Search Results (19,195)

Soil analysis is fundamental to sustainable agriculture; however, traditional laboratory methods are time-consuming, expensive, and environmentally hazardous. Spectroscopy techniques, particularly Near-Infrared (NIR), have gained considerable attention because they require minimal sample preparation, no chemicals, and predict multiple soil properties with a single scan. However, selecting appropriate equipment remains critical, as previous studies have reported inconsistent performance between conventional Near-Infrared (NIR) spectroscopy and advanced Fourier-Transform Near-Infrared (FT-NIR) spectroscopy. Therefore, this study aimed to compare the predictive performance of conventional NIR and advanced FT-NIR spectroscopy for sixteen soil properties. Soil samples (n = 567) were collected from different land-use types across South Korea at a depth of 0–20 cm and analyzed using laboratory methods and spectroscopy techniques. Five models, including partial least squares regression (PLSR), Cubist, support vector machine (SVM), random forest (RF), and memory-based learning (MBL), were evaluated using 15-fold cross-validation to assess prediction accuracy. Overall, conventional NIR spectroscopy yielded consistently higher accuracy for all soil properties than FT-NIR. Strong predictive accuracy was achieved for EC (R² = 0.84), OM (R² = 0.84), avl. P (R² = 0.77), TN (R² = 0.84), and CEC (R² = 0.76). In contrast, FT-NIR provided good prediction accuracy only for Ex. K (R² = 0.72) and TN (R² = 0.84). The average performance of NIR (R² = 0.67) outperformed FT-NIR spectroscopy (R² = 0.63) across all soil properties. These findings demonstrate that, despite their lower spectral resolution, NIR spectra provide robust predictive capability across a wide range of soil properties, which can significantly reduce the investment cost of advanced equipment such as FT-NIR for routine soil analysis. Full article

The complex environment of metal mines causes significant noise interference in microseismic signals. This leads to low accuracy and high false alarm rates when using the conventional Short-Term Average/Long-Term Average (STA/LTA) method for first-arrival picking. To address these issues, this paper proposes an improved approach that combines Variational Mode Decomposition (VMD) with STA/LTA(V-STA/LTA). The proposed method selects effective mode components through multimodal decomposition. Subsequently, an energy-weighted fusion is achieved based on energy distribution characteristics to improve the accuracy of arrival time-picking. First, the microseismic signal is decomposed by VMD. The center frequencies of the Intrinsic Mode Functions (IMFs) are then calculated through Fast Fourier Transform (FFT). This helps identify and retain the effective mode components, reducing noise interference. Next, the STA/LTA method is applied to each selected mode component for first-arrival picking. Finally, the results from the different components are fused based on their energy weights for improving picking precision. In low signal-to-noise ratio (SNR) conditions, the effectiveness of the V-STA/LTA method was verified through simulation experiments and field data tests. In theoretical simulations, according to test results from multiple sets of different signal-to-noise ratios, the root mean square error (RMSE) (0.0005) and mean absolute error (MAE) (0.00055) of V-STA/LTA are significantly lower than those of STA/LTA and AIC. In actual data, the average accuracy (99.77%) is nearly 1 percentage point higher than that of the traditional STA/LTA (98.93%), improving the accuracy of microseismic signal arrival time-picking. Full article

