Search Results (1,537)

Background/Objectives: The integration of machine learning (ML) and artificial intelligence (AI) has revolutionized the pharmaceutical industry by improving drug discovery, development and manufacturing processes. Based on literature data, an ML model was developed by our group to predict the formation of binary co-amorphous systems (COAMSs) for inhalation therapy. The model’s ability to develop a dry powder formulation with the necessary properties for a predicted co-amorphous combination was evaluated. Methods: An extended experimental validation of the ML model by co-milling and X-ray diffraction analysis for 18 API-API (active pharmaceutical ingredient) combinations is presented. Additionally, one COAMS of rifampicin (RIF) and ethambutol (ETH), two first-line tuberculosis (TB) drugs are developed further for inhalation therapy. Results: The ML model has shown an accuracy of 79% in predicting suitable combinations for 35 APIs used in inhalation therapy; experimental accuracy was demonstrated to be 72%. The study confirmed the successful development of stable COAMSs of RIF-ETH either via spray-drying or co-milling. In particular, the milled COAMSs showed better aerosolization properties (higher ED and FPF with lower standard deviation). Further, RIF-ETH COAMSs show much more reproducible results in terms of drug quantity dissolved over time. Conclusions: ML has been shown to be a suitable tool to predict COAMSs that can be developed for TB treatment by inhalation to save time and cost during the experimental screening phase. Full article

Background/Objectives: The work presented herein focused on the development and characterization of a transdermal caffeine platform fabricated from ultrathin micro- and submicron fibers produced via electrospinning. Methods: The formulations incorporated caffeine encapsulated in a polyethylene oxide (PEO) matrix, combined with various permeation enhancers. A backing layer made of annealed electrospun polycaprolactone (PCL) facilitated the lamination of the two layers to form the final multilayer patch. Comprehensive characterization was conducted, utilizing scanning electron microscopy (SEM) to assess the fiber morphology, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) for chemical detection and to assess the stability of the caffeine, and differential scanning calorimetry (DSC) along with wide-angle X-ray scattering (WAXS) to analyze the physical state of the caffeine within the fibers of the active layer. Additionally, Franz cell permeation studies were performed using both synthetic membranes (Strat-M) and ex vivo human stratum corneum (SC) to evaluate and model the permeation kinetics. Results: These experiments demonstrated the significant role of enhancers in modulating the caffeine permeation rates provided by the patch, achieving permeation rates of up to 0.73 mg/cm² within 24 h. Conclusions: This work highlights the potential of using electro-hydrodynamic processing technology to develop innovative transdermal delivery systems for drugs, offering a promising strategy for enhancing efficacy and innovative therapeutic direct plasma administration. Full article

Recent studies primarily focus on how the fiber content and curing age influence the pore structure and strength of concrete. However, The interfacial bonding mechanism in basalt-fiber-reinforced concrete hydration remains unclear. The lack of a long-term performance-prediction model and insufficient research on multi-field coupling effects form key knowledge gaps, hindering the systematic optimal design and wider engineering applications of such materials. By integrating X-ray computed tomography (CT) with the watershed algorithm, this study proposes an innovative gray scale threshold method for pore quantification, enabling a quantitative analysis of pore structure evolution and its correlation with mechanical properties in basalt-fiber-reinforced concrete (BFRC) and normal concrete (NC). The results show the following: (1) Mechanical Enhancement: the incorporation of 0.2% basalt fiber by volume demonstrates significant enhancement in the mechanical performance index. At 28 days, BFRC exhibits compressive and splitting tensile strengths of 50.78 MPa and 4.07 MPa, surpassing NC by 19.88% and 43.3%, respectively. The early strength reduction in BFRC (13.13 MPa vs. 22.81 MPa for NC at 3 days) is attributed to fiber-induced interference through physical obstruction of cement particle hydration pathways, which diminishes as hydration progresses. (2) Porosity Reduction: BFRC demonstrates a 64.83% lower porosity (5.13%) than NC (11.66%) at 28 days, with microscopic analysis revealing a 77.5% proportion of harmless pores (<1.104 × 10⁷ μm³) in BFRC versus 67.6% in NC, driven by densified interfacial transition zones (ITZs). (3) Predictive Modeling: a two dimensional strength-porosity model and a three-dimensional age-dependent model are developed. The proposed multi-factor model demonstrates exceptional predictive capability (R² = 0.9994), establishing a quantitative relationship between pore micro structure and mechanical performance. The innovative pore extraction method and mathematical modeling approach offer valuable insights into the micro-structural evolution mechanism of fiber concrete. Full article

