Search Results (4,476)

In recent years, the use of drones, also known as unmanned aerial vehicles (UAVs), has experienced a rapid increase due to their wide availability, compact size, low cost, and ease of operation. These devices have found applications in various areas, facilitating human work by covering large distances and operating in inaccessible or dangerous zones. However, their use has also been associated with malicious activities, such as property damage or threats to public security, which highlights the need to develop efficient and precise UAV detection systems. Although approaches based on neural networks have been proposed, they require large amounts of data for training and more computational resources for operation, which limits their applicability. In this study, we propose an alternative approach based on an analysis of audio features obtained through the fast Fourier transform (FFT) algorithm and classification using machine learning (ML) models. Our approach aims to detect the presence of drones using a minimal number of samples, meeting the requirements of efficiency, accuracy, robustness, low cost, and scalability necessary for a functional detection system. Full article

Bandlimited functions are functions whose Fourier transform is confined to a finite band of frequencies. We generalize this concept to representations other than the Fourier transform and show that this leads to a variety of inequalities in arbitrary representations. Several special cases are considered, including frequency, dilation, and the chirplet transform, among others. Examples are given to illustrate each result. We apply the results to quantum mechanical wave functions and probability distributions. For bounded momentum wave functions, we obtain explicit bounds on the position wave function and its derivatives, as well as bounds on the position probability distribution. We also consider the dual problem in which the position wave function is bounded, as in the case of a particle in a box with an arbitrary wave function, and obtain bounds on the corresponding momentum wave function and momentum probability distribution. The case of wave functions that are sums of a finite number of energy eigenfunctions is also developed, and bounds on the associated probability distributions are obtained. A number of specific examples are considered, including a truncated Gaussian wave function and a quantum bump wave function. Full article

Fourier Decomposition (FD) and Koopman Mode Decomposition (KMD) are important tools for time series data analysis, applied across a broad spectrum of applications. Both aim to decompose time series functions into superpositions of countably many wave functions, with strikingly similar mathematical foundations. These methodologies derive from the linear decomposition of functions within specific function spaces: FD uses a fixed basis of sine and cosine functions, while KMD employs eigenfunctions of the Koopman linear operator. A notable distinction lies in their scope: FD is confined to periodic functions, while KMD can decompose functions into exponentially amplifying or damping waveforms, making it potentially better suited for describing phenomena beyond FD’s capabilities. However, practical applications of KMD often show that despite an accurate approximation of training data, its prediction accuracy is limited. This paper clarifies that this issue is closely related to the number of wave components used in decomposition, referred to as the degree of a KMD. Existing methods use predetermined, arbitrary, or ad hoc values for this degree. We demonstrate that using a degree different from a uniquely determined value for the data allows infinite KMDs to accurately approximate training data, explaining why current methods, which select a single KMD from these candidates, struggle with prediction accuracy. Furthermore, we introduce mathematically supported algorithms to determine the correct degree. Simulations verify that our algorithms can identify the right degrees and generate KMDs that can make accurate predictions, even with noisy data. Full article

Gold nanorods (AuNRs) were synthesized and optimized with the aim of obtaining strongly hydrophilic nanomaterials, suitable as a drug delivery system (DDS) for copper-based drugs. After careful purification, AuNRs were characterized by ultraviolet–visible–near-infrared spectroscopy (UV–Vis–NIR), showing two typical localized surface plasmon resonance (LSPR) bands in the range 550–750 nm. Fourier Transform Infrared (FT-IR) and high-resolution X-ray photoelectron (HR-XPS) spectroscopies verified the surface functionalization. Transmission electron microscopy (TEM) showed AuNRs with regular shape and size, with an aspect ratio (AR) of 2.6. Dynamic Light Scattering (DLS) measurements confirmed the size and the stability in water for up to 3 months. The AuNRs were conjugated with copper(I) drugs, i.e., [Cu(PTA)₄]BF₄ (PTA = 1,3,5-triaza-7-phosphadamantane). The drug loading procedures and efficiency were optimized, and the best loading was η (%) = 50 ± 7%. The non-covalent interactions of the Cu(I) complex with the AuNRs were studied by means of UV–Vis–NIR, ζ-potential, HR-TEM, FT-IR, synchrotron radiation-induced X-ray photoelectron (SR-XPS), and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy measurements. The MTT assay performed on Vero E6 cells showed that AuNRs and AuNR-Cu(I) conjugates had no significant effect on cell viability, being biocompatible, causing a reduction in cell viability only after prolonged exposure. Full article

