Search Results (23,170)

Organophosphate esters (OPEs) are commonly used flame retardants and plasticizers, which can easily be released into the soil environment and have potential hazards such as neurotoxicity and developmental toxicity. Establishing an efficient and sensitive detection method plays a crucial role in soil pollution assessment. Currently, there have been numerous studies on the detection of OPEs in soil using ultrasonic extraction and solid-phase extraction, while relatively few studies have focused on the analysis of multiple OPEs in soil by accelerated solvent extraction combined with d-SPE clean-up and ultra-high performance liquid chromatography–tandem mass spectrometry. The d-SPE purification method eliminates the need for column passage, shortens sample preparation time, and avoids the risk of background contamination from OPEs that may be introduced by SPE. This study developed a liquid chromatography–tandem quadrupole mass spectrometry (LC-MS/MS) method for the determination of 25 OPEs in soil, and systematically optimized the pretreatment and instrumental analysis conditions. Accelerated solvent extraction was used for pretreatment, and dichloromethane–methanol (1:1, V/V) was determined as the optimal extraction solvent. A mixed adsorbent of N-propyl ethylenediamine (PSA) and C18 was selected for dispersive purification, effectively removing matrix interference and improving recovery rates. The mass spectrometry parameters such as collision energy and declustering voltage were optimized, significantly enhancing ion response intensity and detection sensitivity. The method showed good linearity within the concentration range of 1–100 ng/mL, with correlation coefficients all greater than 0.994. The spiked recovery rates ranged from 70.6% to 111% with a relative standard deviation (RSD) of 1.2–11.8%. The precision and accuracy met the requirements for environmental sample analysis. The method was applied to the detection of actual soil samples, and the results were stable and reliable. This method is simple to operate, highly sensitive, and widely applicable, providing reliable technical support for the pollution monitoring, source tracing, and ecological risk assessment of OPEs in soil. Full article

Oil palm plantations play an important role in agricultural production and carbon storage in tropical regions. The accurate estimation of aboveground carbon (AGC) is essential for sustainable plantation management, climate change mitigation, and carbon monitoring. Although field measurements provide reliable estimates, they are often time-consuming, labor-intensive, and costly, particularly over large plantation areas. Recent advances in remote sensing and machine learning offer efficient alternatives for AGC estimation using satellite imagery. In this study, we developed a machine learning framework for AGC estimation in oil palm plantations using Sentinel-2 multispectral imagery and Sentinel-1 synthetic aperture radar (SAR) data. Field measurements were integrated with spectral variables, vegetation indices, and SAR-derived parameters extracted from satellite data. A hybrid feature selection approach combining Pearson correlation, mutual information and mRMR was used to identify the most relevant variables. Six machine learning algorithms were evaluated, including Linear Regression, Random Forest, XGBoost, Gradient Boosting, LightGBM, and Extra Trees. Because the 160 observations comprise sixteen 10 m × 10 m grid cells nested within ten 40 m × 40 m field plots, model performance was assessed with leave-one-plot-out cross-validation: all sixteen cells of a plot were held out together, and the hybrid feature selection was repeated inside every fold using only that fold’s training plots. Performance was measured on pooled out-of-fold predictions using R², root mean squared error (RMSE), and average absolute relative error (AARE%). Under this spatially independent design the combined Sentinel-1 + Sentinel-2 dataset gave the highest accuracy (R² = 0.7950, RMSE = 4.14 t C ha⁻¹, AARE = 33.53%), followed by Sentinel-1 alone (R² = 0.7631, RMSE = 4.46 t C ha⁻¹) and Sentinel-2 alone (R² = 0.6108, RMSE = 5.71 t C ha⁻¹). Linear Regression and Extra Trees were the most robust models, whereas the boosted ensembles did not generalize to unseen plots. Repeating the evaluation with an ungrouped random split of the same data inflated R² by up to 0.70, showing that a large part of the accuracy obtainable under that design reflects within-plot spatial autocorrelation rather than predictive skill. These findings indicate that optical-SAR imagery combined with machine learning can provide useful AGC estimates in oil palm plantations, and that spatially independent validation is essential for reporting them honestly. The proposed framework can be used to support plantation-scale carbon mapping, monitoring, and carbon stock assessment, subject to further calibration and independent validation across additional plantations. Full article