Metallic implants used in orthopedics, such as titanium alloys, possess excellent mechanical strength but suffer from corrosion and poor bio-integration, often necessitating revision surgeries. Bioactive coatings, particularly hydroxyapatite, can enhance implant osteoconductivity, but high-purity synthetic hydroxyapatite is costly. This study investigates the development and characterization of a low-cost, biocompatible coating using hydroxyapatite derived from an unconventional natural source dromedary bone applied onto a titanium substrate via plasma spraying. Hydroxyapatite powder was synthesized from dromedary femurs through a thermal treatment process at 1000 °C. The resulting powder was then deposited onto a sandblasted titanium dioxide substrate using an atmospheric plasma spray technique. The physicochemical, structural, and morphological properties of both the source powder and the final coating were comprehensively analyzed using Scanning Electron Microscopy, Energy Dispersive X-ray Spectroscopy, X-ray Diffraction, and Fourier-Transform Infrared Spectroscopy. Characterization of the powder confirmed the successful synthesis of pure, crystalline hydroxyapatite, with Fourier-Transform Infrared Spectroscopy analysis verifying the complete removal of organic matter. The plasma-sprayed coating exhibited good adhesion and a homogenous, lamellar microstructure typical of thermal spray processes, with an average thickness of approximately 95 μm. X-ray Diffraction analysis of the coating revealed that while hydroxyapatite remained the primary phase, partial decomposition occurred during spraying, leading to the formation of secondary phases, including tricalcium phosphate and calcium oxide. Scanning Electron Microscopy imaging showed a porous surface composed of fully and partially melted particles, a feature potentially beneficial for bone integration. The findings demonstrate that dromedary bone is a viable and low-cost precursor for producing bioactive hydroxyapatite coatings for orthopedic implants. The plasma spray method successfully creates a well-adhered, porous coating, though process-induced phase changes must be considered for biomedical applications. Full article

Goat milk can be a vehicle for beneficial microorganisms, such as probiotic lactic acid bacteria (LAB). During lactic fermentation, the hydrolysis of milk proteins can improve their nutritional properties and sensory attributes and even have beneficial health effects. The objective of this study was to evaluate the caseinolytic activity of LAB strains with probiotic potential and to monitor the changes induced by fermentation and during storage in milk components using Fourier transform infrared (FTIR) spectroscopy. First, the proteolytic activity of 36 LAB strains isolated from dairy products was qualitatively assessed. Then, 17 strains with probiotic potential and moderate to high proteolytic activity were selected for further analysis. Casein proteolysis was found to be strain-dependent, with a decrease in total protein concentration ranging from 28% to 87% and an increase in amino acids ranging from 29% to 88%. Furthermore, a notable difference was observed in the amide bands in the FTIR spectra between the beginning and end of incubation, showing a decrease in the intensities of the bands attributed to proteins. In fermented goat milk, LAB growth resulted in a final count between 0.62 and 2.6 log CFU/mL, a 0.29 to 2.0 drop in pH, and lactic acid production between 0.20 and 1 g/L. FTIR spectra revealed time-dependent modifications in amide I and II bands accompanied by a marked reduction in carbohydrate content and an increase in lactic acid signal. After 21 days of storage, the viability of the strains, pH, and lactic acid in the fermented milks were not substantially modified. These results highlight the potential of lactic fermentation with strains selected for their probiotic potential as an approach to producing value-added goat milk products, as well as the usefulness of FTIR spectroscopy for characterizing complex systems such as goat milk. Full article

This study evaluated the efficacy of an environmentally friendly degreasing agent formulated from orange peel extract as both a cleaning agent and corrosion inhibitor for surgical instruments manufactured from 316LVM stainless steel. The extract was obtained via microwave-assisted hydrodistillation and subsequently blended with biodegradable surfactants. Its performance was compared against a benchmark commercial cleaner (West Oxyclean^®) through Tafel polarization, Electrochemical Impedance Spectroscopy (EIS), Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and X-Ray Diffraction (XRD). FTIR analysis confirmed the presence of terpenic compounds, predominantly limonene, alongside ethers, alcohols, and unsaturated structure characteristics of citrus essential oils. Polarization and EIS results showed that the formulation containing 0.12% extract exhibited the highest charge-transfer resistance and the lowest corrosion current density (0.093 μA/cm²), achieving an inhibition efficiency of 81.29%, whereas the 0.08% formulation showed greater corrosive response than the commercial cleaner. SEM imaging demonstrated a progressive decline in both the severity and density of localized corrosion attacks with increasing extract concentration, while XRD diffractograms indicated a marked reduction in corrosion-product formation—completely absent at the optimal concentration. These findings demonstrate that orange peel extract functions as an effective and environmentally sustainable corrosion inhibitor, capable of preserving the structural and surface integrity of surgical-grade steel. Its technical performance, combined with its biodegradable profile, positions it as a promising alternative to conventional industrial cleaners within medical and hospital applications. Full article

