The Past and Future of Aesthetics in Mathematics

This paper explores the connotations of mathematical aesthetics and its connections with art,facilitated by collaboration with Ester,an individual with an artistic professional background.It begins by tracing the historical evolution of aesthetics from the classical pursuit of authenticity to the modern shift toward self-expression in art.The discussion then highlights the similarities in the pursuit of truth between mathematics and art,despite their methodological differences.Through an analysis of aesthetic elements in mathematics,such as lines and function graphs,the article illustrates that the beauty of mathematics is not only manifested in cognitive processes but can also be intuitively expressed through visual arts.The paper further examines the influence of mathematics on the development of art,particularly how Leonardo da Vinci applied mathematical principles to his artworks.Additionally,the article addresses art students’perceptions of mathematics,proposes the customization of math courses for art students,and discusses future trends in the integration of mathematics and art,emphasizing the significance of art therapy and the altruistic direction of art.Lastly,the authors use a poster to visually convey the idea that the beauty of mathematics can be experienced through the senses.

Integration of Mathematics History into Junior Middle School Education: A Pedagogical Approach to Enhance Mathematical Literacy

The integration of the history of mathematics into junior middle school mathematics education represents a significant focus of international research in mathematics and education.The mathematics curriculum standards for compulsory education have emphasized the importance of incorporating the history of mathematics,aiming to gradually integrate it into the mathematics classroom.However,in the practical implementation of junior middle school mathematics education,the effective combination of the history of mathematics with teaching methodologies remains largely unexplored.This article explores the integration of junior middle school mathematics education and the history of mathematics,aiming to provide classroom teaching recommendations for teachers and promote the formation of students’mathematical literacy.

Enhancing Learners’Performance in Grade 7 Mathematics Through 50-30-20 Exercise

Assessment exercises constitute a crucial component of the teaching and learning process,serving the purpose of gauging the degree to which learning objectives have been accomplished.This study aims to assess the mathematics performance of Grade 7 learners using the 50-30-20 exercise.Specifically,this study seeks to determine the learners’pre-test and post-test mean scores,identify significant differences between the pre-test and post-test results,evaluate learners’exercises,and propose enhanced exercises.The research employs a quasi-experimental design,with 40 Grade 7 learners in the school year 2023-2024 as participants,selected through purposive non-random sampling.Statistical data analysis involves the use of mean,standard deviation,paired t-test,and Cohen’s D effect size.Ethical considerations were paramount,as evidenced by a letter of authorization from the school head outlining the strict adherence to voluntary participation,informed parental consent,anonymity,confidentiality,risk mitigation,results-sharing protocols,and the commitment to keeping research data confidential.The data yielded a remarkable outcome:the experimental group exhibited improvement in both the pre-test and post-test.This result substantiates the initial objective of the study,showcasing a noteworthy and favorable performance among the participants.Consequently,it suggests that a majority of the participants strongly agree that the 50-30-20 exercises contribute to enhancing their understanding and problem-solving skills,as well as their ability to grasp mathematical concepts and improve their overall performance in mathematics.Therefore,the 50-30-20 exercises not only facilitated students in understanding mathematics lessons but were also aligned with the Department of Education’s development plan.

MATHEMATICAL MODELING AND BIFURCATION ANALYSIS FOR A BIOLOGICAL MECHANISM OF CANCER DRUG RESISTANCE

Drug resistance is one of the most intractable issues in targeted therapy for cancer diseases.It has also been demonstrated to be related to cancer heterogeneity,which promotes the emergence of treatment-refractory cancer cell populations.Focusing on how cancer cells develop resistance during the encounter with targeted drugs and the immune system,we propose a mathematical model for studying the dynamics of drug resistance in a conjoint heterogeneous tumor-immune setting.We analyze the local geometric properties of the equilibria of the model.Numerical simulations show that the selectively targeted removal of sensitive cancer cells may cause the initially heterogeneous population to become a more resistant population.Moreover,the decline of immune recruitment is a stronger determinant of cancer escape from immune surveillance or targeted therapy than the decay in immune predation strength.Sensitivity analysis of model parameters provides insight into the roles of the immune system combined with targeted therapy in determining treatment outcomes.

