Search Results (202)

Background/Objectives: Fungal colonization and biofilm formation on intrauterine device (IUD) strings are known to contribute to recurrent infections and decreased contraceptive efficacy. This study aims to develop a novel approach to prevent Candida reservoir and biofilm formation on IUD strings, thereby lowering the risk of IUD-associated vulvovaginal candidiasis (VVC). Methods: Cervicovaginal samples were collected from human cervix using a sterile cytobrush, avoiding microbial contamination. Cytological examination using the Papanicolaou method was performed to detect the presence of Candida. The antifungal effect of the essential oils (EOs) was determined by broth dilution and disk diffusion methods. Antifungal and biofilm inhibitory effects of Thymus zygis (Tz) EO-coated IUD strings were determined by agar diffusion and crystal violet binding assays, while fungal growth on the coated strings was assessed using Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray (EDX) analysis. Results: Tz EO exhibited significantly lower minimum inhibitory concentration (MIC ≤ 0.06 µL/mL) and minimum fungicidal concentration (MFC = 0.24 µL/mL) values compared to Melaleuca alternifolia (Ma) EO (MIC > 0.24 µL/mL, MFC = 1.95 µL/mL), along with larger zones of inhibition (ZOI) against both Candida albicans (110.0 ± 6.0 mm vs. 91.3 ± 7.0 mm) and Candida glabrata (84.0 ± 13.1 mm vs. 50.0 ± 9.2 mm), indicating a stronger antifungal potential. On IUD strings coated with 4% (40 μL/g) Tz EO in hypromellose ointment, the biofilm formation of both C. albicans and C. glabrata strains was inhibited by 58.9% and 66.7%, respectively, as confirmed by SEM and EDX. Conclusions: Tz EO-coated IUD strings effectively inhibit Candida growth, suggesting a promising natural strategy to reduce recurrent IUD-associated fungal infections. However, before these results can be translated to clinical practice, additional research is needed. Future investigations may encompass an extended number of Candida isolates, stability and release studies of the EO in relation to the formulation, toxicity to vaginal mucosa, epithelial cells and sperm motility, and the effect on vaginal microbiotia. Full article

Per- and polyfluoroalkyl substances (PFASs) are highly chemically stable synthetic compounds. They are widely used in industrial and commercial sectors due to their ability to repel water and oil, thermal stability, and surfactant properties. However, this stability results in environmental persistence and bioaccumulation, posing significant health risks as PFASs eventually find their way into environmental media. Key PFAS compounds, including PerFluoroOctanoic Acid (PFOA), PerFluoroOctane Sulfonic acid (PFOS), and PerFluoroHexane Sulfonic acid (PFHxS), have been linked to hepatotoxicity, immunotoxicity, neurotoxicity, and endocrine disruption. In response to the health threats these substances pose, global regulatory measures, such as the Stockholm Convention restrictions and national drinking water standards, have been implemented to reduce PFAS exposure. Despite these efforts, a lack of universally accepted definitions or comprehensive inventories of PFAS compounds hampers the effective management of these substances. As definitions differ across regulatory bodies, research and policy integration have become complicated. PFASs are broadly categorized as either perfluoroalkyl acids (PFAAs), precursors, or other fluorinated substances; however, PFASs encompass over 5000 distinct compounds, many of which are poorly characterized. PFAS contamination arises from direct industrial emissions and indirect environmental formation, these substances have been detected in water, soil, and even air samples from all over the globe, including from remote regions like Antarctica. Analytical methods, such as primarily liquid and gas chromatography coupled with tandem mass spectrometry, have advanced PFAS detection. However, standardized monitoring protocols remain inadequate. Future management requires unified definitions, expanded monitoring efforts, and standardized methodologies to address the persistent environmental and health impacts of PFAS. This review underscores the need for improved regulatory frameworks and further research. Full article

Engine oil condition critically affects vehicle performance, fuel efficiency, and engine durability. While conventional oil change strategies are based on fixed intervals or mileage thresholds, they often neglect real operating conditions and the actual state of lubricant degradation. This study investigates nine used engine oil samples collected from passenger vehicles operating in diverse environments, including city traffic, highway routes, hybrid systems, and diesel engines. The oils were assessed using kinematic viscosity measurements and Fourier transform infrared (FTIR) spectroscopy to monitor key degradation indicators—oxidation, nitration, sulfonation, fuel dilution, soot contamination, and additive depletion. Each case is fully documented with detailed operational histories, facilitating a nuanced, real-world understanding of oil aging. The results demonstrate that degradation levels vary considerably, even under similar mileage ranges, highlighting the influence of urban usage patterns and engine design. In several cases, premature or delayed oil changes were observed, confirming that standard service intervals may be suboptimal. FTIR proved effective in detecting subtle chemical transformations, particularly in samples affected by biofuel components or prolonged thermal stress. These findings emphasize the value of integrating laboratory diagnostics into oil change decision-making and support more tailored maintenance strategies. Such an approach can reduce unnecessary oil replacement, limit waste generation, and extend engine lifespan, contributing to both environmental and economic sustainability. This study supports the implementation of condition-based oil change strategies to minimize lubricant waste and promote maintenance practices aligned with sustainability principles. Full article

