Search Results (19,460)

This paper develops a structured analytical framework and a robust numerical methodology for the spectral stability of time-varying bilateral quaternion differential equations of the form $\dot{q}=A\left(t\right)q+qB\left(t\right)$. By systematically extending classical real matrix theory to non-commutative dynamical systems via exact isometric real representations, this study utilizes the Kronecker product of real adjoint matrices to rigorously elucidate the underlying tensor structure of the bilateral evolution operator. This tensor-based reformulation proves that the Floquet multipliers of the bilaterally coupled system can be strictly decoupled into the product of the spectra corresponding to the left and right unilateral subsystems. Second, a “Scalar-Vector Stability Separation Principle” based on logarithmic norms is proposed, demonstrating that the transient energy evolution of the system is governed exclusively by the Hermitian real parts of the coefficient matrices, remaining entirely independent of the anti-Hermitian imaginary parts (rotation terms). Furthermore, for constant-coefficient and slowly varying systems, the Riesz projection from holomorphic functional calculus is introduced to establish algebraic criteria for exponential dichotomies, thereby revealing a cubic scaling law that relates the robustness threshold to the spectral gap (${\epsilon }_0\propto {\beta }^3$). Numerically, a Quaternion Chebyshev Spectral Collocation Method (Q-CSCM) is embedded within this exact vectorization framework to ensure that the algebraic symmetries of the bilateral system are strictly preserved through the isomorphic mapping. By explicitly constructing the fully discrete Kronecker product matrix via the exact real vectorization isomorphism, discrete energy estimates are utilized to rigorously prove that the numerical scheme successfully inherits the intrinsic spectral accuracy of the Chebyshev approximation. Comprehensive numerical experiments demonstrate that, within the low-dimensional regime, this methodology exhibits substantial temporal approximation efficiency advantages and superior numerical robustness compared to an alternative Legendre spectral baseline, as well as traditional explicit and state-of-the-art implicit symplectic Runge–Kutta methods, particularly when solving stiff and critically stable problems such as nonlinear Riccati oscillators. Full article

Highly polar M-mol-X (M = alkali metal, mol = molecule, X = halogen) insertion complexes have been predicted to offer potential practical applications, including molecular interactions with light, ion-pair induced isomerization, etc. In the present work, the insertion complexes of the seven-membered, fused bicyclic norcaradiene and its monocyclic isomer trapped in Li-I, Na-I, and K-I counterion pairs were investigated using ab initio methods. The structures, stability, polarities, and simulated infrared spectra are analyzed and the effects of the insertion on the norcaradiene to cycloheptatriene isomerization process are examined. Furthermore, an uncommon bond between iodine and a fully substituted carbon atom is reported upon and hypothesized to be catalyzed by the presence of the cation in the insertion complexes. Full article

This study reports the synthesis, spectroscopic characterization, and biological evaluation of a novel moxifloxacin hydrazide derivative (MOX-H) and its metal complexes with Co(II), Ni(II), Cu(II), VO(IV), and Gd(III). The ligand was synthesized by hydrazinolysis of moxifloxacin hydrochloride, and the resulting hydrazide was subsequently complexed with the respective metal salts. The interaction between MOX-H and the metal ions yielded the corresponding complexes, formulated as [Co(H₂O)Cl(MOX-H)₂]Cl·2.5H₂O, [Ni(H₂O)Cl(MOX-H)₂]Cl.4.5H₂O, [VO(MOX-H)₂]SO₄.3.5H₂O, [Gd (H₂O)(MOX-H)₂(NO₃)₂]NO₃.2H₂O, and [Cu(MOX-H)₂(H₂O)Cl]Cl·xH₂O (where x = 2, 2.5, 0.5, for products synthesized via template, microwave-assisted, and hydrothermal methods, respectively). The synthesized analogues were characterized by elemental analysis (CHN), FT-IR, UV-visible, and ¹H NMR spectroscopy, and mass spectrometry, as well as thermogravimetric (TG/DTG) and magnetic measurements. FT-IR spectra confirmed coordination through the hydrazide carbonyl and amine groups, while UV–visible and magnetic data indicated predominantly octahedral geometries. The thermal behavior exhibited multistep decomposition with activation parameters supporting exothermic processes. When compared to the free ligand, the metal complexes showed increased antimicrobial activity against both Gram-positive and Gram-negative bacteria and fungus species, particularly for the Co(II) and Cu(II) complexes, which showed the largest inhibition zones. The Cu(II)–MOX-H complex exhibited the lowest MIC values (4.88–9.76 µg/mL) among all tested compounds, confirming its outstanding antibacterial potency and high sensitivity compared to the free ligand and standard drug. Cytotoxicity assays demonstrated selective anticancer activity, with the Cu(II)–MOX-H complex showing the highest potency (IC₅₀ ≈ 2.95 µM against MCF-7 and IC₅₀ ≈ 0.98 µM against HepG-2), while maintaining minimal toxicity toward normal cells. These findings were corroborated by molecular docking investigations, which showed that the MOX-H complexes had substantial binding affinities (−9 to −10 kcal/mol) toward DNA topoisomerase II, consistent with their observed biological effects. Full article

