Accurate Calculation Method Research Articles

Direct cubic B-spline interpolation: A fuzzy interpolating method for weightless, robust and accurate DVC computation

Authentic interpolation, by which the interpolated curve exactly goes through the input data points, has always been adopted by digital volume/image correlation (DVC/DIC) methods. However, the heavy utilization of random-access memory (RAM) caused by authentic interpolation, especially in the case of DVC, remains unresolved until today. In order to realize weightless DVC, direct cubic B-spline interpolation, which is a fuzzy interpolating method simplified from the conventional cubic B-spline interpolation, and its implementation for DVC, are introduced in details. Both numerical and real experiments were conducted to verify the accuracy and robustness of the weightless DVC based on the direct cubic B-spline interpolation. Results show that the direct cubic B-spline interpolation has even better accuracy and robustness for weightless DVC compared to its conventional counterpart.

Protein-DNA interface hotspots prediction based on fusion features of embeddings of protein language model and handcrafted features

The identification of hotspot residues at the protein-DNA binding interfaces plays a crucial role in various aspects such as drug discovery and disease treatment. Although experimental methods such as alanine scanning mutagenesis have been developed to determine the hotspot residues on protein-DNA interfaces, they are both inefficient and costly. Therefore, it is highly necessary to develop efficient and accurate computational methods for predicting hotspot residues. Several computational methods have been developed, however, they are mainly based on hand-crafted features which may not be able to represent all the information of proteins. In this regard, we propose a model called PDH-EH, which utilizes fused features of embeddings extracted from a protein language model (PLM) and handcrafted features. After we extracted the total 1141 dimensional features, we used mRMR to select the optimal feature subset. Based on the optimal feature subset, several different learning algorithms such as Random Forest, Support Vector Machine, and XGBoost were used to build the models. The cross-validation results on the training dataset show that the model built by using Random Forest achieves the highest AUROC. Further evaluation on the independent test set shows that our model outperforms the existing state-of-the-art models. Moreover, the effectiveness and interpretability of embeddings extracted from PLM were demonstrated in our analysis. The codes and datasets used in this study are available at: https://github.com/lixiangli01/PDH-EH.

An Accurate Method for Calculation of Self-Inductance of HTS Coils With and Without Turn-to-Turn Insulation

An Accurate Method for Calculation of Self-Inductance of HTS Coils With and Without Turn-to-Turn Insulation

A fast analytical dose calculation approach for MRI-guided proton therapy.

Objective.Magnetic resonance (MR) is an innovative technology for online image guidance in conventional radiotherapy and is also starting to be considered for proton therapy as well. For MR-guided therapy, particularly for online plan adaptations, fast dose calculation is essential. Monte Carlo (MC) simulations, however, which are considered the gold standard for proton dose calculations, are very time-consuming. To address the need for an efficient dose calculation approach for MRI-guided proton therapy, we have developed a fast GPU-based modification of an analytical dose calculation algorithm incorporating beam deflections caused by magnetic fields.Approach.Proton beams (70-229 MeV) in orthogonal magnetic fields (0.5/1.5 T) were simulated using TOPAS-MC and central beam trajectories were extracted to generate look-up tables (LUTs) of incremental rotation angles as a function of water-equivalent depth. Beam trajectories are then reconstructed using these LUTs for the modified ray casting dose calculation. The algorithm was validated against MC in water, different materials and for four example patient cases, whereby it has also been fully incorporated into a treatment plan optimisation regime.Main results.Excellent agreement between analytical and MC dose distributions could be observed with sub-millimetre range deviations and differences in lateral shifts <2 mm even for high densities (1000 HU). 2%/2 mm gamma pass rates were comparable to the 0 T scenario and above 94.5% apart for the lung case. Further, comparable treatment plan quality could be achieved regardless of magnetic field strength.Significance.A new method for accurate and fast proton dose calculation in magnetic fields has been developed and successfully implemented for treatment plan optimisation.

