Search Results (3,184)

Dye-sensitized solar cells (DSSCs) are a promising alternative to traditional silicon-based technologies due to their low production costs, ease of fabrication, and wide range of applications. Among the semiconductors used in DSSCs, TiO₂ stands out for its simple, inexpensive synthesis and lower environmental impact. However, TiO₂ has limitations due to its wide bandgap and high charge-carrier recombination. In this study, the incorporation of rGO and its effect on the degree of GO reduction on Cu-doped TiO₂ particles were evaluated to enhance light interaction, improve electronic mobility, and suppress recombination. Electrophoretic deposition was employed as an alternative method to obtain Cu-doped, rGO-decorated mesoporous TiO₂ films, which were evaluated for power conversion efficiency (PCE) in DSSCs. The materials were characterized using SEM, ICP-OES, UV-Vis, XRD, BET, DLS, and TEM, while the photoanodes were analyzed using FTIR, chronoamperometry, and photovoltaic efficiency tests. The results showed clusters between 1.4 and 2.6 µm, confirming doping, a decrease in the energy gap to 2.99 eV, a stable anatase crystalline phase, and an increase in the specific surface area to 234.82 m²/g. The fabricated cells exhibited a PCE of 2.26% with a TiO₂:Cu-rGO photoanode after 20 min of GO reduction, compared to 0.96% for DSSCs with a conventional configuration. Full article

Background: The evaporation of volatile ingredients from topical formulations strongly influences transdermal permeation and overall bioavailability, yet coupled evaporation–permeation dynamics are mostly simplified or neglected in existing models. Methods: We developed a mechanistic framework that couples Fickian gas-phase evaporation and transdermal permeation, both driven by the activity coefficients of volatiles. The model equations are implemented in a hybrid MATLAB–Python architecture with the volatile activity computed on-the-fly using UNIFAC and the gas-phase diffusivity calculated by the kinetic equation of Fuller–Schettler–Giddings (FSG). Initial validation used published IVPT data for 4-Tolunitrile and Nitrobenzene. Results: For 4-Tolunitrile, the FSG-based model estimated an initial evaporation coefficient of K_evap,i = 7.9348 × 10⁻¹⁰ mol·cm⁻²·s⁻¹, and parameter optimization converged to 8.3929 × 10⁻¹¹ mol·cm⁻²·s⁻¹ (≈1/10 of the FSG estimate). The optimized model predicted an accumulation amount of 19.15% versus an experimental value of 16.97% in the receptor fluid (RF) at 24 h. For Nitrobenzene, the FSG initial estimation value of K_evap,i = 6.6480 × 10⁻¹⁰ mol·cm⁻²·s⁻¹ was optimized to 8.1174 × 10⁻¹¹ mol·cm⁻²·s⁻¹ (≈1/8 of the FSG value), and the predicted amount of 24 h RF is 27.61% (experimental 23.19%). Both optimized K_evap,i values are roughly one order of magnitude lower than the initial FSG estimates, but >20× larger than Stokes–Einstein (SE)-derived values. Sensitivity scans show that further tuning of internal skin parameters (e.g., diffusion coefficient (D_SC,i) and partition coefficient (P_SCw,i)) produced only marginal improvements in RF prediction once K_evap,i was optimized. Conclusions: The coupled evaporation–permeation framework reproduces key IVPT kinetics for volatile solutes when the effective evaporation coefficient is calibrated. The kinetic-theory estimates (FSG-based) are a reasonable starting point, but typically overestimate the evaporation rate constant under finite-dose unoccluded IVPT conditions. By implementing the on-the-fly computation of volatile activity using UNIFAC, the approach is extensible to modelling transdermal permeation of volatiles from multicomponent/non-ideal formulations. Full article

