Search Results (9,169)

The chemical components of the e-liquids and aerosols contained in electronic nicotine delivery systems (ENDSs), better known as vapes, were evaluated. The analytical technique used was gas chromatography–mass spectrometry, where the extraction and injection methods were established in this study. The work consisted of the analysis of twenty samples of disposable electronic cigarettes prefilled with new e-liquid, of a known brand, flavor, volume, and, in some of them, the percentage of nicotine and the number of puffs per device were indicated on the label. We detected the presence of many substances (at a qualitative and semi-quantitative level), and we achieved the quantification of benzene, toluene, and xylenes (BTX), dangerous substances that cause severe damage to health. Several of the e-liquids and aerosols present BTX concentrations above the permissible exposure limit (PEL), recommended by the Occupational Safety and Health Administration (OSHA): benzene in aerosol samples 80% > PEL, and toluene in aerosol samples 45% > PEL. The number of chemical compounds found in the samples increases from 13 to 167, the average being 52 compounds for the water extraction method, 42 compounds for the methanol extraction method of e-liquids, and 107 compounds for the direct aerosol analysis. It is a fact that many of those compounds, especially BTX, can cause serious effects on human health, affecting the respiratory, digestive, cardiovascular, pulmonary, and immune systems, as well as the brain. Therefore, the use of these devices should be considered with caution, since the substances and their chemical nature may pose significant health risks to both users and those exposed to secondhand emissions. Full article

This paper presents the fuzzy real-time safety level (Fuzzy RealTSL) methodology. It aims to address the data uncertainties resulting from a lack of sensors in complex sociotechnical systems and reduce the need for the determination of their safety level in real-time during their operation. To achieve this, the methodology utilizes: (1) safety constraints from STPA (systems theoretic process analysis) analysis and EWaSAP (early-warning-signs analysis process), (2) fuzzy logic as the mathematical backbone to identify the degree of confidence about the occurrence of unsafe system states, (3) a modified centroid point and spread ordering to enable ordering sequences of unsafe system states that can lead to accidents according to how detrimental they are to the system safety. The RealTSL methodology is presented through its step-by-step application to the panel alignment system of a solar park utilizing rotating solar arrays. This paper aims to open a new perspective on the STAMP literature for discussions of uncertainties from a lack of information about the system’s state and to make it easier to measure its safety level. Knowing the safety level of a system in real-time is crucial for the systems in question as it enables proactive risk management and enhances decision-making by providing immediate insights into potential hazards, thus safeguarding against accidents. Full article

Sulla coronaria is indigenous to the Mediterranean region. It is grown as fodder in southern Italy because it contains various secondary metabolites with beneficial activities on animals. Recently, its potential use in cosmeceutical treatments for skin problems was reported. In this scenario, to contribute to a possible cosmeceutical application, we characterized the phytochemical profile of Sulla coronaria flowers’ hydroalcoholic extract by HPLC-DAD, Folin-Ciocalteu, Aluminum Chloride methods, DPPH assay, and, for the first time, we evaluated the antioxidant and anti-inflammatory activities on dermal fibroblasts. The phytochemical analysis confirmed the significant content of phenolic compounds (TPC 69.8 ± 0.6 mg GAE/g extract, TFC 15.07 mg CE/g extract) and the remarkable presence of rutin, quercetin, and isorhamnetin derivatives that give to the phytocomplex a good antioxidant activity as highlighted by the DPPH assay (IC₅₀ of 8.04 ± 0.5 µg/mL). Through the reduction in NO• and ROS levels in human dermal fibroblasts, the biological tests demonstrated both the safety of the extract and its ability to counteract the inflammatory state generated by Interleukin-1β exposure. Our findings indicate that the antioxidant activities of the phytocomplex are strictly related to the anti-inflammatory action of the Sulla coronaria flowers extract, confirming that this plant could be a valuable source of bioactive molecules for cosmeceutical and nutraceutical applications. Full article