Background: Among atmospheric-pressure mass spectrometry imaging (MSI) methods, desorption electrospray ionization (DESI) and desorption electro-flow focusing ionization (DEFFI) represent cost-effective, high-throughput approaches that utilize pneumatically assisted charged solvent droplets to directly desorb and ionize analytes from sample surfaces. Methods and Results: In this study, we systematically compare the performance of conventional DESI-MSI with previously reported DEFFI-MSI configurations on the Orbitrap mass spectrometer platform, focusing on evaluating the lateral spatial resolution, signal intensity, and imaging speed. By scanning a standard patterned sample which has sharp edges, DESI-MSI achieved a spatial resolution of 70 µm, while DEFFI-MSI achieved 15 µm (approximately 4.7-fold improvement). For the representative ion at m/z 782.5621, DEFFI-MSI demonstrated significantly higher signal intensity across solvent flow rates ranging from 0.5 to 1.5 µL min⁻¹. The enhanced ion yield directly translates to improved Orbitrap-based MSI efficiency: in both negative- and positive-ion modes, DEFFI generates rich full-scan mass spectra within the maximum 10 ms ion injection time, whereas DESI produces weaker mass spectra under the same conditions. Conclusions: Taken together, these results quantify the key performance metrics between DESI-MSI and DEFFI-MSI, demonstrating that DEFFI is the preferred method on Orbitrap-based MSI, because it simultaneously enhances spatial resolution, signal intensity, and imaging speed. Full article

Infrared (IR) spectroscopy is a powerful tool for characterizing molecular structures and chemical groups, offering advantages such as low cost, rapid analysis, and non-destructive testing. When analyzing heterogeneous objects, spectra are typically measured from different regions to capture the local variations, presenting a multi-instance learning (MIL) problem. However, existing methods primarily rely on multi-instance assumptions or explicit bag representations, often failing to fully capture the intrinsic information from implicit representations. We introduce a bag dissimilarity regularized MIL framework for analyzing IR spectra of heterogeneous objects, which integrates both explicit and implicit representations to effectively learn the MIL bags. Specifically, a bag dissimilarity regularization term is utilized to extract implicit representations, which subsequently guide the classifier based on explicit representations to enhance generalization performance. The proposed method was validated on two heterogeneous detection tasks: polydimethylsiloxane (PDMS) block assessment and polyethylene terephthalate (PET) fiber inspection. Experimental results demonstrate that our approach significantly outperforms existing methods on both datasets with a considerable margin. Full article

