Haoyan Zhang | Mathematics | Best Researcher Award

Assoc. Prof. Dr. Haoyan Zhang | Mathematics | Best Researcher Award

Associate Professor from Civil Aviation University of China, China

Haoyan Zhang is an accomplished researcher and academic in the field of mathematical finance and stochastic analysis. He is currently serving as an Associate Professor at the College of Science, Civil Aviation University of China. With a solid academic foundation in applied mathematics and probability theory, Dr. Zhang has demonstrated a sustained commitment to high-quality research, teaching, and academic collaboration. His work spans key topics such as option and bond pricing, stochastic volatility, optimal stopping problems, and Markov processes—areas that are critical in both theoretical and applied finance. Over the years, he has published extensively in reputable international journals and contributed significantly to advancing knowledge in mathematical modeling and financial engineering. His overseas research experience at the Université de Lausanne has further enhanced his academic profile, adding an international dimension to his work. As a main participant in an NSFC-funded project and a consistent contributor to peer-reviewed literature, Dr. Zhang has established himself as a reliable and innovative researcher. With an upward trajectory in his academic career and a growing influence in his domain, he exemplifies the qualities befitting a nominee for the Best Researcher Award.

Professional Profile

Education

Haoyan Zhang began his academic journey with a Bachelor of Science degree in Applied Mathematics from Lanzhou University, China, graduating in 2012. This foundational training laid the groundwork for his pursuit of advanced mathematical research, particularly in fields involving applied probability and quantitative analysis. He then enrolled in the Ph.D. program in Probability and Mathematical Statistics at the School of Mathematical Science, Nankai University, one of China’s top institutions in mathematical sciences. From 2012 to 2018, he honed his expertise in areas such as stochastic processes, optimal stopping theory, and mathematical modeling in finance. His doctoral studies provided him with a rigorous understanding of Markov processes and stochastic differential equations—core techniques essential for solving complex problems in finance and economics. During this time, he also gained exposure to high-level academic collaborations and laid the foundation for his future publication record. His time as a Ph.D. candidate also included an overseas research visit to the Université de Lausanne, Switzerland, further broadening his academic perspective. Dr. Zhang’s educational background is a strong testament to his analytical rigor, technical proficiency, and sustained academic curiosity, positioning him well for a distinguished research career.

Professional Experience

Dr. Haoyan Zhang has accumulated significant academic experience in higher education and research institutions. He began his professional career in 2018 as a Lecturer at the College of Science, Civil Aviation University of China. In this role, he was involved in both teaching and research, contributing to the academic development of undergraduate and graduate students while advancing his own scholarly projects. Over the next four years, he built a strong foundation in academic publishing and collaborative research, particularly in the areas of financial mathematics and stochastic processes. In 2023, he was promoted to Associate Professor, a recognition of his academic excellence and growing contributions to the field. His promotion also reflects his increasing role in research leadership and academic mentorship. Beyond his domestic engagements, Dr. Zhang broadened his professional experience through an international research visit to the Faculty of Business and Economics at the Université de Lausanne, Switzerland, in 2016. This experience allowed him to collaborate with leading scholars in actuarial science and financial engineering. His professional trajectory illustrates a steady ascent marked by dedication, research productivity, and academic responsibility, making him a valuable member of the scholarly community.

Research Interest

Dr. Haoyan Zhang’s research interests lie primarily in financial engineering and applied mathematics, with a strong emphasis on stochastic analysis and probabilistic modeling. He has developed extensive expertise in option pricing and bond pricing, focusing on the mathematical structures that govern financial markets under uncertainty. His work frequently involves the application of stochastic differential equations, Markov processes, and optimal stopping theory to problems in quantitative finance. Dr. Zhang is particularly interested in modeling and analyzing skewed and perturbed diffusion processes, such as the skew-extended CIR and sticky Brownian motion models. These models are central to understanding complex financial instruments and market behaviors, including risk assessment and asset valuation. Another key area of interest is parameter estimation and hitting time problems, which have important implications for decision-making under uncertainty. Dr. Zhang’s research bridges the gap between theory and practice, offering valuable tools for real-world financial applications. Through consistent publication in reputable journals and collaboration with fellow researchers, he continues to explore the interplay between mathematical rigor and financial innovation. His work contributes to a deeper understanding of market dynamics and enhances the analytical frameworks available to economists, risk managers, and policy makers.