The energy management strategy (EMS) of fuel cell hybrid electric vehicles (FCHEVs) plays an important role in determining both hydrogen economy and the state-of-charge (SOC) regulation and prevention of over-charge/discharge. Existing fuzzy logic-based EMS typically employs a single fuzzy logic controller with fixed SOC thresholds, which struggles to adapt to complex and varying driving conditions. To address this limitation, this paper proposes a dual-fuzzy logic control strategy comprising a primary fuzzy logic controller (FLC1) and a secondary fuzzy logic controller (FLC2), which operate in coordination to achieve refined power distribution through ΔSOC adjustment, defined as the difference between the state of charge (SOC) of a power battery and its ideal SOC (ISOC). A series of systematic simulations are conducted under different ISOC coefficients (0.45, 0.50, 0.55, 0.60, and 0.65), and the results are compared with those obtained from the switch-fuzzy control strategy. The findings indicate that an ISOC of 0.55 yields the optimal comprehensive performance. Building on this, an extremum-seeking control (ESC) algorithm is introduced to perform online adaptive optimization of the ISOC. A comprehensive cost function that integrates hydrogen consumption, power loss, and SOC deviation is constructed to dynamically adjust the ISOC. Simulation verification is conducted on the MATLAB/Simulink R2024b and AVL CRUISE co-simulation platform under the New European Driving Cycle (NEDC). Results demonstrate that the ESC adaptive strategy achieves hydrogen consumption reductions of 10.0%, 34.6%, and 45.7% under initial SOC conditions of 35%, 75%, and 85%, respectively, compared with the switch-fuzzy control. Furthermore, it delivers an additional 1.21% hydrogen saving over the optimal dual-fuzzy control at an initial SOC of 75%. Notably, the ISOC update in the proposed strategy does not require prior knowledge of future driving cycles, and the optimization itself is performed online. However, the ESC hyperparameters (perturbation amplitude, frequency, filter time constants, integrator gain) and the cost function weights are pre-calibrated offline based on typical operating conditions, and the real-time cost evaluation relies on component efficiency signals derived from the vehicle model, providing a practical and intelligent upgrade pathway for fuzzy logic-based EMS in FCHEV applications. Full article

For the application of unmanned aerial vehicle (UAV)-based passive target localization, the positions of the UAVs play an important role because different UAV configurations provide distinct TDOA measurement geometries. In addition, the uncertainty of the target position affects the localization performance of different UAV configurations. Focusing on the problem of target localization by UAVs, this paper studies a UAV path optimization method for passive target localization considering target-position uncertainty. First, a passive localization signal model is established, and the TDOA method based on the Chan algorithm is deployed for target passive localization. Second, the Cramer–Rao lower bound (CRLB) for the Chan–TDOA localization method is derived as the criterion of the UAVs’ path optimization. To consider target-position uncertainty, the global CRLB is calculated within the uncertainty region of the target position instead of only applying the traditional single-point CRLB. Third, to improve computational efficiency, an analytical approximation of the global CRLB is derived from a second-order Taylor expansion instead of repeatedly calculating the multiple integral terms. By combining this objective with the PSO algorithm, the UAVs’ configuration is searched and applied at each time step. Finally, numerical simulations are performed to verify the validity and effectiveness of the proposed analytical global CRLB path-optimization method. Full article

