Fast Method Research Articles

AIUPred: combining energy estimation with deep learning for the enhanced prediction of protein disorder.

Intrinsically disordered proteins and protein regions (IDPs/IDRs) carry out important biological functions without relying on a single well-defined conformation. As these proteins are a challenge to study experimentally, computational methods play important roles in their characterization. One of the commonly used tools is the IUPred web server which provides prediction of disordered regions and their binding sites. IUPred is rooted in a simple biophysical model and uses a limited number of parameters largely derived on globular protein structures only. This enabled an incredibly fast and robust prediction method, however, its limitations have also become apparent in light of recent breakthrough methods using deep learning techniques. Here, we present AIUPred, a novel version of IUPred which incorporates deep learning techniques into the energy estimation framework. It achieves improved performance while keeping the robustness of the original method. Based on the evaluation of recent benchmark datasets, AIUPred scored amongst the top three single sequence based methods. With a new web server we offer fast and reliable visual analysis for users as well as options to analyze whole genomes in mere seconds with the downloadable package. AIUPred is available at https://aiupred.elte.hu.

A fast scene geometric modeling approach for digital twins combining neural rendering and model retrieval

ABSTRACT Digital twin technology is a crucial driving technology for the realization of Industry 4.0, which enables simulation, analysis, and prediction by constructing geometric scenes that correspond to physical scenes. Current automation in scene modeling is limited, relying heavily on costly and inefficient manual operations. This hinders digital twin technology progress. This paper proposes a framework for a fast scene geometric modeling method that combines neural rendering and model retrieval for digital twins. Neural rendering techniques first train the collected image data, and the point cloud data of physical entities are rendered. Then based on the semantic mapping algorithm between the point cloud data of physical entities and the multi-view image data of 3D CAD models proposed in this study, the corresponding geometric models are retrieved from the geometric asset library by inputting the point cloud data, and all the retrieved geometric models are embedded in the geometric scene to complete the scene geometric modeling. Finally, in a case study of the digital twin-based scene construction for decommissioned lithium battery dismantling, the effectiveness of this method is demonstrated, which can improve the speed and reduce the cost of scene geometric modeling.

A Simple Tube Escape Assay to Test Learning and Memory in Zebrafish with Minimized Habituation.

Various methods have been used in rodents to evaluate learning and memory. Although much less frequently used, the zebrafish emerges as an alternative model organism in this context. For example, it allows assessing potential behavioral deficits because of neurodevelopmental disorders or environmental neurotoxins. A variety of learning tasks have been employed in previous studies that required extensive habituation and training sessions. Here, we introduce a simpler and faster method to evaluate learning and memory of zebrafish with minimum habituation. A new apparatus, a transparent L-shaped tube, was developed in which we trained each zebrafish to swim through a long arm and measured the time to swim through this arm. We demonstrate that in this task, zebrafish could acquire both short-term (1 h) and long-term memory (4 days). We also studied learning and memory of a gene knockout (KO) zebrafish that showed social impairments related to autism. We found KO mutant zebrafish to show a quantitative impairment in habituation, learning, and memory performance compared with wild-type control fish. In conclusion, we established a novel learning apparatus and sensitive paradigm that allowed us to evaluate learning and memory of adult zebrafish that required only a brief habituation period and minimal training.

Tabu search based on novel neighborhood structures for solving job shop scheduling problem integrating finite transportation resources

As advancements in transportation equipment intelligence continue, the job shop scheduling problem integrating finite transportation resources (JSPIFTR) has attracted considerable attention. Within the domain of shop scheduling, the neighborhood structure serves as a cornerstone for enabling intelligent optimization algorithms to effectively navigate and discover optimal solutions. However, current algorithms for JSPIFTR rely on generalized neighborhood structures, which incorporate operators like insertion and swap. While these structures are tailored to the encoding vectors, their utilization often leads to suboptimal optimization efficacy. To address this limitation, this paper introduces novel neighborhood structures specifically designed to the distinctive properties of JSPIFTR. These innovative structures leverage the intrinsic structural information in integrated scheduling, thereby enhancing the optimization effectiveness of the algorithm. Firstly, two theorems are presented to demonstrate the feasibility of the neighborhood solution. Secondly, different neighborhood structures for critical transportation and processing tasks are subsequently designed based on the analysis of the problem properties and constraints. Thirdly, an efficient fast evaluation method is developed to expediently calculate the objective value of the neighborhood solution. Finally, the novel neighborhood structures are combined with the tabu search (TS_NNS) and compared with other state-of-the-art methods on EX and NEX benchmarks. The comparative results demonstrate the remarkable performance of the neighborhood structure, with the TS_NNS enhancing the best solutions across 23 instances.

