Search Results (229)

This research introduces an enhanced fault detection approach, variational mode decomposition (VMD), for identifying open-circuit IGBT faults in the grid-side converter (GSC) of a doubly fed induction generator (DFIG) wind turbine system. VMD has many advantages over other decomposition methods, notably for non-stationary signals and noise. VMD’s robustness stems from its ability to decompose a signal into intrinsic mode functions (IMFs) with well-defined centre frequencies and bandwidths. The proposed methodology integrates VMD with a hybrid convolutional neural network–long short-term memory (CNN-LSTM) architecture to efficiently extract and learn distinctive temporal and spectral properties from three-phase current sources. Ten operational scenarios with a wind speed range of 5–16 m/s were simulated using a comprehensive MATLAB/Simulink version R2022b model, including one healthy condition and nine unique IGBT failure conditions. The obtained current signals were decomposed via VMD to extract essential frequency components, which were normalised and utilised as input sequences for deep learning models. A comparative comparison of CNN-LSTM and CNN-only classifiers revealed that the CNN-LSTM model attained the greatest classification accuracy of 88.00%, exhibiting enhanced precision and resilience in noisy and dynamic environments. These findings emphasise the efficiency of integrating advanced signal decomposition with deep sequential learning for real-time, high-precision fault identification in wind turbine power electronic converters. Full article

Under the combined influence of climate change and human activities, the non-stationarity of reservoir runoff has significantly intensified, posing challenges for traditional statistical models to accurately capture its multi-scale abrupt changes. This study focuses on Qianping (QP) Reservoir and systematically integrates climate-driven mechanisms with machine learning approaches to uncover the patterns of runoff evolution and develop high-precision prediction models. The findings offer a novel paradigm for adaptive reservoir operation under non-stationary conditions. In this paper, we employ methods including extreme-point symmetric mode decomposition (ESMD), Bayesian ensemble time series decomposition (BETS), and cross-wavelet transform (XWT) to investigate the variation trends and mutation features of the annual runoff in QP Reservoir. Additionally, four models—ARIMA, LSTM, LSTM-RF, and LSTM-CNN—are utilized for runoff prediction and analysis. The results indicate that: (1) the annual runoff of QP Reservoir exhibits a quasi-8.25-year mid-short-term cycle and a quasi-13.20-year long-term cycle on an annual scale; (2) by using Bayesian estimators based on abrupt change year detection and trend variation algorithms, an abrupt change point with a probability of 79.1% was identified in 1985, with a confidence interval spanning 1984 to 1986; (3) cross-wavelet analysis indicates that the periodic associations between the annual runoff of QP Reservoir and climate-driving factors exhibit spatiotemporal heterogeneity: the AMO, AO, and PNA show multi-scale synergistic interactions; the DMI and ENSO display only phase-specific weak coupling; while solar sunspot activity modulates runoff over long-term cycles; and (4) The NSE of the ARIMA, LSTM, LSTM-RF, and LSTM-CNN models all exceed 0.945, the RMSE is below 0.477 × 10⁹ m³, and the MAE is below 0.297 × 10⁹ m³, Among them, the LSTM-RF model demonstrated the highest accuracy and the most stable predicted fluctuations, indicating that future annual runoff will continue to fluctuate but with a decreasing amplitude. Full article

The unregulated consumption of corticosteroids causes significant adverse effects on human health. Therefore, it is important to develop methodologies that allow their analysis in pharmaceutical matrices with competitive analysis times and costs. The determination of corticosteroids by micellar electrokinetic chromatography (MEKC) using a background electrolyte (BGE) composed of phosphate buffer and a micellar pseudo-stationary phase constituted by a mixture of surfactants is proposed as an alternative quantification technique. The variables involved in the BGE: phosphate concentration, surfactant (sodium dodecyl sulfate (SDS) or sodium lauryl ether sulfate (SLES)), sodium taurocholate (STC) and the pH value were optimized using a Taguchi L₉ (3⁴) experimental design. Employing the optimal BGE, the separation of the three corticosteroids is possible in a linear range of 1.05–10.0 mg L⁻¹, with limits of detection (LOD) of 0.28–0.35 mg L⁻¹. The relative standard deviation (RSD) values obtained for the repeatability (n = 3) and intermediate precision (n = 9) were less than 5.0%. Pharmaceutical formulations (ointments, injectable solution and ophthalmic solution) were analyzed using the proposed methodology (MEKC) and the official methodology (high-performance liquid chromatography, HPLC), and no significant differences were found between the corticosteroid contents obtained from both methods. Full article