Accurately simulating convective initiation (CI) in capped High Plains dryline environments remains a significant challenge for convection-permitting numerical weather prediction. As a follow-up work to Lu and White, this study utilizes the Model for Prediction Across Scales (MPAS) at a 3 km grid resolution to evaluate the sensitivity of dryline morphology and CI to two planetary boundary layer (PBL) parameterization schemes: the non-local Yonsei University (YSU) and the local Mellor-Yamada-Nakanishi-Niino (MYNN) frameworks. Radar observations and simulated maximum reflectivity show that while the YSU scheme successfully replicates the timing and spatial development of convective cores triggered along the elevated terrain slope at 21:30 UTC, the MYNN scheme completely suppresses deep convection throughout the study period. Vertical thermodynamic profiles indicate that YSU establishes a deeply mixed boundary layer that weakens the regional capping inversion, enabling surface parcels to break the stable lid and reach their level of free convection (LFC). Conversely, the MYNN scheme confines moisture to a thin layer near the surface beneath an unyielding temperature inversion, preventing parcels from achieving free buoyancy. For the 3 km “grey zone” of turbulence resolution, both PBL schemes successfully resolve horizontal convective rolls (HCRs) near the primary dryline boundary. YSU’s non-local mixing permits these HCR perturbations to couple vertically into deep, cap-breaching updraft plumes, while MYNN’s local turbulent kinetic energy (TKE) closure traps them as shallow horizontal waves. It was shown that the MYNN failure is driven by an intrusive synoptic wind bias, generating anomaly wind velocities of 24–28 m/s throughout the column. These winds act as a mechanical sweeper across the terrain slope which shears, flattens, and dilutes the moisture pool below 2000 m Mean Sea Level (MSL) and physically reduces fuel from the western initiation zone. In contrast, the YSU scheme maintains a well-regulated, moderate wind profile (8–12 m/s aloft), preserving a state of mesoscale equilibrium that allows moisture to ascend the terrain slope and continuously feed developing convective cells. Our findings demonstrate that the choice of PBL parameterization plays significant role in not only local vertical mixing but also the structural translation of macroscale synoptic forcing versus localized thermodynamic regulation in complex terrain. Full article

Asthma is one of the most prevalent chronic respiratory diseases worldwide, and environmental pollutants such as desert dust play a significant role in triggering respiratory sensitization and aggravating asthma symptoms. In this study, a mathematical model is proposed to investigate the dynamics of dust-induced asthma progression. The population is divided into unaware susceptible individuals, aware susceptible individuals, dust-sensitized individuals, and asthmatic individuals, while two additional variables describe dust concentration in the human population and the environment. Fundamental qualitative properties of the model, including positivity, boundedness, existence of equilibria, and stability conditions, are established. It is shown that the asthma-free equilibrium is locally and globally asymptotically stable whenever the dust-induced asthma threshold is below unity, whereas a unique asthma-persistent equilibrium exists when the dust-induced asthma threshold exceeds unity. To reduce the burden of asthma, an optimal control problem is formulated by incorporating three time-dependent interventions: awareness campaigns, medical intervention for dust-sensitized individuals, and environmental dust reduction. Pontryagin’s Maximum Principle is employed to characterize the optimal controls and derive the corresponding adjoint system. Numerical simulations, performed using the forward–backward sweep method, demonstrate that the proposed interventions significantly reduce the number of asthmatic individuals compared with the uncontrolled case. Furthermore, a cost-effectiveness analysis based on the Average Cost-Effectiveness Ratio (ACER) and Incremental Cost-Effectiveness Ratio (ICER) is conducted to compare seven intervention strategies. The results indicate that the medical intervention strategy is the most economically attractive option, while the combined strategy involving all controls achieves the largest reduction in asthma burden. Full article

As a noninvasive liquid biopsy approach, extracellular vesicle (EV)-based detection offers significant advantages in reflecting real-time tumor dynamis and overcoming the limitations of conventional tissue biopsy. EVs, nanoscale vesicles secreted by cells, carry diverse biomolecules such as proteins and nucleic acids, playing key roles in tumor progression, metastasis, and immune evasion, and have emerged as promising biomarkers for cancer liquid biopsy. Surface-enhanced Raman spectroscopy (SERS), characterized by high sensitivity, resistance to photobleaching, minimal sample consumption, and multiplexing capability, has shown great potential in EV analysis. This review systematically summarizes current methods for EV isolation, characterization, and storage, with a focus on label-free and label-based SERS detection strategies for early cancer diagnosis, treatment response monitoring, and prognosis evaluation. Furthermore, the integration of SERS with machine learning and deep learning algorithms has substantially improved diagnostic accuracy and cancer subtyping. Despite remaining challenges, such as optimization of SERS substrate performance, intelligent processing of Raman spectral fingerprints, and clinical translation, EV-based SERS technology holds great promise for precision oncology. Full article