The aerospace industry faces the challenge of maintaining product excellence amidst intricate processes and demands for cost and time efficiency. Mathematical modeling emerges as a valuable tool for optimizing the engineering process and enhancing quality, with potential applications extending beyond aerospace to other sectors with high quality and safety standards. This study develops and validates a mathematical model specific to the aerospace industry, aiming to assess the impact of human resource expertise on product quality. Through a case study within an aerospace organization, an IDEF0-methodology-based mathematical model, coupled with weighted averages, was constructed to depict the comprehensive engineering process and quantify knowledge’s impact on deliverable quality. Simulation data, gathered through human resource knowledge assessments and non-conformity analyses, revealed a direct correlation between technical knowledge levels and deliverable quality, consequently impacting final product quality. The proposed model serves as a tool for estimating potential deliverable error rates and pinpointing critical areas within the process that necessitate refinement. The research underscores the significance of knowledge investment and effective knowledge management strategies in upholding quality and competitiveness across industries with stringent quality requirements. Full article

Background: Millions of people’s access to food is threatened by the prevalence of micronutrient deficiencies in food, particularly in low- and middle-income nations. Objectives: The aim of this study was to evaluate the socio-economic impact of fortified food products on improving the food security of consumers in these regions. Methods: This study examined the use of popular products, such as yogurt fortified with inactive baker’s yeast, from April 2023 to December 2023. A questionnaire was developed using a descriptive–inferential approach grounded in practical research. Results: The factors of expertise, level of education, and gender significantly influenced the enhancement of food security. Approximately 88% of the variations in food security enhancement factors were attributed to acceptance and consumption, food safety and health, and financial capability and pricing. Among these factors, the acceptance index made the greatest contribution to improving food security. Conclusions: Specialized communication and information operations are urgently needed in this area, considering the limited knowledge consumers have about the health effects of newly introduced fortified foods. Therefore, by addressing current shortcomings, this study can help planners, policymakers, and producers of fortified food items increase the demand for fortified goods and improve national food security. Full article

Due to the flammable and explosive nature of explosives, there are significant potential hazards and risks during transportation. During the operation of explosive transport vehicles, there are often situations where the vehicles around them approach or change lanes abnormally, resulting in insufficient avoidance and collision, leading to serious consequences such as explosions and fires. Therefore, in response to the above issues, this article has developed an explosive transport vehicle driving warning system based on object detection algorithms. Consumer-level cameras are flexibly arranged around the vehicle body to monitor surrounding vehicles. Using the YOLOv4 object detection algorithm to identify and distance surrounding vehicles, using a game theory-based cellular automaton model to simulate the actual operation of vehicles, simulating the driver’s decision-making behavior when encountering other vehicles approaching or changing lanes abnormally during actual driving. The cellular automaton model was used to simulate two scenarios of explosive transport vehicles equipped with and without warning systems. The results show that when explosive transport vehicles encounter the above-mentioned dangerous situations, the warning system can timely issue warnings, remind drivers to make decisions, avoid risks, ensure the safety of vehicle operation, and verify the effectiveness of the warning system. Full article

Self-driving cars are one of the main areas of research today, but it has to be acknowledged that the information from the sensors (the perceptron) is a huge amount of data, which is now unmanageable even when projected onto a single traffic junction. In the case of self-driving, the nodes have to be sequenced and organized according to the planned route. A self-driving car in Hungary would have to be able to interpret more than 70,000 traffic junctions to be able to drive all over the country. Besides the huge amount of data, another problem is the issue of validation and verification. For self-driving cars, this implies a level of complexity using traditional methods that calls into question the economics of the already existing system. Fuzzy Petri nets provide an alternative solution to both problems. They allow us to obtain a model that accurately describes the reliability of a node through its dynamics, which is essential in perception since the more reliable a node is, the smaller the deep learning mesh required. In this paper, we outline the analysis of a traffic node’s safety using Petri nets and fuzzy analysis to gain information on the reliability of the node, which is essential for the modeling of self-driving cars, due to the deep learning model of perception. The reliability of the dynamics of the node is determined by using the modified fuzzy Petri net procedure. The need for a fuzzy extension of the Petri net was developed by knowledge of real traffic databases. Full article