Buffalo milk is a rich source of precursor fatty acids for bioactive compounds and provides an optimal environment for bacterial growth. This study aimed to isolate and select lactic acid bacteria strains with potential to conjugated linoleic acid (CLA) production for technological application in fermented buffalo milk. Fifty-eight strains were isolated from raw milk, kefir, artisanal cheese, kombucha, and jaboticaba juice and tested for CLA biosynthesis. In milk fermentation, selected strains with linoleic acid (LA) conversion rates ranging from 65.66% to 21.86% were L. paraplantarum, L. plantarum, P. pentosaceus, and L. fermentum. The highest viability average values between 11.85 and 11.15 Log CFU/mL were observed after 8 h of fermentation for the L. plantarum, control L. plantarum, and L. fermentum treatments, while it took 10 h of fermentation for L. paraplantarum and P. pentosaceus to reach a stationary phase, with pH stabilizing at 4.60 ± 0.1 after 30 h. Despite L. paraplantarum showing the highest in vitro CLA production (0.99 mg/mL), in buffalo milk, all strains similarly produced c9t11 CLA, with no detectable t11c12 CLA. P. pentosaceus and L. fermentum showed a fatty acid profile with higher PUFA content, especially in CLA and MUFA, related to a lower degree of atherogenicity (IA) and thrombogenicity index (ThI). These findings boost understanding of dairy (raw milk, artisanal cheese, and milk kefir) and non-dairy substrates (kombucha and jaboticaba juice) as reservoirs for functional bacteria and highlight buffalo milk as a matrix for diversification of naturally enriched fermented dairy products. Full article

Since the 1990s, cannabis has experienced a gradual easing of access restrictions, accompanied by the expansion of its legalization and commercialization. This shift has led to the proliferation of cannabis-based products, available as cosmetics, food supplements, and pharmaceutical dosage forms. Consequently, there has been a growing demand for reliable and reproducible extraction techniques alongside precise analytical methods for detecting and quantifying cannabinoids, both of which are essential for ensuring consumer safety and product quality. Given the variability in extraction and quantification techniques across laboratories, significant attention has recently been directed toward method validation. Validated methods ensure precise cannabinoid measurement in cannabis-based products, supporting compliance with dosage guidelines and legal limits. Thus, this review highlights recent advancements in these areas, with a particular focus on High-Performance Liquid Chromatography (HPLC) coupled with Ultraviolet (UV) detection, as it is considered the gold standard for cannabinoid analysis included in cannabis monographs present in several pharmacopeias. The research focused on studies published between January 2022 and December 2024, sourced from PubMed, Scopus, and Web of Science, that employed an HPLC-UV analytical technique for the detection of phytocannabinoids. Additionally, the review examines cannabinoid extraction techniques and the validation methodologies used by the authors in the selected papers. Notably, ultrasound extraction has emerged as the most widely utilized technique across various matrices, with Deep Eutectic Solvents (DESs) offering a promising, efficient, and environmentally friendly extraction alternative. Analytical chromatographic separations continue to be predominantly conducted using C18 reversed-phase columns. Nevertheless, in recent years, researchers have explored various stationary phases, particularly to achieve the enantioseparation of cannabinoids. Full article

The antihypertensive drugs indapamide, atenolol, metoprolol, propranolol and bisoprolol were considered in this research. Because they have structures that are affected by pH, developing a chromatographic method was challenging. Based on the speciation diagram of these compounds versus pH scale, a mixed-mode stationary phase (hydrophobic stationary phase, C18 and strong cation exchanger (SCX)) was our first choice. Design of Experiments (DoE) was used to estimate how various factors such as pH, mobile phase composition and flow rate influenced chromatographic performance. As a result, the separation was achieved in 24 min using an aqueous phosphate buffer phase (pH 7.20) and 20 mM triethylamine, with methanol being used as organic modifier (30%). Their retention mechanism was investigated. The new method was validated in term of linearity, limits of detection and quantification, precision, accuracy, and robustness. The method was applied to river water samples, and good results were obtained. Full article