We report the enhancement of organic photodetector (OPD) performance through the incorporation of CsPbBr₃ perovskite nanocrystals (PNCs) into P3HT:PCBM devices. The optimized device (HPD_01) exhibits a maximum responsivity of 0.083 A/W and a specific detectivity of ~4.7·10¹⁰ Jones, and a minimum NEP of 5.2·10⁻¹² W·Hz^−1/2 at the self-powered operating point (V ≈ 0 V), outperforming the nanoparticle-free reference. Frequency- and distance-dependent measurements under visible light communication conditions demonstrate that the optimized device maintains strong signal detection up to 1 MHz and at distances exceeding 15 cm. Notably, the external quantum efficiency spectra reveal an additional contribution in the 450–575 nm range, which is absent in the reference device. This enhancement is consistent with a radiative absorption–reemission energy-transfer mechanism, supported by quantitative spectral overlap analysis showing that 99.5% of the PNC photoluminescence falls within the 450–575 nm EQE enhancement window and that the maximum differential EQE gain occurs at 519 nm—only 2 nm from the PNC emission peak. Our results suggest that controlled PNC incorporation enables efficient optical energy coupling, leading to high-sensitivity, fast-response OPDs suitable for optical communication applications. Full article

The widespread utilization of synthetic dyes within the textile industry, driven by their chemical recalcitrance and diverse chromatic spectra, constitutes a significant global environmental challenge. Improper discharge of these highly stable effluents into natural water bodies leads to severe ecological imbalances, affecting aquatic life and soil integrity while posing indirect risks to human health due to their mutagenic potential. Conventional physicochemical treatment methods are often hindered by prohibitive operational costs and the frequent generation of hazardous secondary pollutants. Consequently, there is an urgent demand for sustainable biotechnological alternatives to mitigate these industrial impacts. Bioremediation, specifically using white-rot fungi, represents a robust and eco-friendly strategy for the degradation of complex aromatic structures. Species such as Trametes versicolor, Pleurotus ostreatus, and Phanerochaete chrysosporium utilize a specialized extracellular enzymatic complex to mineralize toxic compounds effectively. Here we review the ligninolytic capacity of white-rot fungi and their specialized enzymatic systems for environmental sustainability. The primary points are: (i) the biochemical mechanisms of the ligninolytic system of laccases and peroxidases during dye degradation; (ii) the influence of operational parameters such as pH, temperature, and nutrient availability on fungal metabolic efficiency; (iii) the diverse environmental applications of these microorganisms in treating real textile effluents; (iv) the current biotechnological challenges, including maintaining enzymatic stability in non-sterile industrial environments; and (v) the future perspectives for scaling up fungal treatment systems from laboratory research to large-scale industrial implementation. Full article

We present a temperature-dependent photoluminescence (PL) study of solution-grown CsPbBr₃ bulk crystal and thin film, using one-photon and two-photon excitations. Twin planes are observed in X-ray diffraction spectra in crystal. In analyzing PL peak position and spectral widths as function of temperature, we find that the electron–phonon interaction is generally stronger in CsPbBr₃ crystals than in films. Moreover, with one photon excitation, emissions from excitons and trapped excitons are observed in CsPbBr₃ crystal. Under two-photon excitation, only the emissions from trapped excitons are observed in bulk crystal. Our work demonstrates that two-photon excitation PL is more sensitive to the trapped excitons inside CsPbBr₃, implicating an optical method to probe the inside quality of the crystal. Full article

The detection of plastic explosives in vapor form is extremely challenging due to the very low volatility of their primary components, such as RDX and PETN. To overcome this limitation, volatile chemical markers like 2,3-dimethyl-2,3-dinitrobutane (DMNB) are added to explosive formulations to enable indirect vapor detection. This study presents a rapid method for detecting and quantifying DMNB vapors using a handheld ion mobility spectrometer (IMS) operating near ambient temperature, ammonia-doped and equipped with a non-radioactive corona discharge ionization source. The instrument, model LCD-3.2E (Smiths Detection Ltd.), is based on a twin drift–cell time-of-flight configuration and simultaneously records ion mobility spectra in both positive and negative modes. DMNB generated distinct product ion peaks in both modes, with reduced mobility values (K₀) of 1.42 cm²V⁻¹s⁻¹ (positive) and 1.37 cm²V⁻¹s⁻¹ (negative). The method demonstrated high sensitivity, with limits of detection calculated at 1.4 ppb_v (10.2 × 10⁻³ mg m⁻³) in positive mode and 3.1 ppb_v (22.7 × 10⁻³ mg m⁻³) in negative mode. The IMS system provided rapid responses within seconds and covered a quantifiable concentration range of 5–3000 ppb_v, with saturation estimated to appear above approximately 5 ppm_v (36.6 mg m⁻³). The simultaneous dual-polarity response of the DT IMS enhances both the selectivity and reliability of identification. These findings confirm the capability of portable IMSs for fast trace vapor detection in DMNB, supporting its application in field-based screening scenarios such as luggage inspection or container interrogation, where indirect detection of plastic explosives is required. Full article

