Search Results (18)

In alpine skiing, accurate and real-time estimation of body pose and inclinations due to turning is critical as it demonstrates the skier’s turning behavior and abilities. Although inertial measurement units (IMUs) ease measuring kinematics in extreme conditions and provide such indications of skiers’ behavior, they often suffer from sensor placement and orientation variability. This study explains the impact of sensor placement and orientation on the captured signals and proposes a preprocessing algorithm that can rotate raw signals from various locations and orientations similar to those near the Center of Mass (CoM). The preprocessing algorithm involves a sensor fusion approach using a quaternion-based complementary filter (CF) to rotate raw signals and extract turning motions via the global wavelet spectrum. Our experiment, validated on data collected from 14 sensors including two smartphones placed on different body parts during skiing sessions, demonstrates that the preprocessing algorithm can effectively reconstruct side motions, represent skiing turns, and detect turns independent of sensor placement and orientation. In field experiments with six skiers, the suggested preprocessing algorithm consistently detected skiing turns with an overall RMSE of 0.77 and MAE of 0.50 on all of the sensors relative to a reference sensor. Full article

In tunnel engineering, joint shear slip caused by external disturbances is a key factor contributing to landslides, instability of surrounding rock masses, and related hazards. Therefore, accurately characterizing the macromechanical properties of joints is essential for ensuring engineering safety. Given the significant influence of rock joint morphology on mechanical behavior, this study employs the frequency spectrum fractal dimension (D) and the frequency domain amplitude integral (Rq) as quantitative descriptors of joint morphology. Using Fourier transform techniques, a reconstruction method is developed to model joints with arbitrary shape characteristics. The numerical model is calibrated through 3D printing and direct shear tests. Systematic parameter analysis validates the selected quantitative indices as effective descriptors of joint morphology. Furthermore, multiple machine learning algorithms are employed to construct a robust predictive model. Machine learning, recognized as a rapidly advancing field, plays a pivotal role in data-driven engineering applications due to its powerful analytical capabilities. In this study, six algorithms—Random Forest (RF), Support Vector Regression (SVR), BP Neural Network, GA-BP Neural Network, Genetic Programming (GP), and ANN-based MCD—are evaluated using 300 samples. The performance of each algorithm is assessed through comparative analysis of their predictive accuracy based on correlation coefficients. The results demonstrate that all six algorithms achieve satisfactory predictive performance. Notably, the Random Forest (RF) algorithm excels in rapid and accurate predictions when handling similar training data, while the ANN-based MCD algorithm consistently delivers stable and precise results across diverse datasets. Full article

Chloramphenicol (CAM), a well-known broad-spectrum antibiotic, inhibits peptide bond formation in bacterial ribosomes. It has been reported to affect ribosome assembly mainly through disrupting the balance of ribosomal proteins. The present study investigates the multifaceted effects of CAM on the maturation of the 50S ribosomal subunit in Escherichia coli (E. coli). Using label-free quantitative mass spectrometry (LFQ-MS), we observed that CAM treatment also leads to the upregulation of assembly factors. Further cryo-electron microscopy (cryo-EM) analysis of the ribosomal precursors characterized the CAM-treatment-accumulated pre-50S intermediates. Heterogeneous reconstruction identified 26 distinct pre-50S intermediates, which were categorized into nine main states based on their structural features. Our structural analysis highlighted that CAM severely impedes the formation of the central protuberance (CP), H89, and H58 during 50S ribosomal subunit maturation. The ELISA assay further demonstrated the direct binding of CAM to the ribosomal precursors, suggesting that the interference with 50S maturation occurs through a combination of direct and indirect mechanisms. These findings provide new insights into the mechanism of the action of CAM and provide a foundation for a better understanding of the assembly landscapes of the ribosome. Full article

This study introduces an innovative approach for the reconstruction of wind turbine tower states using a tangential recursion algorithm. The primary objective is to enable real-time monitoring of the operational condition of wind turbine towers. The proposed method is rooted in strain–load theory, which enables the accurate identification of tower load states. The tangential recursion algorithm is utilized to translate the strain data acquired from strategically placed sensors into reconstructed point positions. The subsequent refinement of these positions incorporates considerations of torsional loads and geometric deformations, culminating in the comprehensive and precise reconstruction of the tower’s deformation behavior. Through the use of the OpenFAST V8 simulation software, a thorough analysis is conducted to investigate the load and deformation characteristics of the NREL 5 MW wind turbine tower across diverse operational scenarios. Furthermore, the load conditions corresponding to rated operating circumstances are applied to a finite element model constructed with the lumped mass method. The identification of tower load states and the comprehensive reconstruction of deformation patterns are realized through the extraction of strain data from critical points in the finite element model. The credibility and accuracy of the proposed method are rigorously evaluated by juxtaposing the identification and reconstruction outcomes with the results derived from the OpenFAST simulations and finite element analyses. Notably, the proposed method circumvents the requirement for external auxiliary calibration equipment for the tower, rendering it adaptable to a broader spectrum of operational contexts and making it consistent with unfolding trajectories in wind power advancement. Full article