La-doped ZnO nanoclusters confined within mesoporous SBA-15 were synthesized using an impregnation–calcination method and evaluated for their visible-light-driven photocatalytic degradation of Rhodamine B (RhB). Small-angle X-ray diffraction (XRD) and transmission electron microscopy (TEM) confirmed the preservation of the 2D hexagonal mesostructure of SBA-15 post-loading. In contrast, wide-angle XRD and Fourier-transform infrared spectroscopy (FT-IR) analyses revealed that the incorporated ZnO existed predominantly as highly dispersed amorphous or ultrafine clusters within the mesopores. N₂ adsorption–desorption measurements exhibited Type IV isotherms with H1 hysteresis loops. Compared to pristine SBA-15, the specific surface area and pore volume of the composites decreased from 729.35 m² g⁻¹ to 521.32 m² g⁻¹ and from 1.09 cm³ g⁻¹ to 0.85 cm³ g⁻¹, respectively, accompanied by an apparent increase in the average pore diameter from 5.99 nm to 6.55 nm, attributed to non-uniform pore occupation. Under visible-light irradiation, the photocatalytic performance was highly dependent on the La doping level. Notably, the 5% La-ZnO/SBA-15 sample exhibited superior activity, achieving over 99% RhB removal within 40 min and demonstrating the highest apparent rate constant (k = 0.1152 min⁻¹), surpassing both undoped ZnO/SBA-15 (k = 0.0467 min⁻¹) and other doping levels. Reusability tests over four consecutive cycles showed a consistent degradation efficiency exceeding 93%, with only a ~7 percentage-point decline, indicating excellent structural stability and recyclability. Radical scavenging experiments identified h⁺, ·OH, and ·O₂⁻ as the primary reactive species. Furthermore, photoluminescence (PL) quenching observed at the optimal 5% La doping level suggested suppressed radiative recombination and enhanced charge carrier separation. Collectively, these results underscore the synergistic effect of La doping and mesoporous confinement in achieving fast, efficient, and recyclable photocatalytic degradation of organic pollutants. Full article

The integration of Reverse Osmosis (RO) desalination with Renewable Energy (RE) sources offers a sustainable approach to freshwater production, particularly in remote and off-grid regions. However, the variable and intermittent output of RE power can cause operational instability that affects membrane performance and system reliability. This study experimentally evaluated a flat sheet seawater RO membrane under variable conditions emulating a Photovoltaic (PV)-powered system over three days. Three scenarios were examined: (i) steady full-load operation representing PV with battery storage, (ii) variable operation representing sunny-day PV output, and (iii) highly variable operation representing cloudy-day PV output. A Variable Frequency Drive (VFD) regulated by an Arduino microcontroller adjusted high-pressure pump operation in real time to replicate power fluctuations without energy storage. Each scenario operated for eight hours per day and was tested with and without end-of-day rinsing. Under the highly variable cloudy-day scenario without rinsing, water permeability decreased by 37%, salt rejection decreased by 18%, and membrane resistance increased by 37%, indicating compaction and fouling effects. Fourier Transform Infrared Spectroscopy with Attenuated Total Reflectance (FTIR-ATR) confirmed structural changes in membranes exposed to fluctuating conditions. These results highlight the need for improved operational strategies to protect membrane longevity in RE-powered desalination systems. Full article

