Search Results (752)

This study examined the effect of east–west orientation of willow tree (Salix alba L.) rows on soil biological activity and weed dynamics in a temperate maize (Zea mays L.) intercropped agroforestry (AF) system in Eastern Hungary. The experiment evaluated how the year (2022, 2023), location (distance from the rows), and irrigation (IR) influenced spatial patterns of earthworm (EW) parameters and weed cover. The study aimed to assess how willow-based AF systems influence soil biological and weed community dynamics under varying IR and row spacing, in comparison with monoculture cropland (MC) systems, and to evaluate their potential role in climate change adaptation in arable farming. Both soil sampling for the EW survey and vegetation studies were conducted along perpendicular transects extending from the tree rows to measure EW abundance and biomass, as well as total weed cover. Experimental results revealed clear spatial gradients in EW distribution and weed abundance near the tree rows, driven by litter input, shading, moisture, and reduced disturbance. These effects were intensified under IR at narrower row spacings. No significant differences were observed between AF-South (shaded), AF-Center, and MC plots; however, significantly higher EW abundance and biomass were found on the AF-North (sunny) side. As for the location, significantly greater total EW abundance was found at AF-North (105.0 individual m⁻²) compared with the MC plots. AF systems enhance soil biological activity and shape weed dynamics through spatial ecological gradients influenced by tree row spacing and irrigation, supporting their role as sustainable land-use systems while emphasizing the need for site-specific management and further long-term optimization. Full article

The field of infrared (IR) photodetection is undergoing rapid development through the emergence of solution-processable nanoparticle (NP)-based materials and fabrication strategies. This review critically examines recent advances in fabrication approaches for NP-based IR detectors, emphasizing the relationship between synthesis, surface engineering, deposition processes, and device architecture in determining detector performance. Representative material platforms are discussed, including colloidal quantum dots (CQDs) such as PbS and HgTe, which enable tunable operation from the near-infrared (NIR) and short-wave infrared (SWIR) to selected mid-wave (MWIR), long-wave (LWIR), and emerging very-long-wave infrared (VLWIR) regimes depending on material composition and operating conditions. Further platforms including plasmonic metal NPs, black phosphorus, and topological nanomaterials are evaluated for their unique mechanisms of optical enhancement and broadband response. Fabrication approaches including continuous-flow synthesis, ligand exchange, blade coating, inkjet printing, electrophoretic deposition, and other scalable solution-processing methods are analyzed with respect to their influence on film quality, charge transport, interface engineering, and integration compatibility. The review further compares major device architectures, including photoconductors, photodiodes, plasmonic absorbers, and phototransistors, using key performance metrics such as specific detectivity (D*), responsivity (R), response speed, and operating temperature, while emphasizing the importance of measurement conditions in cross-platform comparisons. Critical challenges including dark-current generation, 1/f noise, transport limitations associated with ligand chemistry, environmental instability of narrow-bandgap materials, manufacturability constraints, and toxicity considerations are also discussed. Emerging directions such as neuromorphic sensing, CMOS-compatible integration, and sustainable lead-free nanomaterials are highlighted. By linking nanoscale material design and fabrication processes to device-level performance, this review provides a framework for advancing NP-based IR technologies toward scalable and application-relevant sensing systems. Full article

The photoreceptor bacteriorhodopsin (HsBR) from Halobacterium salinarum is a model system for studying ultrafast photoinduced reactions in proteins. Recent time-resolved serial femtosecond crystallography (TR-SFX) experiments require high pump energies, raising concerns about nonlinear excitation and multi-photon effects. Here, we systematically investigate the influence of excitation energy, pulse duration and the sign of the chirp on the initial HsBR photo-reaction using femtosecond Vis-pump IR-probe spectroscopy in the retinal C=C stretching region. An acousto-optic programmable dispersive filter enabled independent control of pulse energy and chirp. Within the tested range, the retinal dynamics were independent of pulse duration and chirp, indicating that fluence alone does not fully describe excitation conditions. Increasing excitation energy leads to nonlinear saturation of the retinal signals and the appearance of an additional band near 1550 ${\mathrm{cm}}^{-1}$. However, this band rises linearly with the excitation energy. Hence, the additional band is not directly caused by non-resonant multi-photon absorption. Spectral decomposition reveals two components: a low-energy contribution consistent with the known retinal isomerization dynamics and a high-energy contribution attributed to a small population of photo-damaged HsBR likely formed via a resonant two-photon process. These findings clarify the role of excitation conditions in ultrafast HsBR spectroscopy and suggest that spectral changes at high pump energies mainly arise from damaged species upon resonant two-photon excitation. Full article