Under severe ice and snow weather, ice-covered pantograph–catenary arcs affect the safe operation of high-speed trains. This study investigates the impact of ice-covered arc electrical characteristics, plasma parameters, and material ablation mechanisms. By constructing a comprehensive pantograph–catenary icing experimental platform, arc voltage, current signals, high-speed dynamic images, and emission spectra were synchronously collected under different icing thicknesses ranging from 0 to 15 mm. Research indicates that ice coverture causes frequent “extinction–reignition” phenomena during the arc initiation stage due to the latent heat absorbed by melting ice, significantly reducing the initial stability of arc combustion. Spectral analysis confirms that the arc excitation temperature and energy density are positively correlated with the concentration of hydrogen ions produced by water vapor ionization, reaching a peak under the 5 mm icing condition. Experimental results show that the average energy density of ice-covered arcs is approximately double that of the non-iced condition, causing the ablation pits on the carbon strip to exhibit characteristics of greater depth and wider copper deposition zones. This study reveals the unique mechanisms and damage characteristics of icing pantograph–catenary arcs, providing an important basis for the safe design and maintenance of pantograph–catenary systems in high-cold railway environments. Full article

Reliable traffic load characterization remains a critical challenge in many African countries due to the lack of continuous field measurements. This study developed an integrated dynamic traffic monitoring and weigh-in-motion system on representative highways in Kenya to obtain long-term, multi-source traffic data. Traffic operations were quantified across hourly, weekly, and monthly scales, including flow variability, vehicle class composition, axle loads, overload behavior, and speed distributions. Results indicate that the spatiotemporal characteristics of traffic volume show pronounced short-term fluctuations but strong long-term stability. Despite their lower proportion, multi-axle heavy trucks dominate structural loading, with overload ratios exceeding 80% and gross weights approaching 100 t. Over 60% of vehicles operate at medium-to-low speeds (20–60 km/h), extending load duration and increasing pavement damage potential. These combined effects indicate that average indicators alone underestimate true loading demand. The proposed framework provides field-based traffic load spectra and a transferable methodology for traffic monitoring and pavement design optimization across developing regions in Africa. Full article

Unmanned aerial vehicles (UAVs) are an alternative to traditional pesticide applications in orchards. Particularly, drones are an example of UAVs that have increased in popularity in recent years; however, relatively few studies have evaluated how spraying operation modes interact with other drone parameters within a single experimental framework. This study evaluated the effects of operation mode, application volume, flight height, and droplet size on spray coverage, droplet density, droplet spectra, and droplet size uniformity using the spraying drone DJI Agras T40 under a simulated canopy structure. A four-factorial experimental design was used; treatments included three operation modes (i.e., standard mode, fruit-tree mode, and spinning mode), two application volumes (i.e., 37.4 L/ha and 74.8 L/ha), two flight heights (i.e., 3 m and 5 m), and two droplet sizes (i.e., 150 μm and 300 μm). Operation mode was among the most influential factors affecting spray deposition quality. The spinning mode achieved the highest overall spray coverage (20.81%) and droplet density (172.44 drops/cm²), while the standard mode provided the most uniform spatial distribution. Results from the interaction analyses indicated that the parameter combination that produced the highest spray coverage within the tested ranges was an application volume of 74.8 L/ha, a flight height of 3 m, and a droplet size of 150 μm in the standard mode. For the fruit-tree mode, the highest spray coverage was observed at an application volume of 74.8 L/ha, a flight height of 5 m, and a droplet size of 300 μm. For the spinning mode, the combination associated with the highest spray coverage was 74.8 L/ha, 3 m, and 300 μm. In conclusion, the results provide data-driven guidance on how drone operational parameters influence spray deposition and can support future validation under commercial orchard conditions. Full article

