Search Results (3,078)

High-efficiency diesel and lean-burn engines produce lower exhaust temperatures, which can delay the activation of after-treatment catalysts such as Diesel Oxidation Catalysts (DOCs). This study explores ion beam sputtering as a post-synthesis strategy to enhance the low-temperature activity of commercial Pt/CeO₂–ZrO₂ catalysts. Low-energy ions (0.5–1.5 keV) were applied with controlled variations in treatment number, beam current, and exposure time to selectively generate oxygen vacancies and improve Pt dispersion. Structural and chemical effects were characterized using X-ray diffraction (XRD), BET surface area measurements, X-ray photoelectron spectroscopy (XPS) and extended X-ray absorption fine structure (EXAFS). Catalytic performance was evaluated through CO and C₃H₆ oxidation under conditions mimicking lean-burn engine exhaust. Increasing the number of ion treatments progressively lowered light-off temperatures, correlating with enhanced Pt–Ce³⁺ interactions and improved surface reducibility. Variations in beam current and exposure time further modulated these surface effects, confirming the tunable nature of the approach. The results demonstrate that ion beam sputtering selectively modifies the catalyst surface without altering the bulk structure, directly linking atomic-scale modifications to improved low-temperature activity. This strategy offers a promising route to overcome delayed light-off issues in modern high-efficiency engines, providing a precise, controllable method to optimize emission control catalysts. Full article

(Bi_0.5Na_0.5)TiO₃-based lead-free ferroelectric ceramics are among the most extensively researched energy storage materials today. In this paper, (1 − x)Bi_0.46Sr_0.06Na_0.5TiO_3−xCaTiO₃ ceramics were synthesized through a solid-phase sintering method by synergistically adjusting CaTiO₃ components after introducing Sr²⁺ at the A-site. The XRD patterns revealed that all samples formed a single perovskite solid solution, with the 111 and 200 peaks shifting to higher levels as the CaTiO₃ increased, indicating a gradual decrease in cell volume. The SEM images exhibited dense crystals without any apparent porosity, which were formed by the different components of the ceramics. Through energy storage, dielectric, and charge–discharge performance tests, it was found that with a 10%mol CaTiO₃ addition, the samples obtained a maximum breakdown field strength of 260 kV/cm and corresponding saturation polarization strength of 32.80 μC/cm² and thereby exhibited a reversible energy storage density valued 3.52 J/cm³. In addition, the dielectric constant varied by less than 10% within the temperature range of 63.7 °C to 132.7 °C and presented good frequency (10–250 Hz) stability at 180 kV/cm. Moreover, the ceramics demonstrated a maximum current density reaching 349.58 A/cm² and a maximum power density of 18.90 MW/cm³ for their charge–discharge performance, all of which makes them suitable for pulse system applications. Full article

The oxygen reduction reaction (ORR) is a crucial process in electrochemical systems, such as fuel cells, as it effectively converts oxygen into water, thereby contributing significantly to sustainable energy generation. In this study, copper oxide (CuO) thin films were deposited onto silver (Ag) substrates using a modified successive ionic layer adsorption and reaction (SILAR) method, followed by an investigation of their electrocatalytic performance toward ORR in an alkaline medium. Comprehensive electrochemical characterizations, including cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and open circuit potential (OCP), were employed to evaluate catalyst behaviour. Elemental analysis through energy-dispersive X-ray spectroscopy (EDX) confirmed the uniform distribution of CuO, while scanning electron microscopy (SEM) revealed a sponge-like surface morphology which potentially enhances catalytic efficiency. Moreover, EIS spectra revealed a lower charge transfer resistance for the CuO/Ag electrode (3.37 kΩ) compared to bare Ag (4.23 kΩ), reflecting improved ORR kinetics. Among different deposition cycles, 15 SILAR cycles yielded the highest current density of 0.8 mA cm⁻² at 0.60 V. Kinetic analysis revealed that the reaction is irreversible, with a lower value of Tafel slope (32 mV dec⁻¹) and high transfer coefficient (α = 0.45), indicating a concerted reduction mechanism. The ORR pathway was found to follow a four-electron (4e⁻) transfer process. Full article