Near-infrared radiation contributes to photoaging through oxidative stress and matrix metalloproteinase activation. Botanical extracts with antioxidant properties may offer additional protection beyond conventional UV filters. To evaluate the effect of hydrogel formulations containing Rosmarinus officinalis and Crataegus monogyna extracts on the directional reflectance of human skin across various spectral ranges. Directional reflectance was measured on the forearm skin of healthy female volunteers before and after application of a base hydrogel and hydrogels containing plant extracts. Hyperspectral imaging was used across spectral ranges of 335–2500 nm. To assess the application properties, rheological and textural evaluation of extract-based hydrogels was performed. The obtained results are satisfactory and indicate the expected application effectiveness of hydrogels with C. monogyna and R. officinalis extracts. Significant reductions in skin reflectance were observed in the IR spectrum after application of both botanical formulations. Median reflectance decreased by 3.5% with rosemary and 2.3% with hawthorn in the 1000–1700 nm range, and by 17.8% and 20.3% respectively in the 1700–2500 nm range. No statistically significant changes were observed in the UV or visible light ranges. Hydrogels enriched with R. officinalis and C. monogyna extracts reduced infrared reflectance of the skin, suggesting potential as adjunctive agents in photoprotection. These findings support further investigation into extract-based formulations for IR-related skin damage prevention. Full article

This study assesses the technical feasibility of using polar orbiting satellite constellations to generate temperature profiles in the middle atmosphere, based on image analysis from the UVSQ-Sat NG nanosatellite. We first identified the phenomena influencing the temperature of this layer of the atmosphere, specifying their amplitudes and spatio-temporal resolutions. We then present the UVSQ-Sat NG nanosatellite and its Nanocam instrument, whose images of the Earth’s limb served as the basis for our processing. Finally, we detail the processing methodology, demonstrating its applicability to any image of the Earth’s limb acquired in the spectral range from near-UV to near-IR, subject to the following strict conditions: a measurement dynamic range greater than 1000 and rigorous control of instrumental noise. This approach paves the way for continuous, global monitoring of the middle atmosphere, which is essential for improving climate and weather models. Full article

Road freight transport (RFT) faces growing pressure from increasing freight demand, stricter environmental requirements, and persistent driver shortages. Automation technologies (ATes)—especially semi-autonomous driving—are increasingly viewed as a practical pathway toward improving the sustainability performance of freight operations; however, their effects depend strongly on infrastructure and operational conditions. This study evaluates the sustainability potential of autonomous and semi-autonomous trucks through an integrated framework combining (i) a structured review of technical and regulatory developments, (ii) surveys of transport enterprises (TEes) and road users (RUs), (iii) SWOT/TOWS analysis, and (iv) a cost minimization logistics model that links operational feasibility to infrastructure readiness (IR). The proposed model minimizes cost per tonne-kilometre and introduces an Infrastructure Readiness Score (IRS) to represent the share of a route that can be operated in automated mode; it also accounts for fuel savings from platooning and higher maintenance and capital costs of semi-autonomous vehicles (SAVs). Results indicate that, as IRS increases, semi-autonomous operations achieve higher daily mileage and lower unit costs, with a break-even point at approximately IRS ≈ 0.125. Beyond this threshold, unit costs decline from EUR 0.0433 to EUR 0.0348 per tonne-kilometre as IRS rises toward 0.6, after which further infrastructure improvements yield diminishing mileage gains. These cost and utilization improvements imply sustainability benefits via improved energy efficiency and reduced emissions intensity per tonne-kilometre. Nevertheless, survey evidence highlights major adoption barriers, including insufficient IR, regulatory uncertainty, technological reliability concerns, and limited public trust in fully autonomous systems. Overall, the findings support semi-autonomous trucking as the most feasible near-term stage of transition, while emphasizing that infrastructure upgrades and governance mechanisms are critical for scaling sustainability gains. Full article