Research Skills

Dr. Haoyan Zhang possesses a robust set of research skills that make him a leading figure in the domain of mathematical finance and stochastic analysis. He is proficient in modeling complex financial systems using advanced tools such as stochastic differential equations, Markov processes, and skew diffusion models. His ability to derive and solve mathematical models has enabled him to address real-world problems in bond and option pricing with analytical precision. One of his key skills lies in applying optimal stopping theory to solve practical problems such as American option pricing and decision-making under uncertainty. He is also adept at developing numerical methods and approximation techniques, such as lattice-based models and Bayesian estimation, which enhance the computational feasibility of his theoretical models. Dr. Zhang has demonstrated strong capabilities in both independent and collaborative research environments, having co-authored numerous publications with researchers across institutions. His exposure to international academic settings, particularly during his visit to the Université de Lausanne, equipped him with interdisciplinary insights and research methodologies. With a solid command of mathematical programming tools and statistical analysis, Dr. Zhang continues to deliver high-impact research that merges mathematical theory with financial application.

Awards and Honors

While Dr. Haoyan Zhang has not listed individual honors or awards in the provided information, his academic accomplishments speak to a career marked by recognition and achievement. He has successfully progressed from Lecturer to Associate Professor at the Civil Aviation University of China, an advancement that reflects institutional recognition of his scholarly contributions. Furthermore, he was selected as a main participant in a project funded by the National Natural Science Foundation of China (NSFC), under Grant No. 11571190, from January 2016 to December 2019. Participation in a nationally competitive grant signifies a high level of peer recognition and trust in his research capabilities. Additionally, his selection as a visiting scholar at the Faculty of Business and Economics, Université de Lausanne, Switzerland, further underscores his growing international profile and academic merit. His continuous output in reputable journals and contributions to collaborative research projects further bolster his standing within the academic community. These milestones collectively represent a body of recognition that, while not individually titled, qualifies him as a high-achieving academic deserving of broader accolades such as the Best Researcher Award.

Conclusion

In conclusion, Dr. Haoyan Zhang presents a compelling case for the Best Researcher Award in recognition of his scholarly accomplishments, depth of expertise, and dedication to academic advancement. With a well-defined research focus in financial mathematics and stochastic modeling, he has consistently contributed to solving complex problems in areas such as option pricing, bond pricing, and optimal stopping. His academic journey—from his undergraduate training at Lanzhou University to his doctoral research at Nankai University and international engagement in Switzerland—demonstrates a sustained commitment to excellence. Professionally, his steady progression from Lecturer to Associate Professor, along with participation in national research grants and publication in peer-reviewed journals, reflects his credibility as a thought leader in his field. Dr. Zhang’s work not only advances theoretical understanding but also offers practical solutions to real-world financial challenges. Though opportunities remain to further his role as a principal investigator and to enhance his mentorship record, his trajectory clearly indicates a rising academic with impactful research potential. He stands out as a worthy candidate whose research achievements and academic profile merit formal recognition through this prestigious award.

Publications Top Notes

  1. Title: A Novel Idea to Solve Optimal Stopping Problem With Finite Time Horizon and Its Application in American Put
    Authors: Haoyan Zhang, Lingyun Gao
    Year: 2025

  2. Title: Bond Pricing under CIR Process with Threshold Setting
    Authors: Zhang H., Tang L., Wang F., Du Y.
    Year: 2024

  3. Title: Hitting Times for Sticky Skew CIR Process
    Authors: Zhang H., Tian Y.
    Year: 2024

  4. Title: First Hitting Time and Option Pricing Problem under Geometric Brownian Motion with Singular Volatility
    Authors: Zhang H., Zhou Y., Li X., Wu Y.
    Year: 2023