A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing

Carcinoma of unknown primary (CUP) is a type of metastatic cancer with tissue-of-origin (TOO) unidentifiable by traditional methods. CUP patients typically have poor prognosis but therapy targeting the original cancer tissue can significantly improve patients’ prognosis. Thus, it’s critical to develop accurate computational methods to infer cancer TOO. While qPCR or microarray-based methods are effective in inferring TOO for most cancer types, the overall prediction accuracy is yet to be improved. In this study, we propose a cross-cohort computational framework to trace TOO of 32 cancer types based on RNA sequencing (RNA-seq). Specifically, we employed logistic regression models to select 80 genes for each cancer type to create a combined 1356-gene set, based on transcriptomic data from 9911 tissue samples covering the 32 cancer types with known TOO from the Cancer Genome Atlas (TCGA). The selected genes are enriched in both tissue-specific and tissue-general functions. The cross-validation accuracy of our framework reaches 97.50% across all cancer types. Furthermore, we tested the performance of our model on the TCGA metastatic dataset and International Cancer Genome Consortium (ICGC) dataset, achieving an accuracy of 91.09% and 82.67%, respectively, despite the differences in experiment procedures and pipelines. In conclusion, we developed an accurate yet robust computational framework for identifying TOO, which holds promise for clinical applications. Our code is available at http://github.com/wangbo00129/classifybysklearn.

Bond dissociation energies of the fifth‐row elements (InI): A quantum theoretical benchmark study

AbstractThe bond dissociation energies (BDE) of most main‐group elements have been accurately measured. However, the BDE values for heavy elements, particularly those from the fifth period (InI), are still missing or poorly validated. This study aims to identify the most accurate computational methods for calculating BDE values of compounds containing fifth‐row elements, including In, Sn, Sb, Te, and I, with a focus on readily accessible methods in software packages. The investigation involved a benchmark study using density functional theory (DFT), in addition to the 2nd order Møller–Plesset perturbation theory (MP2) and the coupled cluster with single, double, and perturbative triple excitations CCSD(T). The DFT functionals used in the study include APFD, B3LYP, B3LYP‐D3, B3P86, B97‐D3, BHandH, HSEH1PBE, M06‐2X, MN12‐SX, MN15‐L, and TPSSH. The functionals were carefully selected to cover some popular functionals as well as to cover all levels of the Jacob's ladder of DFT accuracy. The computed BDE values were compared with experimental values, and the results were filtered to remove any possible outliers. The statistical errors (MAPE, RMSE, and Pearson's) were then calculated and used to assess the performance of the methods.

Bioinformatic analysis of highly consumed phytochemicals as P-gp binders to overcome drug-resistance.

P-glycoprotein (P-gp) is an adenosine triphosphate (ATP)-dependent membrane efflux pump for protecting cells against xenobiotic compounds. Unfortunately, overexpressed P-gp in neoplastic cells prevents cell entry of numerous chemotherapeutic agents leading to multidrug resistance (MDR). MDR cells may be re-sensitized to chemotherapeutic drugs via P-gp inhibition/modulation. Side effects of synthetic P-gp inhibitors encouraged the development of natural products. Molecular docking and density functional theory (DFT) calculations were used as fast and accurate computational methods to explore a structure binding relationship of some dietary phytochemicals inside distinctive P-gp binding sites (modulatory/inhibitory). For this purpose, top-scored docked conformations were subjected to per-residue energy decomposition analysis in the B3LYP level of theory with a 6-31g (d, p) basis set by Gaussian98 package. Consecutive application of computational techniques revealed binding modes/affinities of nutritive phytochemicals within dominant binding sites of P-gp. Blind docking scores for best-ranked compounds were superior to verapamil and rhodamine-123. Pairwise amino acid decomposition of superior docked conformations revealed Tyr303 as an important P-gp binding residue. DFT-based induced polarization analysis revealed major electrostatic fluctuations at the atomistic level and confirmed larger effects for amino acids with energy-favored binding interactions. Conformational analysis exhibited that auraptene and 7,4',7'',4'''-tetra-O-methylamentoflavone might not necessarily interact to P-gp binding sites through minimum energy conformations. Although there are still many hurdles to overcome, obtained results may propose a few nutritive phytochemicals as potential P-gp binding agents. Moreover; top-scored derivatives may have the chance to exhibit tumor chemo-sensitizing effects.