Aggravation of Cancer,Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

The global populationhas beenandwill continue to be severely impacted by theCOVID-19 epidemic.The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer,heart disease,and diabetes.Here,using ordinary differential equations(ODEs),two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease.After that,we highlight the stability assessments that can be applied to these models.Sensitivity analysis is used to examine how changes in certain factors impact different aspects of disease.The sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19,which could result in a dramatic increase in the diagnosis of various ailments in the years to come.The correlation between diabetes and cardiovascular illness is also illustrated graphically.The effects of smoking and obesity are also found to be significant in disease compartments.Model fitting is also provided for interpreting the relationship between real data and the results of thiswork.Diabetic people,in particular,need tomonitor their health conditions closely and practice heart health maintenance.People with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable diets.The main purpose of this study is to emphasize the importance of regular checks,to warn people about the effects of COVID-19(including avoiding healthcare centers and doctors because of the spread of infectious diseases)and to indicate the importance of family history of cancer,heart diseases and diabetes.The provision of the recommendations requires an increase in public consciousness.

Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

Community detection on elite mathematicians’collaboration network

Purpose:This study focuses on understanding the collaboration relationships among mathematicians,particularly those esteemed as elites,to reveal the structures of their communities and evaluate their impact on the field of mathematics.Design/methodology/approach:Two community detection algorithms,namely Greedy Modularity Maximization and Infomap,are utilized to examine collaboration patterns among mathematicians.We conduct a comparative analysis of mathematicians’centrality,emphasizing the influence of award-winning individuals in connecting network roles such as Betweenness,Closeness,and Harmonic centrality.Additionally,we investigate the distribution of elite mathematicians across communities and their relationships within different mathematical sub-fields.Findings:The study identifies the substantial influence exerted by award-winning mathematicians in connecting network roles.The elite distribution across the network is uneven,with a concentration within specific communities rather than being evenly dispersed.Secondly,the research identifies a positive correlation between distinct mathematical sub-fields and the communities,indicating collaborative tendencies among scientists engaged in related domains.Lastly,the study suggests that reduced research diversity within a community might lead to a higher concentration of elite scientists within that specific community.Research limitations:The study’s limitations include its narrow focus on mathematicians,which may limit the applicability of the findings to broader scientific fields.Issues with manually collected data affect the reliability of conclusions about collaborative networks.Practical implications:This study offers valuable insights into how elite mathematicians collaborate and how knowledge is disseminated within mathematical circles.Understanding these collaborative behaviors could aid in fostering better collaboration strategies among mathematicians and institutions,potentially enhancing scientific progress in mathematics.Originality/value:The study adds value to understanding collaborative dynamics within the realm of mathematics,offering a unique angle for further exploration and research.

Mathematical Modeling of Cell Polarity Establishment of Budding Yeast

The budding yeast Saccharomyces cerevisiae is a powerful model system for studying the cell polarity establishment.The cell polarization process is regulated by signaling molecules,which are initially distributed in the cytoplasm and then recruited to a proper location on the cell membrane in response to spatial cues or spontaneously.Polarization of these signaling molecules involves complex regulation,so the mathematical models become a useful tool to investigate the mechanism behind the process.In this review,we discuss how mathematical modeling has shed light on different regulations in the cell polarization.We also propose future applications for the mathematical modeling of cell polarization and morphogenesis.

A Mathematical Modeling of 3D Cubical Geometry Hypothetical Reservoir under the Effect of Nanoparticles Flow Rate,Porosity,and Relative Permeability

This study aims to formulate a steady-state mathematical model for a three-dimensional permeable enclosure(cavity)to determine the oil extraction rate using three distinct nanoparticles,SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3),in unconventional oil reservoirs.The simulation is conducted for different parameters of volume fractions,porosities,and mass flow rates to determine the optimal oil recovery.The impact of nanoparticles on relative permeability(kr)and water is also investigated.The simulation process utilizes the finite volume ANSYS Fluent.The study results showed that when the mass flow rate at the inlet is low,oil recovery goes up.In addition,they indicated that silicon nanoparticles are better at getting oil out of the ground(i.e.,oil reservoir)than Al_(2)O_(3)and Fe_(2)O_(3).Most oil can be extracted from SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3)at a rate of 97.8%,96.5%,and 88%,respectively.

