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Viscosity is crucial in subsurface and surface transport, used in engineering domains like heat transfer and pipeline design. However, measurements are limited, necessitating predictive viscosity relationships. Existing models lack precision or pertain to limited fluids, and accurately forecasting dead oil viscosity remains challenging due to errors. The study presents a mathematical algorithm to accurately estimate viscosity values in hydrocarbon fluids. It uses a robust non-linear regression technique to establish a reliable relationship between fluid viscosity and temperature within a specific temperature range. The algorithm is applied to extra-heavy to light crude oil samples from Iranian oilfields, revealing viscosity values ranging from 0.29 cp to 5328.74 cp within a dataset of 243 viscosity data points. After modeling each of these five fluids, the highest values obtained for the maximum absolute error and relative error are related to the fluid with an API gravity of 12.92. The maximum absolute error and relative error for this fluid sample are 1.25 cp and 6.04%, respectively. The algorithm offers acceptable precision in outcome models, even with limited training data, demonstrating its effectiveness in training models with less than 30% of available data. Moreover, these models end up with a near-unity coefficient of determination in testing data, reaffirming their proficiency at reflecting empirical data with remarkable accuracy.

We introduce and study the bounded word problem and the precise word problem for groups given by means of generators and defining relations. For example, for every finitely presented group, the bounded word problem is in

Hydrogen-based technologies are progressing in several areas, such as transportation and energy, especially regarding their use as a replacement for greenhouse gas-emitting fuels. However, hydrogen is known for its explosiveness and large-scale flammability; hence, there is a need to ensure it can be detected and measured without risk. Several types of hydrogen sensors are available on the market. Each sensor is suited to a specific environment and operating conditions. In recent years, Artificial Intelligence tools have been increasingly used to improve the design and performance of these sensors in terms of safety, reliability, sensitivity, speed, and selectivity. This paper provides a review of available hydrogen sensors, their fields of application, and the main directions explored by the scientific community for integrating Artificial Intelligence tools to improve their performance. A comparative analysis is presented based on criteria related to sensor technologies, data processing tools, and target performance. This review highlights the results achieved and the challenges that remain to be addressed in various application fields.

In the Internet era, soccer teaching has gotten rid of the previous theoretical teaching mode and paid more attention to the use of video and multimedia for network teaching. In this paper, from the perspective of a fuzzy mathematical algorithm, the mathematical set algorithm is used to construct a fuzzy matrix through algorithm mapping, calculate the NMI value of the equivalent algorithm and the comprehensive rating weights of U1-U10 in the evaluation elements of soccer network teaching, and derive the fuzzy transformation value of the rating result of soccer network teaching platform as 83.7895. The probability distribution value is inferred to be 45.8% on average by creating the affiliation function and then calculating the search accuracy, platform recall, and teaching F1 metrics of the Zadeh mathematical operator. After calculating the weighted average value of B=87.6617 for the Zadeh mathematical operator through the metrics, an empirical analysis of the feasibility of invoking the fuzzy mathematical algorithm in the soccer teaching web platform was conducted. The results showed that the total number of students who wanted to continue using the platform was 36,530, accounting for 91.33% of the total number of students, indicating that the use of fuzzy mathematical algorithms to participate in the teaching of the online platform is significantly better than the traditional teaching model and is conducive to improving the effectiveness of student autonomy.