Potential multi-ship conflict situations in coastal or near-shore port areas have always been one of the important factors affecting ship navigation safety and a key target of maritime traffic regulatory authorities. In recent years, with the continuous development and integration of various emerging technologies in the maritime field, maritime traffic supervision has also shown a trend of intelligent and autonomous development. The traditional supervision method dominated by human experience is evolving towards data and model-driven practices. In order to solve the problem of ship navigation safety supervision under multi-ship conflict scenarios, it is urgent to build an intelligent conflict mitigation decision-making model. Therefore, this paper designs a novel risk mitigation decision-making model for multi-ship conflict scenarios from the perspective of maritime supervision. The model proposed in this paper first extracts high-density ship clusters based on AIS (Automatic Identification System) data and uses the MCD (Mean Core Density) and PRM (Proportion of Relative Motion) as feature indicators to further mine potential multi-ship conflict scenarios. Finally, a global optimization decision-making model is constructed to effectively mitigate conflict risks. Experimental verification shows that the intelligent decision-making model for the mitigation of maritime traffic conflict proposed in this paper can autonomously identify conflict scenarios and make reasonable decisions in real time. It can effectively ensure the navigation safety of ships in multi-ship conflict scenarios and further improve the supervision level of maritime departments. Full article

The use of dedicated lanes, known as managed lanes (MLs), on freeways is an established traffic management strategy to reduce congestion. Allowing automated vehicles (AVs) in existing MLs or dedicating MLs for AVs, referred to as AVMLs, has been suggested in the literature as a tool to improve traffic operation and safety performance as AVs and driver-operated vehicles (DVs) coexist in a mixed-vehicle environment. This paper focuses on investigating the safety impacts of deploying AVMLs on freeways by repurposing general-purpose lanes (GPLs). Four ML strategies considering different lane positions and access controls were implemented in a traffic microsimulation under different AV market adoption rates (MARs) and traffic demand levels, and trajectories were used to extract rear-end and lane change conflicts. The time-to-collision (TTC) surrogate safety measure was used to identify critical conflicts using a time threshold dependent on the type of following vehicle. Rates of conflicts involving different vehicle types for all ML strategies were compared to the case of heterogeneous traffic. The results indicated that the rates of rear-end conflicts involving the same vehicle type as the lead and following vehicle, namely DV-DV and AV-AV conflicts, increased with ML implementation as more vehicles of the same type traveled in the same lane(s). By comparing the aggregated conflict rates, the design options that were deemed to negatively impact traffic efficiency and capacity were also found to negatively impact traffic safety. However, other ML options were found to be feasible in terms of traffic operation and safety performance, especially at traffic demand levels below capacity. Specifically, one left-side AVML with continuous access was found to have lower or comparable aggregated conflict rates compared to heterogenous traffic at 25% and 50% MARs, and, thus, it is expected to have positive or neutral safety impacts. Full article