The marine environment has long been affected by chronic operational oil pollution, leading to the deaths of hundreds of thousands of seabirds. In many countries Beached Bird Survey programmes have been established, in which dead birds with oil-contaminated plumage are counted along shorelines. This study analyses data from Beached Bird Surveys conducted in the western Gulf of Gdańsk (southern Baltic Sea) between 1965/66 and 2024/25 to assess long-term trends in oil pollution. Over a total of 55 seasons, 12,264 dead birds representing 49 different species were recorded, of which 2748 individuals (22%) had oiled plumage. The oil rate was very high up to the 1977/78 season, ranging from 58% to 95%. During that period, the highest densities of oiled birds were also recorded, with values exceeding 20 individuals. A significant decline in the number of oiled birds occurred in the early 1980s, and, apart from two anomalous seasons in the mid-1990s, numbers have remained low since then. This sharp drop coincides with the enforcement of MARPOL regulations and the introduction of regular aerial surveillance to detect oil spills and identify violators. The resulting reduction in ship-based pollution has supported more sustainable use of this ecologically important marine region. The findings highlight the effectiveness of international regulations and monitoring efforts in reducing chronic oil pollution and improving the health of the Baltic Sea ecosystem. Full article

As the safety requirements of elevator systems continue to rise, the detection of loose bolts and the high-precision segmentation of anti-loosening lines have become critical challenges in elevator landing door inspection. Traditional manual inspection and conventional visual detection often fail to meet the requirements of high precision and robustness under real-world conditions such as oil contamination and low illumination. This paper proposes two improved algorithms for detecting loose bolts and segmenting anti-loosening lines in elevator landing doors. For small-bolt detection, we introduce the DS-EMA model, an enhanced YOLOv8 variant that integrates depthwise-separable convolutions and an Efficient Multi-scale Attention (EMA) module. The DS-EMA model achieves a 2.8 percentage point improvement in mAP over the YOLOv8n baseline on our self-collected dataset, while reducing parameters from 3.0 M to 2.8 M and maintaining real-time throughput at 126 FPS. For anti-loosening-line segmentation, we develop an improved DeepLabv3+ by adopting a MobileViT backbone, incorporating a Global Attention Mechanism (GAM) and optimizing the ASPP dilation rate. The revised model increases the mean IoU to 85.8% (a gain of 5.4 percentage points) while reducing parameters from 57.6 M to 38.5 M. Comparative experiments against mainstream lightweight models, including YOLOv5n, YOLOv6n, YOLOv7-tiny, and DeepLabv3, demonstrate that the proposed methods achieve superior accuracy while balancing efficiency and model complexity. Moreover, compared with recent lightweight variants such as YOLOv9-tiny and YOLOv11n, DS-EMA achieves comparable mAP while delivering notably higher recall, which is crucial for safety inspection. Overall, the enhanced YOLOv8 and DeepLabv3+ provide robust and efficient solutions for elevator landing door safety inspection, delivering clear practical application value. Full article

Lubricating oils are utilised in equipment and machinery to reduce friction and enhance material utilisation. The utilisation of oil leads to an increase in its thickness and density over time. Current methods for assessing oil life are slow, expensive, and complex, and often only applicable in laboratory settings and unsuitable for real-time or field use. This leads to unexpected equipment failures, unnecessary oil changes, and economic and environmental losses. A comprehensive review of the extant literature revealed no studies and no national or international patents on neural network algorithm-based oil life modelling and classification using green sensors. In order to address this research gap, this study, for the first time in the literature, provides a green conductivity sensor with high-accuracy prediction of oil life by integrating real-time field measurements and artificial neural networks. This design is based on analysing resistance change using a relatively low-cost, three-dimensional, eco-friendly sensor. The sensor is characterised by its simplicity, speed, precision, instantaneous measurement capability, and user-friendliness. The MLP and LVQ algorithms took as input the resistance values measured in two different oil types (diesel, bench oil) after 5–30 h of use. Depending on their degradation levels, they classified the oils as ‘diesel’ or ‘bench oil’ with 99.77% and 100% accuracy. This study encompasses a sensing system with a sensitivity of 50 µS/cm, demonstrating the proposed methodologies’ efficacy. A next-generation decision support system that will perform oil life determination in real time and with excellent efficiency has been introduced into the literature. The components of the sensor structure under scrutiny in this study are conducive to the creation of zero waste, in addition to being environmentally friendly and biocompatible. The developed three-dimensional green sensor simultaneously detects physical (resistance change) and chemical (oxidation-induced polar group formation) degradation by measuring oil conductivity and resistance changes. Measurements were conducted on simulated contaminated samples in a laboratory environment and on real diesel, gasoline, and industrial oil samples. Thanks to its simplicity, rapid applicability, and low cost, the proposed method enables real-time data collection and decision-making in industrial maintenance processes, contributing to the development of predictive maintenance strategies. It also supports environmental sustainability by preventing unnecessary oil changes and reducing waste. Full article