Tomographic cross correlations between galaxy surveys and the CMB gravitational lensing potential. Effect of the redshift bin mismatch

Upcoming surveys of the large-scale structure of our Universe will employ a large coverage area of about half of the sky and will significantly increase the observational depth. With these surveys, we will be able to cross-correlate cosmic microwave background (CMB) gravitational lensing and galaxy surveys divided into narrow redshift bins to map the evolution of the cosmological parameters with redshift. We study the effect of the redshift bin mismatch of objects that is due to photometric redshift errors in tomographic cross-correlation measurements. We used the code FLASK to create Monte Carlo simulations of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) and Planck CMB lensing convergence. We simulated log-normal fields and divided galaxies into nine redshift bins with the Gaussian and modified Lorentzian photometric redshift errors. To estimate the parameters, we used angular power spectra of CMB lensing and galaxy density contrast fields and the maximum likelihood estimation method. We show that even with simple Gaussian errors with a standard deviation of $ the galaxy auto-power spectra in tomographic bins are offset by $2-15<!PCT!>$. The estimated cross-power spectra between galaxy clustering and CMB lensing are also biased, with smaller deviations $<5<!PCT!>$. As a result, the $ $ parameter deviates between $0.2-1.2\ due to the redshift bin mismatch of the objects. We propose a computationally fast and robust method based on the scattering matrix approach to correct for the redshift bin mismatch of the objects. The estimates of the parameters in tomographic studies such as the linear galaxy bias, the cross-correlation amplitude, and $ $ are biased due to the redshift bin mismatch of the objects. The biases in these parameters are alleviated with our scattering matrix approach.

A Fast and Sensitive One-Tube SARS-CoV-2 Detection Platform Based on RTX-PCR and Pyrococcus furiosus Argonaute

Since SARS-CoV-2 is a highly transmissible virus, alternative reliable, fast, and cost-effective methods are still needed to prevent virus spread that can be applied in the laboratory and for point-of-care testing. Reverse transcription real-time fluorescence quantitative PCR (RT-qPCR) is currently the gold criteria for detecting RNA viruses, which requires reverse transcriptase to reverse transcribe viral RNA into cDNA, and fluorescence quantitative PCR detection was subsequently performed. The frequently used reverse transcriptase is thermolabile; the detection process is composed of two steps: the reverse transcription reaction at a relatively low temperature, and the qPCR performed at a relatively high temperature, moreover, the RNA to be detected needs to pretreated if they had advanced structure. Here, we develop a fast and sensitive one-tube SARS-CoV-2 detection platform based on Ultra-fast RTX-PCR and Pyrococcus furiosus Argonaute-mediated Nucleic acid Detection (PAND) technology (URPAND). URPAND was achieved ultra-fast RTX-PCR process based on a thermostable RTX (exo-) with both reverse transcriptase and DNA polymerase activity. The URPAND can be completed RT-PCR and PAND to detect nucleic acid in one tube within 30 min. This method can specifically detect SARS-CoV-2 with a low detection limit of 100 copies/mL. The diagnostic results of clinical samples with one-tube URPAND displayed 100% consistence with RT-qPCR test. Moreover, URPAND was also applied to identify SARS-CoV-2 D614G mutant due to its single-nucleotide specificity. The URPAND platform is rapid, accurate, tube closed, one-tube, easy-to-operate and free of large instruments, which provides a new strategy to the detection of SARS-CoV-2 and other RNA viruses.

Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm.

Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively. The proposed method can also be used along with Orbitrap mass spectrometers that have faster MS/MS acquisition rates, like the recently released Orbitrap Astral mass spectrometer, to further reduce the mass spectrometer time required per sample.

Development of the discrete vortex method in combination with the fast multipole method in hydrodynamic problems

Development of the discrete vortex method in combination with the fast multipole method in hydrodynamic problems

The use of a portable X-ray fluorescence spectrometer for measuring nickel in plants: sample preparation and validation.