Two Zn(II) coordination compounds based on glaucine-derived Schiff bases were synthesized and investigated as potential materials for dye-sensitized solar cells (DSSCs). The structures of all compounds were established by X-ray diffraction analysis and quantum chemical modeling (DFT/TD-DFT). Their photophysical properties (absorption and luminescence spectra in solution and the solid state), electrochemical characteristics, and photovoltaic parameters in DSSC devices were studied. The highest power conversion efficiency (PCE ~5.18%) was demonstrated by the free ligands, which is attributed to their favorable absorption spectrum and optimal alignment of energy levels relative to the conduction band of TiO₂ and the redox couple of the electrolyte. The Zn(II) coordination compounds exhibited significantly lower efficiency (~2.1%). Impedance spectroscopy results indicated more efficient charge transfer at the TiO₂/dye/electrolyte interface for the organic derivatives. Full article

Diseases like downy mildew (DM) and powdery mildew (PM) are characterized by whitish symptoms on leaves of many plant species. Hyperspectral imaging (HSI) has been successfully used for the detection and identification of various diseases associated with different symptoms. Proximal HSI (400–1000 nm) was tested under controlled conditions for its potential to differentiate among whitish disease symptoms on leaves of apple and grapevine due to DM, PM, and a non-melanized mutant of apple scab at the leaf and tissue (microscopic) level. Spectral traits were analyzed by using difference spectra and spectral ratios, spectral vegetation indices like NDVI, and average brightness and half NIR increase introduced here and were confirmed by supervised spectral angle mapper classification. Although similar, spectral signatures of whitish symptoms were significantly different and could be used for spectral separation of diseases; differences were greater on the tissue level than on the leaf level. However, disease detection and differentiation were affected by spectral differences between plant species, leaf sides, the variability of symptoms in space and time, and the integrity of superficial pathogen structures. In the case of similar disease symptoms, additional spectral information on the effects of pathogens on plant metabolism, e.g., leaf water patterns, supports spectral differentiation of leaf diseases. Full article

We present an innovative, cost-effective framework integrating laboratory Hyperspectral Imaging (HSI) of the Bechar 010 Lunar meteorite with ground-based lunar HSI and supervised Machine Learning (ML) to generate high-fidelity mineralogical maps. A 3 mm thin section of Bechar 010 was imaged under a microscope with a 30 mm focal length lens at 150 mm working distance, using 6x binning to increase the signal-to-noise ratio, producing a data cube (X × Y × $\lambda$ = $791\times 1024\times 224$, $0.24$ mm × $0.2$ mm resolution) across 400 nm to 1000 nm (224 bands, $2.7$ nm spectral sampling, $5.5$ nm full width at half maximum spectral resolution) using a Specim FX10 camera. Ground-based lunar HSI was captured with a Celestron 8SE telescope (3 km/pixel), yielded a data cube ($371\times 1024\times 224$). Solar calibration was performed using a Spectralon reference (99% reflectance < 2% error) ensured accurate reflectance spectra. A Support Vector Machine (SVM) with a radial basis function kernel, trained on expert-labeled spectra, achieved 93.7% classification accuracy (5-fold cross-validation) for olivine (92% precision, 90% recall) and pyroxene (88% precision, 86% recall) in Bechar 010. LIME analysis identified key wavelengths (e.g., 485 nm, 22.4% for M3; 715 nm, 20.6% for M6) across 10 pre-selected regions (M1 to M10), indicating olivine-rich (Highland-like) and pyroxene-rich (Mare-like) compositions. SAM analysis revealed angles from $0.26$ rad to $0.66$ rad, linking M3 and M9 to Highlands and M6 and M10 to Mares. K-means clustering of Lunar data identified 10 mineralogical clusters (88% accuracy), validated against Chandrayaan-1 Moon mineralogy Mapper (${\mathrm{M}}^3$) data (140 m/pixel, 10 nm spectral resolution). A novel push-broom HSI approach with a telescope achieves 0.8 arcsec resolution for lunar spectroscopy, inspiring full-sky multi-object spectral mapping. Full article