This work investigates the potential industrial applications of two sodium bentonite samples (white and yellow), obtained from raw Ca-rich bentonite from Maputo Province in Southern Mozambique. Bentonite bio-organoclays were successfully developed from two Mozambican montmorillonite clays through the intercalation of protonated dimer fatty acid-based polyamide chains using a solution casting method. X-ray diffraction (XRD) analysis confirmed polymer intercalation, with the basal spacing (d₀₀₁) increasing from approximately 1.5 nm to 1.7 nm as the polymer concentration varied between 2.5 and 7.5 wt.%. However, the extent of intercalation was limited at this stage, suggesting that polymer concentration alone had a minimal effect, likely due to the formation of agglomerates. In a subsequent optimization phase, the influence of temperature (30–90 °C), stirring speed (1000–2000 rpm), and contact time (30–90 min) was evaluated while maintaining a constant polymer concentration. These parameters significantly enhanced intercalation, achieving d001 values up to 4 nm. Statistical Design of Experiments and Response Surface Methodology revealed that temperature and stirring speed exerted a stronger influence on d001 expansion than contact time. Optimal intercalation occurred at 90 °C, 1500 rpm, and 60 min. The predictive models demonstrated high accuracy, with R² values of 0.9861 for white bentonite (WB) and 0.9823 for yellow bentonite (YB). From statistical modeling, several key observations emerged. Higher stirring speeds promoted intercalation by enhancing mass transfer and dispersion; increased agitation disrupted stagnant layers surrounding the clay particles, facilitating deeper penetration of the polymer chains into the interlayer galleries and preventing particle settling. Furthermore, the ANOVA results showed that all individual and interaction effects of the factors investigated had a significant influence on the d₀₀₁ spacing for both WB and YB clays. Each factor exhibited a positive effect on the degree of intercalation. Full article

This work presents an analysis of the sub-ionospheric VLF transmitter signal disturbances which were detected more than one week before the Turkey–Syria EQ occurrence. We have applied the multi-terminator method when considering amplitude and phase variations of the TBB transmitter signal (Turkey), selected because of a good signal to noise ratio for the amplitude, a stable phase variation, and a ray-path propagation crossing the pre-seismic sensitive region, estimated from the combination of the Dobrovolsky area and the Fresnel zone. New spectral features, i.e., inflexions and jumps, are considered in this study, besides the minima and maxima investigated in. The spectral occurrence probabilities are derived at three specific locations: Graz facility, TBB station and EQ epicenter. We show that two main precursors occurred from 27 to 30 January, and from 31 January to 3 February. More important are the prior precursors detected from 23 January to 25/26 January, where anomaly fluctuations were found to be similar to those at the EQ epicenter area, approximately. A forecasting model is proposed, in which the main steps can provide, in the presence of spectral anomalies, first hints regarding the longitudinal locations of the seismic preparation zone. Full article

Traditional coal quality assessment methods rely exclusively on the laboratory testing of physical samples, which impedes detailed stratigraphic evaluation and limits the integration of intelligent precision mining technologies. To resolve this challenge, this study investigates geophysical logging as an innovative method for coal quality prediction. By integrating scanning electron microscopy (SEM), X-ray analysis, and optical microscopy with interdisciplinary methodologies spanning mathematics, mineralogy, and applied geophysics, this research analyzes the coal quality and mineral composition of the Shanxi Formation coal seams in northern Jiangsu, China. A predictive model linking geophysical logging responses to coal quality parameters was established to delineate relationships between subsurface geophysical data and material properties. The results demonstrate that the Shanxi Formation coals are gas coal (a medium-metamorphic bituminous subclass) characterized by low sulfur content, low ash yield, low fixed carbon, high volatile matter, and high calorific value. Mineralogical analysis identifies calcite, pyrite, and clay minerals as the dominant constituents. Pyrite occurs in diverse microscopic forms, including euhedral and semi-euhedral fine grains, fissure-filling aggregates, irregular blocky structures, framboidal clusters, and disseminated particles. Systematic relationships were observed between logging parameters and coal quality: moisture, ash content, and volatile matter exhibit an initial decrease, followed by an increase with rising apparent resistivity (LLD) and bulk density (DEN). Conversely, fixed carbon and calorific value display an inverse trend, peaking at intermediate LLD/DEN values before declining. Total sulfur increases with density up to a threshold before decreasing, while showing a concave upward relationship with resistivity. Negative correlations exist between moisture, fixed carbon, calorific value lateral resistivity (LLS), natural gamma (GR), short-spaced gamma-gamma (SSGG), and acoustic transit time (AC). In contrast, ash yield, volatile matter, and total sulfur correlate positively with these logging parameters. These trends are governed by coalification processes, lithotype composition, reservoir physical properties, and the types and mass fractions of minerals. Validation through independent two-sample t-tests confirms the feasibility of the neural network model for predicting coal quality parameters from geophysical logging data. The predictive model provides technical and theoretical support for advancing intelligent coal mining practices and optimizing efficiency in coal chemical industries, enabling real-time subsurface characterization to facilitate precision resource extraction. Full article