The influence of lactic acid bacteria (LAB) strains of various species isolated from Chinese traditional sourdough on the properties of rice sourdough and the textural and flavor qualities of steamed rice bread (SRB) was investigated. Lactiplantibacillus plantarum-fermented rice sourdough had a higher total titratable acidity (13.10 mL) than the other groups. Strains Lacticaseibacillus paracasei PC1 (LPC), Lactobacillus helveticus H1 (LH), Lactobacillus crustorum C1 (LC), Lactobacillus paralimentarius PA1 (LPA), and Lactiplantibacillus plantarum P1 (LP) showed marked protein hydrolysis during rice sourdough fermentation and increased free amino acid levels in rice sourdoughs relative to the control. The Fourier Transform Infrared Spectroscopy results indicated that LAB fermentation could promote the strengthening of inter-intramolecular hydrogen bonds and cause modifications in protein structures; however, these effects varied among the different strains. The LC and LPC strains had the most significant effect on improving the specific volume and textural properties of SRBs. Gas chromatography-mass spectrometry (GC-MS) and GC-ion mobility spectrometry (IMS) identified 33 and 35 volatile compounds, respectively, in the LAB-fermented SRBs, and differentiation was observed in the volatile profiles of SRBs made using different LAB strains. The differential impacts of LAB strains during rice sourdough fermentation can assist in the selection of candidate microorganisms for the production of high-quality gluten-free rice products. Full article

This study presents an energy-efficient, room-temperature synthesis and characterization of methacrylated pullulan (Pull-MA) hydrogel developed for controlled nutrient delivery in agricultural applications. Fourier Transform Infrared Spectroscopy (FTIR) and Differential Scanning Calorimetry (DSC) analyses confirmed the successful functionalization of pullulan with methacrylate groups, accompanied by a decrease in thermal transition temperatures, indicative of increased polymer chain mobility. The synthesized Pull-MA hydrogel exhibited a high swelling capacity, reaching an equilibrium swelling ratio of 1068% within 5 h, demonstrating its suitability as a carrier matrix. The room-temperature synthesis approach enabled the in situ incorporation of microbial inoculant into the hydrogel network, preserving microbial viability and activity. SEM analysis performed under the different magnifications (1000, 2500, 5000, 10,000, 25,000×) has confirmed brittle nature of xerogels and increasing in structural irregularities with increasing in cultivation broth content.The biological performance of the fertilizer-loaded hydrogels was evaluated through seed germination assays using maize and pepper as model crops. The optimized formulation, T2 (Pull-MA: cultivation broth 1:5 w/w), significantly improved germination efficiency, as evidenced by increased relative seed germination (RSG), root growth rate (RRG), and germination index (GI) compared to both the control and the low-fertilizer formulation (T1, 1:2.5 w/w). These findings highlight the potential of Pull-MA hydrogels as bioactive seed-coating materials that enhance early seedling development through controlled nutrient release. The results lay a solid foundation for further optimization and future application of this system under real field conditions. Full article

Background: Advancements in low-cost additive manufacturing and artificial intelligence have enabled new avenues for developing accessible myoelectric prostheses. However, achieving reliable real-time control and ensuring mechanical durability remain significant challenges, particularly for affordable systems designed for resource-constrained settings. Objective: This study aimed to design and validate a low-cost, 3D-printed prosthetic arm that integrates single-channel electromyography (EMG) sensing with machine learning for real-time gesture classification. The device incorporates an anatomically inspired structure with 14 passive mechanical degrees of freedom (DOF) and 5 actively actuated tendon-driven DOF. The objective was to evaluate the system’s ability to recognize open, close, and power-grip gestures and to assess its functional grasping performance. Method: A Fast Fourier Transform (FFT)-based feature extraction pipeline was implemented on single-channel EMG data collected from able-bodied participants. A Support Vector Machine (SVM) classifier was trained on 5000 EMG samples to distinguish three gesture classes and benchmarked against alternative models. Mechanical performance was assessed through power-grip evaluation, while material feasibility was examined using PLA-based 3D-printed components. No amputee trials or long-term durability tests were conducted in this phase. Results: The SVM classifier achieved 92.7% accuracy, outperforming K-Nearest Neighbors and Artificial Neural Networks. The prosthetic hand demonstrated a 96.4% power-grip success rate, confirming stable grasping performance despite its simplified tendon-driven actuation. Limitations include the reliance on single-channel EMG, testing restricted to able-bodied subjects, and the absence of dynamic loading or long-term mechanical reliability assessments, which collectively limit clinical generalizability. Overall, the findings confirm the technical feasibility of integrating low-cost EMG sensing, machine learning, and 3D printing for real-time prosthetic control while emphasizing the need for expanded biomechanical testing and amputee-specific validation prior to clinical application. Full article