Human norovirus (HuNoV), particularly the GII.4 genotype, is a leading cause of acute gastroenteritis worldwide, posing a significant public health and economic burden due to its low infectious dose. To address the need for rapid and sensitive detection, we developed a colorimetric biosensor utilizing a structure-optimized aptamer and gold nanoparticles (AuNPs). Biotin-modified aptamers could protect AuNPs from aggregation in salt solution. Upon specific binding to GII.4 HuNoV virus-like particles (VLPs), this protective effect is disrupted, leading to AuNP aggregation and a measurable color shift quantified by the A620/A520 absorbance ratio. Under optimized conditions, the assay demonstrated a linear response (y = 0.004597x + 0.3277, R² = 0.9922) to GII.4 HuNoV VLP concentrations ranging from 0.1 to 3.0 μg/mL, with the recovery rates between 91.74% and 106.43%. The biosensor exhibited high specificity for GII.4 HuNoV, showing minimal cross-reactivity with other common diarrheal pathogens, and achieved an exceptional detection limit of 27.2 copies/mL in a fecal matrix. Molecular docking and point mutation confirmed the critical roles of specific nucleotide bases (T20, C22, G31, and G44) in the aptamer and the Asn55 residue in the viral capsid for binding. This work establishes a sensitive, rapid, and cost-effective aptamer-based colorimetric platform suitable for the large-scale monitoring of GII.4 HuNoV. Full article

This study develops a tractable, closed-form expression for the asymptotic variance of the coefficient of variation (CV) estimator under a reparameterized Birnbaum–Saunders (BirSau) distribution. Using the method of moments, we derive analytical formulas for the mean, variance, and coefficient of variation of $X\sim \mathrm{BirSau}(\mu ,\lambda )$ and construct a plug-in estimator for the CV. By applying the delta method within this new nonlinear parametrization, we obtain an explicit and compact expression for the asymptotic variance of the CV estimator, thereby extending general asymptotic theory to a distribution-specific setting where higher-order moments lack closed forms under the classical parametrization. Extensive Monte Carlo simulations are conducted to examine the estimator’s finite-sample performance under various parameter configurations and sample sizes. The results demonstrate that the estimator exhibits decreasing bias and variance as the sample size increases, with strong convergence to its theoretical asymptotic behavior. A real-data application using rainfall measurements from northeastern Thailand further illustrates the practical utility of the proposed approach in quantifying relative variability across regions. These findings provide a concise analytical foundation for the coefficient of variation under the Birnbaum–Saunders framework, enhancing its theoretical development and facilitating practical implementation in environmental and reliability analyses. Full article

Self-emulsifying delivery systems (SEDSs) generate micro/nanoemulsions within the gastrointestinal tract, enhancing the bioavailability of hydrophobic phytochemicals. Turmeric rice is a staple across Asia, yet the mechanism of curcumin binding with rice remains unclear. This study utilized curcumin SEDS and pre-heating to produce curcumin instant rice (CIR). The CIR maintained its appearance and increased the levels of slowly digestible starch to 26.43–28.38% following steamer steaming (SST). In contrast, cooker water-boiling treatment (CWBT) enhanced resistant starch (16.73–38.24%), curcumin loading (3.77–61.39 mg/100 g), total phenolic content (23.09–193.79 mg GAE/100 g DW), and antioxidant activity. Following 50 min of CWBT, the gelatinization process disrupted the ordered structure of starch, facilitating the formation of amylose–lipid complexes. This process resulted in a maximum resistant starch content of 47.81% and a curcumin loading of 66.50 mg/100 g. Differential scanning calorimetry revealed an endothermic peak for type II crystals (105–130 °C), while X-ray diffraction exhibited V-type patterns, confirming the observed changes. Pre-heating enhanced the curcumin encapsulation and RS of CIR, thereby enhancing its bioavailability relative to conventional turmeric rice. Full article