This paper is a result of the search for design assumptions for a sensor to detect oil dispersed in the sea waters (oil-in-water emulsions). Our approach is based on analyzing changes in the underwater solar radiance (L) field caused by the presence of oil droplets in the water column. This method would enable the sensor to respond to the presence of oil contaminants dispersed in the surrounding environment, even if they are not located directly at the measurement point. This study draws on both literature sources and the results of current numerical modeling of the spread of solar light in the water column to account for both downward and upward irradiance (Es). The core principle of the analysis involves simulating the paths of a large number of virtual solar photons in a seawater model defined by spatially distributed Inherent Optical Properties (IOPs). The IOPs data were taken from the literature and pertain to the waters of the southern Baltic Sea. The optical properties of the oil used in the model correspond to crude oil extracted from the Baltic shelf. The obtained results were compared with previously published spectral analyses of an analogous polluted sea model, considering vertical downward radiance, vertical upward radiance, and downward and upward irradiance. It was found that the optimal wavelength ratio of 555/412, identified for these quantities, is also applicable to scalar irradiance. The findings indicate that the most effective way to determine this index is by measuring it using a sensor with its window oriented in the direction of upward-traveling light. Full article

Hospital-acquired infections (HAIs) remain a major clinical and economic burden, with pathogens such as Escherichia coli contributing to high rates of morbidity and mortality. Traditional manual disinfection methods are often insufficient, particularly in high-risk hospital environments. In this study, we investigated innovative strategies to enhance surface decontamination and reduce infection risk. First, we assessed the efficacy of the SMEG BPW1260 bedpan washer-disinfector, a thermal disinfection system for human waste containers. Our results demonstrated a reduction in Clostridium difficile and Escherichia coli contamination by >99.9% (>3 log reduction), as measured by colony-forming units (CFU) before and after treatment. Molecular techniques, including spectrophotometry, cell counting, and quantitative PCR (qPCR) for DNA quantification, confirmed reduction in bacterial contamination. Specifically, Clostridium difficile showed a reduction of approximately 89% in both optical density (OD) and cell count (cells/mL). In the case of Escherichia coli, a reduction of around 82% in OD was observed, with an even more pronounced decrease in cell count, reaching approximately 99.3%. For both bacteria, DNA quantification by qPCR was below detectable limits. Furthermore, we optimized the energy efficiency of the disinfection cycle, achieving a 45% reduction in power consumption compared to standard protocols without compromising antimicrobial efficacy. Secondly, we developed a sustainable cleaning solution based on methyl ester sulfonate surfactants derived from waste cooking oil. The detergent’s antibacterial activity was tested on contaminated surfaces and further enhanced through the incorporation of nanoassemblies composed of silver, electrostatically bound either to biomimetic magnetic nanoparticles or to conventional magnetic nanoparticles. Washing with the detergent alone effectively eliminated detectable contamination, while the addition of nanoparticles inhibited bacterial regrowth. Antimicrobial testing against E. coli revealed that the nanoparticle-enriched formulations reduced the average MIC values by approximately 50%, with MIC₅₀ values around 0.03–0.06 mg/mL and MIC₉₀ values between 0.06 and 0.12 mg/mL, indicating improved inhibitory efficacy. Finally, recognizing the infection risks associated with intra-hospital transport, we tested the SAFE-HUG Wheelchair Cover, a disposable non-woven barrier designed to reduce patient exposure to contaminated wheelchair surfaces. Use of the cover resulted in a 3.3 log reduction in surface contamination, based on viable cell counts. Optical density and bacterial DNA were undetectable in all covered samples at both 1 and 24 h, confirming the strong barrier effect. Together, these approaches—thermal no-touch disinfection, eco-friendly detergent boosted with nanoparticles, and protective transport barriers—respond to the urgent need for effective, sustainable infection control methods in healthcare settings. Our findings demonstrate the potential of these systems to counteract microbial contamination while minimizing environmental impact, offering promising solutions for the future of infection prevention in healthcare settings. Full article