The all-d-enantiomeric-peptide RD2 was developed for the treatment of Alzheimer’s disease. This study aimed to develop a specific and highly sensitive liquid chromatography-mass-spectrometric (UHPLC-ESI-QTOF) method for quantifying RD2 in the mouse brain and to validate it according to the ICH M10 guideline to investigate the pharmacokinetic profile of RD2 in its target organ. Sample preparation, chromatographic separation and quantification were very challenging due to RD2’s highly hydrophilic properties, the complex matrix and the required lower limit of quantification (LLOQ). Chromatographic separation was performed on an Acquity UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm particle size) within 5 min at 50 °C with a flow rate of 0.5 mL·min⁻¹. Mobile phases consisted of water and acetonitrile with 0.2% formic acid and 0.015% heptafluorobutyric acid. Ions were generated by electrospray ionization in the positive mode, and RD2 was quantified by QTOF-MS. The developed extraction method revealed complete recovery. The linearity of the calibration curve was in the range of 2 ng·mL⁻¹ to 500 ng·mL⁻¹ (R² > 0.99) with a LLOQ of 5 ng·mL⁻¹. The intraday and interday accuracy and precision ranged from 0.4% to 12.2% and from 1.0% to 12.0%. RD2 remained stable in the freshly homogenized brain even after several freeze–thaw cycles, but stability decreased over time during long-term storage at −80 °C. Using this validated method, RD2-spiked brain homogenate samples and samples of a pharmacokinetic study with RD2 in mice were analyzed. Full article

Robustness falsification is a critical verification task for ensuring the safety of cyber-physical systems (CPS). Under partially observable conditions, where internal states are hidden and only input–output data is accessible, existing deep reinforcement learning (DRL) approaches for CPS robustness falsification face two key limitations: inadequate temporal modeling due to unidirectional network architectures, and sparse reward signals that impede efficient exploration. These limitations severely undermine the efficacy of DRL in black-box falsification, leading to low success rates and high computational costs. This study addresses these limitations by proposing DRL-BiT-MPR, a novel framework whose core innovation is the synergistic integration of a bidirectional temporal network with a multi-granularity reward function. Specifically, the bidirectional temporal network captures bidirectional temporal dependencies, remedies inadequate temporal modeling, and complements unobservable state information. The multi-granularity reward function includes fine-grained, medium-grained and coarse-grained layers, corresponding to single-step local feedback, phased progress feedback, and global result feedback, respectively, providing multi-time-scale incentives to resolve reward sparsity. Experiments are conducted on three benchmark CPS models: the continuous CARS model, the hybrid discrete-continuous AT model, and the controller-based PTC model. Results show that DRL-BiT-MPR increases the falsification success rate by an average of 39.6% compared to baseline methods and reduces the number of simulations by more than 50.2%. The framework’s robustness is further validated through theoretical analysis of convergence and soundness properties, along with systematic parameter sensitivity studies. Full article

Background: Most ICU patients are in the terminal phase and require complex palliative care support and End-of-Life Care (EoLC). Nurses play a central role in symptom management, emotional support, and shared decision-making. However, evidence on nurses’ experiences in providing EoLC remains fragmented and lacks a comprehensive synthesis. Objective: This review aimed to identify, map, and synthesize global evidence on ICU nurses’ experiences in delivering EoLC, including challenges, coping strategies, and implications for critical care nursing practice. Methods: A scoping review was conducted following Arksey and O’Malley’s framework and PRISMA-ScR guidelines. Systematic searches were performed in the PubMed, Scopus, and EBSCOhost databases for studies published between 2015 and 2025. Thematic analysis was applied to the qualitative studies to identify patterns and key issues. Results: Twelve qualitative studies conducted in diverse countries met the inclusion criteria. Five major themes emerged: (1) emotional and moral challenges; (2) cultural and spiritual influences; (3) communication and interprofessional collaboration; (4) professional development and organizational support; and (5) resource constraints. These findings indicate that ICU nurses’ experiences with EoLC are multidimensional and shaped by the cultural context and institutional policies. Conclusions: ICU nurses’ experiences with EoLC reflect complex ethical, emotional, and organizational dimensions. Improving care quality requires structured training, organizational support, and culturally sensitive policies to strengthen critical care nursing practice. Full article

To address the slow convergence and sensitivity to a low signal-to-noise ratio (SNR) of the minimum-entropy autofocus (MEA) algorithm in the refocusing of moving targets, this paper proposes a sparsity-assisted minimum-entropy autofocus algorithm. Within the framework of the traditional gradient descent MEA with variable step size, the proposed method introduces soft-thresholding-based sparse reconstruction to make moving targets more prominent and suppress background clutter in the image domain. A joint metric combining image entropy and the Hoyer sparsity measure is then constructed, and a three-point adaptive, variable step-size search is employed to reduce the number of evaluations of the cost function, thereby effectively mitigating clutter interference and significantly accelerating the optimization while maintaining good focusing quality. Simulation and real-data experiments demonstrate that, under complex phase errors and different SNR conditions, the proposed algorithm outperforms the conventional variable-step MEA in terms of image entropy, image sparsity, and runtime, while keeping the phase error estimation accuracy within a small range. These results indicate that the proposed method can achieve satisfactory moving-target focusing performance and exhibits promising engineering applicability. Full article

