model successfully minimized rehandling and maintained an even distribution of weight across the vessel, ensuring operational safety and stability. This approach shows great potential for enhancing stowage efficiency and can be applied to real-world shipping scenarios, improving productivity. Future work will aim to incorporate additional factors, such as container size, type, and cargo fragility, to further improve the robustness and adaptability of the stowage-planning system. By integrating these additional considerations, the system will become even more capable of handling the complexities of modern maritime logistics. Full article

Federated learning offers a framework for developing local models across institutions while safeguarding sensitive data. This paper introduces a novel approach for heart disease prediction using the TabNet model, which combines the strengths of tree-based models and deep neural networks. Our study utilizes the Comprehensive Heart Disease and UCI Heart Disease datasets, leveraging TabNet’s architecture to enhance data handling in federated environments. Horizontal federated learning was implemented using the federated averaging algorithm to securely aggregate model updates across participants. Blockchain technology was integrated to enhance transparency and accountability, with smart contracts automating governance. The experimental results demonstrate that TabNet achieved the highest balanced metrics score of 1.594 after 50 epochs, with an accuracy of 0.822 and an epsilon value of 6.855, effectively balancing privacy and performance. The model also demonstrated strong accuracy with only 10 iterations on aggregated data, highlighting the benefits of multi-source data integration. This work presents a scalable, privacy-preserving solution for heart disease prediction, combining TabNet and blockchain to address key healthcare challenges while ensuring data integrity. Full article