Learning to represent 2D human face with mathematical model

How to represent a human face pattern?While it is presented in a continuous way in human visual system,computers often store and process it in a discrete manner with 2D arrays of pixels.The authors attempt to learn a continuous surface representation for face image with explicit function.First,an explicit model(EmFace)for human face representation is pro-posed in the form of a finite sum of mathematical terms,where each term is an analytic function element.Further,to estimate the unknown parameters of EmFace,a novel neural network,EmNet,is designed with an encoder-decoder structure and trained from massive face images,where the encoder is defined by a deep convolutional neural network and the decoder is an explicit mathematical expression of EmFace.The authors demonstrate that our EmFace represents face image more accurate than the comparison method,with an average mean square error of 0.000888,0.000936,0.000953 on LFW,IARPA Janus Benchmark-B,and IJB-C datasets.Visualisation results show that,EmFace has a higher representation performance on faces with various expressions,postures,and other factors.Furthermore,EmFace achieves reasonable performance on several face image processing tasks,including face image restoration,denoising,and transformation.

Practical Use of the Subjective Mathematical Model of Bayes and Its External Validation in Dental Medicine & Dentistry

Objective: Our study aims to validate the subjective Bayes mathematical model using the mathematical model of logistic regression. Expert systems are being utilized increasingly in medical fields for the purposes of assisting diagnosis and treatment planning in Dentistry. Existing systems used few symptoms for dental diagnosis. In Dentistry, few symptoms are not enough for diagnosis. In this research, a conditional probability model (Bayes rule) was developed with increased number of symptoms associated with a disease for diagnosis. A test set of recurrent cases was then used to test the diagnostic capacity of the system. The generated diagnosis matched that of the human experts. The system was also tested for its capacity to handle uncommon dental diseases and the system portrayed useful potential. Method: The study used the Subjective Mathematical Bayes Model (SBM) approach and employed Logistic Regression Mathematical Model (LMR) techniques. The external validation of the subjective mathematical Bayes model (MSB) concerns the real cases of 625 patients who developed alveolar osteitis (OA). We propose strategies for reproducibility and reporting standards, outlining an updated WAMBS (when to Worry and how to Avoid the Misuse of Bayesian Statistics) checklist. Finally, we outline the impact of Bayesian analysis Logistic Regression Mathematical Model (LMR) techniques and on artificial intelligence, a major goal in the next decade. Results: The internal validation had identified seven (7) etiological factors of OA, which will be compared to the cases of MRL, for the external validation which retained six (6) etiological factors of OA. The experts in the internal validation of the MSB had generated 40 cases of OA and a COP of (0.5), which will be compared to the MRL that collected 625 real cases of OA to produce a Cop of (0.6) in the external validation, which discriminates between healthy patients (Se) and sick patients (Sp). Compared to real cases and the logistic regression model, the Bayesian model is efficient and its validity is established.

Measurement Analysis and Evaluation of Twenty- Five Years of Chinese Mathematics Textbooks: Visual Analysis Based on CiteSpace Knowledge Graph (1999-2024)

At present,textbooks based on core literacy have become the inevitable demands of China’s curriculum reform,and the literacy of textbook goal construction is the key to the implementation of core literacy requirements,which is a huge challenge for textbook compilers.In this paper,we use the visual metrology of the CiteSpace knowledge graph to analyze Chinese mathematics textbooks(1999-2024),hoping to guide the future direction of Chinese mathematics textbook research.

Mathematical Modeling of the Co-Infection Dynamics of HIV and Tuberculosis Incorporating Inconsistency in HIV Treatment

A non-linear HIV-TB co-infection has been formulated and analyzed. The positivity and invariant region has been established. The disease free equilibrium and its stability has been determined. The local stability was determined and found to be stable under given conditions. The basic reproduction number was obtained and according to findings, co-infection diminishes when this number is less than unity, and persists when the number is greater than unity. The global stability of the endemic equilibrium was calculated. The impact of HIV on TB was established as well as the impact of TB on HIV. Numerical solution was also done and the findings indicate that when the rate of HIV treatment increases the latent TB increases while the co-infected population decreases. When the rate of HIV treatment decreases the latent TB population decreases and the co-infected population increases. Encouraging communities to prioritize the consistent treatment of HIV infected individuals must be emphasized in order to reduce the scourge of HIV-TB co-infection.