This paper proposes an Enhanced Projection-Iterative-Methods-based Optimizer (EPIMO) to overcome the limitations of its predecessor, the Projection-Iterative-Methods-based Optimizer (PIMO), including deterministic parameter decay, insufficient diversity maintenance, and static exploration–exploitation balance. The enhancements incorporate three core strategies: (1) an adaptive decay strategy that introduces stochastic perturbations into the step-size evolution; (2) a mirror opposition-based learning strategy to actively inject structured population diversity; and (3) an adaptive adjustment mechanism for the Lévy flight parameter $\beta$ to enable phase-sensitive optimization behavior. The effectiveness of EPIMO is validated through a multi-stage experimental framework. Systematic evaluations on the CEC 2017 and CEC 2022 benchmark suites, alongside four classical engineering optimization problems (Himmelblau function, step-cone pulley design, hydrostatic thrust bearing design, and three-bar truss design), demonstrate its comprehensive superiority. The Wilcoxon rank-sum test confirms statistically significant performance improvements over its predecessor (PIMO) and a range of state-of-the-art and classical algorithms. EPIMO exhibits exceptional performance in convergence accuracy, stability, robustness, and constraint-handling capability, establishing it as a highly reliable and efficient metaheuristic optimizer. This research contributes a systematic, adaptive enhancement framework for projection-based metaheuristics, which can be generalized to improve other swarm intelligence systems when facing complex, constrained, and high-dimensional engineering optimization tasks. Full article

Benzo[a]pyrene (BaP), a potent carcinogenic polycyclic aromatic hydrocarbon, is a critical food contaminant originating from environmental deposition and thermal processing, posing a significant threat to public health and driving stringent global regulations. This review critically examines recent advancements in analytical methodologies for BaP determination, giving particular emphasis to sample preparation and detection techniques. The discussion covers the evolution from conventional methods, such as solid-phase extraction, towards more efficient and sustainable approaches, including magnetic, dispersive, and molecularly imprinted solid-phase extraction, as well as microextraction techniques and gel permeation chromatography. For detection, the performance of established chromatographic methods, such as gas chromatography–mass spectrometry (GC-MS) and high-performance liquid chromatography with fluorescence detection (HPLC-FLD), is evaluated against emerging rapid techniques such as sensors, immunoassays, and spectroscopic methods. The analysis reveals that while significant progress has been made in improving sensitivity, selectivity, and throughput, challenges remain in balancing speed with accuracy, managing matrix effects, and translating novel materials from research to routine application. The review concludes by underscoring the necessity for future development to focus on the integration of smart materials, automation, and advanced data science to achieve robust, on-site, and holistic monitoring solutions for ensuring food safety against BaP contamination. Full article

The primary objective of the current study is to establish and validate for the first time a method to determine and quantify praziquantel (PZQ) and its main degradation products loaded in poly(methyl methacrylate–co-2-(diethylamino)ethyl methacrylate) P(MMA-co-DEAEMA) microparticles. A high-performance liquid chromatography (HPLC) approach was developed and validated in accordance with the United States Pharmacopeia (USP) guidelines, addressing parameters such as accuracy, linearity, solution stability, precision, specificity, robustness, sensitivity, and system suitability. The method employed a gradient mobile phase consisting of ultrapure water and acetonitrile, flowing at a rate of 1 mL/minute over a Phenomenex Kinetex^® C18 column (5 µm, 100 Å, 250 × 4.6 mm) maintained at 35 °C. Detection was performed at the wavelength of 210 nm using a DAD/UV detector. Samples of the active pharmaceutical ingredient (API) praziquantel, microencapsulated praziquantel, placebo, and a mixture of related substances (A, B, and C) were prepared with 0.5% formic acid in water/ethanol, 45:55 v/v as the diluent, and injected at 20 °C. The method demonstrated a limit of quantification (LOQ) of 0.20 µg/mL for praziquantel and related substances. The method exhibited an excellent linear response, with all correlation coefficients (R²) values exceeding 0.998, which is well above the recommended specified limit of R² > 0.995. Percent recoveries fell within the acceptable range of (95.0–105.0%), and all results indicated a percentage of relative standard deviation (%RSD) ≤ 2.0, indicating a robust methodology. Thus, the proposed HPLC technique proved to be selective, accurate, sensitive, and consistent in analyzing both the material content and its main degradation products. Full article