This study evaluated the effects of various concentrations of PVP-40 on the in vitro cryopreservation and recovery of Babesia bovis and Babesia bigemina. We also assessed a reduced dose of attenuated Babesia strains to determine its efficacy in preventing clinical disease. A microaerophilic stationary phase blood culture system was used to recover Babesia parasites that were cryopreserved in solutions with various PVP-40 concentrations and Babesia parasites in 20% PVP-40 were used to vaccinate naïve cattle. The animals were vaccinated intramuscularly with frozen parasites cryopreserved in 20% PVP-40, with a dose of either 1 × 10⁸ or 1 × 10⁷ erythrocytes infected with both attenuated B. bigemina and B. bovis produced from blood cultures. The control group received uninfected erythrocytes. During the vaccination, clinical parameters such as rectal temperature and hematocrit levels were unaffected. The animals were relocated to a farm in a Babesia hyperendemic area to test the efficacy of these live vaccines in controlling disease onset. Some vaccinated animals showed mild disease. In the vaccinated groups, parasites were detected in blood smears for only one day during the challenge. In contrast, the control group experienced fever for three consecutive days, a decline in hematocrit levels, and significant health deterioration. In this group, parasites were detected in smears for four consecutive days. All the animals in the control group required treatment to manage their high parasitemia and prevent mortality. In this study, we demonstrated that increasing the concentration of PVP-40 to cryopreserve parasites improved the recovery and proliferation of Babesia spp. in blood culture, and we also showed that when animals were vaccinated with cryopreserved, in vitro cultured, attenuated Babesia parasites in 20% PVP-40, they were effectively protected from severe clinical babesiosis. Full article

Objectives: A simple method for quantifying fluconazole in small blood volumes has been developed using volumetric absorptive microsampling (VAMS^®) technology and isocratic high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection. Methods: For sample collection, Mitra^® devices are used to keep the sample volume at 10 µL. For the quantitative determination of fluconazole, the Mitra^® samples are extracted using acetonitrile as the extraction agent, containing 2-(4-chlorophenyl)-1,3-bis(1,2,4-triazol-1-yl)propan-2-ol as the internal standard. A Synergi 4 μm Polar-RP 80 Å (150 × 2 mm) column forms the stationary phase, and a mixture of acetonitrile and phosphate buffer is the mobile phase. The UV detection is set at a wavelength of 210 nm. The therapeutic concentration range of 5 to 160 mg/L is covered, and the linear equation with 1/x² weighting is used to determine unknown samples. This method has been validated according to the current EMA and FDA guidelines for bioanalytical methods. Results: The validation data obtained after analysing whole blood samples (EDTA) showed within- and between-run accuracy between 94.4% and 115% and precision between 0.4% and 9.4%, respectively. A lower limit of quantification (LLOQ) of 5 mg/L was sufficient for therapeutic drug monitoring in paediatric patients receiving fluconazole as antifungal prophylaxis after haematopoietic cell transplantation. Conclusions: So far, 211 samples from 49 patients were successfully analysed, and concentrations between 5.84 mg/L and 107 mg/L were determined for whole blood Mitra^® samples. To our knowledge, this is the first application of VAMS^® technology using simple and cheap HPLC-UV quantification. Full article

Background/Objectives: Latanoprost is a leading active pharmaceutical ingredient belonging to the synthetic prostaglandin F2α analogs, widely used as a first-line treatment for open-angle glaucoma and increased intraocular pressure. This study addresses the critical need for an accurate and precise chromatographic method that is capable of simultaneously quantifying latanoprost and six latanoprost-related substances in antiglaucoma eye drops. This will be crucial for patient safety and treatment efficacy. This method enables the separation of latanoprost isomers, (15S)-latanoprost, latanoprost enantiomer, and 5,6-trans latanoprost from latanoprost signal. Furthermore, it is specific for the well-known latanoprost degradants—the major latanoprost acid and the minor 15-ketolatanoprost—as well as synthetic derivatives, such as triphenylphosphine oxide (TPPO) and propan-2-yl 5-(diphenylphosphoryl)pentanoate (IDPP). Using forced degradation studies using high temperatures, UV light, alkalis, acids, and oxidizing agents, the degradation profiles of the drugs were characterized and the method’s stability-indicating power was confirmed. Methods: Separation was achieved on a stationary combined system comprising chiral and cyano columns. Reverse-phase gradient elution and UV 210 nm detection were employed. The novel method was validated according to the European Medicines Agency International Council for Harmonisation Q2 Validation of analytical procedures—Scientific guideline. Results: The method was shown to be linear in the range of 40–60 µg/mL for latanoprost and 0.05–2.77 µg/mL for related substances, confirmed by a correlation coefficient of r = 0.999. Recoveries for latanoprost were obtained within the range of 98.0–102.0% for assays and 90.0–110.0% for impurities. The detection and quantification limits for latanoprost were 0.025 µg/mL and 0.35 µg/mL, respectively. Conclusions: The analytical procedure developed is adequately sensitive, precise, and accurate compared to existing methods. The method can be reliably used to control the critical quality attributes of low-dose latanoprost products, ensuring their required high pharmaceutical quality, which translates into improvements in patient care. This advancement holds significant implications for enhancing the therapeutic management of glaucoma, ensuring drug safety and efficacy. Full article