Synthetic azo dyes are widely used in the textile industry; however, their use often poses environmental challenges. Here, we characterized the compost bacterium Bacillus subtilis strain CKCC for the decolorization of various azo dyes, including Congo Red, Reactive Black 5, Reactive Green 19, Reactive Red 120, and Reactive Blue 4. The application of strain CKCC exhibited high decolorization efficiency by utilizing various extracellular enzymes, including azoreductase and ligninolytic enzymes such as laccase, lignin peroxidase, and manganese peroxidase, which are essential for the decolorization of azo dyes. Fourier transform infrared spectroscopy (FTIR) analysis revealed structural changes during decolorization, consistent with the degradation of key functional groups. This transformation was attributed to the cleavage of azo linkages by azoreductase, with ligninolytic enzymes functioning on phenolic and aromatic moieties. While FTIR confirmed these structural changes, our findings only provided insights at the functional-group level, and the presence or absence of specific decolorized metabolites, such as aromatic amines, requires additional analytical techniques. In this study, the phytotoxic metabolites positively affected the germination and growth of Vigna radiata, confirming that decolorization using strain CKCC significantly reduced the toxic properties of the metabolites produced during dye decolorization. Hence, our isolated strain CKCC offers a potentially effective and environmentally sustainable method for treating azo-dye effluent in the textile industry. Full article

In this preliminary study, chitosan-based molecularly imprinted polymers crosslinked with glutaraldehyde were synthesized and evaluated for the selective removal of m-cresol, a volatile phenol associated with the sensory defect known as smoke taint in wine. Three formulations of chitosan-based molecularly imprinted polymers (MIP-Gs) were synthesized using glutaraldehyde as a crosslinker and m-cresol as a template. Non-imprinted polymers (NIP-Gs) served as controls. The polymers were characterized by Fourier-transform infrared spectroscopy, thermogravimetric analysis, and scanning electron microscopy, which confirmed successful crosslinking and structural differences between MIPs and NIPs. Adsorption performance was evaluated using solid-phase extraction cartridges packed with the synthesized polymers, employing a Cabernet Sauvignon wine. The MIPs exhibited higher adsorption efficiency and selectivity toward m-cresol compared to NIPs, achieving removal rates of 15% to 40%, depending on polymer formulation and analyte concentration. Molecular dynamics simulations were used to investigate polymer–analyte interactions at the molecular level, providing mechanistic insight into the preferential binding of m-cresol within the imprinted cavities. Physicochemical analyses of red wine showed that m-cresol removal occurred with minimal impact on key phenolic parameters, supporting the functional selectivity of MIPs. These results demonstrate that chitosan-based MIPs constitute a promising class of materials for selective adsorption applications in complex liquid systems. Full article

This study investigates the synthesis, dual functional applications, and electrochemical performance of the amine-functionalized metal-organic framework (MOF), namely UiO-66-NH₂. The material was synthesized via the solvothermal method and characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and scanning and transmission electron microscopy (SEM/TEM). UiO-66-NH₂ was assessed as a catalyst for the reduction of nitroarenes, specifically 2-nitrophenol (2-NP) and 4-nitrophenol (4-NP), under both dark and photo-assisted (i.e., photocatalysis) conditions. Complete photoreduction of nitroarenes was achieved under photocatalysis, highlighting its photo-assisted catalytic efficacy. UiO-66-NH₂ before and after nitroarenes adsorption capacities were investigated, and subsequent electrochemical assessments confirmed its suitability as a supercapacitor electrode. Cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) analyses demonstrated that nitroarene adsorption and light irradiation markedly improved specific capacitance. 2-NP@UiO-66-NH₂ showed specific capacitance of 221 F/g at 1 A/g under UV radiation. UiO-66-NH₂ demonstrated remarkable cycling stability (100%) across 7000 cycles. Structural and property modifications of UiO-66-NH₂, adsorption of redox-active species, and photo-assisted mechanisms can significantly enhance the energy storage efficacy. The results illustrate the dual role of UiO-66-NH₂ as an effective photo-assisted catalyst and electroactive supercapacitor material, facilitating integrated environmental remediation and energy storage applications. Full article