  5. Title: Perturbed Skew Diffusion Processes
    Authors: Tian Y., Zhang H.
    Year: 2023

  6. Title: Bayesian Estimation of the Skew Ornstein-Uhlenbeck Process
    Authors: Bai Y., Wang Y., Zhang H., Zhuo X.
    Year: 2022

  7. Title: Hitting Time Problems of Sticky Brownian Motion and Their Applications in Optimal Stopping and Bond Pricing
    Authors: Zhang H., Tian Y.
    Year: 2022

  8. Title: On Some Properties of Sticky Brownian Motion
    Authors: Zhang H., Jiang P.
    Year: 2021

  9. Title: Pricing Perpetual American Swaption
    Authors: Zhang H., Tian Y.
    Year: 2021

  10. Title: European Option Pricing under Stochastic Volatility Jump-Diffusion Models with Transaction Cost
    Authors: Tian Y., Zhang H.
    Year: 2020

Syed Anwar | signal processing | Best Researcher Award

Syed Anwar | signal processing | Best Researcher Award

Principal Investigator at Childrens National Hopsital, United States.

Syed Muhammad Anwar is a distinguished researcher in the fields of medical imaging, deep learning, and computer vision. He is currently a Principal Investigator at the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National Hospital in Washington, DC, and serves as an Associate Professor at George Washington University. With over two decades of academic and professional experience, Dr. Anwar has co-founded tech ventures and contributed significantly to cutting-edge research in machine learning and medical image analysis. His expertise spans across multiple countries and academic institutions, with an impressive h-index of 38 and over 6,800 citations. A prolific scholar and inventor, he has secured numerous grants and awards for his research contributions in both academia and industry, particularly in the development of healthcare technologies. His leadership roles in education, research, and industry highlight his commitment to innovation and interdisciplinary collaboration in emerging technology fields.

Profile👤

Scopus

ORCID

Education📝

Dr. Anwar’s educational background showcases an impressive academic journey through prestigious institutions. He earned his PhD in Electronic and Electrical Engineering from the University of Sheffield, UK, in 2012, where his research focused on detecting neuronal fields using MR imaging. Prior to that, he obtained a distinction in his MS in Data Communications, also from the University of Sheffield. His undergraduate education was completed at the University of Engineering and Technology (UET), Taxila, where he graduated with honors in Computer Engineering, finishing with the second-highest percentage in his class. In 2019-2020, he was awarded a prestigious Fulbright Fellowship at the University of Central Florida, focusing on deep learning for medical image analysis. His diverse and interdisciplinary academic foundation, spanning engineering and medical technology, forms the basis of his expertise in cutting-edge research areas like artificial intelligence, machine learning, and medical image computing.

Experience👨‍🏫

Dr. Anwar’s career spans a wide array of academic and industry positions. Currently, he serves as Principal Investigator at Children’s National Hospital and Associate Professor at George Washington University. He was previously an Associate Professor at the University of Engineering and Technology, Taxila, where he held numerous administrative and advisory roles. He has also worked internationally, including as a Research Fellow at the University of Surrey, UK, and a Research Associate at the University of Central Florida, USA. Dr. Anwar has extensive experience in the tech industry, having co-founded several companies, including EcoEdge AI and Sense Digital Pvt. Ltd., where he served as CTO. His industrial roles have focused on deep learning, medical imaging, and healthcare solutions. Additionally, he has mentored entrepreneurs and served as an advisor at national incubation centers, underscoring his role as a bridge between academia and industry in technology and innovation.

Research Interest🔬 

Dr. Anwar’s research interests are deeply rooted in medical image analysis, artificial intelligence, and deep learning. His work primarily focuses on utilizing deep learning models to improve medical diagnostics, especially in fields such as brain tumor segmentation, pediatric health, and cardiac health monitoring. He is particularly interested in applying machine learning techniques to enhance medical imaging technologies, exploring areas like brain-computer interfaces and wearable health technologies. His projects also delve into federated learning for medical imaging security and using AI to predict health outcomes, such as in sickle cell disease management. Throughout his career, Dr. Anwar has sought to bridge the gap between medical science and computational technology, aiming to create innovative, data-driven healthcare solutions. His interdisciplinary research has earned him international recognition, positioning him as a key figure in advancing AI-driven medical applications.