X-ray fluorescence is a fast, cost-effective, and eco-friendly method for elemental analyses. Portable X-ray fluorescence spectrometers (pXRF) have proven instrumental in detecting metals across diverse matrices, including plants. However, sample preparation and measurement procedures need to be standardized for each instrument. This study examined sample preparation methods and predictive capabilities for nickel (Ni) concentrations in various plants using pXRF, employing empirical calibration based on inductively coupled plasma optical emission spectroscopy (ICP-OES) Ni data. The evaluation involved 300 plant samples of 14 species with variable of Ni accumulation. Various dwell times (30, 60, 90, 120, 300s) and sample masses (0.5, 1.0, 1.5, 2.0g) were tested. Calibration models were developed through empirical and correction factor approaches. The results showed that the use of 1.0g of sample (0.14gcm-2) and a dwell time of 60s for the study conditions were appropriate for detection by pXRF. Ni concentrations determined by ICP-OES were highly correlated (R2 = 0.94) with those measured by the pXRF instrument. Therefore, pXRF can provide reliable detection of Ni in plant samples, avoiding the digestion of samples and reducing the decision-making time in environmental management.

Recombinase polymerase amplification: method’s characteristics and applications in diagnostics of infectious diseases

Isothermal amplification techniques have been actively developed in recent years and are gradually introduced into the range of methods for infectious disease diagnostics. One of the fastest isothermal methods is recombinase polymerase amplification (RPA). This review contains information about the principle of RPA, the role of individual reaction components and primer design considerations. It provides information on characteristics of various methods of RPA results detection, effects of inhibitors, temperature and agitation on the efficiency of reaction. Approaches to quantitative and multiplex RPA are described, as well as some variants of portable devices designed to identify infectious agents. The conclusion summarizes advantages and disadvantages of RPA in comparison with other amplification methods.

Combined nomograms for calculating the bearing capacity and reinforcement of high-strength and normal concrete RC columns

PurposeThis paper aims to obtain a calculation method by hand without iteration.Design/methodology/approachThis paper adopts strains as known quantities to solve the internal forces and deformations of the section, simplifies the deflection curve of the column and obtains nomograms that can calculate the bearing capacity and reinforcement of circular reinforced concrete (RC) columns by hand.FindingsNomograms include five variables: mechanical reinforcement ratio, relative normal force, dimensionless bending moment, slenderness ratio and ultimate dimensionless curvature. Nomograms corresponding to all classes of concrete have been drawn, and their dimensionless form makes them widely applicable. The calculation results of nomograms are compared and analysed with numerical calculation results, and the difference is within 5%, meeting the engineering requirements.Originality/valueCalculating the bearing capacity of compression bending components requires considering second-order effects. Therefore, the calculation of the bearing capacity of circular RC columns requires iterative calculation, as it includes dual nonlinearity of material and geometry, and the two are coupled with each other. To calculate the bearing capacity of the section adopting ordinary concrete, it is necessary to solve the transcendental equation iteratively. For high-strength concrete, it can only be solved by numerical integration. A fast calculation method by hand is proposed in this paper.

A New Fast Estimation Method for Critical Pressure and Critical Temperature of Binary Mixture Based on the Modified Redlich–Kister Method

A New Fast Estimation Method for Critical Pressure and Critical Temperature of Binary Mixture Based on the Modified Redlich–Kister Method

Fast and High-Resolution T2 Mapping Based on Echo Merging Plus k-t Undersampling with Reduced Refocusing Flip Angles (TEMPURA) as Methods for Human Renal MRI.

To develop a highly accelerated multi-echo spin-echo method, TEMPURA, for reducing the acquisition time and/or increasing spatial resolution for kidney T2 mapping. TEMPURA merges several adjacent echoes into one k-space by either combining independent echoes or sharing one echo between k-spaces. The combined k-space is reconstructed based on compressed sensing theory. Reduced flip angles are used for the refocusing pulses, and the extended phase graph algorithm is used to correct the effects of indirect echoes. Two sequences were developed: a fast breath-hold sequence; and a high-resolution sequence. The performance was evaluated prospectively on a phantom, 16 healthy subjects, and two patients with different types of renal tumors. The fast TEMPURA method reduced the acquisition time from 3-5 min to one breath-hold (18 s). Phantom measurements showed that fast TEMPURA had a mean absolute percentage error (MAPE) of 8.2%, which was comparable to a standardized respiratory-triggered sequence (7.4%), but much lower than a sequence accelerated by purely k-t undersampling (21.8%). High-resolution TEMPURA reduced the in-plane voxel size from 3 × 3 to 1 × 1 mm2, resulting in improved visualization of the detailed anatomical structure. In vivo T2 measurements demonstrated good agreement (fast: MAPE = 1.3%-2.5%; high-resolution: MAPE = 2.8%-3.3%) and high correlation coefficients (fast: R = 0.85-0.98; high-resolution: 0.82-0.96) with the standardized method, outperforming k-t undersampling alone (MAPE = 3.3-4.5%, R = 0.57-0.59). TEMPURA provides fast and high-resolution renal T2 measurements. It has the potential to improve clinical throughput and delineate intratumoral heterogeneity and tissue habitats at unprecedented spatial resolution.