This study investigated the chemical recycling of poly(ethylene terephthalate) (PET) fiber residues from two sources—high-molar mass mooring ropes and low-molar mass textile-grade fibers—to produce functional oligomers. Glycolysis was carried out using polyethylene glycol (PEG400) as the depolymerizing agent, and two catalysts were assessed, zinc acetate and lithium octoate, with the latter reported on for the first time in this application. Reactions were performed for 180 min under mechanical stirring, inert atmosphere, reflux, and controlled heating. The resulting oligomers were characterized by Fourier-transform infrared spectroscopy (FTIR), hydroxyl and acidity indices, and thermogravimetric analysis (TGA). Both PET feedstocks showed high reactivity toward glycolysis. Monitoring the reactions by acidity index indicated that conversion reached equilibrium at approximately 120 min. ATR-FTIR confirmed the formation of ester and hydroxyl groups, consistent with oligomer structures. Glycolysis of PET derived from mooring ropes produced oligoesters with hydroxyl values of 228 and 242 mgKOH/g for zinc acetate and lithium octoate, respectively, and molar masses of 1296 and 1338 g/mol for zinc acetate and lithium octoate, respectively. These values are suitable for subsequent syntheses such as polyester polyol production. Full article

In video scene graph prediction, the aim is to capture structured object interactions that occur over time in dynamic visual content. While recent spatiotemporal attention-based models have improved performance, they often suffer from high computational costs and limited structural consistency across long sequences. Therefore, we developed a Fourier transformer mixer network (FTM-Net), a modular, frequency-aware architecture that integrates spatial and temporal modeling via spectral operations. It incorporates a resolution-invariant Fourier Mixer for global spatial encoding and a Fast Fourier Transform (FFT)-Net-based temporal encoder that efficiently represents long-range dependencies with less complexity. To improve structural integrity, we introduce a spectral consistency loss function that synchronizes high-frequency relational patterns between frames. Experiments conducted utilizing the Action Genome dataset demonstrate that FTM-Net surpasses previous methodologies in terms of both Recall@K and mean Recall@K while markedly decreasing parameter count and inference duration, providing an efficient, interpretable, and generalizable approach for structured video comprehension. Full article

Blasting-induced vibrations from new tunnel construction pose a significant threat to the structural safety of existing tunnel linings due to dynamic stress concentration. To address this, this study establishes a transient-response analytical model for composite lining tunnels using wave function expansion and a combination of the Duhamel integral and Fourier transform methods. Through a case study of the Hongshan South Road Tunnel, the research systematically quantifies the influence of critical factors such as load rise time, lining thickness, and material stiffness. Numerical results reveal that under blasting P-wave action, the inner vault of the secondary lining exhibits the most significant dynamic stress concentration, identifying it as the primary vulnerable zone. Furthermore, peak dynamic stress and vibration velocity increase sharply as the load rise time decreases, indicating that short-duration, high-intensity impacts present the greatest hazard. To mitigate these effects, the study identifies several optimization strategies: increasing the thickness of the initial support and employing high-modulus materials effectively reduce stress peaks. Specifically, maintaining the elastic modulus ratio of the surrounding rock to the initial support at approximately 2.0 provides an optimal balance for enhancing blast resistance. The findings suggest that tunnel design should prioritize optimizing the stiffness of the initial support and utilizing grouting to reinforce the surrounding rock. This research provides a robust theoretical framework and specific parameter optimization directions for the seismic and blast-resistant design of composite lining tunnels. Full article

