Search Results (7,446)

Nitrosamines (NAs) pose a risk due to their carcinogenic properties, especially in processed and cured meats where nitrites and nitrates are widely used. The objective of this study was to develop an integrated Ultra-High-Performance Liquid Chromatography–High-Resolution Mass Spectrometry (UHPLC–HRMS) workflow for detecting both volatile (VNAs) and non-volatile (NVNAs) nitrosamines in meat matrices. Comparison of two ionization techniques showed that heated electrospray ionization (HESI) and atmospheric pressure chemical ionization (APCI) provided complementary coverage and sensitivity. Extraction and cleanup were optimized for meat, although recovery rates remained variable, underscoring the analytical complexity. The method was applied to raw, cooked, cured, and grilled meats, as well as to in vitro gastric digestion and co-digestion with spinach. Results revealed that some NAs were present even in untreated raw meat (≈3.0 µg/kg, N-nitrosodi-n-butylamine), while the addition of nitrites and nitrates significantly increased their levels (more than 10 µg/kg, N-nitrosodiethylamine, N-nitrosodimethylamine, N-nitrosodi-n-butylamine). Gastric digestion was the most critical condition, further promoting nitrosamine formation, particularly for N-nitrosodiethylamine, N-nitrosodi-n-butylamine, and N-nitrosopiperidine. Ascorbate exhibited a dual role, acting as an inhibitor at low nitrite concentrations but becoming pro-oxidant at high levels (300 mg/kg). Cooking alone had limited impact, whereas cooking combined with digestion yielded the highest and most consistent nitrosamine concentrations. The inclusion of spinach during digestion modestly altered nitrosamine levels, reflecting both its nitrate content and polyphenolic profile. Nonparametric ANOVA (aligned rank transform) confirmed that preservative treatment, rather than processing or interaction effects, was the main driver of variability (total nitrosamines: H = 24.15, p = 2.33 × 10⁻⁵), with the combination of preservative ascorbate plus nitrite producing significantly higher levels than other treatments (q = 0.000656). N-nitrosodimethylamine consistently emerged as the most relevant marker for dietary exposure, in agreement with EFSA guidance. Overall, this study underscores both the analytical and biochemical complexity of nitrosamine detection and formation in meat products, while highlighting the importance of preservative formulation and the potential role of dietary antioxidants in mitigating exposure. Full article

The agricultural sector is under increasing pressure to adopt sustainable practices without compromising profitability. A sustainable farm focuses on natural processes and renewable resources rather than on synthetic inputs. Social and digital innovations create new opportunities to address these challenges. Collective Awareness Platforms (CAPs) provide a socio-technical tool designed to encourage collaboration, knowledge sharing, and the adoption of sustainable practices among farmers. This research analyzes the potential of CAPs in a part of Greek agriculture based on data gathered from 182 participants in Macedonia and Thessaly. Results indicate that although 97.8% of participants use digital devices, awareness of CAPs remains very limited. Despite that, 51.1% were open to adopting new methods, and CAPs scored impressively high for their potential in knowledge transmission (μ = 4.21). These findings uncover both the potential benefits and challenges we face in integrating CAPs into sustainable farming. Policy implications involve the necessity to improve digital literacy and provide training, supported by European agricultural policies. Full article

There is a widespread belief that koala conservation measures should be focused on ending forestry operations in native forests and that plantations should be the alternative source for timber. While advocates for conservation continue to promote this strategic approach, they overlook the fact that hardwood plantations also provide important habitats. Ongoing operations in both natural and planted forests continue to threaten the viability of the koala species, and populations in one of the koala’s core habitats in northern New South Wales (NSW) continue to decline. To improve conservation outcomes for this species in the wild, the Great Koala National Park (GKNP) has been proposed. While the process of establishing this park continues, ongoing forestry operations exert continuous pressure on koalas and their habitat within the proposed area of the park. This paper investigates how community stakeholders are collaborating with scientists to identify areas of high koala habitat value within the hardwood eucalypt plantations inside the proposed GKNP that are currently excluded from conservation and will be subject to ongoing timber extraction. Investigations of Tuckers Nob State Forest, which is inside the proposal area, confirmed the presence of both koalas and original forest inside the plantations which were excluded from conservation by the state government. Original trees and remnants were identified using historical aerial photography, which were orthorectified and matched against current NSW government imagery (SIX Maps); composite mosaics of photographic sheets and closeups (Quantum GIS) were imported into Google Earth Pro. Koala drone surveys, habitat ground-truthing, and on-ground scat and koala surveys of 120 ha involving various community stakeholders were conducted in December 2024 and revealed 25 koalas, necessitating the reclassification of this area from plantation to prime koala habitat. Here, as in many other plantations in NSW, the findings of this study indicate significant numbers of original trees that are part of highly diverse nutrient-rich sites attractive to koalas. This leads to the conclusion that the exclusion of specific areas of the proposed park from conservation to allow for ongoing logging is inconsistent with recognized koala protection strategies. Hence, koala protection strategies need to consider the integrity of the reserve system in its entirety, and the whole area of the GKNP should be accorded the requisite status of a World Heritage Site. Full article