Awards and Honors🏆

Dr. Anwar has received numerous prestigious awards and honors throughout his career. He was a Fulbright Fellow at the University of Central Florida, USA, where he focused on applying deep learning to medical image analysis. He has also been awarded several research grants, including a $220,000 seed grant from IGNITE for his work in fashion retrieval using deep learning and a $1200 grant from NVIDIA for hardware development. His contributions to academia have been widely recognized, with multiple travel grants awarded by the Higher Education Commission of Pakistan for presenting his research at international conferences. Additionally, Dr. Anwar has played a leading role in student mentorship, entrepreneurship, and incubation programs, where he has been recognized as a mentor at national incubation centers and the Pak-US Alumni Network. His leadership roles and innovative research projects have earned him a reputation for academic excellence and contribution to the global research community.

Skills🛠️

Dr. Anwar possesses a robust set of technical and leadership skills. His core expertise lies in deep learning, medical image analysis, and artificial intelligence. He is proficient in applying machine learning algorithms to a variety of real-world problems, especially in healthcare technologies. His strong background in software and hardware engineering includes experience with EEG-based systems, brain-computer interfaces, and remote health monitoring. Additionally, Dr. Anwar is skilled in research design, grant writing, and project management, having secured significant funding for his projects. His entrepreneurial abilities are demonstrated through his co-founding of tech startups and his role as CTO, where he has led development teams in creating innovative AI solutions. He also excels in academic mentoring, having supervised multiple PhD students and contributed to curriculum development in machine learning and computer vision at universities.

Conclusion 🔍 

Dr. Syed Muhammad Anwar is a highly accomplished researcher whose contributions to medical image analysis, deep learning, and AI in healthcare make him a strong candidate for the Best Researcher Award. His distinguished career, which spans academia, industry, and entrepreneurial ventures, highlights his ability to blend research innovation with real-world applications. His extensive publication record, high citation count, and successful leadership in numerous research projects underscore his academic impact. Dr. Anwar’s interdisciplinary approach, combining engineering with healthcare solutions, and his ability to secure significant research funding demonstrate his excellence in research and innovation. With a deep commitment to advancing technology for medical applications, Dr. Anwar’s work continues to influence both academic research and the practical development of AI-driven healthcare systems.

Publication Top Notes

Title: BPMN extension evaluation for security requirements engineering framework
Authors: Zareen, S., Anwar, S.M.
Year: 2024
Citation Count: 1

Title: Development of a Modular Real-time Shared-control System for a Smart Wheelchair
Authors: Ramaraj, V., Paralikar, A., Lee, E.J., Anwar, S.M., Monfaredi, R.
Year: 2024
Citation Count: 0

Title: An automated framework for pediatric hip surveillance and severity assessment using radiographs
Authors: Lam, V.K., Fischer, E., Jawad, K., Cleary, K., Anwar, S.M.
Year: 2024
Citation Count: 0

Title: Quantitative Metrics for Benchmarking Medical Image Harmonization
Authors: Parida, A., Jiang, Z., Packer, R.J., Anwar, S.M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: MR to CT Synthesis Using 3d Latent Diffusion
Authors: Tapp, A., Parida, A., Zhao, C., Anwar, S.M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: Zero-Shot Pediatric Tuberculosis Detection in Chest X-Rays Using Self-Supervised Learning
Authors: Capellan-Martin, D., Parida, A., Gomez-Valverde, J.J., Ledesma-Carbayo, M.J., Anwar, S.M.
Year: 2024
Citation Count: 0

Title: Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: A two-center study
Authors: Liu, X., Jiang, Z., Roth, H.R., Bornhorst, M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: EEG-Based Emotion Recognition during Mobile Gameplay
Authors: Khan, S.H., Raheel, A., Majid, M., Anwar, S.M., Arsalan, A.
Year: 2024
Citation Count: 0

Title: CHILD FER: DOMAIN-AGNOSTIC FACIAL EXPRESSION RECOGNITION IN CHILDREN USING A SECONDARY IMAGE DIFFUSION MODEL
Authors: Lee, E., Lee, E.-J., Anwar, S.M., Yoo, S.B.
Year: 2024
Citation Count: 0

Title: Self-Supervised Learning for Seizure Classification using ECoG spectrograms
Authors: Lam, V., Oliugbo, C., Parida, A., Linguraru, M.G., Anwar, S.M.
Year: 2024
Citation Count: 0

Laxmi Rathour | Mathematics | Young Scientist Award

Laxmi Rathour | Mathematics | Young Scientist Award

Research Scholar at National Institute of Technology Mizoram, India.