A comprehensive understanding of the linear/nonlinear dynamic behavior of wireless microresonators is essential for micro-electromechanical systems (MEMS) design optimization. This study investigates the dynamic behaviour of a magnetoelectric (ME) microresonator, using a finite element method (FEM) and machine learning algorithm. First, the linear/nonlinear behaviour of a fabricated thin-film ME microactuator is assessed in both the time domain and frequency spectrum. Next, a data driven system identification (DDSI) procedure and simulated annealing (SA) method are implemented to reconstruct differential equations from measured datasets. The Duffing equation is employed to replicate the dynamic behavior of the ME microactuator. The Duffing coefficients such as mass, stiffness, damping, force amplitude, and excitation frequency are considered as input parameters. Meanwhile, the microactuator displacement is taken as the output parameter, which is measured experimentally via a laser Doppler vibrometer (LDV) device. To determine the optimal range and step size for input parameters, the sensitivity analysis is conducted using Latin hypercube sampling (LHS). The peak index matching (PIM) and correlation coefficient (CC) are considered assessment criteria for the objective function. The data-driven developed models are subsequently employed to reconstruct/predict mode shapes and the vibration amplitude over the time domain. The effect of driving signal nonlinearity and total harmonic distortion (THD) is explored experimentally under resonance and sub-resonance conditions. The vibration measurements reveal that as excitation levels increase, hysteresis variations become more noticeable, which may result in a higher prediction error in the Duffing array model. The verification test indicates that the first bending mode reconstructs reasonably with a prediction accuracy of about 92 percent. This proof-of-concept study demonstrates that the simulated annealing approach is a promising tool for modeling the dynamic behavior of MEMS systems, making it a strong candidate for real-world applications. Full article

Alkylresorcinols (ARs) are polyphenolic compounds with a wide spectrum of biological activities and are potentially involved in the regulation of host metabolism. The present study aims to establish whether ARs can be produced by the human gut microbiota and to evaluate alterations in content in stool samples as well as metabolic activity of the gut microbiota of C57BL, db/db, and LDLR (−/−) mice according to diet specifications and olivetol (5-n-pentylresorcinol) supplementation to estimate the regulatory potential of ARs. Gas chromatography with mass spectrometric detection was used to quantitatively analyse AR levels in mouse stool samples; faecal microbiota transplantation (FMT) from human donors to germ-free mice was performed to determine whether the intestinal microbiota could produce AR molecules; metagenome sequencing analysis of the mouse gut microbiota followed by reconstruction of its metabolic activity was performed to investigate olivetol’s regulatory potential. A significant increase in the amounts of individual members of AR homologues in stool samples was revealed 14 days after FMT. Supplementation of 5-n-Pentylresorcinol to a regular diet influences the amounts of several ARs in the stool of C57BL/6 and LDLR (−/−) but not db/db mice, and caused a significant change in the predicted metabolic activity of the intestinal microbiota of C57BL/6 and LDLR (−/−) but not db/db mice. For the first time, we have shown that several ARs can be produced by the intestinal microbiota. Taking into account the dependence of AR levels in the gut on olivetol supplementation and microbiota metabolic activity, AR can be assumed to be potential quorum-sensing molecules, which also influence gut microbiota composition and host metabolism. Full article

Although data-independent acquisition (DIA) has the ability to identify and quantify all peptides in a sample, highly complex mixed mass spectra present difficulties for accurate peptide and protein identification. Additionally, the correspondence between the precursor and its fragments is broken, making it challenging to perform peptide identification directly using conventional DDA search engines. In this paper, we propose a cosine-similarity-based deconvolution method: CorrDIA. This is achieved by reconstructing the correspondence between precursor and fragment ions based on the consistency of extracted ion chromatograms (XICs). A deisotope peak cluster operation is added and centered on the MS/MS spectrum to improve the accuracy of spectrum interpretation and increase the number of identified peptides. The resulting MS/MS spectra can be identified using any data-dependent acquisition (DDA) sequencing software. The experimental results demonstrate that the number of peptide results increased by 12 percent and 21 percent respectively, and the repetition rate decreased by 12 percent. This reduces mass spectra complexity and difficulties in mass spectra analysis without the need for any mass spectra libraries. Full article