Estrogen deficiency is associated with endothelial dysfunction, vascular inflammation, increased lipoprotein oxidation, accumulation of lipid-rich material, and platelet activation. The absence of estrogen causes physiological, metabolic, and biochemical changes that increase the risk of cardiometabolic disease development caused by a deregulation in metabolic processes such as lipid metabolism and plasma lipoprotein levels. High-density lipoprotein (HDL) has cardioprotective properties related to the quality and the quantity of its components that can be modified by some nutritional factors. Guava (Psidium guajava L.), a widely cultivated fruit in Mexico, is notable for its high polyunsaturated fatty acid and dietary fiber content in its seeds, but its effect on health is understudied. This study aimed to evaluate the effect of guava-seed supplementation on body weight, blood pressure, lipid profile, HDL composition, and paraoxonase-1 (PON1) activity in an ovariectomized rat model (OVX). Four groups with six adult female Wistar rats each were classified as a SHAM group: rats with simulated ovariectomy; OVX group: rats with ovariectomy; OVX + GS group: ovariectomized rats supplemented with 6 g of guava seeds; OVX + DGS group: ovariectomized rats supplemented with 6 g of defatted guava seeds. Biochemical parameters, size, and lipid concentration of HDL subclasses, apolipoproteins, and PON1 activity were determined. A decrease in body weight gain, systolic blood pressure, mean arterial pressure, and triglycerides in plasma was observed at the end of the experiment in the supplemented groups. The supplementation of 6 g of guava seeds for 30 days decreased biochemical parameters in ovariectomized rats; these results could be attributed to the seed composition, suggesting a protective effect against the risk of developing diseases in menopausal states. Full article

Nanothermites are widely applied as specific power sources for microscale initiators and pyrotechnics. Increasing the charge density enhances energy storage within a confined combustion chamber, but it also alters the reaction kinetics. To systemically explore this phenomenon, the combustion and pressurization characteristics of electrosprayed nanothermite-based hybrid energetic materials (THEMs) with different metallic oxides (Fe₂O₃, CuO, and Bi₂O₃) and various energetic additives (nitrocellulose (NC), octogen (HMX), ammonium perchlorate (AP), and hexanitrohexaazaisowurtzitane (CL-20)) across various loading densities were tested. The results showed that increasing the loading density decreased the porosity of the loaded nanothermites and then rapidly decreased the convective heat transfer efficiency during the combustion propagation process. When the loading density exceeded a critical value, a dramatic decrease in the peak pressure, several orders-of-magnitude decrease in the pressurization rate, and an order-of-magnitude increase in the combustion duration occurred. Due to the dual effects of the porous microstructure on heat and mass transfer, the critical density of both the electrosprayed Al/CuO/NC/CL-20 composites and their physically mixed counterparts is between 37.9 and 43.9% theoretical maximum density (TMD). Because of the different synergistic catalytic effects, the fast reactivity at the high-loading-density maintaining capacity of the applied additives was AP > HMX ≈ CL-20 > NC. Owing to their intrinsic properties of low ignition temperature and high gas yield, the Bi₂O₃-THEMs could maintain high-speed reactivity even at 59.7% TMD. These results provide valuable insights into the rational design and tailoring of the reactivity of nanothermites for specific applications. Full article