CD5L (CD5 molecule-like) is a secreted glycoprotein that controls key mechanisms in inflammatory responses, with involvement in processes such as infection, atherosclerosis, and cancer. In macrophages, CD5L promotes an anti-inflammatory cytokine profile in response to TLR activation. In the present study, we questioned whether CD5L is able to influence human macrophage plasticity, and drive its polarization toward any specific phenotype. We compared CD5L-induced phenotypic and functional changes to those caused by IFN/LPS, IL4, and IL10 in human monocytes. Phenotypic markers were quantified by RT-qPCR and flow cytometry, and a mathematical algorithm was built for their analysis. Moreover, we compared ROS production, phagocytic capacity, and inflammatory responses to LPS. CD5L drove cells toward a polarization similar to that induced by IL10. Furthermore, IL10- and CD5L-treated macrophages showed increased LC3-II content and colocalization with acidic compartments, thereby pointing to the enhancement of autophagy-dependent processes. Accordingly, siRNA targeting ATG7 in THP1 cells blocked CD5L-induced CD163 and Mer tyrosine kinase mRNA and efferocytosis. In these cells, gene expression profiling and validation indicated the upregulation of the transcription factor ID3 by CD5L through ATG7. In agreement, ID3 silencing reversed polarization by CD5L. Our data point to a significant contribution of CD5L-mediated autophagy to the induction of ID3 and provide the first evidence that CD5L drives macrophage polarization.

In large-scale game activities, the computer big data system is collected, and then large-scale real-time data collection, processing and control systems are used to bring mathematical algorithm models, and state information reliability algorithms are used to illustrate the system control machine design and its Implementation based on VMS. This article calculates the most by calculation. The main design ideas in the game mathematical model, the research found that the system controller proposed by the system is a method to solve the multi-state process synchronization problem in the Client/Server computing system, and can effectively deal with the algorithm application research in the model.

Based on the background of artificial intelligence, this paper uses the 8∼13Hz synchronization/desynchronization principle of C3 and C4 channels related to mathematical model algorithm events to design a set of virtual information control model system based on LabVIEW mathematical algorithm platform. In the mathematical information operation model, the EEG signal is filtered and feature extracted by using a digital band-pass filter and power spectrum estimation to control the direction of signal transmission. Experiments show that this mathematical algorithm can achieve the control accuracy of signal transmission, laying a foundation for building a completer and more complex signal system on the LabVIEW platform.

In recent years, with the rapid advancement of multi-mode teaching theory, this paper adopts an interactive large classroom method and derives from the interaction of mathematics. In combination with online course optimization, the performance is improved through the use of a multi-mode system and the use of interactivity The principle and empirical formula, and finally through the comparative analysis of mathematical statistics, proved that the human-computer interaction mathematical algorithm has a significant effect, “problem English human-computer interaction mathematical algorithm plays an active role in online courses.

The implementation of content-based image retrieval (CBIR) mainly depends on two key technologies: image feature extraction and image feature matching. In this paper, we extract the color features based on Global Color Histogram (GCH) and texture features based on Gray Level Co-occurrence Matrix (GLCM). In order to obtain the effective and representative features of the image, we adopt the fuzzy mathematical algorithm in the process of color feature extraction and texture feature extraction respectively. And we combine the fuzzy color feature vector with the fuzzy texture feature vector to form the comprehensive fuzzy feature vector of the image according to a certain way. Image feature matching mainly depends on the similarity between two image feature vectors. In this paper, we propose a novel similarity measure method based on k-Nearest Neighbors (kNN) and fuzzy mathematical algorithm (SBkNNF). Finding out the k nearest neighborhood images of the query image from the image data set according to an appropriate similarity measure method. Using the k similarity values between the query image and its k neighborhood images to constitute the new k-dimensional fuzzy feature vector corresponding to the query image. And using the k similarity values between the retrieved image and the k neighborhood images of the query image to constitute the new k-dimensional fuzzy feature vector corresponding to the retrieved image. Calculating the similarity between the two k-dimensional fuzzy feature vector according to a certain fuzzy similarity algorithm to measure the similarity between the query image and the retrieved image. Extensive experiments are carried out on three data sets: WANG data set, Corel-5k data set and Corel-10k data set. The experimental results show that the outperforming retrieval performance of our proposed CBIR system with the other CBIR systems.

The English-Chinese machine translation system is a current research topic. This paper designs an English-Chinese comparison system based on Lagrangian search mathematical algorithm. This paper proposes a Lagrangian algorithm to describe the English short syntax and improves the English-Chinese translation algorithm. When expanding nodes, the algorithm expands on the inspiration node and expands on other nodes. The experimental results show that the improved Lagrangian search algorithm can obtain better translation results and search efficiency in the system.