The present work investigates the effect of powdered lignocellulose from alfalfa straw obtained by a chemo-extrusion method, as well as its carboxymethylated derivative, on the physicomechanical properties and swelling behavior of vulcanizates based on nitrile butadiene rubber (NBR, BNKS-28 AMN grade). Carboxymethylation of lignocellulose was performed using microwave activation. The functional group composition of the modified lignocellulose was characterized by Fourier-transform infrared (FTIR) spectroscopy, which confirmed successful carboxymethylation and revealed a reduction in crystallinity. Thermogravimetric analysis (TGA) was used to determine the thermal stability of the swelling carboxymethylated fillers. The degree of crystallinity of the carboxymethylated swelling fillers was evaluated by X-ray diffraction (XRD). It was shown that the introduction of powdered lignocellulose and its carboxymethylated derivative into the rubber compounds lead to an increase in compound viscosity and prolong the optimum cure time, while having no effect on the scorch time, in a manner similar to that observed for the commercial product sodium carboxymethylcellulose (NaCMC). It has been shown that the introduction of powdered lignocellulose and its carboxymethylated derivative increases the tensile strength of the rubber and improves its resistance to the action of mineralized water compared with the samples containing NaCMC. It was also demonstrated that carboxymethylated lignocellulose exhibits enhanced sorption capacity comparable to that of NaCMC. Overall, carboxymethylation of lignocellulose derived from alfalfa straw significantly improves the stability and sorption characteristics of nitrile butadiene rubber composites. These findings indicate that carboxymethylated lignocellulose is a sustainable and effective alternative to industrial NaCMC for use as a functional filler in elastomeric materials. Full article

In the present study, potato starch (PS) was functionalized with theaflavin (TF). Potato starch aldehyde (DPS)–theaflavin (DPS-TF) conjugates were prepared by conjugating TF with DPS. The synthesized DPS-TF conjugates were characterized via UV–visible spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), proton nuclear magnetic resonance (¹H-NMR) and scanning electron microscopy (SEM) analysis and tested for antioxidant and antimicrobial activities. The UV–vis spectrum results demonstrated that DPS-TF conjugates exhibited the characteristic absorption peaks of theaflavin at 280 nm, which can be attributed to the benzotropolone structure present in theaflavin. The absorbance values of the peaks progressively intensified as the concentration of grafted theaflavins increased. FTIR confirmed the depletion of the aldehyde groups and the presence of TF-specific vibrations in the conjugates in DPS-TF. ¹H-NMR demonstrated that the conjugation occurred between the H-6, H-8, H-6′, and H-8′ positions of theaflavin and the aldehyde groups of starch aldehyde. XRD demonstrated that the DPS-TF conjugates were in the amorphous state. SEM observation demonstrated that DPS-TF exhibited a mixed morphology of flakes and lumps, which differed from that of native starch and starch aldehyde. The scavenging activity of DPS-TF against DPPH and ABTS radicals was significantly higher than that of DPS (p < 0.05), with the antioxidant activity increasing in line with the concentration of theaflavins. In comparison with PS and DPS, DPS-TF conjugates demonstrated superior antimicrobial activity against Escherichia coli and Staphylococcus aureus. Furthermore, an elevated grafting ratio corresponds to a heightened level of these functional properties. This study highlights the promise of the starch aldehyde–theaflavin conjugates for use as a viable antioxidant and antimicrobial agent for food applications. Full article

Cancer is one of the leading causes of mortality worldwide, with breast and colon cancers being among the most common neoplasms in men and women, respectively. Despite significant advancements in treatment, there is a pressing need to enhance specificity and reduce systemic side effects. Importantly, a distinctive feature of cancer cells is their acidic extracellular environment, which profoundly influences cancer progression. In this study, we evaluated the anticancer activity of a pH-sensitive nanocomposite based on silver nanoparticles and pegylated carboxymethyl chitosan (AgNPs-CMC-PEG) in breast cancer (MCF-7) and colon cancer (HCT 116) cell lines. To achieve this, we synthesized and characterized the nanocomposite using UV-Vis spectroscopy, Dynamic Light Scattering (DLS), Fourier-Transform Infrared Spectroscopy (FT-IR), and Scanning Electron Microscopy (STEM-in-SEM). Furthermore, we assessed cytotoxic effects, apoptosis, and reactive oxygen species (ROS) generation using MTT, DAPI, and H2DCFDA assays. Additionally, we analyzed the expression of DNA methyltransferases (DNMT3a) and histone acetyltransferases (MYST4, GCN5) at the mRNA level using RT-qPCR, along with the acetylation and methylation of H3K9ac and H3K9me2 through Western blot analysis. The synthesized nanocomposite demonstrated an average hydrodynamic diameter of approximately 175.4 nm. In contrast, STEM-in-SEM analyses revealed well-dispersed nanoparticles with an average core size of about 14 nm. Additionally, Fourier-transform infrared (FTIR) spectroscopy verified the successful surface functionalization of the nanocomposite with polyethylene glycol (PEG), indicating effective conjugation and structural stability. The nanocomposite exhibited a pH and concentration dependent cytotoxic effect, with enhanced activity observed at an acidic pH 6.5 and at concentrations of 150 µg/ml, 75 µg/ml, and 37.5 µg/ml for both cell lines. Notably, the nanocomposite preferentially induced apoptosis accompanied by ROS generation. Moreover, expression analysis revealed a decrease in H3K9me2 and H3K9ac in both cell lines, with a more pronounced effect in MCF-7 at an acidic pH. Furthermore, the expression of DNMT3a at the mRNA level significantly decreased, particularly at acidic pH. Regarding histone acetyltransferases, GCN5 expression decreased in the HCT 116 line, while MYST4 expression increased in the MCF-7 line. These findings demonstrate that the AgNPs-CMC-PEG nanocomposite has therapeutic potential as a pH-responsive nanocomposite, capable of inducing significant cytotoxic effects and altering epigenetic markers, particularly under the acidic conditions of the tumor microenvironment. Overall, this study highlights the advantages of utilizing pH-sensitive materials in cancer therapy, paving the way for more effective and targeted treatment strategies. Full article