Labor shortages in seedling nurseries, particularly in manual inspection and replanting, hinder operational efficiency despite advancements in automation. This study aims to develop a cost-effective, GPU-free machine vision system to automate the detection of deficient seedlings in plug trays, specifically for small-scale nursery operations. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. Under controlled laboratory conditions, the DDRP-Machine achieved high detection accuracy (96.0–98.7%) and precision rates (82.14–83.78%). Benchmarking against deep-learning models such as YOLOv5x and Mask R-CNN showed comparable performance, while requiring only one-third to one-fifth of the cost and avoiding complex infrastructure. The Batch Detection (BD) mode significantly reduced processing time compared to Continuous Detection (CD), enhancing real-time applicability. The DDRP-Machine demonstrates strong potential to improve seedling inspection efficiency and reduce labor dependency in nursery operations. Its modular design and minimal hardware requirements make it a practical and scalable solution for resource-limited environments. This study offers a viable pathway for small-scale farms to adopt intelligent automation without the financial burden of high-end AI systems. Future enhancements, adaptive lighting and self-learning capabilities, will further improve field robustness and including broaden its applicability across diverse nursery conditions. Full article

ZnO thin films were deposited on soda–lime glass substrates using the chemical spray pyrolysis method at a temperature of 500 °C. After the deposition, the substrates were irradiated with 10 keV H⁺ and Ar⁺ ions using a Colutron ion gun. We investigated the optical, structural, and morphological properties of the irradiated samples using Rutherford Backscattering Spectrometry, Ultraviolet and Visible Spectroscopy, X-ray diffraction, and Scanning Electron Microscopy. Our results showed a slight decrease in the optical band gap of the irradiated samples, which can be attributed to the quantum confinement effect caused by changes in the crystallite size. The diffractograms displayed diffraction peaks corresponding to the characteristic planes of the hexagonal wurtzite phase of ZnO, indicating that the films were polycrystalline with a preferential orientation along the c-axis. We also observed a reduction in the average crystallite size of the samples after ion irradiation. The morphological study showed that the average grain size increased and the shape changed from spherical in the pristine sample to flake-like after irradiation. Additionally, the samples irradiated with Ar⁺ ions exhibited a bimodal distribution in grain size, which is attributed to the defects and nucleation centers generated during the irradiation process. Full article

This study synthesizes three new composites: chitin-cross-linked poly(ortho-phenylenediamine)-grafted silicon dioxide (CT-PoPD-grafted SiO₂), chitosan-cross-linked PoPD-grafted SiO₂ (CS-PoP-grafted SiO₂), and guar-gum-cross-linked PoPD-grafted SiO₂ (GG-PoPD-grafted SiO₂). These biopolymer-based materials were developed as cost-effective, biocompatible adsorbents with increased surface area for removing Acid Red 1 AR1) and Crystal Violet (CV) dyes. Structural and morphological analyses through Fourier-transform infrared spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy (XPS) confirmed their successful synthesis. Adsorption studies were conducted under various conditions, including adsorbent dosage, pH, temperature, and contact time. Among the composites, GG-PoPD-grafted SiO₂ demonstrated superior performance, achieving 99.1% and 95.6% removal of AR1 and CV, respectively. Kinetic analysis revealed a pseudo-second-order model, while thermodynamic results indicated a spontaneous and endothermic adsorption process. In conclusion, the GG-PoPD-grafted SiO₂ composite exhibits significant potential as an effective and sustainable material for wastewater treatment. Full article

Selenium, a crucial trace element, has garnered significant attention in functional food development due to its effective conversion into organic forms. This study systematically investigated the selenium enrichment potential and metabolic regulation mechanisms of 50 lactic acid bacteria (LAB) strains from Xinjiang. Through sodium selenite tolerance tests, eight core strains with over 80% selenium enrichment were selected, with optimal enrichment conditions being a 37 °C temperature, 2% sodium chloride concentration, and pH of 6.0 in MRS medium. Functional tests demonstrated that selenium-enriched strains exhibited a significantly enhanced antioxidant capacity (demonstrated by DPPH and ABTS free radical scavenging activities) and improved gastrointestinal fluid tolerance, with strain No.41 showing the most outstanding performance. Scanning electron microscopy combined with energy-dispersive X-ray spectroscopy (SEM-EDX) revealed nanoscale selenium (1.34 keV) on cell surfaces. Further characterization showed that 68.94% of selenium was incorporated into selenoproteins, 7.61% into nucleic acids, and 7.02% into polysaccharides. Integrated metabolomic and proteomic studies have shown that selenium reduces the content of L-cysteine primarily by replacing sulfur and competing for key sites in cysteine-S-conjugate-β-lyase, S-adenosyl-L-cysteine hydrolase, and homocysteine synthase, ultimately leading to the synthesis of selenocysteine and selenomethionine. A correlation analysis between differential metabolites and proteins revealed selenium’s significant impacts on the metabolic networks of LAB, antioxidant mechanisms, energy metabolism, and membrane stability. This research provides new insights for developing selenium-enriched probiotics for functional dairy products and health supplements. Full article