The existing scientific literature indicates that flowable short fiber-reinforced composites (SFRCs) can be used for direct restoration due to their favorable mechanical properties. However, there is a lack of data on the mechanical properties of SFRCs designed specifically for indirect CAD/CAM restorations. This study aims to fabricate a novel experimental SFRC CAD/CAM block and evaluate its fracture toughness and polishability as an indirect restoration in comparison with different conventional resin-based CAD/CAM blocks with different compositions. Fourier-transform infrared spectroscopy (FTIR) was employed to analyze the chemical structure of the Experimental SFRC group, while the microstructure of specimens from each group was examined using scanning electron microscopy (SEM). Then, this study divided the specimens into three groups—Group 1 (Grandio blocks), Group 2 (Cerasmart 270), and Group 3 (Experimental SFRC)—with 30 specimens in each group. Each group was then subdivided into sub-groups for the fracture toughness test, which evaluated resistance to crack propagation, and the surface roughness test, which assessed surface topography. FTIR analysis showed that the experimental SFRC exhibited distinct spectral changes after polymerization, confirming successful chemical reactions and network formation. SEM analysis showed that the Experimental SFRC block had a polymeric matrix with randomly oriented, well-dispersed short fibers. Grandio blocs exhibited a dense nanohybrid structure with irregular fillers, while Cerasmart 270 displayed a more uniform microstructure with evenly dispersed nano-sized spherical fillers. The Experimental SFRC showed the highest fracture toughness (2.758 MPa·√m), surpassing the other groups (p < 0.05) and highlighting its superior resistance to crack propagation. Regarding surface roughness Ra, the novel Experimental SFRC group (0.182) presented a significant difference compared to other groups (p < 0.05) but within clinical acceptance, and they can be well polished for clinical use after milling. The Cerasmart 270 block showed the lowest surface roughness Ra (0.135) among the groups, which is attributed to its filler size, geometry, and composition, resulting in a smoother surface. The higher fracture toughness of the Experimental SFRC among the groups suggests superior resistance to crack propagation, attributed to the incorporation of short fibers that enhance energy absorption and reduce brittleness, thereby supporting its suitability for high-stress-bearing clinical applications. Full article

Industrial wastewater can be reused in other everyday processes to help combat water scarcity worldwide. One contaminant in industrial wastewater is hexavalent chromium, which is highly toxic and can cause kidney, liver, and respiratory problems, making its removal vital. In this study, PLA-based films containing modified zirconia nanoparticles were developed via a solution-mixing process for hexavalent chromium adsorption. Obtaining the films involved two stages: the first was the chemical modification of ZrO₂ nanoparticles with thiamine hydrochloride (vitamin B1) using fixed-frequency ultrasound at an output of 750 W and 50% amplitude for 60 min. The second stage involved preparing the films by mixing them in the solution using an ultrasonic bath. The nanoparticle concentrations were 0.25, 0.5, and 1 wt%. The results obtained from characterization using Fourier-transform infrared spectroscopy (FT-IR) revealed the characteristic bands of PLA and the characteristic peak of the Zr-O bond corresponding to the ZrO₂ nanoparticles. Thermogravimetric analysis (TGA) showed that the ZrO₂ nanoparticles provided thermal stability to the PLA polymer. X-ray diffraction (XRD) showed a broad peak of amorphous PLA at 16.8° and signals corresponding to the crystalline phase of ZrO₂. The morphology of a cross-section of the films was observed using scanning electron microscopy (SEM), revealing a rough surface with pores. Finally, hexavalent chromium adsorption tests were carried out, measuring the adsorption efficiency under the parameters of pH, concentration, and contact time. The PLAZrO₂ sample achieved an adsorption efficiency of 83% at pH 2. Full article