This article provides a comprehensive analysis of long-term changes in the minimum river flow of the southern rivers of Western Kazakhstan (Temir, Oiyil, Zhem) for the period 1940–2022, with an emphasis on summer minimum and winter low flow as key indicators of water and environmental sustainability in conditions of increasing climate variability. The study combines a typology of the climate control mechanisms of minimum flow, analysis of structural homogeneity, and assessment of the internal organization of time series based on ITA and the integral IPTA method, which allow us to reveal the hidden fluctuations and stable phase states of the hydrological regime. The calculation of the climate sensitivity index (CSI_min) showed pronounced seasonal asymmetry: summer runoff is largely controlled by atmospheric precipitation, while winter minimum runoff is determined by temperature regime and soil freezing depth. Parametric and nonparametric tests (Pettitt, ADF, SNHT) revealed significant structural shifts in the 1960s–1990s period, corresponding to large-scale climatic anomalies in the region. Summer series are characterized by phases of prolonged low water levels and negative trends in the mid-20th century, while for the winter period, a steady increase in minimum flow has been established, due to regional warming and an increase in the share of underground recharge. IPTA confirmed the presence of long-term phases with high internal heterogeneity in the summer season and a more stable winter runoff structure. The results demonstrate the high climatic sensitivity of minimum runoff and confirm the need to move from static standards to dynamically adaptable methods of water resource assessment. The proposed approach can serve as a tool for developing adaptation strategies, assessing the risk profile of basins, and improving the sustainability of water management planning in arid regions. Full article

The rapid growth and diversification of the cosmetic industry have led to increasingly complex formulations containing numerous bioactive ingredients, excipients, and synthetic additives, often delivered through advanced nanostructured systems. Ensuring product safety, efficacy, and regulatory compliance requires analytical approaches capable of accurately detecting both declared components and hazardous contaminants such as heavy metals, phthalates, nitrosamines, and banned preservatives or dyes. Traditional sample preparation methods are often solvent-intensive, time-consuming, and environmentally burdensome, prompting a shift toward green microextraction strategies aligned with the principles of green analytical chemistry. Techniques including solid-phase microextraction (SPME), stir bar sorptive extraction (SBSE), and dispersive liquid–liquid microextraction (DLLME) offer miniaturized, solvent-efficient workflows with improved selectivity and sensitivity for complex cosmetic matrices. This review summarizes advances from the past five years in green microextraction methods for the determination of organic and inorganic species in cosmetic products. Emphasis is placed on their integration with separation techniques and applicability across product categories. Emerging trends, analytical challenges, and future directions toward more sustainable cosmetic safety assessment are also highlighted. Full article

Background: The rapid growth of e-commerce has intensified the need for last-mile delivery systems that can navigate urban congestion while minimizing environmental impact. Hybrid truck–drone networks offer a promising solution by combining heavy-duty ground transport with aerial flexibility; however, their deployment faces significant challenges in jointly managing operational risks, energy limits, and regulatory compliance. Methods: This study proposes a hybrid matheuristic framework to solve this multi-objective problem, simultaneously minimizing transportation cost, service time, energy consumption, and operational risk. A two-phase approach combines a metaheuristic for initial truck routing with a Mixed-Integer Linear Programming (MILP) formulation for optimal drone assignment and scheduling. This decomposition strikes a balance between exact optimization and computational scalability. Results: Experiments across various instance sizes (up to 100 customers) and fleet configurations demonstrate that integrating MILP enhances solution diversity and convergence compared to standalone strategies. Sensitivity analyses reveal significant impacts of drone speed and endurance on system efficiency. Conclusions: The proposed framework provides a practical decision-support tool for balancing complex trade-offs in time-sensitive, risk-constrained delivery environments, thereby contributing to more informed urban logistics planning. Full article