A novel pumped storage system using centrifugal pumps to transfer water between reservoirs in coastal hydropower plants has significantly mitigated grid instability. However, frequent start–stop operations of large vertical centrifugal pumps, which serve as the core equipment, severely affect the operational stability of these systems. In this study, the intrinsic connection between the cavitating flow field and irreversible losses during the process was analyzed using the entropy production theory. The time–frequency characteristics of pressure pulsation in pump were analyzed by using the continuous wavelet transform. The results indicate that with the reduction in the flow rate and rotational speed, the sheet cavitation at the impeller inlet rapidly weakens until it vanishes. The cavity cavitation within the draft tube commences to emerge in the turbine mode. Separation vortices are formed due to the mismatch in the flow angle at the impeller outlet. These vortices induce local cavitation, causing both a rapid energy loss increase and high-amplitude, low-frequency pressure pulsations. During transient processes, flow instabilities induce high-amplitude, low-frequency pressure pulsations within the stay vane region, with maximum amplitude attained during runaway condition. The research results provide a theoretical foundation for the stable operation of centrifugal pumps. Full article

The inlet pressure steel pipe is an important part of the hydropower unit, and its inspection tasks mainly include cleaning with high-pressure water, surface anti-corrosion layer detection and internal flaw detection. In order to accomplish the above tasks effectively, a multifunctional, non-contact magnetic, tracked climbing robot is presented in this paper. Focusing on the pressure steel pipe inspection tasks, the design of the climbing robot system is given, including the mechanism and control system. By analyzing the slippage and overturning situations, the magnetic attraction constraints for reliable adhesion are obtained, which are used as the basis for designing magnetic adhesion modules. To enable climbing robots to meet the requirement of following the welding seam during the inspections, the improved Deeplabv3+ semantic segmentation method is proposed for welding seam recognition. Experiment results show that the climbing robot can achieve reliable adsorption and flexible movement on the internal face of inlet pressure steel pipe, and the climbing robot can meet the requirements of safety and efficiency for pressure steel pipe inspection processes. Full article

The contemporary world presents increasingly complex challenges for adolescents. In addition to normative developmental tasks, adolescents must now navigate epidemic health crises, armed conflicts, family dissolution, economic instability, and academic pressures. Consequently, adolescents experience diminished security and elevated levels of anxiety, loneliness, and depression. While the need for emotional support has intensified across all demographics, adolescents’ psychological needs remain particularly underserved. The American Psychological Association has recently advocated for the expansion of group therapy services, a format that aligns particularly well with adolescents’ socioemotional needs, serving as a developmental bridge from childhood to adulthood. Research on adolescents’ group legs much behind the adult literature. The aim of the current paper is to show the potential power of group therapy with adolescents based on a selective review of our empirical studies examining the impact of therapy groups on adolescents’ well-being. The reviewed papers encompass randomized controlled trials and process research identifying critical therapeutic factors, collectively establishing the intervention’s validity. Results demonstrate the superiority of these groups compared to non-treatment controls and equivalence to individual therapy in reducing stress, anxiety, and aggression while enhancing self-perception, self-control, and academic functioning. These findings support the conclusion that group psychotherapy significantly contributes to adolescent well-being. Considering adolescents’ high yet unmet need for emotional support, group therapy appears to be a valid alternative. Full article

Coastal lagoons are fragile and dynamic ecosystems that are particularly vulnerable to climate change and anthropogenic pressures such as urbanization and eutrophication. These vulnerabilities highlight the need for frequent and spatially extensive monitoring of water quality (WQ). While satellite remote sensing offers a valuable tool to support this effort, the optical complexity and shallow depths of lagoons pose major challenges for retrieving water column biogeochemical parameters such as chlorophyll-a ([chl-a]) and suspended particulate matter ([SPM]) concentrations. In this study, we develop and evaluate a robust satellite-based processing chain using Sentinel-2 MSI imagery over two French Mediterranean lagoon systems (Berre and Thau), supported by extensive in situ radiometric and biogeochemical datasets. Our approach includes the following: (i) a comparative assessment of six atmospheric correction (AC) processors, (ii) the development of an Optically Shallow Water Probability Algorithm (OSWPA), a new semi-empirical algorithm to estimate the probability of bottom contamination (BC), and (iii) the evaluation of several [chl-a] and [SPM] inversion algorithms. Results show that the Sen2Cor AC processor combined with a near-infrared similarity correction (NIR-SC) yields relative errors below 30% across all bands for retrieving remote-sensing reflectance R_rs(λ). OSWPA provides a spatially continuous and physically consistent alternative to binary BC masks. A new [chl-a] algorithm based on a near-infrared/blue R_rs ratio improves the retrieval accuracy while the 705 nm band appears to be the most suitable for retrieving [SPM] in optically shallow lagoons. This processing chain enables high-resolution WQ monitoring of two coastal lagoon systems and supports future large-scale assessments of ecological trends under increasing climate and anthropogenic stress. Full article