The influence of porosity on rock mechanical properties constitutes a critical research focus. This investigation explores the relationship between pore structure parameters and mechanical characteristics through reconstructed numerical models. The study employs an integrated approach combining laboratory experiments and numerical simulations. Initially, high-resolution X-ray computed tomography (CT) was utilized to capture three-dimensional geometric features of Sichuan white sandstone microstructures, complemented by mechanical parameter acquisition through standardized testing protocols. The research workflow incorporated advanced image processing techniques, including adaptive total variation denoising algorithms for CT image enhancement and deep learning-based threshold segmentation for feature extraction. Subsequently, pore structure reconstruction models with controlled porosity variations were developed for systematic numerical experimentation. Key findings reveal a pronounced degradation trend in both mechanical strength and elastic modulus with increasing porosity levels. Based on simulation data, two empirical models were established: a porosity–compressive strength correlation model and a porosity–elastic modulus relationship model. These quantitative formulations provide theoretical support for understanding the porosity-dependent mechanical behavior in rock mechanics. The methodological framework and results presented in this study offer valuable insights for geological engineering applications and petrophysical characteristic analysis. Full article

A series of new isatin hydrazones bearing phosphorus-containing moiety was synthesized through a simple, high-yield and easy work-up reaction of phosphine oxide (Phosenazide) or phosphinate (2-chloroethyl (4-(dimethylamino)phenyl)(2-hydrazinyl-2-oxoethyl)phosphinate, CAPAH) hydrazides with aryl-substituted isatins. The ³¹P NMR technique showed that, in most cases, out of 12 examples in solution, the ratio of the two spatial isomers varied from 1:1 to 1:3. Quantum chemical calculations confirmed the predominance of Z,syn form both in the gas phase and in solution. According to X-ray analysis data in crystals, they exist only in Z,syn form too. Most of the phosphine oxide derivatives and 5-methoxy- and 5-bromoaryl phosphinate analogs exhibit anti-aggregant activity at the level of acetylsalicylic acid but inhibit platelet activation processes more effectively. The 5-chloro type phosphinate derivative exhibits anti-aggregant properties more effectively than acetylsalicylic acid under the conditions of the tissue factor (TF)-activated thromboelastography (TEG) model, the ex vivo thrombosis model. Thus, all the obtained results can become the basis for future pharmaceutical developments to create effective anti-aggregation drugs with broad antithrombotic potential. Full article

Wire electrical discharge machining (WEDM), as a significant branch of non-traditional machining technologies, is widely applied in fields such as mold manufacturing and aerospace due to its high-precision machining capabilities for hard and complex materials. This paper systematically reviews the research progress in WEDM process optimization from two main perspectives: traditional optimization methods and artificial intelligence (AI) techniques. Firstly, it discusses in detail the applications and limitations of traditional optimization methods—such as statistical approaches (Taguchi method and response surface methodology), Adaptive Neuro-Fuzzy Inference Systems, and regression analysis—in parameter control, surface quality improvement, and material removal-rate optimization for cutting metal materials in WEDM. Subsequently, this paper reviews AI-based approaches, traditional machine-learning methods (e.g., neural networks, support vector machines, and random forests), and deep-learning models (e.g., convolutional neural networks and deep neural networks) in aspects such as state recognition, process prediction, multi-objective optimization, and intelligent control. The review systematically compares the advantages and disadvantages of traditional methods and AI models in terms of nonlinear modeling capabilities, adaptability, and generalization. It highlights that the integration of AI by optimization algorithms (such as Genetic Algorithms, particle swarm optimization, and manta ray foraging optimization) offers an effective path toward the intelligent evolution of WEDM processes. Finally, this investigation looks ahead to the key application scenarios and development trends of AI techniques in the WEDM field for cutting metal materials. Full article