Background: Indirect measurement methods play a central role in the assessment of deviant sexual interests, including pedohebephilia. Among these approaches, eye-tracking paradigms that assess gaze behavior may serve as indirect indicators of deviant vs. non-deviant sexual interest. However, the diagnostic utility of eye-tracking measures for distinguishing pedohebephilia from sexual interest in adults (teleiophilia) remains unclear. Objective: The aim of this study was to examine differences in gaze behavior among individuals with pedohebephilic and teleiophilic sexual interest and to determine the extent to which eye-tracking measures can differentiate pedophilia and hebephilia from teleiophilia. Method: Gaze behavior was assessed using an eye tracker while images of children were presented alongside images of adults. Gaze measures included the time to first fixation, first fixation count and total duration of fixation. Sexual interest was determined through a clinical interview as part of a standard intake procedure of an outpatient prevention program. Results: The sample comprised men with pedophilia, hebephilia and a teleiophilic control group. Men with pedophilic sexual interest showed a significantly higher number of first fixations and a shorter time to first fixation on child stimuli compared with adult stimuli, while the teleiophilic group showed the opposite pattern. Findings for the hebephilic group were inconclusive. Total fixation duration was more evenly distributed between child and adult stimuli in the pedophilic group, whereas the other two groups showed longer fixation durations for adult stimuli [¹]. Conclusions: The findings suggest that eye-tracking may provide a useful additional approach for assessing deviant sexual interest. Full article

The phenoloxidase gene Laccase2 (Lac2) is an indispensable survival gene in insects, playing key roles in cuticle tanning, exoskeleton development and pigment deposition. However, in lepidopteran insects, the roles of Lac2 in mandibular development and feeding behavior remain largely unexplored. In this study, we demonstrated that Lac2 is essential for mandibular development in early larvae of the model lepidopteran, the silkworm, Bombyx mori. We cloned and characterized BmLac2 and found that it is evolutionarily conserved in lepidopteran insects. Disruption of BmLac2 via CRISPR/Cas9 system induced mandibular defects, which directly impaired larval feeding behavior and culminated in developmental arrest and larval mortality. Moreover, knockout of BmLac2 led to dopamine accumulation during the dormancy stage, but the dopamine level returned to normal after molting, without altering feeding motivation in mutant larvae. Furthermore, RNA sequencing (RNA-seq) and quantitative real-time polymerase chain reaction (qRT-PCR) analyses revealed that loss of BmLac2 affected the expression of genes associated with cuticular formation and immunity, also contributing to larval mortality alongside feeding defects. Altogether, BmLac2-mediated mandibular development and cuticular melanization play key roles in regulating feeding behavior and immunity in early-stage silkworm larvae, making this gene a potential target for early intervention against lepidopteran pests. Full article

Background: The early-life gut microbiota plays a critical role in programming intestinal barrier function and immune homeostasis, with profound implications for long-term host health. However, the effects of early-life compound probiotic intervention on the maturation of intestinal barrier function and the underlying molecular mechanisms remain incompletely understood, particularly in large-animal models relevant to human physiology. Methods: In this preclinical study, 3627 neonatal piglets—a well-established translational model for human infant gut development—were orally administered a novel compound probiotic formulation comprising Bifidobacterium longum subsp. infantis BZ, Lactobacillus plantarum LZ, and Pediococcus acidilactici PZ during early life. A total of 1512 fecal samples collected at seven time points from birth to day 180 were analyzed by 16S rRNA sequencing, and 525 samples from three developmental windows (days 10, 25, and 70) were subjected to LC-MS-based metabolomics. The candidate metabolite indole-3-lactic acid (ILA) was further mechanistically validated in a DSS-induced colitis mouse model and in IPEC-J2 cells. Results: Early-life probiotic intervention significantly enhanced intestinal barrier integrity, as evidenced by improved intestinal morphology and upregulated expression of tight junction proteins—zonula occludens-1 (ZO-1), occludin (OCLN), and Claudin-1 (CLDN1)—in the jejunum (p < 0.05). Notably, intervention at birth was more effective than post-weaning administration, and two administrations (birth + weaning) yielded superior outcomes compared with a single administration (p < 0.05). Microbiome analysis revealed enhanced microbial diversity and enrichment of beneficial genera during the juvenile-to-adult transition (p < 0.05). Metabolomic profiling identified ILA as a signature metabolite consistently elevated by probiotic supplementation. Conclusions: These findings provide evidence that early-life compound probiotic intervention is associated with improved intestinal barrier maturation, with ILA identified as a key candidate metabolite that may mediate this effect, as supported by functional validation in murine and cellular models. This provides a mechanistic rationale for probiotic-based strategies to support intestinal health in human infants during critical developmental windows. Full article