Rapid and simultaneous determination of curcuminoids and gingerols in food products containing turmeric and ginger using paper spray mass spectrometry.

Turmeric and ginger are extensively employed as functional ingredients due to their high content of curcuminoids and gingerols, considered the key bioactive compounds found in these roots. In this study, we present an innovative and fast method for the assay of curcuminoids and gingerols in different foods containing the two spices, with the aim of monitoring the quality of products from a nutraceutical perspective. The proposed approach is based on paper spray tandem mass spectrometry coupled with the use of a labeled internal standard, which has permitted to achieve the best results in terms of specificity and accuracy. All the calculated analytical parameters were satisfactory; accuracy values are around 100% for all spiked samples and the precision data result lower than 15%. The protocol was applied to several real samples, and to demonstrate its robustness and reliability, the results were compared to those arising from the common liquid chromatographic method.

Experimental investigation on seismic behavior of damaged self-centering friction beam-column joints after repair

Self-centering beam-column joints are an effective strategy to improve the seismic resilience of frame structures. Extensive research has been conducted on the seismic performance of newly constructed self-centering joints, involving experiments, theoretical analyses, and simulations. Nevertheless, less attention has been paid to evaluating the seismic resilience of self-centering joints after repair. To address this gap, this paper presents a series of experiments to investigate the mechanical properties of damaged self-centering friction beam-column joints (SCFJ) after repair. Three SCFJs damaged by cyclic loading are repaired using epoxy injection, CFRP wrapping, and replacement concrete. The repaired joints are then subjected to cyclic loading under the same conditions as the original loading. A comprehensive analysis is conducted of the hysteretic curve, skeleton curve, energy dissipation, stiffness degradation, and residual displacement of both the original and repaired SCFJs. The results show that the repaired SCFJs maintain their commendable self-centering capacity. Specifically, the replacement concrete method is the most effective in restoring the initial seismic performance of the SCFJs. The epoxy injection method is the fastest repair method and successfully restore the SCFJ to approximately its original ultimate strength and approximately 85% of its energy dissipation and self-centering capacity. The CFRP wrapping method is able to largely restore the self-centering capacity of the SCFJ to its original level, but with a notable decrease in stiffness.

A fast, reliable, low‐cost, and efficient xylan extraction for xylooligosaccharides production

AbstractA fast, reliable, low‐cost, and efficient method for the recovery of xylan from agro‐residue materials is needed to improve the use of xylan in industrial processes. Xylan was extracted from two agrowastes (corncobs and wheat bran) using a cost‐effective alkali extraction method. The characteristic band patterns and bending vibrations associated with hemicellulose and beta glycoside linkage could be seen in the corncob‐extracted xylan (CCEx) and wheatbran‐extracted xylan (WBEx). Scanning electron microscopy (SEM) analysis showed that the extracted xylans consisted of aggregated and nonaggregated particles with irregular morphology and rough surfaces. Particle‐size analysis displayed average sizes of 205.6, 210.8, and 794.2 nm for commercial beechwood xylan (Bx), CCEx, and WBEx, respectively. Alkali extraction was performed with different concentrations of NaOH, from 5% to 20%, with a solid–liquid ratio of 1:20. It was found that 82.90 and 76.77% of xylan were extracted from corncob and wheat bran, respectively, which represents a higher yield obtained in a shorter duration in comparison with studies in the literature. The enzymatic hydrolysis of wheat bran and corncob that used 250 IU/mL of Enterobacter hormaechie KS1 xylanase yielded 334.38 and 162.35 mg/g of xylooligosaccharides. Their properties were studied and were found to be very similar to those of commercial xylan. They could reduce costs if applied in industry.