Microbial fuel cells (MFCs) can have high pollutant removal efficiencies and generate electricity; however, the use of selective membranes represents a considerable expense. In this investigation, the performance of a membraneless MFC was evaluated at different hydraulic retention times (HRTs) of 12, 24, 36, and 48 h. The chemical oxygen demand removal efficiencies (CODREs) were 93.5, 90.9, 87.3, and 85.4%, and the biochemical oxygen demand (BODRE) values were 94.5, 91.5, 88.9, and 85.5 at HRTs of 48, 36, 24, and 12 h, respectively. Lower concentrations of solids (suspended solids and total dissolved solids), total nitrogen, phosphorus, fats and oils, and microbiological contamination (helminth eggs and fecal coliforms) were detected when operating the system at a 48 h HRT. At an HRT of 12 h, no decrease in electrical conductivity was detected, whereas at 48 h, it decreased by 19.6%. The oxidation–reduction potential and OCV increased at longer HRTs. The microorganisms detected at the anode were Achromobacter denitrificans, Achromobacter anxifer, and Pseudomonas aeruginosa. The 48 h HRT improved the chemical, physical, and microbiological quality of the municipal wastewater, favoring voltage generation. Full article

Lubricant condition analysis is a valuable diagnostic tool for assessing engine performance and ensuring the reliable operation of diesel engines. While traditional diagnostic techniques—such as Fourier transform infrared spectroscopy (FTIR)—are constrained by slow response times, high costs, and the need for specialized personnel. In contrast, dielectric spectroscopy, impedance analysis, and soft computing offer real-time, non-destructive, and cost-effective alternatives. This review examines recent advances in integrating these techniques to predict lubricant properties, evaluate wear conditions, and optimize maintenance scheduling. In particular, dielectric and impedance spectroscopies offer insights into electrical properties linked to oil degradation, such as changes in viscosity and the presence of wear particles. When combined with soft computing algorithms, these methods enhance data analysis, reduce reliance on expert interpretation, and improve predictive accuracy. The review also addresses challenges—including complex data interpretation, limited sample sizes, and the necessity for robust models to manage variability in real-world operations. Future research directions emphasize miniaturization, expanding the range of detectable contaminants, and incorporating multi-modal artificial intelligence to further bolster system robustness. Collectively, these innovations signal a shift from reactive to predictive maintenance strategies, with the potential to reduce costs, minimize downtime, and enhance overall engine reliability. This comprehensive review provides valuable insights for researchers, engineers, and maintenance professionals dedicated to advancing diesel engine lubricant monitoring. Full article

Large steam turbine generators are increasingly vulnerable to damage from shaft voltages and bearing currents due to the widespread adoption of modern power electronic excitation systems and more flexible operating regimes. Earthing brushes provide a critical path for discharging these shaft currents and voltages, but their effectiveness depends on the timely detection of brush degradation or faults. Conventional monitoring of shaft voltage and current is often rudimentary, typically limited to peak readings, making it challenging to identify specific fault conditions before mechanical damage occurs. This study addresses this gap by systematically analyzing shaft voltage and current signals under various controlled earthing brush fault conditions (floating brushes, worn brushes, and oil/dust contamination) in several large turbine generators. Experimental site tests identified distinct electrical signatures associated with each fault type, demonstrating that online shaft voltage and current measurements can reliably detect and classify earthing brush faults. These include unique RMS, DC, and harmonic patterns in both voltage and current signals, enabling accurate fault classification. These findings highlight the potential for more proactive maintenance and condition-based monitoring, which can reduce unplanned outages and improve the reliability and safety of power generation systems. Full article

The global consumption of fresh and ready-to-eat (RTE) fruits and vegetables has surged due to increasing awareness of their nutritional benefits. However, this trend has been accompanied by a rise in foodborne illness outbreaks linked to microbial contamination. This narrative review synthesizes current knowledge on the prevalence and diversity of foodborne pathogens in fresh produce, including bacterial, viral, and fungal agents. It critically evaluates both conventional and emerging detection methods, ranging from culture-based techniques and immunoassays to advanced molecular diagnostics, biosensors, flow cytometry (FC), and hyperspectral imaging (HSI). Additionally, this review discusses cutting-edge control strategies, such as natural antifungal agents, essential oils, biocontrol methods, and non-thermal technologies like cold plasma and UV-C treatment. Emphasis is placed on sampling methodologies, sustainability, One Health perspectives, and regulatory considerations. By highlighting recent technological advances and their limitations, this review aims to support the development of integrated, effective, and safe microbial control approaches for the fresh produce supply chain. Full article