This paper investigates within-scene path loss prediction at 1.8 GHz in a smart-campus micro-urban environment using multivariate machine-learning (ML) models. We leverage an open measurement campaign from Covenant University (Nigeria) comprising three routes with per-sample geospatial predictors—longitude, latitude, altitude, elevation, Tx–Rx distance, and clutter height—and train Random Forests (RF), Gradient Boosting (GB), Support Vector Regression (SVR), Gaussian Processes (GP), and a shallow neural network (NN). A unified pipeline with 5-fold cross-validation (CV), seeded reproducibility, and Optuna-driven hyperparameter search is adopted; performance is reported as RMSE/MAE/R² (mean ± sd). To contextualize feature reliability, we include Pearson correlation heatmaps and Variance Inflation Factors (VIFs), a systematic ablation of predictors, and TreeSHAP beeswarm analyses on held-out splits. We also evaluate spatially aware validation (blocked CV within route and leave-one-route-out checks) to mitigate optimism due to spatial autocorrelation. Results show that multivariate ML consistently outperforms classical empirical formulas (COST-231, ECC-33) in this campus setting, with RF achieving the lowest errors across routes (RMSE ≈ 2.14/2.16/2.95 dB for X/Y/Z, respectively), while GB ranks second and kernel methods (SVR/GP) and the NN trail closely behind. Ablation confirms that distance plus coordinates drive the largest gains, with terrain/clutter providing route-dependent refinements. SHAP analyses align with these findings, highlighting stable, interpretable contributions of geospatial covariates. Spatial CV increases absolute errors moderately but preserves model ranking, supporting the robustness of conclusions. Overall, scenario-aware, multivariate ML yields material accuracy gains for smart-campus planning at 1.8 GHz. Full article

Adequate intake of fruits and vegetables (F + V) supports healthy growth and development in children, yet many New Zealand children do not meet national dietary recommendations, and methods to evaluate intake require good reliability. Objectives: To establish the validity and reliability of a modified 24 h multiple pass recall (MPR) for evaluating F + V and carotenoid intakes in children aged 9–13 years. The reliability of the Veggie Meter^® (VM^®), a non-invasive reflection spectrometer to estimate skin carotenoid scores and derive blood carotenoid concentrations, was also examined. Methods: Thirty-two children (20 boys, 12 girls) completed three 24 h MPRs and parent-assisted weighed food diaries (WFDs) on randomised weekdays and weekends. Skin carotenoid scores were assessed using the VM^®. The validity of the MPR was evaluated against WFDs using log-transformed Pearson correlations and mean x-axis bias. The reliability was assessed by the coefficient of variation (CV) and Pearson correlations. Results: Participants did not meet recommended F + V intakes (5–5.5 servings/day): MPR (mean fruit 1.3 servings/day; vegetables 2.0), WFD (fruit 1.3; vegetables 1.9). The MPR was a valid tool to estimate fruit and vegetable daily servings (combined-day Pearson coefficients > 0.71) with only trivial–small standardized mean bias-offset vs. WFD; however, the reliability was poor for the MPR-estimated carotenoid intake (CV 126%) and F + V intake. In contrast, the VM^® was reliable (Pearson correlation 0.97–0.99) with low measurement error (CV 4.0–5.2%). Conclusions: The modified 24 h MPR was valid but unreliable for estimating F + V and carotenoid intake. The VM^® demonstrated high reliability as a biomarker of skin carotenoid status in children. Full article