Laxmi Rathour is an emerging scholar in the field of mathematics, currently serving as a researcher at the National Institute of Technology (NIT), Mizoram. With a strong academic background and a focused research agenda, her expertise lies in both pure and applied mathematics, particularly in areas such as Multi-Attribute Decision Making (MADM), Multi-Criteria Decision Making (MCDM), and Nonlinear Analysis. She is actively involved in research, contributing to journals and collaborating internationally as a reviewer for prestigious publications like Mathematical Reviews (USA) and Zentralblatt Math (Germany). As she continues to pursue her Ph.D., Rathour is deeply engaged in advancing mathematical theory and its practical applications. Her research presence is growing on platforms such as SCOPUS and ResearchGate, and she is quickly establishing herself as a dedicated and impactful researcher in her field, making significant strides in her academic and professional career.

Profile👤

Scopus

ORCID

Education📝

Laxmi Rathour holds a Master’s degree in Mathematics from the Indira Gandhi National Tribal University in Amarkantak, Madhya Pradesh, India. She pursued her postgraduate studies from July 2019 to August 2021, during which she developed her foundational knowledge and research skills in various mathematical disciplines. Currently, she is furthering her academic pursuits by working toward a Ph.D., with a focus on advanced mathematical topics such as Meta Heuristic algorithms and Fractional Calculus. Her educational background has provided her with a strong grounding in both theoretical and applied aspects of mathematics, equipping her to explore complex mathematical problems. Rathour’s academic journey reflects her dedication to research and her desire to contribute new knowledge to the field of mathematics. Her ongoing Ph.D. studies are expected to deepen her expertise and enhance her impact as a researcher.

Experience👨‍🏫

Laxmi Rathour has been affiliated with the National Institute of Technology (NIT), Mizoram, since July 2023, where she serves as a researcher in the Department of Mathematics. Her role involves conducting research in specialized areas such as Multi-Objective Transportation Problems (MOTP) and Nonlinear Analysis. Prior to joining NIT, Rathour was actively involved in research during her master’s studies at Indira Gandhi National Tribal University, where she began developing her interests in optimization and decision-making algorithms. Additionally, she has gained experience as a voluntary reviewer for international mathematical publications, enhancing her exposure to global academic standards. This role has provided her with valuable insights into current trends in mathematical research, as well as opportunities to engage with complex theoretical concepts and methodologies, which have contributed to her growth as a researcher.

Research Interest🔬 

Laxmi Rathour’s research interests lie in a variety of mathematical disciplines, primarily focusing on applied and pure mathematics. Her areas of expertise include Multi-Attribute Decision Making (MADM), Multi-Criteria Decision Making (MCDM), and Multi-Objective Transportation Problems (MOTP), which are important in the context of optimization and decision-making processes. Additionally, she explores Fractional Calculus, Nonlinear Analysis, and Meta Heuristic algorithms. Rathour’s work in Fixed Point Theory and Approximation Theory contributes to solving complex mathematical models, with applications in both academic and real-world problems. Her research is oriented toward advancing mathematical theory while also seeking practical applications in optimization and decision-making, making her contributions valuable in a wide range of industries and scientific disciplines.

Awards and Honors🏆

Though specific awards and honors are not explicitly listed, Laxmi Rathour’s academic achievements and professional engagements highlight her growing recognition in the field of mathematics. She has earned respect as a reviewer for leading mathematical journals, including Mathematical Reviews (USA) and Zentralblatt Math (Germany). These roles demonstrate her expertise and the recognition she has gained within the global mathematical community. In addition to her reviewer positions, Rathour’s research has been published in several national and international journals, further indicating her contributions to her field. As her career progresses, it is likely that she will continue to earn accolades for her research and academic achievements, solidifying her status as an accomplished mathematician.