Roughness of rock fractured surfaces is one of the most important factors controlling fluid flow in rock masses. Roughness quantification is of prime importance for modelling the flow of ground waters as well as reservoir fluid mechanics. In this study, with the aid of high-resolution 3D X-ray CT scanning and image processing techniques, the roughness of four different rock types is reconstructed with a resolution of 16.5 microns. Moreover, the correlation and structure functions are used to analyse height fluctuations as well as statistical intermittency of the studied rock fractured surfaces. It is observed that at length scales smaller than a critical length scale, fractures surfaces are correlated and show multifractality. Monofractals are neither intermittent nor correlated; hence, a meaningful link between statistical intermittency and the correlation function of multifractals is expected. However, a model that considers this relationship and predicts multifractal spectra of disordered systems is still missing. A simple power law that can exactly forecast the multiscaling spectrum of rock fracture process zone is being introduced. It is explained how the exponent of this power function λ_i is related to the crossover length of correlation function ξ, and how this critical length scale can be objectively identified. Full article

A patient with oral squamous cell carcinoma (OSCC) underwent complex surgical tumor therapy, including the reconstruction of soft tissues using a radial forearm flap. Due to venous congestion that could only partly be resolved by revision surgery, leech therapy was started on the second postoperative day. The patient developed pneumonia and sepsis and died as a result of septic shock, despite having received targeted broad-spectrum antibiotic therapy since day 5. Aeromonas spp. were cultured from both the patient’s specimens and unused leeches. Biochemical identification and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) yielded inconsistent identification results. Finally, microbiological identification of Aeromonas spp. was performed via 16S rDNA sequencing and use of the basic local alignment search tool (BLAST), and strains from both the patient and the leeches were identified as Aeromonas veronii. Aeromonas spp. strains derived from the patient and leeches and independent laboratory strains were submitted to randomly amplified polymorphic DNA (RAPD) subtyping. RAPD of A. veronii strains from both sources revealed an identical pattern, strongly suggesting the transmission of A. veronii from the leeches to the patient. Physicians should be aware of the potential for severe lethal infections as a fatal side-effect of leech therapy in critically ill patients, which should be addressed using antibiotic prophylaxis. Full article

The computational spectrometer has significant potential for portable in situ applications. Encoding and reconstruction are the most critical technical procedures. In encoding, the random mass production and selection method lacks quantitative designs which leads to low encoding efficiency. In reconstruction, traditional spectrum reconstruction algorithms such as matching tracking and gradient descent demonstrate disadvantages like limited accuracy and efficiency. In this paper, we propose a new lightweight convolutional neural network called the wide-spectrum encoding and reconstruction neural network (WER-Net), which includes optical filters, quantitative spectral transmittance encoding, and fast spectral reconstruction of the encoded spectral information. The spectral transmittance curve obtained by WER-net can be fabricated through the inverse design network. The spectrometer developed based on WER-net experimentally demonstrates that it can achieve a 2-nm high resolution. In addition, the spectral transmittance encoding curve trained by WER-Net has also achieved good performance in other spectral reconstruction algorithms. Full article

The application potential of Pt/Ti₄O₇ has been reported, but the lack of research on the relationship between Pt loading, MSI, and catalytic activity hinders further development. Micron-sized Ti₄O₇ powders synthesized by a thermal reduction method under an H₂ atmosphere were used as a support material for Pt-based catalysts. Using a modified polyol method, Pt/Ti₄O₇-5, Pt/Ti₄O₇-10, and Pt/Ti₄O₇-20 with different mass ratios (Pt to Pt/Ti₄O₇ is 0.05, 0.1, 0.2) were successfully synthesized. Uniformly dispersed platinum nanoparticles exhibit disparate morphologies, rod-like for Pt/Ti₄O₇-5 and approximately spherical for Pt/Ti₄O₇-10 and Pt/Ti₄O₇-20. Small-angle deflections and lattice reconstruction induced by strong metal–support interactions were observed in Pt/Ti₄O₇-5, which indicated the formation of a new phase at the interface. However, lattice distortions and dislocations for higher loading samples imply the existence of weak metal–support interactions. A possible mechanism is proposed to explain the different morphologies and varying metal–support interactions (MSI). With X-ray photoelectron spectroscopy, spectrums of Pt and Ti display apparent shifts in binding energy compared with commercial Pt-C and non-platinized Ti₄O₇, which can properly explain the changes in absorption ability and oxygen reduction reaction activity, as described in the electrochemical results. The synthetic method, Pt loading, and surface coverage of the support play an important role in the adjustment of MSI, which gives significant guidance for better utilizing MSI to prepare the target catalyst. Full article