TXS 0506+056 is a blazar associated with neutrino events. The study on its variation mechanics and periodicity analysis is meaningful to understand other BL Lac objects. The local cross-correlation function (LCCF) analysis presents a 3$\sigma$ correlation in both the $\gamma$-ray versus optical and optical versus radio light curves. The time lag analysis suggests that the optical and $\gamma$-ray band share the same emission region, located upstream of the radio band in the jet. We use both the weighted wavelet Z-transform and generalized Lomb–Scargle methods to analyze the periodicity. We find two plausible quasi-periodic oscillations (QPOs) at ${506}_{-56}^{+133}$ days and ${175}_{-7}^{+15}$ days for the light curve of the optical band. For the $\gamma$-ray band, we find that the spectrum varies with the softer when brighter (SWB) trend, which could be explained naturally if a stable very high energy component exists. For the optical band, TXS 0506+056 exhibits a harder when brighter (HWB) trend. We discover a trend transition from HWB to SWB in the X-ray band, which could be modeled by the shift in peak frequency assuming that the X-ray emission is composed of the synchrotron and the inverse Compton (IC) components. The flux correlations of $\gamma$-ray and optical bands behave anomalously during the period of neutrino events, indicating that there are possible other hadronic components associated with neutrino. Full article

Acetone carboxylase (AC) from Xanthobacter autotrophicus is a 360 KDa α₂β₂γ₂ heterohexamer that catalyzes the ATP-dependent formation of phosphorylated acetone and bicarbonate intermediates that react at Mn(II) metal active sites to form acetoacetate. Structural models of X. autotrophicus AC (XaAC) with and without nucleotides reveal that the binding and phosphorylation of the two substrates occurs ~40 Å from the Mn(II) active sites where acetoacetate is formed. Based on the crystal structures, a significant conformational change was proposed to open and close a tunnel that facilitates the passage of reaction intermediates between the sites for nucleotide binding and phosphorylation of substrates and Mn(II) sites of acetoacetate formation. We have employed electron paramagnetic resonance (EPR), kinetic assays, and hydrogen/deuterium exchange mass spectrometry (HDX-MS) of poised ligand-bound states and site-specific amino acid variants to complete an in-depth analysis of Mn(II) coordination and allosteric communication throughout the catalytic cycle. In contrast with the established paradigms for carboxylation, our analyses of XaAC suggested a carboxylate shift that couples both local and long-range structural transitions. Shifts in the coordination mode of a single carboxylic acid residue (αE89) mediate both catalysis proximal to a Mn(II) center and communication with an ATP active site in a separate subunit of a 180 kDa α₂β₂γ₂ complex at a distance of 40 Å. This work demonstrates the power of combining structural models from X-ray crystallography with solution-phase spectroscopy and biophysical techniques to elucidate functional aspects of a multi-subunit enzyme. Full article

This study proposes a bionic helical configuration design concept, focusing on glass-fiber-reinforced polymer matrix composites. Through a combination of experimental and numerical simulation methods, it systematically investigates the resistance to multiple impacts and damage tolerance. The research designs and fabricates two types of bionic laminates: a cross-helical and a symmetric-helical structures. By conducting repeated impact experiments at 5 J of energy for 1, 5, 10, and 15 impact times and employing advanced characterization techniques, such as ultrasonic C-scan and X-ray CT, the study reveals the mechanisms of interlaminar damage propagation and failure characteristics. Based on experimental findings, a finite element model encompassing the entire impact process and post-impact compression behavior is established. Utilizing this model, three optimized novel bionic configurations are further developed, providing new insights and theoretical support for the structural design of high-performance impact-resistant polymer matrix composites. Full article