Background/Objectives: Cardiovascular disease (CVD), particularly coronary artery disease (CAD), is increasingly linked to microvascular inflammation driven by interactions between immune, vascular, and neuroendocrine systems. Mast cells (MCs), strategically positioned near blood vessels, play pivotal roles in this process through the release of inflammatory and vasoactive mediators, contributing to increased vascular permeability, endothelial dysfunction, and tissue inflammation in conditions including ischemia–reperfusion (I/R) and CVD. This comprehensive review examines the cellular and molecular mechanisms underlying MC-mediated microvascular inflammation, with emphasis on neuroimmune regulation through the heart–brain axis, and evaluates the therapeutic potential of flavonoids. Methods: A review of in vitro, animal, and clinical studies was conducted to assess MC-mediated cardiovascular pathology and the pharmacological effects of natural flavonoids on MC activation and microvascular inflammation. Results: Psychological and physical stress activates hypothalamic corticotropin-releasing hormone (CRH) signaling, directly triggering coronary MC degranulation via CRHR-1 and CRHR-2 receptors, while co-released neuropeptides, including neurotensin and urocortin, amplify this neuroimmune cascade. Traumatic brain injury, autonomic dysregulation, and atrial fibrillation further perpetuate this bidirectional heart–brain axis, linking neurological stress to microvascular injury and adverse cardiac remodeling. An autocrine–paracrine CRH amplification loop sustains chronic coronary microvascular inflammation, contributing to heart failure with preserved ejection fraction (HFpEF) and MC activation disease (MCAD)-related cardiovascular manifestations. Natural flavonoids were found to inhibit MC activation, suppress inflammatory mediator synthesis, and protect microvascular integrity through multiple molecular targets, including calcium signaling, transcription factors, oxidative stress pathways, and CRHR-1-mediated neuroimmune signaling. Conclusions: While challenges remain regarding bioavailability and standardization, multi-compound formulations targeting multiple risk factors hold promise for preventing CVD progression. Future research directions for advancing these natural compounds toward clinical implementation are identified. Full article

Ensuring the authenticity of origin labeling is a challenge for brown algae products such as kelp, wakame, and hijiki. While conventional DNA analysis has high discriminatory capabilities, it is not necessarily suitable for routine screening of large quantities of samples due to time and cost considerations. This study aimed to identify the species (variety) and geographical origin of brown algae (kelp, wakame, and hijiki), with both variety and origin evaluated for kelp and geographical origin evaluated for wakame and hijiki. To achieve this, classification methods were developed for each of three spectroscopic analysis techniques—excitation emission matrix (EEM), Fourier transform infrared spectroscopy (FT-IR), and near-infrared spectroscopy (NIR)—using machine learning algorithms, and their classification performance was systematically compared and evaluated. Six classification models, k-nearest neighbors (KNN), convolutional neural networks (CNN), LightGBM, XGBoost, random forest, and support vector machines, were constructed to distinguish varieties and origins based on EEM, NIR, and FT-IR data. Depending on the combination of methods, high-precision identification was obtained (>99%), especially for kelp variety identification using NIR + KNN (≈100%). These results suggest that each spectral dataset contains characteristic information specific to each sample and that selecting a model suited to these characteristics is effective for highly accurate identification of variety (in kelp) and geographical origin. The selected method can serve as a rapid and simple identification tool that contributes to verifying the authenticity of brown algae products and improving raw material traceability. Full article

Proton exchange membrane water electrolysis (PEMWE) is currently limited by the sluggish kinetics and poor durability of the oxygen evolution reaction (OER). In this work, a structurally uniform IrB_160-4 catalyst was synthesized through a simple, scalable one-pot aqueous method. This template-free method enables near-quantitative yields and gram-scale preparation, with products rapidly separated via simple filtration. The catalyst consists of uniform, nanoclusters self-assembled from highly crystalline ~3 nm Ir nanoparticles. The optimized catalyst exhibits superior OER activity over commercial Ir-Black. The assembled proton exchange membrane electrolyzer, utilizing a low anodic iridium loading of 0.5 mg cm⁻², demonstrates excellent performance (2.0 A cm⁻² @ 1.79 V) and high durability (>1500 h). This synthesis strategy provides a feasible method for achieving efficient and stable PEM water electrolysis for hydrogen production. Full article