Background: Endothelial dysfunction plays a central role in the pathophysiology of erectile dysfunction (ED) and reflects systemic vascular impairment. Photoplethysmography-derived flow-mediated dilation (PPG-FMD) has emerged as a novel, non-invasive approach for assessing endothelial function. This study aimed to investigate the utility of PPG-FMD as a marker of systemic endothelial function in patients with ED without overt coronary artery disease. Methods: In this observational cross-sectional comparative study, patients with vascular ED (n = 24), non-vascular ED (n = 18), and healthy controls (n = 30) were evaluated. Endothelial function was assessed using PPG-FMD. Key parameters, including dilation index, time to maximum dilation, area under the curve, and dilation index slope, were analyzed and compared across groups. Results: PPG-FMD parameters indicated significantly impaired endothelial function in patients with vascular ED compared to both non-vascular ED patients and controls (p < 0.01). Dilation index and area under the curve were significantly reduced in the vascular ED group. Conclusions: These preliminary findings support the presence of systemic endothelial dysfunction in vascular ED and suggest that PPG-FMD–derived parameters may serve as a non-invasive indicator of endothelial function. Further studies incorporating larger cohorts and validation against established endothelial assessment methods are required to determine its clinical applicability. Full article

Contemporary urban development imposes an increasingly pronounced need for aligned spatial transformations with the preservation of natural resources, adaptation to climate change, and the improvement of quality of life. In this context, the concept of green infrastructure has been recognized as an integrative framework that connects ecological processes with spatial and urban planning. However, the ways in which green infrastructure is strategically articulated and operationalized through planning processes vary depending on the institutional and spatial context. The aim of this paper is to identify the dominant strategic approaches to green infrastructure planning and to examine their implications for spatial and urban planning. The research is based on a qualitative comparative analysis of selected European green infrastructure strategies, while the Green Infrastructure Strategy of the City of Belgrade is considered as an analytical case study within the specific institutional and planning context of Serbia. The analysis focuses on three key components of strategic articulation—visions, objectives, and measures—in order to identify recurring patterns that shape the integration of green infrastructure into planning practice. The results indicate a high degree of convergence among strategic approaches, particularly regarding the emphasis on quality of life, ecosystem services, biodiversity conservation, and the strengthening of climate resilience. The identified patterns indicate the need for transformation of regulatory frameworks, the improvement of planning procedures and instruments, and the adoption of a spatial logic based on connectivity and multifunctionality. The analytical examination of the Belgrade Strategy shows that its structure of visions, objectives, and measures encompasses the key regulatory, procedural, and spatial prerequisites for incorporating green infrastructure into planning practice, and at the same time, its operationalization depends on institutional capacities, information systems, financial instruments, and mechanisms of intersectoral coordination. The paper concludes that green infrastructure strategies play an important role in mediating between public policies and spatial planning solutions, while their effectiveness depends on the alignment of regulatory, procedural, and spatial instruments. Full article

Background/Objectives: Traditional medicinal plants play a crucial role in infants’ healthcare in underdeveloped countries and communities where access to modern medicine is limited. In Limpopo, the Vhavenda tribe has a custom of feeding babies as young as a day old with tshiunza, a very light and warm, soft porridge prepared in medicinal plant extracts, believed to help treat various ailments and boost the immune and digestive systems. However, reports of negative side effects, including vomiting, haematuria, renal inflammation and hospitalisations, highlight safety concerns of these traditional practices. This study aimed to profile the chemical composition of soft porridge samples prepared in aqueous extracts of medicinal plants reported to be commonly used in infants’ food in the Venda region of Limpopo; Annona senegalensis (roots), Piliostigma thonningii (leaves), Carissa edulis (roots) and Bauhinia galpinii (leaves). Methods: Ultrahigh-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-qTOF-MS) was used for metabolic profiling, followed by putative compound identification using feature-based molecular networking and a compound fragmentation predictor tool, SIRIUS. To evaluate the toxicity of these plants, a cytotoxicity assay was conducted using plant extracts on African monkey kidney cells. Results: Different classes of polyphenols, including flavonoids (flavan-3-ols and flavonols) and hydroxycinnamoyl amides, were among the dominant compounds putatively identified in the methanolic extracts of soft porridge prepared from the four plant extracts. A. senegalensis aqueous extracts were inactive (IC₅₀ > 500 µg/mL, 55.57% viability at 500 µg/mL), while P. thonningii was non-cytotoxic (105–132% viability within the tested concentration range). Conclusions: Although no toxic compounds were identified and no cytotoxic potential was observed in the tested plant extracts, this does not translate to the safe use of medicinal plants in infants’ food. Therefore, future studies should conduct pharmacological and toxicological evaluations to better understand the potential risks of these plant extracts to infant health. Full article