This study evaluates the swelling potential in clayey soils of the Paleogene Brebi, Mera, and Moigrad formations in the Transylvanian Basin (Romania) by integrating direct free-swelling tests (FS; STAS 1913/12-88) with indirect index-property diagrams and semi-quantitative X-ray diffraction (XRD; RIR method). The indirect analysis combines three swelling-susceptibility classification charts—Seed et al. (AI–clay), Van der Merwe (PI–clay), and Dakshanamurthy and Raman (LL–PI)—with mineralogical trends from the Casagrande plasticity chart, complemented by Holtz and Kovacs’s clay-mineral reference fields and Skempton’s activity concept (AI = PI/% < 2 µm). The geotechnical dataset comprises 88 Brebi, 46 Mera, and 263 Moigrad specimens (with parameter counts varying by test), an XRD was performed on a representative subset. The free swell (FS) results indicate that Brebi soils range from low to active behavior (50–135%) without reaching the very active class; most Brebi specimens fall in the medium-activity range. Moigrad spans the full FS spectrum (20–190%) but is predominantly in the medium-to-active range. In contrast, Mera soils exhibit predominantly active behavior, covering the full range of activity classes (30–170%). The empirical classification charts diverge systematically: clay-sensitive schemes tend to assign higher swell susceptibility than the LL–PI approach, especially in carbonate-influenced soils. XRD results corroborate these patterns: Brebi is calcite-rich (mean ≈ 53.5 wt% CaCO₃) with minor expandable minerals (mean ≈ 3.1 wt%); Mera is feldspathic (orthoclase mean ≈ 55.3 wt%) with variable expandable phases; and Moigrad has a higher clay-mineral content (mean ≈ 38.8 wt%). Overall, swelling is controlled by the combined effects of clay-fraction reactivity, clay volume continuity, and carbonate-related microstructural constraints. Full article

Spatial resolution is a critical parameter for optical frequency domain reflectometry (OFDR). Phase-sensitive OFDR (Φ-OFDR) measures strain by detecting phase variations between adjacent sampling points, having the potential to achieve the theoretical limitation of spatial resolution. However, the results of Φ-OFDR suffer from large fluctuations due to multiple types of noise, including coherent fading and system noise. This work presents an OFDR-based strain sensing method that combines phase demodulation with cross-correlation analysis to achieve high spatial resolution. In the phase demodulation, the frequency-shift averaging (FSAV) and rotating vector summation (RVS) algorithms are first employed to suppress coherent fading noise and achieve accurate strain localization. Then the cross-correlation approach with an adaptive window is proposed. Guided by the accurate strain boundary obtained from phase demodulation, the length and position of the cross-correlation window are automatically adjusted to fit for continuous and uniform strain regions. As a result, an accurate and complete strain distribution along the entire fiber is finally obtained. The experimental results show that, within a strain range of 100–700 με, the method achieves a spatial resolution of 0.27 mm for the strain boundary, with a root-mean-square error approaching 0.94%. The processing time reaches approximately 0.035 s, with a demodulation length of 1.6 m. The proposed approach offers precise spatial localization of the strain boundary and stable strain measurement, demonstrating its potential for high-resolution OFDR-based sensing applications. Full article

Background/Objectives: Fluvoxamine (FLU) is a selective serotonin reuptake inhibitor and one of the most potent agonists of the sigma-1 receptor. Emerging evidence shows that FLU exerts protective effects in multiple organs, making it a promising candidate for topical ocular therapy. Developing an FLU eyedrop for glaucoma can address a significant treatment gap with potentially fewer side effects compared with conventional therapies. To optimise formulation development, precise quantification of FLU in ocular compartments such as aqueous humour, as well as systemic circulation, is essential to characterise drug absorption, ocular bioavailability, and safety. Methods: We developed and validated a UHPLC-MS method for FLU detection in aqueous humour and serum using simple sample preparation steps. Results: The 11-min-long reverse phase chromatography followed by SRM-based mass spectrometry detection provides a highly selective and sensitive FLU detection method. Our method was proved to be linear in the 0.0625–1.5 µg/mL range and was validated according to the EMA guidelines. Conclusions: The simplicity of sample preparation, the tolerable matrix effects, and the favourable detection parameters provide a robust tool for preclinical pharmacokinetic and pharmacodynamic studies of FLU’s ocular protective effects. Full article