Debate persists over whether classical econometric or modern machine learning (ML) approaches provide superior forecasts for volatile monthly price series. Despite extensive research, no systematic cross-domain comparison exists to guide model selection across diverse asset types. In this study, we compare traditional econometric models with classical ML baselines and hybrid approaches across financial assets, futures, commodities, and market index domains. Universal Python-based forecasting tools include month-end preprocessing, automated ARIMA order selection, Fourier terms for seasonality, circular terms, and ML frameworks for forecasting and residual corrections. Performance is assessed via anchored rolling-origin backtests with expanding windows and a fixed 12-month horizon. MAPE comparisons show that ARIMA-based models provide stable, transparent benchmarks but often fail to capture the nonlinear structure of high-volatility series. ML tools can enhance accuracy in these cases, but they are susceptible to stability and overfitting on monthly histories. The most accurate and reliable forecasts come from models that combine ARIMA-based methods with Fourier transformation and a slight enhancement using machine learning residual correction. ARIMA-based approaches achieve about 30% lower forecast errors than pure ML (18.5% vs. 26.2% average MAPE and 11.6% vs. 16.8% median MAPE), with hybrid models offering only marginal gains (0.1 pp median improvement) at significantly higher computational cost. This work demonstrates the domain-specific nature of model performance, clarifying when hybridization is effective and providing reproducible Python pipelines suited for economic security applications. Full article

Static eccentricity is an important early-stage fault in marine diesel generators, as small air-gap deviations caused by misalignment or mechanical wear can escalate into bearing damage and rotor–stator contact. To address the challenge of detecting such subtle faults, this study proposes a current signal analysis method based on the two-dimensional short-time Fourier transform (2D STFT) for early detection of static eccentricity faults in marine diesel generators. Using three-phase currents measured during normal operation and fault data synthesized with a physics-based electromechanical coupling model (1–5% eccentricity), we construct a two-dimensional phase–time representation rather than treating each phase as an independent one-dimensional time series and then apply 2D STFT. This formulation enables the simultaneous capture of inter-phase relationships and spatial patterns in the time–frequency–phase domain. Experiments indicate a distinct energy rise near 1020 Hz as static eccentricity increases. This trend enables the proposed method to distinguish small faults of approximately 5% eccentricity, which remain difficult to detect using conventional 1D STFT. As a result, the approach improves the diagnostic accuracy of non-contact, current-based monitoring for static eccentricity faults. Future work will include validation using real in-service fault data and extensions to other fault modes such as dynamic eccentricity and bearing defects. Full article

The rapid spread of the invasive brown macroalga Rugulopteryx okamurae has caused severe ecological and economic damage along the European coasts. Efforts to mitigate its impact have been largely ineffective, highlighting the need for alternative strategies to valorise this invasive species. This study explores the use of R. okamurae aqueous extract (RO extract) as a natural reducing and stabilizing agent for the green synthesis of gold (Au@RO), silver (Ag@RO), and platinum (Pt@RO) nanoparticles. The synthesized nanoparticles were extensively characterized using ultraviolet–visible spectroscopy (UV-Vis), transmission electron microscopy (TEM), X-ray diffraction (XRD), zeta potential analysis, and Fourier-transform infrared spectroscopy (FTIR). The results confirmed the successful formation of spherical and stable nanoparticles. Furthermore, the antioxidant activity of the RO extract was determined before and after the synthesis of the nanoparticles by the determination of the reducing power, total phenolic content and 1,1-diphenyl-2-picryl-hydrazyl (DPPH) radical scavenging activity. Notably, Pt@RO showed the highest enhancement in antioxidant activity among the nanoparticles synthesized. The findings demonstrate that R. okamurae can be repurposed as a valuable bioresource for the environmentally friendly production of metal nanoparticles with promising applications. Full article