Background/Objectives: Uterine sarcoma, a rare cancer originating in the smooth muscle of the uterus, exhibits high rates of recurrence and metastasis. It represents one of the most challenging types of cancer due to its chemorefractory nature, showing little response to conventional chemotherapy methods and displaying a relative survival rate of 30–40%. A potentially promising approach for treating uterine sarcoma involves combination therapy with paclitaxel (PAC), a microtubule-targeting agent, and seliciclib (SEL), a cyclin-dependent kinase inhibitor. SEL has been identified as a drug that can enhance the effectiveness of PAC through synergistic effects. To further refine this treatment strategy, an efficient analytical tool capable of simultaneously measuring the concentrations of PAC and SEL in blood plasma is needed. This tool would make it easier to study the pharmacokinetic interactions of potential drugs and assist in monitoring therapy when administering this combination treatment. Regrettably, a method meeting these specific requirements has not been documented in the existing literature. Methods: This article introduces the first HPLC technique employing a PDA detector to concurrently measure PAC and SEL levels in plasma. The methodology underwent validation in accordance with the ICH standards for validating bioanalytical methods. Results: The method exhibited linearity in the concentrations ranging from 0.8 to 100 µg mL⁻¹ for both PAC and SEL. The limits of quantification were determined and found to be 1.34 and 1.25 µg mL⁻¹ for PAC and SEL, respectively. All the other validation criteria conformed to the ICH validation standards. The HPLC-PDA method was successfully employed to quantify both PAC and SEL in plasma samples with a high level of reliability (in terms of accuracy and precision). The eco-friendliness of the approach was verified using three thorough assessments. This technique serves as a valuable asset in establishing the correct dosage and administration schedule for the combined treatment involving PAC and SEL, ensuring the desired therapeutic effects and safety in managing uterine sarcoma. Conclusions: The proposed HPLC-PDA method is the first reliable and eco-friendly method developed to simultaneously determine PAC and SEL in high-throughput plasma samples in clinical laboratories. Full article

In today’s interconnected industrial landscape, the ability to predict and monitor the operational status of equipment is crucial for maintaining efficiency and safety. Diesel engines, which are integral to numerous industrial applications, require reliable fault detection mechanisms to reduce operational costs, prevent unplanned downtime, and extend equipment lifespan. Traditional anomaly detection methods, such as thermometry, wear indicators, and radiography, often necessitate significant expertise, involve costly equipment shutdowns, and are limited by high usage costs and accessibility. Addressing these challenges, this study introduces a novel approach for fault detection in diesel engines by analyzing torsional vibration data in the time domain. The proposed method leverages short-term Fourier transform (STFT) and continuous wavelet transform (CWT) techniques, integrated with a convolutional neural network (CNN) to identify hidden patterns and diagnose engine conditions accurately. The method achieved a detection accuracy of 96.5% with STFT and 92.2% with CWT. To ensure robustness, the model was tested under various noise conditions, maintaining accuracies above 70% for noise levels up to 40%. This research provides a practical and efficient solution for real-time fault detection in diesel engines, offering a significant improvement over traditional methods in terms of cost, accessibility, and ease of implementation. Full article

This study characterized the physicochemical properties of broiler poultry litter (BPL) produced from intensively reared commercial broilers that were collected from 110 commercial poultry farms at the end of the production cycle (sixth week). A further 20 samples were collected from the end use point where BPL was utilized as a soil amendment by the farmers after a period of storage for improving poultry litter management practices, developing new litter treatment technologies, or enhancing its use as a sustainable resource. The dry matter (DM), moisture, ash, organic matter (OM), and organic carbon (OC) from the manure samples were 83.04, 16.96, 27.08, 72.92, and 42.39%, respectively. The pH, electrical conductivity (EC) (dS m⁻¹), and Kjeldahl nitrogen (N) were 8.43, 5.74, and 24.2 g kg⁻¹, respectively. The BPL from the cement floor had higher levels of P and K than the mud floor. The correlation studies revealed that the OM, C, N, and Zn had significant positive correlations; pH, moisture, and ash had positive correlations; and EC, DM, and Ca had positive correlations. The EC level of BPL negatively correlated with pH, Fe, and Mn. The N content was found to have a highly significant (p < 0.01) positive correlation with the OM, OC, Ca, and Zn content of BPL, and it was found to have a highly significant (p < 0.01) negative correlation with the ash content, pH, and K content of BPL. The P content of BPL showed a positive correlation (p < 0.01) with the K content and a negative correlation with the Zn (p < 0.05) and Fe (p < 0.01) contents of BPL. Zn was found to be negatively (p < 0.01) correlated with the ash content; the pH; and the K, Fe, and P content of BPL. According to the findings of this study, BPL as such at the end of the production cycle is rich in OM, nitrogen, macrominerals, and microminerals; however, at the point of utility (after a period of storage of 4 to 6 months), there was a loss of OM, N, and mineral concentrations, highlighting the importance of proper storage and composting. Overall, this study on the physicochemical properties of broiler poultry litter is crucial for improving agricultural practices, protecting the environment, and preserving the health and safety of human beings and livestock. Full article