Skills🛠️

Laxmi Rathour possesses a diverse skill set that complements her research in mathematics. Her technical expertise includes proficiency in decision-making algorithms such as MADM and MCDM, as well as optimization techniques involving Multi-Objective Transportation Problems (MOTP). Additionally, she is skilled in using Meta Heuristic algorithms and advanced mathematical methods such as Fractional Calculus and Nonlinear Analysis. These skills are crucial for tackling complex mathematical problems, particularly in the areas of optimization and decision-making. Beyond her technical capabilities, Rathour also has strong analytical and problem-solving abilities, which are essential for conducting high-level research. Her role as a reviewer further underscores her critical thinking and editorial skills, making her a well-rounded researcher with both theoretical and applied mathematical expertise.

Conclusion 🔍 

Laxmi Rathour is a promising researcher in the field of mathematics, with a particular focus on decision-making algorithms, optimization, and advanced mathematical theories. Her academic journey, which began at Indira Gandhi National Tribal University and continues with her Ph.D. studies, reflects her dedication to expanding her knowledge and contributing to the global body of mathematical research. Her current role at the National Institute of Technology, Mizoram, allows her to further her research in specialized areas while also engaging with the broader academic community through publications and peer-review activities. As she continues to develop her skills and expertise, Rathour is poised to make significant contributions to both the theoretical and applied aspects of mathematics, positioning herself as an influential figure in the field.

Publication Top Notes

A simple and efficient preprocessing step for convex hull problem
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). A simple and efficient preprocessing step for convex hull problem. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S179383092350091X

Tracing roots and linkages: Harnessing graph theory and social network analysis in genealogical research, based on the kin naming system
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). Tracing roots and linkages: Harnessing graph theory and social network analysis in genealogical research, based on the kin naming system. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S1793830924500678

On r-dynamic k-coloring of ladder graph families
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). On r-dynamic k-coloring of ladder graph families. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S1793830924500356

Duality under novel generalizations of the D-Type-I functions for multiple objective nonlinear programming problems
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). Duality under novel generalizations of the D-Type-I functions for multiple objective nonlinear programming problems. Scientific African. https://doi.org/10.1016/j.sciaf.2024.e02067

A Time-Sequential Probabilistic Hesitant Fuzzy Approach to a 3-Dimensional Green Transportation System
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). A Time-Sequential Probabilistic Hesitant Fuzzy Approach to a 3-Dimensional Green Transportation System. In book: Smart Green Innovations for Sustainable Development. https://doi.org/10.1007/978-3-031-56304-1_9

Generalized Rational Type Contraction and Fixed Point Theorems in Partially Ordered Metric Spaces
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Generalized Rational Type Contraction and Fixed Point Theorems in Partially Ordered Metric Spaces. Journal of Advances in Applied & Computational Mathematics. https://doi.org/10.15377/2409-5761.2023.10.13

Integration of Rational Functions
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Integration of Rational Functions. Journal of Multidisciplinary Applied Natural Science. https://doi.org/10.47352/jmans.2774-3047.186

Possible directions of increasing the efficiency of the health system through software development
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Possible directions of increasing the efficiency of the health system through software development. Brazilian Journal of Science. https://doi.org/10.14295/bjs.v3i1.450

A Newton-like Midpoint Method for Solving Equations in Banach Space
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). A Newton-like Midpoint Method for Solving Equations in Banach Space. Foundations. https://doi.org/10.3390/foundations3020014

Coupled Fixed Point Theorems with Rational Type Contractive Condition via C-Class Functions and Inverse Ck-Class Functions
Author: Laxmi Rathour
Year: 2022
Citation: Rathour, L. (2022). Coupled Fixed Point Theorems with Rational Type Contractive Condition via C-Class Functions and Inverse Ck-Class Functions. Symmetry. https://doi.org/10.3390/sym14081663