A Novel Unit Classification Method for Fast and Accurate Calculation of Radiation Patterns

This paper proposes a novel unit classification technique to enhance the accuracy of the conventional pattern multiplication method by taking the mutual coupling effect and edge effect into consideration. The proposed technique classifies antenna elements into different groups based on their positions in arrays, specifically corner, edge, and inner groups. By simulating the radiation patterns of antenna elements with different boundary conditions, the pattern multiplication method is then used to calculate the radiation pattern of the antenna array based on the simulated results. Several numerical examples, including a square array, a hexagonal array, and a phased array, are provided to validate the effectiveness of the proposed method. The numerical results demonstrate that the proposed method not only reduces the computational time and memory usage but also significantly improves the accuracy. The proposed method provides a powerful tool for synthesizing and predicting the radiation pattern of array antennas and offers new avenues for optimizing array antennas and phased array antennas.

Improving One-Electron Exact-Two-Component Relativistic Methods with the Dirac-Coulomb-Breit-Parameterized Effective Spin-Orbit Coupling.

In photochemical processes, spin-orbit coupling plays a crucial role in determining the outcome of the reaction. However, the exact treatment of the Dirac-Coulomb-Breit two-electron operator required for rigorous inclusion of spin-orbit coupling is computationally prohibitive. To address this challenge, we present a Dirac-Coulomb-Breit-parameterized screened-nuclear spin-orbit factor to approximate two-electron spin-orbit couplings in the effective one-electron spin-orbit Hamiltonian. We propose two schemes, the universal and row-dependent parameterizations, to further improve the accuracy of the method. Benchmark calculations on both atomic and molecular systems are performed and compared to results from the computationally expensive four-component Dirac-Coulomb-Breit method. The Dirac-Coulomb-Breit-parameterized approach offers a more computationally feasible method for accurate spin-orbit coupling calculations.

An accurate calibration and calculation method of six-port circuit for microfluidic sensing application

An accurate calibration and calculation method of six-port circuit for microfluidic sensing application

Calculation of transportation resistance of different soils in Dredging Engineering

Pipeline transportation is a process of continuous balance between pumping pressure and pipeline resistance. Therefore, accurate calculation of pipeline transportation resistance can optimize the accuracy of the pump model and working parameters. The slurry transported in the dredging project is complicated, and the dredged soil in different regions is quite different resulting in different motion states in the transportation process. Different types of flow patterns are suitable for different resistance calculation models. In this paper, according to the actual dredger filling project, the real transmission resistance of the project is obtained by means of pipeline pressure monitoring data analysis. Three different transmission resistance calculation formulas of Wang Shaozhou formula, Durand formula and DHLLDV model are used to compare the clay, fine sand and medium coarse sand. The calculation results show that the Durand formula is the best for calculating the transmission resistance of medium coarse sand; the DHLLDV model is better for calculating the transport resistance of fine silt; the error between the DHLLDV model of clay transport resistance and Wang Shaozhou formula is small. In this paper, the calculation error analysis of three different kinds of soil is carried out, and the best calculation formula for three types of soil is obtained. The accurate calculation method of theoretical formula in dredging and filling projects is obtained, and the reference table of three kinds of soil for transportation resistance is proposed, which provides a reference for dredging project transportation.

Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning

The turnover number kcat, a measure of enzyme efficiency, is central to understanding cellular physiology and resource allocation. As experimental kcat estimates are unavailable for the vast majority of enzymatic reactions, the development of accurate computational prediction methods is highly desirable. However, existing machine learning models are limited to a single, well-studied organism, or they provide inaccurate predictions except for enzymes that are highly similar to proteins in the training set. Here, we present TurNuP, a general and organism-independent model that successfully predicts turnover numbers for natural reactions of wild-type enzymes. We constructed model inputs by representing complete chemical reactions through differential reaction fingerprints and by representing enzymes through a modified and re-trained Transformer Network model for protein sequences. TurNuP outperforms previous models and generalizes well even to enzymes that are not similar to proteins in the training set. Parameterizing metabolic models with TurNuP-predicted kcat values leads to improved proteome allocation predictions. To provide a powerful and convenient tool for the study of molecular biochemistry and physiology, we implemented a TurNuP web server.