Mathematical Modeling of HIV Investigating the Effect of Inconsistent Treatment

HIV is a retrovirus that infects and impairs the cells and functions of the immune system. It has caused a great challenge to global public health systems and leads to Acquired Immunodeficiency Syndrome (AIDS), if not attended to in good time. Antiretroviral therapy is used for managing the virus in a patient’s lifetime. Some of the symptoms of the disease include lean body mass and many opportunistic infections. This study has developed a SIAT mathematical model to investigate the impact of inconsistency in treatment of the disease. The arising non-linear differential equations have been obtained and analyzed. The DFE and its stability have been obtained and the study found that it is locally asymptotically stable when the basic reproduction number is less than unity. The endemic equilibrium has been obtained and found to be globally asymptotically stable when the basic reproduction number is greater than unity. Numerical solutions have been obtained and analyzed to give the trends in the spread dynamics. The inconsistency in treatment uptake has been analyzed through the numerical solutions. The study found that when the treatment rate of those infected increases, it leads to an increase in treatment population, which slows down the spread of HIV and vice versa. An increase in the rate of treatment of those with AIDS leads to a decrease in the AIDS population, the reverse happens when this rate decreases. The study recommends that the community involvement in advocating for consistent treatment of HIV to curb the spread of the disease.

Curriculum Reform of Higher Vocational Mathematics Under the Background of Digital Transformation

Under the background of digital transformation,the reform of the higher vocational mathematics curriculum faces urgent challenges and opportunities.This article explores the impact of digital transformation on the reform of higher vocational mathematics curriculum and emphasizes the importance of improving teaching methods centered on learners.The article proposes specific reform methods and discusses the practical application of digital technology in the reform process.By combining digital technology with specific reform methods,further conducting innovative practice research,and continuously exploring the path of reform,we can effectively improve the quality of higher vocational mathematics classroom teaching and provide strong support for the cultivation of comprehensive qualities and employment abilities.

Enhancement of Innovation Competence of College Students Majoring in Mathematics Education through Curriculum Optimization

The innovation competence of K-12 education teachers undoubtedly plays a crucial role in fostering the innovation abilities of their students.K-12 mathematics education equips students with the critical thinking and problem-solving skills essential for their future studies in colleges and universities,helping them grasp complex techniques to address challenges in everyday life and their careers.Therefore,it is of great significance to study strategies for improving the innovation competence of college students majoring in Mathematics Education,as they will likely become K-12 education mathematics teachers directly after graduating from colleges or universities.In this paper,we study strategies for enhancing the innovation competence of college students majoring in Mathematics Education through curriculum optimization.We analyze and explain in detail the importance of innovation competence for college students majoring in Mathematics Education and the difficulties encountered in enhancing college students’innovation competence.With the help of the analysis of the importance and challenges of enhancing college students’innovation competence,we propose several strategies to improve the innovation competence of college students majoring in Mathematics Education based on curriculum optimization.The findings presented in this paper can be applied to develop strategies for college students majoring in Physics and Chemistry Education.

Measurement Analysis and Evaluation of Twenty-Five Years of Mathematics Education Research in China:Visual Econometric Analysis Based on CiteSpace Knowledge Mapping(1999-2024)

Since the new century,China’s mathematics curriculum reform in basic education has continued to move forward in attempts and explorations,presenting many new changes,trends,movements,and developments.Sorting out,analyzing,and summarizing the achievements,experiences,problems,and challenges in this journey are conducive to providing insights for the reform and development of the Chinese basic education mathematics curriculum in the new era.This paper analyses the research on mathematics education in China(1999-2024)using the visual measurement of CiteSpace knowledge mapping,hoping to provide directions for the future of mathematics education in China.

Teaching Reform and Practice of “Mathematical Analysis” under the New Engineering Education Paradigm

With the advent and promotion of the new engineering education paradigm,university mathematics courses face new challenges and opportunities.As a fundamental course for engineering majors,the reform of“Mathematical Analysis”is particularly crucial.This paper explores the necessity,specific practices,and outcomes of teaching reform in“Mathematical Analysis”within the context of the new engineering education.By reforming teaching content,methods,and assessment approaches,this study aims to enhance students’mathematical literacy and comprehensive abilities to meet the demands of the new engineering education development.

A Study on the Application of Task-Driven Teaching Method in High School Mathematics Teaching: Taking “The Determination of Vertical Line and Plane” as an Example

The“Ordinary High School Mathematics Curriculum Standards(2017 Edition,2020 Revision)”clearly stated in“Teaching Suggestions”that“teaching activities based on the core literacy of mathematics should grasp the essence of mathematics,create appropriate teaching situations,put forward appropriate mathematical questions,stimulate students to think and communicate,and form and develop the core literacy of mathematics.”The task-driven teaching model is a new type of teaching method that takes tasks as the main line,teachers as the guide,and students as the main body,which can enable students to engage deeply in classroom discussions and think actively.Based on the characteristics and principles of the task-driven teaching method,this paper designs a high school mathematics classroom teaching based on the task-driven teaching method,hoping to provide a reference for the majority of front-line teachers.