In this study, we introduce a novel Electrowetting-on-Dielectric (EWOD) sensor designed to quantify marine dispersants at the spill point. The sensor quantifies changes in the surface tension of liquid droplets at varying dispersant concentrations through the deformation response of the droplet under applied voltage. Analyzed responses include droplet length and contact angle (CA) on the device surface upon sensor activation. This sensor offers significant advantages over existing chemical methods, which are costly and complex. Moreover, compared to conventional methods based on the same principle, it demonstrates enhanced sensitivity at low concentrations. Additionally, the sensor’s portability enables instantaneous and in situ measurements of marine dispersant concentrations, thus providing a crucial tool for effective oil spill response by facilitating on-site decision-making and offering higher temporal resolution for studies on the marine dispersant’s environmental impact. The device’s potential extends beyond marine dispersants to detecting various contaminants affecting surface tension. Its adaptability underscores the EWOD device’s role as a versatile tool for environmental monitoring and on-site analysis, addressing the urgent need for efficient and sustainable solutions in environmental management. Full article

Petroleum pollution has become a substantial challenge in soil ecology. The soil bacterial consortia play a major role in the biodegradation of petroleum hydrocarbons. The main objective of this study was to assess changes in bacterial composition and diversity in oil-contaminated dryland soils. The Illumina MiSeq high-throughput sequencing technique was used to study the bacterial diversity and structural change in hyper-arid oil-contaminated soil in the Arava Valley of Israel. The diversity and abundance of soil bacteria declined significantly following oil pollution. The dominant phyla in the petroleum-contaminated soils were Proteobacteria (~33% higher vs. control soil) and Patescibacteria (~2.5% higher vs. control soil), which are oil-associated and hydrocarbon-degrading bacteria. An opposite trend was found for the Actinobacteria (~8%), Chloroflexi (12%), Gemmatimonadetes (3%), and Planctomycetes (2%) phyla, with the lower abundances in contaminated soil vs. control soil. Investigation of long-term contaminated sites revealed significant genus-level taxonomic restructuring in soil bacterial communities. The most evident changes were observed in Mycobacterium, Alkanindiges, and uncultured bacterium-145, which showed marked abundance shifts between spill and control soils across decades. Particularly, hydrocarbon-degrading genera such as Pseudoxanthomonas demonstrated persistent dominance in contaminated sites. While some genera (e.g., Frigoribacterium, Leifsonia) declined over time, others—particularly Nocardioides and Streptomyces—exhibited substantial increases by 2014, suggesting potential ecological succession or adaptive selection. Minor but consistent changes were also detected in stress-tolerant genera like Blastococcus and Quadrisphaera. The effect of oil contamination on species diversity was greater at the 1975 site compared to the 2014 site. These patterns highlight the dynamic response of bacterial communities to chronic contamination, with implications for bioremediation and ecosystem recovery. The study results provide new insights into oil contamination-induced changes in soil bacterial community and may assist in designing appropriate biodegradation strategies to alleviate the impacts of oil contamination in drylands. Full article

A certified reference material (CRM) for aflatoxins (AFTB1, AFTB2, AFTG1, AFTG2) and zearalenone (ZEN) in corn/peanut blended vegetable oil (GBW(E)100863) was developed to address the critical need for matrix-specific reference materials in mycotoxin analysis. The CRM was prepared by blending naturally contaminated corn and peanut oils, followed by homogenization, sterilization, and sub-packing. Homogeneity and stability studies were conducted using high-performance liquid chromatography isotope-dilution tandem mass spectrometry with a dilute-and-shoot pretreatment process. The CRM demonstrated excellent homogeneity and stability, with no significant degradation observed under either short-term (65 °C for 14 days) or long-term (25 °C for 12 months) storage conditions. An inter-laboratory comparison involving six authoritative laboratories confirmed the CRM’s accuracy and reliability, with recovery rates ranging from 90.3% to 97.3% and low relative standard deviations (RSDs) of 3.79% to 7.99%. The CRM provided a robust metrological tool for mycotoxin analysis in complex oil matrices. This study not only enriches the national reference materials library but also supports food safety initiatives by facilitating accurate and reliable mycotoxin detection in vegetable oils, thereby enhancing regulatory compliance and public health protection. Full article