Cosmic rays represent one of the most important energy transformation processes of the universe. They bring information about the surrounding universe, our galaxy, and very probably also the extragalactic space, at least at the highest observed energies. More than one century after their discovery, we have no definitive models yet about the origin, acceleration and propagation processes of the radiation. The main reason is that there are still significant discrepancies among the results obtained by different experiments located at ground level, probably due to unknown systematic uncertainties affecting the measurements. In this document, we will focus on the detection of galactic cosmic rays from ground with air shower arrays up to 10${}^{18}$ eV. The aim of this paper is to discuss the conflicting results in the 10${}^{15}$ eV energy range and the perspectives to clarify the origin of the so-called ‘knee’ in the all-particle energy spectrum, crucial to give a solid basis for models up to the end of the cosmic ray spectrum. We will provide elements useful to understand the basic techniques used in reconstructing primary particle characteristics (energy, mass, and arrival direction) from the ground, and to show why indirect measurements are difficult and results are still conflicting. Full article

In ultra-high vacuum systems, obtaining the composition of a mass spectrum is often a challenging task due to the highly overlapping nature of the individual profiles of the gas species that contribute to that spectrum, as well as the high differences in terms of degree of contribution (several orders of magnitude). This problem is even more complex when not only the presence but also a quantitative estimation of the contribution (partial pressure) of each species is required. This paper aims at estimating the relative contribution of each species in a target mass spectrum by combining a state-of-the-art machine learning method (multilabel classifier) to obtain a pool of candidate species based on a threshold applied to the probability scores given by the classifier with a genetic algorithm that aims at finding the partial pressure at which each one of the species contributes to the target mass spectrum. For this purpose, we use a dataset of synthetically generated samples. We explore different acceptance thresholds for the generation of initial populations, and we establish comparative metrics against the most novel method to date for automatically obtaining partial pressure contributions. Our results show a clear advantage in terms of the integral error metric (up to 112 times lower for simpler spectra) and computational times (up to 4 times lower for complex spectra) in favor of the proposed method, which is considered a substantial improvement for this task. Full article

This study numerically investigates the beneficial effects of positive pre-swirl on the aerodynamic performance and internal flow field in a centrifugal compressor stage with variable inlet guide vanes (VIGVs) at low mass flow rates. Four positions of VIGV are considered, including 0°, 30°, 45°, and 60° angle. The latter three positions of VIGV induce positive pre-swirl. Numerical results show that as positive pre-swirl increases, the aerodynamic performance curve of the stage moves in the low mass flow rate direction. In the three cases of positive pre-swirl, there was an improvement of approximately 9.95% of stall/surge margin greater than in conditions with no pre-swirl. The regulation of IGV can effectively improve the unstable flow of the compressor stage at low mass flow rates. A low frequency that has a great influence on the internal flow of the compressor stage is found, and the unstable flow caused by low frequency is analyzed by the combination of streamline distribution, spectrum analysis, vector, entropy increase, and modal decomposition method. Meanwhile, the modal decomposition method and flow field reconstruction techniques are used to investigate the coherent flow structures caused by low frequency under different guide vane openings. Full article

Dynamic analysis of a combination of misaligned rotors, the disturbance of the Cardan joint and the rotor–stator rubbing within a restricted clearance space in a viscous fluid is complex and can result in persistent vibration anomalies that are often misunderstood. It becomes increasingly important to gain some insights into how the transmission of coupled motion responds dynamically under a variety of conditions. This paper introduces an efficient simulation of the misaligned multi-degree-of-freedom rotor’s model, which was developed to predict the transient dynamic behaviours of a driveshaft deflection. The model accounts for tight clearance as a function of contact deformation according to nonlinear Hertzian contact theory. The paper also examines recent research by considering the influence of parameters such as eccentric masses, applied torques and flexible coupling joint perturbation introduced in the proposed rotor system. The simulation results indicated that the viscous fluid surrounding the driveshaft had sufficient torsional flexibility to dampen the rubbing impact to the driven shaft displacement. In addition, the torsional fluctuations of the flexible coupling abruptly increased, and then significantly impacted the vibration of the submerged driveshaft. Parametric studies involving the interconnected rotor models indicated that the effects of fluid on a close-bounds contact area can create partial disturbance reduction. The high rubbing contact is shown to be lost through the Hooke’s joints during power transmission. The speed-frequency spectrum maps provide valuable information on all the modelled excitations over the frequency of the twice-running speed resonance in a viscous medium. Further, nonlinear characteristics are reconstructed through orbit shapes and can be adopted in the condition monitoring of rotors in engineering practice. Full article