Understanding how birds adjust their flight in response to biomechanical characteristics and environmental conditions can be useful for interpreting homing behavior. This study investigates homing pigeons’ (Columba livia) flight behavior using multi-sensor biologgers, integrating GPS, tri-axial accelerometer, pressure, and temperature sensors. Flight biomechanics were assessed by extracting: wingbeat frequency from the Short-Time Fourier Transform of the total acceleration signal and peak-to-peak acceleration from the dorso-ventral component. Landscape characteristics were provided by classifying land cover along the route using a geographic atlas and by computing flight altitude above ground level through the combination of pressure-derived altitude and a digital elevation model. The results reveal a progressive decrease in wingbeat frequency along the homing route, showing a linear relationship with traveled distance. To assess whether this pattern can be interpreted in terms of flight regulation, flight altitude was modeled as a function of biomechanical and environmental variables using a linear mixed-effect approach. The analysis indicates that flight altitude is significantly affected by wingbeat frequency as well as by temperature, ground speed, and land cover, with wingbeat frequency and temperature showing the strongest negative association. Full article

The rising volume of sludge production poses significant environmental threats. Sludge has a high moisture content (MC), which increases its disposal and transport expenses. On the other hand, sludge has low dewaterability due to its high concentration of soluble organic compounds. To reduce sludge production, understanding and improving preconditioning and mechanical dewatering are crucial for breakthroughs in advanced sludge dewatering. The sludge samples used in this analysis were obtained from the Sarabium municipal wastewater treatment plant, with a moisture content of 97% and a specific filtration resistance (SRF) of 9.15463 × 10¹⁵ m/kg. Sludge dewatering was enhanced by treating the samples chemically with ferric chloride, aluminum sulfate, Moringa olifera, and cationic polyacrylamide CPAM and physically with wood chips, slag, rice husk, and wheat straw. The experiments examined the sludge’s initial characterization (specific resistance to filtration (SRF) and time to filtrate (TTF)). To verify the structural characteristics (density), elemental composition, and the presence of various functional groups, a characterization investigation was conducted using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDS). The results showed that chemical conditioning with ferric chloride is better than aluminum sulfate and Moringa. Wood chips also provide better results for physical conditioning than rice husk, wheat straw, and slag. The reaction occurred at the carbonyl group, where FTIR showed more activated sites during SEM analysis, as evidenced by the FTIR results. Still, when CPAM was added to conditioned sludge, there was no difference in sludge dewatering performance, and the activated sites remained unchanged. Hence, this research found that mechanical sludge dewatering was improved by conditioning with ferric chloride (pH of 6 and dose of 0.12 g/g of dry solid) and wood chips (dose of 1.5 g/g of dry solid), which reduced sludge volume after dewatering by 82.5% under low pressure, which in turn minimizes transportation, energy, and handling costs. This study supports SDG 3 and SDG 6 by improving sludge dewatering efficiency and promoting sustainable wastewater management using natural wood chips. Full article