Long-Range Perception System for Road Boundaries and Objects Detection in Trains

This article introduces a long-range sensing system based on millimeter-wave radar, which is used to detect the roadside boundaries and track trains for trains. Due to the high speed and long braking distance of trains, existing commercial vehicle sensing solutions cannot meet their needs for long-range target detection. To address this challenge, this study proposes a long-range perception system for detecting road boundaries and trains based on millimeter-wave radar. The system uses high-resolution, long-range millimeter-wave radar customized for the strong scattering environment of rail transit. First, we established a multipath scattering theory in complex scenes such as track tunnels and fences and used the azimuth scattering characteristics to eliminate false detections. A set of accurate calculation methods of the train’s ego-velocity is proposed, which divides the radar detection point clouds into static target point clouds and dynamic target point clouds based on the ego-velocity of the train. We then used the road boundary curvature, global geometric parallel information, and multi-frame information fusion to extract and fit the boundary in the static target point stably. Finally, we performed clustering and shape estimation on the radar track information to identify the train and judge the collision risk based on the position and speed of the detected train and the extracted boundary information. The paper makes a significant contribution by establishing a multipath scattering theory for complex scenes of rail transit to eliminate radar false detection and proposing a train speed estimation strategy and a road boundary feature point extraction method that adapt to the rail environment. As well as building a perception system and installing it on the train for verification, the main line test results showed that the system can reliably detect the road boundary more than 400 m ahead of the train and can stably detect and track the train.

High throughput computations of the effective removal of liquified gases by novel perchlorate hybrid material

The utilization of hybrid materials in separation technology, sorbents, direct air capture (DAC) technology, sensors, adsorbents, and chiral material recognition has increased in the past decade due to the recognized impact of atmospheric pollutants and hazardous industrial gases on climate change. A novel hybrid material, perchlorate hybrid (PClH), has been proposed in this study for the effective sensory detection and trapping of atmospheric pollutants and industrial hazardous gases. The study evaluated the structural properties, adsorption mechanism, electronic sensitivity, and topological analysis of PClH using highly accurate computational methods (M062X-D3BJ/def2-ccpVTZ and DSDPBEP86/def2-ccpVTZ). The computational analysis demonstrated that PClH has considerable adsorption energies and favorable interaction with CO2, NO2, SO2, COCl2, and H2S. PClH is more suitable for detecting liquefiable gases such as COCl2, CO2, and SO2, and can be easily recovered under ambient conditions. Developing such materials can contribute to reducing hazardous gases and pollutants in the atmosphere, leading to a cleaner and safer environment.

An accurate and efficient quasi-dynamic simulation method of electricity-heat multi-energy systems

Quasi-dynamic energy flow computation (EFC) has become a critical tool to determine and predict the states of the multi-energy system (MES), which helps improve MES’ operation efficiency and issues the security warning. However, methods in literature suffer numerical problems including fake oscillations, divergence, etc., Also, with the increasing of system dimensions, the computation efficiency can be hardly guaranteed due to the cross iterations between different nonlinear equations. This paper proposes an accurate and efficient method for quasi-dynamic energy flow computation. Using a scheme with total variation decreasing property, the numerical instability in solutions of thermal dynamics are effectively reduced. By estimating local truncation errors in a cheap way, the simulation step sizes are controlled adaptively and hence the overall simulation efficiency is greatly increased. Numerical tests were performed in a small system and the famous Barry Island system, which verified the advantages of the proposed method in both efficiency and accuracy.

Local compression behavior of UHPFRC: Experiments and bearing capacity calculation model

To evaluate the mechanical properties of the anchorage zone of prestressed UHPFRC structure, an experimental study was conducted on 54 UHPFRC specimens with central channels using local pressure tests. The local compression bearing capacity and load–displacement relationship were obtained. The experimental results indicated that there were four stages of local compression behavior in specimens: compaction, elastic deformation, crack development in the peripheral concrete and its interface with the wedge, and failure. The local compression cracking load of UHPFRC specimens was generally 40%-80% of the ultimate load. The local compression area ratio had a large effect on the vertical stiffness of UHPFRC local compression specimens. The increase in steel fiber length-diameter ratio (from 65 to 80) improved the transverse flexibility of the specimens. The average increases of UHPFRC local compression cracking load and ultimate load were up to 18.81% and 10.04% when the steel fiber volume content increases from 1% to 3%. The increase of the local compression area ratio on the local compression bearing capacity of UHPFRC ranged from 0.10% to 30.93%. Finally, the analytical formula was proposed to calculate the local compression bearing capacity of UHPFRC by fully considering the effect of the tensile strength of UHPFRC on the hooping action of peripheral concrete. This research provided a novel insight into the accurate bearing capacity calculation methods for UHPFRC in anchorage zones.