The rapid development of urbanization has led to population growth, increased resource consumption, and intensified environmental pollution. Consequently, urban ecological security has increasingly become a key factor constraining the sustainable development of socio-economic systems. This study constructed an urban ecological security evaluation system based on the Pressure-State-Response (PSR) model and used Xuzhou, a typical coal resource city, as a case study to apply and validate the model. Specifically, the analytic hierarchy process and entropy weight method were used to determine the index weights, and the ecological security index was used to evaluate the ecological security status of each system in Xuzhou from 2006 to 2022. Finally, the grey prediction GM (1,1) model was used to predict the ecological security status of Xuzhou in the next five years. The results show that the “disposal capacity of waste gas treatment facilities”, “per capita disposable income”, and “agricultural fertilizer application intensity” occupy a large weight in the whole evaluation system. The pressure index generally showed a fluctuating upward trend, and the state index fluctuated around 0.12. There is a simultaneous upward trend in the response index and the composite index. The ecological security level of the composite index has increased from “unsafe” in 2006 to “relatively safe” in 2022 and will continue to improve to “ideal security” in the future. This study provides a scientific basis for the formulation of sustainable development policies in Xuzhou and also provides a reference for the ecological safety management and assessment of other similar cities. Full article

Background: Intravenous thrombolysis is one of the most effective therapies for the treatment of acute ischemic stroke (AIS), with urokinase offering a cost-effective alternative to newer agents like alteplase and tenecteplase, especially in resource-limited settings. Methods: This review provides a comprehensive overview of the application of intravenous thrombolysis with urokinase for AIS in the clinical practice of stroke management, including the efficacy, safety, and cost-effectiveness of urokinase compared to other thrombolytic agents. Results: Urokinase, a first-generation thrombolytic drug, is a non-specific plasminogen activator that offers a cost-effective alternative. It has been used in clinical practice for over two decades to improve neurological outcomes in patients with AIS if administered within 6 h of ictus. Numerous studies have indicated that urokinase remains a viable option for patients who cannot access alteplase or tenecteplase because of economic constraints, time window limitations, availability, or other reasons. Conclusions: In low- and middle-income countries, urokinase is a cost-effective alternative thrombolytic drug. High-level evidence-based medical research is therefore urgently needed to confirm that urokinase is not inferior to new-generation thrombolytic drugs, and to assess whether it may even be superior in some patient populations. Full article

Gas extraction is crucial for coal mine safety, yet pipeline blockages by solid slag and water severely hinder efficiency and pose risks. Traditional detection methods are limited by rapid signal attenuation and noise interference. In this study, an acoustic detection technology is introduced for pipeline blockages, utilizing sensors at potential blockage points to collect sound wave data. Experiments with a scaled pipeline model reveal that slag blockages produce characteristic peaks in the 1200 Hz–2000 Hz range, while water blockages show peaks in the 1 kHz–2 kHz and 3.5 kHz–4.5 kHz bands. The longitudinal blockage intensity and extraction pressure significantly affect the sound pressure levels. A reliable fitting model predicts the blockage intensity based on acoustic signals, achieving high accuracy. This novel method enhances blockage identification, offering a non-invasive, cost-effective solution that improves coal mine safety and efficiency. Full article