Grid-connected inverter (GCI) plays a crucial role in facilitating stable and efficient power delivery, especially under severe and complex grid conditions. Harmonic distortions and imbalance of the grid voltages may degrade the grid-injected current quality. Moreover, inductive-capacitance (LC) grid impedance and the grid frequency fluctuation also degrade the current control performance or stability. In order to overcome such an issue, this study presents a frequency-adaptive current control strategy of a GCI based on incomplete state observation under severe grid conditions. When LC grid impedance exists, it introduces additional states in a GCI system model. However, since the state for the grid inductance current is unmeasurable, it yields a limitation in the state feedback control design. To overcome such a limitation, this study adopts a state feedback control approach based on incomplete state observation by designing the controller only with the available states. The proposed control strategy incorporates feedback controllers with ten states, an integral controller, and resonant controllers for the robustness of the inverter operation. To reduce the reliance on additional sensing devices, a discrete-time full-state current observer is utilized. Particularly, with the aim of avoiding the grid frequency dependency of the system model, as well as the complex online discretization process, observer design is developed in the stationary reference frame. Additionally, a moving average filter (MAF)-based phase-locked loop (PLL) is incorporated for accurate frequency detection against distortions of grid voltages. For evaluating the performance of the designed control strategy, simulations and experiments are executed with severe grid conditions, including grid frequency changes, unbalanced grid voltage, harmonic distortion, and LC grid impedance. Full article

NASA’s Juno mission, involving a pioneering spacecraft the size of a basketball court, has been instrumental in observing Jupiter’s atmosphere and surface from orbit since it reached the intended orbit. Over its first decade of operation, Juno has provided unprecedented insights into the solar system’s origins through advanced remote sensing and technological innovations. This study focuses on change detection in terms of Juno’s trajectory, leveraging cutting-edge data computing techniques to analyze its orbital dynamics. Utilizing 3D position and velocity time series data from NASA, spanning 11 years and 5 months (August 2011 to January 2023), with 5.5 million samples at 1 min accuracy, we examine the spacecraft’s trajectory modifications. The instantaneous average acceleration, jerk, and snap are computed as approximations of the first, second, and third derivatives of velocity, respectively. The Hilbert transform is employed to visualize the spectral properties of Juno’s non-stationary 3D movement, enabling the detection of extreme events caused by varying forces. Two unsupervised machine learning algorithms, DBSCAN and OPTICS, are applied to cluster the sampling events in two 3D state spaces: (velocity, acceleration, jerk) and (acceleration, jerk, snap). Our results demonstrate that the OPTICS algorithm outperformed DBSCAN in terms of the outlier detection accuracy across all three operational phases (OP1, OP2, and OP3), achieving accuracies of 99.3%, 99.1%, and 98.9%, respectively. In contrast, DBSCAN yielded accuracies of 98.8%, 98.2%, and 97.4%. These findings highlight OPTICS as a more effective method for identifying outliers in elliptical orbit data, albeit with higher computational resource requirements and longer processing times. This study underscores the significance of advanced machine learning techniques in enhancing our understanding of complex orbital dynamics and their implications for planetary exploration. Full article

Nitrogen-containing heterocyclic compounds (NHCs) are common environmental pollutants that need to be monitored due to their high toxicity. Typically, gas or liquid chromatography combined with mass spectrometric detection is used for this task. However, many NHCs are highly polar compounds, which can cause difficulties when using these methods. On the other hand, supercritical fluid chromatography is well-established in the analysis of polar compounds and could provide an alternative to conventional techniques. The presented work proposes an approach to the simultaneous determination of 20 NHCs in soils by supercritical fluid chromatography–tandem mass spectrometry with the limits of quantification in the range 0.08–1.23 mg kg⁻¹. The separation is carried out in gradient mode on a cyanopropyl stationary phase in 6 min. The approach was validated and tested on real objects—peat and sandy soils contaminated with rocket fuel transformation products. Full article