To address the prominent issues in current potato peeling processes (such as high labor intensity, excessive flesh loss, hard-to-remove peel from bud eyes/concaves), a non-contact waterjet method was proposed. Based on the computational fluid dynamics (CFD) method, the Fluent software was used to simulate and analyze the flow field of fan-shaped nozzle models with different slot angles. The simulation results indicated that the 25° scattering angle nozzle had excellent performance: it ensured effective potato surface coverage and minimized jet energy loss, fitting peeling needs. A one-way fluid–structure interaction (FSI) model of the nozzle–potato system was built to study waterjet–potato mechanical interactions. Surface stress distribution under waterjet impact was analyzed, and jet dynamic pressure was mapped to solid stress via FSI interface load transfer. Simulations revealed that with a 25° scattering angle, 200 mm standoff distance, and 5 MPa pressure, the maximum shear stress at potato surface characteristic points was 0.032 MPa—within the 0.025–0.04 MPa target range and matching potato skin–substrate peeling strength threshold. This confirmed the energy–mechanical response coordination, validated by experiments. The research results can provide an effective technical reference for potato peeling processing. Full article

A multiscale 3D CFD model of CO₂ methanation over Ni/Al₂O₃ was developed in COMSOL Multiphysics 6.3 for a lab-scale isothermal fixed-bed Sabatier reactor and validated against published data. The multiscale approach integrated bulk convection–diffusion, fluid flow, and pressure distribution with intraparticle diffusion–reaction phenomena coupled with Langmuir–Hinshelwood–Hougen–Watson-based kinetics, thus solving mass-transfer limitations without empirical effectiveness factors. Model validation was carried out by (i) kinetics, (ii) reactor performance, and (iii) hydrodynamics. Simulation results showed strong diffusion-dominated species transport at the bed entrance that lessened downstream as partial pressures decreased and products accumulated, resulting in a diffusion-relieved regime near the outlet. Sensitivity studies identified 320–350 °C and up to 10 bar as favorable conditions for high CH₄ yield. Additionally, slightly H₂-rich feed accelerated approach to equilibrium, while lower flow rates achieved near-complete conversion within the first half of the reactor bed. Simulations were carried out in COMSOL Multiphysics 6.3 on a dual Intel Xeon Platinum 8168 (48 cores at 2.7 GHz) workstation with 512 GB RAM to solve a 12-million-element mesh. The developed framework identifies a practical operating window and quantifies the conversion–throughput trade-off with flow rate, guiding operating condition selection and providing a basis for process intensification and lab-to-pilot scale-up of CO₂ methanation. Full article

Fiber-optic sensing (FOS) technology has emerged as a cutting-edge research focus in the sensor field due to its miniaturized structure, high sensitivity, and remarkable electromagnetic interference immunity. Compared with conventional sensing technologies, FOS demonstrates superior capabilities in distributed detection and multi-parameter multiplexing, thereby accelerating its applications across biomedical, industrial, and aerospace fields. This paper conducts a systematic analysis of the sensing mechanisms in fiber-optic pressure sensors, with a particular focus on the performance optimization effects of fiber structures and materials, while elucidating their application characteristics in different sensing scenarios. This review further examines current manufacturing technologies for fiber-optic pressure sensors, covering key processes including fiber processing and packaging. Regarding practical applications, the multifunctional characteristics of fiber-optic pressure sensors are thoroughly investigated in various fields, including biomedical monitoring, industrial and energy monitoring, and wearable devices, as well as aerospace monitoring. Furthermore, current challenges are discussed regarding performance degradation in extreme environments and multi-parameter cross-sensitivity issues, while future research directions are proposed, encompassing the integration and exploration of novel structures and materials. By synthesizing recent advancements and development trends, this review serves as a critical reference bridging the gap between research and practical applications, accelerating the advancement of fiber-optic pressure sensors. Full article

