Software Impacts最新文献

The Munich Procedure, a protocol presented as R code and initially developed on the basis of archaeometric portable X-ray fluorescence (p-XRF) data, offers adaptability and standardisation to evaluate coefficient corrections. These corrections are derived from linear regressions calculated by comparing p-XRF values with laboratory chemical analyses of the same sample set. The versatility of this procedure allows collaboration and ensures consistent data structure. Not tied to specific instrumentation, this approach helps to universally improve the accuracy of p-XRF data, benefiting specialists in a variety of industries. By providing a common baseline for performance evaluation, it enables discussion across different applications.

Due to the stable increase in electric mobility, it is important to assess the growing burden on the power system in general and on the existing charging stations, to plan future development and extension of the electric infrastructure. The simulator proposed in this paper is based on Python software and allows modeling of the flow of electric vehicles circulating on a highway. It allows to evaluate the impact of electric vehicles for different penetration level, allocation strategies, charging rates and capacities of the charging stations. The simulator is applied to a case study to illustrate the functionalities of the code and a range of Key Performance Indicators is proposed to illustrate charging times. Finally, it is demonstrated that the simulator outcomes can highlight crucial aspects from both the drivers’ and the charging station operators’ perspectives.

The software presented is designed to perform metamaterial calculations via a multiscale model, where an original problem (a metamaterial structure) with a large number of degrees of freedom is divided into the sum of smaller problems with much less degrees of freedom each, therefore reducing noticeably the computational cost in terms of RAM consumption. RAM usage has been reduced by more than 90% in different probes of metamaterial, and the larger the dimension of the problem, the greater the enhancement. Those results are published as a promising probe of concept of the theory.

We present software for calculating the analytical distributions of potential and field in microlens made of polymer-stabilized blue-phase liquid crystals. The microlens is located between two electrodes with a circular opening on the upper electrode. The program is encoded using the derived analytical solution formulas of the potential and electric field. It is faster, more energy-saving, and has less memory configuration than the finite-difference equation method solving by using the Poisson Equation with boundary conditions. The software outputs relevant Data files and a MATLAB code that can draw the distributions of potential, electric field, and directors, allowing the calculations visualized.

Efficient classification and quality assessment of rice varieties are essential for market pricing, food safety, and consumer satisfaction in the global rice sector. Leveraging pre-trained ResNet architectures, Rice-ResNet significantly enhances feature extraction, ensuring accurate classification and quality detection of rice cultivars. This system, accessible in Python repositories, promises improved crop management and yield. Despite requiring real-world implementation, Rice-ResNet marks a significant advancement in rice classification, fostering enriched digital experiences.

The advent of computational techniques, particularly atomistic simulations, has lessened the dependency on physical experiments in various scientific fields. Yet, the preparation complexity for simulations using platforms like LAMMPS and GROMACS persists. We introduce SMI2PDB, a Python tool that automates molecular systems assembly from SMILES to PDB format, easing molecular dynamics simulation setups. SMI2PDB manages molecule configuration and quantification effortlessly, establishes stable conformers, applies random rotations, and positions them in a simulation box with a Sobol sequence to reduce overlaps. This script facilitates the rapid preparation of complex organic mixtures for use in simulations, enhancing the exploration of novel materials.

Pdb2dat, developed in Python, is an open-source, self-contained utility that facilitates the conversion of PDB files into LAMMPS data files, catering to the need of initializing atomistic simulation from initial atomic configurations. It extracts molecular details from PDB files, uses Rdkit and Xyz2mol for bonding analysis and 3D conformer generation, and uses Pysimm for assigning force field types and charges. Designed to be lightweight and fully Pythonic, pdb2dat is suitable for use in privilege-limited high-throughput environments. The output details system topologies for use in MD simulations, significantly simplifying the preparatory steps needed by researchers to explore materials phenomena through LAMMPS.

The software ‘Particle Droplet Population Balance Simulation’ (Particle-Droplet-PBS) simulates the time of particle-shell formation and particle growth in burning spray droplets. Application examples are provided to demonstrate how the code can be used to incorporate a variety of particles, precursor chemicals and solvents. The software solves the population balance equations for particle coagulation and nucleation, while applying an adaptive grid method requiring only two cells per droplet. Thus, the computation time is drastically reduced. This enables users without access to high-performance work stations to run droplet simulations in a timely manner, making it a valuable tool for research and process engineering.

René Thom’s work on topological instabilities applied new methods to questions of dynamical stability that traditionally belonged to the domain of dynamical systems theorists. Topological instability focuses on universal properties of bifurcations in systems where multiple equilibria form and disappear as a function of system parameters. However, the complete mathematical description is quite abstract and the analysis benefits from graphical intuitions. Here we provide the code, in the form of a Mathematica notebook, used in our recent Games and Economic Behaviour paper (Harriset al., 2023). It illustrates our main results providing the intuition necessary to explore the bifurcations in the formal proofs.

Classification of sentences is a challenging problem in the field of natural language processing. We present a prototype for classifying the pairs of sentences using their syntactic and semantic relations. The sentences are classified into three classes — entailment, contradiction and neutral. The grammatical relations of the sentences are extracted and these relations are represented as word embeddings using global vector, Glove. The word to word semantics is found using Wordnet semantic relations. The prototype is based on statistical measures which was implemented using Python 3.6.9 version.