High-resolution frequency domain decomposition for modal analysis of bridges using train-induced free-vibrations

Modal parameters are structural inherent characteristics that can be applied for revealing performance of railway bridges. Free vibration signals generated by a passage of train are commonly utilized to estimate the modal parameters of railway bridges due to their higher signal-to-noise ratios compared to random vibrations caused by ambient loads. However, since free vibration signals rapidly decay over time, the available free-vibration data is typically short-time. When using the fast Fourier transform-based spectral estimation method for modal identification from short-time vibration data, a phenomenon known as spectral leakage occurs, leading to miss-identification of some structural modes. In this study, the classical frequency domain decomposition (FDD) is improved for modal identification of railway bridges, in which the higher resolution auto-power spectral density (PSD) and cross-PSD functions are calculated through the autoregressive (AR) model-based method. The AR model-based method improves both the smoothness and resolution of the PSD functions compared to the fast Fourier transform technique. These AR model-based PSD functions are then employed in the FDD process to facilitate frequency and mode shape identification while avoiding spurious noise modes. The proposed eigenvalue fitting technique is subsequently utilized to estimate damping ratios. Numerical simulation data as well as vibration data from an actual bridge are analyzed to validate the proposed method, with a comparison made to the Welch’s PSD-based method. The results demonstrate that the modified FDD approach enables more effective identification of structural modes, even in the presence of closely-spaced modes.

Voltage Error Estimation-Based Fault Diagnosis Method for Three- phase PWM-inverter in Grid-connected Photovoltaic Power System Without any Over-rating

Inverter is an essential component of a grid connected PV system. In fact, an open-switch fault in this power converter could result an important system malfunction and consequently leads to system disconnection. In this context, this paper focuses on the fault-tolerant control of PWM-inverter with redundancy leg for grid-connected PV system. In addition, a fast method of fault detection and compensation is used to maintain the continuous operation of the converter when there is a half-leg open-circuit fault (IGBT+ anti-parallel diode) on one of PWM-inverter legs. Therefore, it can detect this type of fault and compensate it in less than 50 μs by using a time criterion instead of voltage criterion. Also, the fuzzy logic technique is employed to control the active and reactive power injected into the network without exceeding the whole system power capacity limits. Note that, in this study, the active and reactive power references of the chosen operating point (the reactive-to-active power ratio: tgφ = Q/P = 0.19) are based on experimental tests. Simulation results show the feasibility and the effectiveness of the proposed fault diagnosis method in terms of fault detection and service continuity in presence of a half-leg open-circuit fault in PWM-inverter without any over-rating of the PV system components or instability.

A fast solution method for the interaction between the rigid overhead contact system and pantograph on long railway lines

Currently, simulation is an important method for studying the interaction between the pantograph and the rigid overhead contact system (ROCS). However, when solving the ROCS model for long railway line scenarios, the problem of intractable or inefficient computation arises due to the excessively large size of the matrix. To address this issue, this paper proposes a method called: a fast solution method for the interaction between the rigid overhead contact system and pantograph on long railway lines based on a coupled window approach (hereinafter referred to as: CW-RCP). The CW-RCP method utilises coupled windows to simulate the ROCS model, effectively limiting the length of the ROCS involved in each computation. This approach greatly enhances computational efficiency. After deriving the dynamic equations and solving equations of the CW-RCP method in detail, the effectiveness, advantages, and applications of this method are discussed. The results demonstrate that the CW-RCP method can effectively compensate for the computational inefficiencies of traditional methods without compromising computational accuracy.

Total and Class-Specific Determination of Fluorinated Compounds in Consumer and Food Packaging Samples Using Fluorine-19 Solid-State Nuclear Magnetic Resonance Spectroscopy.

Hamburger wrapping paper, coated with water-based barrier coatings, used in the food packaging industry was studied by using the total organic fluorine (TOF) method based on combustion ion chromatography and fluorine-19 solid-state nuclear magnetic resonance (19F ss-NMR) spectroscopy. Although the TOF method is a fast and affordable method used to screen for per- and polyfluoroalkyl substances (PFAS), the amount of fluorine it measures is heavily dependent on the extraction step and, therefore could lead to inaccurate results. Fluorine-19 ss-NMR spectroscopy can differentiate between organic and inorganic fluorinated sources, eliminating the need for sample clean up. To illustrate this, the 19F ss-NMR spectra of clean coated paper samples that contained naturally occurring F- ions from the talc raw material and spiked samples containing perfluorooctanoic acid were compared. A range of experimental conditions was explored to improve sensitivity for low PFAS concentrations (in the order of 10-20 mg/kg). Despite the disadvantages of ss-NMR spectroscopy, such as the low limit of detection and resolution, the results demonstrate it can be a viable tool to directly detect PFAS moieties in consumer and food packaging. Therefore, 19F solid-state NMR spectroscopy challenges and complements current methods, which only provide indirect evidence of the presence of PFAS.