Soft wearable actuators must align with anatomical joints, conform to limb geometry, and operate at low pneumatic pressures. Yet most twisting mechanisms rely on bulky attachment interfaces and relatively high actuation pressures, limiting practicality in assistive applications. This study introduces the first Twisting Soft Sleeve Actuator (TSSA), a self-contained, wearable actuator that produces controlled bidirectional torsion. The design integrates helically folded bellows with internal stabilization layers to suppress radial expansion and enhance torque transmission. The TSSA is fabricated from thermoplastic polyurethane using a Bowden-type fused filament fabrication (FFF) process optimized for airtightness and flexibility. Performance was characterized using a modular test platform that measured angular displacement and output force under positive pressure (up to 75 kPa) and vacuum (down to −85 kPa). A parametric study evaluated the effects of fold width, fold angle, wall thickness, and twist angle. Results demonstrate bidirectional, self-restoring torsion with clockwise rotation of approximately 30 degrees and a peak output force of about 40 N at 75 kPa, while reverse torsional motion occurred under vacuum actuation. The TSSA enables anatomically compatible, low-pressure torsion, supporting scalable, multi-degree-of-freedom sleeve systems for wearable robotics and rehabilitation. Full article

Coral reef ecosystems are biodiversity hotspots that provide essential ecological and environmental services but are increasingly threatened by anthropogenic pressure and climate change. Effective conservation of reef systems within Marine Protected Areas (MPAs) can be enhanced using spatially explicit approaches that integrate habitat mapping and ecological metrics at seascape scales. In this study, we characterized the benthic seascape of Cayo Arenas and identified optimal priority conservation zones in one of the core zones of the recently established Southern Gulf of Mexico Reefs National Park (SGMRNP). In July 2023, ground-truthing was performed to quantify the cover of sand, calcareous matrix, macroalgae, hard corals and octocorals. Cluster analysis of quantitative data and ecological similarity between classes was used to identify the main benthic habitat classes. Object-based and supervised classification algorithms on a PlanetScope image were used to construct a thematic map of the benthic reef system. Based on the thematic map, habitat connectivity, β-diversity, patch compactness, and availability for commercial species were estimated. In addition, a benthic change analysis (2017–2013), based on the spectral characteristics of PlanetScope images, was performed. The layers obtained were then used to perform an iterative weighted overlay analysis (WOA) using 126 combinations. Six main habitat classes, with different coverages of hard corals, calcareous matrix, macroalgae, and sand, were identified. Habitats with calcareous matrix and sandy substrates dominated the seascape. High habitat compactness, connectivity, and β-diversity values were observed, suggesting habitat stability and ecologically dynamic areas. Based on the WOA, eight optimal priority areas for conservation were recognized. These areas are characterized by heterogeneous habitats, moderate coral cover, and high connectivity. We provide a spatially explicit approach that can strengthen conservation planning within the SGMRNP and other MPAs, particularly by assisting zonation and sub-zonation processes. Full article

The main objective of this study is to determine the knowledge and awareness levels of climate change among preparatory class students at Zonguldak Bülent Ecevit University in the Western Black Sea Region of Türkiye using an unsupervised clustering approach. Within this scope, a survey was administered to university students (n = 280). Participant scores for the survey sections containing five-point Likert-type questions on climate change awareness were calculated using min–max normalization. The normalized data was then processed using the k-means algorithm, a well-known technique in unsupervised machine learning. This resulted in a classification (clustering) related to climate change awareness. The number of clusters was determined using the Silhouette index. Three clusters identified using k-means and Silhouette index ($S\approx 0.55)$ revealed the knowledge and application levels of student groups regarding climate change awareness. As a result of clustering, it was determined that Cluster-3 students (n = 134, 47.9%), defined as having a high level of knowledge and application, had a higher impact value in their overall assessments of green space-focused issues related to climate change awareness compared to the overall assessments of students in other clusters. Some notable findings concerning the attitudes of Cluster-3 students highlight climate change awareness-related practices. These include minimizing water consumption to levels necessary for ecosystem water management (mean = 95.7, std. deviation = 10.9) and exercising controlled, sustainable daily energy use to alleviate pressure on green spaces (mean = 94.4, std. deviation = 12.5). This study offers practical insights for policymakers, educators, and institutions, emphasizing the need to enhance climate education and to promote the active involvement of younger generations in shaping sustainable environments. Full article