The infrared (IR)—visible light (VIS) dual-camera system provides complementary cues for image fusion, but issues such as geometric mismatch caused by different imaging methods, inconsistent resolution/field-of-view, and installation offsets often lead to ghosting and artifacts. This study aims to develop a fast-deployable and repeatable calibration workflow based on cost-effective calibration board. We designed an infrared-visible high-contrast checkerboard plate that can be generated through structural parameterization and efficiently manufactured using Python/OpenSCAD. We also established a corner-based registration pipeline that estimates global homography to align the visible-light images onto the infrared pixel grid for fusion and quantitative evaluation. Experiments conducted in a controlled indoor environment demonstrated stable sub-pixel performance within a range of 1.5–2.5 m, with an average re-projection error of 0.47–0.50 pixels per frame and a 95th percentile lower than 0.51 pixels. The corner position re-projection error test further confirmed stability near image boundaries, with a median value of 0.53–0.63 pixels and a 95th percentile of 0.54–0.64 pixels. Overall, the proposed target design and workflow can achieve practical infrared-visible calibration under typical deployment constraints and have repeatable accuracy, providing geometrically consistent input for subsequent fusion and dataset construction. Full article

Trichloroethylene (TCE) is a pervasive groundwater contaminant, yet the practical application of nanoscale zero-valent iron (nZVI) is often limited by particle aggregation, rapid surface oxidation, and inefficient utilization of reactive electrons. Here, we developed a support–sulfidation coupled design to improve TCE dechlorination by integrating ZIF-8-enabled contaminant enrichment and dispersion with sulfidation-enabled surface-state regulation. A ZIF-8-supported sulfidated nZVI composite (ZIF-8@S-nZVI) was synthesized and systematically compared with nZVI, S-nZVI, and ZIF-8@nZVI. Among the tested materials, ZIF-8@S-nZVI exhibited the fastest TCE removal, the highest ethylene formation, and the highest chloride release, indicating the most effective dechlorination performance rather than merely adsorption-driven apparent removal. The optimal Fe:ZIF-8 mass ratio was 6:1. The composite also maintained high dechlorination capability over 20–40 °C, pH 6–9, and initial TCE concentrations of 10–40 mg/L, although 20 °C, near-neutral pH, and lower pollutant loading were kinetically more favorable. Multiscale characterization by FT-IR, N₂ adsorption–desorption and BET, XRD, EDS, SEM, and XPS indicated that ZIF-8 mitigated particle aggregation and retained partial pore accessibility, whereas sulfidation was associated with a more persistent Fe(II)-rich surface state after reaction. Together, these coupled effects promoted local TCE enrichment and sustained interfacial transformation. This study provides mechanistic insight and practical guidance for the rational design of MOF-supported sulfidated iron materials for chlorinated-solvent-contaminated groundwater remediation. Full article

Here, we report a highly efficient and stable catalytic system based on monometallic oxides supported on HY zeolites for the catalytic oxidation of chlorobenzene (CB). Among the transition and rare-earth metal oxides screened, the 30Cu/HY catalyst demonstrates exceptional performance, achieving near 100% CB conversion at 300 °C (500 ppm CB, 10,000 h⁻¹) alongside outstanding 24 h continuous stability without deactivation. Quantitative Py-IR analysis reveals that this superior activity is fundamentally driven by extensive solid-state ion exchange, forming robust Lewis acid centers (Cu-Y structures) that synergize with zeolitic Brønsted acid sites to efficiently polarize and cleave C-Cl bonds. Through an integrated approach combining in situ DRIFTS, real-time mass spectrometry, TGA, and NLDFT pore size analysis, we elucidate that the exceptional deep-oxidation capability of Cu/HY continuously mineralizes carbonaceous intermediates. This property minimizes coke deposition (2.91 wt%) and preserves the hierarchical pore architecture, preventing the coverage of active sites and severe pore blockage by partially oxidized intermediates (such as phenolic, aldehydic, and quinonic species) and stable carbonate species responsible for the deactivation of other metal oxides. These insights provide a mechanistic framework for the rational design of robust, chlorine-resistant catalysts for the sustainable abatement of persistent organic pollutants. Full article