The present study is the first report on the chemical and enantiomeric compositions of essential oils from the Ecuadorian species Gynoxys hallii Hieron., Gynoxys calyculisolvens Hieron., and Gynoxys azuayensis Cuatrec. All the volatile fractions presented a sesquiterpene-based chemical profile, typical of other volatile fractions from this genus. Both qualitative (GC-MS) and quantitative (GC-FID) chemical analyses were carried out on two stationary phases of different polarity (non-polar and polar). The main constituents of G. hallii essential oil on the two columns, respectively, were α-pinene (33.6–31.5%), (E)-β-caryophyllene (6.2–6.4%), germacrene D (35.7–38.3%), and bicyclogermacrene (3.8–4.0%). In G. calyculisolvens, the major compounds were α-pinene (11.2–11.0%), p-cymene (4.0–3.7%), α-copaene (3.6–3.7%), (E)-β-caryophyllene (8.1–8.3%), germacrene D (20.8–22.0%), and germacrene D-4-ol (8.4–8.6%). Finally, the main components of G. azuayensis were α-pinene (4.5–4.1%), germacrene D (14.1–12.4%), bicyclogermacrene (2.6–3.0%), tridecanal (6.4–6.2%), and spathulenol (7.8–7.1%). Furthermore, enantioselective analyses were conducted on the three volatile fractions, using two stationary phases based on β-cyclodextrins. As a result, twelve chiral components were investigated, detecting both enantiomerically pure compounds and scalemic mixtures with various enantiomeric excess. Full article

This study investigates the fermentation of white cabbage with salicornia and CaCl₂ to assess its effect on the fermentation profiles and properties of the final products. Two sets of experiments were performed: A—cabbage with salt and salicornia, and B—cabbage with salt, salicornia, and CaCl₂. The fermentative processes were studied through the microbial (lactic-acid bacteria (LAB), coliforms, and fungi), physicochemical (pH, total acidity), and mineral properties. A diminution of pH values (4.07, 3.58) and increased acidity values (0.70, 0.77 g lactic acid/100 mL) were registered at the end of the fermentation period (A and B, respectively). A stationary phase followed the exponential growth of LAB, and a slight decrease was observed (6.01, 5.51 Log CFU/g) in both experiments. A fungi decline was observed during the first week and the coliform populations disappeared after about 13 days of fermentation. Staphylococcus coagulase-positive, Escherichia coli, and Salmonella were not detected in the final products. The utilization of CaCl₂ resulted in fermented cabbage with analogous microbial and sensorial characteristics to fermented cabbage without CaCl₂ but with an increased hardness. However, Ca interfered with the diffusion of K, Mg, and Zn, resulting in lower levels of these elements in the final product, particularly Zn, which exhibited a reduction of 37%, reducing the nutritional value of the final products. Full article

Di-isopropyl methyl phosphonate (DIMP) has no major commercial uses but is a by-product or a precursor in the synthesis of the nerve agent sarin (GB). Also, DIMP is utilized as a simulant compound for the chemical warfare agents sarin and soman in order to test and calibrate sensitive IMS instrumentation that warns against the deadly chemical weapons. DIMP was measured from 2 ppb_v (15 μg m⁻³) to 500 ppb_v in the air using a pocket-held ToF ion mobility spectrometer, model LCD-3.2E, with a non-radioactive ionization source and ammonia doping in positive ion mode. Excellent sensitivity (LoD of 0.24 ppb_v and LoQ of 0.80 ppb_v) was noticed; the linear response was up to 10 ppb_v, while saturation occurred at >500 ppb_v. DIMP identification by IMS relies on the formation of two distinct peaks: the monomer M·NH₄⁺, with a reduced ion mobility K₀ = 1.41 cm² V⁻¹ s⁻¹, and the dimer M₂·NH₄⁺, with K₀ = 1.04 cm² V⁻¹ s⁻¹ (where M is the DIMP molecule); positive reactant ions (Pos RIP) have K₀ = 2.31 cm² V⁻¹ s⁻¹. Quantification of DIMP at trace levels was also achieved by GC-MS over the concentration range of 1.5 to 150 μg mL⁻¹; using a capillary column (30 m × 0.25 mm × 0.25 μm) with a TG-5 SilMS stationary phase and temperature programming from 60 to 110 °C, DIMP retention time (RT) was ca. 8.5 min. The lowest amount of DIMP measured by GC-MS was 1.5 ng, with an LoD of 0.21 μg mL⁻¹ and an LoQ of 0.62 μg mL⁻¹ DIMP. Our results demonstrate that these methods provide robust tools for both on-site and off-site detection and quantification of DIMP at trace levels, a finding which has significant implications for forensic investigations of chemical agent use and for environmental monitoring of contamination by organophosphorus compounds. Full article