Background/Objectives: Communication training in undergraduate nursing skills courses is often overshadowed by procedural skill acquisition, leaving limited opportunities for students to develop patient-centered communication skills and engage in reflective learning. This study evaluated a reflection-integrated CICARE communication program embedded in a Fundamentals of Nursing skills course and explored students’ learning experiences. Methods: A quasi-experimental study with an embedded qualitative component was conducted among second-year undergraduate nursing students in China. The quantitative component used a non-equivalent control group design, while reflective journals from the Intervention Group provided qualitative data on students’ learning experiences. Two intact classes were assigned to the Intervention Group (n = 65), and two intact classes were assigned to the Control Group (n = 66). The Intervention Group received an 18-week CICARE-based communication program integrated into skills training, including scenario-based role-play, emotional cue recognition, demonstration videos, feedback, and reflective journals. The Control Group received conventional skills training. Outcomes included communication competence, empathy, professional identity, clinical judgment, and course performance. Analysis of covariance was used to compare post-intervention outcomes after adjustment for baseline scores. Reflective journals from the Intervention Group were analyzed thematically. Results: After adjustment for baseline scores, the Intervention Group showed significantly higher communication competence than the Control Group (adjusted mean difference = 2.699, 95% CI: 0.108–5.291, p = 0.041). Empathy was also higher in the Intervention Group (adjusted mean difference = 3.796, 95% CI: 0.538–7.053, p = 0.023). The between-group difference in professional identity was not statistically significant (p = 0.073). The Intervention Group achieved higher total clinical judgment scores than the Control Group (31.52 ± 5.50 vs. 27.20 ± 6.45, p < 0.001), with significant differences in noticing, interpreting, and reflecting. Course performance was also higher in the Intervention Group. In their reflective journals, students described greater patient-centered awareness, attention to patients’ emotional needs, professional reflection, and motivation for self-directed learning. Conclusions: Integrating CICARE-based communication training with reflective learning may strengthen communication competence, empathy, clinical judgment, and course performance in undergraduate nursing skills education. Further studies with longer follow-up are needed to determine whether the observed differences persist over time and whether professional identity and action-oriented clinical responses improve with longer educational exposure. Registration: This study was not registered. Full article

Childhood obesity is an important global health issue closely related to metabolic syndrome and metabolic dysfunction-associated fatty liver disease (MASLD), currently the most common chronic liver disease in children. Oxidative stress and insulin resistance are the driving forces in hepatocyte injury and disease progression. There is growing interest in new biomarkers for detecting and monitoring metabolic and hepatic changes. We aimed to synthesize current evidence regarding biomarkers of oxidative stress and MASLD, and the potential modulatory role of selenium in pediatric populations. A literature search of PubMed, Scopus, Web of Science, and the Cochrane Library identified studies in children and adolescents (0–18 years) published between January 2000 and December 2025. Associative diagnostic biomarkers included indicators of oxidative damage, antioxidant-defense markers, and integrated oxidative stress indices, which appear promising but lack pediatric reference ranges, while prognostic biomarkers capture the inflammatory consequences of redox imbalance but with limited liver specificity. Metabolomics profiling and multiomics approaches remain experimental. Selenium, an essential trace element with antioxidant properties, plays a role in maintaining redox balance through selenoproteins, but pediatric evidence is limited and at times contradictory. Few biomarkers are clinically ready. Further longitudinal studies in pediatric populations are needed to better clarify the role of selenium, as well as to support the development of age-appropriate diagnostic strategies utilizing multiomics for MASLD, empowering clinicians to implement timely interventions in childhood obesity. Full article