5-Fluorouracil (5-FU) is a cornerstone chemotherapeutic agent that is extensively utilized in the management of malignancies; however, its clinical utility is constrained by its narrow therapeutic index and dose-limiting toxicities. The study aimed to study the hepato-nephroprotective effects of epigallocatechin gallate (EGCG) and EGCG mediated selenium nanoparticles and their effect in mitigating the toxicity induced by 5-FU. EGCG-functionalized selenium nanoparticles (EGCG-SeNPs) were produced by mixing sodium selenite, with EGCG acting as both the reducing and stabilizing agent. Nanoparticles were characterized using UV-vis spectroscopy, FT-IR, dynamic light scattering, zeta potential analysis, and transmission electron microscopy. 35 adult rats were randomly assigned to control, 5-FU, 5-FU + Na₂SeO₃, 5-FU + EGCG, and 5-FU + EGCG-SeNPs groups. Hepatorenal toxicity was induced by intraperitoneal 5-FU administration during the final five days of the experiment. Serum biochemical markers, tissue oxidative stress, antioxidant enzyme, inflammatory cytokine levels, and apoptosis-related gene expression were evaluated. Immunohistochemical analysis of Nrf2 and Keap1 and histopathological examination of tissues were performed. 5-FU induced severe hepatorenal toxicity, evidenced by marked elevations in liver and kidney function biomarkers, excessive oxidative stress, inflammatory cytokine overproduction, NF-κB activation, and apoptotic signaling. Treatment with EGCG-SeNPs markedly ameliorated 5-FU-induced hepatic and renal dysfunction, restoring liver enzyme and kidney biomarker levels to near-normal levels more effectively than EGCG or sodium selenite alone. EGCG-SeNPs significantly suppressed lipid peroxidation, NGAL, and inflammatory mediators while robustly enhancing antioxidant defenses and activating the Nrf2/HO-1 pathway with concomitant Keap-1 downregulation, strongly inhibited NF-κB signaling, normalized cytokine balance, reduced poly (ADP-ribose) (PAR) activation, and attenuated apoptosis. EGCG–SeNPs confer superior protection against 5-FU–induced hepatorenal toxicity compared to EGCG or inorganic selenium alone. The potent protective effects of EGCG–SeNPs are mediated through coordinated antioxidant, anti-inflammatory, and anti-apoptotic mechanisms, primarily via activation of the Nrf2/HO-1 axis and suppression of NF-κB signaling. Full article

In this study, a low-cost AS7265x-based multispectral electronic tongue system was developed for estimating milk composition and adulteration indicators and supported with an explainable artificial intelligence (XAI) framework. Experimental analyses were conducted on 190 augmented commercial milk samples, where fat, protein, solids-not-fat (SNF), density, freezing point, and added water ratio were treated as target variables. Sensor data were modeled as RAW, DERIVED, and FUSION feature sets, and regression performance was compared using Random Forest, Gradient Boosting, AdaBoost, KNN, and XGBoost. Model validation was carried out with both five-fold cross-validation and Leave-One-Out (LOO) strategies to assess field-level generalizability. Results showed that a narrow-band, low-cost optical sensor platform can estimate not only fat and protein but also SNF, density, and freezing point with high accuracy. Within the XAI framework, permutation-based importance analysis and SHAP were used to identify critical spectral bands for each target parameter, enabling data-driven recommendations for band-oriented sensor design optimization. The study presents a scalable methodology that integrates low-cost sensor design, multi-parameter quality estimation, and explainable modeling beyond traditional fat–protein-focused approaches. Across all six targets, the XAI analysis consistently identified the near-infrared channel at 860 nm (asIR_3) as the most informative band, reflecting the combined effect of water absorption and Mie scattering by fat globules; the visible channel at 680 nm (asVIS_4) emerged as a secondary band, reflecting dissolved-matter scattering. These bands are therefore the natural starting point for cost-reduced versions of the sensor. Among the compared feature sets (RAW, DERIVED, FUSION), the 18-band RAW configuration provided the most balanced performance across all six targets. Full article

Ultrafast fiber lasers operating near 2 μm have emerged as a critical platform for advancing mid-infrared photonics due to their narrow pulse durations, high peak powers, and broad tunability. These sources exploit the rich energy-level structures of Tm³⁺ and Ho³⁺ doped fibers and reside within an atmospheric transmission window, enabling applications spanning nonlinear microscopy, precision micromachining, optical frequency metrology, biophotonics, and free-space optical communication. Recent progress in low-loss fiber fabrication, dispersion-engineered cavity design, and mode-locking technologies has significantly expanded the performance boundaries of 2 μm ultrafast fiber lasers. This review systematically examines the underlying pulse-formation mechanisms and categorizes state-of-the-art mode-locking approaches. Representative laser architectures are compared with respect to pulse duration, energy scalability, repetition-rate enhancement, spectral characteristics, and environmental stability. Key application pathways in high-resolution spectroscopy, biomedical diagnostics, and mid-IR supercontinuum generation are highlighted. Finally, the remaining challenges and prospective research directions are discussed to inform the development of next-generation ultrafast photonic sources in the 2 μm band. Full article