This study presents a comprehensive numerical framework for Background-Oriented Schlieren (BOS) to systematically evaluate its performance and reconstructive capabilities under complex flow conditions. This framework integrates two stages: forward modeling, using ray tracing to simulate image degradation, and inverse processing, using optical flow and a conjugate gradient algorithm to extract displacements and reconstruct phase information. This method is first validated using turbulent flow fields in the Johns Hopkins Turbulence Database, where the reconstructed phase screens closely match the original data, with relative errors below 4% and structural similarity indices above 0.75 in all cases, providing a possible restoration method for degraded flow field images. It is then applied to shock wave fields with varying Mach numbers; this method achieves meaningful reconstruction at short ranges but fails under long-range imaging due to severe wavefront distortions. However, even in degraded conditions, the extracted optical flow fields preserve structural features correlated with the underlying shock patterns, indicating potential for BOS-based target recognition. These findings highlight both the capabilities and limitations of BOS and suggest new pathways for extending its use beyond traditional flow visualization. Full article

Background/Objectives: Chronic lung diseases are among the leading causes of death worldwide. In the treatment of these diseases, non-steroidal anti-inflammatory drugs can be effective. We have previously developed an excipient formulation alongside a modern manufacturing protocol, which we aim to further investigate. We have chosen two new model drugs, meloxicam (MX) and its water-soluble salt, meloxicam-potassium (MXP). The particles in dry powder inhaler (DPI) formulation were expected to have a spherical shape, fast drug release, and good aerodynamic properties. Methods: The excipients were poloxamer-188, mannitol, and leucine. The samples were prepared by spray drying, preceded by solution preparation and wet grinding. Particle size was determined by laser diffraction, shape by scanning electron microscopy (SEM), crystallinity by powder X-ray diffraction (PXRD), interactions by Fourier-transform infrared spectroscopy (FT-IR), in vitro drug dissolution by paddle apparatus, and in vitro aerodynamic properties by Andersen cascade impactor and Spraytec^® device. Results: We achieved the proper particle size (<5 μm) and spherical shape according to laser diffraction and SEM. The XRPD showed partial amorphization. FT-IR revealed no interaction between the materials. During the in vitro dissolution tests, more than 90% of MX and MXP were released within the first 5 min. The best products exhibited an aerodynamic diameter of around 4 µm, a fine particle fraction around 50%, and an emitted fraction over 95%. The analysis by Spraytec^® supported the suitability for lung targeting. Conclusions: The developed preparation process and excipient system can be applied in the development of different drugs containing DPIs. Full article

This study investigates the electromagnetic performance of two carbon fiber monopole antennas integrated into a UAV copter frame, with emphasis on design adaptation, impedance matching, and propagation behavior. A comprehensive experimental campaign was conducted to characterize key parameters such as center frequency, bandwidth, gain, VSWR, and S₁₁. Both antennas exhibited dual-band resonance at approximately 381 MHz and 1.19 GHz, each achieving a 500 MHz bandwidth where VSWR ≤ 2. The modified antenna achieved a minimum reflection coefficient of –14.6 dB and a VSWR of 1.95 at 381.45 MHz, closely aligning with theoretical predictions. Gain deviations between measured (0.15–0.19 dBi) and calculated (0.19 dBi) values remained within 0.04 dB, while received power fluctuations did not exceed 1.3 dB under standard test conditions despite the composite material’s finite conductivity. Free-space link-budget tests at 0.5 m and 2 m of separation revealed received-power deviations of 0.9 dB and 1.3 dB, respectively, corroborating the Friis model. Radiation pattern measurements in both azimuth and elevation planes confirmed good directional behavior, with minor side lobe variations, where Antenna A displayed variations between 270° and 330° in azimuth, while Antenna B remained more uniform. A 90° polarization mismatch led to a 15 dBm signal drop, and environmental obstructions caused losses of 9.4 dB, 12.6 dB, and 18.3 dB, respectively, demonstrating the system’s sensitivity to alignment and surroundings. Additionally, signal strength changes observed in a Two-Ray propagation setup validated the importance of ground reflection effects. Small-scale fading analysis at 5 m LOS indicated a Rician-distributed envelope with mean attenuation of 53.96 dB, σ_dB = 5.57 dB, and a two-sigma interval spanning 42.82 dB to 65.11 dB; the fitted K-factor confirmed the dominance of the LOS component. The findings confirm that carbon fiber UAV frames can serve as effective directional antenna supports, providing proper alignment and tuning. These results support the future integration of lightweight, structure-embedded antennas in UAV systems, with potential benefits in communication efficiency, stealth, and design simplification. Full article