To investigate the influence of laser cladding overlap rate on the microstructure and corrosion resistance of cladded layers, Ni60-WC composite coatings with different overlap rates (30%, 50%, and 70%) were prepared on E690 offshore steel in this study. The relationship between the corrosion resistance and microstructure of the cladded layers fabricated at different overlap rates was analyzed using an electrochemical workstation, scanning electron microscope, X-ray diffractometer, and energy dispersive spectrometer. The results demonstrate that the overlap rate exerts a significant impact on the corrosion resistance of the cladded layers, and the corrosion resistance of the cladded layers gradually improves with the increase in overlap rate. The cladded layer prepared with a 70% overlap rate exhibits excellent corrosion resistance, featuring the highest open-circuit potential (−0.31 V vs. SCE), the lowest corrosion current density (3.35 μA/cm²), the largest capacitive arc radius in the electrochemical impedance spectroscopy (EIS), and a relatively flat surface after corrosion tests. Microstructural characterization results indicate that the increase in overlap rate promotes grain refinement and the formation of reinforcing phases (e.g., M₂₃C₆). The coating with a 70% overlap rate possesses the densest microstructure and abundant flocculent carbides, which act as an effective barrier against the penetration of corrosive media, thereby endowing it with optimal performance. Full article

Adaptive Equivalent Consumption Minimization Strategies (A-ECMSs) are one of the best methodologies to optimize fuel consumption of plug-in hybrid vehicles (PHEVs) coupled with low computational requirements. In this paper, a review of A-ECMSs is proposed. Starting from an economic-environmental contextualization, hybrid vehicles are presented and classified, together with their modeling methodologies and the physical-mathematical representation of their components. Next, the control theory for hybrid vehicles is introduced and classified, deriving the A-ECMS approach. Several works accounting for different A-ECMS implementations, based on technology integration, time horizon, adaptivity mechanism, and technique, are addressed. The literature analysis shows a broad coverage of possibilities: the simple proportional-integral (PI) rule for equivalence factor adaptivity is often used, imposing a given battery state-of-charge (SoC); it is possible to optimally plan the battery SoC trajectory through offline optimization with optimal algorithms or by predicting ahead conditions with model predictive control (MPC) or neural networks (NNs); the integration with emerging technologies such as Vehicle-To-Everything (V2X) can be helpful, accounting also for car-following data and GPS information. Moreover, speed prediction is another common technique to optimally plan the battery SoC trajectory. Depending on available on-board computational power and data, it is possible to choose the best A-ECMS according to its application. Full article

Salt-tolerance improvement of tomatoes is largely a task of modern selection and plant molecular genetics because of cultivation on dry and irrigated lands under salt stress. To reveal the salt resistance gene, we need quantitative real-time polymerase chain reaction (qRT-PCR) normalization through reference genes analysis. Sometimes, housekeeping gene expression changes in response to various stress factors, especially salinity. In this manuscript, we evaluated expression changes of elongation factor 1α X53043.1 (EF1α), actin BT013707.1 (ACT), ubiquitin NM_001346406.1 (UBI), nuclear transcript factor XM_026030313.2 (NFT-Y), β-tubulin NM_001247878.2 (TUB), glyceraldehyde-3 phosphate dehydrogenase NM_001247874.2 (GAPDH), phosphatase 2A catalytic subunit NM_001247587.2 (PP2a), and phosphoglycerate kinase XM_004243920.4 (PGK) in salt-sensitive Solanum lycopersicum L. YaLF line and salt tolerance Rekordsmen cv. under 100 mM NaCl. We also suggested potential correlations between relative water content (RWC), ion accumulation, and reference gene expression in tomato genotypes with contrasting salinity tolerance. We used geNorm, NormFinder, BestKeeper, ∆Ct, and RefFinder algorithms to establish a set of the most reliable tomato candidate genes. The most stable genes for YaLF tomatoes were ACT, UBI, TUB, and PP2a. Despite differences in ranks, the NFT-Y was present in Rekordsmen’s stable set. Full article