A 3D simulation model of thermal runaway in Li-ion batteries coupled particles ejection and jet flow

A coupled simulation model of the 18650 lithium-ion batteries (LIB) thermal runaway (TR) is presented in this study, which includes TR decomposition reaction, gas generation and combustion processes, solid particles ejection and particles heat transfer process. The model considers a combination of solid heat conduction, gas convection, flame and particles radiation, which is validated to accurately capture the temperature evolution and two typical jet processes during TR. Model validation conducts with experimental measurements for the temperature of the battery surface. The simulation results show that the “ignition” time of the flammable gas mixture is delayed and the rate of flame temperature increase is slowed down when the effect of solid particles is considered. The radiation heat transfer rate and convection heat transfer rate on the adjacent battery surfaces are 80.3W and 12.76W, and are approximately 4.29 times and 1.76 times larger than the results calculated by the model without solid particles, respectively. The difference between these two can be further magnified in confined space. The model developed in this study combines the effect of the solid particles’ radiation into the TR simulation innovatively. It can provide a more accurate calculation method for the prediction of TR propagation.

Improvement methods for thermal backflow phenomenon in engine compartment blow-type air cooler module

Regarding the thermal backflow problem in the central area of the engine compartment's blow-type cooler module, a computational model for the entire machine's outflow field is first established and validated using experimental results. Next, the formation of thermal backflow phenomenon is analyzed, and a more accurate calculation method for the cooler that takes into account the thermal backflow phenomenon is proposed. Finally, a new structure that can eliminate the thermal backflow phenomenon is presented, and the heat dissipation effect is analyzed. The conclusion shows that the calculated values of the engine compartment cooler module are consistent with experimental results, verifying the correctness of the computational model. The negative pressure caused by the “pump” suction effect in the central area of the cooler module is the fundamental reason for the generation of the thermal backflow phenomenon. The dual heat exchanger model can significantly improve the calculation accuracy of the cooler when taking into account the thermal backflow phenomenon (by at least 10%), providing a more accurate method for evaluating the cooler's heat dissipation ability. The proposed new structure can eliminate the thermal backflow phenomenon in the cooler module and improve the heat dissipation uniformity. After the elimination of the thermal backflow phenomenon, the heat dissipation ability of the cooler is improved by at least 25%. In addition, the improvement of the heat dissipation uniformity of the cooler can effectively solve the problem that multiple coolers in the engine compartment have inconsistent heat dissipation capabilities. The proposed calculation method for the cooler taking into account the thermal backflow phenomenon and the new structure for eliminating the thermal backflow provide a reference for the development of similar products in the future.

Seismic behavior of wall-type spiral stirrups-confined RC column to steel beam joint

This study proposes a new interior diaphragm joint between wall-type reinforced concrete column with high-strength spiral stirrups and steel beams, and the quasi-static test was conducted to investigate the seismic performance of the new joint under cyclic lateral force. Finite element model (FEM) simulation was carried out using the software ABAQUS, and the correctness of the FEM was verified by the results of the test. Additionally, the effect of parameters including the strength of concrete, thickness of the beam flange, interior diaphragm, joint flange, and joint web on the seismic performances of the joint was analyzed. Based on the parametric analysis and existing codes, a shear capacity formula was determined with the consideration of the shear capacity of the joint web and flange, and concrete. The comparison between the calculated and FEM results indicates that this formula could be regarded as an accurate calculation method for the shear-bearing capacity of different joint types in engineering design.

Evaluating Methods That Calculate Aircraft Emission Impacts on Air Quality: A Systematic Literature Review

Aircraft operations from above ground level to 3000 feet impact air quality and cause health issues, particularly for people working and living in and around airports. This paper evaluates the current emission calculation methods to identify the most accurate way to generate an emission inventory. Journal articles on aircraft influence on air quality were selected for a systematic literature review (SLR). After screening 277 articles written in English, 60 articles on emission calculation methods were included in the analysis. Based on the analysis, air quality can be more accurately assessed when considering direct emissions from an aircraft than when measuring atmospheric pollutant concentrations. While the International Civil Aviation Organization’s (ICAO) advanced approach was the most widely used from the literature reviewed, airport-specific, time-in-mode, and actual atmospheric conditions where aircraft operate offer the potential for significant improvement. The SLR demonstrates a need for more accurate emission calculation methods to assess the aircraft’s influence on air quality. The SLR guides airlines and airports to maintain an accurate emission inventory, which will set future targets to improve air quality.